ARTICLE IN PRESS
Health & Place 15 (2009) 849–862
Contents lists available at ScienceDirect
Health & Place
journal homepage: www.elsevier.com/locate/healthplace
Environmental correlates of children’s active transportation:
A systematic literature review
Karina Pont a,, Jenny Ziviani a, David Wadley b, Sally Bennett a, Rebecca Abbott c
a
b
c
School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, QLD 4072, Australia
School of Human Movement Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
a r t i c l e in fo
abstract
Article history:
Received 21 August 2008
Received in revised form
11 November 2008
Accepted 3 February 2009
This systematic review investigated the environmental (physical, economic, socio-cultural and political)
correlates of active transportation (AT) among young people aged 5–18 years to better inform the
promotion of active living. Greater distance, increasing household income and increasing car ownership
are consistently associated with lower rates of AT among children. Having a non-white ethnic
background has a convincing positive association with AT. Having recreation facilities and walk or bike
paths present are possibly associated with higher rates of AT. Further research requires longitudinal and
intervention studies, utilizing multi-level design methodologies and objective measures of environmental attributes.
& 2009 Elsevier Ltd. All rights reserved.
Keywords:
Environment
Active travel
Children
Adolescents
Review
Introduction
Adequate physical activity is essential in children’s healthy
development and in helping to reduce chronic disease throughout
their lifespan (US Department of Health and Human Services,
1996; World Health Organization, 2008). However, there is
widespread concern that children’s physical activity levels are
decreasing and becoming insufficient for maintaining health
(Dollman et al., 2005; Sleap and Warburton 1996). Of note, more
than half of the school-aged children surveyed from 34 countries
(Janssen et al., 2005) failed to meet guidelines of at least 60 min
of moderate- to vigorous-intensity physical activity every day,
recognized by the World Health Organization and others (Cavill
et al., 2001; Pate et al., 1998; World Health Organization, 2008).
In this review, consistent with the UN Convention on the Rights of
the Child (United Nations, 1989), any person below the age of 18
years, unless under the law applicable to the child majority is
attained earlier, is considered a child.
There has been much research on how to increase physical
activity in the lives of children (van Sluijs et al., 2007). Some
researchers have argued that a sustainable approach could involve
increasing children’s habitual forms of physical activity, such as
using AT (Duncan et al., 2008; Hohepa et al., 2008; Racioppi et al.,
2002). While the causal relationship is unclear, it has also been
Corresponding author. Tel.: +617 3346 7469; fax: +617 33651622.
E-mail address: [email protected] (K. Pont).
1353-8292/$ - see front matter & 2009 Elsevier Ltd. All rights reserved.
doi:10.1016/j.healthplace.2009.02.002
found that children who use AT to and/or from school are more
physically active, have higher levels of energy expenditure and are
more likely to meet physical activity guidelines than children who
are driven (Mackett et al., 2005; Timperio et al., 2006).
In order to promote AT among children in an informed fashion,
it is first necessary to understand the environmental factors which
facilitate or impede it. While AT has been examined in adults
(Wendel-Vos et al., 2007), relatively little is known about its
bearing in children. Two relevant literature reviews examining AT
have been conducted (McMillan, 2005; Panter et al., 2008), but
they have used a narrow definition of environment, limited to
urban form correlates and the physical environment. The current
systematic review was therefore undertaken with the aim of
identifying those factors in the broader physical, economic, sociocultural and political environment found to be most highly
associated with the tendency for children to use AT.
Methods
This systematic review used one axis of the ANGELO (ANalysis
Grid for Environments Linked to Obesity) Framework (Swinburn
et al., 1999) to classify the types of environments that influence
the extent to which children engage in AT for access within their
communities. The ANGELO framework was developed to identify
characteristics that contribute to the ‘obesogenicity’ of modern
environments. It considers environmental factors influencing
nutrition and physical activity levels in the adult population
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K. Pont et al. / Health & Place 15 (2009) 849–862
(Swinburn et al., 1999), and has been used in previous systematic
reviews of environmental determinants of physical activity
(Wendel-Vos et al., 2007; Ferreira et al., 2007).
Four types of environment are represented: (1) the physical,
which refers to ‘‘what is available’’ and includes the man-made
physical attributes of the neighborhood, such as the presence
of footpaths, bikeways and controlled crossings, as well as nonman-made factors, such as the weather; (2) the political,
pertaining to the power structures, laws, rules and regulations
that influence actions; (3) the economic, which covers both
the direct costs associated with activities, as well as the indirect
costs, such as time; and (4) the socio-cultural, referring to the
community’s or society’s attitudes, values and beliefs related to
health behaviors (Swinburn et al., 1999). This review employed
an adapted version of the ANGELO framework, in which these
categories were used to group environmental determinants
identified in the scientific literature.
Eligibility criteria
Papers were included if they met the following criteria with
respect to types of studies, types of participants, factors of interest
and types of outcomes.
Types of studies
Cross-sectional studies, randomised controlled trials, quasirandomised controlled trials, non-randomised controlled trials,
and cohort studies published in peer-reviewed journals between
1985 and May 2008 were included in the systematic review if they
also met the following three criteria:
Types of participants
Participants were children between 5 and 18 years at the
commencement of the study (studies with mixed age groups were
included if over 50% of the participants were so defined). Studies
of children with medical conditions or disabilities that could
restrict AT were excluded. However, those which included
children who were already overweight or obese at baseline were
included so as to reflect a public health approach that recognizes
the increasing prevalence of children as overweight.
Factor of interest
The study explored the environmental (physical, economic,
socio-cultural or political) factors impacting rates of AT among
children.
Types of outcomes
Studies had to report empirical data-measuring rates or
frequency of AT.
Any form of AT was included in the review. Walking, riding a
bicycle or using a scooter, skate board, inline skates and roller
skates are examples of AT. Any destination within a community
was admitted. Proxy reports for physical activity, numbers of
roads crossed, duration spent in AT and step counts were
excluded.
Data sources
Ten electronic databases (Medline, Cinahl, ERIC, PsychInfo,
Cochrane Database, PAIS, APAIS, Sociological Abstracts, SportDiscus and Web of Science) were searched for studies published
between January 1985 and 21 May 2008 using full text and MeSH
terms to identify relevant publications that contained at least one
term from each of the three categories of search terms used:
(a) exp CHILD/ OR exp ADOLESCENT/ OR student* OR pupil* OR
teenage* OR young people OR young person OR youth* or boy*
OR girl* OR pediatri* OR paediatri*
(b) walk* OR bicycl* OR cyclist* OR bik* OR scooter* OR inline
skat* OR roller skat* or roller blad*
(c) commut* OR transport* OR travel*
The searches were not limited to the English language, or in any
other way. They yielded 919 publications.
Assessment of eligibility
Article titles, abstracts and, where available, full text articles
were examined by the first and second author to determine if the
material was eligible to be included in the review. Eligibility was
determined by screening according to responses to the four
questions detailed in Appendix A. If the two reviewers disagreed
on any response, the paper was examined again and agreement
reached by consensus. Following a lengthy assessment procedure,
827 papers were excluded. The bibliographical reference lists of
the 92 remaining papers were searched for potentially relevant
studies missed in the database searches. This step yielded an
additional 131 studies. Of them, 18 were included in the next stage
of the review (a revised total of 110).
Full text articles of these 110 studies were read and examined
again for inclusion in the review, according to the inclusion/
exclusion criteria outlined above and detailed in Appendix B. This
assessment resulted in a total of 38 papers deemed appropriate
for data analysis (Alton et al., 2007; Carlin et al., 1997; Carver
et al., 2005; Centers for Disease Control and Planning, 2005; de
Bruijn et al., 2005; Evenson et al., 2006, 2003; Fulton et al., 2005;
Gilhooly and Low, 2005; Ham et al., 2008; Harten and Olds, 2004;
Kerr et al., 2007, 2006; Martin et al., 2007; McDonald, 2008;
McMillan et al., 2006, 2007; Merom et al., 2006; Mota et al., 2007;
Nelson et al., 2008; Pabayo and Gauvin, 2008; Roberts et al., 1997,
1996; Roberts and Norton, 1994; Salmon et al., 2007; Schlossberg
et al., 2006; Shi et al., 2006; Sirard et al., 2005; Spallek et al., 2006;
Timperio et al., 2006, 2004; Towner et al., 1994; Tudor-Locke et al.,
2003; Yarlagadda and Srinivasan, 2008; Yelavich et al., 2008;
Ziviani et al., 2006). See Fig. 1, which summarizes the procedures
undertaken.
Quality assessment
The methodological quality of the included publications was
appraised independently by the first two authors, with any
disagreements in ratings being reviewed by the fourth author
and discussed until consensus was achieved. There was 86.1%
agreement between the first two authors, with 82 individual
ratings reviewed by the fourth author. The Checklist for the
Evaluation of Research Articles (Part V: Survey Designs and Cross
Sectional Studies) (DuRant, 1994) was adapted to increase its
relevance and sensitivity for the types of papers included in the
review. Modifications included: making the questions more
explicit to aid decision making; changing ‘‘study hypotheses’’ to
‘‘study objectives’’, since most of the included studies were of an
exploratory nature; breaking down complex questions; accepting
a response and follow-up rate of 85% or more (compared with
90%); and deleting one question relating to adherence to study
protocol. The methodological quality of all included papers was
assessed to evaluate external validity of measurement tools
(description of the sample, sampling methods, study methodology, measurement, external validity of measurement tools, bias
from blinding and follow-up) using the assessment detailed in
Appendix C.
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Search strategy
*
*
*
*
((child/ or adolescence/ or student or pupil or teenage or youth or
young person or young people or boys or girls or pediatri* or
paediatri*) and (walk* or bicycl* or bik* or cyclist or scooter* or
inline skat* or roller skat* or roller blad*) and (commut* or travel* or
transport*))
CINAHL
116
Cochrane
Central
37
ERIC
59
PAIS
29
Medline
386
PsychInfo
78
Sociological
Abstracts
126
SportDiscus
213
Web of
Science
171
Database Searches
Total articles
retrieved
1215
Different articles
919
Inclusion Screening
Assessment
Screening Assessments
Included
92
Excluded
827
Reference searches
of
included articles
Different articles
retrieved
131
Reference Searches
Inclusion Screening
Assessment
Excluded
113
Screening Assessments
Included
18
Inclusion
Assessment
110
Inclusion Assessments
Excluded
72
Included
38
Quality
Assessment
Quality Assessments
Data Extraction
Data
Extraction
Fig. 1. Flow chart of systematic review process.
Data extraction
The 38 selected publications were entered into a database,
which catalogued information about each one’s sample size,
age-range, and gender of participants. The country in which the
research was conducted, as well as the destinations of travel
examined and the total percentage of AT reported for the sample,
were also entered.
Due to the variety of variables and statistical methods used to
evaluate the associations in the scientific literature, it was not
possible to conduct a meta-analysis. We have therefore adopted a
semi-quantitative approach.
Only variables with reported correlations with AT were entered
in the analysis of this review. Correlates were recorded as a
‘significant positive’, ‘significant negative’ or ‘non-significant’
association between the independent variable (environmental
attribute) and the outcome measure (rates of non-motorized
transport among children). Independent variables were first
grouped within the types of environment as defined by the
ANGELO framework (Swinburn et al., 1999) and then within
groups of comparable environmental attributes such as distance
and safety from traffic danger. In addition, the method of data
analysis for the dependent variable was noted (odds ratio, w2,
prevalence, etc.). According to these procedures, any one publication was able to contribute to multiple records (e.g., separately for
different environmental attributes). It was also possible for one
publication to be recorded in one such environmental variable
multiple times if the study had multiple correlates contained in
one comparable group, or reported males, females or different
ages for one or more variables within that group. This provision
allowed one publication to report both significant and nonsignificant findings for a single environmental attribute.
Any available unadjusted odds ratios were used to report the
relationship between environmental variables and the desired
outcome of AT. The rationale for adopting this approach was to
reduce any bias among publications in which different variables
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were adjusted for in the data analysis. If unadjusted odds ratios
were not available, the adjusted odds ratios were reported. Where
odds ratio data were not available, correlational statistics were
used. If no tests of association were reported, descriptive data
were entered into Stata 10 and analyzed using the control ‘‘tabi’’
to report a directional correlation with significance.
For all data, significance was preferably determined by
reported p-values, with po0.05 considered significant. In the
absence of reported p-values, confidence intervals were used.
Significance was recognized when the 95% confidence intervals
did not include 1.00 in the case of odds ratio data. All necessary
data were inversed such that all reported studies for each
comparable group had the same referent, and all positive
relationships referred to an increased chance of using active
forms of transport.
We regarded evidence to be ‘‘convincing’’ if more than half the
publications reporting on a specific environmental attribute found
a statistically significant association in the same direction.
A possible association was registered if the same number of
publications were represented in non-significant and significant
associations. To ensure stability, a minimum of five publications in
total reporting on a specific environmental attribute was used to
draw conclusions.
Results
Quality assessment
The quality assessments revealed that the majority (94.8%)
of the 38 included studies did not report a sample calculation.
Four publications did not clearly report inclusion criteria and
11 (28.9%) failed to specify their study sample (providing gender
and age breakdown). All papers recounted the research methodology, adequately answered the research objectives, and measured variables using appropriate methods. One study did not
clearly describe the outcome and control variables. There was
consistency among the theoretical and operational definitions in
all studies. Twenty-seven publications (71.1%) did not report
complete reliability or validity testing on the outcome measures
relevant to the review. Of the three studies, which reported
reliability and validity testing, and one study that reported
validity testing, none reported their scales undergoing standardization for the population being examined.
Nine studies (23.7%) had a response rate of 85% or more and, of
the four using repeated measures, three had a follow-up response
rate less than 85%. Regarding sampling, 14 studies (36.8%) used
random methods to determine the groups (e.g. schools) to be
included, 22 (57.9%) employed purposeful sampling, (for example,
being matched for socio-economic status) and two papers
reported using convenience methods to determine group inclusion. Children in 11 (28.9%) studies were invited to participate
through random sampling methods, whereas 25 (65.8%) studies
invited all children in a particular group (e.g., class or school)
to participate. One paper reported selecting individuals as a
convenience sample, and one did not report its method sampling
of individuals within the group. See Table 1 for a summary.
Study characteristics
Table 2 shows the characteristics of the 38 studies in the
systematic review, ordered alphabetically. All were published
since 1994 and all were cross-sectional. Most originate from the
United States (44.7%) or Australia (26.3%). Most examined travel
to and/or from school only, with 18.4% considering travel to other
destinations, such as play areas or general AT. An average of 34.0%
of children engaged in AT, with a range of 7.9–91.9%.
Potential environmental determinants
Tables 3–6 show, respectively the potential physical, political,
economic and socio-cultural environmental determinants. Of the
105 variables examined, 15 were represented by five or more
publications, thus enabling conclusions to be drawn regarding the
evidence for environmental determinants of children’s AT.
Physical environment
Seven of the 43 physical environmental determinants identified were represented by five or more publications, with one
determinant, namely distance to a destination, providing convincing evidence for a significant inverse relationship with children’s
AT (Table 3). Increasing distance to a destination was the most
frequently examined physical environmental determinant, with
nine subscribing publications all indicating associations with
lower rates of children’s AT (Timperio et al., 2004; Gilhooly and
Low, 2005; Merom et al., 2006; Schlossberg et al., 2006; Ziviani
et al., 2006; Nelson et al., 2008; Ham et al., 2008; McMillan, 2007;
Yarlagadda and Srinivasan, 2008). Two publications (Schlossberg
et al., 2006; Yarlagadda and Srinivasan, 2008) reported nonsignificant associations between distance travelled and rates of
children’s AT, and none identified a positive relationship. This
finding provides convincing evidence that increasing distances
travelled are inversely associated with rates of children’s AT.
Having parks, play areas, sporting venues or recreation
facilities in neighborhoods was found to have a possible association with higher rates of AT among children. Seven publications
examined this relationship, with five (Alton et al., 2007; Evenson
et al., 2006; Timperio et al., 2004; Mota et al., 2007; Kerr et al.,
2007) reporting a positive relationship between the presence of
recreation spaces in the neighborhood and children’s AT, while
five others (Evenson et al., 2006; Timperio et al., 2004; Martin
et al., 2007; Kerr et al., 2007; Carver et al., 2005) found
non-significant associations. No publication reported a negative
association between the presence of parks, play areas, sporting
venues or recreation facilities in the neighborhood and rates of
children’s AT. For example, Evenson et al. (2006) found that girls
aged 10–15 years who knew of 10 or more recreations facilities
near their home had significantly higher rates of AT to school
compared with girls who knew of fewer than seven facilities. In
the same study, AT rates to school were higher in children who
knew of seven–nine recreation facilities near their home,
compared with those who knew of fewer than seven. However,
this increase was not significant. Kerr et al. (2007) examined
whether walking for transportation was higher if there was at
least one recreation or open space within 1 km of the homes
of children. They found a significant increase in such walking
among children with these types of land-use, irrespective of their
gender, ethnicity or household income, or even if the household
had two or more cars. A non-significant increase was found
among children with no or one car in their household.
The relationship between rates of children’s AT and greater
population density was addressed in six publications. Nonsignificant associations were reported in four (Copperman and
Bhat, 2007; Kerr et al., 2006, 2007; McDonald, 2008), with four
more (Kerr et al., 2006, 2007; McDonald, 2008; Nelson et al.,
2008) also reporting significant positive associations between this
determinant and children’s AT. de Bruijn et al. (2005) were the
only investigators to report a negative association, showing that
adolescents living in a town with fewer than 50,000 inhabitants
are 33% less likely to use a bicycle for transportation than those
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Table 1
Summary of quality assessment results of included publications.
Author (year) [Reference code]
Sample description
Study methodology
Measurement
External validity
Bias
Sampling methods
Alton et al. (2007) [1]
Carlin et al. (1997) [2]
Carver et al. (2005) [3]
Centers for Disease Control (2005) [4]
Copperman and Bhat (2007) [5]
de Bruijn et al. (2005) [6]
Evenson et al. (2006) [7]
Evenson et al. (2003) [8]
Ewing et al. (2004) [9]
Fulton et al. (2005) [10]
Gilhooly and Low (2005) [11]
Ham et al. (2008) [12]
Harten and Olds (2004) [13]
Kerr et al. (2007) [14]
Kerr et al. (2006) [15]
Martin et al. (2007) [16]
McDonald (2008) [17]
McMillan (2007) [18]
McMillan (2006) [19]
Merom et al. (2006) [20]
Mota et al. (2007) [21]
Nelson et al. (2008) [22]
Pabayo and Gauvin (2008) [23]
Roberts et al. (1997) [24] Roberts and Norton (1994) [25] Roberts et al. (1996) [26]
Salmon et al. (2007) [27]
Schlossberg et al. (2006) [28]
Shi et al. (2006) [29]
Sirard et al. (2005) [30]
Spallek et al. (2006) [31]
Timperio et al. (2006) [32]
Timperio et al. (2004) [33]
Towner et al. (1994) [34]
Tudor-Locke et al. (2003) [35]
Yarlagadda and Srinivasan (2008) [36]
Yelavich et al. (2008) [37]
Ziviani et al. (2006) [38]
3/4
4/4
3/4
3/4
1/4
1/4
3/4
3/4
2/4
2/4
3/4
2/4
3/4
2/4
3/4
3/4
2/4
2/4
2/4
3/4
3/4
3/4
3/4
2/4
3/4
3/4
3/4
3/4
2/4
3/4
3/4
3/4
3/4
3/4
3/4
2/4
3/4
3/4
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
2/2
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
3/3
2/3
3/3
3/3
1/3
0/2
1/2
0/2
0/2
0/2
1/2
0/2
0/2
0/2
0/2
0/2
2/3
0/2
2/3
2/3
0/2
0/2
0/2
0/2
1/2
1/2
0/2
0/2
0/2
0/2
0/2
0/2
0/2
0/2
0/2
1/2
1/2
0/2
0/2
0/2
0/2
1/2
1/1
0/1
0/1
0/2
0/1
0/1
0/2
1/1
0/1
0/1
0/1
0/1
0/1
0/1
1/1
0/2
0/2
0/1
0/1
0/1
1/1
0/1
0/1
0/1
1/1
1/1
0/1
0/1
1/1
2/3
0/1
0/1
0/1
1/1
0/1
0/1
0/1
0/1
b, e
a, e
b, e
c, d
b, y
a, e
b, e
a, e
b, d
b, e
c, e
b, e
a, e
b, d
a, f
b, d
b, d
b, e
b, e
b, d
b, e
b, e
a, e
a, e
a, d
a, e
b, e
b, e
b, e
a, e
a, d
a, e
a, e
b, e
a, e
b, d
b, e
b, e
a ¼ group sample selected through random sampling.
b ¼ group sample selected through purposeful sampling.
c ¼ group sample selected through convenience sampling.
d ¼ individuals selected to participate through random sampling.
e ¼ all individuals in group selected for participation.
f ¼ individuals selected to participate through convenience sampling.
Data could not be extracted for inclusion in the systematic review.
Data between narrative and tabulations differ, therefore cannot be accurately extracted for inclusion in the systematic review.
y
Methods of selecting individuals to participate not specified.
living in a town with more than 50,000. A possible positive
association therefore exists between increasing population density and rates of children’s AT.
Seven publications examined the influence of a child’s
residential situation. Living in a central city, small city, town,
suburban or urban area was found to have a non-significant
association with rates of AT in three of the seven relevant
publications (Timperio et al., 2004; Martin et al., 2007; Pabayo
and Gauvin, 2008). Four others (Copperman and Bhat, 2007; Shi et
al., 2006; Tudor-Locke et al., 2003; Yarlagadda and Srinivasan,
2008) reported non-significant associations and one (Tudor-Locke
et al., 2003) also reported a significant inverse association.
Five studies examined the association between the presence
of walk and/or bike paths and rates of children’s AT. Three (Ewing
et al., 2004; Fulton et al., 2005; Kerr et al., 2006) discerned
significant positive associations, while three (Evenson et al., 2006;
Ewing et al., 2004; Mota et al., 2007) reported non-significant
associations. Of note, Kerr et al. (2006) found that children whose
parents reported walking and biking facilities in the neighborhood
were two and a half times more likely to walk or bike to school at
least once a week compared with children who did not have such
infrastructure. There were no reported negative associations with
this determinant. Therefore, a possible positive association exists
between the presence of walk and/or bike paths and children’s AT.
Evidence for a possible significant positive association
was found between having mixed or commercial land-use in
the neighborhood and rates of children’s AT. Four of the five
publications represented (Copperman and Bhat, 2007; Kerr
et al., 2007, 2006; McMillan, 2007) reported significant positive
associations, and four (Copperman and Bhat, 2007; Kerr et al.,
2007, 2006; Yarlagadda and Srinivasan, 2008) found nonsignificant associations.
Economic environment
Twelve economic environmental determinants were identified,
two of which were studied in five or more publications, allowing
conclusions to be drawn (Table 4).
Car ownership was the most frequently cited variable in the
economic environment with 12 publications represented. Nine
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Table 2
Selected characteristics of publications included in the systematic review.
Author (year) [Reference
code]
Alton et al. (2007) [1]
Carlin et al. (1997) [2]
Population
AT measure
Sample
size
Age range
(years)
Sex
Country (locality)
Modes
Data source
Recall period
AT Dest.
% AT
473
5979
9–11
5–7, 8–10
MF
MF
Walk
Walk
A, f
c, f
7 days
1 day
General
School
41.9
31–35
12–13
MF
Walk, bike
a, f
7 days
51.4
Walk
Usual travel
School,
General
School
17.0
2 days
General
21.0
Usual travel
7 days
7 days
General
school
School
School
School
School
79.2
42.3
9.1
7.9
14.0
57–67
School
16.2–42.0
General
General
School
School
School
School
School
School
32.5
14.1
25.1
47.9
11.4
22.6
22.6
29.7
School
School
52.6
37.5
1588
5–18
MF
England (West Midlands)
Australia (Victoria, Western
Australia)
Australia (New South
Wales)
US1
1104
6–17
MF
US (California)
Walk, bike
Consumer-Styles ,
b, f
BATSyy
3859
480
4448
709
1124
1784
12–18
10–15
G6–12y
GK–12y
G4–12y
5–12
MF
F
MF
MF
MF
MF
Netherlands1
US1
US (North Carolina)
US (Florida)
US1
Scotland (Midlothian)
Bike
Walk,
Walk,
Walk,
Walk,
Walk,
a, f
a, f
YRBSyy
MTOP, FDOTyy
c, e
a, h; b, f
7917
5–18
MF
US1
Walk, bike, bus, car NPTS, NHTSyy
Harten and Olds (2004) [13]
136
Kerr et al. (2007) [14]
3161
Kerr et al. (2006) [15]
259
Martin et al. (2007) [16]
7433
McDonald (2008) [17]
14553
McMillan (2007) [18]
1244
McMillan (2006) [19]
1074
Merom et al. (2006) [20]
808
11–12
5–18
5–18
9–15
5–18
G3–5y
G3–5y
5–12
MF
MF
MF
MF
MF
MF
MF
MF
Walk,
Walk
Walk,
Walk,
Walk,
Walk,
Walk,
Walk,
Mota et al. (2007) [21]
Nelson et al. (2008) [22]
705
4013
G7–12y
15–17
F
MF
Australia (South Australia)
US (Georgia)
US1
US1
US1
US1
US (California)
Australia (New South
Wales)
Portugal (Averio)
Ireland1
Pabayo and Gauvin (2008)
[23]
Roberts et al. (1997) [24]
3616
9,13,16
MF
6,9
MF
436
0–14
2873
Carver et al. (2005) [3]
Centers for Disease Control
(2005) [4]
Copperman and Bhat
(2007) [5]
de Bruijn et al. (2005) [6]
Evenson et al. (2006) [7]
Evenson et al. (2003) [8]
Ewing et al. (2004) [9]
Fulton et al. (2005) [10]
Gilhooly and Low (2005)
[11]
Ham et al. (2008) [12]
Roberts and Norton (1994)
[25]
Roberts et al. (1996) [26]
Salmon et al. (2007) [27]
Schlossberg et al. (2006)
[28]
Shi et al. (2006) [29]
Sirard et al. (2005) [30]
Spallek et al. (2006) [31]
Timperio et al. (2006) [32]
Timperio et al. (2004) [33]
Towner et al. (1994) [34]
Tudor-Locke et al. (2003)
[35]
Yarlagadda and Srinivasan
(2008) [36]
Yelavich et al. (2008) [37]
Ziviani et al. (2006) [38]
347
yy
bike, skate
bike
bike, bus, car
bike
car, bus
bike
bike
bike
bike
bike
bike
bike,
a, g
SMARTRAQyy
b, f
YMCLSyy
NHTSyy
b, f
b, f
car, bus b, e
yy
Usual travel
5 days; usual
travel
Usual travel, 1
day
3 days
2 days
Usual travel
Usual travel
1 day
z
Usual travel
Usual travel
a, f
a, f
Usual travel
QCAHSyy
Usual travel
School
22.5
c, f
z
School
31–55
MF
Walk, bike, car, bus
Walk, bike, scooter,
inline skates, car,
bus, train
Canada (Quebec)
Walk, car, bus,
public transport
Australia (Victoria, Western Walk, bike, car,
Australia) Canada (Quebec), public transport
NZ (Auckland), Sweden
(Västerbotten), US
(Maryland)
NZ (Auckland)
Walk
b, f
1 day
School
39.7
6, 9
MF
NZ (Auckland)
c, f
1 day
School
44.1
4–13
G6–8y
MF
MF
Australia1
US (Oregon)
b, e
b, f
Usual travel
Usual travel
School
School
30.0
25.1
824
219
871
912
1210
4639
12–14
G5
4–12
5–6, 10–12
5–6, 10–12
11–14
MF
MF
MF
MF
MF
MF
China (Jiangsu)
US (South Carolina)
Australia (Queenalsand)
Australia (Victoria)
Australia (Victoria)
England (Tyne and Wear)
a, f
a, f
c, d
a, b, f
b, f
a, f
z
7 days
Usual travel
Usual travel
Usual travel
z
87.7
16.4
19.3
32.85
83.6–91.9
46.6–74.5
1518
14–16
MF
Philippines (Cebu)
CLHNSyy
Usual travel
School
School
School
School
General
School, play
areas
School
4354
o18
MF
US (California)
5 days
School
18.68
1157
6–13
MF
NZ (Otago)
Walk, bike, car, bus, BATSyy
public transport
Walk
a, d; b, f
1 day; usual
travel
School
61.4
MF
Australia (Queensland)
Walk
School
42.8–52.1
13423
720
287
63
y
G7
Walk, bike, car,
public transport
Walk,
Walk, bike
Walk, bike
Walk, bike
Walk
Walk, bike
Walk, bike
Walk, bike, car, bus,
public transport
Walking, motorized
b, f
z
41.2
a ¼ child self-reported data.
b ¼ parent proxy report data.
c ¼ data reported by parent and child together.
d ¼ data collected by face-to-face interview or show of hands.
e ¼ data collected by telephone survey.
f ¼ data collected by paper questionnaire.
g ¼ data collected by computerized questionnaire.
Data could not be extracted for inclusion in the systematic review.
Data between narrative and tabulations differ, therefore cannot be accurately extracted for inclusion in the systematic review.
y
Sample age range reported as child’s grade in school.
1
Sample is nationally representative.
yy
Data is from a secondary source. Secondary data sources included: YRBS (US Youth Risk Behavior Survey), SMARTRAQ (Strategies for Metro Atlanta’s Regional
Transportation and Air Quality Study), NHTS (National Household Travel Survey), ConsumerStyles Survey, NPTS (National Personal Transportation Survey), MTOP (survey by
Gainsville Metropolitan Transport Planning), FDOT (survey by Florida Department of Transportation), CLHNS (Cebu Longitudinal Health and Nutrition Survey), YMCLS
(Youth Media Campaign Longitudinal Study), BATS (San Francisco Bay Area Travel Survey), QCAHS (Qubec Child and Adolescent Health and Social Survey).
z
Recall period not specified.
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K. Pont et al. / Health & Place 15 (2009) 849–862
855
Table 3
Potential physical environmental determinants of children’s AT.
Variable
Referent
Destination (friends’/play area/shops)
Parks/play areas/sporting venues/ recreation facilities in neighborhood
Convenience stores near home
Distance
Distance (too far)
Distance
Distance (20 + min)
Time taken to walk/bike
Mother’s home-work car travel time
Indirect route
Mixed land use
Limited public transport
Public transport stops close
Dead-end density
Street connectivity
Intersection density
Average block area
Neighborhood (Central City/Small City or Town/Suburb/Urban)
Neighborhood (Metro suburban, 2nd city, town, rural)
Residential/population density/population of town
Road barrier en route
Railroad track barrier en route
Route along busy road
Busy traffic in neighborhood
Child thinks parents perceive busy traffic in neighborhood
Safe roads in neighborhood/safe to walk/ride
Walk and Bike Paths Present
Poor footpath condition
Lack of Controlled/Manned Crossings
Lack of Sheltered Walkways/no protection from weather
Walkability
Good neighborhood aesthetics/trees along street
Weather (good)
Season (summer)
Pollution/Exhaust fumes/bad smells
Not much garbage/litter in neighborhood
A lot of crime in neighborhood
Streets are well lit at night
Walkers/riders can be seen by people in their homes/homes facing street
Loose/stray dogs in neighborhood
Heavy schoolbag
Car parking difficult at school
School
Disagree
Disagree
Increasing
Disagree
Decreasing
o20 min
Increasing
Increasing
Direct
Increasing
Disagree
Disagree
Increasing
Increasing
Decreasing
Increasing
Rural
Urban
Increasing
No
No
No
Increasing
Disagree
Disagree
No
Disagree
Disagree
Disagree
Increasing
Increasing
Poor/raining
Other
Increasing
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
Association
Negative
Non-significant
13
13
1, 7, 14, 21y, 33
21y, 3y
28, 36y, 36y
3y
11y, 12y, 18y, 18y, 20, 28, 32, 36y, 38y
4y, 27
17y
15
9y
36y
28, 32
5y, 14, 15, 36y
32
21y
28
14, 15
28
5y
5y, 29y, 35y, 36y
30y
5y, 14, 15, 17y
28
28
27, 32
32
28
14, 21y
28
35y
9y, 16, 30y
6
20, 32
28
16y, 18y , 32
27, 3y
32
7
7
27
3y, 7, 14 16, 33
17y
5y, 14, 18y
15
10, 16, 23
14, 15, 17y, 22
7, 3y, 32
32
7, 3y
7, 9y, 21y
3y
9y, 10, 15
38y
27, 38y
38y
9y
7, 21y
5y, 38y
5y
38y
7
7
7
7
7
27, 38y
27
27, 32
4
Positive
15
15
16y
Bold variables indicate five or more publications reporting on the variable, which can be used to draw conclusions.
Result was presented as an adjusted odds ratio.
y
Result was not presented as an odds ratio.
Table 4
Potential economic environmental determinants of children’s AT.
Variable
Area-level SES
School SES
Family-level SES
Household income
Parent employed
Parent’s occupation status
Child employed
Car and telephone ownership
Car ownership
TV ownership
Bicycle ownership
Dual income household
Referent
Increasing
Increasing
Increasing
Increasing
No
Increasing
No
No
Increasing
No
Increasing
Disagree
Association
Negative
Non-Significant
Positive
17y
17y, 32, 37
31y
13, 29y
16, 17
13, 32, 36y
2y
35y
37, 32
13, 29y
16, 17, 18y, 23y, 31y, 35y
36y
2y, 21
34y
2, 5y, 9y, 20, 26y, 32, 33, 35y, 37
35y
Bold variables indicate five or more publications reporting on the variable, which can be used to draw conclusions.
Result was presented as an adjusted odds ratio.
y
Result was not presented as an odds ratio.
10
9y, 17y, 18y, 20, 32, 33, 36y
5y
36y
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K. Pont et al. / Health & Place 15 (2009) 849–862
Table 5
Potential socio-cultural environmental determinants of children’s AT.
Variable
Referent
Association
Negative
Ethnicity (African-American/Black)
Ethnicity (Hispanic/Asian/Dutch/Maori/Pacific Islander/Other)
White
White
Ethnicity (African-American, Hispanic, Asian, Pacific Islander, Other)
Ethnicity (Caucasian/non-Hispanic white)
Ethnicity (Asian)
Percentage of non-Hispanic Blacks in neighborhood
Both parents born in country of study site
Language spoken at home (other)
Gender of responsible parent
Only child
Other children in household (0-2)
Parent (divorced/widowed/separated/single)
White
Other
Other
Increasing
1 or no parents born overseas
English
Female
Disagree
3+
Married/de facto/both
parents
Increasing
Increasing
Don’t work
Don’t work
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
Low
Low
Increasing
Increasing
Disagree
Number of adults in household
Relationship with parents/eat meals as a family
Parent drives to work
Parent actively commutes to work
Parent walked to school as a child
Parent concerned about child safety
Parent concerned about traffic safety
Child thinks parent is concerned about safety
Child concerned about safety
Parent worried about child going out on own
Parent worried child will take risks
Parent concerns (high)
Parent barriers to physical activity (e.g., time, finances)
Positive relationship with neighbors
Parent/family support for physical activity
Parents think child’s interaction with others on the way to/from school is
important
Parent education
School affiliation (private/independent/Catholic/Church of England)
School type (secondary)
Limited time/driving is convenient
Friends/people to hang out with in neighborhood/close to home
Many people/children in neighborhood are physically active
Friends think physical activity is important
Friends think physical activity is fun
No other children to walk to school with
No adults to walk to school with
Adult sometimes/always at home after school
Parent has flexible work schedule
Increasing
Public/local authority
Vocational
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
36y
5y
5y
16y, 18y
20
6, 16, 20
Non-Significant
Positive
10, 17
8, 10, 17y
8, 16, 17y
6, 8, 10, 16, 17y,
37
30y
5y, 36y
36y
20
10
16, 32, 36y
37, 37
10, 16, 20, 32
37
6, 16
36y
23y
2, 20
5y, 18y
10
37
20
1, 4y, 27
4y, 27, 33
27, 32
32
16y, 18y
27
1, 15, 21y, 27, 32
21y, 27, 32, 33, 38y
32
32
7
27
10, 16
8, 16, 21,
29y
2, 20, 31y
2, 8, 10, 16, 21, 29y,
31y
6
16y, 18y, 27 38y
3y
7, 16, 21y
16
16
27
27
8, 32
36y
20
37
1, 33
8
15
16
3y, 13
16, 18y
16y, 18y
10
3y, 32
8
Bold variables indicate five or more publications reporting on the variable, which can be used to draw conclusions.
Result was presented as an adjusted odds ratio.
y
Result was not presented as an odds ratio.
Table 6
Potential political environmental determinants of children’s AT.
Variable
Referent
Association
Negative
Parent is confident he/she can influence child’s physical activity
Parent sets television viewing limits
Parent allows child to walk in neighborhood
Parent allows child to bike on own
Parent allows child to take public transport on own
Parents allow child to walk to transit stop
Parents allow unsupervised play
Child is licensed driver
Most drivers exceed speed limit in nearby streets
School doesn’t encourage children to walk to school
Walking school bus at school
Disagree
Increasing
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
Disagree
Non-Significant
16
16
7
7
7
5y, 17y
Bold variables indicate five or more publications reporting on the variable, which can be used to draw conclusions.
Result was presented as an adjusted odds ratio.
y
Result was not presented as an odds ratio.
10
9y, 17y
27
27
37
Positive
7
ARTICLE IN PRESS
K. Pont et al. / Health & Place 15 (2009) 849–862
papers (Carlin et al., 1997; Copperman and Bhat, 2007; Ewing
et al., 2004; Roberts et al., 1996; Timperio et al., 2006, 2004;
Tudor-Locke et al., 2003; Yelavich et al., 2008) reported negative
associations between an increasing number of household cars and
rates of AT among children. The greatest effect of this variable was
observed by Timperio et al. (2004), who showed that girls aged
5–6 years whose families owned two or more cars were 70% less
likely to use AT in the community than those whose families own
no car or one car. However, they found that car ownership was
not significantly associated with AT among 5–6 year old boys.
Seven investigations (Ewing et al., 2004; McDonald, 2008;
McMillan, 2007; Merom et al., 2006; Timperio et al., 2006,
2004; Yarlagadda and Srinivasan, 2008) calculated non-significant
associations. There is accordingly evidence of a convincing
negative association between increasing household car ownership
and children’s AT.
A convincing relationship was also found between increasing
household income and decreased rates of children’s AT. All six
publications (Spallek et al., 2006; Tudor-Locke et al., 2003; Pabayo
and Gauvin, 2008; Martin et al., 2007; McDonald, 2008; McMillan,
2007), which examined this variable found a significant negative
association. Two (Martin et al., 2007; McDonald, 2008) also
reported non-significant and one (Fulton et al., 2005) a positive
association.
Socio-cultural environment
Six of the 40 socio-cultural environmental determinants
identified were analyzed by five or more publications. Three of
these determinants provided evidence for a positive relationship,
and three determinants for an inverse association with rates of AT
among children (Table 5).
Parental concern about traffic safety was the most frequently
examined socio-cultural environmental determinant, with seven
subscribing publications. Three (Centers for Disease Control
and Planning, 2005; Timperio et al., 2004; Salmon et al.,
2007) reported an inverse relationship between this variable
and children’s AT. A non-significant association was reported in
five of the seven enquiries (Timperio et al., 2004, 2006; Ziviani
et al., 2006; Mota et al., 2007; Salmon et al., 2007). Three others
(Timperio et al., 2004, 2006; Kerr et al., 2006) claimed that parent
concerns about traffic safety are associated with higher rates of AT
among children, and two (Alton et al., 2007; Timperio et al., 2004)
found a positive correlation. Evidence for a convincing nonsignificant relationship between this determinant and children’s
AT has thus been established.
The relationship between an increasing level of parents’
educational attainment and rates of AT among children was
examined in seven publications. Four (Evenson et al., 2003; Shi
et al., 2006; Mota et al., 2007; Martin et al., 2007) concluded that
higher parent educational attainment is associated with lower
rates of children’s AT. However, all seven (Carlin et al., 1997;
Evenson et al., 2003; Fulton et al., 2005; Shi et al., 2006; Spallek
et al., 2006; Mota et al., 2007; Martin et al., 2007) reported nonsignificant associations between this determinant and children’s
AT, with one (Fulton et al., 2005) actually reporting a positive
association.
Convincing evidence was found for a positive relationship
between respondents’ with minority ethnic backgrounds (Hispanic,
Asian, Dutch, Māori, Pacific Islander, or Other) and children’s AT.
All six of the publications represented (de Bruijn et al., 2005;
Evenson et al., 2003; Fulton et al., 2005; Martin et al., 2007;
McDonald, 2008; Yelavich et al., 2008) reported a positive
relationship. Three (Evenson et al., 2003; Fulton et al., 2005;
McDonald, 2008) also found non-significant relationships. In the
857
United States, Fulton et al. (2005) found that children with a
Hispanic ethnic background were two and a half times more likely
to walk or bike to school than those with a non-Hispanic White
ethnic background. De Bruijn et al (2005) in the Netherlands and
Yelavich et al. (2008) in New Zealand both found that children
with an immigrant background were two and a half to three times
more likely to use AT than those who did not have an immigrant
background.
The relationship between parents’ concerns about child safety
(kidnapping, crime, strangers, child molestation or bullying, for
example) and children’s AT was examined in six publications.
A non-significant association between this determinant and
children’s AT was reported by five (Martin et al., 2007; Timperio
et al., 2006; Kerr et al., 2006; Mota et al., 2007; Alton et al., 2007;
Salmon et al., 2007). Three (Centers for Disease Control and
Planning, 2005; Alton et al., 2007; Salmon et al., 2007) reported a
negative and none a positive association.
The relationship between parents’ marital status and children’s
AT was examined in five publications and considerable variance in
the finding was observed. Children living with a parent who
described their martial status as divorced, widowed, separated or
single were reported by three publications (de Bruijn et al., 2005;
Merom et al., 2006; Martin et al., 2007) to have lower rates of AT
compared with children with parents who are married, in a de
facto relationship or both live at home. Four studies (Timperio et
al., 2006; Fulton et al., 2005; Merom et al., 2006; Martin et al.,
2007) reported non-significant associations, and one (Fulton et al.,
2005) found that children of parents who described their martial
status as divorced, widowed, separated or single had higher rates
of AT. Martin et al. (2007) found significantly higher rates of
walking or cycling to school among children whose parent/s were
divorced, separated or had never been married compared with
children whose parents are currently married. However, a nonsignificant inverse association was found between children whose
parent had been widowed and rates of walking or cycling to
school. Merom et al. (2006) reported a non-significant association
between parents’ marital status and children walking or cycling
to/from school five to nine times per week. Yet, children whose
parents are single or divorced were significantly more likely to
walk or cycle to/from school 10 times per week compared with
children whose parents are married or living in a de facto
relationship. Significantly higher rates of walking or cycling to
school were found by Fulton et al. (2005) among children who
have one parent living at home compared with those who have
both parents living at home. They also found a non-significant
increase in walking or cycling to school among children who have
a step-parent living at home. In summary, a convincing nonsignificant association was found between parents’ marital status
and AT.
Three of the five (Martin et al., 2007; Timperio et al., 2006;
Yarlagadda and Srinivasan, 2008) concerned publications reported
non-significant associations between children with no other
siblings living at home or being an only child and rates of AT.
Two others (McMillan, 2007; Copperman and Bhat, 2007)
reported a positive association.
Political environment
Eleven variables in the political environment were identified
by eight publications (Evenson et al., 2006; Fulton et al., 2005;
Martin et al., 2007; McDonald, 2008; Salmon et al., 2007; Yelavich
et al., 2008; Copperman and Bhat, 2007; Ewing et al., 2004).
None of the variables identified was examined by five or more
publications. Therefore, no conclusions about the relationship
between aspects of the political environment and rates of AT
among children can be made. See Table 6.
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K. Pont et al. / Health & Place 15 (2009) 849–862
Discussion
Among adults, physical environmental characteristics such as
high population density, street connectivity, land-use mix and
adequate walk/bike infrastructure have been found to foster
AT and collectively have been used to describe walkable neighorhoods (Saelens et al., 2003; Sallis et al., 2004). Socio-cultural
influences such as local safety and social supports, however, have
been found to contribute less explanatory power (Owen et al.,
2004; Wendel-Vos et al., 2007), and political and economic
environmental factors are seldom explored. While there have
been a few, albeit limited, reviews of AT for adults, this is, to our
knowledge the first systematic review of evidence on the
relationships between rates of AT among children and factors in
their physical, economic, political and socio-cultural environments.
Our investigation finds convincing evidence that greater
distance, increasing household income and increasing car ownership were consistently associated with lower rates of AT among
children. Within the locales represented in the 38 included
studies, evidence was found for a convincing relationship between
having a non-white ethnic background and higher rates of AT.
Possible positive associations were also found for the presence of
nearby recreation facilities, and bike and/or walk facilities. This
review supports recent findings from the Panter et al. (2008) nonsystematic review that observed environmental factors such as
safety and social interactions, as well as the presence of facilities,
which assist walking and cycling, are associated with increased AT
in children and adolescents.
Children are deeply embedded in their family contexts, and so
behaviors, such as AT, are influenced by their parents’ attitudes,
values and beliefs. As such, there are factors uniquely relevant to
children, which are not salient in the decisions adults make about
their own AT. Parental attitudes and their influence on children’s
AT became apparent when findings from proxy surveys about
children’s AT were examined in this review. The factors influencing AT are not discrete, but manifest in complex interactions. It is
therefore important to view findings within their national context
and in light of personal attributes and family demands.
For children, parental decisions and family rules can be
interpreted as the political climate in which children live. It is
seldom examined in relation to AT. Parents act as gatekeepers
between observable environments and children’s behaviors
(Davison and Lawson, 2006). How parents perceive environments
in relation to traffic and child safety, their own child/children and
their unique family context (marital status, ethnicity, availability
of cars, or socio-economic status for example) and demands (such
as time and financial demands, as well as participating in extracurricular activities) informs decisions in relation to their children
and AT for schooling or other utilitarian purposes within their
community.
Many developmental factors can make it dangerous for
children to travel independently. They have poorer peripheral
vision, only a developing ability to judge speeds accurately,
limited interpretation of traffic signals and they are more prone
to acting impulsively compared with adults (Chakravarthy et al.,
2007). Hence, governments in many countries have recommended
that children up to the age of 10 years be accompanied by an
adult near a road, and/or should always hold an adult’s hand
while crossing it (Queensland Transport, 2008; Directgov,
2008; National Highway Traffic Safety Administration, 2008;
Accident Compensation Corporation, 2008; The Hospital for
Sick Children, 2008). None of the articles reviewed in this
current paper examined parents’ knowledge of such recommendations or their attitudes towards them if they existed in their
community.
Considerable variation was noted in the measurement of
independent and dependent variables in the studies appraised.
With respect to rates of AT among children, measurement was
achieved through self-reported usual mode of travel, mode of
travel on the day of survey completion, travel diaries over a
number of days, or frequency of mode of travel over a specific time
period, through parent proxy or children’s self-reported data.
Although the validity of self-report data of older children has been
documented (Sallis, 1991), the range of methods used to measure
AT, and the duration of observation and categorization of AT
frequency can confound results. Merom et al. (2006), for example,
found that a child’s language spoken at home, parents’ marital
status and car ownership were significantly associated with
‘regular ‘AT use (10 AT trips a week), but were not significantly
associated with ‘frequent’ AT use (5–9 AT trips per week).
Underutilization of objective measures of the physical and
economic environment was also compounded by the diversity of
referents and category cut-off points evident in their measurement. The measurement of characteristics in the physical
environment, such as distance or street connectivity, was greatly
facilitated by the use of geographic information systems (GIS). Of
the 38 studies reviewed, only four (Kerr et al., 2007, 2006;
Schlossberg et al., 2006; Timperio et al., 2006) used GIS-based
methodologies. The use of objective techniques such as GIS is
a useful way accurately to examine the observable physical
environment, and can assist in distinguishing between the
influence of the observed and perceived environment and
engagement in AT. Through accurate measurement of the
observable environment, any differences between the influence
of the observed or perceived environment on AT, along with
interventions to increase rates of AT among children, can be
targeted more effectively. Nuances evident in the language used in
questionnaires could also have influenced the accurate synthesis
of self-reported data. Depending on the phrasing of a question
(for example, regarding parental concerns about traffic safety),
the response could vary from being a pure correlation between an
environmental factor and AT to a perceived barrier to AT, further
confounding findings in the scientific literature. These nuances
may have impacted the results regarding variables such as
parental concerns about child safety and traffic safety, weakening
the significance of the results reported.
As highlighted earlier, factors impacting AT need to be
considered in the context of the country in which the study has
been undertaken and the ethnic groups involved. Roberts et al.
(1997) surveyed 13,243 children aged 6–9 years residing in five
countries (Australia, Canada, New Zealand, Sweden, and the
United States). They reported considerable variation by country
in rates of children’s AT to school (31–55%) and from school
(33–69%). Research foci tend to be country-specific and are
therefore indicative of the social and political context. Seven of
the 39 (17.9%) variables represented by five or more publications
are exclusively examined in one country. Mixed land-use, street
connectivity, having an African-American or black ethnic background, and parent/family support for physical activity were
exclusively examined by studies conducted in the United States.
Lack of controlled/manned crossings, positive relationship with
neighbors, and school affiliation were exclusively examined solely
by studies originating in Australia. Furthermore, the majority of
research has been conducted in developed nations thus limiting
generalizability. Additionally, only articles published in English
were included in this review, which would almost certainly limit
its capacity for generalization.
As the majority of included studies were cross-sectional, causal
relationships between AT and the physical, economic, sociocultural and political environments cannot be attributed. Longitudinal work on the effectiveness of certain projects aimed to
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K. Pont et al. / Health & Place 15 (2009) 849–862
increase AT, such as Safe Routes to School (Boarnet et al., 2005a, b;
Staunton et al., 2003) and the Walking School Bus (Collins and
Kearns, 2005; Kearns et al., 2003; Kingham and Ussher, 2007) has
started to emerge. However, enquiries seldom report environmental factors, and therefore are not included in this review.
Self-selection of families which value active lifestyles could
also influence the apparent influence of the environment on AT.
Personal factors and family demands also impact AT but are
possibly unrelated to the environment. Future research using
prospective and longitudinal study designs would be needed to
clarify the complex nature of the relationships amongst environment, personal factors and children’s AT.
Conclusion and future research directions
This review highlights that many environmental factors
influence rates of AT among children. The only environmental
variable that has a convincing positive association with AT is that
of non-white ethnic background. Environmental variables identified as having convincing inverse associations include greater
distance, increasing household income and increasing car ownership. A summary is shown in Table 7.
Current efforts in transportation and health research should
continue to build the evidence base to determine the environmental influences and nature of relationships with AT among
children and to determine the most effective strategies to promote
children’s AT. In undertaking further research, particular attention
should be given to the use of multi-level study designs including
objective measures of the physical environment, as well as the
parents’ and child’s perceptions of environments so that comparisons between objective and perceived attributes of environments,
and their relative impact on AT can be clarified. Overall, allied
859
health professionals, community development workers and city
planners should appreciate the complexity of variables promoting
or inhibiting children’s AT. They should avoid poorly researched
initiatives lest scarce funding and resources be underutilised. This
investigation has shown there is an apparent plethora of knowledge on children’s AT but that little of it is specifically relevant
and, even this segment advances potentially equivocal findings.
Systematic reviews are therefore and economical way to identify
focal studies and ensure a measured and informed approach to
future research and practice.
Acknowledgement
We would like to thank Queensland Health as part of the Eat
Well-Be Active evaluation for their financial support of this
project.
Appendix A
Eligibility screening questions
1. Is there data for children’s non-motorised transport for access
within the community?
& Yes
& Unsure
& No
(Exclude)
2. Are all participants aged 5–18 years? If the study has a mixed age- & Yes
group, is over 50% of data able to be extracted for children aged & Unsure
5–18 years?
& No
(Exclude)
3. Is the study a cross-sectional study, randomised controlled trial, & Yes
quasi-randomised controlled trial, non-randomised controlled & Unsure
trial or cohort study?
& No
(Exclude)
Table 7
Summary of environmental determinants represented by 5 or more publications.
Environment type
Variable
Summary
rating
Physical environmental
determinants
Parks/play areas/sporting venues/ recreation
facilities present in neighborhood
Increasing distance
Increasing mixed land use
Increasing residential/population density
Neighborhood (Central city/small city/town/
suburb/urban)
Walk and bike paths present
+
0
0
0
Increasing household income
Increasing car ownership
4. Does the study explore environmental (physical, economic,
political or socio-cultural) factors Influencing children’s nonmotorised transport for access within the community?
& Yes
& Unsure
& No
(Exclude)
Final Decision
& Include
& Unsure
& Exclude
+
Appendix B
Economic
environmental
determinants
Socio-cultural
environmental
determinants
Eligibility assessment
Ethnicity (Hispanic/Asian/Dutch/Maori/
Pacific Islander/Other)
++
1. Does this study answer the questions: ‘‘Is there a relationship
& Yes
between the physical, economic, socio-cultural or political
& No
environments and children’s non-motorised transport for access (Exclude)
within the community?
Only child
Parent (divorced/widowed/separated/single)
Parent concerned about child safety
Parent concerned about traffic safety
Increasing parent education
0
0
0
0
0
2. Is the study a cross-sectional study, randomised controlled trial, & Yes
quasi-randomised controlled trial, non-randomised controlled & No
trial or cohort study?
(Exclude)
++ ¼ convincing positive association.
+ ¼ possible positive association.
0 ¼ non-significant association.
¼ possible negative association.
¼ convincing negative association.
3. Are the subjects aged 5–18 years at the commencement of the
study? If the study has mixed age groups, are over 50% of the
participants aged 5–18 years and data able to be extracted for
this age group?
& Yes
& No
(Exclude)
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4. Is there empirical data for the physical, economic, socio-cultural & Yes
or political environments with respect to children’s non& No
motorised transport for access within the community?
(Exclude)
5. Is there empirical data for children’s non-motorised transport for & Yes
access within the community (not including county/state/
& No
national averages)?
(Exclude)
Final Decision
& Include
& Exclude
8. Have the measurement of outcome, independent and control variables been
clearly described?
If the article clearly describes the study variables/outcome measures (e.g., includes
form of data collection—if pedometer: how many hours per day, days per
week; if survey/questionnaire—types of questions included) - YES
If article is unclear in description of part or all of variable measurement - NO
9a. Are the variables measured with appropriate and accurate methods?
If data collected is appropriate to answer research questions/objectives, and
methods are considered accurate/acceptable (e.g., self-report survey, parentreport survey, pedometer or travel diary - YES
If data collection methods are not appropriate to answer research questions/
objectives, or inaccurate methods of data collection are used - NO
Appendix C
Assessment criteria for quality appraisal
Questions 1–4 relation to the study’s description of the sample
Question 5 refers to the sampling methods used in the study
Questions 5 and 7 refer to the study’s methodology
Questions 8 and 9 relate to the study’s measurement of
variables
Question 10 relates to the external validity of the measurement
tools utilised in the study
Questions 11 and 12 refer to bias in the study relating to
blinding methods and follow-up of participants
Assessment Criteria for Quality Appraisal
Adapted from the Checklist for the Evaluation of Research Articles (DuRant, 1994)
1. Are the criteria for inclusion of subjects clearly described?
If the article reports criteria for recruitment or inclusion of subjects - YES
If the study does not report criteria for recruitment or inclusion of subjects - NO
2. Has the study sample been clearly described?
If the article has percentage/ratio/number of males/females AND breakdown of
ages (by group or year)/mean and SD - YES
If the study does not report percentage/ratio/number of males/females or
breakdown of ages of subjects - NO
3. Is the study sample appropriate to the study objectives?
If the subjects match the study objective (e.g., are typically developing and go to
school if examining AT to school) - YES
If the study sample does not match the study objective (e.g., examines typically
developing children, but reporting for children with disabilities) - NO
4. Does the study have a sample size calculation?
If the article reports a sample size calculation being carried out - YES
If the article does not report a sample size calculation - NO
5a. How was the group sample selected? Choose best option.
If group was chosen non-randomly for convenience - CONVENIENCE SAMPLING
If group was chosen non-randomly for a particular purpose (e.g., rural vs. urban
school) - PURPOSEFUL SAMPLING
If group was chosen using randomisation - RANDOM SAMPLING
5b. How were the individuals selected to participate? Choose best option
If all children in a particular group were asked to participate (e.g., all in particular
school/neighborhood/grade/take certain mode to school)- ALL IN
PARTICULAR GROUP
If children were selected for convenience (e.g., in school choir) - CONVENIENCE
If children were selected using methods of randomisation - RANDOM
6. Is the study design (methodology) clearly described?
If the article clearly describes the study methodology (e.g., cross-sectional, RCT,
etc.) - YES
If the study methodology is unclear - NO
7. Does the design of the study adequately answer the research objectives?
If the study design can answer the research questions/objectives - YES
If the study cannot answer the research questions/objectives - NO
9b. Do the operational definitions match the theoretical variables?
If the study’s variables/background info/definitions are congruent with the
accepted definitions/indicators of that variable (e.g., SES measured by
household income, number of cars/household goods, maternal/paternal
education) - YES
If the study’s variables/background info/definitions are incongruent/contradict
accepted definitions/indicators of that variable - NO
10a. Have scales relevant to the review undergone reliability or validity
testing?
If article states that the scales relevant to the review (e.g., anxiety/worry/
motivation scales) have undergone reliability testing - RELIABILITY ONLY
If article states that the scales relevant to the study have undergone validity testing
-VALIDITY ONLY
If article states that the scales relevant to the review undergone reliability and
validity testing - RELIABILITY AND VALIDITY
If the article does not state that scales relevant to the review have undergone
reliability/validity testing - NO
If no scales have been used (i.e., only observable measures, e.g., household income,
pedometer counts, sex, connectivity) - N/A
10b. If the scale has been validated, have the scales relevant to the undergone
standardisation for the particular population?
If the article states standardisation procedures have been carried out on children
for the scale - YES
If the article does not state that scales relevant to the review undergone
standardisation on children, or any standardisation procedures - NO
If the scales have not been validated - N/A
11. Were outcome variables measured using appropriate ‘‘blinding’’ methods?
If the study states it used methods to blind results for appropriate variables (e.g.,
taping pedometers so data could not be viewed by participants) - YES
If the article does not state blinding was used (where variables could be blinded);
If blinding is not appropriate for variables (e.g., surveys/questionnaires) - N/A
12a. Is the response rate 85% or more?
If the article states that more than 85% of people approached participated in the
study - YES
If the study’s refusal/non-respondents rate was more than 15% - NO
12b. Is the follow-up response rate 85% or more?
If the number of drop-outs is 85% or more at follow up - YES
If drop-out rate is more than 15% - NO
If there was no follow up in the study - N/A
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