PMID- 35644240
OWN - NLM
STAT- MEDLINE
DCOM- 20220623
LR  - 20220623
IS  - 1879-1298 (Electronic)
IS  - 0045-6535 (Linking)
VI  - 303
IP  - Pt 3
DP  - 2022 Sep
TI  - Association between mixed dioxin exposure and hyperuricemia in U.S. adults: A 
      comparison of three statistical models.
PG  - 135134
LID - S0045-6535(22)01627-7 [pii]
LID - 10.1016/j.chemosphere.2022.135134 [doi]
AB  - 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.
CI  - Copyright (c) 2022 Elsevier Ltd. All rights reserved.
FAU - Zhang, Fan
AU  - Zhang F
AD  - Department of Epidemiology and Health Statistics, School of Public Health, 
      Qingdao University, Qingdao, 266071, China.
FAU - Wang, Hao
AU  - Wang H
AD  - Department of Epidemiology and Health Statistics, School of Public Health, 
      Qingdao University, Qingdao, 266071, China.
FAU - Cui, Yixin
AU  - Cui Y
AD  - Department of Epidemiology and Health Statistics, School of Public Health, 
      Qingdao University, Qingdao, 266071, China.
FAU - Zhao, Longzhu
AU  - Zhao L
AD  - Department of Epidemiology and Health Statistics, School of Public Health, 
      Qingdao University, Qingdao, 266071, China.
FAU - Song, Ruihan
AU  - Song R
AD  - Department of Epidemiology and Health Statistics, School of Public Health, 
      Qingdao University, Qingdao, 266071, China.
FAU - Han, Miaomiao
AU  - Han M
AD  - Department of Epidemiology and Health Statistics, School of Public Health, 
      Qingdao University, Qingdao, 266071, China.
FAU - Wang, Weijing
AU  - Wang W
AD  - Department of Epidemiology and Health Statistics, School of Public Health, 
      Qingdao University, Qingdao, 266071, China.
FAU - Zhang, Dongfeng
AU  - Zhang D
AD  - Department of Epidemiology and Health Statistics, School of Public Health, 
      Qingdao University, Qingdao, 266071, China.
FAU - Shen, Xiaoli
AU  - Shen X
AD  - Department of Epidemiology and Health Statistics, School of Public Health, 
      Qingdao University, Qingdao, 266071, China. Electronic address: 
      shenxiaoli@qdu.edu.cn.
LA  - eng
PT  - Journal Article
DEP - 20220526
PL  - England
TA  - Chemosphere
JT  - Chemosphere
JID - 0320657
RN  - 0 (Benzofurans)
RN  - 0 (Dibenzofurans, Polychlorinated)
RN  - 0 (Dioxins)
RN  - 0 (Polychlorinated Dibenzodioxins)
RN  - DFC2HB4I0K (Polychlorinated Biphenyls)
SB  - IM
MH  - Adult
MH  - Bayes Theorem
MH  - *Benzofurans/analysis
MH  - Dibenzofurans, Polychlorinated
MH  - *Dioxins/toxicity
MH  - Humans
MH  - *Hyperuricemia/epidemiology
MH  - Models, Statistical
MH  - Nutrition Surveys
MH  - *Polychlorinated Biphenyls/analysis
MH  - *Polychlorinated Dibenzodioxins/analysis
OTO - NOTNLM
OT  - Bayesian kernel machine regression (BKMR)
OT  - Dioxin
OT  - Hyperuricemia
OT  - Mixed exposure
OT  - Weighted quantile sum (WQS) regression
EDAT- 2022/06/02 06:00
MHDA- 2022/06/24 06:00
CRDT- 2022/06/01 10:30
PHST- 2022/02/23 00:00 [received]
PHST- 2022/05/08 00:00 [revised]
PHST- 2022/05/24 00:00 [accepted]
PHST- 2022/06/02 06:00 [pubmed]
PHST- 2022/06/24 06:00 [medline]
PHST- 2022/06/01 10:30 [entrez]
AID - S0045-6535(22)01627-7 [pii]
AID - 10.1016/j.chemosphere.2022.135134 [doi]
PST - ppublish
SO  - Chemosphere. 2022 Sep;303(Pt 3):135134. doi: 10.1016/j.chemosphere.2022.135134. 
      Epub 2022 May 26.