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Occup Environ Med 68:920-927 doi:10.1136/oem.2010.062521
  • Workplace
  • Original article

Associations between cigarette smoking, obesity, sociodemographic characteristics and remote-sensing-derived estimates of ambient PM2.5: results from a Canadian population-based survey

  1. Randall V Martin5,7
  1. 1Population Studies Division, Health Canada, Ottawa, Ontario, Canada
  2. 2Division of Occupational and Environmental Health, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
  3. 3Department of Medicine, McGill University, Montreal, Quebec, Canada
  4. 4Division of Clinical Epidemiology, Research Institute, McGill University Health Center, Montreal, Quebec, Canada
  5. 5Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada
  6. 6Department of Epidemiology and Biostatistics, McGill University, Montreal, Quebec, Canada
  7. 7Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts, USA
  1. Correspondence to Dr Paul J Villeneuve, Population Studies Division, Health Canada, 50 Columbine Driveway, Room 165, PL0801A, Ottawa, ON K1A 0K9, Canada; paul_villeneuve{at}hc-sc.gc.ca
  • Accepted 15 April 2011
  • Published Online First 24 May 2011

Abstract

Objectives Long-term exposure to ambient fine particles (PM2.5) has been shown to increase mortality. Variables measured on the same spatial scales of air pollution may confound associations, and so the authors' objectives were to evaluate the associations between PM2.5 and individual-level measures of smoking, obesity and sociodemographic status. The authors present an approach to evaluate the impact that uncontrolled confounding from smoking may have on associations between PM2.5 and mortality.

Methods Individual-level behavioural and sociodemographic data were obtained from a 2003 national survey of 122 548 Canadians. Estimates of ground-level PM2.5 at a resolution of 10×10 km between 2001 and 2006 were derived from satellite remote sensing. Exposures were assigned to the residence of the participants at the time of the survey. Differences in the prevalence of smoking across concentrations of PM2.5 and RRs drawn from the literature were used to model the bias on rate ratios.

Results Participants in areas with higher concentrations of PM2.5 had a higher income and educational attainment, smoked less and were more likely immigrants. Smoking had a negative confounding effect on the associations between PM2.5 and mortality. To compensate for this bias, for a 10 μg/m3 increase in PM2.5, mortality from lung cancer and heart disease in the referent exposure group needed to be increased by 6.9% and 3.2%, respectively.

Conclusions Associations were found between sociodemographic and lifestyle characteristics and PM2.5 at a resolution of 10×10 km. The authors present a model to adjust for uncontrolled confounding of smoking that can be readily adapted to exposures measured at different spatial resolutions.

Footnotes

  • Funding Health Canada provided funding for this study.

  • Competing interests None.

  • Ethics approval Ethics approval was provided by the Statistics Canada.

  • Provenance and peer review Not commissioned; externally peer reviewed.