LAUSR

Growing evidence suggests that metal exposure contributes to metabolic syndrome (MetS), but little is known about the effects of combined exposure to metal mixtures. This cross-sectional study included 3748 adults who were recruited from the Medical Physical Examination Center of Tongji Hospital, Wuhan, China. The levels of 21 metal(loid)s in urine were measured by inductively coupled plasma mass spectrometry. MetS was diagnosed according to National Cholesterol Education Program's Adult Treatment Panel III recommendations. Multivariate logistic regression model was uesd to explore the effects of single-metal and multi-metal exposures. The elastic net (ENET) regularization with an environmental risk score (ERS) was performed to estimate the joint effects of exposure to metal mixtures. A total of 636 participants (17%) were diagnosed with MetS. In single metal models, MetS was positively associated with zinc (Zn) and negatively associated with nickel (Ni). In multiple metal models, the associations remained significant after adjusting for the other metals. In the joint association analysis, the ENET models selected Zn as the strongest predictor of MetS. Compared to the lowest quartile, the highest quartile of ERS was associated with an elevated risk of MetS (OR = 3.72; 95% CI: 2.77, 5.91; P-trend < 0.001). Overall, we identified that the combined effect of multiple metals was related to an increased MetS risk, with Zn being the major contributor. These findings need further validation in prospective studies.