Air pollution mixture complexity and its effect on PM

Fine particulate matter Mortality Pollutant mixture Time series Toxicity

Journal

Environmental epidemiology (Philadelphia, Pa.)
ISSN: 2474-7882
Titre abrégé: Environ Epidemiol
Pays: United States
ID NLM: 101719527

Informations de publication

Date de publication:
Dec 2024
Historique:
received: 18 06 2024
accepted: 23 08 2024
medline: 1 11 2024
pubmed: 1 11 2024
entrez: 1 11 2024
Statut: epublish

Résumé

Fine particulate matter (PM The PMCI is constructed as an index spanning seven different pollutants, relative to the PM We estimate a relative excess risk of 1.0042 (95% confidence interval: 1.0023, 1.0061) for an interquartile range increase (from 1.09 to 1.95) of the PMCI. The PMCI predicts a substantial part of within-country relative risk heterogeneity with much less between-country heterogeneity explained. The Akaike information criterion and Bayesian information criterion of the main model are lower than those of alternative meta-regression models considering the oxidative capacity of PM The PMCI represents an efficient and simple predictor of local PM

Sections du résumé

Background UNASSIGNED
Fine particulate matter (PM
Methods UNASSIGNED
The PMCI is constructed as an index spanning seven different pollutants, relative to the PM
Results UNASSIGNED
We estimate a relative excess risk of 1.0042 (95% confidence interval: 1.0023, 1.0061) for an interquartile range increase (from 1.09 to 1.95) of the PMCI. The PMCI predicts a substantial part of within-country relative risk heterogeneity with much less between-country heterogeneity explained. The Akaike information criterion and Bayesian information criterion of the main model are lower than those of alternative meta-regression models considering the oxidative capacity of PM
Conclusions UNASSIGNED
The PMCI represents an efficient and simple predictor of local PM

Identifiants

DOI: 10.1097/EE9.0000000000000342 PMID: 39483640 PMC: PMC11527422
pubmed: 39483640
doi: 10.1097/EE9.0000000000000342
pii: EE-D-24-00062
pmc: PMC11527422
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e342

Informations de copyright

Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.

Déclaration de conflit d'intérêts

The authors declare that they have no conflicts of interest with regard to the content of this report.

Auteurs

Pierre Masselot (P)

Environment & Health Modelling (EHM) Lab, Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, United Kingdom.
ORCID: 0000-0002-7326-1290

Haidong Kan (H)

Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China.

Shailesh K Kharol (SK)

Environment and Climate Change Canada, Toronto, Ontario, Canada.
AtmoAnalytics Inc., Brampton, Ontario, Canada.

Michelle L Bell (ML)

School of the Environment, Yale University, New Haven, Connecticut.
School of Health Policy and Management, College of Health Sciences, Korea University, Seoul, Republic of Korea.

Francesco Sera (F)

Department of Statistics, Computer Science and Applications "G. Parenti," University of Florence, Florence, Italy.

Eric Lavigne (E)

School of Epidemiology & Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada.
Air Health Science Division, Heatlh Canada, Ottawa, Canada.

Susanne Breitner (S)

IBE-Chair of Epidemiology, LMU Munich, Munich, Germany.
Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.

Susana das Neves Pereira da Silva (S)

Department of Epidemiology, Instituto Nacional de Saúde Dr. Ricardo Jorge, Lisbon, Portugal.

Richard T Burnett (RT)

Health Canada, Ottawa, Canada.

Antonio Gasparrini (A)

Environment & Health Modelling (EHM) Lab, Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, United Kingdom.

Jeffrey R Brook (JR)

University of Toronto, Toronto, Ontario, Canada.

Classifications MeSH