Variations in long-term fine particulate matter air pollution associations with mortality by particle size, source, and composition

总结 死亡率与细颗粒物（PM2.5）空气污染暴露的关系一直很好 记录在案。然而，关于每单位质量有多少死亡与PM2.5暴露有关的估计， 在不同的研究中差异很大，增加了将这些影响估计普遍应用于新的 政策和卫生决策的情况（例如，到世界各地的其他城市或国家）。在这 工作，我们将评估这些健康影响如何随PM2.5质量来源，尺寸分布和 美国国立卫生研究院-美国退休人员协会（NIH-AARP）“饮食与健康研究”大型队列的组成，包括50多万老年人， 居住在美国各地城市和州的成年人。这一组的参与者都很好 其特征在于许多个体特征（例如，年龄、性别、种族、有无糖尿病， 身高、体重和吸烟），以及居住地普查区域生态协变量（例如，人口与 住房密度、平均收入）。自1995-1996年以来，研究参与者一直在跟踪死亡率， 死因已经确定我们将通过以下方式增强NIH-AARP队列数据库： 长期参与者PM2.5质量来源、组成和粒径分布（即，PM质量< 1.0 µm） 暴露，并比较它们各自与死亡率的关系。这将使我们能够创新地测试 假设PM2.5的质量死亡率效应估计值随颗粒大小，成分， 和/或源特性，无论是整体还是潜在敏感的子群体， 对空气污染暴露导致的超额死亡率进行了信息性评估。有了这个新的见解，PM2.5 通过考虑PM2.5，可以在缓解公共卫生和医疗保健行动期间优化健康效益 资源和组成，包括最好地保护最脆弱的人口， 清洁空气对健康的好处替代能源的选择，以应对气候变化。

SUMMARY Mortality associations with fine particulate matter (PM2.5) air pollution exposures have been well documented. However, the estimate as to how many deaths per unit mass are associated with PM2.5 exposure has varied widely across studies, adding to the uncertainty of generally applying these effect estimates to new situations for policy and health decision-making (e.g., to other cities or countries around the world). In this work, we will evaluate how these health impacts vary with PM2.5 mass source, size distribution, and composition in the large NIH-AARP “Diet and Health Study” cohort, comprising more than a half million older adults living in cities and states across the United States. Participants in this cohort have been well characterized by numerous individual characteristics (e.g., age, sex, race, presence or absence of diabetes, height, weight and smoking), as well as by residence census tract ecologic covariates (e.g., population and housing density, average income). The study participants have been followed since 1995-1996 for mortality, and cause of death has been ascertained. We will enhance the NIH-AARP cohort database by determining long-term participant PM2.5 mass source, composition, and size distribution (i.e., PM mass < 1.0 µm) exposures, and compare their respective associations with mortality. This will allow us to innovatively test the hypothesis that the PM2.5 mass –mortality effect estimates vary as a function of particle size, composition, and/or source characteristics, both overall and in potentially sensitive sub-populations, enabling a more informative assessment of excess mortality due to air pollution exposures. With this new insight, the PM2.5 health benefits can be optimized during mitigative public health and healthcare actions by considering PM2.5 source and composition, including to best protect the most vulnerable populations, and when evaluating the clean air health benefits of alternative energy source choices to address climate change.