We identified the most important hypothesized correlates of active transportation to school in Canadian youth residing close to their school using indicators of: 1) the strength of associations identified via regression analyses; 2) population attributable risk; and 3) the potential for intervention. The most important finding of this national study was that the choice to engage in active transportation to school was governed by multiple factors at the individual- and area-levels, as opposed to one or more very specific factors.
There are major differences between our study design and methods from those used in previous studies in this field. Our study involved a geographically diverse sample from across the country, but at the same time was limited to urban youth who lived in close proximity to their school (ie, within 1 mile or 1.6 km) and would therefore likely not be eligible for school bussing. We measured multiple active transportation correlates at multiple levels, and because of this, employed multi-level analytical approaches.
Despite differences in study design and methods, many of the individual and family correlates that were identified in our study have been identified in previous studies that examined determinants of active transportation, such as gender
[6, 9–11], family structure
[14, 15], and the number of cars in the household
. However, unlike previous American studies which found that Hispanic and Black students were more likely to engage in active transportation to school
[6, 12, 13], we did not find any associations for ethnicity. This may be related to the differing ethnic minority compositions in the United States and Canada. We also did not find an association between the number of siblings and active transportation, while several others have identified such an association
[8, 14, 15, 40]. Finally, most other studies have found that youth with a lower family SES were more likely to engage in active transportation to school
[8, 14, 15, 21]. Our results showed more of a U-shape pattern with SES, wherein students in the middle SES categories were the most likely to engage in active transportation to school.
School correlates of active transportation are not well understood as few studies have investigated these associations. Our main finding for schools was that, of the three potential school correlates examined, only one was associated with active transportation. Specifically, and to our surprise, the presence of active transportation programs (walk/bike to school days and walking school bus programs) was negatively associated with active transportation to school. This may be an artifact of the lack of temporality in our cross-sectional study design. That is, it is possible that schools with lower active transportation rates implemented walk/bike to school days and walking school bus programs in an attempt to address this public health issue.
Several neighborhood factors were also correlated with active transportation to school. Consistent with findings from a recent systematic review, we found no association with street connectivity (a measure of the directness of travel routes), but a positive association with the percentage of streets with sidewalks and the total length of streets
. Our finding that climate measures were associated with active transportation to school differs from other studies that were not as geographically diverse
[6, 23]. We also investigated several neighborhood variables that, to date, have been unstudied. Of these, our findings suggest that there is a relationship between aspects of the environment that are related to safety and aesthetics (e.g., presence of sidewalks, presence of shabby housing, presence of litter).
As discussed above, several individual and area-level variables were correlated with active transportation in our study. In order to supply information for the development of informed policy, we identified the most important correlates based upon the strength of the identified association, its population attributable risk, and the potential for intervention (see Table
6). Using these criteria, the most important correlates of active transportation to school were gender, the perception of residential neighborhood safety, the percentage of roads with sidewalks, and the total length of streets. In order to increase female engagement in active transportation to school, interventions could follow similar existing programs, such as the LEAP program implemented in South Carolina
. Additionally, other programs, such as ENACT suggest that resident-led neighborhood programs are effective at increasing active transportation to school by improving perception of neighborhood safety, with safety in numbers
At the area-level, we propose that the type of intervention would vary depending on whether it is an existing school or a newly constructed school. For existing schools, improvements to the existing active transportation infrastructure (e.g., traffic calming strategies, cross-walks, bicycle paths, new sidewalks and traffic diversion efforts), such as done by the Safe Routes to School intervention in California, may improve rates of active transportation to school
. Newly constructed schools should be built in active transportation friendly environments.
The main limitations of our study include the following methodological issues. First, this study may have been affected by selection, as after excluding multiple schools and students, our final sample was reduced from 26 078 to 3 997 (many students were removed because they did not reside in an urban core, and because they did not live within ~1 mile of their school). Third, there may be measurement error with the distance from school inclusion, as the geographical center of the postal code area was considered as a proxy for the students’ home location. Due to the fact that these analyses were limited to urban areas, the estimated locations should be relatively precise
. Fourth, we only have information on the trip from home to school; differences in mode of transportation may exist between journeys going to and leaving from school
[5, 9]. Fifth, outside of family structure and number of vehicles in the home, we were not able to examine potential parental correlates, and parents are clearly very involved in transportation decisions for their children. Sixth, due to the cross-sectional nature of the data, temporality between the variables cannot be assured. Finally, although there was sufficient power to study the individual and family variables and active transportation to school, power was more limited for the school and neighborhood variables.