Long-term Exposure to PM2.5 and Mortality for the Older Population: Effect Modification by Residential Greenness.
Long-term Exposure to PM2.5 and Mortality for the Older Population: Effect Modification by Residential Greenness.
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DOI：
10.1097/ede.0000000000001348
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发表时间：
2021-07-01
期刊：
影响因子：
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通讯作者：
Bell ML
中科院分区：
文献类型：
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作者：
Son JY;Sabath MB;Lane KJ;Miranda ML;Dominici F;Di Q;Schwartz J;Bell ML
尽管许多研究表明，绿色度越高，死亡风险就越低，但很少有研究考察绿色度对空气污染-健康关联的调节作用。我们评估了居住环境的绿色度，将其作为长期接触细颗粒物(PM2.5)和死亡率之间关系的影响修饰物。我们使用了北卡罗来纳州(北卡罗来纳州)和密歇根州(密歇根州)所有医疗保险受益人的数据(2001-2016)。我们使用集合预测模型估计了PM2.5的年平均值。我们使用COX比例风险模型估计了每增加1μg/m~3的死亡风险，控制了人口统计学、医疗补助资格和地区水平的协变量。我们使用归一化差异植被指数(NDVI)，通过衡量城市化程度和社会经济地位，通过绿色度来调查健康差异。PM2.5与死亡风险呈正相关。危险比(HR)：NC为1.12(95%可信区间1.12，1.13)，MI为1.01(95%CI为1.00，1.01)。农村地区的小时数高于城市地区。在每一类城市化中，绿色程度较低的地区的HR值普遍较高。对于综合差异，无论其他因素如何，低绿度或低SES地区的HR更高。在两个州的高绿度和高SES地区，HRS最低。在我们的研究中，低SES和高绿色区的人PM2.5与死亡率的相关性低于低SES和低绿色区的人。差异因素及其相互作用的多个方面可能会影响暴露在空气污染中的健康差异。调查结果应考虑到不确定因素，例如我们使用的PM2.5模型数据，并需要进一步调查。
Although many studies demonstrated reduced mortality risk with higher greenness, few studies examined the modifying effect of greenness on air pollution–health associations. We evaluated residential greenness as an effect modifier of the association between long-term exposure to fine particles (PM2.5) and mortality. We used data from all Medicare beneficiaries in North Carolina (NC) and Michigan (MI) (2001–2016). We estimated annual PM2.5 averages using ensemble prediction models. We estimated mortality risk per 1 μg/m3 increase using Cox proportional hazards modeling, controlling for demographics, Medicaid eligibility, and area-level covariates. We investigated health disparities by greenness using the Normalized Difference Vegetation Index (NDVI) with measures of urbanicity and socioeconomic status. PM2.5 was positively associated with mortality risk. Hazard ratios (HRs) were 1.12 (95% confidence interval (CI) 1.12, 1.13) for NC and 1.01 (95% CI 1.00, 1.01) for MI. HRs were higher for rural than urban areas. Within each category of urbanicity, HRs were generally higher in less green areas. For combined disparities, HRs were higher in low greenness or low SES areas, regardless of the other factor. HRs were lowest in high-greenness and high-SES areas for both states. In our study, those in low SES and high greenness areas had lower associations between PM2.5 and mortality than those in low SES and low greenness areas. Multiple aspects of disparity factors and their interactions may affect health disparities from air pollution exposures. Findings should be considered in light of uncertainties, such as our use of modeled PM2.5 data, and warrant further investigation.