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Modelling spatio-temporal variation in exposure to particulate matter: a two-stage approach

Lookup NU author(s): Dr Phillip Diggle, Professor Stephen Rushton, Dr Roy Sanderson, Dr Peter Lurz, Dr Svetlana Glinyanaya, Professor Mark Pearce, Professor Tanja Pless-Mulloli

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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 = PM4) 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. Copyright © 2007 John Wiley & Sons, Ltd.


Publication metadata

Author(s): Fanshawe TR, Diggle PJ, Rushton SP, Sanderson RA, Lurz PWW, Glinianaia SV, Pearce MS, Parker L, Charlton M, Pless-Mulloli T

Publication type: Article

Publication status: Published

Journal: Environmetrics

Year: 2008

Volume: 19

Issue: 6

Pages: 549-566

Print publication date: 17/12/2007

ISSN (print): 1180-4009

ISSN (electronic): 1099-095X

Publisher: John Wiley & Sons Ltd.

URL: http://dx.doi.org/10.1002/env.889

DOI: 10.1002/env.889


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