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.
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Acknowledgements
The authors of this study would like to thank all the participants and staff of this study. The authors of this study would like to thank the editor and reviewers for improving the quality of the manuscript. Thank Siyu Duan for her selfless dedication to the establishment of cohort baseline and the measurement of urinary metals in this study. Thank Dr. Zhang Rui and Dr. Zhao Yi for their support for this project.
Funding
This project was supported by the “Light of the West” Talent Training Plan Project of Chinese Academy of Sciences (XAB2022YM18), the Natural Science Foundation Project of Ningxia, China (2022AAC05024, 2023AAC02032 and 2022AAC05028), and the Key Research and Development Project of Ningxia (Grant No. 2021BEG02026).
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Zhongyuan Zhang: conceptualization, methodology, investigation, writing—original draft, data curation. Rui Wang: conceptualization, methodology, formal analysis, writing—original draft, data curation. Pei He: conceptualization, methodology, investigation, formal analysis, data curation. Yuqing Dai: methodology, formal analysis, data curation. Siyu Duan: methodology, formal analysis, data curation. Meiyan Li: investigation. Zhuoheng Shen: investigation. Xiaoyu Li: supervision. Jian Sun: conceptualization, investigation, formal analysis, writing—original draft, supervision.
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Zhang, Z., Wang, R., He, P. et al. Study on the correlation and interaction between metals and dyslipidemia: a case–control study in Chinese community-dwelling elderly. Environ Sci Pollut Res 30, 105756–105769 (2023). https://doi.org/10.1007/s11356-023-29695-z
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DOI: https://doi.org/10.1007/s11356-023-29695-z