Associations Between Environmental Characteristics and ActiveCommuting to School Among Children: a Cross-sectional Study

Marie-Jeanne Aarts & Jolanda J. P. Mathijssen &

Johannes A. M. van Oers & Albertine J. Schuit

# International Society of Behavioral Medicine 2012

AbstractBackground Active commuting to school can contribute toactive living among children, and environmental character-istics might be related to transportation mode to school.Purpose The purpose of this study is to explore the associ-ation between physical and social environmental character-istics in the home, neighborhood, and school environmentand walking and bicycling to school.Method Data were collected among parents (n05,963) ofchildren of primary schools in four Dutch cities. Parentsreported mode of transportation to school, and individual,home environmental, neighborhood, and school environ-mental characteristics. Social as well as physical character-istics were included for the home and neighborhoodenvironment. Multilevel multinomial logistic regressionanalyses were conducted to quantify the association be-tween environmental characteristics and walking and bi-cycling to school.

Results Three quarter of all children usually commute toschool by active transportation, but age and distance fromhome to school were important prerequisites. Besides homeenvironmental characteristics, lower neighborhood socio-economic status was negatively associated with walking[odds ratio (OR)00.51] and bicycling (OR00.86). Per-ceived social safety was positively related to walking andbicycling (OR01.04 for both), as was perceived social co-hesion (OR01.04 and 1.02 for walking and bicycling).Living in the city center was positively associated withwalking (OR01.91), whereas living in a city green neigh-borhood was negatively associated with walking and bi-cycling (OR00.48 and 0.76, respectively). Traffic safety asperceived by school boards was positively associated withbicycling (OR01.25).Conclusion This study shows that there is a relation betweenseveral characteristics in the home, neighborhood, and schoolenvironment and walking and bicycling to school amongDutch primary school children. Especially the social neigh-borhood characteristics were related to active commuting.Therefore, apart from providing a physical infrastructure thatfacilitates safe and convenient active commuting to school,policy makers should be aware of opportunities to facilitateactive commuting by social initiatives in local communities.

Keywords Children .Physical activity .Active commuting .

Environment

Introduction

As in many other western countries, the majority of primaryschool children in The Netherlands do not meet the recom-mended health guidelines for physical activity [1]. Becauseof the health risks related to this lack of physical activity [2,3], it is important to find appropriate ways to stimulate

M.-J. Aarts : J. J. P. Mathijssen : J. A. M. van OersTilburg School of Social and Behavioral Sciences, DepartmentTranzo, Scientific Center for Care and Welfare, Tilburg University,PO Box 90153, 5000 LE Tilburg, The Netherlands

M.-J. Aarts : J. A. M. van Oers :A. J. SchuitNational Institute for Public Health and the Environment,Public Health and Health Services Division,PO Box 1, 3720 BA Bilthoven, The Netherlands

M.-J. Aarts (*)CAPHRI School for Public Health and Primary Care,Department of Health Services Research, Maastricht University,PO Box 616, 6200 MD Maastricht, The Netherlandse-mail: mj.aarts@maastrichtuniversity.nl

A. J. SchuitDepartment of Health Sciences and EMGO Institute for Health andCare Research, VU University Amsterdam,De Boelelaan 1105,1081 HVAmsterdam, The Netherlands

Int.J. Behav. Med.DOI 10.1007/s12529-012-9271-0

physical activity among children. Active commuting to andfrom school is an opportunity for children to be physicallyactive on a regular basis. Accelerometer data have shownthat children that go to school by means of active commut-ing are more physically active when compared to childrenthat use motorized travel, both during the journey fromhome to school itself [4], as well as during other timeperiods [5]. Maximizing the number of children that activelycommute to school can therefore be seen as a promisingpublic health strategy, to which also policy sectors outsidethe public health domain may contribute [6, 7].

According to the social ecology theory of health fromDahlgren and Whitehead [8], in addition to individual char-acteristics, both social and physical environmental character-istic may influence people’s health behavior, such as physicalactivity. With regard to active commuting to school, researchindicates that apart from individual characteristics of the childand the parents, environmental characteristics such as real andperceived safety and walking and bicycling facilities are re-lated to the mode of transportation to school [9, 10], andhence, optimizing (the perception of) these environmentalcharacteristics may be a valuable policy approach to increasethe number of children involved in active commuting.

Because parents act as gatekeepers for their children’scommuting behavior [11], both objective environmentalcharacteristics such as urban density, mixed land use plan-ning, proximity, and connectivity as well as parents’ per-ception of their living environment such as road safety mayplay an important role in the choice for transportation modeto school [11–13]. Moreover, not only the physical environ-mental characteristics but also social environmental charac-teristics may be related to active commuting to school [13].Panter and colleagues further indicate that three componentsof the living environment should be considered in relation tochildren’s commuting behavior: the neighborhood aroundthe home, the route from home to school, and the schoolenvironment [14]. It is therefore important to consider allthese different types of environmental characteristics (ob-jectively measured vs subjectively measured, physical andsocial environmental characteristics, and home, neighbor-hood, and school setting) when studying the associationbetween environmental characteristics and active commut-ing behavior of children. Furthermore, specific environmen-tal characteristics may be related to different forms of activecommuting, i.e., walking or bicycling [15, 16].

For policy makers to optimize the revenues of theirenvironmental policies aimed at stimulating active commut-ing among children, it is important to have insight into thecomplex relation between environmental characteristics andactive commuting to school. Much research addressing theabovementioned themes has been traditionally conducted inthe USA [9, 10] and Australia [17–20]. European countriesand cities however have a different infrastructure e.g. in

terms of street connectivity pattern, and therefore, Europeanstudies addressing this theme are specifically important aswell [14]. A UK study by Page et al. for example showedthat shorter distance from home to school was related toactive commuting to school [21]. Bringolf-Isler et al.showed that major road crossings and distance were signif-icantly related to non-active transportation and that increas-ing age of the child, daycare attendance, parental safetyconcerns, number of cars in the household, and belongingto French-speaking population were significantly associatedwith increased regular car trips in a Swiss setting [22].Panter et al. have shown that in a UK setting, parentalattitudes and safety concerns, the presence of social supportfrom parents and friends, and parent-reported neighborhoodwalkability were predictors of active commuting, with chil-dren receiving peer and family support and living in sup-portive environments (e.g., neighborhoods with high socialcohesion) being more likely to walk or cycle [23]. Thesestudies show that the relation between the environment andactive commuting behavior may be even country specific,and in order to assist local policy makers in designingpolicies that stimulate active commuting among children,country-specific results are warranted.

Therefore, the aim of this study is to explore the correlationbetween (perceived) characteristics in the home, neighbor-hood, and school environment related to active commutingto school among Dutch children. This study includes social aswell as physical environmental characteristics and examinesthe association with both walking and bicycling.

Methods

Study Setting

Cross-sectional data were collected between September2007 and January 2008 from parents of children of 42primary schools in four medium-sized Dutch cities in thesouthern part of The Netherlands. The number of inhabitantsranges from 77,450 to 201,259, and the degree of urbaniza-tion ranges from 727 to 1,716 citizens per km2. Althoughone city was somewhat smaller and less urbanized com-pared to the other cities, the municipalities were comparableregarding the composition of their population such as thepercentage of non-Western immigrants (9.9–13.4 %) andpercentage of inhabitants aged 0–14 years (16.7–17.6 %).The selection procedures and characteristics of the partici-pating cities are described in more detail elsewhere [24].

Study Population

Data were collected among parents of children aged 4–12 years. In the Netherlands, children in this age group attend

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primary school, which, in most cases, is close to or within thearea of residence.We invited all regular primary schools in thefour cities that were not already participating in projects aimedat stimulating physical activity among children (n0115). Wefirst invited them by letter, followed by a telephone call. Of the115 invited schools, 42 agreed to participate.

As outlined elsewhere [24], the schools in our study wererepresentative of the total population of schools in the par-ticipating municipalities in terms of school size, socioeco-nomic status (SES), and the type of neighborhood. Becauseno medical or physical measurements were conducted andconsidering the negligible (psychological) burden to fill inthe questionnaire, no ethics approval was required accordingto the Dutch Central Committee on Research InvestigatingHuman Subjects. Via a take-home envelope handed to theirchildren, parents were given written information aboutthe study and by returning the questionnaire they gaveconsent for the inclusion of their data in the study. Intotal, 11,094 parents were provided with a question-naire. Response rate was 60 %, resulting in 6,624returned questionnaires. During data entry, 12 question-naires could not be read, and 11 questionnaires wereremoved because they were completely empty, leaving6,601 questionnaires for analysis.

Questionnaires and Measures

This study encompassed a questionnaire for parents and aquestionnaire for the school board. The questionnaire forparents was based on questionnaires used in previous Dutchresearch [25, 26] and included the following topics: usualmode of transportation to school, individual factors (genderand age of the child, and parental report of height andweight of their child), social home environmental factors(parental education, parental ethnic background, workingsituation of parent(s), number of siblings, number of daysper week that the child goes home after school time), phys-ical home environmental characteristics (distance fromhome to school and number of cars in the household),perceived social neighborhood characteristics (social safety,social cohesion, degree of unoccupied houses, presence oftrash and litter, and presence of dog dirt), perceived physicalneighborhood characteristics (degree of high- vs low-risebuildings, presence of green, presence of water, traffic situ-ation, quality of sidewalks and bike lanes, and diversity ofroutes), and perceived physical characteristics of the schoolenvironment (traffic safety around school). In addition, typeof neighborhood and neighborhood SES were determinedbased on the child’s postal code [27, 28] (postal codereported by parents), and additional physical school envi-ronmental characteristics (traffic safety around school andsufficiency of bicycle shed at school as perceived by schoolboards) were derived from a questionnaire provided to the

board of the participating schools. The exact formulation ofthe items in the questionnaire, the calculation of all variablesin the analysis, and the descriptive data for each variable(such as mean or frequencies) are summarized in theAppendix.

Conceptually related items were summed when internalconsistency was acceptable (Cronbach’s alpha>0.6); other-wise, items were treated separately. Missing values were notimputed, unless it concerned a missing value on one of theitems of a sum score consisting of more than four items. Inthat case, the missing value was replaced by the mean of theother values. If more than one item was missing within onesum score, the sum score was not calculated. Throughoutthe questionnaire for parents, “neighborhood” was definedas the area that could be reached by parents in 10 to 15 minby foot or in 5 to 8 min by bike from the respondent’sresidence (street network distance). This matches the gener-al perception of a typical Dutch neighborhood and, in com-parison with distances in meters, distances in minutes aremore easily interpreted by the respondents [29, 30]. Themultinomial outcome measure is usual mode of transporta-tion to school encompassing the following categories: (1)walking, (2) bicycling, and (3) the reference category inac-tive transportation (on the back of parent’s bike or in abuggy, on the back of parent’s moped/scooter, brought bycar, or by bus).

Statistical Analyses

Questionnaires were excluded from further analyses becauseof missing values on the outcome measure transport modal-ity (n0366), and three important potential confounders: ageof the child (n02), distance from home to school (n0113),and parental education (n0154). Furthermore, question-naires of children living more than 3 days per week onanother address than the address described in the question-naire (n035) and questionnaires of children with severedisabilities that could hamper active commuting (n060)were removed. Some questionnaires had to be removedbecause of more than one exclusion criterion, and thefinal data base thus encompassed 5,963 respondents.Based on our power analysis described elsewhere [24],our study provided adequate power to detect smalleffects (f 200.02).

Descriptive analyses were conducted with SPSS, version17.0. T tests and chi-square tests were performed for con-tinuous and categorical variables respectively to assess dif-ferences (p<0.05) in characteristics (age, gender, BMI of thechild, and transport modality of the child, and parentaleducation and net household income) between the respond-ents that were included in the final analyses (n05,963)versus the respondents that were excluded for analysis(n0638).

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Multilevel multinomial logistic regression analyses wereconducted with SAS version 9.2, using PROC GLIMMIX.Inactive transportation was regarded as the reference cate-gory in all analyses. Random intercepts were allowed tocorrect for the clustering of the data within schools in allanalyses. After crude bivariate analyses in which the asso-ciation of each individual independent variable with modeof transportation was calculated, the association betweeneach individual independent variable with mode of trans-portation was calculated adjusted for age of the child anddistance from home to school (which were considered asimportant preconditions for active commuting to school)and parental education (which is considered as a goodindicator for SES in the Netherlands [31, 32] and was seenas an important possible confounder). In all analyses, paren-tal education was indicated by highest completed level ofeducation of the parent who filled in the questionnaire; inthe majority of cases, this was either the biological mother(86.4 %) or biological father (12.5 %).

Finally, in order to explore the association between envi-ronmental characteristics and active commuting to schooladjusted for the other environmental characteristics, a mul-tilevel forward sequential multinomial logistic regressionanalysis was performed. In a sequential analysis, variablesenter the equation in a theory-based order [33]. According tothe theoretical framework of Dahlgren and Whitehead [8], itwas assumed that proximal variables (individual character-istics and home environmental characteristics) are moreclosely related to children’s active commuting behavior thandistal characteristics (neighborhood and school environ-ment). Based on previous results from this research project[34], it was assumed that social neighborhood character-istics were more closely related to active commuting thanphysical neighborhood characteristics. Hence, the first stepof the sequential analysis consisted of a block of proximalvariables (individual and both social and physical homeenvironmental variables), followed by the second stepwhich introduced a block of distal (neighborhood) socialvariables to the model. During the third step, a block ofdistal (neighborhood) physical variables was added to themodel. The last step comprised the introduction of a blockof physical school environmental variables to the model.All steps in the sequential analysis were adjusted for ageof the child, distance from home to school, and parentaleducation. In order to prevent important variables to beexcluded from the model in a forward analysis too easily,a more liberal probability level of p>0.15 was chosen todecide on deletion of variables from the model [33, 35].The sequential analyses ended when all variables in themodel reached significance. In the final multivariate mod-els, only those variables with a p value <0.05 are shown.Prior to entry into the multivariate models, correlationsbetween (continuous) independent variables were checked

for collinearity, but none of the correlations exceeded theexclusion criterion of r>0.5 [33]. Because there werehardly any differences in characteristics between boysand girls and because there was no significant associationbetween gender and mode of transportation to school, datafor boys and girls were combined in the regressionanalyses.

Results

With regard to selective dropout, there were no differencesin age, gender, BMI, and mode of transportation of the child(walking, bicycling, inactive transportation) of the respond-ents that were included in the analyses, compared to thoserespondents that were excluded for analysis. However, therespondents that were excluded for analyses had a signifi-cant lower parental education level and net household in-come. Table 1 shows the characteristics of the studypopulation in terms of age, gender, BMI, the percentage ofoverweight and obese children (as determined by age- andgender-specific cutoff points as provided by Cole et al.[36]), parental education level, and net household income.This table also shows that approximately three quarter of allchildren usually commute to school by means of activetransportation (walking or cycling). The descriptive data inFig. 1 show that with increasing age, fewer children aregoing to school by means of inactive transportation (broughtto school by car or on the back of parent’s bike, moped, or ina buggy), in favor of children commuting to school by bike.Figure 2 depicts that within a distance of 1 km betweenhome and school, the majority of children (approximately70 %) commutes to school by foot. With increasing distanceup to 5 km from home to school, fewer children go to schoolby foot, in favor of children going to school by bike or byinactive transportation.

The results from the bivariate analyses are not shown, butcan be obtained from the corresponding author on request.Tables 2 and 3 summarize the results of the adjusted andfinal multivariate multilevel analyses and show the associa-tion between several environmental characteristics and ac-tive commuting to school. Only statistically significantassociations (p value <0.05) are shown, but the nonsignifi-cant results can be obtained from the correspondingauthor on request. The results of the final multivariateanalyses will be addressed per block of variables below(Tables 2 and 3).

Individual and Social and Physical Home EnvironmentalCharacteristics

In the final multivariate analyses, age of the child (years)was positively related to walking [odds ratio (OR)01.31]

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and bicycling (OR01.71) to school, whereas parental edu-cation was positively related to bicycling only (OR01.10).

Living in a single-parent family with the parent working 12–36 h per week was negatively associated with walking toschool (OR00.61). The number of siblings was positivelyrelated to walking (OR01.44) and bicycling (OR01.24), aswell as the number of days per week the child goes directly tohome after school (OR01.18 and 1.13 for walking and bi-cycling, respectively). The distance from home to school(kilometers) was negatively related to walking (OR00.18)and bicycling (OR00.70) to school, as well as thenumber of cars in the household (OR00.58 and 0.49for walking and bicycling, respectively).

Social Neighborhood Characteristics

A lower neighborhood SES was negatively associated withwalking (OR00.51) and bicycling (OR00.86) to school.Perceived social safety was positively related to walkingand bicycling to school (OR01.04 for both walking andbicycling), as was perceived social cohesion (OR01.04and 1.02 for walking and bicycling, respectively). The per-ceived presence of dog dirt was positively associated withwalking to school (OR01.19).

Physical Neighborhood Characteristics

Living in a city center type of neighborhood was pos-itively associated with walking to school (OR01.91),whereas living in a city green type of neighborhoodwas negatively associated with walking (OR00.48) andbicycling (OR00.76) to school. The perceived presenceof green was negatively associated with walking toschool (OR00.89), whereas the perceived diversity ofroutes was positively associated with bicycling to school(OR01.12).

Table 1 Characteristics of the study population

Total(n05,963)

Boys(n03,001)

Girls(n02,950)

Age (years) 7.8 (2.4) 7.8 (2.4) 7.8 (2.4)

BMIa (kg/m2) 16.3 (2.7) 16.3 (2.7) 16.2 (2.6)

Overweightb (%) 9.9 8.5 11.3

Obesityb (%) 2.8 3.1 2.4

Parental education (%)

Lowc 28.3 28.3 28.2

Intermediated 35.3 35.0 35.7

Highe 36.4 36.7 35.1

Net household income(Euros per month)

2,788 (1,351) 2,797 (1,326) 2,781 (1,376)

Usual mode of transportation to school

% Walking 43.4 43.5 43.2

% Bicycling 31.8 32.2 31.4

% Inactive 24.8 24.3 25.4

Values are mean (SD), unless otherwise specified. Twelve respondentshad a missing value on the gender of their childa Based on parental self-report of height and weight of their childb Based on age- and gender-specific cutoff points as provided by Coleet al. [36]c No education, primary education, lower general secondary education,or lower vocational educationd Higher general secondary education, pre-university education, orintermediate vocational educatione Higher vocational education or university

Fig. 1 Usual mode of transportation to school by age. In The Nether-lands, children aged 4–12 years are educated together at the sameprimary school. In the current study sample, 3 children in the lowestgrade were aged 3 years and 12 children in the highest grade were aged13 years. For this figure, these children were included in the lowest(4 years) and highest (12 years) age groups, respectively

Fig. 2 Usual mode of transportation to school by distance from hometo school

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Table 2 Association between environmental characteristics and walking to school

Variable Range/coding Adjusteda analyses Final multivariateb analysesOR (CI) OR (CI)

Individual and social and physical home environmental characteristics

Gender 0–1 (00boy, 10girl)

Age of the child (years) 3–13c 1.33 (1.29–1.38) 1.31 (1.26–1.37)

Parental education 1–8 0.95 (0.90–1.00)

Parental ethnic background 0–1 (00Dutch,10non-Dutch)

1.63 (1.24–2.14)

Working situation of parentsd Dummy coded: two-parentfamily, one parentworks 36 h per weekor more, one parentworks 12–36 h perweek is reference

0.58 (0.39–0.85)(single-parent family,parent works 12–36 hper week)

0.61 (0.40–0.94)(single-parent family,parent works12–36 h per week)

1.44 (1.16–1.79)(two-parent family,one parent works36 h per week ormore, one parentworks less than12 h per week)

Number of siblings 0–5 1.47 (1.33–1.63) 1.44 (1.29–1.61)

Distance from home to school (km) 0.5–6.0 0.19 (0.17–0.21) 0.18 (0.16–0.21)

Number of days childgoes home after school

0–5 1.21 (1.13–1.30) 1.18 (1.09–0.27)

Number of cars in the household 0–2 0.69 (0.59–0.81) 0.58 (0.48–0.69)

Social neighborhood characteristics

Neighborhood SES −4−4 (higher scoresrepresent lower SES)

0.58 (0.51–0.67) 0.51 (0.44–0.60)

Social safety 5–25 1.04 (1.02–1.07) 1.04 (1.01–1.07)

Social cohesion 6–30 1.04 (1.02–1.06) 1.04 (1.02–1.07)

Degree of unoccupied houses 1–5

Presence of trash and litter 1–5

Presence of dog dirt 1–5 1.15 (1.09–1.22) 1.19 (1.12–1.27)

Physical neighborhood characteristics

Type of neighborhoodd Dummy coded: citynon-center is referencee

1.91 (1.06–3.47)(city center)

0.48 (0.34–0.68)(city green)

Degree of high- vs low-rise buildings 2–10 (higher scorerepresent morehigh-rise buildings)

Presence of green 1–5 0.89 (0.82–0.98)

Presence of water 1–5

Traffic situation 5–25 (higher scoresrepresent less favorabletraffic situation)

Quality of sidewalks and bike lanes 4–20

Diversity of routes 1–5 1.09 (1.01–1.17)

Physical school environmental characteristics

Traffic safety around school(as perceived by parents)

0–1 (0–unsafe, 10safe) 0.73 (0.61–0.88) 0.70 (0.58–0.85)

Traffic safety around school(as perceived by school board)

1–5 (higher scoresrepresent higherperceived safety)

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Physical School Environmental Characteristics

The traffic safety around school as perceived by parents wasnegatively associated with walking and bicycling to school(OR00.70 and 0.72, respectively) indicating that childrenfrom parents that perceive the school environment as safeare less likely to walk or bicycle to school. Conversely, thetraffic safety around school as perceived by the school boardwas positively associated with bicycling to school (OR0

1.25). The sufficiency of the school’s bicycle shed (as per-ceived by the school board) was positively associated withwalking to school (OR01.91) and negatively associatedwith bicycling to school (OR00.69).

Discussion

Main Findings of This Study

This study showed that apart from characteristics in thehome environment such as the number of siblings, thenumber of days a child goes home directly after school,and the number of cars in het household, also characteristicsof the physical and social neighborhood environment arerelated to active commuting among Dutch primary schoolchildren. Neighborhood SES, perceived social cohesion,and perceived social safety were positively associated withactive commuting, as well as physical neighborhood char-acteristics such as living in a city center type of neighbor-hood type and the diversity of routes showed significant

positive associations with active commuting. Perceivedpresence of green was negatively associated with walkingand bicycling to school.

Discussion of the Main Findings and Comparisonwith Previous Research

This study confirmed that short distance from home toschool and a higher age of the child are factors related toactive commuting to school, a finding already known fromprevious studies [4, 19, 22]. With regard to the home envi-ronmental characteristics, this study showed that the numberof siblings was positively related to walking and bicyclingto school. This might be explained by the fact that siblingswalk together to school (safety in numbers), but as data fromother studies are somewhat inconsistent [18, 19], this topicrequires further study. In contrary to the general idea thatparents who are working (nearly) full time are more likely todrive their children to school by car [12, 22, 37], this studydid not show a consistent relation between the workinghours of the parents and their children’s mode of transpor-tation to school. This may be partly explained by the lownumber of respondents in some of the working situationcategories. We did find a positive association between thenumber of days a child goes home after school and walkingand bicycling to school. This might indicate that not the totalnumber of working hours by parents but the opportunity tosupervise the child during the journey from school to homeor a parent being present at home after school time may bean important factor related to active commuting. The

Table 2 (continued)

Variable Range/coding Adjusteda analyses Final multivariateb analysesOR (CI) OR (CI)

Sufficiency of bicycle shed at school(as perceived by school board)

1–4 1.44 (1.12–1.84) 1.91 (1.28–2.87)

All analyses are multilevel (random intercepts were allowed) to correct for the clustering of the data within schools. Only statistically significantassociations (p value<0.05) are shown

OR odds ratio, CI confidence intervala Adjusted for age of the child, distance from home to school, and parental educationb Adjusted for age of the child, distance from home to school, and parental education. In addition, the final multivariate model included thefollowing independent variables: working situation of parents, number of siblings, number of days child goes home after school, number of cars inthe household, neighborhood SES, social safety, social cohesion, presence of dog dirt, type of neighborhood, presence of green, diversity of routes,traffic safety around school (as perceived by parents), traffic safety around school (as perceived by school board), and sufficiency of bicycle shed atschool (as perceived by school board). Only those variables that show a statistical significant association with walking to school are shown in thistablec In The Netherlands, children aged 4–12 years are educated together at the same primary school. In the current study sample, 3 children in thelowest grade were aged 3 years and 12 children in the highest grade were aged 13 yearsd Only the dummy categories that show significant associations (p value <0.05) with walking to school are displayed (dummy categories that didnot show a significant association with walking to school were omitted)e Results of for work area type of neighborhood are as not shown because of extreme low number of respondents living in this type of neighborhood (n09)

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Table 3 Association between environmental characteristics and bicycling to school

Variable Range/coding Adjusteda analyses Final multivariateb analysesOR (CI) OR (CI)

Individual and social and physical home environmental characteristics

Gender 0–1 (00boy, 10girl)

Age of the child (years) 3–13c 1.73 (1.67–1.80) 1.71 (1.64–1.78)

Parental education 1–8 1.07 (1.02–1.13) 1.10 (1.04–1.16)

Parental ethnic background 0–1 (00Dutch,10non-Dutch)

Working situation of parentsd Dummy coded: two-parent family, oneparent works 36 h perweek or more, oneparent works 12–36 hper week is reference

1.48 (1.07–2.05)(two-parent family,both parents work12–36 h per week)

1.33 (1.07–1.65)(two-parent family,one parent works 36 hper week or more,one parent works lessthan 12 h per week)

Number of siblings 0–5 1.26 (1.14–1.39) 1.24 (1.12–1.38)

Distance from hometo school (km)

0.5–6.0 0.68 (0.64–0.72) 0.70 (0.66–0.75)

Number of days child goeshome after school

0–5 1.14 (1.06–1.22) 1.13 (1.05–1.22)

Number of cars in the household 0–2 0.56 (0.48–0.65) 0.49 (0.41–0.58)

Social neighborhood characteristics

Neighborhood SES −4−4 (higher scoresrepresent lower SES)

0.91 (0.83–0.99) 0.86 (0.77–0.95)

Social safety 5–25 1.04 (1.03–1.08) 1.04 (1.01–1.07)

Social cohesion 6–30 1.03 (1.01–1.04) 1.02 (1.00–1.04)

Degree of unoccupied houses 1–5

Presence of trash and litter 1–5

Presence of dog dirt 1–5

Physical neighborhood characteristics

Type of neighborhoodd Dummy coded:city non-centeris referencee

0.76 (0.58–0.99)(city green)

Degree of high- vslow-rise buildings

2–10 (higher scorerepresent morehigh-rise buildings)

0.95 (0.91–0.99)

Presence of green 1–5

Presence of water 1–5

Traffic situation 5–25 (higher scoresrepresent lessfavorable trafficsituation)

0.98 (0.96–0.99)

Quality of sidewalks and bike lanes 4–20

Diversity of routes 1–5 1.16 (1.09–1.25) 1.12 (1.04–1.21)

Physical school environmental characteristics

Traffic safety around school(as perceived by parents)

0–1 (0–unsafe, 10safe) 0.76 (0.64–0.91) 0.72 (0.60–0.87)

Traffic safety around school(as perceived by school board)

1–5 (higher scoresrepresent higherperceived safety)

1.22 (0.99–1.50) 1.25 (1.03–1.53)

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importance of social support from parents in stimulatingactive school transportation was shown in other studies aswell [23], and likewise, data from Switzerland show apositive association between daycare attendance and regularcar trips to school [22]. A study among Spanish adolescentsfurther showed that especially higher maternal professionallevel might be inversely associated with active commutingto school [38]. Comparable with other studies [15, 18, 22],the number of cars in the household was negatively associ-ated with active transportation to school.

Regarding the social neighborhood characteristics, chil-dren in lower SES neighborhoods were less likely to go toschool by means of active transportation. Previous researchhas shown a negative association between the likelihood ofwalking/bicycling home from school in deprived neighbor-hoods as well [14, 21]. Moreover, the current study under-lined the importance of perceived social neighborhoodcharacteristics such as perceived social safety and perceivedsocial cohesion, which were consistently related to walkingand bicycling to school. Social contacts that facilitate col-lectively commuting to school and parents’ perceptions ofsocial neighborhood characteristics were shown to be par-ticularly important for primary school children and adoles-cents in other studies as well [39, 40]. Together, thesefindings suggest an important role for social neighborhoodcharacteristics in relation to active commuting to school.The rather counterintuitive finding that the perceived pres-ence of dog dirt was positively related to walking to schoolmight reflect the walkability of those areas, which attracts

both dog walkers and active commuters to school. It is alsopossible that active commuters are actually out in theirneighborhood noticing these factors.

With regard to the physical neighborhood character-istics, living in a city center neighborhood was positive-ly related to walking to school, whereas living in a citygreen neighborhood was negatively associated withwalking and bicycling to school. In general, city centerneighborhoods are considered more walkable, due to theproximity of facilities. Together with a discouragingparking environment for cars in city center neighbor-hoods, this might be an explanation for the abovemen-tioned findings. Moreover, the perceived presence ofgreen was negatively associated with walking to schoolin the present study, which indicates that although livingin a green environment may stimulate active commutingamong adults [41], for children this might not be thecase. Although we did include items on perceived trafficsituation and quality of sidewalks and bike lanes in ourstudy, these were not significantly related to eitherwalking or cycling to school, which is in contrast withmany other studies showing the possible associations offor example major road crossings [22], road safety [13],road density [14], and the presence of walk and bikepaths [18] with active commuting among children. Inthe current study, quality of foot paths and bike laneswere pooled to one variable to prevent multicolinearity,while it may be more realistic to assess the associationbetween foot paths and walking and bike lanes and

Table 3 (continued)

Variable Range/coding Adjusteda analyses Final multivariateb analysesOR (CI) OR (CI)

Sufficiency of bicycle shed at school(as perceived by school board)

1–4 0.73 (0.57–0.93) 0.69 (0.54–0.90)

All analyses are multilevel (random intercepts were allowed) to correct for the clustering of the data within schools. Only statistically significantassociations (p value <0.05) are shown

OR odds ratio, CI confidence intervala Adjusted for age of the child, distance from home to school, and parental educationb Adjusted for age of the child, distance from home to school, and parental education. In addition, the final multivariate model included thefollowing independent variables: working situation of parents, number of siblings, number of days the child goes home after school, number of carsin the household, neighborhood SES, social safety, social cohesion, presence of dog dirt, type of neighborhood, presence of green, diversity ofroutes, traffic safety around school (as perceived by parents), traffic safety around school (as perceived by school board), and sufficiency of bicycleshed at school (as perceived by school board). Only those variables that show a statistical significant association with bicycling to school are shownin this tablec In The Netherlands, children aged 4–12 years are educated together at the same primary school. In the current study sample, 3 children in thelowest grade were aged 3 years and 12 children in the highest grade were aged 13 yearsd Only the dummy categories that show significant associations (p value <0.05) with bicycling to school are displayed (dummy categories that didnot show a significant association with bicycling to school were omitted)e Results of for work area type of neighborhood are as not shown because of extreme low number of respondents living in this type of neighborhood (n09)

Int.J. Behav. Med.

bicycles separately. In the UK study from Panter et al.,it was concluded that both attitudinal and environmentalperceptions of parents were associated with children’sactive commuting behavior [23]. Possibly, the overallneighborhood type included as a variable in the presentstudy already accounted for much of the differences inthe physical environmental characteristics. An alternativeexplanation for the lack of a clear association betweenperceived physical neighborhood characteristics and ac-tive commuting might be found in the specific Dutchinfrastructure, which possibly already provides childrenwith a facilitating physical environment with regard towalking and bicycling.

While the traffic safety around school as perceivedby the school board showed a positive association withbicycling to school, children of parents reporting thatthey perceive the traffic situation around school as safewere less likely to walk or bicycle to school. As thisstudy has a cross-sectional design and causality cannotbe demonstrated, a possible explanation for this findingmight be that parents who do walk or bicycle with theirchildren to school have more experience with the(unsafe) traffic situation around school. The fact thatonly 23.8 % of the school boards in this study perceivethe traffic situation around their school as safe indicatedthat there is room for improvement of traffic situationaround primary schools. Furthermore, the capacity ofbicycle sheds at primary schools as perceived by schoolboards was positively related to walking to school, andnegatively related to bicycling to school. Although thisfinding may seem awkward at first, this might reflectreverse causality as schools where many children walkand few children bicycle to school perceive to haveenough bicycle shed capacity and vise versa.

Strengths and Limitations of This Study

This large-scale explorative study addresses a broad spec-trum of social as well as physical environmental associa-tions with walking and bicycling to school, which is in linewith the social ecological perspective on health as presentedby Dahlgren and Whitehead [8]. However, because of thecross-sectional design, no causal relationships can be dem-onstrated, and this hampers the interpretation of some of thefindings. Moreover, this study relied mostly on parentalperceptions of the neighborhood characteristics. Althoughthe neighborhood characteristics as perceived by parentsmay be of crucial importance [11, 42], and social neighbor-hood characteristics are also difficult to measure objectively,measurement of neighborhood characteristics by means ofneighborhood audits or geographical information systemsmay be a valuable tool in future research. This study alsorelied on parental report of their children’s usual

commuting behavior to school because more objectivemethods such as accelerometer data are often unable toadequately measure bicycling, and therefore are notsuitable for measuring active commuting. Further, thisstudy only asked parents to report the usual mode oftransportation to school, and we implicitly assumed thatthis was also the usual mode of transportation backfrom school to home in the afternoon. Although it ispossible that there are temporal differences in transportmode (i.e., between morning and afternoon trips) [37],UK data show that travel mode to and from school ishighly correlated [4]. Due to the abovementioned diffi-culties, there are no data available on the validity andreliability of the measures used in this study at thismoment.

With regard to the analyses of this study, a sequentialregression analysis was applied, so that variables enter themodel in a theory-driven manner. Additional analyses(which can be obtained from the corresponding author onrequest) have shown that altering the sequence of entry ofblocks of variables (i.e., reverse the order of entry of socialand physical neighborhood variables into the model) did notmodify the results of the study. Lastly, because the studywas conducted in four medium-sized Dutch cities, caution iswarranted in generalizing the findings of this study to otherareas.

Conclusions

This study shows the relation between several character-istics in the home, neighborhood, and school environmentand walking and bicycling to school. This study suggests apotentially important role for social characteristics at theneighborhood level in relation to walking and bicycling toschool. Therefore, apart from providing a physical infra-structure that facilitates safe and convenient active commutingto school, policy makers should be aware of opportunities tofacilitate active commuting by social initiatives in local com-munities. Future research should focus on the effectiveness ofsuch initiatives to further underpin the possible role of socialenvironmental characteristics in relation to children’s com-muting behavior.

Acknowledgments This project was supported by a grant fromZonMw, The Netherlands Organization for Health Research andDevelopment (grant number 71600003). The authors thank TNOQuality of Life and the ChecKid research team for providing thequestionnaires of their research projects. We thank Denise Hung,Eva Laan, Anne Snijders, and Coryke van Vulpen for theirassistance in the data collection, and Karin van Beek, TimGotjé, and Nienke Raaijmakers for their assistance in the datacleaning.

Int.J. Behav. Med.

Appendix

AOverview

ofthedepend

entandindepend

entvariablesinclud

edin

theanalyses

Con

cept

Num

berof

items

Exact

form

ulationof

items

Cronb

ach’s

alph

aAnswer

catego

ries

Recod

e/sum

scorecalculation

andrang

eDescriptiv

edata:mean(SD)or

prop

ortio

ns

Dependent

variable

(questionn

aire

forparents)

Mod

eof

transportatio

nto

scho

ol

1Whatistheusualmod

eof

transportatio

nto

scho

olforyo

urchild

?

NA

Walking

,bicycling;

ontheback

ofparent’sbike/in

abu

ggy,on

the

back

ofparent’smop

ed/scooter,

brou

ghtby

car,by

bus,other

(with

possible

specificationin

open

questio

n)

Ontheback

ofparent’sbike/in

abu

ggy,on

theback

ofparent’s

mop

ed/scooter,brou

ghtby

car

andby

buswererecodedinto

inactiv

etransportatio

n(reference

catego

ry)

43.4

%walking

,31

.8%

bicycling,

24.8

%inactiv

e

Individu

alfactors(questionn

aire

forparents)

Genderof

the

child

1Whatisthegend

erof

your

child

?NA

Boy,girl

NA

50.3

%bo

y,49

.5%

girl,0.2%

missing

value

Age

ofthechild

1How

oldisyo

urchild

?NA

Openqu

estio

nRange

from

3to13

yearsa

7.82

(2.39)

Socialandph

ysical

homeenvironm

entalfactors(questionn

aire

forparents)

Parental

education

1Whatisyo

urhigh

est

completed

education?

NA

Noeducation,

prim

aryeducation,

lowervo

catio

naledu

catio

n,lower

generalsecond

aryeducation,

interm

ediate

vocatio

nal

education,

high

ergeneral

second

aryeducationor

pre-un

iversity

education,

high

ervo

catio

naleducation,

university

Parentaleducationwas

treatedas

anordinalvariable

rang

ingfrom

1to

8,high

erscores

represent

high

ereducation

4.1%

noeducation,

2.5%

prim

aryeducation,

10.8

%lower

vocatio

naleducation,

10.8

%lower

general

second

aryeducation,

24.8

%interm

ediate

vocatio

nal

education,

10.6

%high

ergeneralsecond

aryeducation

orpre-un

iversity

education,

24.8

%high

ervo

catio

nal

education,

11.5

%un

iversity

Parentalethn

icbackgrou

nd1

Whatisyo

urcoun

try

ofbirth?

NA

The

Netherlands,Surinam

,The

Netherlands

Antilles,Turkey,

Morocco,othercoun

try

Surinam

,The

Netherlands

Antilles,

Turkey,Morocco,andother

coun

trywererecodedinto

“other

coun

try”

84.0

%bo

rnin

theNetherlands,

15.5

%bo

rnin

another

coun

try,0.5%

missing

value

Working

situationof

parent(s)

2Which

situationismost

applicable

toyo

uand

your

partner?

(respo

ndents

wereaskedto

indicate

theircivilstatus

and

working

situation)

NA

For

civilstatus:married/official

registratio

nof

cohabitatio

nand

livingtogether;liv

ingtogether,

notmarried;un

married,never

been

married;divo

rced,

separated;

widow

(er);endu

ring

relatio

nship,

livingapart;liv

ing

with

myparents;other(open

answ

ers)

Based

ontheircivilstatus,

respon

dentswerecatego

rizedas

either

sing

le-parentfamily

ortwo-parent

family.Num

berof

working

hoursof

therespon

dent

and(ifapplicable)thepartnerwas

calculated.Full-tim

ejobwas

recodedinto

38hperweek.

Part

timejobworking

hourswere

3.1%

sing

le-parentfamily,

parent

works

less

than

12h

perweek;

5.5%

sing

le-parent

family,parent

works

12–36

hperweek;

2.3%

sing

le-parent

family,parent

works

36hper

weekor

more;

2.2%

two-

parent

family,bo

thparents

workless

than

12hperweek;

Appendix

Int.J. Behav. Med.

Appendix

A(con

tinued)

Con

cept

Num

berof

items

Exact

form

ulationof

items

Cronb

ach’s

alph

aAnswer

catego

ries

Recod

e/sum

scorecalculation

andrang

eDescriptiv

edata:mean(SD)or

prop

ortio

ns

filledin

bytherespon

dents(open

questio

n).Other

answ

ercatego

ries

wererecodedin

0h

perweek,

except

forrespon

dents

who

indicatedthat

they

areself-

employ

ed/entrepreneurwhich

was

recodedinto

38h.

Working

hoursof

therespon

dentsand(if

applicable)thepartnerwere

collapsed

into

threecatego

ries:

less

than

12hperweek,

12–36

hperweek,

and36

hperweekor

more

1.4%

two-parent

family,on

eparent

works

12–36

hper

week,

oneparent

works

less

than

12hperweek;

6.9%

two-parent

family,bo

thparentswork12–36

hper

week;

23.2

%two-parent

family,on

eparent

works

36h

perweekor

more,on

eparent

works

less

than

12hperweek;

47.5

%two-parent

family,o

neparent

works

36hperweekor

more,on

eparent

works

12–

36hperweek;

5.6%

two-

parent

family,bo

thparents

work36

hperweekor

more;

2.3%

missing

value

For

working

situationof

the

respon

dent

and(ifapplicable)

theirpartner:full-tim

ejob;

part-

timejob(…

hours);ho

usew

ife/

househusband

/volun

tary

work;

outof

work/un

able

towork;

stud

enton

adaytim

ecourse;

other(openansw

ers)

Finally,respo

ndentswereclassified

into

nine

catego

ries

(see

next

column).These

nine

catego

ries

werecodedinto

eigh

tdu

mmy

variables,with

two-parent

family,

oneparent

works

36hperweek

ormore,on

eparent

works

12–

36hperweekas

reference

catego

ryNum

berof

siblings

1How

manybrothers

and

sistersdo

esyo

urchild

have?

NA

Openqu

estio

n.Range

from

0to

8siblings.5,

6,7,

or8siblings

werecombinedinto

onecatego

ry“5

siblings

ormore”

10.6

%0siblings;54

.5%

1sibling;

24.7

%2siblings;

6.8%

3siblings;1.9%

4siblings;1.5%

5siblings

ormore

Distancefrom

hometo

scho

ol

1Whatisthedistance

(in

kilometers)

betweenyo

urho

useandyo

urchild

’sscho

ol?

NA

Lessthan

1km

,1–

2km

,2–

5km

,morethan

5km

Lessthan

1km

was

recodedinto

0.5km

,1–2km

was

recodedinto

1.5km

,2–5km

was

recodedinto

3.5km

,morethan

5km

was

recodedinto

6.0km

50.0

%less

than

1km

;28

.3%

1–2km

;18

.7%

2–5km

;3.0%

morethan

5km

Num

berof

days

per

weekthat

thechild

goes

home

afterscho

oltim

e

1How

manydays

perweek

does

your

child

goho

me

afterscho

oltim

e?

NA

0,1,

2,3,

4,5days

Range

from

0to

5days.

1.7%

0days;1.6%

1day;

7.6%

2days;19

.2%

3days;

16.5

%4days;51

.9%

5days;1.4%

missing

value.

Int.J. Behav. Med.

Appendix

A(con

tinued)

Con

cept

Num

berof

items

Exact

form

ulationof

items

Cronb

ach’s

alph

aAnswer

catego

ries

Recod

e/sum

scorecalculation

andrang

eDescriptiv

edata:mean(SD)or

prop

ortio

ns

Num

berof

cars

inho

usehold

1How

manycars

does

your

householdhave?

NA

Nocar,1car,2or

morecars

2or

morecars

was

recodedinto

2cars

5.3%

nocar;49

.3%

1car;

44.9

%2or

morecars;0.5%

missing

value

Socialneighb

orho

odcharacteristics(questionn

aire

forparents)

Neigh

borhoo

dSES

1Whatisyo

urpo

stal

code?

NA

NA

Statusscorebasedon

thepo

stal

code

oftherespon

dent’saddress.

The

status

scoreisbasedon

percentage

unem

ploy

edpeop

le,

percentage

peop

lewith

low

education,andpercentage

oflow-

incomeho

useholds.Scorescould

rang

efrom

−4to

4,high

erscores

representlower

neighb

orho

odSES

−0.18

(1.16)

0.4%

missing

value

Socialsafety

5The

streetsin

the

neighb

orho

odarewelllit

atnigh

t.

0.60

9Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree)

Negativelywordeditemswere

reversed.Sum

scorewas

compu

ted,

rang

efrom

5to

25,

high

erscores

representgreater

social

safety

19.19(3.79)

0.9%

missing

value

Pedestrians

andcyclistscan

beeasily

seen

bythe

residentsof

theho

uses

intheneighb

orho

od.

The

risk

ontrou

bleandpetty

crim

ein

theneighb

orho

odmakes

itun

safe

towalk

throug

htheneighb

orho

odwith

mychild

during

daytim

e.The

risk

ontrou

bleandpetty

crim

ein

theneighb

orho

odmakes

itun

safe

towalk

throug

htheneighb

orho

odwith

mychild

atnigh

t.The

neighb

orho

odissafe

enou

ghformychild

towalkor

play

onthestreets

with

outsupervision(during

daytim

e).

Socialcohesion

6Peoplein

theneighb

orho

odarewillingto

help

each

other.

0.84

1Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree)

Sum

scorewas

compu

ted,

rang

efrom

6to

30,high

erscores

representgreatersocial

cohesion

23.20(4.76)

0.9%

missing

value

Int.J. Behav. Med.

Appendix

A(con

tinued)

Con

cept

Num

berof

items

Exact

form

ulationof

items

Cronb

ach’s

alph

aAnswer

catego

ries

Recod

e/sum

scorecalculation

andrang

eDescriptiv

edata:mean(SD)or

prop

ortio

ns

The

neighb

orho

odisatig

htcommun

ityThe

peop

lein

the

neighb

orho

odcanbe

trusted.

Ingeneral,thepeop

lein

the

neighb

orho

odgetalon

gwell.

Peoplein

theneighb

orho

odsharethesameno

rmsand

values.

There

aremanychild

ren

livingin

the

neighb

orho

od.

Degreeof

unoccupied

houses

1There

areno

tmany

unoccupied

build

ings

orho

uses

inthedirect

environm

ent.

NA

Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree)

Scoresrang

efrom

1to

5;high

erscores

representm

oreun

occupied

houses

1.56

(1.12)

1.5%

missing

value

Presenceof

trashandlitter

1There

isno

tmuchtrash

orlitterin

thedirect

environm

ent.

NA

Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree)

Scoresrang

efrom

1to

5;high

erscores

representmoretrashor

litter

1.89

(1.18)

1.2%

missing

value

Presenceof

dog

dirt

1There

isno

tmuchdo

gdirtin

thedirect

environm

ent.

NA

Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree)

Scoresrang

efrom

1to

5;high

erscores

representmoredo

gdirt

3.38

(1.46)

1.1%

missing

value

Phy

sicalneighb

orho

odcharacteristics(questionn

aire

forparents)

Typ

eof

neighb

orho

od1

Whatisyo

urpo

stal

code?

NA

NA

Based

onpo

stal

code

ofresidence

address:city

center,city

non-

center,city

green,

towncenter,

ruralarea,workarea.Dum

my

coded,

city

non-center

isreference

4.9%

city

center;50

.6%

city

non-center;40

.3%

city

green;

0.5%

towncenter;2.5

%rural

area;0.2%

workarea;1.1%

missing

value

Degreeof

high

-vs.

low-rise

build

ings

2There

areno

tmanyhigh

-rise

build

ings

inou

rneighb

orho

od.

0.60

6Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree)

Negativelywordeditemswere

reversed.Sum

scorewas

compu

ted,

rang

efrom

2to10

;high

erscores

representmore

high

-risebu

ildings.

3.43

(1.92)

1.7%

missing

value

There

aremanylow-rise

build

ings

inou

rneighb

orho

od.

Presenceof

greenin

the

neighb

orho

od

1There

ismuchgreenin

the

direct

environm

ent.

NA

Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree)

Scoresrang

efrom

1to

5;high

erscores

represent

moregreen

4.21

(1.11)

0.8%

missing

value

Int.J. Behav. Med.

Appendix

A(con

tinued)

Con

cept

Num

berof

items

Exact

form

ulationof

items

Cronb

ach’s

alph

aAnswer

catego

ries

Recod

e/sum

scorecalculation

andrang

eDescriptiv

edata:mean(SD)or

prop

ortio

ns

Presenceof

water

inthe

neighb

orho

od

1There

ismuchwater

inthe

direct

environm

ent.

NA

Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree).

Scoresrang

efrom

1to

5;high

erscores

representmorewater

3.63

(1.48)

1.2%

missing

value

Traffic

situation

5There

aresufficient

pedestrian

crossing

sand

trafficlig

htsto

help

pedestrians(children)

crossing

busy

trafficpo

ints

intheneighb

orho

od.

0.65

5Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree)

Negativelywordeditemswere

reversed.Sum

scorewas

compu

ted,

rang

efrom

5to

25;

high

erscores

representless

favo

rabletrafficsituation

16.78(4.51)

0.5%

missing

value

The

speedof

thetrafficin

the

neighb

orho

odisusually

low

(maxim

um30

km/h).

Mostdriversin

the

neighb

orho

oddrivetoo

fast.

There

isso

muchtrafficin

ourneighb

orho

odthat

itis

difficultor

inconv

enient

formychild

towalk

there.

There

arealotof

exhaust

fumes

(from

cars,bu

ses)

intheneighb

orho

od.

Qualityof

sidewalks

andbike

lanes

4Mostsidewalks

inthe

neighb

orho

odarewell

maintained.

0.60

3Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree)

Sum

scorewas

compu

ted,

rang

efrom

4to

20;high

erscores

representbetterqu

ality

12.47(3.76)

3.2%

missing

value

Mostsidewalks

inthe

neighb

orho

odareseparated

from

thestreet

(byparked

cars,plants,concrete

obstacles).

Moststreetsin

the

neighb

orho

odhave

bike

lanes.

Mostbike

lanesin

the

neighb

orho

odareseparated

from

thestreet

(byparked

cars,plants,concrete

obstacles).

Diversity

ofroutes

1There

aremanydifferent

routes

intheneighb

orho

odmychild

cantake

toget

somew

here.

NA

Five-po

intLikert-type

scale

(stron

glydisagree

tostrong

lyagree)

Scoresrang

efrom

1to

5;high

erscores

representgreaterdiversity

3.84

(1.18)

0.8%

missing

value

Int.J. Behav. Med.

Appendix

A(con

tinued)

Con

cept

Num

berof

items

Exact

form

ulationof

items

Cronb

ach’s

alph

aAnswer

catego

ries

Recod

e/sum

scorecalculation

andrang

eDescriptiv

edata:mean(SD)or

prop

ortio

ns

Phy

sicalscho

olenvironm

entalcharacteristics(questionn

aire

forparentsandqu

estio

nnaire

forscho

olbo

ards)

Traffic

safety

arou

ndscho

olas

perceived

byparents

1Doyo

uthinkthetraffic

situationarou

ndyo

urchild

’sscho

olissafe?

NA

Yes;yes,prov

ided

that

Iwatch

my

child

carefully

;no

(reasoncould

bespecified)

“Yes”and“yes,prov

ided

that

Iwatch

mychild

carefully

”were

recodedinto“safe”

(cod

e1),“no”

was

recodedinto

“unsafe”

(cod

e0)

61.6

%un

safe;38

.4%

safe;

0.4%

missing

value

Traffic

safety

arou

ndscho

olas

perceived

byscho

oldirectionb

1How

doyo

ujudg

ethetraffic

safety

arou

ndyo

urscho

ol?

NA

Verysafe;safe;average;

unsafe;

very

unsafe

Scoresrang

efrom

1to

5,high

erscores

representgreatersafety.

2.84

(0.91)

Sufficiency

ofbicycleshed

atscho

olas

perceivedby

scho

oldirectionb

1Doesthecapacity

ofthe

bicycleshed

satisfy

the

needsof

your

scho

ol?

NA

Yes,morethan

sufficient;yes,

sufficient;no

,insufficient;no

,very

insufficient

Scoresrang

efrom

1to

4;high

erscores

representgreater

sufficiency

2.90

(0.70)

SDstandard

deviation,

NAno

tapplicable

aIn

The

Netherlands,childrenaged

4–12

yearsareeducated

together

atthesameprim

aryscho

ol.Inthecurrentstudy

sample,3child

renin

thelowestg

rade

wereaged

3yearsand12

child

renin

the

high

estgradewereaged

13years

bDerived

from

thequ

estio

nnaire

forscho

olbo

ard

Int.J. Behav. Med.

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