OBJECTIVE: The aims of this study were (1) to assess the relationships between transport to and from school (active vs. passive), sedentary behaviours, measures of socio-economic position and perceived environmental variables, and (2) to determine which, if any, variables were predictors of active transportation. METHODS: The sample comprised 705 girls with mean age of 14.7 (SD = 1.6) years old. Questionnaires were used to describe travel mode to school and to estimate weekly television and computer use (screen time). Girls were assigned to active transportation (AT) or passive transportation (PT) groups depending on whether they walked or bicycled (AT) to and from school or travelled by car or bus (PT). Screen time was determined by the number of hours they reported watching television and using computers in the week preceding the examination, including weekends. Socio-economic position was established by parental occupation and educational level. A questionnaire assessed Perceived Neighbourhood Environments. RESULTS: No statistically significant differences were seen for screen time between travel groups. Occupational status of both mother (r = -0.17) and father (r = -0.15) and father's educational level (r = -0.10) were significantly and negatively associated with AT, while street connectivity (r = 0.10) was positively and significantly associated with AT. Logistic regression analysis showed that the likelihood of active commuting decreased by around 50% with increasing father's occupation (odds ratio (OR) = 0.51; p </= 0.05) and father's education (OR = 0.52; p </= 0.05) from low to middle socio-economic position groups. Further, the data showed that girls who agreed that 'there are many four-way intersections in my neighbourhood' were more likely to be active (OR = 1.63; p </= 0.05). CONCLUSION: The data of this study showed that lower socio-economic position is associated with active commuting to school and that street connectivity is a predictor of active transportation in adolescent girls.
OBJECTIVE: The aims of this study were (1) to assess the relationships between transport to and from school (active vs. passive), sedentary behaviours, measures of socio-economic position and perceived environmental variables, and (2) to determine which, if any, variables were predictors of active transportation. METHODS: The sample comprised 705 girls with mean age of 14.7 (SD = 1.6) years old. Questionnaires were used to describe travel mode to school and to estimate weekly television and computer use (screen time). Girls were assigned to active transportation (AT) or passive transportation (PT) groups depending on whether they walked or bicycled (AT) to and from school or travelled by car or bus (PT). Screen time was determined by the number of hours they reported watching television and using computers in the week preceding the examination, including weekends. Socio-economic position was established by parental occupation and educational level. A questionnaire assessed Perceived Neighbourhood Environments. RESULTS: No statistically significant differences were seen for screen time between travel groups. Occupational status of both mother (r = -0.17) and father (r = -0.15) and father's educational level (r = -0.10) were significantly and negatively associated with AT, while street connectivity (r = 0.10) was positively and significantly associated with AT. Logistic regression analysis showed that the likelihood of active commuting decreased by around 50% with increasing father's occupation (odds ratio (OR) = 0.51; p </= 0.05) and father's education (OR = 0.52; p </= 0.05) from low to middle socio-economic position groups. Further, the data showed that girls who agreed that 'there are many four-way intersections in my neighbourhood' were more likely to be active (OR = 1.63; p </= 0.05). CONCLUSION: The data of this study showed that lower socio-economic position is associated with active commuting to school and that street connectivity is a predictor of active transportation in adolescent girls.