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Activity Number:
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49
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Type:
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Invited
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Date/Time:
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Sunday, August 2, 2009 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #302791 |
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Title:
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Spatial-Temporal Association Between Daily Mortality and Exposure to Ozone and Particulate Matter Using Geocoded Mortality Data
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Author(s):
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Montserrat Fuentes*+ and Eric Kalendra and Marie Lynn Miranda and Benjamin Strauss
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Companies:
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North Carolina State University and North Carolina State University and Duke University and Duke University
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Address:
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Statistics Department, Raleigh, NC, 27695,
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Keywords:
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spatial statistics ; Bayesian inference ; air pollution ; mortality analysis ; risk assessment ; exposure assessment
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Abstract:
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Fine particulate matter (PM2.5) has been linked to premature mortality. This study uses a unique spatial data architecture consisting of geocoded North Carolina mortality data for 2000--2006, combined with Census 2000 data. We study the association between mortality and exposure to PM2.5 and ozone, using different exposure metrics. We develop and implement a novel multi-stage Bayesian framework to study the spatio-temporal associations between mortality and population exposure to daily PM2.5 mass and ozone, while accounting for different sources of uncertainty. Most of the pollution-mortality risk assessment has been done using aggregated mortality and pollution data, and that can lead to significant bias and error in the estimated risk. We estimate this error and provide a mathematical adjustment for analysis that uses aggregated data to reduce the risk assessment error.
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