Estimating particulate matter-mortality dose-response curves and thresholdlevels: An analysis of daily time-series for the 20 largest US cities

Numerous studies have shown a positive association between daily mortality and particulate air pollution, even at concentrations below regulatory limi ts. These findings have motivated interest in the shape of the exposure-res ponse relation. The authors have developed flexible modeling strategies for time-series data that include spline and threshold exposure-response model s; they apply these models to daily time-series data for the 20 largest US cities for 1987-1994, using the concentration of particulate matter <10 mu m in aerodynamic diameter (PM10) as the exposure measure. The spline model showed a linear relation without indication of threshold for PM10 and relat ive risk of death for all causes and cardiorespiratory causes; by contrast, for other causes, the risk did not increase until approximately 50 mu g/m( 3) PM10. For all-cause mortality, a linear model without threshold was pref erred to the threshold model and to the spline model, using the Akaike info rmation criterion (AIC). The findings were similar for cardiovascular and r espiratory deaths combined. By contrast, for causes other than cardiovascul ar and respiratory, a threshold model was more competitive with a threshold value estimated at 65 mu g/m(3). These findings indicate that linear model s without a threshold are appropriate for assessing the effect of particula te air pollution on daily mortality even at current levels.