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09-1 Methods to Investigate the Effects of Multiple Air Pollution Constituents

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RFA 09-1

RFA 09-1 seeks proposals for the development of innovative statistical methods for the characterization of air pollutant mixtures and/or the study of the health effects of air pollution mixtures. As much as $750,000 will be available for studies funded under RFA 09-1. HEI expects to fund up to 3 studies at $100,000 to $150,000 per year. 
 Winter 2009 RFA booklet

How to Apply

This RFA is closed.

Publications from this RFA

Research Report 183, Parts 1 and 2
Brent A Coull
et al.
Eun Sug Park
et al.
June 2015

This report contains two studies, by Drs. Brent A Coull and Eun Sug Park and their colleagues, and a Commentary discussing each study individually, as well as an Integrative Discussion of the two. 
Part 1. Statistical Learning Methods for the Effects of Multiple Air Pollution ConstituentsBrent A. Coull et al.
Part 2. Development of Enhanced Statistical Methods for Assessing Health Effects Associated with an Unknown Number of Major Sources of Multiple Air Pollutants. Eun Sug Park et al. 

Research Report 183, Part III
John Molitor
Eric Coker
Michael Jerrett
Beate Ritz
Arthur Li
April 2016

This report is Part 3 of HEI Research Report 183, Development of Statistical Methods for Multipollutant Research. It describes a study to develop and apply statistical methods to analyze the effects of multipollutant exposures on health, expanding beyond the two-pollutant approaches used in many studies to date. HEI funded three innovative studies in recent years to improve the tools for analyzing complex multipollutant exposures. In this last report from these studies, John Molitor and colleagues describe a Bayesian framework to identify spatial clusters of air pollution exposures — and other covariates such as socioeconomic status — and estimated pregnancy outcomes associated with those clusters, using a data set for Los Angeles county.