PMID- 30557812
OWN - NLM
STAT- MEDLINE
DCOM- 20190612
LR  - 20190613
IS  - 1873-6750 (Electronic)
IS  - 0160-4120 (Linking)
VI  - 123
DP  - 2019 Feb
TI  - Association between exposure to a mixture of phenols, pesticides, and phthalates 
      and obesity: Comparison of three statistical models.
PG  - 325-336
LID - S0160-4120(18)31673-8 [pii]
LID - 10.1016/j.envint.2018.11.076 [doi]
AB  - BACKGROUND: The evaluation of the chemical impact on human health is usually 
      constrained to the analysis of the health effects of exposure to a single 
      chemical or a group of similar chemicals at one time. The effects of chemical 
      mixtures are seldom analyzed. In this study, we applied three statistical models 
      to assess the association between the exposure to a mixture of seven xenobiotics 
      (three phthalate metabolites, two phenols, and two pesticides) and obesity. 
      METHODS: Urinary levels of environmental phenols, pesticides, and phthalate 
      metabolites were measured in adults who participated in the U.S.-based National 
      Health and Nutrition Examination Survey (NHANES) from 2013 to 2014. Body 
      examination was conducted to determine obesity. We fitted multivariable models, 
      using generalized linear (here both logistic and linear) regression, weighted 
      quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) 
      models to estimate the association between chemical exposures and obesity. 
      RESULTS: Of 1269 individuals included in our final analysis, 38.5% had general 
      obesity and 58.0% had abdominal obesity. In the logistic regression model 
      established for each single chemical, bisphenol S (BPS), mono (carboxyoctyl) 
      phthalate (MCOP), and mono (2-ethyl-5-carboxypentyl) phthalate (MECPP) were 
      associated with both general and abdominal obesity (fourth vs. first quartile). 
      In linear regression, MCOP was associated with BMI and waist circumference. In 
      WQS regression analysis, the WQS index was significantly associated with both 
      general obesity (OR = 1.63, 95% CI: 1.21-2.20) and abdominal obesity (OR = 1.66, 
      95% CI: 1.18-2.34). MCOP, bisphenol A (BPA), bisphenol S (BPS), and mono ethyl 
      phthalate (MEP) were the most heavily weighing chemicals. In BKMR analysis, the 
      overall effect of mixture was significantly associated with general obesity when 
      all the chemicals were at their 60th percentile or above it, compared to all of 
      them at their 50th percentile. MCOP, BPA, and BPS showed positive trends. By 
      contrast, MECPP showed a flat and modest inverse trend. CONCLUSION: When 
      comparing results from these three models, MCOP, BPA, and BPS were identified as 
      the most important factors associated with obesity. We recommend estimating the 
      joint effects of chemical mixtures by applying diverse statistical methods and 
      interpreting their results together, considering their advantages and 
      disadvantages.
CI  - Copyright (c) 2019 Elsevier Ltd. All rights reserved.
FAU - Zhang, Yuqing
AU  - Zhang Y
AD  - State Key Laboratory of Reproductive Medicine, Center for Global Health, School 
      of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key 
      Laboratory of Modern Toxicology of Ministry of Education, School of Public 
      Health, Nanjing Medical University, Nanjing 211166, China.
FAU - Dong, Tianyu
AU  - Dong T
AD  - State Key Laboratory of Reproductive Medicine, Center for Global Health, School 
      of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key 
      Laboratory of Modern Toxicology of Ministry of Education, School of Public 
      Health, Nanjing Medical University, Nanjing 211166, China.
FAU - Hu, Weiyue
AU  - Hu W
AD  - State Key Laboratory of Reproductive Medicine, Center for Global Health, School 
      of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key 
      Laboratory of Modern Toxicology of Ministry of Education, School of Public 
      Health, Nanjing Medical University, Nanjing 211166, China.
FAU - Wang, Xu
AU  - Wang X
AD  - State Key Laboratory of Reproductive Medicine, Center for Global Health, School 
      of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key 
      Laboratory of Modern Toxicology of Ministry of Education, School of Public 
      Health, Nanjing Medical University, Nanjing 211166, China.
FAU - Xu, Bo
AU  - Xu B
AD  - State Key Laboratory of Reproductive Medicine, Center for Global Health, School 
      of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key 
      Laboratory of Modern Toxicology of Ministry of Education, School of Public 
      Health, Nanjing Medical University, Nanjing 211166, China.
FAU - Lin, Zhongning
AU  - Lin Z
AD  - State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School 
      of Public Health, Xiamen University, Xiamen, China.
FAU - Hofer, Tim
AU  - Hofer T
AD  - Department of Toxicology and Risk Assessment, Norwegian Institute of Public 
      Health, 0456 Oslo, Norway.
FAU - Stefanoff, Pawel
AU  - Stefanoff P
AD  - Department of Zoonotic, Food- and Waterborne Infections, Norwegian Institute of 
      Public Health, 0456 Oslo, Norway.
FAU - Chen, Ying
AU  - Chen Y
AD  - Wuxi Maternal and Child Health Hospital, Nanjing Medical University, Wuxi 214002, 
      China.
FAU - Wang, Xinru
AU  - Wang X
AD  - State Key Laboratory of Reproductive Medicine, Center for Global Health, School 
      of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key 
      Laboratory of Modern Toxicology of Ministry of Education, School of Public 
      Health, Nanjing Medical University, Nanjing 211166, China.
FAU - Xia, Yankai
AU  - Xia Y
AD  - State Key Laboratory of Reproductive Medicine, Center for Global Health, School 
      of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key 
      Laboratory of Modern Toxicology of Ministry of Education, School of Public 
      Health, Nanjing Medical University, Nanjing 211166, China. Electronic address: 
      yankaixia@njmu.edu.cn.
LA  - eng
PT  - Comparative Study
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20181214
PL  - Netherlands
TA  - Environ Int
JT  - Environment international
JID - 7807270
RN  - 0 (Environmental Pollutants)
RN  - 0 (Pesticides)
RN  - 0 (Phenols)
RN  - 0 (Phthalic Acids)
RN  - 0 (Sulfones)
RN  - 80-09-1 (bis(4-hydroxyphenyl)sulfone)
SB  - IM
MH  - Adult
MH  - Bayes Theorem
MH  - Environmental Exposure
MH  - Environmental Pollutants/analysis/*toxicity/urine
MH  - Female
MH  - Humans
MH  - Linear Models
MH  - Logistic Models
MH  - Male
MH  - *Models, Statistical
MH  - Nutrition Surveys
MH  - Obesity/*etiology/urine
MH  - Pesticides/analysis/*toxicity
MH  - Phenols/*toxicity/urine
MH  - Phthalic Acids/*toxicity/urine
MH  - Sulfones
MH  - Waist Circumference
OTO - NOTNLM
OT  - Bayesian kernel machine regression (BKMR)
OT  - Chemical mixture
OT  - Obesity
OT  - Obesogen
OT  - Weighted quantile sum (WQS) regression
EDAT- 2018/12/18 06:00
MHDA- 2019/06/14 06:00
CRDT- 2018/12/18 06:00
PHST- 2018/07/31 00:00 [received]
PHST- 2018/11/29 00:00 [revised]
PHST- 2018/11/29 00:00 [accepted]
PHST- 2018/12/18 06:00 [pubmed]
PHST- 2019/06/14 06:00 [medline]
PHST- 2018/12/18 06:00 [entrez]
AID - S0160-4120(18)31673-8 [pii]
AID - 10.1016/j.envint.2018.11.076 [doi]
PST - ppublish
SO  - Environ Int. 2019 Feb;123:325-336. doi: 10.1016/j.envint.2018.11.076. Epub 2018 
      Dec 14.