From the School of the Environment, Yale University, New Haven, CT.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA.
Epidemiology. 2021 Jul 1;32(4):477-486. doi: 10.1097/EDE.0000000000001348.
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 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 to 1.13) for NC and 1.01 (95% CI = 1.00 to 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.
尽管许多研究表明,绿色植物覆盖率越高,死亡率风险越低,但很少有研究探讨绿色植物覆盖率对空气污染与健康关系的调节作用。本研究评估了居住绿色植物覆盖率作为长期细颗粒物(PM2.5)暴露与死亡率之间关联的一个调节因素。
我们使用了北卡罗来纳州(NC)和密歇根州(MI)所有医疗保险受益人的数据(2001-2016 年)。我们使用集合预测模型来估算每年 PM2.5 的平均值。我们使用 Cox 比例风险模型来估计每增加 1μg/m3 时的死亡率风险,同时控制了人口统计学、医疗补助资格和区域水平的协变量。我们使用归一化差异植被指数(NDVI)并结合城市度和社会经济地位指标来研究绿色植物覆盖率的健康差异。
PM2.5 与死亡率风险呈正相关。NC 的危险比(HR)为 1.12(95%置信区间(CI)=1.12 至 1.13),而 MI 的 HR 为 1.01(95% CI = 1.00 至 1.01)。农村地区的 HR 高于城市地区。在每个城市类别中,绿色植物覆盖率较低的地区的 HR 通常较高。对于综合差异,无论其他因素如何,低绿色植物覆盖率或低 SES 地区的 HR 较高。在 NC 和 MI 两个州,高 SES 和高绿色植物覆盖率地区的 HR 最低。
在我们的研究中,那些处于低 SES 和低绿色植物覆盖率地区的人与那些处于低 SES 和低绿色植物覆盖率地区的人相比,PM2.5 和死亡率之间的关联较低。多种差异因素及其相互作用可能会影响空气污染暴露导致的健康差异。应考虑到不确定性,例如我们使用的模型化 PM2.5 数据,同时需要进一步调查。