Beelden van eigen gezondheid bij jongeren 12

Transcription

Overweight and obesity
in Dutch adolescents
Associations with health lifestyle, personality, social context and
future consequences: methods & tables
N.J.A. van Exel
X. Koolman
G. de Graaf
W.B.F. Brouwer
Correspondence:
Erasmus MC
institute for Medical Technology Assessment (iMTA)
PO Box 1738
3000 DR Rotterdam
T 010 408 25 07
F 010 408 90 94
E [email protected]
institute for Medical Technology Assessment 2005
Report number 06.82
Copyright. All rights reserved. Save exceptions stated by the law, no part of this publication may be reproduced in
any form without the prior written permission of iMTA.
ABSTRACT
This report is part of a study that investigated adolescents’ health behaviour in relation to
attitudes about their health lifestyle and their consideration of the future consequences of
their behaviour. The study focussed on young adolescents in the age of 12 to 14 years,
attending 1st or 2nd grade of secondary education.
This report is meant to serve as a reference book for future output from the project by
providing a description of the measures selected for inclusion in the “Health & Future”
questionnaire, the study sample, the results of intermediate analyses of multiple-item scales
as well as a full overview of the data collected, in relation to the main outcome variable
“overweight”.
ACKNOWLEDGEMENT
We wish to acknowledge ZonMW (www.zonmw.nl) for funding the project (2100.0100), the
members of the advisory board (Annex A) for their constructive contributions, and the
schools and their pupils (Annex C) for their enthusiastic participation.
AFFILIATIONS
Job van Exel:
Erasmus MC, institute for Medical Technology Assessment (iMTA)
and Department of Health Policy & Management (iBMG).
Xander Koolman:
Erasmus MC, Department of Health Policy & Management (iBMG).
Gjalt de Graaf:
Vrije Universiteit Amsterdam, Faculty of Social Sciences, Department
of Public Administration & Organisation Science.
Werner Brouwer:
Erasmus MC, institute for Medical Technology Assessment (iMTA)
and Department of Health Policy & Management (iBMG).
Contents
1
2
Introduction
5
1.1
5
1.2
About the study
6
1.3
About this report
7
Methods
9
2.1
About the “Health & Future” questionnaire
9
2.1.1
Aim of the questionnaire
9
2.1.2
Selection of topics
9
2.1.3
Recruitment of schools and pupils
10
2.1.4
Administration of the questionnaire
12
2.2
3
Contents of the “Health & Future” questionnaire
12
2.2.1
About you (questions 1 to 8)
12
2.2.2
About your health (questions 9 to 14)
15
2.2.3
About your future (questions 15 to 22)
17
2.2.4
About home (questions 23 to 34)
19
2.2.5
About school (questions 35 to 43)
20
2.2.6
About your leisure time (questions 44 to 52)
20
2.2.7
About what you eat (questions 53 to 55)
21
2.2.8
About money (questions 56 to 63)
23
Results
25
3.1
Study population
25
3.1.1
Participating schools and number of respondents
25
3.1.2
Representativeness of the sample
26
3.2
Length, weight, BMI and prevalence of overweight and obesity
27
3.3
Variables
31
3.3.1
About you
31
3.3.2
About your health
32
3.3.3
About your future
33
3.3.4
About home
34
3.3.5
About school
36
3.3.6
About your leisure time
37
3.3.7
About what you eat
38
3.3.8
About money
40
References
43
Annex A
Members advisory board
53
Annex B
Validity and reliability of self-reported height and weight
55
Annex C
Literature review
57
About you
57
About your health
58
About your future
61
About home
63
About school
65
67
About what you eat
68
About money
70
Annex D
International and national survey questionnaires reviewed
71
Annex E
Questionnaire “Health & Future” [in Dutch]
73
Annex F
Attitudes of youths about their health lifestyle (format A)
91
Annex G
Attitudes of youths about their health lifestyle (format B)
93
List of tables
Table 1
Big-Five personality dimensions and markers for 30-item short version ...............14
Table 2
Confirmatory factor analysis Big-Five personality dimensions ..............................16
Table 3
International Body Mass Index (BMI) cut-off points for overweight and obesity in
adolescents; by gender and age ...........................................................................17
Table 4
Food Availability at Home Index (FAHI) scoring system........................................19
Table 5
Physical Activity Index (PAI) scoring system .........................................................20
Table 6
Healthy Eating Index (HEI) scoring system ...........................................................22
Table 7
Unhealthy Eating Index (UEI) scoring system .......................................................22
Table 8
Number of respondents per school (n=2,006) .......................................................26
Table 9
Reference population according to gender, age, education level, and ethnicity....27
Table 10 Length, weight and BMI .........................................................................................27
Table 11 Length, weight and BMI according to body image.................................................30
Table 12 Personal characteristics, BMI, overweight and obesity .........................................31
Table 13 Health, BMI, overweight and obesity .....................................................................32
Table 14 Future, BMI, overweight and obesity .....................................................................33
Table 15 Home environment, BMI, overweight and obesity .................................................34
Table 16 School environment, BMI, overweight and obesity................................................36
Table 17 Leisure time, BMI, overweight and obesity ............................................................37
Table 18 Eating behaviour, BMI, overweight and obesity.....................................................38
Table 19 Money, BMI, overweight and obesity.....................................................................40
List of figures
Figure 1 Schematic overview of the Dutch education system .............................................10
Figure 2 Participating schools..............................................................................................25
Figure 3 Cumulative distribution of length, weight and BMI according to gender ................28
1
1.1
Introduction
Obesity1 is one of the main current public health concerns in Western countries (Daniels et
al. 2005; NHS HDA 2003; ILSI 2000; Seidell 1999), as it is associated with morbidity and
mortality at least as much as smoking, alcoholism and poverty (Manson & Bassuk 2003;
Sturm & Wells 2001). Recent studies have suggested that the prevalence of overweight and
obesity among adolescents varies between 10-25% and 2-12%, respectively, depending on
country, measure and definition (McCarthy et al. 2003). Overweight and obesity prevalence
rates show a persistent, upward trend (NHS HDA 2003; Spurgeon 2002; Yarnell et al. 2001;
Reilly et al. 1999). In addition, children and adolescents in the most overweight group are
becoming heavier (Troiano & Flegal 1998). Though most young adolescents seem to have a
basic perception of a healthy lifestyle (e.g., Watt & Sheiham 1999), they have relatively
unhealthy lifestyles as compared to other age groups. From a public health perspective, they
have therefore been categorised as a risk group (Daniels et al. 2005). The World Health
Organization labelled the rapid increase in obesity over the past two decades as a global
epidemic (WHO 1998), Swinburn and Egger (2004) described the trend as a “runaway
weight-gain train”.
Childhood obesity has been shown to have consequences for health and quality of life in
both the short and longer term. In the short term, childhood obesity is associated with
physical and psycho-social problems such as new-onset asthma, decreased health-related
quality of life, lower body- and self-esteem, behavioural problems, and social isolation. In the
longer term, childhood obesity is associated with an increased risk of adult obesity, with
increased morbidity and mortality in adult life, including cardiovascular diseases, type 2
diabetes and certain cancers, as well as with significant social and economic consequences
(see e.g., Flegal et al. 2005; Fonseca & Gaspar de Matos 2005; Wright et al. 2005; Janssen
et al. 2004; Friedlander et al. 2003; Gilliland et al. 2003; Strauss & Pollack 2003; Strauss
2001; Graham et al. 2000; ILSI 2000; Stradmeijer et al. 2000; Gunnell et al. 1998; Averett &
Korenman 1996; Mendelson et al. 1996; Gortmaker et al. 1993).
For a more comprehensive review see, for instance, Skidmore & Yarnell (2004), Zametking
et al. (2004), Reilly et al. (2003), Edmunds et al. (2001), NTFPTO (2000) and Dietz (1998).
1
Obesity is a condition in which weight gain, predominantly fat, has reached the point of endangering health
(NHS HDA 2003). For adults, obesity is defined as a Body Mass Index (BMI; weight in kilograms divided by height
in meters squared) of 30 kg/m2 or more (WHO 1998)). For children and adolescents, age- and gender-specific
cut-off points have been established (Cole et al. 2000).
5
The primary causes of overweightness and obesity at young ages include sociodemographic factors like family income, social class and parental obesity, and unhealthy
lifestyles, characterised by an imbalance between energy intake and expenditure (e.g., Bray
& Champagne 2005; Vereecken et al. 2005; Bosch et al. 2004; Swinburn et al. 2004; Storey
et al. 2003; Whitaker 2003; Wang 2001; ILSI 2000; McMurray et al. 2000; Rössner 1998).
Komlos & Baur (2004) moreover hypothesised there may be a relation between trends in
physical state, in terms of height and weight, and the biological standard of living, a person’s
socio-economic and epidemiological environment that includes social inequality, and the
quality of the health care system and social safety nets. Such assertions make clear that
countering the increase in obesity rates may be no means be simple. Indeed, Swinburn and
Egger (2004) argued that obesity seems to be perpetuated and accelerated in a series of
vicious positive feedback cycles, including movement inertia, and mechanical and
psychological dysfunction. Overall, they stated, there are too many accelerators and not
enough brakes. Still, although this study must mainly be viewed as a quest to gather
knowledge, this study was initiated in the hope that it may help to find new brakes or find
better ways to use the existing ones.
1.2
About the study
This study investigated adolescents’ health behaviour in relation to their attitudes about their
health lifestyle and their consideration of future consequences of their behaviour, focussing
on young adolescents in the age of 12 to 14 years, attending 1st or 2nd grade of secondary
education. The study consisted of two phases.
First, discourse analysis was conducted using Q-methodology to identify operant attitudes
among youths about their health lifestyle, with a focus on overweightness. Q-methodology is
a fairly novel method in health research in the Netherlands, but has been around for about 70
years and has been applied extensively in many fields including health research (Brown
1980; Stephenson 1935; Van Exel & De Graaf 2005; Cross 2005). In this Q-methodological
study, youths rank-ordered statements on issues like eating behaviour, overweightness,
health risks, health perceptions and motivations/obstacles for adopting a healthier lifestyle.
Q-factor analysis revealed five attitudes: “carefree sporty”, “worrying dependent”, “contended
independent”, “looks over matter”, and “indifferent solitary”. This Q-methodological study
showed that youths were more or less non-interested in their own health, however because
6
of different reasons. For most youths, neither current nor future health was of major concern,
because they felt physically fit, were generally satisfied and happy, or because they simply
did not care. Some were primarily involved with their eating behaviour, because of concerns
with the consequences on appearance or with being physically unfit or overweight. This
preoccupation with eating some times appeared far from healthy. Only one of the five health
lifestyle attitudes combined healthy eating and exercising behaviour. Most youths appeared
to have little knowledge and many questions regarding (their) health and overweightness.
This phase of the study was concluded, the results have been published in more detail
elsewhere (Van Exel et al. 2005, 2006; De Graaf et al. 2006).
Next, survey analysis was conducted to investigate associations of these five attitudes about
health lifestyle with health behaviour, in terms of eating and exercising behaviour, and
adolescents’ expectations and consideration of future consequences of their behaviour. Aim
of this analysis is to explore possible alternative, target-group specific strategies for
prevention of overweight and obesity among youths in the different discourses. This
document reports on the second phase of the study.
1.3
About this report
This report is meant to serve as a reference book for future output from the project (e.g.,
papers, presentations, et cetera) by providing:
a comprehensive but concise description of the “Health & Future” questionnaire,
a full overview of the data collected, in relation to the main outcome variable “overweight”,
the results of intermediate analyses of multiple-item scales.
Section two of this report accounts for the selection of measures, the data collection, and
includes the results of intermediate analyses of multiple-item scales that were used in this
study. Section three describes the study, discusses the representativeness of the sample,
and reports descriptive statistics for all variables included in the “Health & Future”
questionnaire, including bivariate correlarions with measures of the main outcome variable
“overweight”.
7
8
2
2.1
Methods
About the “Health & Future” questionnaire
2.1.1 Aim of the questionnaire
The aim of the “Health & Future” questionnaire was to collect a coherent set of data that
makes it possible to investigate associations of adolescents’ attitudes about health lifestyle
with their actual eating and exercising behaviour, and their expectations and consideration of
the future consequences of their behaviour.
2.1.2 Selection of topics
A three-step strategy was adopted for the selection of topics and measures to be included in
the “Health & Future” questionnaire. First, interviews were held with eight Dutch policy,
research and field experts in the fields of adolescents, behaviour, health and overweightness
or obesity, including members of the advisory board of this project (see Annex A). Next, a
literature review was conducted in search of personal and contextual / environmental
variables that may be associated with health lifestyle, health behaviour, overweight and
obesity in adolescents (see Annex C). Finally, key international and national survey
questionnaires (or study protocols) addressing the same target group and topics, identified
through the review and interviews, were examined (see Annex D).
Based on these resources, a long-list of topics was developed, and structured according to
eight themes:
1. About you
2. About your health
3. About your future
4. About home
5. About school
6. About your leisure time
7. About what you eat
8. About money.
Sets of questions were developed within each theme, as much as possible relying on
available formats and formulations from existing, validated questionnaires (see Annex D) and
former questionnaires developed by project team members (e.g., Brouwer & Van Exel 2005;
Van Exel et al. 2004; Van Exel & Brouwer 2003). The draft questionnaire was discussed with
9
the advisory board, in terms of the selection of topics and corresponding questions, the
appropriateness of the total set of questions for answering the research question, the
feasibility of the questionnaire for the target group, and the recruitment of schools and pupils
(see section 2.1.3). The revised final draft questionnaire was tested in a small convenience
sample of adolescents in the target audience, which lead to some minor changes in
language use. The final questionnaire is included in Annex E [in Dutch].
2.1.3 Recruitment of schools and pupils
The intended survey population was adolescents attending school at pre-vocational2 and
general secondary3 education levels (see Figure 1). Dutch adolescents enter secondary
school after eight years of primary education starting age 4. The different levels of secondary
education prepare adolescents for middle vocational education or higher vocational /
academic education (bachelor / master system). Some 817 thousand youths attended school
at secondary education level in curriculum year 2004/2005, of whom about 351 thousand 1st
and 2nd graders (CBS 2005).
Figure 1 Schematic overview of the Dutch education system
2
3
i.e., VMBO beroepsgericht, theoretisch of gemengd.
i.e., HAVO, VWO of Gymnasium.
10
In order to investigate adolescents’ health behaviour in relation to their attitudes about their
health lifestyle and their consideration of future consequences of their behaviour, taking into
consideration the main individual and contextual variables that are associated with
overweight and obesity, the primary aim in the data collection was to have a fair distribution
over smaller and larger schools in lower and higher urbanized areas throughout the country.
Schools were approached for participating in the study based on the city of location, the size
of the school and the education levels offered by the school. The aim was to recruit between
1,000 and 1,250 pupils (i.e., 50 classes of 20-25 pupils) from ten schools; 40 to 50 each (i.e.,
two classes) at three small schools, 80 to 100 each (i.e., four classes) at three middle sized
schools, and 160-200 each (i.e., ten classes) at four large schools. The following approach
was adopted:
1. 20 cities were selected, one larger and one smaller city in each of the ten provinces in
the Netherlands.
2. A list of schools offering secondary education was collected from the telephone
directory of each from city.
3. For each city two schools were randomly selected from this list, and information was
retrieved regarding the size of the school and education levels offered through the
internet or by telephone.
4. The list of schools was categorised according to the size of the school, based on
number of 1st grade classes; up to 3 was classified as a small school, between 4 and
7 as a middle sized school, and more than 7 as a large school.
5. Within each category, schools were pre-selected based on city of location and
education levels offered in order to ariive at a fair spread of schools across the
country and a fifty-fifty distribution of classes between pre-vocational and general
secondary education level.
6. The pre-selected schools were approached by telephone. If a school was not
interested, a matching school was selected and approached (from the list in point 5,
moving up with each refusal).
7. Schools that were interested in participating in the study were sent an information
package regarding the aim and the set-up of the study. An appointment was made for
call back.
8. With the schools that agreed to participate, agreements were made regarding the
number of questionnaires to send, a contact person for the study, and time and
procedure for administration of the questionnaires. Steps 6 and 7 were repeated until
ten schools agreed to participate.
11
To increase response, pupils were informed that there would be a raffle of prizes among
respondents returning a completed questionnaire: a first prize of €100 and five prizes of €20
among respondents from all schools, and a €10 prize among respondents from each class.
2.1.4 Administration of the questionnaire
The contact person at each school received a package for each class recruited, containing
30 questionnaires, a stamped envelope with mail back address, and instructions for the
teacher(s) administering the questionnaire. The contact person distributed the packages
among the selected teacher(s) and went through the instructions with them.
The instructions for the teachers, apart from a few practical details, emphasised three issues.
First, teachers were emphatically requested to ask pupils, on the day before administering
the questionnaire, to weigh and measure themselves at home the next morning, before
coming to school. Second, teaches were asked to organize the school desks like is usually
done for written exams, so that pupils would work individually and have sufficient privacy.
Third, teachers were asked to emphasise to their pupils, before distributing the
questionnaire, that anonymity was guaranteed and that neither the school nor the teacher
would have access to information contained in individual questionnaires. The sheet
containing personal information necessary for the raffle was attached as backpage to the
questionnaire. After completion, pupils separated this backpage from the main questionnaire,
and handed both in separately.
2.2
Contents of the “Health & Future” questionnaire
The “Health & Future” questionnaire (see Annex E) consisted of eight clearly demarcated
sections, corresponding to the themes identified in the selection of topics (see 2.1.2). Here,
we briefly introduce the questions that were included in each section, including an account of
the measures used, some data consideration issues, and results of intermediate analyses of
any multiple-item scales.
2.2.1 About you (questions 1 to 8)
This section of the questionnaire asked adolescents about personal characteristics: gender,
age, country of birth, education level, grade (1st or 2nd), attitude about health lifestyle,
happiness and personality.
12
Normal age in 1st and 2nd grade of secondary school is 12 to 14. In the questionnaire there
were five answer categories to age (question 2), ranging from 11 to 15. For ease of
presentation, in any tables where age is included as a categorical variable the ages of 11
and 12 will be aggregated under the label “12-”, and the ages of 14 and 15 will be
aggregated under the label “14+”. Actual ages will be used in all analyses.
Ethnicity was assessed using the common definition by the Dutch National Bureau of
Statistics (CBS): if both parents were born in the Netherlands, the adolescent is classified as
being autochthonous; if at least one of the parents was born outside the Netherlands, the
adolescent is classified as being allochthonous. Within the allochthonous population a further
distinction is made between those from western and non-western origin, the latter defined as
originating from Africa, Latin America, Asia (excl. Indonesia and Japan) or Turkey.
The survey population included adolescents attending two secondary education levels,
namely pre-vocational and general secondary education (see section 2.1.3). Unless stated
otherwise, education level is included as a categorical variable distinguishing between prevocational and general secondary education levels in all tables and analyses; sub-levels are
ignored.
Adolescents’ attitude about their health lifestyle (question 6) was assessed using the results
of a Q-methodological study, conducted in the first phase of this study (see section 1.2). The
five operant attitudes about health lifestyle among adolescents in 1st and 2nd grade of
secondary school were: “carefree sporty”, “worrying dependent”, “contended independent”,
“looks over matter”, and “indifferent solitary”. Attitude membership was assessed in two
ways. The large majority of questionnaires included the format presented in Annex F, which
asked adolescents to elicit which of the attitudes about health lifestyle fitted them best. A
small sample, half of the adolescents in one of the large schools, received a questionnaire
including the format presented in Annex G, which asked them to elicit to which extent each of
the attitudes about health lifestyle fitted them (five answer categories, ranging from “not at
all” to “very well”).
Happiness (question 7) was assessed using a visual analogue scale ranging from 0 “very
unhappy” to 10 “very happy”, on which respondents were asked to indicate how happy they
generally feel.
13
Personality (question 8) was assessed using a short version of the Dutch translation of
Goldberg’s adjective 100 list for the Big-Five personality dimensions (Goldberg 1992; Gerris
et al. 1998). The Big-Five dimensions, more easily remembered by the acronym OCEAN,
are: ‘openness to experience’ (O), ‘conscientiousness’ (C), ‘extraversion’ (E),
‘agreeableness’ (A), and ‘neuroticism’ (N). This 30-item short version was used before in
similar study populations (De Bruijn et al. 2005; Gerris et al. 1998; Scholte et al. 1997).
Furthermore, this 30-item short version is part of the Family Survey of the Dutch Population
(De Graaf, De Graaf, Kraaykamp & Ultee 2000) and has been used in publications using
data from this survey (e.g., Bekkers 2005; Bekkers & De Graaf 2002).
Respondents were presented 30 general human traits, six for each Big-Five personality
dimension (see Table 1), and asked to indicate to what extent these traits applied to
themselves (seven answer categories, ranging from “not at all” to “definitely”).
Table 1
Big-Five personality dimensions and markers for 30-item short version
Openness to experience
Conscientiousness
Extraversion
Agreeableness
Neuroticism
(O)
(C)
(E)
(A)
(N)
Artistic
Careful
Bashful *
Agreeable
Anxious
Complex
Neat
Introverted
Cooperative
Fearful
Creative
Organized
Quiet
Helpful
High-strung
Deep
Sloppy
Reserved
Kind
Irritable
Imaginative
Systematic
Talkative *
Pleasant
Nervous
Innovative
Thorough
Withdrawn
Sympathetic
Touchy
Source: Gerris et al. (1998). Note: * two markers were missing in questionnaire due to a print failure.
Because the validity of this set of markers for the Big-Five personality dimensions was
demonstrated before (De Bruijn et al. 2005; Bekkers 2005; Bekkers & De Graaf 2002; Gerris
et al. 1998; Scholte et al. 1997), we proceeded straightaway with confirmatory factor analysis
using a five-factor criterion.4 The final selection of markers used for attribution of youths to
personality dimensions was reached in four consecutive steps:
(1) Five factors were extracted from 28 markers (explained variance 48.7%;
communalities 0.265-0.683; Kaiser-Meyer-Olkin sampling adequacy 0.861). Three
markers showed factor-loadings >.30 on more than one factor and were excluded
from further analysis: fearful (N), systematic (C) and withdrawn (E).
4
Confirmatory factor analysis is used to confirm the findigns of earlier exploratory factor analysis, i.e., that scale
items (here: markers) load on to the anticipated factor (here: personality dimensions) and correlate weakly with
the other factors (Bowling 1997).
14
communalities 0.260-0.693; KMO sampling adequacy 0.837). Two markers showed
factor-loadings >.30 on more than one factor and were excluded from further analysis:
complex (O) and nervous (N).
communalities 0.255-0.697; KMO sampling adequacy 0.834). Two markers showed
factor-loadings >.30 on more than one factor and were excluded from further analysis:
careful (C) and high-strung (N).
communalities 0.258-0.720; KMO sampling adequacy 0.809; see Table 2). Scale
reliability ranged from .57 for neuroticism (N) to .80 for conscientiousness (C).
2.2.2 About your health (questions 9 to 14)
This section of the questionnaire addressed some key health and health perception
variables: health status, chronic health conditions, length, weight, body image, and smoking
behaviour.
Health status (question 9) was assessed using a visual analogue scale ranging from 0 “worst
conceivable health condition” to 10 “best conceivable health condition”, on which
respondents were asked to indicate how healthy they generally feel.
The questionnaire included self-report measures of length and weight (questions 10 and 11).
The reliability of self-reported values of length and weight is often contested, especially in
this age group (see Annex B for a discussion). Generally, self-reported values lead to
underestimation of body mass at the individual level, and of the prevalence of overweight
and obesity at the population level.
We attempted to reduce the inaccuracy of self-reported values by asking all teachers
emphatically to instruct their pupils, on the day before administering the questionnaire, to
weigh and measure themselves at home the next morning, before coming to school (see
section 2.1.4). Although this specific instruction may have helped to reduce the information
problem of adolescents in growth not knowing their actual length and weight, it will not help
to overcome other possible reasons for reporting a height or weight that deviates from the
actual value. To emphasise the importance of reporting true values and as a means to check
for possible bias, a question was added asking respondents to indicate whether they were
“pretty certain” or “not so certain” of their self-reported length and weight: 75% indicated they
15
Table 2
I.
II.
Confirmatory factor analysis Big-Five personality dimensions
Openness to experience (O)
Conscientiousness (C)
III. Extraversion (E)
IV. Agreeableness (A)
V. Neuroticism (N)
Artistic
Openness to
experience (O)
Conscientiousness
(C)
Extraversion
(E)
Agreeableness
(A)
Neuroticism
(N)
communalities
0.703
0.072
0.077
0.061
-0.043
0.511
Creative
0.710
0.108
0.008
0.149
-0.050
0.541
Deep
0.468
0.028
0.134
0.156
0.166
0.289
Imaginative
0.636
-0.131
-0.146
0.096
0.121
0.467
Innovative
0.429
0.103
-0.071
0.233
0.063
0.258
Neat
0.068
0.832
0.042
0.143
0.025
0.720
Organized
0.072
0.767
0.013
0.194
0.076
0.638
Sloppy
0.105
-0.799
0.043
0.073
0.185
0.691
Thorough
0.167
0.719
0.119
0.194
0.067
0.601
Introverted
-0.015
-0.019
0.733
-0.164
0.180
0.597
Quiet
-0.013
0.142
0.775
-0.091
0.028
0.630
Reserved
0.041
-0.007
0.739
-0.034
0.146
0.570
Agreeable
0.121
0.099
-0.225
0.458
-0.189
0.320
Cooperative
0.095
0.144
0.016
0.747
0.107
0.600
Helpful
0.096
0.182
0.029
0.704
0.120
0.554
Kind
0.047
0.052
-0.100
0.688
-0.098
0.498
Pleasant
0.200
0.005
-0.053
0.640
-0.051
0.455
Sympathetic
0.230
0.039
-0.082
0.563
-0.003
0.377
Anxious
0.046
0.064
0.236
0.094
0.581
0.408
Irritable
0.131
-0.051
-0.047
-0.141
0.753
0.608
Touchy
0.022
-0.015
0.194
-0.012
0.772
0.635
Mean
Explained variance
Scale reliability (Cronbach's alpha)
0.522
9.5%
12.3%
9.1%
13.1%
8.2%
.59
.80
.67
.73
.57
16
were pretty certain of their length, 76% of their weight. Those not so certain of their length
tended to report lower values (p<.01), while those not so certain of their weight tended to
report higher values (p<.01). Nevertheless, BMI values - our key variable of interest - did not
differ significantly (p<.01) between those that are pretty certain of both their length and
weight, and those that are not so certain of one or both parameters.
Overweight and obesity were assessed by calculating BMI values and by using international
gender and age specific cut-off points (Table 3).
Table 3
International Body Mass Index (BMI) cut-off points for overweight and obesity in adolescents;
by gender and age
Age
Girls
Boys
Overweight
Obese
Overweight
Obese
11
20.74
25.42
20.55
25.10
12
21.68
26.67
21.22
26.02
13
22.58
27.76
21.91
26.84
14
23.34
28.57
22.62
27.63
15
23.94
29.11
23.29
28.30
Source: Cole et al. 2000
Body image (question 12) was assessed by asking “What do you think of your own body?”,
with five possible answer categories that ranged from “much too thin” to “much too thick”,
with “exactly right, actually” as middle answer category. Furthermore, we asked respondents
whether they had one or more chronic conditions or disabilities (question 13) and about their
smoking behaviour during the last four weeks (question 14).
2.2.3 About your future (questions 15 to 22)
This section included a series of questions aiming to assess adolescents’ appreciation and
expectations of their future and the future consequences of their behaviour. As this seems to
be a fairly novel subject area in this age group, we will discuss the approach and measures
chosen more extensively.
Adolescents’ appreciation of their future was assessed using four different measures. The
first measure was Strathman et al.’s (1994) 12-item “consideration of future consequences”
17
(CFC) scale.5 Two researchers independently translated the CFC scale into Dutch and
simplified the wording to make the scale it more comprehensible for young adolescents (in
conformance with Cauffman & Steinberg 2000). Both versions were compared with the aid of
a third researcher, and combined into a Dutch CFC scale for adolescents (CFCDA; question
15). Respondents were asked to indicate for each statement how characteristic it is of them
on a Likert-type scale ranging from 1 (extremely uncharacteristic) to 5 (extremely
characteristic). Possible scores therefore range from 12 to 60, with higher scores indicating
higher consideration of future consequences. For ease of interpretation and comparability
with other measures used in this study, final scores on the CFCDA were re-scaled to
represent a range between 0 “lowest” and 10 “highest”
consideration of future consequences. The second
measure (question 17), that we have called “meaning
of future life”, asked respondents how important it is to
them what their life will be like in 2, 5 and 25 years from
now, with four possible answer categories that ranged
from “very important” to “not at all important”. The third
measure (question 18) asked respondents to make a
series of trade-offs between money values now and in
the future, i.e., 2, 5 and 25 years from now. Answers
were used to calculate adolescents’ discounting rates.
This is a fairly standard economic approach, but novel
in this context. The fourth measure (question 19) asked
* long live the here and now
respondents to consider three investments that would yield a better health at age 70 or
extend their live with 3 years: improve their dietary behaviour, exercise 30 minutes per day
more, and take an injection that would make them pretty sick for the next week.
Adolescents’ expectations of their future was assessed by asking for their life expectancy
(question 16) and expected health status at the age of 40 and 70 (questions 20 and 21).
For all questions regarding the future we used carefully specified and mutually consistent
ages and timelines. The anchor ages chosen were 40 and 70 years, rounded numbers that
were expected to correspond fairly with the age of this target group’s parents and
grandparents. Previous research has shown that people tend to use close family members
as reference for eliciting expectations regarding their future health and life expectancy (e.g.,
5
See also: http://www.missouri.edu/~psyas/cfc.pdf
18
Brouwer & Van Exel 2005). Furthermore, the timeline of 25 years corresponds to the first
anchor age, more or less the age of their parents. The time line of 5 years more or less
coincides with the end of the secondary school period, and was expected to be a more
common focus for this target group when talking about “the future”. The timeline of 2 years
was added because, after the interviews in the phase of the study (see section 1.2), we
expected this to be a fair approximation of “distant future” in the perception of many
adolescents.
2.2.4 About home (questions 23 to 34)
The aim of this section was to gain insight in the characteristics of adolescents’ home
situation, and its role in health attitudes, behaviours and future expectations. The questions
concerned the composition of the household, the country of birth and employment status of
both parents, perception of relative family wealth, religious upbringing, availability at will of
healthy and unhealthy foods, whether they are allowed to smoke or drink alcohol at home, a
set of statements assessing the adolescent-parents relationship, parenting style, and
happiness at home.
Analogous to the approach of Watt & Sheiham (1998), a Food Availability at Home Index
(FAHI) was constructed in order to assess adolescents’ access to unhealthy food at home.
Table 4 presents the questions selected and the scoring system used. FAHI scores range
between 0 and 10, higher scores indicate higher access to unhealthy food at home. FAHI
scores were negatively associated (p<.01) with mother having a job, perceived relative family
wealth, religious upbringing, and the health belief statement “I eat healthy” (question 22).
Table 4
Food Availability at Home Index (FAHI) scoring system
Item
Do you have these products at
home and are you allowed to
have one if you feel like it?
(question 30, statements C - G)
Answer caregories
Score
1. Biscuit
Yes
No
2
0
2. Candy / chocolate
Yes
No
2
0
3. Chips / nuts / popcorn
Yes
No
2
0
4. Snacks
Yes
No
2
0
5. Soft drink
(not light / sugar-free)
Yes
No
2
0
Analogous to the approach of Kremers et al. (2003), a fourfold typology of parenting style
(PS) was constructed, based on the interaction between parental involvement (I) and
19
parental strictness (S) (question 33, statement A “My parents are interested in what I do or
what I am concerned with” and statement C “My parents are strict”): authoritative (high I; high
S; 24% of respondents), authoritarian (low I; high S; 2%), indulgent (high I; low S; 71%), and
neglectful (low I; low S; 3%).
2.2.5 About school (questions 35 to 43)
The aim of this section was to gain insight in the characteristics of adolescents’ school
environment, and its role in health attitudes, behaviours and future expectations. The
questions concerned travel mode and travel time to school, school performance, bullying,
availability of healthy and unhealthy foods at school and close to school, where they go to
after school, who is home when they come home from school, and happiness at school.
2.2.6 About your leisure time (questions 44 to 52)
The aim of this section was to gain insight in how adolescents spend their leisure time, and
its role in health attitudes, behaviours and future expectations. The questions concerned the
number of good friends, time spent on several sedentary and non-sedentary behaviours on
school and weekend days, membership of a sports club (and if so, hours training and
participation in competition), statements regarding reasons for exercising, solitude and
boredom, and happiness during leisure time.
Analogous to the approach of Watt & Sheiham (1998), a Physical Activity Index (PAI) was
constructed in order to assess adolescents’ level of physical activity. Table 5 presents the
questions selected and the scoring system used. PAI scores range between 0 and 10, higher
scores indicate higher levels of physical activity.
Table 5
Physical Activity Index (PAI) scoring system
Item
Answer caregories
Score
1. How do you usually travel to/from
school?
By bike or walking
By schoolbus, public transport, car or otherwise
2
0
2. Are you member of a sports club?
Yes
No
2
0
3. Do you participate in a sports
competition?
Yes
No
2
0
4. On average, how much time do you
spend playing outside on
weekdays?
More than 2 hours per day / Between 1 and 2 hours per day
One hour or les per day / Not at all
2
0
5. On average, how much time do you
spend playing outside on
weekenddays?
More than 2 hours per day / Between 1 and 2 hours per day
One hour or les per day / Not at all
2
0
20
PAI scores correlate statistically significantly and in expected directions with all of six
statements about playing sports (Likert-type scale, “totally agree” - “totally disagree”;
question 50), correlation coefficients however were moderate to low: “When I play sports,
that is because I enjoy it” (-; p<.01); “When I play sports, that is because I want to keep fit” (-;
p<.01); “When I play sports, that is because I want to look good” (-; p<.05); “When I play
sports, that is because I meet friends then” (-; p<.01); “When I play sports, that is because I
want to become one of the best” (-; p<.01); and “When I play sports, that is because my
parents oblige me” (+; p<.01).
PAI scores also correlate statistically significantly (p<.01) and in expected directions with five
out of seven health belief statements (Likert-type scale, “totally agree” - “totally disagree”;
question 22), correlation coefficients however were moderate to low: “I eat healthy” (-); “I
exercise enough to stay fit” (-); “Living healthy makes me feel better” (-); “If I live unhealthy I
may incur all sorts of diseases in the future” (-); and “If I live unhealthy, I may die sooner” (-).
2.2.7 About what you eat (questions 53 to 55)
The aim of this section was to gain insight in adolescents’ eating behaviour. Van Assema et
al. (2002) suggested that most often used food frequency questionnaires have only limited
capacity to make a valid assessment of adolescents fruit and vegetable intake. Brener et al.
(2002) assessed the test-retest reliability of a large range of self-report measures included in
the YRBSS (see also section 2.1.2),
and found the reliability of nearly all
items to be at least moderate, and of
nearly half to be substantial. Notably,
dietary and physical activity
behaviours had relatively low
reliability. They argued that nutrition
and physical activity may be less
salient to adolescents and therefore
recalled less reliably, but that
inconsistent responses may also be
related to variability in these
behaviours among adolescents.
Matheson et al. (2002) agreed that
self-report questionnaires may result in
sizable errors in quantitative estimates
21
of food and energy intakes, but argued they are appropriate for ranking children's relative
intakes. The questions concerning eating behaviour have therefore been focussed on two
salient issues. First, the questionnaire asked about the frequency of consumption of a variety
of unhealthy snacks and the context of snacking in terms of location and activities (questions
53, 54). Second, the questionnaire asked about frequency of eating breakfast, lunch, and
dinner at the table together with the family, and the frequency of consumption of a variety of
target (un)healthy food types: milk, soft-drinks (not light), fruit and vegetables.
Analagous to the approach of Watt & Sheiham (1998), a Healthy Eating Index (HEI) and an
Unhealthy Eating Index (UEI) were constructed in order to assess adolescents’ eating
behaviour. Table 6 and Table 7 present the questions selected and the scoring system used.
HEI and UEI scores range between 0 and 10, higher HEI scores indicate healthier eating,
higher UEI scores indicate unhealthier eating.
Table 6
Healthy Eating Index (HEI) scoring system
Item
Answer caregories
1. How often do you eat breakfast?
Every day / Often, but not every day
Once or twice a week / (Almost) Never
2
0
2
0
3. How often do you drink milk?
2
0
4. How often do you eat fruit?
2
0
5. How often do you eat vegetables?
2
0
(more than only something to drink or a snack)
2. How often do you eat dinner at the table,
together with your family?
Score
(more than only something to drink or a snack)
(salad / cooked vegetables)
Table 7
Unhealthy Eating Index (UEI) scoring system
Item
Answer caregories
1. How often do you eat cookies / cakes?
2
0
2. How often do you eat sweets / chocolate?
2
0
3. How often do you eat chips / nuts /
popcorn?
2
0
4. How often do you eat snacks?
2
0
2
0
(like hamburger, French fries, pizza)
5. Hof often do you drink soft drinks (regular,
not light)?
Score
22
HEI and UEI scores were not correlated. HEI and UEI scores correlated statistically
significantly (p<.01) with PAI scores, correlation coefficients however are low; healthier
eating is associated with higher levels of physical activity, unhealthier eating with lower levels
of physical activity.
HEI scores correlate statistically significantly (p<.01) and in expected directions with six out
of seven health belief statements (Likert type from “totally agree to totally disagree; question
22) , correlation coefficients however are low: “I eat healthy” (-); “I exercise enough to stay fit”
(-); “Living healthy makes me feel better” (-); “If I live unhealthy I may incur all sorts of
diseases in the future” (-); “If I live unhealthy, I may die sooner” (-); and “If I were regularly ill,
I would start living healthier” (-). HEI scores correlate statistically significantly and in expected
directions with two of six statements about playing sports (Likert type from “totally agree to
totally disagree; question 50), correlation coefficients however are low: “When I play sports,
that is because I enjoy it” (-; p<.01); and “When I play sports, that is because I want to keep
fit” (-; p<.01).
UEI scores correlate statistically significantly (p<.01) and in expected directions with five out
of seven health belief statements (Likert type from “totally agree to totally disagree; question
22) , correlation coefficients however are low: “I eat healthy” (+); “Living healthy makes me
feel better” (+); “If I live unhealthy I may incur all sorts of diseases in the future” (+); “If I live
unhealthy, I may die sooner” (+); and “If I were regularly ill, I would start living healthier” (+).
Contrary to HEI scores, UEI scores do not correlate with the statement “I exercise enough to
stay fit”. UEI scores correlate statistically significantly and in expected directions with two of
six statements about playing sports (Likert type from “totally agree to totally disagree;
question 50), correlation coefficients however are moderate to low: “When I play sports, that
is because I want to keep fit” (+; p<.01); and “When I play sports, that is because I meet
friends then” (-; p<.05).
2.2.8 About money (questions 56 to 63)
The aim of this section was to gain insight in the size of adolescents’ monthly budget, where
they get their money from (pocket money, job), how they spend it, and the influence of any
spending restrictions imposed by parents and competing popular activities (e.g., mobile
phones, music, clothing, cosmetics, alcoholic drinks, smoking) on the amount of money
spent on sweets and snacks.
23
24
3
3.1
3.1.1
Results
Study population
Participating schools and number of respondents
Ten smaller and larger schools in lower and higher urbanized areas throughout the country
were recruited to participate in the study (see Figure 2); completed questionnaires were
received from 2,006 pupils, with school proportions ranging between 2 and 18 percent (see
Table 8).
Figure 2 Participating schools
Note: numbers correspond to those in Table 8.
25
Table 8
Number of respondents per school (n=2,006)
School
City
1 Agnieten College - Carolus Clusius
Zwolle
263 (13)
2 Bornego College
Heerenveen
362 (18)
3 Carmel College Salland
Raalte
4 CSG De Lage Waard
Papendrecht
5 CSG Dingstede
Meppel
6 Gomarus Scholengemeenschap
Gorinchem
285 (14)
7 Hondsrug College
Emmen
145 (7)
8 Ichthus College
Veenendaal
148 (7)
9 Jacobus Fruytier scholengemeenschap
Apeldoorn
317 (16)
10 Sint Laurens College
Rotterdam
215 (11)
Total
3.1.2
N (%)
34 (2)
183 (9)
54 (3)
2006 (100)
Representativeness of the sample
Table 9 presents proportions in the reference and study populations according to gender,
age, education level, grade and ethnicity. As Table 9 makes clear, the study sample deviates
from the reference population on all selected variables, but most importantly with respect to
education level and grade:
General secondary education is considerably over-represented; higher education level is
associated with higher proportions of female pupils (47.5% VMBO; 52.7% HAVO; 55.0%
VWO) and Dutch ethnicity (76.6% VMBO; 83.5% HAVO; 87.1% VWO).
1st grade is over-represented; this is associated with lower age (12.8 in 1st; 13.7 in 2nd).
Regarding the other variables:
Female gender is slightly over-represented; this difference is associated with the bias on
education level.
Older ages are over-represented; this can partly be explained by difference in reference
date between the reference population (1st of October) and the study sample (second half
of May); furthermore, this difference is associated with the bias on grade.
Dutch ethnicity is over-represented; in part, this difference is associated with bias the in
education level.
26
Table 9
Reference population according to gender, age, education level, and ethnicity
CBS 2005
(%)
Variable
This study
(%)
Gender
Female
Male
49.2
50.8
53.0 (+3.8)
47.0 (-3.8)
Age
12
13
14
30.1 a
45.9
23.9
15.0 (-15.1)
51.0 (+5.1)
34.0 (+10.1)
Education level
Pre-vocational (VMBO)
General secondary (HAVO/VWO)
52.7 b
47.3
41.6 (-11.1)
58.4 (+11.1)
Grade
First
Second
49.9
50.1
56.7 (+6.8)
43.3 (-6.8)
Ethnicity
Dutch
Other
78.3
21.7
90.2 (+11.9)
9.8 (-11.9)
Note: a Source: MinOCW 2006.
3.2
b
approximation based on adolescents in third grade.
Length, weight, BMI and prevalence of overweight and obesity
Table 10 presents self-reported length and weight, and BMI based on these values (for a
discussion of the validity and reliability of self-reported values, see Annex B). Self-reported
length systematically exceeded mean values from standard growth charts for adolescent
length-for-age (TNO/LUMC 1998), with larger differences at younger ages. When looking at
age- and gender-specific mean length and weight, boys’ self-reported weight was higher and
girls’ self-reported weight was lower than values from standard growth charts for adolescent
weight-for-length (TNO/LUMC 1998). Figure 3 shows cumulative distributions of self-reported
length, weight and BMI according to gender.
Table 10 Length, weight and BMI
Variable
Mean (SD)
95% CI
Min - max
Percentiles
th
1.20 - 1.99
5
10th
50th
90th
95th
1.52
1.56
1.66
1.77
1.80
Length
1.66 (0.1)
1.66 - 1.67
- girls
1.65 (.01)
1.65 - 1.66
1.32 - 1.88
1.54
1.57
1.65
1.74
1.76
- boys
1.68 (.01)
1.67 - 1.68
1.20 - 1.99
1.52
1.55
1.67
1.80
1.83
Weight
51.8 (9.4)
51.4 - 52.3
35 - 118
39
41
51
64
69
- girls
51.4 (8.7)
50.9 - 51.9
35 - 118
39
41
50
62
65
- boys
52.2 (9.9)
51.6 - 52.9
35 - 111
39
40
51
65
70
BMI
18.6 (2.6)
18.5 - 18.7
11.6 - 37.2
15.1
15.6
18.4
21.9
23.1
- girls
18.7 (2.6)
18.6 - 18.9
11.6 - 37.2
15.2
15.8
18.4
22.0
23.3
- boys
18.5 (2.5)
18.3 - 18.7
12.0 - 30.6
15.0
15.6
18.3
21.7
22.9
27
100%
80%
Cumulative Percent
1,93
1,90
1,88
1,86
1,84
1,82
1,80
1,78
1,76
1,74
1,72
1,70
1,68
1,66
1,64
1,62
1,60
1,58
1,56
1,54
1,52
1,50
1,48
1,46
1,44
1,42
1,39
1,35
1,20
111
96
88
85
83
79
81
77
75
73
71
69
67
65
63
61
59
57
55
53
51
49
47
45
43
39
41
37
35
100%
girls
boys
80%
Cumulative Percent
100%
80%
Cumulative Percent
Figure 3 Cumulative distribution of length, weight and BMI according to gender
[including gender-specific cut-off points (age 13; see Table 3) for overweight and obesity (in bold)]
60%
40%
20%
girls
0%
boys
Length (meters)
60%
40%
20%
girls
0%
boys
Weight (kilograms)
60%
40%
20%
0%
28,4
25,6
24,3
23,4
22,9
22,4
21,9
21,5
21,2
21,0
20,6
20,3
20,1
19,8
19,6
19,4
19,1
18,8
18,6
18,4
18,2
17,9
17,7
17,5
17,3
17,0
16,8
16,5
16,3
16,0
15,8
15,5
15,2
14,9
14,2
11,6
Body Mass Index (BMI)
28
Using gender- and age-specific international BMI cut-off points for overweight and obesity in
adolescents (Cole et al. 2000; Table 3), prevalence of overweight was 7.6%, and of obesity
0.7%. These rates are fairly low as compared to recent reference values (TNO 2006), but
comparable to those reported for Dutch adolescents of 12 to 15 years in 1997 (Hirasing et al.
2001). Recent reference values include 10.5% / 1.5% for girls and 10.6% / 1.2% for boys in
2nd grade of secondary education in curriculum year 2003/2004 from a regional study, and
16.2% / 2.9% for girls and 15.7% / 3.0% for boys aged 12 to 14 years in 2002-2004 from a
representative sample in a national study (TNO 2006).
To assess whether the sample bias (see section 3.1.2) affects the prevalence rates of
overweight and obesity, in particular with respect to the variables education level and
ethnicity, two sets of weights were calculated through direct standardisation. A first set of
weights was based on education level and grade (range from 0.81 to 1.90). A second set on
education level, grade and ethnicity (range from 0.74 to 4.63). Weighing the data, however,
had no significant effect on the prevalence of overweightness and obesity. There are two
main reasons why this weighing procedure may not have led to prevalence rates that are
more in conformance with the higher values observed in other studies. First, when weighing
data it is assumed that the observations that are exploded are representative of the
corresponding sub-population. This may not be the case. Second, it is possible that the low
prevalence rates are the result of selection bias. The ten participating schools may constitute
a relatively slim selection from the total population.
Finally, we investigated the association of length, weight and BMI with body image (see
Table 11). BMI values based on self-reported height and weight seem to be largely
consistent with adolescents’ body image.
Irrespective of the fact whether the sample is biased or slim, quantile regression (Koenker &
Bassett 1978) will be applied as primary method for subsequent multivariate analysis of the
data. Quantile regression is an appropriate technique when differences in association are
expected between parts of the distribution of the outcome variable and the explanatory
variables. Quantile regression therefore seems very suitable for analysis of the correlates of
overweight, as our primary interest goes out to the attitudes, health behaviour and
consideration of future consequences of the at risk group, i.e. adolescents in the 80th centile
of the BMI distribution. Quantile regression has been used for this purpose before
(Kobayashi & Kobayashi 2006; Wei et al. 2006; Sturm & Datar 2005; Kan & Tsai 2004;
Zimmermann et al. 2004; Herpertz-Dahlmann et al. 2003; Smith et al. 2003).
29
Table 11 Length, weight and BMI according to body image
Total
Height
N
%
Mean
SD
Much too thin
A bit too thin
Exactly right, actually
A bit too thick
Much too thick
25
238
1068
580
62
86.2%
98.8%
98.9%
99.0%
93.9%
1.64
1.66
1.66
1.67
1.68
(0.1)
(0.1)
(0.1)
(0.1)
(0.1)
1.43
1.40
1.20
1.40
1.50
Total
1973 98.6%
1.66
(0.1)
27
233
1047
572
62
93.1%
96.7%
96.9%
97.6%
93.9%
45.5
46.1
50.1
56.2
66.0
(10.4)
(6.5)
(8.0)
(8.5)
(15.3)
35
35
35
37
44
Total
1941 97.0%
51.8
(9.3)
Much too thin
A bit too thin
A bit too thick
Much too thick
24
230
1036
567
59
82.8%
95.4%
95.9%
96.8%
89.4%
15.8
16.7
18.0
20.2
23.0
Total
1916 95.7%
18.6
Weight Much too thin
A bit too thin
A bit too thick
Much too thick
BMI
Girls
Min Max
Boys
N
%
Mean
SD
Min Max
N
%
Mean
SD
Min
Max
1.88
1.86
1.92
1.99
1.99
16
97
530
356
45
94.1%
99.0%
98.5%
98.9%
97.8%
1.64
1.65
1.65
1.66
1.68
(0.1)
(0.1)
(0.1)
(0.1)
(0.1)
1.50
1.45
1.32
1.47
1.55
1.88
1.80
1.86
1.87
1.80
9
141
536
223
16
75.0%
98.6%
99.3%
99.1%
84.2%
1.66
1.66
1.67
1.68
1.68
(0.1)
(0.1)
(0.1)
(0.1)
(0.1)
1.43
1.40
1.20
1.40
1.50
1.87
1.86
1.92
1.99
1.99
1.20 1.99
1044
98.6%
1.65
(0.1)
1.32 1.88
925
98.5%
1.67
(0.1)
1.20
1.99
73
72
90
96
118
17
94
522
349
44
100.0%
95.9%
97.0%
96.9%
95.7%
42.5
45.1
49.2
55.3
63.8
(9.2)
(5.5)
(6.8)
(7.6)
(15.1)
35
35
35
38
47
73
58
83
84
118
10
139
523
222
17
83.3%
97.2%
96.9%
98.7%
89.5%
50.6
46.7
50.9
57.5
71.0
(10.8)
(7.1)
(8.9)
(9.6)
(15.2)
36
35
35
37
44
72.0
72.0
90.0
96.0
111.0
35
118
1026
96.9%
51.4
(8.7)
35
118
911
97.0%
52.3
(10.0)
35
111.0
(2.0)
(1.5)
(1.9)
(2.4)
(4.2)
11.6
12.1
12.0
12.8
17.0
20.3
20.8
28.4
30.6
37.2
16
93
514
345
43
94.1%
94.9%
95.5%
95.8%
93.5%
15.2
16.5
18.0
20.1
22.6
(1.8)
(1.3)
(1.8)
(2.3)
(4.4)
11.6
13.7
13.0
15.1
17.0
19.8
19.5
26.4
29.1
37.2
8
137
520
221
15
66.7%
95.8%
96.3%
98.2%
78.9%
16.8
16.8
18.0
20.3
24.1
(2.0)
(1.6)
(2.0)
(2.5)
(3.2)
15.1
12.1
12.0
12.8
18.1
20.3
20.8
28.4
30.6
29.1
(2.6)
11.6 37.2
1011
95.5%
18.7
(2.6)
11.6 37.2
901
96.0%
18.5
(2.5)
12.0
30.6
30
An additional advantage is that for quantile regression it is not necessary to classify
adolescents into (over)weight categories. Assuming that BMI values based on self-reported
height and weight are valid representations of actual values, but systematically
underestimate measured values, analysing the data as a distribution partly mitigates the
problem of the low observed overweight and obesity prevalence rates in this sample. An
issue to account for in the interpretation of results, however, is that adolescents in the
heaviest quartiles of measured weight tend to underreport weight by significantly more than
those in lighter quartiles, so that effect sizes most probably will constitute an
underestimation.
Furthermore, as is commonly done, logit and generalised ordered logit analysis will be
applied to data categorised according to age and gender specific cut-off points for overweight
and obesity (see were pretty certain of their length, 76% of their weight. Those not so certain
of their length tended to report lower values (p<.01), while those not so certain of their weight
tended to report higher values (p<.01). Nevertheless, BMI values - our key variable of
interest - did not differ significantly (p<.01) between those that are pretty certain of both their
length and weight, and those that are not so certain of one or both parameters.
Overweight and obesity were assessed by calculating BMI values and by using international
gender and age specific cut-off points (Table 3).
Table 3). This will primarily be done to obtain results that are comparable to other studies.
3.3
Variables
3.3.1
About you
Table 12 Personal characteristics, BMI, overweight and obesity
Variable
Category
Value
BMI
th
Mean
90
Proportion Proportion
overweight
obese
Gender
Female
Male
1062 (53)
942 (47)
18.7
18.5
22.0
21.7
.067
.085
.005
.010
Age
1213
14+
301 (15)
1023 (51)
682 (34)
18.0
18.4
19.1
20.7
21.7
22.7
.072
.073
.082
.011
.007
.006
Country of birth
Netherlands
Other
1910 (95)
96 (5)
18.6
18.6
21.9
21.7
.076
.078
.008
-
Ethnicity
Dutch
Allochthonous, western
Allochthonous, non-western
1809 (90)
74 (4)
117 (6)
18.6
18.9
19.1
21.8
22.6
22.8
.072
.129
.109
.006
.014
.018
31
Variable
Category
Value
BMI
th
Mean
90
overweight
obese
Education
Pre-vocational
General secondary
825 (42)
1157 (58)
18.8
18.5
22.2
21.5
.091
.062
.013
.004
Grade
First
Second
1137 (57)
867 (43)
18.3
19.0
21.5
22.2
.075
.077
.011
.002
Attitude about
health lifestyle
Carefree sporty
Worrying dependent
Contended independent
Looks over matter
Indifferent solitary
(39)
(22)
(14)
(24)
(2)
18.2
19.6
18.4
18.6
19.5
21.1
23.8
21.3
21.9
23.6
.048
.156
.059
.059
.185
.003
.023
.004
.037
Happiness a
Mean or lower
Above mean
601 (30)
1376 (70)
19.0
18.4
22.7
21.5
.115
.059
.012
.005
Personality b
Neuroticism
(+)
(-)
875 (50)
867 (50)
18.5
18.8
21.4
22.2
.057
.100
.001
.013
Extraversion
(+)
(-)
921 (53)
821 (47)
18.6
18.7
21.8
22.0
.074
.085
.003
.011
Openness to experience (+)
(-)
851 (49)
891 (51)
18.6
18.7
22.1
21.8
.087
.071
.006
.008
Conscientiousness
(+)
(-)
833 (48)
909 (52)
18.8
18.5
22.1
21.6
.094
.065
.008
.007
Agreeableness
(+)
(-)
812 (47)
930 (53)
18.8
18.5
22.1
21.7
.093
.067
.009
.006
722
398
250
445
29
Note: a descriptive statistics happiness (mean (SD); 95%CI; min-max): 7.94(1.27); 7.88-7.99; 1-10.
versus negative personality-factor loaders.
3.3.2
b
positive
About your health
Table 13 Health, BMI, overweight and obesity
Variable
Category
Value
BMI
Mean
90th
overweight
obese
Health status a
Mean or lower
Above mean
783 (39)
1205 (61)
19.1
18.3
22.8
21.3
.116
.051
.012
.004
Body image
Much too thin
A bit too thin
A bit too thick
Much too thick
29
241
1080
586
66
(1)
(12)
(54)
(29)
(3)
15.8
16.7
18.0
20.2
23.0
19.7
18.6
20.4
23.1
28.0
.023
.157
.517
.002
.009
.121
Chronic condition
No
Yes, low burden
Yes, high burden
1719 (86)
265 (13)
19 (1)
18.6
19.0
20.0
21.8
22.2
28.3
.071
.096
.222
.007
.004
.111
Smoking
No
Yes, now and then
Yes, every day
1833 (92)
121 (6)
50 (2)
18.6
19.0
19.9
21.8
21.9
24.4
.072
.080
.196
.002
.022
Note: a descriptive statistics health status (mean (SD); 95%CI; min-max): 7.69(1.27); 7.64-7.75; 0-10.
32
3.3.3
About your future
Table 14 Future, BMI, overweight and obesity
Variable
CFCDA
a
Category
Value
BMI
Mean
90th
overweight
obese
Mean or lower
Above mean
859 (43)
1146 (57)
18.5
18.7
21.8
21.9
.077
.074
.006
.008
Life expectancy b
Mean or lower
Above mean
941 (53)
827 (47)
18.7
18.5
22.0
21.5
.082
.063
.006
.009
Meaning of future
c
life…
… in 2 years
(+)
(-)
1765 (89)
226 (11)
18.7
18.2
21.9
21.4
.074
.086
.006
.014
… in 5 years
(+)
(-)
1827 (92)
162 (8)
18.7
18.2
21.9
21.4
.077
.060
.007
-
… in 25 years
(+)
(-)
1761 (88)
229 (12)
18.6
18.6
21.9
21.4
.075
.070
.007
.005
Discounting rate
2 years
Up to 5%
5 to 12%
12 to 22%
22 to 58%
58 to 124%
over 124%
418
208
288
615
285
181
(21)
(10)
(14)
(31)
(14)
(9)
18.9
18.8
18.2
18.5
18.5
18.8
22.3
22.2
21.1
21.7
21.9
21.2
.094
.080
.051
.071
.074
.089
.010
.015
.004
.003
.004
.018
Discounting rate
5 years
Up to 15%
15 to 38%
38 to 58%
58 to 119%
over 119%
786
578
388
140
102
(39)
(29)
(19)
(7)
(5)
18.7
18.5
18.5
18.6
19.4
21.9
21.3
21.9
22.3
22.9
.077
.072
.062
.093
.125
.009
.004
.003
.008
.031
Discounting rate
25 years
Up to 20%
20 to 32%
32 to 45%
over 45%
1524
235
108
132
(76)
(12)
(5)
(7)
18.6
18.4
18.5
19.3
21.8
21.4
22.2
23.4
.072
.061
.067
.154
.006
.004
.010
.024
Invest in a better
health at age 70
Dietary behaviour
(y)
(n)
1521 (76)
468 (24)
18.7
18.5
21.9
21.5
.074
.072
.010
-
Exercising
(y)
(n)
1371 (69)
624 (31)
18.6
18.6
21.7
22.1
.068
.090
.008
.007
Injection
(y)
(n)
1039 (52)
957 (48)
18.7
18.6
21.8
21.9
.077
.072
.009
.005
Dietary behaviour
(y)
(n)
1282 (64)
706 (36)
18.6
18.7
21.8
22.1
.071
.083
.010
.003
Exercising
(y)
(n)
1225 (62)
761 (38)
18.4
18.7
21.7
22.1
.067
.090
.010
.003
Injection
(y)
(n)
929 (47)
1060 (53)
18.5
18.7
21.6
22.0
.061
.088
.009
.006
Invest in 3 years
life extension
Health expectancy
at age…
… 40 d
Mean or lower
Above mean
1120 (56)
877 (44)
19.1
18.3
22.2
21.4
.095
.052
.007
.008
e
Mean or lower
Above mean
1064 (53)
928 (47)
18.9
18.4
22.2
21.3
.095
.052
.007
.008
… 70
Statements health lifestyle & future health f
“I eat healthy”
(+)
(-)
1662 (83)
333 (17)
18.5
19.2
21.7
23.1
.063
.135
.006
.016
“I exercise enough to stay fit”
(+)
(-)
1747 (88)
248 (12)
18.5
19.7
21.5
23.8
.064
.165
.004
.030
33
Variable
Category
Value
BMI
th
Mean
90
overweight
obese
“Living healthy makes me feel better”
(+)
(-)
1757 (89)
222 (11)
18.6
18.6
21.9
22.0
.075
.075
.006
.020
“If I live unhealthy I may incur
all sorts of diseases in the future”
(+)
(-)
1500 (76)
484 (24)
18.6
18.7
21.9
21.9
.074
.079
.008
.004
“If I live unhealthy I may die sooner”
(+)
(-)
1363 (68)
632 (32)
18.6
18.7
21.8
22.1
.073
.083
.009
.003
“If I want, I can easily live healthier
than I do now”
(+)
(-)
1332 (67)
651 (33)
18.6
18.7
21.8
22.1
.072
.086
.009
.005
“If I were regularly ill, I would start
living healthier”
(+)
(-)
1411 (71)
585 (29)
18.5
18.6
21.9
21.9
.075
.076
.007
.009
Note: descriptive statistics: mean (SD); 95%CI; min-max. a 5.69(1.26); 5.63-5.74; 0.8-9.4. A higher score
indicates a higher consideration of future consequences. b 85.6(13.9); 85.0-86.3; 10-200. c (very) important
d
e
f
versus (completely) unimportant. 7.26(1.23); 7.21-7.31; 1-10. 6.28(1.51); 6.21-6.35; 0-10. (totally) agree
versus (totally) disagree.
3.3.4
About home
Table 15 Home environment, BMI, overweight and obesity
Variable
Category
Family
composition
Country of birth…
BMI
Value
th
Mean
90
overweight
obese
Two biological parents
(y)
(n)
1753 (87)
253 (13)
18.6
19.0
21.9
22.3
.072
.101
.007
.013
Single parent
(y)
(n)
154 (8)
1852 (92)
19.4
18.6
23.0
21.8
.142
.070
.021
.006
Only child
(y)
(n)
127 (6)
1879 (94)
18.8
19.1
21.8
22.9
.071
.143
.007
.017
… mother
Netherlands
Other
1869 (93)
137 (7)
18.6
19.2
21.8
22.9
.071
.141
.006
.023
… father
Netherlands
Other
1861 (93)
145 (7)
18.6
18.9
21.8
22.6
.073
.111
.006
.022
Employment status Mother employed
(y)
(n)
1332 (67)
665 (33)
18.6
18.7
21.8
22.0
.070
.086
.006
.008
Father employed
(y)
(n)
1912 (96)
74 (4)
18.6
18.9
21.9
21.8
.077
.060
.008
-
(Much) Wealthier
About as wealthy
(Much) Less wealthy
459 (23)
1369 (69)
162 (8)
18.4
18.7
19.2
21.3
22.0
23.5
.059
.075
.126
.011
.005
.020
Religious
upbringing
Yes, Catholic
Yes, Protestant
Yes, Islamic
Yes, other
No
110
1202
44
124
512
(6)
(60)
(2)
(6)
(26)
18.3
18.7
20.4
18.5
18.5
22.2
21.9
27.3
21.5
21.5
.100
.074
.216
.051
.071
.009
.004
.081
.017
.006
Food availability
at will
Milk
(y)
(n)
1912 (96)
82 (4)
18.6
18.7
21.9
21.7
.076
.080
.008
.000
Fruit
(y)
(n)
1978 (99)
27 (1)
18.6
19.5
21.9
24.5
.075
.136
.007
.045
Family wealth
a
34
Variable
Category
Value
BMI
th
Mean
90
overweight
obese
Biscuit
(y)
(n)
1510 (76)
489 (24)
18.6
18.7
21.8
22.0
.072
.086
.005
.015
Candy / chocolate
(y)
(n)
1133 (57)
857 (43)
18.5
18.8
21.4
22.3
.060
.096
.003
.014
Chips / nuts / popcorn
(y)
(n)
835 (42)
1152 (58)
18.5
18.7
21.5
22.0
.065
.083
.002
.011
Snacks
(y)
(n)
489 (25)
1498 (75)
18.5
18.7
21.4
22.0
.062
.080
.004
.008
Soft drink
(not light / sugar-free)
(y)
(n)
1651 (83)
344 (17)
18.6
18.6
21.8
22.2
.074
.081
.006
.016
(-)
(+)
896 (45)
1107 (55)
18.9
18.5
22.1
21.5
.090
.064
.013
.003
Food Availability at Home Index (FAHI) b,c
Smoking at home
Never
Sometimes
Always
1579 (80)
266 (13)
139 (7)
19.2
18.7
18.6
22.9
21.9
21.9
.106
.082
.073
.008
.004
.008
Drinking at home
Never
Sometimes
Always
536 (27)
1291 (65)
172 (9)
19.1
18.6
18.6
22.8
21.7
22.0
.094
.067
.089
.006
.003
.016
Statements relationship parents
d
“My parents are interested in what I do
or what I am concerned with”
(+)
(-)
1902 (95)
93 (5)
18.6
19.1
21.8
22.3
.074
.111
.006
.033
“My parents give me a compliment
when I do good”
(+)
(-)
1856 (93)
140 (7)
18.6
18.9
21.9
22.7
.073
.113
.007
.015
“My parents are strict”
(+)
(-)
512 (26)
1467 (74)
18.4
18.7
21.4
22.0
.058
.083
.004
.009
“I am generally satisfied about
my relationship with my mother”
(+)
(-)
1816 (92)
167 (8)
18.6
18.7
21.9
21.8
.075
.077
.007
.006
“I am generally satisfied about
my relationship with my father”
(+)
(-)
1765 (90)
205 (10)
18.6
18.9
21.9
22.1
.073
.093
.006
.016
Parenting style
Authorative
Authoritarian
Indulgent
Neglectful
479
32
1405
60
(24)
(2)
(71)
(3)
18.4
18.6
18.7
19.4
21.4
21.5
22.0
24.9
.060
.031
.080
.158
.004
.007
.053
Happiness
at home e
Mean or lower
Above mean
810 (41)
1186 (59)
18.8
18.5
22.1
21.8
.087
.068
.010
.005
Note: a categories “Much wealthier” and “Wealthier” were aggregated into “(Much) Wealthier”, and “Much less
wealthy” and “less wealthy” into “(Much) Less wealthy”. b mean or lower versus above mean. c descriptive
statistics (mean (SD); 95%CI; min-max): 5.66(3.25); 5.51-5.80; 0-10. A higher score indicates a higher availability
at will of unhealthy food at home. d (totally) agree versus (totally) disagree. e descriptive statistics (mean (SD);
95%CI; min-max): 8.50(1.44); 8.43-8.56; 0-10.
35
3.3.5
About school
Table 16 School environment, BMI, overweight and obesity
Variable
Category
BMI
Value
th
Mean
90
overweight
obese
Usual travel mode
to school
Walking
Cycling
Public transport / school bus
Car (as passenger)
32
1692
264
13
(2)
(85)
(13)
(1)
19.2
18.6
19.0
20.5
22.0
21.8
22.9
-
.067
.069
.117
.222
.033
.006
.004
.222
Travel time to
a
school
Mean or lower
Above mean
1192 (60)
803 (40)
18.6
18.7
21.9
21.9
.080
.070
.011
.003
School
performance
Very good
Good
Satisfactory
Unsatisfactory
Very unsatisfactory
(14)
(49)
(28)
(9)
(1)
18.5
18.5
18.7
19.1
18.8
21.6
21.6
22.2
22.7
21.6
.076
.064
.078
.136
.111
.015
.006
.006
.006
.000
Teased at school
Never
Sometimes
Often
1668 (83)
285 (14)
45 (2)
18.6
18.7
19.4
21.7
22.6
24.1
.066
.118
.195
.004
.018
.049
Food availability
at school
Milk
(y)
(n)
1507 (76)
488 (24)
18.6
18.4
21.8
21.9
.072
.085
.005
.012
Fruit
(y)
(n)
99 (5)
1883 (95)
18.4
18.6
21.4
21.9
.042
.077
.010
.007
Healthy sandwiches
(y)
(n)
658 (33)
1327 (67)
18.3
18.7
21.3
22.0
.061
.083
.009
.006
Biscuit
(y)
(n)
1333 (67)
658 (33)
18.6
18.5
21.9
21.5
.077
.070
.007
.006
Candy / chocolate
(y)
(n)
1946 (97)
55 (3)
18.6
18.4
21.8
22.6
.075
.098
.007
-
Snacks
(y)
(n)
830 (45)
1156 (58)
18.2
18.8
21.3
22.2
.054
.091
.006
.008
Soft / energy drinks
(y)
(n)
1943 (97)
56 (3)
18.6
18.1
21.8
22.1
.075
.092
.007
-
Biscuit
(y)
(n)
1932 (97)
68 (3)
18.6
18.7
21.8
22.2
.075
.078
.007
.015
Candy / chocolate
(y)
(n)
1949 (97)
50 (3)
18.6
18.4
21.8
22.3
.075
.085
.007
-
Snacks
(y)
(n)
1836 (92)
163 (8)
18.6
18.5
21.8
21.9
.075
.076
.006
.019
Soft / energy drinks
(y)
(n)
1952 (98)
46 (2)
18.6
18.4
21.8
22.2
.076
.066
.007
-
Food availability
near school
275
970
557
173
21
Usual destination
after school
Home
To a friend’s home
Hang around with friends
Other place / activity b
1780
87
95
36
(89)
(4)
(5)
(2)
18.6
18.6
18.4
19.3
21.9
21.4
21.6
23.7
.076
.049
.083
.139
.007
.056
Home after
school
Mother only
Father only
Both
Neither
1381
70
305
234
(69)
(4)
(15)
(12)
18.6
17.8
18.6
18.9
21.8
20.6
21.9
22.3
.075
.030
.075
.089
.006
.015
.007
.009
36
Variable
Category
Happiness
at school c
Value
Mean or lower
Above mean
BMI
782 (39)
1216 (61)
th
Mean
90
18.7
18.6
22.0
21.8
overweight
obese
.085
.070
.012
.004
Note: descriptive statistics: mean (SD); 95%CI; min-max. a 31.8(21.5); 30.8-32.7; 1-120 [maximized]. b relatives,
baby-sitter, after-school centre, sports or hobby club, job. c 7.66(1.43); 7.59-7.72; 0-10
3.3.6
Table 17 Leisure time, BMI, overweight and obesity
Variable
Category
Value
BMI
th
overweight
obese
Mean
90
16 (1)
232 (12)
1746 (88)
19.5
18.8
18.6
25.7
22.6
21.8
.143
.100
.072
.071
.009
.007
(-)
(+)
1131 (57)
864 (43)
18.6
18.7
21.8
22.0
.070
.084
.007
.008
(-)
(+)
1370 (69)
624 (31)
18.6
18.7
21.8
22.1
.074
.082
.005
.012
… TV, video, DVD a,d
(-)
(+)
1036 (52)
958 (48)
18.7
18.6
22.0
21.8
.079
.073
.003
.012
… PC, web, games a,e
(-)
(+)
1057 (53)
938 (47)
18.6
18.6
21.8
22.0
.071
.082
.006
.009
… Phone, SMS a,f
(-)
(+)
791 (40)
1204 (60)
18.6
18.7
21.9
21.9
.083
.072
.005
.009
… Play (sports)
(-)
965 (48)
18.9
22.7
.103
.010
(+)
1031 (52)
18.4
21.3
.051
.005
(-)
(+)
975 (49)
1017 (51)
18.7
18.5
22.0
21.7
.076
.076
.007
.007
Number of good
friends
None
One or two
Three or more
Weekly time
spent on…
… homework a,b
… reading
outside
a,c
a,g
… Other hobby’s
a,h
Member of sports
club i
No
Individual sport
Team sport
Both
835
573
465
100
(42)
(29)
(24)
(5)
18.9
18.5
18.3
18.3
22.3
21.8
21.3
21.2
.098
.064
.053
.053
.010
.004
.002
.021
Weekly hours
training j,k
Mean or lower
Above mean
810 (71)
324 (29)
18.5
18.3
21.6
20.9
.067
.039
.006
-
Participate in
competition j
No
Yes
339 (30)
797 (70)
18.6
18.3
21.8
21.3
.060
.058
.009
.003
(-)
(+)
946 (47)
1059 (53)
19.0
18.3
22.8
21.3
.107
.048
.013
.002
“When I play sports, that is because
I enjoy it”
(+)
(-)
1875 (95)
95 (5)
18.6
18.9
21.8
23.1
.073
.116
.006
.023
I want to keep fit”
(+)
(-)
1798 (91)
169 (9)
18.6
18.1
21.9
21.2
.077
.044
.006
.006
I want to look good”
(+)
(-)
1423 (73)
538 (27)
18.6
18.4
21.8
21.8
.077
.070
.007
.007
Physical Activity Index (PAI)
a,l
Statements exercising m
37
Variable
Category
Value
BMI
th
Mean
90
overweight
obese
I meet friends then”
(+)
(-)
1316 (67)
650 (33)
18.5
18.7
21.7
22.0
.075
.076
.003
.014
I want to become one of the best”
(+)
(-)
599 (31)
1358 (69)
18.3
18.7
21.2
22.0
.068
.079
.007
.006
my parents oblige me”
(+)
(-)
185 (9)
1777 (91)
18.7
18.6
22.1
21.8
.083
.074
.007
Statements leisure time
“In my leisure time I am alone” n
“In my leisure time I am bored” n
Happiness
leisure time o
(Very) Often
Sometimes
Rarely
Never
200
772
760
225
(11)
(39)
(38)
(11)
18.7
18.8
18.5
18.6
22.3
22.1
21.5
22.0
.086
.088
.059
.080
.010
.009
.004
.009
(Very) Often
Sometimes
Rarely
Never
103
635
798
432
(5)
(32)
(41)
(22)
19.8
18.7
18.5
18.7
24.2
22.0
21.5
22.0
.130
.084
.061
.079
.050
.003
.007
.005
827 (42)
1150 (58)
18.8
18.5
22.5
21.5
.099
.060
.007
.007
Mean or lower
Above mean
Note: descriptive statistics (mean (SD); 95%CI; min-max). a mean or lower versus above mean. b 5.71(3.76);
5.55-5.88; 0-18. c 4.08(3.80); 3.91-4.25; 0-18. d 8.08(3.80); 7.83-8.32; 0-18. e 8.35(5.65); 8.10-8.59; 0-18.
e
3.51(3.84); 3.34-3.67; 0-18. f 8.88(5.46); 8.63-9.13; 0-18. g 7.97(5.40); 7.73-8.20; 0-18. i comparable to
national figures for this age group (SCP 2003). j members only. k 4.19(4.49); 3.93-4.46; 0-60. l 6.42(2.91); 6.30m
n
6.50; 0-10. (totally) agree versus (totally) disagree. categories “Very often” and “Often” were aggregated into
o
“(Very) Often”. 8.59(1.19); 8.54-8.64; 2-10.
3.3.7
About what you eat
Table 18 Eating behaviour, BMI, overweight and obesity
Variable
Category
BMI
Value
th
Mean
90
overweight
obese
Eating in-between meals… (what)
…biscuit
(Almost) Never
Once or twice per week
Regularly, but not daily
Daily
250
369
555
809
(13)
(19)
(28)
(41)
19.2
18.7
18.6
18.4
22.9
22.1
22.1
21.3
.115
.088
.079
.054
.021
.011
.004
.004
… candy or
chocolate
(Almost) Never
Daily
211
485
626
657
(11)
(25)
(32)
(33)
19.4
19.1
18.3
18.3
23.4
22.2
21.3
21.3
.140
.095
.057
.059
.020
.009
.005
.005
… chips, nuts or
popcorn
(Almost) Never
Daily
336
1036
448
156
(17)
(52)
(23)
(8)
19.0
18.6
18.4
18.3
22.6
21.8
21.8
21.1
.111
.065
.078
.054
.012
.007
.005
.007
… snacks
(Almost) Never
Daily
721
1068
152
37
(36)
(54)
(8)
(2)
18.9
18.5
18.5
18.1
22.1
21.6
21.6
21.0
.093
.064
.085
.029
.013
.004
.029
38
Variable
Category
Value
BMI
th
Mean
90
overweight
obese
Eating in-between meals… (where)
…on the way to or
from school
(Almost) Never
Daily
1568
215
105
57
(81)
(11)
(5)
(3)
18.7
18.5
18.1
18.6
22.0
21.2
21.3
2.9
.079
.054
.061
.057
.007
.010
.019
… during breaks
at school
(Almost) Never
Daily
336
510
385
742
(17)
(26)
(20)
(38)
19.1
18.5
18.6
18.5
22.9
21.6
21.8
21.4
.116
.060
.079
.063
.016
.011
.006
… when coming
home from
school
(Almost) Never
Daily
131
328
561
947
(7)
(17)
(29)
(48)
18.7
18.9
18.7
18.5
22.0
22.2
22.3
21.5
.082
.086
.091
.061
.016
.009
.008
… when watching
TV or behind
computer
(Almost) Never
Daily
706
536
448
264
(36)
(27)
(23)
(14)
18.8
18.9
18.3
18.1
21.9
22.7
21.5
2.9
.072
.109
.053
.051
.008
.008
.002
.012
… in the street,
downtown
(Almost) Never
Daily
1158
491
247
67
(59)
(25)
(13)
(3)
18.7
18.6
18.4
18.0
21.9
21.8
21.7
21.0
.081
.064
.065
.063
.004
.011
.009
.016
… at the sports
club
(Almost) Never
Daily
1321
382
186
71
(67)
(19)
(9)
(4)
18.8
18.4
18.2
18.1
22.0
21.7
2.6
21.2
.083
.063
.052
.058
.009
.006
.014
… breakfast
(Almost) Never
Daily
156
147
155
1517
(8)
(7)
(8)
(77)
19.2
18.7
18.6
18.6
22.9
22.3
21.8
21.8
.134
.086
.083
.067
.013
.007
.008
… lunch
(Almost) Never
Daily
91
167
250
1467
(5)
(8)
(13)
(74)
19.1
18.8
18.5
18.6
23.6
21.9
22.0
21.8
.153
.076
.072
.072
.012
.006
.013
.006
… dinner, with the
family at the
dining table
(Almost) Never
Daily
70
75
120
1707
(4)
(4)
(6)
(87)
19.1
18.5
18.4
18.6
23.6
22.3
21.5
21.8
.138
.087
.061
.073
.009
… milk
(Almost) Never
Daily
433
219
332
990
(22)
(11)
(17)
(50)
18.6
18.8
18.9
18.5
22.0
22.1
22.0
21.6
.092
.072
.083
.068
.002
.014
.010
.007
… soft drink
(not light /
sugar-free)
(Almost) Never
Daily
262
484
456
770
(13)
(25)
(23)
(39)
19.1
18.8
18.5
18.4
22.6
22.0
22.0
21.3
.112
.069
.077
.067
.016
.009
.009
.003
Eating meals…
39
Variable
Category
Value
BMI
th
Mean
90
overweight
obese
… fruit
(Almost) Never
Daily
158
376
630
803
(8)
(19)
(32)
(41)
18.5
18.6
18.8
18.6
21.4
21.8
22.0
21.9
.073
.069
.087
.070
.003
.013
.007
… vegetables
(Almost) Never
Daily
54
145
584
1186
(3)
(7)
(30)
(60)
18.8
18.9
18.6
18.6
22.8
21.9
21.9
21.9
.148
.068
.066
.078
.019
.015
.009
.005
Healthy Eating Index (HEI) a,b
(-)
(+)
1136 (57)
843 (43)
18.7
18.5
22.1
21.6
.086
.061
.007
.007
Unhealthy Eating Index (UEI) a,c
(-)
(+)
1064 (54)
924 (46)
18.9
18.3
22.2
21.2
.089
.059
.013
.001
Note: descriptive statistics (mean (SD); 95%CI; min-max). a mean or lower versus above mean. b 8.11(2.11);
c
8.02-8.20; 0-10. A higher score indicates more healthy eating. 4.69(2.62); 4.58-4.81; 0-10. A higher score
indicates more unhealthy eating.
3.3.8
About money
Table 19 Money, BMI, overweight and obesity
Variable
Category
BMI
Value
th
Mean
90
overweight
obese
Monthly allowance
a
from parents
Mean or lower
Above mean
1477 (77)
450 (23)
18.6
18.9
21.8
22.3
.071
.098
.007
.009
Monthly earnings b
Mean or lower
Above mean
1312 (70)
552 (30)
18.5
19.1
21.7
22.3
.075
.087
.010
.004
Do your parents let Yes
you decide where Largely
you spend your
Sometimes
money on?
No
577
1039
329
37
(29)
(52)
(17)
(2)
18.6
18.7
18.5
18.8
21.5
22.1
21.8
23.0
.058
.086
.070
.088
.005
.010
.029
Are you allowed to
spend it on candy
or snacks?
No
Yes
756 (38)
1208 (62)
18.7
18.5
22.3
21.5
.098
.061
.012
.004
Do you save?
No
Yes
269 (14)
1712 (86)
18.8
18.6
21.5
21.9
.063
.078
.008
.007
Mean or lower
Above mean
1190 (74)
418 (26)
18.5
18.9
21.8
22.2
.077
.082
.006
.007
Monthly savings
c,d
Savings purpose
c
Specific objective
(n)
(y)
910 (53)
792 (47)
18.6
18.5
21.9
21.9
.076
.078
.009
.005
Money to fall back on
(n)
(y)
720 (42)
982 (58)
18.5
18.6
21.9
21.8
.076
.077
.010
.005
Just what I have left
(n)
(y)
1234 (73)
468 (27)
18.6
18.5
22.0
21.7
.083
.060
.008
.004
My parents oblige me
(n)
(y)
1533 (90)
169 (10)
18.5
18.6
21.8
22.2
.075
.092
.006
.012
40
Variable
Monthly amount
spent on…
Category
Value
BMI
th
Mean
90
overweight
obese
… candy, biscuits e,f
(-)
(+)
1245 (64)
705 (36)
18.5
18.8
21.8
22.1
.070
.082
.008
.007
… snacks e,g
(-)
(+)
1302 (67)
629 (33)
18.6
18.7
21.9
21.7
.074
.077
.010
.002
(-)
(+)
1752 (91)
167 (9)
18.6
19.0
21.9
22.3
.075
.082
.008
.006
… cigarettes e,i
(-)
(+)
1819 (95)
96 (5)
18.6
19.2
21.9
22.9
.074
.101
.007
.011
… clothing, shoes e,j
(-)
(+)
1559 (82)
352 (18)
18.6
18.8
21.8
22.1
.074
.081
.008
.006
… CD’s, DVD’s e,k
(-)
(+)
1525 (80)
390 (20)
18.6
18.7
21.7
22.3
.070
.097
.005
.016
… cosmetics e,l
(-)
(+)
1447 (75)
473 (25)
18.6
18.8
21.8
22.1
.077
.069
.007
.009
… mobile phone e,m
(-)
(+)
1313 (68)
614 (32)
18.6
18.8
21.8
22.2
.075
.079
.009
.005
… alcoholic drinks
e,h
Note: descriptive statistics (mean (SD); 95%CI; min-max). a 23.50(29.39); 22.19-24.82; 0-500. b 23.98(53.36);
21.55-26.40; 0-1000. c savers only. d 25.73(34.84); 24.04-27.43; 0-500. Monthly earnings from allowance and
jobs, proportion that indicated to save, and the amount saved per month are comparable to national averages
reported by the Dutch National Institute for Budget Information (NIBUD 2005). e mean or lower versus above
f
g
h
i
mean. 2.78(4.04); 2.60-2.96; 0-50. 1.74(7.71); 1.40-2.08; 0-300. 0.72(4.33); 0.53-0.91; 0-100. 0.66(5.02);
0.43-0.88; 0-120. j 10.2(44.3); 8.22-12.2; 0-1500. k 3.12(16.8); 2.36-3.87; 0-600. l 2.46(6.08); 2.19-2.74; 0-100.
m
5.77(10.9); 5.28-6.26; 0-160
41
References
Ackard DM, Neumark-Sztainer D, Story M, Perry C. Overeating among adolescents: prevalence and associations
with weight-related characteristics and psychological health. Pediatrics 2003;111(1):67-74
Ackard DM, Neumark-Sztainer D, Story M, Perry C. Parent-child connectedness and behavioral and emotional
health among adolescents. Am J Prev Med 2006;30(1):59-66
Adams K, Sargent RG, Thompson SH, Richter D, Corwin SJ, Rogan TJ. A Study of Body Weight Concerns and
Weight Control Practices of 4th and 7th Grade Adolescents. Ethnicity and Health 2000;5(1):79-94
Anderson PM, Butcher KF. Reading, writing and raisinets: are school finances contributing to children's obesity?
Working paper 11177. Cambridge, MA: NBER, 2005
Averett Sl, Korenman S. The Economic Reality of The Beauty Myth. Journal of Human Resources
1996;31(2):304-330
Ball K, Crawford D, Kenardy J. Longitudinal relationships among overweight, life satisfaction, and aspirations in
young women. Obes Res 2004;12(6):1019-1030
Bekkers R, ND de Graaf. Shifting backgrounds of participation in voluntary associations in the Netherlands. Mens
& Maatschappij 2002;77(4): 338-360
Bekkers R. Giving and volunteering in the Netherlands: sociological and psychological perspectives. Utrecht: PhD
dissertation. 2004
Bekkers R. Participation in voluntary associations: relations with resources, personality and political values.
Political Psychology 2005;26(3): 439-454
Bell AC, Kremer PJ, Magarey AM, Swinburn BA. Contribution of 'noncore' foods and beverages to the energy
intake and weight status of Australian children. Eur J Clin Nutr 2005;59(5):639-645
Bell AC, Swinburn BA. What are the key food groups to target for preventing obesity and improving nutrition in
schools? Eur J Clin Nutr 2004;58(2):258-263
Berkey CS, Rockett HR, Field AE, Gillman MW, Colditz GA. Sugar-added beverages and adolescent weight
change. Obes Res 2004;12(5):778-788
Berkey CS, Rockett HRH, Gillman MW, Colditz GA. One-year changes in activity and inactivity among 10- to 15year-old boys and girls: relationship to change in body mass index. Pediatrics 2003;111(4):836-843 [2003a]
Berkey CS, Rockett HRH, Gillman MW, Field AE, Colditz GA. Longitudinal study of skipping breakfast and weight
change in adolescents. Int J Obes Relat Metab Disord 2003;27(10):1258-1266 [2003b]
Black DR, Taylor AM, Coster DC. Accuracy of self-reported body weight: Stepped Approach Model component
assessment. Health Educ Res 1998;13(2):301-307
Blaylock J, Smallwood D, Kassel K, Variyam J, Aldrich L. Economics, food choices, and nutrition. Food Policy
1999;24(2-3):269-286
Bogg T, Robberts BW. Conscientiousness and health-related behaviors: a meta-analysis of the leading
behavioural contributors to mortality. Psychological Bulletin 2004;130(6): 887-919
Borghans L, Golsteyn BH. Time discounting and the body mass index. Evidence from the Netherlands. Econ Hum
Biol 2006;4(1):39-61
Bosch J, Stradmeijer M, Seidell J. Psychosocial characteristics of obese children/youngsters and their families:
implications for preventive and curative interventions. Patient Educ Couns 2004;55(3):353-362
Bowling A. Research methods in health: investigating health and health services. Buckinham: Open University
Press, 1997
Boynton-Jarrett R, Thomas TN, Peterson KE, Wiecha J, Sobol AM, Gortmaker SL. Impact of television viewing
patterns on fruit and vegetable consumption among adolescents. Pediatrics 2003;112(6):1321-1326
Braet C, Ipema J. Conflicts in adolescence. Is there a relationship between emotional eating and emotional eating
in obese youngsters? Int J Adolesc Med Health 1997;9(2):123-133
Bray GA, Champagne CM. Beyond energy balance: there is more to obesity than kilocalories. J Am Diet Assoc
2005;105(5 Suppl 1):S17-S23
Brener ND, Eaton DK, Lowry R, McManus T. The association between weight perception and BMI among high
school students. Obes Res 2004;12(11):1866-1874
Brener ND, Kann L, McManus T, Kinchen SA, Sundberg EC, Ross JG. Reliability of the 1999 youth risk behavior
survey questionnaire. J Adolesc Health 2002;31(4):336-342
43
Brener ND, Mcmanus T, Galuska DA, Lowry R, Wechsler H. Reliability and validity of self-reported height and
weight among high school students. J Adolesc Health 2003;32(4):281-287
Brouwer WBF, NJA van Exel. Expectations regarding length and health related quality of life: some empirical
findings. Soc Sci Med 2005;61(5): 1083-1094
Brown SR. Political Subjectivity: Applications of Q-methodology in political science. Yale University Press. 1980.
Brug J, Van Lenthe F (eds). Environmental determinants and interventions for physical activity, nutrition and
smoking: a review. Rotterdam: Erasmus MC, 2005
Bulk-Bunschoten AMW, Renders CM, van Leerdam FJM, HiraSing RA. Signaleringsprotocol overgewicht in de
jeugdgezondheidszorg. Amsterdam: VUMC, 2004
Cauffman E, Steinberg L. (Im)maturity of judgment in adolescence: why adolescents may be less culpable than
adults. Behavioral Sciences & the Law 2000;18(6):741-760
CBS. Jaarboek onderwijs in cijfers 2006. Voorburg/Heerlen: Centraal Bureau voor de Statistiek, 2005.
Chen EY, Brown M. Obesity stigma in sexual relationships. Obes Res 2005;13(8):1393-1397
Chou SY, Grossman M, Saffer H. An economic analysis of adult obesity: results from the Behavioral Risk Factor
Surveillance System. J Health Econ 2004;23(3):565-587
Classen T, Hokayem C. Childhood influences on youth obesity. Econ Hum Biol 2005;3(2):165-187
Cohane GH, Pope HG. Body image in boys: A review of the literature. Int J Eat Disord 2001;29(4):373-379
Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity
worldwide: international survey BMJ 2000;320:1240
Cooke LJ, Wardle J, Gibson EL, Sapochnik M, Sheiham A, Lawson M. Demographic, familial and trait predictors
of fruit and vegetable consumption by pre-school children. Public Health Nutr. 2004 Apr;7(2):295-302
Courtenay WH. Key Determinants of the Health and Well-Being of Men and Boys. International Journal of Men’s
Health 2003;2(1):1-27
Craeynest M, Crombez G, De Houwer J, Deforche B, Tanghe A, De Bourdeaudhuij I. Explicit and implicit attitudes
towards food and physical activity in childhood obesity. Behav Res Ther 2005;43(9):1111-1120
Cross RM. Exploring attitudes: the case for Q methodology. Health Education Research 2005;20(2): 206-213.
Daniels SR, Arnett DK, Eckel RH, Gidding SS, Hayman LL, Kumanyika S, Robinson TN, Scott BJ, St Jeor S,
Williams CL. Overweight in children and adolescents: pathophysiology, consequences, prevention and
treatment. Circulation 2005;111:1999-2012
Darling N, Steinberg L. Parenting style as context: an integrative model. Psychological Bulletin 1993;113(3):487496
Davis C, Levitan RD, Muglia P, Bewell C, Kennedy JL. Decision-making deficits and overeating: a risk model for
obesity. Obes Res 2004;12(6):929-935
De Bruijn GJ, Kremers SP, Schaalma H, van Mechelen W, Brug J. Determinants of adolescent bicycle use for
transportation and snacking behavior. Prev Med 2005;40(6):658-667 [2005a]
De Bruijn GJ, Kremers SP, van Mechelen W, Brug J. Is personality related to fruit and vegetable intake and
physical activity in adolescents? Health Educ Res 2005;20(6): 635-644 [2005b]
De Graaf G, WBF Brouwer, NJA van Exel. Beelden van de eigen gezondheid bij jongeren in klas 1 en 2 van het
voortgezet onderwijs: Een Q methodologisch onderzoek. TSG 2006;84(4): 215-222
De Graaf ND, De Graaf PM, Kraaykamp G & Ultee WC. Familie Enquête Nederlandse Bevolking. Nijmegen:
datafile. 2000.
De Vries H, Lechner L, Mudde A. Sekseverschillen in determinanten van leefstijl-gedragingen in Nederland. TSG
2002;80(4):237-246
Dietz WH. Health consequences of obesity in youth: childhood predictors of adult disease. Pediatrics
1998;101:518-525
Dietz WH. The obesity epidemic in young children: reduce television viewing and promote playing. BMJ
2001;322:313-314
Dohmen T, Falk A, Huffman D, Sunde U, Schupp J, Wagner G. Five facts about risk attitudes: evidence from a
large, representative, experimentally-validated survey. Draft discussion paper. Bonn: IZA, 2005 [2005b]
Dohmen T, Falk A, Huffman D, Sunde U, Schupp J, Wagner G. Individual risk attitudes: new evidence from a
large, representative, experimentally-validated survey. Discussion paper 1730. Bonn: IZA, 2005 [2005a]
44
Edmunds L, Waters E, Elliott EJ. Evidence based management of childhood obesity. BMJ 2001;323:916-919
Eisenberg ME, Neumark-Sztainer D, Story M. Associations of weight-based teasing and emotional well-being
among adolescents. Arch Pediatr Adolesc Med 2003;157(8):733-738
Eisenberg ME, Olson RE, Neumark-Sztainer D, Story M, Bearinger LH. Correlations between family meals and
psychosocial well-being among adolescents. Arch Pediatr Adolesc Med 2004;158(8):792-796
Eisenmann JC, Bartee RT, Wang MQ. Physical activity, TV viewing, and weight in US youth: 1999 Youth Risk
Behavior Survey. Obesity Research 2002;10(5):379-385
Elgar FJ, Roberts C, Moore L, Tudor-Smith C. Sedentary behaviour, physical activity and weight problems in
adolescents in Wales. Public Health 2005;119(6):518-524
Elgar FJ, Roberts C, Tudor-Smith C, Moore L. Validity of self-reported height and weight and predictors of bias in
adolescents. J Adolesc Health 2005;37(5):371-375
Elkins WL, Cohen DA, Koralewicz LM, Taylor SN. After school activities, overweight, and obesity among inner city
youth. J Adolesc 2004;27(2):181-189
Erickson SJ, Robinson TN, Haydel KF, Killen JD. Are overweight children unhappy?: Body mass index,
depressive symptoms, and overweight concerns in elementary school children. Arch Pediatr Adolesc Med
2000;154(9):931-935
Evenson KR, Huston SL, McMillen BJ, Bors P, Ward DS. Statewide prevalence and correlates of walking and
bicycling to school. Arch Pediatr Adolesc Med 2003;157(9):887-892
Faith MS, Berman N, Heo M, Pietrobelli A, Gallagher D, Epstein LH, Eiden MT, Allison DB. Effects of contingent
television on physical activity and television viewing in obese children. Pediatrics 2001;107(5):1043-1048
Faith MS, Leone MA, Ayers TS, Heo M, Pietrobelli A. Weight criticism during physical activity, coping skills, and
reported physical activity in children. Pediatrics 2002;110(2 Pt 1):e23
Fallon EM, Tanofsky-Kraff M, Norman AC, McDuffie JR, Taylor ED, Cohen ML, Young-Hyman D, Keil M, Kolotkin
RL, Yanovski JA. Health-related quality of life in overweight and nonoverweight black and white adolescents. J
Pediatr 2005;147(4):443-450
Ferreita I, Van der Horst K, Wendel-Vos W, Kremers S, Van Lenthe F, Brug J. Potential environmental
determinants of physical activity in youth. In: Brug J, Van Lenthe F (eds), 2005
Finke MS, Huston SJ. Factors Affecting the Probability of Choosing a Risky Diet. Journal of Family and Economic
Issues 2003;24(3):291-303
Flegal KM, Graubard BI, Williamson DF, Gail MH. Excess deaths associated with underweight, overweight, and
obesity. JAMA 2005;293(15):1861-1867
Flegal KM, Troiano RP, Pamuk ER, Kuczmarski RJ, Campbell SM. The influence of smoking cessation on the
prevalence of overweight in the United States. N Engl J Med 1995;333(18):1165-1170
Flood V, Webb K, Lazarus R, Pang G. Use of self-report to monitor overweight and obesity in populations: some
issues for consideration. Aust N Z J Public Health 2000;24(1):96-99
Fonseca H, Gaspar de Matos M. Perception of overweight and obesity among Portuguese adolescents: an
overview of associated factors. Eur J Public Health 2005;15(3):323-328
Fonseca H, Ireland M, Resnick MD. Familial correlates of extreme weight control behaviors among adolescents.
Int J Eat Disord 2002;32(4):441-448
Forshee RA, Anderson PA, Storey ML. The role of beverage consumption, physical activity, sedentary behavior,
and demographics on body mass index of adolescents. Int J Food Sci Nutr 2004;55(6):463-478
Forshee RA, Storey ML, Ginevan ME. A risk analysis model of the relationship between beverage consumption
from school vending machines and risk of adolescent overweight. Risk Anal 2005;25(5):1121-1135
Forshee RA, Storey ML. Total beverage consumption and beverage choices among children and adolescents. Int
J Food Sci Nutr 2003;54(4):297-307
Fortenberry JD. Reliability of adolescents' reports of height and weight. J Adolesc Health 1992;13(2):114-117
Fouts G, Burggraf K. Television Situation Comedies: Female Weight, Male Negative Comments, and Audience
Reactions. Sex Roles 2000;42(9-10):925-932
Fouts G, Vaughan K. Television Situation Comedies: Male Weight, Negative References, and Audience
Reactions. Sex Roles 2002;46(11-12):439-442
French SA, Story M, Fulkerson JA, Gerlach AF. Food environment in secondary schools: a la carte, vending
machines, and food policies and practices. Am J Public Health 2003;93(7):1161-1167
45
French SA, Story M, Neumark-Sztainer D, Fulkerson JA, Hannan P. Fast food restaurant use among adolescents:
associations with nutrient intake, food choices and behavioral and psychosocial variables. Int J Obes Relat
Metab Disord 2001;25(12):1823-1833
Friedlander SL, Larkin EK, Rosen CL, Palermo TM, Redline S. Decreased quality of life associated with obesity in
school-aged children. Arch Pediatr Adolesc Med 2003;157(12):1206-1211
Friedman MA, Brownell KD. Psychological correlates of obesity: moving to the next research generation. Psychol
Bull 1995;117(1):3-20
Friestad C, Klepp KI. Socioeconomic status and health behaviour patterns through adolescence: results from a
prospective cohort study in Norway. Eur J Public Health 2006;16(1):41-47
Galan I, Gandarillas A, Febrel C, Meseguer C. Validation of self-reported weight and height in an adolescent
population. Gac Sanit 2001;15(6):490-497
Gardner M, Steinberg L. Peer influence on risk taking, risk preference, and risky decision making in adolescence
and adulthood: an experimental study. Dev Psychol 2005;41(4):625-635
Gerris JRM, Houtmans MJM, Kwaaital-Roosen EMG, Schipper JC, Vermulst AA, Janssens JMAM. Parents,
adolescents and young adults in Dutch families: a longitudinal study. Nijmegen: Institute of Family Studies,
University of Nijmegen. 1998
Giammattei J, Blix G, Marshak HH, Wollizer AO, Pettitt DJ. Television watching and soft drink consumption:
associations with obesity in 11- to 13-year-old schoolchildren. Arch Pediatr Adolesc Med 2003;157:882-886
Gilliland FD, Berhane K, Islam T, McConnell R, Gauderman WJ, Gilliland SS, Avol E, Peters JM. Obesity and the
risk of newly diagnosed asthma in school-aged children. Am J Epidemiol 2003;158(5):406-415
Goldberg LR. The development of markers for the Big-Five factor structure. Psychological Assessment
1992;4:26-42
Gordon-Larsen P, Adair LS, Popkin BM. Ethnic differences in physical activity and inactivity patterns and
overweight status. Obes Res 2002;10(3):141-149
Gordon-Larsen P, Nelson MC, Page P, Popkin BM. Inequality in the built environment underlies key health
disparities in physical activity and obesity. Pediatrics 2006;117(2):417-424
Gortmaker SL, Must A, Perrin JM, Sobol AM, Dietz WH. Social and economic consequences of overweight in
adolescence and young adulthood. N Engl J Med 1993;329(14):1008-1012
Gortmaker SL, Must A, Sobol AM, Petterson K, Colditz GA, Dietz WH. Television viewing as a cause of
increasing obesity among children in the United States, 1986-1990. Arch Pediatr Adolesc Med
1996;150(4):356-362
Graham MA, Eich C, Kephart B, Peterson D. Relationship among body image, sex, and popularity of high school
students. Percept Mot Skills 2000;90:1187-1193
Greenberg BS, Eastin M, Hofschire L, Lachlan K, Brownell KD. Portrayals of overweight and obese individuals on
commercial television. Am J Public Health 2003;93(8):1342-1348
Griffin AC, Younger KM, Flynn MA. Assessment of obesity and fear of fatness among inner-city Dublin
schoolchildren in a one-year follow-up study. Public Health Nutr 2004;7(6):729-735
Gruber J, Frakes M. Does falling smoking lead to rising obesity? J Health Econ 2006;25(2):183-197
Guggenheim K, Poznanski R, Kaufmann NA. Attitudes of adolescents to their body build and the problem of
juvenile obesity. Int J Obes 1977;1(2):135-149
Gunnell DJ, Frankel SJ, Nanchahal KH, Peters TJ, Smith GD. Childhood obesity and adult cardiovascular
mortality: a 57-year follow-up study based on the Boyd Orr cohort. Am J Clin Nutr 1998;67:1111-1118
Halpern CT, King RB, Oslak SG, Udry JR. Body mass index, dieting, romance, and sexual activity in adolescent
girls: relationships over time. J Res Adolesc 2005;15(4):535-559
Harrison K. Television viewing, fat stereotyping, body shape standards, and eating disorder symptomatology in
grade school children. Communication Research 2000;27(5):617-640
Hebl MR, Mannix LM. The weight of obesity in evaluating others: a mere proximity effect. Pers Soc Psychol Bull
2003;29(1):28-38
Herpertz-Dahlmann B, Geller F, Bohle C, Khalil C, Trost-Brinkhues G, Ziegler A, Hebebrand J. Secular trends in
body mass index measurements in preschool children from the City of Aachen, Germany. Eur J Pediatr
2003;162(2):104-109
Hill AJ, Silver EK. Fat, friend unhealthy: 9-year old children’s perception of body shape stereotypes. Int J Obes
1995;19:423-430
46
Himes JH, Faricy A. Validity and reliability of self-reported stature and weight of US adolescents. Am J Hum Biol
2001;13(2):255-260
Himes JH, Hannan P, Wall M, Neumark-Sztainer D. Factors associated with errors in self-reports of stature,
weight, and body mass index in Minnesota adolescents. Ann Epidemiol 2005;15(4):272-278
Hirasing RA, Fredriks AM, van Buuren S, Verloove-Vanhorick SP, Wit JM. Increased prevalence of overweight
and obesity in Dutch children, and the detection of overweight and obesity using international criteria and new
reference diagrams. Ned Tijdschr Geneeskd 2001;145(27):1303-1308
Honjo K, Siegel M. Perceived importance of being thin and smoking initiation among young girls. Tob Control
2003;12(3):289-295
Huston SJ, Finke MS. Diet Choice and the Role of Time Preference. Journal of Consumer Affairs 2003;37(1):143160
Inchley JC, Currie DB, Todd JM, Akhtar PC, Currie CE. Persistent socio-demographic differences in physical
activity among Scottish schoolchildren 1990-2002. Eur J Public Health 2005;15(4):386-388
ISLI. Overweight and obesity in European children and adolescents: causes and consequences, prevention and
treatment. Brussels: International Life Sciences Institute Europe. 2000
James J, Thomas P, Clavan D, Kerr D. Preventing childhood obesity by reducing consumption of carbonated
drinks cluster randomised controlled trial. BMJ 2004;328(7450):1237-1240
Jansen W, Van de Looij-Jansen PM, Ferreira I, De Wilde EJ, Brug J. Differences in measured and self-reported
height and weight in Dutch adolescents. Annals of Nutrition and Metabolism, in press
Janssen I, Craig WM, Boyce WF, Pickett W. Associations between overweight and obesity with bullying
behaviours in school-aged children. Pediatrics 2004;113(5):1187-1194
Kan K, Tsai WD. Obesity and risk knowledge. J Health Econ 2004;23(5):907-934
Kelly AM, Wall M, Eisenberg ME, Story M, Neumark-Sztainer D. Adolescent girls with high body satisfaction: who
are they and what can they teach us? J Adolesc Health 2005;37(5):391-396
Klaczynski PA, Goold KW, Mudry JJ. Culture, obesity stereotypes, self-esteem, and the “thin ideal”: a social
identity perspective. Journal of Youth and Adolescence 2004;33(4):307-317
Klein-Hessling J, Lohaus A, Ball J. Psychological predictors of health-related behaviour in children. Psychology,
Health & Medicine 2005;10(1): 31-43
Kobayashi M, Kobayashi M. The relationship between obesity and seasonal variation in body weight among
elementary school children in Tokyo. Econ Hum Biol 2006, in press
Koenker R, Bassett G. Regression quantiles. Econometrica 1978;46(1):33–50
Komlos J, Baur M. From the tallest to (one of) the fattest: the enigmatic fate of the American population in the
20th century. Economics and Human Biology 2004;2:57-74
Komlos J, Smith PK, Bogin B. Obesity and the rate of time preference: is there a connection? J Biosoc Sci
2004;36(2):209-219
Kremers SP, Brug J, de Vries H, Engels RC. Parenting style and adolescent fruit consumption. Appetite
2003;41(1):43-50
Kremers SP, De Bruijn GJ, Schaalma H, Brug J. Clustering of energy balance-related behaviours and their
intrapersonal determinants. Psychology and Health 2004;19(5):595-606
Lau RR, Quadrel MJ, Hartman KA. Development and change of young adults' preventive health beliefs and
behavior: influence from parents and peers. J Health Soc Behav 1990;31(3):240-259
Ludwig DS, Peterson KE, Gortmaker SL. Relation between consumption of sugar-sweetened drinks and
childhood obesity: a prospective, observational analysis. Lancet 2001;357:505-508
Lundborg P. Having the wrong friends? Peer effects in adolescent substance use. J Health Econ 2006;25(2):214233
Mair M, Barlow A, Woods SE, Kierans C, Milton B, Porcellato L. Lies, damned lies and statistics? Reliability and
personal accounts of smoking among young people. Soc Sci Med 2006;62(4):1009-1021
Mann L, Harmoni R, Power C. Adolescent decision-making: the development of competence. J Adolesc
1989;12(3):265-278
Manson JE, Bassuk SS. Obesity in the United States: a fresh look at its high toll. JAMA 2003;289:229-230
47
Marshall SJ, Biddle SJ, Gorely T, Cameron N, Murdey I. Relationships between media use, body fatness and
physical activity in children and youth: a meta-analysis. Int J Obes Relat Metab Disord 2004;28(10):12381246.
Martens MK, van Assema P, Brug J. Why do adolescents eat what they eat? Personal and social environmental
predictors of fruit, snack and breakfast consumption among 12-14-year-old Dutch students. Public Health Nutr
2005;8(8):1258-1265
Matheson DM, Hanson KA, McDonald TE, Robinson TN. Validity of children's food portion estimates: a
comparison of 2 measurement aids. Arch Pediatr Adolesc Med 2002;156(9):867-871
Matheson DM, Killen JD, Wang Y, Varady A, Robinson TN. Children’s food consumption during television
viewing. Am J Clin Nutr 2004;79:1088-1094
McCarthy HD, Ellis SM, Cole TJ. Central overweight and obesity in British young aged 11-16 years: cross
sectional surveys of waist circumference. BMJ 2003;326:624-627
McCreary DR, Sadava SW. Gender Differences in Relationships Among Perceived Attractiveness, Life
Satisfaction, and Health in adults as a function of Body Mass Index and perceived weight. Psychology of Men
and Masculinity 2001;2: 108-116
McCreary DR, Sasse DK. An exploration of the drive for muscularity in adolescent boys and girls. J Am Coll
Health 2000;48(6):297-304
McCreary DR. Differences in the Relationship Between Body Mass Index and Perceived Weight: Exploring the
Paradox. International Journal of Men’s Health 2002;1(1):31-42
McMurray RG, Harrell JS, Deng S, Bradley CB, Cox LM, Bangdiwala SI. The influence of physical activity,
socioeconomic status, and ethnicity on the weight status of adolescents. Obesity Research 2000;8(2):130-139
Mellin AE, Neumark-Sztainer D, Story M, Ireland M, Resnick MD. Unhealthy behaviors and psychosocial
difficulties among overweight adolescents: the potential impact of familial factors. J Adolesc Health
2002;31(2):145-153
Mendelson BK, Mendelson MJ, White DR. Body-esteem scale for adolescents and adults. J Pers Assess
2001;76(1):90-106
Mendelson BK, White DR, Mendelson MJ. Self-esteem and body esteem: effects of gender, age and weight. J
Appl Dev Psychol 1996;17:321-346
Mendelson BK, White DR. Relation between body-esteem and self-esteem of obese and normal children. Percept
Mot Skills 1982;54(3):899-905
Millstein SG, Halpern-Felsher BL. Perceptions of risk and vulnerability. J Adolesc Health 2002;31(1 Suppl):10-27
MinOCW. Referentieraming Voortgezet Onderwijs. Den Haag: Ministerie van Onderwijs, Cultuur & Wetenschap,
2006
Myers A, Rosen JC. Obesity stigmatization and coping: relation to mental health symptoms, body image, and selfesteem. Int J Obes Relat Metab Disord 1999;23(3):221-230
Nelson MC, Gordon-Larsen P, Adair LS, Popkin BM. Adolescent physical activity and sedentary behavior:
patterning and long-term maintenance. Am J Prev Med 2005;28(3):259-266
Neumark-Sztainer D, Falkner N, Story M, Perry C, Hannan PJ, Mulert S. Weight-teasing among adolescents:
correlations with weight status and disordered eating behaviors. Int J Obes Relat Metab Disord
2002;26(1):123-131
Neumark-Sztainer D, French SA, Hannan PJ, Story M, Fulkerson JA. School lunch and snacking patterns among
high school students: associations with school food environment and policies. Int J Behav Nutr Phys Act
2005;2(1):14
Neumark-Sztainer D, Hannan PJ, Story M, Croll J, Perry C. Family meal patterns: associations with
sociodemographic characteristics and improved dietary intake among adolescents. J Am Diet Assoc
2003;103(3):317-322
Neumark-Sztainer D, Hannan PJ. Weight-related behaviors among adolescent girls and boys: results from a
national survey. Arch Pediatr Adolesc Med 2000;154(6):569-577
Neumark-Sztainer D, Story M, Resnick MD, Blum RW. Lessons learned about adolescent nutrition from the
Minnesota Adolescent Health Survey. J Am Diet Assoc 1998;98(12):1449-56
Neumark-Sztainer D, Wall M, Story M, Fulkerson JA. Are family meal patterns associated with disordered eating
behaviors among adolescents? J Adolesc Health 2004;35(5):350-359
48
NHS HDA. The management of obesity and overweight: an analysis of diet, physical activity and behavioural
approaches; evidence briefing. London: National Health Service, Health Development Agency. 2003
[www.hda.nhs.uk/evidence]
NIBUD. Nationaal Scholierenonderzoek 2004/2005. Een onderzoek naar inkomsten, uitgaven, baantjes en
omgaan met geld. Utrecht: Nationaal Instituut voor Budgetvoorlichting, 2005
NTFPTO [National Task Force on the Prevention and Treatment of Obesity]. Overweight, obesity and health risk.
Arch Intern Med 2000;160:898-904
Patrick H, Nicklas TA. A review of family and social determinants of children's eating patterns and diet quality. J
Am Coll Nutr 2005;24(2):83-92
Patrick K, Norman GJ, Calfas KJ, Sallis JF, Zabinski MF, Rupp J, Cella J. Diet, physical activity, and sedentary
behaviours as risk factors for overweight in adolescence. Arch Pediatr Adolesc Med 2004;158:385-390
Pesa JA, Syre TR, Jones E. Psychosocial differences associated with body weight among female adolescents:
the importance of body image. J Adolesc Health 2000;26(5):330-337
Pope HG Jr, Olivardia R, Gruber A, Borowiecki J. Evolving ideals of male body image as seen through action
toys. Int J Eat Disord. 1999;26(1):65-72
Popkin BM, Duffey K, Gordon-Larsen P. Environmental influences on food choice, physical activity and energy
balance. Physiol Behav 2005;86(5):603-613
Quadrel MJ, Fischhoff B, Davis W. Adolescent (in)vulnerability. Am Psychol 1993;48(2):102-116
Reilly JJ, Dorosty AR, Emmett PM. Prevalence of overweight and obesity in British children: cohort study. BMJ
1999;319(7216):1039
Reilly JJ, Methven E, McDowell ZC, Hacking B, Alexander D, Stewart L, Kelnar CJH. Health consequences of
obesity. Arch Dis Child 2003;88:748-752
Roberts BP, Blinkhorn AS, Duxbury JT. The power of children over adults when obtaining sweet snacks. Int J
Paediatr Dent 2003;13(2):76-84
Robinson TN. Reducing children’s television viewing to prevent obesity: a randomized controlled trial. JAMA
1999;282 (16):1561-1567
Rõssner S. Childhood obesity and adulthood consequences. Acta Pediatrica 1998;87(1):1-5
Ryan YM, Gibney MJ, Flynn MA. The pursuit of thinness: a study of Dublin schoolgirls aged 15 y. Int J Obes Relat
Metab Disord 1998;22(5):485-487
Sandvik C, De Bourdeaudhuij I, Due P, Brug J, Wind M, Bere E, Perez-Rodrigo C, Wolf A, Elmadfa I, Thorsdottir
I, Vaz de Almeida MD, Yngve A, Klepp KI. Personal, social and environmental factors regarding fruit and
vegetable intake among schoolchildren in nine European countries. Ann Nutr Metab 2005;49(4):255-266
Sanigorski AM, Bell AC, Kremer PJ, Swinburn BA. Lunchbox contents of Australian school children: room for
improvement. Eur J Clin Nutr 2005;59(11):1310-1316
Sarlio-Lahteenkorva S, Parna K, Palosuo H, Zhuravleva I, Mussalo-Rauhamaa H. Weight satisfaction and selfesteem among teenagers in Helsinki, Moscow and Tallinn. Eat Weight Disord 2003;8(4):289-295
Schuit AJ, van Loon AJ, Tijhuis M, Ocke M. Clustering of lifestyle risk factors in a general adult population. Prev
Med 2002;35(3):219-224
Schwimmer JB, Burwinkle TM, Varni JW. Health-related quality of life of severely obese children and adolescents.
JAMA 2003;289(14):1813-1819
SCP. Rapportage Sport. Den Haag: Sociaal Cultureel Planbureau, 2003
Scragg R, Laugesen M, Robinson E. Cigarette smoking, pocket money and socioeconomic status: results from a
national survey of 4th form students in 2000. N Z Med J 2002;115(1158):U108
Seidell JC. Obesity: a growing problem. Acta Pediatr Suppl 1999;88(428):46-50
Skidmore PML, Yarnell JWG. The obesity epidemic: prospects for prevention. QJM 2004;97(12):817-825
Smith PK, Bogin B, Bishai D. Are time preference and body mass index associated? Evidence from the National
Longitudinal Survey of Youth. Econ Hum Biol 2005;3(2):259–270
Smith PK, Bogin B, Varela-Silva MI, Loucky J. Economic and anthropological assessments of the health of
children in Maya immigrant families in the US. Econ Hum Biol 2003;1(2):145-160
Sobal J, Nicolopoulos V, Lee J. Attitudes about overweight and dating among secondary school students. Int J
Obes Relat Metab Disord 1995;19(6):376-381
49
Spurgeon D. Childhood obesity in Canada has tripled in past 20 years. BMJ 2002;324:1416
Staffieri JR. A study of social stereotype of body image in children. J Pers Soc Psychol 1967;7(1):101-104
Stamatakis E, Primatesta P, Chinn S, Rona R, Falascheti E. Overweight and obesity trends from 1974 to 2003 in
English children: what is the role of socioeconomic factors? Arch Dis Child 2005;90(10):999-1004
Steinberg L, Cauffman E. Maturity of judgment in adolescence: Psychosocial factors in adolescent decision
making. Law and Human Behavior 1996;20(3):249-272
Steinberg L. Risk taking in adolescence: what changes, and why? Ann N Y Acad Sci 2004;1021:51-58
Steinberg L. Single parents, stepparents, and the susceptibility of adolescents to antisocial peer pressure. Child
Dev 1987;58(1):269-275
Stephenson W. Correlating persons instead of tests. Character and Personality 1935;4:17-24.
Storey ML, Forshee RA, Waver AR, Sansalone WR. Demographic and lifestyle factors associated with body mass
index among children and adolescents. Int J Food Sci Nutr 2003;54(6):491-503
Stradmeijer M, Bosch J, Koops W, Seidell J. Family functioning and psychosocial adjustment in overweight
youngsters. Int J Eat Disord 2000;27(1):110-114
Strathman A, Gleicher F, Boninger DS, Edwards CS. The consideration of future consequences: Weighing
immediate and distant outcomes of behavior. Journal of Personality and Social Psychology 1994;66: 742-752
Strauss RS, Pollack HA. Social marginalization of overweight children. Arch Pediatr Adolesc Med
2003;157(8):746-752
Strauss RS, Rodzilsky D, Burack G, Colin M. Psychococial correlates of physical activity in healthy children. Arch
Pediatr Adolesc Med 2001;155(8):897-902
Strauss RS. Childhood obesity and self-esteem. Pediatrics 2000;105(1):15-19
Strauss RS. Comparison of measured and self-reported weight and height in a cross-sectional sample of young
adolescents. Int J Obes Relat Metab Disord 1999;23(8):904-908
Sturm R, Datar A. Body mass index in elementary school children, metropolitan area food prices and food outlet
density. Public Health 2005;119(12):1059-1068
Sturm R, Wells KB. Does obesity contribute as much to morbidity as poverty and smoking? Public Health
2001;115:229-235
Swallen KC, Reither EN, Haas SA, Meier AM. Overweight, obesity, and health-related quality of life among
adolescents: the National Longitudinal Study of Adolescent Health. Pediatrics 2005;115(2):340-347
Swinburn B, Egger G, Raza F. Dissecting obesogenic environments: the development and application of a
framework for identifying and prioritizing environmental interventions for obesity. Prev Med 1999;29(6):563570
Swinburn B, Egger G. The runaway weight train: too many accelerators, not enough brakes. BMJ 2004;329:736739
Swinburn BA, Caterson I, Seidell JC, James WP. Diet, nutrition and the prevention of excess weight gain and
obesity. Public Health Nutr 2004;7(1A):123-146
Tiggemann M, Gardiner M, Slater A. "I would rather be size 10 than have straight A's": a focus group study of
adolescent girls' wish to be thinner. J Adolesc 2000;23(6):645-659
Tiggemann M, Slater A. Thin ideals in music television: a source of social comparison and body dissatisfaction.
Int J Eat Disord 2004 Jan;35(1):48-58
TNO. Prevalentie van overgewicht en obesitas bij jeugdigen 4-15 jaar in de periode 2002-2004. Leiden: TNO
Kwaliteit van Leven, 2006
TNO/LUMC. Groeidiagrammen 1-21 jaar meisjes / jongens op basis van groeionderzoek 1997. Bohn Stafleu van
Loghum, 1998. In: Bulk-Bunschoten et al. 2004
Troiano RP, Flegal KM. Overweight children and adolescents: description, epidemiology, and demographics.
Pediatrics 1998;101(3):497-504
Utter J, Neumark-Sztainer D, Jeffery R, Story M. Couch potatoes or french fries: are sedentary behaviors
associated with body mass index, physical activity, and dietary behaviors among adolescents? J Am Diet
Assoc 2003;103(10):1298-1305
Van Assema P, Brug J, Ronda G, Steenhuis I, Oenema A. A short Dutch questionnaire to measure fruit and
vegetable intake: relative validity among adults and adolescents. Nutr Health 2002;16(2):85-106
50
Van der Horst K, Oenema A, Ferreita I, Wendel-Vos W, Giskes K, Brug J. Potential environmental determinants
of selected dietary behaviours in youth. In: Brug J, Van Lenthe F (eds), 2005
Van Exel NJA, B van den Berg, MA Koopmanschap, GAM van den Bos, WBF Brouwer. Informele zorg: een goed
om te waarderen. TSG 2004;82(4): 236-242
Van Exel NJA, G de Graaf, WBF Brouwer. “Everyone dies, so you might as well have fun!” Attitudes of youths
about their health lifestyle. SSM 2006, in press
Van Exel NJA, G de Graaf, WBF Brouwer. Beelden van de eigen gezondheid onder jongeren: Een Qmethodologisch onderzoek onder leerlingen in klas 1 en 2 van het voortgezet onderwijs. IMTA report 05.77
(www.imta.nl/publications/0577.html). Rotterdam: Erasmus MC, iMTA. 2005
Van Exel NJA, G de Graaf. Q-methodology: A sneak preview. 2005 (beschikbaar via www.jobvanexel.nl).
Van Exel NJA, WBF Brouwer. Jeugdroken: Rol voor overheid en ouders. TSG 2003;81(1): 24-26
Van Mens-Verhulst J, Moerman CJ. Seksebewust epidemiologisch onderzoek. TSG 2002;80(4):219-24
Van Reek J, Adriaanse H, Knibbe R. Alcohol consumption and correlates among children in the European
Community. Int J Addict 1994;29(1):15-21
Vandewater EA, Huang X. The Influence of Parental Weight Status on the Relationship between Television
Viewing and Childhood Overweight. Ann Arbor, MI: Institute for Social Research, University of Michigan, 2005
Vandewater EA, Shim MS, Caplovitz AG. Linking obesity and activity level with children's television and video
game use. J Adolesc 2004;27(1):71-85
Vereecken CA, Inchley J, Subramanian SV, Hublet A, Maes L. The relative influence of individual and contextual
socio-economic status on consumption of fruit and soft drinks among adolescents in Europe. Eur J Public
Health 2005;15(3):224-232
Wake M, Salmon L, Waters E, Wright M, Hesketh K. Parent-reported health status of overweight and obese
Australian primary school children: a cross-sectional population survey. Int J Obes Relat Metab Disord
2002;26(5):717-724
Wang Y. Cross-national comparison of childhood obesity: the epidemic and the relationship between obesity and
socioeconomic status. Int J Epidemiol 2001;30:1129-1136
Wang Z, Patterson CM, Hills AP. A comparison of self-reported and measured height, weight and BMI in
Australian adolescents. Aust N Z J Public Health 2002;26(5):473-478
Warschburger P. The unhappy obese child. Int J Obes 2005;29(Suppl 2):S127-S129
Watt RG, Sheiham A. Dietary patterns and changes in inner city adolescents. Journal of Human Nutrition &
Dietetics 1996;9(6):451-461
Wei Y, Pere A, Koenker R, He X. Quantile regression methods for reference growth charts. Stat Med
2006;25(8):1369-1382
Whitaker RC. Obesity prevention in pediatric primary care: four behaviours to target. Arch Pediatr Adolesc Med
2003;157:725-727
WHO. Obesity: Preventing and managing the global epidemic. Geneva: World Health Organization. 1998
Williams J, Wake M, Hesketh K, Maher E, Waters E. Health-related quality of life of overweight and obese
children. JAMA 2005;293(1):70-76
Wills W, Backett-Milburn K, Gregory S, Lawton J. Young teenagers' perceptions of their own and others' bodies: a
qualitative study of obese, overweight and 'normal' weight young people in Scotland. Soc Sci Med
2006;62(2):396-406
Yarnell JWG, McCrum EE, Patterson CC, Skidmore P, Shields MD, McMahon J, Evans AE. Prevalence and
awareness of excess weight in 13 and 14 year olds in Northern Ireland using recent international guidelines.
Acta Pediatrica 2001;90(12):1435-1439
Zametkin AJ, Zoon CK, Klein HW, Munson S. Psychiatric aspects of child and adolescent obesity: a review of the
past 10 years. J Am Acad Child Adolesc Psychiatry 2004;43(2):134-150
Zimmermann MB, Gübeli C, Püntener C, Molinari L. Detection of overweight and obesity in a national sample of
6–12-y-old Swiss children: accuracy and validity of reference values for body mass index from the US Centers
for Disease Control and Prevention and the International Obesity Task Force. Am J Clin Nutr 2004;79(5):838843
51
52
Annex A
Members advisory board
Jaap Seidell
Vrije Universiteit Amsterdam, Faculteit der Aard- en Levenswetenschappen,
Voeding en Gezondheid / Kenniscentrum Overgewicht (www.overgewicht.org)
Jolien Pon
Stichting Gezond Gewicht / Dikke Vrienden zomerkamp (www.gezondgewicht.nl)
Karen van Reenen
Nederlandse Hartstichting / Heart Dance Awards (www.heartdanceaward.com)
Saskia van Dorsselaer
Trimbos Instituut / HBSC panelonderzoek (Health Behaviour in School-Aged
Children; www.hbsc.org)
Isabel Ferreira, Hans Brug
Erasmus MC, iMGZ / ENDORSE project (determinantenonderzoek naar
overgewicht onder jongeren; www2.eur.nl/fgg/mgz)
53
54
Annex B
Validity and reliability of self-reported height and weight
Many studies investigated the validity and reliability of self-reported height and weight in
adolescents, and the subsequent classification of adolescents into (over)weight categories
on the basis of accepted cut-points for body mass index.
Fortenberry (1992) found that adolescents over-reported their height by 0.5 cm (females) /
0.6 cm (males), and underreported their weight by 1.5 kg (females) / 1.2 kg (males).
Adolescents in the heaviest quartiles of measured weight underreported weight by
significantly more than those in lighter quartiles. There were no differences in the accuracy of
height or weight reports when subjects were grouped by height quartile. In conclusion,
Fortenberry suggested that although the bias in self-report could affect results of survey
research; the magnitude of such an effect would likely be small.
Himes and Faricy (2001) observed that biases in reporting stature and weight were
consistently negative, with intra-class coefficients between measured and self-reported
dimensions within age and gender groups ranging from 0.57 to 0.91 for stature and from 0.85
to 0.98 for weight, respectively.
Strauss (1999) observed that the correlation between self-reported and actual weight of
young adolescents ranged from 0.87 to 0.94, and between self-reported and actual height
from 0.82 to 0.91. Self-reported weights were significantly lower than measured weights for
girls compared to boys, and differences between actual and self-reported weight were
significantly greater for obese children compared with non-obese children. Nevertheless, the
use of self-reported weight and height resulted in the correct classification of weight status in
94% of children.
Brener et al. (2003) administered self-reported height and weight twice, 2 weeks apart, and
compared these with measured values. Differences between self-reported values were small,
and highly correlated with their measured counterparts. Adolescents over-reported their
height by 2.7 inches and underreported their weight by 3.5 pounds; resulting mean BMI
values based on self-reported values (23.5 kg/m2) underestimated BMI based on measured
values (26.2 kg/m2) by 2.6 points, as well as the prevalence of overweight (14.9% and
26.0%, respectively).
Wang et al. (2002) found that self-reported heights were significantly higher than measured
heights, and self-reported weights significantly lower than measured weights. There were no
differences between boys and girls in the accuracy of self-reported height or weight, but bias
was much higher in overweight or obese adolescents than normal/underweight adolescents.
The resulting percentage misclassification of overweight or obesity was 30%. They
55
suggested efforts to improve the accuracy of self-reporting are needed for self-report
measures in adolescents to be reliable.
Elgar et al. (2005) found that self-reported and measured height and weight were highly
correlated, but that underreporting of body weight by an average of .52 kg contributed to
underestimation of the prevalence of overweight and obesity: 13.9% was identified as
overweight and 2.8% as obese based on self-reported data, while measured data showed
rates of 18.7% and 4.4%, respectively. Body mass index (BMI) and body dissatisfaction
predicted bias in self-reported weight.
Galan et al. (2001) observed under-reporting of weight by 0.07% for males and 0.79% for
females, and of height by 0.51% for males and 0.98% for females. Although the correlation
between self-reported and objective BMI was 0.87 for males and 0.90 for females, the
prevalence of high BMI (≥85th percentile) was underestimated by about 34%. Consequently,
they suggest, analysis of BMI based on self-report as a continuous variable entails a small
margin of error, but that its use as a categorical variable involves a considerable
underestimate of the prevalence of high BMI.
Flood et al. (2000) found that self-reported weights and heights led to misclassification of
relative weight status: 62% of males and 47% of females were classified as overweight or
obese based on measured weights and heights, compared with 39% and 32% based on selfreport.
Himes et al. (2005) found that self-reported stature, weight and BMI on the average were
valid representations of actual values, but argued that the prevalence of overweight based on
self-reported data systematically underestimate measured values.
Black et al. (1998) compared the accuracy of self-reported body weight of two groups of
people, a group that was explicitly informed that body weight would be measured
immediately following questionnaire completion, and a group that was not informed. They
found that people from the group that was informed reported more accurately and with
consistent accuracy across the weight range, whereas the accuracy of people from the
uninformed group decreased as body weight increased.
56
Annex C
Literature review
The computerized literature databases Medline and Scopus were searched, using the
following keyword combinations:
Overweight, obesity
Child, adolescent, youth, young people
Health attitude, health behaviour, physical activity, sedentary behaviour, fruit, vegetables,
snacks, soft-drinks
Home, family, school, peers
Personality, self-esteem, body-image, happiness, well-being
Availability, family meals, vending machines, pocket money.
About you
Many studies have addressed gender differences in health behaviour (e.g., Inchley et al.
2005; De Vries et al. 2002; Van Mens-Verhulst & Moerman 2002; Neumark-Sztainer &
Hannan 2000)
De Bruijn et al. (2005b) found the Big-Five personality dimensions to be associated with
healthy behaviours. Agreeableness was positively associated with vegetable consumption,
openness to experience with vegetable and fruit consumption, and extraversion with sportsrelated physical activity. Based on a meta-analysis of studies addressing the relation
between conscientiousness-related traits and health behaviours, Bogg and Robberts (2004)
concluded that these traits were negatively associated with risky health behaviours and
positively with beneficial health behaviours. Klein-Hessling et al. (2005) observed that selfefficacy is associated with health protective behaviours, and stress experiences and
maladaptive coping with health risk behaviours. Braet and Ipema (1997) hypothesised that
neuroticism may be associated with emotional eating, in particular in obese girls older than
12.
Craeynest et al. (2005) investigated explicit and implicit attitudes towards food and physical
activities among obese and non-obese adolescents. They found no differences in the explicit
attitude towards food and physical activity between the groups. Obese adolescents had a
more pronounced positive implicit attitude towards both health and unhealthy food, but there
was no difference in implicit attitude towards sedentary, moderate and high intense physical
activities.
57
Falkner et al. (2001) examined associations of weight status with social relationships, school
experiences, psychological well-being, and some future aspirations. Compared to normal
weight peers, obese girls were less likely to hang out with friends, more likely to report being
held back a grade, to consider themselves poor students, and to report serious emotional
problems, hopelessness, or a suicide attempt in the last year; obese boys were less likely to
hang out with friends, more likely to feel that their friends do not care about them, to report
having serious problems in the last year, to consider themselves poor students, and to
expect to quit school. Erickson et al. (2000) asked themselves whether overweight children
were more unhappy than normal weight children, and only found a relationship between
depressive symptoms and BMI in preadolescent girls, that seemed to be explained by an
excess of overweight concerns.
About your health
Friedman and Brownell (1995) presented a list of potential risk factors for psychological
problems in obese individuals based on a literature review, including social / environmental
and cognitive factors. Social / environmental risk factors concerned societal pressure to be
thin, teasing and discrimination history, reactions to weight by family and peers and peer
interpersonal relationships; cognitive factors concerned body image dissatisfaction and
distortion, and self-concept. Obesity is associated with poorer psychosocial functioning, even
compared with other chronic diseases, because of its visibility and negative evaluation – as a
sign for lacking self-control, absent intention for self-restraint, or offence against esthatic
ideals (Warschburger 2005). Stradmeijer et al. (2000) found that overweight adolescents
displayed lower body-esteem scores than their normal weight peers, had lower selfperceptions of their physical appearance, athletic competence, social acceptance, and global
self-worth (see also Mendelson et al. 2001, 1996; Mendelson & White 1982). Watt and
Sheiham (1999) found that the main reason for a sample of 13-14 year olds to change their
dietary pattern was a desire to improve appearance, with health and other considerations
being less important. Ryan et al. (1998) observed a high level of dissatisfaction with body
weight in a sample of schoolgirls aged 15 years: 59% reported that they wanted to be
slimmer and 68% had previously tried to lose weight. Dissatisfaction was expressed by
overweight, normal weight and even underweight girls, reporting the use of unhealthy weight
control practices including random avoidance of staple foods, fasting, smoking and purging,
in their pursuit of the 'perfect' female figure. Watt and Sheiham (1999) found that girls were
more likely to perceive themselves overweight than boys, and that four out of five young
people who perceived themselves overweight actually were not, based on self-reported
height and weight. Griffin et al. (2004) found that significantly more girls than boys were
58
affected by fear of fatness. In a qualitative study, Wills et al. (2006) observed that acceptance
of body size and shape was fairly common among overweight and obese young adolescents,
contradicting the common perceptions that overweight and obesity are associated with body
dissatisfaction and that young adolescents strive for thinness and have a fear of fatness.
Sobal et al. (1995) found that female secondary school students were more concerned about
their own body weight than male peers, while males emphasized thinness in partners more
than did females and showed lower comfort in dating very overweight partners. Honjo and
Siegel (2003) observed that perceived importance of being thin among young female
adolescents was associated with future smoking initiation. Some studies suggest a negative
correlation between obesity and smoking behaviour (Gruber & Frakes 2006; Chou et al.
2004), while Flegal et al. (1995) found that smoking cessation was associated with significant
weight gain. Classen and Hokayem (2005) found overweight or obesity to be associated with
self-reported depression among youth, in particular among girls. Pesa et al. (2000) observed
that overweight female adolescents seem to suffer from low self-esteem but that this may be
explained by body image, supporting earlier evidence that the effect of shape and weight on
self-esteem among adolescents is not so much related to actual body mass but to
perceptions of being overweight and body image dissatisfaction. Kelly et al. (2005) found that
adolescent girls with high body satisfaction were more likely to report parental an peer
attitudes that encouraged healthy eating and exercising to be fit, and less likely to report
weight related concerns and behaviours. Sarlio-Lahteenkorva et al. (2003) found girls
frequently reported feelings of over- and underweight, while boys were mostly satisfied with
their current weight; low self-esteem was associated with feelings of overweight among girls
and underweight among boys.
According to McCreary and Sasse (2000), much of the existing research on disordered
eating has centred on the drive for thinness, which is most commonly observed in girls. Hill
and Silver (1995) asked girls and boys to rate four silhouettes representing a thin and a
heavy girl and boy, and found that the overweight body shapes were associated with poor
social functioning, impaired academic success, and low perceived health, healthy eating and
fitness, and a greater perceived relevance of weight among girls. Staffieri (1967) asked boys
to assign 39 adjectives of behaviour/personality traits to three silhouettes representing
extreme endomorph (fat), mesomorph (muscular) and ectomorph (thin) body types. The fat
body type was associated with socially unfavourable and aggressive adjectives, the thin body
type with personally unfavourable and socially submissive adjectives, and the muscular body
type with favourable adjectives. Cohane and Pope (2001) reviewed the literature of body
image in boys. Boys generally displayed less overall body concern than girls, many reported
dissatisfaction with their bodies, often associated with reduced self-esteem, and boys
frequently wanted to be bigger, but most studies failed to distinguish between bigness due to
59
increased muscle and due to fat. The male standard of bodily attractiveness, thus, appears
to be bigger, bulkier, and more muscular; whereas girls typically want to be thinner, boys
more commonly desire to be physically big (Courtenay 2003; Pope et al. 1999; Guggenheim
1977). Therefore, males more often think they are underweight, and nearly half of overweight
males think their weight is normal (McCreary 2002; McCreary & Sadava 2001). Adams et al.
(2000) observed that young adolescent males selected significantly larger body size
silhouettes for ideal adult body size than females, and expressed less personal concern
about weight.
Television viewing also plays a role in constructing and internalizing negative stereotypes of
overweight and obese individuals, possibly contributing to poorer self-and peer-perceptions.
Greenberg et al. (2003) analysed 10 prime-time fictional programs and observed that
overweight and obese television characters were mostly associated with specific negative
characteristics. Fouts and Burggraf (2000) conducted a content analysis of 18 prime-time
television situation comedies and found that below-average weight females were
overrepresented, that the heavier the female character, the significantly more negative
comments were made about or to her, usually by men, and that negative comments were
significantly associated with audience laughter. Similarly, Fouts and Vaughan (2002)
conducted a content analysis of 27 different prime-time television situation comedies, and
found that above-average weight males were underrepresented, that the heavier the male
character, the more negative references he made about his own body shape/weight, and that
his negative comments about himself were significantly associated with audience reactions.
Harrison (2000) investigated relationships between children’s television viewing and
interpersonal attraction to television characters, fat stereotyping, body shape standards and
eating disorder symptomatology, and found that the time boys spent watching television was
associated with the likelihood of associating negative stereotypes to overweight females.
Tiggemann and Slater (2004) demonstrated that the content of music videos that
emphasized appearance and featured thin and attractive women had negative
consequences for adolescent female's body image. Also in Tiggeman et al. (2000)
adolescent females reported experiencing media pressure to be thin, but indicated that this
did not necessarily mean they were dissatisfied with their bodies.
Friedlander et al. (2003) found that overweight children have increased odds of low scores
for several health-related quality-of-life domains, including psychosocial health, self-esteem,
and physical functioning. Swallen et al. (2005) found that overweight or obese adolescents
were more likely to have a functional limitation, had significantly worse self-reported health,
and young adolescents of 12 to 14 years were significantly more likely to be depressed and
to report low self-esteem and poor school/social functioning compared with normal weight
60
peers. Williams et al. (2005) found that child and parent-proxy reported health-related quality
of life scores were similar and decreased with increasing child weight. Associations were
found with physical and social functioning subscale scores, but not with emotional and school
functioning. Wake et al. (2002) observed that parental concern about their child's weight was
strongly associated with their child's actual BMI. Schwimmer et al. (2003) compared the
health-related quality of life (HRQoL) of children and adolescents who are healthy, obese, or
diagnosed as having cancer. Compared with healthy children and adolescents, obese
children and adolescents reported significantly lower HRQoL in all domains, similar to those
diagnosed as having cancer. Parent proxy report showed that the child or adolescent's
weight was inversely correlated with HRQoL, physical functioning, social functioning, and
psychosocial functioning. Fallon et al. (2005) also found overweight to be associated with
poorer quality of life in adolescence, both from self- and parent-proxy reports. According to
Warschburger (2005), overweight and obesity are associated with functional impairments
(including breathing and joint difficulties), may lead to psychosocial strain (including negative
self-esteem, increased anxiety and depression), and that overweight and obese children
report lower levels of HRQoL. Neumark-Sztainer et al. (1998) highlighted chronic illness as
one of the main risk factors for inadequate food intake patterns. Fonseca and Gaspar de
Matos (2005) observed that overweight adolescents were significantly more likely to describe
themselves as not healthy. Will et al. (2006) conducted in-depth interviews with normal
weight, overweight and obese teenagers and found that they rarely mentioned any healthrelated consequences of their own or others' fatness; wearing 'nice' clothes and being slowed
down were raised as considerations by girls and boys, respectively.
About your future
Although there is some evidence suggesting that being overweight or obese may have a
lasting effect on life satisfaction and future life aspirations (e.g., Ball et al. 2004), there are
few studies addressing future expectations of adolescents in relation to overweightness.
Davis et al. (2004) argued that overeating and overweight is not just a passive response to
salient environmental triggers and powerful physiological drives, but is also about inability to
advantageously assess future consequences of current choices. They found greater
decision-making impairments - in terms of ability to inhibit short-term rewards when the longterm consequences are deterious - in healthy adult women with high BMI, even greater than
in previous studies with drug addicts.
Adolescent risk-taking behaviour is often attributed to their ignorance, misunderstanding or
underestimation of adverse outcomes. Mann et al. (1989) argued that although by the age of
15 years many adolescents show a reliable level of decision-making competence, young
61
adolescents (12-14 years) are less able to create options, identify a wide range of risks and
benefits, foresee the consequences of alternatives, and gauge the credibility of information
from sources with vested interests. Others have also demonstrated the immature judgement
of young adolescents as compared to middle / late adolescents and adults (Cauffmann &
Steinberg 2000; Steinberg & Cauffmann 1996). Quadrel et al. (1993) reviewed the literature
on the “adolescent invulnerability hypothesis”, that poses that adolescents perceive
themselves invulnerable to the threats associated with risk behaviours, and investigated
differences in the cognitive decision-making processes of adolescents and adults. Both from
the review and their own study they found no evidence that adolescents were less competent
in decision-making than adults. They displayed similar knowledge of the possible
consequences of risk behaviours and made similar judgments of their and others’ risk levels,
both showing overconfidence in their level of knowledge and optimism regarding their
personal vulnerability. Millstein and Halpern-Felsher (2002) found that adolescents tended to
overestimate personal health behaviour-linked risks more than younger adults, and were less
likely to see themselves as invulnerable. Steinberg (2004) suggested that the greater
propensity of adolescents to take risks is not due to age differences in risk perception or
appraisal, but to a disjunction between novelty and sensation seeking and the development
of self-regulatory competence (in terms of thinking before acting, choosing between
alternative courses of action differing in level of risk, and interrupting a risky behavioural
trajectory that is already set in motion). Komlos et al. (2004) hypothesized that recent trends
in obesity may be partly related to an increase in the marginal rate of time preference, the
rate at which people are willing to trade current for future benefits. Weight control requires
people to forego current consumption and to invest time and effort – and perhaps money - in
exercise, for the sake of potential future health benefits. A higher discounting rate may then
be associated with higher food intake, less physical activity and, consequently, with weight
gain. They argued international evidence suggests that such a relationship is plausible.
Borghans and Goldsteyn (2006) support the idea that the increasing incidence of overweight
may be related to increasing individual discounting rates over time, as evident from rises in
credit card debts, gambling and the development of more hedonic lifestyles. They found
some evidence that differences in overweight are associated with the way people discount
future health benefits, depending on the choice of proxy for the discount rate, but no
evidence that these proxies changed over time, so that the increase in BMI was more likely
explained by shifts in other parameters. Other authors also discussed the positive
association between overweight / obesity and time preference, time-inconsistent choice,
myopic choice or impatience (Finke & Huston 2003; Huston & Finke 2003; Offer 2001).
Kan and Tsai (2004) found evidence of a relationship in the general population between
individuals' knowledge concerning the health risks of obesity and their tendency to be obese.
62
Dohmen et al. (2005a, 2005b) found evidence of heterogeneity of risk attitudes across
individuals; women were more risk averse than men, willingness to take risks was negatively
related to age, individuals with highly educated mothers were less risk averse. Individual risk
preference was however reasonably stable across domains.
About home
Steinberg (1987) observed that youngsters living with both natural parents were less
susceptible to pressure from their friends to engage in deviant behaviour than youngsters
living in other family structures, while youngsters growing up in stepfamilies - in the presence
of an additional adult - were equally at risk for involvement in deviant behaviour as were their
peers growing up in single-parent households. Lundborg (2006) found that living in a single
parent household had significant effects for health risk behaviours like smoking and illicit
drug use.
Watt and Sheiham (1999) found that young people from lower social class groupings were
more likely to be less healthy eaters, and that boys were less healthy eaters than girls.
Among others, Vereecken et al. (2005), Stamatakis et al. (2005), Storey et al. (2003) and
Wang (2001) observed associations between socio-economic status or family income /
wealth and food habits of young adolescents and the prevalence of obesity. Friestad and
Klepp (2006) found a relation between socio-economic status and a composite measure of
health enhancing behaviour.
Eisenberg et al. (2004) investigated the association between frequency of family meals and
multiple indicators of adolescent health and well-being, and found that eating family meals
enhances adolescent health and well-being. Neumark-Sztainer et al. (2003, 2004) found that
family meal patterns, including frequency, priority, structure and atmosphere of family meals,
potentially play an important role in promoting positive dietary intake among adolescents.
Patrick and Nicklas (2005) argued that adolescents eating patterns are strongly influenced by
both physical and social characteristics of mealtime structure, including availability and easy
access to healthy and unhealthy types of food, portion size, whether families eat together,
TV-viewing during meals, the source of foods (e.g., take-away, home-cooking), and parents’
attitudes and time constraints.
Kremers et al. (2003) explored the possible influence of parenting style, the emotional
climate within which child development and socialization occurs (Darling & Steinberg 1993),
on adolescent food choice patterns. They used a two-dimensional classification of parenting
style, based on the interaction of parental involvement / responsiveness (I) and parental
strictness / control (S), resulting in a fourfold typology of parenting styles: authoritative (high
I; high S), authoritarian (low I; high S), indulgent (high I; low S), and neglectful (low I; low S).
63
Fruit consumption as well as fruit-specific cognitions were most favourable among
adolescents who were being raised with an authoritative parenting style, while children of
parents with indulgent parenting styles consumed more fruit than adolescents from
authoritarian or neglectful homes. Patenting styles were associated with adolescents’
gender, age and religiosity. Lau et al. (1990) explored the influence from parents and peers
on young adults' health beliefs and behaviour concerning drinking, diet, exercise, and
wearing seat belts. They argued that parental influence is strong and enduring, but
distinguished three “windows of vulnerability”, critical periods in which individuals were
particularly open to the influence from socializing agents. The first period of vulnerability is
adolescence, when individuals typically seek independence from parents. In combination
with higher exposure to alternative health beliefs, norms and behaviours from peers, this
individualization process may be associated with increased (health) risk seeking.
Ackard et al. (2006) discussed the importance of parent-child connectedness: adolescents'
perceptions of low parental caring, difficulty talking to their parents about problems, and
valuing their friends' opinions for serious decisions were significantly associated with
compromised behavioural and emotional health. Mellin et al. (2002) examined the potential
impact of familial factors on unhealthy behaviours and psychosocial difficulties among
overweight adolescents. Overweight adolescents reported engaging in significantly more
unhealthy behaviours and experiencing more psychosocial distress than their nonoverweight peers, but among the overweight youth, higher levels of reported family
connectedness and parental expectations and moderate levels of parental monitoring were
associated with the lowest levels of unhealthy behaviours and psychosocial distress.
According to Neumark-Sztainer et al. (1998) low socioeconomic status, minority status, and
low family connectedness were some of the main risk factors for inadequate food intake
patterns. Fonseca et al. (2002) found that the main protective factors associated with
adolescents engaging in extreme weight control behaviours included high parental
expectations, maternal presence, and connectedness with friends and other adults for boys,
and family connectedness, positive family communication, parental supervision/monitoring,
and maternal presence for girls. Classen and Hokayem (2005) investigated the influence of a
range of child and mother variables on the likelihood that a child will become an obese or
overweight youth, and found significant effects for the mother’s BMI, education level, number
of children and employment status. The likelihood of being overweight or obese in youth
increased with mother’s BMI, decreased with her education level and number of children,
and was higher when she worked more than 35 hours per week.
Swinburn et al. (1999) developed a conceptual model for helping characterize elements of
adolescents´ environment influencing food intake and physical activity as obesogenic
64
(promoting fatness) or leptogenic (promoting leanness). This two-dimensional framework
dissects the environment into size (micro and macro) by type: physical (what is available),
economic (what are the costs), political (what are the "rules"), and socio-cultural (what are
the attitudes and beliefs). Ferreira et al. (2005) adopted this framework for a literature review
of potential environmental determinants of physical activity in children and adolescents. Most
convincing evidence was found for home environmental factors, especially parental support
and encouragement and indicators of socio-economic status. Van der Horst et al. (2005) did
the same for potential environmental determinants of selected dietary behaviours in children
and adolescents. Here also, most studies focussed on the micro-environmental, household
level, in particular on socio-cultural and economic factors; parental fat and energy intakes are
associated with intakes of their offspring, and higher parental education and authorative
parenting styles are associated with higher fruit and vegetable intakes of their offspring.
In a study by Watt and Sheiham (1999), young people indicated that availability of healthy
foods and encouragement and support from close family were most helpful factors in
promoting positive changes in dietary pattern, next to own willpower. Popkin et al. (2005)
reviewed the literature on the ways the environment, conceived as the external context in
which individual make decisions, affects diet, physical activity, and obesity. They argued
there is a significant association of the availability of food sources and physical activityrelated facilities with individual-level health behaviour, but also an inequitable distribution of
such facilities, with high minority, low educated populations at strong disadvantage. GordonLarsen et al. (2006) support these findings; they found lower-SES and minority groups had
reduced access to facilities, which in turn was associated with decreased physical activity
and increased overweight. Brug and Van Lenthe (2005) argued there still is a lack of
convincing evidence for the role of environmental factors as determinants of physical activity
and nutritional behaviour, in particular regarding the interaction with individual factors.
About school
Friedman and Brownell (1995) highlighted teasing about physical appearance as a potential
risk factor for psychological problems in obese individuals, in particular when teasing
becomes internalized as thoughts and views about oneself. A range of studies (e.g., Elgar et
al. 2005; Janssen et al. 2004; Neumark-Sztainer et al. 2002) indeed reported that overweight
and obese school-aged children were more likely to be victims as well as perpetrators of
bullying than their normal-weight peers. In a study by Eisenberg et al. (2003), 15-30% of
adolescents reported weight-based teasing by peers or family members. Teasing about body
weight was found to have profound effects on young people's psychosocial well-being, as it
was associated with low body satisfaction, low self-esteem, high depressive symptoms, and
65
suicide ideation and attempt. Strauss and Pollack (2003) found that many overweight
adolescents are socially marginalized. In a study by Fonseca and Gaspar de Matos (2005), a
significantly greater proportion of obese/overweight versus non-overweight youth reported
difficulty in making friends. Not in the last place this may be related to the proximity effect or
courtesy stigma, the tendency for individuals who associate with stigmatized individuals to
face negative interpersonal and professional outcomes (Hebl & Mannix 2003). Obese people
are stigmatised (Myers & Rosen 1999; Ryan et al. 1998), more than almost all other social
groups (Klaczynski et al. 2004). As a result of this threat, non-stigmatized adolescents may
avoid or break off contact with those who are stigmatized because of their overweightness or
obesity. Chen and Brown (2005) asked college students to rank order six drawings of
potential sexual partners, including an obese partner, partners with various other disabilities,
and a healthy partner. They found that the least-preferred partners were obese, in particular
among men. Halpern et al. (2005) examined associations among body mass, involvement in
romantic relationships, and dieting among adolescent females. They observed that for each
one point increase in BMI, the probability of having a romantic relationship decreased by 67%, while involvement in a nonsexual romantic relationship was associated with a significant
increase in the likelihood of dieting.
Bell and Swinburn (2004) found that a substantial proportion of total energy intake was
consumed at school, and that energy-dense foods and beverages were over-represented in
the school environment: biscuits, snack bars and fruit/cordial drinks brought from home and
fast food, packaged snacks, and confectionary sold at canteens. Sanigorski et al. (2005)
studied the lunchbox contents of schoolchildren: though an encouraging 68% of children had
fruit in their lunchboxes, over an alarming 90% had energy-dense, micronutrient-poor snacks
('junk food'). Bell et al. (2005) observed that children and adolescents obtain a considerable
proportion of their daily energy intake from foods and beverages that do not fit the
requirements of a healthy diet, but found no clear association with weight status. NeumarkSztainer et al. (2005) found that food-related policies and the food environment at school (i.e,
open/closed campus during lunchtime, availability and hours of operation of vending
machines, type of food sold in vending machines) had a significant impact on students’ lunch
and snacking patterns. Also French et al. (2003) argued that he availability of healthful foods
and beverages in schools as well as school food policies that foster healthful food choices
among students need greater attention. Anderson and Butcher (2005) investigated the effect
of school food policies on students body mass, and estimated that the increase in availability
of junk foods in schools can account for about one-fifth of the increase in average BMI
among adolescents over the last decade.
66
According to Evenson et al. (2003), travel to and from school can be an important and
regular source of physical activity for youth. Kremers et al. (2004) found that 37% of Dutch
adolescents always used a bike for transport, and 42% occasionally. De Bruijn et al. (2005a)
found that bicycle use was more likely among adolescents that were native Dutch, went to
school in a less-urbanized city, and had a more positive intention and perceived stronger
behavioural control and subjective norm towards bicycle use.
Falkner et al. (2001) examined associations of weight status with social relationships, school
experiences, psychological well-being, and future aspirations, in terms of expectations
regarding educational, occupational and financial success. Falkner et al. found that obese
boys and girls were less likely to hang out with friends, were more likely to consider
themselves poor students, and obese boys were more likely to expect to quit school. Pesa et
al. (2000) observed overweight adolescents to have higher grades, but lower school
connectedness. Neumark-Sztainer et al. (1998) highlighted poor school achievement as one
of the main risk factors for inadequate food intake patterns.
Childhood obesity is associated with insufficient (vigorous) physical activity and more time
spent on sedentary behaviours like TV/video viewing, video/computer game use and
reading/doing homework - the “couch-potato” hypothesis (e.g., Elgar et al. 2005; Patrick et al.
2004; Vandewater et al. 2004; Berkey et al. 2003a; Giammattei et al. 2003; Utter et al. 2003;
Eisenmann et al. 2002; Gordon-Larsen et al. 2002; Faith et al. 2001; Strauss et al. 2001;
McMurray et al. 2000; Robinson 1999; Gortmaker et al. 1996).
The evidence regarding the association between sedentary behaviour and obesity is mixed.
Marshall et al. (2004) reviewed empirical evidence of associations of media use – TV/video
viewing, video/computer game use - with body fatness and physical activity. They conclude
that there were statistically significant effects in expected directions, but that these effects
were small and that the relationship between sedentary behaviour and health was unlikely to
be explained using single markers of inactivity. Gordon-Larsen et al. (2002) found there are
important gender and ethnic differences in the associations between sedentary behaviour,
physical activity and overweightness. Faith et al. (2002) investigated the effect weight
criticism during physical activity by family and peers, and found it to be associated with
reduced sports enjoyment, perceived activity compared with peers, and mild-intensity leisure
activity. Forshee et al. (2004) observed a strong negative association between BMI and
participation in team sports or exercise programs for young adolescent males and females.
Vandewater and Huand (2005) argued that the relationship between television viewing and
weight status differs greatly for different children, and that parental weight status is an
67
important moderator of this relationship. Elkins et al. (2004) investigated associations
between participating in after school sports activities and body mass, and found that
participation in an increasing number of athletic activities was associated with lower weight
status. They however observed considerable variations between different sports, potentially
related to the level of vigorous activity or practice sessions each sport provides and selfselection of overweight adolescents to sports in which their weight is an advantage (or less a
disadvantage). Strauss et al. (2001) observed that adolescents are largely sedentary.
Physical activity was correlated with self-efficacy and social influence, and was an important
component in the development of self-esteem.
There is also evidence of an interaction between sedentary behaviours and unhealthy energy
intake. Many authors reported a positive association between time watching TV/videos and
unhealthful dietary behaviour. Matheson et al. (2004) found that a significant proportion of
children’s daily energy intake is consumed during television viewing, and although the fat
content of the foods consumed during television viewing did not differ significantly from that
of the foods consumed with the television off, less soda, fast food, fruit, and vegetables were
consumed with the television on. Boynton-Jarrett et al. (2003) also found an inverse relation
between time watching TV/videos and playing video games and fruit and vegetable
consumption. Worth noting is that, from all this evidence, it appears there is a difference in
the association with overweightness between more passive types of sedentary behaviour,
like TV/video viewing, and more active types, such as reading/doing homework and
video/computer game use. In the same line, Utter et al. (2003) found that leisure time
physical activity was not associated with TV/video viewing, but was positively associated with
computer use and time spent reading/doing homework.
Gardner and Steinberg (2005) investigated peer influence on risk taking, risk preference, and
risky decision making, and found that adolescents took more risks, focused more on the
benefits than the costs of risky behaviour, and made riskier decisions when in peer groups
than alone. Lundborg (2006) found significant peer effects for potentially health damaging
behaviours like binge-drinking, smoking and illicit drug use.
About what you eat
Childhood obesity is associated with consumption of sugar-sweetened (soft) drinks,
packaged meals and fast foods (e.g., Bray & Champagne 2005; Elgar et al. 2005; Berkey et
al. 2004; James et al. 2004; Giammattei et al. 2003; Dietz 2001; Ludwig et al. 2001).
Neumark-Sztainer et al. (1998) listed the main risk factors for inadequate food intake
patterns, which include: low socioeconomic status, minority status, chronic illness, poor
school achievement, low family connectedness, weight dissatisfaction, and overweight.
68
Ackard et al. (2003) found associations between overeating, being overweight or obese, and
a number of adverse behaviours and negative psychological experiences, but could not
ascertain whether overeating was an early warning sign of additional psychological distress
or a potential consequence of compromised psychological health. Martens et al. (2005)
investigated the relative importance of personal and social environmental predictors of the
consumption of fruit, high-fat snacks and breakfast, and observed that adolescents' attitudes
were the most important determinants of different health-related eating behaviours.
Guggenheim et al. (1977) observed that teenagers generally have well-informed opinions on
good nutrition and on the causes and prevention of obesity, but that overweight teenagers
appeared to be more conscious of their food intake than under- and normal-weight peers.
Neumark-Sztainer et al. (2003) found that frequency of family meals was positively
associated with intake of fruits, vegetables, grains, and calcium-rich foods and negatively
associated with soft drink consumption. In a study among schoolchildren in nine European
countries, Sandvik et al. (2005) found that children generally held a positive attitude towards
fruit and vegetable intake, had a more positive attitude towards fruit than towards vegetables,
and girls were more positive than boys. They perceived their social environment as
supportive towards fruit and vegetable intake, and reported availability of fruit and vegetables
to be (very) good at home but low at school and during leisure time activities.
De Bruijn et al. (2004) found that snacking behaviour was inversely associated with female
gender and a more positive intention, a more positive attitude, and stronger perceived
behavioural control towards restricting snacking. French et al. (2001) found that frequency of
fast food restaurant use was positively associated with intake of total energy, percent energy
from fat, daily servings of soft drinks, cheeseburgers, french fries and pizza, but also with
student employment, television viewing, home availability of unhealthy foods, and perceived
barriers to healthy eating, while it was inversely associated with daily servings of fruit,
vegetables and milk, and with students' own and perceived maternal and peer concerns
about healthy eating. Forshee and Storey (2003) found no association between BMI and
consumption of regular carbonated soft drinks, a positive association with consumption of
regular carbonated soft drinks, and a negative association with drinking milk. These findings
were confirmed by Forshee et al. (2005, 2004).
In a longitudinal study of the effect skipping breakfast on weight, Berkey et al. (2003b) found
that overweight children who never ate breakfast lost weight compared to overweight
children who ate breakfast nearly every day, while normal weight children who never ate
breakfast gained weight relative to peers who ate breakfast nearly every day. Elgar et al.
(2005) reported associations between obesity and skipping breakfast.
69
Friedman and Brownell (1995) suggested that health risk attitudes or behaviours related to
obesity should be considered jointly, because risk factors may interact and exacerbate each
other. Schuit et al. (2002) investigated the degree of clustering of common lifestyle risk
factors, as co-occurrence of such behaviours can help identify high-risk groups. They found
that risk factors like smoking, low vegetable/fruit consumption, excessive alcohol intake and
low physical activity tended to aggregate, particularly in young adults. Friestad and Klepp
(2006) also argued in favour of composite measures of health behaviours, rather than
studying single forms of health-enhancing and health-compromising behaviour. Kremers et
al. (2004) focused on the clustering of motivations underlying energy balance-related
behaviours among adolescents. They found that attitude, subjective norm, perceived
behavioural control and intention measures related to energy-dense snacks, the use of highfat sandwich fillings, fruit consumption, active transport and physical activity during leisure
time clustered more strongly than the behaviours themselves. Nelson et al. (2005)
investigated physical activity and sedentary behaviour patterning and identified seven
homogeneous groups of adolescents with similar behaviours.
About money
Roberts et al. (2003) investigated associations between more open relationships between
parents and their children, and the influence of children on parental decision-making
concerning the consumption of sweet snacks and drinks. They found that the child’s
influence declined with the parent’s age, but that parental efforts to limit their children's intake
of sweet snacks and drinks were undermined by access to money, which allowed the child to
out-manoeuvre his or her parents. Scragg et al. (2002) found that cigarette smoking in young
adolescents was positively associated with pocket money amount. Van Reek et al. (1994)
observed an association between pocket money and adolescent drinking.
70
Annex D
International and national survey questionnaires reviewed
1. Health Behaviour in School-Aged Children (HBSC; www.hbsc.org): a cross-national
research study among young people attending school, aged 11, 13 and 15 years old.
HBSC was initiated in 1982, the sixth survey was conducted in 2001/2002, and there are
now 41 participating countries (predominantly Europe and US). All national survey
questionnaires share a core set of questions looking at individual and social resources,
health behaviours and health outcomes.
2. Global School-based Student Health Survey (GSHS; www.who.int): a school-based
survey among young people aged 13 to 15. GSHS, an initiative of the World Health
Organization, uses a self-administered questionnaire to obtain data on young people's
health behaviour and protective factors related to the leading causes of morbidity and
mortality among children and adults worldwide. Key topics addressed include alcohol and
drug use, sexual behaviours, dietary behaviours, physical activity, and mental health.
3. Youth Risk Behavior Surveillance System (YRBSS; www.cdc.gov): a school-based
surveys among 9th through 12th grade students, that was developed in 1990 to monitor
priority health risk behaviours, often established during childhood and early adolescence,
that contribute markedly to the leading causes of death, disability, and social problems
among youth and adults. These behaviours include tobacco, alcohol and other drug use,
unhealthy dietary behaviours, inadequate physical activity, and sexual behaviours.
4. Dutch National Youth Survey (Nationaal Scholierenonderzoek [NSO]; www.scp.nl): a
school-based survey aimed at obtaining data on behaviour, health, opinions and attitudes
to finances, lifestyle and the future of school-going adolescents in the Netherlands. NSO
was initiated in 1984, the seventh survey was conducted in 2001/2002.
5. Electronic Monitor and Education (Elektronische Monitor en Voorlichting [E-MOVO];
www.ggd.nl): a web-based survey conducted by the East-Netherlands Regional Public
Health Service. E-MOVO collects data on behaviour and health among school-going
adolescents and uses the data to provide respondents with individualized feedback and
links to web-based information on relevant health issues.
6. Rotterdam Youth Monitor (RYM; www.ggd.rotterdam.nl): a monitoring program of the
Rotterdam Municipal Health Service aimed at assessing the physical, mental and social
development of all children born in the city at 7 different occasions in their development.
7. Dutch Obesity Intervention for youTh (DOit; www.doitproject.com): a randomized
controlled trial investigating the effectiveness of a school-based program aimed at weight
gain prevention in adolescents.
71
72
Annex E
Questionnaire “Health & Future” [in Dutch]
VRAGENLIJST
GEZONDHEID & TOEKOMST
Dit is een onderzoek naar hoe Nederlandse scholieren
in klas 1 en 2 van het voortgezet onderwijs denken
over hun gezondheid nu en in de toekomst. Lees de
vragen goed door en beantwoord ze zo eerlijk mogelijk.
Denk niet te lang na en kies gewoon het antwoord dat
het beste bij je past. Het gaat ons om jouw mening, er
zijn dus geen goede of foute antwoorden.
Deze vragenlijst is ANONIEM, jouw antwoorden
worden NIET door iemand op school gelezen.
Volledig ingevulde vragenlijsten doen mee voor een
HOOFDPRIJS VAN €100 en vijf prijzen van €20.
Daarnaast wordt in iedere klas nog €10 verloot.
Heb je nog vragen? Stel ze gerust!
Job van Exel
010-4082507
[email protected]
73
OVER JOU
1.
Ben je een meisje of een jongen?
○ meisje
○ jongen
2.
Hoe oud ben je?
○ 11
○ 12
○ 13
○ 14
○ 15
3.
Waar ben je geboren?
○ Nederland
○ Suriname
○ De Antillen of Aruba
○ Turkije
○ Marokko
○ anders, namelijk ________________
4.
Welk schooltype volg je?
○ VMBO, beroepsgericht
○ VMBO, theoretisch of gemengd
○ HAVO
○ HAVO / VWO
○ VWO (en Gymnasium)
5.
In welke klas zit je?
○
○
G&T05.nr
brugklas
tweede klas
6.
Welke beschrijving past het best bij jou? Bij mij past nummer
Mijn uiterlijk vind ik eigenlijk best
wel heel belangrijk. Ik het er vaak met
mijn vrienden / vriendinnen over. Je
kunt dus wel zeggen dat ik best veel
bezig ben met hoe ik er uitzie.
Natuurlijk is je uitstraling ook wel
belangrijk. Iemand kan dik zijn en toch
overal bijhoren. Of knap zijn, maar een
bitch. Als het over gezondheid gaat,
denk ik met name na over gezond eten,
want als je slecht eet ga je er
minder mooi uitzien.
2
1
Ik maak me niet zo druk over mijn
gezondheid of mijn uiterlijk. Ik ben
tevreden met mijn eigen lichaam, niet
te dik en niet te dun. Het leven draait
niet om uiterlijk, uitstraling is veel
belangrijker. Het gaat erom dat je je
goed voelt en daar heeft uiterlijk niet
zoveel mee te maken. Gezondheid
interesseert me eigenlijk niet zo. Ik
weet wel dat bepaalde dingen niet zo
gezond zijn, maar daar trek ik me
niet al teveel van aan.
5
Ik denk best wel eens na over
mijn gezondheid, meestal over wat
gezond eten is en wat niet. Ik vind dat
ik eigenlijk gezonder zou moeten eten,
vooral niet teveel eten en snoepen.
Maar ik vind het moeilijk om goed te
letten op wat ik eet. Het liefst wil ik
niet al teveel opvallen en er gewoon bij
horen. Ik vind het onzin als anderen
zeggen dat dik zijn je eigen schuld is.
Als je dik bent hoor je er gewoon bij.
7.
het best
3
WAT PAST
HET BEST
BIJ JOU?
4
Ik zit eigenlijk niet zo lekker in
mijn vel en voel me vaak niet zo fit. Ik
doe niet veel met leeftijdsgenoten en
voel me op school niet op mijn gemak.
Ik ben veel tijd kwijt aan gamen,
computeren en TV kijken. Ik beweeg te
weinig, want ik vind sporten niet zo
leuk. Ik ben nu eenmaal meer een
zitzak dan een sportfreak. Ik eet de
meeste dingen wel, maar het
interesseert me eigenlijk niet zo of
wat ik eet wel of niet gezond is.
Ik sport veel en graag, gewoon
omdat ik sporten leuk vind. Gymles is
dus een van de hoogtepunten van de
schoolweek. Met mijn gezondheid ben
ik niet zo bezig, maar ik voel me
eigenlijk best gezond. Ik denk niet
zoveel na over wat nou gezond of
ongezond eten is en ik vind niet dat ik
gezonder zou moeten eten. Op school
heb ik het prima naar mijn zin. Ik zit
eigenlijk best wel lekker in mijn vel.
Geef je geluk een cijfer. Zet hieronder een kruisje op de plaats die het
beste klopt met hoe gelukkig jij je over het algemeen voelt.
De ‘0’ betekent “heel ongelukkig”. De ‘10’ betekent “heel gelukkig”.
F
F
F
F
F
F
F
F
F
F
0
1
2
3
4
5
6
7
8
9
heel
ongelukkig
G&T05.nr
F
10
heel
gelukkig
8.
Hieronder staan een aantal eigenschappen. Kruis aan in welke mate jij deze
eigenschappen bezit.
helemaal
niet
prettig
fantasierijk
prikkelbaar
schuchter
slordig
terughoudend
onderzoekend
zenuwachtig
zorgvuldig
stil
hulpvaardig
snel geraakt
spraakzaam
ordelijk
gesloten
veelzijdig
vriendelijk
nauwkeurig
vernieuwend
behulpzaam
ongerust
aangenaam
artistiek
angstig
netjes
teruggetrokken
systematisch
sympathiek
nerveus
creatief
G&T05.nr
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
niet
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
meer niet deels niet meer wel
dan wel deels wel dan niet
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
wel
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
helemaal
wel
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
OVER JE GEZONDHEID
9.
Geef je gezondheid een cijfer. Zet hieronder een kruisje op de plaats die het
beste klopt met hoe gezond jij je over het algemeen voelt.
De ‘0’ betekent de slechtste gezondheid die je je kunt voorstellen. De ‘10’
betekent de beste gezondheid die je je kunt voorstellen.
F
F
F
F
F
F
F
F
F
F
F
0
1
2
3
4
5
6
7
8
9
10
slechtste
gezondheid
beste
gezondheid
10. Hoeveel weeg je (zonder kleren aan)?
Mijn gewicht weet ik…
11. Hoe lang ben je (zonder schoenen aan)?
Mijn lengte weet ik…
kilo
○ vrij zeker
1 meter en
○ vrij zeker
○ niet zo zeker
centimeter
○ niet zo zeker
12. Wat vind je van je eigen lichaam?
○ veel te dun
○ een beetje te dun
○ eigenlijk precies goed
○ een beetje te dik
○ veel te dik
13. Heb je last van één of meer langdurige ziekten, aandoeningen of handicaps?
○ nee
○ ja, maar ik kan de meeste dingen gewoon doen
○ ja, en ik kan veel dingen niet gewoon doen
14. Heb je de afgelopen vier weken gerookt?
○
○
○
G&T05.nr
nee
ja, af en toe
ja, elke dag
OVER JE TOEKOMST
15. Passen deze uitspraken bij jou?
helemaal
niet
niet
a. ik denk na over hoe mijn leven later zal zijn, en
probeer met de dingen die ik nu doe mijn
toekomst te verbeteren
○
○
○
○
○
b. ik doe vaak dingen waarvan ik misschien pas
over een paar jaar plezier heb
○
○
○
○
○
c. ik doe alleen wat ik nu leuk vind. wat er later
gebeurt zie ik dan wel weer
○
○
○
○
○
d. ik doe alleen iets als ik er nu meteen plezier
van heb
○
○
○
○
○
e. ik kies graag voor de gemakkelijke oplossing
○
○
○
○
○
f. ik wil best nu iets doen wat ik minder leuk vind,
als ik daar later plezier van heb
○
○
○
○
○
g. ik vind het belangrijk goed te weten welke
dingen slecht voor je kunnen zijn, ook als je
daar pas veel later iets van merkt
○
○
○
○
○
h. ik denk dat het beter is om iets te doen dat
heel belangrijk is voor later, dan iets dat een
beetje belangrijk is voor nu
○
○
○
○
○
dat sommige dingen slecht kunnen zijn voor
later, daar maak ik me niet zo druk om. dat los
ik later dan wel op, voor het te erg wordt
○
○
○
○
○
j. nu minder leuke dingen doen omdat dat beter
is voor later vind ik niet nodig. over de
toekomst maak ik me later wel druk
○
○
○
○
○
k. ik doe alleen wat ik nu leuk vind. problemen in
de toekomst los ik dan wel weer op.
○
○
○
○
○
○
○
○
○
○
i.
l.
nu dingen doen waarvan ik weet dat ik ze leuk
vind is voor mij belangrijker dan dingen doen
waar ik misschien later een keer plezier van heb
16. Hoe oud denk je te worden?
G&T05.nr
____ jaar
een
heel
goed
beetje
goed
17. Hoe belangrijk vind jij het, hoe het met je zal gaan…
heel
niet
helemaal niet
belangrijk
belangrijk
belangrijk
belangrijk
… over 2 jaar?
… over 5 jaar?
… over 25 jaar?
○
○
○
○
○
○
○
○
○
○
○
○
18. Wat heb je liever?
a. ik heb liever €100 nu dan €110 over 2 jaar
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
a. nu gezonder eten zodat je een betere gezondheid hebt als
je 70 jaar bent
○ ja
○ nee
b. nu iedere dag 30 minuten extra bewegen zodat je een
betere gezondheid hebt als je 70 jaar bent
○ ja
○ nee
c. nu een prik waarvan je een week goed ziek bent zodat je
een betere gezondheid hebt als je 70 jaar bent
○ ja
○ nee
d. nu gezonder eten zodat je later 3 jaar ouder wordt
○ ja
○ ja
○ nee
○ nee
○ ja
○ nee
b. ik heb liever €100 nu dan €125 over 2 jaar
c. ik heb liever €100 nu dan €150 over 2 jaar
d. ik heb liever €100 nu dan €250 over 2 jaar
e. ik heb liever €100 nu dan €500 over 2 jaar
f. ik heb liever €100 nu dan €200 over 5 jaar
g. ik heb liever €100 nu dan €500 over 5 jaar
h. ik heb liever €100 nu dan €1.000 over 5 jaar
i.
ik heb liever €100 nu dan €5.000 over 5 jaar
j. ik heb liever €100 nu dan €10.000 over 25 jaar
k. ik heb liever €100 nu dan €100.000 over 25 jaar
l.
ik heb liever €100 nu dan €1.000.000 over 25 jaar
19. Zou je dit doen?
e. nu iedere dag 30 minuten extra bewegen zodat je later
3 jaar ouder wordt
f. nu een prik waarvan je een week goed ziek bent zodat je
later 3 jaar ouder wordt
G&T05.nr
20. Geef een rapportcijfer aan je gezondheid als je 40 jaar oud bent. Zet een
kruisje op de plaats die het beste klopt met hoe gezond jij verwacht te zijn
als je 40 jaar bent. De ‘0’ betekent de slechtste gezondheid die je je kunt
voorstellen. De ‘10’ betekent de beste gezondheid die je je kunt voorstellen.
F
F
F
F
F
F
F
F
F
F
F
0
1
2
3
4
5
6
7
8
9
10
slechtste
gezondheid
beste
gezondheid
21. Geef een rapportcijfer aan je gezondheid als je 70 jaar oud bent. Zet een
kruisje op de plaats die het beste klopt met hoe gezond jij verwacht te zijn
als je 70 jaar bent. De ‘0’ betekent de slechtste gezondheid die je je kunt
voorstellen. De ‘10’ betekent de beste gezondheid die je je kunt voorstellen.
F
F
F
F
F
F
F
F
F
F
F
0
1
2
3
4
5
6
7
8
9
10
slechtste
gezondheid
beste
gezondheid
22. Gezond leven betekent dat je gezond eet (drie maaltijden op een dag / weinig
tussendoortjes / voldoende groente en fruit) en genoeg beweegt of sport om
fit te blijven. Wat vind je van deze uitspraken?
helemaal
mee eens
mee
eens
niet
mee eens
helemaal
niet
mee eens
a. ik eet gezond
F
F
F
F
b. ik beweeg genoeg om fit te blijven
F
F
F
F
c. als ik gezond leef dan voel ik mij beter
F
F
F
F
d. als ik nu ongezond leef dan kan ik later
allerlei ziektes krijgen
F
F
F
F
e. als ik nu ongezond leef dan kan ik eerder
doodgaan
F
F
F
F
f. als ik dat wil dan kan ik makkelijk gezonder
gaan leven dan ik nu doe
F
F
F
F
g. als ik vaak ziek zou zijn dan zou ik gezonder
gaan leven
F
F
F
F
G&T05.nr
OVER THUIS
23. Met welke mensen woon jij in één huis?
Kruis alles wat van toepassing is aan
○ eigen moeder
○ pleegmoeder, stiefmoeder of partner vader
○ eigen vader
○ pleegvader, stiefvader of partner moeder
○ zus(sen)
○ broer(s)
24. Waar is je moeder geboren?
○ Nederland
○ Suriname
○ Turkije
○ Marokko
25. Waar is je vader geboren?
○ Nederland
○ Suriname
○ Turkije
○ Marokko
26. Heeft je moeder betaald werk?
○ ja
○ nee
G&T05.nr
27. Heeft je vader betaald werk?
○ ja
○ nee
28. Hoe rijk is jullie gezin in vergelijking met andere gezinnen in Nederland?
○ veel rijker
○ rijker
○ ongeveer even rijk
○ minder rijk
○ veel minder rijk
29. Word jij thuis opgevoed met een bepaald geloof?
○ ja, Rooms-Katholiek
○ ja, Protestant (zoals Hervormd of Gereformeerd)
○ ja, Islamitisch
○ ja, anders
○ nee, niet gelovig opgevoed
30. Hebben jullie deze producten thuis en mag je die pakken als je er zin in hebt?
a. melk
b. fruit
c. koek (zoals sultana, liga, ontbijtkoek)
d. snoep / chocola
e. chips / nootjes / popcorn
f. snacks (zoals hamburger, friet, kroket, pizzabroodje)
g. frisdrank of energiedranken
31. Mag je thuis roken of zou het mogen?
○ altijd
○ soms
○ nooit
G&T05.nr
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
32. Mag je thuis alcoholhoudende drank drinken of zou het mogen?
○ altijd
○ soms
○ nooit
33. Geef aan wat je van deze uitspraken vindt.
helemaal
mee eens
mee
eens
niet
mee eens
helemaal
niet
mee eens
a. mijn ouders hebben belangstelling voor wat ik
doe of wat mij bezig houdt
F
F
F
F
b. mijn ouders geven mij een compliment als ik
iets goed doe
F
F
F
F
c. mijn ouders zijn streng
F
F
F
F
d. ik ben meestal tevreden over de relatie met
mijn moeder
F
F
F
F
e. ik ben meestal tevreden over de relatie met
mijn vader
F
F
F
F
34. Geef je geluk THUIS een cijfer. Zet hieronder een kruisje op de plaats die
het beste klopt met hoe gelukkig jij je over het algemeen thuis voelt.
F
F
F
F
F
F
F
F
F
F
0
1
2
3
4
5
6
7
8
9
heel
ongelukkig
OVER SCHOOL
35. Hoe ga je meestal van huis naar school?
○ lopend
○ op de fiets
○ met het openbaar vervoer
○ ik word met de auto gebracht / gehaald
○ anders, namelijk ____________________
G&T05.nr
F
10
heel
gelukkig
36. Hoe lang doe je er meestal over van huis naar school?
minuten
37. Als je denkt aan je laatste rapport, hoe waren dan je schoolprestaties?
○ zeer goed
○ goed
○ voldoende
○ onvoldoende
○ zeer onvoldoende
38. Hoe vaak ben je in de laatste maand op school gepest?
○ nooit
○ soms (minder dan één keer per week)
○ vaak (één keer per week of meer)
39. Kun jij onderstaande producten bij jou op school kopen (bijvoorbeeld in de
kantine of uit een automaat)?
a. melk
b. fruit
c. gezonde broodjes (bijvoorbeeld met kaas of vleeswaren)
d. koek (zoals sultana, liga, ontbijtkoek)
e. snoep / chocola
f. snacks (bijvoorbeeld hamburger, friet, kroket, pizzabroodje)
g. frisdrank of energiedranken
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ ja
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
○ nee
40. Kun jij onderstaande producten ergens vlakbij school kopen (bijvoorbeeld bij
een supermarkt of tankstation)?
a. koek (zoals sultana, liga, ontbijtkoek)
b. snoep / chocola
c. snacks (bijvoorbeeld hamburger, friet, kroket, pizzabroodje)
d. frisdrank of energiedranken
G&T05.nr
○ ja
○ ja
○ ja
○ ja
○ nee
○ nee
○ nee
○ nee
41. Waar ga je meestal naar toe als je uit school komt?
○ naar huis
○ naar een vriend / vriendin thuis
○ met vrienden / vriendinnen ergens naartoe of een beetje rondhangen
○ naar een oppas, opvang of huiswerkbegeleiding
○ anders, namelijk ____________________
42. Als je na school naar huis gaat of zou gaan, wie is er dan thuis?
○ mijn moeder (of pleegmoeder / stiefmoeder / partner vader)
○ mijn vader (of pleegvader / stiefvader / partner moeder)
○ beide
○ geen van beide
43. Geef je geluk OP SCHOOL een cijfer. Zet hieronder een kruisje op de plaats
die het beste klopt met hoe gelukkig jij je over het algemeen op school voelt.
F
F
F
F
F
F
F
F
F
F
0
1
2
3
4
5
6
7
8
9
heel
ongelukkig
OVER JE VRIJE TIJD
44. Hoeveel goede vrienden of vriendinnen heb je op dit moment?
○ geen
○ één
○ twee
○ drie of meer
G&T05.nr
F
10
heel
gelukkig
45. Hoeveel tijd besteed je OP EEN SCHOOLDAG gemiddeld aan de volgende
dingen?
helemaal 1 uur of
meer dan
1 à 2 uur
niet
minder
2 uur
a. huiswerk maken
F
F
F
F
b. lezen (krant, tijdschrift, strip, boek)
F
F
F
F
c. televisie / video / DVD kijken
F
F
F
F
d. computeren (internet, games, chatten, playstation)
F
F
F
F
e. telefoneren / SMS’en
F
F
F
F
f. spelen of sporten buiten of op straat
F
F
F
F
g. andere hobby
F
F
F
F
46. Hoeveel tijd besteed je OP EEN WEEKEND DAG gemiddeld aan de volgende
dingen?
helemaal 1 uur of
meer dan
1 à 2 uur
niet
minder
2 uur
a. huiswerk maken
F
F
F
F
b. lezen (krant, tijdschrift, strip, boek)
F
F
F
F
c. televisie / video / DVD kijken
F
F
F
F
d. computeren (internet, games, chatten, playstation)
F
F
F
F
e. telefoneren / SMS’en
F
F
F
F
f. spelen of sporten buiten of op straat
F
F
F
F
h. andere hobby
F
F
F
F
47. Sport je bij een vereniging of club?
○ nee (ga verder met vraag 0)
○ ja, ik doe aan ____________________________________________
(naam sport(en), bijvoorbeeld voetbal / hockey)
48. Hoeveel uur per week train je voor deze sporten?
Bij elkaar gemiddeld
uur per week
49. Doe je voor één of meerdere sporten mee aan competitiewedstrijden?
○ nee
○ ja
G&T05.nr
50. Als ik sport, doe ik dat omdat…
helemaal
mee eens
mee
eens
niet
mee eens
helemaal
niet
mee eens
a. …ik sporten leuk vind
F
F
F
F
b. …ik fit wil blijven
F
F
F
F
c. …ik er goed wil uitzien
F
F
F
F
d. …ik daar vrienden en vriendinnen tegenkom
F
F
F
F
e. …ik bij de beste in mijn sport wil horen
F
F
F
F
f. …ik dat moet van mijn ouders
F
F
F
F
51. In mijn vrije tijd…
heel vaak
vaak
soms
zelden
nooit
a. …ben ik alleen
F
F
F
F
F
b. …verveel ik mij
F
F
F
F
F
52. Geef je geluk IN JE VRIJE TIJD een cijfer. Zet hieronder een kruisje op de
plaats die het beste klopt met hoe gelukkig jij je over het algemeen in vrije
tijd voelt. De ‘0’ betekent “heel ongelukkig”. De ‘10’ betekent “heel gelukkig”.
F
F
F
F
F
F
F
F
F
F
F
0
1
2
3
4
5
6
7
8
9
10
heel
ongelukkig
heel
gelukkig
OVER WAT JE EET
53. Hoe vaak eet jij TUSSENDOORTJES?
(bijna)
nooit
1 of 2
vaak,
elke
keer maar niet
dag
per week elke dag
a. koek (zoals sultana, liga, ontbijtkoek)
F
F
F
F
b. snoep / chocola
F
F
F
F
c. chips / nootjes / popcorn
F
F
F
F
d. snacks (zoals hamburger, friet, kroket, pizzabroodje)
F
F
F
F
G&T05.nr
54. Als je tussendoortjes neemt, wanneer doe je dat dan meestal?
(bijna)
nooit
1 of 2
vaak,
elke
keer maar niet
dag
per week elke dag
a. op weg naar / van school
F
F
F
F
b. in de pauze op school
F
F
F
F
c. als ik thuis kom van school
F
F
F
F
d. als ik TV kijk / computer
F
F
F
F
e. op straat / in de stad
F
F
F
F
f. bij de (sport)club of (sport)vereniging
F
F
F
F
55. Hoe vaak eet of drink jij…?
(bijna)
nooit
1 of 2
vaak,
elke
keer maar niet
dag
per week elke dag
a. ontbijt (meer dan iets te drinken of een tussendoortje)
F
F
F
F
b. lunch (meer dan iets te drinken, een tussendoortje of
F
F
F
F
c. avondeten, samen met je familie aan tafel (meer
F
F
F
F
d. melk
F
F
F
F
e. frisdrank (niet light)
F
F
F
F
f. fruit
F
F
F
F
g. groente (salade / gekookte groente)
F
F
F
F
snack)
dan iets te drinken, een tussendoortje of snack)
OVER GELD
56. Hoeveel geld (bijvoorbeeld zakgeld of kleedgeld) krijg je van je ouders?
Ik krijg gemiddeld ____ Euro per maand
57. Hoeveel geld verdien je met bijbaantjes?
Ik verdien gemiddeld ____ Euro per maand
G&T05.nr
58. Mag je van je ouders zelf beslissen wat je met je geld doet?
○ ja
○ grotendeels
○ soms wel en soms niet
○ nee
59. Mag je van je ouders dit geld uitgeven aan snoep of snacks (zoals hamburger,
friet, kroket, pizzabroodje)?
○ nee
○ ja
60. Spaar je?
○ nee (ga verder met vraag 0)
○ ja
61. Hoeveel spaar je?
Ik spaar gemiddeld ____ Euro per maand
62. Waarom spaar je?
Kruis alles wat van toepassing is aan
○ voor een speciaal doel (bijvoorbeeld een stereo, MP3-speler)
○ om iets achter de hand te hebben als ik geld nodig heb
○ geen reden, ik hou gewoon geld over
○ omdat het moet van mijn ouders
63. Hoeveel van je eigen geld besteed je gemiddeld per maand aan…?
a. snoep / chocola / koek / chips
____ Euro per maand
b. snacks (zoals hamburger, friet, kroket, pizzabroodje) ____ Euro per maand
c. alcoholhoudende dranken
____ Euro per maand
d. sigaretten / shag
____ Euro per maand
e. kleding en schoenen
____ Euro per maand
f. CD’s / DVD’s e.d.
____ Euro per maand
g. cosmetica, make-up, kapper, e.d.
____ Euro per maand
h. mobiele telefoon
____ Euro per maand
G&T05.nr
Scheur deze bladzijde los van de vragenlijst
en lever deze apart in bij je leraar
VUL HIERONDER JE NAAM EN JE KLAS IN
ZODAT WE JE KUNNEN TERUGVINDEN
ALS JE IN DE PRIJZEN VALT!
NAAM: __________
KLAS: ____
VOND JE HET LEUK OM MEE TE DOEN?
WIJ DOEN VAKER DIT SOORT ONDERZOEK.
WIL JE NOG EENS MEEDOEN?
VUL DAN JE GEGEVENS IN!
NAAM:
_________________
ADRES: _________________________
STRAAT EN HUISNU MMER
______ _____________
POSTCODE
WOONPLAATS
Je bent aan het einde van de vragenlijst gekomen.
Hartelijk dank voor het meedoen!
G&T05.nr
Q
Annex F
Attitudes of youths about their health lifestyle (format A)
The way I look is very important
to me. I discuss my looks a lot with my
friends. It is fair to say I am pretty
involved with my appearance. Of
course, personality is also important.
Someone can be overweight and still
belong to the group, or be beautiful
but still be a bitch. When I think about
my health, I am particularly concerned
with what I eat, because when you eat
unhealthy you look worse.
2
1
I do not worry too much about
my health or my looks. I am satisfied
with my body as it is, not too
overweight and not too thin. In life it
is not about how you look, it is about
who you are. It is important to feel
good, and looks have little to do with
that. I am not really interested in my
health. I can tell healthy from
unhealthy foods but, for the most
part, I eat what I like.
5
Sometimes I think about my health,
usually about what I should or should
not eat. I really should eat healthier,
in particular I shouldn’t eat too much
and eat less snacks. However, I find it
difficult to watch what I eat. I’d
rather not attract too much attention
at school and simply belong to the
group. I think it is nonsense to say
that being overweight is your own
fault. Only being overweight, does not
make you different form others.
3
WHICH
DESCRIPTION
FITS YOU
MOST?
I do not feel so good in general,
and often do not feel fit physically. I
do not do much with peers and do not
feel at ease at school. I spend a lot of
time playing computer games and
watching TV. I exercise little, because
I do not enjoy it. I am simply more a
‘couch-potato’ than a ‘sport freak’. I
eat most types of food, but I do not
really care whether what I eat is
healthy or not.
4
I often play sports, simply because
I love doing it. Gym class therefore
is one of the high points of the school
week. I do not think much about my
health, but I actually feel pretty
healthy. I give little thought to
whether food is healthy or not and I
do not feel I should live healthier.
I feel at ease at school. Actually, I
feel pretty good in general.
91
92
Annex G
Attitudes of youths about their health lifestyle (format B)
DOES THIS DESCRIPTION
FIT YOU?
I do not worry too much about my health or my
looks. I am satisfied with my body as it is, not too
overweight and not too thin. In life it is not about how
you look, it is about who you are. It is important
to feel good, and looks have little to do with that.
I am not really interested in my health. I can tell
healthy from unhealthy foods but, for the most part,
I eat what I like.
The way I look is very important to me. I discuss my
looks a lot with my friends. It is fair to say I am
pretty involved with my appearance. Of course,
personality is also important. Someone can be
overweight and still belong to the group, or be
beautiful but still be a bitch. When I think about my
health, I am particularly concerned with what I eat,
because when you eat unhealthy you look worse.
I do not feel so good in general, and often do
not feel fit physically. I do not do much with peers
and do not feel at ease at school. I spend a lot of
time playing computer games and watching TV.
I exercise little, because I do not enjoy it. I am
simply more a ‘couch-potato’ than a ‘sport freak’.
I eat most types of food, but I do not really care
whether what I eat is healthy or not.
I often play sports, simply because I love doing it.
Gym class therefore is one of the high points of the
school week. I do not think much about my health,
but I actually feel pretty healthy. I give little
thought to whether food is healthy or not and
I do not feel I should live healthier. I feel at ease
at school. Actually, I feel pretty good in general.
Sometimes I think about my health, usually about what
I should or should not eat. I really should eat healthier,
in particular I shouldn’t eat too much and eat less
snacks. However, I find it difficult to watch what I
eat. I’d rather not attract too much attention at school
and simply belong to the group. I think it is nonsense to
say that being overweight is your own fault. Only being
overweight, does not make you different form others.
not
at all
not
a little
well
very
well
not
at all
not
a little
well
very
well
not
at all
not
a little
well
very
well
not
at all
not
a little
well
very
well
not
at all
not
a little
well
very
well
93

Beelden van eigen gezondheid bij jongeren 12

Transcription

Similar documents

24 januari 2009

Abstract - Maastricht University Research Portal

- Kete Hamilton

Crash - Bekegem

Abstract

Woord vooraf…………………………..

Examenopgaven VBO-MAVO-D

Internodium - Semper Florens

Thoughts on rain - Gerrit Rietveld Academie

thesis