Particulate Air Pollution and Mortality in the United States: Did the Risks Change from 1987 to 2000?

Francesca Dominici, Roger D. Peng, Scott L. Zeger, Ronald H. White, and Jonathan M. Samet

Abstract

Evaluation of the public health impact of air quality regulations, referred to as accountability research, is increasingly viewed as a necessary component of responsible governmental policy interventions. The authors present an example of accountability assessment based on evaluating change in the short-term effect of airborne particles over a period of increasingly stringent regulation that might have changed the chemical composition and toxicity of these particles. They used updated data and methods of the National Morbidity Mortality Air Pollution Study to estimate national average relative rates of the effects of particulate matter ≤ 10 µm in aerodynamic diameter on all-cause, cardiovascular, and respiratory mortality and on other-cause mortality for 1987–2000. They estimated national average relative rates of the effects of particulate matter ≤ 2.5 µm in aerodynamic diameter on all-cause mortality for 1999–2000. The authors found strong evidence that lag 1 exposures to particulate matter ≤ 10 µm and ≤ 2.5 µm in aerodynamic diameter continue to be associated with increased mortality. They also found a weak indication that the lag 1 effects of particulate matter ≤ 10 µm in aerodynamic diameter on mortality declined during 1987–2000 and that this decline occurred mostly in the eastern United States. The methodology presented can be used to track the health effects of air pollution routinely on regional and national scales.

Data

The data for the National Mortality, Morbidity, and Air Pollution Study (NMMAPS) is available from the Internet Health and Air Pollution Surveillance System (iHAPSS) website at http://www.ihapss.jhsph.edu/data/NMMAPS/R/. There you can download the NMMAPSdata package for reading the NMMAPS data into R. The data are also available in CSV format if you are not an R user.

Code

Code for running the first stage city-specific models and the regional pooling of coefficients can be found in these files:
  • trends.R
  • analyze-trend.R
For pooling the estimates, you can use the tlnise package for R which is available from CRAN. In order to do the regional analysis, you need to know the region classification for each city. The list of (abbreviated) city names and the region classifications can be found in this file:
  • city-region.csv