BACKGROUND: It has been shown that multiple metals exposure is associated with hyperuricemia. However, previous studies on the association and interaction between multiple metals exposure and hyperuricemia have been controversial, and there has been little evaluation of the potential mediating role of estimating glomerular filtration rate (eGFR). METHODS: In this study, levels of 12 metals in the urine of 3756 study participants were measured using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The associations between urinary metals and the hyperuricemia were analyzed by multivariable logistic regression model and restricted cubic spline (RCS). Weighted Quantile Sum (WQS) regression was used to explore the weight of each metal. Bayesian Kernel Machine Regression (BKMR) was used to explore the join effect of mixed metal exposure. Mediation analysis was used to explore the role of eGFR in relationship between urinary metal concentration and hyperuricemia. RESULTS: In the multi-metal model, the multivariate-adjusted odds ratio (OR) and 95 % confidence interval (CI) of hyperuricemia were 0.89 (0.81,0.99) for Fe, 0.79 (0.70,0.89) for Se, 0.84 (0.75,0.93) for Cd, 0.87 (0.79,0.96) for Pb, 1.36 (1.23,1.51) for Zn (all P <
0.05). The RCS regression indicated signification nonlinear associations for Zn and Pb (all P-non-linear <
0.05). The WQS regression model based on the negative fit showed that the maximum weight of Cd is 43.1 %. In the BKMR model, metal mixtures showed an overall negative association with the risk of developing hyperuricemia, and we also found interactions between Zn and Pb. Mediation analysis showed that eGFR mediated the association between Fe, Se, Cd, Pb and hyperuricemia with mediation ratios of 11.18 %, 12.10 %, 9.60 %, and 12.01 %, respectively. CONCLUSIONS: The metal mixture in urine is negatively correlated with hyperuricemia, with Cd having the greatest impact. eGFR may play a partial role in association of Fe, Se, Cd and Pb exposure with hyperuricemia.