A spatial joint analysis of metal constituents of ambient particulate matter and mortality in England

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Title: A spatial joint analysis of metal constituents of ambient particulate matter and mortality in England
Authors: Lavigne, A
Freni Sterrantino, A
Fecht, D
Liverani, S
Blangiardo, M
De Hoogh, K
Molitor, J
Hansell, A
Item Type: Journal Article
Abstract: Background Few studies have investigated associations between metal components of particulate matter on mortality due to well-known issues of multicollinearity. Here, we analyze these exposures jointly to evaluate their associations with mortality on small area data. Methods We fit a Bayesian Profile Regression (BPR) to account for the multicollinearity in the elemental components (iron, copper and zinc) of PM10 and PM2.5. The models are developed in relation to mortality from cardiovascular and respiratory disease and lung cancer incidence in 2008-11 at small area level, for a population of 13.6 million in the London-Oxford area of England. Results From the BPR, we identified higher risks in the PM10 fraction cluster likely to represent the study area, excluding London, for cardiovascular mortality RR 1.07 (95%CI 1.02, 1.12) and for respiratory mortality RR 1.06 (95%CI 0.99, 1.31), compared to the study mean. For PM2.5 fraction, higher risks were seen for cardiovascular mortality RR 1.55 (CI 95% 1.38, 1.71) and respiratory mortality RR 1.51 (CI 95% 1.33, 1.72), likely to represent the 'highways' cluster. We did not find relevant associations for lung cancer incidence. Conclusion Our analysis showed small but not fully consistent adverse associations between health outcomes and particulate metal exposures. The BPR approach identified subpopulations with unique exposure profiles and provided information about the geographical location of these to help interpret findings.
Issue Date: 1-Aug-2020
Date of Acceptance: 24-Apr-2020
DOI: 10.1097/EE9.0000000000000098
ISSN: 2474-7882
Publisher: Lippincott, Williams & Wilkins
Start Page: e098
End Page: e098
Journal / Book Title: Environmental Epidemiology
Volume: 4
Issue: 4
Copyright Statement: © 2020 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
Sponsor/Funder: Medical Research Council (MRC)
Funder's Grant Number: G0901841
Keywords: Bayesian profile regression
Multipollutant effect
Particulate matter elements
Publication Status: Published
Online Publication Date: 2020-07-16
Appears in Collections:Faculty of Medicine
School of Public Health

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