Inflammation factors mediate the association between heavy metal and Homa-IR index: An integrated approach from the NHANES (2011∼2016).

INTRODUCTION

The interplay between heavy metals exposure and insulin resistance (IR), specifically through the mediation of inflammation factors, is crucial for understanding metabolic disturbances. This study utilizes data from the NHANES (2011∼2016) to investigate these relationships in a large, diverse U.S.

METHODS

The study analyzed the associations between heavy metals (cadmium (Cd), lead (Pb), mercury (Hg), manganese (Mn)) and the Homeostatic Model Assessment for Insulin Resistance (Homa-IR) index. The analyses included descriptive statistics, Pearson's correlations, linear and non-linear regression models, and advanced statistical models such as Weighted Quantile Sum (WQS) regression and Bayesian Kernel Machine Regression (BKMR). Inflammation factors were assessed for their mediating role in these associations.

RESULTS

The findings highlighted significant positive correlations between specific heavy metals and the Homa-IR index. Both linear and non-linear associations were evident, with certain metals showing a more pronounced impact in the presence of high inflammation markers. It was found that the Homa-IR index was negatively associated with Pb (β (95 %CI) = -0.0126 (-0.0238 ∼ -0.0015), P = 0.0268) and Hg (β (95 %CI) = -0.0090 (-0.0180 ∼ -0.0001), P = 0.0487). The WQS regression indicated an overall positive relationship between heavy metal mixtures (Estimate: 0.0050, P < 0.05) and the Homa-IR index where Cu had the highest weights (0.7741), while BKMR analyses detailed the varying effects of individual metals at different exposure levels. In the mediation analysis, it can be found that monocyte (Mono) mediated the association between Pb and Homa-IR index (direct effect:0.0546, indirect effect:0.0082) and neutrophil (Neu) (direct effect:0.0521, indirect effect:0.0047) can mediate the association between Hg and Homa-IR index.

CONCLUSIONS

This study confirms that exposure to heavy metals is associated with increased insulin resistance and that inflammation significantly mediates this relationship. Understanding these pathways is essential for developing targeted interventions to mitigate the metabolic consequences of environmental exposures.