Department of Agricultural and Resource Economics, University of California, Berkeley, CA, 94720, USA.
Department of Economics, University of Chicago, Chicago, IL, USA.
Environ Health. 2019 Nov 21;18(1):101. doi: 10.1186/s12940-019-0544-9.
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.
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.
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.
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.
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。
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。
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。
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。