health behaviour in school - aged children is a general health survey of preadolescent and adolescent children conducted in affiliation with who.6 in canada , cycle 6 of this survey ( 2009/10 ) involved administration of both student- ( n=26  078 ) and school - level administrator ( n=436 ) questionnaires .
we combined these data with environmental measures describing school neighbourhoods that were obtained using geographic information systems .
the survey involved a systematic multi - stage cluster sample design that involved students and schools from 11 of 13 canadian territories and provinces.6 the sample available for the current analysis was 19  576 students with complete data ( weighted sample 20  076 ) from 419 schools . implicit or explicit consent to participate was obtained from school boards , individual schools , parents / guardians and students , as per local jurisdictional requirements .
the study protocol was approved by the general research ethics board of queen 's university ( study approval number : geduc-430 - 09 ) .
based upon a standard self - report module , reports of active transportation injuries were identified for all participants for a 12-month period prior to survey administration.6 injuries that required medical attention and which occurred : ( 1 ) in the  street / road / parking lot or while ( 2 )  biking / cycling or  walking / running ( not for a sports team or exercise) were operationally defined as active transportation injuries .
three levels of active transportation to school were identified : ( 1 ) youth who did not regularly engage in active transportation ; ( 2 ) youth who regularly engaged and lived near their school ; and ( 3 ) youth who regularly engaged but lived far from school .
participants who reported that their usual mode of transportation to school was  bus , train , streetcar , subway , or boat / ferry or  car , motorcycle , or moped were placed in category 1 .
students who reported regular active transportation ( by walking or bicycling ) with travel times either < 5  min for cycling or < 15  min for walking were placed in category 2 .
those reporting greater lengths of time for walking or bicycling were placed in category 3 .
potential individual - level confounders were gender , age , ethnicity , perceived family socioeconomic status , perceived residential neighbourhood safety and participation in organised sports .
potential area - level confounders describing the school neighbourhood were : urban / rural geographic status , average precipitation levels as reported by environment canada , summary measures of total road lengths , street or road connectivity,7 speed limits in the 1  km buffer surrounding each school , and canada census of population estimates of median household incomes for 2006 ( pcensus for mappoint ; tetrad computer applications inc .
an initial descriptive analysis was used to characterise the study sample using proportions and measures of central tendency .
examination of the clustered and nested structure of the data revealed an intraclass correlation of 2.6% ( 0.026 ) at the school - level.8 we therefore modelled effects at individual- and school - levels while accounting for this clustering .
multi - level logistic regression modelling was used with random intercepts permitted for each school .
standardised weights ( mean=1.00 ) were calculated and applied to account for the fact that children from different provinces and territories , school board types , languages of instruction , and urban / rural geographic status had different probabilities of entering the sample .
following bivariate analyses , multi - level models were built as follows : ( 1 ) the active transportation variable and all individual - level factors were entered as risk factors ( multivariate model 1 ) ; ( 2 ) backwards selection methods were performed using a change in estimate of > 10% for retention of individual - level variables9 ; then area - level variables were added to the retained individual - level factors ( multivariate model 2 ) ; and ( 3 ) backwards selection was reperformed for the final model , using the same change - in - estimate approach ( multivariate model 3 ) .
conservatively , any covariate whose removal from the model caused a change in the estimate greater than 10% or was statistically significant ( p<0.05 ) was retained in model 3 .
finally , the modelling process was repeated for two specific active transportation injury outcomes : ( 1 ) walking or running injuries and ( 2 ) cycling injuries .
a priori , the study was powered to identify an or of 1.2 with > 80% power ( =0.05 ) for the main analysis .
health behaviour in school - aged children is a general health survey of preadolescent and adolescent children conducted in affiliation with who.6 in canada , cycle 6 of this survey ( 2009/10 ) involved administration of both student- ( n=26  078 ) and school - level administrator ( n=436 ) questionnaires .
we combined these data with environmental measures describing school neighbourhoods that were obtained using geographic information systems .
the survey involved a systematic multi - stage cluster sample design that involved students and schools from 11 of 13 canadian territories and provinces.6 the sample available for the current analysis was 19  576 students with complete data ( weighted sample 20  076 ) from 419 schools . implicit or explicit consent to participate was obtained from school boards , individual schools , parents / guardians and students , as per local jurisdictional requirements .
the study protocol was approved by the general research ethics board of queen 's university ( study approval number : geduc-430 - 09 ) .
based upon a standard self - report module , reports of active transportation injuries were identified for all participants for a 12-month period prior to survey administration.6 injuries that required medical attention and which occurred : ( 1 ) in the 
street / road / parking lot or while ( 2 )  biking / cycling or  walking / running ( not for a sports team or exercise) were operationally defined as active transportation injuries .
three levels of active transportation to school were identified : ( 1 ) youth who did not regularly engage in active transportation ; ( 2 ) youth who regularly engaged and lived near their school ; and ( 3 ) youth who regularly engaged but lived far from school .
participants who reported that their usual mode of transportation to school was  bus , train , streetcar , subway , or boat / ferry or  car , motorcycle , or moped were placed in category 1 .
students who reported regular active transportation ( by walking or bicycling ) with travel times either < 5  min for cycling or < 15  min for walking were placed in category 2 .
those reporting greater lengths of time for walking or bicycling were placed in category 3 .
potential individual - level confounders were gender , age , ethnicity , perceived family socioeconomic status , perceived residential neighbourhood safety and participation in organised sports .
potential area - level confounders describing the school neighbourhood were : urban / rural geographic status , average precipitation levels as reported by environment canada , summary measures of total road lengths , street or road connectivity,7 speed limits in the 1  km buffer surrounding each school , and canada census of population estimates of median household incomes for 2006 ( pcensus for mappoint ; tetrad computer applications inc . ,
an initial descriptive analysis was used to characterise the study sample using proportions and measures of central tendency .
examination of the clustered and nested structure of the data revealed an intraclass correlation of 2.6% ( 0.026 ) at the school - level.8 we therefore modelled effects at individual- and school - levels while accounting for this clustering .
multi - level logistic regression modelling was used with random intercepts permitted for each school .
standardised weights ( mean=1.00 ) were calculated and applied to account for the fact that children from different provinces and territories , school board types , languages of instruction , and urban / rural geographic status had different probabilities of entering the sample .
following bivariate analyses , multi - level models were built as follows : ( 1 ) the active transportation variable and all individual - level factors were entered as risk factors ( multivariate model 1 ) ; ( 2 ) backwards selection methods were performed using a change in estimate of > 10% for retention of individual - level variables9 ; then area - level variables were added to the retained individual - level factors ( multivariate model 2 ) ; and ( 3 ) backwards selection was reperformed for the final model , using the same change - in - estimate approach ( multivariate model 3 ) .
conservatively , any covariate whose removal from the model caused a change in the estimate greater than 10% or was statistically significant ( p<0.05 ) was retained in model 3 .
finally , the modelling process was repeated for two specific active transportation injury outcomes : ( 1 ) walking or running injuries and ( 2 ) cycling injuries . a priori ,
the study was powered to identify an or of 1.2 with > 80% power ( =0.05 ) for the main analysis .
a weighted sample of 20  076 students from 419 schools with complete data was available for analysis .
about a third ( 33.6% ) of the sample engaged in active transportation to school and 357 ( 1.8% of the sample ) incurred an active transportation injury ( table 1 ) .
of these injuries , 68.9% occurred while cycling , 31.1% occurred while walking or running , 45.1% required medical treatment ( eg , placement of a cast or stitches ) and 40.6% caused the participant to miss at least 1  day of school or usual extracurricular activities .
approximately one injury was reported for every 2900  h of exposure to active transportation .
description of sample demographics , engagement in active transportation and the occurrence of active transportation injuries ( n=20  076 ) 
 table 2 summarises bivariate , then adjusted models that describe the association between engagement in active transportation and the occurrence of related injury .
ors can be interpreted as relative risks.10 model 3 provides final estimates for this relationship while controlling for potential confounders .
a statistically significant positive association that followed a graded trend ( ptrend=0.02 ) was observed , with an adjusted 1.52-fold increase ( 95% ci 1.08 to 2.15 ) in the relative odds of active transportation injury for youth who regularly engage in active transportation over longer distances .
two covariates were retained in the final model : age group ( or : 0.75 ; 95% ci 0.57 to 0.97 for ages 1415 vs 1113 ) and urban / rural status ( or : 1.64 ; 95% ci 1.14 to 2.36 for urban vs rural communities ; ptrend=0.008 ) .
results of multi - level logistic regression analysis examining potential risks for active transportation injury associated with engagement in active transportation to school ( n=20  076 ) adjusted for individual - level variables ( gender , age , ethnicity , family socioeconomic status , perceived neighbourhood safety and participation in organised sports ) . adjusted for retained individual - level variables ( age ) and area - level variables ( urban / rural geographic status , street connectivity , speed limit surrounding school , % roads with speed limit 60  km / h , total length of roads , school neighbourhood median family income , total rain and total snow ) . adjusted for retained individual ( age ) and area - level ( urban / rural geographic status ) variables .
the most important finding from this study was that as young people engaged in active transportation for longer distances , their risks for active transportation injury increased irrespective of their mode of active transportation .
many health promotion interventions aim to increase participation in active transportation to school due to its inherent benefits to health.11 however , these same interventions do not necessarily consider the negative outcomes of active transportation to school such as injury .
our findings therefore contribute to a more comprehensive understanding of this public health issue and associated health promotion messages .
it is difficult to establish temporality in our observed effects due to the cross - sectional design .
our use of self - reported measures of injury and active transportation may have contributed to non - differential misclassification leading to bias of the ors towards no effect .
for example , it is quite possible that some of the events that were classified as active transportation injuries were actually recreational .
our lack of detailed information about some relevant contextual factors ( eg , bicycle helmet laws , cycling infrastructure , pedestrian guards and crossings ) are a further limitation , and the analysis also does not account for the timing of injuries and whether they were experienced outside of school commuting times .
finally , there is the possibility of selection bias , such that youth not attending school on the day of survey administration may have been more likely to have active transportation injuries which in turn are differentially related to more active transportation to school .
if this bias existed , it would again bias our or estimates towards no effect . the two main strengths of this research were our use of a large nationally representative sample of students as well as our focus on the negative side effects of an important public health topic with obvious benefits to health .
. negative health outcomes of active transportation remain understudied in the adolescent health promotion literature , and there is a need for future studies to evaluate the relative benefits ( eg , reduced obesity ) and potential harms ( eg , increased injury ) within the same analyses .
public health interventions targeted at increasing active transportation to school in canadian youth should consider possible unintentional injury outcomes of active transportation .
interventions aimed at increasing physical activity should not lose sight of possible injury - related outcomes .
examples of interventions include the walking school bus where children travel together in large groups12 and environmental solutions that foster improvements to walking and cycling infrastructure.13 if well designed , these population health interventions could have a very positive impact on the physical health of canadian youth overall , while limiting the potential for associated injuries .
the relationship between active transportation to school and active transportation injury was examined in a nationally representative sample of canadian youth using multi - level analytical methods .
response relationship between active transportation to school and active transportation injury across increasing travel distances .
we suggest that new and existing interventions promoting active transportation to school should further incorporate injury control strategies in order to continue encouraging physical activity in the safest possible manner .
engagement in active transportation to school represents one possible strategy of promoting physical activity in groups of young people . while the positive effects of active transportation are obvious , possible negative effects of such practices in terms of unintentional injury
this national study of young people from across canada aimed to understand the effects of engagement in active transportation to school on the risks for related injury .
modest increases in risk for active transportation injury were evident , rising in accordance to distance travelled to school .
injury does represent one possible negative consequence of what in general is a positive behaviour for the health of young people .
 active transportation to school provides a means for youth to incorporate physical activity into their daily routines , and this has obvious benefits for child health . 
 studies of active transportation have rarely focused on the negative health effects in terms of injury . 
 this cross - sectional study is based on the 2009/10 canadian health behaviour in school - aged children survey . 
 a sample of children aged 1115  years ( n=20  076 ) was studied . 
 multi - level logistic regression was used to examine associations between walking or bicycling to school and related injury . 
 regular active transportation to school at larger distances ( approximately > 1.6  km ; 1.0 miles ) was associated with higher relative odds of active transportation injury ( or : 1.52 ; 95% ci 1.08 to 2.15 ) , with a suggestion of a dose  
 response relationship between longer travel distances and injury ( p=0.02 ) . 
 physical activity interventions for youth should encourage participation in active transportation to school , while also recognising the potential for unintentional injury . 
Methods
Overview of study design and measures
Participants
Key measures
Analysis
Results
Discussion
Conclusion