Are Environmental Influences on Physical Activity Distinct for Urban, Suburban, and Rural Schools? A Multilevel Study Among Secondary School Students in Ontario, Canada

Authors


  • Data used in this analysis were drawn from the SHAPES-Ontario project (S.L. and S.M.), funded as part of the Smoke-Free Ontario Strategy through the Ontario Ministries of Health and Long-term Care and of Health Promotion. The project was conducted by the SHAPES team at the University of Waterloo. S.M. is a senior scientist within the Propel Centre for Population Health Impact at the University of Waterloo and S.L. is an associate professor within the School of Public Health and Health Systems at the University of Waterloo and a Cancer Care Ontario Research Chair in Population Studies. The Canadian Cancer Society provided funding to develop SHAPES, the system used to collect the SHAPES-Ontario data. A grant from the Canadian Heart Health Surveys Follow-up Study ancillary projects (E.P.H., S.L., and S.E.) was used to fund the expertise required to measure the GIS-derived features of the built environment for each participating school.

Address correspondence to: Scott Leatherdale, Associate Professor, (sleather@uwaterloo.ca), School of Public Health and Health Systems, University of Waterloo, 200 University Ave West, Waterloo, ON N2L 3G1, Canada.

ABSTRACT

BACKGROUND

This study examined differences in students' time spent in physical activity (PA) across secondary schools in rural, suburban, and urban environments and identified the environment-level factors associated with these between school differences in students' PA.

METHODS

Multilevel linear regression analyses were used to examine the environment- and student-level characteristics associated with time spent in PA among grades 9 to 12 students attending 76 secondary schools in Ontario, Canada, as part of the SHAPES-Ontario study. This approach was first conducted with the full data set testing for interactions between environment-level factors and school location. Then, school-location specific regression models were run separately.

RESULTS

Statistically significant between-school variation was identified among students attending urban (σ2μ0 = 8959.63 [372.46]), suburban (σ2μ0 = 8918.75 [186.20]), and rural (σ2μ0 = 9403.17 [203.69]) schools, where school-level differences accounted for 4.0%, 2.0%, and 2.1% of the variability in students' time spent in PA, respectively. Students attending an urban or suburban school that provided another room for PA or was located within close proximity to a shopping mall or fast food outlet spent more time in PA.

CONCLUSION

Students' time spent in PA varies by school location and some features of the school environment have a different impact on students' time spent in PA by school location. Developing a better understanding of the environment-level characteristics associated with students' time spent in PA by school location may help public health and planning experts to tailor school programs and policies to the needs of students in different locations.

Ancillary