Related Experiment Video
Updated: Jul 16, 2025

Cell-free Biochemical Fluorometric Enzymatic Assay for High-throughput Measurement of Lipid Peroxidation in High Density Lipoprotein
Published on: October 12, 2017
Study on the correlation and interaction between metals and dyslipidemia: a case-control study in Chinese
Zhongyuan Zhang1,2, Rui Wang1,2, Pei He1,2
1School of Public Health, Ningxia Medical University, No.1160, Shengli Street, Xingqing District, Yinchuan, 750004, People's Republic of China.
Abstract:
Previous studies on the association between metals and dyslipidemia are not completely consistent. There are few studies investigating the relationship between mixed metal exposure and dyslipidemia as well as the effects of metals on dyslipidemia in community-dwelling elderly. To evaluate the correlations and interaction effect between the urinary concentrations of metals and the risk of dyslipidemia in community-dwelling elderly. We designed a case-control study to assess the correlation between urine metals and dyslipidemia in elderly people in the Yinchuan. The urinary levels of 13 metals, including calcium, vanadium, iron, cobalt, zinc, copper, arsenic, selenium, molybdenum, cadmium, tellurium, and thallium, were measured by inductively coupled plasma-mass spectrometry (ICP-MS), and the blood biochemical analyzer was used to measure the blood lipid levels of 3384 senior individuals from four different areas of Yinchuan city. Logistic regression and restricted cubic splines (RCS) were used to explore the correlation and dose-response relationship between urinary metals and the risk of dyslipidemia. Least absolute shrinkage and selection operator (LASSO) regression was used to select metals, and then weighted quantile sum (WQS) regression was used to explore the weight of each metal in mixed metals. Bayesian kernel machine regression (BKMR) was used to explore the interactions between metals on dyslipidemia risk. (1) After selection by LASSO regression, in the multi-metal model, compared with the lowest quartile, the adjusted ORs (95%CI) of the highest quartiles were 0.47 (0.37-0.60) for Fe, 1.43 (1.13-1.83) for Zn, 1.46 (1.11-1.92) for As, 0.59 (0.44-0.80) for Se, 1.53 (1.18-2.00) for Mo, and 1.36 (1.07-1.73) for Te. (2) In the WQS regression model, Fe and Mo accounted for the largest weight in the negative and positive effects of dyslipidemia, respectively. (3) In the BKMR model, there may be a positive interaction between Te and Se on dyslipidemia. Among the mixed metals, Fe, As, Se, Mo, and Te were associated with the prevalence of dyslipidemia, with Fe and Mo contributing the most. There may be certain interactions between Te and Se.
Related Concept Videos
Coronary Artery Disease IV: Preventive Measures
Cholesterol: Significance and Regulation
Considering cholesterol and...
Coronary Artery Disease I: Introduction
Blood Studies for Cardiovascular System III: Serum Lipid Profile
Serum lipids are fats and fatty substances in the blood and are crucial for various bodily functions, including energy storage, cellular structure, and hormone production. Serum lipids consist of cholesterol, triglycerides, and phospholipids.
Cholesterol is a soft, fat-like substance found in all body cells. It is crucial for producing hormones, vitamin D, and substances that aid...
Atherosclerosis III: Management
Lipids: Dietary Sources and Requirements

