The cost of vision loss in Canada CNIB and the Canadian

Transcription

The cost of vision loss in Canada
Report by Access Economics Pty Limited for the
CNIB and the Canadian
Ophthalmological Society
CONTENTS
Glossary of acronyms............................................................................................................. i
Executive summary................................................................................................................ ii
1.
Background ................................................................................................................... 5
1.1
Definitions..........................................................................................................................5
1.1.1
Better eye, worse eye
5
1.1.2
Severity definitions used in this report
5
1.2 Main causes of impairment ................................................................................................5
1.2.1
Age related macular degeneration (AMD)
5
1.2.2
Cataract
5
1.2.3
Diabetic retinopathy
5
1.2.4
Glaucoma
5
1.2.5
Refractive error (RE) and other causes of vision loss
5
2.
Estimating prevalence .................................................................................................. 5
2.1
Population data..................................................................................................................5
2.1.1
Age, gender and growth
5
2.1.2
Ethnicity
5
2.2 Data sources for prevalence of vision loss.........................................................................5
2.2.1
Population-based eye studies
5
2.2.2
Canadian self-reported survey data
5
2.2.3
Data from Canadian journal articles and research studies
5
2.3 Prevalence rates for VL .....................................................................................................5
2.3.1
White population VL
5
2.3.2
Aboriginals and Visible Minorities (AVM) VL
5
2.3.3
Cataract-induced VL in AVM
5
2.3.4
VL caused by AMD, Glaucoma and RE in AVM
5
2.3.5
Diabetes and DR in the AVM population
5
2.3.6
Summary of VL in AVM populations
5
2.4 Summary ...........................................................................................................................5
3.
Health system expenditure .......................................................................................... 5
3.1
3.2
3.3
4.
Total expenditure on ‘vision care’ ......................................................................................5
Expenditure on particular eye disorders.............................................................................5
Total health system expenditure ........................................................................................5
3.3.1
Health system expenditure, top down
5
3.3.2
Health system expenditure, bottom up
5
Other financial costs .................................................................................................... 5
4.1
Productivity losses .............................................................................................................5
4.1.1
Employment participation
5
While every effort has been made to ensure the accuracy of this document, the uncertain nature of economic data, forecasting
and analysis means that Access Economics Pty Limited is unable to make any warranties in relation to the information
contained herein. Access Economics Pty Limited, its employees and agents disclaim liability for any loss or damage which
may arise as a consequence of any person relying on the information contained in this document.
4.1.2
Absenteeism from paid and unpaid work
5
4.1.3
Presenteeism
5
4.1.4
Premature mortality
5
4.1.5
Funeral costs
5
4.2 DWL from transfers............................................................................................................5
4.2.1
Lost taxation revenue
5
4.2.2
Social security payments
5
4.2.3
Deadweight losses
5
4.3 Care and other assistance.................................................................................................5
4.4 Aids and devices ...............................................................................................................5
4.4.1
Canes and accessories
5
4.4.2
Writing aids/stationery
5
4.4.3
Variable speed tape recorders
5
4.4.4
Computer voice synthesizer software
5
4.4.5
Electronic Braille display systems
5
4.4.6
Talking time pieces
5
4.4.7
Sunglasses with non-corrective lenses
5
4.4.8
Hand held magnifiers
5
4.4.9
Video magnifiers/CCTVs
5
4.4.10 Screen magnification software
5
4.4.11 Other aids for the sight impaired
5
4.4.12 Summary of aids and devices
5
4.5 Summary of other financial costs.......................................................................................5
5.
Burden of disease ......................................................................................................... 5
5.1
Willingness to pay and the value of a life year ...................................................................5
5.1.1
Measuring burden: DALYs, YLLs and YLDs
5
5.1.2
Willingness to pay and the value of a statistical life year
5
5.2 Burden of disease from vision loss ....................................................................................5
5.2.1
Disability weights
5
5.2.2
Deaths from VL
5
5.2.3
Years of life lost due to disability
5
5.2.4
Years of life due to premature death
5
5.3 Total DALYs due to VL ......................................................................................................5
6.
Summary........................................................................................................................5
Appendix A: EDPRG prevalence tables ............................................................................... 5
Appendix B: Prevalence projections by age, gender and disease .................................... 5
References .............................................................................................................................. 5
FIGURES
Figure 1-1: Vision problems among Canadian seniors (% of age group)
Figure 1-2: Prevalence of AMD by age and gender in whites (% population)
Figure 1-3: Prevalence of cataract by age and gender in whites (% population)
Figure 1-4: Rates of cataract surgery by age
Figure 1-5: Prevalence of DR by age and gender in whites (% population)
Figure 1-6: Prevalence of glaucoma by age and gender in whites(% population)
Figure 1-7: Prevalence of myopia by age and gender in whites (% population)
Figure 1-8: Prevalence of hyperopia by age and gender in whites (% population)
Figure 1-9: Prevalence of hyperopia across countries by age, gender and source study
(% population)
Figure 1-10: Prevalence of myopia across countries by age, gender and source study
(% population)
Figure 2-1: Prevalence and incidence approaches to cost measurement
Figure 2-2: Canadian population by age (’000 people), 2006 and 2031
Figure 2-3: White and AVM populations, 2006-2032 (% total)
Figure 2-4: Aboriginals and Visible Minorities, 1981-2017, selected years (%
population)
Figure 2-5: Age distribution of non-white males (% population), 2001
Figure 2-6: Age distribution of non-white females (% population), 2001
Figure 2-7: Ethnic composition of Canadian population compared to Australia’s
Figure 2-8: Prevalence of seeing disabilities by age and gender (2001)
Figure 2-9: Uncorrected VL, by ethnicity, age and gender (% population)
Figure 2-10: Under corrected VL from myopia, by ethnicity, age and gender (%
population)
Figure 2-11: Under corrected VL from hyperopia, by ethnicity, age and gender (%
population)
Figure 2-12: Canadians unable to see clearly at any distance or at all, by ethnicity, age
and gender (% population)
Figure 2-13: Cataract prevalence, by ethnicity, age and gender (% population)
Figure 2-14: Glaucoma, by ethnicity, age and gender (% population)
Figure 2-15: Causes of VL in Prince George, Canada
Figure 2-16: Myopia in Chinese children in Canada and Hong Kong
Figure 2-17: Causes of blindness by ethnicity (US)
Figure 2-18: Probability of developing VL after contracting selected diseases, by
ethnicity
Figure 2-19: Prevalence rates of VL, by ethnicity and cause, 2007
Figure 2-20: Prevalence of VL, by cause, 2007-2032
Figure 2-21: Prevalence of VL by gender, 2007 to 2032
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Figure 2-22: Projections of VL, by ethnicity, 2007 to 2032
Figure 2-23: Relative share of total VL, by ethnicity, 2007 to 2032
Figure 3-1: Canadian health system expenditure, 2007 (% of total)
Figure 3-2: Expenditure on vision care, Canada, 1975-2007
Figure 4-1: DWL of taxation
Figure 4-2: Comparison of assistance with activities of daily living between study
groups
Figure 5-1: Loss of wellbeing due to VL (DALYs), by age and gender, 2007
Figure 6-1: Financial costs of VL, by type of cost (% total)
Figure 6-2: Financial costs of VL, by bearer (% total)
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TABLES
Table 2–1: Canadian population projections, males (‘000), 2006-2031, selected years
Table 2–2: Canadian population projections, females (‘000), 2006-2031, selected years
Table 2–3: Ethnic composition of Canadian population (% total), 2001
Table 2–4: Prevalence of diabetes, by age and gender, 2005 (%)
Table 2–5: CCHS prevalence of eye diseases in AVM
Table 2–6: Causes of blindness in CNIB clients (2007)
Table 2–7: Prevalence of POAG among the Eskimo (%)
Table 2–8: Prevalence of diabetes among Canadian Aboriginal peoples (1991)
Table 2–9: Prevalence of blindness by cause, 2006 to 2031 (% population)
Table 2–10: causes of VL, by disease, in white populations
Table 2–11: Prevalence of VL due to AMD, by severity (% of age group)
Table 2–12: Prevalence rates for VL from cataracts, by age and severity (%)
Table 2–13: Prevalence rates for vision impairment (<6/12) from DR, and proportion by
stage of vision loss
Table 2–14: Proportion of people with glaucoma by age and severity (%)
Table 2–15: Prevalence rates for VL from RE, by age and severity (%)
Table 2–16: Estimated VL prevalence in Canadian whites by disease and age
Table 2–17: Prevalence of VL in US whites with cataracts (2000)
Table 2–18: Prevalence of VL in US blacks with cataracts (2000)
Table 2–19: Prevalence of VL in US Hispanics with cataracts (2000)
Table 2–20: Prevalence of VL in US ‘Other’ with cataracts (2000)
Table 2–21: Relative risk of developing VL from cataracts, by race
Table 2–22: Prevalence of VL in whites with cataract, by age
Table 2–23: Prevalence of VL in non- whites with cataract, by age
Table 2–24: Prevalence of cataract-induced VL in Canadian AVM, by age
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Table 2–25: Prevalence of eye diseases by ethnicity, US, 2000
Table 2–26: Causes of VL by ethnicity
Table 2–27: Prevalence of VL, by ethnicity and cause, US, 2000
Table 2–28: Prevalence (%) of VL within specified diseases, by ethnicity
Table 2–29: Relative risk of VL by eye disease, non-whites to whites
Table 2–30: Prevalence of eye diseases in whites
Table 2–31: Fraction of whites with each eye disease who have VL, by age and gender
(%)
Table 2–32: prevalence of VL within disease groups, non-whites
Table 2–33: Prevalence of VL in AVM
Table 2–34: Under corrected VL in AVM
Table 2–35: Prevalence of VL from DR within diabetic AVM groups
Table 2–36: Prevalence of diabetes in AVM population, 2005 (%)
Table 2–37: Estimated prevalence of DR-induced VL in AVM
Table 2–38: Prevalence of VL in AVM by age, gender and disease
Table 2–39: Prevalence of VL, by cause and ethnicity, 2007
Table 2–40: All vision loss, by age, gender and ethnicity, 2007
Table 2–41: Cataract vision loss, by age, gender and ethnicity, 2007
Table 2–42: DR vision loss, by age, gender and ethnicity, 2007
Table 2–43: Glaucoma vision loss, by age, gender and ethnicity, 2007
Table 2–44: AMD vision loss, by age, gender and ethnicity, 2007
Table 2–45: RE/Other vision loss, by age, gender and ethnicity, 2007
Table 3–1: Total expenditure on certain eye procedures, 2004-05
Table 3–2: Drug expenditure on nervous system and sense organ disorders, 1998
Table 3–3: Expenditure on nervous system and sense organ disorders (1998)
Table 3–4: Frequency of selected hospital procedures (2001)
Table 3–5: Rebates for certain ophthalmological procedures in Ontario (2006)
Table 3–6: Average treatment costs for neovascular AMD (2005)
Table 3–7: Estimated VL health system expenditure (top down), 2007
Table 4–1: Estimated AWE, by age and gender, 2007
Table 4–2: percentage of population employed, by age and gender
Table 4–3: Provincial sales taxes
Table 4–4: Income sources (CNIB)
Table 4–5: VL-related social security payments and beneficiaries
Table 4–6: Excess usage of social security payments
Table 4–7: Annual direct AMD non-medical related utilisation costs per person (2005$)
Table 4–8: Canes/accessories for the blind (2000-01$)
Table 4–9: Writing and stationery items (2000-01$)
Table 4–10: Talking time pieces (2000-01$)
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Table 4–11: Sunglasses with non-corrective lenses (2000-01$)
Table 4–12: Hand held magnifiers (2000-01$)
Table 4–13: Other stationery (2000-01$)
Table 4–14: Large button telephones (2000-01$)
Table 4–15: Summary of aids and devices (2000-01$)
Table 4–16: Estimates of additional aids and devices
Table 4–17: Summary of other financial costs of VL, 2007
Table 5–1: Value of a statistical life in Canadian studies ($ million)
Table 5–2: Estimated years of healthy life lost due to disability (YLD), 2007 (DALYs)
Table 5–3: Years of life lost due to premature death (YLL) due to VL, 2007
Table 5–4: Net cost of lost wellbeing, $million, 2007
Table 6–1: VL, total costs by type of cost and bearer, 2007
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GLOSSARY OF ACRONYMS
AMD
AVM
AWE
BMES
CACS
CCHS
CCTV
CERA
CIHI
CNIB
COS
DALY
DR
DWL
EDPRG
GST
HST
ICES
MVIP
NGS
NHEX
NPHS
PALS
POAG
PST
RE
UK
US
UV
VL
VSL(Y)
age related macular degeneration
Aboriginal and Visible Minorities
Average Weekly Earnings
Blue Mountains Eye Study
Comprehensive Ambulatory Classification System
Canadian Community Health Survey
closed circuit television
Centre for Eye Research Australia
Canadian Institute for Health Information
CNIB
Canadian Ophthalmological Society
Disability Adjusted Life Year
diabetic retinopathy
deadweight loss
Eye Disease Prevalence Research Group
Goods and Services Tax
Harmonized Sales Tax
Institute for Clinical Evaluative Sciences
Melbourne Visual Impairment Project
National Grouping System
National Health Expenditure database
National Population Health Survey
Participation and Activity Limitation Survey
Primary Open Angle Glaucoma
Provincial Sales Taxes
refractive error
United Kingdom
United States
ultraviolet
vision loss
Value of a Statistical Life (Year)
i
EXECUTIVE SUMMARY
This report estimates the cost of vision loss (VL) in Canada, utilising a prevalence-based
approach. Direct health system expenditures on visually impairing eye conditions are
included, as well as other financial costs (such as productivity losses) and the value of the
loss of healthy life (measured in Disability Adjusted Life Years or DALYs).
Prevalence of vision loss
A variety of data sources were used to construct a model of Canadian VL by age, gender,
ethnicity, severity and type. In 2007, there were an estimated 816,951 Canadians with
VL.

Of this total, 780,534 (95.5%) were white and 36,416 (4.5%) were Aboriginals and
Visible Minorities (AVM).

‘Refractive Error and Other’ is the main source of VL for the white population (68.1% of
the total), and cataract is the main cause of VL in AVM (36.1% of the total)1.

For whites, the second largest source of VL is cataract (15.5%) and, for the AVM
population, DR is the second largest source (24.4% of the total).

AVM have lower prevalence of VL for all diseases other than DR, largely due to lower
prevalence of eye diseases at equivalent ages to whites, a younger age profile, and
less likelihood of developing VL once they have contracted a given eye disease.
PREVALENCE OF VL, BY CAUSE AND ETHNICITY, 2007
All ethnicities
White
AVM
Number % total Number % total Number % total
1
AMD
Cataract
DR
Glaucoma
RE/Other
89,241
133,836
29,920
24,937
539,236
10.9%
16.4%
3.7%
3.1%
66.0%
84,641
120,685
20,992
22,565
531,650
10.8%
15.5%
2.7%
2.9%
68.1%
All VL
817,171
100.0%
780,534
100.0%
4,380
13,151
8,928
2,373
7,586
36,417
12.0%
36.1%
24.5%
6.5%
20.8%
100.0%
‘Other’ represents minor diseases – ie, not the ‘big five’ of cataract, diabetic retinopathy (DR), age-related
macular degeneration (AMD), glaucoma, or refractive error (RE). ‘Other’ diseases have not been the subject of
population eye health studies.
ii
PREVALENCE RATES OF VL, BY CAUSE AND ETHNICITY, 2007
3.5%
All races
White
AVM
3.0%
3.0%
2.5%
Prevalence (%)
2.5%
2.0%
2.0%
1.6%
1.5%
1.0%
0.4%
0.1%
0.5% 0.1%
0.1%
0.3%
0.2%
0.1% 0.1%
0.0%
0.1%
0.6%
0.3%
0.5%
0.0%
AMD
Cataract
DR
0.1%
Glaucoma RE/Other
All VI
The prevalence of VL is projected to almost double in absolute numbers, and increase from
2.5% of the population in 2007 to 4.0% in 2032.

VL affects women more than men, reflecting greater longevity in females. In 2007,
females accounted for 58.4% of VL; by 2032, this will have fallen slightly to 56.3%.

Despite the fact that the AVM share of the total population is rapidly increasing, the
increase in this group’s share of VL at the end of the projection period is less than
commensurate, partly due to AVM having a considerably younger age profile than the
white population with no substantial aging over the forecast period.
PREVALENCE OF VL, BY CAUSE, 2007-2032
4.5%
4.0%
All VI
Cataracts
DR
Glaucoma
AMD
RE/Other
3.5%
2.5%
2.0%
1.5%
1.0%
0.5%
2032
2031
2030
2029
2028
2027
2026
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
0.0%
2007
Prevalence (%)
3.0%
iii
Costs
In 2007, the financial cost of VL was $15.8 billion. Of this:

$8.6 billion (54.6%) was direct health system expenditure;

$4.4 billion (28.0%) was productivity lost due to lower employment, absenteeism and
premature death of Canadians with VL;

$1.8 billion (11.1%) was the DWL from transfers including welfare payments and
taxation forgone;

$0.7 billion (4.4%) was the value of the care for people with VL; and

$305 million (1.9%) was other indirect costs such as aids and home modifications and
the bring-forward of funeral costs.
Additionally, the value of the lost wellbeing (disability and premature death) was a
further $11.7 billion.
VL, TOTAL COSTS BY TYPE OF COST AND BEARER, 2007
Individuals
Family/
Friends
Federal
Government
Provincial
Governments
Society/
Other
Employers
Total
Total cost ($ million)
Burden of disease
Health system costs
Productivity costs
Carer costs
Other Indirect costs
Deadweight losses
Transfers
Total financial costs
Total costs including
burden of disease
11,710
1,499
2,847
0
61
0
-917
3,490
15,200
0
0
0
413
62
0
0
474
0
388
886
218
0
0
917
2,409
0
5,670
619
0
61
0
0
6,350
0
0
80
0
61
0
0
141
0
1,081
0
62
61
1,757
0
2,960
11,710.4
8,637.9
4,431.4
692.8
304.9
1,757.0
0
15,824
474
2,409
6,350
141
2,960
27,534
Cost per person with visual impairment ($)
14,334
0
0
0
0
0
14,334
Health system costs
1,835
0
475
6,941
0
1,323
10,573
Productivity costs
Carer costs
Deadweight losses
Transfers
burden of disease
3,485
0
74
0
-1,122
4,272
0
505
76
0
0
581
1,084
267
0
0
1,122
2,948
757
0
74
0
0
7,773
98
0
74
0
0
172
0
76
74
2,151
0
3,624
5,424
848
373
2,151
0
19,370
18,606
581
2,948
7,773
172
3,624
33,704
Burden of disease
In per capita terms, this amounts to a financial cost of $19,370 per person with VL per
annum. Including the value of lost wellbeing, the cost is $33,704 per person per annum.
iv
FINANCIAL COSTS OF VL, BY TYPE OF COST (% TOTAL)
DWL
11.1%
Indirect Costs
1.9%
Carer Costs
4.4%
Productivity Costs
28.0%
Health System Costs
54.6%
Individuals with VL bear 22.1% of the financial costs, and their families and friends bear a
further 3.0%. Federal government bears 15.2% of the financial costs (mainly through
taxation revenues forgone and welfare payments). Provincial governments bear 40.1% of
the costs, reflecting the nature of Canada’s Federal system, while employers bear 0.9% and
the rest of society bears the remaining 18.7%.
If the burden of disease (lost wellbeing) is included, individuals bear 55.2% of the costs and
Provincial governments bear 23.1% while the Federal government bears a lesser 8.7%, with
family and friends 1.7%, employers 0.5% and others in society 10.8%.
FINANCIAL COSTS OF VL, BY BEARER (% TOTAL)
Society/Other
18.7%
Individuals
22.1%
Employers
0.9%
Family/Friends
3.0%
Federal Government
15.2%
Provincial Governments
40.1%
v
Finally, an important finding from this analysis was the observation that, for an advanced
Western nation, Canada has a serious deficiency in eye health data. CNIB’s Health
Economic Statement (http://www.costofblindness.org/media/health-state.asp) observes
that, with respect to blindness and vision loss, there is ‘strong argument for saying that
Canada has the worst record of supporting research of all the G8 countries’. The importance
of good eye health to Canadians is shown from survey data in the same document revealing
that two-thirds of Canadians would cash in all their savings or sell everything they owned to
save their eyesight. With a rapidly aging population, it is high time for a Canadian population
eye health study to monitor incidence, prevalence and morbidity outcomes and economic
impacts more robustly in the future.
Access Economics
12 December 2008
vi
1. BACKGROUND
This report estimates the cost of vision loss (VL) in Canada, utilising a prevalence-based
approach. Direct health system expenditures on visually impairing eye conditions are
included, as well as other financial costs (such as productivity losses) and the value of the
loss of healthy life (measured in Disability Adjusted Life Years or DALYs).
1.1
DEFINITIONS
Statistics Canada (2004a) reported that the majority (51%) of Canadians had some form of
‘vision problem’ in 2003, while Statistics Canada (2001) found that that 2.5% had a ‘visual
disability’. A ‘vision problem’ is not considered a visual disability if it can be corrected
(eg, with glasses or contact lenses for refractive error - RE). Figure 1-1 shows the
differences between the two categories within age and gender cohorts for Canadian seniors
(people aged 65 years or older), where prevalence is understandably higher (70%-90%).
FIGURE 1-1: VISION PROBLEMS AMONG CANADIAN SENIORS (% OF AGE GROUP)
100%
90%
80%
Prevalence (%)
70%
60%
Male, uncorrected
50%
Male, corrected
40%
Female, uncorrected
Female, corrected
30%
20%
10%
80+
75 to 79
70 to 74
65 to 69
All Seniors
0%
Y e a rs o f a ge
Source: Statistics Canada (2004a).
In this report, the term ‘vision loss’ rather than ‘visual disability’ will be used.
Vision loss is broadly defined as a limitation in one or more functions of the eye or visual
system, most commonly impairment of visual acuity (sharpness or clarity of vision), visual
fields (the ability to detect objects to either side or above or below the direction in which the
person is looking) and colour vision.
1
Normal vision is recorded as 20/20 in the Imperial system used in Canada (6/6 in metric),
which means that a person can see at 20 feet (6 meters) what a person with normal vision
can see at 20 feet. Degrees of VL are measured similarly, where the first number in the
measure is the furthermost distance at which the person can clearly see an object and the
second number is the distance at which a person with normal vision could see the same
object. For example, 20/40 vision means that the person can clearly see at 20 feet (but not
more) an object that a person with unimpaired vision could see at 40 feet (but not more).
The Blind Persons Regulations, Consolidated Regulations of Canada 1978 (Chapter 371A)2
states that ‘a person shall be considered legally blind whose central acuity does not exceed
20/200 in the better eye with correcting lenses’. This means that if a person with their
glasses on can see the big 'E' on a Snellen eye chart, but none of the other optotypes, for
legal purposes they are considered blind and are eligible for certain government tax credits
as well as concessions from some retailers and other service providers. The Canadian
definition of legal blindness also includes ‘or a visual field extent of less than 20 degrees in
diameter horizontally’.
1.1.1
BETTER EYE, WORSE EYE
VL can differ from one eye to the other (asymmetrical vision loss). As a result of this,
prevalence rates can be reported for either the better or the worse eye in terms of the extent
of vision loss. Asymmetrical vision loss, however, has little impact on function or disability,
and indeed, it is often only when vision loss becomes bilateral that it is identified and treated.
When reporting prevalence rates, better eye measures would provide conservative
estimates, while worse eye measures may tend to overstate costs and impairment.
In this study, the conservative approach has thus been to report VL prevalence for the
better eye.
SEVERITY DEFINITIONS USED IN THIS REPORT
1.1.2
Best corrected visual acuity (BCVA) is defined as the best possible vision a
person can achieve with corrective lenses measured in terms of Snellen lines on
an eye chart.
Common definitions for visual acuity used in Canada (Jutai et al, 2006), and in this report are
as follows.

Blindness is defined as BCVA of 20/200 or worse (≤6/60) in the better-seeing eye.

Vision loss is defined as BCVA less than 20/40 (<6/12) in the better-seeing eye. It
thus comprises blindness and low vision.

Low vision is defined as VL that is not blindness, and is categorized as:

mild VL – BCVA worse than 20/40 (<6/12) but better than or equal to 20/60
(6/18) in the better-seeing eye; and

2
moderate VL – BCVA worse than 20/60 (<6/18) but better than or equal to
20/200 (6/60) in the better-seeing eye.
http://www.amdcanada.com/template.php?section=4&lang=eng&subSec=3d&content=4_3 (accessed 28 March
2008)
2
1.2
MAIN CAUSES OF IMPAIRMENT
1.2.1
AGE RELATED MACULAR DEGENERATION (AMD)
AMD is an incurable eye disease and a leading cause of blindness in elderly people. The
macula is the part of the retina that enables central vision and the seeing of fine detail.
Damage to the macula is characterized by a ‘black spot’ – losing the centre of the picture. In
‘early AMD,’ small yellow deposits called drusen form under the macula. Vision is usually
lost with more advanced stages of AMD. There are two types of ‘late AMD’.

Dry (geographic/atrophic): In around one third of cases of late AMD, the macula
thins. Vision loss is directly related to the location and amount of retinal thinning, but
the progress of dry AMD is slower than that of the ‘wet’ type. There is no known
treatment or cure for the ‘dry’ type of AMD.

Wet (exudative/neovascular): Two thirds of those with late AMD have this type.
Abnormal blood vessels grow under the retina and macula; these vessels bleed and
leak fluid, causing the macula to bulge or lift up. Vision loss may be rapid and severe.
Thermal laser surgery may be used in the early stages and may prevent severe eye
damage for some patients. Photodynamic laser therapy with verteporfin provides an
improvement over thermal laser treatment, but does not preclude recurrence, so that at
best it slows the rate of vision loss.
Causes of AMD are not well understood, but may include age and a genetic component, with
family history increasing the risk of AMD three to four times. People who smoke are twice as
likely to develop AMD. People who have a family history of AMD and smoke are up to 144
times more likely to develop the disease. In summary, in most cases there is no effective
prevention of or treatment for AMD. Because AMD is painless, usually progresses slowly
and generally occurs in one eye first, it may be difficult to self-detect AMD early (Access
Economics, 2006).
Current treatments for AMD, such as photodynamic therapy, are limited both in terms of their
ability to retard progression of disease and thus loss of vision, as well as only being effective
for a proportion of people with neovascular AMD. However, emerging therapies have the
potential to enhance the efficacy and coverage of treatment options for people with AMD.

Anti-angiogenesis is a treatment that aims to block the process of angiogenesis in
neovascular AMD. Theoretically this will retard progression of neovascular AMD and
reduce its recurrence. Anti-angiogenesis treatments include:
o
Pegaptanib (Macugen). This requires six weekly injections in the affected eye
over a period of at least two years. Pegaptanib has been shown to retard the
progression of wet AMD.
o
Ranibizumab (Lucentis) is new treatment, shown to be effective in both
retarding the progression of wet AMD and restoring some vision to a
significant number of patients.
o
Bevacizumab (Avastin) has been fairly widely used ‘off label’ for AMD,
although it is not indicated for this condition. As yet, no extensive head to
head clinical trials have been conducted comparing bevacizumab and
ranibizumab with respect to both safety and efficacy.
Figure 1-2 shows the prevalence of AMD by gender among whites, based on an international
meta-analysis of these ethnicities by the Eye Disease Prevalence Research Group – EDPRG
(Congdon et al, 2004a). Details of the source studies used by the EDPRG are provided in
3
Appendix A, and include studies from the United States (US), West Indies, Australia and the
Netherlands.
FIGURE 1-2: PREVALENCE OF AMD BY AGE AND GENDER IN WHITES (% POPULATION)
14%
12%
White Female
Prevalence (%)
10%
8%
White Male
6%
4%
2%
85+
80-84
Years of age
75-79
70-74
65-69
60-64
55-59
50-54
0%
Note: See Appendix A for underlying data.
Source: Congdon et al (2004a) and Access Economics (2006).
1.2.2
CATARACT
A cataract is a cloudy area in the eye's lens that forms when proteins clump together. Over
time, the cataract may grow larger and cloud more of the lens, making it hard to see. The
most common symptoms are blurry vision, problems with light, ‘faded’ colours, double or
multiple vision and the need for frequent changes in glasses or contact lenses.
The four main types of cataract are age related (most common), congenital, secondary
(eg, due to diabetes or steroid use) and traumatic (eg, due to eye injury). Causes of cataract
are still uncertain, although age, smoking, diabetes and ultraviolet (UV) exposure have been
shown to increase risk. Detection is through an eye examination including a visual acuity
test (eye chart test) and pupil dilation (where the pupil is widened with eye drops to allow the
eye care professional to see more of the lens and look for other eye problems).
Cataract surgery may be indicated to improve vision, with the cloudy lens removed and
replaced with a substitute lens. Surgery is safe and very effective, with almost all people
having better vision and improved quality of life afterward, and only a small percentage
experiencing complications such as infection, bleeding or inflammation. Cataract surgery is
generally performed as same-day surgery without general aesthetic, with a six week total
recovery period.
4
Figure 1-3 shows the prevalence of cataract by age, gender and ethnicity.
FIGURE 1-3: PREVALENCE OF CATARACT BY AGE AND GENDER IN WHITES (% POPULATION)
80%
70%
White Female
60%
White Male
Prevalence (%)
50%
40%
30%
20%
10%
80+
75-79
Years of age
70-74
65-69
60-64
55-59
50-54
40-49
0%
5
Taylor (2001) shows that, in Australia, rates of cataract surgery double with each decade of
life. Figure 1-4 shows rate of cataract by age group. While younger people have lower rates
of cataract surgery than older cohorts, because there are fewer people in the oldest cohorts3,
the average age of cataract surgery in Canada is 74 years4. Conversely, while surgery rates
increase in older cohorts, prevalence of cataract increases faster still, leading to higher rates
of VL in the oldest of the old.
FIGURE 1-4: RATES OF CATARACT SURGERY BY AGE
Source: Taylor (2001).
1.2.3
DIABETIC RETINOPATHY
Diabetic retinopathy (DR) is a complication of diabetes mellitus, usually affecting both eyes,
wherein microaneurysms develop on the tiny blood vessels inside the retina. As the disease
progresses, some blood vessels that nourish the retina are blocked, causing vision loss
through either proliferative retinopathy or macular edema.
Left: Normal vision. Right: The same scene as it might be viewed by a person with DR.
DR often has no early symptoms. Sometimes the person sees specks of blood, or spots,
‘floating’ in their vision. Diagnosis can be made via a visual acuity test (eye chart test),
dilated eye examination, retinal photography and/or fluorescein angiogram. Macular edema
6
3
There are over ten times as many Canadian septuagenarians as nonagenarians.
4
Canadian Ophthalmological Society, correspondence of 11 April 2008.
is treated with focal laser surgery, which stabilizes vision and reduces the risk of vision loss
by 50%.
Proliferative retinopathy is treated with scatter
laser surgery that, while it can worsen peripheral,
colour and/or night vision, can save the rest of a
person’s sight.
If bleeding is severe and
persistent, a vitrectomy may be necessary, where
blood and gel are removed from the centre of the
eye and replaced with a salt solution, under local
or general anesthetic.
Although both laser treatment and vitrectomy can
effectively reduce vision loss they do not cure DR, and the patient remains at risk for new
bleeding. Multiple treatments may be necessary.
To prevent the onset and progression of DR (and the need for surgery), people with diabetes
should control their levels of blood sugar, blood pressure and blood cholesterol. Early
diagnosis and treatment can prevent almost all severe vision loss. The earlier treatment is
received, the more likely it is to be effective. Prevalence is shown in Figure 1-5.
7
FIGURE 1-5: PREVALENCE OF DR BY AGE AND GENDER IN WHITES (% POPULATION)
8%
7%
6%
Prevalence (%)
5%
4%
3%
White Female
2%
White Male
1%
Years of age
75+
65-74
50-64
40-49
18-39
0%
1.2.4
GLAUCOMA
Glaucoma is a group of diseases that, while initially asymptomatic, can damage the eye's
optic nerve and result in blindness. The optic nerve comprises nerve fibers that connect the
retina with the brain. In the front of the eye is a space called the anterior chamber – clear
fluid flows in and out of this space, leaving the chamber at the angle where the cornea and
iris meet. When the fluid reaches the angle, it flows through a spongy meshwork, like a
drain, and leaves the eye.
Primary open-angle glaucoma (POAG), the most common type, occurs when, for unknown
reasons, the fluid passes too slowly through the meshwork drain. As the fluid builds up, the
pressure inside the eye rises. Unless the pressure at the front of the eye is controlled, it can
damage the optic nerve and cause vision loss. Although people can see objects clearly in
front of them, they miss things to the side and out of the corner of their eye. Peripheral vision
may deteriorate without treatment, like looking through a tunnel, until there is no vision left.
Left: Normal vision. Right: The same scene as it might be viewed by a person with glaucoma.
8
Other less common types of glaucoma include:

Closed-angle glaucoma, in which the fluid at the front of the eye is blocked from
reaching the angle, resulting in a sudden increase in pressure, pain, redness and
blurred vision. Immediate (medical emergency) laser surgery is required to clear the
blockage and protect sight.

Congenital glaucoma, occurring in children born with defects in the angle of the eye
that slow fluid drainage, causing cloudy eyes, sensitivity to light and excessive tearing.
Prompt surgery provides an excellent chance of saving vision.

Secondary glaucoma, which develops as a complication of other medical conditions,
such as surgery, advanced cataract, eye injuries, certain eye tumours, uveitis (eye
inflammation), diabetes or the use of corticosteroid drugs. Treatment includes
medicines and laser or conventional surgery.
Increased risk for glaucoma occurs with age, family history and ethnicity. Glaucoma is
detected through an eye examination including visual acuity, visual field, tonometry and optic
nerve examination.
Although there is no cure for glaucoma, early diagnosis and treatment may help protect eyes
against serious vision loss and blindness. Treatments include:

Eye drops (very common) – eye drops taken several times a day can lower pressure
by helping fluid drain from the eye or causing the eye to make less fluid. Rare side
effects include headaches or eye irritation.

Laser surgery (‘laser trabeculoplasty’) – helps fluid drain from the eye by burning
holes in the meshwork with a high-energy light beam. The effects of laser surgery
wear off so that, after two years, the pressure increases again in more than half of all
patients. Repeating laser surgery is often not useful.

Conventional surgery – can make a new opening for the fluid to leave the eye. Such
surgeries are often performed after eye drops and laser surgery have failed to control
pressure. Surgery is around 80-90% effective at lowering pressure. However, if the
new drainage opening closes, a second operation may be needed. Conventional
surgery works best in the absence of other previous eye surgery.
Possible side effects of glaucoma surgery include cataract, inflammation or infection inside
the eye, and swelling of blood vessels behind the eye – all of which are treatable. In some
cases, vision may worsen after surgery.
9
FIGURE 1-6: PREVALENCE OF GLAUCOMA BY AGE AND GENDER IN WHITES(% POPULATION)
8%
7%
White Female
Prevalence (%)
6%
5%
White Male
4%
3%
2%
1%
80+
75-79
Years of age
70-74
65-69
60-64
55-59
50-54
40-49
0%
1.2.5
REFRACTIVE ERROR (RE) AND OTHER CAUSES OF VISION LOSS
A large part of remaining vision loss is caused by RE. Less common conditions such as
neuro-ophthalmic disorders, retinitis pigmentosa and other retinal conditions account for the
remaining prevalence of VL and blindness.
As noted above, RE is the most frequent yet most easily correctible source of eye problems
in Canada, occurring when optical defects result in light not focusing properly on the retina.
Myopia (near-sightedness with blurry distant vision) and hyperopia (farsightedness with
close objects blurry) are the most well-known RE. Most infants have some degree of
hyperopia, although vision usually normalizes by six years of age. Most myopia occurs later
during adolescence. The extent of RE is measured in diopters. Other common forms of REs
include astigmatism (uneven focus) and presbyopia (age related problem with near focus).
Myopia is a very common disorder. Prevalence is greater in women
through age 60, after which rates become more comparable between
genders. Myopia affects more whites than other races, and is generally
less frequent with age, Hyperopia is less common, but prevalence
generally increases with age. It is also most frequent in Whites. Prevent
Blindness America (2002:12)
Almost all RE can be corrected by eyeglasses or contact lenses. Refractive
surgery is another alternative treatment, but one not without risk.
Figure 1-7 and Figure 1-8 highlight that RE is less common in males than females. Myopia
tends to decrease with age, whereas hyperopia increases. (Older black males have
10
significantly less of either condition than other groups – hyperopia is over 18 times more
prevalent in older white females than equally aged black males.)
FIGURE 1-7: PREVALENCE OF MYOPIA BY AGE AND GENDER IN WHITES (% POPULATION)
50%
45%
40%
White Female
35%
White Male
Prevalence (%)
30%
25%
20%
15%
10%
5%
80+
75-79
Years of age
70-74
65-69
60-64
55-59
50-54
40-49
0%
Source: Congdon et al (2004a) and Access Economics (2006). Note: Myopia = (-1.00 diopters or worse).
FIGURE 1-8: PREVALENCE OF HYPEROPIA BY AGE AND GENDER IN WHITES (% POPULATION)
30%
White Female
25%
White Male
Prevalence (%)
20%
15%
10%
5%
80+
75-79
Years of age
70-74
65-69
60-64
55-59
50-54
40-49
0%
Source: Congdon et al (2004a) and Access Economics (2006). Note: Hyperopia = (+3.00 diopters or worse).
11
RE is the most common source of VL in Western countries; Figure 1-9 and Figure 1-10 show
that population-based eyes studies demonstrate little variance in the prevalence of hyperopia
and myopia in white populations across countries with similar cultures and income levels.
12
FIGURE 1-9: PREVALENCE OF HYPEROPIA ACROSS COUNTRIES BY AGE, GENDER AND SOURCE STUDY (% POPULATION)
Prevalence of hyperopia of +3 diopters or greater in white persons (A) and black and Hispanic persons (B). BES= Baltimore Eye Study; BDES=Beaver Dame Eye Study;
BMES=Blue Mountains Eye Study; RS=Rotterdam Study; Melbourne VIP = Melbourne Visual Impairment Project; Proyecto VER=Vision Evaluation and Research.
Source: Congdon et al (2004b).
13
FIGURE 1-10: PREVALENCE OF MYOPIA ACROSS COUNTRIES BY AGE, GENDER AND SOURCE STUDY (% POPULATION)
Prevalence of myopia of -1 diopter or less in white persons (A) and black and Hispanic persons (B). BES= Baltimore Eye Study; BDES=Beaver Dame Eye Study; BMES=Blue
Mountains Eye Study; RS=Rotterdam Study; Melbourne VIP = Melbourne Visual Impairment Project; Proyecto VER=Vision Evaluation and Research.
Source: Congdon et al (2004b).
14
2. ESTIMATING PREVALENCE
Prevalence approaches to cost estimation, for a given health condition, measure the number
of people with that given condition (in this case VL) in a base period (in this case calendar
year 2007) and the costs associated with treating them, as well as other financial and nonfinancial costs (productivity losses, carer burden, loss of quality of life) in that year, due to the
condition. This report adopts a prevalence approach to cost measurement rather than an
incidence approach, as the data sources lend themselves to utilization of such an approach,
and for consistency with other studies of the cost of VL (eg, in Australia, Japan and the US).
Figure 2-1 depicts the difference between a prevalence approach (areas A+B+C in Figure
2-1) and an incidence approach, the latter estimating the present value of the lifetime costs
of new cases of VL in 2005 (area C plus the present value of C* in Figure 2-1). Consider
person A, who first experienced VL and its impacts in 1990 and continued to experience
them until death in 2005. This person would be included in a prevalence approach (but not
in an incidence approach), although only the costs incurred in 2005 would be included (ie, A
but not A*, where A includes the present value of premature mortality costs if the death was
premature). Person B developed VL during the late 1990s and experiences impairment and
its impacts through to 2008 (with costs of B+B*+B**, shaded in blue); she also would be
counted (but only costs of B) using a prevalence approach, but not using an incidence
approach. Person C (shaded in red) is newly diagnosed with VL in 2005 and his costs in
2005 (C) would be included in a prevalence approach but not future costs (C*).
FIGURE 2-1: PREVALENCE AND INCIDENCE APPROACHES TO COST MEASUREMENT
1990
2006
2010
To estimate the number of cases of VL in the population, epidemiological data on prevalence
rates are applied to population data. Ideally for projections, the number of cases of VL
should be stratified by gender, age, ethnicity, severity (mild and moderate VL and blindness)
and cause (AMD, cataract, DR, glaucoma, RE and ‘other’). A first step is thus to assimilate
population data by gender, age and ethnicity, for 2007 and subsequent years (next section).
2.1
POPULATION DATA
2.1.1
AGE, GENDER AND GROWTH
Statistics Canada (2006) reports that Canada has the second youngest population in the
G85. In 2006, around one in seven Canadians (13.7%)6 was aged 65 years or older and
Statistics Canada (2006) projects that by 2031 these ‘senior citizens’ will account for around
5
The Group of Eight represents the world’s largest industrialised economies: US, UK, Russia, France, Germany,
Italy, Japan and Canada.
6
Statistics Canada 2006 Census Online, www.statcan.ca (Cat, No, 97-551-XCB2006005).
15
one quarter of the population (Figure 2-2)7. Thus, as many eye diseases are age related, the
overall prevalence of VL will increase over the medium term.
These projections were compiled using data from the 2001 Census. Although 2006
Census data have recently become available for that year, population projections by
five year age-gender cohorts are not yet provided by Statistics Canada from the 2006
Census. Accordingly, this report uses Statistics Canada’s existing projections8.

FIGURE 2-2: CANADIAN POPULATION BY AGE (’000 PEOPLE), 2006 AND 2031
3,000
2006
2031
2,500
Persons ('000)
2,000
1,500
1,000
500
100+
95–99
90–94
85–89
80–84
75–79
70–74
65–69
60–64
55–59
50–54
45–49
40–44
35–39
30–34
25–29
20–24
15–19
10–14
5–9
0–4
0
Age group (years)
Source: Statistics Canada (2006).
7
Statistics Canada (2006) makes projections for the entire Canadian population out to 2031, with special data
requests available out to 2056. Projections presented here are from the medium growth, medium immigration
scenario (scenario 3).
8
16
This also enables consistency with the other vision health projections (Buhrmann, forthcoming).
TABLE 2–1: CANADIAN POPULATION PROJECTIONS, MALES (‘000), 2006-2031, SELECTED YEARS
Age group
0–4
5–9
10–14
15–19
20–24
25–29
30–34
35–39
40–44
45–49
50–54
55–59
60–64
65–69
70–74
75–79
80–84
85–89
90–94
95–99
100+
Total
2006
2007
2008
2009
2010
2011
2016
2021
2026
2031
868
943
1,068
1,109
1,153
1,125
1,122
1,183
1,357
1,335
1,170
1,029
778
591
490
387
249
115
38
7
1
16,116
872
927
1,054
1,121
1,154
1,138
1,128
1,181
1,322
1,353
1,206
1,038
833
613
490
396
255
123
39
8
1
16,251
875
917
1,037
1,130
1,152
1,152
1,139
1,179
1,279
1,372
1,241
1,054
879
641
495
402
263
131
40
8
1
16,386
876
914
1,020
1,131
1,153
1,165
1,154
1,175
1,241
1,386
1,268
1,081
919
670
504
405
270
138
41
8
1
16,520
879
911
1,002
1,123
1,161
1,173
1,169
1,173
1,217
1,384
1,294
1,114
958
699
515
407
278
143
44
9
1
16,654
884
911
982
1,113
1,171
1,178
1,183
1,172
1,210
1,362
1,321
1,144
991
732
531
409
286
148
48
9
1
16,787
914
928
952
1,029
1,176
1,199
1,238
1,236
1,202
1,220
1,350
1,295
1,107
936
662
449
307
175
64
12
1
17,451
931
960
971
1,001
1,095
1,206
1,263
1,294
1,268
1,216
1,215
1,327
1,256
1,050
852
567
344
192
77
17
2
18,102
929
979
1,004
1,022
1,069
1,129
1,275
1,322
1,329
1,284
1,214
1,198
1,291
1,197
964
736
440
220
87
21
2
18,711
913
980
1,026
1,057
1,092
1,105
1,203
1,338
1,360
1,346
1,282
1,199
1,171
1,235
1,105
841
579
288
103
24
3
19,249
17
TABLE 2–2: CANADIAN POPULATION PROJECTIONS, FEMALES (‘000), 2006-2031, SELECTED YEARS
Age group
0–4
5–9
10–14
15–19
20–24
25–29
30–34
35–39
40–44
45–49
50–54
55–59
60–64
65–69
70–74
75–79
80–84
85–89
90–94
95–99
100+
Total
2006
2007
2008
2009
2010
2011
2016
2021
2026
2031
829
900
1,017
1,056
1,100
1,101
1,101
1,168
1,342
1,337
1,194
1,054
806
637
554
491
389
228
99
26
4
16,431
832
885
1,001
1,067
1,103
1,115
1,110
1,165
1,309
1,351
1,229
1,067
863
660
555
495
392
241
102
27
4
16,571
834
876
986
1,075
1,102
1,129
1,121
1,162
1,268
1,366
1,260
1,087
912
689
560
497
395
253
104
29
4
16,709
834
873
970
1,075
1,105
1,141
1,138
1,157
1,232
1,376
1,284
1,117
956
718
571
497
397
263
108
30
4
16,848
835
871
954
1,067
1,115
1,148
1,154
1,156
1,207
1,373
1,306
1,152
1,000
748
583
497
402
269
114
32
4
16,986
841
870
934
1,058
1,124
1,152
1,172
1,155
1,199
1,350
1,330
1,183
1,037
782
600
498
406
274
121
33
5
17,123
868
883
907
978
1,128
1,178
1,225
1,227
1,188
1,211
1,345
1,320
1,165
1,007
739
544
417
291
148
42
6
17,815
885
912
921
952
1,051
1,186
1,255
1,283
1,263
1,203
1,211
1,336
1,302
1,134
955
674
460
303
160
52
8
18,507
883
931
953
968
1,028
1,113
1,268
1,317
1,321
1,278
1,204
1,207
1,321
1,270
1,080
875
576
341
170
58
10
19,172
868
931
973
1,001
1,046
1,094
1,200
1,333
1,357
1,338
1,281
1,202
1,197
1,292
1,214
996
753
432
196
63
11
19,780
18
ETHNICITY
2.1.2
Canada is a racially diverse country. While ‘white’ Europeans make up the great majority of the
population (82%), the 2001 Census data showed that Aboriginals (North American Indians, Metis
and Inuit) comprised 5% while ‘Visible Minorities’ comprised 13% (East Asians – mainly Chinese),
South Asians – mainly Indians, and blacks and other migrant groups9 (Table 2–3).
TABLE 2–3: ETHNIC COMPOSITION OF CANADIAN POPULATION (% TOTAL), 2001
Ethnicity
% of population
Aboriginal
Chinese and other East Asian
South Asian
Black
Other
White
4.6%
4.1%
3.1%
2.2%
4.1%
81.7%
Source: Statistics Canada, topic-based tabulations 95F0363XCB2001004 and 97F0011XCB2001003.
Note: Shares may not sum to 100% due to rounding.
While at present whites outnumber Aboriginal and Visible Minorities (AVM) by four to one, by the
end of the projection period (2032) whites only outnumber AVM by two to one (Figure 2-3)10.
9
For consistency with Statistics Canada data, the term ‘Aboriginal’ is used in this report and ‘North American Indians’ is
used rather than ‘First Nations’. For the same reason, ‘black’ is used instead of Caribbean Canadian or African Canadian,
and ‘white’ is used instead of European or Caucasian.
10
Statistics Canada makes projections for the population as a whole to 2031, and by race to 2017. Access Economics has
extended these trends to 2032, as that represents 25 years after the base year (2007)
19
FIGURE 2-3: WHITE AND AVM POPULATIONS, 2006-2032 (% TOTAL)
90
White
Aboriginals and Visible Minorities
Percentage of Canadian population
80
70
60
50
40
30
20
10
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
0
Source: Statistics Canada (2005a, 2005b, 2006).
Statistics Canada (2005a and 2005b) makes projections for Aboriginal and, separately, Visible
Minorities populations to 2017. However, both populations’ shares of the Canadian total have been
growing in a fairly linear manner – due to high migration (Visible Minorities) and high birth rates
(Aboriginal peoples). Out to 2017, official projections maintain these trends (Figure 2-4). Access
Economics has extended the same trends from 2018 through to 2032.
20
FIGURE 2-4: ABORIGINALS AND VISIBLE MINORITIES, 1981-2017, SELECTED YEARS (% POPULATION)
25%
Visible Minorities (%)
Aboriginal Peoples
Trend
Trend
Share of population, by race
20%
15%
10%
5%
0%
1981
1986
1991
1996
2001
2006
2011
2017
In Canada, demographic aging is less of an issue for non-white populations. Aboriginals in
particular have a young age profile (over 60% are under 30 years old), although the East Asian
population is fairly evenly spread across all age groups (Figure 2-5 and Figure 2-6).
Statistics Canada (2005b) publishes an age-gender profile for Aboriginal peoples at the beginning,
middle and end (2017) of its projections. In the absence of further data, Access Economics has
assumed that the 2017 profile is maintained through to 2032. This errs on the side of conservatism,
as the Aboriginal population might age between 2017 and 2032, which would increase the
prevalence of VL.
Statistics Canada (2005a) does not publish an age-gender profile for its Visible Minorities
projections. However, given most of the growth in this population occurs through immigration, it
could reasonably be expected to maintain a similar age-gender profile to that which it has at present.
The age-gender profile (as well as total numbers) for whites was estimated as a residual after
subtracting Aboriginal and Visible Minorities (AVM) projections from Statistics Canada (2006) total
population projections.
21
FIGURE 2-5: AGE DISTRIBUTION OF NON-WHITE MALES (% POPULATION), 2001
8%
East Asian
South Asian
Black
Other Visible Minority
Aboriginal
Percent of population
7%
6%
5%
4%
3%
2%
1%
65 +
55-64
45-54
35-44
25-34
15-24
< 15
0%
Age group (years)
FIGURE 2-6: AGE DISTRIBUTION OF NON-WHITE FEMALES (% POPULATION), 2001
8%
East Asian
South Asian
Black
Other Visible Minority
Aboriginal
Percent of population
7%
6%
5%
4%
3%
2%
1%
Age group (years)
22
65 +
55-64
45-54
35-44
25-34
15-24
<15
0%
It is noteworthy that there is a strong concordance between the ethnic compositions of Canada and
Australia (Figure 2-7). Australia is also similar to Canada in culture and standard of living11, and has
similar principles and values underlying its health system.
FIGURE 2-7: ETHNIC COMPOSITION OF CANADIAN POPULATION COMPARED TO AUSTRALIA’S
100
90
Canada
Percent of Population
80
Australia
70
60
50
40
30
20
10
0
European
Asian
Aboriginal
Black /
Islander
Other /
Mixed
Note: ‘Black / Islander’ for Canada refers to blacks (72% of whom have Caribbean island heritage) and to Pacific islanders
for Australia. Australian data are 2006, Canadian data are 2001.
Source: Statistics Canada (2004b) and Statistics Canada Online Topic Based Tabulations, www.statcan.ca (Cat No
97F0010XCB2001004) and, Australian Bureau of Statistics, Australia Year Book 2007 (Cat No 1301.0).
2.2
DATA SOURCES FOR PREVALENCE OF VISION LOSS
A variety of data sources were reviewed to estimate prevalence of VL stratified by age, gender,
ethnicity, severity (mild and moderate VL and blindness) and cause (AMD, cataract, DR, glaucoma,
RE and ‘other’). Since this level of granularity is not available from any single Canadian
epidemiological data source, various data sources were combined in order to ensure that Canadian
aggregates were used wherever possible, with credible alternative sources used where there were
found to be data gaps.
Three types of data sources were used.

Population-based eye studies. These are the gold standard, where the degree, type and
cause of VL are assessed by experts over a large sample of people. However, because such
11
In 2006, according to World Bank statistics Australia’s per capita income was $US 36,000, where Canada’s was
$US 36,200 (see http://web.worldbank.org/WBSITE/EXTERNAL/DATASTATISTICS).
23
studies require large amounts of time, money and equipment, they are very rare, and none
have been conducted in Canada, although data from the EDPRG eye studies (Appendix A)
were utilised where appropriate.

Canadian surveys. These large scale collections assemble data from, typically, tens of
thousands of respondents, across all ages, genders, ethnicities and geographic areas. The
down side is that they are self-diagnosed and self-reported, and thus may suffer a substantial
degree of error. Another issue is that publicly available data are usually highly aggregated.
Relevant studies in Canada include the Canadian Community Health Survey (CCHS), the
National Population Health Survey (NPHS) – a longitudinal study, and the Participation and
Activity Limitation Survey (PALS)12.

Canadian journal articles and research studies. These often provide a great deal of detail,
but only in relation to a small subject area – eg, myopia among children of Chinese
immigrants, or use of visual support services by the poor in a particular city, for example.
Extensive literature searching has only uncovered a handful of such studies conducted in
Canada. Examples include:

Cheng et al (2007) on the prevalence of myopia in Chinese-Canadian children;




2.2.1
Hanley et al (2005) on complications of diabetes (including DR) among Aboriginal
Canadians;
Meddings et al (1998) on the relationship between the development of cataract at a
young age and socioeconomic status in British Columbia;
Chang et al (1999) on AMD in Chinese-Canadians; and
Iskedjian et al (2003) on the costs of treating patients with glaucoma in Canada.
POPULATION-BASED EYE STUDIES
Population-based eye studies in the US, Australia and the Netherlands show that the prevalence of
VL and its underlying eye diseases do not vary greatly between white populations in these countries.
Accordingly, data from these studies form the basis of estimates for the white Canadian population.
However, these population studies also show significant differences in VL prevalence between given
racial groups (eg, East Asian and black) living in wealthy countries (such as Canada) and those
living in poorer countries (eg, China, Barbados). Accordingly, wherever possible, data for non-white
groups are sourced from Canadian surveys and journal articles (see the following sections).
2.2.2
CANADIAN SELF-REPORTED SURVEY DATA
While data from national health surveys are self diagnosed and self reported, they may still be a
reasonably good indicator of overall VL, and some major eye diseases.

People generally know they have vision problems. The Canadian Ophthalmological Society’s
(2006) eye examination guidelines note that less than 1% of the population are unaware of
having decreased vision. The exception is glaucoma, where only half of those with the
condition are aware of it.

Surveys may be a reasonably accurate diagnostic tool. Djafair et al (2003) conducted an
interesting evaluation of survey questionnaires as a diagnostic tool. Administering typical
survey questions to over 500 patients in a Canadian hospital (whose VL was also able to be
12
Neither the PALS or the CCHS are published in hard copy, but selected data can be tabulated from these surveys at the
Statistics Canada website (www.statcan.ca)
24
clinically assessed) resulted in a sensitivity of 82.6% and a specificity of 88.9% for best
corrected VL.
Conversely, while rates between races are reasonably similar within the CCHS and within the
EDPRG data (Congdon et al, 2004a), they do tend to be quite different to each other. (As noted
above, the approach adopted herein is to use EDPRG data for Canadian whites, and Statistics
Canada data for the AVM population.) The only disease for which AVM prevalence is similar to US
whites is glaucoma, which is the disease least likely to be self-diagnosed as most people don’t know
they have it. Cataract rates in US whites are some three times higher than in Canadian AVM.
Refractive error rates for US whites are around ten times or more higher than Canadian AVM rates –
when both are assessed on a best-corrected basis. Moreover the age patterns (for both races) are
reversed in CCHS data (increasing with age, where EDPRG data shows decreases with age). As
eye health questions are optional for CCHS participants, the data also has a number of gaps due to
responses being too small to be statistically valid &/or not contravene privacy regulations.
2.2.2.1
PARTICIPATION AND ACTIVITY LIMITATION SURVEY (PALS, 2001)
The PALS asks respondents the following questions.

With your glasses or contact lenses, do you have any difficulty seeing ordinary newsprint?

Have you been diagnosed by an eye specialist as being legally blind?

Besides glasses or contact lenses, do you use any other aids or specialized equipment for
persons who are blind or visually impaired eg, magnifiers or Braille reading materials?
Figure 2-8 shows the prevalence of seeing disabilities according to this source’s definition, differing
somewhat from Statistics Canada (2004a) (recall Figure 1-1).
FIGURE 2-8: PREVALENCE OF SEEING DISABILITIES BY AGE AND GENDER (2001)
16%
14%
14.9%
Male
Female
11.5%
Prevalence (%)
12%
10%
8%
6.0%
6%
4%
3.3% 3.4%
2.5%
2%
0.12% 0.13%
0.44% 0.38%0.4%
0.42% 0.24%
0.4% 0.7%
0.9%
0%
0-4
5-9
10-14
15-24
25-44
45-64
65-74
75+
Age group (years)
Source: Statistics Canada Online PALS (2001) www.statcan.ca.
25
2.2.2.2
CANADIAN COMMUNITY HEALTH SURVEY (2005) AND NATIONAL POPULATION HEALTH
SURVEY (NPHS)
A major limitation for our purposes is that PALS does not provide any information about ethnicity.
The CCHS in contrast collects detailed data about ethno-cultural identities and background.
Unfortunately, in its publicly available form, the CCHS amalgamates this into only two categories
‘White’ and ‘Other’.

The CCHS classified respondents as (under corrected) hyperopic if they could not see well
enough to read ordinary newsprint (with glasses); and (under corrected) myopic if they could
not recognise a friend across the street (with glasses). The CCHS also asked respondents if
they could see at all (ie, blindness), but this was amalgamated in the category ‘myopic and
hyperopic and/or blind’.
Figure 2-9 shows that in Canada, non-whites have a higher degree than whites of uncorrected VL in
younger years, but generally lower rates in older age. This pattern is also apparent for VL from best
corrected myopia (Figure 2-10) and for Canadians unable to see clearly at any distance or at all
(Figure 2-12). There is a generally higher prevalence of VL from under corrected hyperopia among
non-whites (Figure 2-11).
FIGURE 2-9: UNCORRECTED VL, BY ETHNICITY, AGE AND GENDER (% POPULATION)
100%
90%
80%
Prevalence (%)
70%
60%
50%
White Female
White Male
Non-white Female
Non-white Male
40%
30%
20%
10%
Years of age
Source: Statistics Canada CCHS public use microdata files.
26
80 +
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
18-19
15-17
12-14
0%
FIGURE 2-10: UNDER CORRECTED VL FROM MYOPIA, BY ETHNICITY, AGE AND GENDER (% POPULATION)
8%
7%
Prevalence (%)
6%
White Female
White Male
Non-white Female
Non-white Male
5%
4%
3%
2%
1%
80 +
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
18-19
15-17
12-14
0%
Years of age
Note: Data for non-white males over 65 not supplied.
FIGURE 2-11: UNDER CORRECTED VL FROM HYPEROPIA, BY ETHNICITY, AGE AND GENDER (%
POPULATION)
6%
White Female
White Male
Non-white Female
Non-white Male
5%
3%
2%
1%
ALL AGES
80 +
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
18-19
15-17
0%
12-14
Prevalence (%)
4%
Years of age
27
FIGURE 2-12: CANADIANS UNABLE TO SEE CLEARLY AT ANY DISTANCE OR AT ALL, BY ETHNICITY, AGE
AND GENDER (% POPULATION)
8%
7%
White Female
White Male
Non-white Female
Non-white Male
Prevalence (%)
6%
5%
4%
3%
2%
1%
80 +
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
18-19
15-17
12-14
0%
Years of age
While elderly male non-whites continue to fit the pattern by having lower cataract prevalence13 than
their white contemporaries, there is a divergence for older non-white women, who have the highest
cataract prevalence (Figure 2-13).
13
The CCHS only reports cataract prevalence, not VL from cataract.
28
FIGURE 2-13: CATARACT PREVALENCE, BY ETHNICITY, AGE AND GENDER (% POPULATION)
45%
40%
35%
White Female
White Male
Non-white Female
Non-white Male
Prevalence (%)
30%
25%
20%
15%
10%
5%
80 +
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
18-19
0%
Years of age
Over most age ranges, it is non-white males who have the highest rates of glaucoma14 (Figure
2-14). Another important fact to note with glaucoma is that its prevalence appears to be increasing in
Canada. Data from various CCHSs and NPHSs compiled by Peruccio et al (2007) show that the
prevalence of glaucoma in Canadians over the age of 20 years increased by 64% between 1994
and 2003. Moreover, this is not just due to population aging, as the same trend can be seen within
each age group – and in fact the increase is highest in those under 50 years. Some of this increase
can be ascribed to improved diagnosis over this period. A similar trend is evident in diabetes, and
thus presumably DR (see discussion around Table 2–4).
14
The CCHS only reports prevalence of glaucoma, not of VL from glaucoma
29
FIGURE 2-14: GLAUCOMA, BY ETHNICITY, AGE AND GENDER (% POPULATION)
14%
12%
Prevalence (%)
10%
White Female
White Male
Non-white Female
Non-white Male
8%
6%
4%
2%
80 +
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
18-19
0%
Years of age
Diabetic Retinopathy causes around 600 new cases of blindness in Canada each year15. Despite
acknowledging that DR is ‘the leading cause of adult blindness in Canada’16 Statistics Canada does
not collect any information on this disease. (The CCHS asks people with diabetes if they have had
an eye examination where their pupils were dilated but does not provide the results of these tests.)
However, it is possible to derive the prevalence of VL from DR from the CCHS in conjunction with
another Statistics Canada publication: Wilkins and Park (1996) calculated from the 1994-95 NPHS
that people with diabetes were almost twice as likely as those without (odds ratio of 1.72) to have a
vision limitation. Most of this is likely to refer to DR, although Canadians with diabetes also have
higher rates of cataract and glaucoma than those without (James et al, 1997). Thus an upper limit
for prevalence of VL from DR could be calculated by taking each age-gender cohort in the diabetic
population (from Table 2–4) and assigning it 1.72 times the VL prevalence experienced by that
cohort in the general population. (This is discussed in more detail in section 2.3.5)
15
Public Health Agency of Canada, National Diabetes Fact Sheet 2007, http://www.phac-aspc.gc.ca/ccdpccpcmc/diabetes-diabete/english/pubs/ndfs-fnrd07-eng.html
16
http://www.statcan.ca/english/research/82-619-MIE/2005002/sequelae.htm (accessed 3 Feb 2008)
30
TABLE 2–4: PREVALENCE OF DIABETES, BY AGE AND GENDER, 2005 (%)
Age
Male
Female
All
12-14
15-19
20-24
25-34
35-44
45-54
55-64
65-74
75+
0.3
0.9
0.9
2.1
5.0
11.8
17.3
16.8
0.3
0.7
1.2
1.9
4.0
8.5
12.3
13.1
0.3
0.3
0.8
1.1
2.0
4.5
10.1
14.6
14.6
Total
5.3
4.4
4.9
Source: Statistics Canada http://www40.statcan.ca/l01/cst01/health53b.htm
One important fact to note with diabetes is that it is growing faster than population growth.
Moreover, this growth is not just due to population aging either, as the prevalence of diabetes has
increased significantly within every age-gender cohort (by an average of over 50% in the decade to
2005, potentially due to increasing rates of obesity and other risk factors). Again, as with glaucoma,
the highest increases in prevalence are in the younger ages. This could have significant
implications for the prevalence of blindness in Canada over the next 25 years. However, in the
interests of conservatism, age-gender prevalence rates were modelled to remain constant in the
future.
A summary of eye disease prevalence in AVM groups from the 2005 CCHS is contained in Table 2–
5. As noted above, for the white Canadian population, studies in the EDRPG dataset are used.
The CCHS does not report the prevalence of either AMD or DR. DR, however, can be estimated
indirectly (and is done so in Section 2.3.5, covering VL caused by DR in AVM groups). The
prevalence of AMD in Canadian AVMs is assumed to be the same as the average prevalence in
non-white Americans (from Congdon et al, 2004a).
31
TABLE 2–5: CCHS PREVALENCE OF EYE DISEASES IN AVM
Males
Cataract
Glaucoma
Hyperopia
Myopia
AMD
0.0%
0.4%
0.0%
0.2%
0.3%
0.1%
1.9%
2.0%
4.4%
11.7%
13.2%
22.9%
16.0%
21.0%
20.99%
20.99%
0.00%
0.05%
0.00%
0.15%
0.82%
0.56%
0.64%
1.18%
4.45%
1.85%
6.26%
9.53%
5.70%
5.99%
5.99%
5.99%
0.47%
1.31%
0.00%
0.00%
0.00%
0.83%
0.40%
1.46%
2.52%
1.48%
2.24%
2.53%
2.82%
2.45%
2.45%
2.45%
0.00%
0.00%
0.80%
0.00%
0.00%
0.32%
0.00%
0.10%
0.92%
0.62%
3.40%
2.16%
2.26%
2.64%
2.64%
2.64%
0.24%
0.39%
0.64%
1.06%
1.75%
2.88%
4.69%
7.55%
7.55%
15-19
20-24
25-29
0.00%
0.05%
0.09%
0.18%
0.00%
0.00%
0.00%
0.18%
2.19%
0.00%
0.00%
0.00%
30-34
0.43%
0.25%
1.42%
0.98%
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0.28%
0.56%
0.19%
1.41%
3.46%
10.05%
21.14%
34.68%
36.80%
41.99%
41.99%
41.99%
0.18%
0.50%
0.21%
0.99%
0.65%
2.34%
2.08%
3.07%
11.50%
2.95%
2.95%
2.95%
1.53%
1.63%
1.25%
3.20%
5.15%
3.02%
0.88%
0.31%
3.20%
3.19%
3.19%
3.19%
0.00%
0.00%
0.39%
0.00%
1.00%
0.87%
0.95%
3.17%
3.24%
2.55%
2.55%
2.55%
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Females
0.50%
0.70%
0.97%
1.34%
1.85%
2.57%
3.59%
5.02%
5.02%
Note: Figures in italics contain no data in original, and are interpolated from relative changes between cohorts in the same
ethnicity or gender.
Source: Source: Statistics Canada CCHS public use microdata files, Congdon et al (2004a).
2.2.3
DATA FROM CANADIAN JOURNAL ARTICLES AND RESEARCH STUDIES
2.2.3.1
CANADIAN POPULATION STUDIES
Maberley et al (2006) conducted an analysis of all ophthalmological records (around 2,500, of which
962 were suitable) in Prince George, a medium-sized Canadian city, over a five year period. They
concluded that ‘The overall prevalence of low vision and blindness in Canada are in keeping with
32
data from large population-based studies from other developed nations’. As Figure 2-15 shows,
cataract, visual pathway disorders17 and AMD were the leading causes of VL in this study.
FIGURE 2-15: CAUSES OF VL IN PRINCE GEORGE, CANADA
Other (iris, trauma, lid)
5%
Glaucoma
3%
DR
7%
Cataract
29%
Refractive
8%
Cornea / conjunctiva
11%
AMD
13%
Visual pathway
12%
Other retinal causes
12%
Source: Maberley et al (2006).
CNIB has a database of its clients that can also be used to derive an estimate of the causes of
blindness in Canada (Table 2–6), assuming that registering with CNIB is equally likely for all causes
of blindness. The fact that the elderly blind may have difficulty registering may represent a source of
bias, however.
TABLE 2–6: CAUSES OF BLINDNESS IN CNIB CLIENTS (2007)
Cause
Persons (‘000)
AMD
DR
Glaucoma
Other
50.2
7.5
7.6
49.2
Total
114.5
Source: CNIB
2.2.3.2
CHINESE CANADIANS
Chang et al (1999) reports in a study of 20,000 patients presenting for fluorescein angiography that
the rate of AMD in Chinese Canadians (30.4%) was over twice as high as in white Canadians
17
Visual pathway disorders (ICD10 H446-H48) are conditions which impede the visual pathway. Occasionally acute vision
loss is caused by homonymous hemianopia and, more rarely, cortical blindness.
33
(14.6%). From this, it may be plausible to assume that AMD in Chinese-Canadians is twice as high
as the overall population estimate provided by Maberley et al (2006).
Cheng et al (2007) report that Chinese Canadian children aged six years have a prevalence rate of
myopia of 22.4%, which is several times the prevalence reported by Robinson (1999) for Canadian
six year olds in general of 6.4%. Cheng et al (2007) also report that the prevalence of myopia
among Chinese children in Canada is broadly similar to earlier findings from Chinese children in
China (Hong Kong) – Figure 2-16. The assumption is made that Chinese-Canadian teenagers have
the same rates of myopia as do their counterparts in China in Figure 2-16. However, this appears to
decline in later years; Wong (2006) records that Chinese in China over the age of 40 and 60 years
have myopia prevalence of 22.9% and 19.4% respectively.
FIGURE 2-16: MYOPIA IN CHINESE CHILDREN IN CANADA AND HONG KONG
100
90
Prevalence of myopia (%)
80
70
60
50
40
30
Canada 2003
Hong Kong 1996
20
Hong Kong 2000
10
Hong Kong 2001
0
5
6
7
8
9
10
11
12
13
14
15
Age (years)
Source: Cheng et al (2007).
If nature dominates nurture for the Canadian Chinese population, as well as having twice the rate of
AMD, it is also possible that Chinese Canadians may have twice the rate of DR. The 2001 PALS
found that 17.4% of Canadians who have diabetes report a seeing disability. Wong et al (2006)
found that 35% of the Chinese population in Taiwan with diabetes have a seeing disability. The
Institute for Clinical Evaluative Sciences - ICES (Glazier et al, 2007) note that in the US, African and
Hispanic populations have twice the rate of diabetes as do whites; diabetes among Asian Americans
is higher than in whites and rising faster than in other ethnic groups; and that in the United Kingdom
(UK), South Asians have at least three times the rate of diabetes as the white population.
2.2.3.3
ABORIGINALS
Data availability for VL in North American Indians, Metis and Inuit is also scarce. Hanley et al (2005)
found 23.3% of North American Indian diabetics in remote communities had DR, with similar figures
34
also being reported by Maberley et al (2002). This is around a third higher than for the general
population (albeit lower than the Chinese figures). ICES (Glazier et al, 2007) note that the
prevalence of diabetes in Aboriginal communities in Ontario (13%) was three times higher than for
the non-indigenous population.
Van Rens et al (1988) reported remarkably high levels of POAG in Eskimo women in Alaska (Table
2–7). Similarly, Adams and Adams (1974) reported that the prevalence of POAG in Canadian Inuit
women was up to 40 times that in non-Inuit women. TABLE 2–7: PREVALENCE OF POAG AMONG THE ESKIMO (%)
Age (years)
<49
50-59
60-69
70+
Males
3.1
2.6
3.7
0.5
Females
3.6
11.8
11.8
1.2
Source: Van Rens et al (1988).
Young et al (2000) state that Canada’s North American Indians have a ‘high prevalence of serious
and untreated diabetic retinopathy’.18 Health Canada (2002b) reports that 25% of Mohawks who
have had diabetes for ten years also have DR.
TABLE 2–8: PREVALENCE OF DIABETES AMONG CANADIAN ABORIGINAL PEOPLES (1991)
9
8
Prevalence (%)
7
6
5
4
3
2
1
0
Total
Aboriginal
18
On-Reserve Off-Reserve Total North
North
North
American
American
American
Indians
Indians
Indians
Metis
Inuit
They cite Ross and Flick (1991) as their source, but this article does not appear to be electronically available.
35
Source: Health Canada (2002b).
2.2.3.4
BLINDNESS
Buhrmann et al (forthcoming) estimate the prevalence of blindness by cause in Canada out to 2031,
by applying the breakdown from Congdon et al (2004a) to Statistics Canada’s (total) population
projections for selected years.
TABLE 2–9: PREVALENCE OF BLINDNESS BY CAUSE, 2006 TO 2031 (% POPULATION)
Cause
AMD
DR
Glaucoma
2006
2011
2016
2021
2026
2031
0.4
0.0
0.1
0.4
0.0
0.1
0.5
0.0
0.1
0.5
0.1
0.1
0.5
0.1
0.1
0.6
0.1
0.1
Other
0.2
0.2
0.2
0.2
0.2
0.2
Total
0.7
0.7
0.7
0.8
0.9
1.0
Source: Buhrmann et al (forthcoming).
2.3
PREVALENCE RATES FOR VL
2.3.1
WHITE POPULATION VL
As noted above, there have not yet been any major population eye health studies conducted in
Canada. Thus, for Canadian whites, the choice falls to using self-diagnosed and self-reported data
from the CCHS, or using data from American or Australian eye health studies. Australian data
(Centre for Eye Research Australia, 2005)19 is preferred for two reasons. First, Australian VL data
for each disease is available by age cohort, which is essential for working with population
projections. Second – and potentially reflecting similar ethnic mix and health systems – the
Australian proportion of total VL caused by each of the major diseases is significantly closer to
Canada’s than the US data (Table 2–10). As the table shows, the proportion of VL caused by
cataract in the US is more than three times higher than in Canada, whereas the ratio between
Canada and Australia is around 1.30 to 1.00 At the other end of the scale, the proportion of VL due
to RE and other is more than five times smaller in the US than it is Canada, whereas the ratio
between Australia and Canada is around 1.39 to 1.00.
TABLE 2–10: CAUSES OF VL, BY DISEASE, IN WHITE POPULATIONS
Disease
Cataract
Glaucoma
DR
AMD
RE/Other
US
Canada
Australia
59.2%
3.3%
4.9%
22.9%
9.7%
18.6%
7.0%
7.0%
16.3%
51.3%
14.3%
2.9%
1.6%
10.1%
71.2%
Sources: US (Congdon et al, 2004a), Canada (Maberley et al, 2006), Australia (CERA, 2005)
19
These data have been published in a number of journal articles, including Taylor, Pezzullo and Keeffe (2006)
36
Australian VL
Access Economics (2007) used data from the MVIP to determine the prevalence of VL caused by
AMD (Table 2–11). Severity was measured according to the better seeing eye (noting that with
AMD it can become the worse one over time). For Canada, the distribution between mild, moderate
and severe VL from AMD and by age are based on these data, as it was considered likely that AMD
incidence and progression follows a similar pathway in Canada.
TABLE 2–11: PREVALENCE OF VL DUE TO AMD, BY SEVERITY (% OF AGE GROUP)
Age
Mild
0-69
70-74
75-79
80-84
85-89
90+
40+
0.00
0.17
0.00
1.00
2.13
3.15
0.10
Moderate
0.00
0.00
0.87
1.00
4.26
6.29
0.33
Severe
0.00
0.17
0.00
1.00
3.19
4.72
0.13
Source: Access Economics (2007).
The Centre for Eye Research Australia (CERA, 2005) estimated the prevalence of VL caused by
cataract in Australia, also from the MVIP (Table 2–12). For Canada, as with AMD, the distribution
between mild, moderate and severe VL from cataract and by age are based on these data.
TABLE 2–12: PREVALENCE RATES FOR VL FROM CATARACTS, BY AGE AND SEVERITY (%)
Age
40-49
50-59
60-69
70-79
80-89
90+
Total VL (<20/40)
0.0%
0.0%
0.1%
1.4%
6.6%
15.2%
VL by severity
Mild (6/12 to 6/18)
Moderate (<6/18 to 6/60)
Severe (>6/60)
Total
60.2%
26.7%
13.0%
Source: CERA (2005).
Access Economics (2008c, forthcoming) provides estimates of the prevalence of VL caused by DR
(Table 2–13), based on combined data from the MVIP and Blue Mountains Eye Study (BMES). For
Canada, the distribution between mild, moderate and severe VL from DR and by age are again
based on these data.
TABLE 2–13: PREVALENCE RATES FOR VISION IMPAIRMENT (<6/12) FROM DR, AND PROPORTION BY
STAGE OF VISION LOSS
Age
40-49
50-59
60-69
70-79
80-89
90+
Total VL (<20/40)
0.0%
0.0%
0.2%
0.1%
0.5%
0.6%
VL by severity
Mild (6/12 to 6/18)
Severe (>6/60)
Total
30.6%
47.8%
21.6%
(a) Prevalence based on combined data from the MVIP and BMES. (b) Stages of vision loss based on MVIP.
Source: Access Economics (2008c).
Access Economics (2008b) estimated the prevalence of VL caused by POAG, by degrees of
severity, from the MVIP and the BMES (Table 2–14). For Canada, the distribution between mild,
moderate and severe VL from glaucoma and by age are once again based on these data.
37
TABLE 2–14: PROPORTION OF PEOPLE WITH GLAUCOMA BY AGE AND SEVERITY (%)
Age Group
0-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Mild
0.0
0.2
0.4
0.5
1.2
1.7
2.2
1.1
Moderate
Severe
0.0
1.7
2.8
3.7
8.4
11.5
15.1
7.7
0.0
2.9
2.6
3.3
1.8
2.5
4.8
20.6
Source: Based on combined data from the MVIP and BMES.
Most people with glaucoma in developed countries are unaware they have the disease (Canadian
Ophthalmological Society, 2007). Even among those regularly visiting eye professionals, the
probability of diagnosis depends on the severity of the condition. Hence, the more severe forms
have the highest (diagnosed) prevalence.

Wong et al (2004) examined the presence of undiagnosed glaucoma in people who had visited
an eye care provider in the previous year using MVIP data. They found that 81% of possible
cases, 72% of probable cases and 59% of definite cases of glaucoma were previously
undiagnosed by the eye care provider.
CERA (2005) estimated the prevalence of VL caused by RE in Australia from the MVIP (Table 2–
15). For Canada, the relativities between mild, moderate and severe VL from RE and by age are
based on these data, as it is likely that RE incidence and progression follows a similar pathway in
Canada.
TABLE 2–15: PREVALENCE RATES FOR VL FROM RE, BY AGE AND SEVERITY (%)
Age
40-49
50-59
60-69
70-79
80-89
90+
Total VL (<20/40)
VL by severity
Total
0.5%
1.8%
3.9%
7.8%
13.0%
7.9%
Mild (6/12 to 6/18)
Severe (>6/60)
83.4%
14.6%
2.0%
Source: CERA (2005).
In addition to the above breakdowns by severity, CERA (2005) also gives an overall prevalence of
VL caused by each major eye disease, which is used as the basis for the prevalence of VL by cause
for Canadian whites (Table 2–16).
38
TABLE 2–16: ESTIMATED VL PREVALENCE IN CANADIAN WHITES BY DISEASE AND AGE
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Cataract
DR
0.00%
0.08%
0.01%
0.16%
0.73%
2.37%
5.49%
8.71%
15.17%
0.00%
0.09%
0.12%
0.16%
0.16%
0.10%
0.44%
0.78%
0.68%
0.58%
Glaucoma
AMD
RE
Other
0.00%
0.16%
0.20%
0.34%
1.52%
1.32%
1.23%
0.00%
0.00%
0.00%
0.00%
0.08%
0.22%
1.70%
2.31%
8.77%
12.97%
0.71%
0.29%
1.05%
2.62%
2.51%
5.38%
6.30%
9.87%
13.13%
12.80%
7.86%
0.18%
0.14%
0.52%
0.17%
0.25%
0.43%
0.64%
0.78%
0.92%
3.75%
2.44%
Source CERA (2005).
2.3.2
ABORIGINALS AND VISIBLE MINORITIES (AVM) VL
There are severe data problems in estimating the prevalence of VL among Canada’s AVM
populations. While the CCHS collects the prevalence of eye diseases, by age, for the AVM
population, it does not collect data on the causes of VL. Moreover, the prevalence data are not
disaggregated by race, despite known differences between races (Figure 2-17). There have been
some international population eye health studies covering the causes of VL in non-whites, but the
races (blacks and Hispanics) covered were not representative of Canada’s AVM population (blacks
are 2% of the Canadian population, and Hispanic does not rate a category in the Canadian census).
Moreover the data is not available by age-cohort which, given how greatly the incidence of VL varies
by age, makes it very difficult to map to Canada’s AVM population.
FIGURE 2-17: CAUSES OF BLINDNESS BY ETHNICITY (US)
Source: Congdon et al (2004a).
Access Economics’ approach has been to estimate from international sources the likelihood that a
non-white person who has an eye disease will develop VL, and apply that ratio to the CCHS
39
prevalence of that disease in Canada’s AVM population. The next few paragraphs illustrate the
concepts involved using illustrative round numbers.
Suppose, for example, that 25% of the US non-white population who have cataract will also have VL
from that disease. Suppose further, that 10,000 Canadian AVM have cataract. Then - if making the
assumption that the share of non-whites with cataract who have VL is similar on both sides of the
border - there are an estimated 2,500 (=10,000 * 25%) AVM who suffer VL because of their
cataracts.
Prevalence rates of cataract by age group among Canadian AVM are known and Congdon et al
(2004a) reports that, in America, if a white and a non-white both have cataract, the white is more
likely to suffer VL from the disease (for illustrative purposes, suppose twice as likely). Assuming that
American, Australian and Canadian whites are similar in this relative risk, then if 80% of 80 year old
(Australian) whites with cataract have VL, it follows that half as many (40%) of Canadian non-whites
(Canadian) with cataract will have VL. So if the CCHS reports that there are 1,000 80 year old
Canadian AVM with cataract, 400 of them (=1,000 * 40%) are estimated to have VL.
2.3.3
CATARACT-INDUCED VL IN AVM
Because there are multiple races and multiple diseases, this section works through one disease in
detail – cataract – using actual data, and other disease prevalence rates are similarly calculated.
Using the NEI disease prevalence (http://www.nei.nih.gov/eyedata/tables.asp) and 2000 US Census
data (http://factfinder.census.gov/), an estimated 7.47% of the white population had cataract (Row A,
Table 2–17). Access Economics (2006) shows that 2.79% of white Americans had VL (Row B).
Congdon et al (2004a) show that 59.2% of this total VL was caused by cataract (Row C). Thus, the
prevalence of cataract-induced VL was 1.65% (59.2% times 2.79%) of the white population (Row D).
Thus, it can be deduced that 22.1% (1.65/7.47) of whites who have cataract will also have VL from
those cataracts (Row E).
TABLE 2–17: PREVALENCE OF VL IN US WHITES WITH CATARACTS (2000)
Factor
%
A. Prevalence of cataract
B. Prevalence of VL
C. Proportion of VL caused by cataract
D. Prevalence of cataract-induced VL (C*B)
E. Percent of cataract population who have VL (D/A)
7.47%
2.79%
59.2%
1.65%
22.1%
Sources: Access Economics (2006), Congdon et al (2004a).
For blacks, the same data show that 6.42% of the black population had cataract (Row A, Table 2–
18). Access Economics (2006) shows that 2.28% of black Americans had VL (Row B). Congdon et
al (2004a) show that 50.9% of this total VL was caused by cataract (Row C). Thus, the prevalence
of cataract-induced VL was 1.16% (50.9% times 2.79%) of the black population (Row D) and it can
be deduced that 18.1% (1.16/6.42) of blacks who have cataract will also have VL from those
cataracts (Row E).
40
TABLE 2–18: PREVALENCE OF VL IN US BLACKS WITH CATARACTS (2000)
Factor
%
B. Prevalence of VL
6.42%
2.28%
50.9%
1.16%
18.1%
For Hispanics, the data record that 6.96% of the Hispanic population had cataract (Row A, Table 2–
19). Access Economics (2006) shows that 1.96% of Hispanic Americans had VL (Row B).
Congdon et al (2004a) show that 46.7% of this total VL was caused by cataract (Row C). Thus, the
prevalence of cataract-induced VL was 0.91% (46.7% times 1.96%) of the Hispanic population (Row
D) and it can be deduced that 13.1% (0.91/6.96) of Hispanics who have cataract will also have VL
from those cataracts (Row E).
TABLE 2–19: PREVALENCE OF VL IN US HISPANICS WITH CATARACTS (2000)
Factor
%
B. Prevalence of VL
6.96%
1.96%
46.7%
0.91%
13.1%
Finally, for other races, according to the data, 6.96% of the remaining population of other races had
cataract (Row A, Table 2–20). Access Economics (2006) shows that 2.15% of ‘other’ Americans
had VL (Row B). Congdon et al (2004a) show that 52.3% of this total VL was caused by cataract
(Row C). Thus, the prevalence of cataract-induced VL was 1.12% (52.3% times 2.15%) of the
remainder of the population (Row D) and it can be deduced that 16.2% (1.12/6.96) of other races
who have cataract will also have VL from those cataracts (Row E).
TABLE 2–20: PREVALENCE OF VL IN US ‘OTHER’ WITH CATARACTS (2000)
Factor
%
B. Prevalence of VL
6.96%
2.15%
52.3%
1.12%
16.2%
Drawing this together, it is possible to estimate how much less likely the average non-white is to
develop VL after contracting cataracts than is the average white (Table 2–21). Weighting the three
non-white races (black, Hispanic and ‘other’) by their respective shares of the Canadian AVM
population (blacks 12%, Latin Americans20 4%, ‘other’ 84%) yields the result that 16.3% of Canadian
20
As noted above, the Canadian census does not include the category ‘Hispanic’; ‘Latin American’ is used as a proxy.
41
AVM with cataract will have VL from their cataracts (Row E). This in turn indicates that an AVM
person with cataract is only 74% as likely to develop VL as is a white person with cataract (Row F).
TABLE 2–21: RELATIVE RISK OF DEVELOPING VL FROM CATARACTS, BY RACE
Race/Ethnic group
A. Whites (Table 2–17)
B. Blacks (Table 2–18)
C. Hispanic (Table 2–19)
D. Other (Table 2–20)
E. Non-white weighted average
F. Ratio average non-white to white (E/A)
Prevalence of VL in
those with cataract
Share of Canadian
AVM population
22.1%
18.1%
13.1%
16.2%
16.3%
12%
4%
84%
0.74
Source: Derived from previous tables.
Having derived above that, over the whole population, an AVM person with cataract is around threequarters as likely to have VL as a white person, this is then applied to the fraction of whites with
cataracts who have VL (Column C in Table 2–22). The latter, in turn, is derived from the prevalence
of cataract-induced VL (from Table 2–16, reproduced as Column A in Table 2–22) and from the
prevalence of cataract as a disease in whites (from the Australian Bureau of Statistics, 2006,
Column B below).
TABLE 2–22: PREVALENCE OF VL IN WHITES WITH CATARACT, BY AGE
Age
A. Prevalence of
cataract
B. Prevalence of
cataract induced VL
35-39
40-44
45-49
0.2%
0.2%
0.5%
0.0%
0.0%
0.0%
C. Fraction of those
with cataracts who have
VL (B/A)
0.0%
0.0%
0.0%
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0.5%
1.5%
1.5%
5.1%
5.1%
13.2%
13.2%
19.9%
19.9%
0.0%
0.1%
0.0%
0.2%
0.7%
2.4%
5.5%
8.7%
15.2%
0.0%
5.5%
0.7%
3.2%
14.2%
17.9%
41.5%
43.8%
76.2%
Sources: CERA (2005), Australian Bureau of Statistics (2006).
The likelihood that a non-white with cataract will develop VL (Column C in Table 2–23) can then be
derived from the fraction of whites with cataracts who have VL (from Table 2–22, reproduced as
Column A in Table 2–23) and the relative risk between whites and non-whites (from Table 2–21,
reproduced as Column B).
42
TABLE 2–23: PREVALENCE OF VL IN NON- WHITES WITH CATARACT, BY AGE
Age
A. Fraction of whites
VL
B. Relative risk of
developing VL from
cataract (nonwhite/white)
C. Fraction of non-whites
VL (A*B)
35-39
40-44
45-49
0.0%
0.0%
0.0%
0.74
0.74
0.74
0.0%
0.0%
0.0%
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0.0%
5.5%
0.7%
3.2%
14.2%
17.9%
41.5%
43.8%
76.2%
0.74
0.74
0.74
0.74
0.74
0.74
0.74
0.74
0.74
0.0%
4.1%
0.5%
2.3%
10.5%
13.2%
30.5%
32.2%
56.1%
Source: derived from Tables 2-21 and 2-22.
Finally, having derived how likely a non-white with cataract is to develop VL (Table 2–23), it remains
to ascertain how many non-whites have cataract. This information is provided by the CCHS (Table
2–5) and reproduced as Column A in Table 2–24. Multiplying the number of AVM with cataract
(Column A) by their chance of having VL (Column B) gives the prevalence of VL from cataract in the
AVM population by age group. For example, if 22.9% of AVM aged between 70 and 74 have
cataract, and 10.5% of these develop VL, then around 2.4% of AVM in this age group will have VL
caused by cataract.
43
TABLE 2–24: PREVALENCE OF CATARACT-INDUCED VL IN CANADIAN AVM, BY AGE
A Prevalence of
cataract in nonwhites
B Fraction of nonwhites with
cataracts who
have VL
C Prevalence of
cataract-induced
VL in non-whites
(A*B)
Males
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Females
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0.3%
0.1%
0.0%
0.0%
0.0%
0.0%
1.9%
2.0%
4.4%
11.7%
13.2%
22.9%
16.0%
21.0%
21.0%
21.0%
0.0%
0.0%
4.1%
0.5%
2.3%
10.5%
13.2%
30.5%
32.2%
56.1%
0.0%
0.0%
0.2%
0.1%
0.3%
2.4%
2.1%
6.4%
6.8%
11.8%
0.3%
0.6%
0.2%
1.4%
3.5%
10.0%
21.1%
34.7%
36.8%
42.0%
42.0%
42.0%
0.0%
0.0%
0.0%
0.0%
4.1%
0.5%
2.3%
10.5%
13.2%
30.5%
32.2%
56.1%
0.0%
0.0%
0.0%
0.0%
0.1%
0.1%
0.5%
3.6%
4.9%
12.8%
13.5%
23.5%
Source: Derived from above tables and data from the CCHS.
2.3.4
VL CAUSED BY AMD, GLAUCOMA AND RE IN AVM
The exercise in the previous section can be repeated for VL in AVM caused by the other major eye
diseases, except DR, which is dealt with by a different method, using solely Canadian data, in
Section 2.3.5. Table 2–25 reports the prevalence of each eye disease in each non-white group from
the NEI dataset (weighted by 2000 Census age cohorts, as above).
TABLE 2–25: PREVALENCE OF EYE DISEASES BY ETHNICITY, US, 2000
White
A. AMD
B. Cataract
C. Glaucoma
D. RE/Other
0.8%
7.5%
0.7%
16.7%
Black
0.4%
6.4%
1.6%
8.6%
Hispanic
0.4%
7.0%
0.9%
10.7%
Other
0.4%
7.0%
1.0%
10.9%
Source: US Census 2000 (http://factfinder.census.gov/servlet/STTable?_bm=y&-geo_id=01000US&qr_name=ACS_2006_EST_G00_S0101&-ds_name=ACS_2006_EST_G00_)
EDPRG (http://www.nei.nih.gov/eyedata/tables.asp)
44
The prevalence of VL caused by each eye disease is derived from Congdon et al (2004a), which
reports both the total prevalence of VL for each race in the US (Row E in Table 2–27) and the
percentage of this VL which is caused by each major disease (Table 2–26). The prevalence of VL
by disease is then derived as per cataract in the previous section, presented in Table 2–28.
TABLE 2–26: CAUSES OF VL BY ETHNICITY21
White
A. AMD
B. Cataract
C. Glaucoma
D. RE/Other
22.9%
59.2%
3.3%
9.7%
Black
Hispanic
3.2%
50.9%
14.3%
17.0%
14.3%
46.7%
7.6%
18.5%
Other
13.5%
52.3%
8.4%
15.1%
TABLE 2–27: PREVALENCE OF VL, BY ETHNICITY AND CAUSE, US, 2000
White
A. AMD
B. Cataract
C. Glaucoma
D. RE/Other
E. Sum
0.64%
1.65%
0.09%
0.27%
2.79%
Black
0.07%
1.16%
0.33%
0.39%
2.28%
Hispanic
0.28%
0.91%
0.15%
0.36%
1.96%
Other
0.29%
1.12%
0.18%
0.32%
2.15%
Source: Access Economics (2006), Table 2–26.
TABLE 2–28: PREVALENCE (%) OF VL WITHIN SPECIFIED DISEASES, BY ETHNICITY
White
A. AMD
B. Cataract
C. Glaucoma
D. RE/Other
95.2
22.1
14.0
1.6
Black
17.4
18.1
20.1
4.5
Hispanic
63.2
13.1
16.7
3.4
Other
69.5
16.2
17.9
3.0
Source: Derived from Table 2–25 and Table 2–27.
Extending the above analysis across ethnicities and diseases, Figure 2-18 shows the variance in the
probability of VL across diseases and ethnic groups. For example, AMD appears to have a
significantly greater likelihood of causing VL in whites than in blacks, while RE is more likely to
cause VL in blacks than whites. This may possibly be due to genetic factors or to socioeconomic
factors governing access to medical care (and thus detection and treatment).
21
DR is not included as it is calculated separately in Section 2.3.5. Rates are white 5%, black 15%, Hispanic 13%, other
11%.
45
FIGURE 2-18: PROBABILITY OF DEVELOPING VL AFTER CONTRACTING SELECTED DISEASES, BY
ETHNICITY
Probability of visual impairment after
contracting specified disease (%)
100.0
White
Black
Hispanic
Other
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Cataract
Glaucoma
DR
RE/Other
AMD
Source: Derived from EDPRG (Congdon et al, 2004a) and US Census data.
As with the methodology for cataract, the relative risk of VL from a particular disease is compared
between whites and each other group and a weighted average is developed using the population
weights for each group among the Canadian AVM total (Table 2–29).
TABLE 2–29: RELATIVE RISK OF VL BY EYE DISEASE, NON-WHITES TO WHITES
Disease
A. AMD
B. Cataract
C. Glaucoma
D. RE/Other
Relative Risk
1.52
0.74
1.29
1.96
Source: Derived from previous tables and Canadian Census data.
To derive an age breakdown for the relative risks for the non-white population, data on prevalence of
each disease were used from the Australian Bureau of Statistics (2006) and the Australian Institute
of Health and Welfare (2005) (Table 2–30).
TABLE 2–30: PREVALENCE OF EYE DISEASES IN WHITES
Age
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
AMD
0.1%
0.3%
0.3%
0.8%
0.8%
1.1%
1.1%
3.7%
3.7%
6.3%
6.3%
Cataract
0.2%
0.5%
0.5%
1.5%
1.5%
5.1%
5.1%
13.2%
13.2%
19.9%
19.9%
Glaucoma
0.2%
0.8%
0.8%
1.3%
1.3%
2.4%
2.4%
6.3%
6.3%
7.2%
7.2%
RE/Other
43.9%
77.4%
77.4%
70.9%
70.9%
52.8%
52.8%
54.1%
54.1%
51.2%
51.2%
Source: Australian Bureau of Statistics (2006), Australian Institute of Health and Welfare (2005).
46
Recall that the prevalence of VL in whites by cause was shown in Table 2–16. Using that prevalence
and the prevalence of each disease (Table 2–30) gives the fraction of VL caused by that disease
(Table 2–31) for each five-year age cohort in the white population.
TABLE 2–31: FRACTION OF WHITES WITH EACH EYE DISEASE WHO HAVE VL, BY AGE AND GENDER (%)
Age
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
AMD
0.0%
0.0%
0.0%
7.4%
20.2%
45.4%
61.5%
100.0%
100.0%
Cataract
0.0%
0.0%
0.0%
5.5%
0.7%
3.2%
14.2%
17.9%
41.5%
43.8%
76.2%
Glaucoma
0.0%
0.0%
0.0%
0.0%
0.0%
6.7%
8.2%
5.4%
24.3%
18.3%
17.0%
RE/Other
2.0%
0.6%
2.0%
3.9%
3.9%
11.0%
13.1%
19.7%
26.0%
32.3%
20.1%
Note: AMD prevalences in 85 years and older capped at 100%
Source: Congdon et al (2004a), Access Economics (2007).
Combining the fractions in Table 2–31 with the relative risks (non-white to white) from Table 2–29
leads to the prevalence of VL within disease groups in non-whites as per Table 2–32.
TABLE 2–32: PREVALENCE OF VL WITHIN DISEASE GROUPS, NON-WHITES
Age
AMD
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0.0%
0.0%
0.0%
10.5%
28.6%
64.4%
87.3%
100.0%
100.0%
Cataract
0.0%
0.0%
0.0%
4.1%
0.5%
2.3%
10.5%
13.2%
30.5%
32.2%
56.1%
Glaucoma
0.0%
0.0%
0.0%
0.0%
0.0%
8.7%
10.6%
7.0%
31.2%
23.5%
21.8%
RE/Other
4.0%
1.1%
4.0%
7.7%
7.6%
21.5%
25.7%
38.6%
50.8%
63.3%
39.4%
Source: Derived from previous tables.
Using this with the prevalence of eye disease in AVM from CCHS data (Table 2–5) results in the
prevalence of VL from that disease (Table 2–33).
47
TABLE 2–33: PREVALENCE OF VL IN AVM
Males
AMD
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Females
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
2.3.5
0.00%
0.00%
0.00%
0.11%
0.50%
1.85%
4.09%
7.55%
7.55%
AMD
0.00%
0.00%
0.00%
0.14%
0.53%
1.66%
3.13%
5.02%
5.02%
Cataract
Glaucoma
RE/Other
0.00%
0.00%
0.00%
0.00%
0.05%
0.00%
0.00%
0.18%
0.06%
0.31%
2.40%
0.00%
0.00%
0.00%
0.54%
1.01%
0.06%
0.27%
0.16%
1.22%
1.21%
2.11%
6.41%
6.76%
11.77%
0.40%
1.87%
1.41%
1.31%
1.96%
2.59%
3.22%
2.01%
Cataract
Glaucoma
RE/Other
0.00%
0.00%
0.00%
0.14%
0.05%
0.49%
3.63%
4.85%
12.82%
0.00%
0.00%
0.00%
0.00%
0.00%
0.18%
0.33%
0.80%
0.92%
0.06%
0.02%
0.13%
0.47%
0.30%
0.39%
0.89%
2.48%
2.92%
13.52%
23.54%
0.69%
0.64%
3.63%
2.26%
DIABETES AND DR IN THE AVM POPULATION
The above methods cannot be fully used for DR in the Canadian AVM population, because the
CCHS does not report on the prevalence of DR in AVM. However, there are sufficient Canadian
data from other sources to estimate age-gender prevalence of DR using an alternate methodology
discussed in this section.
Data from various Canadian publications enable an estimate of VL from DR in the AVM population
to be calculated directly (rather than having to rely on non-Canadian EDPRG data.) Statistics
Canada’s Health Report (Wilkins and Park, 1996) shows that the prevalence of VL among Canadian
diabetics is 72% higher than in the general population. However, as Access Economics (2008c)
notes, diabetics also have higher rates of cataract, glaucoma and macular edema, with the result
that the prevalence of DR in diabetics is roughly equivalent to the combined prevalence of these
three other diseases in diabetics. Thus, it was assumed that half of the increased rate of VL (36%)
is due to DR (rather than the other three associated eye diseases). Increasing the 2005 CCHS
figures for the prevalence of under corrected VL in the AVM population (Table 2–34) by 36%
enabled an estimate of the prevalence of DR-induced VL among diabetics in this population (Table
2–35).
48
TABLE 2–34: UNDER CORRECTED VL IN AVM
Age
Male
Female
20-24
25-34
1.3%
0.4%
1.0%
3.9%
35-44
0.6%
1.4%
45-54
55-64
65-74
0.2%
1.7%
1.7%
1.0%
3.1%
2.0%
75+
3.7%
4.7%
Source: Statistics Canada, CCHS public use microdata files.
TABLE 2–35: PREVALENCE OF VL FROM DR WITHIN DIABETIC AVM GROUPS
Age
Male
Female
20-24
1.8%
1.4%
25-34
35-44
45-54
55-64
65-74
75+
0.5%
0.8%
0.3%
2.3%
2.3%
5.0%
5.3%
1.9%
1.3%
4.2%
2.8%
6.4%
Source: Derived from Table 2–34.
Although the CCHS does not provide an estimate of diabetic prevalence in the AVM population,
ICES (Glazier et al, 2007) reports that rates of diabetes among First Nation groups in Ontario are
among the highest in the world, and are some three times higher than for the rest of the population.
ICES also reports that diabetes in Ontario’s South Asian population is three times the general
population. They also note the prevalence of diabetes in black Americans is twice as high as the
general population, which might reasonably be assumed to apply also to black Canadians. Finally,
ICES reports that the prevalence of diabetes in Toronto neighbourhoods is strongly correlated with
the percentage of the population from Visible Minorities. Taken together, Access Economics has
conservatively assumed that the rate of diabetes in the AVM population is twice that of the white
population. Statistics Canada publishes rates of diabetes for the general population (Table 2–4).
Doubling these rates thus yields an estimate of the prevalence of diabetes in the AVM population
(Table 2–36).
TABLE 2–36: PREVALENCE OF DIABETES IN AVM POPULATION, 2005 (%)
Age
12-14
15-19
20-24
25-34
35-44
45-54
55-64
65-74
75+
Total
Male
Female
All
0.0%
0.6%
1.8%
1.8%
4.2%
10.0%
23.6%
34.6%
33.6%
10.6%
0.0%
0.6%
1.4%
2.4%
3.8%
8.0%
17.0%
24.6%
26.2%
8.8%
0.6%
0.6%
1.6%
2.2%
4.0%
9.0%
20.2%
29.2%
29.2%
9.8%
Source: As per Table 2–4, and ICES (Glazier et al, 2007).
49
Multiplying the prevalence of diabetes in the AVM population (Table 2–36) by the prevalence of VL
in the AVM diabetic population (Table 2–35) provides the prevalence of AVM diabetics who have
DR-induced VL (Table 2–37).
TABLE 2–37: ESTIMATED PREVALENCE OF DR-INDUCED VL IN AVM
20 to 24
25 to 34
35 to 44
45 to 54
55 to 64
65 to 74
75 and older
Male
Female
0.03%
0.01%
0.03%
0.03%
0.55%
0.80%
1.69%
0.02%
0.13%
0.07%
0.11%
0.71%
0.68%
1.67%
Source: Derived from earlier tables.
2.3.6
SUMMARY OF VL IN AVM POPULATIONS
Combining the prevalence of VL from DR (Table 2–37) with the prevalence estimates for the other
eye diseases (Table 2–33) enables a completion of the estimates of VL by disease for the whole
AVM population (Table 2–38). As noted above, the CCHS does not report VL by disease, only the
prevalence of the diseases. However, it does report the total number of AVM who have undercorrected VL (Table 2–34). Self-reported VL for AVM was 0.8% for males and 2.0% for females.
The estimates here, derived from ratios of diagnosed VL between races, are 0.5% for AVM males,
and 0.7% for AVM females (Table 2–40).
50
TABLE 2–38: PREVALENCE OF VL IN AVM BY AGE, GENDER AND DISEASE
Males
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Female
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
2.4
AMD
0.00%
0.00%
0.00%
0.11%
0.50%
1.85%
4.09%
7.55%
7.55%
AMD
0.00%
0.00%
0.00%
0.14%
0.53%
1.66%
3.13%
5.02%
5.02%
Cataract
0.00%
0.00%
0.00%
0.18%
0.06%
0.31%
2.40%
2.11%
6.41%
6.76%
11.77%
Cataract
0.00%
0.00%
0.00%
0.14%
0.05%
0.49%
3.63%
4.85%
12.82%
13.52%
23.54%
DR
0.03%
0.03%
0.03%
0.55%
0.55%
0.80%
0.80%
1.69%
1.69%
1.69%
1.69%
Glaucoma
DR
0.07%
0.11%
0.11%
0.71%
0.71%
0.68%
0.68%
1.67%
1.67%
1.67%
1.67%
Glaucoma
0.00%
0.00%
0.00%
0.00%
0.00%
0.54%
1.01%
0.40%
1.87%
1.41%
1.31%
0.00%
0.00%
0.00%
0.00%
0.00%
0.18%
0.33%
0.80%
0.92%
0.69%
0.64%
RE/Other
0.05%
0.00%
0.06%
0.27%
0.16%
1.22%
1.21%
1.96%
2.59%
3.22%
2.01%
RE/Other
0.06%
0.02%
0.13%
0.47%
0.30%
0.39%
0.89%
2.48%
2.92%
3.63%
2.26%
SUMMARY
A variety of data sources were used to construct a model of Canadian VL by age, gender, ethnicity,
severity and type. There was found to be little difference in the prevalence of visually impairing eye
conditions among white populations in US, Australian and European population eye health studies,
so these studies (Congdon et al, 2004a and CERA, 2005) were used to estimate the prevalence of
VL for white Canadians.
For AVM, self-reported data from the CCHS were used to estimate the prevalence of cataract,
glaucoma and RE, with supplementation from Canadian academic studies and journal articles for
DR and AMD, since these conditions are not covered in the CCHS. DR was estimated from other
Canadian sources and AMD was estimated from the average prevalence rates for non-whites in the
US. The risk of VL within each disease for AVM was derived from the risk for non-whites in the US.
These data show that differences in the rates of VL from ‘disease x’ are related to differences in
prevalence of that disease across ethnicities as well as differences in access to treatment and
genetic factors that may affect progression of VL. Since the self-reported data do not distinguish
between mild and medium levels of VL, the severity distribution is assumed to be the same for AVM
as for whites (by disease).
In total, there were an estimated 816,951 Canadians with VL in 2007 (Table 2–39).

Of this total, 780,534 (95.5%) were white and 36,417 (4.5%) were AVM.

RE / Other is the main source of VL for the white population (68% of the total), and cataract is
the main cause of VL in AVM (36% of the total).
51

For whites the second largest source of VL is cataract (15.5%) and, for the AVM population,
DR is the second largest source (24.5% of the total).22

AVM have lower prevalence of VL for all diseases other than DR (Figure 2-19), largely due to
lower prevalence of eye diseases at equivalent ages to whites, a younger age profile, and less
likelihood of developing VL once they have contracted a given eye disease.
TABLE 2–39: PREVALENCE OF VL, BY CAUSE AND ETHNICITY, 2007
All ethnicities
Number
White
% total Number
AVM
% total Number
AMD
Cataract
DR
Glaucoma
RE/Other
89,241
133,836
29,920
24,937
539,236
10.9%
16.4%
3.7%
3.1%
66.0%
84,641
120,685
20,992
22,565
531,650
10.8%
15.5%
2.7%
2.9%
68.1%
All VL
817,171
100.0%
780,534
100.0%
4,380
13,151
8,928
2,373
7,586
36,417
% total
12.0%
36.1%
24.5%
6.5%
20.8%
100.0%
Note: For corresponding prevalence rates, see Table 2–40 to Table 2–45.
FIGURE 2-19: PREVALENCE RATES OF VL, BY ETHNICITY AND CAUSE, 2007
3.5%
All races
White
AVM
3.0%
Prevalence (%)
3.0%
2.5%
2.5%
2.0%
2.0%
1.6%
1.5%
1.0%
0.4%
0.1%
0.5% 0.1%
0.1%
0.3%
0.2%
0.1% 0.1%
0.0%
0.1%
0.6%
0.3%
0.5%
0.0%
AMD
Cataract
DR
0.1%
Glaucoma RE/Other
All VI
Note: Estimates are raw prevalence rates, not age-standardised, so low AVM figures reflect low average age.
The prevalence of VL is projected to increase from 2.5% of the population in 2007 to 4.0% in 2032
(Figure 2-20). In terms of numbers of people, there are projected to be almost twice as many
22
As noted earlier, Canadian Aboriginals have some of the highest rates of diabetes in the world, and Asians have some
three to six times the diabetes prevalence of whites.
52
Canadians with VL in 25 years than in 2007, with VL from cataract, AMD and glaucoma all projected
to increase by more than 100% over the next 25 years (114%, 113% and 117% respectively).
Detailed tables underlying the projections in this section may be found in Appendix B. Summaries
for 2007 are provided in Table 2–40 through to Table 2–45 at the end of this section.
FIGURE 2-20: PREVALENCE OF VL, BY CAUSE, 2007-2032
4.5%
4.0%
All VI
Cataracts
DR
Glaucoma
AMD
RE/Other
3.5%
Prevalence (%)
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
2032
2031
2030
2029
2028
2027
2026
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
0.0%
VL affects women more than men (Figure 2-21), reflecting greater longevity in females now and in
the future. In 2007, females accounted for 58.4% of VL, by 2032, this will have fallen slightly to
56.3%.
53
FIGURE 2-21: PREVALENCE OF VL BY GENDER, 2007 TO 2032
Persons with visual Impairment
(000)
1,000
900
800
700
600
500
400
300
Males
Females
200
100
0
2007
2010
2015
2020
2025
2032
While the AVM share of the total population is rapidly increasing (recall Figure 2-3), the rise in this
group’s share of VL at the end of the projection period is smaller than their increase in population
share (Figure 2-23). This is partly due to AVM having a considerably younger age profile than the
white population. It is also due to the assumption that the Visible Minorities population – which is
mostly growing through migration – is not aging over the forecast period23.
1,600
100,000
90,000
White
AVM
1,400
1,200
80,000
70,000
1,000
60,000
800
50,000
600
40,000
30,000
400
20,000
200
10,000
0
0
2007
23
AVM persons with visual impairment
White persons with visual impairment ('000)
FIGURE 2-22: PROJECTIONS OF VL, BY ETHNICITY, 2007 TO 2032
2010
2015
2020
2025
2032
This assumption is necessary as Statistics Canada does not disaggregate its growth forecasts for Visible Minorities by
age cohorts. However, it is plausible.
54
FIGURE 2-23: RELATIVE SHARE OF TOTAL VL, BY ETHNICITY, 2007 TO 2032
96%
White
5.0%
96%
AVM
4.9%
95%
4.8%
95%
4.7%
95%
4.6%
95%
4.5%
95%
4.4%
95%
4.3%
95%
AVM persons with visual impairment
White persons with visual impairment ('000)
5.1%
95%
4.2%
2007
2010
2015
2020
2025
2032
55
TABLE 2–40: ALL VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007
56
Prevalent cases
Males
White
Prevalence rate
Males
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
0
0
0
0
0
0
0
0
9,369
4,964
16,752
27,740
21,291
34,347
35,808
56,857
0
0
0
0
86
24
24
87
207
64
173
1,102
805
2,207
3,112
2,380
0
0
0
0
86
24
24
87
9,577
5,028
16,924
28,842
22,096
36,555
38,920
59,237
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
57,986
41,730
18,606
2,540
1,146
690
60,526
42,877
19,296
80-84
85-89
90+
All Males
325,451
14,646
340,097
All Males
AVM
Total
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.89%
0.43%
1.66%
2.99%
2.92%
6.38%
8.19%
15.51%
0.00%
0.00%
0.00%
0.00%
0.03%
0.01%
0.01%
0.03%
0.08%
0.03%
0.09%
0.99%
0.77%
2.98%
5.92%
8.00%
0.00%
0.00%
0.00%
0.00%
0.01%
0.00%
0.00%
0.01%
0.72%
0.37%
1.40%
2.78%
2.65%
5.97%
7.94%
14.95%
24.15%
36.04%
40.26%
16.65%
19.11%
28.81%
23.70%
34.75%
41.06%
2.5%
0.5%
2.1%
Female
White
AVM
Total
Female
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
0
0
0
0
0
0
0
0
9,080
4,895
16,903
28,374
21,967
36,264
40,146
71,038
0
0
0
0
49
347
345
205
389
271
487
1,568
1,182
1,715
3,895
4,232
0
0
0
0
49
347
345
205
9,469
5,166
17,390
29,942
23,148
37,979
44,041
75,270
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.9%
0.4%
1.7%
3.0%
2.9%
6.4%
8.2%
15.5%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.1%
0.1%
0.1%
0.1%
0.2%
1.3%
1.1%
1.9%
6.1%
11.5%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.7%
0.4%
1.4%
2.8%
2.7%
5.8%
7.9%
15.2%
80-84
85-89
90+
All
Females
All
Persons
89,952
83,576
52,888
4,114
1,760
1,213
94,066
85,336
54,101
24.1%
36.0%
40.3%
21.5%
25.4%
31.0%
24.0%
35.4%
40.6%
455,083
21,771
476,854
3.4%
0.7%
2.9%
780,534
36,417
816,951
80-84
85-89
90+
All
Females
All
Persons
3.0%
0.6%
2.5%
TABLE 2–41: CATARACT VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007
Prevalent cases
Males
White
Prevalence rate
Males
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0
0
0
0
0
0
0
0
0
0
0
783
78
873
3,173
8,692
13,186
10,086
7,010
0
0
0
0
0
0
0
0
0
0
0
198
63
229
1,261
626
978
375
334
0
0
0
0
0
0
0
0
0
0
0
980
141
1,102
4,434
9,319
14,164
10,462
7,344
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All Males
43,882
4,063
47,945
All Males
Female
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All
Females
All
Persons
0
0
0
0
0
0
0
0
0
0
0
801
80
921
3,557
10,860
20,455
20,201
19,927
0
0
0
0
0
0
0
0
0
0
0
166
58
450
2,334
1,791
2,458
969
861
0
0
0
0
0
0
0
0
0
0
0
967
138
1,371
5,892
12,651
22,914
21,170
20,788
76,803
9,088
85,891
120,685
13,151
133,836
AVM
Total
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.2%
0.7%
2.4%
5.5%
8.7%
15.2%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.2%
0.1%
0.3%
2.4%
2.1%
6.4%
6.3%
13.9%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.2%
0.9%
2.4%
5.5%
8.5%
15.6%
0.3%
0.1%
0.3%
Female
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All
Females
All
Persons
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.2%
0.7%
2.4%
5.5%
8.7%
15.2%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.1%
0.5%
3.6%
4.9%
12.8%
14.0%
22.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.2%
1.1%
2.6%
5.8%
8.8%
15.6%
0.6%
0.3%
0.5%
0.5%
0.2%
0.4%
57
TABLE 2–42: DR VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007
Prevalent cases
Males
White
AVM
Total
Prevalence rate
Males
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0
0
0
0
0
0
0
0
0
0
881
1,130
1,141
879
447
1,623
1,881
792
270
0
0
0
0
86
24
24
87
87
55
53
610
575
593
421
503
258
94
48
0
0
0
0
86
24
24
87
87
55
933
1,740
1,717
1,472
869
2,125
2,138
886
318
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.1%
0.2%
0.2%
0.1%
0.4%
0.8%
0.7%
0.6%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.6%
0.6%
0.8%
0.8%
1.7%
1.7%
1.6%
2.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.2%
0.2%
0.2%
0.2%
0.5%
0.8%
0.7%
0.7%
All Males
9,043
3,517
12,560
All Males
0.1%
0.1%
0.1%
Female
White
AVM
Total
Female
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All
Females
All
Persons
0
0
0
0
0
0
0
0
0
0
889
1,155
1,177
928
502
2,028
2,917
1,586
768
0
0
0
0
49
347
345
205
206
232
224
842
794
616
435
616
320
120
61
0
0
0
0
49
347
345
205
206
232
1,112
1,997
1,971
1,544
937
2,643
3,237
1,706
829
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.1%
0.2%
0.2%
0.1%
0.4%
0.8%
0.7%
0.6%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.7%
0.7%
0.7%
0.7%
1.7%
1.7%
1.7%
1.6%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.2%
0.2%
0.2%
0.2%
0.5%
0.8%
0.7%
0.6%
11,950
5,411
17,360
0.1%
0.2%
0.1%
20,992
8,928
29,920
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All
Females
All
Persons
0.1%
0.1%
0.1%
58
TABLE 2–43: GLAUCOMA VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007
Prevalent cases
Males
White
AVM
Total
Prevalence rate
Males
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0
0
0
0
0
0
0
0
0
0
0
0
0
885
879
1,246
3,643
1,533
568
0
0
0
0
0
0
0
0
0
0
0
0
0
402
532
118
285
78
37
0
0
0
0
0
0
0
0
0
0
0
0
0
1,288
1,410
1,364
3,928
1,611
605
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.2%
0.2%
0.3%
1.5%
1.3%
1.2%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.5%
1.0%
0.4%
1.9%
1.3%
1.5%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.2%
0.3%
0.3%
1.5%
1.3%
1.3%
All Males
8,753
1,453
10,206
All Males
0.1%
0.0%
0.1%
Female
White
AVM
Total
Female
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All
Females
All
Persons
0
0
0
0
0
0
0
0
0
0
0
0
0
935
985
1,556
5,651
3,069
1,615
0
0
0
0
0
0
0
0
0
0
0
0
0
164
209
297
177
50
24
0
0
0
0
0
0
0
0
0
0
0
0
0
1,099
1,194
1,853
5,828
3,119
1,639
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.2%
0.2%
0.3%
1.5%
1.3%
1.2%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.2%
0.3%
0.8%
0.9%
0.7%
0.6%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.2%
0.2%
0.4%
1.5%
1.3%
1.2%
13,812
920
14,731
0.1%
0.0%
0.1%
22,565
2,373
24,937
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All
Females
All
Persons
0.1%
0.0%
0.1%
59
TABLE 2–44: AMD VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007
Prevalent cases
Males
White
Prevalence rate
Males
White
AVM
Total
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.2%
1.7%
2.3%
8.8%
13.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.5%
1.9%
4.1%
7.0%
8.9%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.3%
1.7%
2.4%
8.6%
13.2%
0.2%
0.1%
0.2%
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0
0
0
0
0
0
0
0
0
0
0
0
0
436
968
6,236
5,537
10,157
5,996
0
0
0
0
0
0
0
0
0
0
0
0
0
83
264
551
624
420
214
0
0
0
0
0
0
0
0
0
0
0
0
0
519
1,232
6,787
6,161
10,577
6,210
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All Males
29,330
2,156
31,486
All Males
Female
White
AVM
Total
Female
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All
Females
All
Persons
0
0
0
0
0
0
0
0
0
0
0
0
0
461
1,085
7,791
8,590
20,342
17,043
0
0
0
0
0
0
0
0
0
0
0
0
0
128
341
611
600
360
184
0
0
0
0
0
0
0
0
0
0
0
0
0
589
1,427
8,402
9,190
20,702
17,227
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.2%
1.7%
2.3%
8.8%
13.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.5%
1.7%
3.1%
5.2%
4.7%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.3%
1.7%
2.3%
8.6%
12.9%
55,311
2,225
57,536
0.4%
0.1%
0.3%
84,641
4,380
89,022
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All
Females
All
Persons
0.3%
0.1%
0.3%
60
TABLE 2–45: RE/OTHER VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007
Prevalent cases
Males
White
Prevalence rate
Males
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.9%
0.4%
1.6%
2.8%
2.8%
5.8%
6.9%
10.7%
14.0%
16.5%
10.3%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.3%
0.2%
1.2%
1.2%
2.0%
2.6%
3.0%
2.4%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.7%
0.4%
1.3%
2.5%
2.4%
5.3%
6.3%
10.0%
13.4%
15.7%
10.3%
1.8%
0.1%
1.5%
AVM
Total
0
0
0
0
0
0
0
0
9,369
4,964
15,871
25,828
20,072
31,274
30,341
39,060
33,739
19,163
4,762
0
0
0
0
0
0
0
0
120
9
120
294
167
900
634
582
395
179
57
0
0
0
0
0
0
0
0
9,490
4,973
15,991
26,122
20,239
32,174
30,975
39,642
34,134
19,342
4,819
All Males
234,443
3,457
237,900
Female
White
AVM
Total
Female
White
AVM
Total
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All
Females
All
Persons
0
0
0
0
0
0
0
0
9,080
4,895
16,015
26,418
20,709
33,020
34,017
48,803
52,338
38,378
13,535
0
0
0
0
0
0
0
0
184
39
263
560
330
358
575
917
559
260
83
0
0
0
0
0
0
0
0
9,264
4,934
16,278
26,978
21,039
33,378
34,592
49,720
52,897
38,638
13,617
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.9%
0.4%
1.6%
2.8%
2.8%
5.8%
6.9%
10.7%
14.0%
16.5%
10.3%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.1%
0.5%
0.3%
0.4%
0.9%
2.5%
2.9%
3.8%
2.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.7%
0.4%
1.3%
2.5%
2.4%
5.1%
6.2%
10.0%
13.5%
16.0%
10.2%
297,207
4,129
301,336
2.2%
0.1%
1.8%
531,650
7,586
539,236
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All
Females
All
Persons
2.0%
0.1%
1.6%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
All Males
61
3. HEALTH SYSTEM EXPENDITURE
After ascertaining the prevalence of VL from the various eye disorders, costs to the Canadian
economy can be calculated. Financial costs included direct health system expenditure (medicines,
surgery, lenses, and so on) and indirect costs (for example, lower levels of employment for visually
impaired people and time spent by caregivers for people with VL).
While available data from Canada are not sufficient to uniformly adopt a ‘top-down’ approach (that
is, national expenditure on all forms of treatment for visually impairing eye conditions) or ‘bottom-up’
estimates (known costs and quantities of specific eye care procedures), using a combination
approach enables a reasonable estimate of total health system expenditure.
3.1
TOTAL EXPENDITURE ON ‘VISION CARE’
The Canadian Institute for Health Information (CIHI) tracks health expenditure on its National Health
Expenditure (NHEX) database, including expenditure on ‘vision care’. The vision care category
includes expenditures for the professional services of optometrists and dispensing opticians, as well
as expenditures for eyeglasses and contact lenses. Expenditure on vision care was nearly
$3.5 billion in 200724, representing 2.2% (Figure 3-1) of all health system expenditure ($160.1 billion
in 2007).
FIGURE 3-1: CANADIAN HEALTH SYSTEM EXPENDITURE, 2007 (% OF TOTAL)
Other Health Spending
6.1%
Administration
3.6%
Public Health
5.8%
Hospitals
28.4%
Capital
4.6%
Drugs
16.8%
Other Institutions
10.4%
Other Professional Services
8.6%
Vision Care
2.2%
Physicians
13.4%
Source: CIHI NHEX.
Apart from differentiating the services of particular types of health professionals (eg, optometrists),
the NHEX does not divide expenditure by disease category.
24
Expenditure for 2007 ($3,483m) was still a provisional forecast at time of drafting.
62
Expenditure on health care in Canada has been growing rapidly – considerably faster than Gross
Domestic Product. After adjusting for inflation, health care spending grew at an average annual real
rate of 3.8% between 1975 and 1991, by 0.8% per annum from 1991 to 1996 and by 5.1% from
1996 to 2003. However, expenditure on vision care has risen even faster, rising from 1.8% of the
total in 1975 to 2.2% in 2007 (Figure 3-2).
FIGURE 3-2: EXPENDITURE ON VISION CARE, CANADA, 1975-2007
1,000,000
100,000
1,000
Vision Care
Services
Total
10,000
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1,000
1975
100
Total health expenditure ($m)
Vision care expenditure ($m)
10,000
Source: CIHI NHEX.
NHEX data from earlier years (before 2007) provides more detail than are currently available for
2007. Total health system expenditure reported by the NHEX for Canada was $141.2 billion in 2005.
The majority of this, $99.1 billion (or 70.1%) was publicly funded, with the remaining $42.2 billion
(29.9%) privately funded.
The NHEX reports that in 2005, nearly all Canadian public expenditure (93.6%) came from
Provincial and Territory governments. Only 4.3% came from the Federal Government, with
municipal governments and worker’s compensation funds comprising the remaining 2.1%.
Households accounted for the majority (58.1%) of total private expenditure on health care in Canada
in 2005. Private health insurance entities constituted 29.2%, and ‘other’ (including hospital nonpatient revenue, capital expenditures for privately owned facilities and health research) made up the
remaining 12.7%.
Expenditure on vision care totalled $3.19 billion in 2005. In 2003 when the total was $2.64 billion,
the NHEX showed that private spending on vision care in Canada was $2.44 billion, whereas public
spending only amounted to $200 million.
Of private expenditure, households contributed
$1.91 billion and private health insurance $0.53 million.
3.2
EXPENDITURE ON PARTICULAR EYE DISORDERS
While ‘vision care’ is only a small component of overall health system expenditure on visually
impairing conditions, it can be supplemented from other sources. In a number of cases, detailed
63
information about the costs of certain eye procedures are available. Less frequently, numbers of
eye procedures performed are also available. Where both are available, ‘bottom up’ calculations of
expenditure can be estimated.
CIHI’s National Grouping System (NGS) attempts to provide reasonably comparable and consistent
statistics on the utilization, cost and distribution of physicians’ services for which payment was made
on a fee-for-service basis by provincial and territorial medical care insurance plans. CIHI (2007)
data on eye examinations and cataract surgery summed to around $144 million in 2004-05 (Table
3–1). Assuming expenditure on these procedures has risen by the same amount as total health
system expenditure, this figure would have risen to $153 million by 2007.
TABLE 3–1: TOTAL EXPENDITURE ON CERTAIN EYE PROCEDURES, 2004-05
Procedure
Eye Examinations
Cataract Surgery
Total
Number
Average $/case
Expenditure $m
373,148
284,523
657,671
$41.44
$452.30
$219.15
$15.5
$128.7
$144.2
Source: CIHI (2007). Note $/case is derived from the other two columns.
Additionally, some partial information is available on drug expenditure from Health Canada (2002a)
The Economic Burden of Illness in Canada 1998. Drug expenditure on two categories of eye
disorders – glaucoma and conjunctiva disorders – totalled $143.2 million in 1998 (Table 3–2). Given
the NHEX shows expenditure on drugs has increased by 214% since then, proportionally, this figure
in 2007 would be $307 million (Table 3–3).
TABLE 3–2: DRUG EXPENDITURE ON NERVOUS SYSTEM AND SENSE ORGAN DISORDERS, 1998
$m
Disorder
Glaucoma
Conjunctiva disorders
Ear infections
Parkinson’s disease
Other nervous system and sense organ disorders
Sub-total for nervous system and sense organ disorders
54.7
88.5
92.7
24.1
276.4
536.4
Total for all diseases
12,385.2
Source: Health Canada (2002a).
Health Canada (2002a) gives a breakdown of the ICD-10 block ‘Nervous System and Sense Organ
Disorders’, of which vision conditions are a major component. Unfortunately Health Canada were
unable to supply more detailed data than as provided in Table 3–3, to isolate the vision component.
TABLE 3–3: EXPENDITURE ON NERVOUS SYSTEM AND SENSE ORGAN DISORDERS (1998)
$m
Hospital Care
Drugs
Physician Care
Research
Total
1,425.6
536.4*
824.8
35.7
2,822.5
% of total health system expenditure
5.20%
4.30%
7.10%
0.20%
3.36%
Source: Health Canada (2002a). * Matches the Table 3-2 sub-total.
64
CIHI (2005) Exploring the 70/30 Split: How Canada’s Health System is Financed, provides quite
detailed information on the costs of a selected range of hospital procedures. The only procedure
listed there relevant to VL – ‘Retinal procedures’ – averaged $2,538 in 2003 (around half the cost of
most procedures). Charts in the same document show that these costs can be broken down to
provincial level. The CIHI website shows a casemix spreadsheet with the following reporting (Table
3–4) of eye operations by volume in 2000-01. This, together with the above data on cost of retinal
procedures, allows an estimate of the cost and quantity of retinal procedures (4,126 cases in
2000/01). A more detailed breakdown of hospital expenditures is not possible.
TABLE 3–4: FREQUENCY OF SELECTED HOSPITAL PROCEDURES (2001)25
Case Mix Description
Retinal procedures
Orbital procedures
Lens insertion
Other ophthalmic dx
Major eye infections
Other intraocular procedures
Other ophthalmic proc
Extraocular procedures
Iris and lens procedures
Hyphema
Volume FY00/01
4,126
2,889
1,284
1,134
847
715
492
289
110
95
Source: CIHI secure.cihi.ca/cihiweb/en/downloads/Casemix_ICDimpact_AppA_CMG_02_03.xls
For specialist consultations, data on Medicare rebates are available for some provinces. Rebates
for ophthalmological procedures from the Ontario Ministry of Health and Long-Term Care’s
Schedule of Benefits for Physician Services 2006 are shown in Table 3–5. However, for these data
to be useful there is also a need to know the numbers of each procedure performed.
TABLE 3–5: REBATES FOR CERTAIN OPHTHALMOLOGICAL PROCEDURES IN ONTARIO (2006)
Ophthalmological Listing
A235 Consultation
A935 Special surgical consultation (see General Preamble GP17)
A236 Repeat consultation
A233 Specific assessment
A234 Partial assessment
A237 Periodic Oculo-visual Assessment
A115 Major eye examination
A230 Orthoptic assessment
A250 Retinopathy of prematurity assessment
A252 Initial vision rehabilitation assessment
A251 Special ophthalmologic assessment
Cost ($)
71.30
132.50
45.85
42.15
22.45
42.15
42.15
25.00
120.00
240.00
120.00
Source: Ontario Ministry of Health and Long-Term Care’s Schedule of Benefits for Physician Services 2006.
25
COS advise that it is ‘totally unbelievable’ that there are four times as many retinal procedures as lens insertions (and in
Australia it is more like the other way round). Accordingly, information from this table is regarded as unreliable and not
utilized for final costings. It is still included, however, as part of the census of information available from official sources in
Canada.
65
Cruess et al (2007) provide a comprehensive coverage of the average costs involved in treating
AMD in Canada (Table 3–6), which can be used with prevalence data to estimate the total cost of
AMD.
TABLE 3–6: AVERAGE TREATMENT COSTS FOR NEOVASCULAR AMD (2005)
Treatment
Cost ($)
Verteporfin, one eye only
Simultaneous verteporfin treatment, both eyes
Intravitreal coriscosteroids, per eye
Photodynamic therapy with intravitreal steroid injection
$2,112
$2,266
$183
$308
Source: Cruess et al (2007).
Ray et al (2005) provide costs for both cataract surgery and retinal laser treatment for DR in
Canada of $1,323 and $709 in 2003. Interestingly, these procedures were substantially less
expensive in Canada than the same operations in Australia - $2,061 and $2,237 respectively.26
Iskedjian et al (2003) conducted an Ontario-based costing analysis of glaucoma in Canada and
estimated the total cost of procedures associated with the treatment of glaucoma to be $344 for
mild, $420 for moderate, and $511 for severe forms of glaucoma in 2001. These estimates included
the cost of the procedure itself, physician’s fee, assistant’s fee, and the anaesthetist’s fee. Costs
associated with hospital resources and medications were not included.
3.3
TOTAL HEALTH SYSTEM EXPENDITURE
3.3.1
HEALTH SYSTEM EXPENDITURE, TOP DOWN
This top down estimate relies primarily on two sources: Health Canada’s 2002 publication The
Economic Burden of Illness in Canada 1998 and CIHI’s National Health Expenditure Database
(NHEX), and is calculated as outlined below.

Total health system expenditure in 2007 was $160.1 billion dollars. Expenditure on ‘nervous
system and sense disorders’ in 1998 was 3.36% (from Table 3–3) of health system
expenditure (Health Canada, 2002a). However, health system expenditure as defined in this
source only covers hospitals, physicians, drugs and research. Assuming nervous system and
sense disorders are also responsible for the same ratio (3.36%) of the total health system
expenditure reported for 2007 by the NHEX ($160.1 billion) then total health system
expenditure on nervous system and sense disorders in 2007 would be $5.38 billion. This
provides an upper limit on expenditure on VL (for the above categories).

Health Canada (2002a) does not provide any further breakdowns, except for drugs (Table 3–
2). Within drugs there are a number of subcategories that can be attributable to VL (noting
that the category ‘other’ accounts for the majority of expenditure). Specifically, expenditure on
glaucoma and conjunctiva disorders can be attributed to VL, ear infections to other sense
organ disorders, and Parkinson’s to nervous system disorders. Thus represented, VL
accounts for 55.1% of such drug expenditure as it is able to be attributed to separately
identified categories; other sense organ disorders (ear infections) account for 35.7% and
nervous system disorders (Parkinson’s) account for 9.3%. It is assumed that expenditure in
‘other’ would have the same distribution between these identifiable categories.
26
In the original article, all costs were in Euros, converted to Canadian dollars at then prevailing exchange rates.
66

Assuming that, if VL accounts for 55.1% of all drug expenditure on ‘nervous system and sense
disorders’ then VL would also account for the same proportion of health system expenditure
on nervous system and sense disorders, and 55.1% of $5.38 billion equals $2.97 billion. This
provides an upper limit for VL expenditure under the hospital, research, physicians and drug
categories.

The NHEX also provides explicit expenditure for the professional services category under
‘Vision Care’,27 which includes optometrists, ophthalmologists, glasses and contact lenses, of
$3.48 billion. Adding vision care to the $5.38 billion estimate of expenditure on hospitals,
physicians, drugs and research yields a total of $6.45 billion in 2007.

The NHEX further shows that expenditure on ‘Other institutions’ is composed of nursing
homes (90%) and mental institutions (10%). Access Economics (2006) calculated that 3.0%
of US nursing home patients had been institutionalized due to VL. Thus, 2.7% (=3.0% * 90%)
of the total ‘other institutions’ of $16.7 billion (NHEX) is estimated to be due to VL, or
$448.8 million.

This still leaves an amount to be calculated for public health, administration, capital, and other
expenditure ‘not elsewhere classified’. These categories collectively account for 20% of total
health system expenditure (Figure 3-1). Thus, given the categories already calculated account
for 80% of health system expenditure, these remaining categories are equivalent to a quarter
of those already calculated (=20% / 80%), or $1.7 billion
Thus, a top down estimate of health system expenditure on VL in Canada for 2007 is
$8.64 billion.
TABLE 3–7: ESTIMATED VL HEALTH SYSTEM EXPENDITURE (TOP DOWN), 2007
Type of cost
Hospital
Physicians
Pharmaceuticals
Vision Care (optometry, ophthalmology and lenses)
Research
Other Institutions
Other (capital, public health, administration, other institutions and
professional services)
Total
3.3.2
Total ($m)
1,497.7
866.5
563.5
3,483.7
37.5
444.8
1,740.3
$8,637.9
HEALTH SYSTEM EXPENDITURE, BOTTOM UP
For a bottom up approach, estimates were undertaken for each of the five major eye diseases,
either for total expenditure, or by the categories covered under the top-down approach, but for each
individual disease.
For AMD, Cruess et al (2008) estimated the total to society of AMD in Canada was $1.12 billion in
2005. For the average patient, medical costs accounted for over three quarters of this figure
(76.7%) and non-medical costs (primarily aids, equipment and carers) the remainder (23.3%).
Subtracting non-medical costs proportionally leaves health system expenditure of $858.7 million. As
27
For total health system expenditure, the NHEX divides Professional Services is divided into two subcategories ‘Vision
Care’ and ‘Other’.
67
these estimates apply to 2005, allowing for cumulative inflationary increases of 4.7% yields a total
for 2007 health system expenditure of $898.9 million.
For RE, given this is the only form of VL correctable by lenses, the assumption was made most of
the NHEX category ‘vision care’ would be attributable to RE. Conversely, it was also assumed that
RE required little in the way of hospital care, physicians, drugs or the other categories in Table 3–7.
Thus, expenditure on RE would be around $3.48 billion.
For glaucoma, following the methodology adopted in the top-down approach, the ratio of glaucoma
drug expenditure to total nervous drug expenditure (10.2%) was assumed to hold for glaucoma’s
share of total ‘nervous system and sense organ disorders’ health system expenditure. Nervous
system and sense disorders in turn were (3.36%) of total health system expenditure. This yields a
total of $549 million for glaucoma.
Total expenditure on cataract surgery is estimated at $136.6 million, taking the $128.7 million in
2004-05 from Table 3–1 and allowing for inflation to 2007. Assuming that most such surgery takes
place in hospitals, then given hospitals account for 28.4% of total health system expenditure, if the
same ratio holds for cataract, total health system expenditure for cataract would be $481 million.
For diabetic retinopathy (DR), given there is only one frequency of procedure number, which COS
advise is not plausible, costs are assumed to be the same as the average for the other diseases
($6,875 per person per year), which for the total of 29,920 people with VL from DR, gives a total of
$205.71 million.
Thus, estimating from the bottom up, total health system expenditure on VL was $5.62 billion in
Canada in 2007. As with the top-down estimate, this figure needs to be scaled up to account for
factors such as capital expenditure, research, public health and other unallocated health
expenditure. For consistency, the same mark-up (25.2%) is used, giving a total bottom-up
estimate of $7.04 billion.
3.3.2.1
SUMMARY
The bottom-up estimate above is around 18.5% lower than the top-down estimate derived earlier.
Most of this difference would be due to the fact that the bottom-up estimate only includes the ‘big
five’ eye diseases (cataract, DR, glaucoma, AMD, RE). For example, Maberley et al (2006) in their
study of VL in one Canadian city found that 12% of VL was caused by visual pathway disease
(which is not included in the bottom up estimates).
Accordingly, while Access Economics has a preference to err on the side of caution, in this case the
top-down estimate is considered more reliable. Thus the total cost of VL-related health
expenditure in Canada is estimated as $8,637.9 million in 2007. This equates to $10,570 per
person with VL per annum.
68
4. OTHER FINANCIAL COSTS
In addition to health system costs, VL also imposes a number of other important financial costs on
society and the economy, including the following.

Productivity losses of people with VL comprise those from lower employment participation,
absenteeism and/or premature mortality.

Carer costs comprise the value of care services provided in the community primarily by
informal carers and not captured in health system costs.

Other costs comprise the cost of aids, home modifications and other pertinent financial costs
not captured elsewhere.

Transfer costs comprise the deadweight loss (DWL) associated with government transfers
such as taxation revenue forgone, welfare and disability payments.
It is important to make the economic distinction between real and transfer costs.

Real costs use up real resources, such as capital or labour, or reduce the economy’s overall
capacity to produce goods and services.

Transfer payments involve payments from one economic agent to another that do not use up
real resources eg, a disability support pension or taxation revenue.
Data on other financial costs are drawn from a variety of sources eg, the literature (focusing on
Canadian literature but sometimes supplemented by other international material).
4.1
PRODUCTIVITY LOSSES
Productivity losses are the cost of production that is lost when people with VL are unable to work
because of the condition. They may work less than they otherwise would (either being employed
less, being absent more often or being less productive while at work) or they may die prematurely.
This represents a real cost to the Canadian economy. Access Economics adopts a human capital
approach to measurement of productivity losses in developed countries.
4.1.1
EMPLOYMENT PARTICIPATION
Some insight into the employment impact of VL is provided by CNIB (2005). A survey of people
living with vision loss found that the employment rate among those of working age was only 24.7%
compared to 67.6% for the general population of the same age (Table 4–2). The chances of being
employed are thus almost two-thirds (64%) lower for someone who is visually impaired. In addition
to 24.7% who were employed, 49.2% listed themselves as unemployed, while the remaining 26.1%
were ‘retired’ or ‘other’ and are assumed to be not participating in the labour force. Thus, of those
actively participating in the labour force, 67% of people with VL describe themselves as
unemployed. Of those who were employed, 63% were working full time, but only 29% had a
permanent position. Alternate data from the 2001 PALS indicates that the employment rate among
those with VL was 32%. Given the PALS survey has a larger sample size than the CNIB survey, the
former is preferred. On PALS data, people with VL are around half as likely to be employed as
those with full sight (53% lower).
This reduced employment result was then combined with employment rates for each respective agegender group (Table 4–2) to calculate, from the number of people with VL in that age group, how
many would be unemployed. The lost productivity for those unemployed due to VL was then
69
measured by the average weekly earnings (AWE) of $855.06 that they would have otherwise been
earning (Table 4–1).28
TABLE 4–1: ESTIMATED AWE, BY AGE AND GENDER, 2007
Age
Male
Female
Persons
15-19
20-24
25-34
35-44
45-54
55-59
60-64
65+
Total
$264.49
$576.08
$926.61
$926.61
$1,096.00
$1,096.00
$1,095.09
$1,095.09
$1,036.21
$192.03
$493.65
$686.58
$686.58
$670.28
$670.28
$681.15
$681.15
$645.82
$227.35
$537.13
$817.92
$817.92
$897.63
$897.63
$890.38
$890.38
$855.06
Source: Derived from Statistics Canada Employment, Earnings and Hours, Cat No 72-002-XIB.
TABLE 4–2: PERCENTAGE OF POPULATION EMPLOYED, BY AGE AND GENDER
Age
Male
Female
15-19 years
20-24 years
25-34 years
35-44 years
45-54 years
55-64 years
45%
73%
86%
88%
85%
64%
49%
70%
78%
79%
78%
51%
Source: Statistics Canada, Labor force characteristics by age and sex http://www40.statcan.ca/l01/cst01/labor20a.htm
The annual cost of lost earnings due to reduced employment is thus estimated as
$4.06 billion in 2007.
4.1.2
ABSENTEEISM FROM PAID AND UNPAID WORK
In addition to workforce separation, people with VL may be absent from work more often as a result
of their impairment. Our literature search was unable to locate published works on such
absenteeism rates for people with VL in Canada.
However, Access Economics (2006) calculated (from the National Health Interview Survey-Disability
data set) that in the US, VL was shown to result in an additional 4.1 days off work per annum. This
estimate could also be applied to Canada, noting it is small ($155 per person with VL) relative to the
productivity cost associated with lower workforce participation.
In cases of absenteeism, employers often choose to make up lost production through overtime
employment of another employee that attracts a premium on the ordinary wage. The overtime
premium represents lost employer profits. On the other hand, the overtime premium also indicates
how much an employer is willing to pay to maintain the same level of production. Thus, if overtime
employment is not used, the overtime premium also represents lost employer profits due to lost
28
As Statistics Canada does not break down AWE for each age-gender group, these were estimated from the distribution
in Australia, due to the similarities (see footnote 11).
70
production. While productivity remains at the same level, the distribution of income between wages
and profits changes29. For this study it is assumed that the overtime rate is 40%30.
According to traditional microeconomic theory (in particular the work of Gary Becker in the 1960s),
people will work until they are indifferent between the marginal value of the income earned relative
to the personal value of the time sacrificed that could be used for unpaid domestic work or leisure.
However no-one else tends to value the individual's leisure similarly. The typical approach to
overcome this problem is to value leisure time at a discounted proportion of earnings which takes
into account taxes that reduce the effective income from work and restrictions on the amount of time
that can be used for work (for both biological and governmental regulation reasons). Access
Economics assumes that visually impaired people incur the same loss of time from unpaid work
(‘leisure’) as from paid work, but that the value of this time is 30% of paid work.
Based on these parameters and the AWE for each age-gender group, Access
Economics estimates that in 2007, the total cost of absenteeism due to VL is
$231.7 million. Of this, $22.8 million is the workplace absenteeism cost borne by the
employee, $122.5 million is the workplace absenteeism cost borne by the employer, and
$86.5 million is the value of absenteeism from unpaid work.
4.1.3
PRESENTEEISM
VL can also affect a person’s ability to work effectively while at work. Presenteeism can be
estimated by multiplying the number of days worked with VL by the percentage reduction in
effectiveness on days worked with VL. Workers with VL must have productivity reasonably close to
their sighted counterparts; otherwise they would not continue to be employed. With the right
equipment, they should be just as productive as anyone else. However, the CNIB survey found that
around three-quarters (73.8%) of workers with VL indicated that their workplace was taking some
measures to accommodate them; mostly in the form of adapted equipment, flexible scheduling and
modified responsibilities. Around a quarter (23.5%) indicated that they did not receive job
accommodation measures that they needed, with the greatest unmet need being for adaptive
computers. Daum et al (2004) in a study of productivity and visual status in the US found that vision
loss reduced productivity in the workforce by between 2.5% and 28.9%. Taking a simple average of
an 15.7% reduction in productivity, and applying this to the 23.5% of VL workers without proper
equipment, yields an estimated overall lower productivity for VL workers of 3.7%.
Such a low level of productivity highlights the significant impact of VL on employment outcomes.
Given these results, Access Economics estimates that in 2007, the total cost of
‘presenteeism’ (lower productivity while at work) due to VL is $133.9 million.
29
While the opportunity cost of any overtime employment of another employee is implicitly taken into account through the
overtime premium, this methodology does not allow for the choice to use salaried or part-time employees to make up the
production at ordinary or no additional wage costs. However given that workers are assumed to value their leisure time at
30% of their earnings, the difference in estimated economic costs if this choice is taken into account would be small – the
only difference would be that ‘society’ would incur these costs rather than the ‘employer’.
30
Based on the lower bound of workplace injuries literature - NOHSC assumed an overtime rate of 40% (Access
Economics 2004b).
71
4.1.4
PREMATURE MORTALITY
The production loss arising from premature mortality associated with VL through falls and
depression is calculated as the expected remaining lifetime earnings multiplied by the number of
people who died prematurely who would otherwise have been employed. As discussed in Section
5.2.2, the estimated number of deaths due to VL is 313. Since most (98%) of these deaths are in
the 75+ age group where employment rates are low, lifetime earnings lost are not large.
The estimated annual cost due to lost productivity from premature death due to
VL is $3.4 million in 2007.
Premature death also leads to additional search and hiring costs for replacement workers. These
are estimated as the number of people with VL who die prematurely (by age and gender) multiplied
by their chance of being employed multiplied by the search and hiring cost brought forward three
years (the search and hiring cost is estimated as 26 weeks at AWE and the three year bring forward
reflects average staff turnover rates). Since premature mortality costs are very low, these costs are
tiny.
In 2007, additional search and hiring costs are estimated at only $9,040 for
people with VL, based on the present value of bringing forward three years of average
cost of staff turnover (26 weeks at AWE).
4.1.5
FUNERAL COSTS
The ‘additional’ cost of funerals borne by family and friends of people with VL is based on the
additional likelihood of death associated with VL in the period that the person experiences it.
However, some people (particularly older people) would have died during this time anyway.
Eventually everyone must die and thus incur funeral expenses – so the true cost is the cost brought
forward (adjusted for the likelihood of dying anyway in a given year). The most recent official data
on funeral costs from are from 1991 (Statistics Canada, 1998), at which point an average funeral
cost around $3,510. Updating this to allow for inflation to 2007 yields a current cost of $4,301. (This
roughly accords with the figure from the Australian Bureau of Transport and Road Economics
(2000), which after allowing for inflation and conversion to Canadian dollars, equates to $3,541.)
The bring forward of funeral costs associated with premature death for people with VL
is estimated at around $1.1 million in 2007.
4.2
DWL FROM TRANSFERS
Lost taxation revenue is considered a transfer payment, rather than an economic cost. However,
raising additional taxation revenue does impose real efficiency costs on the Canadian economy,
known as DWLs. Besides the cost of administering the taxation system costs, DWLs arise from the
distortionary impact of taxes on workers’ work and consumption choices.
4.2.1
LOST TAXATION REVENUE
Reduced earnings due to reduced workforce participation, absenteeism and premature death will
also have an effect on taxation revenue collected by Canadian Governments. As well as forgone
income (personal) taxation, there will also be a fall in indirect (consumption) tax, as those with lower
incomes spend less on the consumption of goods and services.
72
Personal income tax forgone is a product of the average personal income tax rate and the forgone
income. With VL and lower income, there will be less consumption of goods and services,
estimated up to the level of the disability pension. Without VL, it is assumed that consumption would
comprise (on average) virtually all household income - based on Statistics Canada reports that
Canadians only save 3% of their income (Chawla and Wannell, 2005). The indirect tax forgone is
estimated as a product of the forgone consumption and the average indirect tax rate.
The (Federal) Canadian Goods and Services Tax (GST) rate is 5%, however most Provinces also
levy separate sales taxes. In fact in Canada there are three types of sales taxes: provincial sales
taxes or PST, the federal Goods and Services Tax or GST, and the Harmonized Sales Tax or HST.
Every province except Alberta implements a Provincial Sales Tax or HST. The Yukon Territory,
Northwest Territories and Nunavut do not have any type of regional sales tax.
The HST is used in certain provinces to combine the federal GST and the PST into a single,
blended, sales tax. Currently, there is a 13% HST in the provinces of New Brunswick,
Newfoundland, and Nova Scotia. The HST is collected by the Canada Revenue Agency, which then
remits the appropriate amounts to the participating provinces.
Separate PST are collected in the provinces of British Columbia, Saskatchewan, Manitoba, Ontario,
Quebec, and Prince Edward Island. Goods to which the tax is applied vary by province, as do the
rates. Moreover, for those provinces whose provincial sales tax is applied to the combined cost and
GST, provincial revenues decline or increase with respective changes in the GST.
TABLE 4–3: PROVINCIAL SALES TAXES
Province
Alberta
British Columbia
Saskatchewan
Manitoba
Ontario
Quebec
Prince Edward Island
Rate
0
7%
5%
7%
8%
7.5%
10%
Notes
Alcohol 10%
Alcohol 10%
Lodging 5%
Alcohol and entertainment at restaurants 10%
Alcohol at retail stores 12%
Also applied to Federal GST, so effectively 7.875%
Also applied to Federal GST, so effectively 10.5%
Source: www.taxtips.ca
From these sources it is possible to estimate taxation revenue forgone due to VL. Both Federal and
Provincial direct taxes have progressive rates. For a Canadian on the average income of $40,082,
total Federal income tax would be $6,166 at an average rate of 15.4%. Given the multiplicity of
Provincial direct taxes, Quebec was chosen as being representative as it has one of the largest
populations and its tax rates are roughly mid range. A Quebecois on an income of $40,082 would
pay $2,551 in direct taxes at an average tax rate of 6.4%. These average taxation rates are sourced
from the Canadian Revenue Authority.
For indirect taxes, although Federal GST is 5%, the numerous Provincial indirect taxes (Table 4–3)
mean that, again, Quebec is selected as a representative Province, with its effective indirect tax of
7.875%.
Personal income tax forgone is then calculated as the product of the average personal income tax
rate (21.8%) and the forgone income. With VL and lower income, there will be less consumption of
goods and services, with the indirect taxation rate estimated as 12.9%.
73
Around $1.75 billion in lost potential tax revenue is estimated to be incurred in
2007, due to the reduced productivity of people with VL.
Lost taxation revenue is considered a transfer payment, rather than an economic cost per se.
4.2.2
SOCIAL SECURITY PAYMENTS
The CNIB (2005) study on the needs of blind or visually impaired people briefly covered their
sources of income.

The CNIB study encompassed 352 adult client participants nation-wide with VL. Of these, 61%
were female (213), and 39% were male (139), while 57% of adult participants were working
age (21–64), and 43% were seniors (65+).

The most frequent source of income for all adult client participants was some form of
government income supplement program (federal or provincial). However, unsurprisingly there
were age related differences in the programs that were providing benefits. The vast majority of
senior participants reported receiving a federal pension (91%), compared to only 26% of
working age participants. Conversely, 41% of working age participants reported receiving
provincial disability benefits, compared to only 6% of seniors. Income from employment was
low overall (12% for all adult consumer participants), and again age made a difference. Of
working age participants 24% reported income from employment or self-employment,
compared to 2% of seniors. Seniors were more likely to report receiving a private pension
(31%) than were working age participants (8%). Table 4–4 provides an overview of income
sources for adult participants.
TABLE 4–4: INCOME SOURCES (CNIB)
Income Source
All
Working Age
Seniors
Federal pension*
54%
26%
91%
Provincial disability benefits
Private pension
Private income
Employment
Spousal support
26%
18%
13%
12%
8%
41%
8%
8%
19%
9.5%
6%
31%
19%
1%
5%
Self-employment
Family support
Other
4%
2.3%
8%
5.4%
3%
8%
1.3%
1.3%
8%
* Federal pensions included Old Age Pension, Disability Pension, and Veterans Pension.
Source: CNIB (2005).
Publicly available data exist for social security spending and recipients in Canada – reported by
Human Resources and Social Development Canada as part of its Social Security Statistics Canada
and Provinces 1978-79 to 2002-03.31 Selected payments that people with VL may access are
presented in Table 4–5 – these data refer to aggregate payments to all recipients rather than
payments to people with VL only.
31
See: http://www.hrsdc.gc.ca/en/cs/sp/sdc/socpol/tables/page02.shtml (accessed Wednesday 6 February, 2008).
74
TABLE 4–5: VL-RELATED SOCIAL SECURITY PAYMENTS AND BENEFICIARIES
Total
payments
($000)
Old age security
Veterans' and civilians' disability pensions
Canada and Quebec pension plans
Employment assistance for persons with disabilities
Provincial welfare programs
Total
Beneficiaries
(number)
$/beneficiary
20,464,192
1,473,118
3,330,019
378,318
20,552,751
3,941,039
164,805
340,116
5,193
8,939
9,791
46,198,398
Source: Human Resources and Social Development Canada, Social Security Statistics Canada and Provinces 1978-79 to
2002-03.
The data from Table 4–5 can be used to calculate the excess number of people with VL who receive
payment relative to population norms. These excess usage rates can then be multiplied by the
average payment rates to estimate the social security payments for people with VL.

CNIB (2005) did not include unemployment benefits as a source of income for the visually
impaired. Presumably then, working age people with VL are either employed or on disability
pension.
TABLE 4–6: EXCESS USAGE OF SOCIAL SECURITY PAYMENTS
Income Source
Working
Age
Federal pension*
Provincial
disability benefits
26%
41%
4.2.3
Usage % of
total
population
2%
8%
Excess
usage
24.4%
32.8%
VL
working
age pop
209,122
209,122
VL who
get
benefit
54,372
85,740
Pop who
get benefit
504,921
2,577,363
%
Attributable
to VL
10.8%
3.3%
DEADWEIGHT LOSSES
The welfare payments calculated immediately above are, like taxation revenue losses, not
themselves economic costs but rather a financial transfer from taxpayers to the income support
recipients. The real resource cost of these transfer payments is only the associated DWL.
DWLs refer to the costs of administering welfare pensions and raising additional taxation revenues.
For any given fiscal position, invalid and sickness benefits must be financed through taxation.
Although welfare payments and forgone taxation are not real costs (so should not be included in the
estimation of total costs), it is still worthwhile estimating them as that helps us understand how the
total costs of VL are shared between the taxpayer, the individual and other financiers.
DWL is the loss of consumer and producer surplus, as a result of the imposition of a distortion to the
equilibrium (society preferred) level of output and prices. Taxes alter the price and quantity of goods
sold compared to what they would be if the market were not distorted, and thus lead to some
diminution in the value of trade between buyers and sellers that would otherwise be enjoyed (Figure
4-1).
75
FIGURE 4-1: DWL OF TAXATION
Price ($)
Supply
Deadweight Loss (cost
of raising taxation
revenue)
Price plus Tax
Taxation Revenue
Price
Demand
Output
Actual Quantity
Supplied
Potential Quantity
Supplied
Usher (2002) estimates the DWL of raising revenue in Canada at 20.2%.
Access Economics estimates that around $1.75 billion in DWL is incurred in 2007, due
to the additional taxation required to replace that forgone due to lost productivity of
people with VL and welfare payments. Of this, $1.2 billion is a result of the governmentfinanced component of health system expenditures, $348 million is due to taxation
revenue forgone and $185 million is due to welfare expenditures.
4.3
CARE AND OTHER ASSISTANCE
Carers are people who provide informal care to others in need of assistance or support. Most
informal carers are family or friends of the person receiving care. Carers may take time off work to
accompany people with VL to medical appointments, stay with them in hospital, or care for them at
home. Carers may also take time off work to undertake many of the unpaid tasks that the person
with VL would do if they did not have VL and were able to do these tasks.
A recent study focusing on AMD only rather than overall VL calculated the burden of neovascular
AMD in the Canadian population (Cruess et al, 2007). This cross-sectional, observational analysis
was conducted in relation to self-reported functional health, wellbeing and disease burden among
elderly subjects in Canada with (n=67) and without (n=99) neovascular AMD.

32
Subjects with neovascular AMD reported significantly worse vision-related functioning and
overall wellbeing than controls (adjusted mean scores on the NEI-VFQ-2532: 48.0 vs. 87.5) and
significantly more depression symptoms than controls (Hospital Anxiety and Depression Scale:
5.8 vs. 4.3). The annual neovascular AMD cost per patient was $11,334, which is over eight
National
Eye
Institute
Visual
Functioning
Questionnaire
http://www.nei.nih.gov/resources/visionfunction/vfq_ia.pdf
76
(25
questions).
See,
for
example,
times that of elderly subjects without neovascular AMD ($1,412). Over half of the neovascular
AMD costs were direct medical costs.

Subjects with neovascular AMD also reported more than twice the need for assistance with
daily activities compared with controls (19% vs. 9%). This allows us to calculate the excess
care required by people with AMD relative to the rest of the population – by taking the
difference between the two figures.
FIGURE 4-2: COMPARISON OF ASSISTANCE WITH ACTIVITIES OF DAILY LIVING BETWEEN STUDY GROUPS
19%
Neovascular AMD
Control group
13%
9%
4%
Daily activities Home care
overall
5%
3%
2%
3%
4%
4%
5%
2%
1%
Other Administrative transportation
tasks
0%
Self care
Transportation for health care
Leisure activities
Cruess et al (2007) also reported unit costs for non-medical related costs of AMD with data sourced
from the Canadian Management Information Systems database. These data relate to people with
AMD only rather than people with VL as a whole.
The main unit cost categories were direct vision-related medical costs, direct non vision-related
medical costs, and direct non-medical costs (living in government-sponsored assisted living
facilities, assistance received for daily activities, and social benefits received). Given that other
health-related costs data sources have already been identified in this study (see Sections 3 and 4),
the most useful data from Cruess et al (2007) related to the non-medical costs.
After collecting the unit costs, annual utilisation costs were then calculated by multiplying the
number of units consumed by the unit cost. Overall, people with AMD had much higher non-medical
costs ($2,553.25) which included home care/living assistance compared to the control group
($601.02).
TABLE 4–7: ANNUAL DIRECT AMD NON-MEDICAL RELATED UTILISATION COSTS PER PERSON (2005$)
Direct non medical related utilisation costs per person
AMD
Total living situation related costs
$240.68
Control
$0.00
Total costs of assistance for daily activities received
$2,312.57
$601.02
Total
$2,553.25
$601.02
77
Cruess (2007) provides an overview of carer costs for AMD ($2,553.25 per person per annum) and
for an age-matched control group ($601.02). Thus, the difference between the two groups
($1,952.23 pa) is the cost of care that is specific to AMD. Access Economics has assumed that
additional care is not due to having a particular eye disease as such, so much as to the VL caused
by that disease. AMD’s disability weight (0.235) is 1.6 times higher than the average disability
weight across all eye diseases (0.145). So, factoring down, the expected care costs for people with
VL – above their fully sighted counterparts – would be $1,208.99 per person per year. Thus, for the
total visually impaired population of 0.82 million, annual carer costs attributable to VL is
$0.63 billion.
Rehabilitation and library costs
According to CNIB, the cost of provision of rehabilitation services for people with vision loss in 2007
was $32.8 million. In addition, the cost of special library services for people with vision loss was
$7.4 million. Only 23% of these funds are provided by government. The rest is provided by support
from the public.
Also, there are two other significant organizations providing services in Quebec – the Institut
Nazareth et Louis Braille and MAB-Mackay (the Montreal Association for the Blind and the Mackay
Rehabilitation Centre). Financial information from most recent annual reports on their websites33
suggests costs relating to these organisations are estimated as $12.8 million and $8.8 million
respectively in 2007.
In total, the rehabilitation and library costs are estimated as $61.8 million and total cost of care is
estimated as $0.693 billion.
4.4
AIDS AND DEVICES
People who are visually impaired or blind require a variety of devices, special equipment and home
modifications to function adequately and to enhance their quality of life.
The greater need for devices and home modifications due to VL and blindness has been established
in international studies (for example, Brezin, 2005; Access Economics, 2004a).

In the Australian study, the cost of devices and modifications was estimated as A$318 to
A$571 per visually impaired person on average in 2004. The French study estimated only
additional utilization, not costs.
Two sets of supports are provided for people with low vision and those who are blind because of the
different needs of these two populations. For people who are blind, support primarily involves
assistance using non-visual sensory data. For those with low vision, supports primarily involve
magnifying or enlarging, brightening and enhancing contrast in visual displays or cues.
CNIB is the primary source for devices for the visually impaired and, as a result, prices reported are
from CNIB price lists for the period 2000-01, weighted by the number of items sold of each of the
brands/models available. Volumes of sales were reported in the December 2003 Price Survey of
Assistive Devices and Supports for Persons with Disabilities produced by the Department of Human
Resources and Social Development.
33
http://www.mab.ca/ and http://www.inlb.qc.ca/apropos/ra2006-2007.aspx#s11
78

4.4.1
These data are inflated to 2007 by Consumer Price Inflation and population growth. They
provide a good indication of the types of aids and modifications used, as well as the volume in
which they are used across Canada and their price.
CANES AND ACCESSORIES
Two different brands/types of canes were priced—a mobility (way-finding) cane and a support cane.
Each is available in three identically priced models. In 2000, 1,278 canes were sold at an average
price of $21.78.

The mobility cane folds, comes with a rubber tip grip bottom, handle and connecting elastics.
The average price for the 626 mobility canes sold was $20.00.

The support cane is made of moulded plastic, has a height adjustment and a rubber tip grip
bottom. A total of 652 of these were purchased at an average price of $23.50. These types of
cane can also be used by some people with mobility limitations.
In addition, three frequently purchased accessories were priced.

Replacement cane elastics for the folding mobility canes—163 were purchased at a price of
$0.30 each.

Roller tips used for some types of mobility canes (the cane slides on a ball bearing allowing
continuous contact with the ground, providing an alternative method for way finding—a
sweeping motion rather than the more common tapping motion)—163 of these were
purchased at $11.00 each.

Flip-up ice spikes which replace grip bottoms on support canes—166 were purchased at a
price of $8.80 each.
TABLE 4–8: CANES/ACCESSORIES FOR THE BLIND (2000-01$)
Product
Canes
Way Finding Canes
Support Canes
Accessories
For Way finding Canes:
Replacement cane plastics
Roller Tips
For Support Canes:
Ice Spikes (flip-up)
Sub total
Number
sold
per
year
Average
price
Cost per
year (in
2000-01)
1,278
626
652
$21.78
$20.00
$23.50
$27,834.84
$12,520.00
$15,322.00
163
163
$0.30
$11.00
$48.90
$1,793.00
166
$8.80
$1,460.80
1,770
n/a
$31,144.70
Note: Numbers may not sum exactly due to rounding.
4.4.2
WRITING AIDS/STATIONERY
Writing and reading for the blind primarily uses the Braille system of embossed dot patterns. Braille
embossers are devices designed to produce Braille writing on paper. They can be as simple as
slates/frames and stylus or manual, Braille typewriters such as the Perkins Brailler. However, there
are also more advanced computerized brailing devices such as the Mountbatten Brailler. There are
also high speed computer Braille printers.
79
4.4.2.1
BRAILLE SLATES/FRAMES AND STYLUSES
Braille slates/frames and stylus systems are used to manually emboss Braille dots. Braille slates are
part of a frame such that a two-line slate can be stepped down a page with a hinge system to give a
whole page of Braille. Plastic slates are lighter than metal ones but tend to have a lower life
expectancy. Frames without hinges only work with a fixed size of paper, but are very popular as a
highly portable note-taking device.
The stylus handle design significantly affects ease of use. The easier to use, large handle styluses,
however, are less convenient to carry.
The weighted average price of the 16 slates commonly purchased at CNIB is $56.61. A total of 790
basic four-line plastic slates were sold at $6.50. However, this was the minimum price slate – and
prices varied to a maximum of $158.50 for a 28-line, full page, heavy duty metal slate.
The average price of the six CNIB styluses available at CNIB is $6.00. The ‘Erasable’ stylus is
priced at $21.50.
4.4.2.2
BRAILLE TYPEWRITERS
The average price of the five manual Perkins Braillers sold at CNIB is $1,393.20. The electric
Perkins Brailler is priced at $1,750.
4.4.2.3
NOTE TAKERS
Note takers are computerized devices which have either standard or Braille-input keyboards. They
usually have built-in speech output and/or Braille displays. They may be either palmtop or laptop
devices. Standard-key note takers are used by persons with vision impairment, Braille note takers
by persons who are blind.
Common features that come with note takers include word processing, diary, telephone directory,
database and communications functions, and plugs which allow the user to connect peripheral
devices such as printers, modems and Braille embossers.
The note taker available at CNIB provides a Braille-input keyboard and Braille display/computer
output at a price of $5,365.
4.4.2.4
COMMON STATIONERY
Three types of Braille paper were priced. Each is rawhide tag manila and regular weight, and
contains approximately 250 sheets per package. The average price paid for 1,094 purchases of the
best selling Braille paper was $24.34.
In addition, CNIB sells a number of Braille calendars. In 2000-01, 532 were sold at a price of $2.00.
80
TABLE 4–9: WRITING AND STATIONERY ITEMS (2000-01$)
Product
Number sold Average
per year
price
Braille Paper (250 sheet package)
1,094
Cost per
year (in
2000-01)
$24.34 $26,627.96
8.5 x 11 inches
560
$14.25
$7,980.00
11 x 11 inches
322
$17.75
$5,715.50
Computer paper, 12.5 x 11 Cerlox
212
$61.00 $12,932.00
Embossing Sheets
1,319
$3.00
$3,957.00
532
$2.00
$1,064.00
Braille Calendar
Total
2,945
n/a $36,783.50
4.4.3
VARIABLE SPEED TAPE RECORDERS
A total of 12 cassette recorders were available from CNIB at an average price of $263.33. Prices
varied from a minimum of $62.50 for a portable to $528.50 for a large, desk-top model. Most prices
were near or at the overall average.
4.4.4
COMPUTER VOICE SYNTHESIZER SOFTWARE
Five types of common computer software used by people who are blind are available from CNIB.
Three of these convert data from either a file or a screen display to voice.
The average price of this software was $1,328.33. Two also included scanning capacity and convert
written documents to computer files, as well as providing a voice synthesizer. The average price of
these two packages was $1,795. These software packages can also be used with electronic Braille
display systems (see next sub-section).
4.4.5
ELECTRONIC BRAILLE DISPLAY SYSTEMS
An electronic Braille display system is a device designed to present computer screen text as Braille.
A Braille display uses a series of electronic ‘pins’, which are either in the up or down position. Text
on the screen is displayed as Braille through the pattern of up and down pins. Braille displays make
excellent computer access devices for Braille-literate persons but are very expensive. The model
available at CNIB is priced at $18,708.
4.4.6
TALKING TIME PIECES
Three types of time pieces were priced—talking clocks, wrist watches and a talking key chain. All
prices include batteries.
A total of 1,406 talking clocks were purchased in 2000 at an average price of $20.65. The cost of the
four different devices ranged from a low of $14.95 to a high of $28.50.
In 2000, a total of 4,650 talking wrist watches were purchased, at an average price of $19.24. Four
different brands were commonly sold, varying from a price of $9.00 to a high of $65.00. Price varies
considerably with watch style and features. For example, the more expensive watches have a gold
or silver casing and choice of alarm sounds, while the lower range watches are encased in plastic.
81
Talking time-keeping key chains cost an average of $11.00 and in 2000, 1,652 were sold.
TABLE 4–10: TALKING TIME PIECES (2000-01$)
Product
Number sold Average Cost per year
per year
price
(in 2000-01)
Talking clocks
1,278
$21.78
$27,834.84
Talking wrist watches
4,650
$19.24
$89,466.00
Talking key chain
1,652
$11.00
$18,172.00
Total
7,580
n/a
$135,472.84
4.4.7
SUNGLASSES WITH NON-CORRECTIVE LENSES
A total of 4,570 regular sunglasses were sold by CNIB in 2000 at an average price of $12.35.
Sunglasses with UV protection were most popular. A total of 3,544 pairs were sold in 2000 at an
average price of $13.00. The remaining 631 pairs of regular sunglasses were sold at $8.00.
TABLE 4–11: SUNGLASSES WITH NON-CORRECTIVE LENSES (2000-01$)
Product
4.4.8
Number sold Average
per year
price
Cost per year
(in 2000-01)
Sunglasses with UV protection
Regular sunglasses
3,544
631
$13.00
$8.00
$46,072.00
$5,048.00
Total
4,175
n/a
$51,120.00
HAND HELD MAGNIFIERS
Magnifiers vary in strength and can come with small lights or ‘illuminators’. The average price of the
4,531 magnifiers sold in the year 2000 by CNIB was $33.70. At one end of the spectrum in this
group are simply-designed, light, plastic magnifiers, which are priced in the $9.50-$14.50 range. At
the other end are more solidly built models with glass lenses and/or illuminators, which are priced in
the $43.50 to $50.00 range.
Magnifying sheets were also priced. These are plastic covers that fit over and magnify book or
newspaper pages. A total of 2,180 sheets were sold in 2000 at a price of $2.20.
TABLE 4–12: HAND HELD MAGNIFIERS (2000-01$)
Product
4.4.9
Number sold Average Cost per year (in 2000-01)
per year
price
Magnifiers/hand
readers
4,521
$33.70
$152,357.70
Total
4,521
n/a
$152,357.70
VIDEO MAGNIFIERS/CCTVS
Screen magnifiers enlarge what is displayed on a computer monitor so people with vision problems
can read the text on the screen. Closed Circuit Televisions (CCTVs) are devices that use a camera
82
to magnify printed text and images placed under it. These are then presented enlarged on a
television screen or computer monitor.
CNIB has two electronic video magnifiers that connect to an ordinary TV. The black and white only
magnifier is priced at $1,119, while the colour model costs $1,499. CNIB also has a number of full
CCTV systems, which include the monitor and TV screen and which can be connected to a
computer. The average price of the black and white CCTVs offered is $2,875 and the colour CCTVs
have an average price of $4,348.
4.4.10
SCREEN MAGNIFICATION SOFTWARE
Screen magnification software significantly enlarges screen text and graphics to a size that a vision
impaired users can easily view. CNIB offers two such products at an average price of $814.50
4.4.11
OTHER AIDS FOR THE SIGHT IMPAIRED
4.4.11.1
STATIONERY
Three different writing pads with bolded lines were priced. These pads include 100 white sheets of
black thick lined writing paper. In total, 1,200 pads were purchased in 2000, each at $3.80. In
addition, 10,829 large print calendars were purchased at a price of $2.00.
TABLE 4–13: OTHER STATIONERY (2000-01$)
Product
Writing pads
4.4.11.2
per year
price
(in 2000-01)
1,200
$3.80
$4,560.00
Large print calendars
10,829
$2.00
$21,658.00
Total
12,029
n/a
$26,218.00
LARGE BUTTON TELEPHONES
Two prices for large button telephones with high sales volumes were obtained from CNIB price list.
The first model phone also has speaker phone capacity. A total of 244 of these phones were sold in
2000 at a price of $33.00.
The second phone provides features for persons who are also hearing impaired—a hearing aid
attachment and an adjustable very loud ringer. In 2000, 226 of these were sold at $70.00.
83
TABLE 4–14: LARGE BUTTON TELEPHONES (2000-01$)
Product
4.4.12
per year
price
(in 2000-01)
Phone with speaker phone
capacity
244
$33.00
$8,052.00
Phone for hearing impaired
226
$70.00
$15,820.00
Total
470
n/a
$23,872.00
SUMMARY OF AIDS AND DEVICES
Overall, available CNIB data on prices and volumes show that there was around $456,968.74 spent
on vision impairment-related aids and devices (Table 4–15) in 2000-01. In today’s dollars that would
equate to around $524,046.72 (after inflating by the Consumer Price Index).
84
TABLE 4–15: SUMMARY OF AIDS AND DEVICES (2000-01$)
Number
sold per
year
Average
price
Cost per
year
(in 2000-01)
1,278
626
$21.78
$20.00
$27,834.84
$12,520.00
Support Canes
652
$23.50
$15,322.00
Accessories for Way Finding Canes
Replacement cane plastics
Roller Tips
163
163
$0.30
$11.00
$48.90
$1,793.00
Accessories for Support Canes
Ice Spikes (flip-up)
166
$8.80
$1,460.80
1,770
n/a
$31,144.70
790
$6.50
$5,135.00
1,094
560
322
$24.34
$14.25
$17.75
$26,627.96
$7,980.00
$5,715.50
Embossing Sheets
Braille Calendar
212
1,319
532
$61.00
$3.00
$2.00
$12,932.00
$3,957.00
$1,064.00
Sub total
2,945
n/a
$36,783.50
Talking clocks
1,278
$21.78
Talking Wrist Watches
4,650
$19.24
Talking Key Chain
1,652
$11.00
$27,834.84 $89,466.00 $18,172.00 Sub total
7,580
n/a
$135,472.84 Product
Canes
Way Finding Canes
Sub total
Braille slates
Braille Paper (250 sheet
package)
8.5 x 11 inches
11 x 11 inches
Computer paper, 12.5 x 11
Cerlox
Magnifiers/Hand Readers
4,521
$33.70
3.5-4.4X magnifier
1,514
$32.52
5X–11X magnifier w/light
1,076
$43.50
$152,357.70 $49,235.28 $46,806.00 Sub total
4,521
n/a
$152,357.70
Sunglasses with UV protection
Regular sunglasses
3,544
631
$13.00
$8.00
$46,072.00
$5,048.00
Sub total
4,175
n/a
$51,120.00
Writing pads
Large print calendars
1,200
10,829
$3.80
$2.00
$4,560.00
$21,658.00
Sub total
12,029
n/a
$26,218.00
Phone with speaker phone
capacity
Phone for hearing impaired
244
226
$33.00
$70.00
$8,052.00
$15,820.00
Sub total
470
n/a
$23,872.00
Total
$456,968.74
The above data are supplemented by estimates of volumes data on: Braille slates/frames and
styluses; Braille typewriters; note takers; variable speed tape recorders; computer voice synthesiser
85
software; electronic Braille display systems; video magnifiers/CCTVs; and screen magnification
software. Volume data were estimated by using US usage per person data from Access Economics
(2006).
These additional devices added $15.1 million for CNIB clients, resulting in an overall total for CNIB
aids and modifications of $15.6 million.
TABLE 4–16: ESTIMATES OF ADDITIONAL AIDS AND DEVICES
Product
Number
sold per
year
Average
price
Cost per
year
(in 2000-01)
Stylus
Erasable stylus
Braille typewriter
Note takers
Variable speed tape recorders
835
835
835
835
835
6
21.5
1750
5365
263.33
$5,012
$17,959
$1,461,742
$4,481,282
$219,955
Computer voice synthesisers
Electronic Braille display
systems
Video magnifiers (black and
white)
281
1328.33
$372,977
281
18708
$5,252,954
281
1119
$314,200
CCTVs (black and white)
281
2875
$807,261
Screen magnification software
281
814.5
$228,701
Total
$13,162,042
Total (inflated to 2007$)
$15,094,084
Using an active CNIB client base of 42,000 people this translates to $371.86 per person with VL.
Multiplying this by the number of people with VL gives us a total cost of aids and
modifications of $303.9 million. This cost has been allocated equally between
individuals, family and friends, government, employment and society / other (health
insurance entities).
4.5
SUMMARY OF OTHER FINANCIAL COSTS
In total, the non-health related financial costs of VL are estimated to be around
$7.1 billion in 2007.
TABLE 4–17: SUMMARY OF OTHER FINANCIAL COSTS OF VL, 2007
$ million
Productivity costs
Carer costs
Aids and modifications, funerals
DWL
Total other financial costs
86
4431
693
305
,1,757
7,186
5. BURDEN OF DISEASE
The main cost of VL is the loss of wellbeing and quality of life that it entails. Access Economics
adopts ‘burden of disease’ methodology in order to quantify this substantial cost component. This
methodology was developed by the World Health Organization, the World Bank and Harvard
University to comprehensively measure mortality and disability from diseases, injuries and risk
factors in 1990, projected to 2020 (Murray and Lopez, 1996). The approach is non-financial, where
pain, suffering and premature mortality are measured in terms of Disability Adjusted Life Years
(DALYs), with 0 representing a year of perfect health and 1 representing death (the converse of a
QALY or ‘quality-adjusted life year’ where 1 represents perfect health). The DALY approach has
been successful in avoiding the subjectivity of individual valuation and is capable of overcoming the
problem of comparability between individuals and between nations. This report treats the value of a
life year as equal throughout the lifespan.
5.1
WILLINGNESS TO PAY AND THE VALUE OF A LIFE YEAR
5.1.1
MEASURING BURDEN: DALYS, YLLS AND YLDS
In the last decade a non-financial approach to valuing human life has been derived, where loss of
wellbeing and premature mortality – called the ‘burden of disease and injury’ – are measured in
terms of Disability Adjusted Life Years, or DALYs. This approach was developed by the World
Health Organization (WHO), the World Bank and Harvard University for a study that provided a
comprehensive assessment of mortality and disability from diseases, injuries and risk factors in
1990, projected to 2020 (Murray and Lopez, 1996). Methods and data sources are detailed further in
Murray et al (2001) and the WHO continues to revisit the estimates for later years.
A DALY of 0 represents a year of perfect health, while a DALY of 1 represents death. Other health
states are attributed values between 0 and 1 as assessed by experts on the basis of literature and
other evidence of the quality of life in relative health states. For example, the disability weight of 0.18
for a broken wrist can be interpreted as losing 18% of a person’s quality of life relative to perfect
health, because of the inflicted injury. Total DALYs lost from a condition are the sum of the mortality
and morbidity components – the Year(s) of Life Lost due to premature death (YLLs) and the Year(s)
of healthy life Lost due to Disability (YLDs).
The DALY approach has been successful in avoiding the subjectivity of individual valuation and is
capable of overcoming the problem of comparability between individuals and between nations,
although some nations have subsequently adopted variations in weighting systems, for example
age-weighting for older people. This report treats the value of a life year as equal throughout the
lifespan.
As these approaches are not financial, they are not directly comparable with most other cost and
benefit measures. In public policy making, it is often desirable to apply a monetary conversion to
ascertain the cost of an injury, disease or fatality or the value of a preventive health intervention, for
example, in cost benefit analysis. Such financial conversions tend to utilise ‘willingness to pay’ or
risk-based labour market studies as described in the next section.
5.1.2
WILLINGNESS TO PAY AND THE VALUE OF A STATISTICAL LIFE YEAR
The burden of disease as measured in DALYs can be converted into a dollar figure using an
estimate of the Value of a ‘Statistical’ Life (VSL). As the name suggests, the VSL is an estimate of
the value society places on an anonymous life. Since Schelling’s (1968) discussion of the
87
economics of life saving, the economic literature has focused on willingness to pay (WTP) – or,
conversely, willingness to accept (WTA) – measures of mortality and morbidity, in order to develop
estimates of the VSL.
Estimates may be derived from observing people’s choices in situations where they rank or trade off
various states of wellbeing (loss or gain) either against each other or for dollar amounts eg, stated
choice models of people’s WTP for interventions that enhance health or WTA poorer health
outcomes or the risk of such states. Alternatively, risk studies use evidence of market trade-offs
between risk and money, including numerous labour market and other studies (such as installing
smoke detectors, wearing seatbelts or bike helmets and so on).
The extensive literature in this field mostly uses econometric analysis to value mortality risk and the
‘hedonic wage’ by estimating compensating differentials for on-the-job risk exposure in labour
markets; in other words, determining what dollar amount would be accepted by an individual to
induce him/her to increase the probability of death or morbidity by a particular percentage. Viscusi
and Aldy (2002), in a summary of mortality studies, find the VSL ranges between US$4 million and
US$9 million with a median of US$7 million (in year 2000 US dollars), similar but marginally higher
than the VSL derived from studies of US product and housing markets. They also review a parallel
literature on the implicit value of the risk of non-fatal injuries.
Weaknesses in the WTP approach, as with human capital approaches to valuing life and wellbeing,
are that there can be substantial variation between individuals. Extraneous influences in labour
markets such as imperfect information, income/wealth or power asymmetries can cause difficulty in
correctly perceiving the risk or in negotiating an acceptably higher wage in wage-risk trade off
studies, for example.
As DALYs are enumerated in years of life rather than in whole lives it is necessary to calculate the
Value of a ‘Statistical’ Life Year (VSLY) based on the VSL. This is done using the formula:34
VSLY = VSL / Σi=0,…,n-1(1+r)i
Where: n = years of remaining life, and
r = discount rate.
Clearly there is a need to know n (the years of remaining life), and to determine an appropriate value
for r (the discount rate). There is a substantial body of literature, which often provides conflicting
advice, on the appropriate mechanism by which costs should be discounted over time, properly
taking into account risks, inflation, positive time preference and expected productivity gains. In
reviewing the literature, Access Economics (2008) found the most common rate used to discount
healthy life was 3%, perhaps the most eminent sources being Nordhaus, 2002 (Yale); Murphy and
Topel, 2005 (University of Chicago); Cutler and Richardson, 1998 (Harvard); WHO, 2002; Aldy and
Viscusi, 2006). This report assumes a discount rate for future streams of health in Canada of 3%.
Further it is assumed that on average people have 40 years of life remaining.35
34
The formula is derived from the definition:
i
VSL = ΣVSLYi/(1+r)^ where i=0,1,2….n
where VSLY is assumed to be constant (i.e. no variation with age).
35
This assumption relates to the average years of life remaining for people included in VSL studies, not the years of life
remaining for people with VL.
88
Access Economics (2008a) identified 16 Canadian VSL studies (Table 5–1). Converting the study
findings into 2007 Canadian dollars, the average of VSL estimates was $4.66 million36. A discount
rate of 3% was applied to calculate the 2007 Canadian VSLY at $195,837.
TABLE 5–1: VALUE OF A STATISTICAL LIFE IN CANADIAN STUDIES ($ MILLION)
Authors
Year
Currency
Study Area
Belhadji
Meng and
Smith
Transport
Canada
Krupnick et
al.
1994
CAD
1990
USD
Transport
Occupational
Risk
1996
USD
Transport
2000
CAD
Viscusi
Alberini et
al.
Alberini et
al.
Meng and
Smith
Hara
Associates
Miller
Martinello
and Meng
Dionne and
Lanoie
2005
USD
2002
USD
2002
USD
1999
USD
Health
Occupational
Risk
Occupational
Risk
Occupational
Risk
Occupational
Risk
2000
2000
USD
USD
1992
USD
2002
CAD
Meng
Vodden et
al.
Cousineau
et al.
Bellavance
et al.
Average
1989
USD
1994
CAD
1991
USD
Mixed
Occupational
Risk
Occupational
Risk
Occupational
Risk
2007
USD
Mixed
Health
Mixed
Occupational
Risk
Lowest
estimate
Highest
estimate
0.4
3.2
Single/
average
estimate
VSL
in
2007
$CAN
1.2
1.6
1.2
2.1
1.8
2.7
2.5
2.9
3.9
4.7
2.4
3.0
0.5
0.9
2.4
3.3
1.3
3.7
2.4
3.3
2.4
3.4
2.4
2.5
3.5
3.6
3.1
5.1
4.7
5.3
4.0
7.6
6.1
7.9
4.8
8.0
9.2
11.2
4.7
1.7
2.1
5.2
BURDEN OF DISEASE FROM VISION LOSS
5.2.1
DISABILITY WEIGHTS
5.7
3.1
Disability weights for mild, moderate and severe VL are based on the Dutch weights from the global
burden of disease study (Murray and Lopez, 1996). These are:
36
Figures converted to $2007 Canadian using OECD Purchasing Power Parity rates. One additional study (Lanoie et al,
1995) was rejected as an outlier beyond reasonable parameters, given its VSL estimate was $37.5 million.
89

0.020 for mild VL;

0.170 for moderate impairment; and

0.430 for severe impairment (blindness).
Section 1.2 presents the distribution of severity for each of the major eye diseases. To derive a total
for Canada, these individual disease distributions were weighted by their overall prevalence. This
yields an average disability weighting for Canadian VL of 0.093.
The burden of disease is thus calculated on a prevalence basis from the prevalence estimates from
Section 2.4, together with disability weights, for the year 2007.
DEATHS FROM VL
5.2.2
The Australian Institute of Health and Welfare (Begg et al, 2007) estimates that in Australia in 2003,
the visually impaired population numbered 510,761, and that the number of deaths due to that VL
was 163. Given the number of visually impaired persons in Canada in 2007 is 817,171 on a pro-rata
basis, the expected number of deaths caused by VL was 261.
YEARS OF LIFE LOST DUE TO DISABILITY
5.2.3
Based on the disability weight outlined above and the total number of people experiencing VL, the
YLD for VL has been calculated by gender (Table 5–2), for the year 2007.
In total, YLD for VL was an estimated 75,891 DALYs in 2007.
TABLE 5–2: ESTIMATED YEARS OF HEALTHY LIFE LOST DUE TO DISABILITY (YLD), 2007 (DALYS)
Estimated disability weight
Prevalence
YLD
0.093
0.093
340,097
476,854
31,572
44,268
Males
Females
YEARS OF LIFE LOST DUE TO PREMATURE DEATH.
5.2.4
Based on the relative risk of mortality due to VL outlined above, it is estimated that there are around
261 deaths per year due to VL. YLL were estimated from the age-gender distribution of deaths by
the corresponding YLL for the age of death in the Standard Life Expectancy Table (West Level 26)
with a discount rate of 3% and no age weighting.
In total, YLL for VL was an estimated 1,467 DALYs in 2007.
TABLE 5–3: YEARS OF LIFE LOST DUE TO PREMATURE DEATH (YLL) DUE TO VL, 2007
15-29
Males
Females
Persons
90
30-39
0
0
0
40-49
0
0
0
50-59
4
2
6
22
15
37
60-69
58
38
96
70-79
181
153
334
80+
359
635
993
Total
623
844
1,467
5.3
TOTAL DALYS DUE TO VL
The overall loss of wellbeing due to VL is estimated as 77,306 DALYs.
Figure 5-1 illustrates the YLD and YLL components by age and gender. The greatest impact of VL
is in old age, reflecting the physiology of VL and higher YLD due to the large number of Canadians
with VL in this cohort.
FIGURE 5-1: LOSS OF WELLBEING DUE TO VL (DALYS), BY AGE AND GENDER, 2007
16,000
Female YLL
14,000
Male YLL
Female YLD
12,000
Male YLD
DALYs
10,000
8,000
6,000
4,000
2,000
90+
85-89
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
0
Age Groups
Multiplying the number of DALYs by the VSLY ($195,837) provides an estimate of the dollar value of
the loss of wellbeing due to VL.
The estimated gross cost of lost wellbeing from VL is $15.2 billion in 2007.
Bearing in mind that the wage-risk studies underlying the calculation of the VSL take into account all
known personal impacts – suffering and premature death, lost wages/income, out-of-pocket
personal health costs and so on – the estimate of $15.2 billion should be treated as a ‘gross’ figure.
However, costs specific to VL that are unlikely to have entered into the thinking of people in the
source wage/risk studies should not be netted out (e.g. publicly financed health spending, care
provided voluntarily). The results after netting out are presented in Table 5–4.
91
TABLE 5–4: NET COST OF LOST WELLBEING, $MILLION, 2007
Gross cost of wellbeing
Less health costs borne out-of-pocket
Less individual production losses net of tax
Less other indirect costs borne out-of-pocket
Plus transfers to people with VL
Net cost of lost wellbeing
The estimated net cost of lost wellbeing from VL is $11.7 billion in 2007.
92
15,200
1,499
2,847
61
917
11,710
6. SUMMARY
In 2007, the financial cost of VL was $15.8 billion (Table 6–1). Of this:

$8.6 billion (54.6%) was direct health system expenditure;

$4.4 billion (28.0%) was productivity lost due to lower employment, absenteeism and
premature death of Canadians with VL;

$1.8 billion (11.1%) was the DWL from transfers including welfare payments and taxation
forgone;

$0.7 billion (4.4%) was the value of the care for people with VL; and

$305 million (1.9%) was other indirect costs such as aids and home modifications and the
bring-forward of funeral costs.
Additionally, the value of the lost wellbeing (disability and premature death) was a further
$11.7 billion.
TABLE 6–1: VL, TOTAL COSTS BY TYPE OF COST AND BEARER, 2007
Individuals
Family/
Friends
Federal
Government
Provincial
Governments
Society/
Other
Employers
Total
Total cost ($ million)
Burden of disease
Health system costs
Productivity costs
Carer costs
Deadweight losses
Transfers
burden of disease
11,710
1,499
2,847
0
61
0
-917
3,490
15,200
0
0
0
413
62
0
0
474
0
388
886
218
0
0
917
2,409
0
5,670
619
0
61
0
0
6,350
0
0
80
0
61
0
0
141
0
1,081
0
62
61
1,757
0
2,960
11,710.4
8,637.9
4,431.4
692.8
304.9
1,757.0
0
15,824
474
2,409
6,350
141
2,960
27,534
Cost per person with visual impairment ($)
14,334
0
0
0
0
0
14,334
Health system costs
1,835
0
475
6,941
0
1,323
10,573
Productivity costs
Carer costs
Deadweight losses
Transfers
burden of disease
3,485
0
74
0
-1,122
4,272
0
505
76
0
0
581
1,084
267
0
0
1,122
2,948
757
0
74
0
0
7,773
98
0
74
0
0
172
0
76
74
2,151
0
3,624
5,424
848
373
2,151
0
19,370
18,606
581
2,948
7,773
172
3,624
33,704
Burden of disease
In per capita terms, this amounts to a financial cost of $19,370 per person with VL per annum.
Including the value of lost wellbeing, the cost is $33,704 per person per annum.
The shares by each type of financial cost are illustrated in Figure 6-1, while the financial cost shares
by bearer are shown in Figure 6-2.
93
FIGURE 6-1: FINANCIAL COSTS OF VL, BY TYPE OF COST (% TOTAL)
DWL
11.1%
Indirect Costs
1.9%
Carer Costs
4.4%
Productivity Costs
28.0%
Health System Costs
54.6%
Individuals with VL bear 22.1% of the financial costs, and their families and friends bear a further
3.0%. Federal government bears 15.2% of the financial costs (mainly through taxation revenues
forgone and welfare payments). Provincial governments bear 40.1% of the costs, reflecting the
nature of Canada’s Federal system, while employers bear 0.9% and the rest of society bears the
remaining 18.7%.
If the burden of disease (lost wellbeing) is included, individuals bear 55.2% of the costs and
Provincial governments bear 23.1% while the Federal government bears a lesser 8.7%, with family
and friends 1.7%, employers 0.5% and others in society 10.8%.
FIGURE 6-2: FINANCIAL COSTS OF VL, BY BEARER (% TOTAL)
Society/Other
18.7%
Individuals
22.1%
Employers
0.9%
Family/Friends
3.0%
Federal Government
15.2%
Provincial Governments
40.1%
94
As well as cost information, an important finding from this analysis was the observation that, for an
advanced Western nation, Canada has a serious deficiency in eye health data. CNIB’s Health
Economic Statement (http://www.costofblindness.org/media/health-state.asp) observes that,
with respect to blindness and vision loss, there is ‘strong argument for saying that Canada has the
worst record of supporting research of all the G8 countries’. The importance of good eye health to
Canadians is shown from survey data in the same document revealing that two-thirds of Canadians
would cash in all their savings or sell everything they owned to save their eyesight. With a rapidly
aging population, it is high time for a Canadian population eye health study to monitor incidence,
prevalence and morbidity outcomes and economic impacts more robustly in the future.
95
APPENDIX A: EDPRG PREVALENCE TABLES
Recognizing the need for national estimates of VL, Prevent Blindness America and the National Eye
Institute invited the principal investigators of several population-based vision studies to a meeting in
Fort Lauderdale, Florida, in May 2001, to standardize disease definitions and methods of data
reporting so that available data from many of these studies might be analysed together.
Prevalence of eye disease and associated blindness and low vision were calculated based on
studies from the US, Western Europe, the West Indies and Australia. The number of individuals
with each disease and the total number in the respective populations were provided in five year age
increments by age, gender and ethnicity for the adult population from each of the studies.
Prevalence rates were then combined using a meta-analysis technique for reducing the overall
variance of the pooled rate.
TABLE A-1: SOURCE STUDIES FOR EDRPG DATA
Study and location
Baltimore Eye Survey, US
Barbados Eye Studies, West Indies
Beaver Dam Eye Study, US
BMES, Australia
MVIP, Australia
Proyecto Vision Evaluation Research, US
Rotterdam Eye Study, The Netherlands
Salisbury Eye Evaluation Project, US
B/VL
RE
BW
BW
W
W
W
H
W
BW
W
H
W
AMD Cataract DR Glaucoma
BW
B
W
W
W
B
W
W
W
BW
W
BW
BW
B
W
W
W
H
W
W
W
H
W
Note: B = Black, H = Hispanic, W = White, B/VL = Blindness / VL
TABLE A-2: PREVALENCE OF AMD BY AGE, GENDER AND WHITE/BLACK (% POPULATION)
Age
White Female
White Male
Black Female
Black Male
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85+
0.2
0.2
0.4
0.7
1.5
3.2
6.8
13.6
0.3
0.4
0.6
1.1
2.1
3.9
6.9
12.0
0.9
1.1
1.4
1.7
2.1
2.5
2.9
3.3
0.2
0.4
0.6
0.9
1.5
2.4
3.8
5.9
96
TABLE A-3: PREVALENCE OF CATARACT BY AGE, GENDER AND WHITE/BLACK (% POPULATION)
Age
White Female
White Male
Black Female
Black Male
40-49
50-54
55-59
60-64
65-69
70-74
75-79
80+
1.8
5.0
9.4
16.8
27.5
40.8
54.5
72.9
2.8
4.9
8.2
13.8
22.4
34.0
47.2
67.2
2.2
7.3
12.8
20.0
28.5
37.4
46.1
58.2
1.7
4.5
7.6
11.9
17.5
24.1
31.3
43.3
TABLEA-4: PREVALENCE OF DR BY AGE, GENDER AND WHITE/BLACK (% POPULATION)
Age
White Female
White Male
Black Female
Black Male
18-39
40-49
50-64
65-74
75+
1.1
1.9
3.3
5.3
5.2
0.7
1.5
4.2
7.6
5.3
0.8
1.9
6.3
6.8
5.8
0.6
1.9
4.3
4.2
4.9
TABLE A-5: PREVALENCE OF GLAUCOMA BY AGE, GENDER AND WHITE/BLACK (% POPULATION)
Age
White Female
White Male
Black Female
Black Male
40-49
50-54
55-59
60-64
65-69
70-74
75-79
80+
0.8
0.9
1.0
1.2
1.6
2.2
3.3
6.9
0.4
0.6
0.8
1.2
1.7
2.3
3.2
5.5
2.3
3.0
3.5
4.1
4.8
5.6
6.5
8.3
1.5
2.2
2.9
3.7
4.8
6.2
7.9
11.6
97
TABLE A-6: PREVALENCE OF MYOPIA BY AGE, GENDER AND WHITE/BLACK (% POPULATION)
Age
White Female
White Male
Black Female
Black Male
40-49
50-54
55-59
60-64
65-69
70-74
75-79
80+
46.4
30.3
23.7
19.4
16.8
15.5
15.2
16.8
37.0
26.2
22.0
19.4
17.9
17.5
18.0
21.1
18.4
13.2
11.4
10.3
9.8
9.9
10.4
12.7
22.5
16.3
13.1
10.4
8.1
6.3
4.9
3.1
TABLE A-7: PREVALENCE OF HYPEROPIA BY AGE, GENDER AND WHITE/BLACK (% POPULATION)
Age
White Female
White Male
Black Female
Black Male
40-49
50-54
55-59
60-64
65-69
70-74
75-79
80+
3.7
7.4
10.5
14.1
17.9
21.6
24.7
28.0
3.6
6.4
8.7
11.4
14.2
17.1
19.9
23.5
3.1
5.4
7.1
8.9
10.6
12.0
13.1
13.6
2.2
3.3
3.8
3.9
3.8
3.3
2.6
1.5
TABLE A-8: PREVALENCE OF ALL VL BY AGE, GENDER AND WHITE/BLACK (% POPULATION)
Age
40- 49
50-54
55-59
60-64
65-69
70-74
75-79
80 +
98
White Female
White Male
Black Female
Black Male
0.3
0.4
0.5
0.7
1.2
2.3
4.8
24.1
0.3
0.3
0.4
0.6
1.0
1.9
4.0
20.2
0.1
0.4
0.7
1.3
2.4
4.2
7.0
15.1
0.3
0.7
1.2
2.2
3.8
6.4
10.4
23.7
TABLE A-9: PREVALENCE OF MILD VL BY AGE, GENDER AND WHITE/BLACK (% POPULATION)
Age
White Female
White Male
Black
40-49
50-54
55-59
60-64
65-69
70-74
75-79
80 +
0.2
0.2
0.3
0.4
0.7
1.3
2.8
12.3
0.1
0.2
0.2
0.3
0.6
1.0
2.2
9.5
0.0
0.1
0.3
0.6
1.2
2.3
3.8
7.7
TABLE A-10: PREVALENCE OF MODERATE VL BY AGE, GENDER AND WHITE/BLACK (% POPULATION)
Age
White Female
White Male
Black
40-49
50-54
55-59
60-64
65-69
70-74
75-79
80 +
0.1
0.1
0.1
0.2
0.3
0.5
1.1
4.9
0.1
0.1
0.1
0.1
0.2
0.4
0.9
3.8
0.0
0.1
0.1
0.3
0.5
0.9
1.5
3.1
TABLE A-11: PREVALENCE OF BLINDNESS BY AGE, GENDER AND WHITE/BLACK (% POPULATION)
Age
White Female
White Male
Black Female
Black Male
40-49
50-54
55-59
60-64
65-69
70-74
75-79
80 +
0.1
0.1
0.1
0.2
0.2
0.4
0.9
6.8
0.1
0.1
0.1
0.2
0.2
0.4
0.9
6.8
0.1
0.2
0.3
0.4
0.7
1.1
1.7
4.2
0.3
0.5
0.8
1.3
2.0
3.2
5.1
12.8
99
APPENDIX B: PREVALENCE PROJECTIONS BY AGE, GENDER
AND DISEASE
TABLE B-1: ALL VL BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total males
% of males
% of total prevalence
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total females
% of females
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total persons
% of total population
100
2007
2010
2015
2020
2025
2032
0
0
0
0
0
0
0
0
0
86
24
24
87
9,577
5,028
16,924
28,842
22,096
36,555
38,920
59,237
60,526
42,877
19,296
340,097
2.1%
41.6%
0
0
0
0
49
347
345
205
9,469
5,166
17,390
29,942
23,148
37,979
44,041
75,270
94,066
85,336
54,101
476,854
2.9%
58.4%
0
0
0
93
26
26
94
8,465
5,090
18,076
30,861
25,511
41,772
40,874
60,658
65,860
49,695
22,356
369,458
2.2%
42.0%
0
0
0
0
53
381
377
223
8,388
5,202
18,376
32,271
26,902
43,143
46,199
75,476
96,399
95,603
60,609
509,602
3.0%
58.0%
0
0
0
108
31
30
108
8,009
4,278
18,808
35,009
28,515
54,331
50,178
64,591
72,030
61,082
27,469
424,576
2.5%
42.8%
0
0
0
0
61
442
435
256
7,904
4,429
18,850
36,151
30,400
56,520
56,063
79,852
99,527
108,488
68,785
568,162
3.2%
57.2%
0
0
0
124
35
35
125
8,056
4,076
15,672
36,928
32,472
61,212
65,545
80,323
78,328
70,652
31,774
485,355
2.7%
43.3%
0
0
0
0
70
512
502
295
7,997
4,239
15,750
37,614
34,116
64,140
73,219
97,566
106,756
117,435
74,469
634,679
3.5%
56.7%
0
0
0
143
41
40
144
8,194
4,128
14,856
32,110
34,337
70,126
74,498
106,150
98,929
80,104
36,029
559,828
3.0%
43.7%
0
0
0
0
81
589
579
340
8,149
4,343
14,869
32,816
35,531
72,227
83,586
128,058
131,653
128,081
81,229
722,129
3.8%
56.3%
0
0
0
172
49
48
174
7,903
4,200
15,155
31,493
29,488
71,676
89,502
130,352
140,017
113,655
51,054
684,941
3.6%
43.7%
0
0
0
0
98
712
701
413
7,902
4,471
15,320
32,127
30,500
71,940
97,684
156,188
183,910
170,860
108,336
881,162
4.5%
56.3%
0
0
0
0
135
371
369
292
19,046
10,193
0
0
0
0
147
407
403
318
16,853
10,292
0
0
0
0
169
473
465
364
15,912
8,707
0
0
0
0
195
547
537
420
16,053
8,315
0
0
0
0
224
630
619
484
16,342
8,470
0
0
0
0
270
762
749
587
15,806
8,672
34,315
58,784
45,245
74,534
82,961
134,507
154,591
128,212
73,397
816,951
2.49%
36,452
63,132
52,413
84,915
87,073
136,134
162,258
145,298
82,965
879,059
2.63%
37,658
71,159
58,915
110,851
106,241
144,443
171,557
169,570
96,254
992,738
2.86%
31,421
74,541
66,587
125,352
138,764
177,889
185,084
188,087
106,243
1,120,033
3.10%
29,725
64,925
69,868
142,353
158,084
234,208
230,582
208,185
117,258
1,281,957
3.43%
30,475
63,620
59,987
143,616
187,186
286,541
323,928
284,515
159,390
1,566,103
4.01%
TABLE B-2: VL FROM AMD BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)
2007
2010
2015
2020
2025
2032
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total males
% of males
0
0
0
0
0
0
0
0
0
0
0
0
0
519
1,232
6,787
6,161
10,577
6,210
31,486
0.2%
35.4%
0
0
0
0
0
0
0
0
0
0
0
0
0
591
1,304
6,973
6,712
12,251
7,195
35,027
0.2%
35.9%
0
0
0
0
0
0
0
0
0
0
0
0
0
762
1,591
7,462
7,377
15,051
8,841
41,084
0.2%
37.1%
0
0
0
0
0
0
0
0
0
0
0
0
0
861
2,044
9,249
8,061
17,411
10,226
47,853
0.3%
38.4%
0
0
0
0
0
0
0
0
0
0
0
0
0
987
2,327
12,148
10,115
19,743
11,596
56,917
0.3%
39.3%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,027
2,799
14,909
14,179
27,961
16,435
77,309
0.4%
40.1%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total females
% of females
0
0
0
0
0
0
0
0
0
0
0
0
0
589
1,427
8,402
9,190
20,702
17,227
57,536
0.3%
64.6%
0
0
0
0
0
0
0
0
0
0
0
0
0
666
1,511
8,441
9,436
23,193
19,300
62,546
0.4%
64.1%
0
0
0
0
0
0
0
0
0
0
0
0
0
857
1,826
8,951
9,777
26,315
21,889
69,615
0.4%
62.9%
0
0
0
0
0
0
0
0
0
0
0
0
0
977
2,341
10,926
10,513
28,477
23,675
76,908
0.4%
61.6%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,104
2,675
14,304
12,938
31,053
25,806
87,880
0.5%
60.7%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,140
3,144
17,443
18,004
41,440
34,465
115,636
0.6%
59.9%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total persons
0
0
0
0
0
0
0
0
0
0
0
0
0
1,108
2,659
15,189
15,351
31,279
23,437
89,022
0.27%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,257
2,815
15,414
16,148
35,445
26,495
97,573
0.29%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,619
3,416
16,413
17,155
41,366
30,730
110,700
0.32%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,839
4,385
20,175
18,574
45,888
33,901
124,761
0.35%
0
0
0
0
0
0
0
0
0
0
0
0
0
2,092
5,003
26,452
23,053
50,796
37,402
144,797
0.39%
0
0
0
0
0
0
0
0
0
0
0
0
0
2,167
5,943
32,351
32,183
69,402
50,900
192,945
0.49%
101
TABLE B-3: VL FROM CATARACT BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)
2007
2010
2015
2020
2025
2032
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total males
% of males
0
0
0
0
0
0
0
0
0
0
0
980
141
1,102
4,434
9,319
14,164
10,462
7,344
47,945
0.3%
35.8%
0
0
0
0
0
0
0
0
0
0
0
1,055
160
1,254
4,711
9,564
15,420
12,121
8,505
52,789
0.3%
36.3%
0
0
0
0
0
0
0
0
0
0
0
1,205
183
1,608
5,727
10,217
16,903
14,893
10,446
61,183
0.4%
37.3%
0
0
0
0
0
0
0
0
0
0
0
1,295
210
1,821
7,298
12,678
18,421
17,227
12,084
71,034
0.4%
38.3%
0
0
0
0
0
0
0
0
0
0
0
1,196
230
2,087
8,316
16,687
23,197
19,534
13,704
84,952
0.5%
39.1%
0
0
0
0
0
0
0
0
0
0
0
1,237
234
2,190
10,005
20,483
32,688
27,680
19,393
113,910
0.6%
39.8%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total females
% of females
0
0
0
0
0
0
0
0
0
0
0
967
138
1,371
5,892
12,651
22,914
21,170
20,788
85,891
0.5%
64.2%
0
0
0
0
0
0
0
0
0
0
0
1,046
158
1,547
6,301
12,810
23,614
23,716
23,288
92,480
0.5%
63.7%
0
0
0
0
0
0
0
0
0
0
0
1,180
182
1,969
7,581
13,715
24,641
26,949
26,457
102,673
0.6%
62.7%
0
0
0
0
0
0
0
0
0
0
0
1,247
207
2,251
9,534
16,672
26,616
29,233
28,689
114,448
0.6%
61.7%
0
0
0
0
0
0
0
0
0
0
0
1,139
225
2,550
10,912
21,597
32,627
31,930
31,328
132,307
0.7%
60.9%
0
0
0
0
0
0
0
0
0
0
0
1,163
226
2,692
12,897
26,318
45,067
42,468
41,688
172,519
0.9%
60.2%
0
0
0
0
0
0
0
0
0
0
0
1,947
279
2,473
10,325
21,970
37,077
31,632
28,133
133,836
0.41%
0
0
0
0
0
0
0
0
0
0
0
2,101
318
2,800
11,012
22,374
39,034
35,836
31,793
145,268
0.44%
0
0
0
0
0
0
0
0
0
0
0
2,385
365
3,577
13,308
23,932
41,544
41,841
36,903
163,856
0.47%
0
0
0
0
0
0
0
0
0
0
0
2,542
417
4,071
16,831
29,351
45,037
46,459
40,773
185,482
0.51%
0
0
0
0
0
0
0
0
0
0
0
2,335
455
4,637
19,228
38,284
55,824
51,464
45,032
217,259
0.58%
0
0
0
0
0
0
0
0
0
0
0
2,400
460
4,882
22,902
46,801
77,754
70,148
61,081
286,428
0.73%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total persons
102
TABLE B-4: VL FROM DR BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)
2007
2010
2015
2020
2025
2032
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total males
% of males
0
0
0
0
86
24
24
87
87
55
933
1,740
1,717
1,472
869
2,125
2,138
886
318
12,560
0.1%
42.0%
0
0
0
0
93
26
26
94
94
60
998
1,883
1,957
1,665
933
2,212
2,330
1,023
367
13,763
0.1%
42.3%
0
0
0
0
108
31
30
108
108
69
1,045
2,164
2,225
2,096
1,124
2,411
2,566
1,254
449
15,786
0.1%
42.8%
0
0
0
0
124
35
35
125
124
79
889
2,362
2,551
2,389
1,397
2,953
2,807
1,451
519
17,840
0.1%
43.0%
0
0
0
0
143
41
40
144
143
91
856
2,292
2,772
2,740
1,596
3,789
3,516
1,647
590
20,400
0.1%
43.1%
0
0
0
0
172
49
48
174
173
110
888
2,467
2,706
2,977
1,923
4,639
4,913
2,310
822
24,373
0.1%
43.1%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total females
% of females
0
0
0
0
49
347
345
205
206
232
1,112
1,997
1,971
1,544
937
2,643
3,237
1,706
829
17,360
0.1%
58.0%
0
0
0
0
53
381
377
223
223
252
1,184
2,177
2,255
1,738
1,006
2,704
3,334
1,911
929
18,746
0.1%
57.7%
0
0
0
0
61
442
435
256
254
289
1,245
2,493
2,595
2,196
1,208
2,931
3,474
2,174
1,057
21,112
0.1%
57.2%
0
0
0
0
70
512
502
295
293
333
1,123
2,719
2,954
2,515
1,507
3,545
3,749
2,363
1,149
23,630
0.1%
57.0%
0
0
0
0
81
589
579
340
338
384
1,122
2,697
3,198
2,854
1,726
4,529
4,599
2,585
1,257
26,877
0.1%
56.9%
0
0
0
0
98
712
701
413
410
465
1,217
2,946
3,197
3,057
2,045
5,514
6,362
3,428
1,667
32,230
0.2%
56.9%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total persons
0
0
0
0
135
371
369
292
293
287
2,045
3,737
3,688
3,015
1,805
4,769
5,376
2,591
1,147
29,920
0.09%
0
0
0
0
147
407
403
318
317
312
2,182
4,060
4,212
3,403
1,940
4,917
5,664
2,934
1,296
32,509
0.10%
0
0
0
0
169
473
465
364
362
358
2,290
4,658
4,820
4,292
2,333
5,342
6,039
3,428
1,506
36,897
0.11%
0
0
0
0
195
547
537
420
417
413
2,012
5,081
5,505
4,904
2,904
6,497
6,556
3,814
1,669
41,471
0.11%
0
0
0
0
224
630
619
484
481
475
1,978
4,989
5,970
5,594
3,322
8,318
8,115
4,231
1,847
47,277
0.13%
0
0
0
0
270
762
749
587
584
575
2,104
5,413
5,903
6,034
3,968
10,153
11,275
5,738
2,489
56,603
0.15%
103
TABLE B-5: VL FROM GLAUCOMA BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)
104
2007
2010
2015
2020
2025
2032
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total males
% of males
0
0
0
0
0
0
0
0
0
0
0
0
0
1,288
1,410
1,364
3,928
1,611
605
10,206
0.1%
40.9%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,460
1,506
1,402
4,276
1,865
701
11,211
0.1%
41.7%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,855
1,824
1,502
4,689
2,291
860
13,020
0.1%
42.9%
0
0
0
0
0
0
0
0
0
0
0
0
0
2,107
2,297
1,860
5,112
2,650
995
15,021
0.1%
43.7%
0
0
0
0
0
0
0
0
0
0
0
0
0
2,417
2,621
2,441
6,435
3,005
1,129
18,047
0.1%
44.2%
0
0
0
0
0
0
0
0
0
0
0
0
0
2,584
3,155
2,996
9,062
4,251
1,593
23,641
0.1%
44.5%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total females
% of females
0
0
0
0
0
0
0
0
0
0
0
0
0
1,099
1,194
1,853
5,828
3,119
1,639
14,731
0.1%
59.1%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,245
1,260
1,880
5,965
3,495
1,836
15,680
0.1%
58.3%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,614
1,525
2,018
6,145
3,965
2,083
17,349
0.1%
57.1%
0
0
0
0
0
0
0
0
0
0
0
0
0
1,836
1,971
2,450
6,581
4,290
2,253
19,381
0.1%
56.3%
0
0
0
0
0
0
0
0
0
0
0
0
0
2,072
2,251
3,165
8,126
4,677
2,457
22,749
0.1%
55.8%
0
0
0
0
0
0
0
0
0
0
0
0
0
2,109
2,639
3,857
11,379
6,243
3,280
29,507
0.1%
55.5%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total persons
0
0
0
0
0
0
0
0
0
0
0
0
0
2,386
2,605
3,217
9,755
4,730
2,244
24,937
0.08%
0
0
0
0
0
0
0
0
0
0
0
0
0
2,705
2,766
3,282
10,241
5,360
2,537
26,891
0.08%
0
0
0
0
0
0
0
0
0
0
0
0
0
3,469
3,348
3,520
10,834
6,255
2,943
30,368
0.09%
0
0
0
0
0
0
0
0
0
0
0
0
0
3,944
4,268
4,311
11,693
6,940
3,248
34,403
0.10%
0
0
0
0
0
0
0
0
0
0
0
0
0
4,489
4,872
5,607
14,561
7,683
3,585
40,797
0.11%
0
0
0
0
0
0
0
0
0
0
0
0
0
4,692
5,794
6,852
20,441
10,494
4,873
53,147
0.14%
TABLE B6: VL FROM RE BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)
2007
2010
2015
2020
2025
2032
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total males
% of males
0
0
0
0
0
0
0
0
9,490
4,973
15,991
26,122
20,239
32,174
30,975
39,642
34,134
19,342
4,819
237,900
1.5%
44.1%
0
0
0
0
0
0
0
0
8,371
5,030
17,078
27,923
23,395
36,802
32,419
40,506
37,121
22,435
5,589
256,668
1.6%
44.5%
0
0
0
0
0
0
0
0
7,901
4,209
17,763
31,639
26,108
48,010
39,912
42,999
40,495
27,594
6,873
293,503
1.7%
45.1%
0
0
0
0
0
0
0
0
7,932
3,997
14,783
33,271
29,711
54,033
52,508
53,583
43,927
31,913
7,949
333,606
1.9%
45.5%
0
0
0
0
0
0
0
0
8,051
4,037
14,000
28,622
31,334
61,895
59,638
71,084
55,665
36,174
9,011
379,511
2.1%
45.6%
0
0
0
0
0
0
0
0
7,730
4,090
14,268
27,788
26,547
62,898
71,620
87,326
79,176
51,454
12,812
445,709
2.3%
45.6%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total females
% of females
0
0
0
0
0
0
0
0
9,264
4,934
16,278
26,978
21,039
33,378
34,592
49,720
52,897
38,638
13,617
301,336
1.8%
55.9%
0
0
0
0
0
0
0
0
8,165
4,950
17,193
29,048
24,489
37,948
36,121
49,641
54,050
43,288
15,256
320,149
1.9%
55.5%
0
0
0
0
0
0
0
0
7,649
4,140
17,605
32,477
27,623
49,883
43,923
52,237
55,491
49,086
17,299
357,414
2.0%
54.9%
0
0
0
0
0
0
0
0
7,704
3,905
14,626
33,647
30,954
56,561
57,867
63,972
59,297
53,073
18,703
400,310
2.2%
54.5%
0
0
0
0
0
0
0
0
7,811
3,959
13,748
28,979
32,108
63,647
66,021
84,462
73,363
57,836
20,381
452,316
2.4%
54.4%
0
0
0
0
0
0
0
0
7,492
4,007
14,103
28,018
27,077
62,943
76,960
103,057
103,099
77,281
27,235
531,271
2.7%
54.4%
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90+
Total persons
0
0
0
0
0
0
0
0
18,753
9,907
32,269
53,100
41,278
65,552
65,567
89,362
87,032
57,980
18,436
539,236
1.64%
0
0
0
0
0
0
0
0
16,536
9,980
34,270
56,971
47,884
74,750
68,540
90,147
91,171
65,724
20,845
576,817
1.73%
0
0
0
0
0
0
0
0
15,551
8,349
35,368
64,116
53,731
97,893
83,835
95,236
95,986
76,680
24,172
650,917
1.87%
0
0
0
0
0
0
0
0
15,636
7,902
29,409
66,918
60,665
110,594
110,376
117,555
103,224
84,986
26,652
733,916
2.03%
0
0
0
0
0
0
0
0
15,862
7,996
27,748
57,601
63,443
125,542
125,659
155,547
129,029
94,010
29,391
831,827
2.23%
0
0
0
0
0
0
0
0
15,222
8,097
28,371
55,806
53,624
125,841
148,580
190,383
182,275
128,734
40,047
976,979
2.50%
105
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The cost of vision loss in Canada CNIB and the Canadian

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