Long-term associations between time-varying exposure to ambient PM2.5 and mortality: an analysis of the UK Biobank.

IF 4.7 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Jacopo Vanoli, Arturo de la Cruz, Francesco Sera, Massimo Stafoggia, Pierre Masselot, Malcolm N Mistry, Sanjay Rajagopalan, Jennifer K Quint, Chris Fook Sheng Ng, Lina Madaniyazi, Antonio Gasparrini
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引用次数: 0

Abstract

Background: Evidence for long-term mortality risks of PM2.5 comes mostly from large administrative studies with incomplete individual information and limited exposure definitions. Here we assess PM2.5-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 PM2.5 concentrations from spatio-temporal 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 PM2.5 was associated with hazard ratios (HRs) of 1.27 (95%CI: 1.06-1.53) for all-cause, 1.24 (1.03-1.50) for non-accidental, 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 (HR=0.88, 95%CI: 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 PM2.5 exposure with all-cause, non-accidental, 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 PM2.5 and mortality.

环境 PM2.5 时变暴露与死亡率之间的长期关联:英国生物库分析。
背景:有关 PM2.5 导致长期死亡风险的证据大多来自大型行政研究,这些研究的个体信息不完整,暴露定义也有限。在此,我们利用混杂因素和暴露的详细信息,评估了英国生物库队列中 PM2.5 与死亡率的关联:方法:我们将住宅数据与时空机器学习模型得出的高分辨率 PM2.5 浓度联系起来,重建了 498,090 名受试者的详细暴露历史。我们拆分了时间到事件的数据,并在 8 年的滞后窗口内分配了每年的暴露量。我们利用控制环境和个人水平因素以及趋势的时变暴露的 Cox 比例危险模型进行了拟合。在二次分析中,我们使用分布式滞后模型检查了滞后结构,并将结果与其他暴露源和定义进行了比较:在完全调整模型中,PM2.5每增加10微克/立方米,全因死亡率的危险比(HRs)为1.27(95%CI:1.06-1.53),非事故死亡率的危险比(HRs)为1.24(1.03-1.50),呼吸系统死亡率的危险比(HRs)为2.07(1.04-4.10),肺癌死亡率的危险比(HRs)为1.66(0.86-3.19)。我们没有发现与心血管死亡相关的证据(HR=0.88,95%CI:0.59-1.31)。我们发现,环境和个人层面的生活方式因素都有很大的混杂性。分布式滞后分析表明,不同死亡原因的相关暴露窗口存在差异。使用信息量更大的暴露摘要和来源可获得更高的风险估计值:我们发现长期 PM2.5 暴露与全因、非意外、呼吸系统和肺癌死亡率有关,但与心血管死亡率无关。这项研究得益于对时变暴露的精细重建和对混杂因素的广泛控制,进一步支持了长期 PM2.5 与死亡率之间似是而非的因果关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Epidemiology
Epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
6.70
自引率
3.70%
发文量
177
审稿时长
6-12 weeks
期刊介绍: Epidemiology publishes original research from all fields of epidemiology. The journal also welcomes review articles and meta-analyses, novel hypotheses, descriptions and applications of new methods, and discussions of research theory or public health policy. We give special consideration to papers from developing countries.
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