Backgrounds: Previous studies have suggested the potential links between dioxins or dioxin-like polychlorinated biphenyls (DL-PCBs) and obesity. However, the combined effects of dioxins and DL-PCBs on obesity are still unclear.
Methods: Nine kinds of dioxins and DL-PCBs were measured among 852 adults using the National Health and Nutrition Examination Survey (NHANES) from 2003-2004. We conducted generalized linear regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models to evaluate the association of these chemicals with obesity, and mediation analysis was performed to explore the mediating effect of glycated hemoglobin A1c (HbA1c).
Results: Dioxins and DL-PCBs were identified as risk factors for obesity according to logistic regression models. Both WQS and BKMR regression indicated that combined exposure to dioxins and DL-PCBs was linked to obesity, of which 1,2,3,4,6,7,8-hpcdd showed the greatest contributions. The results from mediation analyses suggested that the relationships of dioxins with obesity or obesity indices were mediated by HbA1c, with the proportion of mediation ranging from 5.21% to 9.04% and the beta estimates (95%CI) were 0.007 (0.002, 0.010), 0.007 (0.0005, 0.020), 0.380 (0.133, 0.800), 0.408 (0.132, 0.800), respectively.
Conclusion: Our findings revealed that mixed exposure to dioxins and DL-PCBs is positively correlated with obesity.
Keywords: Bayesian kernel machine regression (BKMR); Combined effect; Dioxins; Obesity; Weighted quantile sum (WQS) regression.
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