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Interactions of psychosocial factors with built environments in explaining adolescents' active transportation.
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https://doi.org/10.1016/j.ypmed.2017.04.008Abstract
The present study examined independent and interacting associations of psychosocial and neighborhood built environment variables with adolescents' reported active transportation. Moderating effects of adolescent sex were explored. Mixed-effects regression models were conducted on data from the Teen Environment and Neighborhood observational study (N=928) in the Seattle, WA and Baltimore regions 2009-2011. Frequency index of active transportation to neighborhood destinations (dependent variable) and 7 psychosocial measures were reported by adolescents. Built environment measures included home walkability and count of nearby parks and recreation facilities using GIS procedures and streetscape quality from environmental audits. Results indicated all 3 environmental variables and 3 psychosocial variables (self-efficacy, social support from peers, and enjoyment of physical activity) had significant positive main effects with active transportation (Ps<0.05). Three of 21 two-way interactions were significant in explaining active transportation (Ps<0.1): self-efficacy×GIS-based walkability index, barriers to activity in neighborhood×MAPS streetscape scores, and self-efficacy×GIS-based counts of parks and recreation facilities. In each two-way interaction the highest active transportation was found among adolescents with the combination of activity-supportive built environment and positive psychosocial characteristics. Three-way interactions with sex indicated similar associations for girls and boys, with one exception. Results provided modest support for the ecological model principle of interactions across levels, highlight the importance of both built environment and psychosocial factors in shaping adolescents' active transportation, demonstrated the possibility of sex-specific findings, and suggested strategies for improving adolescents' active transportation may be most effective when targeting multiple levels of influence.
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