Time series analysis of personal exposure to ambient air pollution and mortality using an exposure simulator

• Type of Material: Article
• Authors: Howard Chang, Emory University; Montserrat Fuentes, North Carolina State University; H. Christopher Frey, North Carolina State University
• Language: English
• Date: 2012-09
• Publisher: Nature Publishing Group: Open Access Hybrid Model Option B
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2012 Nature America, Inc. All rights reserved
• Final Published Version (URL): http://www.nature.com/jes/journal/v22/n5/full/jes201253a.html
• Title of Journal or Parent Work: Journal of Exposure Science and Environmental Epidemiology
• ISSN: 1559-0631
• Volume: 22
• Issue: 5
• Start Page: 483
• End Page: 488
• Grant/Funding Information: The research is supported by Grant DMS-0635449, DMS-0706731, DMS-0706731, DMS-0353029 from the National Science Foundation, US EPA Grant RD-83329201-4, US EPA STAR Research Assistance Agreement No. R833863, and Grant No. 1 R01 ES014843-01A2 from the National Institutes of Health.
• Keywords: time series analysis; exposure modeling; particulate matter
• Research Categories: Biology, Biostatistics

Abstract

This paper describes a modeling framework for estimating the acute effects of personal exposure to ambient air pollution in a time series design. First, a spatial hierarchical model is used to relate Census tract-level daily ambient concentrations and simulated exposures for a subset of the study period. The complete exposure time series is then imputed for risk estimation. Modeling exposure via a statistical model reduces the computational burden associated with simulating personal exposures considerably. This allows us to consider personal exposures at a finer spatial resolution to improve exposure assessment and for a longer study period. The proposed approach is applied to an analysis of fine particulate matter of <2.5 μm in aerodynamic diameter (PM2.5) and daily mortality in the New York City metropolitan area during the period 2001–2005. Personal PM2.5 exposures were simulated from the Stochastic Human Exposure and Dose Simulation. Accounting for exposure uncertainty, the authors estimated a 2.32% (95% posterior interval: 0.68, 3.94) increase in mortality per a 10 μg/m3 increase in personal exposure to PM2.5 from outdoor sources on the previous day. The corresponding estimates per a 10 μg/m3 increase in PM2.5 ambient concentration was 1.13% (95% confidence interval: 0.27, 2.00). The risks of mortality associated with PM2.5 were also higher during the summer months.