Spatiotemporal air pollution exposure assessment for a Canadian population-based lung cancer case-control study

• Main Authors: Hystad Perry, Demers Paul A, Johnson Kenneth C, Brook Jeff, van Donkelaar Aaron, Lamsal Lok, Martin Randall, Brauer Michael
• Format: Article
• Language: English
• Published: BMC 2012-04-01
• Series: Environmental Health
• Subjects: Air pollution; Canada; Exposure assessment; Lung cancer; Residential mobility; Spatiotemporal
• Online Access: http://www.ehjournal.net/content/11/1/22

<p>Abstract</p> <p>Background</p> <p>Few epidemiological studies of air pollution have used residential histories to develop long-term retrospective exposure estimates for multiple ambient air pollutants and vehicle and industrial emissions. We present such an exposure assessment for a Canadian population-based lung cancer case-control study of 8353 individuals using self-reported residential histories from 1975 to 1994. We also examine the implications of disregarding and/or improperly accounting for residential mobility in long-term exposure assessments.</p> <p>Methods</p> <p>National spatial surfaces of ambient air pollution were compiled from recent satellite-based estimates (for PM_2.5and NO₂) and a chemical transport model (for O₃). The surfaces were adjusted with historical annual air pollution monitoring data, using either spatiotemporal interpolation or linear regression. Model evaluation was conducted using an independent ten percent subset of monitoring data per year. Proximity to major roads, incorporating a temporal weighting factor based on Canadian mobile-source emission estimates, was used to estimate exposure to vehicle emissions. A comprehensive inventory of geocoded industries was used to estimate proximity to major and minor industrial emissions.</p> <p>Results</p> <p>Calibration of the national PM_2.5surface using annual spatiotemporal interpolation predicted historical PM_2.5measurement data best (R²= 0.51), while linear regression incorporating the national surfaces, a time-trend and population density best predicted historical concentrations of NO₂(R²= 0.38) and O₃(R²= 0.56). Applying the models to study participants residential histories between 1975 and 1994 resulted in mean PM_2.5, NO₂and O₃exposures of 11.3 μg/m³(SD = 2.6), 17.7 ppb (4.1), and 26.4 ppb (3.4) respectively. On average, individuals lived within 300 m of a highway for 2.9 years (15% of exposure-years) and within 3 km of a major industrial emitter for 6.4 years (32% of exposure-years). Approximately 50% of individuals were classified into a different PM_2.5, NO₂and O₃exposure quintile when using study entry postal codes and spatial pollution surfaces, in comparison to exposures derived from residential histories and spatiotemporal air pollution models. Recall bias was also present for self-reported residential histories prior to 1975, with cases recalling older residences more often than controls.</p> <p>Conclusions</p> <p>We demonstrate a flexible exposure assessment approach for estimating historical air pollution concentrations over large geographical areas and time-periods. In addition, we highlight the importance of including residential histories in long-term exposure assessments.</p> <p>For submission to: Environmental Health</p>