Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
Environ Sci Technol. 2022 Sep 20;56(18):13160-13168. doi: 10.1021/acs.est.2c01568. Epub 2022 Aug 31.
Dyslipidemia may be a potential mechanism linking fine particulate matter (PM) to adverse cardiovascular outcomes. However, inconsistent associations between PM and blood lipids have resulted from the existing research, and the joint effect of PM elemental constituents on blood lipid profiles remains unclear. We aimed to explore the overall associations between PM elemental constituents and blood lipid profiles and to identify the significant PM elemental constituents in this association. Sixty-nine elderly people were recruited between September 2018 and January 2019. Each participant completed a survey questionnaire, 3 days of individual exposure monitoring, health examination, and biological sample collection at each follow-up visit. Bayesian kernel machine regression (BKMR) models were used to identify the joint effects of the 17 elemental constituents on blood lipid profiles. Total cholesterol, low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C) levels were significantly increased in older adults when exposed to the mixture of PM elemental constituents. Copper and titanium had higher posterior inclusion probabilities than other constituents, ranging from 0.76 to 0.90 (Cu) and 0.74 to 0.94 (Ti). Copper and titanium in the PM elemental constituent mixture played an essential role in changes to blood lipid levels. This study highlights the importance of identifying critical hazardous PM constituents that may cause adverse cardiovascular outcomes in the future.
血脂异常可能是细颗粒物(PM)与不良心血管结局相关的潜在机制。然而,由于现有研究,PM 与血液脂质之间的关联并不一致,PM 元素成分对血脂谱的联合影响仍不清楚。我们旨在探讨 PM 元素成分与血脂谱之间的总体关联,并确定该关联中的重要 PM 元素成分。
2018 年 9 月至 2019 年 1 月期间,共招募了 69 名老年人。每位参与者在每次随访时完成一份问卷调查、3 天的个体暴露监测、健康检查和生物样本采集。
贝叶斯核机器回归(BKMR)模型用于识别 17 种元素成分对血脂谱的联合影响。当老年人暴露于 PM 元素成分混合物中时,总胆固醇、低密度脂蛋白胆固醇(LDL-C)和非高密度脂蛋白胆固醇(non-HDL-C)水平显著升高。
铜和钛的后验纳入概率高于其他成分,范围为 0.76 至 0.90(Cu)和 0.74 至 0.94(Ti)。PM 元素成分混合物中的铜和钛在血液脂质水平的变化中起着重要作用。
本研究强调了识别可能导致未来不良心血管结局的关键危险 PM 成分的重要性。