Air quality and acute deaths in California, 2000-2012

Abstract

Many studies have sought to determine if there is an association between air quality and acute deaths. Many consider it plausible that current levels of air quality cause acute deaths. However, several factors call causation and even association into question. Observational data sets are large and complex. Multiple testing and multiple modeling can lead to false positive findings. Publication, confirmation and other biases are also possible problems. Moreover, the fact that most data sets used in studies evaluating the relationships among air quality and public health outcomes are not publicly available makes reproducing the claims nearly impossible. Here we have built and made publicly available a dataset containing daily air quality levels, PM2.5 and ozone, daily temperature levels, minimum and maximum and daily relative humidity levels for the eight most populous California air basins. We analyzed the dataset using a moving median analysis, a standard time series analysis, and a prediction analysis within the following analysis strategy. We examine the eight air basins separately to see if estimates replicate across locations. We use leave one year out cross validation analysis to evaluate predictions. Both the moving medians analysis and the standard time series analysis found little evidence for association between air quality and acute deaths. The prediction analysis process was a run as a large factorial design using different models and holding out one year at a time. Among the variables used to predict acute death, most of the daily death variability was explained by time of year or weather variables. In summary, the empirical evidence is that current levels of air quality, ozone and PM2.5, are not causally related to acute deaths for California. An empirical and logical case can be made air quality is not causally related to acute deaths for the rest of the United States.