Air Pollution and Mortality

Estimating Regional and National Dose-Response Relationships

Francesca Dominici Francesca Dominici is Assistant Professor, Department of Biostatistics, Bloomberg School of Public Health, The Johns Hopkins University, Baltimore, MD 21205 . Michael Daniels is Assistant Professor, Department of Statistics, Iowa State University, Ames, IA . Scott L. Zeger is Professor and Chairman, Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205 . Jonathan M. Samet is Professor and Chairman, Department of Epidemiology, Johns Hopkins University, Baltimore, MD 21205 (Email: . The research described in this article was partially supported by a contract and grant from the Health Effects Institute (HEI), an organization jointly funded by the Environmental Protection Agency (EPA; R824835) and automotive manufacturers. The contents of this article do not necessarily reflect the views and policies of HEI, EPA, or motor vehicle or engine manufacturers. Funding for Francesca Dominici was provided by the HEIs Walter A. Rosenblith New Investigator Award. Funding of Michael Daniels was provided by National Science Foundation grant DMS9816630. Funding was also provided by Johns Hopkins Center in Urban Environmental Health grant 5P30ES03819-12. The authors thank John Bachmann of the EPA for kindly providing us with the data on particulate matter composition, Giovanni Parmigiani for comments and suggestions on the statistical models, and Ivan Coursac for assistance with data base development.

Michael Daniels Francesca Dominici is Assistant Professor, Department of Biostatistics, Bloomberg School of Public Health, The Johns Hopkins University, Baltimore, MD 21205 . Michael Daniels is Assistant Professor, Department of Statistics, Iowa State University, Ames, IA . Scott L. Zeger is Professor and Chairman, Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205 . Jonathan M. Samet is Professor and Chairman, Department of Epidemiology, Johns Hopkins University, Baltimore, MD 21205 (Email: . The research described in this article was partially supported by a contract and grant from the Health Effects Institute (HEI), an organization jointly funded by the Environmental Protection Agency (EPA; R824835) and automotive manufacturers. The contents of this article do not necessarily reflect the views and policies of HEI, EPA, or motor vehicle or engine manufacturers. Funding for Francesca Dominici was provided by the HEIs Walter A. Rosenblith New Investigator Award. Funding of Michael Daniels was provided by National Science Foundation grant DMS9816630. Funding was also provided by Johns Hopkins Center in Urban Environmental Health grant 5P30ES03819-12. The authors thank John Bachmann of the EPA for kindly providing us with the data on particulate matter composition, Giovanni Parmigiani for comments and suggestions on the statistical models, and Ivan Coursac for assistance with data base development.

Scott L Zeger Francesca Dominici is Assistant Professor, Department of Biostatistics, Bloomberg School of Public Health, The Johns Hopkins University, Baltimore, MD 21205 . Michael Daniels is Assistant Professor, Department of Statistics, Iowa State University, Ames, IA . Scott L. Zeger is Professor and Chairman, Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205 . Jonathan M. Samet is Professor and Chairman, Department of Epidemiology, Johns Hopkins University, Baltimore, MD 21205 (Email: . The research described in this article was partially supported by a contract and grant from the Health Effects Institute (HEI), an organization jointly funded by the Environmental Protection Agency (EPA; R824835) and automotive manufacturers. The contents of this article do not necessarily reflect the views and policies of HEI, EPA, or motor vehicle or engine manufacturers. Funding for Francesca Dominici was provided by the HEIs Walter A. Rosenblith New Investigator Award. Funding of Michael Daniels was provided by National Science Foundation grant DMS9816630. Funding was also provided by Johns Hopkins Center in Urban Environmental Health grant 5P30ES03819-12. The authors thank John Bachmann of the EPA for kindly providing us with the data on particulate matter composition, Giovanni Parmigiani for comments and suggestions on the statistical models, and Ivan Coursac for assistance with data base development.

Jonathan M Samet Francesca Dominici is Assistant Professor, Department of Biostatistics, Bloomberg School of Public Health, The Johns Hopkins University, Baltimore, MD 21205 . Michael Daniels is Assistant Professor, Department of Statistics, Iowa State University, Ames, IA . Scott L. Zeger is Professor and Chairman, Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205 . Jonathan M. Samet is Professor and Chairman, Department of Epidemiology, Johns Hopkins University, Baltimore, MD 21205 (Email: . The research described in this article was partially supported by a contract and grant from the Health Effects Institute (HEI), an organization jointly funded by the Environmental Protection Agency (EPA; R824835) and automotive manufacturers. The contents of this article do not necessarily reflect the views and policies of HEI, EPA, or motor vehicle or engine manufacturers. Funding for Francesca Dominici was provided by the HEIs Walter A. Rosenblith New Investigator Award. Funding of Michael Daniels was provided by National Science Foundation grant DMS9816630. Funding was also provided by Johns Hopkins Center in Urban Environmental Health grant 5P30ES03819-12. The authors thank John Bachmann of the EPA for kindly providing us with the data on particulate matter composition, Giovanni Parmigiani for comments and suggestions on the statistical models, and Ivan Coursac for assistance with data base development.

Abstract

We analyzed a national data base of air pollution and mortality for the 88 largest U.S. cities for the period 1987–1994, to estimate relative rates of mortality associated with airborne particulate matter smaller than 10 microns (PM₁₀) and the form of the relationship between PM₁₀ concentration and mortality. To estimate city-specific relative rates of mortality associated with PM₁₀, we built log-linear models that included nonparametric adjustments for weather variables and longer term trends. To estimate PM₁₀ mortality dose-response curves, we modeled the logarithm of the expected value of daily mortality as a function of PM₁₀ using natural cubic splines with unknown numbers and locations of knots. We also developed spatial models to investigate the heterogeneity of relative mortality rates and of the shapes of PM₁₀ mortality dose-response curves across cities and geographical regions. To determine whether variability in effect estimates can be explained by city-specific factors, we explored the dependence of relative mortality rates on mean pollution levels, demographic variables, reliability of the pollution data, and specific constituents of particulate matter. We implemented estimation with simulation-based methods, including data augmentation to impute the missing data of the city-specific covariates and the reversible jump Markov chain Monte Carlo (RJMCMC) to sample from the posterior distribution of the parameters in the hierarchical spline model. We found that previous-day PM₁₀ concentrations were positively associated with total mortality in most the locations, with a .5% increment for a 10 μg/m³ increase in PM₁₀. The effect was strongest in the Northeast region, where the increase in the death rate was twice as high as the average for the other cities. Overall, we found that the pooled concentration-response relationship for the nation was linear.

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Air Pollution and Mortality

Estimating Regional and National Dose-Response Relationships

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Air Pollution and Mortality

Estimating Regional and National Dose-Response Relationships

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