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Urban area disadvantage and physical activity: a multilevel study in Melbourne, Australia
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  1. Anne M Kavanagh1,2,
  2. Jane L Goller1,3,
  3. Tania King1,2,
  4. Damien Jolley4,
  5. David Crawford5,
  6. Gavin Turrell6
  1. 1Australian Research Centre in Sex, Health and Society, La Trobe University, Melbourne, Australia
  2. 2Key Centre for Women’s Health in Society, School of Population Health, University of Melbourne, Melbourne, Australia
  3. 3Department of Human Services, Victoria, Australia
  4. 4Monash Institute of Health Services Research, Monash University, Melbourne, Australia
  5. 5Centre for Physical Activity and Nutrition Research School Exercise and Nutrition Sciences, Deakin University, Victoria, Australia
  6. 6School of Public Health, Queensland University of Technology, Brisbane, Australia
  1. Correspondence to:
 Dr A M Kavanagh
 Key Centre for Women’s Health in Society, University of Melbourne, Melbourne 3010, Australia; a.kavanaghunimelb.edu.au

Abstract

Objective: To estimate variation between small areas in the levels of walking, cycling, jogging, and swimming and overall physical activity and the importance of area level socioeconomic disadvantage in predicting physical activity participation.

Methods: All census collector districts (CCDs) in the 20 innermost local government areas in metropolitan Melbourne, Australia, were identified and ranked by the percentage of low income households (<$400/week) living in the CCD. Fifty CCDs were randomly selected from the least, middle, and most disadvantaged septiles of the ranked CCDs and 2349 residents (58.7% participation rate) participated in a cross sectional postal survey about physical activity. Multilevel logistic regression (adjusted for extrabinomial variation) was used to estimate area level variation in walking, cycling, jogging, and swimming and in overall physical activity participation, and the importance of area level socioeconomic disadvantage in predicting physical activity participation.

Results: There were significant variations between CCDs in all activities and in overall physical participation in age and sex adjusted models; however, after adjustment for individual SES (income, occupation, education) and area level socioeconomic disadvantage, significant differences remained only for walking (p = 0.004), cycling (p = 0.003), and swimming (p = 0.024). Living in the most socioeconomically disadvantaged areas was associated with a decreased likelihood of jogging and of having overall physical activity levels that were sufficiently active for health; these effects remained after adjustment for individual socioeconomic status (sufficiently active: OR 0.70, 95% CI 0.55 to 0.90 and jogging: OR = 0.69, 95% CI 0.51 to 0.94).

Conclusion: These research findings support the need to focus on improving local environments to increase physical activity participation.

  • SES, socioeconomic status
  • CCD, census collector district
  • physical activity
  • socioeconomic status
  • multilevel analysis
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Footnotes

  • Funding: the first author is supported by a Victorian Health Promotion Foundation (VicHealth) Senior Research Fellowship. The fifth and sixth author are supported by a National Health and Medical Research Council/National Heart Foundation Career Development Awards (187028 and CR 01B 0502). The project was funded by the Victorian Health Promotion Foundation.

  • Conflicts of interest: none.

  • Ethics approval: the project was approved by the La Trobe University Human Ethics Committee.

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