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Activity Number: 541
Type: Contributed
Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #309625
Title: An Association Between Ozone Exposure and Chronic Lower Respiratory Disease Mortality in the United States: A Bayesian Hierarchical Approach
Author(s): Yongping Hao*+ and Heather Strosnider and Lina Balluz
Companies: CDC and CDC and CDC
Keywords: Ambient ozone exposure ; chronic lower respiratory disease mortality ; Poisson Bayesian hierarchical model
Abstract:

Epidemiological studies typically have shown a link between respiratory disease mortality and ozone exposure. This nationwide study examines the ecological association between ambient ozone and chronic lower respiratory disease mortality (CLRDM) at the county level, where prevention strategies could be initiated or enhanced. Median daily ozone levels (MDOL) during 2001-2006 were derived from EPA modeled data and CLRDM (ICD10: J40-J47) for 2002-2007 from NCHS. We developed a Poisson Bayesian hierarchical model to estimate the association, adjusted for poverty, smoking, obesity, and urbanization, with random effects at county and state levels. We weighted non-spatial and spatial (conditional autoregressive) structures by introducing a balance parameter. We restricted analyses to non-Hispanic whites, aged 65 and older, accounting for 78% of CLRDM. MDOL ranged from 27ppb to 52ppb (median 39ppb). The estimated relative risk of CLRDM associated with a 10ppb increment in ozone was 1.020 (95% CI, 1.019 to 1.021). Compared to non-spatial, spatial, and convolution models, the weighted model yielded the lowest deviance information criterion. Use of the balance parameter improved model fit.


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