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美国成年人接触重金属混合物与高脂血症风险之间的关联:一项横断面研究。

Association between exposure to mixture of heavy metals and hyperlipidemia risk among U.S. adults: A cross-sectional study.

作者信息

Wang Guosheng, Fang Lanlan, Chen Yuting, Ma Yubo, Zhao Hui, Wu Ye, Xu Shengqian, Cai Guoqi, Pan Faming

机构信息

Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China; The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.

Department of Rheumatism and Immunity, First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230022, China.

出版信息

Chemosphere. 2023 Dec;344:140334. doi: 10.1016/j.chemosphere.2023.140334. Epub 2023 Oct 1.

Abstract

Previous studies have suggested that exposure to heavy metals might increase the risk of hyperlipidemia. However, limited research has investigated the association between exposure to mixture of heavy metals and hyperlipidemia risk. To explore the independent and combined effects of heavy metal exposure on hyperlipidemia risk, this study involved 3293 participants from the National Health and Nutrition Examination Survey (NHANES), including 2327 with hyperlipidemia and the remaining without. In the individual metal analysis, the logistic regression model confirmed the positive effects of barium (Ba), cadmium (Cd), mercury (Hg), Lead (Pb), and uranium (U) on hyperlipidemia risk, Ba, Cd, Hg and Pb were further validated in restricted cubic splines (RCS) regression model and identified as positive linear relationships. In the metal mixture analysis, weighted quantile sum (WQS) regression, Bayesian kernel machine regression (BKMR), and quantile-based g computation (qgcomp) models consistently revealed a positive correlation between exposure to metal mixture and hyperlipidemia risk, with Ba, Cd, Hg, Pb, and U having significant positive driving roles in the overall effects. These associations were more prominent in young/middle-aged individuals. Moreover, the BKMR model uncovered some interactions between specific heavy metals. In conclusion, this study offers new evidence supporting the link between combined exposure to multiple heavy metals and hyperlipidemia risk, but considering the limitations of this study, further prospective research is required.

摘要

先前的研究表明,接触重金属可能会增加患高脂血症的风险。然而,针对接触重金属混合物与高脂血症风险之间关联的研究较少。为了探究重金属暴露对高脂血症风险的独立和综合影响,本研究纳入了来自美国国家健康与营养检查调查(NHANES)的3293名参与者,其中2327人患有高脂血症,其余人未患高脂血症。在单个金属分析中,逻辑回归模型证实了钡(Ba)、镉(Cd)、汞(Hg)、铅(Pb)和铀(U)对高脂血症风险有正向影响,Ba、Cd、Hg和Pb在受限立方样条(RCS)回归模型中得到进一步验证,并被确定为呈正线性关系。在金属混合物分析中,加权分位数和(WQS)回归、贝叶斯核机器回归(BKMR)和基于分位数的g计算(qgcomp)模型一致显示,接触金属混合物与高脂血症风险之间存在正相关,Ba、Cd、Hg、Pb和U在总体影响中具有显著的正向驱动作用。这些关联在年轻/中年个体中更为突出。此外,BKMR模型还发现了特定重金属之间的一些相互作用。总之,本研究提供了新的证据支持多种重金属联合暴露与高脂血症风险之间的联系,但考虑到本研究的局限性,还需要进一步的前瞻性研究。

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