Associations Between Serum Multiple Metals Exposures and Metabolic Syndrome: a Longitudinal Cohort Study
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Associations Between Serum Multiple Metals Exposures and Metabolic Syndrome: a Longitudinal Cohort Study Xiuming Feng 1,2,3,4 & Longman Li 1,2,3 & Lulu Huang 1,2,3,4 & Haiying Zhang 1,2,3 & Zengnan Mo 1,2,3,5 & Xiaobo Yang 1,2,3,4 Received: 7 July 2020 / Accepted: 1 September 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Although many studies have confirmed metabolic syndrome (MetS) is correlated with metal exposures, few studies have elucidated the associations of multiple metals with MetS risk. We aim to explore the relationship between serum 22 metals and MetS. We determined serum 22 metals using ICP-MS and used LASSO regression to select metals independently related with MetS to construct multiple-metals model. We further explored the dose-response relationship between positive metals and MetS by the restricted cubic spline regression. After screening by LASSO regression, serum 11 metals were selected to construct multiple-metals model in cross-sectional analysis, while 5 metals in longitudinal analysis. In the 11-metal model, only tin and zinc were associated with MetS in cross-sectional analysis (ORtin = 2.22, 95% CI:1.43, 3.45; ORzinc = 2.17, 95% CI: 1.42, 3.32; both Ptrend < 0.05). Besides, the same results were found in the 5-metal model in longitudinal analysis (HRtin = 1.66, 95% CI: 0.87, 3.17; HRzinc = 1.83, 95% CI: 1.07, 3.14; both Ptrend < 0.05). Moreover, there were positive linear relationships between serum tin and zinc concentrations and the increasing risk of MetS (both Poverall < 0.05, Pnon-linearity > 0.05). Furthermore, the interaction between high tin and high zinc was also associated with increasing MetS risk (Pinteraction < 0.05). We found that serum tin and zinc were independently and interactively associated with MetS in the southern Chinese men. Our results suggested that high tin and zinc may be the risk factors of MetS. Keywords Metabolic syndrome . Co-exposure . Cross-sectional analysis . Longitudinal cohort analysis
Introduction Metabolic syndrome (MetS) refers to abnormal metabolic status, including abdominal obesity, dyslipidemia, hyperglycemia, and elevated blood pressure [1, 2]. With the development of society
and economy, the change of lifestyle is the major contributor to the increasing incidence of MetS [3, 4]. Physical inactivity, a high-fat and high-cholesterol diet, drinking, and smoking accounted for the major causes of MetS. Previous studies have indicated that MetS is one of the important risk factors of
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s12011-020-02371-w) contains supplementary material, which is available to authorized users. * Xiaobo Yang [email protected] Xiuming Feng [email protected] Longman Li [email protected] Lulu Huang [email protected]
1
Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
2
Guangxi key Laboratory for Genomic and Personalized Medicine, Nanning, Guangxi, China
3
Guangxi Co
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