Estimating the mortality impacts of particulate matter: What can be learned from between-study variability?
Estimating the mortality impacts of particulate matter: What can be learned from between-study variability?
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DOI：
10.2307/3454508
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发表时间：
2000-02-01
影响因子：
10.4
通讯作者：
Spengler, JD
中科院分区：
文献类型：
--
作者：
Levy, JI;Hammitt, JK;Spengler, JD
对颗粒物（PM）浓度和死亡率之间联系的流行病学研究得出了一系列估计，导致对关系的大小和因果关系的强度存在分歧。以前的荟萃分析，这篇文献提供了汇总效应估计，但没有解决研究之间的变异性，可能与分析模型，污染模式，暴露人群。为了确定研究特定因素是否可以解释空气动力学直径小于或等于10 μ m的颗粒物（PM10）死亡率时间序列研究中的一些变异性，我们采用了经验贝叶斯荟萃分析。我们估计，PM10浓度每增加10 μ g/m3，死亡率平均增加0.7%，在空气动力学直径小于或等于2.5 μ m（PM2.5）/PM10的颗粒物比率较高的地点，影响更大。这一发现并没有改变纳入了一些潜在的混杂因素和影响修饰符，虽然有一些证据表明，PM的影响受到气候，住房特征，人口统计，二氧化硫和臭氧的存在。虽然还需要进一步的分析来确定哪些因素会影响PM10和死亡率之间的关系，但这些发现可以帮助指导未来的流行病学调查和政策决策。
Epidemiologic studies of the link between particulate matter (PM) concentrations and mortality rates have yielded a range of estimates, leading to disagreement about the magnitude of the relationship and the strength of the causal connection. Previous meta-analyses of this literature have provided pooled effect estimates, but have not addressed between-study variability that may be associated,vith analytical models, pollution patterns, and exposed populations. To determine whether study-specific factors can explain some of the variability in the time-series studies on mortality from particulate matter less than or equal to 10 mu m in aerodynamic diameter (PM10), we applied an empirical Bayes meta-analysis. We estimate that mortality rates increase on average by 0.7% per 10 mu g/m(3) increase in PM10 concentrations, with greater effects at sites with higher ratios of particulate matter less than or equal to 2.5 mu m in aerodynamic diameter (PM2.5)/PM10. This finding did not change with the inclusion of a number of potential confounders and effect modifiers, although there is some evidence that PM effects are influenced by climate, housing characteristics, demographics, and the presence of sulfur dioxide and ozone. Although further analysis would be needed to determine which factors causally influence the relationship between PM10 and mortality, these findings can help guide future epidemiologic investigations and policy decisions.