A new model for investigating the mortality effects o multiple air pollutants in air pollution mortality time-series studies

Abstract

Because the U.S. Environmental Protection Agency regulates air pollutants independently, the majority of time-series studies on air pollution and mortality have focused on estimating the adverse health effects of a single pollutant. However, due to the sometimes high correlation between air pollutants, the results from studies that focus on a single air pollutant can be difficult to interpret. In addition, the high correlation between air pollutants can produce problems of interpretation for the standard method of investigating the adverse health effects due to multiple air pollutants. The standard method involves simultaneously including the multiple air pollutants in a single statistical model. Because of this, the development of new models to concurrently estimate the adverse health effects of multiple air pollutants has recently been identified as an important area of future research. In this article, a new model for disentangling the joint effects of multiple air pollutants in air pollution mortality time-series studies is introduced. This new model uses the time-series data to assign each air pollutant a weight that indicates the pollutant's contribution to the air pollution mixture that affects mortality and to estimate the effect of this air pollution mixture on mortality. This model offers an improvement in statistical estimation precision over the standard method. It also avoids problems of interpretation that can occur if the standard method is used. This new model is then illustrated by applying it to time-series data from two U.S. counties.