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空气污染与美国大样本队列人群死亡的关系:多污染物分析,以及时空分解。

Air pollution and mortality in a large, representative U.S. cohort: multiple-pollutant analyses, and spatial and temporal decompositions.

机构信息

Department of Agricultural and Resource Economics, University of California, Berkeley, CA, 94720, USA.

Department of Economics, University of Chicago, Chicago, IL, USA.

出版信息

Environ Health. 2019 Nov 21;18(1):101. doi: 10.1186/s12940-019-0544-9.

Abstract

BACKGROUND

Cohort studies have documented associations between fine particulate matter air pollution (PM) and mortality risk. However, there remains uncertainty regarding the contribution of co-pollutants and the stability of pollution-mortality associations in models that include multiple air pollutants. Furthermore, it is unclear whether the PM-mortality relationship varies spatially, when exposures are decomposed according to scale of spatial variability, or temporally, when effect estimates are allowed to change between years.

METHODS

A cohort of 635,539 individuals was compiled using public National Health Interview Survey (NHIS) data from 1987 to 2014 and linked with mortality follow-up through 2015. Modelled air pollution exposure estimates for PM, other criteria air pollutants, and spatial decompositions (< 1 km, 1-10 km, 10-100 km, > 100 km) of PM were assigned at the census-tract level. The NHIS samples were also divided into yearly cohorts for temporally-decomposed analyses. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) in regression models that included up to six criteria pollutants; four spatial decompositions of PM; and two- and five-year lagged mean PM exposures in the temporally-decomposed cohorts. Meta-analytic fixed-effect estimates were calculated using results from temporally-decomposed analyses and compared with time-independent results using 17- and 28-year exposure windows.

RESULTS

In multiple-pollutant analyses, PM demonstrated the most robust pollutant-mortality association. Coarse fraction particulate matter (PM) and sulfur dioxide (SO) were also associated with excess mortality risk. The PM-mortality association was observed across all four spatial scales of PM, with higher but less precisely estimated HRs observed for local (< 1 km) and neighborhood (1-10 km) variations. In temporally-decomposed analyses, the PM-mortality HRs were stable across yearly cohorts. The meta-analytic HR using two-year lagged PM equaled 1.10 (95% CI 1.07, 1.13) per 10 μg/m. Comparable results were observed in time-independent analyses using a 17-year (HR 1.13, CI 1.09, 1.16) or 28-year (HR 1.09, CI 1.07, 1.12) exposure window.

CONCLUSIONS

Long-term exposures to PM, PM, and SO were associated with increased risk of all-cause and cardiopulmonary mortality. Each spatial decomposition of PM was associated with mortality risk, and PM-mortality associations were consistent over time.

摘要

背景

队列研究记录了细颗粒物空气污染 (PM) 与死亡率风险之间的关联。然而,在包含多种空气污染物的模型中,对于共同污染物的贡献以及污染-死亡率关联的稳定性仍存在不确定性。此外,当根据空间变异性的规模对暴露进行分解时,或者当允许在不同年份之间改变效应估计时,PM 与死亡率之间的关系是否存在空间差异尚不清楚。

方法

使用 1987 年至 2014 年公共国家健康访谈调查 (NHIS) 数据编制了一个包含 635539 人的队列,并通过 2015 年的死亡率随访进行了链接。在普查区层面分配了 PM、其他标准空气污染物以及 PM 的空间分解(<1 公里、1-10 公里、10-100 公里、>100 公里)的模型化空气污染暴露估计值。NHIS 样本还按时间分解的年度队列进行了划分。使用包含多达六种标准污染物、PM 的四个空间分解以及时间分解队列中的两年和五年滞后平均 PM 暴露的回归模型来估计危险比 (HR) 和 95%置信区间 (CI)。使用时间分解分析的结果计算了荟萃分析固定效应估计值,并与使用 17 年和 28 年暴露窗口的独立时间结果进行了比较。

结果

在多污染物分析中,PM 表现出与死亡率最具相关性的污染物关联。粗颗粒物质 (PM) 和二氧化硫 (SO) 也与超额死亡风险相关。在 PM 的所有四个空间尺度上都观察到了 PM 与死亡率的关联,在局部(<1 公里)和邻里(1-10 公里)变化中观察到了更高但估计精度较低的 HR。在时间分解分析中,PM 与死亡率的 HR 在每年的队列中均保持稳定。使用两年滞后 PM 的荟萃分析 HR 等于每 10μg/m 的 1.10(95%CI 1.07,1.13)。在使用 17 年(HR 1.13,CI 1.09,1.16)或 28 年(HR 1.09,CI 1.07,1.12)暴露窗口的独立时间分析中观察到类似的结果。

结论

长期暴露于 PM、PM 和 SO 与全因和心肺死亡率风险增加有关。PM 的每个空间分解都与死亡率风险相关,并且 PM 与死亡率之间的关联在时间上是一致的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e52/6873509/14a385923bcd/12940_2019_544_Fig1_HTML.jpg

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