Abstract: In environmental health research, populations are often simultaneously exposed to multiple environmental contaminants, forming exposure mixtures that may have synergistic or interactive effects on health outcomes, posing challenges to traditional single-exposure analyses. The weighted quantile sum regression (WQS) model is a statistical method designed to assess the combined health impacts of multiple exposure factors. By weighting and summing the quantiles of exposure factors, this model generates a composite index, effectively addressing multicollinearity and evaluating the overall effect of mixed exposures. The WQS model holds significant value in epidemiology, particularly environmental epidemiology, such as assessing the impact of mixed heavy metal exposures on health indicators. Studies have demonstrated that the WQS model can effectively reveal the relative contributions of individual exposure factors, providing a scientific basis for environmental health risk assessment. However, the application of the model requires consideration of data distribution and the stability of weight estimation. Future research may combine the WQS model with other statistical method to further optimize its performance and expand its applications in various fields.