Building obesity in Canada: understanding the individual- and neighbourhood-level determinants using a multi-level approach

  • Theodora Pouliou | dora.pouliou@gmail.com Administrative Data Research Centre for Wales, College of Medicine, Swansea University, Swansea, United Kingdom.
  • Susan J. Elliott School of Public Health and Health Systems, Faculty of Applied Health Sciences, University of Waterloo, Waterloo, Canada.
  • Antonio Paez School of Geography and Earth Sciences, McMaster University, Hamilton, Canada.
  • K. Bruce Newbold School of Geography and Earth Sciences, McMaster University, Hamilton, Canada.

Abstract

The objective of this paper was to identify heterogeneities associated with the relationships between the body mass index (BMI) and individual as well as socio-environmental correlates at the individual- and area-levels. The data sources used were: (i) the 2003 Canadian Community Health Survey; (ii) the 2001 Canadian Census; and (iii) the Enhanced Points of Interest (EPOI) database from the Desktop Mapping Technologies Inc. Participants were adults (≥20 years; n = 12,836; based on a survey weight scheme Nweighted = 5,418,218) from Toronto and Vancouver census metropolitan areas with no missing BMI records. In addition to conventional 1 km-buffers, we constructed activity-space-buffers to better assess the walkability and potentially increased BMI of individuals. Multi-level analysis was then applied to estimate the relative effects of both individual- and area-level risk-factors for increased BMI. The findings demonstrate a negative association between BMI and energy expenditure, mixed land uses, residential density and average value of dwellings, while a positive association was found with low educational attainment. Relationships were independent of individual characteristics such as age and ethnic- ity. Although the majority of the variation in these outcomes was found to be due to individual-level differences, this study did show significant differences at the area-level as well. The activity-space-buffers presented a vast improvement compared to the conventional 1 km-buffers. The results presented support the rationale that targeting high-risk individuals will only address a portion of the increasing BMI problem; it is essential to also address the characteristics of places that compel indi- viduals to make unhealthy choices.

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Published
2014-11-01
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Original Articles
Keywords:
body mass index, obesity, built environment, walkability index, geographical information system, Canada.
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How to Cite
Pouliou, T., Elliott, S. J., Paez, A., & Newbold, K. B. (2014). Building obesity in Canada: understanding the individual- and neighbourhood-level determinants using a multi-level approach. Geospatial Health, 9(1), 45-55. https://doi.org/10.4081/gh.2014.5