Exploring a Model of Footwear Asymmetry on Heel

Transcription

Exploring a Model of Footwear Asymmetry on
Heel-Raise Performance and Postural Stability
Christopher Charles Sole
A thesis submitted for the degree of PhD
at the University of Otago,
Dunedin,
New Zealand
Date: 25th March 2012
Acknowledgements
The following individuals have provided advice, encouragement and support in many
different ways for which I am deeply grateful:
My supervisory committee, Professor S. John Sullivan and Associate Professor
Stephan Milosavljevic, School of Physiotherapy, who have had to listen to my
ravings, consider a new paradigm regarding footwear, bounce off ideas, develop and
plan detailed methodology, initiate and facilitate contact with others, read and edit
countless manuscript revisions and generally keep the focus on the mountain summit
while I remained bogged down in the valley.
The University of Otago, for providing a PhD Scholarship.
Mr Andrew Gray, biostatistician, Department of Preventive and Social Medicine,
who provided many hours of discussion, explanations, statistical design and expertise
towards unravelling the data’s secrets.
Mr Bruce Knox, research technician, School of Physiotherapy, who provided time
for on-going technical laboratory support during data collection, the discussions over
suitable analysis for the data and the generation of numerous calculations and
spreadsheets for force platform data analysis.
Dr Allan Carman, research fellow, School of Physiotherapy, who suggested possible
ideas for the laboratory-based study, helped with pilot work, provided technical
laboratory support and was always positive and encouraging.
Professor David Fielding, Department of Economics, whose patient statistical
explanations helped to clarify and complete the data analysis.
Professor Tim Noakes, University of Cape Town, who inspired me to keep asking
questions even when the answers might be different from what the world thinks.
Mr Justin Barnesley who provided engineering advice with regard to the
manufacture, measurement and verification of wedges.
The Mechanical Engineering Department of the Otago Polytechnic for advice about
precision measuring equipment for hardness and thickness testing.
Mrs Sandra Rogers who proof-read extracts recommending changes to general
manuscript format and grammar.
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Without the 144 participants, who freely provided their footwear and time to
repeatedly perform heel raises or stand on one leg and walk for 20 minutes, no data
could have been gathered.
My wife, Dr Gisela Sole, who without her constant belief in me and my ideas, this
would not have been started. She challenged me to put myself on the line, provided
feedback, shared background reading and many research articles. All this helped me
focus on the essentials. Her encouragement and love kept me going when all I wanted
was to throw in the towel.
Our growing children, Claudia and Sebastian Sole, whose athletic prowess and
footwear have given me wonderful opportunities to apply my theories and measure
outcomes.
My athletes who have been willing to try out new ideas as hypotheses have been
tested in the real world and who look forward for me to hand in and devote more time
to their training.
My patients, providing me with challenging real life data as varied and complex as
one can imagine. The many shoes assessed have required careful assessment and
observation to detect clues and patterns. These are often intuitively provided by
individuals as they seek to understand the nature of their own foot-ground interface.
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Publications
The following publication and conference presentations have arisen directly from
work conducted for this thesis.
Refereed journal publications
Sole, C.C., Milosavljevic, S., Sole, G., & Sullivan, S.J. (2010). Exploring a model of
asymmetric shoe wear on lower limb performance. Physical Therapy in Sport, 11, 6065.
Conference presentations
Sole, C.C., Gray, A., Milosavljevic, S., Sole, G., Sullivan, S.J. The effect of medial
and lateral wedging on barefoot single-leg heel raise performance. Research paper
presented at the Sports Medicine New Zealand Conference, Wellington, November
2006
Sole, C.C. Footwear: Asking the right questions. Paper presented at Sports Medicine
New Zealand Otago branch meeting, Dunedin, 2006
Sole, C.C. Footwear: Asking the right questions. Paper presented at the New Zealand
Massage Therapy Conference, Invercargill, May 2009
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Abstract
Current views of human structure and footwear prescription are encompassed in the
poor foot paradigm. An alternative paradigm is proposed which includes evolutionary
and anthropological viewpoints that humans are well adapted for life on earth. Early
footwear was designed for protection and warmth but has evolved through cultural
forces of fashion, finance and mass manufacture. Footwear can change the
anterioposterior, mediolateral and vertical orientation of the foot-ground interface,
changing somato-sensory information and neuromuscular work needed to keep the
human tower upright. A unifying conceptual model of footwear asymmetry patterns
influencing the foot-ground interface is proposed for the assessment of footwear and
the simulation in the experiments. The aims of this thesis were to determine the
frequency and magnitude of mediolateral asymmetry in worn footwear and then
simulate quantifiable amounts, based upon clinical observations, of mediolateral
asymmetry barefoot and in footwear while measuring the effect on performance and
postural stability using dynamic tasks.
It was hypothesised that incremental mediolateral asymmetry (from 1 to 3 mm)
would progressively impair neuromuscular performance and postural stability. A preexisting footwear asymmetry or an extended habituation period with simulated
asymmetry was hypothesized to further impair barefoot performance. The two tasks
identified as having ecological validity and able to be repeatedly performed without
undue fatigue were the single-leg heel-raise (Study 1) and the transition from doubleto single-leg stance (Study 2).
Study 1 was a randomized repeated measures cross-over trial of 38 participants (23.0
± 4.9 years), performing the tasks barefoot and in simulated 1 mm medial or lateral
asymmetry. Sustained heel raises, the maximum number of heel-raises and the rate
they were performed all had significant (P < .001) decreases in performance of
40.3%, 23.4%, and 10.7% respectively with the medial wedge, simulating lateral heel
wear, compared to the control. The rate heel-raises were performed was 6.6% (CI 0.2
to 12.3%, p = .042) better in participants with neutral footwear. Assessment of 294
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shoes showed 37.4% were neutral, 4.8% had 1 mm medial, while 57.8% had between
1 mm and 8 mm of lateral heel wear and/or compression.
Study 2 was a blinded randomized repeated measures trial using 106 participants
(32.4 ± 13.3 years) performing the task of double- to single-leg stance on two force
platforms while barefoot and in their chosen footwear. Medial and lateral footwear
asymmetry was simulated using 1, 2 and 3 mm of heel wedging and a 20-minute walk
habituation period was included for the last of 8 conditions. In 212 shoes, the
frequency of heel asymmetry was biased 57.6% laterally, compared to 0.9% medially.
Time to stabilization was 11.9% (CI 4.0 to 19.2%, p = 0.01) quicker barefoot than in
footwear. Other postural stability measures were either unchanged or greater barefoot.
Barefoot and shod single-leg mediolateral postural stability performance was 7.1%
(CI -2.3 to 17.3%, P = .143) and 13.1% (CI 3.3 to 24.0%, P = .008) worse in
participants who had asymmetrically worn footwear. The simulation had a significant
destabilizing effect post-walk for all conditions except neutral footwear. Incremental
simulated lateral asymmetry of 1, 2 and 3 mm systematically reduced participants’
single-leg mediolateral postural stability performances post-walk by 10.3% (CI -0.9 to
22.8%, P = .074), 14.6% (CI 3.0 to 27.6%, P = .013) and 20.9% (CI 8.6 to 34.7%,
P = .001). Simulated medial asymmetry had a lessor effect with 1.1% (CI -8.9 to
12.1%, P = .843), 11.6% (CI 0.2 to 24.3%, P = .045) and 4.8% (CI -5.9 to 16.7%, P =
.394). A similar effect was measured for the mean velocity of the COP and in the
corrected footwear conditions.
The findings indicate that footwear asymmetry is likely to affect human performance
and balance. This may have implications for footwear assessment, design and
interventions to neutralise mediolateral asymmetry. The conceptual human tower
embedded in asymmetric footwear needs neuromuscular compensations in order to
remain vertical. Should these compensations fail, abnormal mechanical joint loading
and muscular fatigue or inhibition leading to injury and a decrease in skilled
performance are possible. Lateral asymmetry was predominantly measured in
footwear in this study and individuals wearing these had worse mediolateral stability
suggesting a link to a global balance deficit. These may be important factors linked to
ankle inversion injuries or falls in the elderly and the development of medial knee
osteoarthritis.
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Table of Contents
Acknowledgements …………………………………………………………………. ii
Publications …………………………………………………………………….….... iv
Abstract …………………………….…………………………………………..…….v
List of Figures ……………………….…………………………………………..… xii
List of Tables ………………………….……………………………………….……xv
List of Abbreviations ………………….…………………………………………..xviii
CHAPTER 1. Introduction .......................................................................................... 1
1.1
Preamble: Personal and Clinical Observations.......................................1
1.1.1
Clinical Approach Based on Traditional Paradigm......................................1
1.1.2
Perturbed Single-leg Dynamic Stability Affected by Footwear...................2
1.1.3
Insights from my Childhood and Intense Training Years ............................2
1.1.4
Insights from First Studies in Zoology and Botany .....................................3
1.1.5
Insights from Personal Footwear, Work and Back Pain ..............................3
1.1.6
Insights from Patterns Observed in Footwear Design and Wear .................4
1.2
Historical Background to Sports Footwear Prescription .......................5
1.3
The Research Problem...............................................................................5
1.4
The Research Model...................................................................................8
1.5
The Research Aims.....................................................................................8
1.6
Objectives ....................................................................................................8
1.7
Hypotheses ..................................................................................................9
1.8
Research Pathway ......................................................................................9
1.9
Significance of the Research....................................................................11
CHAPTER 2. Literature Review............................................................................... 13
2.1
Introduction ..............................................................................................13
2.2
Evolutionary and Developmental Aspects Relating to Bipedalism .....15
2.2.1
Natural Selection of Adaptations for Bipedal Walking and Running ........17
2.2.2
Barefoot and the Evolution of Footwear ....................................................19
2.3
The Foot-Ground Interface .....................................................................26
2.3.1
Barefoot, Footwear and Efficiency of Movement......................................27
2.3.2
Barefoot, Footwear and Anterioposterior Loading ....................................30
2.3.3
Barefoot, Footwear and Mediolateral Loading ..........................................37
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2.3.4
Barefoot, Footwear and Somatosensory Influences ...................................45
2.4
Footwear and Injury ................................................................................50
2.5
Footwear Degradation Through Use ......................................................53
2.6
Footwear Assessment ...............................................................................56
2.7
Dynamic Postural Stability and Neuromuscular Control ....................60
2.7.1
The Heel Raise Task Used to Assess Neuromuscular Efficiency ..............62
2.7.2
The Transition from Double- to Single-Leg Stance Task Used to Assess
Dynamic Postural Stability.........................................................................69
2.7.3
2.8
Force Platform Measures ...........................................................................73
Summary ...................................................................................................78
CHAPTER 3. Paradigms and Conceptual Models .................................................. 80
3.1
Introduction ..............................................................................................80
3.2
Footwear and the Evolutionary Well-Adapted Paradigm....................87
3.3
Conceptual Model of the Human Body as a Tower ..............................90
3.4
Conceptual Model of Footwear Asymmetry ..........................................97
3.4.1
Asymmetry by Design................................................................................97
3.4.2
Asymmetry by Structural Degradation ....................................................100
3.4.3
Modelling Mediolateral Asymmetry........................................................100
3.4.4
Neutralising Mediolateral Asymmetry.....................................................102
3.4.5
Summary of the Conceptual Model of Footwear Asymmetry ................103
3.5
Wedge Design, Construction and Specifications .................................105
3.5.1
Background ..............................................................................................105
3.5.2
Design.......................................................................................................105
3.5.3
Construction and Specifications...............................................................106
3.6
Footwear Asymmetry Assessment ........................................................106
3.7
Summary and Directions for Studies ...................................................107
CHAPTER 4. Study 1 Exploring a Model of Footwear Asymmetry on a Barefoot
Heel-Raise Task ...................................................................................... 110
4.1
Introduction ............................................................................................110
4.2
Methodology ...........................................................................................113
4.2.1
Participants ...............................................................................................113
4.2.2
Informed Consent, Screening and Familiarisation ...................................113
4.2.3
Experimental design .................................................................................114
4.2.4
Wedge Design to Simulate Footwear Asymmetry...................................115
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4.2.5
Heel-Raise Task .......................................................................................117
4.2.6
Study Procedure .......................................................................................119
4.2.7
4.2.8
Statistical Analysis ...................................................................................126
4.3
Results .....................................................................................................127
4.3.1
Participant demographics .........................................................................127
4.3.2
Sports and Exercise Participation.............................................................128
4.3.3
Sustained Heel-Raise (SHR) ....................................................................129
4.3.4
Maximum Number of Heel-Raises (MHR).............................................130
4.3.5
Rate of Heel-Raises (RHR) ......................................................................131
4.3.6
Shoe Condition Effect ..............................................................................132
4.3.7
Footwear...................................................................................................133
4.4
4.4.1
Discussion................................................................................................139
Primary Finding of Asymmetric Heel Perturbation on Heel-Raise
Performance .............................................................................................139
4.4.2
Hypotheses ...............................................................................................140
4.4.3
The Heel-Raise Task ................................................................................141
4.4.4
4.4.5
Simulated Asymmetry and the Link to Biomechanical and Sensory Effects
…………………………………………………………………………..148
4.4.6
The Tower Conceptual Model and Simulated Mediolateral Asymmetry 153
4.4.7
Methodological Considerations................................................................155
4.4.8
Direction for Study 2................................................................................158
4.5
Conclusion...............................................................................................159
CHAPTER 5. Study 2 Exploring Simulated Incremental Footwear Mediolateral
Asymmetry on Dynamic Postural Stability ......................................... 161
5.1
Introduction ............................................................................................161
5.2
Methodology ...........................................................................................164
5.2.1
Participants ...............................................................................................164
5.2.2
The Dynamic Balance Task: Transition from Double- to Single-Leg Stance
…………………………………………………………………………..165
5.2.3
Experimental Design ................................................................................166
5.2.4
Blinding of the Simulated Shoe Wear Conditions ...................................168
5.2.5
Wedge Design and Specifications............................................................169
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5.2.6
Instrumentation.........................................................................................170
5.2.7
Procedures ................................................................................................170
5.2.8
5.2.9
Data Processing ........................................................................................174
5.2.10
Statistical Analysis ...................................................................................178
5.3
Results .....................................................................................................183
5.3.1
Participant Demographics ........................................................................184
5.3.2
Sports and Exercise Participation.............................................................185
5.3.3
Footwear...................................................................................................186
5.3.4
Barefoot versus Shoe................................................................................192
5.3.5
Shoe and Simulated Asymmetric Shoe Conditions..................................198
5.3.6
Pre- and post-habituation walk.................................................................205
5.3.7
Summary of Key Findings .......................................................................216
5.4
Discussion................................................................................................221
5.4.1
Hypotheses ...............................................................................................221
5.4.2
5.4.3
Barefoot Versus Shoe...............................................................................227
5.4.4
The Effect of Increasing Heel Asymmetry on Postural Stability
Performance (Non-Walk Period)..............................................................232
5.4.5
The Effect of a 20 min Brisk Habituation Walk on Postural Stability
Performance .............................................................................................235
5.4.6
Phases of the Task and Dependent Variables...........................................237
5.4.7
Age, BMI and Gender on Postural Stability Performance .......................239
5.4.8
The Human Tower, Simulated Asymmetry and the Postulated Link to
Postural Instability....................................................................................239
5.4.9
Methodological Considerations................................................................241
5.5
What this Study Contributes.................................................................247
5.6
Directions for Future Research.............................................................249
5.7
Conclusion...............................................................................................250
CHAPTER 6. Summary and Recommendations ................................................... 251
6.1
Summary of the Research Pathway......................................................251
6.2
The Evolutionary Perspective on Human Function............................253
6.3
The Tower Conceptual Model...............................................................255
6.4
Contribution to Scientific and Clinical Knowledge ............................255
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6.5
Recommendations for Future Research...............................................256
6.6
Recommendations for Clinical Practice...............................................257
6.7
Footwear Assessment .............................................................................258
6.8
Heel-Raise and Hip-Flexion Tasks........................................................259
6.9
Footwear Selection or Design Criteria that Minimise Asymmetry ...259
6.10
Osteoarthritis ..........................................................................................260
6.11
Take-Home Message ..............................................................................260
References………………………………………………………………………….262
Appendices.………………………………………………………………………...308
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List of Figures
Figure 1.1 The research problem, what is known and the knowledge gap ………..... 7
Figure 1.2 Research pathway …...…………………………………………….………10
Figure 2.1 Schematic illustration of the time-line from barefoot bipedalism to the use
of modern day footwear ……………………………………………... ........ 25
Figure 3.1 Design features of a used modern stability running shoe. …………….... 81
Figure 3.2 Paradigms of lower limb and foot function require different solutions for
footwear and orthotic interventions …………………………………….. . 83
Figure 3.3 Anthropological and evolutionary perspectives in adults and children
suggest whole-body structure and dynamic barefoot function is welladapted for movement……………………………………………………. . 84
Figure 3.4 Asymmetric degradation of a symmetric sports shoe through use……. . 89
Figure 3.5 The conceptual model of the human body as a tower built upon the foot as
the foundation…………………………………………………………........ 93
Figure 3.6 Postulated interactions of footwear, ground surface and external events on
whole-body dynamic function ……………………………………….. ....... 96
Figure 3.7 Outer- and midsole design may affect degradation…………………… .. 98
Figure 3.8 Footwear design (heel height and shape) and wear (lateral heel)
asymmetry...................................................................................................... 99
Figure 3.9 The medial structural degradation of a grid midsole is measured using the
thumb compression test.…………………………………………………...100
Figure 3.10 Medial (A) and lateral (B) asymmetry is simulated barefoot with a lateral
(A) or medial (B) wedge respectively.................................………………..101
Figure 3.11 Overt lateral 20 mm wear of outer-sole and hard midsole (Asker C 100
units) measured in a work shoe. Actual heel height is 3 cm……………..102
Figure 3.12 Stability sports shoe designed with dual density midsole at the heel. The
medial is harder (Asker C 75 units) than the lateral heel (Asker C 50
units)…………………………………………………………………………103
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Figure 3.13 A conceptual model explaning two patterns of footwear asymmetry at the
heel originating from either design and/or wear effects……………..….104
Figure 3.14 The wedge design: A. Cross section and B. Oblique view……………..106
Figure 4.1 Two patterns of heel asymmetry modelled in this study ….……………112
Figure 4.2 The cross-over experimental design with three control (no wedge)
conditions: pre-wedge, post-lateral wedge and post-medial wedge........ 114
Figure 4.3 Verification of wedge thickness…………………. .................................... 115
Figure 4.4 The heel-raise position with lateral (A) or medial (B) wedges affixed to the
heels. ………………. ................................................................................... 116
Figure 4.5 The starting position for both SHR and MHR tasks. ……….. ............... 118
Figure 4.6 The sustained single-leg heel-raise task procedure.................................. 120
Figure 4.7 The maximum number of heel-raises task procedure. ............................ 121
Figure 4.8 Evaluating the hardness of a midsole from a dual-density stability sports
shoe using an Asker C Durometer and thumb compression test. ........... 124
Figure 4.9 The % difference between the medial wedge and all other experimental
conditions (95% CI) for SHR where P < .001…………………………..130
conditions (95% CI) for MHR where P < .001………………………….131
conditions (95% CI) for RHR where P < .001.. ........................................ 132
Figure 4.12 Flat canvas shoes without a midsole but attached beneath the inner-sole
is an 8.74 mm soft (Asker C 30) rubber heel. ........................................... 134
Figure 4.13 Conceptual model of changes to GRF levers as a result of the medial
wedge and the counter balancing effect of lateral ankle muscle force to
maintain equilibrium in single-leg stance.. ............................................... 151
Figure 5.1 Laboratory set-up and starting position…………………………………166
Fiure 5.2 Repeated measures experimental design………………………………….167
Figure 5.3 Medial wedge placed underneath inner-sole simulating lateral wear.... 169
Figure 5.4 Wedges used to simulate increasing heel asymmetry .............................. 169
Figure 5.5 The procedure followed by each participant for the dynamic task........ 172
xiii
Figure 5.6 Filtered raw data for the synchronised light signal, ground reaction forces
(N) and centre of pressure (mm) in the anterioposterior (Fx, COPx) and
mediolateral (Fy, COPy) directions for one subject................................. 176
Figure 5.7 A graphical illustration of SDFx non-transformed residuals, age and
gender (left) with log-transformed data (right) during double-leg
stance. ........................................................................................................... 179
Figure 5.8 The dependent and independent variables analysed for each phase.. ... 180
Figure 5.9 Assessment performed on a flat shoe in terms of asymmetry, outer-sole,
midsole and actual heel-height. .................................................................. 188
Figure 5.10 A conceptual model of the foot-ground interface, forces and lever arms
barefoot, in neutral footwear and laterally worn footwear adapted from
Kerr et al. (2009). ………………........................................................ ……226
Figure 5.11 Flat canvas shoes require alternative measurement approaches. Placing
the heels together is a method to measure outer-sole wear with the
difference 1 mm lateral wear......................................................................246
Figure 5.12 Hardness of rubber outer-sole of a flat canvas shoe (Asker C 90 units),
and symmetric inner-sole with an 8.74 mm heel (Asker C 30 units). . ... 246
xiv
List of Tables
Table 2.1 Foot Strike Patterns (%) of Habitual Barefoot and Shod Runners from
Kenya and the USA (Lieberman et al., 2010) ……………………………33
Table 4.1 Mean Thickness and Density of 36 Wedges Used to Simulate Asymmetry
……………………………………………………………………………....116
Table 4.2 Demographics of Participants (mean ± SD, range)……………………...127
Table 4.3 Frequency of Self-Reported Previous Musculoskeletal Injuries...... …..128
Table 4.4 Frequency of Sports and Exercise Reported by the Participants ........... 128
Table 4.5 Geometric means (95% CI) of SHR (s), MHR (n) and RHR (reps.min-1) for
Control and Wedge Conditions.................................................................. 129
Table 4.6 Frequency of Shoe Type Worn by the 38 Participants (n = Shoe
Pairs)……………………………………………………………………….133
Table 4.7 Reported Age of Footwear.......................................................................... 134
Table 4.8 Frequency of Shoe Heel Outer-Sole Wear Asymmetry in 294 Shoes (n =
Shoe Pairs)…..……………………………………………………………..135
Table 4.9 Frequency of Asymmetric Shoe Compression at the Heel (n = Shoe
Pairs)……………………………………………………………………….136
Table 4.10 Shoe Type, Midsole Compression Difference, Outer-Sole Wear and Total
Asymmetry for Participants wearing Orthotics in 12.9% of Shoes ....... 137
Table 4.11 Total Mediolateral Asymmetry in 294 Shoes (n = Shoe Pairs) ............... 138
Table 5.1 The Stata Command Structure Used During the Analysis of Barefoot and
Shoe Conditions ........................................................................................... 181
Table 5.2 Demographics of Participants (mean ± SD, range).................................. 184
Table 5.3 Frequency of Self-Reported Previous Musculoskeletal Injuries............. 185
Table 5.4 Frequency of Sports and Exercise Reported by the Participants ........... 186
Table 5.5 Frequency of Shoe Type Worn by the 106 Participants (n = Pairs) ....... 187
Table 5.6 Frequency of Shoe Heel Outer-Sole Wear Asymmetry in 212 Shoes (n =
Shoe Pairs)..………………………………………………………………..189
Table 5.7 Frequency of Asymmetric Shoe Compression (n = Shoe Pairs) ............. 190
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Table 5.8 Shoe Type, Midsole Compression Difference, Outer-Sole Wear and Total
Asymmetry for 8.5% of Participants Wearing Orthotics ....................... 190
Table 5.9 Total Mediolateral Asymmetry in 212 Shoes (n = Shoe Pairs) ............... 191
Table 5.10 Percentage Change for the Dependent Variables Comparing Barefoot to
the Shoe Only Condition............................................................................. 194
Table 5.11 Percentage Change for the Dependent Variables Comparing Intrinsic
Shoe Asymmetry with Barefoot and Shoe Postural Stability Performance
………………………………………………………………………………196
Table 5.12 Percentage Change for the Dependent Variables Comparing Barefoot and
Shoe Postural Stability in Women versus Men, During Transition and
Single-Leg Stance ........................................................................................ 198
Table 5.13 Percentage Change for Mvelox Comparing Shoe-Only to Simulated
Asymmetric Shoe Conditions During Transition..................................... 199
Table 5.14 Percentage Change for Dependent Variables Comparing Effect of Order
on Wedge-Shoe Performance ..................................................................... 200
Table 5.15 Percentage Change for Mvelox and and Maxdis Comparing Shoe-Only to
Simulated Asymmetric Shoe Conditions During Transition……..…….201
Table 5.16 Combined Shoe and Simulated Shoe Asymmetry in Two Groups ........ 202
Table 5.17 Percentage Change for SDFy Comparing Neutral to Corrected Grouped
Wedge-Shoe Conditions.............................................................................. 204
Table 5.18 Percentage Change for Dependent Variables Comparing All Conditions
Pre- to Post-Walk Postural Stability…………………………..…………206
Table 5.19 Percentage Change for Maxdis in Shoe and Simulated Asymmetric Shoe
Conditions During Double- and Second 5 s of Single-Leg Stance Post-Walk
……………………………………………………………………………...208
Table 5.20 Percentage Change for SDFy and Mvelo in Shoe-Only and Simulated
Asymmetric Shoe Conditions During Double- and Single-Leg Stance
(Total Time and Second 5 s) Post-Walk .................................................... 209
Table 5.21 Corrected Wedge-Shoe Conditions for Pre- and Post-Walk................... 211
Table 5.22 Percentage Change for SDFy and Mvelo in Seven Corrected Shoe
Conditions During Total Time and Second 5 s of Single-Leg Stance PostWalk ............................................................................................................. 212
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Table 5.23 Percentage Change for Dependent Variables in Neutral and NonCorrected Shoe Conditions During Double- and Single-Leg Stance (Total
Time and Second 5 s) Post-Walk. .............................................................. 214
Table 5.24 Percentage Change for SDFy and Mvelo in Four Corrected Shoe
Conditions During the Second 5 s Single-Leg Stance Post-Walk. .......... 215
Table 5.25 Summary of Changes to Postural Stability Measures (*P < .05) ........... 217
xvii
List of abbreviations
2-D
Two dimensional
3-D
Three dimensional
BMI
Body mass index
CI
Confidence interval
CNS
Central nervous system
COM
Centre of mass
COP
Centre of pressure
EKAM
External knee adduction moment
EMG
Electromyography
EVA
Ethyl vinyl acetate
GRF
Ground reaction force
FFS
Fore-foot strike
ICC
Intraclass correlation coefficient
Maxdis
Maximum COP displacement
MBT
Masai Barefoot Technology
MFS
Mid-foot strike
MHR
Maximum number of single-leg heel-raises
Mvelo
Mean COP velocity (overall)
Mvelox
Mean COP velocity in the anterioposterior direction
Mveloy
Mean COP velocity in the mediolateral direction
RFS
Rear-foot strike
RHR
Rate of maximum single-leg heel-raises
SD
Standard deviation
SDFx
Standard deviation of the GRF in the anterioposterior direction
SDFy
Standard deviation of the GRF in the mediolateral direction
SEM
Standard error of measurement
SHR
Sustained single-leg heel-raises
TTSFx
Time to stabilisation of GRF in the anterioposterior direction
TTSFy
Time to stabilisation of GRF in the mediolateral direction
xviii
CHAPTER 1. Introduction
1.1
1.1.1
Preamble: Personal and Clinical Observations
Clinical Approach Based on Traditional Paradigm
As an elite athlete, coach and physiotherapist, I have had the opportunity to explore
diverging concepts regarding the etiology of acute and chronic musculoskeletal
injuries. My understanding, assessment and treatment protocols have had to be revised
over the years as I realised the traditional paradigms of foot function and footwear I
used had some limitations. My approach to treatment involved spinal and joint
mobilisation techniques, based mainly on the Maitland concept (Maitland, 1991;
Maitland, Banks, English, & Hengeveld, 2002), deep soft tissue massage in relaxed,
stretched and loaded positions (Hunter, 1998), neurodynamic techniques (Butler,
2000) and therapeutic exercise. The latter included closed kinetic chain exercises,
central core stabilisation and functional loading exercises.
After graduating as a physiotherapist in 1995 my initial assessment of the foot and
sports footwear followed the traditional method as taught in Physiotherapy, Podiatry
and Sports Medicine Schools (Martin, 1997a, 1997b; McPoil, 1988; Nigg & Segesser,
1992; Noakes, 2003). Patients were observed while standing, walking and running,
and sports shoes were chosen with the aim of decreasing sub-talar and forefoot
pronation. My clinical assessment of the foot was based on principles proposed by
Root, Orien and Week (1977). I worked closely with a podiatrist who fitted rigid style
orthoses (Root et al., 1977) after casting the foot in a non-weight-bearing position. He
also constructed medial forefoot wedges in order to bring the ground to meet the first
metatarsal and toe. The tendency was to prescribe anti-pronation structured stability,
or motion control shoes in an effort to stabilise the foot and decrease the observed
mid- and forefoot over-pronation. Many patients found these difficult and
uncomfortable to wear and they needed on-going major modifications. More
importantly, their level of activity or performance appeared to decrease in order to
1
manage the pain and discomfort and, anecdotally, many gave up exercise altogether.
Only short-term benefit was achieved with standard treatment protocols, and injuries
would re-surface at the same site or injuries would occur elsewhere in the body. In
some cases there was a cyclical nature to the injury, such as back pain being totally
absent and then severe without obvious overload. Clinical results were unsatisfactory
and required a major re-assessment of the approach I was using.
1.1.2
Perturbed Single-leg Dynamic Stability Affected by Footwear
There have been a number of watershed events or chance happenings which caused
me to radically rethink my position and paradigm. Working with a young provinciallevel tennis player with repeated episodes of pain in the mid-back, I observed that
during single-leg stance her ability to resist pressure in an adduction direction at her
wrists with arms abducted to 90° could be influenced by placing a bunch of business
cards under her first toe and medial or lateral heel. I could not explain the relationship
exhibited. It took me more than ten years of observations and reflection to modify my
reasoning and to develop a clinical test to quantify the precise amount of lateral or
medial hindfoot wedging needed by a patient in a particular shoe.
1.1.3
Insights from my Childhood and Intense Training Years
I grew up in the Xhosa-speaking tribal territory of Transkei, Eastern Cape, South
Africa. All physical education and play at school was barefoot, whether on the fields
or in the gym. I raced and trained twice daily in cheap flat shoes (takkies, Onitsuka
Tiger flats or Puma Athletics), spikes or barefoot as did most of my African training
partners. Today, these would be termed minimalist type footwear. Performance and
finance drove the selection of running shoes that were simply replaced when they
wore out. Training surfaces included tarmac, grass (athletic track, sports fields, and
golf courses), beaches and off-road bush tracks comprised of sand, stones and rocks.
During this teenage and young adult period my detailed diaries note that I was never
injured to the extent that I required physiotherapy or other medical treatment. I was
South African Junior 1500m Champion (1974 and 1975), Scottish Youth 800m and
1500m Champion (1974), and the National U19 1000m and 2000m record holder. I
was also part of a 10-man university team that set the World University records in the
2
24 Hour relay (1979, 1980), and won the Table Mountain Race 12 times, still holding
the record. I competed at National level in Cross Country and track for over 25 years
and still compete locally (New Zealand) in the Masters 50+ category.
Running sport shoe design dramatically changed in the 1980’s and by 1986 it was
impossible to purchase minimalist shoes. From 1986 onwards I increasingly became
incapacitated with many lower back, groin and leg injuries which were resistant to
standard physiotherapy, chiropractic and medical treatment protocols.
1.1.4
Insights from First Studies in Zoology and Botany
My first degree majors at the University of Cape Town, South Africa, were Zoology
and Botany, including a 6-month course on Genetics, Anthropology and Evolutionary
Biology. The selective value of evolutionary change was interwoven and interlinked
with all plant and animal studies whether in anatomy, behaviour or ecology. Function
and selection perfection for habitats and survival were interrelated. Knowledge of
human evolution was also expanding at a rapid rate as more fossil evidence was
discovered within and outside Southern Africa.
1.1.5
Insights from Personal Footwear, Work and Back Pain
While working for 2 years as the sole physiotherapist at a day hospital in Retreat, a
marginalised community within greater Cape Town, I was daily lifting many patients
with limb amputations, head injuries, obesity and neurological disorders. I suffered
severe low back pain. X-rays taken in 2000 revealed degenerative changes at the
L5/S1 level with an associated bilateral spondylolysis and grade 1 spondylolisthesis. I
found working barefoot provided immediate relief to my symptoms and was able to
continue without any intervention.
3
1.1.6
Insights from Patterns Observed in Footwear Design and Wear
In 1998 an orthopaedic surgeon suggested to me that most of his patients undergoing
surgery for medial meniscus lesions and medial knee joint cartilage damage were
wearing anti-pronation shoes. His patients were advised to change to a neutral shoe
which contradicted current practise. However, at that stage, little research was
available to support a possible relationship between shoes and medial knee joint wear.
Further questions arose as I mulled over the consequences of my then contradictory
approach to foot stability and foot function.
Probably one of the most important experiences for me was the purchase in 2001 of
the most expensive scientifically advanced neutral shoe on the market, the Asics
Nimbus. I suffered severe back, groin, hamstring, calf, Achilles tendon and medial
knee pain, making it impossible to run. Using the traditional approach of bringing the
ground to meet the foot with medial forefoot wedging prescribed by the podiatrist
aggravated the pain. A careful assessment of the shoe showed that the very soft lateral
heel and forefoot gel pad were in effect, most likely, increasing my supination at heelstrike and acting as a stability shoe. Placing a small wedge under the lateral heel
decreased pain immediately.
Finally, the greatest paradigm shift for me occurred after expanding footwear
assessment to include all the footwear worn by individual patients. I previously only
assessed sport-specific footwear. Traditional teaching suggested neutral, rigid or flat
foot structure, pathology and patterns of wear had simply a one-to-one relationship
(Yamashita, 2005). The most frequently encountered problem was medial collapse or
wear of the foot and shoe (Clarke, Frederick, & Hamill, 1983; Nesbitt, 1999).
However, detailed foot and footwear analysis failed to show clear relationships and a
single individual may have completely diverging wear patterns in different shoes.
This finding suggested that footwear design and use, rather than foot structure, could
be critical in determining wear. Further, two predominant patterns of footwear
asymmetry at the heel were observed, either laterally or medially. Removing or
neutralising this asymmetry appeared to have a profound effect on my clinical
outcomes.
4
1.2
Historical Background to Sports Footwear Prescription
Historically, foot function has been characterised by clearly defined intrinsic factors
independent of footwear, and this paradigm has permeated almost all modern day
practice, research, theory and manufacture of sports footwear (Richards, Magin, &
Callister, 2009; Vernon, Parry, & Potter, 2004). This “poor foot” paradigm suggests
that the foot is pathologic or genetically inferior in design and hence needs to be
corrected or changed to an ideal position. As a result, orthotics and shoes are
prescribed to correct the foot and skeletal alignment regardless of the current status of
individuals’ footwear. Despite this widely accepted approach to the foot and footwear
design, injury prevention and optimisation of footwear remain problematic
(Brüggemann, 2007; Mündermann, Wakeling, Nigg, Humble, & Stefanyshyn, 2006;
Von Tscharner, Goepfert, & Nigg, 2003). Reviews and research challenge the belief
that excessive foot eversion leads to excessive pronation upon which current sports
footwear is designed (Ball & Afheldt, 2002a, 2002b; Nigg & Wakeling, 2001; Payne,
1999; Richards, Magin, & Callister, 2009). Rather than attempting to correct an
abnormal foot, consideration needs to be given to other factors.
New insights that take into account structural anatomy, function, evolutionary history
and the survival of the fittest explain barefoot as the most efficient means of human
locomotion (Bramble & Lieberman, 2004; Lieberman & Bramble, 2007; Lieberman et
al., 2010). Barefoot gait also provides the least loading stress to hip, knee and foot
joints (Rao & Joseph, 1992; Shakoor & Block, 2006; Shakoor et al., 2010; Wolf et al.,
2008). Thus an alternative “evolutionary perfection” paradigm of human structure and
function identifies evolutionary forces as positively adaptive towards selection
pressures and optimisation of human function.
1.3
The Research Problem
Nigg and Wakeling (2001) proposed that footwear should support the
individual’s “preferred skeletal alignment” or pathway rather than changing skeletal
alignment to an ideal. Should footwear and orthoses counteract this preferred
5
pathway, muscle activation will be increased, leading to fatigue and a decrease in
performance (Mündermann et al., 2006).
Current approaches do not consider the potential significance of the status of patients’
used footwear. Although footwear degradation is acknowledged, it is evaluated in
terms of patients’ fixed movement patterns. A one-to-one relationship is believed to
exist between foot and lower limb type, injuries and wear patterns (Yamashita, 2005).
Asymmetric medial or lateral outer sole heel wear and/or midsole compression
patterns are often seen clinically in worn footwear, but the effect of this wear on
dynamic postural stability, fatigue, injury, pain and performance is unknown (Asplund
& Brown, 2005; Noakes, 2003; Sheehan, 1979; Singh, 1970). The frequency and
position of this asymmetric heel wear has not been quantified in the general
population. Figure 1.1 summarizes the research problem, what is known and the
knowledge gap that this thesis is focussed on addressing. The relationship between
simulated increasing heel asymmetry on single-leg neuromuscular performance is
explored.
6
.
The
The Problem
Problem
The
The frequency
frequency of
of chronic
chronic lower
lower limb
limb injuries
injuries due
due to
to running
running has
has not
not changed
changed
since
sophisticated
footwear
developed.
since sophisticated footwear developed.
The
The optimal
optimal footwear
footwear design
design is
is still
still unknown.
unknown.
The
footwear
design andon
degradation
on physical
The contribution
contribution of
of mediolateral
footwear design
and degradation
physical and
postural
and postural
stability
performance
is unknown.
stability
performance
is unknown.
The frequency
frequency of
of mediolateral
mediolateral asymmetry
asymmetry in
in worn
worn footwear
footwear is
is unknown.
unknown.
The
What is known
Footwear affects postural stability, joint and muscle loading of the lower limb.
Thick soft midsoles negatively affect balance by increasing mediolateral
instability.
Anterioposterior footwear asymmetry caused by heel height increases instability,
joint and muscle loading of the lower limb and spine.
Mediolateral footwear asymmetry produced by design includes increased medial
or laterally stiffer midsoles and orthotics.
Motion control shoes and medial wedging decrease medial foot pronation but
increase medial hip, knee and lateral ankle joint loading.
Laterally stiffer shoes or lateral wedging increase medial foot pronation but
decrease medial hip, knee and lateral ankle joint loading.
Mediolateral footwear asymmetry produced by use includes both outer sole wear
and midsole compression degradation.
What is not known
What is the typical frequency of medial versus lateral asymmetry in used
footwear?
Does footwear heel mediolateral asymmetry affect single-leg dynamic balance
and neuromuscular performance?
Figure 1.1 The research problem, what is known and the knowledge gap
7
1.4
The Research Model
Inherent intrinsic biomechanical factors, such as over-pronation, have traditionally
been considered to contribute towards injuries. This thesis considers effects of
asymmetric footwear degradation and design features on whole body performance,
and whether this factor could potentially contribute towards injuries.
1.5
(1)
The Research Aims
To determine the frequency of medial and lateral heel asymmetry in footwear
within the general population.
(2)
To determine the influence of medial and lateral hindfoot perturbation on
lower limb performance in an uninjured population.
(3)
To determine the influence of medial and lateral hindfoot perturbation on
dynamic postural stability in an uninjured population.
1.6
(1)
Objectives
Investigate the literature on the effect of barefoot, footwear and asymmetry
on human evolutionary structure, function, performance and postural
stability.
(2)
Identify laboratory-based weight-bearing tasks relevant to measuring neuromuscular performance.
(3)
Synthesise evidence for a new paradigm with regard to human structure,
function, barefoot, footwear, injuries and performance.
(4)
Create a model simulating typical footwear asymmetric wear patterns.
(5)
Explore the simulated effect of medial and lateral hindfoot asymmetry on
dynamic movement performance tasks.
(6)
Create a model to explain the possible effect of mediolateral asymmetry on
joint loading and neuromuscular function.
8
1.7
Hypotheses
H1: Asymmetric medial or lateral heel wear will be evident and measurable in the
typical daily footwear of a substantial percentage of a sampled population.
H2: The frequency of asymmetric medial or lateral heel wear will be biased laterally.
H3: The performance of the heel-raise and dynamic balance tasks will be impaired in
individuals whose footwear has mediolateral heel asymmetry compared to those
who do not display such heel asymmetry.
H4: Medial and lateral hindfoot positional perturbations will decrease the
performance of the heel-raise or the dynamic balance tasks compared to the
neutral state.
H5: Progressively increasing medial and lateral asymmetry will increase the
performance impairment of the dynamic balance task compared to the neutral
state.
H6: Increasing the length of time spent in simulated asymmetry will further impair
the performance of the dynamic balance task compared to the neutral state.
1.8
Research Pathway
The first step of this research (Figure 1.2) was to conduct a literature review regarding
evolutionary human history in the context of adaptive changes for bipedal gait,
footwear development and its impact on human performance (Chapter 2). The
literature search also included studies pertaining to footwear-induced changes to the
anterioposterior and mediolateral foot-ground interface affecting lower limb
neuromuscular performance, postural stability and risk of injury. A brief overview of
recent narrative and systematic reviews relating to injuries and footwear interventions
is presented. Limitations of research on footwear degradation and assessment will
highlight the present knowledge gap. Footwear brand names and models used in the
course of this research are included as each has specific design features relevant to the
discussion. Finally the review concludes with an examination of the neuromuscular
tasks chosen to assess the effect of mediolateral footwear asymmetry.
9
Chapter 2
Evolutionary theory, barefoot and footwear
Foot-ground interface
Anterioposterior and mediolateral loading
Neuromuscular tasks
Chapter 3
Paradigm shift: poor versus perfect design
Foot-ground interface and asymmetry
Conceptual models:
Human body as a tower
Footwear asymmetry and wedge design
Chapter 4
Heel-raise task
Footwear assessment
Chapter 5
Transition from double- to single-leg stance
task
Footwear assessment
Chapter 6
Summary of research pathway
Future research
Clinical recommendations
Figure 1.2 Research pathway
10
Chapter 3 presents the current paradigm with regard to foot function and footwear
alongside a new paradigm synthesised from collated, reviewed and critiqued research.
A model of footwear mediolateral asymmetry and its hypothesised effects on human
structure and function is described. In order to simulate mediolateral asymmetry heel
wedges were designed which could be placed inside footwear to tilt the heel medially
or laterally.
Standard clinical tasks were used to investigate the effect of hindfoot asymmetry
commonly found in footwear. The first study investigates the effect of simulated
asymmetric wear on a clinically measured single-leg heel-raise performance task
(Chapter 4). The description, design and verification of these wedges (artificial
perturbations) are presented in this Chapter. The second study investigates the effect
of simulated asymmetric wear on the dynamic transition task from double- to singleleg stance as measured on a force platform (Chapter 5). The clinical assessment of
footwear is described and results from the two participant groups are reported in each
Chapter. Footwear brand names reported or illustrated are included as they are
typically used by the participants in the two studies. A summary of the research
pathway, future research, clinical recommendations and key outcomes are discussed
in Chapter 6.
1.9
Significance of the Research
The frequency of running-related injuries has not changed over 30 years despite
significant research into prevention (Brüggemann, 2007; Fredericson & Misra, 2007;
McKenzie, Clement, & Taunton, 1985; Taunton et al., 2003). The solution is either
intractable or the questions that are being explored in research are not the right
questions. This thesis therefore challenges the entrenched traditional foot-footwear
paradigm which appears to permeate research, clinical teaching and practise, footwear
assessment, design and prescription. It starts by looking at the problem from a
completely different perspective and timeframe. Given the theory of evolution and
natural selection, the solution likely lies in our past and hence the need for an
alternative paradigm. This frees up new avenues for exploration as footwear can then
be evaluated as an extrinsic man-made environmental filter which may no longer fit
11
the original design specifications for protection and warmth only. The conceptual
model formulated to explain the effect of footwear asymmetry on the human body as
a tower which can be tilted may help to explain why very small asymmetries at the
foot can have large diverse neuromuscular-skeletal effects higher up the kinetic chain.
The model for footwear asymmetry provides a new and unique overview and
understanding of the different processes leading to footwear degradation. While the
size of the interventions used in this study is atypical in footwear research, they are
aligned with the conceptual model. This study takes a small, but important, step
towards measuring the effect of asymmetric hindfoot perturbations on postural
stability and whole-body dynamic function. The results of this study will contribute to
the understanding of the importance of such asymmetry on whole-body
neuromuscular functioning and abnormal joint loading. These two interlinked
processes play a pivotal role in the development and progression of osteoarthrosis.
Analysing possible mechanisms of footwear asymmetry will provide valuable
information about footwear strategies to reduce joint loading and thereby enhance
musculoskeletal health and performance.
12
CHAPTER 2.
Literature Review
2.1
Introduction
The ability to stand upright and walk on two legs is widely recognized as a
crucial hominid adaptation that had profound effects on the course of human
evolution. (Day & Wickens, 1980, p 385)
The astonishing discovery of the Laetoli hominid footprints preserved in a volcanic
ash walkway dated 3.6 to 3.8 million years ago represents the earliest evidence of
barefoot bipedalism in human evolution (Day & Wickens, 1980; Raichlen, Gordon,
Harcourt-Smith, Foster, & Haas, 2010; White, 1980). Studies of these footprints
indicate that their morphology and the dynamic forces transmitted through the feet for
propulsion were similar to those of barefoot humans today (Day & Wickens, 1980;
Vaughan & Blaszczyk, 2008) and that the efficiency of the extended limb gait was
likely an important selection pressure (Raichlen, Gordon, Harcourt-Smith, Foster, &
Haas, 2010). The emergence and survival of the genus Homo may have been the
result of skeletal and muscular adaptations linked directly to enhanced barefoot
endurance running performance (Bramble & Lieberman, 2004; Carrier et al., 1984;
Ker, Bennett, Bibby, Kester, & Alexander, 1987; Lieberman, Bramble, Raichlen, &
Shea, 2009; Rolian, Lieberman, & Hallgrimsson, 2010).
Contrary to this evolutionary history where only the fittest survived, is the modern
day paradigm that the foot is poorly adapted to life on earth and needs to be fixed
(Root et al., 1977; Yamashita, 2005). As a result, extensive footwear and orthotic
research has been dedicated to finding ways to improve this poor foot function
(Butler, Hamill, & Davis, 2007; Cheung & Ng, 2009; Vicenzino, 2004; Williams III,
McClay Davis, & Baitch, 2003). Over the last thirty years scientific development in
sport shoe design occurred using the paradigm that the human foot was not optimally
designed for walking and running; hence the need for footwear to guide, control and
support an inherently poor design (Butler, Davis, & Hamill, 2006; Butler, Hamill et
13
al., 2007; Cheung & Ng, 2008, 2009). This spawned a multibillion dollar industry
producing sophisticated stability and motion control shoes that are inherently
asymmetric at the heel, by introducing harder midsoles on the medial side and softer
cushioning properties on the lateral margin (Cheung, Ng, & Chen, 2006; Reinschmidt
& Nigg, 2000; Richards et al., 2009). Over and above shoe design stability features,
foot orthoses are commonly prescribed for the treatment and prevention of lower limb
injuries based on the concept of setting the foot into a subtalar neutral position (Ball &
Afheldt, 2002a, 2002b; Chuter, Payne, & Miller, 2003; Dixon & McNally, 2008).
Despite all the research and interventions, the relationship of footwear design to
effective injury prevention has not been established (Brüggemann, 2007; Nigg, 2001;
Richards et al., 2009; Taunton et al., 2003), suggesting that other factors remain not
currently being addressed. The type and frequency of running-related injuries has not
improved over the last two decades (Fredericson & Bergman, 1999; Fredericson &
Misra, 2007; McKenzie, Clement, & Taunton, 1985; Taunton et al., 2003) despite the
scientific advancement in research, footwear and orthotic design and prescription. The
reported incidence of lower extremity running-related injuries range from 37 to 56%
(van Mechelen, 1992) or 19 to 79% (van Gent et al., 2007) increasing to 90% in those
running marathons (Fredericson & Misra, 2007). In the most recent study of 442
female and 306 male runners aged 13 to 18 years, the injury incidence was 68% and
59% respectively (Tenforde et al., 2011). This incidence is even higher in triathletes
followed prospectively over 10-weeks (Burns, Keenan, & Redmond, 2005). One
hundred and thirty-one sustained 155 running injuries during the study period. The
advice given with regard to prevention and treatment in 1985 (McKenzie et al., 1985)
is essentially the same 20 years later (Yamashita, 2005). Effective management of
running-related lower extremity injuries appears to be elusive and the search for
solutions may need to include a different perspective.
This chapter considers the evolutionary and developmental aspects relating to foot
function and footwear, and the mechanical and sensory influences of footwear on the
foot-ground interface and human dynamic function. Further, footwear factors will be
presented that are not currently assessed or accounted for in research, such as wear
asymmetry and the effect on postural stability. The reason for this focus is two-fold.
Firstly, the incidence and type of intrinsic injuries from one sport alone has not
14
improved despite overwhelming scientific efforts to prove relationships and offer
solutions. Secondly, if the present poor foot paradigm which directs research and
footwear design were effective, questioning its very foundations and this thesis would
be superfluous. Since the case for the poor foot paradigm is argued in almost all
footwear and related research, this overview attempts to redress the imbalance. As this
subject matter covers an extensive field it is not possible within the confines of this
thesis to present and evaluate both points of view in detail.
2.2
Evolutionary and Developmental Aspects Relating to
Bipedalism
Nothing in biology makes sense except in the light of evolution. (Dobzhansky,
1973, p 125)
A possible missing link in biomechanical models of the human foot, gait, footwear
and injury prevention research is the failure to recognise evolutionary theory and
value adaptive processes in human functional anatomy, biology and disease
(Dobzhansky, 1967; Lewis, 2009). The struggle for existence, in the genus Homo
hunter-gatherers, selected individuals who could survive the harsh realities of their
environments (Roman-Franco, 2009). In his book, The Ascent of Man, Bronowski
(1981) interprets humans as highly integrated, evolving structures, influenced by
changing behaviour. The selected morphological changes of human anatomical
structures such as the brain, eyes, hands and feet gave humans the impetus to be richer
and more flexible in behaviour than any other animal (Bronowski, 1981). This
allowed them to move and occupy environments very different to the African
landscape ensuring their success and survival (Ayala & Escalante, 1996).
Morphological studies of evolutionary changes to Primate and Homo joints support
the contention for these to be logically correlated and well adapted to the refined
requirements of human behaviour (Lewis, 1977, 1980a, 1980b, 1980c).
Research indicates that the foot was already well adapted to the push-off phase of
bipedalism by at least 3.6 million years ago (DeSilva, 2010; Wang & Crompton,
2004). Energy expenditure and efficiency of movement was an important selection
15
pressure in bipedal gait (Raichlen et al., 2010), as were anatomical changes such as
the length of the calcaneus and Achilles force moment arm (Raichlen, Armstrong, &
Lieberman, 2011). Despite this natural selection pressure over millions of years,
researchers have been influenced by contrary views which suggest “man’s foot and
his entire ambulatory structure has not evolved sufficiently to meet his needs, … the
reason why man has a multitude of foot and gait problems” (Caselli & Alchermes,
1988, p 443). Using this argument, the evolutionary selection process did not quite
work for Homo and subsequent species, although for all other plants and animals, ongoing adaptation is perfected for diverse habitats (Attenborough, 1980). In order for
life to endure in a challenging environment, natural selection must favour the
adaptations which shift the precarious balance between living and dying towards life
(Dobzhansky, 1950). Humans are the most successful product of biological evolution
(Dobzhansky, 1960) but are the only organisms who can change their environment via
cultural and technological evolution, which may threaten or extend their existence.
The theory of evolution by natural selection provided a revolutionary new way of
viewing the diversity, relationships, function and origins of species on Earth. This is
driven by environmental changes and accidental genetic modifications allowing
successful adaptations for the exploitation of new niches (Ayala & Escalante, 1996;
Niemitz, 2010). Essential to this understanding is the idea of the survival of the fittest
(Lewis, 2009) and the anatomical modifications necessary to provide advantages
(Latimer & Lovejoy, 1989; Lewis, 1980a; Lieberman, Raichlen, Pontzer, Bramble, &
Cutright-Smith, 2006).
16
2.2.1
Natural Selection of Adaptations for Bipedal Walking and
Running
Humans have exceptional capabilities to run long distances in hot, arid
conditions. These abilities, unique among primates and rare among mammals,
derive from a suite of specialised features that permit running humans to store
and release energy effectively in the lower limb, help keep the body’s centre
of mass stable and overcome thermoregulatory challenges of long distance
running. (Lieberman & Bramble, 2007, p 288)
Fossil evidence from around 4.4 million years ago suggests that upright walking and
endurance running played a major role in human evolution as the central African
environment changed (Bramble & Lieberman, 2004; Raichlen, Pontzer, & Sockol,
2008). The evolutionary selection process ensured the survival of those who were best
adapted for walking and running as it allowed them to hunt and kill large animals for
food without sophisticated weaponry (Lieberman et al., 2009). Large distances were
covered during pursuit hunting where the prey was forced to run until it collapsed
from hyperthermia (Liebenberg, 2006, 2008). Selection forces not only favoured those
who performed better, but also those whose tracking skills were well developed and
this required advanced levels of brain capacity (Liebenberg, 2006, 2008; Lieberman et
al., 2009). It further favoured a co-operative social system in which whole families of
all ages could be involved, learning and teaching tracking skills, moving vast
distances and sharing food (Liebenberg, 2006, 2008). Criticism of this theory is based
on some recent ethnographic evidence that modern hunter-gatherers rarely use
persistence hunting and that tracking abilities were likely too cognitively complex for
early Homo (Pickering & Bunn, 2007). However, arguments using modern day
comparisons are flawed as hunting strategies evolved using new weapons while
indigenous peoples’ tracking skills continue to astound Western anthropologists
(Liebenberg, 2008; Lieberman, Bramble, Raichlen, & Shea, 2007).
In terms of human evolutionary history, the human body is considered perfectly
adapted to the environmental demands of endurance running and walking, from both a
structural and mechanical perspective (Bramble & Lieberman, 2004; Lieberman et al.,
17
2009). Many derived features are suggested to have ensured the very survival of the
genus Homo. These include:
•
head and trunk stabilisation (Lieberman, 1996);
•
light, longer legs and more efficient bipedal movement (Raichlen et al., 2010);
•
muscles such as the gluteus maximus (Lieberman et al., 2006) which optimise
ground reaction forces, joint moments, power and efficiency (Alexander, 1991);
•
a high percentage of slow-twitch muscle fibres (Lieberman et al., 2009);
•
narrower waists, decoupled shoulder girdles related to dynamic postural
stabilization and breathing during running (Bramble & Lieberman, 2004);
•
efficient thermoregulation (Bramble & Carrier, 1983);
•
efficient stride length and energy usage (Carrier, Heglund, & Earls, 1994;
Raichlen et al., 2010);
•
energy saving elastic storage mechanisms in the foot arch and tendons
(Alexander, 1991a, 1991b; Ker et al., 1987; McMahon, 1987);
•
improved Achilles tendon power leading to running efficiency (Raichlen et al.,
2011);
•
adducted first toe and shorter forefoot (Rolian et al., 2010; Rolian, Lieberman,
Hamill, Scott, & Werbel, 2009; Zipfel, Desilva, & Kidd, 2009);
•
sensory functions of the plantar foot surface vital for normal gait (Eils et al.,
2004; Inglis, Kennedy, Wells, & Chua, 2002; Robbins, Gouw, & Hanna, 1989).
In summary, those individuals who could travel efficiently the furthest and fastest
were most likely to survive and thrive. Based on the fossil evidence, selection
pressure, the rapid spread of Homo from Central African origins and present day
human structure, the foot and body should be considered perfectly adapted for long
distance movement and life on earth (Bronowski, 1981; Lieberman & Bramble, 2007;
Lieberman et al., 2009). Thus, the question that needs to be asked is: what has gone
wrong in present day humans who face a number of health risks and problems? Does
evolutionary theory not hold for Homo s. sapiens? Instead of rejecting the theory,
research needs to assess the effect of new human behaviours and cultural adaptations
on the environment, such as diet, exercise, footwear and tools. If humans were all
African hunter-gatherers for 99% of current evolutionary time, understanding what
18
enabled survival may provide the clues as to what present behaviours and lifestyles
may do the very opposite (Roman-Franco, 2009). It is here that the answers and
challenges to human health and wellness may be found. The first step is to find
populations whose present lifestyles may feature aspects of the historical past which is
proving more difficult in the modern world (Lieberman et al., 2007).
2.2.2
Barefoot and the Evolution of Footwear
Man is born barefoot, and barefoot he compassed the earth. Therefore it
should be to barefoot peoples that we should turn to study the natural anatomy
and physiology of the foot to obtain a base for the study of footgear. (Stewart,
1972, p 119)
Common foot conditions, such as the deformed shape and function of hallux valgus,
hammer toes and painful feet, have been compared between barefoot and shoewearing peoples in Africa (Barnicot & Hardy, 1955; Engle & Morton, 1931;
Gottschalk, Beighton, & Solomon, 1981; Hoffmann, 1905; Morton & Engle, 1930;
Zipfel & Berger, 2007), China (Schulman, 1949; Sim-Fook & Hodgson, 1958), India
(D'Aout, Pataky, De Clercq, & Aerts, 2009; Rao & Joseph, 1992), the Pacific Islands
and Japan (Ashizawa, Kumakura, Kusumoto, & Narasaki, 1997; Kusumoto, Suzuki,
Kumakura, & Ashizawa, 1996; Shine, 1965). These foot conditions were found to be
less common in the barefoot groups. In Japan an increase in frequency of painful
hallux valgus over 10 years was mirrored by changes in fashionable footwear allowed
from the age of 14 years (Kato & Watanabe, 1981). No deformities were present in
children up to the age of 14 who were still using traditional footwear styles.
The feet of barefoot populations are characterised by flexibility, thickening of the
plantar skin related to the environment, widespread toes aligned with the metatarsals,
wide variability in arch height and absence of deformities (Sim-Fook & Hodgson,
1958; Staheli, 1991; Stewart, 1972). These anthropological studies focused on
qualitative descriptions of foot function and shape and lack same ethnic group
controls. However, their findings suggest that footwear can and does change the shape
and function of the barefoot (Frey, Thompson, & Smith, 1995; Sachithanandam &
Joseph, 1995).
19
Footwear, as used today, is a recent development in human evolutionary history
occupying about 1% of human time (Jungers, 2010; Stewart, 1945; Trinkaus & Shang,
2008). Stewart (1972) provides a comprehensive evolutionary history of footwear
based on fossil evidence, museum collections and anthropological research. Early
designs evolved using available plant or animal material for thermal or mechanical
protection (Stewart, 1945, 1972; Trinkaus, 2005). Fibrous or leather slip-on sandals
dated from 8,300 years ago have been found in caves in Missouri (Kuttruff, DeHart,
& O'Brien, 1998), while some Spanish rock paintings showing footwear suggest some
protective footwear may have been worn around 15,000 years ago (Trinkaus & Shang,
2008). Inferences about the use of footwear have been made by measuring decreases
in pedal phalangeal robusticity (Trinkaus, 2005; Trinkaus & Shang, 2008). In 2008
archaeologists discovered a complete right leather shoe and two preserved leather and
grass samples in an Armenian cave which have been dated to the 4th Millennium BC
(Pinhasi et al., 2010). The heelless shoe was 10 cm wide in the forefoot and was made
from a single piece of leather that wrapped around the foot, and the foot imprint of the
individual’s hallux and heel are still evident.
These discoveries and those from the Italian and Swiss Alps, Israel and elsewhere
indicate regional variations in individual hand-made production and styling, with the
prime purpose being protection according to the climate (Pinhasi et al., 2010; Stewart,
1945, 1972). Māori, the indigenous people of New Zealand, used bast (rope-like leafbases or bark derived) flat flexible sandals which provided protection from coral and
rocks but did not have water drag effects and were securely laced similar to the
Greeks and Romans (Stewart, 1945). These sandals wore quickly so that in
expeditions individuals carried from 5 to 20 spares. Footwear was simply made to fit
the foot and replaced when worn. The present day Tarahumara Indians of the isolated
Mexico’s Copper Canyons who cover vast distances over inhospitable terrain, still
make their own flat non-constricting sandaled footwear, These Huaraches use a
similar design but different material, which is easily fixed or replaced when worn
(McDougall, 2009).
Heels in the modern sense may initially have been used as a prostheses for the
wounded Mongolian warrior, Timur the lame (Tamerlane), and appear from 1600
onwards with heights driven by fashion (Stewart, 1945). The manufactured, modern
20
heeled shoe (late 1860’s) is very different from the original sandal or moccasins
handmade designs that were similar to the barefoot state (Lieberman et al., 2010;
Thompson & Zipfel, 2005; Zipfel & Berger, 2007). It is characterised by standard
widths which may or may not conform to the user’s foot shape (Frey et al., 1995;
Soames & Evans, 1987). The toe box is likely to be narrower and pointed, forcing
toes to occupy unnatural positions (Stewart, 1945, 1972) and relative torsional
inflexibility (Stacoff, Kalin, & Stüssi, 1991).
Habitual use of modern footwear from early childhood influences foot shape and
function (D'Aout, Pataky, De Clercq, & Aerts, 2009; Rao & Joseph, 1992; Staheli,
1991; Staheli, Chew, & Corbett, 1987; Staheli & Giffin, 1980). A study of 441
participants aged from 1 to 80 years found that flat feet are usual in infants, common
in children and within the normal range of observations in adult feet (Staheli et al.,
1987). Static footprints of 2,300 children between the ages of 4 and 13 years
established the incidence of flat feet to be 8.6% in children who wore closed shoes
and 2.8% in children who had never worn shoes (Rao & Joseph, 1992). The authors
concluded that shoe-wearing in early childhood was detrimental to the development of
the normal longitudinal arch. A retrospective study of 1,846 skeletally mature adults
found the incidence of flat feet was 3.27% in those who began wearing shoes before
the age of 15 and 1.75% in those who began to wear shoes from the age of 16
(Sachithanandam & Joseph, 1995). Flat foot was highest in the obese and in those
who had worn footwear for over 8 hours per day. However, even after adjusting for
these variables, flat foot was most prevalent in those who began using footwear before
they were 6 years old (Sachithanandam & Joseph, 1995).
In contrast, a study of 1,851 children between 3 and 12 years in both rural and urban
Congo found age, followed by footwear worn, to be the major determinant of foot
arch structure (Echarri & Forriol, 2003). However, no assessment of the type and
frequency of footwear worn was reported other than 1,119 of the children habitually
wore shoes. In the African context this detail is important as shoes worn are very
different to Western affluent populations and predominant footwear type near the
Equator tends to be minimal footwear such as sandals. The findings from another
study, using biomechanical as well as anthropological markers of foot function,
support the contention that footwear has a negative impact (D'Aout et al., 2009). Foot
21
function was compared between 70 habitual barefoot and 137 shod walkers in India to
48 western participants. Barefoot walkers had wider feet, lower peak pressures and
unremarkable arch structure (both Indian groups) while Western feet had greater
variance in arch height (D'Aout et al., 2009). A study of 858 Austrian children’s feet
and their footwear confirmed the significant relationship between incorrect shoe size
and toe deformity (Klein et al., 2009). In essence, the “modern” Western foot, from
which studies derive their findings, can be considered abnormal (D'Aout et al., 2009).
However, foot function may return to pre-shod levels if the individuals habitually go
barefoot or wear minimal footwear (Lieberman et al., 2010; Robbins & Hanna, 1987).
Stewart, an orthopaedic surgeon, concludes his review of the history, uses and abuses
of footgear with a succinct message:
In view of the evidence one wonders if our western habit of shoeing our
children at the earliest possible age, and of wearing shoes from bed-up to beddown, is unwise, if not positively detrimental. Might it not be better to
encourage our children and ourselves to go barefooted, in the sanctity of our
own homes at least, to develop and retain the inherent strength and pliability
of our feet? (Stewart, 1970, p 122)
Any form of footwear placed between the sole and the ground has the potential to
alter foot and whole-body dynamics by altering normal sensory feedback loops, and
changing force vectors and load distributions (Hennig & Milani, 2000; Milani,
Hennig, & Lafortune, 1997; Reinschmidt & Nigg, 2000). In the barefoot state the
foot-ground contact area remains unchanged over time during weight-bearing as the
skin and underlying structures do not undergo wear in the same way as footwear does.
Thus, walking barefoot will not change the inherent structure and function of the foot,
but it provides a great deal of variability in terms of input signals from the plantar
surface which may be important for healthy whole-body dynamic functioning and
enhanced perception of information (Davids, Glazier, Araujo, & Bartlett, 2003;
Davids, Shuttleworth, Button, Renshaw, & Glazier, 2004). In a study of 8 healthy
runners who ran on a treadmill in three conditions, soft shoe, hard shoe and barefoot,
it was found that the two shoe conditions decreased joint variability at the knee and
ankle compared to the barefoot condition (Kurz & Stergiou, 2003). Joint variability
during stance was defined by the spanning set of means and standard deviation curves
22
of the angular displacement of the knee (flexion/extension) and ankle (plantar/
dorsiflexion). The barefoot condition produced the most variability, especially at footstrike and toe-off, suggesting both sensory and mechanical changes (Kurz & Stergiou,
2003). Similar results are reported from 29 participants running on a track (Rodgers &
Leveau, 1982). Barefoot was compared to footwear and footwear plus orthotic. The
dependent variables for each foot were the maximum angle of pronation, percentage
of support time in pronation and pronation velocity. Variability barefoot was so great
that this data was not even analysed (Rodgers & Leveau, 1982). Thus, footwear
influences lower extremity variability and this may be important in varying joint and
soft tissue forces and spreading load. It has been suggested that this variability may be
necessary to prevent running injuries (Hamill, van Emmerik, Heiderscheit, & Li,
1999). Bone and joint structure changes to the foot have been used as evidence for
footwear use in early humans (Trinkaus, 2005; Zipfel & Berger, 2007)
The optimisation of footwear is a goal in the treatment of injuries, but the preventative
effects have not been proven scientifically nor is there a suitable objective measure to
achieve this condition (Mayer, Müller, Hirschmüller, & Baur, 2004; Mündermann et
al., 2006). The premise is that our footwear is designed better than the natural
barefoot state and that the body (or foot) needs help with regard to shock absorption,
load transfer, stability and movement (Hennig & Milani, 2000; Reinschmidt & Nigg,
2000). Fashion, finance, sport and scientific research have driven the development of
footwear. Interestingly, in recent years there has been a trend to move away from
motion control shoes and return to historically earlier, basic designs. These include
the Nike Free running shoe (Brüggemann, Goldmann, & Potthast, 2008; Potthast et
al., 2005), Vibram FiveFingers (Squadrone & Gallozzi, 2009) and Vivo Barefoot from
Terra Plana (Nigg, 2009). The Masai Barefoot Technology (MBT) shoe is an attempt
to simulate barefoot ground variability (Landry, Nigg, & Tecante, 2010; Nigg, Emery,
& Hiemstra, 2006; Ramstrand, Andersson, & Rusaw, 2008; Ramstrand, Thuesen,
Nielsen, & Rusaw, 2010).
Figure 2.1 illustrates the evolutionary timeline from barefoot bipedalism to the use of
present day footwear. Within this context is the development of footwear from the
need for protection and warmth only, to the demands of fashion, finance and
23
biomedical scientific analysis. Finally, the return to elementary footwear designs
based on the original criteria has emerged over the past few years.
24
5 years ago
Minimalist footwear, barefoot running retraining
30 years ago
Development of anti-pronation shoes
150 years ago
Industrial manufacturer of footwear/ fashion/ science
15,000 years ago
First dated footwear found, used for protection and warmth
only
100,000 to 50,000 years
ago
Homo sapiens hunter-gatherers/farmers
1 million years ago
Homo erectus in Asia and Europe barefoot hunter-gatherer
2 million years ago
3 million years ago
Australopithecus in Africa
4 million years ago
Bipedalism evolved
Figure 2.1 Schematic illustration of the time-line from barefoot bipedalism to the
use of modern day footwear
25
2.3
The Foot-Ground Interface
… forces acting on the foot during the stance phase act as an input signal
producing a muscle reaction. … If an intervention counteracts the preferred
movement path, muscle activity must be increased. An optimal shoe, insert, or
orthotic reduces muscle activity. (Nigg, 2001, p 2)
The foot-ground interface is the critical point of contact and feedback for whole-body
orientation, stability, movement and shock absorption. Forces acting on the foot
during the stance phase act as mechanical, sensory, vibratory input signals to which
the whole body adapts (Nigg, 2001). The complex nature of the interactions between
the 26 bones and 30 articulations gives the foot the degrees of freedom necessary to
achieve rapid moulding to accommodate ground variability (Morey-Klapsing,
Arampatzis, & Brüggemann, 2007). Simultaneously, it can instantaneously produce
rapid variable movements or be stable when required, but the filter between the
interfaces, such as footwear, may affect this dynamic control (Arampatzis, MoreyKlapsing, & Brüggemann, 2005; Morey-Klapsing et al., 2007). The control of this
dynamic system is centrally modulated but it has been suggested that somatosensory
information from the lower limb plays an important role (Inglis, Horak, Shupert, &
Jones-Rycewicz, 1994).
Interest in research into appropriate footwear emerged concomitant with the
increasing numbers of competitive distance runners and recreational joggers in the
1970s and 1980s (McKenzie et al., 1985). The foot-ground interface was hypothesised
to be the key to resolving the plethora of reported running injuries (Cheung, Ng, &
Chen, 2006; Clarke et al., 1983; Sheehan, 1977; Taunton et al., 2003). This
biomechanical model focused on improving the lower limb orientation to the ground
using footwear and orthotic modifications (Asplund & Brown, 2005). The aim was to
improve performance or muscle efficiency, improve stability by decreasing excess
anterioposterior or mediolateral movement and reduce injuries (Cheung & Ng, 2009;
Grau et al., 2008; Perry & Lafortune, 1995; Rodgers & Leveau, 1982). Cognizance of
evolutionary anthropological history or adaptive value of human bipedal structure is
missing in this model.
26
2.3.1
Barefoot, Footwear and Efficiency of Movement
The energetic cost of running is relatively high in man. In spite of this,
humans are adept endurance runners, capable of running down, for example,
zebra and kangaroo. (Carrier et al., 1984, p 483)
An early laboratory study compared running performance in shoes and orthotics to
barefoot running (Burkett, Kohrt, & Buchbinder, 1985). Twenty-one subjects ran on a
treadmill and the aerobic cost (as a percentage of their maximum oxygen
consumption, VO2 max) was determined whilst running barefoot, with shoes, and
with shoes plus orthotics. A significant increase in aerobic cost was found when
comparing the shoes plus orthotics to barefoot running. The authors (Burkett et al.,
1985) suggested that it was the increased mass of the footwear that contributed
towards decreased efficiency. The increased oxygen consumption of 3 to 5% running
with shoes compared to barefoot has been reported by others (Flaherty, 1994;
Squadrone & Gallozzi, 2009). The findings of decreased performance efficiency with
footwear has also been confirmed when comparing barefoot to footwear and weighted
socks (Divert et al., 2008). Twelve trained subjects ran on a 3-D treadmill ergometer
in six conditions, including barefoot, weighted diving socks (150 and 350g) and two
running shoes weighing 150 and 350g respectively. Increasing mass increased oxygen
consumption irrespective of whether the runners ran in the diving socks or shoes. Net
efficiency, which has both metabolic and mechanical components, decreased in the
sock or shoe conditions compared to barefoot.
The mechanical effects of the foot-ground interface are modified by the shoe which
leads to a decrease of stored elastic energy and a loss of 30% of the energy
(Stefanyshyn & Nigg, 2000a, 2000b). Barefoot running improves the efficiency and
strength of the calf-ankle-foot complex (Divert, Mornieux, Baur, Mayer, & Belli,
2005; Divert et al., 2008; Nigg, 2009). The results from a study comparing oxygen
consumption, heart rate and perceived exertion while steady-state running barefoot
and in footwear on a treadmill and outdoors confirm this relationship (Hanson, Berg,
Deka, Meendering, & Ryan, 2011). Oxygen consumption in shoes for 10 participants
was 5.7% and 2.0% greater outdoors and on the treadmill respectively. Heart rate and
27
perceived exertion was similarly affected. Another way of measuring mechanical
efficiency is calculating the gear ratio, defined as the ratio of the moment arm of the
ground reaction force (GRF) to the moment arm of the counteracting muscle group
(Carrier, Heglund, & Earls, 1994). Human feet and toes allow variable gearing during
running which optimises muscle contractile properties (Carrier et al., 1994).
Two contrasting studies consider the effects of footwear on mechanical and
neuromuscular measures of efficiency. Forty male subjects ran barefoot and in two
types of typical running shoes. The hardness of the shoe midsoles was measured with
a Shore C Durometer (0 to 100 units) giving hardness values of 35 and 36 (cushion
shoe) and 45 and 36 (control shoe) on the medial and lateral sides respectively (Von
Tscharner et al., 2003). Timing of post-heel-strike EMG activity of various lower leg
muscles was significantly delayed when wearing Adidas Super Nova Cushion and
Control shoes (Von Tscharner et al., 2003). Further, the intensity of the pre-heel-strike
muscle activity also increased in the two shoes. The authors concluded that tibialis
anterior adjusts to external conditions and that increased activity would suggest faster
fatigue, especially of the fast-twitch fibres, when wearing the shoes tested versus the
barefoot state (Von Tscharner et al., 2003). Although the shoes were of different
designs, no differences between the shoes were measured.
The second laboratory study using 14 runners compared the gear ratios at the ankle
and knee for 5 running shoes (on tartan) and barefoot (grass) (Braunstein, Arampatzis,
Eysel, & Brüggemann, 2010). The five running shoes chosen (Asics Nimbus, Nike
Pegasus 2004, Nike Pegasus 2005, Adidas Supernova and Nike Tailwind) were
specified as having differences in midsole cushioning material (air or gel embedded in
ethyl vinyl acetate, EVA), midsole geometry, heel height and mass. No durometer
hardness values of the midsoles were reported and all are of similar neutral design
with actual heel heights (9 to 15 mm) and mass (347 to 389 g per shoe) typical of
these shoe designs. The gear ratios and joint moments between the five shoes were
similar. The important finding was that wearing shoes affects the gearing at the ankle
and knee joints due to changes in the moment arms of the GRFs. During barefoot
running the knee and ankle joints produced lower gear ratios in mid- and late-stance
respectively, suggesting higher mechanical stress running in shoes. The reason for
comparing running barefoot on grass to footwear on the synthetic track was not
28
explained and was a significant source of error. Grass surface variability would be
greater and potentially more difficult, thus reducing the actual differences between
footwear and barefoot running. Neither study indicated how much habituation time
was accorded to each condition which could also affect results. In terms of
evolutionary selection, footwear used in these studies increased biological structural
loading, which increases risks for injury and therefore lowers individual safety or
survival factors (Diamond, 2002).
The effect of inverted (medial) orthoses on EMG of leg muscles was investigated for
15 asymptomatic participants with a pronated foot type (Murley & Bird, 2006). The
participants walked with a range of inverted custom-made foot orthoses. An increase
of at least 30% in muscle activity was recorded for tibialis anterior compared to
barefoot walking, irrespective of the shoe and degree of medial posting. Further,
peroneus longus maximum EMG increased by 21% in the 15° inverted orthoses
compared to barefoot and there was a trend of increasing muscle activity in the
orthotics compared to the shoe-only condition. The authors addressed the criticism of
earlier studies that found subject-specific and variable responses to footwear and
orthotic changes (Nigg, Stefanyshyn et al., 2003; Nigg, Stergiou et al., 2003) by using
participants with a similar foot structure and custom-made orthoses for each
individual. This increased muscle activity may have had a fatiguing and deleterious
effect on whole-body function which would be a disadvantage in the context of
evolutionary adaptive value. Although the authors argued that this increased muscle
activity is beneficial, Nigg (2001) suggested quite the reverse. If footwear or inserts
were to optimise performance, muscle activity should decrease (Nigg, 2001; Nigg,
Nurse, & Stefanyshyn, 1999).
A study that addressed limitations of habituation time and number of steps
analysed used an instrumented treadmill with an in-built pressure sensor which
measured repeated consecutive steps (Squadrone & Gallozzi, 2009). Eight healthy
experienced barefoot runners ran for 6 minutes on the treadmill in three conditions:
barefoot, Vibram Fivefingers Classic (148 g, 4 mm uniform thickness barefoot shoe)
and a standard neutral running shoe (341 g, no detail provided), similar to the shoes
used by Braunstein et al. (2010). Ten days habituation time was given for each
individual to run in each shoe before the single randomised trial. Oxygen consumption
29
was 2.8 % lower for the Fivefingers compared to the standard running shoe, while
lower limb kinematics was similar between barefoot and the Fivefingers. Compared to
the standard running shoe, athletes landed more on their forefoot with reduced impact
forces, had shorter stride length and foot contact times when running barefoot and
with the Fivefingers. This study’s weakness was the small sample size and the lack of
a control group of non-habituated barefoot runners. Despite this, it adds to the
evidence of performance benefits and decreased stress while running barefoot (De
Wit, De Clercq, & Aerts, 2000; Divert et al., 2005) and in minimal shoes (Vibram
Fivefingers), enhancing the claims evolutionists (Carrier et al., 1984; Lieberman et al.,
2009; Rolian et al., 2009) and others (Robbins & Gouw, 1990; Robbins & Hanna,
1987) have made about the adaptive value of human dynamic function and structure.
Although performance and efficiency of movement is affected by footwear as
shown above (Stefanyshyn & Nigg, 2000a, 2000b), studies and reviews have focussed
on footwear as a function of correcting lower limb malalignment (Brauner, Sterzing,
Gras, & Milani, 2009). This involves manipulating the three major directional loads
acting at the foot during weight-bearing activities. These are anterioposterior,
mediolateral and vertical foot-ground loads. In the barefoot habituated runners above,
the magnitude of the vertical forces was reduced by the body intrinsically changing
the way the foot meets the ground. In the next two sections, the effect of footwear on
the anterioposterior and mediolateral GRFs is discussed.
2.3.2
Barefoot, Footwear and Anterioposterior Loading
Thus it appears that (shoe) heels from a physiological standpoint are of
primary rather than tertiary importance, being the most destructive factor in
foot physiology. (Stewart, 1945, p 137)
Heeled shoes have been the subject of much research into their effects on the
musculoskeletal system and wearing shoes with symmetrical curved heels such as the
MBT shoes (Boyer & Andriacchi, 2009; Nigg, Emery et al., 2006; Nigg, Hintzen, &
Ferber, 2006; Romkes, Rudmann, & Brunner, 2006) has been shown to change the
anterioposterior position of the body (Li, Hong, & Mao, 2003). As a consequence,
effects higher up the kinetic chain have been measured (Menant, Perry et al., 2008) if
30
the centre of gravity (COG) is shifted too far posteriorly (curved negative heeled
shoes) or anteriorly (high heeled shoes). Documented effects of heeled shoes include
the following:
Increases in:
•
external adduction moments of the knee, indicating compressive loading of the
medial joint compartment (Block & Shakoor, 2009; Kerrigan et al., 2009;
Kerrigan, Lelas, & Karvosky, 2001; Shakoor & Block, 2006; Shakoor, Lidtke,
Sengupta, Fogg, & Block, 2008; Shakoor et al., 2010);
•
impact force (Hong, Lee, Chen, Pei, & Wu, 2005; Snow & Williams, 1994;
Stefanyshyn, Nigg, Fisher, O'Flynn, & Liu, 2000);
•
plantar fascia tension and pronation (Reinschmidt & Nigg, 1995; Robbins &
Hanna, 1987; Wolf et al., 2008);
•
Achilles tendon loading (Reinschmidt & Nigg, 1995);
•
weight on the metatarsal heads (Corrigan, Moore, & Stephens, 1993; Snow,
Williams, & Holmes, 1992; Stewart, 1972; Zipfel & Berger, 2007);
•
ankle inversion stress, lateral weight shift and asymmetric muscular fatigue
(Gefen, Megido-Ravid, Itzchak, & Arcan, 2002; Kerr, Arnold, Drew, Cochrane,
& Abboud, 2009; Snow & Williams, 1994; Stacoff, Steger, Stüssi, &
Reinschmidt, 1996; Wright, Neptune, van den Bogert, & Nigg, 2000);
•
heart rate and oxygen consumption during gait (Li et al., 2003);
•
muscle work at the hip, knee and ankle (Esenyel, Walsh, Walden, & Gitter,
2003; Poterio-Filho et al., 2006; Stefanyshyn et al., 2000);
and decreases in:
•
postural muscle tone and foot position sense (Robbins, Gouw, & McClaran,
1992; Robbins, Waked, & McClaran, 1995; Sekizawa, Sandrey, Ingersoll, &
Cordova, 2001);
•
leg venous pressure impairing the efficiency of the muscular calf pump
(Poterio-Filho et al., 2006);
•
ankle and foot plantar flexor muscle power and work during stance (Esenyel,
Walsh, Walden, & Gitter, 2003);
31
•
dynamic postural stability (Menant, Perry et al., 2008; Menant, Steele, Menz,
Munro, & Lord, 2008).
Heeled shoes have also been hypothesised to decrease stimulation of brain
neurotransmitters as a result of decreased concentric and eccentric ankle-foot muscle
activity (Flensmark, 2004, 2009). This decrease was suggested to affect brain health
and mental disease (Flensmark, 2004, 2009); however, the putative association still
needs to be confirmed.
Bilateral 2 cm heel lifts changed the erector spinae (earlier onset) and gluteus medius
(later onset) muscle activation patterns versus barefoot in 13 normal subjects while
walking (Bird, Bendrups, & Payne, 2003). In another study using 15 young females
and 2 days habituation to a 2 cm heel lift, erector spinae activity increased
immediately by 19.2% after heel strike (Barton, Coyle, & Tinley, 2009). After
habituation it was 24% higher than in the shoe only condition with an earlier onset
(Barton, Coyle et al., 2009). The observed changes in electromyographic activity may
be linked to the shift of the centre of mass forwards and the increase in vertical and
anterioposterior forces (Stefanyshyn, Nigg, Fisher, O'Flynn, & Liu, 2000), requiring
more work for maintaining postural stability (Menant, Perry et al., 2008).
Increasing heel height also increases impact forces (Lieberman et al., 2010;
Squadrone & Gallozzi, 2009) and medial forefoot pressure (Yung-Hui & Wei-Hsien,
2005). This increased impact has been associated with increased risk for degenerative
joint disorders (Kerrigan, Todd, & Riley, 1998; Mündermann, Dryrby, & Andriacchi,
2005; Radin, Burr et al., 1991).
Impact collision forces and foot strike patterns while running over a 25 m track
(indoor) and Kenyan school playground (hard-baked earth outdoors) have been
compared in habitually barefoot (or minimal footwear without heels) versus runners
who normally wear modern elevated cushioned running shoes (Lieberman et al.,
2010). The strength of this study was the laboratory and real-life field experiments.
Participants were habituated to the shoe conditions (barefoot/shoe), and a large
number of running trials were performed at self-selected running speeds. Two
embedded force plates were used in the laboratory study, with a total length of 1.2 m
32
allowing undirected foot strikes. High speed video cameras and 3-D kinematic and
kinetic analysis were used to calculate foot-strike type, joint angles, running speed
and impact-transient magnitudes while running barefoot or in the supplied Asics
Cumulus 10 neutral running shoe (USA) or own running footwear (Kenya). Table 2.1
summarizes participant group profiles and frequency of foot strike patterns.
Table 2.1
Foot Strike Patterns (%) of Habitual Barefoot and Shod Runners from
Kenya and the USA (Lieberman et al., 2010)
Participants
Age ± SD
(years)
Rear-foot Strike
%
Mid-foot Strike
%
Fore-foot Strike
%
B
S
B
S
B
S
8 adults USA
Habitual footwear
19.1 ± 0.4
(shoes)
83
100
17
0
0
0
14 adults Kenya
Recent footwear
23.1 ± 3.5
(12.4 ± 5.6)
9
29
0
18
91
54
8 adults USA
Recent barefoot
38.3 ± 8.9
(< 2 yrs)
25
50
0
13
75
37
16 adolescents
Kenya
13.5 ± 1.4
(barefoot)
12
-
22
-
66
-
17 adolescents
Kenya
15.0 ± 0.8
(shod < 5 yrs)
62
97
19
3
10
0
B: Barefoot; S: Shoes; SD: Standard deviation; RFS: rear-foot strike; MFS: mid-foot strike; FFS: forefoot strike
One finding was the rear-foot strike (RFS) pattern of individuals who habitually ran in
heeled shoes and the mid- (MFS) and fore-foot (FFS) strike patterns of those
habitually barefoot differed (see Table 2.1). Kenyan runners who only recently started
using shoes were more likely to use FFS (54%) and reverted almost completely when
barefoot (91%). More importantly, those barefoot runners who used FFS patterns had
three times lower collision forces and lacked an impact transient of the GRF
compared to those barefoot and in shoes who used RFS patterns. This may be related
to the flatter foot placement found while running barefoot or in minimal footwear
compared to conventional running shoes (Bishop, Fiolkowski, Conrad, Brunt, &
Horodyski, 2006; De Wit, De Clercq, & Aerts, 2000; Squadrone & Gallozzi, 2009).
This flatter foot placement has also been shown to decrease impact and knee loading
while barefoot running using the Pose method (Arendse et al., 2004). It has long been
33
argued that this impact transient typically measured while walking and running has
deleterious effects on joint loading such as the knee (Andriacchi & Mündermann,
2006; Brandt, Dieppe, & Radin, 2009; Chen, O'Connor, & Radin, 2003; Jefferson,
Collins, Whittle, Radin, & O'Connor, 1990; Radin, Yang, Riegger, Kish, & O'Connor,
1991).
Another important finding from this study is that the RFS pattern commonly thought
to be immutable can change to MFS or FFS depending upon the footwear worn
(Squadrone & Gallozzi, 2009). For example, habitually barefoot adults (USA) had
RFS patterns of 25% while running barefoot but 50% while in the supplied new
cushioned shoe suggesting the shoe design has a large influence in this running
pattern. Barefoot Kenyan children had a ratio of 12% to 66% RFS to FFS patterns. In
contrast, the frequency of RFS in Western endurance runners is 75 to 80%
(Hasegawa, Yamauchi, & Kraemer, 2007). In terms of running performance and
efficiency, MFS and FFS runners, have shorter ground contact times, have a higher
frequency of inversion at contact and run faster (Hasegawa et al., 2007; Lieberman et
al., 2010). These strike patterns improve the storing and releasing of elastic energy in
the longitudinal arch which has evolutionary significance (Jungers et al., 2009; Kerr et
al., 2009; Raichlen et al., 2011) and may be responsible for improved running
economy barefoot (Flaherty, 1994). It is therefore not surprising that Africans
dominate elite middle to long distance racing in the world despite little difference in
physiological factors (Coetzer et al., 1993).
Laboratory-based studies using footwear and orthotics to modify the heel touchdown
and mid-stance angles during walking and running predominantly use RFS
participants who may already have an adapted gait as a result of their habitual heeled
footwear (Stackhouse, Davis, & Hamill, 2004). Reducing the heel height may be a
simpler method of decreasing excessive impact, motion at the heel and fore-foot and
improving foot muscle strength (Brüggemann et al., 2008; Lieberman et al., 2010;
Nigg, 2009; Potthast et al., 2005). This effect was noted when comparing elite middle
distance runners running fast barefoot, in their spikes or running shoes (Stacoff et al.,
1991). Improving foot muscle strength and whole-body neuromuscular control has
become the focus of new directions in rehabilitation and research (Biewener & Daley,
34
2007; Bonacci, Chapman, Blanch, & Vicenzino, 2009; Landry, Nigg, & Tecante,
2010; Wikstrom, Tillman, Schenker, & Borsa, 2008a).
Masai Barefoot Technology (MBT) shoes are widely used in Europe as a therapeutic
tool theoretically simulating barefoot walking by destabilising the anterioposterior
foot-ground interface (Boyer & Andriacchi, 2009; Nigg, Emery, & Hiemstra, 2006;
Nigg, Hintzen, & Ferber, 2006; Romkes, Rudmann, & Brunner, 2006; Stewart,
Gibson, & Thomson, 2007). An argument for the use of these shoes (and other
minimalist footwear) is that traditional footwear designed with the aim of stability and
support leads to the deterioration of foot, ankle and muscle function (Boyer &
Andriacchi, 2009; Landry et al., 2010; Potthast et al., 2005). However, while these
shoes simulate barefoot variability, they are very different to actual barefoot gait
(Nigg, 2009; Nigg, Hintzen et al., 2006). Compared to barefoot or other conventional
footwear, these rounded heel-less unstable shoes:
•
increase ankle dorsiflexion at initial contact and mid-stance (Boyer &
Andriacchi, 2009);
•
increase tibialis and gastrocnemius muscle activity during the stance phase
(Romkes et al., 2006);
•
shift anteriorly and increase the centre of pressure variability (Nigg, Hintzen et
al., 2006; Stewart et al., 2007);
•
decrease gait step length and speed (Romkes et al., 2006)
•
improve static balance after 12 weeks of use (Nigg, Emery et al., 2006);
•
improve reactive balance barefoot and in shoes after 8 weeks in children with
disabilities (Ramstrand, Andersson, & Rusaw, 2008).
Using a 6-week habituation period, 28 healthy participants used the MBT shoe for
daily work and comparisons were made before and after 6 weeks of muscle activity
and postural sway while standing barefoot in the MBT shoe and a stable shoe (Landry
et al., 2010). Muscle activity of flexor digitorum longus, the peroneal and anterior
compartments, all increased in the unstable shoe, as did postural sway which suggests
that MBT shoes selectively activate foot muscles. In a 6-week prospective study of 40
golfers with non-specific back pain, the golfers in the intervention group who wore
35
unstable sandals had decreased perceived pain compared to the controls (Nigg, Davis,
Lindsay, & Emery, 2009). There was no change to their golfing performance or to
their static balance and dynamic balance times.
In an epidemiological study of 100 subjects (50 in each group) over 10 months, shoe
type influenced lower limb injury rate (Brüggemann et al., 2008). The group using the
Nike Free shoe, a minimalist shoe attempting to mimic barefoot running kinematics,
had a 29% lower injury rate. A previous study from the same group showed improved
foot-toe function using this shoe (Potthast et al., 2005). Although “barefoot shoes”
such as the Adidas Feet You Wear, INOV-8 Bare Grip, New Balance Minimus, Nike
Free, Vivo Barefoot and Vibram FiveFingers (Squadrone & Gallozzi, 2009) are a
contradiction in terms, they appear to provide benefits to individuals and only long
term epidemiological studies can evaluate their effectiveness (Jungers, 2010;
Lieberman et al., 2010; Nigg, 2009). The importance of these new barefoot shoes is
the return to simpler symmetrical designs brought about by the problems associated
with present footwear (Brüggemann, 2007; Nigg, 2009; Richards et al., 2009).
The conclusion drawn from these studies is that changes in the human body’s
anterioposterior orientation caused by footwear type compared to barefoot may not
optimise the preferred movement pathway. Rather, they may increase metabolic,
muscular and biomechanical loading. The unstable shoe, such as MBT, could be used
as training and strengthening tool in the short term. In the long term heeled footwear
may be damaging to whole-body systems causing injury. This changes the way the
foot meets the ground during walking and running. Based on the evidence presented,
the heeled shoe does not have adaptive evolutionary value and must be considered a
technological change with significant risk (Dobzhansky, 1960). The presence of a
heel, compared to a flat shoe, increases all components of the GRFs (Snow &
Williams, 1994). Study 2 (Chapter 5) measures anterioposterior GRF’s during the
performance of a weight-bearing dynamic transition task. The effect of personal
footwear compared to barefoot and increasing mediolateral asymmetry on the
variability of the anterioposterior GRF is investigated. The research presented
indicates anterioposterior GRF changes can be measured when comparing very
different footwear characteristics. The question proposed in Study 2 is whether subtle
differences between footwear conditions can also be measured using this GRF
36
variable. The assessment of personal footwear worn by participants for Study 1
(Chapter 4) and Study 2 (Chapter 5) includes heel-height and midsole hardness, two
characteristics known to influence anterioposterior GRF’s. The next section considers
the mediolateral GRF component and footwear.
2.3.3
Barefoot, Footwear and Mediolateral Loading
…the elite women runners….ground reaction forces showed peaks of 3.3
times body weight in the vertical component, 0.8 times body weight in the
braking phase, and 0.3 times body weight in the mediolateral direction. The
asymmetry in their ground reaction forces was expressed mainly in the
mediolateral component (Williams, Cavanagh, & Ziff, 1987, p 107)
Changes to mediolateral loading at the foot have received widespread attention as it
has long been thought that typical high versus low foot arch structure and excessive
supination (increased lateral loading) or pronation (increased medial loading) are
associated with specific injuries to the lower limbs (McKenzie et al., 1985; Williams,
McClay, & Hamill, 2001; Yamashita, 2005). Orthotics that have a medial arch with or
without medial posting at the fore- or hindfoot posting are likely to increase lateral
loading at heel-strike (Ball & Afheldt, 2002a; Dixon & McNally, 2008; Mündermann,
Nigg, Humble, & Stefanyshyn, 2003; Yu et al., 2007) while lateral fore- or hind-foot
posting increase medial loading (Milani, Schnabel, & Hennig, 1995; Nester, Van Der
Linden, & Bowker, 2003). There may also be subject-specific unpredictable responses
to shoe design and orthotic insert and these may be over-estimated using skin versus
bone pin markers measurements (Ball & Afheldt, 2002a; Dixon & McNally, 2008;
Milani & Hennig, 2000; Mündermann et al., 2003; Nigg, Stergiou et al., 2003;
Stacoff, Reinschmidt et al., 2000; Stacoff et al., 2001; Yu et al., 2007). This section
discusses changes in mediolateral loading measured in prospective studies of ankle
and lower leg injured participants. Pronation, joint coupling and the control of these
using medial footwear modifications are next considered. Finally, studies that assess
footwear, the effect of lateral wedging and lateral stiffer shoes are discussed in the
context of entire lower limb function.
37
Changes to mediolateral loading occur as a result of injury and footwear. A
prospective study of risk factors in lower limb injuries in 223 physical education
students over a period of 6 to 18 months has been reported for ankle inversion sprains
(Willems, Witvrouw, Delbaere, De Cock, & De Clercq, 2005). Static lower leg
alignment, 3-D kinematics and plantar pressure profiles were collected during the
barefoot stance phase of the running gait. Ankle injured participants (22 inversions
sprains, one bilateral) were compared to 36 non-injured students. Those at risk had
increased lateral plantar pressure and centre of pressure (COP) shifts at initial, midand forefoot contact during the push off phase. These also had increased total foot
contact time suggesting a time delay and inhibition at initiating the push off phase of
the first toe. A mobile foot type was identified during contact of the first metatarsal to
heel-off with increased pressure under the medial side of the foot. The pressure under
the hallux was decreased, indicating poorer ankle-foot-first toe function and the
possible loss of the homogenizing action of flexor hallucis on the talocrural joint
(Potthast, Lersch, Segesser, Koebke, & Brüggemann, 2008; Potthast et al., 2005). No
assessment of the participants’ current and changing footwear status, amount of time
spent barefoot and gait trials within their own footwear was undertaken, so deductions
about the cause of these differences cannot be resolved (Willems, Witvrouw,
Delbaere, De Cock et al., 2005). This is an important consideration as a systematic
review of 8 controlled trials or interventions of preventive measures for ankle sprains
noted that the age of footwear plays a role and hence should be assessed (Verhagen,
van Mechelen, & de Vente, 2000).
Nevertheless, the prospective study (Willems, Witvrouw, Delbaere, De Cock et al.,
2005) highlights the mediolateral shift of the body during gait. Similar findings were
reported in another prospective 10 week study on gait-related lower leg overuse
injuries of 131 participants starting a walk to run program (Ghani Zadeh Hesar et al.,
2009). Intrinsic lower leg injuries developed in 20.6% of participants. These runners
landed more laterally and had greater force under the lateral aspect of the foot
throughout the foot contact phase (Ghani Zadeh Hesar et al., 2009). Using the same
cohort and experimental design, the findings for intrinsic gait-related risk factors for
Achilles tendinopathy suggest that a laterally directed force following heel strike and
decreased force transfer to the first toe were risk factors, rather than the frequently
described over-pronation (Van Ginckel et al., 2009). No footwear was assessed and
38
running trials were conducted barefoot which may not have been usual for these
individuals.
A prospective study of 131 triathletes also reported supination as increasing overuse
injury risk by a factor of four (Burns et al., 2005). Another prospective study
compared mediolateral plantar pressure distribution during gait of 65 patients with
functional and mechanical ankle instability to 100 healthy controls (Becker,
Rosenbaum, Claes, & Gerngro, 1997). Patients with functional ankle instability had
significantly greater lateral heel loading while walking. These findings provide a
rationale for assessing the contribution footwear may have to either increase or
neutralise these lateral forces.
Pronation is a normal shock-absorbing component of the gait phase as weight is
transferred from the heel to the first toe for propulsion. Supination occurs at initial
foot contact (heel or forefoot strike) and heel-off (Payne, 1999). Excessive pronation
is the diagnosis most commonly reported with respect to overuse injuries of the foot,
ankle and lower limbs (Razeghi & Batt, 2000). As a result footwear design and
prescription is presently based on reducing the excessive medial moments thought to
be damaging to the lower limb and hence reducing injury risk (Butler et al., 2006;
Butler et al., 2007). These laboratory-based studies indicate decreased pronation
(eversion) with motion control footwear, but show increased impact indicating a
trade-off between control and cushioning (Mayer et al., 2004; Reinschmidt & Nigg,
2000). A further complication with regard to changing mediolateral loading is that
during walking there is a power flow from the tibia to the foot during most of the
stance phase, while in running this power flow occurs in both directions and is more
variable between individuals (Bellchamber & van den Bogert, 2000). There thus
appears to be no simple cause and effect relationship between tibial rotation and foot
pronation (Bellchamber & van den Bogert, 2000; Hargrave, Carcia, Gansneder, &
Shultz, 2003) with subject-specific neurophysiological dynamic factors playing a role
(Nigg, Khan, Fisher, & Stefanyshyn, 1998), and it yet remains widely touted as such
(Brauner et al., 2009). The movement coupling between the calcaneus and tibia
changes during the stance phase of running and is more complex than a mitred or
universal joint (Stacoff, Nigg et al., 2000). Further, variability at the ankle and knee
joints is greatest while running barefoot versus hard and soft shoes, and this suggests
39
the body responds to sensory information the foot receives and then adapts by varying
joint forces and spreading the load (De Wit et al., 2000; Milani, Schnabel, & Hennig,
1995).
Shoes designed with medial or lateral flares (wide heels) were manufactured as a
result of studies which suggested that these reduced maximum pronation and total
rearfoot movement (Clarke et al., 1983; Nigg & Morlock, 1987). An influential study
using 10 runners, 36 different shoe combinations of flares, hardness, heights and a
single rear foot mounted camera was used to determine the degree of pronation
relative to the lower leg during foot contact (Clarke et al., 1983). The conclusions
were that soft shoes (Shore A 25 hardness) and shoes without flares allowed more
pronation and rearfoot motion compared to harder (Shore A 35 or 45 hardness) and
flared shoes with 15° or 30°. In this study heel height had no effect on the measured
variables, which has not been confirmed in later research (Kerrigan et al., 2009;
Kerrigan, Lelas, & Karvosky, 2001). The limitations of this study included the 2-D
kinematics analysing rear-foot motion, ignoring whole-body effects such as joint
moments and muscle activity, and not including a comparison to the participants’
barefoot condition. Further, the small number of subjects used to compare 36
conditions was also a limitation. Subsequent studies using different techniques were
unable to confirm these findings (Lafortune, Cavanagh, Sommer, & Kalenak, 1994;
Perry & Lafortune, 1995; Stacoff, Reinschmidt et al., 2000; Stacoff et al., 2001). If the
design aim of footwear is to decrease pronation, impact loading (Perry & Lafortune,
1995) and knee external adduction moments (Franz et al., 2008) are likely to increase,
albeit with subject-specific responses (Nigg, Stergiou et al., 2003; Stacoff,
Reinschmidt et al., 2000; Stacoff et al., 2001). However, the shoes with the flares
were found to increase the magnitude of the mediolateral GRF. These alter joint
moments at the ankle, knee and hip, and are likely to be associated with injuries to
these structures up the kinetic chain (Cheung et al., 2006; Noakes, 2003).
Determining the optimum footwear design has so far proved to be elusive. Selectively
modifying heel design may change the direction and magnitude of mediolateral
loading (Nigg & Segesser, 1986) although subsequent research suggests this to be
inconsistent (Nigg, Stefanyshyn et al., 2003; Nigg, Stergiou et al., 2003; Stacoff et al.,
2001; Stacoff, Reinschmidt et al., 2000). A study to stepwise control pronation
40
included 28 young recreational heel-toe runners (22.3 ± 17.1 km.week-1) who ran
slowly (3.5 m.s-1) over 13 m in heel-modified neutral running shoes (Puma Bisley 3)
(Brauner et al., 2009). The heel midsole was abraded to create 3 different shoes with
the medial side thicker than the lateral margin (0°, 1°, 2° and 3°), similar to the effect
of lateral heel wear or compression. Frontal plane kinematics were calculated from
data recorded using an accelerometer, goniometer, and single force platform. A small
systematic decrease in pronation excursion was measured from the neutral to the 3°
shoe (14.5° ± 1.3° to 12.7° ± 1.5°) without changes in ground reaction force
parameters or maximum supination angle. Runners did not perceive differences in
shoe design. Limitations of this study included a 2-D kinematic analysis of foot
motion only over a short runway, shoe mounted goniometer changed between shoes
and no comparison with barefoot running gait. Detail with regard to habituation time
in each condition was lacking, as was a comparison with the participants’ own
running shoes or other footwear. However, the importance of this study is the small
systematic alteration of shoe characteristics that is very different to most shoe
intervention studies. The aim was to find a way of optimising footwear for each
individual.
Changing mediolateral conditions at the foot has an effect higher up the kinetic chain
such as at the knee (Haim, Rozen, Dekel, Halperin, & Wolf, 2008). However, this
effect is modified by lower-limb and trunk movement. A direct relationship, thus,
cannot be inferred only from changes in foot pressure to knee loading (Andrews,
Noyes, Hewett, & Andriacchi, 1996; Erhart, Mündermann, Mündermann, &
Andriacchi, 2008). The medial compartment of the knee is 10 times more likely to be
affected by osteoarthritis in the general population (Ahlback, 1968) and this is
reflected in a large external adduction moment caused by increased medial forces
(Block & Shakoor, 2009, 2010). As a result, analysis of changes to mediolateral
loading using footwear modifications, include joint moments at the hip, knee and
ankle, as well as foot motion (Erhart, Mündermann, Mündermann, & Andriacchi,
2008; Kerrigan et al., 2009; Mündermann, Asay, Mündermann, & Andriacchi, 2008;
Mündermann, Dryrby, & Andriacchi, 2005; Shakoor & Block, 2006; Shakoor, Lidtke,
Sengupta, Fogg, & Block, 2008). The subject-specific variability in ankle and knee
joint moments (Kakihana, Akai, Nakazawa, Naito, & Torii, 2007; Kakihana, Akai et
al., 2005; Kerrigan et al., 2002) noted in studies with regard to lateral heel wedging
41
may be linked to the large uniform prescription of 4° to 10° irrespective of the shoe
condition. Only a few studies have addressed this issue by considering subjectspecific alterations based on pain reduction (Barrios, Crenshaw, Royer, & Davis,
2009; Butler, Marchesi, Royer, & Davis, 2007), comparing barefoot to different shoe
designs (Kerrigan et al., 2009; Shakoor & Block, 2006; Shakoor et al., 2008; Shakoor
et al., 2010) or comparing a new shoe with and without lateral wedging (Barrios et al.,
2009). The following study partly addressed this fundamental issue by using small
hardness changes at the lateral heel midsole (Fisher, Dyrby, Mündermann, Morag, &
Andriacchi, 2007).
In contrast to the running study (Brauner et al., 2009) discussed, 3-D kinematics and
kinetics were used to assess knee loading which is directly related to the ratio of
medial to lateral joint reaction forces (Fisher et al., 2007). Six shoe conditions were
tested while walking on an 11 m runway. These included two shoes with a stiffer
lateral heel midsole (medial/lateral Asker C Durometer hardness 50/60 and 50/75),
two shoes with the lateral heel thicker than the medial (4° and 8° angle) and a placebo
flat shoe (medial/lateral Asker C durometer hardness density 50/50). These were
compared to the 14 participants’ own control walking shoes (Fisher et al., 2007). Only
the peak knee adduction moments, associated with medial knee osteoarthritis, were
reported. These were reduced up to 16 % for the stiffer and altered angle shoe but not
for the placebo shoe. Participants with higher knee adductions moments in their own
control shoes had greater reductions in adduction moments with the interventions. The
reduction in knee adduction moments was more predictable with the 4° angled shoe,
although the effect was greater in the 8° angled shoe. However, there was more
variation (larger confidence intervals) between subjects suggesting subject-specific
relationships to each intervention. In comparison, walking in flat mobility shoes
compared to a standard stability walking and personal shoes a decrease of 8 to 13 %
in medial knee loading has been reported (Shakoor et al., 2008). An 11.9 % decrease
in the external knee adduction moment has also been measured walking barefoot
compared to own personal footwear (Shakoor & Block, 2006).
A key element missing from this study is the lack of detail with regard to the control
participants’ shoe(s) to which all comparisons were made. This might partly explain
the difference in external knee adduction moments and subject-specific reactions.
42
Specifically, shoe assessment with regard to medial and lateral density (which was
reported in detail for the intervention shoes), heel height (other shoes were reported as
flat), age and frequency of use (Taunton et al., 2003), and asymmetric heel wear or
compression are all critical factors influencing the mediolateral GRFs and knee
adduction moments (Block & Shakoor, 2010; Kerrigan et al., 2001; Shakoor et al.,
2010). Further, no barefoot walking comparison assessment was made, which is
important when contemplating interventions to reduce knee adduction moments
(Shakoor & Block, 2006; Shakoor et al., 2008). Habituation details for each shoe prior
to testing were absent. Surprisingly, the results for the flat placebo shoe were similar
to the participants’ shoes. This result differs from other studies (Shakoor et al., 2008;
Shakoor et al., 2010). Mediolateral stability is related to midsole softness (Robbins,
Waked, Gouw, & McClaran, 1994; Robbins, Waked, & Krouglicof, 1998) and the flat
soft placebo shoe with hardness Asker C 50 units may explain these results. The
question whether an asymmetric or uniform increase in hardness would be equally
beneficial has not yet been answered and requires further research.
A general limitation of the footwear studies to-date has been the focus on foot
eversion (pronation) only, the use of 2-D kinematics (Grau et al., 2000), and shoe and
skin mounted markers which over-estimate movement (Reinschmidt, Stacoff, &
Stüssi, 1992; Stacoff, Nigg, Reinschmidt, van den Bogert, Lundberg et al., 2000;
Stacoff, Reinschmidt, & Stüssi, 1992). Studies evaluating footwear changes need to
include the hip, knee and ankle in order to explore and understand relationships
(Barton, Levinger, Menz, & Webster, 2009; Kerrigan et al., 2009). Many studies have
small sample sizes and do not report confidence intervals. The lack of habituation to
the conditions such as barefoot (D'Aout et al., 2009) and participant-specific
characteristics relevant to the intervention (Mündermann et al., 2006) may also affect
experimental results. Footwear used in most experiments has been new or specifically
adapted for the intervention, and the current status of footwear worn by participants
has not been analysed or considered a variable in the research process.
Despite these limitations, results indicate that footwear can affect the lever arms
between the heel and ground, thereby affecting the size and symmetry of mediolateral
moments and hence joint stress at the hip, knee and ankles (Divert et al., 2005; Kerr et
al., 2009; Robbins, Waked, Allard, McClaran, & Krouglicof, 1997; Shakoor & Block,
43
2006; Shakoor, Lidtke et al., 2008; Shakoor et al., 2010). Typically this change has
been reported between 8 to 16 % at the knee (Fisher et al., 2007; Shakoor et al., 2008)
and 4 to 11 % at the hip (Shakoor & Block, 2006) while walking. During running,
these have been reported to be higher, 38 % for knee varus torque and 54 % in hip
internal rotation torque when comparing stability running shoes with barefoot
(Kerrigan et al., 2009). If the primary research focus is on foot motion only, other
neuromuscular influences up the kinetic chain may be missed (Kerrigan et al., 2009).
There is increasing evidence that the human body interacts with the ground in a
dynamic variable way, altering movement patterns based on current sensory input to
produce the most efficient and least damaging pathways (Kersting & Brüggemann,
2006; Nigg & Wakeling, 2001; Perry, Radtke, & Goodwin, 2007; van Emmerik &
van Wegen, 2002).
Study 1 (Chapter 4) investigates the effect on the performance of a neuromuscular
heel-raise task while perturbing barefoot mediolateral conditions. Measurement of the
mediolateral perturbation uses typical clinical assessment, rehabilitation and sporting
performance measures of time and number. Study 2 (Chapter 5) measures
mediolateral GRF’s directly using two force platforms while participants perform a
weight-bearing dynamic transition task. The effect of personal footwear compared to
barefoot and increasing mediolateral asymmetry on the variability of the mediolateral
GRF is investigated. The research presented indicates mediolateral GRF changes can
be measured when comparing very different footwear characteristics and
interventions. The question proposed in Study 2 is whether subtle differences between
footwear conditions can also be measured using this GRF variable. Personal footwear
is also assessed in both studies. The characteristics most likely to influence changes to
mediolateral GRF’s were chosen based on the research presented here. These include
the measurement of medial and lateral outersole thickness and midsole hardness. The
next section briefly considers studies assessing the effect of sensory influences and
how these provide further insight into the foot-ground interface.
44
2.3.4
Barefoot, Footwear and Somatosensory Influences
The inadequacy of this footwear in protecting against injury is postulated …
on inadequate … plantar surface sensory-mediated feedback control…
(Robbins, Hanna, & Gouw, 1988, p 85)
Biomechanical models for the lower limb have been inadequate to comprehensively
direct the prescription of footwear. Over the past two decades, the role of the
sensorimotor system in the etiology of injury and effects of footwear on this system
have been explored. Footwear is considered a potential modulator of neuromuscular
control and athletic performance (Bonacci et al., 2009). A systematic review
concludes footwear changes muscle activity of the legs and back (Murley, Landorf,
Menz, & Bird, 2009). This section will provide an overview of reported mechanisms
whereby footwear may affect changes to the sensorimotor system.
Important sensory feedback loops within the joints, syndesmosis, ligaments, tendons,
muscles and plantar surface of the foot contribute towards the control of posture and
gait (Inglis et al., 2002; Nurse & Nigg, 2001; Perry, McIlroy, & Maki, 2000;
Vuillerme & Pinsault, 2007). Psychophysical studies have shown specific regional
sensory variation on the plantar surface, with the highest thresholds in the hallux and
toes, followed by the heel, lateral forefoot, lateral arch and metatarsals (Inglis et al.,
2002; Nurse & Nigg, 1999). The fact that the medial longitudinal arch has low
sensitivity to inputs may be interpreted as having a lesser role in this important
regulatory feedback mechanism. The brain has the ability to distinguish location
specific inputs and this feedback is important in regulating muscle timing and
intensity (Nurse & Nigg, 2001). The processing of cutaneous messages from the sole
allows the CNS to analyse information and initiate responses to reduce the gap
between the body position and the equilibrium position (Kavounoudias, Roll, & Roll,
1998; Roll, Kavounoudias, & Roll, 2002; Watanabe & Okubo, 1981). The
information from the sole influences muscle-rhythm control directly or indirectly at
the cerebral-basal-ganglia level, which is important when considering interventions at
the foot (Watanabe & Okubo, 1981). The processing of this information is dependent
on accurate and reliable somatosensory inputs from the foot (Vuillerme & Pinsault,
2007).
45
Changes in proprioceptive or cutaneous information from the periphery may disrupt
the model of the body that the brain uses for movement, potentially causing sensorimotor incongruence (McCormick, Zalucki, Hudson, & Moseley, 2007) and global
deficits in performance (Evans, Hertel, & Sebastianelli, 2004; Franettovich, Chapman,
Blanch, & Vicenzino, 2010; Goldie, Evans, & Bach, 1994). If sensory information is
inhibited or changed from a portion of the foot due to faulty footwear, movement
patterns and muscle activity may also be affected, potentially contributing towards
injury (Bullock-Saxton, 1994; Bullock-Saxton, Janda, & Bullock, 1994). Studies have
investigated the effect of changing sensory input from the sole of the foot on postural
responses and gait by:
•
vibration (Nurse & Nigg, 1999);
•
cooling (Nurse & Nigg, 2001);
•
anaesthesia (Fiolkowski, Bishop, Brunt, & Williams, 2005; Perry, McIlroy, &
Maki, 2000; Schwellnus, Azevedo, Rayner, Arendse, & Noakes, 2004);
•
type of footwear or surfaces (Chen, Nigg, Hulliger, & de Koning, 1995; Perry,
Radtke, & Goodwin, 2007; Robbins, Waked, Allard, McClaran, & Krouglicof,
1997; Vuillerme & Pinsault, 2007);
•
orthotics (Bird et al., 2003);
•
textured insoles (Chen, Nigg, & De Koning, 1994; Nurse, Hulliger, Wakeling,
Nigg, & Stefanyshyn, 2005; Waddington & Adams, 2000, 2003).
All show some effect on muscle activity, dynamic postural function and gait. Some
important findings of these studies indicate that cutaneous mechanoreceptors provide
distinctive information in balance reactions which cannot be substituted using vision
(Perry et al., 2000). The specific distribution pattern and type of plantar cutaneous
afferent mechanoreceptors in the sole of the foot are thought to code for contact
pressures and provide input with regard to foot-ground position, standing balance,
weight transfer and movement control (Eils et al., 2002; Hennig & Sterzing, 2009;
Kennedy & Inglis, 2002; Perry et al., 2000). This important kinaesthetic information
may be reduced or altered (Robbins & Gouw, 1991; Robbins & Waked, 1997) by
using footwear that reduces the variability of sensory input and decreases the quality
of information required centrally for optimal performance (Davids et al., 2004; Kurz
& Stergiou, 2003; Perry et al., 2007). These are critical both for maintaining balance
46
in single-limb stance and detecting foot contact during movement. Altering sensory
feedback, changes gait kinetics and muscular activation patterns (Nurse & Nigg,
2001). The loss of sensation from the foot interferes with the automatic ability to alter
leg stiffness essential for efficient movement and postural stability (Fiolkowski et al.,
2005).
The protection of the barefoot compared to the rest of body skin has been investigated
in 12 normally shod healthy males (Robbins, Gouw, McClaran, & Waked, 1993). A
volley of 35 painful abrading loads to the foot and thigh skin sites over a 5-min period
was administered. Plantar skin required 600% greater abrading loads to reach pain
threshold. At 24 hours after abrasion, redness and hypersensitivity was observed in all
subjects for the thigh whereas only 8.3% reported hypersensitivity on the plantar
surface (Robbins et al., 1993). The conclusion reached was that plantar skin possesses
a high pain threshold and is well protected through sensory feedback from abrasive
injuries while barefoot. In habituated barefoot individuals, it is possible this difference
would be amplified. Further research by this group on the sensitivity of the plantar
surface to loading barefoot and in athletic footwear confirms the idea of a sensorymediated feedback control system imparting protection during gait and the negative
effect footwear has on this somatosensory system (Robbins & Gouw, 1991; Robbins
et al., 1989; Robbins et al., 1988) Specific sites of the plantar surface were identified
as more or less sensitive to penetration and loading and affected by footwear and
modified irregular surfaces. A load of 9 kg and 10 mm penetrometer induced pain at
the heel pad, first toe and first metatarsal-phalangeal joint in 6%, 32% and 66% of
participants respectively (Robbins, Gouw, & Hanna, 1989). This research on plantar
surface sensitivity was investigated further in the following studies.
Waddington and Adams (1999) found ankle injured subjects have impaired single-leg
ankle inversion discrimination in both the injured and uninjured limbs. These psychophysical experiments involved standing participants estimating the position of their
ankle when suddenly exposed to an inversion movement on a motorised platform.
Elite uninjured netball and football players also performed more poorly while in
socks, football and netball sports shoes when compared to the barefoot state
(Waddington & Adams, 2000, 2003). Improving sensory information in the shoes
using a textured insole enhanced single-leg ankle inversion performance to barefoot
47
levels. In two prospective studies which evaluated risk factors for ankle sprains
between 1 to 3 years in 241 male (Willems, Witvrouw, Delbaere, Mahieu et al., 2005)
and 159 female (Willems, Witvrouw, Delbaere, Philippaerts et al., 2005) physical
education students, impaired ankle inversion discrimination and postural stability
were some of the factors implicated. It has been argued that footwear acts as a filter
damping critical noise from the foot-ground interface and thus impairing sensory
information (Nigg, 2001; Perry et al., 2007). For example, decreasing
somatosensation from the foot using a foam mat increased the destabilizing effect of
trunk extensor muscle fatigue on postural stability (Vuillerme & Pinsault, 2007). To
enhance the accuracy of foot position sense, more sensory information is needed. One
way suggested to achieve this is to increase variability or noise from the foot-ground
interface, which is thought to occur with the textured insole or barefoot (Davids et al.,
2003; Davids et al., 2004).
Impact and balance using GRF’s collected from a force platform were compared on
footwear EVA of varying stiffness (Robbins & Waked, 1997) in 12 healthy men (30 ±
6 years). Two tasks were performed. The first, a step forward and down 4.5 cm,
landing on one foot and balancing for 5 s (ten trials) and the second four trials of
single leg stance for 30 s (Robbins & Waked, 1997). Four different support surfaces
(bare platform, 7, 12, 25 Shore A durometer hardness) were tested. Maximum impact
expressed as a percentage of body weight and sway velocity, radial and rectangular
area of COP values was systematically significantly different between each condition.
Sway velocity was 25.9 % lower on the bare force-platform than on the softest
interface. A similar effect was measured in the other variables with impact moderating
over the ten trials. These results support the notion that foot position sense and
stability is affected by midsole properties which interfere with mechanoreceptor
stimulus (Robbins & Waked, 1998; Robbins & Waked, 1997; Robbins, Waked, &
Krouglicof, 1998). A similar experiment compared nine interfaces: thin (7 mm) and
thick (14 mm) high and low resiliency and the bare force-platform (Robbins et al.,
1998). Four trials of 15 s with eyes-open in single-leg barefoot stance were compared
in 30 older (66 ±3.0 years) and 30 younger (34 ± 6.0 years) men. Stability was
inferred using COP derived measures of mean velocity, radial and rectangular area.
Sway velocity was 223% and 17% poorer for younger and older groups respectively
while standing on the soft surface equivalent to typical athletic and walking shoes
48
midsoles. Comparing thin interfaces and progressive softness, sway velocity was
worse by 311% and 31% for young and old respectively. Similar findings were
reported for the COP radial and rectangular areas. Further, participants over 60 years
had significantly poorer stability for all measures compared to the young. These
studies did not directly assess human somatosensory function but argue a case for
impairment based on the gross instability measured (Robbins et al., 1997; Robbins et
al., 1998).
In conclusion, these and other sensory studies (Robbins et al., 1993; Robbins et al.,
1992; Robbins et al., 1997; Robbins et al., 1995) indicate that small changes to the
foot-ground interface have the potential to influence single-leg balance and gait
performance. Decreasing somatosensation from one area of the foot alters sensory
feedback and motor output (Robbins et al., 1998). Footwear introduces a filter to the
foot-ground interface and the very presence of it changes sensory input and
performance compared to the barefoot state (Perry et al., 2007). No studies have
assessed the effect of footwear mediolateral asymmetry created by design or typical
wear patterns at the heel. This thesis does not directly measure somatosensory
changes at the foot or brain. Study 1 (Chapter 4) and Study 2 (Chapter 5) assess and
measure the extent of mediolateral asymmetry of personal footwear because it is
deduced that this asymmetry will change somatosensation in areas of increased or
decreased wear and affect global neuromuscular performance. Both studies then
introduce an asymmetry and measure changes to performance and postural stability.
The inference is that these asymmetric changes will affect the somatosensory system
and hence whole body performance. Similarly, the extent of personal asymmetric
footwear is compared to the quality of barefoot and in-shoe performance (Sections
4.3.6 and 5.3.4). Asymmetric heel wear may change somatosensation at the foot by
changing contact pressures in a similar way as the anaesthesia experiments (Perry et
al., 2000; Schwellnus et al., 2004). This in turn disturbs sensory feedback to the brain,
requiring additional sensory re-weighting to compensate for the deficit (Vuillerme &
Pinsault, 2007). Should the compensation be incomplete, global postural stability and
performance may be affected. The focus of this thesis is to explore the relationship
between heel asymmetry and single-leg performance.
49
2.4
Footwear and Injury
An average 54% increase in the hip internal rotation torque, a 36% increase in
knee flexion torque, and a 38% increase in knee varus torque were measured
when running in running shoes compared with barefoot. (Kerrigan et al., 2009,
p 1058)
Despite the lack of support from research, most early recommendations for sports
footwear suggested that runners were more likely to need correction for
biomechanical abnormalities, such as forefoot and hindfoot varus or valgus
alignments (Kannus, 1992; McKenzie et al., 1985). However, no clear one-to-one
relationships between structure, mechanics and injuries have been elucidated (Davis,
2005; Hetsroni et al., 2010; Nigg, 2001; Nigg, Stergiou et al., 2003). Rather,
experimental evidence suggests non-systematic subject-specific changes occur in
lower limb movement when using shoes and orthotics (Nigg, 2001; Nigg, Stergiou et
al., 2003). Narrative and systematic reviews of the literature regarding footwear,
injuries and prevention confirm that little epidemiological evidence exists for their
prescription. These reviews include:
•
the role of impact forces and foot pronation (Nigg, 2001);
•
interventions for preventing lower limb soft-tissue injuries in runners (Yeung &
Yeung, 2001);
•
interventions for preventing and treating stress fractures in the lower limbs
(Rome, Handoll, & Ashford, 2005);
•
the association with patellofemoral pain syndrome in runners (Cheung et al.,
2006);
•
insoles for the prevention and treatment of back pain (Sahar et al., 2009);
•
effectiveness of foot orthoses for the treatment and prevention of lower limb
injuries (Hume et al., 2008);
•
footwear, foot type, injury and running performance (Richards et al., 2009);
•
insoles and shoes for knee osteoarthritis (Hinman & Bennell, 2009); and
•
foot orthoses for patellofemoral pain (Hossain, Alexander, Burls, & Jobanputra,
2011).
50
The systematic review by Richards et al. (2009) with regard to present day running
shoe design, foot type, injury prevention or performance benefits failed to confirm
any benefits ascribed to these shoes by laboratory studies and manufacturers’ claims
(Richards et al., 2009). The authors conclude that the prescription of this footwear is
not evidence based. “If we accept this finding, we are then faced with the realisation
that we have been prescribing a treatment without proven benefit for >20 years.
Worse still, these footwear prescription practices have not gone uncontested in the
literature. … In spite of these findings, guidelines that unequivocally recommend the
PCECH (pronation control, elevated cushioned heel) design continue to be published.
” (Richards et al., 2009, p 161)
A systematic review of the clinical effects of foot orthoses in the treatment and
prevention of plantar fasciitis, tibial stress fractures and patellofemoral pain syndrome
found the effects were insignificant, with effect sizes not calculated because of a lack
of information in the clinical controlled trials (Hume et al., 2008). Foot orthoses were
not effective in treating or preventing patellofemoral pain, but some studies showed
moderate beneficial effects for treating plantar fasciitis and posterior tibial stress
fractures. In another recent systematic review of foot orthoses and knee pain, Hossain
et al. (2011) assessed two trials with a total of 210 participants with risk of
performance bias. Their findings indicate no clear advantage of foot orthoses over
simple insoles (over 1 year) or physiotherapy (Hossain et al., 2011).
Evaluating the evidence from randomised controlled trials for interventions using
foot inserts and footwear modifications for preventing lower limb stress fractures
found that 13 prevention trials all involved military recruits in training, so the
participant group may not be generalized to non-military populations (Rome et al.,
2005). Pooling of data was not possible. While 4 trials evaluating shock-absorbing
insoles found fewer bone stress injuries in the intervention group, insufficient
evidence was found to determine the best insert. Evaluation of 6 randomised
controlled trials with regard to back pain and insoles (2,061 participants) and in three
mixed populations (256 participants) showed these to be low quality studies (Sahar et
al., 2009). The authors concluded there was strong evidence that insoles were not
effective for the prevention of back pain. An earlier review of insoles and footwear
51
modifications (5 trials, 903 participants in intervention groups, 3006 controls)
indicated there was no evidence that these interventions prevented lower limb soft
tissue running injuries (Yeung & Yeung, 2001). These studies also used mainly male
military recruits, limiting the generalizability of the results.
A review of footwear and insole design and modifications on knee osteoarthritis
prevention and progression indicates further clinical trials are needed to determine
their effectiveness (Hinman & Bennell, 2009). Wearing heeled stabilizing shoes can
increase the risk of disease progression by a minimum factor of 2.8. Long-term effects
of wearing high heeled shoes on disease incidence and progression remain unknown
(Hinman & Bennell, 2009). Flexible shoes with no heel may be optimal, while a
clinical trial over 12 months indicates variable stiffness shoes improve pain and
function.
Based upon the results of these reviews, little has changed from the 1990’s to the
present day with regard to the efficacy of footwear interventions to prevent lower limb
injuries. Each review concludes that more epidemiological research and quality
clinical trials are required to answer the fundamental question as to which footwear
design is beneficial. The claims of footwear manufacturers regarding injury
prevention misrepresent current knowledge and evidence (Richards et al., 2009).
This thesis does not undertake an epidemiological study of footwear and injuries but
Study 1 (Chapter 4) and Study 2 (Chapter 5) evaluate a broad range of used footwear
for degradation and mediolateral asymmetry providing detail not previously reported.
Furthermore, the measurement of heel-raise performance (Study 1) and postural
stability (Study 2) while perturbing the mediolateral foot-ground interface by
incremental amounts based upon typical wear patterns measured will provide further
insight into footwear properties and healthy human performance. A factor not
considered in clinical trials is the current status of the individuals’ footwear and how
particular characteristics such as asymmetric heel wear or hardness may mediate
effects of experimental conditions (Hinman & Bennell, 2009). The next two sections
review research in this area.
52
2.5
Footwear Degradation Through Use
The life expectancy of a shoe is determined more by the compression of the
midsole than by the wear to the outersole. The midsoles of most shoes … wear
out after about 500 to 700 km of use. (Noakes, 2003, p 265)
Aside from design issues, footwear research is complicated by two other factors.
These are, firstly, the effect of use on shoe characteristics such as outer sole wear and
midsole compression and, secondly, the number of different shoes worn by
individuals during a typical week. An individual’s shoe condition degrades through
use (Asplund & Brown, 2005; Hennig & Milani, 2000; House, Waterworth, Allsopp,
& Dixon, 2002; McPoil, 2000). Asymmetric medial or lateral outer-sole heel wear
and/or midsole compression patterns are often seen clinically in worn footwear, but
the effect of this wear on whole-body dynamic stability, fatigue, injury, pain and
performance is unknown (Asplund & Brown, 2005; Noakes, 2003; Sheehan, 1979).
Further, these changes are seldom considered prior to the prescription of footwear
modifications. Studies assessing wear have generally focused on gross midsole
degradation and cushioning properties (Hennig & Milani, 2000; House et al., 2002;
Kong, Candelaria, & Smith, 2009)
No prospective epidemiological studies currently exist which study the effect of shoe
use, design and wear on balance, injury and performance (Barton, Bonanno, & Menz,
2009; Mayer et al., 2004; Richards et al., 2009). The possible reasons for this include
difficulties with funding, supplying appropriate new footwear and monitoring wear
and use in a sufficiently large cohort over an extended period. Studies have assessed
the effect of shoe wear on some biomechanical parameters after prolonged use, either
using a mechanical degradation process or actual human wear (Cook, Kester, &
Brunet, 1985; Kong et al., 2009). For example, mechanical degradation, simulating
100 km of wear, of four different insoles used in combat assault boots by 9 military
recruits did not influence peak pressures while running (Dixon, Waterworth, Smith, &
House, 2003). In contrast, the peak pressure at the heel increased in three participants
who ran up to 500 km in supplied Reebok Aztrek DMX shoes (Verdejo & Mills,
2004). A shift medially of this pressure was noted in one participant. Disintegration
53
and structural damage of the EVA midsole was confirmed using electron microscopy
(Verdejo & Mills, 2004). Midsole density decreased in two pairs and increased in the
third compared to an unused shoe. The limitation in this study included the small
number of participants and lack of reporting changes to the outer-sole. It nevertheless
provides insight into the nature of EVA degradation.
In a longitudinal study, 24 runners were allocated one model of three new shoes (Nike
Pegasus 2005/Asics GT 2100/Spira Volaire II) differing in their cushioning material:
air or gel or spring (Kong et al., 2009). Running kinematics and kinetics were
determined while the runners ran on a 20 m laboratory runway with an embedded
force platform. This was used to calculate stance time, maximum vertical force and
loading rates. Data from a single video camera was used to calculate changes to the
torso, hip, knee and ankle angles. No individual joint loading or other neuromuscular
measures were made. Each runner then ran 200 miles and was reassessed in the
laboratory (Kong et al., 2009). No detailed analysis of each shoe was given, either
before or after the wear period, thus it is unclear if the outer- or midsole was affected
in any way from use. Further limitations of this study were the small group size of
between 5 and 10 participants in each shoe condition. Large inter- and intra-subject
variability between trials, between left and right legs and changes between rear- to
fore-foot striking occurred during the testing procedure. Shoe degradation had the
effect of increasing stance time thought to affect performance and efficiency. Other
changes measured were increased plantarflexion at toe-off but decreased ankle
dorsiflexion and forward lean of the upper body (Kong et al., 2009). No differences
between shoes were measured. The main conclusion was that constant external loads
maintained by the body are unaffected by degradation or different cushioning
properties. This has previously been reported in studies using different footwear
midsole characteristics (Kersting & Brüggemann, 1999, 2006; Kersting, Kriwet, &
Brüggemann, 2006; Nigg, Cole, & Brüggemann, 1995).
A more comprehensive study compared 19 different running shoe models new and
after 220 km of wear in 12 runners using an in-shoe pressure system (Halm PD-16)
and force platform to measure GRF forces (Hennig & Milani, 2000). In comparison to
the previous study, substantial differences were found in the peak pressure and
relative load patterns due to different shoe constructions and changes after 220 km
54
were identified. Unfortunately neither detailed shoe types/designs nor any changes to
the outer- or midsole following wear were provided. However, wear led to changes in
foot pressure at different sites. In shoe type M pressure increased laterally at the heel
and decreased at the first toe after 220 km of running. Limitations of this study
included the effect of in-shoe pressure devices (F-scan) which may interfere with
normal walking and running gait patterns (Kong & De Heer, 2009) and the number of
participants running in each shoe model.
The effects of repeated in vivo loading on shock attenuation and mediolateral stability
while running using GRF force data has also been investigated (Hamill & Bates,
1988). Six healthy participants were assessed running on a short runway over a single
force platform in new shoes. Two groups of three participants were assigned either an
unnamed Asics trainer/racer or trainer differing only in the method of manufacture of
the midsole cushioning material (compression molded versus regular EVA). Both
models had a dual density design with the lateral heel softer than the medial heel
(racer) and alternating hard and soft sections (trainer). Two weeks of training was
allowed between testing sessions in order to cover about 140 km. They were then
reassessed after covering three bouts of 140 km in training, thus giving a total of 420
km of wear. Vertical and mediolateral GRFs were analysed. After 420 km, a nonsignificant 7.3% decrease in shock absorbing properties was measured. As the
cushioning compacted, foot mediolateral control improved (Hamill & Bates, 1988).
Limitations of this study included the small sample size, individual variability as
indicated by the large standard deviations, between-day testing variability, habituation
time to the new shoe (Day 1 brand new) and no comparison to the individual’s
barefoot gait forces over the time period. The mediolateral GRF component was
combined to a single absolute value, making it impossible to compare changes in
medial versus lateral directions. This may have provided insight into the effect of shoe
degradation. Further, critical to determining the extent of shoe deterioration,
assessment of the actual outer sole wear or midsole density changes was not reported,
nor was there any comparison to the participants’ current footwear wear
characteristics.
In summary, footwear is known to change with use, either through degradation of the
midsole compressive properties or overt outer-sole wear. Measurement of the effect of
55
these changes while running indicates that individuals alter their gait to accommodate
the changed shoe condition. There is no evidence as to how this might affect injury or
neuromuscular efficiency. Detail with regard to the extent of asymmetric degradation
and its effect on human dynamic performance has not been reported. As a result, one
of the aims of this study is to evaluate the prevalence of mediolateral asymmetry in
worn footwear (Sections 3.4, 4.2.7, 4.3.7, 5.2.8 and 5.3.3) and measure the effect in a
dynamic balance task.
2.6
Footwear Assessment
Look at your shoes from behind. Is the height of the midsole at the heel
significantly higher (1 cm or more) on the outside than it is in the middle of
the shoe? ... The degree of imbalance (1 cm) in the heel would be more than
sufficient to produce a running injury. …use the thumb compression test to
test the midsole hardness … The greater the degree of midsole indentation
produced by this method, the softer the shoe… (Noakes, 2003, p 761)
The limitations of many footwear studies is the paucity of information with regard to
the design and degradation caused by wear, which could influence changes to the
foot-ground interface. The assessment of mediolateral asymmetry has received scant
attention either because of the assumptions based around the benefits of motion
control properties of footwear (Richards et al., 2009) or normal wear patterns
(Vernon, 2006; Vernon, Parry, & Potter, 2004). George Sheehan, one of the early
medical pioneers of exercise, running and health, suggested that very small
mediolateral alterations at the heel, brought about by wear, could influence the onset
of injuries (Sheehan, 1979; Sheehan, 1977). He suggested replacing the shoe or
correcting for this wear by running on the opposite road camber. While footwear
assessment has been described in detail by many researchers (McPoil, 1988, 2000;
Nigg & Segesser, 1992; Noakes, 2003; Yamashita, 2005), the clinical validity of most
criteria used is unknown (Barton, Bonanno et al., 2009; Mayer et al., 2004). For this
thesis the critical features, based on the footwear research previously discussed,
include those which affect anterioposterior and mediolateral orientation of the body to
the foot-ground interface. Outer-sole wear patterns, differences in midsole
56
compression and heel height have consistently been evaluated in past research, but the
objective measurement of mediolateral asymmetry was virtually non-existent.
Outer sole wear patterns attributing clearly delineated patterns of normal, medial and
lateral wear per individual have been described (McPoil, 2000; Yamashita, 2005), but
no epidemiological data was provided to substantiate these claims. Relationships
between shoe structure and design, age, frequency of use and wear patterns of all
footwear worn by the same individual have not been investigated. The assumption is
that the outer sole wear of a single pair of footwear is typical of wear for that
individual in all their other footwear (McPoil, 2000; Noakes, 2003; Yamashita, 2005),
the premise being that each individual has a fixed wear pattern which is immutable
and is caused by one of three foot types: normal, flat flexible or rigid high-arched
(Asplund & Brown, 2005). The hypothesis that a one-to-one relationship exists
between foot type, pathology and shoe wear patterns has been questioned by a
qualitative analysis of shoe wear patterns (Vernon et al., 2004). In this survey, 214
podiatrists were asked to associate pathology with shoe wear patterns. Fifty-six (26%)
podiatrists responded providing 425 possible wear patterns for 4 pathologies. The
results indicated that multiple wear patterns were suggested for particular foot
pathologies which is contrary to traditional beliefs (Vernon et al., 2004). Vernon
(2004) concluded that there are many other external factors such as shoe design, age,
frequency and purpose of use. These factors combined with individual specific
characteristics such as economics, gait, habit, psychological status and weight, also
influence shoe wear patterns. These need to be taken into account when analysing
wear for clinical purposes.
Habitual use of footwear from an early age may influence foot shape, dynamic
function and future pathology (Klein, Groll-Knapp, Kundi, & Kinz, 2009;
Sachithanandam & Joseph, 1995). Outer sole wear patterns may then reflect intrinsic
shoe properties, such as heeled shoes, that are different from the barefoot state and
need not be interpreted as a one-to-one relationship between foot structure and
function. Singh (1970) described, but did not measure, typical lateral outer-sole wear
patterns at the heel in 119 students and 111 children under five years old.
57
The most comprehensive detailed assessment of 30 shoes and 15 variables including
outer sole wear, midsole hardness and heel height was provided by Barton, Bonanno
et al. (2009). Fifteen participants each provided two pairs of shoes but only the
dominant shoe was assessed by two assessors on two occasions. Although intra-and
inter-rater agreement was high (83 to 100%) and reliability for continuous items was
excellent (ICC = .90 to 1.00), the number of shoes assessed (30) and the lack of
degradation, was a limitation. The authors note they were unable to provide pictorial
guidance of abnormal patterns of wear since there were none (Barton, Bonanno et al.,
2009). Outer sole tread was differentiated simply as textured, smooth, no wear, partly
or fully worn. Wear pattern was noted as normal (posterior lateral heel extending
medially to the first toe), medial or lateral. No measurement of this medial and lateral
outer-sole wear was performed.
The second component often assessed is the relative hardness/softness of the midsole
as this is important for mediolateral loading, collapse and compaction (Noakes, 2003).
A standard measurement technique is the thumb compression test whereby force,
simulating body weight, is exerted by the thumb or fingers through the outer sole into
the midsole countered by the other hand within the shoe. The amount of indentation
produced determines the midsole hardness. Previous authors rated 12 shoe midsoles
using this thumb indentation pressure as hard (<0.5 mm), moderate (0.5 to 1.5 mm)
and soft (> 1.5 mm) but found this to have low reliability, thus suggested also using a
Durometer (Barton, Bonanno et al., 2009; Menz & Sherrington, 2000).. These shoes
were not assessed for medial or lateral asymmetry by wear or design and sole
hardness was measured using a central within shoe thumb compression test, which
does not give any indication of mediolateral asymmetry. Midsole hardness can also
be measured using a durometer (Hardin & Hamill, 2002; Hardin, van den Bogert, &
Hamill, 2004). These are extensively used in footwear research (Cinats, Reid, &
Haddow, 1987; Fisher et al., 2007; Perry et al., 2007; Robbins & Waked, 1997;
Robbins, Waked, Gouw, & McClaran, 1994). The Durometer is the international
standard for the hardness measurement of rubber, plastic and other non-metallic
materials (Rex Gauge Company, 2012). Durometers are described in the American
Society for Testing and Material specification ASTM D2240, which is the recognized
specification for the instrument and test procedure. Durometer type depends upon the
strength of the spring and shape of the indentor head. This indentation load senses the
58
“hardness” which can be related to other material characteristics. Increased
“hardness” is reflected in higher Durometer units with 100 units equivalent to wood or
glass.
Barton, Bonanno et al. (2009) measured lateral, medial and within shoe hardness at
the heel using thumb pressure with categories of indentation described as hard (< 0.5
mm), firm (0.5 to 1.5 mm) and soft (> 1.5 mm). A Shore A durometer was also used
to measure hardness in the same areas and the authors note problems with measuring
compression using the Durometer which requires a consistent smooth surface area to
register an accurate reading (Barton, Bonanno et al., 2009). Durometer readings may
not be possible with some shoes. Only 3/30 pairs of shoes had dual density midsoles.
This low number necessitated combining lateral and medial Shore A durometer
hardness values for data analysis and reporting. The reported range was 34 to 100
units for the outer midsoles and 10 to 87 units within the shoe heel. Reliability for
intra- and inter-rater was reported excellent to substantial for both thumb compression
and durometer readings (Barton, Bonanno et al., 2009). Superior reliability in the
second study was thought to be related to more shoes assessed (30 versus 12 shoes)
and detailed descriptions of techniques. The inner sole of these shoes was not assessed
for height, density and asymmetry of wear
Sherrington and Menz (2003) assessed 81 pairs of shoes as part of a retrospective
study of 95 elderly persons following a fall. The shoe type was divided into twelve
categories with the most common being slippers (22%), walking shoes (17%), sandals
(8%) and barefoot (7%). Footwear features assessed were heel height, fixation of shoe
to foot, heel counter stiffness, longitudinal sole rigidity, sole flexion point, tread
pattern (textured/smooth/partly or fully worn) and sole hardness, measured by
pressing down inside the heel of the shoe (soft/firm/hard). Shoe characteristics were
reported as no fixation (63%), flexible heel counter (43%), sole flexing proximal to
metatarsophalangeal joints (43%), excessively soft soles (20%) or stiff soles (19%),
smooth soles (11%) and heel height > 5 cm (3%). Limitations of this study included
assessing only the shoe reported to have been used during the fall, which was more
likely to be a slipper as most falls occurred while walking inside at home. The
influence of other shoes worn, the shoe age, frequency of wear and asymmetry of
wear or design was not assessed. Using the same footwear assessment protocol but a
59
prospective 12-month follow-up of falls in 176 participants, no relationship was found
between footwear worn at the time of the fall and risk except for barefoot and socks
(Menz, Morris, & Lord, 2006). Although barefoot and socks had increased risk,
associated activity may itself carry increased risk.
Although outer sole tread wear and midsole compression are often assessed and
described, objective measurement of mediolateral differences is lacking. Footwear
degradation is evaluated in terms of individuals’ structural imperfections, which
creates a bias in the analysis. It is the individual’s fault. Despite no published data,
current thinking explains wear patterns in terms of foot type. This precludes objective
analysis of footwear design weaknesses and other external factors which may have
contributed to the degradation in the first place (Vernon et al., 2004). Most
importantly, evolutionary history of barefoot gait and footwear are not considered in
this model. The evaluation of footwear in this thesis addresses the issues of objective
measurement of both outer-sole wear and midsole compression and the paucity of real
data of mediolateral asymmetry in a large cohort of individuals and footwear
(Sections 3.4, 4.2.7, 4.3.7, 5.2.8 and 5.3.3). Since very little is known about the effect
of mediolateral asymmetric degradation of footwear on human optimal functioning,
assessment using a dynamic task which requires neuromuscular integration forms a
fundamental part of this overall thesis design.
2.7
Dynamic Postural Stability and Neuromuscular Control
Runners need dynamic stability to maintain their gait despite uneven terrain
and other disturbances. …You are walking along, thinking of other things,
when something unexpected happens. You trip over a fallen branch, or skid on
a patch of ice, or someone jostles you. You stumble, perhaps, but you recover
and continue walking as before. How did you recover? ... Until recent years,
most researchers on human and animal locomotion have thought little about
stability. We have generally only considered static stability. (Alexander, 2007,
p 253)
60
Performance in running is linked to running economy, efficiency and central
neuromuscular control (Coetzer et al., 1993; Noakes, 2007; Noakes, St Clair Gibson,
& Lambert, 2005; Nummela et al., 2006). Injuries and footwear can interfere with this
dynamic system, potentially producing global sensorimotor deficits that can
contribute towards decreased performance (Pintsaar, Brynhildsen, & Tropp, 1996;
Tropp & Odenrick, 1988; Waddington & Adams, 1999). For example, during sudden
gait termination there is evidence of alterations to both feed-forward and feedback
neuromuscular control in patients with chronic ankle instability (Wikstrom, Bishop,
Inamdar, & Hass, 2010) and in healthy participants in footwear compared to barefoot
(Perry et al., 2007). Load sensory feedback involved in stabilisation of running affects
predominantly the more distal joints and muscles of the ankle and foot, while the hip
and knee muscles are controlled in the feed-forward manner insensitive to load
(Daley, Felix, & Biewener, 2007; Daley & Usherwood, 2010). This proximo-distal
control strategy allows efficient management of energy and dynamic stability while
running over uneven terrain (Daley, Felix, & Biewener, 2007).
Measuring changes to neuromuscular control and movement efficiency is more
difficult. The most direct and best method would be to run and measure performance
or use other measures of neuromuscular efficiency such as oxygen consumption
(Section 2.3.1). Global measures of performance or fatigue are affected by many
human factors such as motivation (Riemann, Myers, & Lephart, 2002). An indirect
measurement of neuromuscular control, such as dynamic postural stability or the
performance of a relevant task, may provide insight into factors that impair global
performance. This also reflects the strategy of modelling a complex task, with
numerous degrees of freedom, to a simpler task. This also has to be a pragmatic
choice in terms of laboratory expertise and equipment available. As a first step in
exploring the phenomenon of asymmetric wear in footwear, it was important to
choose tasks which were more amenable to experimental control. Simultaneously
attempting step-wise changes in footwear asymmetry was thought to introduce too
many uncontrolled variables and thus simpler tasks were considered. Furthermore,
this thesis is clinically based so that the tasks chosen are those familiar to most
physiotherapists and can be evaluated in part, in a clinical setting. This increases their
validity for clinical practice. Following the levels of clinical trials, this is a pre-clinical
study, investigating mechanisms whereby footwear asymmetry may affect whole
61
body balance and neuromuscular outcomes (Campbell et al., 2000). The limitation of
this strategy is that the tasks may not be generalizable to human gait and inferences
made from them may be purely speculative.
In this thesis two tasks were selected to challenge dynamic neuromuscular control
while altering mediolateral footwear conditions. The tasks were chosen on the basis
that they incorporate full weightbearing stance and require individuals to perform a
functional active movement.
2.7.1
The Heel Raise Task Used to Assess Neuromuscular Efficiency
Fore-foot strike and mid-foot strike runners require more calf- and footmuscle strength, but avoid uncomfortable potentially injurious impact
transients even when barefoot on hard surfaces. (Jungers, 2010, p 433)
Lower limb movement disorders, fatigue, pain and loss of performance are considered
to be complex inter-related variables. The assessment of these in a clinical setting
poses substantial challenges (Simmonds, 2002, 2006; Wittink, 2005). Fundamental to
a strategy of optimising footwear to enhance performance and recovery from injury,
or alternatively reduce risk, is the need for a dynamic, relevant and applicable graded
functional task (Simmonds, 2006). The measurement of the task is required to
objectively quantify the impact of footwear and shoe inserts on movement and
function in the individual. Currently, no objective clinical outcome measures for
determining optimal footwear conditions have been reported in the literature.
Functional performance tasks in the stance phase that are considered to approximate
normal gait will likely have greater ecological validity than non-weight-bearing tasks
(Waddington & Adams, 1999). Barefoot runners have a mechanical advantage with
reduced foot mass, landing mid- to forefoot (Divert et al., 2005; Squadrone &
Gallozzi, 2009), using the calf complex to control heel plant and effectively using the
elastic stored energy in the Achilles tendon and longitudinal arch of the foot for takeoff (Alexander, 1991; Carrier et al., 1994; McMahon, 1987). Hence, the single-leg
heel raise was considered a useful neuromuscular performance outcome measure
comparing barefoot to footwear or other therapeutic interventions, as it incorporates
62
elements of both mid-stance phase when sensory input is gathered (Perry et al., 2000)
and the more challenging heel-off phase or fore-foot strike pattern of gait. The singleleg heel raise is a commonly used clinical test for evaluating foot, ankle, calf muscle
and Achilles tendon function (Hébert-Losier, Schneiders, Newsham-West, &
Sullivan, 2009; Kaikkonen, Kannus, & Jarvinen, 1994; Lunsford & Perry, 1995). This
test has been used in the rehabilitation literature for decades, such as in the assessment
and retraining of lower leg musculature during the poliomyelitis era (Beasley, 1961).
Subsequently, this was extended to patients with spinal cord (Lunsford & Perry,
1995), ankle (Kaikkonen, Kannus, & Jarvinen, 1994) and Achilles tendon injuries
(Möller, Lind, Movin, & Karlsson, 2002; Möller et al., 2001). The heel-raise task and
outcome measures have been reviewed extensively elsewhere (Hébert-Losier,
Newsham-West, Schneiders, & Sullivan, 2009; Hébert-Losier, Schneiders, NewshamWest, & Sullivan, 2009).
The total number of heel raises and the rate per minute can be used for comparisons
between limbs. Rate has been controlled between 30 and 120 beats per minute by a
metronome in most previous studies (Hébert-Losier, Newsham-West, Schneiders, &
Sullivan, 2009). If it is to be used as a neuromuscular performance factor, and hence a
dependent variable, it needs to be performed as rapidly as possible and timed. The
task can also be used to assess various other neuromuscular factors, including muscle
strength, fatigue, work performed and endurance (Hébert-Losier, Newsham-West et
al., 2009; Riemann, Limbaugh, Eitner, & LeFavi, 2011), in addition to the assessment
of balance (Clark, 2007) and dynamic equilibrium and co-ordination of the wholebody (Maurer, Finley, Martel, Ulewicz, & Larson, 2007; Yocum, McCoy, Bjornson,
Mullens, & Burton, 2010). The limitation is that it is not walking or running gait so
extrapolating heel-raise performance to these activities is not directly possible.
However, it is a closed kinetic chain exercise requiring repeated concentric and
eccentric calf contractions that typically occur while walking and running (Ross &
Fontenot, 2000; Svantesson, Osterberg, Thomee, & Grimby, 1998). Further, since it is
a performance task dependent on global neuromuscular efficiency, large subjectspecific differences should be expected that would not invalidate within and between
subject comparisons.
63
Normative values for the single-leg heel-raise task were evaluated in 203 participants
comprising 122 men and 81 women with a mean age of 34.7 ± 8.5 and 29.3 ± 7.9
respectively (Lunsford & Perry, 1995). A barefoot single maximum trial was
performed on the dominant leg at a rate of 30 beats per minute with a finger tip on the
examiner. The task was terminated using both subjective and objective criteria. These
included pushing down too heavily on the examiner, flexing the knee, a decrease of
50% in the heel height initially achieved as measured by a goniometer and finally the
participant quitting. A mean of 27.9 ± 11.1 (range 6 to 70) repetitions was reported.
There were no differences between the mean number of repetitions between male and
female participants. Three examiners were required to monitor the procedures used in
this study, however the reliability of these measures and procedures were not
assessed. In healthy individuals, the total number of heel-raises achieved may or may
not be dependent upon procedure (Maurer et al., 2007; Möller, Lind, Styf, &
Karlsson, 2005; Ross & Fontenot, 2000), age (Jan et al., 2005; Maurer et al., 2007),
gender (Jan et al., 2005), height, weight and physical activity (Jan et al., 2005; Maurer
et al., 2007; Ross & Fontenot, 2000; Yocum et al., 2010).
Test-retest reliability of the single-leg heel-raise has been assessed in barefoot healthy
53 men and 47 women (Kaikkonen et al., 1994), 13 men and 4 women (Ross &
Fontenot, 2000) and 10 men in their own footwear (Möller, Lind, Styf, & Karlsson,
2005) with mean ages of 32 ± 11, 21.2 ± 1.3 and 37 (31 to 43) years respectively. A
further 148 (91 men and 57 women) patients with ankle injuries (Kaikkonen et al.,
1994) and 112 (99 men and 13 women) with Achilles tendon rupture (Möller et al.,
2002) have been used to assess reliability and validity of this task. Their mean ages
were 36 ± 12 and 39.1 ± 8.2 years respectively. Although different procedures were
used for these studies, these were clearly defined and reported. A heel-raise was
counted only if the anterior ankle touched an individual specific marker or a measured
1 cm or 5 cm heel-height was attained while the rate of performance was arbitrarily
set at 30, 40 or 60 times per minute. The participants were either allowed to touch the
wall if they lost balance and continue (Kaikkonen et al., 1994) or keep their fingers
against the wall throughout the task (Möller et al., 2005) and with a hand-held
dynamometer interface (Ross & Fontenot, 2000). A single maximum effort or two
trials with a 3 to 4 minute rest period were performed on each leg. The studies agreed
on task termination as simply the inability of the participant to lift the heel as a result
64
of muscular fatigue. One (Kaikkonen et al., 1994) or two examiners (Ross &
Fontenot, 2000) were required. The more complex the criteria, the more examiners are
required to ensure these are met. For example, in the study by Ross et al. (2000) these
included increased forward lean of greater than 2% body weight, flexing of the knee,
inability to reach the individual specific marker for 3 consecutive repetitions, or the
subject could no longer continue. Healthy participants were tested twice with an
interval of 1 to 4 weeks (Kaikkonen et al, 1994) or 5 to 7 days (Moller et al, 2005;
Ross & Fontenot, 2000). Achilles tendon rupture patients were evaluated at 6, 12 and
24 months following surgery or conservative management (Möller et al., 2002).
Reliability was excellent for both legs in 100 participants with a mean of 40 ± 15
heel-raises and correlation coefficient (r) between the two test sessions of 0.98 (P <
0.001) (Kaikkonen et al., 1994). The large sample, gender spread and age range
provide a high degree of confidence in using this task to assess changes to the footground interface. For these healthy fit participants there was no difference in
performance between legs. Good reliability of the heel-raise task for 10 participants
was reported as ICCs of 0.78 and 0.84 for the left and right legs respectively (Möller
et al., 2005). The combined mean for the two test sessions was 28.0 ± 4.4 and 29.4 ±
4.6 heel-raises and the difference between days was 1.7 ± 5.4 and 1.2 ± 8.4 heel-raises
for the left and right legs respectively. The authors noted the large range in
performance although no range was reported. The difference in the mean number of
heel-raises between the studies may be linked to the sample size and the 5 cm heel
height required registering a completed heel-raise for the Moller et al. (2005) study.
Only one examiner was required to monitor the procedure. The 17 highly trained
military recruits achieved a mean of 32.0 ± 10.8 (range 12 to 59) and 33.3 ± 10.1
(range 18 to 56) on day 1 and day 7 respectively (Ross & Fontenot, 2000). Reliability
was excellent with an ICC of 0.96 between the two test days and there were no
significant differences between legs or days. None of these studies considered the
influence of age, gender, height, weight and physical activity in their analyses.
Although each of these studies used different procedures, test-retest reliability was
considered good to excellent on either leg. This suggests the heel-raise task is reliable
and consistent irrespective of procedure. The difference in total number of heel-raises
achieved may be explained by the heel-raise height expectation or the amount of
finger-tip support. These studies provide confidence in the clinical use of the heel65
raise task through the strength of their sample size, varied populations studied,
detailed but diverse operational procedures, bilateral leg testing and similar test-retest
reliability results.
A barefoot heel-raise study with finger-tip support on a cane in 95 fit children, aged 7
to 9 years found age, gender, height, weight, BMI and physical activity level had no
significant effect on the dominant single-leg heel-raise performance (Maurer et al.,
2007). Detailed complex operational procedure is described requiring a 2-D video
Camcorder and three examiners. The children completed 36 ± 18 (range 10 to 100).
Inter-rater (ICC = 0.99) and rater versus motion analysis system (ICC = 0.97)
reliability was excellent. The conclusion was that a single therapist’s visual
observation can determine the number of heel-raises accurately. The study also points
out the large variability in performance in these children possibly due to motor-skill
and psychological factors such as motivation and attention durations. No footwear
was assessed as a possible factor in heel-raise performance. Four outliers were
excluded from the results but no detail as to why this was done is given. In contrast to
the children, gender and age but not height or weight influenced heel-raise
performance in 180 (90 male) sedentary volunteers aged between 21 and 80 years (Jan
et al., 2005). The procedure was identical to that of Lunsford & Perry (1995). Testretest reliability, assessed one week apart using 20 participants was excellent with an
ICC of 0.89. The performance range was extremely low from 0 to 46 or 30 for males
and females respectively. Only 26.7% males and 10.0% females achieved more than
20 heel-raises and they were in the 21 to 40 year old category. Termination of the task
was attributed to a loss of balance in 95.6% of participants. Mean heel-raises for
men/women (age category) were 22.1/16.1 (21 to 40 years), 12.1/9.3 (41 to 60 years)
and 4.1/2.7 (61 to 80 years). The exclusion criteria of any form of exercise may
account for these low values and is similar to children from 5 to 12 years with plantar
flexion weakness (Yocum et al., 2010) or post-achilles tendon rupture (Möller et al.,
2002). Results from these studies indicate that the choice of participants will influence
the outcome if they are very young, over 60 years old, have a lower leg injury and are
of different levels of physical activity. The importance of these two studies for this
thesis is that a single examiner is reliable in counting the number of heel-raises and
further test-retest reliability is confirmed in a large non-exercising population. The
66
results for the sedentary population also provide a measure of construct validity as
they performed worse than fit individuals.
Convergent validity of the heel-raise test has been addressed in studies that compare
performance using different tasks or measurements (Kaikkonen et al., 1994; Moller et
al. 2002; Moller et al., 2005; Yocum et al., 2010) while construct validity has been
evaluated in healthy individuals with those recovering from injury or surgery or
compromised in some other way (Kaikkonen et al., 1994; Möller et al., 2002; Yocum
et al., 2010). In ankle injured participants recovering post surgery, the number of heelraises performed was significantly related to subjective opinion and other functional
assessments of each patient (Kaikkonen et al., 1994). The results differentiated
patients who were functionally excellent (53 ±19 heel-raises) to those who were poor
(25 ±18 heel-raises) and to the 100 non-injured reference group (40 ± 15 heel-raises).
A prospective randomised study of 112 patients with Achilles tendon rupture (99 men
and 13 women, mean age of 39.1 ± 8.2 years, range 16 to 65 years) compared
outcomes of conservative management (53) or surgery (59) and function between the
non-injured and injured leg over 2 years (Möller et al., 2002). Measurements included
tendon width, calf circumference, ankle range of movement and muscle strength
testing using an isokinetic dynamometer and a clearly defined endurance heel-raise
task. The number of heel-raises performed, irrespective of treatment method and
gender, was significantly different in the injured side at 6, 12 and 24 months. The
authors concluded that the heel-raise task is an important functional evaluation
method and was preferred because it is reliable, specific and differentiates side to side
differences, correlates with isokinetic measurements, uses a functional weight-bearing
position, is easy to administer and the least expensive (Möller et al., 2002). Reliability
and validity of the heel-raise test was also evaluated in 57 children developing
normally and in 34 children with plantar-flexion weakness (Yocum et al., 2010).
Significant differences in performance were measured between groups and an
improvement with increasing age in the normal group. The ICCs (> 0.90) provide
excellent evidence of intra-rater, inter-rater and test-retest reliability while construct
validity was supported by the differences in performance between the healthy and
impaired function groups. Moderate correlations, as expected, between the single-leg
heel-raise and vertical jump (r = 0.66) and dynamometry (r = 0.56) were found for all
67
children. These studies indicate heel-raise performance is sensitive to impairment and
hence may be useful in assessing footwear asymmetry.
The studies reviewed here used a range of operational procedures but were tightly
defined and hence reliability was similar between studies. The more complex the
procedures, the more removed from clinical practice and the greater number of
examiners or instrumental monitoring are required. No studies validated the
instruments used to measure joint ROM, finger tip pressure, heel-height, electronic
counting and body position (Hébert-Losier, Newsham-West et al., 2009). However, in
keeping within the resources available for this thesis, this limitation of potential
experimenter bias was considered. A previous study compared video and examiner
monitoring of the heel-raises, reporting reliability excellent (ICC=0.97) for a single
examiner (Maurer et al., 2007). Up to four examiners and instruments have been used
to monitor body lean, pressure of fingers on wall or stick or examiner, knee position,
heel height, counting the number of heel-raises and termination point (Lunsford &
Perry, 1995; Yocum et al., 2010). In order to avoid many of these subjective
decisions, procedure in the study of this thesis was kept as simple as possible
(Kaikkonen et al., 1994) and as close to typical clinical practice. This complex
multitude of procedural detail was reduced by eliminating hand support, focusing on
the specific task and termination criteria. Instructions were identical for each
performance which is important for reliability and consistency purposes. These
included to touch down with the heel, go as high as possible each time and go as fast
as possible without falling over or touching down with the opposite leg. This was
clearly defined and the variables (counting and timing with a stopwatch) are well
used, easily available measures, allowing the task to be performed and measured at
any venue.
In summary, the single-leg heel-raise task has been extensively used in clinical
practice and research studies. It is reliable if a standardised procedure is used and
valid in discriminating differences between injured and non-injured populations. The
number of heel-raises performed may be dependent upon the procedure and the
physical fitness of the individuals. Other demographic factors such as age, gender,
height, weight and BMI may also influence the performance and need to be included
in any analysis of the data. For the purpose of this thesis, it was considered that there
68
was sufficient evidence that this measure could be used reliably within the context of
a research study. It is a valid weight-bearing task that is also used in the clinical
setting by physiotherapists as part of assessment and rehabilitation of patients with
various lower limb disorders. To address reliability of this task, Study 1 (Chapter 4)
uses a tightly controlled cross-over experimental design, a detailed pragmatic
repeatable specific procedure adapted from the reviewed studies, inclusion criteria of
age and fitness level and a statistical analysis including all potential demographic
factors and variability of performance. No study reviewed analysed footwear as a
possible factor in heel-raise performance. Study 1 (Chapter 4) breaks new ground as
footwear asymmetry is simulated while barefoot heel-raise performance is compared
to each individual’s footwear condition.
2.7.2
The Transition from Double- to Single-Leg Stance Task Used to
Assess Dynamic Postural Stability
One sensory source that has the potential to provide critical information for
the control of stepping is the input from the soles of the feet regarding
pressure. This afferent information may be particularly relevant to the control
of the swing-limb unloading, foot-lift, foot-contact and weight transfer. …
The implication that sensory information from the sole of the foot is critical in
controlling stability during single-leg support is supported by observations
that subjects are unable to balance on one leg after anaesthesia of the sole.
(Maki & McIlroy, 1997)
Footwear acting as a filter has the potential to interfere with sensory information from
the foot leading to changes in dynamic postural stability (Maki, Holliday, & Topper,
1994; Robbins et al., 1998; Robbins et al., 1995). Rocker-bottomed or MBT shoes,
have been compared to stable control shoes in quiet standing by measuring centre of
pressure (COP) excursion on a force plate and muscle activity (Albright & WoodhullSmith, 2009; Betker, Moussavi, & Szturm, 2005; Landry et al., 2010; Nigg, Hintzen
et al., 2006). These shoes had a destabilizing effect on balance as measured by
increases in COP excursion. Variations in midsole hardness and the very presence of
it compared to barefoot, has been shown to affect the dynamic balance control system
(Perry et al., 2007). Thick, soft midsoles will deform while weight-bearing and act as
69
a cushioning interface but can also perturb balance and postural sense compared to
barefoot stance. Athletic footwear compared to barefoot increased anterioposterior
sway and sway velocity in single limb stance with eyes open or closed in 12 healthy
participants (Papadopoulos, Nikolopoulos, & Athanasopoulos, 2008). An elevated
heel of only 4.5 cm impaired balance in the elderly compared to flat hard shoes
(Menant, Steele et al., 2008)
The choice of a dynamic balance test to explore the effect of increasing footwear
asymmetry on postural stability was made after considering different possibilities.
Walking and running gait, the preferred option, was excluded because of the number
of conditions proposed for the sudy design. Dynamic stability measurements using
unstable platforms (Maki, McIlroy, & Perry, 1996; Perry et al., 2000), cushioning
mats (Vuillerme & Boisgontier, 2008; Vuillerme, Danion et al., 2001), step downs
(Wikstrom, Tillman, & Borsa, 2005), sudden gait termination (Perry et al., 2007;
Perry, Radtke, McIlroy, Fernie, & Maki, 2008), hopping and jumping (Ross &
Guskiewicz, 2004; Ross, Guskiewicz, Gross, & Yu, 2009; Wikstrom, Tillman,
Chmielewski, & Borsa, 2006) have all been used to address the sensitivity and
validity limitations of static balance tests. Some of the dynamic measurements, such
as single jump landings, however, show high variability and performance difficulty
even in a healthy, physically capable, athletic population (Emery, 2003; Hrysomallis,
McLaughlin, & Goodman, 2006). Biomechanical instruments available also determine
the type of laboratory based tasks.
The dynamic task which includes a transition from double- to single-leg stance
(Rogers & Pai, 1990) was chosen over other possible tasks such as the static singleleg stance timed balance test (Emery, 2003). The latter may not be functional or
sensitive enough to assess postural stability in those who can undertake ordinary daily
living activities with little observable impairment (Emery, 2003). The double- to
single-leg stance movement has been used to investigate variables related to
neuromuscular control between uninjured people and those with pelvic pain
(Hungerford, Gilleard, & Hodges, 2003), lower limb injuries (Sole, Milosavljevic,
Nicholson, & Sullivan, 2011; Van Deun et al., 2007) and between young and old
healthy individuals (Jonsson, Seiger, & Hirschfeld, 2004). The variables included in
these studies were EMG of 7 trunk and hip muscles in 14 injured and 14 healthy
70
individuals (Hungerford et al., 2003), gluteal, quadriceps and hamstring muscles in 16
hamstring injured and 18 control participants (Sole et al., 2011) and 14 lower limb
muscles in 10 chronic ankle instability and 30 healthy participants (Van Deun et al.,
2007). Changes in the activation and timing of muscles were measured between
injured and healthy participants. In the subjects with ankle injuries these changes were
measured not only at the ankle but also proximally throughout the lower limb. The
task has also been used to assess gluteus medius/adductor longus muscle activity
EMG ratios in groin injured (9) and matched uninjured (9) football players (Morrissey
et al., 2012). A significant 20 to 40% reduction in activation was measured on both
legs during stance or the moving leg compared to controls. No mention is made of
footwear worn, nor is force platform data analysed or reported. Validity of the task to
identify differences between injured and uninjured subjects is confirmed with these
studies. No reliability was reported with any of these studies.
Postural stability while performing three trials of the hip-flexion task was compared
using the vertical and mediolateral force variability in 28 (20 women) healthy elderly
(70.5 ± 3.8 years) and 28 (16 women) young (29.9 ± 4.2 years) adults (Jonsson et al.,
2004). During the first 5 s there was a rapid decrease in force variability and thereafter
a static phase in single-leg stance up to the total of 30 s. Six elderly participants could
not complete the total time on one leg. However their data was analysed in the
relevant time windows. Differences between the groups related to a more rapid
decrease and lower variability in the static phase for the young participants. Force
variability from both force platforms were analysed, log transformed and expressed as
a percentage of body weight. The results from this study indicate that the task tested
the ability of each participant to shift the centre of mass over the stance leg and then
maintain it above the centre of pressure (Jonsson et al., 2004; Rogers & Pai, 1990).
Anterioposterior force variability was disregarded in this study as thought not to be
influenced by the task (Jonsson et al., 2004). Age, in this case over 65 years old, was a
factor in task performance.
To shift the body centre of mass laterally while moving from bipedal to single-leg
stance is essential for the initiation and continuation of normal human gait (Hanke &
Rogers, 1992; Rogers & Pai, 1990). Hence this task has also been used to compare
transitions between legs of 8 post-acute hemiparetic patients while standing on two
71
force platforms (Rogers, Hedman & Pai, 1993). Individual and resultant mediolateral
GRF components acting on the body was recorded. There were changes in the spatial
and temporal aspects of the mediolateral GRFs such as delays in onset times between
limbs and reversals in the normal direction of force application in the paretic limb.
These affected dynamic lateral weight transfer function essential for normal gait
initiation. Although the task does not include the propulsive gait component, it
requires recruitment of lateral hip muscles of the flexing limb and an ipsilateral
increase in the vertical GRF concurrent with a displacement of the COM towards the
weight bearing leg and COP to the flexing leg similar to gait initiation (MacKinnon &
Winter, 1993; Mann, Hagy, White, & Liddell, 1979; Murray, Seireg, & Scholz, 1967;
Rogers & Pai, 1990; Winter, 1995). Perturbing the foot-ground interface medially or
laterally would in theory affect this ability to shift the centre of mass and require
neuromuscular compensation (Winter, 1995). Standing hip-flexion is also a common
clinical test for pelvic control and requires efficient functioning of the load/unload hip
abductors/adductors (Winter, 1995).
Reliability of the task has only been assessed in one study. Eighteen healthy adult
volunteers (10 female) with a mean age of 31.1 ± 8.6 years (Hanke & Rogers, 1992)
were repeatedly assessed in two blocks of four trials of 5 s. These were completed by
each participant “as fast as possible” and at a natural speed. When comparing trials at
fast speeds moderately high ICC values (0.66 to 0.93) were reported for the dependent
variables. Only the transition phase mediolateral and vertical GRF data was analysed
from underneath the moving leg. No results for the stance limb were reported.
Consistency of measurement is related to instrumentation and tester error or
variability in performance (Hanke & Rogers, 1992) In this thesis, the first two were
minimised by using the force platform and specific GRF measurements from the data.
The timing of each phase (bilateral stance, transition and single-leg stance) could
easily be isolated as they corresponded to the light signal (off/on) and the point when
the vertical GRF reached zero as the flexing limb left the force platform.
A limitation of the task of transition from double- to single-leg stance is that it does
not include the propulsive component of gait (foot-strike and lift-off). However, it is
clinically appropriate for a wide age-range and a component of a number of daily
living activities that include stepping and gait. It is also not too fatiguing to perform
72
repeatedly (Hanke & Rogers, 1992; Jonsson et al., 2004; Rogers & Pai, 1990). In
order to be reliable, clinical tasks need to be strongly controlled and standardized
(Pinsault & Vuillerme, 2009). Along with somatosensory information from the foot,
vision plays a crucial role in postural stability (Redfern, Yardley, & Bronstein, 2001).
In order to perform this dynamic task vision is not restricted and may compensate
individuals for any postural perturbation initiated by changing the foot-ground
interface (Lord & Menz, 2000; Nougier, Bard, Fleury, & Teasdale, 1998; Redfern et
al., 2001). The influence of other individual characteristics such as age, except in one
study (Jonsson, Seiger, & Hirschfeld, 2005), gender, height and weight has also not
been investigated.
2.7.3
Force Platform Measures
In order to measure postural stability while performing the dynamic transition task the
force platform was chosen as the instrument as it is considered to be the gold
standard, is validated and has been used to predict injury risk and assess sensorimotor
deficits (Goldie, Evans, & Bach, 1994; McKeon & Hertel, 2008b; Prieto &
Myklebust, 1993; Tropp, Ekstrand, & Gillquist, 1984b). To quantify standing balance
there are many different types of force assessment systems that are used to calculate
GRF and COP as well as different methods to perform these calculations (Gerbino,
Griffin, & Zurakowski, 2007). The COP displacement and velocity as well as
variation of the horizontal and vertical GRF are typically analysed when comparing
postural stability (Pinsault & Vuillerme, 2009; Ross, Guskiewicz, Gross, & Yu,
2009). Problems with detecting and interpreting small intra- and inter-individual
differences have led to the development of more challenging dynamic tasks and
sophisticated calculations based on the force platform data (McKeon & Hertel, 2008a;
Prieto, Myklebust, Hoffmann, Lovett, & Myklebust, 1996; van Emmerik & van
Wegen, 2002; Wikstrom, Tillman, & Borsa, 2005).
Increased force plate measurement values are thought to indicate impaired balance
(Ross et al., 2009) but in dynamical systems theory the reverse may be true (Davids et
al., 2003; Van Emmerik & Wagenaar, 1996). Further, only 55% of force plate
measures used in research detected balance deficits during single-leg stance in
individuals with ankle instability and thus the sensitivity of these measures to
73
discriminate postural instability is questioned (Ross et al., 2009). Using static singleleg stance and a dynamic single-leg hop, 10 measures identified group differences
between stable and unstable ankles (Ross et al., 2009). In this study 22 uninjured
participants were matched by height, weight, age, gender and leg tested to 22
individuals with diagnosed ankle instability. Three single-leg 20 s trials were
performed using their own footwear which was not assessed. Trials were repeated if
participants lost balance and touched down with the opposite leg. Seven trials were
used for the single-leg hop task and extra trials were given for failed balanced
landings. Stepwise discriminant function analysis determined the force plate measure
differences between groups, the percentage of ankles correctly classified and the
measures that accurately discriminated between groups. The standard deviation of the
mediolateral ground reaction force (static and dynamic single-leg stance) and the
anterioposterior time to stabilization (dynamic hop task) were the most accurate in
discriminating between unstable and stable ankles. The accuracy scores were 0.73 and
0.72, with high effect sizes of 0.92 and 0.80 respectively (Ross et al., 2009). Other
measures reported with “fair” accuracy (>0.69) included the standard deviation of the
anterioposterior ground reaction force and mediolateral mean COP velocity.
Definitive procedural, reliability and validity studies by Goldie et al. (1989, 1992 and
1994) have guided much of the research on postural stability. Using 28 healthy
participants with a mean age of 28.1 ± 8.0 years, bilateral, step, tandem and single-leg
stance positions were evaluated barefoot with eyes-open or closed on a single forceplatform for 32 seconds. The random sequence was repeated 10 minutes later (Goldie,
Bach, & Evans, 1989). Analysis was limited to 15 s because of failed trials. The retest
reliability of the standard deviations of the force/COP measures for the preferred
single-leg stance eyes open were 0.64/0.49 and 0.61/0.30 for anterioposterior and
mediolateral directions (Goldie et al., 1989). Force measures were the best predictors,
reliable and consistent in quantifying postural control between different levels of
stance difficulty. A second study of 24 participants with mean age 25.7 ± 6.5 years
assessed retest reliability of barefoot single-leg stance with eyes-open or closed on
both legs (Goldie, Evans, & Bach, 1992). Four trials of 5 s were performed twice with
a 5 minute rest for each of the 4 conditions. All retest reliability coefficients were
significant and better than the previous study for the force measures and these
included 0.81 and 0.79 for the preferred and non-preferred legs with eyes-open for
74
mediolateral force variability (Goldie et al., 1992) Reliability was improved by
decreasing the stance time and so avoiding balance failures. The strongest predictor
for single-leg postural stability was the variability in the mediolateral force with
values of 70% and 60% for the preferred and non-preferred legs respectively. This
replicated the previous studies findings of 63.2% and 79.0% of the variance were
attributed to the mediolateral force component (Goldie et al., 1989). There were no
significant differences between each leg tested. Neither study considered age, gender,
height, weight or BMI in their analyses although an equal number of males and
females were selected for each study.
The anterioposterior or mediolateral force axis depends upon the clinical condition
being studied (Goldie et al., 1989; Goldie et al., 1992, 1994). Similarly, the reliability,
sensitivity and validity of the COP velocity in both the anterioposterior and
mediolateral directions has been confirmed with repeated tests showing good
intrasubject consistency (Geurts, Nienhuis, & Mulder, 1993; Prieto et al., 1996).
Although there is a correlation between measures, some may quantify different
aspects of postural control; hence a range of measures may be required (Karlsson &
Frykberg, 2000; Maki, Holliday, & Fernie, 1990; Prieto et al., 1996; Ross et al.,
2009). Thus, the analysis of force platform data in this thesis includes a number of
these measures reported to be reliable and relevant to the footwear interventions.
The validity of using force platform measures to discriminate between healthy and
injured individuals has been extensively addressed (Goldie et al., 1994; Goldie,
Matyas, Spencer, & McGinley, 1990; Tropp et al., 1984b; Tropp, Odenrick, &
Gillquist, 1985; Wikstrom, Tillman, & Borsa, 2005; Wikstrom, Tillman,
Chmielewski, & Borsa, 2006). The choice of the task and dependent variables
measuring postural stability appears critical to show differences pre- and/or postinjury (Ross & Guskiewicz, 2004; Ross et al., 2009). A systematic review of postural
control, lateral ankle stability and instrumented testing highlights this fact (McKeon &
Hertel, 2008a). This comprehensive review concludes that testing on a force platform
identifies deficits associated with increased risk of ankle sprain and that occur
following acute sprains (McKeon & Hertel, 2008a). Postural stability is also impaired
in both the injured and uninjured legs compared to controls. Chronic ankle instability
has not been consistently detected with these traditional measures and tasks (McKeon
75
& Hertel, 2008a). A meta-analysis of balance capabilities following ankle trauma also
confirms that postural control impairments are present in patients with an acute and
chronic history of acute ankle injury and this extends to both limbs (Wikstrom, Naik,
Lodha, & Cauraugh, 2009).
In a study of 127 soccer players, those with reduced postural stability, a global deficit
not linked to previous injury, had a significantly higher risk of sustaining an ankle
injury in the following season (Tropp et al., 1984b). Decreased postural stability has
also been linked to ankle inversion injuries in prospective studies of 159 women and
241 men (Willems, Witvrouw, Delbaere, Mahieu et al., 2005; Willems, Witvrouw,
Delbaere, Philippaerts et al., 2005). A similar association has been demonstrated for a
single-leg balance test and ankle injury (Trojian & McKeag, 2006). While in a
prospective study of 100 over 60 year olds, control of lateral stability was found to be
the best predictor of future risk of falling (Maki, Holliday, & Topper, 1994) and is
considered a major problem for postural stability in the elderly (Maki et al., 2008;
Maki & McIlroy, 1996). At 8 weeks following a unilateral ankle inversion injury, 24
balance-trained and 24 untrained athletes, all who had returned to their sports were
assessed in single-leg stance on a force platform (Goldie et al., 1994). The variability
of the mediolateral force was used to compare postural stability. As far as possible
they were age, gender and BMI matched. Postural stability was significantly worse as
measured by the variability of the mediolateral force on the injured leg in the
untrained participants both with eyes-open and -closed. This confirms the validity and
sensitivity of using this measure when assessing changes to the foot-ground interface.
Single-leg stability, as measured by mean velocity changes, has also been used to
evaluate the effectiveness of a 6 month rehabilitation program for back pain and
discriminate between those doing well or poorly (Luoto et al., 1998; Luoto et al.,
1996). Sixty-one healthy volunteers (32 men) and 99 patients divided into 68 (33
men) with moderate pain and 31 (18 men) with severe low back pain were assessed at
the beginning and end of the program. Postural control was significantly worse for the
severe pain group at the beginning compared to the healthy controls. Postural control
deteriorated in the group whose back pain had worsened through the program but was
unchanged in the control and good outcome groups.
76
The influences of age, gender, height, weight and BMI on postural stability have been
assessed (Anker et al., 2008; Farenc, Rougier, & Berger, 2003; Geldhof et al., 2006;
Hue et al., 2007; Laughton et al., 2003; Lord & Menz, 2000; Maki et al., 1990;
Nougier et al., 1998). Based on these studies, there are conflicting results (Farenc,
Rougier, & Berger, 2003; Hue et al., 2007). Age related changes to postural stability
are more likely after 60 years but a sedentary lifestyle may also contribute to these
changes (Maki, Holliday, & Fernie, 1990; Messier et al., 2000). These factors need to
be accounted for when perturbing the foot-ground interface and choosing the
participant group.
The most extensive review and assessment of the sensitivity of age-related changes to
postural stability was with 20 young (21 to 35 years) and 20 elderly (66 to 70 years)
healthy adults (Prieto et al., 1996). This study evaluated 36 COP dependent variables
in quiet bilateral stance with eyes-open or -closed. Only mean COP velocity identified
age-related changes between groups and within group differences related to eyes-open
or –closed. An increase in mean velocity in the elderly was interpreted as worse
postural stability. This study concludes that multiple COP measures may still be
required to address differences within groups. In 50 elderly women greater than 65
years old, mean COP velocity was a predictor of falls and negatively associated with
increased BMI after adjustments for age, vision, reaction time and hearing
(Lichtenstein, Shields, Shiavi, & Burger, 1988). BMI (range 17.4 to 63.8 kg/m²)
predicted 52% of the variance in mean velocity with age contributing a further 3% in
59 male subjects (Hue et al., 2007). Height and foot length were not correlated.
The perturbation of the foot-ground interface in the medial or lateral direction and its
effect on postural stability is the main aim of Study 2. The instrument available, the
participant demographics, the nature of the task chosen and the mediolateral
interventions determine the choice of dependent variables (Goldie et al., 1992).
Reliability and sensitivity of these variables was another factor in helping to identify
variables. Using these criteria force variability in both the anterioposterior and
mediolateral directions (Goldie et al., 1992), COP maximum displacement (Pinsault &
Vuillerme, 2009), mean COP velocity (Geurts et al., 1993; Pinsault & Vuillerme,
2009) and time to stabilisation of the GRFs (Ross et al., 2009; Wikstrom, Tillman, &
77
Borsa, 2005) were chosen to investigate the influence of asymmetric footwear
perturbations. Further discussion of these variables is made in Section 5.2.9.
2.8
Summary
Despite sustained research into optimal footwear design, there is no evidence that
present day (sports) footwear reduces the risk of injuries. However, there is data to
suggest footwear can disrupt normal foot and lower leg morphology and
neuromuscular function. Research has focused on methods to improve human foot
and lower leg function based on an implicit paradigm of poor design. Large
interventions, allowing measurement, have been designed to manipulate the footground interface irrespective of subject-specific characteristics or footwear conditions.
Footwear assessment has lacked detailed objective measures of mediolateral
asymmetry and has been blinded by the assumption that wear patterns are intrinsically
caused. This has prevented analysing design and degradation as two sides of the same
coin. Breaking out of the present paradigm is formidable as it is ingrained in every
aspect of footwear research, design and manufacture, advertising, teaching and
clinical practise.
Asking the right questions, unbiased by history and clinical or research cultures, is the
first place to start. Since no data exist with regard to footwear wear patterns, this
would be the first question to ask and answer. Secondly, what in the footwear design
and environmental conditions caused the degradation or failure? The third question
requires a paradigm shift which starts with the premise of evolutionary adaptive value
in human structure and function. This question re-focuses research on barefoot and
evolutionary footwear designs that gave humans the competitive advantage in the
struggle for existence. Failure to do so may lead to the ever-increasing health burden
of maintaining wellness and dealing with inappropriate solutions that never address
the cause.
Chapter 3 presents the opposing paradigms elucidating the thinking that directs
research and finding solutions to the footwear dilemma. The direction and
interventions in this thesis is based upon a model of mediolateral footwear asymmetry
78
driven by the author’s clinical work. This model is described in Chapter 3. The
synthesis of the paradigms guiding research questions into footwear and the
mediolateral model of footwear asymmetry is a unique contribution to the literature.
79
CHAPTER 3.
Paradigms and Conceptual Models
3.1
Introduction
… the current data show a counter-intuitive result; that movement sensitivity
is worse when wearing athletic shoes. … design of athletic shoes does not take
into account the importance of optimizing the ability of the wearer to achieve
movement discrimination ability that approaches that of the barefoot state.
(Waddington & Adams, 2000, p 126)
The foot-ground interface provides the body with sensory feedback in terms of
vertical orientation with the ground and dynamic stability while moving (Alexander,
2007). Footwear is considered to act as a filter sufficiently altering the quantity and
quality of this information leading to either impaired or enhanced neuromuscular
performance (Waddington & Adams, 2000). The current paradigm with regard to the
understanding, design and prescription of (sports) footwear is that the human foot is
poorly designed and there are clear foot types with particular pathologies that require
specific footwear solutions (Asplund & Brown, 2005; Yamashita, 2005). An
alternative paradigm is proposed that considers lower limb and foot function to be
perfectly adapted for functional movement (Lieberman & Bramble, 2007; Rolian et
al., 2009). Footwear design and prescription should thus provide protection and
warmth without interfering with dynamic function. This paradigm has only recently
gained traction mainly through the efforts of evolutionary biologists (Lieberman et al.,
2009; Rolian et al., 2009; Zipfel & Berger, 2007) and popular literature (McDougall,
2009).
For those who accept the poor foot paradigm, substantial interventions are required to
help the foot and lower limb function optimally (Cheung et al., 2006; Lang, Volpe, &
Wernick, 1997). This paradigm is almost universally accepted and permeates the
literature related to running. An example is the following statement: “Many runners
have biomechanically weak feet. This means that the foot has some basic physical
flaw” (Glover & Schuder, 1988, p 455). It is theorised that the lower limb requires
80
cushioning from the impact loading that is damaging to the body (Nigg & Segesser,
1992). Further, the foot requires control, guidance and stability to decrease variability
of lower limb interactions with the ground (McPoil, 2000). Footwear development
and design (Figure 3.1) mirrors this paradigm (Brauner et al., 2009; Butler et al.,
2006; Reinschmidt & Nigg, 2000). Design features include a cushioned lateral heel
for impact absorption and a harder medial heel for pronation control.
D
D
A
A
C
B
C
Figure 3.1 Design features of a used modern stability running shoe.
A. Cushioned lateral heel (Asker C 40 hardness) with structural degradation (compression);
B. Harder medial heel (Asker C 80 hardness);
C. Foot-ground interface is no longer vertical;
D. Medially directed horizontal vector required to maintain equilibrium.
Orthotic interventions are required to improve and stabilise foot function and decrease
variability in the control and co-ordination of movement (Yamashita, 2005). These
orthoses are usually constructed independent of the individual’s shoe design or wear
features (Lang et al., 1997; Nesbitt, 1999). Laboratory-based studies have focused on
the ability of footwear and orthotics to reduce mediolateral foot motion, specifically
the pronation or medial component (Brauner et al., 2009; Butler, Davis, & Hamill,
2006; Cheung & Ng, 2008; Dixon & McNally, 2008); however, many fail to measure
the interrelated neuromechanical effects throughout the lower limb (Goryachev,
Debbi, Haim, & Wolf, 2011; Kerrigan et al., 2009).
Two leading footwear researchers, Davis (2005) and Nigg (2001), have spent the past
three decades researching the theorised one-to-one relationships between injuries,
81
foot-type, footwear, orthotics, and performance, albeit with little success. For
example, no conclusive evidence has been found to associate impact forces with
injury frequency or type while running (Nigg, 2001). The conclusion of a
comprehensive summary of the design of sport shoes was the following:
.. for running shoes, pronation control and cushioning are still considered to be
the key concepts for injury prevention despite the fact that conclusive clinical
and epidemiological evidence is missing to show the efficacy of these design
strategies. Several design features have been proposed to be effective in
controlling the amount of pronation. However, the kinematic effects of such
features seem to be subject-specific and rather small especially when looking
at the actual skeletal motion. (Reinschmidt & Nigg, 2000, p 71)
As a result of these and other research findings, Nigg proposed that the human body
uses impact forces as an input signal during the stance phase of gait to produce the
most efficient dynamic movement pathway for the current and future steps (Nigg,
2001). This movement pathway may be different for each individual and for each
step. Further, if an intervention to this foot-ground interface counteracts this preferred
pathway, muscle activity will be increased and hence may negatively affect fatigue
and performance (Nigg, Stefanyshyn, Cole, Stergiou, & Miller, 2003; Nigg, Stergiou
et al., 2003). The limitation of this theory is that it fails to integrate barefoot structure
and function into its hierarchy so it is not clear if barefoot is the most efficient
pathway. The preferred shoe design features and orthotic interventions remain
essentially the same as for the prevailing poor foot paradigm described previously and
summarised in Figure 3.2. In summary, individuals have distinct inherited foot types
and these require help, using footwear and orthotics, in order to function optimally.
Determining this optimum footwear condition remains an enigma (Brauner et al.,
2009; Mayer et al., 2004; Mündermann et al., 2006; Nigg, Stergiou et al., 2003).
82
Foot
Anatomy and Function
“Poor”
“Perfect”
Distinct inherited foot:
rigid, flat, high/low arch,
pronated, pathology
Gradation of normal:
function, shape, structure
degraded by footwear
Fix foot: control,
cushioning and guidance
Fix shoe: Foot only needs
protection and warmth
Footwear to improve
function: heels, medial
control and lateral
cushioning
Footwear to equal
barefoot function: flat,
flexible and neutrally
dense
Modern heeled designs
driven by economics,
fashion and science
Early designs simple
non-standard based on
function and foot shape
Shoe wear determined
by foot type/pathology:
normal, medial or lateral
Shoe wear multifactorial
neutral or asymmetric
(medial versus lateral)
One shoe assessment:
one person = one wear
pattern
All shoes assessed for
asymmetry: one person =
many wear patterns
Orthotics to fix foot: with
medial bias to control,
cushion, guide and
support the foot, placed
in any shoe regardless of
design or wear
Shoe needs fixing: scrap,
re-heel, optimise shoe by
neutralising asymmetry
which may be medial or
lateral, different for each
shoe, none for neutral
Figure 3.2 Paradigms of lower limb and foot function require different solutions
for footwear and orthotic interventions.
83
An alternative view is that human structure and function is well-adapted to life on
earth. Should footwear design interfere with barefoot function, foot structure and
function may be degraded (Figure 3.2). Fetching water from the nearest water supply
is a typical daily task in rural Africa. In Figure 3.3, unfettered by footwear, this child
is carrying a 25 l water container from the dam up to the hut set on the hillside. This
remarkable task, in a Western context, may be repeated many times a day but with
variability built into each footstep. International performances by barefoot runners
such as Abebe Bikila (Ethiopia) and Zola Budd (South Africa) are considered
exceptional but represent typical rural Africans (Lieberman et al., 2010; Zipfel &
Berger, 2007).
Figure 3.3 Anthropological and evolutionary perspectives in adults and children
suggest whole-body structure and dynamic barefoot function is well-adapted for
movement.
World-renowned New Zealand athletics coach and shoe-maker, Arthur Lydiard,
believed his legendary 100 mile week training schedules were only possible using his
light, flat, flexible running shoes he designed and manufactured (Gilmour, 2004). His
world class athletes had an advantage because at the first signs of heel wear, he would
re-sole their shoes and keep them in pristine shape (Gilmour, 2004). He believed this
was why his runners very seldom suffered from serious injuries despite their heavy
weekly training. He described present day running shoes as not fit for running. “They
84
don’t run in them. You can’t anyway, because they are so stiff in the sole. ... they’re
still largely a fashion item. Like gumboots, good for mowing the lawns in.” (Gilmour,
2004, p 175). He believed shoes should not interfere with barefoot function and that
if supportive shoes are worn, the foot and muscles of the lower legs get weaker
leading to injury (Boyle, 2006; Gilmour, 2004). For Lydiard, barefoot training was
essential to improve leg, ankle and foot strength. Similarly, Australia’s outspoken
athletic coach, Percy Cerutty recommended that training without shoes was equivalent
to eating a healthy diet (Cerutty, 1960). After a long hiatus, barefoot running training
has been espoused by North American Collegiate coaches as a way to improve lower
limb and foot muscle strength in their athletes in order to compete with the Kenyans
(McDougall, 2009; Siff & Verkhoshansky, 1999). Linked to this barefoot running
adaptation is the Pose style of running. This incorporates shorter stride lengths and a
mid- to fore-foot foot strike pattern. This style has been shown to reduce vertical
impacts and eccentric knee loading while requiring greater power and work performed
at the ankle (Arendse et al., 2004).
Robbins and colleagues have recommended that barefoot gait is superior to present
day footwear in terms of balance, impact loading and proprioception (Robbins &
Waked, 1997; Robbins et al., 1997; Robbins et al., 1998; Robbins, Waked, &
Krouglicof, 2001). Their studies castigating the use of then and still current (sports)
shoes were based on their work assessing proprioception and balance in young and
older individuals barefoot and in different footwear designs (Robbins & Gouw, 1990,
1991). Balance in the older cohorts was worse barefoot than in hard flat shoes which
was explained in terms of the length of habituation to footwear compared to the
younger participants (Robbins, Gouw, & McClaran, 1992). This has also been
confirmed by a wobble board rehabilitation study (Waddington & Adams, 2004). The
importance of the work by Robbins and colleagues was to link both biomechanical
and sensory influences and measure global dynamic function such as balance while
single-leg standing, stepping and walking (Robbins et al., 1994; Robbins et al., 1995).
Their article titles such as “Athletic footwear unsafe: due to perceptual illusions” and
other comments with regard to footwear design were out of step of the then current
thinking (Robbins & Gouw, 1990; Robbins et al., 1989; Robbins & Hanna, 1987;
Robbins et al., 1988; Robbins et al., 1994). Without epidemiological evidence to back85
up their non-running laboratory-based studies and assertions that barefoot populations
have fewer injuries and better balance, they were open to strong rebuttals (Nigg, 2009;
Noakes, 2003; Wright, Stefanyshyn, & Nigg, 1998) and caused considerable debate
amongst sports-shoe manufacturers and other research groups. Although critics
assumed that overwhelming evidence existed for the poor foot paradigm supporting
present day sports footwear design criteria, the conclusion from a recent exhaustive
review of the literature demonstrated that no evidence exists (Richards et al., 2009).
Nine years previously a similar statement (see Section 3.1) prefaced a review of sports
shoe design but still accepted the present model and paradigm (Reinschmidt & Nigg,
2000) as did Noakes (2003) in his comprehensive book on running.
The evidence supporting an alternative paradigm of human structure and function has
been discussed in Chapter 2 (Sections 2.1 and 2.2). These studies include the
comparison of barefoot to footwear in:
•
children (Klein et al., 2009; Kristen, Kastner, Holzreiter, Wagner, & Engel,
1998; Rao & Joseph, 1992; Sachithanandam & Joseph, 1995; Staheli, 1991;
Thompson & Zipfel, 2005; Walther, Herold, Sinderhauf, & Morrison, 2008;
Wolf et al., 2008);
•
medial knee osteoarthritic research (Kerrigan et al., 2009; Kerrigan et al., 1998;
Radzimski, Mündermann, & Sole, 2011; Shakoor & Block, 2006; Shakoor et
al., 2010);
•
oxygen consumption while running (Alexander & Ker, 1990; Divert et al.,
2008; Hanson et al., 2011; Nigg, Stefanyshyn et al., 2003; Stefanyshyn & Nigg,
2000a);
•
human anthropological and evolutionary perspectives (Bramble & Lieberman,
2004; Jungers, 2010; Lieberman et al., 2009; Zipfel & Berger, 2007).
These studies and other reports support the paradigm that barefoot function is efficient
and the least stressful to the human body but may be affected by footwear (D'Aout et
al., 2009; Frey et al., 1995; Frey, Thompson, Smith, Sanders, & Horstman, 1993;
Lieberman et al., 2010). Based on these human evolutionary perspectives, whole-body
structure and dynamic function is proposed to be well-adapted for movement and
hence an alternative paradigm needs to be considered.
86
3.2
Footwear and the Evolutionary Well-Adapted Paradigm
Fitness in the physiologic sense is definable as the tuning of the body to its
finest state. Vitality and use are tightly linked. … The simple notion of ‘use it
or lose it’ is a profound biologic truth. … The sluggishness of our
contemporary existence is penalizing our fitness as a species. The fitness was
hard won through millions of years of harsh challenge and vigorous response.
It seems that we are playing a dangerous game with our heritage. The prey
which we should now be pursuing is our own physical exercise capacity.
(Bortz, 1985, p 153)
If the lower limb and foot is well-adapted for functional movement, then footwear
needs to mimic barefoot function and should only be a minimalist interface between
the foot and the ground (Jungers, 2010; Lieberman et al., 2010; Shakoor & Block,
2006; Shakoor et al., 2010; Squadrone & Gallozzi, 2009; Stewart, 1945, 1972).
Should footwear interfere with normal barefoot function, progressive deficits in foot
and lower limb function are likely to occur, eventually leading to pathology. The
variability noted in barefoot function is considered essential and forms a component
of sensory noise that in complex biological dynamical systems is thought to decrease
joint loading and increase plasticity for complex tasks (Davids et al., 2003; Davids et
al., 2004; Hamill et al., 1999; van Emmerik & van Wegen, 2002). In contrast to the
aim of orthotic interventions in the poor foot paradigm to control and decrease
variability, the “evolutionary well-adapted” paradigm requires interventions to avoid
interfering with normal barefoot function. Hence these should be designed only to
neutralise shoe deficiencies that counteract barefoot function.
As the evidence accumulates regarding design problems with present day footwear
(Brüggemann, 2007; Kerrigan et al., 2009; Lieberman et al., 2010; Richards et al.,
2009; Shakoor, Lidtke et al., 2008; Shakoor et al., 2010), three further footwear
research complications exist. These do not pose problems in barefoot populations.
These are the effect of footwear on barefoot structure (Section 2.2.2), footwear
87
degradation through use (Section 2.5) and the number of different footwear worn
concurrently by individuals (Sections 4.2.7 and 4.3.7).
Firstly, the short- and long-term effects of footwear on barefoot structure and function
need to be considered. Although the outer skin may change in texture and thickness
(D'Aout et al., 2009; Stewart, 1970) through persistent barefoot use, function is
strengthened (Robbins & Hanna, 1987; Stewart, 1970; Zipfel & Berger, 2007).
Decreases in foot bone density and changes in joint quality have been used as markers
in archaeological studies of foot function and footwear use (Trinkaus, 2005; Trinkaus
& Shang, 2008; Zipfel & Berger, 2007). Assessment of barefoot function in
individuals who habitually wear shoes needs to take into account footwear type and
condition typically worn as these influence barefoot function (D'Aout et al., 2009;
Gefen et al., 2002; Rao & Joseph, 1992; Snow, Williams, & Holmes, 1992; Soames &
Evans, 1987; Stewart, 1945, 1972; Zipfel & Berger, 2007). In these individuals,
barefoot is an abnormal state and may or may not be compromised by the footwear
worn.
Footwear structural degradation through use is the second research problem.
Footwear changes over time so degradation can change the original characteristics of
the shoe. This may or may not be related to original design characteristics.
Asymmetric medial or lateral wear patterns (Figure 3.4) are often seen clinically in
worn footwear. The distribution, extent and frequency of this asymmetric wear have
only been anecdotally reported.
The third potential complication with regard to footwear research is closely
related to changing footwear characteristics. People in relatively affluent Western
societies generally use a number of pairs of shoes. As a result, degradation may be
similar but of different magnitude or unique because of shoe type, age, frequency and
purpose of use. If the clinician’s perspective is based upon the poor foot paradigm,
footwear and/or orthotic interventions will be made regardless of individual shoe wear
features. In accordance with this paradigm, structural degradation to the shoes
illustrated in Figures 3.1 or 3.4 may be attributed to the individual’s intrinsic faulty
mechanics. However, the alternative paradigm analyses shoe degradation in a
multifactorial context including age, frequency and purpose of use, shoe construction
88
and design criteria. The questions that need to be asked about these shoes focus on the
variables contributing to the overall disintegration. Extrapolating a wear pattern from
one shoe to another may be based on erroneous assumptions unless each shoe is
individually assessed. No studies to date have collected data on individual shoe wear
patterns. The shoes in Figure 3.1 and Figure 3.4 have different kinds of wear to their
mediolateral foot-ground interface, but both may change the direction and magnitude
of the GRF vectors. This idea is discussed in the next section.
A
C
B
D
E
F
Figure 3.4 Asymmetric degradation of a symmetric sports shoe through use.
A. Medial outer sole wear and midsole compression changes the vertical orientation to the ground
compared to the barefoot state.
B. The medial collapse and wear is caused by the partial (Left shoe) or complete absence (Right
shoe) of the outer heel sole.
C. Medial midsole thickness 15.33 mm of the Right shoe.
D. Lateral midsole thickness 22.45 mm giving a 7 mm difference between medial and lateral heel.
E. A further complication is the density (hardness/softness) of the remaining outer sole (Asker C 85
hard) and
F. the exposed midsole shown in B (Asker C 65 soft).
89
3.3
Conceptual Model of the Human Body as a Tower
If the human body is conceptualised as a tower with the dynamic sensory foot as its
foundation, changes in vertical orientation with the ground require muscular work in
order for the tower to remain in equilibrium and prevent it falling over. An inverted
pendulum model has been described for quiet standing in which the legs, pelvis and
feet form a parallelogram pivoting about both hip and knee joints (Gage, Winter,
Frank, & Adkin, 2004; Winter, 1995; Winter, Patla, Ishac, & Gage, 2003; Winter,
Prince, Frank, Powell, & Zabjek, 1996). The model suggests that muscle activity at
the hips and ankles is co-ordinated. Anterioposterior control is primarily linked to the
ankle musculature while the hip ab/adductors control mediolateral movement using a
load/unload mechanism between the lower limbs (Gage, Winter, Frank, & Adkin,
2004; Winter, 1995). The premise is a rigid structure with movement controlled at the
four corners, but movement occurs at all three joints of the lower limb with up to 33%
measured at the knee joint (Gage et al., 2004). The biomechanical validity of the
model has been tested and confirms the relationships with the methods to estimate
whole-body center of mass (COM) (Gage et al., 2004).
A limitation of this model is that single-leg stance phase is only discussed indirectly
during walking (MacKinnon & Winter, 1993; Winter, 1995). Total mediolateral
balance is achieved by the placement of the foot with errors corrected at the ankle or
hip joints which work in synergy. The model predicts a more important role for the
hip than the ankle and foot musculature in balance whether standing or walking
(Winter, 1995). Further, different patterns exist for maintaining equilibrium in singleleg stance, and Tropp and Odenrick (1988) suggested that a change from an inverted
pendulum model to a multisegment chain model takes place when the ankle can no
longer control posture. Dynamic posture at the foot also needs consideration in
modelling (Humphrey & Hemami, 2010) while sensory re-weighting appears to
change whole body dynamics to a more complex system (Schweigart & Mergner,
2008). During single-leg stance, a continuum of inter-related postural corrections
occurs, linking the entire limb and upper body (Kuo & Zajac, 1993; Runge, Shupert,
Horak, & Zajac, 1999; Zajac, Neptune, & Kautz, 2002, 2003). The inverted pendulum
model does not explain this. Multiaxial changes take place while walking or running
90
over variable terrain and muscles acting as guy ropes automatically readjust to
maintain homeostasis (Alexander, 2007; Daley, 2008; Zajac, 1993, 2002). The tower
model proposed in this thesis considers the foot-ground position as critical in
determining the muscular and joint corrections required up the kinetic chain to
maintain whole body homeostasis.
The foot forms an integral primary part of this single dynamic kinetic system (Zajac,
2002; Zajac et al., 2002) so that interventions at the foot-ground interface are expected
to influence the overall efficient functioning of the complete system (Erhart,
Mündermann, Mündermann et al., 2008; Haim et al., 2008). Footwear can introduce
fixed anterioposterior or mediolateral effects different to the variable nature of uneven
terrain. As discussed in Chapter 2, heeled footwear (Section 2.3.2), increases
metabolic, muscle and joint loads at the hip, knee and ankle (Gefen et al., 2002;
Kerrigan et al., 2009; Poterio-Filho et al., 2006; Reinschmidt & Nigg, 1995; Snow &
Williams, 1994; Stefanyshyn et al., 2000). Compared to barefoot stance (Figure 3.3
and Figure 3.5), the individual standing, walking or exercising in asymmetrically
worn shoes may also require similar muscular and joint compensations to maintain
postural control. Tilting the human tower in any direction at the foot-ground interface
will theoretically require more work to maintain dynamic postural homeostasis. This
thesis considers footwear mediolateral asymmetry as a factor impacting on this kinetic
chain.
Footwear mediolateral interventions increase or decrease joint moments (Andrews et
al., 1996; Andriacchi, 1994; Andriacchi & Mündermann, 2006; Erhart, Mündermann,
Mündermann et al., 2008; Jenkyn, Erhart, & Andriacchi, 2011; Pandy & Andriacchi,
2010; Shelburne, Torry, & Pandy, 2006; Shelburne, Torry, Steadman, & Pandy, 2008)
and consequently muscle activity in the lower limb (Goryachev, Debbi, Haim, &
Wolf, 2011; Mündermann et al., 2006; Murley & Bird, 2006; Murley et al., 2009).
Since biomechanical models and inverse dynamics are best fit estimates there are no
definitive answers (Shelburne, 2011) and these are at present being studied
(Goryachev, Debbi, Haim, Rozen, & Wolf, 2011; Goryachev, Debbi, Haim, & Wolf,
2011; Haim, Rozen, & Wolf, 2010; Haim et al., 2011; Jenkyn et al., 2011; Shelburne
et al., 2008). There are five issues which to date are unresolved:
91
1.
Does mediolateral asymmetric footwear and interventions change the
overall GRF magnitude which is the force opposing the body’s COM at
the same speed and for the same activity?
2.
Does the intervention increase or decrease the frontal plane lever arm
(considering mediolateral footwear asymmetry only) for that particular
joint moment keeping other factors equal such as activity, trunk
movement and if so
3.
Is this change in lever arm length a result of a medial or lateral shift in
COP and/or
4.
A change in the magnitude of the medial component of the GRF and/or
5.
A change in whole body dynamic movement (COM) as a result of the
intervention?
With lateral or medial asymmetry the COM is probably shifted medially (Figure 3.1
and Figure 3.5 C) or laterally (Figure 3.4 and Figure 3.5B) of the midline respectively
(Jenkyn, Erhart, & Andriacchi, 2011). This introduces possible changes to the
magnitude of the overall and the medioalateral component of the GRF concomitant
with a change in the lever arm length, COP mediolateral shift and whole body
dynamic movement. To maintain stability increased activity of specific muscles
which counteract this tendency is predicted (Shelburne, Torry, & Pandy, 2006) and
has been measured (Goryachev, Debbi, Haim, Rozen et al., 2011; Goryachev, Debbi,
Haim, & Wolf, 2011). The magnitude of joint moments is proportional to the GRF
and the perpendicular distance this force acts from each joint centre (Jenkyn et al.,
2011; Noyes, Schipplein, Andriacchi, Saddemi, & Weise, 1992; Shelburne et al.,
2006). Footwear is known to change the length of the lever arms and consequently
joint moments around the ankle, knee and hip (Bergmann, Kniggendorf, Graichen, &
Rohlmann, 1995; Erhart, Dyrby, D'Lima, Colwell, & Andriacchi, 2010; Erhart,
Mündermann, Mündermann et al., 2008; Kerr et al., 2009; Kerrigan et al., 2005;
Sekizawa et al., 2001; Stacoff et al., 1996; Wright et al., 2000) as does a whole foot
6°lateral wedge on the valgus moment arm at the ankle (Kakihana et al., 2007;
Kakihana, Torii et al., 2005). For example, in Figure 3.5, the length of the lever arm
(d) of the medial knee compartment to the vertical GRF vector is increased (lateral
shoe C) or decreased (medial shoe B) compared to the neutral position.
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A
B
C
D
D
VGRF
VGRF
VGRF
E
d
d
E
E d
MLGRF
MLGRF
MLGRF
Figure 3.5 The conceptual model of the human body as a tower built upon the
foot as the foundation.
A: Barefoot with vertical (VGRF) and medial (MLGRF) ground reaction force vectors in neutral.
B: Shoe with medial degradation, foot appears “over-pronated” shifts the VGRF medially.
C: Shoe with lateral degradation, foot appears “over-supinated” shifts the VGRF laterally.
D: The change requires a muscular and joint compensation equivalent and opposite to the disturbance
to maintain equilibrium.
E: The knee adduction moment is affected by the VGRF, MLGRF vector, mediolateral COP shift and
the length of the lever arm (d) from the knee centre. Lateral increases while medial wear decreases the
lever arm length for EKAM.
A simplistic view of the external knee adduction moment (EKAM), a marker of
medial knee joint loading, is the product of the medial lever arm (d) and the GRF
vector and hence will increase or decrease accordingly. In order for the joint to remain
in equilibrium, the internal adduction moment, the product of muscle force and their
lever arms to the joint centre, must counter-balance EKAM. The mediolateral COP
shift, magnitude of the medial GRF and whole-body dynamic movement
(Mündermann et al., 2008) are also closely connected to the changes in lever arm
length and overall magnitude of the adduction moment (Erhart et al., 2008; Haim et
al., 2008; Haim et al., 2011; Jenkyn et al., 2011; Shelburne, Torry, Steadman, &
Pandy, 2008). Conversely, the lateral lever arm lengths and EKAM magnitudes will
be reversed and lateral knee loading will increase with the medially collapsed shoe B.
The ideal is that the adduction and abduction moments around the centre of the knee
joint are equal in magnitude (Figure 3.5 A) otherwise increased joint loading is likely
93
to occur and increased asymmetric muscular force is required to restore this
homeostasis.
Small differences at the foot may be magnified further up the kinetic chain. The GRF
vector is due to gravity and accelerations of the COM that in turn is affected by
footwear, dynamic whole body movements and carrying external loads. The
previously described lifting and carrying of the 25 l water container (Figure 3.3)
wearing either the shoes in Figure 3.1 or Figure 3.4 may become a much more
difficult task fraught with increased injury risk. Increasing the length of time that
asymmetrically degraded footwear is worn may ultimately lead to joint damage and
neuromuscular inhibition causing a cascade of effects up the kinetic chain (Figure
3.6). For example, laterally degraded footwear could place the ankle and foot in an
inverted position; tilt the tower while influencing foot sensation and neuromuscular
co-ordination further up the leg similar to an ankle injury. It is known that a unilateral
inversion ankle injury is related to inhibited muscle function in the low back and hipthigh bilaterally (Bullock-Saxton, 1994; Bullock-Saxton, Janda, & Bullock, 1994).
This thesis further suggests that the effect of footwear asymmetry may introduce
global deficits in postural stability and impair dynamic balance control by degrading
somatosensation from the foot (Figure 3.6). During fatiguing exercise such as lifting
and carrying a heavy load uphill, accurate and reliable somatosensory inputs from the
foot soles and ankle are important in maintaining postural stability (Hennig & Milani,
2000; Vuillerme, Anziani, & Rougier, 2007; Vuillerme, Boisgontier, Chenu,
Demongeot, & Payan, 2007). Thus, where this information is distorted or absent (Eils
et al., 2004) and related to asymmetric shoe design or structural footwear degradation,
the sensory cues supplied by mechano- and proprioreceptors in the foot and lower
limb to the CNS may be disturbed (Nurse & Nigg, 1999), making it more difficult to
maintain optimal postural control (Vuillerme & Pinsault, 2007) and affecting gait
(Nurse et al., 2005; Nurse & Nigg, 2001; Perry et al., 2007; Perry, Santos, & Patla,
2001). As the CNS becomes overloaded a re-weighting of information may not be as
accurate or efficient leading to impaired dynamic stability.
The foot-ground interface and the postulated effects of footwear on whole-body
dynamic function are presented in Figure 3.6. External events, footwear, ground
94
surface, and orthotics influence biomechanical and sensory systems, motor control,
balance and performance (Section 2.3). Should this influence be positive, all factors
are optimised and the body is tuned for function (Nigg & Wakeling, 2001). In
contrast, long-term footwear asymmetry is theorised to have the capacity to
progressively disrupt structure and function. This thesis is focused on modelling and
measuring the influence of one aspect of footwear, mediolateral asymmetry, on
balance and performance.
95
Re-weighting
Cutaneous receptors
Joint position
Mechanoreceptors
Stretch receptors
Somatosensory
Proprioception
Feedback/forward loops
Global and peripheral
Muscle recruitment
(Timing and activation)
96
Performance
Efficiency
Endurance
Fatigue
Power
Speed
VO2
Negative
Long-term exposure to either mediolateral or
anterioposterior asymmetry
Static balance
COM/COP
Dynamic stability
(mediolateral and
anterioposterior)
Postural stability
Orthotic
Motor Control
External Events
Footwear
Figure 3.6 Postulated interactions of footwear, ground surface and external events on whole-body dynamic function
Positive/Neutral
Symmetry similar to barefoot state
Short term asymmetry exposure
Alignment
Equilibrium
GRF (lever arms,
joint moments),
ligaments,
muscles, tendons
Biomechanical
Foot-Ground
Interface
Asymmetry
Ground Surface
3.4
Conceptual Model of Footwear Asymmetry
The conceptual model for this research has developed from clinical observation and
assessment of footwear, and its clinical association with patients’ injuries and
performance. It is theorised that footwear can have positive, neutral or negative
effects on local and global dynamic postural function (Figure 3.6). Footwear that has
design and/or wear asymmetry is postulated to alter neuromuscular pathways and
have negative effects on whole-body stability and functional performance. Footwear
asymmetry by design or material degradation (Section 2.5) is considered abnormal
when compared to the barefoot state (Section 2.2.2).
3.4.1
Asymmetry by Design
Typical design features that are inherently asymmetric include dual density midsoles,
asymmetric placing of cushioning inserts, holes in midsole and flares or curves at the
heel. Shoe design characteristics such as variable heel height and the shape, density
and flexibility of the midsole (Figure 3.7B and Figure 3.8) can change the position of
the foot relative to the ground, compared to barefoot, and may contribute to adverse
loading forces in the foot and lower limbs (Gefen et al., 2002; Shakoor & Block,
2006; Wolf et al., 2008). Shoe outer sole design tread patterns often have asymmetric
placing of small weight-bearing surfaces which may wear rapidly (Figure 3.7A). In
the shoe illustrated, the lateral heel star is completely worn away. Shoe heel grid
midsole design is inexpensive, light weight, flexible but structurally weak with large
empty holes (Figure 3.7B). These rubber cross-bridges may break or collapse causing
disintegration of the midsole (Figure 3.7 B). All these design features may produce
anterioposterior and mediolateral asymmetry (Figure 3.8).
97
A
B
Figure 3.7 Outer- and midsole design may affect degradation.
Anterioposterior asymmetry exists in all footwear with heels and much research
(Section 2.3.2) relating to the deleterious effects during gait has been published
(Kerrigan et al., 2009; Lieberman et al., 2010; Shakoor et al., 2010). Almost all
modern (sports) footwear is designed with a heel either hidden within the shoe or as
part of the midsole. Figure 3.8 dramatically illustrates the principle of heel height on
anterioposterior and mediolateral loading. A decreased base of support (A to B)
combined with outer-sole heel wear, shifts the vertical GRF (VGRF) laterally. In
order for the body to stay in equilibrium, a medially directed muscular force is
required (C).
98
C
C
VGRF
VGRF
B
A
Figure 3.8 Footwear design (heel height and shape) and wear (lateral heel)
asymmetry
99
3.4.2
Asymmetry by Structural Degradation
Structural degradation (Section 2.5) of the outer- and midsole can be influenced by
the design outlined in 3.4.1 as well as shoe age, shoe type, frequency and purpose of
use and individual anthropometry (e.g. height, weight, BMI). Mediolateral asymmetry
may also be produced by overt outer- or inner-sole degradation (Figure 3.9) leading to
a medially or laterally biased hindfoot position within the shoe. The frequency and
extent of this medial or lateral bias in a normal population has not been reported.
Figure 3.9 The medial structural degradation of a grid midsole is measured using
the thumb compression test.
3.4.3
Modelling Mediolateral Asymmetry
In order to model mediolateral asymmetry at the heel, medial or lateral heel wedges
can be used (Figure 3.10). In barefoot stance, a laterally placed hindfoot wedge will
simulate a medial tilt bias of the hindfoot (Figure 3.10A) with a similar lateral tilt bias
occurring with a medially placed hindfoot wedge (Figure 3.10B). Placement of such
hindfoot wedges are considered to have a similar effect in a neutral shoe with no
evident wear or design asymmetry. As no published data exists on measured
quantities of asymmetric heel degradation in footwear, the thickness of the wedges
has been based on clinical measurement of mediolateral differences in shoes where
100
degradation has been observed. Wedge thicknesses of 1, 2 and 3 mm were used in the
following studies (Chapter 4 and 5).
A
B
A
B
Figure 3.10 Medial (A) and lateral (B) asymmetry is simulated barefoot with a
lateral (A) or medial (B) wedge respectively.
101
3.4.4
Neutralising Mediolateral Asymmetry
Within shoe wedges may also neutralise medial or lateral structural asymmetry at the
heel if the thickness is equivalent to the magnitude of the asymmetry. The task is
relatively simple in a shoe in which midsole hardness is sufficient to cause no
compression or collapse, then, only outer-sole wear needs to be measured (Figure
3.11). The difficulty is measuring the amount of asymmetry when both compression
of mid- and inner-sole and wear of outer-sole can compound or neutralise (partially or
completely) each other. Knee pain reduction in a step-down task has been used to
determine individualized 5 to 100 of lateral wedging (Barrios et al., 2009; Butler,
Barrios, Royer, & Davis, 2009). All studies to date do not take into account footwear
asymmetry, if any, when inserting wedging of a standard thickness (Bennell et al.,
2011). Similarly, the design and fabrication of in-shoe orthotics based on foot
structure may or may not neutralise footwear mediolateral asymmetry.
Figure 3.11 Overt lateral 20 mm wear of outer-sole and hard midsole (Asker C
100 units) measured in a work shoe. Actual heel height is 3 cm.
The lateral 20 mm outer-sole heel wear in the dress shoe (Figure 3.11) is probably
caused by the 3 cm actual heel height which encourages the individual to hit the
102
ground harder and laterally (Snow & Williams, 1994), possibly causing increased
impact transients (Lieberman et al., 2010; Radin et al., 1991).This shoe can be
scrapped, repaired or wear can be neutralised from within using a 20 mm lateral heel
wedge. A shoe repairer follows a similar process when re-heeling an outer-sole, such
as in Figure 3.11. Filler is required to replace missing or compressed midsole in order
to correct the foot-shoe-ground interface to perpendicular and then a new outer-sole
replaces the degraded original. Similarly, a farrier practising another traditional craft
will “balance” horseshoe structure and shape to relieve pain and improve performance
(Gill, 2008; Williams & Deacon, 2004). These techniques are both an art and science.
3.4.5
Summary of the Conceptual Model of Footwear Asymmetry
The focus in this thesis is on mediolateral asymmetry, although it is acknowledged
that anterioposterior asymmetry exists in all heeled footwear. Footwear with in-built
design features, such as soft versus hard midsoles on opposite sides, may contribute to
structural degradation in the weakest area leading to mediolateral asymmetry (Figure
3.12). This can be distinguished by medial or lateral bias.
A
B
Figure 3.12 Stability sports shoe designed with dual density midsole at the heel.
The medial is harder (Asker C 75 units) than the lateral heel (Asker C 50 units).
A summary of the conceptual model of footwear asymmetry is presented in Figure
3.13. This thesis will simulate or model these mediolateral effects in barefoot stance
103
and in footwear with the use of a medial wedge (= lateral asymmetry) or a lateral
wedge (= medial asymmetry).
Footwear
Asymmetry
Design
Dual
Density
Midsoles
(harder
medially
or
laterally)
Fig 3.1 &
3.12
Inner or
midsole
too soft
Fig 3.1,
3.4,
3.7A &
3.8
Tread
design
(outer
weightbearing
too
small)
Fig
3.7A
Medial bias
Simulated
with lateral
wedge
Attenuated
with medial
wedge
Wear
Heel
height
Fig 3.1,
3.7, 3.8
& 3.11
Asymmetric
placing of
heel holes,
flares, curves
& cushioning
inserts (air,
gel, adiprene,
abzorb)
Fig 3.1, 3.12
Shoe age,
design,
environment,
frequency and
purpose of use,
anthropometric
factors
Fig 3.4 & 3.11
Lateral bias
Simulated
with medial
wedge
Attenuated
with lateral
wedge
Figure 3.13 A conceptual model explaining two patterns of footwear asymmetry
at the heel originating from either design and/or wear effects.
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3.5
Wedge Design, Construction and Specifications
3.5.1
Background
Wedges were originally designed to neutralise the influence of asymmetric effects
from either design features or heel degradation (Figure 3.12). Although medial or
lateral asymmetry at the heel can range from 0.5 mm to more than 10 mm, only 1, 2
and 3 mm wedges were used to model such asymmetry in these studies. As no
commercially available wedges were available in 1 mm increments and limited to a
maximum of 3 mm in thickness, custom made wedge pairs were designed and
constructed by the primary investigator.
3.5.2
Design
The design allowed the wedges to be used either medially or laterally at the heel
(Figures 3.14). The wedge was thickest at the outer edge where the greatest wear or
compression occurred and tapered toward the centre of the heel. The design allowed
them to be tailor-made to the shoe asymmetric wear magnitude. The length of the
wedge was the length of the calcaneus and the width equal to half the in-shoe heel
width. The outline of each wedge pair was created from the inner-soles of commonly
sized shoes with the largest a men’s size 14. The wedge density or hardness should
not compress during weight-bearing but have minimal weight so performance and
oxygen consumption is not compromised (Burkett et al., 1985; Nigg, Stefanyshyn et
al., 2003; Stefanyshyn et al., 2000).
105
B
A
Figure 3.14 The wedge design: A. Cross section and B. Oblique view.
3.5.3
Construction and Specifications
Since participant foot length characteristics were expected to vary considerably,
wedge pairs of variable length and thickness were constructed. Typical wedges range
from 4.5 to 7 cm long with 0.5 cm increments, giving a total of 6 different lengths for
each thickness (1, 2, and 3 mm) and a total of 36 wedges. The wedges were custom
made using recycled telephone directory paper. The paper was cut in layers so that the
wedge tapers towards < 0.1 mm at the centre of the heel and covered by 2 layers of
parcel wrap tape.
3.6
Footwear Asymmetry Assessment
To understand the relationship between footwear asymmetry and how this might
affect whole-body dynamic function, the assessment of participants’ footwear is
crucial. Although there are many footwear characteristics assessed in clinical work
(Kerrigan et al., 2009; Noakes, 2003), the focus in this study was mediolateral
footwear asymmetry and only features that were relevant to this are considered. The
questions that were asked included:
• What is the frequency of mediolateral asymmetry in used footwear?
•
Is the pattern of wear the same for an individual who wears a number of different
shoes?
106
• Is it possible to measure the mediolateral asymmetry in mm rather than reporting
categories such as “none, normal, medial and lateral”?
• If so, what are the typical amounts of mediolateral asymmetry?
• Do individuals using footwear with mediolateral asymmetry have impaired global
postural stability barefoot and in shoes?
• Does modelling increasing mediolateral asymmetry progressively decrease
postural stability?
• Does increasing the habituation time in simulated mediolateral asymmetry affect
postural stability?
• If orthotics are inserted into used footwear does their construction adhere to the
poor foot paradigm or do they neutralise measured footwear mediolateral
asymmetry?
3.7
Summary and Directions for Studies
The review of the literature explored theories and research that consider global human
function in standing, walking and running. Two prevailing views of foot and ankle
structure and function diverge with respect to poor or good design. If poor,
individuals need protection using footwear and orthotics, if good, barefoot provides
the protection. Without considering the role of evolution, explanations, research and
understanding of lower limb intrinsic injuries and chronic joint overloading remain
based on the concept poor design which may limit the choice of alternative
approaches. The evolutionary well-adapted paradigm offers a possible alternative
solution to the seemingly intractable problems related to the foot-ground interface and
efficient global human function. Footwear appeared in very recent human history to
provide protection and warmth. Economics, fashion, manufacturing techniques and
materials available have subsequently driven designs with little or no scientific basis.
Unlike barefoot, footwear has the capacity to introduce asymmetries by design and/or
structural degradation.
A typical, however brief, weight-bearing posture assumed during locomotion is
single-leg stance. The human body in this position is conceptually viewed as a single
structural tower connected by inter-dependent links forming a dynamic neuromuscular
107
system which immediately responds to changes in the foot-ground interface. This
fundamental principle underpins the models of footwear asymmetry developed for
this research and assists with the explanations relating to globally impaired
performance. Patterns of footwear asymmetry at the heel indicate two very different
extremes. Mediolateral asymmetry is thought to destabilise the foot and whole-body
by introducing asymmetric loading. Some form of compensation using either
muscular or structural contributions is required for the body to maintain equilibrium.
This is theorised to affect performance and postural stability.
Research debate about footwear solutions to injuries and lower limb OA present a
conflict on whether to use medial wedging, neutral footwear or lateral wedging,. The
poor foot paradigm assumes the cause for footwear asymmetry is inherited mediallydirected foot malfunction. For this reason, foot and footwear research has focussed on
ways to eliminate the medial component of this asymmetry. For example, running
shoe design seems to favour medial wedging, with medial posting and/or more
compliant lateral midsole for impact protection. This effect is also created by high
heels and may be by laterally worn shoes, to be examined in this study. The conflict is
that lateral wedging, via direct wedges or more stiff lateral midsole, seems to be
preferred for reducing knee adduction moments to slow progression of knee OA or
even incidence of knee OA. Conversely, barefoot locomotion is the least stressful.
Improved sensory information barefoot probably affects movement control so that
people run/walk differently, by changing foot orientation at foot impact, ankle motion,
muscle activation patterns, joint moments and impact forces experienced.
It is unknown if mediolateral asymmetry from wear simulates what occurs in footwear
with mediolateral asymmetrical design. This leads to one aim of examining the range
of mediolateral asymmetrical wear patterns. The next aim is to examine if
mediolateral asymmetrical wear effects function similar to that seen in mediolateral
asymmetrical design.
It has been argued that barefoot locomotion essentially has neutral foot/ankle posture.
However, that aspect alone cannot account for differences between shod and barefoot
locomotion, since the different sensory flow from barefoot conditions will result in
altered motor function. Since it is well known that people accommodate to sensory
108
inflow, habituation to the barefoot condition may also affect function. So a further aim
of the studies was to examine the combination of mediolateral asymmetry in barefoot
conditions while accounting for habituation to increased sensory inflow.
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CHAPTER 4.
Study 1 Exploring a Model of Footwear Asymmetry on
a Barefoot Heel-Raise Task
4.1
Introduction
Footwear degradation (Section 2.5) caused by use alters footwear characteristics
(Hennig & Milani, 2000; Kong et al., 2009). A postulate of this thesis is that
asymmetric sole wear, biased either medially or laterally, accentuates corresponding
lateral or medial loading of the foot (Sections 2.3.3, 2.5, 2.6 and 3.4). This contributes
to further degradation of the shoe. The conceptual human tower anchored and
embedded in an asymmetrically worn shoe may no longer be grounded vertically and
neuromuscular compensations may be necessary to maintain postural stability
(Section 3.3). The human foot within this shoe may also show marked abnormal
function (Ashizawa et al., 1997; D'Aout et al., 2009; Rao & Joseph, 1992; Staheli,
1991; Stewart, 1972). This is also discussed in Sections 2.2.2, 2.6 and 3.2. If there is
asymmetry of the heel and forefoot alignment by either footwear design or
degradation, then shoe assessment is an important factor in a given clinical
presentation. The effects of footwear degradation on performance measures over time
are difficult to establish as the variety and age of shoes worn by an individual may
affect this relationship. There are few published studies investigating individual’s
footwear characteristics and asymmetric wear patterns (Singh, 1970). Although
comprehensive tests of performance and balance should include all footwear used by
an individual, barefoot assessment avoids the issue of individual variability of
participants’ current footwear. Barefoot somatosensory function may also be the most
sensitive to perturbation while barefoot gait is the most efficient (Lieberman &
Bramble, 2007; Raichlen et al., 2011; Squadrone & Gallozzi, 2009). These ideas are
reviewed in Sections 2.2, 2.3.4 and 3.2. This study simulates either a medial or lateral
asymmetry at the heel in the barefoot state. The question is whether this perturbation
110
does in fact change neuromuscular function during the performance of a clinical
weight-bearing task.
Footwear assessment characteristics relevant to mediolateral degradation and research
limitations are reviewed in Sections 2.5, 2.6 and 3.4 (Barton, Bonanno et al., 2009;
Brüggemann, 2007; Menz & Sherrington, 2000; Noakes, 2003; Reinschmidt & Nigg,
2000; Richards et al., 2009). Important contributing factors to mediolateral asymmetry
associated with injury, performance and postural stability were also considered (Maki
et al., 1994; Menant, Perry et al., 2008; Menant, Steele et al., 2008a; Robbins et al.,
1998). There are many other footwear characteristics assessed in clinical practice
(Kerrigan et al., 2009; McPoil, 2000; Noakes, 2003; Shakoor et al., 2010). For
example, longitudinal bending stiffness or flexibility important for economy and joint
loading (Kerrigan et al., 2009; Roy & Stefanyshyn, 2006; Shakoor et al., 2010;
Shakoor, Sengupta, Lidtke, & Block, 2008; Stefanyshyn & Nigg, 2000b) were not
assessed as the focus was on measuring mediolateral asymmetry neglected in the
literature. Although the shoe upper and heel counter may also show evidence of
degradation and disintegration, these are difficult to measure and in this study are
considered secondary to the hard-ware of outer-, mid- and inner-sole.
The heel-raise task was chosen as a clinically relevant global and local neuromuscular
performance measure to evaluate the effect of simulated mediolateral asymmetry
(Hébert-Losier, Newsham-West et al., 2009; Hébert-Losier, Schneiders, NewshamWest, & Sullivan, 2009; Kaikkonen et al., 1994; Lunsford & Perry, 1995; Maurer et
al., 2007; Möller et al., 2002; Möller et al., 2005; Yocum et al., 2010). The rationale,
reliability and validity for using this task is examined in detail in Section 2.7.1. The
task is ideal as it can be performed repeatedly without excessive fatigue and includes
two measures of performance, time and number. It has sound ecological validity as it
includes mid-stance and heel-off phase of gait whilst single-leg weight-bearing. A
limitation of the task is that it excludes the alternating mediolateral pattern of footstrike and toe-off while walking or running. It may or may not be influenced age,
gender and BMI (Jan et al., 2005; Lunsford & Perry, 1995; Yocum et al., 2010) and
subject-specific characteristics such as fitness (Jan et al., 2005; Kaikkonen et al.,
1994), footwear (Gefen et al., 2002) internal motivation (Yocum et al., 2010) and
111
previous lower limb injuries (Jan et al., 2005; Kaikkonen et al., 1994; Möller et al.,
2001).
The primary purpose of this study was to use medial and lateral wedges to explore
the effect of hindfoot positional medial and lateral perturbations on the heel-raise
performance task in the barefoot condition. The medial or lateral heel wedge was used
to simulate lateral or medial shoe heel wear respectively (Figure 4.1). A secondary
purpose was to assess the participants’ footwear in terms of asymmetry by design or
wear at the heel. Concomitant with this purpose were two further aims. The first was
to establish whether any inserts or orthotics found in participants footwear were
designed based on the poor foot paradigm (Section 3.1) or on the current status of
their footwear (Section 3.4). The second aim was to assess whether the current
asymmetric status of an individual’s footwear was reflected in their barefoot
performance (Sections 2.2.1, 2.2.2 and 3.2).
Figure 4.1 Two patterns of heel asymmetry modelled in this study.
The hypotheses which the thesis set out to test were:
H1: Medial and lateral hindfoot positional perturbations will decrease the
performance of the heel-raise task compared to the neutral barefoot state.
H2: Individuals with footwear measured with mediolateral asymmetry will have
decreased performance of the heel-raise task in the neutral barefoot state.
112
H3: Any orthotic intervention within participants’ footwear is independent of the
current mediolateral status of their footwear.
H4: The frequency of medial and lateral measured shoe asymmetry will have a
lateral bias.
4.2
Methodology
4.2.1
Participants
The University of Otago Human Ethics Committee (Reference no. 06/050 dated 27th
April 2006) granted approval for this study (Appendix 1). Based on previous research
(Section 2.7.1), a sample of 40 for this exploratory study was thought to provide
stable estimates of variance for the important parameters in the model. The inclusion
criteria were men and women, aged 18 to 35 years, who were in good general health
and participate in at least 1 hour of regular activity per week. Age over 40 years,
fitness level and injury is known to influence the performance of single-leg heel-raises
(Section 2.7.1). Exclusion criteria were neurological or orthopaedic injuries to the
head, back and lower limb that required medical treatment within the last 3 months as
these are known to affect the heel-raise task (Section 2.7.1). Volunteers were recruited
by advertisements in the local newspaper, posters on University of Otago billboards
and a presentation to physiotherapy students during a lecture.
4.2.2
Informed Consent, Screening and Familiarisation
Participants were informed of the study procedures and those who met inclusion
criteria gave their informed written consent prior to participating (Appendix 1). The
duration of the screening and heel-raise tasks was 1 hour. It was performed in the
Mark Steptoe Muscle Performance Laboratory in the Centre for Physiotherapy
Research at the University of Otago. Participants completed a brief screening
questionnaire about their current exercise and previous injuries (Appendix 1). Height
and weight were measured as these are possible factors affecting performance.
Participants chose their preferred stance leg based on their own subjective
interpretation of more comfortable balance and power while practicing the heel-raise
113
task. In a clinical situation, the heel-raise task is assessed on both legs, but because of
time and possible fatigue constraints, participants chose their “best” performing leg.
Previous research in healthy individuals has shown performance on either leg to be
similar (Section 2.7.1). The goal was the best performance.
4.2.3
Experimental design
A cross-over design using barefoot control pre-wedge (neutral position) followed by a
participant alternating intervention consisting of either a 1 mm medial or lateral
wedge taped to the bare hindfoot (Figure 4.2). A barefoot control post-wedge (neutral
position) followed each of the interventions. These three repeated neutral barefoot
measures, control pre-wedge, control post-medial wedge and control post-lateral
wedge provide a measure of reliability. The medial and lateral wedges were used to
simulate typical respective asymmetric heel wear (Figure 4.1).
Participants
Barefoot control condition
50%
Medial wedge
50%
Lateral wedge
Lateral wedge
Medial wedge
Figure 4.2 The cross-over experimental design with three control (no wedge)
conditions: pre-wedge, post-lateral wedge and post-medial wedge.
114
4.2.4
Wedge Design to Simulate Footwear Asymmetry
Detailed wedge design, construction and specifications are provided in Section 3.4.
The thickness of 1 mm for Study 1 was chosen based on clinical observation of
typical outer sole asymmetric wear patterns. Although the effects of larger medial and
lateral wedges (between 4 to 10 mm) placed inside footwear have been investigated,
results have been unpredictable (Nigg, Stergiou et al., 2003). The lateral and medial
wedges simulate medial and lateral footwear bias respectively.
B
A
C
D
Figure 4.3 Verification of wedge thickness.
A = 1.09 mm
B = 2.08 mm
C = 3.05 mm
4.2.4.1
Verification of wedge thickness, density and length
Verification of wedge thickness and density was performed by five examiners on all
36 wedges used for Study 1 and Study 2, using a Vernier calliper (Mitutoyo
Corporation, Kawasaki, Kanagawa, Japan) and Asker C Durometer (Rex Durometer
Type C Asker, model 2000, Rex Gauge Company, Buffaloe Grove, Il, USA)
respectively. Test procedure (Sections 2.6 and 4.2.7) using the durometer complied
with international and manufacturer’s guidelines (ASTM D2240). Wedges were
numbered 1 to 36 and randomly selected by each examiner who took three readings at
115
marked points on the wedge (Figure 4.3 D). Means and 95% CI are presented in Table
4.1.
Table 4.1
Mean Thickness and Density of 36 Wedges Used to Simulate Asymmetry
Wedge
Thickness (mm)
Density (Asker C units)
Mean (95% CI)
SD
SEM
Mean (95% CI)
SD
SEM
1 mm
1.10 (1.08 to 1.12)
0.06
0.01
86 (85 to 86)
1.71
0.34
2 mm
2.07 (2.04 to 2.10)
0.09
0.02
85 (85 to 86)
1.80
0.36
3 mm
3.03 (2.99 to 3.07)
0.11
0.02
86 (85 to 86)
1.92
0.38
CI: Confidence interval; SD: Standard deviation; SEM: Standard Error of Mean
4.2.4.2
Fixation to barefoot
The 1 mm wedges were affixed in a standard manner to the lateral or medial heel
using thin adhesive tape (Figure 4.4). The wedge was aligned so that the outer margin
followed the heel outline. When the heel touched the ground the edge was just visible.
Both left and right heels were treated identically for each condition: control no-wedge
and lateral or medial wedge.
A
B
Figure 4.4 The heel-raise position with lateral (A) or medial (B) wedges affixed to
the heels.
116
4.2.5
Heel-Raise Task
The participants performed two tasks barefoot to volitional fatigue in a single test
session. Practice time was allowed for each task prior to commencement of testing. A
5 minute rest period was given between the tasks. The participants were asked to
stand barefoot on their preferred leg on a vinyl coated concrete floor with arms held in
90° abduction to aid balance. The contralateral leg was held off the ground in a
relaxed manner with slight hip and knee flexion. The stance leg was kept as straight as
possible (Figure 4.5). This was the starting position adopted for both the sustained and
maximum number of heel-raise tasks. In keeping within the resources available for
this thesis, the limitation of potential experimenter bias was justified. A single
examiner (candidate) counted and timed the heel-raises. A previous study compared
video and examiner, reporting reliability excellent (ICC=0.97) for a single examiner
(Maurer, Finley, Martel, Ulewicz, & Larson, 2007). Previous studies included a
complex multitude of task and procedural detail (Jan et al., 2005; Lunsford & Perry,
1995) requiring monitoring by more than one examiner or instrument (Section 2.7.1).
This was reduced by eliminating hand support, focusing on the specific task and
termination criteria. Instructions were identical for each performance which is
important for reliability and consistency purposes (Hanke & Rogers, 1992). These
included to touch down with the heel each time, go as high as possible each time and
go as fast as possible without falling over or touching down with the opposite leg This
was clearly defined and the variables (counting and timing with a stopwatch) are well
used measures.
Heel contact pressure and heel height was not measured. Termination criteria were
simply the inability to lift the heel from the floor or a touch down with the opposite
leg (Kaikkonen et al. 1994). Heel height has been measured very differently in
reported studies (see Section 2.7.1). The only apparent effect is to increase or decrease
the total number of heel-raises performed but reliability is not affected.
117
Figure 4.5 The starting position for both SHR and MHR tasks.
4.2.5.1
Sustained single-leg heel-raise (SHR)
Participants were first asked to perform a sustained single-leg heel-raise (SHR), lifting
their heel “as high as possible off the ground” with their knee straight (Figure 4.4),
heel clearing the ground and to “hold the position” for “as long as possible” (Clark,
2007). The time from heel-raise to touchdown was manually measured in seconds
with a digital stopwatch (accuracy 0.1s). The trial also ended by any observed
swivelling of the stance foot or contact of the contralateral foot with the ground.
4.2.5.2
Maximum number of single-leg heel-raises (MHR)
The same starting position as described in Section 4.2.5 and illustrated in Figure 4.5
was used. Participants were then asked to “lift their heel off the ground as high as
possible” and “touch down with the heel each time” (Kaikkonen et al., 1994). They
were encouraged to perform “as many heel-raises as possible” and as “fast as
possible” without falling over or moving their stance foot. The task ended when they
could no longer lift their heel off the ground or when they touched down with the
opposite foot. The time in seconds was measured (to the nearest 0.1 s) with a
stopwatch and the number of heel-raises counted.
118
4.2.5.3
Rate of performing the maximum single-leg heel-raises (RHR)
Although rate has been controlled between 30 and 120 beats per minute by a
metronome in some previous studies (Hébert-Losier, Newsham-West et al., 2009;
Hébert-Losier, Schneiders et al., 2009), rate of performance was used as a
neuromuscular factor and hence is a dependent variable in the analysis. The rate
(RHR) of performing the MHR task, defined as repetitions per minute (reps.min-1),
was calculated from the number of repetitions and the time taken to perform these.
4.2.6
Study Procedure
The study procedure from the arrival into the laboratory is outlined in Figure 4.6 and
Figure 4.7. The SHR task was repeated three times with a 60 second walk interval
between trials (Figure 4.6). There was a 2 minute rest between the barefoot controls
(pre-wedge), medial or lateral wedge conditions and post-wedge barefoot controls.
Participants could walk around the laboratory and habituate to the relevant
intervention during the rest period. The MHR task was a single set of repetitions to
maximum fatigue, similar to previous studies, performed for each condition with a 2
minute walk break between tasks which served as the habituation for the next
condition (Figure 4.7).
119
Arrive in
laboratory
SHR
Trial 1
Complete
Ethics and
personal
questionnaire
Height and
weight
measured
(barefoot)
Walk 60 s
around
Laboratory
SHR
Trial 2
Walk 2 min
Habituation
Recovery
Practice SHR task and
choose leg based on best
balance barefoot then test
barefoot control prewedge
Walk 60 s
around
Laboratory
Medial 1mm
heel wedge
Control post
medial wedge
Repeat
three trials
Completed all
5 conditions
Rest 5 min
before start of
MHR
SHR
Trial 3
Sit and
random
application or
removal of
wedge
condition
Lateral 1mm
heel wedge
Control post
lateral wedge
Figure 4.6 The sustained single-leg heel-raise task procedure.
120
Completed
SHR task
Rest 5 min
before start of
MHR
Practice MHR
task on same leg
previously
chosen
Walk 2 min
Habituation
Recovery
Barefoot
control prewedge
MHR
Sit and
random
application or
removal of
wedge
condition
Medial 1 mm
heel wedge
Control post
medial wedge
MHR task
To fatigue
Lateral 1mm
heel wedge
Control post
lateral wedge
Repeat for
each
condition
Footwear
Assessment
Answer
questions
Completed 5
Conditions
Rest
Figure 4. 7 The maximum number of heel-raises task procedure.
121
4.2.7
Footwear Assessment
Participants were asked to bring as many pairs of their current footwear as possible to
the testing session. Footwear assessment was performed at the completion of the heelraise tasks and participants were asked questions regarding the age and use of their
footwear. See Sections 2.6, 3.4 and 3.6 for a fuller discussion of the literature and
rationale.
4.2.7.1
Footwear classification, age and frequency of use
Up to 16 styles have previously been used to categorize footwear. The standard seven
styles (boot, clog, sandal, Oxford, slipper, mule and moccasin) did not
comprehensively cover the type of footwear assessed (McPoil, 1988; Menz &
Sherrington, 2000). For the purposes of this study, footwear was classified according
to type or design with criteria in order of importance: design asymmetry, heel-height,
midsole present and upper design (dress versus canvas shoe). Shoe age and frequency
of use, which is important in terms of shoe wear and injuries, was based on selfreported recall similar to other studies (Barton, Bonanno et al., 2009).
4.2.7.2
Actual heel height
Heeled footwear is known to affect dynamic stability (Menant, Perry et al., 2008),
asymmetric calf-muscle fatigue (Gefen et al., 2002) increase collision forces
(Lieberman et al., 2010) and foot contact times while running (Divert et al., 2005;
Divert et al., 2008; Lieberman et al., 2010; Squadrone & Gallozzi, 2009) and hence
may affect performance of the heel-raise task. Heel height from 3.8 cm to 6.35 cm in
dress shoes (Kerrigan et al., 2005; Kerrigan, Todd, & Riley, 1998) and 1.2 cm in
standard stability running shoes (Kerrigan et al., 2009) increase medial knee loading.
Other negative effects to foot, ankle and lower leg structure and function have been
reported and discussed in Section 2.3.2 (Frey, Thompson, Smith, Sanders, &
Horstman, 1993; Menz & Morris, 2005; Snow & Williams, 1994). Actual heel height
also called pitch or drop (the difference between fore-foot and heel thickness) was
classified according to flat (0 to 0.9 cm), moderate (1.0 to 3.0 cm) and high (> 3.0 cm)
(Barton, Bonanno et al., 2009). A standard Oxford style shoe (1.5 cm) (Menant, Perry
122
et al., 2008) and running shoe (1.2 cm) (Kerrigan et al., 2009) fall within the second
category.
Actual heel height was measured at the heel and forefoot using a Vernier calliper from
the base of the outer-sole to the top of the inner-sole, thus including any hidden height
within the shoe and the thickness of the midsole. Only the outer medial and lateral
heel was measured with a ruler in previous studies (Barton, Bonanno et al., 2009;
Menz & Sherrington, 2000) and an average recorded so that asymmetry could not be
calculated. Any mediolateral asymmetry in measurement was recorded in mm and
reported.
4.2.7.3
Outer sole wear
Outer sole wear is generally reported in four categories: none, normal, medial and
lateral (Barton, Bonanno et al., 2009; Noakes, 2003; Vernon et al., 2004). However,
for this study an exact measurement was required. Outer sole wear medially and
laterally at the heel and forefoot was measured (nearest mm) with a Vernier calliper
and the difference was reported in mm as neutral (zero or equal wear), medial (wear
medially > laterally) or lateral (wear laterally > medially).
4.2.7.4
Midsole compression
A standard clinical midsole compression or compaction test when comparing medial
and lateral sides involves exerting firm thumb pressure between the outer sole and
inner sole (Noakes, 2003). This pressure is exerted around the perimeter and through
the centre of the shoe (Figure 4.8). A second method to test midsole hardness or
stiffness is the Durometer (Section 2.6). Reliability for intra- and inter-rater was
reported excellent to substantial for both thumb compression and durometer readings
(Barton, Bonanno et al., 2009).
Midsoles were tested for hardness, both medially and laterally at the heel (Figure 4.8)
and forefoot, using an Asker C Durometer (Rex Gauge Company, Inc., Buffalo
Grove, USA). This particular durometer is recommended for measurement of medium
hard elastomeres and plastics used in footwear construction (Rex Gauge Company,
123
2012). Material thickness, surface area and texture impact upon accuracy and
reliability of the results. Guidelines, specifications and test procedure used comply
with the American Society for Testing and Materials Standards (ASTM D2240).
Three readings in the same area medially and laterally were taken as small differences
in placement can produce different readings (Barton, Bonanno et al., 2009). The
mode of the three readings was used and the difference between medial and lateral
was recorded.
Error!
A
BB
.
C
D
Figure 4.8 Evaluating the hardness of a midsole from a dual-density stability
sports shoe using an Asker C Durometer and thumb compression test.
Figure 4.8 illustrates four factors required to enable accurate and reliable durometer
readings: sufficient midsole thickness, minimal area equal to durometer foot contact
124
size (Figure 4.8 A and B), smooth texture of the midsole surface (Figure 4.8 C and D)
and firm uniform vertical pressure of the durometer foot against the midsole sample
(Figure 4.8 A and B). On the Asker C scale (range 0 to 100) a difference of less than
10 units was considered symmetric while differences greater than or equal to 10 units
asymmetric (Fisher et al., 2007). A 10 and 25 unit increase in the Asker C scale is a
20 to 50% increase in midsole hardness respectively (Fisher et al., 2007). A difference
from 10 to less than 20 units was comparable to a 1 mm difference using the thumb
compression test (medium hardness 0.5 to 1.5 mm) while 20 units or more was
equated to the soft category (> 1.5 mm) and assigned a 2 mm difference. For example,
the medial (Asker C 75) and lateral (Asker C 50) midsole hardness measured in
Figure 4.8 A and B is a 25 unit difference in density. Thumb compression medially
has minimal indentation (Figure 4.8 C) compared to laterally (Figure 4.8 D). In this
case the midsole was classed medially as hard and laterally soft. Thus, the 25 unit
difference is analogous to a thumb compression test category “soft” laterally, and
hence assigned a 2 mm difference in asymmetry.
4.2.7.5
Inserts and or orthotics
The presence of an orthotic or insert within the shoe was noted, as were details of any
added medial or lateral wedging (posting) at the heel or forefoot. The relevance of this
information was to ascertain whether the orthotic had been specifically built for the
particular shoe design and degradation characteristics or was designed based on the
poor foot paradigm (Section 3.1) to be placed into any footwear of that individual.
4.2.7.6
Footwear heel and forefoot asymmetry
Asymmetry of wear or design was reported in mm either medially or laterally and was
the combined total of outer sole wear and midsole compression for each shoe
assessed. Frequency of asymmetry between left and right shoes was also noted. In
terms of the footwear assessed, this total could be exclusively outer sole wear if
midsole hardness was equal. Midsole compression could either increase the
asymmetry, if on the same side as the outer sole wear, or attenuate the wear if on the
opposite side. The number of shoes in which this occurred was reported in the results.
125
4.2.7.7
Participants’ footwear rating
For statistical purposes only, a single global footwear condition (neutral or
asymmetric) was assigned for each participant. This was based on the most frequent
(mode) condition for each individual’s footwear collection. The reason for collapsing
the data was the variable number of shoes in each category.
4.2.8
Statistical Analysis
All analysis was performed using SAS 9.1.2. The data were analysed by comparing
the effects of each variable on performance heel-raise tasks. The variables include
age, BMI, gender, order of presentation (medial or lateral wedge), wedge condition
(no wedge, medial or lateral) and overall shoe condition (neutral or asymmetric). A
general linear mixed model was used as it provides a flexible platform to compare the
interaction of fixed and random effects (Altman, 1991; Brown & Prescott, 2006;
Hopkins, 2003). Statistical significance was determined by two-sided P-values less
than .05. After adjusting for multiple comparisons using the most conservative
adjustment (Bonferroni) significance was set at P < .005 (Brown & Prescott, 2006).
Descriptive statistics for age, height, weight, BMI and reported hours spent exercising
are presented as mean ± SD. Previous injuries, footwear type and asymmetry of wear
and/or compression are reported as relative frequencies.
Where data are skewed, geometric means which approximate the median are
considered to be the best measure of central tendency allowing the calculation of a
95% CI (Altman, 1991). Hence, the data for time, number of heel-raises and rate were
log-transformed to resolve the heteroscedasticity and skew in the model residuals. No
data was excluded and all trials analysed. Repeated measurements were accounted for
by clustering within subject and within subject-condition. The geometric means and
95% confidence intervals (95% CI), adjusted for age, BMI, gender and order, were
calculated for SHR, MHR and RHR. Fixed effects for age, BMI, gender, order
(learning or fatigue) and condition were analysed. Where there was evidence of an
effect (P < .05) the percentage increase or decrease of the fixed effect was calculated
with 95% CI. The difference between experimental conditions (no wedge, medial or
lateral wedge) of SHR, MHR and RHR is reported as percentage increases or
126
decreases and 95% CI. Finally, to test for a footwear effect on heel-raise performance
analysis was repeated for each of the SHR, MHR and RHR for the control groups
only. This analysis used a neutral or asymmetric shoe-condition interaction.
4.3
Results
4.3.1
Participant demographics
Thirty-eight individuals with a mean age of 23.0 years participated in the study (Table
4.2). Fifty-two percent chose their left leg to perform the task.
Table 4.2
Demographics of Participants (mean ± SD, range)
Variable
Age (years)
Weight (kg)
Height (m)
BMI (kg.m-2)
Men
(n = 19)
25.0 ± 5.7
18 to 36
Women
(n = 19)
22.0 ± 3.5
18 to 30
Total
(n = 38)
23.0 ± 4.9
18 to 36
73.0 ± 9.2
60 to 90
1.79 ± 0.1
1.69 to 1.91
22.7 ± 2.4
19.6 to 28.4
64.0 ± 6.3
49 to 76
1.68 ± 0.1
1.59 to 1.85
22.4 ± 2.0
18.0 to 26.3
68.0 ± 9.1
49 to 90
1.74 ±0.1
1.59 to 1.91
22.5 ±2.1
18.0 to 28.4
Previous multiple lower limb, including the spine, and ankle inversion injuries were
reported by 29% and 26.3% of participants respectively. A previous closed head
injury or concussion more than a year ago was reported by 21.0% of participants.
Only 13.2% never had been injured. The frequency of self-reported past injuries is
presented in Table 4.3.
127
Table 4.3
Frequency of Self-Reported Previous Musculoskeletal Injuries
Men
(n = 19)
Women
(n =19)
None
1
4
Total
(n = 38)
5
Back (neck, thoracic, lumbar)
1
0
1
Groin, pelvis, hip, thigh
2
1
3
Multiple lower limb and back
5
6
11
Knee, ITB*, patella femoral
2
1
3
Tibial stress, stress fracture, calves
2
1
3
Ankle, achilles
5
5
10
Foot
*ITB Iliotibial Band Friction Syndrome
1
1
2
Injury site
4.3.2
Sports and Exercise Participation
Table 4.4 indicates the type of sports and exercise reported by the participants.
On average, the participants exercised 7.8 ± 4.6 hours per week (range 2 to 21 hours)
indicating a high fitness level. Men and women reported exercising 7.7 ± 3.7 and 7.8
± 5.4 hours per week respectively. Participation in multisport events that included
running, cycling, kayaking or swimming involved 55.2% of individuals. Although
two reported no specific exercise, their daily physical work was substantial and
equivalent to the inclusion criteria.
Table 4.4
Frequency of Sports and Exercise Reported by the Participants
Men
(n = 19)
2 (10.5%)
Women
(n = 19)
-
Total
(n = 38)
2 (5.3%)
Climbing, tramping, walking
-
2 (10.5%)
2 (5.3%)
Commercial gym programmes
-
3 (15.8%)
3 (7.9%)
Cycling, mountain biking, multi-sport
1 (5.3%)
3 (15.8%)
4 (10.5%)
Hockey, rugby
3 (15.8%)
1 (5.3%)
4 (10.5%)
Martial arts
1 (5.3%)
-
1 (2.6%)
Golf, squash, tennis,
2 (10.5%)
1 (5.3%)
3 (7.9%)
-
1 (5.3%)
1 (2.6%)
10 (52.6%)
7 (36.8%)
17 (44.7%)
-
1 (5.3%)
1
Type of sports
None
Rowing
Running, triathlon
Swimming
(2.6%)
128
4.3.3
Sustained Heel-Raise (SHR)
For the SHR, there was evidence of fixed effects for age (P = .010), order (P = .008)
and conditions (medial or lateral wedge) (P < .0001). Improved performance occurred
with increasing age by 6.4% per year (95% CI 1.6 to 11.5%) and with each additional
trial by 1.2% (95% CI 0.3 to 2.0%). Although not significant, increased BMI (P =
.060) decreased performance by 8.7% per unit increase in BMI (95% CI -17.5 to
0.4%). There was no evidence for a gender effect (P = .388). The geometric means
(95% CI) for the SHR are presented in Table 4.5.
Table 4.5
Geometric means (95% CI) of SHR (s), MHR (n) and RHR (reps.min-1) for Control
and Wedge Conditions.
Control preMedial wedge
Control post
Lateral
Control post
wedge
medial wedge
wedge
lateral wedge
SHR
39.2
23.4 *
36.9
39.5
40.2
(31.4 to 48.9)
(18.8 to 29.1)
(29.6 to 45.8)
(31.8 to 49.1)
(32.4 to 50.0)
MHR
37
28 *
40
40
39
(30 to 44)
(23 to 34)
(33 to 47)
(34 to 48)
(33 to 47)
RHR
46.9
41.7 *
52.2
51.3
50.9
(42.0 to 52.6)
(37.7 to 46.2)
(46.9 to 57.7)
(46.2 to 56.6)
(45.8 to 56.6)
DV: Dependent variable; SHR: Sustained Heel-Raise; MHR: Maximum Number of Heel-Raises; RHR:
Rate of Heel-Raises; s: Seconds; n: Number of heel-raises; * P < .0001
DV
The differences between experimental conditions are expressed as a relative
percentage increase or decrease with 95% CI. The SHR of the medial wedge (P <
.001) condition decreased 40.3%, 36.5%, 41.9 % and 40.8% compared to the controls
of pre-wedge, post-medial, post-lateral, and the lateral wedge conditions respectively
(Figure 4.9). No statistically significant difference was found for the SHR
performance with the lateral wedge when compared to the control pre-wedge
condition (P = .847). Similarly, there was no evidence of differences between the
lateral wedge and two control post-wedge conditions following the medial (P = .082)
or lateral (P = .655) wedge conditions. The 8.4% (95% CI 1.3 to 15.1%) decrease
between the control post-medial and post-lateral wedges (P = .022) is interesting and
suggests a decrease in control performance after the medial wedge condition.
However, after adjusting for multiple comparisons only P < .005 would be significant.
129
Control pre-wedge
Control post-medial wedge
Lateral wedge
Control post-lateral wedge
0
5
10
15
20
25
30
35
40
45
50
Favours other condition
Figure 4.9 The % difference between the medial wedge and all other
experimental conditions (95% CI) for SHR where P < .001
4.3.4
Maximum Number of Heel-Raises (MHR)
For MHR, there was evidence of fixed effects for age (P = .031), BMI (P = .020) and
conditions (P < .001). Improved performance occurred with increasing age by 4.1%
per year (95% CI 0.4 to 8.0%) while increased BMI decreased performance by 9.0%
per unit (95% CI -15.8 to -1.6%). Although not statistically significant (P = .06), men
out-performed women by 41.2% (95% CI -1.1 to 101.6%). There was no evidence for
an order (learning/fatigue) effect (P = .654).
The geometric means (95% CI) for the MHR are presented in Table 4.5. The MHR of
the medial wedge (P < .001) condition decreased 23.4%, 28.3%, 29.0% and 30.7%
compared to the controls of pre-wedge, post-lateral, post-medial and the lateral wedge
conditions respectively (Figure 4.10). No statistically significant difference was found
for the MHR performance with the lateral wedge when compared to the control prewedge condition (P = .100). Similarly, there was no evidence of differences between
the performances in the lateral wedge and the two control post-wedge conditions
following the medial (P = .641) or lateral (P = .514) wedge conditions.
130
Control pre-wedge
Control post-medial
wedge
Lateral wedge
Control post-lateral
wedge
0
5
10 15 20 25 30 35 40 45 50
experimental conditions (95% CI) for MHR where P < .001.
4.3.5
Rate of Heel-Raises (RHR)
For the RHR, there was evidence of a fixed effect for condition (P < .001) only. There
was no evidence of effects for age (P = 0.353), BMI (P = 0.826), gender (P = .467) or
order (P = .372). The geometric means (95% CI) for the RHR are presented in Table
4.5. The RHR for the medial wedge condition decreased by 10.7%, 24.3%, 17.9% and
18.3% relative to the controls pre-wedge (P = 0.004), post-medial (P < .001), postlateral (P < .001) and lateral (P < .001) wedge conditions respectively (Figure 4.11).
131
Control pre-wedge
Control post-medial wedge
Lateral wedge
Control post-lateral wedge
0
5
10
15
20
25
30
35
40
45
50
experimental conditions (95% CI) for RHR where P < .005.
Compared to the control pre-wedge, the RHR increased by 9.3% (95% CI 1.3 to
17.9%), 11.0% (95% CI 1.5 to 21.4%) and 8.8% (95% CI -0.6 to 19.1%) for the
lateral (P = .022), controls post-medial (P = .023) and post-lateral (P = .066) wedge
conditions respectively. After adjusting for multiple comparisons only P < .005 was
considered significant. There was no evidence of differences between the rates for the
lateral and controls post-medial (P = .646) or post-lateral (P = .895) wedge
conditions.
4.3.6
Shoe Condition Effect
Although each participant provided an average of 4 pairs of shoes with variable daily
usage, an overall shoe condition (neutral or asymmetric) was compared to
performance. No statistical relationship was evident for a shoe condition effect on the
control pre-wedge performance of the heel-raises for SHR and MHR. However, shoe
condition was significant for RHR (P = .042) with individuals performing better by
6.6% (95% CI 0.2 to 12.3%) where the overall shoe condition was neutral.
132
4.3.7
Footwear
One hundred and forty-seven pairs of shoes were assessed with a median of 4 (range 2
to 8) per person.
4.3.7.1
Footwear classification age and frequency of use
Footwear supplied was divided into six categories according to the design and use
(Table 4.6). These were neutral sports (medial and lateral heel midsole is of equal
hardness), control sports (medial heel harder than lateral midsole) shoes, dress shoes
(similar to Oxfords), flats or loafers, canvas shoes and lastly boots used for work or
tramping. Sports shoes comprised court, cross-trainers (gym) and outdoor footwear
for road or trail running. Flats and canvas shoes were distinguished by the lack of a
midsole in the latter and heel height. Thirty-five percent were neutral and 10.9%
stability sport shoes. The remaining shoes used for work or many other day-to-day
activities were neutral in design, of these 35.4% were flats and canvas shoes.
Table 4.6
Frequency of Shoe Type Worn by the 38 Participants (n = Shoe Pairs)
Neutral sports: heel-height 1.0 to 2.0 cm
Men
n = 70
28 (40.0%)
Women
n = 77
24 (31.2%)
Total
n = 147
52 (35.4%)
Control sports: heel-height 1.0 to 2.0 cm
6 (9.0%)
10 (13.0%)
16 (10.9%)
Dress: heel-height 1.0 to 3.0 cm
11 (15.7%)
10 (13.0%)
21 (14.3%)
Flats or loafers: heel-height 0.5 to 1.5 cm
18 (25.7%)
23 (30.0%)
41 (27.9%)
Canvas: heel-height 0.0 to 1.0 cm (within shoe)
3 (4.3%)
8 (10.4%)
11 (7.5%)
Boot: heel-height 1.5 to 2.5 cm
4 (5.7%)
2 (3.0%)
6 (4.1 %)
Type of shoe
The average reported age of the shoes was 15.7 ± 15.5 months (range 0 to 120
months, median 12). Sixty-two percent were less than or equal to 1 year old (Table
4.7). Self-reported frequency of use for each of the large number of shoes was sketchy
and hence this variable is excluded.
133
Table 4.7
Reported Age of Footwear
Age of shoe (months)
0 to 5
6 to 12
13 to 18
19 to 24
25 to 120
4.3.7.2
Frequency
n = 147 pairs
42 (28.6%)
50 (34.0%)
4 (2.7%)
38 (25.9%)
13 (8.8%)
Actual heel height
No high heels (> 3.0 cm) were assessed in this sample. Moderate heel-height (1.0 to
3.0 cm) was measured in 64.6% of shoes. The rest had less than 1.0 cm drop between
the heel and fore-foot. The description of flats is a misnomer. Viewed from the
outside, many appear to be completely flat, but measuring the heel height from within
the shoe reveals differences. These differences up to 1.0 cm are produced by hidden
heels formed by or attached to the inner-sole comprised of sponge or plastic/rubber of
variable hardness extending to the mid-foot area (Figure 4.12).
Figure 4.12 Flat canvas shoes without a midsole but attached beneath the innersole is an 8.74 mm soft (Asker C 30) rubber heel.
134
4.3.7.3
Outer sole wear asymmetry
Forty-nine percent of all the shoes assessed had asymmetric outer-sole wear (Table
4.8). Of these, only 0.7% had 1 mm medial outer-sole wear while 40.7% had from 1
to 3 mm lateral outer sole heel wear. Lateral forefoot wear occurred in 3.4% of shoes
with three pairs 1 mm and the remaining two pairs 2 and 5 mm respectively. Two
percent had 1 mm medial forefoot wear. Asymmetry of wear between the left and
right shoe was 6.8%. These were 4.8%, 1.4% and 0.7% for 1 mm, 2 mm and 4 mm of
wear respectively. This left and right asymmetry was not linked to the participants
preferred leg for these experiments. The greatest left/right asymmetry of 4 mm was
measured in the medial forefoot of one pair of sports shoes used for Tennis.
Table 4.8
Frequency of Shoe Heel Outer-Sole Wear Asymmetry in 294 Shoes (n = Shoe
Pairs)
Status
Neutral: symmetrical wear or no wear
Men
n = 70
38 (54.3%)
Women
n = 77
37 (48.18%)
Total
n = 147
75 (51.0%)
Wear on lateral heel
1 mm
22 (31.4%)
22 (28.6%)
44 (29.9%)
2 mm
4 (5.7%)
9 (11.7%)
13 (8.8%)
3 mm
1 (1.4%)
2 (2.6%)
3
1 (1.3%)
1 (0.7%)
4 mm
-
(2.0%)
5 mm
4
(5.7%)
4 (5.2%)
8 (5.4%)
6 mm
1
(1.4%)
-
1 (0.7%)
8 mm
-
1 (1.3%)
1 (0.7%)
Wear on medial heel: 1 mm
-
1 (1.3%)
1 (0.7%)
4.3.7.4
Midsole compression asymmetry
Midsole compression asymmetry of 10 or more Asker C units occurred in
27.9% of footwear (Table 4.9). Of these, 22.5% were softer on the lateral heel with
15.7% women’s and 6.8% men’s pairs respectively. Shoes with a dual density midsole
design (10.9%) were 10 or more Asker C units harder on the medial than the lateral
135
side. Midsole hardness greater than or equal to Asker C 70 units, in stability sports
shoes, dress shoes and tramping boots, exhibited no collapse or compaction.
Table 4.9
Frequency of Asymmetric Shoe Compression at the Heel (n = Shoe Pairs)
Men
n = 70
Women
n = 77
Total
n = 147
Softer on the Lateral heel
10 ≤ Difference < 20 units*
9 (12.9%)
19 (24.7%)
28 (19.0%)
Difference ≥ 20 units
1 (1.4%)
4 (5.2%)
5 (3.4%)
Softer on the Medial heel
10 ≤ Difference < 20 units
6 (8.6%)
2 (2.6%)
8 (5.4%)
Status
* Asker C units
The remaining 17% of midsoles with compression were relatively soft with values of
Asker C 60 units or less found in neutral sports shoes, some dress shoes, flats and
canvas shoes. An example of this is the heel insert in Figure 4.12 measuring Asker C
30 units. The difference in density was a result of lateral midsole compression in 6.1%
neutral sports shoes, 4.8% casual flats and a dress shoe. In the forefoot, 2.0% were
softer by 10 Asker C units on the lateral side corresponding to their heel softness.
Footwear with medial midsole compression comprised 4.1% neutral sport shoes and
1.4% dress shoes and flats.
Similar shoe types exhibited opposite compression effects in 10.5% of
participants. For example, two neutral sports shoes of one participant had equal (10
unit difference on the Asker C scale) but opposite compression effects. One pair, 9-12
months old, compressed medially. The second pair, less than 3 months old,
compressed laterally. The participant’s daily flat canvas shoe that was more than 12
months old only had lateral wear of 1 mm at each heel and no compression difference.
4.3.7.5
Inserts and orthotics
Custom-molded prescribed FormorthoticsTM or FootbioticsTM with medial arch
support were worn by 15.8% of participants in 12.9% of shoes (Table 4.10). Lateral
wear from 1 to 6 mm was measured in 79.0% of these shoes. Lateral softness of the
136
heel midsole occurred in 57.9% of shoes. This lateral softness amplified the effect of
the lateral wear and thus increased the overall shoe lateral asymmetry (Table 4.10
Shoe 2).
Table 4.10
Shoe Type, Midsole Compression Difference, Outer-Sole Wear and Total
Asymmetry for Participants wearing Orthotics in 12.9% of Shoes
1
Flats
Midsole
compression
difference
Softer
Asker C units
Neutral
2
Flats
10 lateral
2 mm
3 mm
W1
3
Neutral sports ±5 mm medial
10 lateral
5 mm
6 mm
W2
4
Flats
10 lateral
5 mm
6 mm
W2
5
Stability sports ±8 mm medial
20 lateral
0 mm
2 mm
W2
6
Dress
±5 mm medial
10 lateral
1 mm
2 mm
W3
7
20 lateral
1 mm
3 mm
W3
8
Neutral
0 mm
Neutral
W3
9
Flats
10 lateral
1 mm
2 mm
M1
10
Stability sports
20 lateral
0 mm
2 mm
M1
11
Dress
Neutral
1 mm
1 mm
M1
12
Flats
10 lateral
5 mm
6 mm
M1
13
Canvas
Neutral
1 mm
1 mm
M2
14
Dress
Neutral
1 mm
1 mm
M2
15
Flats
10 lateral
5 mm
6 mm
M3
16
Stability sports
10 lateral
0 mm
1 mm
M3
17
Neutral sports
10 medial
6 mm
5 mm
M3
18
Neutral sports
10 medial
5 mm
4 mm
M3
19
Flats
Neutral
2 mm
2 mm
M3
Shoe Type
Additional posting
±5 mm medial
Outersole
wear
lateral
Total
asymmetry
lateral
Total
n=6
1 mm
1 mm
W1
W: Women; M: Men; W1, M1: number of participant
A difference of 10 and 20 units was equated to a thumb compression of 1 mm and 2
mm respectively. Only two neutral sports shoe pairs (10.5%) were softer medially at
the heel by 10 Asker C units but they had marked lateral wear of 5 and 6 mm
respectively. In this case, the medial compression attenuated some, but not all, of the
lateral outer sole wear and this was shown in the overall shoe asymmetry (Table 4.10
Shoes 17 and 18). Two women had orthotics with an attached 5 to 8 mm medial heel
137
wedge (posting) although none of their shoes had medial wear or compression (Table
4.10 Shoes 3 to 8). Total asymmetry between 1 and 6 mm laterally was measured in
94.7% of shoes. This excluded the asymmetric effect of the medial orthotic arch
support and the 5 to 8 mm medial wedging (posting) of the six pairs.
4.3.7.6
Footwear mediolateral asymmetry
The overall heel asymmetry of the shoes is shown in Table 4.11. Midsole compression
differences accounted for 27.9% in the overall shoe asymmetry. Examples of this are
presented in Table 4.10. This difference could wholly account for the asymmetry if
there was no outer sole wear (Table 4.10 Shoe 5). The difference could increase the
asymmetry if the outer sole wear was on the same side (Table 4.10 Shoes 2 to 4, 6, 7,
9, 10, 12, 15 and 16), or attenuate the asymmetry if on the opposite side of the outer
sole wear (Table 4.10 Shoes 17 and 18). In 6.8% of shoes where left and right shoe
discrepancies existed, the smallest asymmetry was chosen to represent the overall
wear for that shoe. The design of the shoe influenced the overall asymmetry rating.
The 16 pairs of stability shoes all had greater medial hardness while six of these also
had lateral outer sole wear. The pattern of mediolateral asymmetry was 4.8% medial
and 57.8% lateral. Lateral asymmetry of 1 to 3 mm comprised 49.7%.
Table 4.11
Total Mediolateral Asymmetry in 294 Shoes (n = Shoe Pairs)
Neutral: symmetrical design or wear
Men
n = 70
29 (41.4%)
Women
n = 77
26 (33.8%)
Total
n = 147
55 (37.4%)
Worn on lateral heel
1 mm
24 (34.3%)
22 (28.6%)
46 (31.3%)
2 mm
7 (10.0%)
14 (18.2%)
21 (14.3%)
3 mm
1 (1.4%)
5 (6.5%)
6 (4.1%)
4 mm
1 (1.4%)
2 (2.6%)
3 (2.0%)
5 mm
2 (2.9%)
2 (2.6%)
4 (2.7%)
6 mm
2 (2.9%)
2 (2.6%)
4 (2.7%)
8 mm
-
1 (1.3%)
1 (0.7%)
4 (5.7%)
3 (3.9%)
7 (4.8%)
Status
Worn on medial heel: 1 mm
138
4.4
4.4.1
Discussion
Primary Finding of Asymmetric Heel Perturbation on Heel-Raise
Performance
The primary findings of this study showed that the application of a 1 mm medial
hindfoot wedge decreased the performance of the single-leg heel-raise task. Because
the performance decreased for SHR, MHR and RHR relative to barefoot control
conditions, single-leg heel-raise performance may be sensitive to such small
perturbations (1 mm) of lateral heel tilt. Participants did fewer heel-raises (MHR)
more slowly (RHR) with a medial wedge simulating lateral heel wear. Further,
performance of SHR in the control post-medial wedge performance showed a
decreased tendency compared to the control post-lateral wedge. The application of the
medial wedge may thus have adversely affected the control performance. Although
the maximum number of single-leg heel-raises did not significantly alter when a 1 mm
lateral hindfoot wedge was used (simulating medial shoe asymmetry), there was a
tendency for RHR to increase relative to the pre-wedge control. This improved
performance for RHR suggested that the lateral wedge may well have had some
positive effect facilitating performance. The performances of the three control nowedge conditions (pre-wedge and post-medial or post-lateral wedge) were not
significantly different, indicating that there was no learning or fatigue effect on the
tasks.
The main discussion point relates to possible explanations as to why medial and not
lateral simulated asymmetry produced a decreased performance. Two questions are
self-evident. The first is what effect the asymmetry stimulus does to the foot, ankle
and whole lower limb when the heel is on the ground? Is the pre-set up position
critical in determining the quality of performance on the toes? The second asks what
is different about the pre-set position in the medial versus the lateral condition and
how does this relate to the participants’ own footwear conditions? Since no other
research has been published on performance and asymmetry in heel-raises, it is
necessary to look at other footwear intervention studies where neuromuscular or joint
loading outcomes have been measured. Most of these involve walking or running gait
139
but some also include heel-raises and footwear (Gefen et al., 2002) or ankle injuries
(Kaikkonen et al., 1994; Tropp & Odenrick, 1988). Hence, in trying to explain and
understand these findings and relate to what is already known, supposition and
speculation must be the first level of discussion. The next step would be further
investigation.
4.4.2
Hypotheses
In terms of the proposed hypotheses, H1 was partially supported in that the medial
wedge decreased performance compared to the neutral state. The hypothesis is
accepted but holds for the medial direction only. The lateral wedge produced similar
performances to the control conditions. This simulated medial degradation was
measured in 4.8% of footwear. The medial wedge simulated lateral heel wear which
was measured in 57.8% of footwear assessed. Possible explanations and suppositions
relating to these different results are discussed later in this chapter. The medial wedge
may have exacerbated the lateral asymmetry already present in footwear or
destabilised the ankle similar to the effect of a lateral ankle injury. Conversely, the
lateral wedge would attenuate the asymmetric effect of footwear and/or facilitate
ankle-foot-knee function.
The data were unable to establish a link between current shoe condition and control
barefoot heel-raise performance (H2) for SHR and MHR, but decreased performance
was related to shoe asymmetry for RHR. The hypothesis is accepted for RHR only. It
is possible that the collapsing of data to form only two shoe conditions (neutral or
asymmetric) for statistical purposes diluted the effect each individual’s footwear
condition may have had on performance. Furthermore, the relative frequency of each
shoe worn by participants, which was difficult to establish, would also need to be
factored into the shoe condition. Ideally, performance testing in each shoe used by an
individual would provide a more accurate representation. In the current cohort, testing
in each shoe would have provided a considerable challenge to the participants using
the same experimental design.
The orthotics assessed in this cohort of 38 participants was consistent (H3) with the
poor foot paradigm discussed in Chapter 3. The hypothesis was accepted. The
140
prescribed orthotics did not appear to take into account the individual asymmetric
shoe wear patterns and may have contributed to the lateral asymmetry measured.
The fourth hypothesis (H4) that lateral heel wear was more frequent than medial heel
wear was confirmed and accepted. Lateral wear was simulated with the medial wedge.
This fact is important as it may link the decreased performance to the typical
frequency of lateral shoe asymmetry found in this study. Individuals may have been
less resilient to simulated lateral wear than to medial wear. Research related to
chronic medial knee joint stress and footwear interventions uniformly agree that
changing the lateral foot-ground interface can either increase or decrease knee
loading. These results provide evidence that lateral asymmetry is more prevalent in
the footwear of a healthy young population. The type of degradation observed
provides valuable information about present footwear design weaknesses. This
relationship is explored in Sections 4.4.4 and 4.4.5.
4.4.3
The Heel-Raise Task
The single-leg heel-raise task (Section 2.7.1) until volitional fatigue (MHR) is a
simple functional evaluation that approximates rhythmic type of muscle activity
which occurs in daily activities such as walking and running (Möller et al., 2002;
Waddington & Adams, 1999). Performance may be influenced by global and local
sensory information, muscle endurance and strength which were not assessed in this
study. The simulated asymmetry was thought to manipulate mechanical and sensory
input from the foot and ankle. The heel-raise task is not walking or running gait
limiting the application of these results to these activities. Performance of the heelraise compared to walking and running has not been studied. Children with poor
plantar flexion function and hence abnormal walking and running gait, also have poor
heel-raise performance (Yocum et al., 2010). Similarly, patients with poor ankle
functional outcomes post surgery (Kaikkonen et al., 1994) and non-exercising
sedentary individuals (Jan et al., 2005) perform worse. The projection of the findings
from this study to dynamic movement is a topic for future research and hence possible
similarities and differences can only be speculated.
141
4.4.3.1
Reliability of the heel-raise tasks
While the reliability of the heel-raise task used was not formally assessed in this
study, the reliability of measurement of the calf raise test has been reviewed
elsewhere (Clark, 2007; Hébert-Losier, Schneiders et al., 2009) and discussed in
Section 2.7.1. Factors that affect reliability such as participant profile and procedure
were tightly controlled. Criteria for the task and termination were closely aligned to
typical clinical practice where only one examiner is usual. In the SHR, an
improvement in performance of 1.2% (95% CI 0.3 – 2.0%) occurred for each
additional trial (P < .008). There was no order (learning/fatigue) effect for MHR and
RHR. However, the three control conditions in this study do provide a measure of the
reliability for these tasks. For example, the variation across the three control
conditions for the MHR is only 3 heel-raises (7.5%). The medial wedge condition
resulted in a decrease of 9 to 12 heel-raises (23.4 to 30.7% reduction) relative to the
control and lateral wedge conditions. The experimental effect clearly exceeded the
variation between control conditions. Combined with the distinctive non-overlap of
the 95% CIs, there was a clear indication that there was an experimental effect due to
the medial wedge condition.
4.4.3.2
Comparison to other studies
The maximum number of single-leg heel-raises in a poor ankle outcome (25 ± 18
heel-raises) sub-group (Kaikkonen et al., 1994) was similar to the simulated lateral
wear (medial wedge) performance in this study. The control (40 ± 15) and excellent
rehabilitation outcome (53 ± 19) groups compare favourably to the lateral wedge and
control performances in this study. Over a period of time, the effect of lateral outersole wear or compression may result in sub-threshold cumulative adverse sensory
loading leading to chronic disturbance of ankle position sense (Tropp, Askling, &
Gillquist, 1985; Tropp, Ekstrand, & Gillquist, 1984a). It has been shown that at 12
weeks following an acute ankle inversion injury, there is still an increased error in
inversion position sense (Konradsen & Magnusson, 2000; Konradsen, Olesen, &
Hansen, 1998). MHR has also been used to compare fatigue in the lower leg muscles
and shifts in COP while performing the task and during walking (Gefen et al., 2002).
Eight women performed heel-raises to exhaustion, both barefoot and in habitual high142
heel or flat shoes. The stated aim for the number of heel-raises, with opposite hand
support, was between 25 and 40. The actual number performed is not reported so no
comparison with this study is possible.
Although 25 heel-raise repetitions has been suggested to represent normal capacity in
healthy individuals (Lunsford & Perry, 1995), this study showed a large individual
variability in this performance measurement. Task performance such as starting
position, heel height and termination also affect the total number of heel-raises
performed (Hébert-Losier, Newsham-West et al., 2009; Ross & Fontenot, 2000;
Svantesson et al., 1998). In a clinical setting, it is suggested that each individual’s
maximum needs to be determined, on both legs, in order to compare barefoot and
footwear conditions whether injured or uninjured. All participants exercised regularly
so factors other than strength and endurance of the lower limb muscles impacted on
their different performance levels of the heel-raise tasks. A limitation of this study is
the performance was only measured on one leg. Time and possible fatigue in repeated
performances forced this pragmatic choice. Previous studies have shown that in
healthy individuals, the performance between legs is similar (Lunsford & Perry, 1995;
Möller et al., 2005; Ross & Fontenot, 2000) but not following injury (Kaikkonen et
al., 1994; Möller et al., 2002).
The RHR is not usually measured in research but set at arbitrary rates (Section 2.7.1)
in order to control the task. However, neuromuscular performance is very important
as an outcome variable when considering footwear interventions and gait in almost all
sporting contexts. No comparisons can be drawn from other studies. The results from
this study suggest the rate is a useful performance measure and is sensitive to a small
perturbation. It was not affected by age, BMI and gender. The individual rate of
approximately 50 reps.min-1 achieved across the control conditions, is close to the rate
set by Kaikonnen et al. (1994) of 60 reps.min-1.
The SHR has also been used in measuring high level balance in women over 60 years
and to develop normative values in this age group (Clark, 2007). The alternatively
named the Unilateral Forefoot Balance Test was shown to be reliable and valid, and
the results from 31 healthy volunteers (mean age 34.8 ± 13.8 years) was 20.4 ± 9.8 s
(range 2.7 to 30.0) The older cohort and a ceiling set at 30 s may account for some of
143
the difference with the SHR in this study. Based on their data young healthy adults
could be expected to maintain a SHR for a time of 10 s. The results reported here for
a 10 year younger cohort suggest times over 30 s should be closer to normal function
although there is large inter-subject variability in this performance measure. In the
medial wedge condition the geometric mean was 23.4 s (95% CI 18.8 to 29.1) which
is closer to the reported values for the older cohort.
4.4.3.3
Age, BMI and gender on heel-raise performance
No consensus exists on the influence of age, BMI and gender (Hébert-Losier,
Newsham-West et al., 2009) and this is discussed in Section 2.7.1. A strength of this
study was to include these as fixed effects in the statistical model. The participant
inclusion criteria ensured a sample of similar fitness, health and age so differences
were not expected. Although increased age improved performance by 6.4% and 4.1%
in SHR and MHR respectively, this effect may have been magnified by excellent
performances from a few older individuals, who also happened to be males. This may
also explain the tendency in MHR for men to out-perform women by 41.2%. Previous
studies have not shown age or gender to be a factor (Lunsford & Perry, 1995) except
in a sedentary sample especially after 40 years old (Jan et al., 2005) and young
children (Yocum et al., 2010). There were no other gender effects on heel-raise
performance. Increased BMI had the opposite effect on performance with a decrease
of 8.7% and 9.0% for SHR and MHR respectively. RHR was unaffected by each of
these fixed effects and hence should be considered as a useful tool when comparing
individuals.
4.4.4
4.4.4.1
Footwear Assessment
Mediolateral asymmetry in worn footwear
Of the 294 shoes individually assessed for heel asymmetry, 57.8% had lateral and
4.8% medial wear respectively. Asymmetric wear was thus evident and measurable in
the typical daily footwear of a substantial percentage of this sample population.
Lateral wear of 1 mm was measured in 31.3% of shoes. The asymmetric perturbation
of 1 mm was chosen based on clinical anecdotal evidence. These results confirm the
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choice of 1 mm heel wedges as the most frequent heel asymmetry. Considering that
62.5% of shoes were reported less than or equal to 1 year old, it can be concluded that
the most likely initial asymmetric wear will be 1 mm. Thereafter, progressive
asymmetric shoe heel wear is possible and in this study 14.3% had 2 mm while 12.2%
had 3 mm to 8 mm. It is not possible to speculate on the relative time-frame over
which this progressive wear occurred but it would seem likely that once the first 1 mm
of asymmetry is established, the wear encourages further degradation.
Factors that may impact on the extent of the footwear degradation found in this study
include the age of footwear (37.4% older than 1 year), individual’s BMI (18.0 to 26.3
kg.m-²), footwear design (10.9% asymmetric design, 27.9% midsole too soft) and
orthotic intervention (15.8%). It was not possible to analyse the relative frequency and
purpose of use for all shoes assessed as detail provided by the participants was
incomplete. Stability shoes contributed to the total lateral asymmetry by their design
as a result of lateral midsole softness or a combination of outer-sole wear and
softness. No medial midsoles of these shoes had collapsed or compressed. The
relative softness of the neutral footwear midsole design, less than Asker C 70 units,
also added 17.0% to lateral or medial compression.
4.4.4.2
Orthotics and footwear asymmetry
In 94.7% of shoes in which orthotics were inserted, lateral wear or compression was
measured suggesting that the prescription of the orthotics was made without regard
for shoe condition. Molded orthotics and attached medial posting contribute to a
medial bias (Section 2.3.3) or increased supination (Ball & Afheldt, 2002a, 2002b;
Franz et al., 2008). This increases plantar forces and pressures on the fifth metatarsal
increasing the risk of fracture in basketball (Yu et al., 2007), while the decrease in
pronation increases impact loading during running (Perry & Lafortune, 1995). In the
shoes assessed the orthotics would likely contribute to the lateral wear or the
compression measured.
4.4.4.3
Different asymmetry wear patterns in the same individual
Participants in this study provided shoes with mediolateral asymmetry patterns
varying in magnitude and position. In 10.5% of individuals, opposite midsole
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compression effects were measured in their personal footwear collection (Section
4.3.7.4). Shoes of similar design from the same individual had midsole collapse at the
heel either medially or laterally (see example Shoes 15 to 19 in Table 4.10). Shoes
from individuals with medial midsole compression could also have lateral outersole
wear (see shoes 17 and 18 in Table 4.10). In these cases an equal but opposite effect
would neutralise the asymmetry. Medial midsole compression and lateral outersole
wear attenuates the magnitude of the asymmetry in the direction of the greater
asymmetry. Thus these combinations may or may not neutralise the asymmetry.
According to the poor foot paradigm (Sections 2.6, 3.1 and 3.2), wear patterns are
fixed by the individual’s biomechanics. These opposite asymmetries measured in
degraded footwear in the same individual contradict this traditional view. These
findings suggest footwear design weakness needs more thorough investigation using
open-ended questions which allow a number of answers, questions such as why did
the material fail. The traditional view of foot function does not require this question to
be asked, as the failure is caused by the individual using the shoe. These findings
suggest that all footwear worn by an individual needs to be assessed in order to gain a
complete understanding of degradation and wear patterns. Simply assessing the sports
shoe will not provide the complete picture. Both midsole compression and outersole
wear need to be assessed concurrently in all footwear. This complexity has not
previously been discussed in the literature and needs further investigation.
4.4.4.4
Shoe design characteristics of heel-height and midsole hardness
Two design features that may influence mediolateral asymmetry are heel height
(Section 2.3.2) and motion control properties (Section 2.3.3). Although no high heels
were assessed in this study, 64.6% of footwear had between 1.0 and 3.0 cm of actual
heel height. Interestingly, this corresponds with the 57.8% of shoes which had lateral
wear and/or compression. The height of the heel is known to affect joint loading
(Kerrigan et al., 2005; Kerrigan et al., 1998) and mediolateral stability (Robbins &
Waked, 1997) by increasing supination (Stefanyshyn et al., 2000). It is not surprising,
therefore, that heeled footwear is more likely to wear or compress laterally. However,
this lateral wear can be attenuated or increased by the midsole hardness. Thick soft
midsoles can compress neutrally or asymmetrically. In this study, the ratio was 5.4%
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medially and 22.4% laterally. The motion control design with medial harder than the
lateral midsole ensures lateral collapse or compression is more likely. None in this
shoe design category had medial outer-sole wear or midsole compression. The lateral
softness combined with heel height, may also influence the extent of lateral outer-sole
wear as 37.5% of this design also had lateral wear.
4.4.4.5
Current shoe interventions to decrease knee loading
The pattern of mediolateral asymmetry occurring in worn footwear reported in this
study may provide clues in the search for the elusive perfect footwear design
(Sections 2.2.2, 2.3, 3.1 and 3.2). The results in this study indicate differences in
magnitude in lateral and medial degradation for each shoe. Of the 294 shoes assessed,
57.8% had lateral wear ranging from 1 mm (31.3%), 2 mm (14.3%) and 3 to 8 mm
(12.2%). Only 4.8% had medial wear of 1 mm and 37.4% were neutral. These results
highlight the importance of the lateral component in footwear degradation. Standard
interventions irrespective of the individual’s shoe condition may or may not be
appropriate. The design solution to medial midsole compression and over-pronation
was a response to the poor foot paradigm (Section 3.1 and 3.2) and not to the fact that
soft thick midsoles can compress with use (Robbins et al., 1992; Robbins et al., 1994).
The conflict arises between cushioning and stability, as both are thought important to
protect the body, but simultaneously counteract each other (Stüssi, Stacoff, &
Lucchinetti, 1993). It would be better, however, to avoid the collapse of the
components altogether by decreasing the thickness and increasing the stiffness of the
midsole itself (Robbins & Gouw, 1990; Roy & Stefanyshyn, 2006; Stefanyshyn &
Nigg, 2000b). Current research into footwear interventions and medial knee
osteoarthritis is exploring the same path as the dual density shoe design albeit on the
opposite side of the shoe (Block & Shakoor, 2010; Fisher et al., 2007; Hinman &
Bennell, 2009; Jenkyn et al., 2011). This has also been discussed in Section 2.3.3
relating footwear design to controlling pronation or supination at the foot.
Three methods employed to reduce medial knee loading include the use of lateral
wedges (Barrios et al., 2009; Crenshaw, Pollo, & Calton, 2000; Kakihana et al.,
2007), stiffer lateral midsoles (Erhart, Dyrby et al., 2010; Erhart, Mündermann,
Elspas, Giori, & Andriacchi, 2008) and flat neutral footwear (Hinman & Bennell,
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2009; Radzimski et al., 2011; Shakoor, Lidtke et al., 2008; Shakoor et al., 2010). The
conflicting clinical results for lateral wedging (Baker et al., 2007; Barrios et al., 2009;
Bennell et al., 2011; Pham et al., 2004) and individual responses to lateral wedging
(Kakihana et al., 2007; Kakihana, Akai et al., 2005; Kakihana, Akai, Yamasaki,
Takashima, & Nakazawa, 2004) and the stiffer shoe (Erhart, Mündermann, Elspas et
al., 2008; Fisher et al., 2007) suggest the magnitude and type of the intervention may
not be appropriate for the shoe condition (Hinman & Bennell, 2009). Reviews
highlight this fact (Brandt, Dieppe, & Radin, 2008; Hinman & Bennell, 2009;
Radzimski et al., 2011; Shakoor, Lidtke et al., 2008) indicating there is still much
work to be done to find the perfect shoe.
The variable stiffness shoe design (Section 2.3.3) has increased hardness at the lateral
(≥ Asker C 70 units) compared to medial (Asker C 55 units) margin (Erhart,
Mündermann, Elspas et al., 2008). Since this was the most frequently damaged area in
the footwear assessed, this solution has merit. However, over time, the laterally stiffer
midsole shoe is likely to show compression on the medial side, thus potentially
increasing opposite asymmetry. So it, too, may be an incomplete solution to the
problem. This footwear design solution is still based on the prevailing paradigm. See a
fuller discussion in Sections 2.2.2, 3.1 and 3.2. In order to achieve comprehensive
footwear solutions the total footwear design needs to integrate the type of degradation
that currently occurs.
4.4.5
Simulated Asymmetry and the Link to Biomechanical and
Sensory Effects
The 1 mm medial wedge was used to simulate lateral outer heel sole wear, a common
pattern seen in footwear (Asplund & Brown, 2005; Sheehan, 1979). In contrast to
barefoot (Lieberman et al., 2010; Squadrone & Gallozzi, 2009) the lateral outer heel
sole is typically the first point of ground contact during walking and running in heeled
footwear (Kerrigan et al., 2009; Kurz & Stergiou, 2004). In order to explain the
decreased neuromuscular heel-raise performance a biomechanical model is proposed.
This is speculative as no kinetic or kinematic data was gathered during the heel-raise
task. Compared to barefoot, lateral heel wear may increase the amount of inversion of
the calcaneus and talus during stance. This would increase the inversion moment arm
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through the talus prior to achieving maximum amount of functional eversion. This
effect would be similar to that of medially biased orthotics (Yu et al., 2007) and a
sudden inversion movement on a motorised platform (Ramanathan et al., 2011). A
sub-optimal position of the talus within the ankle mortise (Stormont, Morrey, An, &
Cass, 1985) will likely reduce joint congruence and form closure. It may be that such
sub-optimal hindfoot position will alter mechanoreceptor afferent signals and as a
consequence alter muscle recruitment around the ankle joint and foot (Kerr et al.,
2009). The actual presence of the medial or lateral wedge on the bare foot may also
heighten information from the somatosensory system and this is also discussed as a
possible mechanism explaining the changes in performance measured.
4.4.5.1
Conceptual model of the biomechanical effect of the medial wedge
simulating lateral heel degradation
Figure 4.13 provides a conceptual model of the proposed effect of the medial 1 mm
wedge on the ankle joint moments. Mediolateral stability is controlled by the evertor
and invertor muscle activity around the foot and ankle. This shifts the COP medially
or laterally while the total body balance COM moves in the opposite direction (Bauby
& Kuo, 2000; Gefen et al., 2002; Rodgers, 1995). The mediolateral shift in the
vertical GRF increases or decreases the length of the GRF lever arms from the ankle,
knee and hip joint centres (Shelburne et al., 2006). Extrapolating to the knee joint, the
medial wedge would increase the length of the lever arm as the vertical force will pass
more medially to the joint centre (Figure 4.13) while a lateral wedge decreases
mediolateral lever arm length (Erhart et al., 2008; Haim et al., 2011; Shelburne, Torry,
& Pandy, 2005; Shelburne et al., 2008). The muscle lever arms remain constant.
In order to maintain joints in equilibrium, asymmetric muscle force is likely to be
required. The medial wedge condition would supinate the foot and lower leg while the
heel is on the ground. As a result, increased muscle work may have been required to
perform the heel-raises. Increased peroneus longus muscle activity has been measured
in footwear compared to barefoot (Kerr et al., 2009; Ramanathan et al., 2011). A
similar effect was measured in calf muscle activity in women who habitually wore
high-heeled footwear that supinate the foot and lower leg (Gefen et al., 2002). The
lateral gastrocnemius and peroneus longus muscles fatigued more quickly barefoot
149
while participants performed heel-raises to fatigue (Gefen et al., 2002). A 21%
increase in peroneus longus activity while walking has also been shown with 15o
medial orthotics (Murley & Bird, 2006). Medial or lateral footwear-induced shifts in
COP have been shown to affect knee joint loading (Haim et al., 2008) and leg muscle
activity (Goryachev, Debbi, Haim, Rozen, & Wolf, 2011; Goryachev, Debbi, Haim, &
Wolf, 2011) while walking. The medial induced load, equivalent to the medial wedge
or simulated lateral wear of the present study, increased lateral gastrocnemius and
tibialis anterior muscle activity and EKAM. However, muscle activity was not
measured in this study, so this is speculative and further research measuring muscle
activity while performing maximum heel-raises could facilitate understanding of the
mechanisms causing change in performance.
Another interesting finding from these recent walking studies was that the lateral COP
shift did not increase medial gastrocnemius activity (Goryachev, Debbi, Haim, Rozen
et al., 2011; Goryachev, Debbi, Haim, & Wolf, 2011) suggesting this intervention was
beneficial to leg neuromuscular function. The unchanged heel-raise results for the
simulated medial asymmetry (lateral wedge) complement this EMG study.
Asymmetrical muscle contraction of gastrocnemius and soleus has also been shown to
influence abnormal loading of the Achilles tendon (Arndt, Brüggemann, Koebke, &
Segesser, 1999a, 1999b; Arndt, Komi, Brüggemann, & Lukkariniemi, 1998). The
functions of the muscles of the lower leg, especially tibialis posterior and flexor
hallucis maintain talocrural joint contact stress (Potthast, Brüggemann, Lundberg, &
Arndt, 2010). Where muscles have reduced force potentials such as might occur with
asymmetric footwear modelled in this study, joint contact stress will be reduced and
foot function impaired (Potthast, Brüggemann, Lundberg, & Arndt, 2010). Adverse
alterations to such kinaesthetic pathways would potentially also have effects on
postural stability as well as on functional performance and increased fatigue (Kerr et
al., 2009; Tropp, Askling et al., 1985; Wright et al., 2000). The potential changes to
the somatosensory system by the attached wedges are considered next.
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Total GRF (Fgb) passing
through fulcrum
xb
yb
Total muscle
force (Fmlb)
Calcaneus
Talus
stable
Talus
unstable
Medial malleolus with
deltoid ligament
provides bony stability
Tibia
b
xl
Total GRF (Fglb) medial to
fulcrum ankle/knee
b
yl
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Figure 4.13 Conceptual model of changes to GRF levers as a result of the medial wedge and the counter balancing effect of lateral ankle
muscle force (such as peronei and lateral gastrocnemius) to maintain equilibrium in single-leg stance.
Joint moments are the product of the total mediolateral GRF and the lever arm (perpendicular distance between the GRF line of action and joint
centre).
1 mm
Medial
wedge
simulating
lateral wear
Lever arms
unequal around
fulcrum
(xlb > ylb)
Joint moments in
equilibrium with
increased
asymmetric
muscular force
(Fglb.xlb =
Fmlb.ylb)
Posterior view of left heel barefoot (b), simulated lateral wear (lb) and assuming GRF is the same while xb and xlb
GRF lever arm changes and yb and ylb muscle lever arms remain constant
Lever arms equal
around fulcrum
(yb = xb) with
external inversion
= Fgb.xb
internal eversion
= Fmb.yb
Joint moments in
equilibrium
(Fgb.xb = Fmb.yb)
Total muscle force
(Fmb)
Fibula
4.4.5.2
Conceptual model of the somatosensory effect of the medial and
lateral wedges
Barefoot, footwear and sensorimotor influences have been discussed in Section 2.3.4.
Where sensory information is inhibited or changed in all or part of the foot, changes
in foot loading (Perry et al., 2000) and muscle activity of the leg occurs (Nurse et al.,
2005; Nurse & Nigg, 2001). An analogy would be a gymnast who lands on a balance
beam with the heel only partly supported either laterally or medially which results in
the termination or inhibition of the following skilled movement performance. The
application of the medial wedge simulating lateral wear may have thus changed the
contact pressures at the heel compared to the control barefoot conditions. The brief
exposure to contact pressure change suggests that the sensory foot and CNS rapidly
process very small alterations. In a similar way, immediate change to postural stability
has been measured by icing the foot (Perry, Santos, & Patla, 2001) or changing the
ground conditions (Perry et al., 2007; Vuillerme & Pinsault, 2007; Vuillerme,
Teasdale, & Nougier, 2001).
The increased medial pressure may signify increased inversion of the foot, possibly
resulting in a heel-raise motor pattern with greater lateral muscle activity. This results
in greater effort and poorer performance in heel-raise tasks. Mediolateral stability is
controlled centrally and requires somatosensory feedback. If that feedback is reduced,
control is impaired (Bauby & Kuo, 2000). It is hypothesised that these sensory
changes are magnified as the lateral (or medial) asymmetric wear increases. In this
study lateral asymmetry was measured in footwear from 1 to 8 mm and the effect on
the sensory heel-map may create conditions of sensory deprivation in one area of the
heel and increased pressure/excitability on the contralateral side. Conversely, the
lateral wedge may have increased pressure on the lateral aspect of the heel pad
normally experienced in gait and therefore motor patterns were unchanged. Lateral
asymmetry was measured in 57.8% of shoes so that it is possible individuals who
wore these shoes had pre-existing lateral sensory deprivation. So the lateral wedge
may have restored sensory information to levels experienced by individuals in neutral
footwear. Sensory change at the foot and in the brain was not measured in this study
so further study is required to confirm or refute possible links between asymmetry and
the effect on the somatosensory system. In order to further explore this hypothesis, the
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next study models incremental asymmetry and measures these effects on postural
stability.
4.4.6
The Tower Conceptual Model and Simulated Mediolateral
Asymmetry
The conceptual model (Section 3.3) was not directly measured in this study so this
discussion is purely speculative. The use of the medial wedge appeared to have
modelled lateral shoe asymmetry with the potential to perturb sensory input,
movement discrimination, biomechanical loading and performance, about the ankle
and foot. Such changes have been measured at other joints in the lower limb (Franz et
al., 2008; Mündermann et al., 2003; Schmalz, Blumentritt, Drewitz, & Freslier, 2006;
Shakoor, Lidtke et al., 2008; Yu et al., 2007). In terms of the human tower conceptual
model, 1 mm alterations at the foot would be amplified up the kinetic chain, changing
the length of moment arms around joints such as the knee, hip and spine.
Consequently, increased joint loading requires neuromuscular adaptations to maintain
equilibrium. This would involve more work and possibly earlier fatigue.
Small mediolateral changes in the centre of pressure of the vertical ground reaction
force can influence ankle and knee joint loading (Erhart et al., 2008; Haim et al.,
2008; Haim, Rozen, & Wolf, 2010; Jenkyn et al., 2011; Kakihana et al., 2007;
Kakihana, Akai et al., 2005; Nigg, Stergiou et al., 2003). These and other studies have
used large medial or lateral wedging (> 3 mm) producing variable not always
systematic changes. A common measure related to knee joint loading is the EKAM
which is very sensitive to small changes to the lever arm length (Haim et al., 2008;
Haim et al., 2011; Jenkyn et al., 2011; Shelburne et al., 2008). Elegant mathematical
modelling has shown that a 1 mm displacement of the centre of pressure would
change the peak EKAM by 2% and medial knee load by 1% (Shelburne et al., 2008).
This prediction was confirmed using a flat harder lateral heeled shoe in 32 participants
with medial knee osteoarthritis (Jenkyn et al., 2011). A shift of 0.06 cm in the COP
resulted in a significant decrease of 1.62% in the length of the frontal plane lever arm
and a 6.64% decrease in EKAM. This lateral intervention has the opposite effect to
the medial wedge condition in this study. Lateral or medial shoe wedging is known to
displace the COP (Jenkyn et al., 2011; Kakihana, Torii et al., 2005).
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Joint loading can also be influenced by other neuromuscular factors, such as wholebody movement (Erhart, Mündermann, Mündermann et al., 2008; Mündermann et al.,
2008) and the integrated coupling of muscles between the legs, pelvis and spine (van
Wingerden, Vleeming, Buyruk, & Raissadat, 2004; Vleeming, Pool-Goudzwaard,
Stoeckart, van Wingerden, & Snijders, 1995). The relevance of the research on knee
joint loading for this study is that very small changes to the mediolateral foot-ground
interface effect function up the kinetic chain. In this study heel-raise performance
decreased, when lateral heel wear was simulated using a 1 mm medial wedge. This in
effect created the biomechanical conditions detrimental to efficient neuromuscular
function at the ankle (Goryachev, Debbi, Haim, & Wolf, 2011; Kerr et al., 2009) and
knee (Erhart, Mündermann, Elspas et al., 2008; Erhart, Mündermann, Mündermann et
al., 2008; Jenkyn et al., 2011; Shelburne et al., 2008). In contrast, lateral interventions
are used to improve the biomechanical function of the knee (Haim et al., 2011;
Kerrigan et al., 2002; Shelburne et al., 2008).
Although wear or compression has also been observed at the medial heel, simulation
of this wear with the use of a 1 mm lateral heel wedge made no difference to the
performance compared to the barefoot (no wedge) state. It would appear that this
amount of lateral hindfoot perturbation was insufficient to disturb the normal force
closure mechanism at the talus, particularly where eversion is initiated at the onset of
the stance phase (Perry, 1983). In order to see such an effect from lateral positional
hindfoot perturbation it is likely that a wedge displacement of greater than 1 mm will
be necessary. Since 58% of shoes had lateral wear, it is possible that a lateral 1 mm
wedge may have had a beneficial effect. This might also explain the tendency for an
improved RHR performance for the lateral 1 mm wedge over the pre-wedge control.
The barefoot control performance of RHR was also better in participants whose shoe
condition was neutral compared to asymmetric.
Morey-Klapsing et al. (2005) investigated the kinematic and kinetic responses to
sudden medial and lateral tilts of the foot during single-leg standing. In contrast to
lateral tilts, no significant increase in EMG of lower leg muscles was found during
medial tilts. Morey-Klapsing et al. (2005) suggested that this may be due to greater
passive stability on the medial foot in comparison to the lateral foot. Increased
154
passive stability on the medial foot would necessitate less muscle activity contributing
towards stability of the segment. This result has also been confirmed using footwear
induced medial or lateral COP shifts on muscle activity of the leg (Goryachev, Debbi,
Haim, Rozen et al., 2011; Goryachev, Debbi, Haim, & Wolf, 2011). A lateral
perturbation decreased medial knee loading and lateral gastrocnemius activity. This
was considered an improved neuromuscular position. Conversely, the medial shift
increased lateral gastrocnemius activity by 41%. These findings could also help
explain the improved RHR performance seen with the use of lateral wedges in the
current study. Application of these wedges may have been sufficient to align the
ankle/foot complex towards a more stable everted position, thus improving the
efficiency of the movement. It also may explain the decreased performance when
using the medial wedge causing a lateral tilt which would then require more muscular
activity leading to fatigue. This increased muscular activity has been measured during
walking and running with inverted and molded medial orthotics with or without
posting (Mündermann et al., 2006; Murley & Bird, 2006b; Murley et al., 2009)
suggesting that the preferred movement pathway with least muscular activity was not
achieved (Mündermann et al., 2006; Nigg, 2001; Nigg, Stefanyshyn et al., 2003; Nigg
& Wakeling, 2001; Von Tscharner et al., 2003).
4.4.7
Methodological Considerations
This study was subject to several limitations. Firstly, the clinical task chosen is not
walking or running gait. The argument for the use of the heel-raise task was its
reliability and clinical validity, ease of use, a single-leg weight-bearing component
and it is a measure of neuromuscular function (Section 2.7.1). It was also hoped that it
could be used in future studies to help determine optimum footwear conditions. The
fact performance was affected with a 1 mm medial wedge suggests further research in
footwear is warranted.
Secondly, the participants were barefoot and hence un-blinded. This is justified
because footwear would have introduced more uncontrolled variables (Sections 2.3.3,
2.3.4 and 3.4), barefoot performance is an important issue (Sections 2.2.1, 2.2.2 and
2.3.1) and the aim was to disturb the mediolateral loading of the foot with a specific
magnitude uncontaminated by different footwear conditions. The researcher’s un155
blinded position was a pragmatic choice. Employing another researcher to assist with
blinding of the intervention was not possible within the parameters of this PhD study.
A single examiner has been shown to be reliable in counting the number of heel-raises
performed (Section 2.7.1) when compared to video analysis. The task performance
criteria were simplified to allow for reliable control by one examiner as compared to
some previous studies (Section 2.7.1).
Thirdly, the performances were not qualitatively assessed (Yocum et al., 2010).
Although interesting, assessment of participants’ perception of the task difficulty and
performance between interventions was not considered essential to the aim of the
study.
Fourthly, the habituation time for each condition was limited. This was limited by the
research time constraints necessary to encourage unpaid individuals to participate in
the study. Habituation to the condition is known to affect performance and this
limitation has been discussed in the literature review (Sections 2.2.2 and 2.3). This
again was a pragmatic choice. Participants were investigated only barefoot on their
preferred leg. Previous studies have shown that in healthy individuals performance is
similar on both legs so this decision was justified (Section 2.7.1). Time spent barefoot
was not assessed, an oversight, so this may be a non-habituated condition for most
participants. Habituation to barefoot and footwear is discussed more fully in Section
3.1.
Fifthly, subject-specific factors could affect performance of the heel-raise task
(Section 2.7.1). Age, BMI, gender, fitness and previous injuries could impact on heelraise performance so in order to exclude this possibility young healthy fit currently
uninjured participants were chosen. Despite this, only 13% of participants reported
never been previously injured and it is possible this and other factors, such as current
foot function, footwear condition, could affect performance (Sections 2.2.2 and 3.2).
Potential fixed effects of age, BMI and gender were also included in the statistical
model. Participants who continued beyond 30 s in the SHR task, reported foot
discomfort as a reason for stopping.
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The 1 mm perturbation and current footwear condition are further subject-specific
factors. Heel wedges of 1 mm were used to test the effect of hindfoot perturbations
based on anecdotal clinical observation. It is possible, considering the asymmetry of
footwear assessed, that a greater wedge thickness would have a more prominent
effect. For example, most footwear intervention studies use greater amounts of medial
or lateral wedging (Section 2.3.3). However, the use of 1 mm was carefully chosen to
represent the smallest measurable difference in mediolateral asymmetry and is
important when considering footwear degradation or optimisation. Other potential
effects on performance that were not accounted for include the current condition and
different types of footwear used by participants during daily functional activities and
how this may affect the barefoot state (Sections 2.2.2, 3.1, 3.2 and 3.4). Statistical
analysis of the effect of current footwear and barefoot performance was complicated
by the number, condition, age and frequency of use of the footwear. Analysis of the
relationship between shoe age and design, BMI, frequency and purpose of use and
progressive amount of asymmetry was not performed because of the limitations
associated with the retrospective nature of the self-reported data. Collapsing the data
to a single neutral or asymmetric value for each participant may not be an accurate
representation of the true state of their footwear and hence comparisons with their
barefoot performance may be imprecise. Ideally, performance testing needs to be
carried out in each participant’s footwear, which was logistically not possible in this
study. Alternately, a prospective study which supplies new footwear to all participants
and monitors frequency and purpose of use over a period of one to two years would
provide a more accurate picture of the progressive nature of asymmetry and possible
relationships between shoe age and design, BMI, frequency and purpose of use.
Difficulties with the shoe assessment protocol include measurement of the outer-sole
wear, mid- and inner-sole compression, and the effect of orthotics and posting
(Sections 2.6 and 3.4). Asymmetric outer sole wear is most difficult to measure where
there are no clear edges or interfaces between midsole and outer-sole such as in
canvas shoes. Placing the heels together and measuring the gap medially and laterally,
if it exists, between the two heels is possible. Measurement of compression with the
durometer is complicated or impossible where the surface area of the midsole is
uneven, smaller than the head of the durometer, covered by the outer sole or
composed of a grid with empty holes (Section 2.6). The properties of the inner-sole
157
and attached inner cushioning and heel inserts also need to be accounted for when
measuring compression and height. The asymmetric bias of the molded orthotics
cannot be measured easily, although the attached posting can be simply measured
with a Vernier calliper. In this study, the asymmetric effect of the orthotics was
excluded because of these difficulties.
The strengths of the study include firstly, the use of a rigorous cross-over design,
repeated measures, statistical model and exact procedure which provides appropriate
experimental control and reliability. Secondly, the choice of a functional dynamic
task, similar to the stance phase of gait, which can be performed anywhere without
expensive equipment (Section 2.7.1). This task is also clinically applicable as it
employs objective counted and timed measurement. Intra-subject repeated
neuromuscular performance comparisons are possible between limbs and footwear
conditions without excessive fatigue. Thirdly, the detailed footwear assessment
methodology and objective measurement of mediolateral asymmetry advances
knowledge and research into footwear degradation patterns (Sections 2.6 and 3.4).
The large number of shoes assessed representing a typical range of footwear worn by
exercising healthy participants in this age group, is a further strength.
4.4.8
Direction for Study 2
To address some of the methodological issues raised in the previous section
alternative experimental strategies were employed for Study 2. In order to extend the
hypothesis of increasing asymmetry and the effect on performance and postural
stability, the need for a range of wedging, simulating asymmetry, is evident. The
information gained from the assessment of footwear asymmetry suggests a range from
1 to 3 mm would be typical of laterally worn footwear. Although measured medial
asymmetry was only 1 mm in this study, it is possible that in a larger cohort a greater
range of medial asymmetry occurs.
The second aim is to include both new and used footwear within the experimental
protocol. The provision of new footwear and a prospective habituation period would
be ideal but as this study was unfunded the cost would have been prohibitive. Using
footwear in which asymmetric wear can be simulated would allow for blinding of the
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participant to the intervention. Increasing the range from 1 to 3 mm wedging and
including at least one pair of footwear increases the number of conditions. These
would include barefoot control, shoe control, shoe with medial or lateral simulated
wear. This might preclude the use of the heel-raise task to fatigue. An alternative task
and protocol is needed. Assessment and use of the participants’ most frequently used
shoe may only allow for a simpler statistical comparison between shoe asymmetry
and performance but would lose the depth of information gained from the assessment
of all personal footwear. Despite this reservation, this is the approach adopted for
Study 2.
Thirdly, including a larger cohort with a wider age range would be a more
representative sample of the general population, but the heel-raise task and the
number of conditions may not be manageable even for healthy fit individuals. An
alternative task and measure was considered for the expanded experiment.
Biomechanical instruments such as the force platform and associated computations
could be used to measure changes in performance and postural stability while
simulating small systematic changes in heel mediolateral asymmetry. This could also
improve measurement precision. Finally, to test the hypothesis that the longer the time
spent in asymmetric footwear the greater the negative effects on whole-body function,
then including a longer habituation period (hours or days) in each simulated condition
would be advantageous in the study design.
4.5
Conclusion
These findings demonstrate decreased barefoot performance of the single-leg heelraise task when applying a 1 mm medial heel wedge when compared to the control
barefoot and 1 mm lateral heel wedge conditions. The performance decreased 40.3%,
23.4% and 10.7% for SHR, MHR and RHR respectively when compared to the initial
barefoot control condition. The single-leg heel-raise task was thus sensitive to minor
perturbations at the hindfoot, and may be useful in the assessment of the effects of
shoe degradation on performance. In terms of footwear, lateral heel wear was the most
frequently measured asymmetry in this sample. These results are consistent with
either lateral heel wear or asymmetric lateral heel design contributing to decreased
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functional performance in single-leg weight-bearing activities. Shoe asymmetric
degradation can be either independently or a combination of outer-sole wear and
midsole compression. These two effects can amplify or attenuate the asymmetry. An
individual may have different asymmetric patterns of wear in personal footwear. The
decrease in neuromuscular performance with the medial wedge, simulating lateral
heel degradation, may be related to other research on aberrant ankle and knee joint
functioning.
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CHAPTER 5.
Study 2 Exploring Simulated Incremental Footwear
Mediolateral Asymmetry on Dynamic Postural Stability
5.1
Introduction
It was proposed in Chapter 3 that during single-leg stance the human body be
considered a dynamic tower with the foot and shoe forming the foundation (Section
3.3). Should this foundation be perpendicular to the ground, little muscular work is
required to maintain upright posture. However, tilting the tower in any direction at the
foot-ground interface will theoretically require more work to maintain postural
homeostasis and thus disturb postural stability. It is theorised that mediolateral
footwear asymmetry disturbs the foot-ground perpendicular interface and increases
stress elsewhere in the human tower. As described in Section 2.3, heeled neutral
footwear affects both the anterioposterior and mediolateral interfaces (Snow &
Williams, 1994). Footwear studies have measured adverse changes throughout this
kinetic chain (Barton, Coyle et al., 2009; Gefen et al., 2002; Kerrigan et al., 1998;
Reinschmidt & Nigg, 1995; Shakoor & Block, 2006; Shakoor et al., 2010).
Study 1 demonstrated that the application of a 1 mm medial heel wedge, modelling
lateral heel wear, in the barefoot condition decreased performance. MHR and RHR
were 23.4% and 10.7% lower compared to the control condition. This wedge
condition was consistent with the lateral heel wear most commonly seen in the shoes
worn by these participants. These results helped formulate, extend and refine the
experimental design for Study 2. The simulated range of mediolateral asymmetry was
chosen as typical of footwear measured with lateral wear in Study 1. Participants used
their own well habituated footwear thus creating normal real-life conditions. A further
advantage was that it facilitated blinding of the participant to the intervention.
Problems with asymmetric wear already present in the footwear were thus factored
into the analysis. Footwear asymmetry assessment is required not only to determine
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typical degradation patterns but also to calculate the combined effect of simulated and
primary asymmetry.
Study 2 includes a larger more representative sample of the general healthy fit
population, thus the task difficulty needed to accommodate this age range, abilities
and possible fatigue, while still being dynamic enough to challenge postural stability.
Reviewed research (Sections 2.7.2 and 2.7.3) helped determine the inclusion criteria
of activity level, age, injury status. The transition from double- to single-leg stance
(Emery, 2003; Jonsson et al., 2004; Rogers & Pai, 1990, 1993) was selected for this
study as it was considered that a large range of participants would be able to complete
it without failed trials (Section 2.7.2). Finally, to address the limited habituation time
in each simulated condition, an extended walk was included as part of the
experimental design. This represented a typical real-life condition for the participants
thus strengthening the ecological validity.
Footwear, offloading and stability in the diabetic patient has been reviewed (van
Deursen, 2008). Walking in asymmetrical footwear caused by degradation and soft
inserts are considered factors leading to poor balance (van Deursen, 2008). Postural
stability is affected when comparing very different foot-ground interfaces (Nigg,
Hintzen et al., 2006; Robbins et al., 1998). This study seeks to evaluate extremely
small differences between mediolateral asymmetric foot-ground conditions which
have not previously been researched. The rationale for measuring postural stability is
the fine control of mediolateral stability maintained by the foot and ankle evertors and
invertors (Bauby & Kuo, 2000; Gefen et al., 2002; Wright et al., 2000). To maintain
stability against an asymmetric intervention increased muscle activity by these
opposing muscle groups must occur (Goryachev, Debbi, Haim, & Wolf, 2011;
Shelburne et al., 2006). This shifts the COP medially or laterally while the COM
moves in the contralateral direction (Bauby & Kuo, 2000; Erhart, Mündermann,
Mündermann et al., 2008; Haim et al., 2008; Jenkyn et al., 2011; Rodgers, 1995;
Shelburne et al., 2008; Winter, 1995).
In order to compare postural stability between conditions, force platform derived
measures from GRF and COP have been used (Section 2.7.3). During single-leg
stance the body oscillates over its base of support and the magnitude and extent of this
162
movement is used to infer the quality of stability. The variation in force measures in
single-leg stance has been shown to be reliable and is a good predictor of postural
stability, but the axis depends upon the clinical condition being studied (Goldie et al.,
1989; Goldie et al., 1994; Wikstrom, Tillman, Schenker, & Borsa, 2008b). The
dynamic transition task chosen in this study, together with the simulated medial and
lateral heel asymmetry, was expected to influence mediolateral more than
anterioposterior GRF and COP measures. Analysis in this exploratory study has
included a range of dynamic measures and directions considered relevant to the small
asymmetric perturbation. The choice of these specific measures is justified by a
review of their reliability and validity (Section 2.7.2).
The aims of this study were to investigate:
• the prevalence of mediolateral heel asymmetry in a further sample of used
footwear;
• pre-existing footwear asymmetry on barefoot and footwear postural stability
performance;
• simulated incremental variations in mediolateral hindfoot positional asymmetry,
modelling typical wear patterns, on dynamic postural stability;
• the effect of a 20 min walk habituation period to the simulated asymmetry on
dynamic postural stability.
The following hypotheses were formulated for investigation:
H1: There will be a greater frequency of lateral than medial shoe heel asymmetry.
H2: Postural stability performance of individuals will be impaired in footwear
compared to barefoot.
H3: Postural stability performance will be impaired in individuals whose footwear
has mediolateral heel asymmetry compared to those whose footwear is neutral.
H4: Medial and lateral hindfoot positional perturbations will decrease postural
stability performance compared to the neutral state.
H5: Progressively increasing the medial and lateral asymmetry will increase the
performance impairment of the dynamic postural task compared to the neutral
state.
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H6: Increasing the length of time spent in simulated asymmetry will further impair
postural stability performance compared to the neutral state.
5.2
Methodology
5.2.1
Participants
The University of Otago Human Ethics Committee (Reference no. 07/053 dated 26th
March 2007) granted approval for this study (Appendix 2). A sample size calculation
was performed to determine the number of participants necessary to detect a small
change in the dependent variables. The variables of interest were the SDFx, SDFy,
mean COP velocity, maximum displacement of COP and time to stabilization of Fx
and Fy (TTSFx and TTSFy). The differences between interventions or healthy and
injured participants affects the size of the change expected (Sections 2.3.3, 2.3.4 and
2.7.3). Previous studies reported differences for mediolateral force variability (SDFy)
between young and old participants as significant for 0.3/0.5 % body weight (Jonsson
et al., 2004), between stable and ankle injured 0.39/0.54% body weight (Ross,
Guskiewicz, Gross, & Yu, 2009) mean velocity barefoot on very different surfaces
(2.27, 4.65, 6.22 and 8.78 cm.s¯¹) (Robbins & Waked, 1997) and barefoot, hard thin,
soft thin, hard thick, soft thick interfaces as 1.5, 1.5, 6, 2.5, 8.5 cm.s¯¹ respectively
(Robbins, Waked, & Krouglicof, 1998) and TTS values of 0.5 s between ankle injured
and healthy participants (Wikstrom, Tillman, & Borsa, 2005). Since the magnitude of
intervention changes in this study was very small, the expected change in each
variable (an increase or decrease) was likely also to be small. For example in Robbins
et al. (1998) barefoot and the hard thin interface gave similar results. Small effects
were expected due to the 1 mm increments in shoe-wedge conditions. A total sample
size of 101 (rounded up to 105) was considered sufficient to have 80% power to
detect an effect size of 0.2 using an alpha level equal to 0.05, when controlling for the
neutral performance score, assuming correlations of 0.7 between scores.
Volunteers were recruited from university students, staff and from the general
population by advertisements in a local newspaper, posters on University of Otago
billboards, access to approved e-mail lists and a presentation to physiotherapy
164
students during lectures. Inclusion criteria were developed from the reviewed
literature (Sections 2.4, 2.7.2 and 2.7.3). Men and women, aged 18 to 60 years, in
good general health, who were able to maintain balance independently whilst standing
on one leg for 20 s, were included. A wide age range was chosen so results could be
generalizable. Age over 60 years is a factor in postural stability performance and
hence formed part of the exclusion criteria (Maki, Edmondstone, & McIlroy, 2000;
Maki et al., 1990; Prieto et al., 1996).Volunteers were excluded if they reported an
orthopaedic condition of the back and lower limb that required medical treatment
within the last month or any neurological condition including head injury and
concussion within the last 6 months which could impact on single-leg balance (Goldie
et al., 1994; Goldie et al., 1990).
5.2.2
The Dynamic Balance Task: Transition from Double- to SingleLeg Stance
Participants stood with one foot on each of the force platforms (Figure 5.1). They
assumed their comfortable natural stance position with weight equally distributed
between the force platforms and the position of their feet was outlined in chalk for
consistent placement between trials and conditions (Hanke & Rogers, 1992; Jonsson
et al., 2004). The participants’ preferred stance leg, chosen based on the feeling of
best balance, was always placed on the same force platform. The participants were
instructed to hang their arms loosely relaxed at their sides with their head positioned
in neutral and eyes focused on the light source in front of them. Compensatory arm
movements were accepted during the dynamic transition to single-leg stance (Gerbino
et al., 2007; Jonsson et al., 2004). Participants were instructed to “stand as still as
possible” for the first 5 s of the 20 s trial. Upon seeing the visual light cue the
participants were asked to lift their non-preferred leg off the ground “as fast as
possible” until approximately 90° hip flexion. They then had to maintain balance in
single-leg stance on the preferred leg for the remaining portion the 20 s trial time. The
speed the movement was performed is important as faster hip flexion has greater
reliability for unloading the flexing limb (Hanke & Rogers, 1992). Sufficient practice
trials were given at the beginning of the session until the participant felt comfortable
with the pace and procedure.
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Figure 5.1 Laboratory set-up and starting position
For the start of each experimental trial the participant was given an auditory “ready”
cue. A computer-generated beep confirmed data recording had commenced. The
transition to single-leg stance was initiated by a manually activated visual cue. This
light was randomly activated between 5 and 7 s and provided the only source of
unpredictability in the test procedure. Data were captured for the entire 20 s trial
which ended with a computer generated beep. A 20 s rest between trials was given.
The participant walked around the laboratory and returned to the same starting
position for the next trial. Approximately 3 min was allocated between each footwear
condition. The participant was able to walk without shoes, replace them, and then
habituate to the new blinded randomised simulated asymmetric shoe condition.
5.2.3
Experimental Design
The experimental design was a repeated measures single test session (Figure 5.2). The
independent variables were the footwear conditions (barefoot, shoe, shoe with 1, 2, 3
mm medial or lateral wedging), and the dependent variables were GRF and COP force
plate measures. Although no changes were measured for the 1 mm lateral wedge
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condition in Study 1, a comprehensive range of asymmetry in both mediolateral
directions was thought likely to disturb postural stability and is typically found in
footwear (Sections 2.6, 3.4 and 4.3.7.6). The first non-randomised condition was
always the barefoot control condition so that the participants did not have to remove
their socks again for the following seven blinded randomised footwear conditions.
This included shoe only and the insertion of different thickness hindfoot wedges taped
medially or laterally under the shoe insole of both left and right shoes (Figure 5.3). All
106 participants were tested in all conditions pre-20 min walk. Depending on
assessment of wear, the placement of medial and lateral wedges could simulate,
accentuate, or attenuate asymmetric heel wear. The order of the shoe conditions
presented to each participant was randomised using a random number generator
(Microsoft Excel).
Fiure 5.2 Repeated measures experimental design.
Previous research (Section 2.7.2) helped identify and choose the trial length and
number of repetitions (Pinsault & Vuillerme, 2009; Riemann, Myers, Stone, &
Lephart, 2004; Ross & Guskiewicz, 2004; Ross et al., 2009). Three trials of
unperturbed stance are reported to have excellent test-retest reliability for COP
parameters (Pinsault & Vuillerme, 2009). Dynamic single-leg tasks generally require
more trials and decreased duration of trials because of their difficulty and
unpredictability (Goldie et al., 1992; Riemann, Guskiewicz, & Shields, 1999;
167
Riemann et al., 2004). Hanke and Rogers (1992) used four trials of 6 s for 18
participants in the same dynamic transition task used in the current study. In a more
difficult hop task three to seven trials of 20 s have been used (Ross & Guskiewicz,
2004; Ross et al., 2009). Therefore in the present study three 20 s trials was
considered sufficient based on the number of participants, the nature of the dynamic
transition task, the time required for multiple testing and the number of conditions.
To determine the effects of a longer habituation period on balance, participants
completed a 20 min brisk treadmill walk at a self-selected pace following the last
footwear condition (Figure 5.1). A further three trials of the final footwear condition
(9th condition) followed immediately post walk. The treadmill was located in the
adjacent laboratory within 10 m of the force platforms. In order to ensure the same
number of the seven different shoe conditions were used for the habituation walk, the
total of each of these conditions were updated after each test day. Where shoe
condition totals were unequal, the next sequence of random numbers, with the
required last number, was selected. As a result each condition was tested with 15
participants.
5.2.4
Blinding of the Simulated Shoe Wear Conditions
The blinding of the simulated asymmetric shoe conditions is important. It increases
internal validity and decreases participant bias thus improving the experimental
design and significance of the outcomes. Following the three barefoot trials, the
participant walked around the laboratory while the randomised shoe condition was
prepared by the primary investigator out of the sight of the participant. The 1, 2 and 3
mm wedges were placed medially or laterally underneath each shoe insole making it
impossible to see where they were placed or their relative thickness (Figure 5.3).
Once the footwear condition was prepared the participant was asked to put on their
shoes. The participant then walked around the laboratory for two minutes to embed
the new footwear condition before the trials commenced. At the conclusion of the
three trials the shoes were immediately removed and the participant walked around
the room in socks while the procedure was repeated for the next randomised
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condition. The same procedure was adopted for the shoe only condition, but in this
case no wedges were inserted into the shoe.
Figure 5.3 Medial wedge placed underneath inner-sole simulating lateral wear.
5.2.5
Wedge Design and Specifications
In order to model a range of footwear heel asymmetry, wedge pairs of 1.10 (95% CI
1.08 to 1.12), 2.07 (95% CI 2.04 to 2.10) and 3.03 (95% CI 2.99 to 3.07) mm were
produced (Figure 5.4), in lengths ranging from 4.5 to 7.0 cm (Figure 5.3 E). Wedge
design allows placement either medially or laterally at the heel (Figure 5.3 D).
Detailed wedge design, specifications and verification of thickness is described
previously (Sections 3.4 and 4.2.4).
A
B
D
C
E
Figure 5.4 Wedges used to simulate increasing heel asymmetry.
169
5.2.6
Instrumentation
Two force platforms (BP2436 and OR6-5, Advanced Medical Technologies IncTM,
USA) embedded within a recessed floor cavity, sampling at 200 Hz, were used to
register vertical (Fz) and horizontal (Fx and Fy) GRF. The force platforms were
calibrated individually for each day of testing using the EVaRTTM 4.0 Motion Camera
system (Motion Analysis Corporation, CA, USA) and known weights. Signals,
representing changes to horizontal and vertical GRF, were forwarded to an analogueto-digital convertor (National Instruments, USA) and processed in a personal
computer using the EVaRTTM 4.0 software. The laboratory set-up is shown in Figure
5.1.
The visual environment has been shown to affect postural control (Lord & Menz,
2000; Nougier et al., 1998; Schmid, Casabianca, Bottaro, & Schieppati, 2008) and
hence for the performance of the task to be reliable the environment needs to be
controlled and standardized. A light source that was used as a visual cue to initiate the
movement was placed at shoulder height 3 m in front of the participant. This allowed
participants to focus on the light source. It was manually operated (off/on & left/right)
and the signal was synchronised with the force platforms and recorded and stored
separately in the EVaRTTM 4.0 software program. The treadmill (Quinton Instrument
Company, Medtrack ST65, Ultracare Pty Ltd) used for the 20-minute habituation
walk was placed in the adjacent laboratory which was 10m away from the force
platforms.
5.2.7
Procedures
The procedure from the arrival into the laboratory is outlined in Figure 5.5
5.2.7.1
Informed consent, screening and familiarisation
Potential participants were informed of the procedures involved and those who met
the inclusion criteria gave their informed written consent to participate (Appendix 2)
prior to beginning the testing session. The screening and testing lasted for
approximately 1 hour and was performed in the Biomechanics Laboratory in the
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Centre for Physiotherapy Research at the University of Otago. Participants completed
a brief screening questionnaire about their current exercise and previous injuries
(Appendix 2). Height and weight were measured and participants chose their
preferred stance leg based on a subjective feeling of more comfortable balance while
practicing the transition from double-leg to single-leg stance (Jonsson et al., 2004).
Participants were made familiar with the laboratory set-up.
5.2.7.2
The habituation 20 min walk
The purpose of this 20 min neutral gradient treadmill walk was to investigate the
effect of an extended habituation period in the last of the seven simulated shoe wear
conditions. Following the completion of the three trials for each of the barefoot and
the seven in-shoe simulated wear conditions (total 8 conditions), participants walked
in their last footwear condition, at a self-selected brisk pace (Figure 5.5). Immediately
upon completion of the walk, participants performed the task as described previously.
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Arrive in
laboratory
Complete
Ethics and
personal
questionnaire
Barefoot control
condition 1
“Ready” and Beep
Double-leg
stance 5 to 7 s
Trial 1
Trial 2
Next Trial
Height and
weight
measured
barefoot
Comfortable double-leg
stance on two force
platforms, outline feet
position in chalk
Stance leg positioned
on same force
platform for all
participants
Practice Dynamic
Transition Task and
choose stance leg based
on best balance
Light cue
@ 5+ s
Transition “as fast
as possible”
Single-leg
stance 10+ s
Trial 3
Walk around
laboratory 20 s
Remove footwear.
Walk 1 min barefoot.
Remove/Insert blinded
randomised wedge
condition into footwear.
Replace footwear.
Walk in new footwear
condition 2 min.
Completed 3
Trials
Trial 2
Condition 9
Post Walk
Three Trials
Walk briskly on
treadmill in footwear
for 20 min.
Completed all 8
conditions
Keep footwear
on with last
condition
Footwear
Assessment
Remove footwear.
Remove wedge if in
footwear.
Answer questions
regarding footwear.
Completed all 9
conditions
Figure 5.5 The procedure followed by each participant for the dynamic task.
172
5.2.8
Footwear Assessment
Participants were asked to bring their most frequently used day-to-day or sport shoe in
which they would feel comfortable for the dynamic balance testing and walking.
Footwear assessment as detailed in Section 4.2.7 was performed by the primary
investigator at the completion of the dynamic balance task and participants were
asked questions regarding the age and use of their footwear.
5.2.8.1
Footwear was classified into six categories according to design, type and use (Section
4.2.7.1). Sports shoes were differentiated based on neutral or asymmetric design
features such as dual density midsoles (Reinschmidt & Nigg, 2000; Richards et al.,
2009). Shoe age (months) and frequency of use (hours per week) was assessed based
on self-reported recall by the participants (Barton, Bonanno et al., 2009; Noakes,
2003).
5.2.8.2
Actual heel height
The thickness of the heel and forefoot was measured using a Vernier calliper
(accuracy 0.01 mm) and heel height was calculated as the difference in thickness
between the heel and the forefoot (Barton, Bonanno et al., 2009; Menz & Sherrington,
2000).
5.2.8.3
Outer sole wear
Medial and lateral outer sole wear at the heel and forefoot was measured (mm) with a
Vernier calliper and the difference between medial and lateral was calculated. In
footwear with wrap-around outer-soles (in some canvas shoes), the left and right heels
were placed together and any asymmetric wear between the heels was measured. The
results are reported in mm as neutral (no wear or equal wear), medial (wear medially
> laterally) or lateral (wear laterally > medially).
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5.2.8.4
Midsole compression
Midsole hardness testing medially and laterally at the heel and forefoot was
performed using an Asker C Durometer. In footwear with wrap-around outer soles (in
some canvas shoes) or without midsoles (rubber grid design), Durometer readings
reflect the outer sole hardness only. The difference greater than or equal to 10 Asker
C units between medial and lateral midsole compression is reported as softer on the
medial or lateral heel respectively. A difference from 10 to less than 20 units was
comparable to a 1 mm difference using the thumb compression test (medium hardness
0.5 to 1.5 mm), while 20 units or more was equated to the soft category (>1.5 mm)
and assigned a 2 mm difference (see Section 4.2.7.5).
5.2.8.5
Inserts and or orthotics
The presence of an orthotic or insert within the shoe was noted as was detail with
regard to any added medial or lateral posting at the heel or forefoot which could
influence shoe symmetry. This posting was measured with a Vernier calliper and
included in the total asymmetric rating of the footwear. Determining the medial or
lateral bias of the molded orthotic without posting was beyond the scope of this study
and hence was not factored into the overall shoe asymmetry rating.
5.2.8.6
Asymmetry is reported in mm either medially or laterally and is the combined total of
outer sole wear and midsole compression for each shoe assessed. Frequency of
asymmetry between left and right shoes was also noted.
5.2.9
Data Processing
Force platform data from each trial were exported from the EVaRTTM 4.0 program
into an Excel spreadsheet with GRF forces (N) and COP (mm) recorded from both
force platforms together with the synchronised light signal (off/on) data and combined
on the same spreadsheet. Data from the single-leg stance force platform were then
processed. All data were filtered using a fourth-order Butterworth filter with a cut-off
174
frequency of 10 Hz and were separated into discrete time and position phases. These
included double-leg stance (5 s), transition (0.4 to 1.5 s), and single-leg stance
(remains of the 20 s total time period). Single-leg stance was further divided into two
blocks of 5 s (Figure 5.6). The transition phase data were analysed from the light
signal onset to the point when zero forces (vertical GRF Fz = 0) were recorded on the
second force platform which is the point when the foot lifted off the ground. In singleleg stance data was analysed over the total time (10 to 15 s), first 5 s and the next 5 s,
as a previous study has showed differences during the first and last 5 s of single-leg
stance (Jonsson et al., 2004). The first 5 s after the contra-lateral leg has lifted off the
ground is considered a dynamic phase as there is a rapid decrease in force variability.
This is followed by a static phase (next 5 s) where force variability is more or less
constant (Jonsson et al., 2004).
The following static and dynamic force platform measures were calculated to evaluate
postural stability barefoot and in the simulated asymmetric shoe wear conditions
(Section 2.7.3). These were chosen based on the exploratory nature of the study, the
task, the small 1 mm incremental mediolateral perturbations and previous research in
selected force platform measures relating to changes to postural control (Geurts et al.,
1993; Goldie et al., 1989; McKeon & Hertel, 2008a; Prieto et al., 1996; Ross et al.,
2009).
•
The standard deviation (SD), also called the root mean square, of the GRF in the
anterioposterior (SDFx) and mediolateral (SDFy) directions.
•
The maximum displacement (Maxdis) is the maximum two-dimensional vector
or resultant distance in mm from the mean COP to the furthest point.
•
The mean velocity, which is the total length of the COP path divided by the time
taken to cover the distance (mms-1), calculated for the overall (Mvelo),
anterioposterior (Mvelox) and mediolateral (Mveloy) directions.
•
The time to stabilisation for the anterioposterior (TTSFx) and mediolateral
(TTSFy) GRF was calculated (seconds) over the total time of the single-leg
phase following the dynamic transition. The series was considered stable when
the sequential or cumulative average remained within a ¼ SD of the overall
series mean (Colby, Hintermeister, Torry, & Steadman, 1999).
175
Figure 5.6 Filtered raw data for the synchronised light signal, ground reaction
forces (N) and centre of pressure (mm) in the anterioposterior (Fx, COPx) and
mediolateral (Fy, COPy) directions for one subject.
For analysis data was divided into three phases: bilateral stance (B, 5 s), transition (T,
0.4 to 1.5 s) and single-leg stance (S, 10 to 15 s). The transition phase started with the
onset of the light signal and ended when zero forces were recorded by the second
force platform (Fz, opposite leg) as the foot left the platform. TTSFx and TTSFy were
calculated over the total time S.
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The SD of the anterioposterior and mediolateral GRFs is a measure of force
variability. Increased variability is thought to measure decreased postural stability,
although the nature and pattern of the variability may be interpreted differently
(Davids et al., 2003; van Emmerik & van Wegen, 2002). As discussed in section
2.7.3, this force measure is considered to be the most sensitive and reliable but the
nature of the intervention and the task will provoke changes to either the
anterioposterior or mediolateral directions (Goldie et al., 1989; Goldie et al., 1992,
1994; Wikstrom et al., 2008b). In this study the hip-flexion task involves mediolateral
movement of the centre of mass and the asymmetric interventions would also more
likely affect the mediolateral force variability.
The maximum displacement of the COP represents a global measure of impaired
postural performance and has been associated with risk of falling (Prieto et al., 1996)
and has been used extensively (Pinsault & Vuillerme, 2009; Vuillerme, Teasdale et
al., 2001). An increase in this value is thought to indicate impaired postural stability
(Vaillant et al., 2009; Vuillerme, Danion et al., 2001). However, it is influenced by
single large fluctuations and subsequently new analytical methods have evolved
involving centre of mass (Perry et al., 2007) and time to boundary projections (Pope
et al., 2011).
Mean velocity has also been used by many researchers and is thought to indicate the
amount of muscle activity required to maintain stability (Geurts, Nienhuis, & Mulder,
1993; Luoto et al., 1998; Prieto et al., 1996; Robbins & Waked, 1997; Ross et al.,
2009). It is considered reliable and sensitive to detect small differences in changes in
postural stability (Pinsault & Vuillerme, 2009; Prieto et al., 1996). Increased values
would indicate impaired postural stability.
The time to stabilisation has been used to determine how quickly GRF or COP
variability returns to normal values following a dynamic movement such as a step or
hop (Colby et al., 1999; Ross et al., 2009; Wikstrom, Tillman, & Borsa, 2005). These
are sensitive and reliable for evaluating dynamic balance deficits (Colby et al., 1999;
Ross & Guskiewicz, 2004; Ross et al., 2009; Wikstrom, Tillman, & Borsa, 2005).
This method has not been previously used for the hip-flexion task. Although dynamic
it may not sufficiently disturb balance control to register significant changes between
177
conditions. Increased time to stabilisation would indicate poorer postural control
(Wikstrom, Tillman, & Borsa, 2005). The entire single leg stance time period marked
S in Figure 5.6 was used in the calculations.
5.2.10 Statistical Analysis
The StataTM 10.1 (Stata Corp, Texas, USA) statistical software package was used for
all analysis. Age, height, weight, BMI, reported footwear age, frequency of use and
hours spent exercising are presented as descriptive statistics (mean ± SD). Previous
injuries, footwear type and asymmetry of wear and/or compression are reported as
relative frequencies. All data were examined for normality at each level of analysis
and were log-transformed to resolve heteroscedasticity and skew in the model
residuals (Altman, 1991). Figure 5.7 illustrates how the data was graphically assessed
for each dependent variable and phase pre- and post-log transformation. The example
shows plots of the data for residuals (histograms and scatter), age (scatter) and gender
(box) of SDFx during double-leg stance. No data was excluded from each of the three
trials.
A general linear mixed model using both fixed and random effects was used to test for
trial (learning/performance/fatigue/order), condition (barefoot, shoe, shoe with
wedging, corrected shoe wear and wedge), shoe and demographic effects (Brown &
Prescott, 2006; Hopkins, 2003). These analyses were performed for each phase (five
in total) for each dependent variable (eight) and each hypothesis (40 barefoot versus
shoe (H2); 80 barefoot/shoe versus shoe condition (H3); 480 shoe versus simulated
asymmetry (H4) and incremental shoe asymmetry (H5); 280 walk habituation (H6))
giving a total of 880.
178
.4
.5
.8
Density
.3
.6
.2
Density
.4
.1
.2
0
0
-5
0
5
10
-4
-2
0
Standardized residuals
-.5
0
Fitted values: xb + Zu
2
4
-4
-5
-2
0
0
5
2
4
10
.5
1
1.5
Fitted values: xb + Zu
2
2.5
-1
lowess residuals pred
.5
1
lowess lnresiduals lnpred
-4
-5
-2
0
0
5
2
4
10
20
30
40
Age
50
60
20
lowess residuals age
30
40
Age
50
60
lowess lnresiduals age
-4
-5
-2
0
2
0
5
4
10
1
2
1
2
Figure 5.7 A graphical illustration of SDFx non-transformed residuals, age and
gender (left) with log-transformed data (right) during double-leg stance.
179
Figure 5.8 summarizes the overall structure of the analysis for each phase of the
dynamic task, the dependent variables used as markers of postural stability, the
independent conditions compared and the hypotheses being tested. The independent
variables (conditions) were compared with one another and shoe condition (intrinsic
and simulated).
Phases of Dynamic Task Analysed
Bilateral
Stance
(5 s)
Dependent
Variables
SDFx
Barefoot
Mveloy
First
5s
Second
5s
H3
Shoe + simulated
asymmetry
Shoe
H2
Maxdis
Mvelox
Single-leg Stance
(Total time = 10 to
15 s and also
divided into two
time windows)
Independent Variables (Conditions)
SDFy
Mvelo
Transition
(0.4 to 1.5 s)
H3
H4
H5
Shoe
condition
(neutral,
medial and
lateral
asymmetry)
TTSFx
TTSFy
Medial or lateral
asymmetry
(1, 2 and 3 mm)
H6
Walk 20 minutes
Figure 5.8 The dependent and independent variables analysed for each phase
and the hypotheses (H2 to H6) linked to the analysis.
A separate analysis compared the effect of the shoe asymmetric conditions pre- and
post-walk. The differences between experimental conditions are ratios of geometric
means and are reported as percentage differences. Statistical significance was
determined by two-sided P-values less than .05.
180
5.2.10.1 Barefoot versus shoe conditions
The barefoot condition always preceded the shoe condition so order was not included
in this model. The first model did not take into account the shoe asymmetric rating in
terms of wear and its possible effect on barefoot or shoe performance. Age, BMI and
gender were controlled for in this model. Explanatory text of the Stata command
structure is shown in Table 5.1.
Table 5.1
The Stata Command Structure Used During the Analysis of Barefoot and Shoe
Conditions
xi: xtmixed lnvariable age i.gen bmi i.con || sub: || con:
xi: xtmixed
lnvariable
age i.gen bmi i.con
|| sub: || con:
The linear mixed
model
The log
transformed
dependent variable
such as SDFx
during a particular
phase of the
dynamic task
Controlling for
fixed effects of age,
gender, BMI and
barefoot and shoe
condition
Random effects of
106 subjects and
conditions barefoot
and shoe
The second level of analysis asked the question if performance differed while barefoot
or in shoes, if shoes were either neutral or asymmetric? A second general linear mixed
model using both fixed and random effects was used to test for a fixed condition
effect (neutral or asymmetric footwear) on barefoot and in shoe postural stability
performance, while still controlling for age, gender and BMI. Essentially, the
participants’ shoe asymmetric rating was compared to the performance barefoot and
in a separate analysis, in shoes (Figure 5.8). In this case shoe rating was graded as
either neutral or asymmetrically worn in order to ensure sufficient numbers in each
category.
181
5.2.10.2 Shoe and wedge conditions
This general linear mixed model analysis was performed at three levels. The first
excluded the order of presentation of the seven shoe/wedge conditions. If the overall
condition effect was statistically significant using the Wald test, which adjusts for
multiple comparisons, further exploration of the contrasts comparing wedge
conditions was carried out. If not significant, no further exploration was justified. As
before, age, BMI and gender were controlled for in this model.
To assess the effect of order (learning/fatigue), least-squares smoothing was
performed on all dependent variables in each phase. This carries out a locally
weighted regression of the dependent variable on the 7 shoe conditions. Based on
these findings a second level of analysis controlled for order as another fixed effect.
Depending on the assessment of wear, the placement of medial and lateral wedges
could simulate, accentuate or attenuate asymmetric heel wear. As a result, the third
level of analysis combined wedge condition with shoe asymmetry (Figure 5.8) to
produce 13 corrected wedge-shoe conditions. These conditions included medial from
1 to 8 mm, neutral and lateral from 1 to 4 mm. As totals within each group were now
different, the corrected wedge-shoe conditions were grouped to produce eight similarsized groups (medial from 1 to 4 mm, neutral and lateral from 1 to 3 mm). After
adjusting for multiple comparisons, further exploration was performed only on
dependent variables that approached statistical significance of .05.
5.2.10.3 Pre- and post-habituation walk
A general linear mixed model using both fixed and random effects was used to test for
trial (learning/performance/fatigue/order pre- versus post-habituation), condition
(shoe, shoe with wedging, corrected shoe wear and wedge) and demographic effects.
There are two levels of clustering in this case: within subject (as many levels as
participants) and then within order (two levels within each participant). This analysis
was carried out at three levels in order to answer the following question: what is the
effect of the 20 min walk on each of the wedge conditions? Testing for a condition
182
effect would ask whether there was evidence for different scores for at least some of
the seven conditions when controlling for age, BMI, gender and habituation
(effectively the order effect).
The second model analysed whether conditions habituated differently, using a
condition-order interaction. If the interaction was not significant, then it was
concluded that there was no evidence that habituation affected the conditions
differently, and thus only the main effects (the first model) were relevant. With the
interaction, the habituation effect is allowed to vary for different conditions; without
the interaction, there is only one habituation effect that is shared by all conditions. If
the condition-order interaction approached significance set at P < .05 level, then the
effect of habituation on each wedge condition was analysed separately.
Depending on the assessment of wear, the placement of medial and lateral wedges
could simulate, accentuate or attenuate asymmetric heel wear. As a result, the third
level of analysis combined wedge condition with intrinsic shoe asymmetry.
Combining shoe asymmetry and wedge condition produced eleven conditions from 1
to 8 mm medial, neutral and 1 to 3 mm lateral. However, the frequency of trials in
each of these conditions was now skewed so further refinement to balance the number
of trials in each condition was necessary. The first method of grouping produced
seven corrected conditions (medial from 1 to 4 mm, neutral and lateral from 1 to 2
mm). The second method of grouping produced four corrected conditions. Further
analysis of each wedge condition was performed only where the condition-order
interactions approached significance as previously described.
5.3
Results
General participant demographics, sports participation and previous injuries are
followed by the results from the footwear assessment of 212 shoes. Intrinsic footwear
asymmetry combined with the experimental simulation is an integral part of the
overall data analysis. Hence, results on footwear assessment are presented before the
experimental postural stability data. The comparison of postural stability performance
183
barefoot to the shoe condition is then reported. In conjunction with these are results
for the effect of intrinsic mediolateral footwear asymmetry on barefoot and shoe
conditions postural stability performance. The results from the incremental simulated
asymmetry on postural stability follow, including a sub-section on the combined
effect of simulated plus intrinsic shoe asymmetry. Finally, the effect on postural
stability of the 20 min walk and incremental mediolateral asymmetry is presented. A
summary of the significant findings concludes this section.
5.3.1
Participant Demographics
Sixty women and 46 men with an age range of 18 to 60 years volunteered for the
study and fulfilled the inclusion criteria (Table 5.2). The left leg was favoured by 30%
women and 32.6% men.
Table 5.2
Demographics of Participants (mean ± SD, range)
Variable
Age (years)
(range)
Weight (kg)
Men
(n = 46)
35.1 ± 13.7
19 to 59
78.9 ± 9.5
Women
(n = 60)
29.6 ± 12.4
18 to 60
64.2 ± 8.9
All
(n = 106)
32.4 ± 13.3
18 to 60
70.6 ± 11.7
Height (m)
1.80 ± 0.1
1.66 ± 0.1
1.72 ± 0.1
24.4 ± 3.0
23.3 ± 3.2
23.8 ±3.2
-2
BMI (kg.m )
The number of self-reported past injuries is depicted in Table 5.3. A knee injury was
reported by 20.7% of participants while multiple back and lower limb injuries
accounted for a further 17.9%. One or more ankle injuries were reported by 17.0% of
participants. Only 17.0% never had a previous injury. More than 6 months prior to
testing a closed head injury or concussion was experienced by 8.3% or 3.3% women
and 4.3% or 13.0% men respectively.
184
Table 5.3
Frequency of Self-Reported Previous Musculoskeletal Injuries
Injury site
Men
(n = 46)
Women
(n = 60)
None
1 (2.2%)
17 (28.3%)
Total
(n = 106)
18 (17.0%)
14 (30.4%)
5 (8.3%)
19 (17.9%)
1 (2.2%)
4 (6.7%)
5 (4.7%)
-
2 (3.3%)
2 (1.9%)
2 (4.3%)
2 (3.3%)
4 (3.8%)
10 (21.7%)
12 (20%)
22 (20.8%)
Fracture femur, tibia, fibula, ribs
3 (6.5%)
-
3 (2.8%)
Tibial stress, calves
3 (6.5%)
4 (6.7%)
7 (6.6%)
Ankle
7 (15.2%)
11 (18.3%)
18 (17.0%)
Achilles
1 (2.2%)
-
1 (0.9%)
Foot
2 (4.3%)
3 (5.0%)
5 (4.7%)
Upper limb
2 (4.3%)
-
2 (1.9%)
Multiple lower limb and back
Back
Groin, pelvis hip
Thigh
Knee, Ilial tibial band, Anterior cruciate ligament
5.3.2
Sports and Exercise Participation
Table 5.4 indicates the type of sports and exercise reported by the participants. On
average, the men reported exercising 6.63 ± 3.60 hrs per week and the women 6.11 ±
3.56 hrs per week indicating a similar good level of participation and fitness. Cycling,
kayaking, running and swimming were the sports in which 54.0% of individuals
participated. Only 3.8% reported doing no specific exercise although they considered
themselves fit and healthy based on their daily activities and so fulfilled the inclusion
criteria.
185
Table 5.4
Frequency of Sports and Exercise Reported by the Participants
None specified
Men
(n = 46)
3 (6.5%)
Women
(n = 60)
1 (1.7%)
Total
(n = 106)
4 (3.8%)
Walking, tramping
2 (4.3%)
13 (21.7%)
15 (14.2%)
Commercial gym programmes
1 (2.2%)
8 (13.3%)
9 (8.5%)
Swimming, aqua-jogging
1 (2.2%)
2 (3.3%)
3 (2.8%)
Netball, basketball, volleyball, squash, table tennis
2 (4.3%)
5 (8.3%)
7 (6.6%)
28 (60.9%)
19 (31.7%)
47 (44.3%)
Hockey, rugby, soccer, touch rugby
4 (8.7%)
6 (10.0%)
10 (9.4%)
Surfing, sailing, rowing
2 (4.3%)
1 (1.7%)
3 (2.8%)
Mountain biking, cycling, multi-sport
3 (6.5%)
4 (6.7%)
7 (6.6%)
-
1 (1.7%)
1 (0.9%)
Type of sports
Running, triathlon
Rock climbing, martial arts
5.3.3
Footwear
Each participant brought their most frequently used pair of shoes in which they felt
comfortable to perform the task and walk for 20 min. Two hundred and twelve shoes
were assessed.
5.3.3.1
Footwear was divided into the same six categories as Study 1. The type of shoe worn
by participants is shown in Table 5.5. Sixty-four percent of participants chose their
sports shoe in which to perform the task. A stability sports shoe was worn by 15% of
participants.
The average reported age of the shoes was 11.9 ± 11.4 months (range 1 to 72 months,
median 12) with 37.7% six months or less. Twenty-four (22.6%) pairs were older than
one year for 7 men and 17 women. The average reported frequency of use was 4.6 ±
3.9 hours per day (range 1 to 10 hours/day, median 2).
186
Table 5.5
Frequency of Shoe Type Worn by the 106 Participants (n = Shoe Pairs)
Neutral sports: heel-height 1.0 to 2.0 cm
Men
n = 46
27 (58.7%)
Women
n = 60
25 (41.7%)
Total
n = 106
52 (49.0%)
Control sports: heel-height 1.0 to 2.0 cm
2 (4.3%)
14 (23.3%)
16 (15%)
Dress: heel-height 1.0 to 3.0 cm
4 (8.6%)
7 (11.7%)
11 (10.4%)
Flats, or loafers: heel-height 0.5 to 1.5 cm
8 (17.4%)
11 (18.3%)
19 (17.9%)
Canvas: heel-height 0.0 to 1.0 cm (within shoe)
1 (2.2%)
2 (3.3%)
3 (2.8%)
Boot: heel-height 1.5 to 3.0 cm
4 (8.7%)
1 (1.7%)
5 (4.7%)
Type of shoe
5.3.3.2
Actual heel height
No heels greater than 3.0 cm were used by the participants for testing in this study.
Ninety-three (87.8%) shoes had moderate heel height (1.0 to 3.0 cm) while the
remaining footwear comprising flats and canvas shoes had less than 1.0 cm difference
between the heel and fore-foot. The flats and canvas shoes appear from the outside to
have no difference in heel height comparing rearfoot/forefoot, but in many the inner
sole has an attached heel comprised of sponge or other rubber material of varying
density. This was assessed both for height and asymmetric compression (Figure 5.9).
The outer-sole illustrated in Figure 5.9 (A and B) is flat. No midsole is present. Actual
heel height of 1.5 cm is the thickness of the attached heel inside the shoe (Figure 5.9
D). This height excludes the 3 mm inner-sole thickness which extends the length of
the shoe.
187
A
B
C
D
Figure 5.9 Assessment performed on a flat shoe in terms of asymmetry, outersole, midsole and actual heel-height.
.
5.3.3.3
Outer sole wear asymmetry
Figure 5.9 (A and B) illustrates the outer-sole assessment of a flat shoe. The small
weight-bearing tread has a 2 mm thick lateral heel star worn away. Symmetrical
outer-sole or zero wear was found in 57.6% of shoes (Table 5.6). No shoes had
greater medial outer sole wear. Lateral outer-sole heel wear was measured in 35.9% of
shoes. This ranged from 1 to 5 mm (Figure 5.9). Lateral forefoot wear was measured
in 14.2% of shoes with an asymmetry of 1 mm in 77% of these. One pair had greater
medial wear of 1 mm.
Asymmetry of wear between the left and right shoe was measured in 7.6% of shoes.
This wear was equally distributed between the left or right shoe and not linked to the
participant’s preferred stance leg. The most frequent left and right asymmetry was 1
mm in 4.7% of shoes. The greatest difference between the left and right shoe was 5
mm of lateral wear in one pair.
188
Table 5.6
Frequency of Shoe Heel Outer-Sole Wear Asymmetry in 212 Shoes (n = Shoe
Pairs)
Men
n = 46
33 (71.7%)
Women
n = 60
27 (45.0%)
Total
n = 106
61 (57.6%)
8 (17.4%)
19 (31.7%)
27 (25.5%)
2 mm
3 (6.5%)
8 (13.3%)
11 (10.4%)
3 mm
-
2 (3.3%)
2 (1.9%)
4 mm
1 (2.2%)
2 (3.3%)
3 (2.8%)
5 mm
1 (2.2%)
1 (1.7%)
2 (1.9%)
Status
Symmetrical heel wear or zero wear
Lateral heel outer sole asymmetry
1 mm
5.3.3.4
Midsole compression asymmetry
Inner-heel asymmetric compaction in a flat shoe is illustrated in Figure 5.9 (C and D).
In this case, measurement was possible with a Vernier calliper. The 3 mm lateral
asymmetry is the difference between medial and lateral thickness measured (18.8 15.7 = 3.1 mm). Ten or more Asker C units of medial or lateral midsole compression
asymmetry were measured in 21.7% of footwear. This softness was predominantly at
the lateral heel. Stability sports shoes accounted for 72.7% of this lateral softness,
including six pairs which had an Asker C difference of 20 or more units. No midsoles
had compression or compaction with hardness of Asker C 70 units or higher which is
the hardness measured in dress shoes, tramping boots and the medial midsole of
motion control sports shoes. The remaining shoe types exhibiting compression
differences were 5 pairs of neutral sports shoes and one pair of 36-month old flats in
which the thick inner-heel had compressed laterally at the heel. Combined with
compression 30.4% of shoes also had between 1 and 3 mm outer-sole lateral wear.
One neutral sports pair was softer on the medial heel. In the forefoot only 1.9% was
softer by 10 Asker C units on the lateral side. No shoes with midsole asymmetric
compression had medial outer-sole wear.
189
Table 5.7
Frequency of Asymmetric Shoe Compression (n = Shoe Pairs)
Status
Softer on the Lateral heel
10 ≤ Difference < 20 units*
Difference ≥ 20 units
Softer on the Medial heel
10 ≤ Difference < 20 units
Men
n = 46
Women
n = 60
Total
n = 106
3 (6.5%)
12 (20.0%)
15 (14.2%)
-
7 (11.7%)
7 (6.6%)
1 (2.2%)
-
1 (0.9%)
* Asker C Durometer units
5.3.3.5
Inserts and orthotics
Prescribed orthotics were assessed in 8.5% of sports or day-to-day footwear (Table
5.8). Left and right foot orthotic design was identical. These included
FormorthoticsTM without or with medial posting at the heel, forefoot and added arch
supports. One participant wore FootbioticsTM orthotics with approximately 4 mm
medial heel posting, arch and forefoot support and one had 6 mm heel-raises inserted
into both shoes.
Table 5.8
Shoe Type, Midsole Compression Difference, Outer-Sole Wear and Total
Asymmetry for 8.5% of Participants Wearing Orthotics
1
Midsole
compression
difference
Softer laterally
Asker C units
10 lateral (=1 mm)
2
Neutral sports
10 lateral (=1 mm)
2 mm
3 mm
W2
3
Neutral
1 mm
5 mm
W3
4
10 lateral (=1 mm)
0 mm
5 mm
W4
5
Stability sports
20 lateral (=2 mm)
0 mm
2 mm
W5
6
Flats
Neutral
1 mm
1 mm
W6
7
Flats ± 4 mm medial
Neutral
1 mm
5 mm
W7
8
Flats ± 6 mm heel-raise only
Neutral
0 mm
Neutral
W8
9
Flats ± 4 mm medial
Neutral
1 mm
5 mm
M1
Shoe type in which
orthotics inserted and any
additional wedging/posting
Outersole
wear
lateral
Total
asymmetry
lateral
Total
n=9
0 mm
5 mm
W1
W: Women; M: Men
190
Of the five pairs of sports shoes, all but one had a softer lateral heel by 10 or more
Asker C units compared to the medial margin. This was caused by design in stability
shoes or asymmetric compression in neutral shoes. Softness is equated to the thumb
compression categories as described in Section 4.2.7.5 (Barton, Bonanno et al., 2009;
Menz & Sherrington, 2000). Five pairs had lateral outer sole heel wear. No shoes had
medial midsole compression or outer sole wear. The total asymmetry includes the
combination of outer-sole wear, midsole compression and measured posting but
excludes the effect of the orthotics themselves. Lateral asymmetry between 1 and 5
mm was measured in 88.9% of shoes with orthotics.
5.3.3.6
The total footwear mediolateral asymmetry is shown in Table 5.9. Mediolateral
midsole compression differences affected the overall asymmetry rating in 21.7% of
shoes. For example, the flat shoe featured in Figure 5.9 had measured lateral outer
sole wear of 2 mm combined with the 3 mm lateral collapse of the inner-heel (18.8 –
15.7 = 3.1 mm) to give an overall lateral asymmetry of 5 mm.
Table 5.9
Total Mediolateral Asymmetry in 212 shoes (n = Shoe Pairs)
Men
n = 46
29 (63.0%)
Women
n = 60
15 (25.0%)
Total
n = 106
44 (41.5%)
11 (23.9%)
21 (35.0%)
32 (30.2%)
2 mm
2 (4.3%)
11 (18.3%)
13 (12.3%)
3 mm
-
5 (8.3%)
5 (4.7%)
4 mm
1 (2.2%)
3 (5.0%)
4 (3.8%)
5 mm
Medial heel asymmetry: 1 mm
2 (4.3%)
1 (2.2%)
5 (8.3%)
-
7 (6.6%)
1 (0.9%)
Status
Neutral
Lateral heel asymmetry
1 mm
Other examples of these wear and compression effects are presented in Table 5.8.
This difference could wholly account for the asymmetry if no outer sole wear (Table
5.8 Shoe 5), increase the asymmetry if the outer sole wear was on the same side
(Table 5.8 Shoe 2) or attenuate the asymmetry if on the opposite side of the outer sole
wear (no example in the 106 pairs assessed). Zero or symmetrical wear accounted for
191
41.5% of shoes while 57.6% of shoes had 1 to 5 mm laterally biased asymmetry. Only
0.9% had 1 mm medial biased asymmetry. The mean asymmetry was 1.2 ± 1.5 mm
biased laterally (median and mode = 1 mm).
In Section 5.3.4, postural stability performance barefoot is compared to the
participant’s frequently used footwear. The questions which the analysis addresses are
whether there is a difference in performance in those individuals whose footwear was
neutral (41.5%) compared to those whose shoes were asymmetrically degraded
(58.5%). Further fine-tuning of this question relates to the magnitude and mediolateral
direction of this asymmetry but the number of participants in each wear category was
insufficient to provide meaningful statistical comparisons (Table 5.9). All participants
who had footwear with mediolateral asymmetry were combined to form a single
group almost equivalent in terms of numbers as the neutral shoe group. These results
also form an integral part of the analysis of the pre- and post-habituation walk
(Section 5.3.6). Corrected neutral shoes were calculated from the measured total
asymmetry (Table 5.9) and the simulated condition within the shoe. These are
theoretically 100% neutral. The effect of the participants’ habituated footwear (41.5%
neutral) and corrected neutral shoes (100% neutral) on postural stability are compared
to other asymmetric conditions during the phases of the task (see Sections 5.3.6.2 and
5.3.6.3).
5.3.4
Barefoot versus Shoe
Postural stability performance is compared while barefoot and in personal well-worn
footwear. Footwear was 11.9 ± 11.4 months old and worn 4.6 ± 3.9 hours per day.
Factors which are constant such as age, gender, height and weight were not expected
to influence within subject comparisons, so these were entered as covariates into the
statistical model; therefore the main effect would be the change to the foot-ground
interface. The three main aims were to determine if there are 1) any measurable
differences in postural stability barefoot versus personal footwear, 2) whether preexisting footwear asymmetry influences postural stability barefoot and within the
shoe, and 3) whether the COP measures of maximum displacement and mean velocity
are affected.
192
5.3.4.1
Effect on postural stability measures while controlling for age,
gender and BMI
Almost all measures of postural stability were greater barefoot compared to the shoe
only condition for double-leg stance, transition, single-leg stance (total time and first
5 s) while controlling for age, gender and BMI. SDFx and SDFy was 9.4 and 12.2%
greater barefoot during double-leg stance while other variables were unchanged
(Table 5.10). During transition values are 13.8%, 25.9%, 16.5% and 20.9% greater
barefoot for SDFx, Maxdis, Mvelo and Mvelox respectively. Similar patterns are
found during single-leg stance. Increased variability during barefoot, exists for all
dependent variables except for time to stabilisation and Maxdis (Table 5.10). During
single-leg stance the time to stabilisation times decreased by 11.9% and 3.5% for
TTSFx and TTSFy respectively. During the second 5 s of single-leg stance only
Maxdis decreases by 6.5% barefoot compared to the shoe condition (Table 5.10).
193
3.8 (-2.9 to 10.9)
0.4 (-3.3 to 4.2)
Mvelox
Mveloy
.826
.277
.430
4.4 (-5.0 to 14.8)
20.9 (12.7 to 29.7)
16.5 (8.8 to 24.7)
25.9 (17.0 to 35.4)
.373
.001
.001
.001
.337
9.9 (6.2 to 13.6)
15.7 (12.2 to 9.3)
12.8 (9.5 to 16.2)
14.0 (9.1 to 19.2)
7.3 (4.4 to 10.3)
13.1 (9.3 to 16.9)
Mean % (95%CI)
.003
.004
.001
.001
.001
.001
.001
.001
P
10.5 (6.3 to 15.0)
20.0 (15.7 to 24.4)
15.7 (11.9 to 19.7)
16.0 (10.5 to 21.7)
6.9 (3.9 to 10.1)
16.5 (12.0 to 21.2)
Mean % (95%CI)
.001
.001
.001
.001
.001
.001
P
Single-leg Stance
(First 5 s)
8.4 (4.0 to 12.9)
10.0 (5.7 to 14.5)
8.9 (5.0 to 12.8)
-6.5 (-10.6 to -2.3)
8.6 (3.3 to 14.2)
5.0 (0.4 to 9.7)
Mean % (95%CI)
.001
.001
.001
.003
.001
.032
P
Single-leg Stance
(Second 5 s)
194
SDFx: standard deviation of GRF in anterioposterior direction; SDFy: standard deviation of GRF in mediolateral direction; Maxdis: maximum displacement; Mvelo: mean
velocity overall and in the anterioposterior (x) and mediolateral (y) directions; TTS: Time to stabilization of GRF in anterioposterior (Fx) and mediolateral (Fy) directions.
-3.5 (-5.7 to -1.2)
2.3 (-3.2 to 8.0)
Mvelo
.822
-2.8 (-8.2 to 3.0)
.001
P
TTSFy
1.0 (-7.2 to 9.8)
Maxdis
.028
13.8 (7.4 to 20.7)
Mean % (95%CI)
Single-leg Stance
(Total time)
-11.9(-19.2 to -4.0)
12.2 (1.2 to 24.3)
SDFy
.054
P
Transition
TTSFx
9.4 (-0.1 to 19.9)
Mean % (95%CI)
Double-leg Stance
SDFx
DependentVariable
Percentage Change for the Dependent Variables Comparing Barefoot to the Shoe Only Condition (+% is an increase)
Table 5.10
5.3.4.2
Effect of shoe heel asymmetry on postural stability measures
In order to assess the effect of shoe asymmetry on postural stability, the footwear
condition for each participant (Table 5.9) was recoded to form two groups only. The
criterion was whether their footwear was neutral or asymmetric. The ratio between the
groups was 41.5% neutral and 58.5% asymmetric footwear. This may dilute the effect
of differences between medial and lateral and the magnitude of asymmetry but the
numbers in each asymmetric group were too small to provide valid comparisons. The
percentage change (95% CI) for all variables are presented in Table 5.11. There were
no significant differences between individuals whose footwear was either neutral or
asymmetric during double-leg stance. During transition and single-leg stance the
variability of the mediolateral GRF was the only variable significantly affected by the
participants shoe rating. The variability of the mediolateral GRF was identified in the
literature (Section 2.7.3, p 72) as sensitive and reliable and is linked to the task and
intervention (Goldie et al., 1992, 1994). The results for this dependent variable were
significantly different for participants with asymmetrically worn footwear during the
transition and single-leg stance phase. The robustness of the analysis excludes a
possibility that this difference was just due to chance. Hence this change was
considered sufficient to conclude there was an effect on postural stability. Since this
was an exploratory study, a number of dependent variables were chosen, with the
assumption that some may be more specific and sensitive or characterize different
components of postural stability.
Barefoot SDFy was 20.2% greater during transition in those participants whose
footwear was asymmetric. This tendency, along with the 95% CI, was also reflected
in the 7.1 % and 7.5 % increase during the total time and the first 5 s of single-leg
stance respectively. SDFy in footwear was similarly affected by increases of 13.1 %,
13.0 % and 9.8 % during total time, first 5 s and second 5 s of single-leg stance. A
similar trend was observed for SDFx in shoes and TTSFx both barefoot and in shoes.
195
-1.4 (-14.6 to 13.8)
-4.9 (-18.5 to 10.9)
1.5 (-7.7 to 11.6)
-0.5 (-9.3 to 9.2)
Mvelox B
Mvelox S
Mveloy B
Mveloy S
.915
.760
.520
.846
.433
11.5 (-10.5 to 38.9)
8.0 (-15.6 to 38.1)
5.1 (-13.6 to 27.8)
-3.3 (-21.6 to 19.3)
5.8 (-12.5 to 27.8)
-1.1 (-19.6 to 21.6)
.331
.541
.622
.756
.561
.914
.478
3.7 (-6.9 to 15.5)
-2.0 (-10.8 to 7.6)
1.8 (-8.5 to 13.3)
-2.6 (-11.8 to 7.5)
3.1 (-7.0 to 14.3)
-2.0 (-10.5 to 7.5)
-3.9 (-13.8 to 7.1)
1.8 (-9.3 to 14.3)
.426
.783
.362
.307
.513
.670
.741
.597
.559
.672
.469
.761
.008
.143
.177
.680
P
5.0 (-6.0 to 17.2)
-1.0 (-9.7 to 8.5)
1.8 (-8.5 to 13.3)
-1.9 (-11.6 to 8.9)
3.9 (-6.3 to 15.1)
-1.3 (-10.0 to 8.1)
-4.9 (-16.1 to 7.8)
3.0 (-9.0 to 16.6)
13.0 (2.8 to 24.2)
7.5 (-2.1 to 18.1)
8.1 (-2.6 to 19.9)
3.3 (-6.5 to 14.2)
Mean % (95%CI)
P
.391
.822
.743
.718
.470
.774
.431
.638
.012
.131
.143
.523
Single-leg Stance
(First 5 s)
3.0 (-8.7 to 16.2)
-3.8 (-13.6 to 7.1)
3.7 (-7.8 to 16.6)
-4.6 (-14.5 to 6.5)
3.5 (-7.5 to 15.9)
-3.7 (-13.3 to 7.0)
-2.0 (-11.0 to 8.0)
-1.0 (-9.2 to 7.9)
9.8 (-3.9 to 25.6)
1.1 (-10.6 to 14.4)
4.9 (-6.7 to 17.9)
-1.7 (-11.5 to 9.2)
Mean % (95%CI)
196
P
.631
.477
.544
.404
.550
.483
.686
.822
.169
.860
.424
.745
Single-leg Stance
(Second 5 s)
DV: Dependent variable; B: Barefoot; S: Shoe; SDFx: standard deviation of GRF in anterioposterior direction; SDFy: standard deviation of GRF in mediolateral direction;
Maxdis: maximum displacement; Mvelo: Mean velocity overall and in anterioposterior (x) and mediolateral directions (y); TTS: Time to stabilization of GRF in
anterioposterior (Fx) and mediolateral (Fy)
-2.4 (-8.2 to 3.7)
-4.8 (-16.0 to 7.8)
Mvelo S
.874
6.4 (-10.3 to 26.1)
.404
13.1 (3.3 to 24.0)
TTSFy S
-1.0 (-12.3 to 11.8)
Mvelo B
.179
7.5 (-9.3 to 27.3)
.455
7.1 (-2.3 to 17.3)
0.8 (-4.6 to 6.5)
-11.7 (-26.3 to 5.9)
Maxdis S
.763
6.1 (-9.1 to 23.8)
.014
6.8 (-29 to 17.6)
TTSFy B
-2.5 (-17.2 to 14.9)
Maxdis B
.820
20.2 (3.7 to 39.3)
.262
1.9 (-6.7 to 11.1)
Mean % (95%CI)
8.2 (-8.7 to 28.3)
-2.4 (-21.2 to 20.8)
SDFy S
.850
12.2 (-8.3 to 20.7)
.239
P
TTSFx S
-2.0 (-20.9 to 21.3)
SDFy B
.112
10.0 (-6.1 to 28.8)
Mean % (95%CI)
Single-leg Stance
(Total time)
8.6 (-7.3 to 27.2)
-13.5 (-27.7 to 3.5)
SDFx S
.270
P
Transition
TTSFx B
-10.2 (-25.8 to 8.7)
Mean % (95%CI)
Double-leg Stance
SDFx B
DV
Table 5.11
Percentage Difference for the Dependent Variables between Individuals with Neutral or Asymmetric Footwear while Barefoot or in Shoes
(+% is an increase for individuals whose footwear is asymmetric)
5.3.4.3
The effect of age, BMI and gender on postural stability measures
barefoot and shoe
Age, BMI and gender were controlled for during the analysis where the primary aim
was to assess the effect of simulated asymmetry. Nevertheless a brief summary of
their effects is presented. Increasing age had no effect on postural stability measures
during double-leg stance. During transition, mean velocity barefoot (P = .044) and in
shoes (P = .033) was influenced by a 0.8% decrease (95% CI -1.5 to
-0.1%) for each unit increase in age. This effect was even smaller during single-leg
stance barefoot and was significant only in shoes for SDFx (-0.5%, 95% CI -0.8 to 0.1%, P = .013), SdFy (-0.4%, 95% CI -0.7 to -0.1%, P = .019) and Maxdis (-0.4%,
95% CI -0.8 to 0.0%, P = .028).
Increasing BMI had small but variable effects on postural stability measures during all
phases. During double-leg stance in shoes SDFx increased by 4.0% (95% CI 1.2 to
6.9%, P = .005) per unit increase in BMI, while mean velocity barefoot decreased by
2.5% (95% CI -4.3 to -0.7%, P = .007). During transition only SDFx and SDFy
increased by 5.0% (95% CI 1.8 to 8.3%, P = .002) and 3.0% (95% CI 0.5 to 5.4%, P =
.016) while in shoes. A similar effect occurred while barefoot. SdFx and SDFy
increased 3.7% (95% CI 2.2 to 5.3%, P < .001) and 5.7% (95% CI 4.2 to 7.2%,
P < .001) respectively during single-leg stance in shoes for each unit increase in BMI.
Gender had no significant effect on postural stability measures during double-leg
stance. During transition and single-leg stance, women compared to men had between
9 and 25% better postural stability. This was true for the dependent variables SDFx,
SDFy, Maxdis and Mvelo both barefoot and in footwear (Table 5.12).
197
Table 5.12
Percentage Change for the Dependent Variables Comparing Barefoot and Shoe
Postural Stability in Women versus Men, During Transition and Single-Leg Stance
Dependent
Variable
Transition
Single-leg Stance
(Total time)
Mean % (95%CI)
P
Mean % (95%CI)
P
SDFx B
SDFx S
SDFy B
SDFy S
-15.8 (-28.3 to -1.1)
-15.0 (-30.8 to 4.3)
-24.2 (-34.8 to -11.9)
-17.4 (-29.5 to -3.4)
.036
.120
.001
.017
-21.2 (-27.9 to -13.9)
-22.9 (-30.1 to -15.0)
-19.2 (-26.4 to -11.4)
-23.6 (-30.4 to -16.1)
.001
.001
.001
.001
Maxdis B
-14.7 (-28.2 to 2.0)
.071
-18.6 (-27.6 to -8.4)
.001
Maxdis S
Mvelo B
Mvelo S
-19.3 (-32.1 to -4.0)
-18.7 (-34.1 to 0.3)
-20.7 (-34.6 to -3.9)
.015
.053
.018
-14.3 (-23.2 to -4.3)
- 9.7 (-17.7 to -0.9)
-15.8 (-24.2 to -6.6)
.006
.032
.001
SDFx and SDFy: standard deviation of GRF in anterioposterior (x) and mediolateral (y) directions;
Maxdis: maximum displacement; Mvelo: Mean velocity; B Barefoot; S Shoe
5.3.5
Shoe and Simulated Asymmetric Shoe Conditions
Postural stability performance was compared between the personal well-worn
footwear and incremental simulated mediolateral asymmetry in the same shoe. The
seven conditions created multiple possible statistical comparisons and hence analysis
accounted for this. Other factors such as age, gender, BMI and order of presentation
which might influence between- and within-subject comparisons, were controlled for
throughout the analysis. The presentation of results follows a logical progression:
excluding order (5.3.5.1), controlling for order of presentation (5.3.5.2), correcting the
simulated asymmetric condition (5.3.5.3) with the measured actual shoe asymmetry
(5.3.3.7 and Table 5.9). The main aim was to determine if incremental mediolateral
asymmetry systematically influenced postural stability performance.
5.3.5.1
Wedge conditions without order
Adjusting for multiple comparisons, only one significant interaction was found
for Mvelox (P = .056) during transition while controlling for age, gender and BMI. To
determine any relationships between simulated asymmetry and shoe only conditions
this variable was analysed further. Exploratory analysis of other variables and phases
198
indicated non-significant alterations similar to those presented for mean velocity
(Table 5.13).
Table 5.13
Percentage Change for Mvelox Comparing Shoe-Only to Simulated Asymmetric
Shoe Conditions During Transition
Simulated asymmetric shoe
condition
3 mm medial
2 mm medial
1 mm medial
Shoe only
1 mm lateral
2 mm lateral
3 mm lateral
Mean Velocity x
Mean % (95%CI)
-4.2 (-10.0 to 1.9)
3.3 (-3.0 to 9.9)
0.7 (-5.4 to 7.2)
.172
.313
.823
-2.4 (-8.3 to 3.9)
0.2 (-5.8 to 6.7)
5.4 (-1.0 to 12.1)
.443
.942
.100
P
Mvelox: mean velocity in the anterioposterior direction
Comparing the 3 mm with 2 mm (P = .116) and 1 mm (P = 0.016) lateral wedge,
Mvelox decreased 5.1% (95% CI -1.2 to 11.9%) and 8.0% (95% CI 1.4 to 14.9%)
respectively. The remaining comparisons exhibited non-significant trends with
increased values for the greater asymmetry, except for the 3 mm medial wedge
condition. For example, the medial 2 mm is 2.5% (95% CI -3.8 to 8.4%) greater than
the 1 mm wedge (P = .433).
5.3.5.2
Wedge conditions including the effect of order (learning/fatigue)
The effect of order on the random wedge-shoe conditions is presented in Table 5.14.
A positive percentage result indicates an increase in the respective variables so
considered an impaired performance (fatigue). Negative percentage change indicates
improved performance as a result of learning effect (per trial and condition). For most
of the dependent variables, except time to stabilization, order had the effect of linearly
decreasing the values, a learning effect, varying from 0.3 to 3.8 % with a mean
decrease of 1.2%. Although this effect was small and linear, order was then included
and controlled for in the following simulated asymmetry analysis. Only one
significant interaction was found for the shoe-wedge conditions while controlling for
age, gender, BMI and order of presentation. Mvelox (P = .036) and Maxdis (P = .109)
were analysed for each asymmetric condition during the transition phase (Table 5.15).
199
P
.001
.001
.134
.001
.001
.001
Mean % (95%CI)
-1.7 (-2.7 to -0.7)
-3.8 (-5.0 to -2.6)
-0.8 (-1.7 to 0.2)
-1.5 (-2.1 to -0.8)
-1.7 (-2.5 to -1.5)
-0.8 (-1.2 to -0.8)
Double-leg Stance
0.4 (-0.3 to 1.2)
0.2 (-0.4 to 0.8)
-0.6 (-1.4 to 0.3)
-1.2 (-1.9 to -0.5)
-1.2 (-2.0 to -0.4)
-1.2 (-1.9 to -0.5)
Mean % (95%CI)
Transition
.287
.536
.200
.001
.005
.001
P
-1.4 (-1.7 to -1.0)
-1.0 (-1.3 to -0.6)
-0.3 (-0.8 to 0.1)
-2.3 (-2.6 to -2.0)
-2.1 (-2.5 to -1.8)
-2.5 (-2.8 to -2.1)
0.0 (-0.9 to 1.0)
1.0 (0.7 to 1.2)
Mean % (95%CI)
P
.001
.001
.114
.001
.001
.001
.925
.001
Single-leg Stance
(Total time)
-1.6 (-2.0 to -1.2)
-1.0 (-1.3 to -0.6)
-0.8 (-1.3 to -0.3)
-2.5 (-2.8 to -2.2)
-2.3 (-2.7 to -1.9)
-2.2 (-2.9 to -1.4)
Mean % (95%CI)
P
.001
.001
.003
.001
.001
.001
Single-leg Stance
(First 5 s)
-1.2 (-1.7 to -0.7)
-1.5 (-2.0 to -0.9)
-0.3 (-0.8 to 0.3)
-2.2 (-2.6 to -1.7)
-2.0 (-2.5 to -1.6)
-2.3 (-2.8 to -1.8)
Mean % (95%CI)
200
P
.001
.001
.380
.001
.001
.001
Single-leg Stance
(Second 5 s)
SDFx and SDFy: standard deviation of GRF in anterioposterior (x) and mediolateral (y) directions; Maxdis: maximum displacement; Mvelo: Mean velocity overall and in
anterioposterior (x) and mediolateral directions (y); TTS: Time to stabilization of GRF in anterioposterior (Fx) and mediolateral (Fy) directions.
SDFx
SDFy
Maxdis
Mvelo
Mvelox
Mveloy
TTSFx
TTSFy
DV
Percentage Change for Dependent Variables Comparing Effect of Order on Wedge-Shoe Performance (+% is impaired performance)
Table 5.14
The percentage changes (and P-values) for Mvelox and Maxdis of the simulated
asymmetry from shoe only condition after controlling for order is presented in Table
5.15. The trend, although not significant, was decreasing postural stability with
increasing asymmetry away from the shoe only condition, but this pattern was not
evident for the simulated 3 mm medial asymmetry. Controlling for order slightly
improved this relationship (compare with Table 5.13).
Table 5.15
Percentage Change for Mvelox and Maxdis Comparing Shoe-Only to Simulated
Asymmetric Shoe Conditions During Transition
Simulated
asymmetric shoe
condition
3 mm medial
2 mm medial
1 mm medial
Shoe only
1 mm lateral
2 mm lateral
3 mm lateral
Mean Velocity x
Mean % (95%CI)
P
Maximum displacement
Mean % (95%CI)
P
-3.9 (-9.7 to 2.3)
4.1 (-2.1 to 10.8)
1.1 (-5.0 to 7.5)
.210
.201
.737
0.0 (-6.1 to 6.5)
6.1 (-0.4 to 13.1)
4.4 (-2.1 to 11.2)
.998
.068
.188
-2.2 (-8.0 to 4.1)
0.9 (-5.2 to 7.4)
5.9 (-0.5 to 12.7)
.490
.776
.069
0.3 (-5.8 to 6.9)
1.5 (-4.8 to 8.1)
7.4 (0.8 to 14.5)
.915
.652
.027
Mvelox: mean velocity in the anterioposterior direction; Maxdis: maximum displacement
For Mvelox the 3 mm lateral wedge was 5.0% (95% CI -1.3 to 11.7%) and 8.3%
(95% CI 1.7 to 15.2%) greater than the 2 mm (P = .125) and 1 mm (P = .012) lateral
wedge respectively. Mvelox for the 1 mm lateral wedge was 6.1% (95% CI -11.7 to
0.0%) less than the 2 mm medial wedge (P = .049) indicating an improved
performance for this condition. A similar result was found for maximum
displacement. Comparing the simulated 3 mm to 2 mm (P = .077) and 1 mm (P =
.035) lateral conditions, Maxdis was progressively reduced by 5.9% (95% CI -0.6 to
12.8%) and 7.1% (95% CI 0.5 to 14.1%) respectively.
201
5.3.5.3
Grouped corrected wedge-shoe conditions
Dependent on the assessment of wear asymmetry, the placement of medial and lateral
wedges could simulate, accentuate or attenuate asymmetric heel wear. As a result the
third level of analysis combined experimental wedge condition (1, 2 and
3 mm medial or lateral asymmetry) with measured shoe asymmetry (Table 5.16) to
produce 13 corrected wedge-shoe conditions from 1 to 8 mm medial, neutral and from
1 to 4 mm lateral. For example, if the shoe asymmetry was neutral (0 mm) and the
simulated asymmetry 3 mm medial, the corrected wedge-shoe condition was 3 mm
medial (0 + 3 = 3). However, if the shoe asymmetry was 5 mm lateral, the total
corrected wedge-shoe condition was 8 mm medial (5 + 3 = 8). Should the measured
shoe asymmetry be 1 mm medial then the total corrected wedge-shoe condition was
2 mm medial (-1 + 3 = 2).
Table 5.16
Combined Shoe and Simulated Shoe Asymmetry in Two Groups
Corrected Condition
8 mm medial
Trials (n = 2,225)
Trials (n = 2,225)
12
7 mm medial
24
6 mm medial
36
5 mm medial
75
4 mm medial
183
3 mm medial
315
315
2 mm medial
318
318
1 mm medial
306
306
Neutral
294
294
1 mm lateral
281
281
2 mm lateral
243
243
3 mm lateral
135
138
4 mm lateral
3
330
The frequency distribution of measured shoe asymmetry (Table 5.9) was biased
towards neutral and 1 mm lateral wear. As a result, the number of trials within each of
the 13 corrected wedge-shoe conditions was now different compared to the original
202
experimental design. In order to analyse the corrected wedge-shoe conditions the
reduction and collapsing of conditions into similar sized groups was required. One
method to produce similar sized groups was to recode the 4 to 8 mm medial
conditions as one group and the 3 and 4 mm lateral conditions as another group (Table
5.16). Although not perfectly balanced in terms of number of trials, these eight
corrected wedge-shoe conditions were then analysed.
The only dependent variable which approached significance (P = .096) during singleleg stance and warranted further analysis was SDFy (Table 5.17). During single-leg
stance, increasing the asymmetry medially or laterally, there was a trend towards
increased variability of the mediolateral GRF when compared to the true neutral shoe
condition. Mediolateral variability increased 2.6%, 3.6%, 2.4% and 4.2% with
respective increases of medial asymmetry. Similarly, with increased lateral
asymmetry, SDFy increased by 3.4%, 2.7% and 4.1% (Table 5.17). Postural stability
was unaffected by the asymmetry during the other phases of the task.
203
.747
.411
.364
.222
.286
.721
.070
5.3 (-4.2 to 15.7)
1.8 (-7.7 to 12.4)
1.9 (-0.6 to 4.5)
P
1.7 (-8.0 to 12.4)
3.9 (-5.2 to 13.9)
4.3 (-4.8 to 14.4)
5.9 (-3.4 to 16.2)
Mean %
(95%CI)
Double-leg Stance
1.7 (-2.8 to 6.4)
0.2 (-4.4 to 5.0)
2.6 (-3.2 to 8.7)
2.1 (-2.9 to 7.3)
-1.5 (-5.7 to 2.9)
0.8 (-3.5 to 5.3)
1.3 (-3.1 to 5.9)
Mean %
(95%CI)
Transition
.472
.938
.385
.417
.503
.718
.564
P
Mean %
(95%CI)
3.4 (0.7 to 6.2)
2.7 (-0.1 to 5.6)
4.1 (0.6 to 7.6)
.012
.057
.021
.006
.070
.006
.056
P
Single-leg Stance
(Total time)
4.2 (1.2 to 7.3)
2.4 (-0.2 to 5.1)
3.6 (1.0 to 6.3)
2.6 (-0.1 to 5.2)
M: medial; L: lateral; SDFy: standard deviation of GRF in mediolateral (y) direction
4 to 8 mm M
3 mm M
2 mm M
1 mm M
Neutral shoe
1 mm L
2 mm L
3 to 4 mm L
Condition
3.3 (0.6 to 6.1)
3.1 (0.3 to 6.1)
3.8 (0.3 to 7.4)
2.9 (-0.1 to 6.0)
2.0 (-0.7 to 6.0)
3.1 (0.4 to 5.8)
2.3 (-0.3 to 5.0)
Mean %
(95%CI)
.017
.031
.035
.054
.144
.022
.084
P
Single-leg Stance
(First 5 s)
Percentage Change for SDFy Comparing Neutral to Corrected Grouped Wedge-Shoe Conditions
Table 5.17
1.6 (-2.9 to 6.2)
1.0 (-3.6 to 5.8)
2.6 (-3.1 to 8.6)
Mean %
(95%CI)
2.8 (-2.1 to 8.0)
1.3 (-3.0 to 5.7)
1.2 (-3.1 to 5.7)
1.5 (-2.8 to 6.0)
P
204
.495
.685
.376
.256
.570
.584
.504
Single-leg Stance
(Second 5 s)
5.3.6
Pre- and post-habituation walk
The main aim of the 20-min habituation walk was to evaluate the effect of prolonged
exposure to incremental mediolateral asymmetry on postural stability. A corollary was
to compare the interaction of neutral with asymmetric footwear. The results were
presented using three modelling approaches. The first asked whether there was
evidence for different scores for at least some of the seven conditions when
controlling for age, gender, BMI, and habituation (effectively the order effect). The
second model analysed whether conditions habituated differently using a conditionorder interaction. If the interaction was not significant, then one can conclude that
there was no evidence that habituation affected the simulated asymmetric conditions
differently and so only the main effects (the first model) were relevant. The third
model builds on the second but used corrected asymmetric conditions based on actual
shoe asymmetry (Table 5.9) and simulated asymmetry (1, 2 and 3 mm medial or
lateral). This used a similar process as described in 5.3.5.3.
5.3.6.1
The effect of habituation (order) only
No systematic effect was found for all dependent variables post-20 minute walk.
SDFx was largely unaffected throughout the phases. During double-leg stance all
dependent variables, except Maxdis, increased post-walk from 5.2 to 10.1% while
controlling for age, gender, BMI and order (Table 5.18). Maxdis was unaffected by
the 20 min walk (P = .973). In contrast, the only significant change during transition
is a 10.1% decrease in SDFy (P = .001). During single-leg stance (total time) SDFy,
Mvelo, Mvelox and Mveloy increased 2.5%, 6.5%, 3.3% and 9.8% respectively
(Table 5.18). Maxdis and TTSFx decreased post walk by 5.5% and 5.6% respectively.
A similar trend was observed for Maxdis, Mvelo, Mvelox and Mveloy during the
individual 5 s time periods of single-leg stance (Table 5.18), while SDFy increased
7.9% in the second 5 s time period only.
205
P
.062
.032
.973
.035
.044
Mean % (95%CI)
10.1 (-0.5 to 21.9)
9.0 (0.5 to 18.2)
-0.1 (-8.1 to 8.5)
5.2 (0.4 to 10.3)
6.2 (0.2 to 12.7)
No analysis
Double-leg Stance
-2.9 (-7.9 to 2.4)
-10.1 (-13.6 to -6.5)
-0.5 (-6.8 to 6.1)
-2.2 (-7.3 to 3.2)
-2.7 (-8.4 to 3.4)
-2.2 (-7.1 to 3.0)
Mean % (95%CI)
Transition
.280
.001
.872
.424
.380
.397
P
-1.2 (-3.9 to 1.5)
2.5 (0.0 to 5.1)
-5.5 (-9.0 to -1.9)
6.5 (4.0 to 9.1)
3.3 (0.6 to 6.1)
9.8 (7.0 to 12.7)
-5.6 (-11.8 to 0.9)
No analysis
Mean % (95%CI)
P
.378
.054
.003
.001
.017
.001
.092
Single-leg Stance
(Total time)
-1.6 (-4.7 to 1.7)
1.4 (-1.3 to 4.1)
-5.3 (-9.1 to -1.3)
6.4 (3.6 to 9.2)
2.3 (-0.8 to 5.4)
11.1 (8.0 to 14.2)
Mean % (95%CI)
P
.351
.319
.010
.001
.141
.001
Single-leg Stance
(First 5 s)
0.4 (-3.6 to 4.6)
7.9 (3.5 to 12.5)
No analysis
6.6 (3.1 to 10.3)
4.1 (0.3 to 7.9)
8.9 (5.1 to 12.9)
Mean % (95%CI)
P
.001
.032
.001
.836
.001
Single-leg Stance
(Second 5 s)
206
SDFx and SDFy: standard deviation of GRF in anterioposterior (x) and mediolateral (y) directions; Maxdis: maximum displacement; Mvelo: Mean velocity overall and in
anterioposterior (x) and mediolateral directions (y); TTS: Time to stabilization of GRF in anterioposterior (Fx) and mediolateral (Fy) directions
SDFx
SDFy
Maxdis
Mvelo
Mvelox
Mveloy
TTSFx
TTSFy
DependentVariable
Percentage Change for Dependent Variables Comparing All Conditions Pre- to Post-Walk Postural Stability
Table 5.18
5.3.6.2
The effect of the simulated asymmetric wedge-shoe condition on
pre- and post- habituation walk
While controlling for age, gender, BMI, order and correcting for multiple
comparisons significant interactions were found for SDFy (P = 0.036), Maxdis (P =
.048), Mvelo (P = 0.009), Mvelox (P = 0.007) and Mveloy (P = .025) during the
second 5 s of single leg stance. Further analysis for these variables was then
performed. Results are also illustrated for these dependent variables during doubleand single-leg stance for comparative purposes (Tables 5.19 and 5.20). Since no
significant interactions were found for the dependent variables during transition and
first 5 s of single leg stance, no further analysis was performed.
Although maximum displacement during double-leg stance reached significance,
detailed analysis of each asymmetric condition shows them to be highly variable and
non-systematic (Table 5.19). Increases of 18.4% and 28.7% for the simulated 3 mm
medial asymmetry (P = .120) and shoe only (P = .021) conditions suggest impaired
postural stability performance while a 19.2% decrease for the simulated 3 mm lateral
asymmetry (P = .051) would imply an improvement in postural stability for this
condition. In comparison, overall the 20 min walk had no effect on Maxdis (Table
5.18). The individual analysis of Maxdis for the second 5 s of single-leg stance (P =
.267) is provided for comparative purposes only (Table 5.19). Although results were
non-significant, changes were more systematic with increasing asymmetry. Similar
non-systematic results occurred for other postural stability measures that include
increases in the shoe only condition of 40.9% in SDFy, 15.4% in Mvelo and 15.6% in
the 3mm medial condition for Mvelo (Table 5.20).
207
Table 5.19
Percentage Change for Maxdis in Shoe and Simulated Asymmetric Shoe
Conditions During Double- and Second 5 s of Single-Leg Stance Post-Walk
Double-leg Stance
Simulated
asymmetric
condition
3 mm med
2 mm med
1 mm med
Shoe only
1 mm lat
2 mm lat
3 mm lat
Mean % (95%CI)
18.4 (-4.3 to 46.6)
-7.5 (-25.3 to 14.6)
-3.1 (-21.7 to 20.0)
28.7 (4.0 to 59.3)
-4.5 (-22.3 to 17.5)
-5.9 (-24.0 to 16.5)
-19.2 (-34.7 to 0.1)
Single-leg Stance
(Second 5 s)
P
.120
.476
.773
.021
.665
.575
.051
Mean % (95%CI)
8.9 (-2.4 to 21.4)
10.0 (-1.4 to 22.6)
-2.2 (-12.3 to 9.0)
-6.7 (-16.4 to 4.0)
3.0 (-7.4 to 14.4)
9.6 (-1.8 to 22.2)
4.2 (-6.5 to 16.2)
P
.126
.088
.686
.211
.587
.101
.456
Maxdis: maximum displacement
During single-leg stance (total time) a trend occurred, as shown in the percentage
change for Mvelo, Mvelox and Mveloy, while there were non-systematic changes in
SDFy. As the asymmetry increased medially from 1 to 2 to 3 mm, mean velocity
increased 5.7%, 9.3% and 11.7% (Table 5.20). The increase in mean velocity laterally
for similar wedging was 6.1%, 8.5% and 6.1%. Compared to double-leg stance
postural stability was unaffected in the participants’ shoe only condition. The
participants’ own habituated shoe condition included 41.5% of neutral shoes.
During the second 5 s of single-leg stance, there was a trend towards increased values
for SDFy, Maxdis and Mvelo compared to the shoe only condition which remained
largely unchanged following the 20 min walk. This effect was more marked with the
1, 2 and 3 mm simulated medial than the lateral asymmetry (Table 5.20). For
example, SDFy increased 10.3%, 14.6% and 20.9% which paralleled the increase in
simulated medial asymmetry from 1 to 3 mm. A similar increase was observed for
Mvelo with values of 6.4%, 13.3% and 19.2% concomitant with the increase in
simulated medial asymmetry. This pattern was mirrored in the individual mean
velocity anterioposterior and mediolateral directions.
208
Mean velocity
3 mm medial
2 mm medial
1 mm medial
Shoe
1 mm lateral
2 mm lateral
3 mm lateral
SDFy (mediolateral GRF)
3 mm medial
2 mm medial
1 mm medial
Shoe
1 mm lateral
2 mm lateral
3 mm lateral
Simulated asymmetric condition for
dependent variables
15.4 (1.9 to 30.7)
-1.2 (-12.7 to 11.9)
7.6 (-5.0 to 21.8)
15.6 (2.1 to 31.0)
2.4 (-9.3 to 15.5)
2.7 (-9.3 to 16.3)
-4.1 (-15.4 to 8.6)
-6.0 (-24.0 to 16.3)
4.1 (-15.8 to 28.7)
5.2 (-14.9 to 30.2)
40.9 (14.0 to 74.3)
20.5 (-1.9 to 48.1)
4.3 (-15.7 to 28.9)
-0.6 (-19.7 to 22.9)
Mean % (95%CI)
Double-leg Stance
.024
.853
.251
.022
.702
.675
.506
.561
.711
.638
.002
.075
.781
.952
P
11.7 (4.8 to 19.0)
9.3 (2.5 to 16.5)
5.7 (-0.8 to 12.7)
-1.3 (-7.4 to 5.2)
6.1 (-0.3 to 12.9)
8.5 (1.8 to 15.7)
6.1 (-0.5 to 13.1)
3.6 (-3.0 to 10.7)
2.9 (-3.8 to 9.9)
6.6 (-0.3 to 13.9)
-3.6 (-9.8 to 3.0)
5.5 (-1.0 to 12.5)
3.7 (-2.9 to 10.8)
-1.0 (-7.4 to 5.8)
Mean % (95%CI)
Single-leg Stance
(Total time)
.001
.006
.087
.683
.060
.012
.069
.294
.406
.060
.274
.101
.280
.763
P
19.2 (9.5 to 29.7
13.3 (4.2 to 23.3)
6.4 (-2.3 to 15.7)
-5.3 (-12.9 to 3.1)
3.7 (-4.5 to 12.5)
7.4 (-1.3 to 16.9)
3.6 (-4.8 to 12.8)
20.9 (8.6 to 34.7)
14.6 (3.0 to 27.6)
10.3 (-0.9 to 22.8)
-5.2 (-14.9 to 5.5)
1.1 (-8.9 to 12.1)
11.6 (0.2 to 24.3)
4.8 (-5.9 to 16.7)
Mean % (95%CI)
Single-leg Stance
(Second 5 s)
209
.001
.004
.152
.210
.389
.097
.408
.001
.013
.074
.329
.843
.045
.394
P
Percentage Change for SDFy and Mvelo in Shoe-Only and Simulated Asymmetric Shoe Conditions During Double- and Single-Leg Stance
(Total Time and Second 5 s) Post-Walk
Table 5.20
19.9 (2.7 to 39.9)
-3.9 (-17.6 to 12.2)
9.9 (-5.9 to 28.2)
21.1 (3.7 to 41.3)
2.2 (-12.0 to 18.7)
2.0 (-12.6 to 19.0)
-4.1 (-17.8 to 11.9)
3.6 (-3.4 to 11.1)
3.2 (-3.8 to 10.7)
2.5 (-4.4 to 9.9)
1.1 (-5.7 to 8.5)
1.2 (-5.4 to 8.3)
2.1 (-4.8 to 9.5)
-1.5 (-8.1 to 5.7)
Mean velocity y (mediolateral)
3 mm medial
2 mm medial
1 mm medial
Shoe
1 mm lateral
2 mm lateral
3 mm lateral
Mean % (95%CI)
Double-leg Stance
Mean velocity x (anterioposterior)
3 mm medial
2 mm medial
1 mm medial
Shoe
1 mm lateral
2 mm lateral
3 mm lateral
dependent variables
.327
.376
.489
.755
.728
.558
.678
.021
.618
.232
.015
.773
.802
.594
P
14.5 (7.0 to 22.7)
13.1 (5.7 to 21.1)
11.4 (4.1 to 19.3)
0.4 (-6.2 to 7.5)
10.8 (3.7 to 18.4)
10.6 (3.3 to 18.4)
8.4 (1.2 to 16.1)
9.4 (2.0 to 17.3)
5.4 (-1.8 to 13.0)
1.1 (-5.7 to 8.5)
-3.9 (-10.5 to 3.0)
1.3 (-5.4 to 8.4)
6.6 (-0.7 to 14.3)
4.0 (-3.0 to 11.6)
Mean % (95%CI)
Single-leg Stance
(Total time)
.001
.001
.002
.911
.002
.004
.021
.012
.145
.758
.260
.718
.076
.269
P
20.0 (9.5 to 31.7)
14.4 (4.3 to 25.5)
12.1 (2.2 to 22.9)
-4.8 (-13.2 to 4.4)
6.2 (-2.9 to 16.2)
9.9 (0.2 to 20.6)
6.4 (-2.9 to 16.7)
19.1 (8.6 to 30.6)
11.7 (1.9 to 22.5)
1.8 (-7.2 to 11.6)
-7.0 (-15.2 to 2.0)
0.8 (-7.8 to 10.2)
4.2 (-5.0 to 14.3)
0.2 (-8.7 to 9.8)
Mean % (95%CI)
Single-leg Stance
(Second 5 s)
210
.001
.004
.016
.296
.186
.044
.185
.001
.018
.707
.124
.860
.383
.973
P
5.3.6.3
The effect of the seven corrected simulated asymmetric wedgeshoe conditions on pre- and post- habituation walk
The third level of analysis combined experimental simulated asymmetric conditions
(1, 2 and 3 mm medial or lateral) with measured shoe asymmetry to produce eleven
corrected wedge-shoe conditions form 1 to 8 mm medial, neutral and 1 to 3 mm
lateral. As the numbers in each category were skewed, grouping was necessary (Table
5.21). Two groups (seven and four conditions) of corrected asymmetric conditions
were analysed.
Table 5.21
Corrected Wedge-Shoe Conditions for Pre- and Post-Walk
Condition (Wedge - shoe wear)
8 mm medial
6 medial
5 medial
4 medial
3 medial
2 medial
1 medial
Neutral
1 lateral
2 lateral
3 lateral
Trials (n = 636)
6
6
6
48
114
66
90
156
78
54
12
Trials (n =636)
Trials (n = 636)
66
180
114
66
90
156
78
66
156
156
144
While controlling for age, gender, BMI, and order similar significant interactions as
for the non-corrected wedge-shoe conditions were found. No significant interactions
were found for any dependent variable during double-leg stance and transition.
Exploratory analysis of SDFy (P = .180) and Maxdis (P = .195) during double-leg
stance indicated non-significant results and hence are not reported. Further detailed
analysis for dependent variables SDFy (P = .136), Mvelo (P = .050), Mvelox (P =
.010) and Mveloy (P = .042) during single-leg stance is presented (Table 5.22).
211
Table 5.22
Percentage Change for SDFy and Mvelo in Seven Corrected Shoe Conditions
During Total Time and Second 5 s of Single-Leg Stance Post-Walk (% increase =
positive)
Simulated asymmetric
condition for
dependent variables
Single-leg Stance
(Total time)
Single-leg Stance
(Second 5 s)
Mean % (95%CI)
P
Mean % (95%CI)
P
SDFy
4 to 8 mm medial
3 mm medial
2 mm medial
1 mm medial
Neutral
1 mm lateral
2 to 3 mm lateral
4.5 (-0.5 to 5.9)
2.0 (-4.0 to 8.4)
5.6 (-2.4 to 14.4)
1.4 (-5.3 to 8.5)
0.6 (-4.4 to 6.0)
1.3 (-5.8 to 9.0)
5.7 (-2.4 to 14.4)
.276
.515
.174
.699
.812
.720
.173
11.1 (-2.3 to 26.2)
18.6 (7.7 to 30.7)
9.3 (-3.8 to 24.2)
4.6 (-6.2 to 16.7)
-0.04 (-8.3 to 8.3)
3.3 (-8.1 to 16.2)
16.7 (2.7 to 32.6)
.107
.001
.171
.420
.932
.586
.018
Mean velocity
4 to 8 mm medial
3 mm medial
2 mm medial
1 mm medial
Neutral
1 mm lateral
2 to 3 mm lateral
8.3 (0.5 to 16.8)
9.0 (2.9 to 15.4)
9.8 (1.8 to 18.5)
3.6 (-2.9 to 10.5)
2.4 (-2.5 to 7.6)
6.7 (-0.5 to 14.4)
10.9 (2.9 to 19.6)
.038
.003
.015
.289
.338
.068
.007
12.5 (1.8 to 24.5)
15.8 (7.3 to 25.1)
7.2 (-3.1 to 18.5)
3.5 (-5.0 to 12.8)
-0.8 (-7.0 to 6.0)
2.4 (-6.6 to 12.3)
12.7 (1.9 to 24.6)
.021
.001
.177
.431
.820
.613
.020
Mean velocity x
4 to 8 mm medial
6.4 (-2.0 to 15.5)
.140
16.7 (4.7 to 30.0)
.005
3 mm medial
7.0 (0.5 to 13.9)
.034
13.6 (4.6 to 23.3)
.002
2 mm medial
6.8 (-1.7 to 15.9)
.118
1.9 (-8.5 to 13.6)
.727
1 mm medial
0.5 (-6.4 to 7.8)
.901
1.3 (-7.7 to 11.1)
.786
Neutral
-1.1(-6.3 to 4.3)
.676
-3.2 (-9.7 to 3.9)
.369
1 mm lateral
0.4 (-6.9 to 8.3)
.910
-4.0 (-13.1 to 6.0)
.416
2 to 3 mm lateral
8.7 (0.1 to 18.0)
.047
10.4 (-0.9 to 23.0)
.073
Mean velocity y
4 to 8 mm medial
10.3 (1.7 to 19.7)
.019
8.9 (-2.4 to 21.6)
.128
3 mm medial
11.8 (5.0 to 18.9)
.001
18.8 (9.2 to 29.2)
.001
2 mm medial
13.8 (4.9 to 23.5)
.002
12.8 (1.1 to 26.0)
.032
1 mm medial
6.9 (-0.3 to 14.6)
.062
6.4 (-3.2 to 16.9)
.199
Neutral
4.6 (-1.2 to 11.4)
.064
1.1 (-5.9 to 8.6)
.773
1 mm lateral
12.7 (4.5 to 21.5)
.002
7.2 (-3.2 to 18.6)
.181
2 to 3 mm lateral
12.9 (4.1 to 22.6)
.003
13.8 (1.9 to 27.0)
.022
SDFy: standard deviation of GRF in mediolateral (y) direction; Mvelo: Mean velocity overall and in
anterioposterior (x) and mediolateral directions (y).
212
Trends with increasing changes away from the neutral condition appeared for SDFy,
Mvelo, Mvelox and Mveloy during total time and the second 5 s of single-leg stance.
These results mirror the pattern reported without the corrected wedge-shoe conditions
(Table 5.20).
The results from the corrected neutral and non-corrected (41.5% neutral) shoe on
postural stability measures are presented together in Table 5.23. Analysis did not
include comparing performance in the two shoe conditions. During double-leg stance
both shoe conditions indicated a poorer performance immediately after walking for 20
min. In contrast, postural stability performance during single-leg stance was largely
unaffected post-walk for both shoe conditions.
213
9.6 (-5.5 to 27.2)
18.1 (-2.9 to 43.6)
30.8 (4.3 to 64.0)
40.9 (14.0 to 74.3)
8.6 ( -7.9 to 28.1)
28.7 (4.0 to 59.3)
9.8 (-0.2 to 20.8)
15.6 (2.1 to 31.0)
11.2 (-12.5 to 25.2)
21.1 (3.7 to 41.3)
No analysis
1.1 (-5.7 to 8.5)
SDFy
Neutral shoe
Non-corrected shoe
Maximum displacement
Neutral shoe
Non-corrected shoe
Mean velocity
Neutral
Non-corrected shoe
Mean velocity x
Neutral
Non-corrected shoe
Mean velocity y
Neutral
Non-corrected shoe
Mean % (95%CI)
Double-leg Stance
SDFx
Neutral shoe
Non-corrected shoe
Dependent variable
.755
.015
.082
.022
.055
.021
.327
.002
.002
.225
.095
P
0.4 (-6.2 to 7.5)
4.6 (-1.2 to 11.4)
-3.9 (-10.5 to 3.0)
-1.1(-6.3 to 4.3)
-1.3 (-7.4 to 5.2)
2.4 (-2.5 to 7.6)
-10.7 (-19.1 to -1.3)
-7.4 (-14.1 to -0.2)
-3.6 (-9.8 to 3.0)
0.6 (-4.4 to 6.0)
1.6 (-1.4 to 4.0)
-4.3 (-11.2 to 3.1)
Mean % (95%CI)
Single-leg Stance
.911
.064
.064
.260
.676
.683
.338
.046
.027
.274
.812
.191
.244
P
-4.8 (-13.2 to 4.4)
1.1 (-5.9 to 8.6)
-7.0 (-15.2 to 2.0)
-3.2 (-9.7 to 3.9)
-5.3 (-12.9 to 3.1)
-0.8 (-7.0 to 6.0)
-6.7 (-16.4 to 4.0)
2.8 (-5.3 to 11.7)
-5.2 (-14.9 to 5.5)
-0.04 (-8.3 to 8.3)
-2.8 (-10.3 to 5.4)
-6.4 (-16.0 to 4.3)
Mean % (95%CI)
214
.296
.773
.124
.369
.210
.820
.211
.505
.329
.932
.486
.231
P
Single-leg Stance (Second 5 s)
Percentage Change for Dependent Variables in Neutral and Non-Corrected Shoe Conditions During Double- and Single-Leg Stance (Total
Time and the Second 5 s) Post-Walk.
Table 5.23
5.3.6.4
The effect of the four corrected simulated asymmetric wedge-shoe
conditions on pre- and post- habituation walk
A further analysis of four conditions (Table 5.21), where numbers in each group were
almost equal, was performed. No significant interactions were found during doubleleg stance, transition and single-leg stance (total time and first 5 s). Postural stability
was progressively affected by increasing asymmetry from the true neutral shoe
condition during the second 5 s of single-leg stance (Table 5.24). Detailed analysis is
reported for SDFy (P = .074), Mvelo (P = .016), Mvelox (P = .004) and Mveloy (P =
.076). For the corrected neutral shoe condition no statistical difference emerged post
20 min walk. On either side of neutral there was a trend towards an increase in the
variables calculated.
Table 5.24
Percentage Change for SDFy and Mvelo in Four Corrected Shoe Conditions
During the Second 5 s Single-Leg Stance Post-Walk.
dependent variables
Single-leg Stance
(Second 5 s)
Mean % (95%CI)
P
15.8 (7.2 to 25.1)
6.6 (-1.9 to 15.8)
-0.4 (-8.3 to 8.3)
9.2 (0.2 to 19.1)
.001
.133
.932
.044
3 to 8 mm medial
1 to 2 mm medial
Neutral
1 to 3 mm lateral
14.6 (7.9 to 21.8)
5.1 (-1.6 to 12.1)
-0.8 (-7.0 to 5.9)
7.0 (0.0 to 14.5)
.001
.138
.820
.051
Mean velocity x
3 to 8 mm medial
1 to 2 mm medial
Neutral
1 to 3 mm lateral
14.7 (7.4 to 22.5)
1.6 (-5.3 to 9.0)
-3.2 (-9.8 to 3.9)
2.3 (-4.9 to 10.1)
.001
.665
.370
.540
Mean velocity y
3 to 8 mm medial
1 to 2 mm medial
Neutral
1 to 3 mm lateral
15.1 (7.6 to 23.0)
9.1 (1.5 to 17.2)
1.1 (-5.9 to 8.6)
10.1 (2.2 to 18.7)
.001
.018
.773
.011
SDFy
3 to 8 mm medial
1 to 2 mm medial
Neutral
1 to 3 mm lateral
Mean velocity
215
5.3.7
Summary of Key Findings
The findings from this study support footwear results from Study 1 but extend the
conceptual asymmetric model into barefoot and footwear postural stability
performance. The important findings are summarized here and in Table 5.25.
•
In 212 well-worn shoes, the frequency of heel asymmetry was biased laterally
(57.6%) compared to medially (0.9%).
•
Midsole compression asymmetry of 10 or more Asker C units was 21.7% of
shoes, and 0.9% of these, had medial compression.
•
Midsoles with hardness of Asker C 70 units or greater showed no signs of
collapse or compression.
•
In 88.9% of shoes with medially biased orthotics shoes, lateral asymmetry
measured between 1 and 5 mm.
•
Time to stabilization was 11.9% and 3.5% quicker barefoot than in footwear,
but other postural stability measures were either unchanged or greater barefoot
compared to footwear.
•
Barefoot and footwear mediolateral stability performance was 20.2/6.1% and
7.1/13.1% worse during transition and single-leg stance respectively, in
participants who had asymmetrically worn footwear. Other postural stability
variables were unchanged.
•
Increasing the amount of simulated asymmetry compared to neutral
progressively and systematically reduced participants’ postural stability
performances for SDFy, Maxdis and Mvelo after the 20 min walk.
•
The 20 min walk had a variable or no effect on participants’ postural stability
performance during the phases of the task.
•
The 20 min walk enhanced the destabilizing effect on postural stability of
simulated medial and lateral asymmetry compared to the non-walk period.
•
Postural stability during single-leg stance after a 20-minute walk was unaffected
when participants wore their own or corrected neutral shoes.
216
No significant effects
H4 and H5
Simulated asymmetry
With(out) order
H4 and H5 not supported
H4 and H5
Corrected wedge-shoe
asymmetry
H4 and H5 partial support
by SDFy
Double-leg
SDFx (*9.4%)
SDFy (*12.2%)
H3
Asymmetric footwear and
barefoot or shoe
H3 supported by SDFy
H2
Barefoot versus Shoe
H2 supported by TTSFx,
TTSFy and Maxdis only
Hypotheses and
Independent Variables
Comparison between 3 and 2,
3 and 1 mm lateral:
Maxdis (5.9%, *7.1%)
Mvelox (5.0%, *8.3%)
SDFy (*2.6%,*3.6%,
2.4% and *4.2%) with
increased medial and
(*3.4%,* 2.7% and
*4.1%) lateral
asymmetry
SDFy (7.1 %) barefoot
SDFy (*13.1%) shoe
SLS Total Time
SDFx (*13.1%)
SDFy (*7.3%)
Maxdis (*14.0%)
Mvelo (*12.8%)
Mvelox (*15.7%)
Mveloy (*9.9%)
TTSFx (*-11.9%)
TTSFy (*-3.5%)
Phase of Dynamic Task
SDFy (*20.2%) barefoot
SDFy (6.1%) shoe
Transition
SDFx (*13.8%)
Maxdis (*25.9%)
Mvelo (*16.5%)
Mvelox (*20.9%)
Summary of Changes to Postural Stability Measures (*P < .05)
Table 5.25
SDFy (2.3 %, *3.1%,
2.0% and *2.9%) with
increased medial and
(*3.3%, *3.1% and
*3.8%) lateral
asymmetry
SDFy (7.5%) barefoot
SDFy (*13.0%) shoe
SLS First 5 s
SDFx (*16.5%)
SDFy (*6.9%)
Maxdis (*16.0%)
Mvelo (*15.7%)
Mvelox (*20.0%)
Mveloy (*10.5%)
217
SDFy (1.1%) barefoot
SDFy (9.8%) shoe
SLS Second 5 s
SDFx (*5.0%)
SDFy (*8.6%)
Maxdis (*-6.5%)
Mvelo (*8.9%)
Mvelox (*10.0%,)
Mveloy (*8.4%)
H4, H5 and H6 supported by
SDFy and Mvelo
H4, H5 and H6
20 min Walk habituation
and simulated asymmetry
(1, 2, 3 mm medial and
lateral)
H6
20 min Walk habituation (all
shoe conditions)
H6 partial support
Hypotheses and
except
SDFy (*40.9%) shoe
Maxdis (28.7%) shoe
(-19.2%) 3 mm lateral
Mvelo (*15.6%) shoe
Mvelox (*21.1%) shoe
Double-leg
SDFx (10.1%)
SDFy (*9.0%)
Mvelo (*5.2%)
Mvelox (*6.2%)
Transition
No significant effect except
SDFy (*-10.1%)
Mvelo (5.7%, *9.3%,
and *11.7%), Mvelox
(1.1%, 5.4% and *9.4%)
and Mveloy (*11.4%,
*13.1% and *14.5%)
with increased medial
and similarly for lateral
asymmetry Mvelo (6.1%,
*8.5% and 6.1%),
Mvelox (1.3%, 6.6% and
4.0%) and Mveloy
(*10.8%, *10.6% and
*8.4%)
No change in Shoe
condition
SLS Total Time
SDFy (2.5%)
Maxdis (*-5.5%)
Mvelo (*6.5%)
Mvelox (*3.3%)
Mveloy (*9.8%)
TTSFx (-5.6%)
(trends)
SLS First 5 s
Maxdis (*-5.3%),
Mvelo (*6.4%)
Mveloy (*11.1%)
218
SdFy (10.3%, *14.6%
and *20.9%), Mvelo
(6.4%, *13.3% and
*19.2%), Mvelox
(1.8%, *11.7% and
*19.1%) and Mveloy
(*12.1%, *14.4% and
*20.0%) with increased
medial and similarly
with lateral asymmetry
SDFy (1.1%, *11.6%
and 4.8%), Mvelo
(3.7%, 7.4% and 3.6%),
Mvelox (0.8%, 4.2%
and 0.2%) and Mveloy
(6.2%, *9.9% and
6.4%)
No change in shoe
condition
SLS Second 5 s
SDFy (*7.9%)
Mvelo (*6.6%)
Mvelox (*4.1%)
Mveloy (*8.9%)
H4, H5 and H6
and 4 corrected shoesimulated asymmetry
(medial and lateral)
SDFy and Mvelo
(no change in corrected
neutral shoe)
SDFy and Mvelo
H4, H5 and H6
and 7 corrected shoesimulated asymmetry
(medial and lateral)
Hypotheses and
(trends)
Double-leg
(trends for SDFy and
Maxdis)
Transition
(trends)
SLS Total Time
Mvelo (3.6%, *9.8%,
*9.0% and *8.3%),
Mvelox (0.5%, 6.8%,
*7.0% and 6.4%) and
Mveloy (6.9%, *13.8%,
*11.8% and *10.3%)
with increased medial
and similarly with lateral
asymmetry Mvelo (6.7%
and *10.9%), Mvelox
(0.4% and *8.7%) and
Mveloy (*12.7% and
*12.9%)
No change in corrected
neutral shoe
(trends)
SLS First 5 s
(trends)
219
SdFy (6.6% and
*15.8%), Mvelo (5.1%
and *14.6%), Mvelox
(1.6% and *14.7%) and
Mveloy (*9.1% and
*15.1%) increase with
increasing medial and
similarly lateral
asymmetry SdFy
(*9.2%), Mvelo
(*14.6%), Mvelox
(2.3%) and Mveloy
(*10.1%)
SLS Second 5 s
SdFy (4.6%, 9.3%,
*18.6% and 11.1%),
Mvelo (3.5%, 7.2%,
*15.8% and *12.5%),
Mvelox (1.3%, 1.9%,
*13.6% and *16.7%)
and Mveloy (6.4%,
*12.8%, *18.8% and
8.9%) with increased
medial and similarly
with lateral asymmetry
SDFy (3.3% and
*16.7%), Mvelo (2.4%
and *12.7%), Mvelox (4.0% and 10.4%) and
Mveloy (7.2% and
*13.8%)
No change in corrected
neutral shoe
H6
Neutral and Non-corrected
shoe
H6 supported by both in
single-leg stance
Hypotheses and
Double-leg
SDFx (9.6 and *18.1%)
SDFy (*30.8 and *40.9%)
Maxdis (8.6 and *28.7%)
Mvelo (9.8 and *15.6%)
Mvelox (11.2 and* 21.1%)
Transition
No analysis
SLS Total Time
Both shoes conditions
unaffected by walk
except
Maxdis
(*-7.4% and *-10.7%)
SLS First 5 s
Both shoes conditions
unaffected by walk
220
SLS Second 5 s
Both shoe conditions
unaffected by walk
5.4
Discussion
Study 1 explored the effect of 1 mm simulated heel asymmetry on a performance
measure. Study 2 extended this conceptual model by simulating a range of typical
heel asymmetry values found in Study 1. Similar hypotheses were developed based on
the tower conceptual model and results are discussed and expanded in relation to this
idea. A summary of the hypotheses is followed by a detailed discussion about the
implications of the footwear asymmetry assessed and how this might affect COP,
GRF, lever arms, joint moments and loading. The experimental results for barefoot
compared to footwear, the effect of neutral and simulated asymmetry before and after
an extended walk are then discussed. The tower concept is discussed in relation to the
findings from this study. Methodological comments relate to the experimental design,
task and variables chosen and other limitations and strengths of the study. Possible
future research directions conclude this Chapter.
5.4.1
Hypotheses
These results confirm the hypothesis (H1) that the frequency of medial and lateral
footwear heel asymmetry in 212 frequently used shoes from 106 participants was
biased laterally. Thus H1 is accepted. Study 1 findings are thus confirmed. This
sample included 41.5% neutral and 57.6% laterally degraded shoes. Moderate heel
height (1.0 to 3.0 cm) was measured in 87.8% of shoes which might help explain
these results. An increased laterally directed rear-foot heel-strike is typical in heeled
footwear during walking (Gefen et al., 2002; Snow & Williams, 1994). Heeled
footwear also increases the chance of rear-foot heel-strike compared to barefoot (De
Wit et al., 2000; Divert et al., 2005; Lieberman et al., 2010) and in minimal footwear
(Squadrone & Gallozzi, 2009) while running. Thus, individuals walking or running in
the footwear assessed are likely to hit the ground harder (Lieberman et al., 2010) and
more laterally, degrading the heel. This is discussed in Section 5.4.2.
The second hypothesis (H2) was supported by decreased TTSFx and TTSFy and
maximum displacement during single-leg stance barefoot compared to the shoe
condition. However, the results for most postural stability measures were greater
221
barefoot, contradicting the hypothesis. The hypothesis was largely rejected. Greater
variability while barefoot has been found in other studies when compared to footwear
running (De Wit et al., 2000; Divert et al., 2005; Rodgers & Leveau, 1982) and while
assessing postural stability (Robbins et al., 1998). These apparent contradictions are
evaluated and discussed in Section 5.4.3.
A link between the current shoe condition and postural stability was confirmed for
barefoot and shoe postural stability during transition and single-leg stance. The
increase in the variability of the mediolateral GRF confirmed the hypothesis (H3) that
footwear measured with asymmetric medial or lateral heel wear will reduce barefoot
or shoe postural stability performance. This important finding may help to explain
global postural stability impairments or inter-subject variability measured in
previously injured (Wikstrom et al., 2009) and non-injured individuals (McKeon &
Hertel, 2008a; Rogers, Wardman, Lord, & Fitzpatrick, 2001; Vuillerme, Chenu et al.,
2007). The results for all other postural stability measures varied non-systematically
and changes were not significant. The hypothesis was accepted for the mediolateral
GRF during single leg stance.
The hypothesis (H4) that increased medial or lateral asymmetry would decrease
postural stability compared to the neutral state, was largely accepted and supported by
the changes in variability of the mediolateral GRF and mean velocity during singleleg stance before and after a 20 min walk. It was also supported by the unchanged
postural stability measures in the neutral shoe during single-leg stance. The nonsignificant changes to the pre-walk dependent variables by which postural stability is
inferred are discussed in section 5.4.4. The hypothesis was largely rejected for the
pre-walk period.
The results for the neutral shoe, mediolateral GRF and mean velocity during singleleg stance supported H5 which hypothesised that increasing the amount of simulated
asymmetric wear will progressively reduce postural stability performance. Trends for
maximum displacement supporting H5 were also noted. The hypothesis was largely
accepted in the medial direction.
222
The hypothesis (H6) that an extended habituation period such as walking for 20 min
in the simulated asymmetric shoe condition will further reduce postural stability
performance was accepted and supported by the differences to the percentage changes
for the variability in mediolateral GRF and mean velocity before and after a 20 min
walk. The unchanged performance after the walk in the neutral shoe condition also
supported H6.
5.4.2
Footwear Assessment
Of the 212 shoes assessed for heel asymmetry, 57.6% had lateral and 0.9% medial
wear respectively. The frequency of lateral wear was almost identical to the results
from Study 1 for 294 shoes. The most frequent lateral wear was 1 mm (30.2%)
followed by 2 mm (12.3%). Thus, the increasing asymmetric perturbations from 1 to 3
mm chosen to disturb postural stability were within the typical range of lateral wear
found in both studies. Considering that 75.5% of shoes were reported less than or
equal to 1 year old it can be concluded that the most likely initial asymmetric wear
will be 1 mm. Thereafter, progressive asymmetric shoe heel wear is possible and in
this study 15.1% had 3 to 5 mm of lateral heel wear. Compared to the previous study,
it was expected a larger cohort would introduce greater medial asymmetry, but this
was not measured. Asymmetry of wear may be influenced by the age of footwear
(22.6% older than 1 year), footwear design (15% asymmetric design, 21.7% midsoles
too soft), orthotic intervention (8.5%), frequency of use (4.6 ± 3.9 hours per day),
purpose (general exercise, type of work and sports) and the participant’s BMI (23.8 ±
3.2 kg/m²) or weight (70.6 ± 11.7 kg).
The emergence of footwear in human evolutionary history is a very recent
development (Section 2.2.2 and 3.2). Early original shoe designs, comprised of animal
or plant material, were flat, flexible and light (Ashizawa et al., 1997; Kuttruff et al.,
1998; Pinhasi et al., 2010; Stewart, 1945, 1972). These designs matched the foot
shape and width while providing protection and/or warmth. They were easily replaced
or fixed and matched the energetic lifestyle of the individuals (Liebenberg, 2006;
McDougall, 2009). Survival depended upon the ability to walk and run. Present day
mass-produced footwear includes variable thickness midsoles, heels and stability
features all thought to be protective for day-to-day activities. Of the footwear
223
assessed, only the flats and canvas shoes approximate original footwear design
features.
Heeled footwear increases the plantarflexion angle, supination at heel strike (Snow &
Williams, 1994; Stefanyshyn et al., 2000) and the moment of external inversion
compared to barefoot (Kerr et al., 2009; Stacoff, Nigg, Reinschmidt, Van den Bogert,
& Lundberg, 2000; Stacoff et al., 1996). Habitual wearers of high-heeled footwear
exhibit lateral shifts in COP barefoot and in their footwear and an imbalance of lateral
versus medial gastrocnemius activity in fatigue conditions (Gefen et al., 2002).
Increased plantarflexion (Wright et al., 2000) and external inversion moments (Kerr et
al., 2009; Stacoff et al., 1996; Tropp, Askling et al., 1985) may predispose individuals
to ankle inversion injuries. Shoes compared to barefoot increase lateral muscle
activity at the ankle during an inversion movement (Kerr et al., 2009; Ramanathan et
al., 2011). In order to maintain equilibrium, the moments of external inversion and
internal eversion must be equal (Stacoff et al., 1996). Since the muscle lever arm
remains fixed, changes to the length of the GRF lever arm with the addition of shoes
compared to barefoot, requires an increased muscular contraction to counterbalance
the shoe effect (Kerr et al., 2009; Stacoff et al., 1996). If the muscles around the ankle
or higher up the kinetic chain at the knee, hip, pelvis and trunk is unable to counteract
this moment during single-leg stance, an injury may occur (Pintsaar et al., 1996;
Tropp, Askling et al., 1985; Tropp, Odenrick et al., 1985). For example, mediolateral
trunk sway (neuromuscular work) can decrease the knee joint adduction moment
(Mündermann et al., 2008) as do local muscles around the joint (Shelburne et al.,
2006). The hip muscles play an important role in maintaining and counteracting
disturbances to dynamic postural stability (Winter, 1995) and their bilateral efficient
function may be disturbed following an ankle injury (Bullock-Saxton & Bullock,
1993; Bullock-Saxton et al., 1994).
A conceptual model of the possible effect of footwear is presented in Figure 5.10
although no direct data was measured in this study. Asymmetric wear may act in a
similar way as described by Tropp et al. (1985) for ankle inversion injuries and Kerr
et al. (2009) in unanticipated inversion
movements of the ankle in
footwear compared to barefoot. Footwear and inversion movements, increase the GRF
mediolateral lever arm (Figure 5.10). This in turn causes a cascade of neuromuscular
224
adaptations from the ankle throughout the human tower in order to maintain
equilibrium at each joint (Pintsaar et al., 1996). The ground reaction and muscular
forces are illustrated in Figure 5.10 as separate point loads in order to graphically
depict the change in length of the GRF lever arm. However, the point of application
of the GRF represents the point around which the body is rotating (Pintsaar et al.,
1996) which could be through the joint centre (Shelburne et al., 2006; Shelburne et
al., 2008). Equilibrium is achieved by the sum of all the muscular and ligament forces
around each joint throughout the human tower.
Lateral wear or compression of 1 to 5 mm was measured in footwear with prescribed
orthotics. Although orthotic devices are likely to reduce peak eversion and velocity at
the forefoot, they have been shown to increase the initial inversion angle at heel strike
leading to increased lateral heel pressure (Dixon & McNally, 2008). The medially
biased orthotics could contribute to the lateral degradation. Medial orthotics increase
(Franz et al., 2008; Schmalz et al., 2006) while lateral wedges decrease (Barrios et al.,
2009; Fisher et al., 2007; Kerrigan et al., 2002; Shelburne et al., 2008) the EKAM by
a mediolateral shift in the COP and COM, changing the magnitude of the mediolateral
GRF and hence increasing or decreasing the length of the knee medial lever arm
(Erhart et al., 2008; Jenkyn et al., 2011; Shelburne et al., 2008). Medial posting and
custom-molded orthotics increase muscle activity of most muscles of the lower leg
suggesting a destabilizing effect (Mündermann et al., 2006). If neuromuscular work
increases, then the intervention is considered sub-optimal (Mündermann et al., 2006;
Nigg, 2001; Von Tscharner et al., 2003). The conceptual model presented in Figure
5.10 explains why muscular work is likely to be increased when the foot and lower
limb is exposed to asymmetrical loading as a result of shoe degradation or shoe inserts
which are designed independent of shoe construction or mediolateral asymmetry. This
is discussed in relationship to the findings that increasing simulated asymmetry in
footwear, progressively impaired postural stability (Section 5.4.4). Thus, the
combination of the footwear assessment and experimental results suggest that lateral
wear is more likely and this will affect neuromuscular control leading to impaired
postural stability.
225
Muscle
Force (Fms)
Muscle
Force (Fmls)
Muscle
Force (Fmb)
ys
xs
yb
xb
Barefoot
Neutral Shoe
Vertical
GRF (Fgb)
Vertical
GRF (Fgs)
yls
xls
Vertical
GRF (Fls)
Posterior view of heel barefoot (b), in shoe (s) and in laterally worn shoe (ls) and
assuming vertical GRF is the same while xb, xs and xls mediolateral GRF and yb, ys and
yls evertor muscle lever arms
Moment of external inversion = Fgb.xb or Fgs.xs or Fgls.xls (GRF and lever length)
Moment of internal eversion = Fmb.yb or Fms.ys or Fmls.yls (Muscle force and lever
length)
To maintain equilibrium, moments must be equal therefore, change occurs in muscle
force/fatigue or joint loading or neuromuscular control/postural stability
Fgb.xb = Fmb.yb
Fgs.xs = Fms.ys
Fgb.xb = Fmb.yb
Figure 5.10 A conceptual model of the foot-ground interface, forces and lever
arms barefoot, in neutral footwear and laterally worn footwear adapted from
Kerr et al. (2009).
The assessment of only one shoe pair per participant may not provide a complete
picture of individual wear patterns but collectively the results are similar to the
previous study of 294 shoes. Neutral shoes (symmetrical design and/or wear)
accounted for 41.5% in this study and 37.4% in Study 1. In summary, patterns of
asymmetric wear in footwear are more likely to be laterally biased, are mostly similar
between left and right feet and include both compression of inner and midsole and
226
wear of outer sole. In sports or activities in which mediolateral stability is important,
in the young or elderly, asymmetry of footwear should be considered as a contributing
factor where global postural instability exists and for chronic injuries to the lower
limbs. In studies in which postural stability is assessed either barefoot or in
participants’ daily footwear, detailed analysis of heel asymmetry needs to be assessed
and considered a factor influencing results. This may be even more important in
prospective studies in which shoe interventions are also made.
5.4.3
Barefoot Versus Shoe
Unlike Study 1, where no comparison could be made between heel-raise
performances barefoot and in the participants’ regular footwear, Study 2 integrated
both barefoot and footwear in the experimental design (Sections 2.2.2 and 2.3). This
is important and valuable as postural stability is often assessed barefoot but may be
influenced by the current status of footwear worn (Perry et al., 2007; Robbins et al.,
1998). The idea that individuals who spend extended periods in asymmetric footwear,
which then negatively influences their balance barefoot, is a key hypothesis in this
study. This may explain previously reported global deficits (Gauffin, Tropp, &
Odenrick, 1988; Tropp et al., 1984b; Waddington & Adams, 1999) and large interindividual variability in postural stability (Rogers et al., 2001; Vuillerme, Chenu et
al., 2007).
The development and use of the time to stabilisation (TTS) as a measure immediately
following a dynamic movement has arisen because traditional postural stability
measures lacked sensitivity in detecting subtle postural control deficits in single-limb
stance (McKeon & Hertel, 2008a; Wikstrom, Tillman, & Borsa, 2005; Wikstrom,
Tillman, Smith, & Borsa, 2005). In the current study, TTSFx and TTSFy times during
single-leg stance were 11.9% and 3.5% respectively faster barefoot than in footwear,
despite increases in other postural stability measures. This suggests an improved,
more efficient performance while barefoot which supports H4 and is discussed in
Sections 2.2, 2.3, 3.1 and 3.2. Postural stability was measured in 12 physical
education students using their own non-identical athletic footwear with and without
ankle bracing (Papadopoulos et al., 2008). During two trials of 5 s of single-leg stance
with eyes-open or closed increased anterioposterior sway and sway velocity was
227
reported for the shoe and/or bracing conditions compared to barefoot (Papadopoulos
et al., 2008). Only the Maxdis and TTSFx and TTSFy results in the present study
confirm this finding.
In contrast, the finding that most postural stability measures were greater while
barefoot, indicating greater variance in postural stability, has also been found in other
studies (Robbins et al., 1992; Robbins et al., 1998; Waddington & Adams, 2004).
Robbins and colleagues manipulated the foot-ground interface with midsole materials
of different hardness (Sections 2.2.2, 2.3.4 and 3.1). Seventy-two participants of
varying ages performed three single-leg stance trials of 30 s on a force platform in
each condition (Robbins & Waked, 1997; Robbins et al., 1998). Sway velocity was
affected by age and was lowest for the hard thin interface followed by barefoot. They
conclude that “stability when barefoot was average in the young, and dismal in the
old” (Robbins et al., 1997, p 66). This increased variability barefoot can be explained
in three ways by considering barefoot as an abnormal non-habituated condition
compared to the participant’s frequently used shoes, a normal dynamic system
response and, finally, an effect of the current participants’ footwear.
Robbins et al (1998) argued that balance may be sub-optimal when humans are
barefoot on man-made surfaces such as the force platform. Natural surfaces, for
example grass possess a higher coefficient of damping and provide greater sensory
input. This would minimise larger variable postural adjustments and result in precise
control. The sensory function of the foot (Section 2.3.4) is highly developed providing
the central processor, the brain, with a map of the foot-ground interface (BernardDemanze, Vuillerme, Ferry, & Berger, 2009; Chen et al., 1995; Eils et al., 2004;
Inglis et al., 2002; Perry et al., 2001; Robbins et al., 1993). This has selective
evolutionary adaptive value important for efficient gait (Sections 2.2.2 and 3.2).
Barefoot runners automatically recalibrate the way the foot meets the ground using
mid- to fore-foot ground-contact minimizing impact transients and effectively
translating foot-spring arch energy into efficient movement (Ker et al., 1987;
Lieberman et al., 2010; Morio, Lake, Gueguen, Rao, & Baly, 2009). Changing
footwear sensation with footwear or inserts affects variability (Kurz & Stergiou,
2003), proprioception (Robbins et al., 1995; Waddington & Adams, 2003), postural
stability (Maki & McIlroy, 2006; Menant, Steele, Menz, Munro, & Lord, 2008b) and
228
gait quality (Lieberman et al., 2010; Nurse et al., 2005; Robbins et al., 1989). Another
contributing factor to the increased variability barefoot may be the amount of time
participants spend barefoot in functional activities. Should individuals habitually wear
shoes, postural stability assessment barefoot is then an abnormal state (Section 3.2)
and would require an extended habituation period in order to make any useful
comparisons (D'Aout et al., 2009; Lieberman et al., 2010; Squadrone & Gallozzi,
2009). The amount of time spent barefoot by each participant was not investigated.
The second explanation considers dynamical systems theory. Conversely, the paradox
here is that efficient biological dynamical systems should have greater biological
variability thus decreasing joint loading and improving movement plasticity (Davids
et al., 2003; Hamill et al., 1999).The human body and ground interface is analysed
using non-linear dynamics. Increased variability in postural stability measures may
not always be associated with performance deficits or pathology (Davids et al., 2003;
Hamill et al., 1999; van Emmerik & van Wegen, 2002). It is argued that increased
performance variability has a functional role which decreases loading of joints and
allows the human dynamical system to produce a variety of solutions to complex
tasks which offers flexibility during unpredictability (Sections 2.2.2, 2.3, 3.1 and 3.2).
The shoe interface may decrease these options (Kurz & Stergiou, 2003; Lieberman et
al., 2010; Morio et al., 2009) so that the human body is less able to adapt. An example
is the shift between fore- and rear-foot strike running patterns caused by footwear
(Lieberman et al., 2010). While in footwear, postural adaptations are more restrictive
leading to a loss of complexity and variability. Hypoesthesia of 32 participants’ feet
decreased the COP area during double-leg stance without vision, opposite to what was
expected (McKeon & Hertel, 2007). Postural stability was unaffected during singleleg stance with or without vision. This change was explained as a decrease in
exploratory postural movement as a result of decreased sensation, rather than an
improvement in postural stability. Traditional assessments focus on the amount, for
example maximum displacement, rather than the types of postural sway occurring and
may lead to erroneous conclusions about individual’s postural stability (van Emmerik
& van Wegen, 2002). Data exploration in terms of frequencies and shape of COP
variability, the role of stability boundaries and the limits of the base of support
(Laughton et al., 2003; Rougier, 2008; van Emmerik & van Wegen, 2002) was
beyond the scope of this study but is a focus for future analysis.
229
From these results it is clear that the shoe-ground interface has an effect on postural
stability measures, but it is not possible to conclude that increased values barefoot
compared to shoe only, indicate decreased postural stability. The increased variability
barefoot may be evidence of a well-functioning dynamical system which is resilient to
perturbation. These findings are important for any studies analysing postural stability
as a result of injury using barefoot and/or footwear in the foot-ground interface. It
should also be noted that barefoot was always performed first (non-randomized) and
hence an element of learning in the shoe condition cannot be excluded from these
results. However, from analysis done in the shoe and wedge conditions an average
improvement in performance was 1.2% over the 7 conditions and trials, substantially
less than the differences between barefoot and shoe performances.
A third way of interpreting the observed increased variability barefoot is considering
the current asymmetric status of participant’s footwear (Sections 2.5, 2.6, 3.2 and
3.4). The influence of asymmetric compared to neutral footwear worn by the
participants was significant for the variability of the mediolateral GRF. Those
participants whose footwear was measured as asymmetric had increased variability
both barefoot and in shoes. This suggests that asymmetrically worn footwear may
negatively affect postural stability either through local foot and lower limb or global
CNS effects. It is known that even in healthy uninjured participants there is significant
inter-subject variability in postural stability measures and those who perform worst,
improve the most with added sensory cues (Rogers et al., 2001; Vuillerme, Chenu et
al., 2007). It is suggested that there may be a global sensorimotor deficit in those
participants (Rogers, Wardman, Lord, & Fitzpatrick, 2001). Postural control is
impaired after acute lateral ankle sprain, with deficits identified in both injured and
uninjured sides (Evans, Hertel, & Sebastianelli, 2004; Hertel & Olmsted-Kramer,
2007; McKeon & Hertel, 2008a; Tropp et al., 1984a). Some explanations for this have
included the existence of previous injury such as ankle inversion sprains but how this
causes the non-injured leg to be affected is not clear (Tropp, 1986; Tropp & Odenrick,
1988; Waddington & Adams, 1999). One argument is that the injury on one leg
causes the deterioration of the central motor program and hence a poorer output is
adopted for both legs. The alternative view is that there is already a pre-existing
global deficit which pre-dates any injury and may be found in poorer performance
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(Goldie et al., 1994; Waddington & Adams, 1999). Asymmetric footwear may help
explain this pre-existing global neuromuscular impairment theory.
Participants in this study who wore asymmetric footwear had 20.2% and 13.1%
poorer mediolateral balance during transition and single-leg stance. This indicates a
plausible link between footwear condition and global postural stability untainted by
recent injury. This potential link has not been previously described. Predicting the
length of time needed in asymmetric footwear to impair postural stability would
require a prospective study. However, the 20 min walk habituation period was an
attempt to simulate the effect of prolonged footwear asymmetry exposure on global
postural stability. These results indicate up to 20.9% decreased mediolateral stability
during single leg stance. This global deficit may predispose individuals to impaired
performance, injury or may also be associated with falls in the elderly. In Study 1 the
rate the heel-raises were performed in the barefoot neutral state was affected by shoe
condition and simulated 1 mm of lateral wear. Performance was better where the
overall shoe condition was neutral. Heel-raise performance was immediately affected
by the simulated 1 mm lateral asymmetry so it is possible that postural stability will
begin to deteriorate as soon as the individual’s shoe wears asymmetrically.
Conversely, wearing a neutral shoe will lead to recovery in stability as evidenced by
the improvement in performance once the simulated wear was withdrawn in Study 1.
The effect on postural stability in double-leg stance of the neutral versus noncorrected shoe immediately after the 20 minute walk indicated differences in
performance. Further evidence is provided by the postural stability in both the neutral
and non-corrected shoes which was better than the simulated asymmetric conditions
for all other phases of the task.
In a study of 127 soccer players, those with reduced postural stability, a global
deficit, not linked to previous injury, had a significantly higher risk of sustaining an
ankle injury in the following season (Tropp et al., 1984b). Decreased postural stability
has also been linked to ankle inversion injuries in prospective studies of 159 women
and 241 men (Willems, Witvrouw, Delbaere, Mahieu et al., 2005; Willems,
Witvrouw, Delbaere, Philippaerts et al., 2005). A similar association has been
demonstrated for a single-leg balance test and ankle injury (Trojian & McKeag,
2006). While in a prospective study of 100 over 60 year olds, control of lateral
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stability was found to be the best predictor of future risk of falling (Maki et al., 1994)
and is considered a major problem for postural stability in the elderly (Maki et al.,
2008; Maki & McIlroy, 1996). Thus, combining the results from Study 1 and Study 2,
it is possible to conclude that individuals, who wear asymmetrically worn footwear,
may have a global balance deficit and be susceptible to lateral ankle inversion injuries
or falls in the elderly.
5.4.4
The Effect of Increasing Heel Asymmetry on Postural Stability
Performance (Non-Walk Period)
The primary findings of this study show that increasing medial or lateral heel
asymmetry experimentally decreases postural stability as measured by changes in the
variability in the mediolateral GRF during single-leg stance. This result is based on
the combined asymmetry of measured and simulated shoe wear. In this case the
stepwise increase medially is 1, 2, 3 and a composite group of 4 to 8 mm, while
laterally the increase in asymmetry is 1, 2 and a composite group of 3 and 4 mm.
SDFY increased 2.6%, 3.5%, 2.4% and 4.2% and 3.4%, 2.7% and 4.1% with
increasing medial and lateral asymmetry respectively. No significant changes occur
during other phases of the dynamic task and other postural stability variables vary
non-systematically. There is also evidence of some non-significant trends between
increased simulated asymmetry and progressively reduced postural stability
performance during the transition phase. These findings cannot be directly compared
with previous studies since this may be the first study to examine the effect of small
asymmetric perturbations at the foot on postural stability using a force platform
during a transition from double- to single-leg stance. Mean velocity was the most
sensitive variable used to compare single-leg postural stability in 99 patients with
chronic low back pain and 61 healthy uninjured individuals (Luoto et al., 1998).
Assessment was performed prior to a rehabilitation programme and at its conclusion.
Patients with severe low back pain had impaired single-leg postural stability.
Following the rehabilitation program, individuals whose back disability was
unchanged or worse, had matching decreases in stability (Luoto et al., 1998). The
authors conclude that the impairment in neuromuscular co-ordination and strength
between the limb, pelvis and spine easily disturbs postural stability.
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Studies that examine postural stability by changing footwear conditions often use
large differences between conditions. Impaired postural stability, inferred from
increases in a range of force platform derived measures, has been clearly established
using unstable MBT versus control shoes (Nigg, Hintzen et al., 2006), soft thick
versus thin hard midsoles (Robbins & Waked, 1997; Robbins et al., 1998) and foam
versus bare platform with or without vision (Vuillerme, Danion et al., 2001). Where
the distinction between conditions is less clear-cut, postural control differences using
the force platform may not be measured in the absence of challenging specific tasks
and environmental conditions (Riemann, 2002; Riemann et al., 2002). No differences
in double-leg static postural stability, using a 4 week habituation period, were
measured in 37 healthy women (51.1 ± 5.8 years) (Wilson, Rome, Hodgson, & Ball,
2008). They were provided with identical new footwear and four texured foot orthotic
conditions: control, grid, dimple and plain with n ≤ 10 in each condition. Similarly, 15
participants with a unilateral ankle injury showed no differences in COP sway length
and velocity during single-leg stance (Hertel, Denegar, Buckley, Sharkey, & Stokes,
2001). Three trials of 5 s were repeated three times over 4 weeks. The six conditions
randomly tested were their own shoes, molded Aquaplast orthotic, lateral heel wedge,
7° medially posted orthotic, 4° laterally posted orthotic and neutral orthotic.
Irrespective of condition, postural stability improved in the three test sessions over the
4 weeks in both the injured and un-injured limb, indicating both learning and healing
effects. Both studies excluded a comparison with barefoot and details of the
participants’ own shoes are not provided in the second study (Hertel et al., 2001).
Surprisingly, traditional postural stability measures appear to be resistant to change in
the short-term despite relatively large destabilizing asymmetric interventions at the
foot. It is probable that the CNS senses changes and simply re-adapts or recalibrates
neuromuscular co-ordination to maintain homeostasis in healthy functioning
individuals. In terms of the human tower concept, extra work will need to be done by
the musculature to maintain vertical orientation. Ideally EMG measurement of the
back and lower limb muscle activity could verify if in fact changes took place in the
simulated conditions. Evidence for changes in muscular activity following a
mediolateral perturbation is provided by two recent EMG studies. Lower limb muscle
activity was measured while walking in medially or laterally induced footwear bias in
12 healthy males (Goryachev, Debbi, Haim, & Wolf, 2011) and 14 females with
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medial knee osteoarthritis (Goryachev, Debbi, Haim, Rozen et al., 2011). Muscle
activation and duration throughout the kinetic chain was influenced by the
mediolateral changes. For example, the medial condition influenced lateral
gastrocnemius with a significant 41% increase in the healthy participants. Conversely,
the lateral shift decreased lateral gastrocnemius activity but did not increase medial
gastrocnemius activity to the same extent. Increased muscular activity and impaired
postural stability has also been measured in 70 elderly (fallers and non-fallers over 65
years old) compared to 15 young participants barefoot (Laughton et al., 2003).
In the present study, it is possible that the balance task, for this healthy fit group, may
not have been challenging enough and hence not truly reflects dynamic postural
stability performance (Emery, 2003; Hrysomallis et al., 2006; Wikstrom et al., 2009;
Wikstrom, Tillman, Chmielewski et al., 2006). Alternately, measures which may be
more sensitive to small changes, such as time-to-boundary (Hertel & OlmstedKramer, 2007; Hertel, Olmsted-Kramer, & Challis, 2006; Pope et al., 2011) or
diffusion analysis (Laughton et al., 2003) may show differences.
Another possible explanation for this observed homeostasis is provided by the
integration between the different sensory systems that control postural stability. If one
system is changed, such as the somatosensory inputs from the foot and ankle in this
study, then a functional re-weighting of each system occurs in order to adapt to the
changed stimulus (Rogers et al., 2001; Vuillerme, Burdet, Isableu, & Demetz, 2006;
Vuillerme, Nougier, & Prieur, 2001). Sensory re-weighting is a process which
dynamically integrates changing environmental and sensory conditions in order to
maintain postural control (Mahboobin, Loughlin, Atkeson, & Redfern, 2009).
Automatic rapid re-calibration occurs by switching from somatosensory to visual cues
ensuring postural stability is maintained (Vuillerme, Nougier et al., 2001). The
availability of vision has been shown to compensate for postural deficits and the eyesclosed conditions may be necessary to discriminate seemingly healthy individuals
with sensory-motor deficits (Redfern et al., 2001).
As the neuromuscular constraints change, the efficiency of the CNS re-weighting
visual sensory cues is critically linked to the quality of information obtained
(Vuillerme et al., 2006). In this study participants focused on a fixed light source
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which may have improved the visual information and compensated for the
destabilizing effect of the asymmetric intervention (Pinsault & Vuillerme, 2009;
Vuillerme et al., 2006). In order to assess the pure effect of footwear asymmetry,
vision needs to be removed (Pinsault & Vuillerme, 2009). A different experimental
design would be needed to address this important issue but no-vision in itself would
be an abnormal condition for healthy participants. However, the present experimental
design with a focused light source provided a strongly controlled and standardized
task procedure. Consequently, the visual environment was similar for each trial and
participant which is strength in this study. These results suggest that the altered anklefoot neuromuscular function increased reliance on visual information which almost
completely compensated for the asymmetric disturbance (Pinsault & Vuillerme, 2008;
Vuillerme & Pinsault, 2007). A possible alternative to no-vision would be to increase
the task difficulty or habituation time for a healthy cohort. This was partly addressed
using the 20 min habituation walk.
5.4.5
The Effect of a 20 min Brisk Habituation Walk on Postural
Stability Performance
Fatiguing exercise is known to disturb postural stability (Vuillerme & Boisgontier,
2008; Vuillerme & Hintzy, 2007; Vuillerme, Nougier et al., 2001; Vuillerme,
Sporbert, & Pinsault, 2009). Postural stability during 30 s of double-leg stance,
inferred from the COP mean velocity, of 9 participants who walked or ran for 30 min
on a treadmill was decreased post-exercise by 9 to 19% (no confidence intervals
reported) (Derave, Tombeux, Cottyn, Pannier, & De Clercq, 2002). Interestingly, no
change to mean velocity was measured when vision was removed. Although the 20
min brisk walk of the current study was not designed to be a fatiguing exercise but
rather an extended habituation period, the results indicate, irrespective of asymmetric
condition, that this walk was sufficient to disturb postural stability between 2.5 and
11.1%, during the experimental task. This was mostly true for double- and single-leg
stance immediately following the walk. Postural stability was also disturbed during
double-leg stance by the simulated 3 mm medial asymmetry and shoe only conditions.
Thus there is some evidence to suggest that the 20 min walk did affect fatigue (mental
or physical) although this was a fit cohort accustomed to far greater exercise.
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Alternately, the participants’ may have been less focused immediately after the walk
so that double-leg stance performance was more variable until they performed the
dynamic task and had to remain stable during the remaining 15 s of single-leg stance.
However, the dynamic transition phase was not affected except for a 10.1% decrease
in the mediolateral variability of the GRF. Maximum displacement was unaffected
during the first two phases but also decreased by 5.5% during single-leg stance. Time
to stabilisation in the anterioposterior direction was quicker by 5.6%. These decreases
suggest improved postural control post-walk or a protective reluctance to move
beyond perceived safe boundaries. In this context, decreased COP displacement
would be considered an impaired response (van Emmerik & van Wegen, 2002). This
may also be due to a learning effect although the average decrease over the seven
shoe-wedge experimental conditions was only 1.2% so this explanation is unlikely.
Four important findings from the 20 min walk habituation period are evident.
•
Increasing medial or lateral heel asymmetry decreased postural stability as
measured by changes to the variability in the mediolateral GRF and mean
velocity during single-leg stance.
•
The incremental increase in asymmetry systematically and progressively
disturbed postural stability for these variables during single-leg stance.
•
The performance in the corrected neutral shoe was unaffected by the 20 min
walk during single-leg stance.
•
The systematic changes to postural stability with increasing asymmetry are
greater post 20 min walk than during the non-walk experimental procedure.
Vision may have compensated the sensory system while adapting to the asymmetric
challenges during the non-exercise period (Pinsault & Vuillerme, 2009). Hence only
small changes were measured for SDFy. Walking briskly for 20 minutes combined
the effect of some fatigue and extended exposure to the asymmetric change. This may
have broken the threshold for rapid CNS adaptation, re-organization and re-weighting
leading to greater postural stability failure in the most challenging experimental
position. Exercise in the asymmetric condition over a prolonged period may be the
equivalent of no-vision during the non-exercise experiment. Considering the
multisensory control of postural stability, these results suggest that the altered ankle-
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foot neuromuscular function increased reliance on visual information which
incompletely compensated for the disturbance and hence postural stability was
affected.
The corrected neutral shoe condition did not disturb postural stability during singleleg stance after the 20 min brisk walk is important. Postural stability was impaired
barefoot and in the participants’ own shoe in those who had asymmetrically worn
footwear. This suggests that the current asymmetric status of an individual’s shoe and
the length of time spent in it could affect balance, fatigue and performance. The
analysis post-walk did not include separating neutral and asymmetric footwear which
may explain the finding that performance in the non-corrected shoes, which included
41.5% neutral, was similar to the corrected neutral shoe. A comparison of these two
shoe conditions during double-leg stance hints at improved performance for the
corrected neutral shoe. The participants’ were well habituated to their own footwear
with the median of 12 months old. This may also help to explain the unaffected
performance in the non-corrected shoes.
In summary, the 20 min habituation walk altered the testing environment compared to
the non-walk period. This change was sufficient to differentiate small systematic
asymmetric perturbations in footwear for some postural stability variables and
provided evidence that extended exposure to asymmetry may lead to progressive
postural instability.
5.4.6
Phases of the Task and Dependent Variables
The experimental design which incorporated three 30 s trials for double-leg stance
have been shown to have excellent test-retest reliability for non-normalized COP
measures such as maximum displacement and mean velocity (Pinsault & Vuillerme,
2009). In this study double-leg stance lasted only 5 s per trial which may have
affected the reliability, and therefore, the significance of the results. However, the
analysis of the trials and order effects during each phase indicated very small changes
for all variables. The strength of the statistical analysis is the inclusion of all trial data,
rather than the mean of the three trials. Some participants prepared for the transition
by shifting their weight despite being asked to stand as still as possible. Similarly,
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transition was a very small time window where large per trial variability in
performance was possible. The speed of the movement was controlled which has been
shown to affect reliability (Hanke & Rogers, 1992). Although there were these
limitations during the first two phases of the task, the active single-leg stance phase
was thought sufficient to challenge this healthy fit cohort. It is during this phase that
significant changes to postural stability were measured after the 20 min walk. The two
5 s time windows analysed during single-leg stance are different. During the first 5 s,
there is increased variability caused by the transition which is then followed by the
second more stable period. It is during this second time window where the effect of
the simulated asymmetry was more evident. This has previously been described as a
dynamic followed by a static phase of force variability (Jonsson et al., 2004).
There are many other potential analytic methods for evaluating GRF and COP data,
all developed in order to improve sensitivity of measurement and understand the
complexity of dynamic postural control (Hertel et al., 2006; Rougier, 2008; van
Emmerik & van Wegen, 2002; Wikstrom, Tillman, Smith et al., 2005). The chosen
dependent variables were thought to represent a broad spectrum of traditional force
platform derived measures which could explore the relationship between footwear
asymmetry and postural stability (Goldie et al., 1989; Le Clair & Riach, 1996; Ross et
al., 2009). The task and perturbation had more effect in the mediolateral direction thus
making redundant the variability of anterioposterior GRF. Although maximum
displacement of the COP is often used (Pinsault & Vuillerme, 2008; Vuillerme,
Nougier et al., 2001), in this study it may have been affected by single large
movements during the transition phase and hence not sensitive enough to detect
changes to postural stability. Although it was expected that the time to stabilisation
associated with this dynamic task would provide valuable information, it did not. It
may be that the task chosen was less challenging than step downs or jump-landings
which are typically used as the key movement sources for this variable (Ross et al.,
2009; Wikstrom et al., 2008b; Wikstrom, Tillman, Smith et al., 2005). The results do
confirm the variability of the mediolateral GRF and mean velocity as sensitive
measures for assessing changes to postural stability (Geurts et al., 1993; Goldie et al.,
1989; Goldie et al., 1992; Luoto et al., 1998; Pinsault & Vuillerme, 2009; Ross et al.,
2009).
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5.4.7
Age, BMI and Gender on Postural Stability Performance
The effects of age, BMI and gender on postural stability were not an objective in this
study but were controlled for within the analysis. Age-related increases for mean
velocity have been reported in participants over 60 years old (Maki, Holliday, &
Topper, 1991; Maki et al., 1994; Prieto et al., 1996). Although the age range of
participants in this study was 18 to 60, this had very little effect on all postural
stability measures during the dynamic task to single-leg stance. Similarly, increasing
BMI had small variable effects on postural stability measures during all phases. The
effect of weight and height were not analysed separately and may have independent
effects.
Women had between 9 and 25% better postural stability, as evidenced by decreased
scores for SDFx, SDFy, Maxdis and Mvelo compared to men during transition and
single-leg stance. Alternately, they were more reluctant to move out of their COP
boundaries. Other studies have found no gender effects in stability (Hageman,
Leibowitz, & Blanke, 1995; Han, Ricard, & Fellingham, 2009; Luoto et al., 1998;
Orishimo, Kremenic, Pappas, Hagins, & Liederbach, 2009; Rogind, Lykkegaard,
Bliddal, & Danneskiold-Samsoe, 2003). Impaired dynamic postural stability in
women (Wikstrom, Tillman, Kline, & Borsa, 2006) or improved balance for girls
between 7 and 12 years old (Holm & Vollestad, 2008) and in adult women (Farenc et
al., 2003) has also been reported. Since gender was controlled for within the analysis,
further speculation is unwarranted.
5.4.8
The Human Tower, Simulated Asymmetry and the Postulated
Link to Postural Instability
No direct measurement of neuromuscular or joint loading was made in this study so
the following points are speculative. The link between footwear asymmetry and
postural stability performance is theorised by conceptually modelling the human body
in single-leg stance as a dynamic tower built on the foot as the foundation (Section
3.3). Foot-ground sensory information is constantly integrated in the CNS with all
other inputs which then directs dynamic neuromuscular responses for stability and
movement. Should the foundation be tilted medially or laterally, some compensation
239
will be needed within the structure in order to maintain upright stance. If insufficient
or no compensation can be made, then the tower is likely to fall over such as in the
elderly or a tree in gale force winds. The compensation can be both mechanical
(Andriacchi & Mündermann, 2006; Brandt et al., 2009; Mündermann et al., 2005) and
changing muscular work (Goryachev, Debbi, Haim, & Wolf, 2011; Landry et al.,
2010; Laughton et al., 2003; Shelburne et al., 2006). This automatic dynamic
compensation is continually in a state of flux as the body responds to small
perturbations such as walking or running over uneven terrain (Alexander, 2007; Daley
et al., 2007). However, when the perturbation becomes more or less permanent such
as standing on a cambered surface, fixed long term alterations are then required.
Sensory changes in mediolateral regions of the foot may become fixed, unlike the
barefoot state, leading to loss of spatial information and thus poorer CNS coordination leading to impaired postural control.
Mechanical changes may include asymmetric joint compression or distraction in the
spine, hip, knee and ankles. For example, 6 min of running in Brooks Adrenalin
stability shoes, which have in-built mediolateral asymmetry, increased joint loading at
the hip, knee and ankle along with peak mediolateral and vertical GRFs compared to
the same speed running barefoot (Kerrigan et al., 2009). It is hypothesised that the
longer the time spent under the same asymmetric loading conditions, the greater the
cumulative damage to joint surfaces, and loss of integrity will occur. The end result
may be osteoarthritis which is defined as failed repair of damage caused by excessive
mechanical stress (Brandt, Dieppe, & Radin, 2008; Brandt, Radin, Dieppe, & van de
Putte, 2006). Removing the asymmetric mechanical stress allows joints to heal
(Radin, 2005; Radin & Burr, 1984; Radin, Burr et al., 1991). Concomitant with
mechanical changes, neuromuscular activity will also be affected by tilting the tower.
The hip and trunk muscles work together as a unit both globally and locally to
stabilize the spine (Stevens et al., 2007) and pelvis (van Wingerden, Vleeming,
Buyruk, & Raissadat, 2004) by effectively transferring load from the legs (Zajac et
al., 2002, 2003). These form an integrated functioning system (van Wingerden,
Vleeming, Snijders, & Stoeckart, 1993; Vleeming, Pool-Goudzwaard, Stoeckart, van
Wingerden, & Snijders, 1995). Mediolateral asymmetry may disrupt this effective
load transfer system by requiring increased muscular work to maintain the anti240
gravity position. If the muscles work together as inter-related guy ropes maintaining
the structural integrity of the spine, pelvis and legs, some will be performing more
work compared to others. Asymmetry of muscular activity has been measured in
women habitually using high heels and even measured in their barefoot gait (Gefen et
al., 2002) which suggest prolonged exposure may have a detrimental effect. An
immediate muscular effect to this asymmetry is expected (Shelburne et al., 2005,
2006; Shelburne et al., 2008) and has been measured (Goryachev, Debbi, Haim, &
Wolf, 2011). The longer the asymmetry persists, the greater the work required
eventually leading to tightness and fatigue in asymmetric groups of muscles. This
may lead to sensory-motor incongruence and muscle-joint performance described as
joint “micro-klutziness” (Radin, 2004; Radin, Yang et al., 1991). Abnormal changes
to pelvic and back muscle coupling in patients with chronic back pain are thought to
influence postural stability impairment (Luoto et al., 1998). This impaired
neuromuscular control may decrease the muscle force closure mechanism that
intrinsically stabilizes the pelvis (Pool-Goudzwaard, Vleeming, Stoeckart, Snijders,
& Mens, 1998). Postural instability will only be measured when the body is no longer
able to compensate because of mechanical or muscular fatigue and pain. In this study
walking for 20 min in asymmetric footwear may have provided a sufficiently strong
stimulus for this to be measured. Muscular activity and fatigue was not measured in
this study so possible links between these and changes to postural stability found in
this study are purely speculative at this time.
5.4.9
Methodological Considerations
Most laboratory-based studies provide an environment foreign to participants and may
challenge normal natural behaviour affecting the collection and subsequent
interpretation of the data. This challenge of external validity was addressed by
incorporating features such as time given to explaining the protocol, exploring the
environment, practicing the task, using natural foot, leg and arm positions in their own
footwear and facilitating participants to be as relaxed as possible (Jonnson et al.,
2004; Pinsault & Vuillerme, 2009). Thus every effort was made to minimise the
foreign nature of the laboratory protocol. The potential limitations of this study and its
strengths are discussed.
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Limitations associated with this study include the lack of a qualitative assessment of
the performed task, the limited habituation time for each condition, the dynamic task,
variables computed and the assessment of footwear asymmetry. Psycho-physical
assessment of participants’ perception of the task difficulty and sensory perception of
the position and size of simulated asymmetry would have been a powerful study in
itself. Upon reflection, this could quite easily have been simultaneously performed
using video analysis and a questionnaire format. Participants volunteered information
with regard to the task difficulty under different conditions and where they thought
the wedge was placed and its relative size. No data was collected so an interpretation
of their sensory perceptive abilities cannot be made. Despite this, no formal unblinding of the wedge condition occurred. Because participants were not asked which
group they thought they were in, the success of participant blinding is not known.
Although no data was lost by participants falling off the force platform or touching
down (Section 2.7.3), many felt it was harder to balance in certain conditions and
used compensatory body movements differently during transition. This sensory
perception to mediolateral changes at the foot may have provided information relating
to each individual’s global postural stability performance and CNS integration
(Section 2.3.4). Individual specific-factors, such as injury history, were not considered
in the experimental design. Only 17% of participants had never been injured. Previous
multiple lower limb and back injuries reported by the majority of participants could
affect postural stability performance (Section 2.7.3). However, the study exclusion
criteria based on the reviewed literature (Sections 2.7.2 and 2.7.3) of age, fitness,
injury status sought to reduce the effect of these limitations. The statistical analysis
also recognised factors such as age, gender, BMI and order as fixed effects in the
model accepting them to potentially affect outcomes.
Participants were well habituated to their own shoe condition, but habituation time in
the simulated conditions was pragmatically limited by time constraints. This issue was
addressed by the single 20 min walking bout. However, the barefoot condition was
not randomized into the experimental design and did not include a significant
habituation period. The reason was to ensure a smooth transition between conditions
when footwear was worn. This may have impacted on the significance of the barefoot
results.
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The dynamic task chosen may not have sufficiently challenged the fit and healthy
individual’s single-leg postural stability function (Section 2.7.2). Participants also had
the opportunity to prepare themselves during double-leg stance for the subsequent
intended dynamic movement. Randomly including either leg in the single-leg stance
phase would have improved the challenge. This would have created more uncertainty
and unpredictability in the dynamic movement. However, the decision to use one limb
only was based on both time and possible fatigue from repeated testing. Similarly,
excluding vision would have increased the reliance of foot sensation and decreasing
the extent of sensory re-weighting (Pintsaar & Vuillerme, 2009). But vision was
important in controlling the onset of the movement and is typical in real-life
situations. It is clear participants were able to automatically readjust to the new
asymmetric condition. Measurement of muscle activity using EMG of the back and
lower limb (Section 2.7.2) would have provided further information as to how the
body re-adapts to the new asymmetric conditions and may be used for future study
(Rogers & Pai, 1993). An alternative dynamic task such as step downs, hops, heelraises, walking or running should also be considered for future work (Ross et al.,
2009).
The dependent variables chosen were based upon the exploratory nature of this study
and the review of the literature (Section 2.7.3). The large variety of measures reported
in the research appears to be dependent upon equipment and mathematical programs
available and the search for the elusive most sensitive variable. The results do confirm
previous findings that the axis of intervention or perturbation will determine the most
relevant variable (Goldie et al., 1989; Goldie et al., 1992, 1994; Maki et al., 1994;
Maki, McIlroy, & Perry, 1996). In this study the mediolateral axis was perturbed.
Only the mediolateral GRF variability and mean COP velocity appeared to be relevant
to this task and interventions. The remaining variables are redundant and could have
been excluded. They have been reported as they could assist other researchers in this
area.
The 1, 2 and 3 mm heel wedges used to simulate footwear asymmetry were based on
both clinical observation as well as the results of Study 1 although greater asymmetry
was measured in both studies. The aim was to increase the asymmetry systematically
by small measurable amounts and it would not have been practical to continue up to 5
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mm or more. Statistical analysis was compounded by the number of conditions and
the phases of movement and these would need to be addressed by focusing on the
movement or position most likely to disturb postural stability for the study population.
The number of multiple comparisons may also have in-built statistical error although
the study was adequately powered and the Wald test determined whether an effect
existed or not. Analysis of the data from the moving leg was recorded but not
analysed and it may give further information about the propulsive and braking phases
of the mediolateral GRF during the lateral weight transfer portion of movement
(Hanke & Rogers, 1992; Rogers & Pai, 1990).
Other potential effects on performance that were not accounted for include the current
condition and different types of footwear used by participants during daily functional
activities and how this may affect the barefoot state (Sections 2.2.2, 3.2 and 3.4).
Statistical analysis of the effect of one pair on barefoot and shoe performance was
complicated by the different number of shoes in each asymmetric category.
Collapsing the data to a single neutral or asymmetric value may not be an accurate
representation of the true state of their footwear. Hence comparisons with their
barefoot performance may be imprecise. Ideally, performance testing needs to be
carried out in each of the participants’ footwear which was logistically not possible in
this thesis. A prospective study over two years monitoring new supplied footwear and
postural stability may provide a more accurate picture.
Despite the limitations described, a number of strengths need to be highlighted.
Experimental design factors of sample size, control conditions, repeated measures and
randomization were addressed. The wide age range and large sample size allow
conclusions to be inferred about the general population. The standardized
experimental protocol in terms of instructions, initial posture, speed of movement, eye
focus, habituation and practise time all minimize the effects of task outcome
variability (Hanke & Rogers, 1992). Although the task difficulty may not have been a
sufficient challenge for this healthy cohort, it provided an element of normal day-today dynamic movement such as stair climbing or the initiation of walking gait. The
blinding procedure associated with the wedge conditions and the randomization of
shoe conditions and repeated measures all enhance the quality of the outcome
measures. Although the barefoot condition was not randomized within the testing
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protocol, its inclusion for comparative purposes to the shoe only condition is
invaluable as this is often overlooked in footwear research (Section 3.3). The use of
each participant’s habituated footwear and the detailed assessment of this footwear
are two important strengths of this study.
Evaluator error was minimised by using the force platform while potential errors in
calculating the start and end of the transition movement were eliminated by using the
light onset signal and zero GRF on the flexing limb platform (Hanke & Rogers,
1992). Participants were evaluated within their most frequently used footwear in
which they felt comfortable and were well habituated allowing inferences to be made
about their general natural behaviour. The 20 min brisk habituation walk was close to
a normal activity for this active population although the treadmill was unfamiliar to
some. The 20 min habituation time for each condition improves the ecological
validity of the study. There was little time delay between the end of the treadmill walk
and the final three trials by positioning the treadmill close to the force platforms so
that participants could walk directly to them. The selection and range of dependent
variables was comprehensive while a detailed logical statistical analysis of the data
was performed.
The shoe asymmetry protocol (Section 3.4) breaks new ground in terms of the detail
and volume of shoes assessed with regard to the measurement of the outer-sole wear,
mid- and inner-sole compression, and the effect of orthotics and posting. Asymmetric
outer-sole wear is more difficult to measure where there are no clear edges or
interfaces between midsole and outer sole such as in canvas shoes (Figure 5. 11).
Placing the heels together (sole-to-sole) and measuring the gap medially and laterally,
if it exists, between the two heels is possible (Figure 5.11). Measurement of
compression with the Durometer is also difficult where the surface area of the midsole
is uneven or smaller than the head of the Durometer or covered by the outer sole or
composed of a grid with empty holes. The properties of the inner-sole and attached
inner cushioning and heel inserts also need to be accounted for when measuring heel
height, compression or wear.
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Figure 5.11 Flat canvas shoes require alternative measurement approaches.
Placing the heels together is a method to measure outer sole wear with the
difference 1 mm lateral wear.
Figure 5.12 illustrates the outer-sole and wrap around rubber density as Asker C 90
units which is very different from the soft inner-heel of Asker C 30 units. The inner
heels are often of varying density and quality which may completely change the shoe
design and wear characteristics. These can easily be overlooked as they lie beneath
the inner-sole. Flats and canvas shoes accounted for 20.7% of footwear assessed but
not all had measurement problems as detailed here.
Figure 5.12 Hardness of rubber outer-sole of a flat canvas shoe (Asker C 90
units), and symmetric inner-sole with an 8.74 mm heel (Asker C 30 units).
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The asymmetric bias of the molded orthotics assessed in 8.5% of footwear cannot be
easily measured although the attached posting can be simply measured with a Vernier
calliper. Footwear asymmetric assessment followed a rigorous process which has not
been presented before. Finally, this study aimed to expand knowledge of footwear
asymmetry on postural stability by very small step-wise increments based upon
typical measured wear patterns which have not previously been attempted.
5.5
What this Study Contributes
This study contributes both to clinical and research knowledge related to the
assessment of footwear and postural stability. It is unique and original in that it
provides an overview of current thinking in terms of footwear and whole-body
dynamic function and attempts to simulate observed and measured patterns of wear in
a laboratory setting. These measured patterns require an extraordinary shift in
thinking with regard to feet, footwear and human dynamic function.
Although excellent texts exist with regard to the general assessment of worn athletic
footwear (Noakes, 2003) measurement of asymmetry caused by design and wear has
been neglected or only anecdotally reported. Design asymmetry in motion control
sports footwear based upon the poor foot paradigm is very different to early footwear
and needs careful assessment. Paradoxically, the reverse design has recently been
researched and proposed as a mediating influence in medial knee osteoarthritis
(Erhart, Mündermann, Elspas et al., 2008; Fisher et al., 2007; Jenkyn et al., 2011).
This study provides detailed footwear analysis which comprehensively covers all
types of asymmetry patterns and hidden difficulties measuring it within present day
footwear. Since lateral wear is dominant, and lateral wedging or lateral stiffer
midsoles are required to reduce knee adduction moments then lateral wear should be
monitored in people with knee OA. Two questions need to be answered. Is lateral
wear one of the main contributors to large knee adduction moments and the
development of knee OA? Secondly, is medial posting and more compliant lateral
midsoles contributors to large knee adduction moments and the development of knee
OA?
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Problems researching postural stability performance in healthy individuals have led to
developing alternative tasks and measures considered more sensitive (Riemann et al.,
2002). This study shows that small changes in footwear conditions is difficult to
measure in terms of postural stability and interactions between other factors such as
sensory re-weighting need to be carefully considered when planning experimental
protocols. Despite this, increased insight into global postural stability deficits is
provided. Pre-injury impaired postural control exists, but is unexplained. A possible
explanation is the evidence of decreased mediolateral stability performance in
participants’ whose footwear was measured as asymmetric. Further, the longer the
time spent in simulated asymmetry, the worse the performance suggesting that
prolonged exposure to asymmetry may also have adverse effects in healthy
individuals. Conversely, postural stability was unaffected when neutral footwear was
worn, even after a 20 min brisk walk. This provides new insights into a known
phenomenon which is thought to make individuals susceptible to lower limb injuries
and wear and tear chronic pain. This includes diverse conditions such as ankle
inversion injuries or knee osteoarthritis. Although the clinical utility of these results
have yet to be researched they ultimately could be an important clinical tool when
assessing factors relating to postural instability. These results also highlight that the
clinical assessment of single-leg balance, may not differentiate impaired individuals.
Postural stability should be assessed prior to an extended sport and individual-specific
exercise protocol and then reassessed immediately post-exercise.
These results support design parameters for an ideal shoe that should be neutrally
dense but hard enough to prevent compression (Asker C 70 or above), light and
flexible, flat in profile from heel to toe, and with an outer sole which has large
symmetric areas for weight-bearing. To support such a hypothesis future research
should comparatively evaluate shoe design from opposite poles of the symmetric
design spectrum and prospectively assess degradation. Such research should also be
compared to a population who traditionally use a barefoot gait.
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5.6
Directions for Future Research
This unique study has begun the exploration of asymmetry in footwear and its effect
on postural stability. In order to further research the development of footwear
asymmetry and its effect on whole-body dynamic stability and injuries a prospective
study over 2 years may be necessary. This would provide a suitable timeframe, based
on the footwear assessed in this study, in which to assess footwear changes and
monitor neuromuscular performance and injuries. A detailed analysis of all footwear
worn by the individual, amount of time spent barefoot and dynamic testing such as
walking or running using all footwear throughout the period would improve
knowledge of any asymmetric changes that take place and the effect on dynamic
function. In order to measure neuromuscular performance and joint loading,
dependent variables would include muscle EMG activity in a chain of lower limb
muscles, related joint moments at the hip, knee and ankle and GRF forces. The tasks
for uninjured participants would include heel-raises to fatigue, a single-leg step-down
or hop and walking or running. Conditions comprising barefoot, new and all
progressively habituated footwear used by each individual would be assessed
repeatedly over the prospective study period. The aims of this prospective study
would be to:
• expand the current understanding of the cause of global postural stability deficits
which exist in a normal healthy population;
• relate progressive changes in footwear mediolateral asymmetry to lower limb joint
loading and the neuromuscular efficiency;
• develop a reliable method of predicting the magnitude of joint loading in the lower
limb from mediolateral footwear assessment, COP and GRF displacement and less
expensive clinically available equipment such as foot pressure devices;
• develop a clinically relevant and reliable footwear asymmetry assessment
protocol;
• develop a reliable clinical footwear optimisation test and procedure, using
perturbed single-leg stance, squat and heel-raises;
• and establish the relationship between changes in footwear asymmetry to injury
incidence and risk.
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5.7
Conclusion
These findings demonstrate progressively decreased mediolateral postural stability
with increasing shoe heel asymmetry, medially or laterally; during single-leg stance
when compared to the shoe only condition after a 20 min walk. The dynamic task was
thus sensitive to 1, 2 and 3 mm medial or lateral asymmetric perturbations at the
hindfoot after walking. Postural stability was unaffected by the neutral shoe condition
after walking. Barefoot postural stability was more variable than in the participants’
own footwear and this may be explained by the possible lack of barefoot habituation
or the present asymmetric status of an individual’s footwear. Alternately, the dynamic
barefoot stimulates the foot’s sensory map increasing CNS information providing
more variable responses to foot-ground interactions and hence lower specific joint
loading stress. Participants’ who wore asymmetric footwear had worse mediolateral
postural stability barefoot and in their footwear which supports the concept of preexisting global postural stability impairment prior to injury. Lateral heel wear was the
most frequently measured asymmetry in this sample which may provide clues with
regard to acute and chronic injuries such as lateral ankle sprains/instability or medial
knee osteoarthritis.
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CHAPTER 6.
Summary and Recommendations
6.1
Summary of the Research Pathway
This thesis examined the effects of actual and modelled asymmetric footwear on
dynamic heel-raise performance and postural stability. The research literature has not
established clear one-to-one relationships between variations in foot structure, injury
and performance (Davis, 2004, 2005; Razeghi & Batt, 2002). Despite this, up until
very recently, footwear design and prescription have continued to be influenced by
the poor foot paradigm (Section 3.1). Questions about design characteristics thought
to be protective and enhance performance have been raised and explored at frequent
time intervals (Brüggemann, 2007; Kerrigan et al., 2009; Nigg, 2001; Perry &
Lafortune, 1995; Robbins & Gouw, 1991; Shakoor, Lidtke et al., 2008). This thesis
argues that research has neglected to consider asymmetric design and degradation of
the footwear used by participants and patients as a possible factor affecting
neuromuscular performance and injury.
The evolutionary perspective with regard to human structure, function and footwear is
missing from most research models but has recently gained much publicity (Sections
2.1, 2.2 and 3.2). If present, the argument of under-designed or failed natural selection
adaptations is generally asserted (Hutton, 1987) and hence footwear needs to control,
facilitate, shock absorb and support (Sections 2.3 and 3.1). This design strategy
creates a paradox. Footwear design which is claimed by manufacturers to improve
foot and lower-limb function is likely to be associated with a deterioration of footground sensory information vital for efficient neuromuscular function (Section 2. 3).
Extensive re-training and rehabilitation of foot and lower limb musculature is often
suggested pre- and post-injury because of measured impaired global postural stability
and sensorimotor function (Landry et al., 2010; Nigg, Emery et al., 2006; Perry et al.,
2007; Potthast et al., 2005; Robbins & Hanna, 1987; Waddington & Adams, 2003;
Wikstrom et al., 2009). Footwear contributes to this impaired function (Landry et al.,
2010; Waddington & Adams, 2000, 2003). This conflict is further exacerbated by
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changing one component of the foot-ground interface (Brauner et al., 2009; Butler,
Hamill et al., 2007) only to compromise the complementary function or
neuromuscular-joint pattern elsewhere in the kinetic chain (Butler et al., 2009; Dixon,
2008; Mündermann et al., 2006; Stüssi et al., 1993).
In Chapter 3 the poor foot paradigm was juxtaposed with the selective survival value
of evolutionary adaptations (Section 3.2). Evolutionary theory considers human
structure and function perfectly adapted for dynamic movement (Lieberman et al.,
2009). Although recent literature includes this fundamental paradigm shift, the footground interface is still addressed in a piece-meal rather than a holistic fashion.
Footwear is envisioned as a technology for foot protection and warmth only and
should not interfere with foot function (Stewart, 1945). Impaired structure and
function is considered a result of footwear inhibiting normal barefoot development
and imposing a set of foreign biomechanical and sensory constraints (Rao & Joseph,
1992; Staheli, 1991; Stewart, 1972). A conceptual mechanical-sensory model of the
body as a tower was developed (Section 3.3). From the perspective of the foot-ground
interface, small anterioposterior and mediolateral alterations, which change
orientation of the lower limb to the ground, may affect ground reaction forces and
whole-body equilibrium (Fisher et al., 2007; Robbins et al., 1998; Shelburne et al.,
2008). Compensated neuromuscular changes and abnormal joint loading are
consequences (Erhart, Mündermann, Elspas, Giori, & Andriacchi, 2010; Erhart,
Mündermann, Mündermann et al., 2008; Mündermann et al., 2008; Shelburne, Torry,
& Pandy, 2005a). No data collected provides direct support for this model. Linked to
this idea is a unifying conceptual model of footwear asymmetry created by design and
degradation (Section 3.4). Two typical patterns of mediolateral asymmetry are
evident. This fundamental model underpins footwear assessment and the simulation
of mediolateral asymmetry used throughout the thesis.
The simulation and effect of this mediolateral asymmetry during the single-leg
barefoot heel-raise performance task is described in Chapter 4. This task was chosen
as a possible clinical assessment tool for the optimization of footwear as it
corresponds to typical weight-bearing patterns of normal gait (Section 2.7.1).
Concomitant with this was the assessment of participants’ footwear related to the
mediolateral conceptual model (Sections 2.6 and 3.4). These results directed the
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simulation and investigation of further mediolateral asymmetry in Chapter 5. A
dynamic task was used to assess the effects of small graded asymmetric interventions
on postural stability using typical biomechanical measures of GRF and COP (Sections
2.7.2 and 2.7.3). A smaller sample of footwear was again assessed using the same
protocol as in Chapter 4 and confirmed the previous findings.
A postulate of this thesis was that footwear design and degradation through use may
contribute to mediolateral asymmetry (Section 2.5, 2.6 and 3.4). This may cause
further degradation in the medial or lateral components of the shoe. The human tower
embedded in an asymmetrically worn shoe may no longer be grounded vertically.
This may result in altered foot-sensory information coupled with neuromuscular
compensations necessary to maintain postural stability. The longer the exposure to,
and the greater the magnitude of this asymmetry, may engender a cumulative low
threshold effect on whole-body systems eventually leading to over-load and failure.
Results from Study 1 indicate impaired heel-raise performance with 1 mm of
simulated lateral wear but performances was restored when the foot was neutral or
with simulated medial wear (Section 4.3.3). The possible explanation for these
findings relates to the predominance of lateral heel asymmetry in the footwear of
these participants, dynamic ankle-foot structure and function. Study 2 confirmed a
relationship between pre-existing asymmetric footwear and mediolateral single-leg
stance postural stability performance (Section 5.3.4.2). Stability was reduced while
barefoot or in footwear. The 20 min habituation walk extended these findings (Section
5.3.6). Postural stability was unaffected by neutral compared to simulated and
corrected footwear asymmetry. Incremental increases in asymmetry both medially or
laterally had a progressively detrimental effect on single-leg stance postural stability.
A future step in the research pathway will be to determine the potential long-term
effect of this asymmetry on injury rates, joint loading and neuromuscular efficiency.
6.2
The Evolutionary Perspective on Human Function
These studies provide no direct evidence for the evolutionary perspective on human
function (Sections 2.1, 2.2 and 3.2). Barefoot was used in both investigations as a
starting point to explore neuromuscular function. In Study 1 barefoot performance
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was better than a simulated lateral asymmetry. The maximum number of heel-raises
performed and rate of performance was 23.4% and 10.7% poorer in this condition. No
performance was measured in footwear. In Study 2, postural stability barefoot was
compared to personal footwear (Sections 5.3.4.1 and 5.4.3) with performance more
variable barefoot which is thought to have protective evolutionary value (Morio et al.,
2009; van Emmerik & van Wegen, 2002). Increases in variability barefoot compared
to footwear during transition and single leg stance ranged between 5.0% (SDFx) and
25.9% (Maxdis). However, there are other possible explanations for this increased
variability measured while barefoot including the fact that barefoot was always
assessed first and it is not the habituated condition for all participants. In contrast, a
different measure of postural stability, time to stabilisation of both the anterioposterior
and mediolateral GRF’s was 11.9% and 3.5% quicker while barefoot. The current
status of participants’ footwear illuminates a further difference between barefoot and
footwear use (Sections 4.4.3 and 5.4.2). Used footwear degrades and this may be
asymmetric, negatively affecting dynamic function. Habituated barefoot use improves
foot and lower limb function (Lieberman et al., 2010). Measured asymmetry was
similar at 62.6% and 58.5% in both studies for footwear on average almost 1 year old.
This current footwear asymmetric condition and performance was analysed despite
limitations with the data (Sections 4.3.6, 4.4.2 and 5.3.4.2). The rate heel-raises were
performed was 6.6% faster for individuals who had neutral compared to asymmetric
footwear (Section 4.3.6). Mediolateral balance was worse barefoot and in footwear by
20.2%/6.1% and 7.1%/13.1% during transition and single-leg stance respectively for
those individuals whose footwear was asymmetric (Section 5.3.4.2). Postural stability
was unaffected after walking for 20 min in neutral or corrected neutral footwear
compared to the asymmetric conditions (Section 5.3.6.3 and Table 5.23). The effect of
walking barefoot on postural stability was not examined in this study. More research
is required to explore this evolutionary perspective on barefoot, in-shoe performance
and footwear degradation over the long-term.
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6.3
The Tower Conceptual Model
The static tower model may not be a good model for single leg stance in walking and
running because of the dynamics of these tasks. A static snap shot of this single leg
posture may not encapsulate what is happening. The complex dynamic and variable
interrelationships controlled by the central processor during single-leg stance may
never be adequately modelled. However, conceptual models often allow the
exploration of ideas and questions and help focus research on specific questions.
Although no muscle activity or joint moments were directly measured in this thesis,
the effect of the mediolateral asymmetric perturbations at the heel on the human tower
was inferred from the changes in performance. Heel-raise performance was negatively
affected by 1 mm of simulated lateral but not by medial wear. This difference may
also relate to the lateral wear measured in 57.8% of footwear compared to medial
wear of 4.8% so that the simulated medial wear barefoot neutralised the cumulative
footwear asymmetric effect. Postural stability performance of the human tower was
impaired after walking for 20 minutes in asymmetric footwear with effects both
medially and laterally. For example simulating incremental lateral wear, mediolateral
GRF variability and mean COP velocity significantly increased 10.3%, 14.6%, 20.9%
and 6.4%, 13.3%, 19.2% respectively in single-leg stance (Section 5.3.6.2). Similarly,
incremental medial simulated asymmetry affected postural stability by 1.1%, 11.6%
and 4.8% for mediolateral GRF variability and 3.7%, 7.4% and 3.6% for mean
velocity. Differences between medial and lateral performance may also relate to the
footwear used. Lateral versus medial wear was measured in 57.6% compared to 0.9%
of shoes. These results suggest that neuromuscular performance was affected by the
mediolateral perturbations.
6.4
Contribution to Scientific and Clinical Knowledge
Chapter 1 highlighted current problems relating to footwear research. These included
the unchanged injury frequency in running-related injuries and the search for an
optimum footwear design. The knowledge gap posed two questions. What is the
frequency of mediolateral asymmetry in used footwear, and does this affect single-leg
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dynamic balance and performance? Anecdotal reports about footwear degradation
were synthesised into a unifying conceptual model of mediolateral footwear
asymmetry patterns (Section 3.4). This thesis provides evidence for a greater
frequency of lateral footwear degradation in well used footwear. A unique
contribution to scientific knowledge was the rigorous measurement methodology. The
magnitude of mediolateral asymmetry was systematically measured in a range of
typically worn footwear. Global neuromuscular performance, inferred from the
single-leg heel-raise and dynamic transition tasks, was impaired by simulating
mediolateral asymmetry. These results advance knowledge about the effects of
incremental simulated asymmetry, extended exercise time spent while in asymmetric
footwear and the effect of current footwear condition on global performance
measures.
6.5
Recommendations for Future Research
The literature review, the conceptual models developed and the results from the
studies undertaken provide a springboard for further investigations. These require
wide-ranging and diverse approaches to answer the many questions left unanswered.
Firstly, further investigation of asymmetric design and correlation with wear patterns
in footwear is required. The progressive dynamic nature of footwear degradation
could not be determined using the retrospective methodology. The number of
participants in each asymmetric group precluded examining the relationship between
the magnitude of asymmetry and performance of heel-raises or the effect on postural
stability. The link between barefoot, footwear degradation and intrinsic injury rates or
health status is another area where research is absent. This requires a prospective
study following a large sample size over a prolonged period. For example two specific
questions need to be answered. Is lateral wear one of the main contributors to large
knee adduction moments and the development of knee OA? Secondly, is medial
posting and more compliant lateral midsoles contributors to large knee adduction
moments and the development of knee OA?
The results from these studies suggest that the optimization of footwear using the
heel-raise or other clinical single-leg perturbation tasks as assessment procedures may
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be possible. However, the ideal would be walking or running. Biomechanical and
neuromuscular measures of muscle activity and joint loading at the hip, knee and
ankle during running could explore the effect of simulated mediolateral asymmetric
conditions within new and used footwear on COP, GRF, joint moments such as
EKAM and selected EMG muscle activity up the kinetic chain. Extended habituation
time for each condition is required.
Thirdly, over-arching these potential studies is the need to include an evolutionary
perspective and hence finding populations who may not yet be affected by modern
footwear design parameters is crucial. A way to include some of these diverse
questions within the confines of a single study may be possible using large wideranging age- and activity-linked samples from typically Western and predominantly
barefoot African or Pacific Island populations. A prospective one- to two-year
epidemiological study is needed to determine actual non-contact intrinsic injury rates,
time spent barefoot, in footwear and a longitudinal monthly assessment of footwear
degradation in those wearing footwear. A randomised controlled intervention trial
could be embedded within an epidemiological study to address effects of shoe design
and degradation on incidence of injury and on sport or work performance-related
variables. This could include supplying new footwear (minimalist designs) and/or
neutralizing asymmetry over the study period. Although this has logistical and
financial challenges, it is long overdue and would be the first step in answering
unresolved questions about the efficacy of footwear design compared to barefoot
function.
6.6
Recommendations for Clinical Practice
The findings of this study show, firstly, that incremental medial or lateral heel
asymmetry progressively decreased postural stability following activity. This was
measured by changes to the variability of the mediolateral GRF and mean velocity
during single-leg stance. The mediolateral GRF variability (SDFy) increased by
10.3%, 14.6% and 20.9%, and mean velocity by 6.4%, 13.3% and 19.2% with
incremental simulated lateral wear. Secondly, single-leg postural stability post-walk
was unaffected while neutral footwear was worn. Thirdly, individuals who wore
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footwear with pre-existing mediolateral asymmetry had poorer heel-raise performance
(RHR) and impaired mediolateral stability while barefoot and in footwear.
Mediolateral instability has been associated with falls in the elderly and control of
lateral stability during single-leg stance and transition to the next step is considered an
important factor in preventing falls (Maki & McIlroy, 2006). Similarly, global deficits
have been identified pre- and post-lower leg injuries (Bullock-Saxton, 1994; BullockSaxton et al., 1994; Franettovich et al., 2010; Goldie et al., 1994; Trojian & McKeag,
2006; Tropp & Odenrick, 1988; Waddington & Adams, 1999, 2000, 2003).
Laterally worn footwear, such as found in this study, could increase lateral loading
and predispose athletes to injury and impair stability. Should asymmetric footwear
contribute to local and global neuromuscular disintegration, abnormal joint loading is
likely which may lead to degenerative joint changes (Brandt et al., 2008) which
cannot be resolved using drug therapy (Brandt et al., 2009; O'Connor & Brandt, 1993;
Radin, 2004). Further, this decrease in global neuromuscular control may predispose
individuals to seemingly accidental injuries, such as walking and tripping or twisting
an ankle (Waddington & Adams, 2000, 2003). In this study barefoot postural stability
was more variable than in habituated footwear and assessment should take this into
account. Strategies to restore and improve neuromuscular control should therefore
include assessment of barefoot and in-shoe function as well as the extent of footwear
asymmetry.
6.7
Footwear Assessment
Assessment of footwear (Sections 2.6, 3.4, 4.2.7 and 5.2.8) for asymmetry is
recommended for individuals where there is evidence of single-leg or global postural
stability impairments. Asymmetry of footwear also needs to be considered as a
contributing factor in lower limb intrinsic injuries where mediolateral stability is
important. Ideally all footwear used by the individual needs to be assessed as different
designs may have unique and even opposite patterns of wear or collapse. Outersole
wear and midsole or innersole compression can attenuate, neutralise or increase the
asymmetry. Patterns of asymmetric wear in 1 year old footwear are more likely to be
laterally worn and consideration should be given to repairing or replacing footwear
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before degradation occurs. An alternative would be to neutralise the asymmetry. The
length of time spent in asymmetric footwear is important as this study shows a 20 min
brisk walk disturbed mediolateral postural stability proportional to the extent of the
asymmetry. Footwear assessment needs to include the age and frequency of shoe use
and amount of asymmetry, if any, as an indicator of the length of time the individual
spends in that particular shoe.
6.8
Heel-Raise and Hip-Flexion Tasks
In this study, heel-raise performance differentiated between neutral and 1 mm of
simulated lateral wear (Sections 2.7.1, 4.2.5 and 4.4.3). Thus, the single-leg heel-raise
task could be a key part of any clinical assessment relating to neuromuscular
performance. It can be performed barefoot and in footwear and used to compare left
and right leg function. There is large variability in the performance between
individuals, so each individual’s maximum needs to be determined. Since heel-raise
rate was unaffected by age, BMI and gender but influenced by pre-existing footwear
asymmetry it may be the most useful variable in a clinical setting.
The transition from double-to-single leg stance may not be an appropriate task for
healthy individuals when investigating small changes to the foot-ground interface on
postural stability (Sections 2.7.2, 5.2.2 and 5.4.6). Alternately other kinetic and
kinematic measures while performing the task need to be taken. Randomly alternating
either leg during the trials would increase the difficulty.
6.9
Footwear Selection or Design Criteria that Minimise
Asymmetry
Footwear designed for cushioning tends to compress over time, resulting in
increased mediolateral motion (Stüssi et al., 1993). Should this load be applied
excessively laterally at heel contact, inversion may be increased (Avramakis, Stakoff,
& Stüssi, 2000) and the peripheral neural afferent signals perturbed, leading to
decreased whole-body stability and performance (Perry et al., 2007; Robbins et al.,
1994). Footwear that by design increases lateral or medial loading may negatively
259
affect postural stability. Although the relationship between the extent of footwear
asymmetry and design was not specifically addressed in this study, some potential
characteristics are highlighted. Recommendations for footwear design which would
minimise the mediolateral asymmetry typically found in this study are based on the
type of footwear degradation assessed in 506 shoes. This includes footwear that is
flat, uniform density midsoles with hardness of Asker C 70 units or greater and
symmetric outer sole tread pattern.
6.10 Osteoarthritis
Lateral asymmetry was predominantly measured in footwear in this study while
simulated mediolateral asymmetry increased the magnitude of the mediolateral GRF
variability during single leg stance. Since lateral wear is dominant, and lateral
wedging or lateral stiffer midsoles are required to reduce knee adduction moments
then lateral wear should be monitored in people with knee OA. Footwear should be
repaired, replaced or neutralised where appropriate.
6.11 Take-Home Message
Footwear asymmetry is likely to affect whole-body dynamic function, performance
and balance. Mediolateral heel asymmetry difference need only be 1 mm to influence
these factors. Previously, this asymmetry difference has been considered a normal
variation in footwear degradation and hence of no importance. Small mediolateral
changes in footwear may lead to abnormal joint loading and neuromuscular
compensations needed to maintain the integrity of the human tower.
The findings of this thesis suggest that assessment of appropriate footwear should also
be performed following activity, as it was more likely for single-leg balance to be
perturbed following a 20 min walk. Removing the mediolateral asymmetry restored
dynamic function after single-leg heel-raise exercise. Similarly, walking for 20 min in
neutral footwear did not negatively affect single-leg postural stability after exercise.
Conversely, 20 min of walking in footwear with simulated variations of incremental
mediolateral heel asymmetry progressively disturbed postural equilibrium in single-
260
leg stance after exercise. Pre-existing mediolateral asymmetry in footwear influences
the performance of a dynamic task and postural stability and hence may explain
global deficits which are known to exist pre- and post-injury. Non-habituated barefoot
postural stability was more variable than in habituated footwear in this study, so
clinical assessment and rehabilitation needs to take this fact into account.
When prescribing footwear interventions, the state of current footwear used by the
individual should be considered. Lateral asymmetry is more common than medial
asymmetry, and the extent of this asymmetry should influence repair or replacement
of footwear. All footwear used by an individual should be assessed as each shoe may
show unique patterns of degradation (outer-, mid- and innersole) and differences in
asymmetric magnitude. Only assessing the sports shoe may miss evidence of
asymmetry and degradation in other footwear commonly used.
The poor foot paradigm (Section 3.1) should be re-assessed in terms of what is
normal human structure and function. The principles of evolution may help
understand what aided human survival and success (Section 2.1). Natural selection
was strong for structural and physiological adaptations allowing efficient walking and
running (Sections 2.2 and 3.2). This evolutionary well-adapted paradigm should
influence the thinking and research about present human function, structure and
wellness. What made humans so good, considering our African origins, is a question
worth pursuing.
261
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Appendices
Ethics approval Study 1…………………………………………………...309
Ethics approval Study 2 …………………………………………………..310
Participant questionnaire …………………………………………………311
Participant data collection sheet…….…………………………………….313
308
309
310
The effect of simulated asymmetric outer heel shoe wear on the
performance of single leg balance tasks
SPORTS AND INJURIES QUESTIONNAIRE
SECTION 1:
Personal and general information
[Code:_________]
Name: _____________________________ Surname:
____________________________
Address:
________________________________________________________________
_________________________________________________________________
e-mail: ____________________________________
Telephone: ________________________________
Would you like a copy of the results? Yes/No
(This page will be separated from the rest of the questionnaire to prevent
identification of participants during data capturing and analysis.)
311
performance of single leg balance tasks
SPORTS AND INJURIES QUESTIONNAIRE
SECTION 1:
Personal and general information
[Code:_________]
Date of birth: ______/_______/19______
Gender:
Male (1) / Female (2)
Occupation: _________________________________________________
Height (cm): _________
Weight (kg): ___________
Preferred Leg: Left (1)/ Right (2)
Sports participation
What is the main sport in which you currently participate?
___________________________
Approximately how many hours a week do you exercise?
____________________________
Previous injuries
Have you ever had any musculo-skeletal injuries? Please include approximate date.
Have you ever had a head injury or concussion? Please include the approximate date.
Are you currently on any prescribed medication?
Yes/No
If yes, please provide
details:____________________________________________________
312
performance of the single leg heel-raise tasks (Study 1)
SECTION 2:
DATA COLLECTION SHEET
[Code:_________]
Testing order: □ (1) Medial (2) Lateral
□ (1) Lateral (2) Medial
Preferred Stance leg: Left (1) Right (2)
SHR (s)
IV I
Base
1
IV 2
Base
2
Base
3
MHR
Trial 1
(s)
Repeated
heel
raises #
Walk rest 1 minute
Trial 3
Walk rest 1 minute
Trial 2
Walk rest 1 minute
Walk rest 1 minute
Trial 1
performance of the dynamic balance task (Study 2)
SECTION 2: RANDOMISED CONDITIONS
Balance Tasks Shoe:_______________
[Code:_________]
L (0) or R (1) leg
Condition is the same for order 7 and 8
Order :
Bf 1
Conditions: barefoot (Bf),
randomised shoe, shoe + medial (-1, -2,
-3 mm) or lateral wedge (1, 2, 3 mm)
Bf
2
3
4
5
6
7
Walk 8
20
min
Hip Flexion 1
Hip Flexion 2
Hip Flexion 3
313
Footwear Assessment (Study 1 and 2)
Shoe No 1
Age
Orthotic
No/Yes
Shoe No 2
Type/Name
Wear
Lat Med
mm L
Forefoot
mm R
Lat Med
L
Lat Med
Forefoot
R
Lat Med
9-12 months
Greater than 12 months
Type
Posting
Type/Name
Age
L Lat Med
Heel
R Lat Med
Density
L Lat Med
(Asker C) Heel
R Lat Med
0- 3 months
4-8 months
Wear
Density
(Asker C)
Age
Orthotic
No/Yes
Frequency (hrs/d)
0-3 months
Type
Posting
Frequency (hrs/d)
L Lat Med
Heel
R Lat Med
L Lat Med
Heel
R Lat Med
4-8 months
mm L
Lat Med
Forefoot
mm R
Lat Med
L
Lat Med
Forefoot
R
Lat Med
9-12 months
Greater than 12 months
Age
314

Exploring a Model of Footwear Asymmetry on Heel

Transcription

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