The Association Between Blood Mercury and Lipid Biomarkers in US Hypertensive Adults.

Abstract

This cross-sectional research gathered data from a total of 4415 participants sourced from the National Health and Nutrition Examination Survey (NHANES). The Holm-Bonferroni stepdown procedure was utilized to control the type I error rate in multiple comparisons. We employed multivariable linear regression models to assess the correlation between blood Hg and lipid biomarkers. Subsequently, subgroup analyses were conducted, categorized by both gender and race. Additionally, we used smooth curve fittings and generalized additive models to confirm the presence of non-linear relationships. When non-linearity was detected, we applied a recursive algorithm to calculate the inflection points. Finally, we established a weighted two-piecewise linear regression model to illustrate the associations on either side of the inflection point. In our multivariable linear regression models, clear associations emerged. Specifically, positive correlations were observed between blood mercury and TC (β = 0.025; 95% CI 0.009 to 0.041; corrected P = 0.011), LDL-C (β = 0.022; 95% CI 0.007 to 0.036; corrected P = 0.012), and HDL-C (β = 0.007; 95% CI 0.001 to 0.013; corrected P = 0.058). However, there was no significant correlation with TG (β = - 0.007; 95% CI - 0.018 to 0.004; corrected P = 0.526). Notably, it has been demonstrated that distinct inverted U-shaped and U-shaped curves exist when stratified by gender in our analysis. Blood Hg exhibited a positive correlation with TC, LDL-C, and HDL-C in hypertensive adults in the USA. Nonetheless, no significant association was observed with TG.