In reality, people are often co-exposed to multiple heavy metals; however, current research has focused on the association between individual heavy metals and inflammation. Therefore, it is more relevant to explore the combined effects of multiple heavy metal exposure on inflammation. The study included data from the National Health and Nutrition Examination Survey (NHANES), 2011-2016. The systemic immune-inflammation index (SII) was used to reflect systemic immune-inflammation status. In this study, single variable models were used to assess the linear and non-linear relationships between single heavy metal exposures and SII. To analyze the combined effect of mixed heavy metals exposure on SII, we constructed three statistical models, including weighted quantile sum (WQS) regression, quantile-based g computation (qgcomp), and Bayesian kernel machine regression (BKMR). The single-exposure analysis found positive associations between multiple heavy metals and SII, while mercury in blood was negatively associated with SII, and U-shaped correlations were observed between blood lead, urine barium and strontium, and SII. In the WQS model, SII increased significantly with increasing concentrations of mixed heavy metals, while consistent results in the qgcomp model, but not statistically significant. In the BKMR model, exposure to heavy metal mixtures was positively associated with SII, with mercury, cadmium, and cobalt in urine contributing the most to the mixed exposure. In addition, synergistic and antagonistic effects between heavy metals on increasing SII were found in our study. In summary, our results reveal that combined exposure to multiple heavy metals is positively associated with SII in the US adults.
Keywords: Cadmium; Combined effect; Heavy metals; Mercury; NHANES; Systemic immune-inflammation index.
© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.