Fanshawe, T.R. and Diggle, P.J. and Rushton, Steven and Sanderson, R. and Lurz, P.W.W. and Glinianaia, Svetlana V. and Pearce, Mark S. and Parker, L. and Charlton, Martin and Pless-Mulloli, Tanja
(2008)
Modelling spatio-temporal variation in exposure to particulate
matter: a two-stage approach.
Environmetrics, 19 (6).
pp. 549-566.
ISSN 1180-4009
Abstract
Studies investigating associations between air pollution exposure and health outcomes benefit from the estimation of
exposures at the individual level, but explicit consideration of the spatio-temporal variation in exposure is relatively
new in air pollution epidemiology. We address the problem of estimating spatially and temporally varying particulate
matter concentrations (black smoke
=
BS
=
PM
4
) using data routinely collected from 20 monitoring stations in
Newcastle-upon-Tyne between 1961 and 1992. We propose a two-stage strategy for modelling BS levels. In the first
stage, we use a dynamic linear model to describe the long-term trend and seasonal variation in area-wide average
BS levels. In the second stage, we account for the spatio-temporal variation between monitors around the area-wide
average in a linear model that incorporates a range of spatio-temporal covariates available throughout the study
area, and test for evidence of residual spatio-temporal correlation. We then use the model to assign time-aggregated
predictions of BS exposure, with associated prediction variances, to each singleton pregnancy that occurred in
the study area during this period, guided by dates of conception and birth and mothers’ residential locations. In
work to be reported separately, these exposure estimates will be used to investigate relationships between maternal
exposure to BS during pregnancy and a range of birth outcomes. Our analysis demonstrates how suitable covariates
can be used to explain residual spatio-temporal variation in individual-level exposure, thereby reducing the need
to model the residual spatio-temporal correlation explicitly.
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