Association between mixed dioxin exposure and hyperuricemia in U.S. adults: A comparison of three statistical models. (September 2022)
- Record Type:
- Journal Article
- Title:
- Association between mixed dioxin exposure and hyperuricemia in U.S. adults: A comparison of three statistical models. (September 2022)
- Main Title:
- Association between mixed dioxin exposure and hyperuricemia in U.S. adults: A comparison of three statistical models
- Authors:
- Zhang, Fan
Wang, Hao
Cui, Yixin
Zhao, Longzhu
Song, Ruihan
Han, Miaomiao
Wang, Weijing
Zhang, Dongfeng
Shen, Xiaoli - Abstract:
- Abstract: Background: Previous studies on the relationship between dioxin exposures and hyperuricemia have usually been based on multi-chemical linear models. However, the complex nonlinear relationship and interaction between mixed dioxin exposures and hyperuricemia have seldom been studied. In this study, we applied three different statistical models to assess the joint effect of 12 dioxins on hyperuricemia. Methods: A total of 7 dioxin-like polychlorinated biphenyls (DL-PCBs), 3 polychlorinated dibenzo-p-dioxins (PCDDs), and 2 polychlorinated dibenzofurans (PCDFs) were measured in the serum of adults by the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2004. We fitted multivariable logistic regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models to estimate the association of individual and mixed dioxin exposures with hyperuricemia. Results: Among the 1008 individuals included in our analysis, 20.04% had hyperuricemia. In the multivariable logistic regression established for each single dioxin, PCB28, PCB74, PCB105, PCB118, and 1, 2, 3, 4, 6, 7, 8-HPCDD were positively associated with hyperuricemia. With including all dioxins in the multivariable logistic regression model simultaneously, only PCB28 and 1, 2, 3, 4, 6, 7, 8-HPCDD were positively associated with hyperuricemia. In the WQS regression model, the WQS index was significantly associated (OR (95% CI): 2.32 (1.26, 4.28)) with hyperuricemia,Abstract: Background: Previous studies on the relationship between dioxin exposures and hyperuricemia have usually been based on multi-chemical linear models. However, the complex nonlinear relationship and interaction between mixed dioxin exposures and hyperuricemia have seldom been studied. In this study, we applied three different statistical models to assess the joint effect of 12 dioxins on hyperuricemia. Methods: A total of 7 dioxin-like polychlorinated biphenyls (DL-PCBs), 3 polychlorinated dibenzo-p-dioxins (PCDDs), and 2 polychlorinated dibenzofurans (PCDFs) were measured in the serum of adults by the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2004. We fitted multivariable logistic regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models to estimate the association of individual and mixed dioxin exposures with hyperuricemia. Results: Among the 1008 individuals included in our analysis, 20.04% had hyperuricemia. In the multivariable logistic regression established for each single dioxin, PCB28, PCB74, PCB105, PCB118, and 1, 2, 3, 4, 6, 7, 8-HPCDD were positively associated with hyperuricemia. With including all dioxins in the multivariable logistic regression model simultaneously, only PCB28 and 1, 2, 3, 4, 6, 7, 8-HPCDD were positively associated with hyperuricemia. In the WQS regression model, the WQS index was significantly associated (OR (95% CI): 2.32 (1.26, 4.28)) with hyperuricemia, and 1, 2, 3, 4, 6, 7, 8-HPCDD (weighted 0.22) had the largest contribution. In BKMR analysis, a significant positive association was found between mixed dioxin exposure and hyperuricemia when all dioxins were at their 60th percentile or above, compared to their 50th percentile. The univariate exposure-response function showed that PCB105 and PCB118 were positively associated with hyperuricemia. Conclusion: By comparing the three statistical models, we concluded that the whole-body burden of 12 dioxins was significantly positively associated with hyperuricemia. PCB105, PCB118, and 1, 2, 3, 4, 6, 7, 8-HPCDD played the most important roles in hyperuricemia. Graphical abstract: Image 1 Highlights: Three models were fitted to assess the mixed effect of dioxins on hyperuricemia. The whole-body burden of 12 dioxins was positively associated with hyperuricemia. PCB105, PCB118, and 1, 2, 3, 4, 6, 7, 8-HPCDD played the important roles in hyperuricemia. Each model has its advantages and disadvantages. … (more)
- Is Part Of:
- Chemosphere. Volume 303:Part 3(2022)
- Journal:
- Chemosphere
- Issue:
- Volume 303:Part 3(2022)
- Issue Display:
- Volume 303, Issue 3, Part 3 (2022)
- Year:
- 2022
- Volume:
- 303
- Issue:
- 3
- Part:
- 3
- Issue Sort Value:
- 2022-0303-0003-0003
- Page Start:
- Page End:
- Publication Date:
- 2022-09
- Subjects:
- Hyperuricemia -- Dioxin -- Mixed exposure -- Weighted quantile sum (WQS) regression -- Bayesian kernel machine regression (BKMR)
NHANES National Health and Nutrition Examination Survey -- WQS weighted quantile sum -- BKMR Bayesian kernel machine regression -- DL-PCBs dioxin-like polychlorinated biphenyls -- PCDDs polychlorinated dibenzo-p-dioxins -- PCDFs polychlorinated dibenzo furans -- OR odds ratio -- CI confidence interval -- SD standard deviations -- IQR interquartile range -- TEQs toxicity equivalents -- NCHS National Center for Health Statistics -- CDC Centers for Disease Control and Prevention -- 1, 2, 3, 6, 7, 8-HXCDD 1, 2, 3, 6, 7, 8-Hexachlorodibenzo-p-dioxin -- 1, 2, 3, 4, 6, 7, 8-HPCDD 1, 2, 3, 4, 6, 7, 8-Heptachlorodibenzo-p-dioxin -- 1, 2, 3, 4, 6, 7, 8, 9-OCDD 1, 2, 3, 4, 6, 7, 8, 9-octachlorodibenzo-p-dioxinand -- 2, 3, 4, 7, 8-PNCDF 2, 3, 4, 7, 8-Pentachlorodibenzofuran -- 1, 2, 3, 4, 6, 7, 8-HPCDF 1, 2, 3, 4, 6, 7, 8-Heptachlorodibenzofuran -- LOD limits of detection -- CKD chronic kidney disease -- eGFR estimated glomerular filtration rate -- ACR albumin-to-creatinine ratio -- groupPIP group posterior inclusion probability -- condPIP conditional posterior inclusion probability
Pollution -- Periodicals
Pollution -- Physiological effect -- Periodicals
Environmental sciences -- Periodicals
Atmospheric chemistry -- Periodicals
551.511 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00456535/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.chemosphere.2022.135134 ↗
- Languages:
- English
- ISSNs:
- 0045-6535
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- Legaldeposit
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