Journal article
Comparing exposure metrics for the effects of fine particulate matter on emergency hospital admissions
Journal of Exposure Science and Environmental Epidemiology, Vol.23(6), pp.627-636
11/01/2013
DOI: 10.1038/jes.2013.39
PMCID: PMC3805672
PMID: 23942393
Abstract
A crucial step in an epidemiological study of the effects of air pollution is to accurately quantify exposure of the population. In this paper, we investigate the sensitivity of the health effects estimates associated with short-term exposure to fine particulate matter with respect to three potential metrics for daily exposure: ambient monitor data, estimated values from a deterministic atmospheric chemistry model, and stochastic daily average human exposure simulation output. Each of these metrics has strengths and weaknesses when estimating the association between daily changes in ambient exposure to fine particulate matter and daily emergency hospital admissions. Monitor data is readily available, but is incomplete over space and time. The atmospheric chemistry model output is spatially and temporally complete but may be less accurate than monitor data. The stochastic human exposure estimates account for human activity patterns and variability in pollutant concentration across microenvironments, but requires extensive input information and computation time. To compare these metrics, we consider a case study of the association between fine particulate matter and emergency hospital admissions for respiratory cases for the Medicare population across three counties in New York. Of particular interest is to quantify the impact and/or benefit to using the stochastic human exposure output to measure ambient exposure to fine particulate matter. Results indicate that the stochastic human exposure simulation output indicates approximately the same increase in the relative risk associated with emergency admissions as using a chemistry model or monitoring data as exposure metrics. However, the stochastic human exposure simulation output and the atmospheric chemistry model both bring additional information, which helps to reduce the uncertainly in our estimated risk.
Details
- Title: Subtitle
- Comparing exposure metrics for the effects of fine particulate matter on emergency hospital admissions
- Creators
- Elizabeth MannshardtKatarina SucicWan JiaoFrancesca DominiciH. Christopher FreyBrian ReichMontserrat Fuentes - North Carolina State University
- Resource Type
- Journal article
- Publication Details
- Journal of Exposure Science and Environmental Epidemiology, Vol.23(6), pp.627-636
- DOI
- 10.1038/jes.2013.39
- PMID
- 23942393
- PMCID
- PMC3805672
- NLM abbreviation
- J Expo Sci Environ Epidemiol
- ISSN
- 1559-0631
- eISSN
- 1559-064X
- Publisher
- Nature Publishing Group
- Copyright
- Copyright © 2013, Nature America, Inc.
- Grant note
- R21 ES022585/ES/NIEHS NIH HHS/United States R01ES019560/ES/NIEHS NIH HHS/United States 2R01ES014843-04A1/ES/NIEHS NIH HHS/United States R01 ES014843/ES/NIEHS NIH HHS/United States R01 ES019560/ES/NIEHS NIH HHS/United States
- Language
- English
- Date published
- 11/01/2013
- Description audience
- Academic
- Academic Unit
- Statistics and Actuarial Science; Biostatistics; Provost Office Administration
- Record Identifier
- 9983765296602771
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