Methods for Bias Reduction in Time-Series Studies of Particulate Matter Air Pollution and Mortality

Abstract

In many cities of the United States, measurements of ambient particulate matter air pollution (PM) are available only every sixth day. Time-series studies conducted in these cities that investigate the relationship between mortality and PM are restricted to using a single day's PM as the measure of PM exposure, rather than using measurements taken over several consecutive days. Studies showed that using a single-day PM as the measure of PM exposure can result in estimates that have a negative bias, sometimes in the order of over half of the value being estimated. In this article two methods are introduced that can be used to obtain estimates that can in some situations reduce the bias to negligible proportions when only every-sixth-day PM concentrations are available. Using one of these methods, the national average PM mortality effect estimates obtained for total mortality and cardiovascular and respiratory mortality, respectively, correspond to 0.27% and 0.39% increases in mortality per 10-μg/m³ increment in PM. The corresponding effect estimates obtained using the single-day lag-1 PM concentration are 0.18% and 0.23%. The estimates obtained using the lag-1 PM concentration were the most widely reported results from the recent multicity National Morbidity, Mortality, and Air Pollution Study (NMMAPS) analyses. The more accurate estimates obtained from the methods introduced in this article will enable more accurate quantification of the increased incidence in mortality due to elevation in PM levels and the benefit of current or more stringent regulatory standards.