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A hierarchical modelling approach to assess multi pollutant effects in time-series studies

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Title: A hierarchical modelling approach to assess multi pollutant effects in time-series studies
Authors: Blangiardo, M
Pirani, M
Kanapka, L
Hansell, A
Fuller, G
Item Type: Journal Article
Abstract: When assessing the short-term effect of air pollution on health outcomes, it is common practice to consider one pollutant at a time, due to their high correlation. Multi pollutant methods have been recently proposed, mainly consisting of collapsing the different pollutants into air quality indexes or clustering the pollutants and then evaluating the effect of each cluster on the health outcome. A major drawback of such approaches is that it is not possible to evaluate the health impact of each pollutant. In this paper we propose the use of the Bayesian hierarchical framework to deal with multi pollutant concentrations in a two-component model: a pollutant model is specified to estimate the ‘true’ concentration values for each pollutant and then such concentration is linked to the health outcomes in a time-series perspective. Through a simulation study we evaluate the model performance and we apply the modelling framework to investigate the effect of six pollutants on cardiovascular mortality in Greater London in 2011-2012.
Issue Date: 4-Mar-2019
Date of Acceptance: 5-Feb-2019
URI: http://hdl.handle.net/10044/1/68973
DOI: https://dx.doi.org/10.1371/journal.pone.0212565
ISSN: 1932-6203
Publisher: Public Library of Science (PLoS)
Journal / Book Title: PLoS ONE
Volume: 14
Issue: 3
Copyright Statement: © 2019 Blangiardo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Sponsor/Funder: Natural Environment Research Council (NERC)
Medical Research Council
Funder's Grant Number: NE/I00789X/1
MR/M025195/1
Keywords: Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
SHORT-TERM EXPOSURE
AIR-POLLUTION
DAILY MORTALITY
LONDON
ASSOCIATIONS
FRAMEWORK
stat.AP
stat.AP
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
SHORT-TERM EXPOSURE
AIR-POLLUTION
DAILY MORTALITY
LONDON
ASSOCIATIONS
FRAMEWORK
General Science & Technology
MD Multidisciplinary
Publication Status: Published
Open Access location: https://doi.org/10.1371/journal.pone.0212565
Article Number: e0212565
Online Publication Date: 2019-03-04
Appears in Collections:Faculty of Medicine
Epidemiology, Public Health and Primary Care



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