Ambient fine particulate matter and daily mortality: a comparative analysis of observed and estimated exposure in 347 cities.

IF 6.4 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH International journal of epidemiology Pub Date : 2024-04-11 DOI:10.1093/ije/dyae066
Wenhua Yu, Wenzhong Huang, Antonio Gasparrini, Francesco Sera, Alexandra Schneider, Susanne Breitner, Jan Kyselý, Joel Schwartz, Joana Madureira, Vânia Gaio, Yue Leon Guo, Rongbin Xu, Gongbo Chen, Zhengyu Yang, Bo Wen, Yao Wu, Antonella Zanobetti, Haidong Kan, Jiangning Song, Shanshan Li, Yuming Guo
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引用次数: 0

Abstract

Background: Model-estimated air pollution exposure products have been widely used in epidemiological studies to assess the health risks of particulate matter with diameters of ≤2.5 µm (PM2.5). However, few studies have assessed the disparities in health effects between model-estimated and station-observed PM2.5 exposures.

Methods: We collected daily all-cause, respiratory and cardiovascular mortality data in 347 cities across 15 countries and regions worldwide based on the Multi-City Multi-Country collaborative research network. The station-observed PM2.5 data were obtained from official monitoring stations. The model-estimated global PM2.5 product was developed using a machine-learning approach. The associations between daily exposure to PM2.5 and mortality were evaluated using a two-stage analytical approach.

Results: We included 15.8 million all-cause, 1.5 million respiratory and 4.5 million cardiovascular deaths from 2000 to 2018. Short-term exposure to PM2.5 was associated with a relative risk increase (RRI) of mortality from both station-observed and model-estimated exposures. Every 10-μg/m3 increase in the 2-day moving average PM2.5 was associated with overall RRIs of 0.67% (95% CI: 0.49 to 0.85), 0.68% (95% CI: -0.03 to 1.39) and 0.45% (95% CI: 0.08 to 0.82) for all-cause, respiratory, and cardiovascular mortality based on station-observed PM2.5 and RRIs of 0.87% (95% CI: 0.68 to 1.06), 0.81% (95% CI: 0.08 to 1.55) and 0.71% (95% CI: 0.32 to 1.09) based on model-estimated exposure, respectively.

Conclusions: Mortality risks associated with daily PM2.5 exposure were consistent for both station-observed and model-estimated exposures, suggesting the reliability and potential applicability of the global PM2.5 product in epidemiological studies.

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环境细颗粒物与每日死亡率:对 347 个城市的观测暴露量和估计暴露量的比较分析。
背景:在流行病学研究中,模型估计的空气污染暴露产物被广泛用于评估直径≤2.5 µm(PM2.5)颗粒物的健康风险。然而,很少有研究对模型估算的 PM2.5 暴露量与监测站观测到的 PM2.5 暴露量之间的健康影响差异进行评估:方法:我们以多城市多国家合作研究网络为基础,收集了全球 15 个国家和地区 347 个城市的每日全因、呼吸道和心血管死亡率数据。监测站观测到的 PM2.5 数据来自官方监测站。模型估计的全球 PM2.5 产品是利用机器学习方法开发的。采用两阶段分析方法评估了每日暴露于PM2.5与死亡率之间的关联:我们纳入了 2000 年至 2018 年间 1580 万例全因死亡、150 万例呼吸系统死亡和 450 万例心血管死亡。短期暴露于PM2.5与监测站观测到的和模型估计的暴露死亡率相对风险增加(RRI)有关。PM2.5 的 2 天移动平均值每增加 10 微克/立方米,就会导致全因、呼吸系统和心血管疾病的总体 RRI 分别增加 0.67%(95% CI:0.49 至 0.85)、0.68%(95% CI:-0.03 至 1.39)和 0.45%(95% CI:0.08 至 0.82)。根据监测站观测到的 PM2.5,全因、呼吸道和心血管死亡率的 RRI 分别为 0.87% (95% CI: 0.68 to 1.06)、0.81% (95% CI: 0.08 to 1.55) 和 0.71% (95% CI: 0.32 to 1.09):与每日PM2.5暴露相关的死亡率风险在监测站观测到的暴露量和模型估计的暴露量中是一致的,这表明全球PM2.5产品在流行病学研究中的可靠性和潜在适用性。
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来源期刊
International journal of epidemiology
International journal of epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
13.60
自引率
2.60%
发文量
226
审稿时长
3 months
期刊介绍: The International Journal of Epidemiology is a vital resource for individuals seeking to stay updated on the latest advancements and emerging trends in the field of epidemiology worldwide. The journal fosters communication among researchers, educators, and practitioners involved in the study, teaching, and application of epidemiology pertaining to both communicable and non-communicable diseases. It also includes research on health services and medical care. Furthermore, the journal presents new methodologies in epidemiology and statistics, catering to professionals working in social and preventive medicine. Published six times a year, the International Journal of Epidemiology provides a comprehensive platform for the analysis of data. Overall, this journal is an indispensable tool for staying informed and connected within the dynamic realm of epidemiology.
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