Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, USA.
Department of Radiology, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China.
Environ Res. 2023 Sep 1;232:116334. doi: 10.1016/j.envres.2023.116334. Epub 2023 Jun 8.
Air pollution can affect cardiometabolic biomarkers in susceptible populations, but the most important exposure window (lag days) and exposure duration (length of averaging period) are not well understood. We investigated air pollution exposure across different time intervals on ten cardiometabolic biomarkers in 1550 patients suspected of coronary artery disease. Daily residential PM and NO were estimated using satellite-based spatiotemporal models and assigned to participants for up to one year before the blood collection. Distributed lag models and generalized linear models were used to examine the single-day-effects by variable lags and cumulative effects of exposures averaged over different periods before the blood draw. In single-day-effect models, PM was associated with lower apolipoprotein A (ApoA) in the first 22 lag days with the effect peaking on the first lag day; PM was also associated with elevated high-sensitivity C-reactive protein (hs-CRP) with significant exposure windows observed after the first 5 lag days. For the cumulative effects, short- and medium-term exposure was associated with lower ApoA (up to 30wk-average) and higher hs-CRP (up to 8wk-average), triglycerides and glucose (up to 6 d-average), but the associations were attenuated to null over the long term. The impacts of air pollution on inflammation, lipid, and glucose metabolism differ by the exposure timing and durations, which can inform our understanding of the cascade of underlying mechanisms among susceptible patients.
空气污染可影响易感人群的心血代谢生物标志物,但最重要的暴露窗口(滞后天数)和暴露持续时间(平均期长度)尚不清楚。我们研究了在 1550 名疑似冠心病患者中,在不同时间间隔内的 10 种心血代谢生物标志物的空气污染暴露情况。利用基于卫星的时空模型来估算每日居民 PM 和 NO,并将其分配给参与者,最长可达血液采集前一年。采用分布式滞后模型和广义线性模型,通过可变滞后检查单日效应,以及在血液采集前不同时间段内平均暴露的累积效应。在单日效应模型中,PM 与前 22 个滞后日的载脂蛋白 A(ApoA)降低有关,效应峰值出现在第一个滞后日;PM 还与高敏 C 反应蛋白(hs-CRP)升高有关,在第一个滞后日后观察到明显的暴露窗口。对于累积效应,短期和中期暴露与 ApoA 降低(长达 30 周平均)和 hs-CRP、甘油三酯和葡萄糖升高(长达 6 天平均)有关,但随着时间的推移,这些关联逐渐减弱至无。空气污染对炎症、脂质和葡萄糖代谢的影响因暴露时间和持续时间而异,这有助于我们了解易感患者潜在机制的级联反应。