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


    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

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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 = 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.

    Item Type: Article
    Keywords: dynamic linear model; environmental epidemiology; exposure estimation; particulate matter; spatio-temporal process;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
    Item ID: 5772
    Identification Number: https://doi.org/10.1002/env.889
    Depositing User: Martin Charlton
    Date Deposited: 04 Feb 2015 15:12
    Journal or Publication Title: Environmetrics
    Publisher: Wiley
    Refereed: Yes
    URI:

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