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

被引:246
|
作者
Daniels, MJ
Dominici, F
Samet, JM
Zeger, SL
机构
[1] Johns Hopkins Univ, Sch Hyg & Publ Hlth, Dept Biostat, Baltimore, MD 21205 USA
[2] Iowa State Univ, Dept Stat, Ames, IA USA
[3] Johns Hopkins Univ, Sch Hyg & Publ Hlth, Dept Epidemiol, Baltimore, MD USA
关键词
air pollution; models; statistical; mortality;
D O I
10.1093/aje/152.5.397
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Numerous studies have shown a positive association between daily mortality and particulate air pollution, even at concentrations below regulatory limits. These findings have motivated interest in the shape of the exposure-response relation. The authors have developed flexible modeling strategies for time-series data that include spline and threshold exposure-response models; 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 relative 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 preferred to the threshold model and to the spline model, using the Akaike information criterion (AIC). The findings were similar for cardiovascular and respiratory deaths combined. By contrast, for causes other than cardiovascular and respiratory, a threshold model was more competitive with a threshold value estimated at 65 mu g/m(3). These findings indicate that linear models without a threshold are appropriate for assessing the effect of particulate air pollution on daily mortality even at current levels.
引用
收藏
页码:397 / 406
页数:10
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