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Estimating Acute Cardiorespiratory Effects of Ambient Volatile Organic Compounds

Ye, Dongni; Klein, Mitchel; Chang, Howard H.; Sarnat, Jeremy A.; Mulholland, James A.; Edgerton, Eric S.; Winquist, Andrea; Tolbert, Paige E.; Sarnat, Stefanie Ebelt

doi: 10.1097/EDE.0000000000000607
Air Pollution

Background: The health effects of ambient volatile organic compounds (VOCs) have received less attention in epidemiologic studies than other commonly measured ambient pollutants. In this study, we estimated acute cardiorespiratory effects of ambient VOCs in an urban population.

Methods: Daily concentrations of 89 VOCs were measured at a centrally-located ambient monitoring site in Atlanta and daily counts of emergency department visits for cardiovascular diseases and asthma in the five-county Atlanta area were obtained for the 1998–2008 period. To understand the health effects of the large number of species, we grouped these VOCs a priori by chemical structure and estimated the associations between VOC groups and daily counts of emergency department visits in a time-series framework using Poisson regression. We applied three analytic approaches to estimate the VOC group effects: an indicator pollutant approach, a joint effect analysis, and a random effect meta-analysis, each with different assumptions. We performed sensitivity analyses to evaluate copollutant confounding.

Results: Hydrocarbon groups, particularly alkenes and alkynes, were associated with emergency department visits for cardiovascular diseases, while the ketone group was associated with emergency department visits for asthma.

Conclusions: The associations observed between emergency department visits for cardiovascular diseases and alkenes and alkynes may reflect the role of traffic exhaust, while the association between asthma visits and ketones may reflect the role of secondary organic compounds. The different patterns of associations we observed for cardiovascular diseases and asthma suggest different modes of action of these pollutants or the mixtures they represent.

From the aDepartment of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA; bDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA; cDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA; dSchool of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA; and eAtmospheric Research & Analysis, Inc., Cary, NC.

Submitted 22 January 2016; accepted 27 April 2016.

Research reported in this publication was supported by funding from the Electric Power Research Institute (EPRI, 10002467). This publication was also made possible by a Clean Air Research Center grant to Emory University and the Georgia Institute of Technology from the US Environmental Protection Agency (USEPA, RD834799), as well as by grants to Emory University from the USEPA (R82921301), the National Institute of Environmental Health Sciences (R01ES11294), and EPRI (EP-P27723/C13172 and EP-P4353/C2124). The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the USEPA. Furthermore, USEPA does not endorse the purchase of any commercial products or services mentioned in the publication.

The authors report no conflicts of interest.

Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com).

Correspondence: Dongni Ye, 1518 Clifton Rd NE, CNR 2030F, Atlanta, GA 30322. dongni.ye@emory.edu.

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