Annals of Occupational and Environmental Medicine

Research Article

Association between urinary phthalate metabolites and obesity in adult Korean population: Korean National Environmental Health Survey (KoNEHS), 2012–2014: Yangwon Kang, Juha Park, Kanwoo Youn; Ann Occup Environ Med 2019;31:e23. Published online September 9, 2019; DOI: https://doi.org/10.35371/aoem.2019.31.e23

Background

Phthalate is a chemical that is commonly used as a plasticizer in processing plastic products and as a solvent in personal care products. Although previous experimental studies have reported that phthalate metabolites are associated with obesity, epidemiological study results have been inconsistent and insufficient. The objective of the present study was to investigate the association between urinary phthalate metabolites and obesity in adult Korean population.

Methods

The present study selected 4,752 Korean adults aged 19 years or older from the 2012–2014 Korean National Environmental Health Survey data. The concentrations of urinary di-(2-ethyl-5-carboxypentyl) phthalate (DEHP) metabolites—i.e., mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP) and mono-(2-ethyl-5-carboxypentyl) phthalate—mono-benzyl phthalate (MBzP) and mono-n-butyl phthalate (MnBP) were adjusted using the urinary creatinine. We used logistic regression analysis to investigate the association between urinary phthalate metabolite concentration and body mass index (BMI) with respect to sex and age.

Results

Among women, urinary MEHHP and DEHP concentrations were found to have statistically significantly positive associations with obesity (Q4 versus Q1; odds ratio (OR): 1.72, 95% confidence interval (CI): 1.19–2.49 for MEHHP and OR: 1.52, 95% CI: 1.04–2.21 for DEHP). Among men, urinary MnBP concentration was found to have statistically significantly negative association with obesity (Q4 versus Q1; OR: 0.71, 95% CI: 0.50–0.99). In the analysis stratified by sex and age, women aged ≥ 50 years showed statistically significantly positive associations between the concentrations of urinary DEHP metabolites, DEHP, MBzP, and obesity (Q4 versus Q1; OR: 1.94, 95% CI: 1.28–2.94 for MEHHP, OR: 1.88, 95% CI: 1.21–2.94 for MEOHP, OR: 2.04, 95% CI: 1.31–3.18 for DEHP, and Q3 versus Q1; OR: 1.45, 95% CI: 1.02–2.05 for MBzP). Meanwhile, men aged ≥ 50 years showed no significant associations between urinary phthalate concentrations and obesity.

Conclusions

In the present study, we found differences in the associations between urinary phthalate metabolites and BMI according to sex and age. However, because the present study was cross-sectional in nature, additional support through prospective studies is needed to estimate the causal associations.

Citations

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Melissa Mariana, Miguel Castelo-Branco, Amadeu M. Soares, Elisa Cairrao
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Research Article

Pesticide metabolite and oxidative stress in male farmers exposed to pesticide: Kang Myoung Lee, Sang-Yoo Park, Kyungsuk Lee, Sung-Soo Oh, Sang Baek Ko; Ann Occup Environ Med 2017;29:5. Published online February 28, 2017; DOI: https://doi.org/10.1186/s40557-017-0162-3

Abstract PDF PubReader ePub

Background

The objective of this study was to measure malondialdehyde (MDA) and isoprostane which has been used as an index of lipid injury, 8-hydroxy-2′-deoxyguanosine (8-OHdG), which has been used as an index of DNA damage, and dialkyl-phosphate (DAP), which has been used to quantify pesticide exposure, and to investigate the relationship between pesticide exposure and oxidative stress.

Methods

This study was a cross-sectional study that evaluated 84 male farmers exposure to pesticide. In this study, 8-OHdG, isoprostane, and MDA were measured as oxidative stress indices, and dialkyl-phosphate (dimethylphosphate(DMP), diethylphosphate(DEP), dimethylthiophosphate(DMTP), and diethylthiophosphate (DETP)) excreted in the urine was also measured to evaluate pesticide exposure. A linear regression analysis was performed to investigate the relationship between pesticide metabolites, and oxidative stress biomarkers.

Results

A Correlation analysis was performed for pesticide exposure month (PEI), cumulative exposure index (CEI), and DAP as well as the concentration of the oxidative stress biomarkers. The PEM significantly and positively correlated to the levels of 8-OHdG, isoprostane, CEI, and DMP. CEI showed a correlation to 8-OHdG and PEM. DMP, DEP, and DETP showed a positive correlation to 8-OHdG, isoprostane, and MDA. A correlation analysis was adjusted some demographic characteristics, such as age, smoking, drinking, and exercise to determine the relationship between pesticide exposure and oxidative stress. The 8-OHdG, isoprostane, and MDA levels were significantly related to the DMP (ß = 0.320), DEP (ß = 0.390), and DETP (ß = 0.082); DMP (ß = 0.396), DEP (ß = 0.508), and DETP (ß = 0.504); and DMP (ß = 0.432), DEP (ß = 0.508), and DETP (ß = 0.329) levels, respectively.

Conclusions

The concentration between oxidative stress biomarkers and the pesticide metabolite were a positive correlation. Indicators of oxidative stress was associated with a pesticide metabolite DMP, DEP, and DETP. Therefore, Pesticide exposure and oxidative stress were relevant.

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Research Article

Assessment of Arsenic Exposure by Measurement of Urinary Speciated Inorganic Arsenic Metabolites in Workers in a Semiconductor Manufacturing Plant: Kiwhan Byun, Yong Lim Won, Yang In Hwang, Dong-Hee Koh, Hosub Im, Eun-A Kim; Ann Occup Environ Med 2013;25:21-21. Published online October 11, 2013; DOI: https://doi.org/10.1186/2052-4374-25-21

Abstract PDF PubReader ePub

Objectives

The purpose of this study was to evaluate the exposure to arsenic in preventive maintenance (PM) engineers in a semiconductor industry by detecting speciated inorganic arsenic metabolites in the urine.

Methods

The exposed group included 8 PM engineers from the clean process area and 13 PM engineers from the ion implantation process area; the non-exposed group consisted of 14 office workers from another company who were not occupationally exposed to arsenic. A spot urine specimen was collected from each participant for the detection and measurement of speciated inorganic arsenic metabolites. Metabolites were separated by high performance liquid chromatography-inductively coupled plasma spectrometry-mass spectrometry.

Results

Urinary arsenic metabolite concentrations were 1.73 g/L, 0.76 g/L, 3.45 g/L, 43.65 g/L, and 51.32 g/L for trivalent arsenic (As³⁺), pentavalent arsenic (As⁵⁺), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), and total inorganic arsenic metabolites (As³⁺ + As⁵⁺ + MMA + DMA), respectively, in clean process PM engineers. In ion implantation process PM engineers, the concentrations were 1.74 g/L, 0.39 g/L, 3.08 g/L, 23.17 g/L, 28.92 g/L for As³⁺, As⁵⁺, MMA, DMA, and total inorganic arsenic metabolites, respectively. Levels of urinary As³⁺, As⁵⁺, MMA, and total inorganic arsenic metabolites in clean process PM engineers were significantly higher than that in the non-exposed group. Urinary As³⁺ and As⁵⁺ levels in ion implantation process PM engineers were significantly higher than that in non-exposed group.

Conclusion

Levels of urinary arsenic metabolites in PM engineers from the clean process and ion implantation process areas were higher than that in office workers. For a complete assessment of arsenic exposure in the semiconductor industry, further studies are needed.

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Original Article

The Association among Exposure of Bisphenol A, Genetic Polymorphism of Metabolic Enzyme and Urinary Metabolite: Sang Baek Koh, Jun Ho Park, Su Song Yun, Sung Su Oh, Sei Jin Chang, Sun Haeng Choi, Bong Suk Cha; Korean Journal of Occupational and Environmental Medicine 2008;20(2):112-118. Published online June 30, 2008; DOI: https://doi.org/10.35371/kjoem.2008.20.2.112

Abstract PDF

OBJECTIVES
To examine bisphenol A (BPA) exposure with subjects in the manufacturing industry and to determine its correlation with metabolites according to genetic polymorphism of metabolic enzymes.
METHODS
The study subjects comprised 104 workers in the manufacturing industry, 64 and 40 in the exposed and control groups, respectively. The questionnaire variablesincluded age, use of protective equipment, smoking habit and alcohol intake. Their urine samples were collected in the afternoon and urinary BPA concentration was measured by revising with the urinary creatinine concentration. The genetic polymorphism of the metabolic enzymes was examined by using restriction fragment length polymorphism (RFLP) after extracting DNA from leucocytes.
RESULTS
The minimum and maximum BPA level of the exposed group during working time was 34.22 and 221.20 ng/mg, respectively. The urinary BPA concentration was significantly higher in the exposed groups than in the control group. There was no significant difference in the urinary BPA level according to genetic polymorphism of CYP1A1 and CYP2E1, but UGT1A6 showed a significant difference. In multiple regression analysis on the urinary and airborne BPA levels, UGT1A6, use of protective equipments and workplaces were significant variables.
CONCLUSIONS
The urinary BPA concentration was affected by the levels to which workers were exposed during their working time and was considered to be metabolized by UGT1A6.

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Filling gaps between exposure modeling and the analysis of urinary biomarkers using personal air monitoring: An intervention study of permethrin used in home insecticide spray
Seon‐Kyung Park, Heon‐Jun Lee, Eugene Song, Yerin Jung, Hyun Jung Yoo, Jeong‐Eun Oh, Hyeong‐Moo Shin, Jung‐Hwan Kwon
Indoor Air.2022;[Epub] CrossRef
Study Design, Rationale and Procedures for Human Biomonitoring of Hazardous Chemicals from Foods and Cooking in Korea
Seokwon Lee, Ryoung Me Ahn, Jae Hyoun Kim, Yoon-Deok Han, Jin Heon Lee, Bu-Soon Son, Kyoungho Lee
International Journal of Environmental Research and Public Health.2019; 16(14): 2583. CrossRef

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