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Evaluating the Sensitivity of PM2.5-Mortality Associations to the Spatial and Temporal Scale of Exposure Assessment

Crouse, Dan L1; Erickson, Anders C2; Christidis, Tanya3; Pinault, Lauren3; van Donkelaar, Aaron4; Li, Chi4; Meng, Jun4; Martin, Randall V.4; Tjepkema, Michael3; Hystad, Perry5; Burnett, Rick6; Pappin, Amanda3; Brauer, Michael2; Weichenthal, Scott*,7,8

doi: 10.1097/EDE.0000000000001136
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Background: The temporal and spatial scales of exposure assessment may influence observed associations between fine particulate air pollution (PM2.5) and mortality but few studies have systematically examined this question.

Methods: We followed 2.4 million adults in the 2001 Canadian Census Health and Environment Cohort for nonaccidental and cause-specific mortality between 2001-2011. We assigned PM2.5 exposures to residential locations using satellite-based estimates and compared three different temporal moving averages (1-year, 3-year, and 8-year) and three spatial scales (1-km, 5-km, and 10-km) of exposure assignment. In addition, we examined different spatial scales based on age, employment status, and urban/rural location, as well as adjustment for O3, NO2, or their combined oxidant capacity (Ox).

Results: In general, longer moving averages resulted in stronger associations between PM2.5 and mortality. For nonaccidental mortality, we observed a hazard ratio of 1.11 (95% CI: 1.08, 1.13) for the 1-year moving average compared to 1.23 (95% CI: 1.20, 1.27) for the 8-year moving average. Respiratory and lung cancer mortality were most sensitive to the spatial scale of exposure assessment with stronger associations observed at smaller spatial scales. Adjustment for oxidant gases attenuated associations between PM2.5 and cardiovascular mortality and strengthened associations with lung cancer. Despite these variations, PM2.5 was associated with increased mortality in nearly all of the models examined.

Conclusions: These findings support a relationship between outdoor PM2.5 and mortality at low concentrations and highlight the importance of longer exposure windows, more spatially resolved exposure metrics, and adjustment for oxidant gases in characterizing this relationship.

1 University of New Brunswick, Fredericton, NB, Canada

2 University of British Columbia, Vancouver, BC, Canada

3 Statistics Canada, Ottawa, ON, Canada

4 Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada

5 Oregon State University, Corvallis, OR, USA

6 Population Studies Division, Health Canada, Ottawa, ON, Canada

7 Air Health Science Division, Health Canada, Ottawa ON, Canada

8 Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC,

Conflict of Interest: None Declared

Financial Support: Research described in this article was conducted under contract to the Health Effects Institute (HEI), an organization jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. R-82811201) and certain motor vehicle and engine manufacturers. The contents of this article do not necessarily reflect the views of HEI, or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers.

SW received research support from a GRePEC salary award funded by the Cancer Research Society, the Quebec Ministry of Economy, Science and Innovation, and FRQS (Fonds de Recherche du Québec- Santé).

DLC was supported by the Maritime SPOR Support Unit (MSSU), which receives financial support from the Canadian Institutes of Health Research (CIHR), the Nova Scotia Department of Health and Wellness, the New Brunswick Department of Health, the Nova Scotia Health Research Foundation (NSHRF), and the New Brunswick Health Research Foundation (NBHRF).

The analysis presented in this paper was conducted at the New Brunswick Research Data Centre, which is part of the Canadian Research Data Centre Network (CRDCN). The services and activities provided by the New Brunswick Research Data Centre are made possible by the financial or in-kind support of the SSHRC, the CIHR, the CFI, Statistics Canada, and the University of New Brunswick. The views expressed in this paper do not necessarily represent the CRDCN’s or that of its partners’.

Acknowledgments: We thank CANUE (Canadian Urban Environmental Health Research Consortium) for creating the 5-km and 10-km buffered estimates of PM2.5. We would like to acknowledge Alain Robichaud and Richard Ménard for developing the O3 model used to calculate the Ox estimates used in our analyses.

Corresponding Author: Dr. Scott Weichenthal, Faculty of Medicine, Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, 1020 Pins Ave. WestMontreal, QC H3A 1A2, Canada. Email: scott.weichenthal@mcgill.ca, Tel: (514) 398-1584

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