Wong et al. BMC Public Health 2011, 11:618 http://www.biomedcentral.com/1471-2458/11/618 of children and youth as they navigate through neigh- bourhoods. Future studies should identify the factors (e. g., personal factors such as motivation for walking and attitudinal factors, such as parental attitudes towards walking and whether their neighbourhood is suitable for walking [e.g., their preference on place of residence]), that may facilitate child and youth involvement in school travel decision-making. Shift from motorized modes in the morning to active in the afternoon This is the first study specifically examining the corre- lates of mode shift from motorized alternatives in the morning to active in the afternoon. Approximately 10% of both elementary and secondary school students were mode shifters. This represents a sizeable proportion of students that may be an interesting target for under- standing how to intervene on travel practices to encou- rage a larger share of students to take active modes for at least one part of the daily school trip. Living in an urban area, having an input into the decision making process, and having a shorter travel time to school were associated with active school travel in the morning and in the afternoon. Additionally, these variables were also associated with mode shift for both elementary and sec- ondary school students. The mode shift may be partially explained by parent’s schedules and resource accessibility. Elementary school students with mothers who commuted to work in the morning were less likely to walk/bike to school, suggest- ing that a parent’s temporal constraints and desire for convenience affect school travel mode choice [39]. In the afternoon, working parents may not be available to pick children up after school [40], leaving these children and youth with a requirement to find an alternative way to get home. Walking may be feasible for short trips along enabling infrastructures (well-connected street system with signalized intersections), and when they are permitted and prefer to do so. For example, in our sam- ple, more students living in urban areas shifted their tra- vel mode than in rural areas (17.6% vs. 5.9% and 17.3% vs. 1.8% for elementary and secondary school students, correspondingly, p-value < 0.001). Similarly, 20% of ele- mentary and secondary school students being driven to school in 0-15 minutes walked back home whereas about 5% of students who were driven to school in 15 minutes or more shifted their mode in the afternoon (p- value < 0.001). Future studies should further examine the psychosocial (e.g., attitudes towards active commut- ing to school); household (e.g., parents’ scheduling and travel mode to work); and environmental characteristics associated with the mode shifting behaviour reported here. Page 10 of 12 The present study shows the importance of examining mode shift as this is a group of students demonstrating different travel behaviours at different times of the school day. Focusing on mode shift raises the considera- tion as to whether interventions might be more effective by targeting either the a.m. or p.m. periods. Mode shif- ters were more likely to live within walking distance from school. Promoting active school transport in the morning may be more feasible in these mode shifters than those being driven both ways because, for example, parents or other caregivers are already accustomed to allowing their children to take an unescorted trip home in the afternoon. Limitations The nature of cross-sectional study makes causal infer- ence impossible. Our findings solely relied on self- report. Accelerometer may measure active school trans- port and physical activity more accurately. Substantial missing data on selected variables was found in both elementary and secondary school students; however, included and excluded subjects were comparable in terms of sex, grade and region. The strengths of the pre- sent study include a representative sample of Canadian students at a provincial level and analysing morning and afternoon school trips separately demonstrating the var- iation across time particularly in secondary school students. Given that distance is the strongest and consistent correlate of active school transport [20], the inclusion of this variable in the analyses would have been informa- tive. However, in this dataset, self-reported distance was not reported nor did we have access to the home and school location of respondents. Time was used as an indicator of the generalized cost of a particular travel mode but the inclusion of time in the specified models would have been strengthened if we had information on the travel times for each alternative transport mode. Implications The spatial, temporal and age-related variations in AST highlight the need for school-specific travel plans rather than ‘one size fits all’ interventions in promoting active school transport. Engaging children and youth in school transport decision-making may be an important and under-examined process for influencing school transport as well as overall physical activity. A significant propor- tion of children and youth can be described as mode shifters in moving to active modes of transport in the afternoon, and this natural shift might be an opportu- nity for the targeting of future interventions; particularly interventions seeking to maximise opportunities for youth physical activity in the after-school period [41].