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解析多种环境暴露因素与全因死亡率之间的关联:一项对欧洲行政队列和传统队列的分析

Disentangling associations between multiple environmental exposures and all-cause mortality: an analysis of European administrative and traditional cohorts.

作者信息

Dimakopoulou Konstantina, Nobile Federica, de Bont Jeroen, Wolf Kathrin, Vienneau Danielle, Ibi Dorina, Coloma Fabián, Pickford Regina, Åström Christofer, Sommar Johan Nilsson, Kasdagli Maria-Iosifina, Souliotis Kyriakos, Tsolakidis Anastasios, Tonne Cathryn, Melén Erik, Ljungman Petter, de Hoogh Kees, Vermeulen Roel C H, Vlaanderen Jelle J, Katsouyanni Klea, Stafoggia Massimo, Samoli Evangelia

机构信息

Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece.

Department of Epidemiology, Lazio Region Health Service/ASL Roma 1, Rome, Italy.

出版信息

Front Epidemiol. 2024 Jan 12;3:1328188. doi: 10.3389/fepid.2023.1328188. eCollection 2023.

Abstract

BACKGROUND

We evaluated the independent and joint effects of air pollution, land/built environment characteristics, and ambient temperature on all-cause mortality as part of the EXPANSE project.

METHODS

We collected data from six administrative cohorts covering Catalonia, Greece, the Netherlands, Rome, Sweden, and Switzerland and three traditional cohorts in Sweden, the Netherlands, and Germany. Participants were linked to spatial exposure estimates derived from hybrid land use regression models and satellite data for: air pollution [fine particulate matter (PM), nitrogen dioxide (NO₂), black carbon (BC), warm season ozone (O)], land/built environment [normalized difference vegetation index (NDVI), distance to water, impervious surfaces], and ambient temperature (the mean and standard deviation of warm and cool season temperature). We applied Cox proportional hazard models accounting for several cohort-specific individual and area-level variables. We evaluated the associations through single and multiexposure models, and interactions between exposures. The joint effects were estimated using the cumulative risk index (CRI). Cohort-specific hazard ratios (HR) were combined using random-effects meta-analyses.

RESULTS

We observed over 3.1 million deaths out of approximately 204 million person-years. In administrative cohorts, increased exposure to PM, NO, and BC was significantly associated with all-cause mortality (pooled HRs: 1.054, 1.033, and 1.032, respectively). We observed an adverse effect of increased impervious surface and mean season-specific temperature, and a protective effect of increased O, NDVI, distance to water, and temperature variation on all-cause mortality. The effects of PM were higher in areas with lower (10th percentile) compared to higher (90th percentile) NDVI levels [pooled HRs: 1.054 (95% confidence interval (CI) 1.030-1.079) vs. 1.038 (95% CI 0.964-1.118)]. A similar pattern was observed for NO. The CRI of air pollutants (PM or NO) plus NDVI and mean warm season temperature resulted in a stronger effect compared to single-exposure HRs: [PM pooled HR: 1.061 (95% CI 1.021-1.102); NO pooled HR: 1.041 (95% CI 1.025-1.057)]. Non-significant effects of similar patterns were observed in traditional cohorts.

DISCUSSION

The findings of our study not only support the independent effects of long-term exposure to air pollution and greenness, but also highlight the increased effect when interplaying with other environmental exposures.

摘要

背景

作为EXPANSE项目的一部分,我们评估了空气污染、土地/建筑环境特征和环境温度对全因死亡率的独立和联合影响。

方法

我们收集了来自六个行政区队列的数据,涵盖加泰罗尼亚、希腊、荷兰、罗马、瑞典和瑞士,以及瑞典、荷兰和德国的三个传统队列。参与者与通过混合土地利用回归模型和卫星数据得出的空间暴露估计值相关联,这些数据涉及:空气污染[细颗粒物(PM)、二氧化氮(NO₂)、黑碳(BC)、暖季臭氧(O)]、土地/建筑环境[归一化植被指数(NDVI)、与水的距离、不透水表面]和环境温度(暖季和冷季温度的均值和标准差)。我们应用了Cox比例风险模型,该模型考虑了几个特定队列的个体和区域水平变量。我们通过单暴露模型和多暴露模型以及暴露之间的相互作用来评估关联。使用累积风险指数(CRI)估计联合效应。使用随机效应荟萃分析合并特定队列的风险比(HR)。

结果

在约2.04亿人年的观察期内,我们观察到超过310万例死亡。在行政区队列中,PM、NO和BC暴露增加与全因死亡率显著相关(合并HR分别为:1.054、1.033和1.032)。我们观察到不透水表面增加和特定季节平均温度升高有不良影响,而O、NDVI、与水的距离增加以及温度变化对全因死亡率有保护作用。与较高(第90百分位)NDVI水平的地区相比,较低(第10百分位)NDVI水平地区的PM影响更大[合并HR:1.054(95%置信区间(CI)1.030 - 1.079)对1.038(95%CI 0.964 - 1.118)]。NO也观察到类似模式。与单暴露HR相比,空气污染物(PM或NO)加NDVI和暖季平均温度的CRI产生了更强的效应:[PM合并HR:1.061(95%CI 1.021 - 1.102);NO合并HR:1.041(95%CI 1.025 - 1.057)]。在传统队列中观察到类似模式的非显著效应。

讨论

我们研究的结果不仅支持长期暴露于空气污染和绿化的独立效应,还突出了与其他环境暴露相互作用时增强的效应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14c3/10910955/344079acd72f/fepid-03-1328188-g001.jpg

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