Investigating the mixture of air pollutants associated with adverse health outcomes

Abstract

Most investigations of the adverse health effects of multiple air pollutants analyse the time series involved by simultaneously entering the multiple pollutants into a Poisson log-linear model. Concerns have been raised about this type of analysis, and it has been stated that new methodologies or models need to be developed for investigating the adverse health effects of multiple air pollutants. To this end, it has recently been stated that it may be more reasonable to assume that there is a mixture of pollutants considered harmful to health and that assessing the adverse health effects of an air pollution mix may be both more meaningful and more tenable than attempting to isolate the effects of individual pollutants. In this paper, a new model is introduced that is able to reveal the mixture of pollutants associated with an adverse health outcome and the effect of this mixture on the adverse health outcome. The model is shown to have a number of advantages over the traditional method of estimating the adverse health effects of multiple air pollutants. In addition, the model is also shown to be an improvement over a previously proposed, and somewhat ad-hoc, method for estimating the mixture of pollutants associated with an adverse health outcome.