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首页> 外文期刊>Risk analysis >Caveats for Causal Interpretations of Linear Regression Coefficients for Fine Participate (PM2.5) Air Pollution Health Effects
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Caveats for Causal Interpretations of Linear Regression Coefficients for Fine Participate (PM2.5) Air Pollution Health Effects

机译：精细参与（PM2.5）空气污染健康影响的线性回归系数因果解释的警告

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Recent linear regression analyses have concluded that decreasing levels of fine particulate matter (PM2.5) air pollution have increased life expectancy in the United States. These findings have left unresolved questions about the causal relation between reductions in PM2.5 levels and changes in cause-specific (especially, cardiovascular disease, CVD) mortality risks. Their robustness (e.g., sensitivity to deletion of a single data point) has also been questioned. We investigate these issues in the National Mortality and Morbidity Air Pollution Study database. Comparing changes in PM2.5 levels and cause-specific mortality rates for elderly people in 24 cities between two periods separated by a decade (1987-1989 and 1999-2000) shows that reductions in PM2.5 were significantly associated with increases in respiratory mortality rates and with decreases in CVD mortality rates. CVD and all-cause mortality risks fell equally for all months of the year over this period, but average PM2.5 levels increased significantly for winter months. This casts doubts on the causal interpretation that declines in PM2.5 over the decade caused reduced short-term mortality risks. Nonlinear regression suggests that reduced or negative marginal health benefits are associated with reductions of PM2.5 below 1999-2000 levels (about 15 μg/m~3). Such nonlinear relations imply that risk communication statements that project a constant incremental reduction in mortality risks per unit reduction in PM2.5 do not adequately reflect the realistic possibility of nonlinear exposure-response relations and diminishing returns to further exposure reductions.
机译：最近的线性回归分析得出的结论是，减少细颗粒物（PM2.5）空气污染的水平已提高了美国的预期寿命。这些发现尚未解决有关PM2.5水平降低与特定原因（尤其是心血管疾病，CVD）死亡率风险变化之间因果关系的疑问。它们的鲁棒性（例如，对删除单个数据点的敏感性）也受到质疑。我们在“国家死亡率和发病率空气污染研究”数据库中调查了这些问题。比较两个间隔十年（1987年至1989年和1999年至2000年）的24个城市中老年人的PM2.5水平变化和因病致死率，发现PM2.5下降与呼吸道死亡率增加显着相关率和CVD死亡率的降低。在此期间，全年所有月份的CVD和全因死亡率风险均下降，但冬季的平均PM2.5水平显着上升。这引起了对因果解释的怀疑，即在过去十年中PM2.5的下降导致短期死亡率降低。非线性回归表明，降低或负面的边际健康益处与PM2.5降低至1999-2000年水平（约15μg/ m〜3）相关。这种非线性关系意味着预测PM2.5单位降低的死亡率风险将不断降低的风险交流陈述不能充分反映非线性暴露-反应关系的现实可能性，并且减少进一步暴露的收益递减。

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