Statistical Methods

HEI Research Report 187 was funded as part of HEI’s Accountability research program, aimed at understanding whether actions to improve air quality have resulted in improved health outcomes. Corwin M. Zigler and his colleagues used existing and newly developed statistical methods to assess whether an intervention was causally related to changes in pollutant levels or health outcomes, and applied their methods in two well-developed case studies: effects of air quality interventions to reduce PM₁₀ concentrations in nonattainment areas and the impact of installation of scrubber technologies on emissions from coal-fired power plants.

This newsletter reports on a third study under way in Europe to complete the comprehensive HEI effort to examine the potential health effects of air pollution at low levels; HEI's new research program focusing on the health effects of exposure to traffic-related pollution; and the GBD MAPS team's presentation of preliminary data on coal’s impact on health in China. In addition, it covers the publication of two new research reports covering novel statistical methods for studying pollutant mixtures and a “direct” approach evaluating the impact of air quality interventions through “causal inference” methods, as well as the retirement of HEI's Aaron Cohen, a strategy session held with HEI's sponsors, and HEI in the news.