Spatial modeling of air pollution in studies of its short-term health effects

Lee, D. and Shaddick, G. (2010) Spatial modeling of air pollution in studies of its short-term health effects. Biometrics, 66(4), pp. 1238-1246. (doi:10.1111/j.1541-0420.2009.01376.x)

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In studies that estimate the short-term effects of air pollution on health, daily measurements of pollution concentrations are often available from a number of monitoring locations within the study area. However, the health data are typically only available in the form of daily counts for the entire area, meaning that a corresponding single daily measure of pollution is required. The standard approach is to average the observed measurements at the monitoring locations, and use this in a log-linear health model. However, as the pollution surface is spatially variable this simple summary is unlikely to be an accurate estimate of the average pollution concentration across the region, which may lead to bias in the resulting health effects. In this article, we propose an alternative approach that jointly models the pollution concentrations and their relationship with the health data using a Bayesian spatio-temporal model. We compare this approach with the simple spatial average using a simulation study, by investigating the impact of spatial variation, monitor placement, and measurement error in the pollution data. An epidemiological study from Greater London is then presented, which estimates the relationship between respiratory mortality and four different pollutants.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Lee, Professor Duncan
Authors: Lee, D., and Shaddick, G.
Subjects:G Geography. Anthropology. Recreation > GE Environmental Sciences
H Social Sciences > HA Statistics
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Biometrics
Publisher:Wiley-Blackwell Publishing Ltd.
ISSN (Online):1541-0420
Published Online:11 January 2010

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