The Effect of Mixture of Heavy Metals on Obesity in Individuals ≥50 Years of Age

Little is known about the association between a mixture of heavy metals and obesity among individuals ≥50 years of age with comorbidities. Thus, we identified the associations of serum cadmium (Cd), lead (Pb), and mercury (Hg) with obesity using linear regression models; weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) were conducted as secondary analyses. Of the 6434 subjects included in the analysis, 13.8% had obesity and 44.6% had abdominal obesity. In the logistic regression model, serum Hg was associated with obesity and abdominal obesity, and significant trends were observed for these heavy metal tertiles (p < 0.001). Serum Hg levels were also associated with body mass index (BMI) and waist circumference (WC). The WQS index was significantly associated with both obesity (OR = 1.43, 95% CI: 1.40–1.46) and abdominal obesity (β = 1.51, 95% CI: 1.48–1.54). The qgcomp index also found a significant association between heavy metals and both obesity (OR = 1.35, 95% CI: 1.12–1.63) and abdominal obesity (OR = 1.34, 95% CI: 1.12–1.60). Serum Hg was the most heavily weighed heavy metal in these models. In BKMR analysis, the overall effect of the mixture was significantly associated with obesity, BMI, and WC. Serum Hg showed positive trends and was observed as the most important factor associated with obesity, BMI, and WC. Our findings were largely robust to secondary analyses that used three novel mixture modeling approaches: WQS, qpcomp, and BKMR. Given increasing exposure to heavy metals, well-characterized cohorts of individuals aged ≥50 years are required to determine the mixed effects of heavy metals on obesity and related diseases.