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The association between co-exposure to multiple metals and renal function is poorly understood. We aimed to evaluate the individual and joint effects of metal exposure on renal function in this study. We performed a cross-sectional study including 5828 participants in Guangxi, China, in 2019. Urine concentrations of 17 metals were detected by inductively coupled plasma mass spectrometry (ICP-MS). Logistic regression model and restricted cubic spline (RCS) were applied to investigate the association of individual metal exposure with renal dysfunction. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to assess the co-exposure effects of the metals. Participants with the highest quartile of urinary Cu were at 1.84-fold (95% confidence interval (CI): 1.20–2.87) increased risk of renal dysfunction compared with the lowest quartile. The highest quartiles of urinary Sr, Cs, V, Ba, and Se were associated with 0.27-fold (95% CI: 0.17–0.43), 0.33 (95% CI: 0.19–0.53), 0.41 (95% CI: 0.25–0.65), 0.58 (95% CI: 0.36–0.90), and 0.33 (95% CI: 0.19–0.56) decreased risk of renal dysfunction compared with their lowest quartile, respectively. Furthermore, urinary Ba and Cu were non-linearly correlated with renal dysfunction. The WQS analysis showed that mixed metal exposure was inversely associated with renal dysfunction (OR = 0.47, 95% CI: 0.35–0.62), and Sr accounted for the largest weight (52.2%), followed by Cs (32.3%) in the association. Moreover, we observed a potential interaction between Cu, Cs, and Ba for renal dysfunction in BKMR model. Exposure to Se, Sr, Cs, V, and Ba is associated with decreased risk of renal dysfunction, whereas an increased risk is associated with Cu exposure. Co-exposure to these metals is negatively associated with renal dysfunction, and Sr and Cs are the main contributors to the associations.