{"title":"利用三种统计模型解读重金属混合暴露对脂质代谢的影响。","authors":"Changmao Long, Xiangjun Wang, Dongsheng Wang, Yuqing Chen, Baojun Zhang","doi":"10.1007/s10653-024-02328-1","DOIUrl":null,"url":null,"abstract":"<p><p>Lipid metabolism disorders pose a significant threat to human health. However, the relationship between heavy metal mixed exposure and lipid metabolism remains poorly understood. This study recruited 1717 residents living near a chromium factory in northeast China. The concentrations of blood Cr, Mn, Cd, Pb, V, and serum CHOL, TG, LDL and HDL levels were measured. Generalized linear model (GLM), quantile g-computation (Qg-comp), and Bayesian kernel machine regression (BKMR) were simultaneously employed to investigate the associations between heavy metal mixed exposure and lipid markers levels. GLM analysis revealed significant associations between blood Cr concentration and HDL (β = -0.07; 95%CI: -0.09, -0.05), LDL (β = -0.06; 95%CI: -0.11, -0.02), and CHOL (β = 0.07; 95%CI: 0.01, 0.12) levels. V concentration was positively associated with HDL (β = 0.12; 95%CI: 0.06, 0.18) and LDL (β = 0.17; 95%CI: 0.04, 0.30) levels. Qg-comp analysis indicated a negative association between heavy metal mixed exposure and HDL (β = -0.040; 95%CI: -0.073, -0.006) level. BKMR model further confirmed the negative relationship between heavy metal mixed exposure and HDL, with the interaction between blood Cr (> 1.05 μg/L) and blood V (> 5.16 μg/L) contributing to decreased HDL levels. Our findings suggested that heavy metal mixed exposure had impacts on HDL and CHOL levels, and the Cr and V may mutually play a predominant role in the observed abnormal HDL levels.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 1","pages":"20"},"PeriodicalIF":3.2000,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deciphering the impact of heavy metal mixed exposure on lipid metabolism using three statistical models.\",\"authors\":\"Changmao Long, Xiangjun Wang, Dongsheng Wang, Yuqing Chen, Baojun Zhang\",\"doi\":\"10.1007/s10653-024-02328-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Lipid metabolism disorders pose a significant threat to human health. However, the relationship between heavy metal mixed exposure and lipid metabolism remains poorly understood. This study recruited 1717 residents living near a chromium factory in northeast China. The concentrations of blood Cr, Mn, Cd, Pb, V, and serum CHOL, TG, LDL and HDL levels were measured. Generalized linear model (GLM), quantile g-computation (Qg-comp), and Bayesian kernel machine regression (BKMR) were simultaneously employed to investigate the associations between heavy metal mixed exposure and lipid markers levels. GLM analysis revealed significant associations between blood Cr concentration and HDL (β = -0.07; 95%CI: -0.09, -0.05), LDL (β = -0.06; 95%CI: -0.11, -0.02), and CHOL (β = 0.07; 95%CI: 0.01, 0.12) levels. V concentration was positively associated with HDL (β = 0.12; 95%CI: 0.06, 0.18) and LDL (β = 0.17; 95%CI: 0.04, 0.30) levels. Qg-comp analysis indicated a negative association between heavy metal mixed exposure and HDL (β = -0.040; 95%CI: -0.073, -0.006) level. BKMR model further confirmed the negative relationship between heavy metal mixed exposure and HDL, with the interaction between blood Cr (> 1.05 μg/L) and blood V (> 5.16 μg/L) contributing to decreased HDL levels. Our findings suggested that heavy metal mixed exposure had impacts on HDL and CHOL levels, and the Cr and V may mutually play a predominant role in the observed abnormal HDL levels.</p>\",\"PeriodicalId\":11759,\"journal\":{\"name\":\"Environmental Geochemistry and Health\",\"volume\":\"47 1\",\"pages\":\"20\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Geochemistry and Health\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1007/s10653-024-02328-1\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Geochemistry and Health","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1007/s10653-024-02328-1","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
Deciphering the impact of heavy metal mixed exposure on lipid metabolism using three statistical models.
Lipid metabolism disorders pose a significant threat to human health. However, the relationship between heavy metal mixed exposure and lipid metabolism remains poorly understood. This study recruited 1717 residents living near a chromium factory in northeast China. The concentrations of blood Cr, Mn, Cd, Pb, V, and serum CHOL, TG, LDL and HDL levels were measured. Generalized linear model (GLM), quantile g-computation (Qg-comp), and Bayesian kernel machine regression (BKMR) were simultaneously employed to investigate the associations between heavy metal mixed exposure and lipid markers levels. GLM analysis revealed significant associations between blood Cr concentration and HDL (β = -0.07; 95%CI: -0.09, -0.05), LDL (β = -0.06; 95%CI: -0.11, -0.02), and CHOL (β = 0.07; 95%CI: 0.01, 0.12) levels. V concentration was positively associated with HDL (β = 0.12; 95%CI: 0.06, 0.18) and LDL (β = 0.17; 95%CI: 0.04, 0.30) levels. Qg-comp analysis indicated a negative association between heavy metal mixed exposure and HDL (β = -0.040; 95%CI: -0.073, -0.006) level. BKMR model further confirmed the negative relationship between heavy metal mixed exposure and HDL, with the interaction between blood Cr (> 1.05 μg/L) and blood V (> 5.16 μg/L) contributing to decreased HDL levels. Our findings suggested that heavy metal mixed exposure had impacts on HDL and CHOL levels, and the Cr and V may mutually play a predominant role in the observed abnormal HDL levels.
期刊介绍:
Environmental Geochemistry and Health publishes original research papers and review papers across the broad field of environmental geochemistry. Environmental geochemistry and health establishes and explains links between the natural or disturbed chemical composition of the earth’s surface and the health of plants, animals and people.
Beneficial elements regulate or promote enzymatic and hormonal activity whereas other elements may be toxic. Bedrock geochemistry controls the composition of soil and hence that of water and vegetation. Environmental issues, such as pollution, arising from the extraction and use of mineral resources, are discussed. The effects of contaminants introduced into the earth’s geochemical systems are examined. Geochemical surveys of soil, water and plants show how major and trace elements are distributed geographically. Associated epidemiological studies reveal the possibility of causal links between the natural or disturbed geochemical environment and disease. Experimental research illuminates the nature or consequences of natural or disturbed geochemical processes.
The journal particularly welcomes novel research linking environmental geochemistry and health issues on such topics as: heavy metals (including mercury), persistent organic pollutants (POPs), and mixed chemicals emitted through human activities, such as uncontrolled recycling of electronic-waste; waste recycling; surface-atmospheric interaction processes (natural and anthropogenic emissions, vertical transport, deposition, and physical-chemical interaction) of gases and aerosols; phytoremediation/restoration of contaminated sites; food contamination and safety; environmental effects of medicines; effects and toxicity of mixed pollutants; speciation of heavy metals/metalloids; effects of mining; disturbed geochemistry from human behavior, natural or man-made hazards; particle and nanoparticle toxicology; risk and the vulnerability of populations, etc.