The impact of daily mobility on exposure to traffic-related air pollution and health effect estimates

• Published in: Journal of exposure science & environmental epidemiology Vol. 21; no. 1; pp. 42 - 48
• Main Authors: Setton, Eleanor, Marshall, Julian D, Brauer, Michael, Lundquist, Kathryn R, Hystad, Perry, Keller, Peter, Cloutier-Fisher, Denise
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.01.2011; Nature Publishing Group
• Subjects: 692/700/478/174; 704/172; Air Pollutants - analysis; Air pollution; Air Pollution - analysis; Air Pollution - statistics & numerical data; Bias; British Columbia; California; City traffic; Environmental aspects; Environmental Exposure - analysis; Environmental Exposure - statistics & numerical data; Environmental health; Environmental Monitoring - methods; Epidemiology; Estimates; Exposure; Health aspects; Humans; Interpolation; Land use; Medicine; Medicine & Public Health; Mobility; Nitrogen dioxide; Nitrogen Dioxide - analysis; Residence Characteristics; Residential location; Spatial variations; Time Factors; Urban Health; Vehicle Emissions - analysis; Canada; Southern California; United States > US; Canada, British Columbia, Vancouver; USA, California; space-time modeling; measurement error; air pollution; bias
• ISSN: 1559-0631; 1559-064X; 1559-064X
• DOI: 10.1038/jes.2010.14

Epidemiological studies of traffic-related air pollution typically estimate exposures at residential locations only; however, if study subjects spend time away from home, exposure measurement error, and therefore bias, may be introduced into epidemiological analyses. For two study areas (Vancouver, British Columbia, and Southern California), we use paired residence- and mobility-based estimates of individual exposure to ambient nitrogen dioxide, and apply error theory to calculate bias for scenarios when mobility is not considered. In Vancouver, the mean bias was 0.84 (range: 0.79–0.89; SD: 0.01), indicating potential bias of an effect estimate toward the null by ∼16% when using residence-based exposure estimates. Bias was more strongly negative (mean: 0.70, range: 0.63–0.77, SD: 0.02) when the underlying pollution estimates had higher spatial variation (land-use regression versus monitor interpolation). In Southern California, bias was seen to become more strongly negative with increasing time and distance spent away from home (e.g., 0.99 for 0–2 h spent at least 10 km away, 0.66 for ≥10 h spent at least 40 km away). Our results suggest that ignoring daily mobility patterns can contribute to bias toward the null hypothesis in epidemiological studies using individual-level exposure estimates.