Association between exposure to mixture of heavy metals and hyperlipidemia risk among U.S. adults: A cross-sectional study

Abstract

Previous studies have suggested that exposure to heavy metals might increase the risk of hyperlipidemia. However, limited research has investigated the association between exposure to mixture of heavy metals and hyperlipidemia risk. To explore the independent and combined effects of heavy metal exposure on hyperlipidemia risk, this study involved 3293 participants from the National Health and Nutrition Examination Survey (NHANES), including 2327 with hyperlipidemia and the remaining without. In the individual metal analysis, the logistic regression model confirmed the positive effects of barium (Ba), cadmium (Cd), mercury (Hg), Lead (Pb), and uranium (U) on hyperlipidemia risk, Ba, Cd, Hg and Pb were further validated in restricted cubic splines (RCS) regression model and identified as positive linear relationships. In the metal mixture analysis, weighted quantile sum (WQS) regression, Bayesian kernel machine regression (BKMR), and quantile-based g computation (qgcomp) models consistently revealed a positive correlation between exposure to metal mixture and hyperlipidemia risk, with Ba, Cd, Hg, Pb, and U having significant positive driving roles in the overall effects. These associations were more prominent in young/middle-aged individuals. Moreover, the BKMR model uncovered some interactions between specific heavy metals. In conclusion, this study offers new evidence supporting the link between combined exposure to multiple heavy metals and hyperlipidemia risk, but considering the limitations of this study, further prospective research is required.