A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London

Alastair Rushworth, Duncan Lee, Richard Mitchell

Research output: Contribution to journalArticle

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Abstract

It has long been known that air pollution is harmful to human health, as many epidemiological studies have been conducted into its effects. Collectively, these studies have investigated both the acute and chronic effects of pollution, with the latter typically based on individual level cohort designs that can be expensive to implement. As a result of the increasing availability of small-area statistics, ecological spatio-temporal study designs are also being used, with which a key statistical problem is allowing for residual spatio-temporal autocorrelation that remains after the covariate effects have been removed. We present a new model for estimating the effects of air pollution on human health, which allows for residual spatio-temporal autocorrelation, and a study into the long-term effects of air pollution on human health in Greater London, England. The individual and joint effects of different pollutants are explored, via the use of single pollutant models and multiple pollutant indices.

Original languageEnglish
Pages (from-to)29-38
Number of pages10
JournalSpatial and Spatio-temporal Epidemiology
Volume10
DOIs
Publication statusPublished - 15 Jul 2014

Keywords

  • air pollution
  • Gaussian Markov random fields
  • respiratory disease
  • spatio-temporal autocorrelation

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