Statistical Models for Estimating the Health Impact of Air Quality RegulationsEPA Grant Number: R833622
Title: Statistical Models for Estimating the Health Impact of Air Quality Regulations
Investigators: Dominici, Francesca , Peng, Roger D. , Samet, Jonathan M. , White, Ronald H. , Zeger, Scott L.
Current Investigators: Dominici, Francesca , Samet, Jonathan M. , White, Ronald H.
Institution: The Johns Hopkins University
Current Institution: Harvard T.H. Chan School of Public Health
EPA Project Officer: Nolt-Helms, Cynthia
Project Period: July 1, 2007 through September 30, 2010 (Extended to September 30, 2011)
Project Amount: $500,000
RFA: Development of Environmental Health Outcome Indicators (2006) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Health Effects , Health
Despite increasingly stringent national and local air quality regulations in the last three decades, adverse health effects associated with ambient exposure to air pollution persist. Not surprisingly, regulators, regulated industries, and the public are looking for evidence of the gains in public health that have followed the implementation of costly regulatory policies.
We propose statistical models for estimating gains on environmental health outcome indicators at a national scale, such as the number of adverse health events prevented by regulation.
We will use the example of reduction of PM as the PM National Ambient Air Quality Standard (NAAQS) had been implemented across the last two decades. To start, we plan to assess the chronology of the implementation of the NAAQS for PM10 and the corresponding attainment and non-attainment status for all the U.S. counties for the period 1987-2006 (Aim 1). Then we propose to develop: 1) environmental indicators: predictions of county-specific, regional, and national long-term PM trends attributable to regulation accounting for changes in population demographics, industrial activities, and energy demand (Aim 2); 2) outcome indicators: estimates of cross-sectional and longitudinal associations between long-term trends in PM exposure and mortality (morbidity) accounting for individual and area level confounders (Aim 3); and 3) environmental health outcome indicators: estimates of the total reduction of adverse health outcomes prevented by regulation.
The methods proposed in this application will be applied to two national data bases, the National Morbidity Mortality Air Pollution Study (NMMAPS) (1987-2006) and the Medicare Cohort Air Pollution Study (MCAPS) (1999-2006). These national data bases provide the opportunity to: 1) estimate short and long-term effects of PM on mortality and morbidity at a national scale; 2) establish the utility of the development of environmental health outcome indicators at a national scale; and ) develop a surveillance system that can be used to monitor the health impact of future air quality regulations.