混淆
生命银行
危险系数
比例危险模型
医学
人口学
效果修正
分布滞后
队列研究
队列
环境卫生
滞后
危害
统计
置信区间
内科学
生物
生物信息学
数学
计算机科学
社会学
计算机网络
生态学
作者
Jacopo Vanoli,Arturo de la Cruz Libardi,Francesco Sera,Massimo Stafoggia,Pierre Masselot,Malcolm Mistry,Sanjay Rajagopalan,Jennifer K Quint,Chris Fook Sheng Ng,Lina Madaniyazi,Antonio Gasparrini
出处
期刊:Epidemiology
[Ovid Technologies (Wolters Kluwer)]
日期:2024-10-22
卷期号:36 (1): 1-10
被引量:7
标识
DOI:10.1097/ede.0000000000001796
摘要
Background: Evidence for long-term mortality risks of PM 2.5 comes mostly from large administrative studies with incomplete individual information and limited exposure definitions. Here we assess PM 2.5 –mortality associations in the UK Biobank cohort using detailed information on confounders and exposure. Methods: We reconstructed detailed exposure histories for 498,090 subjects by linking residential data with high-resolution PM 2.5 concentrations from spatiotemporal machine-learning models. We split the time-to-event data and assigned yearly exposures over a lag window of 8 years. We fitted Cox proportional hazard models with time-varying exposure controlling for contextual- and individual-level factors, as well as trends. In secondary analyses, we inspected the lag structure using distributed lag models and compared results with alternative exposure sources and definitions. Results: In fully adjusted models, an increase of 10 μg/m³ in PM 2.5 was associated with hazard ratios of 1.27 (95% confidence interval: 1.06, 1.53) for all-cause, 1.24 (1.03, 1.50) for nonaccidental, 2.07 (1.04, 4.10) for respiratory, and 1.66 (0.86, 3.19) for lung cancer mortality. We found no evidence of association with cardiovascular deaths (hazard ratio = 0.88, 95% confidence interval: 0.59, 1.31). We identified strong confounding by both contextual- and individual-level lifestyle factors. The distributed lag analysis suggested differences in relevant exposure windows across mortality causes. Using more informative exposure summaries and sources resulted in higher risk estimates. Conclusions: We found associations of long-term PM 2.5 exposure with all-cause, nonaccidental, respiratory, and lung cancer mortality, but not with cardiovascular mortality. This study benefits from finely reconstructed time-varying exposures and extensive control for confounding, further supporting a plausible causal link between long-term PM 2.5 and mortality.
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