Source-Apportioned PM2.5 and Cardiorespiratory Emergency Department Visits: Accounting for Source Contribution Uncertainty.


Journal

Epidemiology (Cambridge, Mass.)
ISSN: 1531-5487
Titre abrégé: Epidemiology
Pays: United States
ID NLM: 9009644

Informations de publication

Date de publication:
11 2019
Historique:
pubmed: 31 8 2019
medline: 9 9 2020
entrez: 31 8 2019
Statut: ppublish

Résumé

Despite evidence suggesting that air pollution-related health effects differ by emissions source, epidemiologic studies on fine particulate matter (PM2.5) infrequently differentiate between particles from different sources. Those that do rarely account for the uncertainty of source apportionment methods. For each day in a 12-year period (1998-2010) in Atlanta, GA, we estimated daily PM2.5 source contributions from a Bayesian ensemble model that combined four source apportionment methods including chemical transport and receptor-based models. We fit Poisson generalized linear models to estimate associations between source-specific PM2.5 concentrations and cardiorespiratory emergency department visits (n = 1,598,117). We propagated uncertainty in the source contribution estimates through analyses using multiple imputation. Respiratory emergency department visits were positively associated with biomass burning and secondary organic carbon. For a 1 µg/m increase in PM2.5 from biomass burning during the past 3 days, the rate of visits for all respiratory outcomes increased by 0.4% (95% CI 0.0%, 0.7%). There was less evidence for associations between PM2.5 sources and cardiovascular outcomes, with the exception of ischemic stroke, which was positively associated with most PM2.5 sources. Accounting for the uncertainty of source apportionment estimates resulted, on average, in an 18% increase in the standard error for rate ratio estimates for all respiratory and cardiovascular emergency department visits, but inflation varied across specific sources and outcomes, ranging from 2% to 39%. This study provides evidence of associations between PM2.5 sources and some cardiorespiratory outcomes and quantifies the impact of accounting for variability in source apportionment approaches.

Sections du résumé

BACKGROUND
Despite evidence suggesting that air pollution-related health effects differ by emissions source, epidemiologic studies on fine particulate matter (PM2.5) infrequently differentiate between particles from different sources. Those that do rarely account for the uncertainty of source apportionment methods.
METHODS
For each day in a 12-year period (1998-2010) in Atlanta, GA, we estimated daily PM2.5 source contributions from a Bayesian ensemble model that combined four source apportionment methods including chemical transport and receptor-based models. We fit Poisson generalized linear models to estimate associations between source-specific PM2.5 concentrations and cardiorespiratory emergency department visits (n = 1,598,117). We propagated uncertainty in the source contribution estimates through analyses using multiple imputation.
RESULTS
Respiratory emergency department visits were positively associated with biomass burning and secondary organic carbon. For a 1 µg/m increase in PM2.5 from biomass burning during the past 3 days, the rate of visits for all respiratory outcomes increased by 0.4% (95% CI 0.0%, 0.7%). There was less evidence for associations between PM2.5 sources and cardiovascular outcomes, with the exception of ischemic stroke, which was positively associated with most PM2.5 sources. Accounting for the uncertainty of source apportionment estimates resulted, on average, in an 18% increase in the standard error for rate ratio estimates for all respiratory and cardiovascular emergency department visits, but inflation varied across specific sources and outcomes, ranging from 2% to 39%.
CONCLUSIONS
This study provides evidence of associations between PM2.5 sources and some cardiorespiratory outcomes and quantifies the impact of accounting for variability in source apportionment approaches.

Identifiants

pubmed: 31469699
doi: 10.1097/EDE.0000000000001089
pmc: PMC6768727
mid: NIHMS1535947
doi:

Substances chimiques

Coal 0
Dust 0
Particulate Matter 0
Vehicle Emissions 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

789-798

Subventions

Organisme : NIEHS NIH HHS
ID : P30 ES019776
Pays : United States
Organisme : NIEHS NIH HHS
ID : R21 ES022795
Pays : United States
Organisme : NIOSH CDC HHS
ID : T03 OH008609
Pays : United States
Organisme : ACL HHS
ID : T03OH008609
Pays : United States

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Auteurs

Audrey Flak Pennington (AF)

From the Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA.

Matthew J Strickland (MJ)

School of Community Health Sciences, University of Nevada Reno, Reno, NV.

Katherine Gass (K)

Neglected Tropical Diseases Support Center, Task Force for Global Health, Decatur, GA.

Mitchel Klein (M)

From the Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA.

Stefanie Ebelt Sarnat (SE)

From the Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA.

Paige E Tolbert (PE)

From the Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA.

Sivaraman Balachandran (S)

Department of Biomedical, Chemical, and Environmental Engineering, College of Engineering and Applied Sciences, University of Cincinnati, Cincinnati, OH.

Howard H Chang (HH)

Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA.

Armistead G Russell (AG)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA.

James A Mulholland (JA)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA.

Lyndsey A Darrow (LA)

School of Community Health Sciences, University of Nevada Reno, Reno, NV.

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