Dioxins and dioxin-like compounds (DLCs) are common pollutants hazardous to human health. We applied 12 dioxins and DLCs data of 1851 participants (including 484 arthritis patients) from National Health Examination Survey (NHANES) 2001-2004 and quadrupled them into rank variables. Multivariate logistic regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models were used to explore the relationship between individual or mixed exposure to the pollutants and arthritis after adjusting for multiple covariates. In multivariable logistic regression with an individual dioxin or DLC, almost every chemical was significantly positively associated with arthritis, except PCB66 (polychlorinated biphenyl 66) and 1,2,3,4,6,7,8-heptachlorodibenzofuran (hpcdf). The WQS model indicated that the combined exposure to the 12 dioxins and DLCs was positively linked to arthritis (OR: 1.884, 95% CI: 1.514-2.346), with PCB156 (weighted 0.281) making the greatest contribution. A positive trend between combined exposure and arthritis was observed in the BKMR model, with a posterior inclusion probability (PIP) of 0.987 for PCB156, which was also higher than the other contaminants.
Keywords: Arthritis; Bayesian kernel machine regression; Dioxin; Dioxin-like compounds; Environmental exposure; Weighted quantile sum.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.