Wong et al. BMC Public Health 2011, 11:618 http://www.biomedcentral.com/1471-2458/11/618 transport section and hence were excluded (1,376 included). Elementary school students had difficulty in providing information on parental education (19.5% missing data), their anthropometric measures (8.8%), and postal code of their residence (6.5%). However, included and excluded subjects were comparable in terms of sex, grade and regions (Cohen’s d [22] = 0.12 for sex, 0.15 for grade and 0.09 for regions). Cases in which neither parent’s education was available (n = 268 elementary and n = 198 secondary) were recoded to the sample mean of 14.5 years. This construct was devel- oped using an approach similar to that used in previous research [23-25]. After substituting missing data on years of parent’s education with the mean value, among 1,376 and 2,728 elementary and secondary students, 1,086 (78.9%) and 2,479 (90.9%) elementary and second- ary school students had complete data which was used for addressing the first objective. For the second objec- tive, among 1,086 and 2,479 elementary and secondary school students from the first objective, 741 (61.6%) and 1,960 (77.2%) who did not walk/bike to school in the morning were included. Among students included in the second objective, 102 elementary and 272 secondary school students shifted their travel mode from passive in the morning to active in the afternoon. Ethical approval for the study was granted by the institutional research ethics committees at CAMH, York University, as well as at eleven Ontario district school boards. Instruments School transport Travel mode to school in the morning and from school in the afternoon was assessed separately. Respondents were asked ‘how do you usually travel i) to and ii) from school?’ School transport modes for the morning and afternoon were reclassified into a categorical variable with two categories: walking/biking and other. This mir- rors the practice in much of the literature to examine travel behaviour across a broad classification of active and passive travel modes [3]. Mode shifters were defined as those not walking to school in the morning but walk- ing back home in the afternoon. Correlates Socio-demographic (eight variables), behavioural (six variables), psychological (four variables), and environ- mental (seven variables) correlates were assessed (n = 25 in total). Socio-demographic Demographic variables such as sex and grade (Grade 7 to 12) were examined. BMI was computed based on self-reported height and weight. The weight status (nor- mal, overweight and obese) was defined according to age- and sex-specific international BMI (IOTF) cut-offs [26]. Years of highest parental education, a socio- Page 3 of 12 economic status indicator, was assessed considering paternal and maternal education. Parents’ place of birth and having a sibling(s) were also assessed. With respect to the transportation context, driver licensing and num- ber of household cars were examined. Behavioural Students were asked ‘On how many of the last seven days were you physically active for a total of at least 60 min- utes each day?’ Examples such as brisk walking, soccer, swimming were given. The Centers for Disease Control and Prevention (CDC) physical activity recommendation for adolescents [27] is at least 60 minutes of MVPA on most days of the week. In the context of active school transport, physical activity levels over five school days may be more relevant. Therefore, Moderate to Vigorous Physical Activity (MVPA) was classified as zero to four days, and five days or more. Self-reported screen-time was based on the current recommendation of 2 hours or less of screen time daily [28] and grouped as 2 hours per day or less, and more than 2 hours per day. To examine whether there were other behavioural correlates of active school transport, smoking in the past 12 months was asked and categorised as non-smo- kers (never in lifetime)/smoked but not in past 12 months) and smokers (a few puffs to a whole cigarette everyday). Drinking in the past 12 months was cate- gorised as non-drinkers (never/drank but not in past 12 months) and drinkers (just had a sip of alcohol to see what it’s like to almost everyday). Working part-time and participation in extracurricular activities may incur a time cost and reduce the likeli- hood of active school transport. Moreover, students and their households may have other destinations than home in the morning or afternoon that may affect school travel mode choice. Extracurricular participation was categorised as yes and no. For secondary students, working part-time was grouped as ‘don’t work for pay outside home,’ 5 hours/week or less, and 6 hours/week or more. Psychological To measure perceived weight status, respondents were asked ‘do you think of yourself as being too thin, about the right weight, or too fat?’. Perceived physical health was measured by asking ‘how would you rate your phy- sical health?’ with options of excellent, very good, good, fair, and poor and re-grouped into excellent/very good/ good and fair/poor. The extent of parental supervision was asked with the question, ‘In your free time away from home, how often does at least one of your parents know where you are?’. Responses were regrouped as never/rarely/sometimes and often/always. The question of autonomy with respect to school travel was addressed by asking, ‘How often do you get to decide how you travel to school and