Xue Tao, Zheng Yixuan, Li Xin, Liu Jun, Zhang Qiang, Zhu Tong
Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Faraday Discuss. 2021 Mar 1;226:551-568. doi: 10.1039/d0fd00093k. Epub 2020 Nov 25.
Long-term exposure to ambient fine particles (PM) has been evidenced to be a leading contributor to premature mortality in China and many other countries. Previous studies assess the health risk using an exposure-response function, such as an exposure-mortality model (EMM) based on total concentration of PM. However, the risk assessment method can be problematic as it ignores the unequal toxicity between the different chemical components of PM. To derive a components-specific EMM (CS-EMM), we conducted a whole-population-based epidemiology study in China, using the Chinese Population Census data in 2000 and 2010. Concentrations of ambient PM and its components were assessed by satellite-based concentrations of PM and composition fractions simulated by a chemical transport model. We used a difference-in-difference approach to associate county-level changes of census-based total mortality with changes of PM and its components between 2010 and 2000. The chemical components of PM simulated by the model included sulfate (SO), nitrate (NO), ammonium (NH), organic carbon (OC), and black carbon (BC). We further compared CS-EMM with EMM based on a single pollutant of PM (PM-EMM) or black carbon (BC-EMM), by evaluating their performance in a risk assessment. Using census-based total mortality and cross validation we evaluated the performance of the mortality prediction of an EMM, and found that the CS-EMM outperformed PM-EMM or BC-EMM. For instance, CS-EMM, PM-EMM, and BC-EMM all overestimated the average number of county-level deaths by 117, 142, and 149, respectively; hence CS-EMM overestimated by the lowest amount. Moreover, CS-EMM had the advantage of interpreting the toxicity of PM mixture in its entirety. From 2000 to 2010, CS-EMM attributed a 205 496 increase in PM-associated mortality across China to the joint contribution of the growth of total concentration and the reduction of PM toxicity. Among the components, BC contributed 6.4% of PM concentration growth, but corresponded to a 46.7% increment in PM-associated deaths. This study developed a framework to establish and validate an exposure-response function based on PM components, and illustrated its advantages in terms of risk prediction and result interpretation in China. Our approach can be utilized to evaluate how chemical composition modified the health impact of PM, and should help policy-makers target the toxic sources of air pollution.
长期暴露于环境细颗粒物(PM)已被证明是中国和许多其他国家过早死亡的主要原因。以往的研究使用暴露-反应函数评估健康风险,例如基于PM总浓度的暴露-死亡率模型(EMM)。然而,这种风险评估方法可能存在问题,因为它忽略了PM不同化学成分之间的毒性差异。为了推导特定成分的EMM(CS-EMM),我们利用2000年和2010年的中国人口普查数据,在中国开展了一项基于全人群的流行病学研究。通过基于卫星的PM浓度和化学传输模型模拟的成分分数来评估环境PM及其成分的浓度。我们采用双重差分法,将基于普查的县级总死亡率变化与2010年至2000年期间PM及其成分的变化联系起来。该模型模拟的PM化学成分包括硫酸盐(SO)、硝酸盐(NO)、铵(NH)、有机碳(OC)和黑碳(BC)。我们通过评估它们在风险评估中的表现,进一步将CS-EMM与基于单一污染物PM(PM-EMM)或黑碳(BC-EMM)的EMM进行比较。利用基于普查的总死亡率和交叉验证,我们评估了EMM死亡率预测的性能,发现CS-EMM优于PM-EMM或BC-EMM。例如,CS-EMM、PM-EMM和BC-EMM分别高估了县级平均死亡人数117、142和149人;因此,CS-EMM的高估幅度最小。此外,CS-EMM具有全面解释PM混合物毒性的优势。从2000年到2010年,CS-EMM将中国全国范围内与PM相关的死亡人数增加205496例归因于总浓度增长和PM毒性降低的共同作用。在这些成分中,BC对PM浓度增长的贡献为6.4%,但对应于与PM相关死亡人数增加46.7%。本研究建立了一个基于PM成分建立和验证暴露-反应函数的框架,并阐述了其在中国风险预测和结果解释方面的优势。我们的方法可用于评估化学成分如何改变PM对健康的影响,并应有助于政策制定者针对空气污染的有毒来源。