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Article

Urinary Levels of 4-Nonylphenol and 4-t-Octylphenol in a Representative Sample of the Korean Adult Population

1
Department of International Medical Management, Daegu Catholic University, Gyeongsan 38430, Korea
2
College of Pharmacy, Keimyung University, Daegu 42601, Korea
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2017, 14(8), 932; https://doi.org/10.3390/ijerph14080932
Submission received: 19 July 2017 / Revised: 11 August 2017 / Accepted: 16 August 2017 / Published: 18 August 2017
(This article belongs to the Section Environmental Health)

Abstract

:
4-Nonylphenol (4-NP) and 4-t-octylphenol (4-t-OP) are xenoestrogen compounds to which humans are exposed via contaminated food, water, and air. This study assessed the body burden of 4-NP and 4-t-OP in Koreans aged 18–69 years using data from the Korean National Human Biomonitoring Survey conducted in 2009. Based on data from 1865 representative Koreans, 83.2% and 91.8% had urinary 4-NP and 4-t-OP concentrations >0.05 ng/mL (limit of detection). Of the Korean adult population, the geometric mean urinary concentrations of 4-NP and 4-t-OP were 3.70 ng/mL (95% confidence interval (CI) = 3.20–4.27) and 0.60 ng/mL (95% CI = 0.55–0.66), respectively. Urine 4-NP concentrations were significantly associated with place of residence and smoking status, whereas urine 4-t-OP concentrations were not correlated with any of the demographic factors. These findings suggest that most Koreans have detectable levels of 4-NP and 4-t-OP in their urine and that the body burden of 4-NP, but not 4-t-OP, varies according to some demographic factors.

1. Introduction

Humans are potentially exposed to a wide range of toxic chemicals present in commonly used products and in environmental media. Human biomonitoring surveys of these chemicals are important for determining the mean exposure level of a population, describing geographical differences, identifying high-risk groups, and assessing health risks in a population [1]. Therefore, several countries, including the United States (U.S.) and Germany, have conducted nationally representative biomonitoring surveys that have included analyses of phenolic compounds. Among the phenolic compounds to which humans are most commonly exposed are 4-nonylphenol (4-NP) and 4-t-octylphenol (4-t-OP), human-made alkyl phenols [2,3].
As 4-NP and 4-t-OP are intermediates in the production of alkylphenol ethoxylates (APEs), the manufacture and biodegradation of APEs have been demonstrated to be an important source of 4-NP and 4-t-OP environmental contamination [4]. Because 4-NP and 4-t-OP are widespread environmental contaminants found in wastewater, potable water, rivers, and biota [5,6,7], the general public can be exposed to these chemicals through drinking water, contaminated foods, air inhalation, and dermal absorption [8,9]. As estrogen-mimetic compounds, exposure to 4-NP or 4-t-OP can affect the endocrine system by interacting with estrogen receptors and disrupting normal signaling pathways [10]. Several studies have reported that exposure to these chemicals results in reproductive and developmental toxicity in humans. Exposure to 4-NP induces male infertility by exerting a negative impact on spermatogenesis and sperm quality [11], while maternal urinary concentrations of 4-t-OP are reportedly significantly associated with neonatal size at birth [12].
South Korea conducted a human biomonitoring survey for hazardous materials, which included urinary concentrations of 4-NP and 4-t-OP, among a representative sample of Korean adults aged 18–69 years. Previous biomonitoring studies of phenolic compounds have shown that urinary chemical levels vary significantly according to the population studied, reflecting differences in exposure levels depending on geographical location [13,14]. Furthermore, epidemiological studies have revealed many contributing factors to the body burdens of phenolic compounds, including age, household income, and cigarette smoking [14,15]. Therefore, in this study, we used Korean national survey data to examine urinary 4-NP and 4-t-OP concentrations in Korean adults and to elucidate the demographic characteristics that potentially influence these concentrations.

2. Methods

2.1. Study Population

The participants for this study were selected from the Korean National Human Biomonitoring Survey (KNHBS). The KNHBS was a population-based, cross-sectional survey representing the adult population (18–69 years of age) residing in the Republic of Korea. We excluded participants with very low or very high urinary creatinine concentrations (<30 mg/dL or >300 mg/dL), because these are defined by the WHO as too dilute or too concentrated for adequate analysis [16]. A total of 1865 subjects completed interviews without missing data, provided urine samples, and were included in the analyses. This study was supervised by the Korean Food and Drug Administration, and the study protocol was approved by the Asan Medical Center Institutional Review Board (IRB approval # 2009-0369). The study was conducted in accordance with the ethical principles for medical research involving human subjects as defined by the Declaration of Helsinki. Study participants provided written, informed consent.

2.2. Data Collection

Data about participants’ sex, age, education, income, cigarette smoking, and current residence were collected during face-to-face interviews. Education was categorized as less than a high school diploma, high school diploma, and college or higher. Income was classified into four groups based on monthly household income. Cigarette smoking status was defined as never, former, or current. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m2). Then, the participants were divided into four groups: underweight (BMI < 18.5 kg/m2), normal weight (BMI = 18.5–22.9 kg/m2), overweight (BMI = 23.0–25.0 kg/m2), or obese (BMI ≥25.0 kg/m2) according to the World Health Organization’s classification system for Asian populations [17]. Spot urine samples were collected at different times throughout the day, and creatinine adjustments were used to correct for urine dilution. The urine samples were analyzed at the Korean Institute of Science and Technology (Seoul, Korea) using liquid-liquid extraction and gas chromatography-mass spectrometry [18]. In brief, the urine samples were thawed at room temperature and vortex-mixed. After gentle mixing, the samples were added to 50 μL of glucuronidase/arylsulfatase solution (in 0.2 M sodium acetate buffer, pH 5.2), and hydrolysis was allowed to proceed at 55 °C for 3 h. After cooling to room temperature, the samples were added to a 5% K2CO3 solution and extracted with methyl tert-butyl ether. The dried extracts were derivatized with 50 μL of a bis-(trimethylsilyl) trifluoroacetamide/trimethylchlorosilane (100:1, v/v) mixture at 60 °C for 30 min. The samples were analyzed with mass-selective detectors (models 6890 Gas Chromatograph and 5975; Agilent Technologies, Palo Alto, CA, USA) connected to an Ultra-2 column (25 m × 0.2 mm internal diameter, 0.33-μm film thickness; Agilent Technologies). As reference materials, 4-NP and 4-t-OP were obtained from Sigma-Aldrich (Steinheim, Germany), with a purity of >99%. Recovery was assessed by adding known amounts of the standards, and was in the range of 83.5–111.1% for 4-NP and 89.5–102.8% for 4-t-OP. The intra- and interday accuracy and precision were examined by analyzing the four analytes in seven replicates during a single day and on five consecutive days. The intraday accuracy for 4-NP was 95.0–109.5% with a precision of 5.3–14.6%, whereas its interday accuracy was 98.7–103.4% with a precision of 3.0–6.3%. The intraday accuracy of 4-t-OP was 88.0–103.0% with a precision of 6.0–10.1%, whereas its interday accuracy was 96.3–101.1% with a precision of 3.3–6.1%. Linearity in these analytes was checked from 0.1 (limit of quantification (LOQ)) to 200 ng/mL, with correlation coefficients of 0.9971 and 1.0000 for 4-NP and 4-t-OP, respectively. The limit of detection (LOD) and the LOQ for each analyte under the chromatographic conditions were determined at signal-to-noise ratios of 3 and 10, respectively. The LOD and LOQ were 0.05 ng/mL and 0.20 ng/mL, respectively, for 4-NP and 0.05 ng/mL and 0.10 ng/mL, respectively, for 4-t-OP. Individuals whose urinary concentration fell below the LOD were assigned a value of LOD/2 [19]. Creatinine levels were measured by means of a kinetic Jaffé method using a Hitachi 7600 auto-analyzer (Hitachi, Tokyo, Japan).

2.3. Statistical Analyses

We used selected percentile and maximum values to describe the distributions of 4-NP and 4-t-OP levels. We also calculated geometric means with 95% confidence intervals (CIs) for urinary 4-NP and 4-t-OP concentrations by taking the antilog of the mean of the natural log-transformed values. Sample weights were applied to adjust for the differential selection probabilities of selected participants to calculate weighted geometric means. We fitted multiple linear regressions of the log-transformed concentrations with the weights for the predictor variables. The exponentiated model coefficients represent proportional changes in the arithmetic mean associated with each level of the predictor relative to a referent level, adjusting for the other predictors in the model. The difference between the two demographic subgroups in mean values and the presence of a linear trend among subgroups were evaluated by a survey t-test and by defining a linear contrast in each of the general linear models, respectively. All statistical analyses were conducted using SAS 9.4 computer software (SAS Institute, Cary, NC, USA).

3. Results

A total of 1865 eligible subjects participated in the study, yielding a participation rate of 87.1%. The mean age of the subjects was 45.5 years, and 57.0% of the participants were female (Table 1).
Selected percentiles of 4-NP levels in the participants’ urine samples are presented in Table 2; 83.2% of sample values were above the LOD and ranged between 0.05 ng/mL (LOD) and 4477.0 ng/mL. Urinary 4-NP concentration was not clearly associated with sex. However, the 4-NP concentrations of participants aged 40–49 years were lower than those of other age groups at most percentile points.
Table 3 shows the selected percentiles of 4-t-OP levels in the participants’ urine samples by sex and age. 4-t-OP was detected above the LOD (0.05 ng/mL) in 1713 of the 1865 (91.8%) participants, with total concentrations ranging from 0.05 ng/mL (LOD) to 988.7 ng/mL. Similar to 4-NP, the 4-t-OP concentration was not obviously associated with sex. Although there were apparent decreases in the 4-t-OP levels of participants aged 50–59 years compared with other age groups at most of the percentiles, the creatinine-adjusted 4-t-OP concentrations of this age group were not significantly different from those of participants in other age groups at most percentile points.
The population-weighted geometric mean urinary 4-NP concentration in Korean adults aged 18–69 years was 3.70 ng/mL (95% CI = 3.20–4.27; Table 4). Among demographic characteristics, geometric mean urinary 4-NP concentrations were significantly correlated with place of residence; subjects living in urban areas had higher urinary 4-NP concentrations than those living in rural areas (p = 0.005). After adjusting for potential covariates, the adjusted proportional changes in mean 4-NP levels still changed significantly with place of residence (p = 0.020). In addition, compared with never smokers, current smokers showed an adjusted proportional change of 1.73 (95% CI = 1.08–2.76). However, geometric means and adjusted proportional changes in 4-NP levels were not significantly correlated with other demographic variables such as sex, age, BMI, educational level, or income.
The population-weighted geometric mean urinary concentration for 4-t-OP was 0.60 ng/mL (95% CI = 0.55–0.66) (Table 5). The analysis of geometric means and adjusted proportional changes in 4-t-OP levels according to demographic factors showed that sex, age, BMI, education level, income, cigarette smoking, and place of residence were not significantly associated with urinary 4-t-OP levels.

4. Discussion

Our results revealed that the geometric mean of the urinary 4-NP level for Korean adults was 3.70 ng/mL. The US National Health and Nutrition Examination Survey (NHANES) III reported that the geometric mean of urinary 4-NP level was below the LOD (0.1 ng/mL) for the US adult population [20]. On the other hand, several studies conducted in Taiwan showed that the geometric mean of urinary 4-NP concentration was 2.90–4.10 ng/mL for Taiwanese pregnant women with a mean age range of 31.0–33.4 years [21,22,23,24]. Given that 4-NP levels do not significantly differ by sex, the geometric mean of urinary 4-NP concentration in the Korean population is assumed to be similar to that in the Taiwanese population and much higher than that in the U.S. population.
The geometric mean of the urinary 4-t-OP level for Korean adults was 0.60 ng/mL, which is higher than that in the U.S. population. The 2003–2004 NHANES reported a urinary geometric mean 4-t-OP concentration of 0.3 ng/mL for the U.S. population aged 6 years and over [13]. A possible factor influencing the difference is that our study had a lower LOD (0.05 ng/mL) and higher percentage greater than the LOD (91.8%) than did the NHANES study (LOD = 0.2 ng/mL, percentage greater than the LOD, 57.4%), which would yield more precise percentiles and geometric means compared with studies with a higher LOD. Other studies have reported that the geometric mean 4-t-OP concentrations in the urine of Chinese men and women were 0.60 ng/mL and 0.90 ng/mL, respectively [12,25], which is similar to those of the Korean general population shown in this study.
4-NP and 4-t-OP are still used and are commonly detected in environmental media in Asian countries, including Korea, Taiwan, and China, whereas the U.S. has initiated a phase-out of these chemicals [26,27,28]. Therefore, the difference in body burden of 4-NP and 4-t-OP between U.S. and Asian populations may be attributed to a difference in exposure levels. Because a single spot-urine sample per participant was analyzed, within-person variability in urinary concentrations over time may be a limitation of this study. However, estimation of mean population levels based on one spot sample per participant is considered to be a useful approach in cross-sectional studies [13].
Lifestyle factors, including smoking and place of residence, are related to urinary concentrations of some phenolic compounds [29,30,31,32,33], although the biological basis of these associations needs to be elucidated. In this study, subjects living in urban regions had higher urinary 4-NP concentrations than those living in rural regions, and adjusted proportional changes showed that cigarette smoking was significantly associated with increased urinary 4-NP levels. These results indicate that place of residence and smoking emerged as important factors influencing urinary concentrations of 4-NP, which suggests the possibility of variations in exposure to 4-NP based on place of residence and smoking status.
The strength of this study is that it is the first study to assess the body burdens of 4-NP and 4-t-OP and their association with demographic characteristics among Korean adults using nationally representative data. Another strength of this study is that we used sample weights to obtain the urinary 4-NP and 4-t-OP levels in the Korean population, which may have led to more precise estimates of nationally representative values for adult Koreans. However, these findings highlight the need for additional research to identify pathways of human exposure and to evaluate the potential effects of exposure to these chemicals on health.

5. Conclusions

Using nationally representative data, we found that a considerable portion of the Korean general population aged 18–69 years has urinary levels of 4-NP and 4-t-OP above 0.05 ng/mL. The geometric mean urinary levels of 4-NP and 4-t-OP were 3.70 ng/mL (95% CI = 3.20–4.27) and 0.60 ng/mL (95% CI = 0.55–0.66), respectively. Among the sociodemographic characteristics studied, place of residence and cigarette smoking were significant factors of the urinary 4-NP concentration. These findings suggest the need for policies to evaluate the potential health effects on high-risk groups and to reduce human exposure to 4-NP and 4-t-OP.

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. NRF-2015R1D1A1A01056617, NRF-2016R1A2B4011596).

Author Contributions

Hyejin Park contributed to data analysis and interpretation, statistical analysis, and drafting the manuscript. Kisok Kim contributed to design of the study, critical revision of the manuscript, and supervision of the study. All authors have read and approved the final manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Draper, W.M. Biological monitoring: Exquisite research probes, risk assessment, and routine exposure measurement. Anal. Chem. 2001, 73, 2745–2760. [Google Scholar] [CrossRef] [PubMed]
  2. Van Miller, J.P.; Staples, C.A. Review of the potential environmental and human health-related hazards and risks from long-term exposure to p-tert-octylphenol. Hum. Ecol. Risk Assess. 2005, 11, 319–351. [Google Scholar] [CrossRef]
  3. Vazquez-Duhalt, R.; Marquez-Rocha, F.; Ponce, E.; Licea, A.F.; Viana, M.T. Nonyphenol, an integrated vision of a pollutant. Appl. Ecol. Environ. Res. 2005, 4, 1–25. [Google Scholar] [CrossRef]
  4. David, A.; Fenet, H.; Gomez, E. Alkylphenols in marine environments: Distribution monitoring strategies and detection considerations. Mar. Pollut. Bull. 2009, 58, 953–960. [Google Scholar] [CrossRef] [PubMed]
  5. Hawker, D.W.; Cumming, J.L.; Neale, P.A.; Bartkow, M.E.; Escher, B.I. A screening level fate model of organic contaminants from advanced water treatment in a potable water supply reservoir. Water Res. 2011, 45, 768–780. [Google Scholar] [CrossRef] [PubMed]
  6. Gatidou, G.; Vassalou, E.; Thomaidis, N.S. Bioconcentration of selected endocrine disrupting compounds in the Mediterranean mussel, Mytilus galloprovincialis. Mar. Pollut. Bull. 2010, 60, 2111–2116. [Google Scholar] [CrossRef] [PubMed]
  7. Stasinakis, A.S.; Gatidou, G.; Mamais, D.; Thomaidis, N.S.; Lekkas, T.D. Occurrence and fate of endocrine disrupters in Greek sewage treatment plants. Water Res. 2008, 42, 1796–1804. [Google Scholar] [CrossRef] [PubMed]
  8. Ahel, M.; McEvoy, J.; Giger, W. Bioaccumulation of the lipophilic metabolites of nonionic surfactants in freshwater organisms. Environ. Pollut. 1993, 79, 243–248. [Google Scholar] [CrossRef]
  9. Clark, L.B.; Rosen, R.T.; Hartman, T.G.; Louis, J.B.; Suffet, I.; Lippincott, R.; Rosen, J.D. Determination of alkylphenol ethoxylates and their acetic acid derivatives in drinking water by particle beam liquid chromatography/mass spectrometry. Int. J. Environ. Anal. Chem. 1992, 47, 167–180. [Google Scholar] [CrossRef]
  10. Laws, S.C.; Carey, S.A.; Ferrell, J.M.; Bodman, G.J.; Cooper, R.L. Estrogenicactivity of octylphenol, nonylphenol, bisphenol A and methoxychlor in rats. Toxicol. Sci. 2000, 54, 154–167. [Google Scholar] [CrossRef] [PubMed]
  11. Noorimotlagh, Z.; Haghighi, N.J.; Ahmadimoghadam, M.; Rahim, F. An updated systematic review on the possible effect of nonylphenol on male fertility. Environ. Sci. Pollut. Res. Int. 2017, 24, 3298–3314. [Google Scholar] [CrossRef] [PubMed]
  12. Lv, S.; Wu, C.; Lu, D.; Qi, X.; Xu, H.; Guo, J.; Liang, W.; Chang, X.; Wang, G.; Zhou, Z. Birth outcome measures and prenatal exposure to 4-tert-octylphenol. Environ. Pollut. 2016, 212, 65–70. [Google Scholar] [CrossRef] [PubMed]
  13. Calafat, A.M.; Ye, X.; Wong, L.Y.; Reidy, J.A.; Needham, L.L. Exposure of the U.S. population to bisphenol A and 4-tertiary-octylphenol: 2003–2004. Environ. Health Perspect. 2008, 116, 39–44. [Google Scholar] [CrossRef] [PubMed]
  14. Kim, K.; Park, H.; Yang, W.; Lee, J.H. Urinary concentrations of bisphenol A and triclosan and associations with demographic factors in the Korean population. Environ. Res. 2011, 111, 1280–1285. [Google Scholar] [CrossRef] [PubMed]
  15. Calafat, A.M.; Ye, X.; Wong, L.Y.; Reidy, J.A.; Needham, L.L. Urinary concentrations of triclosan in the U.S. population: 2003–2004. Environ. Health Perspect. 2008, 116, 303–307. [Google Scholar] [CrossRef] [PubMed]
  16. Barr, D.B.; Wilder, L.C.; Caudill, S.P.; Gonzalez, A.J.; Needham, L.L.; Pirkle, J.L. Urinary creatinine concentrations in the U.S. population: implications for urinary biologic monitoring measurements. Environ. Health Perspect. 2005, 113, 192–200. [Google Scholar] [CrossRef] [PubMed]
  17. World Health Organization. The Asian-Pacific Perspective: Redefining Obesity and Its Treatment. Available online: http://www.wpro.who.int/nutrition/documents/docs/Redefiningobesity.pdf (accessed on 5 May 2017).
  18. Kim, K.; Park, H.; Lee, J.H. Urinary concentrations of trichlorophenols in the Korean adult population: Results of the National Human Biomonitoring Survey 2009. Environ. Sci. Pollut. Res. Int. 2014, 21, 2479–2485. [Google Scholar] [CrossRef] [PubMed]
  19. Cole, S.R.; Chu, H.; Nie, L.; Schisterman, E.F. Estimating the odds ratio when exposure has a limit of detection. Int. J. Epidemiol. 2009, 38, 1674–1680. [Google Scholar] [CrossRef] [PubMed]
  20. Calafat, A.M.; Kuklenyik, Z.; Reidy, J.A.; Caudill, S.P.; Ekong, J.; Needham, L.L. Urinary concentrations of bisphenol A and 4-nonylphenol in a human reference population. Environ. Health Perspect. 2005, 113, 391–395. [Google Scholar] [CrossRef] [PubMed]
  21. Huang, Y.F.; Pan, W.C.; Tsai, Y.A.; Chang, C.H.; Chen, P.J.; Shao, Y.S.; Tsai, M.S.; Hou, J.W.; Lu, C.A.; Chen, M.L. Concurrent exposures to nonylphenol, bisphenol A, phthalates, and organophosphate pesticides on birth outcomes: A cohort study in Taipei, Taiwan. Sci. Total Environ. 2017, 607–608, 1126–1135. [Google Scholar] [CrossRef] [PubMed]
  22. Tsai, M.S.; Chang, C.H.; Tsai, Y.A.; Liao, K.W.; Mao, I.F.; Wang, T.H.; Hwang, S.M.; Chang, Y.J.; Chen, M.L. Neonatal outcomes of intrauterine nonylphenol exposure—A longitudinal cohort study in Taiwan. Sci. Total Environ. 2013, 458–460, 367–373. [Google Scholar] [CrossRef] [PubMed]
  23. Wang, P.W.; Chen, M.L.; Huang, L.W.; Yang, W.; Wu, K.Y.; Huang, Y.F. Nonylphenol exposure is associated with oxidative and nitrative stress in pregnant women. Free Radic. Res. 2015, 49, 1469–1478. [Google Scholar] [CrossRef] [PubMed]
  24. Wang, P.W.; Chen, M.L.; Huang, L.W.; Yang, W.; Wu, K.Y.; Huang, Y.F. Prenatal nonylphenol exposure, oxidative and nitrative stress, and birth outcomes: A cohort study in Taiwan. Environ. Pollut. 2015, 207, 145–151. [Google Scholar] [CrossRef] [PubMed]
  25. Qin, Y.; Chen, M.; Wu, W.; Xu, B.; Tang, R.; Chen, X.; Du, G.; Lu, C.; Meeker, J.D.; Zhou, Z.; et al. Interactions between urinary 4-tert-octylphenol levels and metabolism enzyme gene variants on idiopathic male infertility. PLoS ONE 2013, 8, e59398. [Google Scholar] [CrossRef] [PubMed]
  26. Li, X.; Ying, G.G.; Zhao, J.L.; Chen, Z.F.; Lai, H.J.; Su, H.C. 4-Nonylphenol, bisphenol-A and triclosan levels in human urine of children and students in China, and the effects of drinking these bottled materials on the levels. Environ. Int. 2013, 52, 81–86. [Google Scholar] [CrossRef] [PubMed]
  27. Asimakopoulos, A.G.; Thomaidis, N.S.; Koupparis, M.A. Recent trends in biomonitoring of bisphenol A, 4-t-octylphenol, and 4-nonylphenol. Toxicol. Lett. 2012, 210, 141–154. [Google Scholar] [CrossRef] [PubMed]
  28. Yu, C.J.; Du, J.C.; Chiou, H.C.; Yang, S.H.; Liao, K.W.; Yang, W.; Chung, M.Y.; Chien, L.C.; Hwang, B.; Chen, M.L. Attention deficit/hyperactivity disorder and urinary nonylphenol levels: A case-control study in Taiwanese children. PLoS ONE 2016, 11, e0149558. [Google Scholar] [CrossRef] [PubMed]
  29. Schettgen, T.; Alt, A.; Dewes, P.; Kraus, T. Simple and sensitive GC/MS-method for the quantification of urinary phenol, o- and m-cresol and ethylphenols as biomarkers of exposure to industrial solvents. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 2015, 995–996, 93–100. [Google Scholar] [CrossRef] [PubMed]
  30. Arbuckle, T.E.; Marro, L.; Davis, K.; Fisher, M.; Ayotte, P.; Bélanger, P.; Dumas, P.; LeBlanc, A.; Bérubé, R.; Gaudreau, É.; et al. Exposure to free and conjugated forms of bisphenol A and triclosan among pregnant women in the MIREC cohort. Environ. Health Perspect. 2015, 123, 277–284. [Google Scholar] [CrossRef] [PubMed]
  31. Geens, T.; Bruckers, L.; Covaci, A.; Schoeters, G.; Fierens, T.; Sioen, I.; Vanermen, G.; Baeyens, W.; Morrens, B.; Loots, I.; et al. Determinants of bisphenol A and phthalate metabolites in urine of Flemish adolescents. Environ. Res. 2014, 134, 110–117. [Google Scholar] [CrossRef] [PubMed]
  32. Engel, L.S.; Buckley, J.P.; Yang, G.; Liao, L.M.; Satagopan, J.; Calafat, A.M.; Matthews, C.E.; Cai, Q.; Ji, B.T.; Cai, H.; et al. Predictors and variability of repeat measurements of urinary phenols and parabens in a cohort of Shanghai women and men. Environ. Health Perspect. 2014, 122, 733–740. [Google Scholar] [CrossRef] [PubMed]
  33. Larsson, K.; Ljung Björklund, K.; Palm, B.; Wennberg, M.; Kaj, L.; Lindh, C.H.; Jönsson, B.A.; Berglund, M. Exposure determinants of phthalates, parabens, bisphenol A and triclosan in Swedish mothers and their children. Environ. Int. 2014, 73, 323–333. [Google Scholar] [CrossRef] [PubMed]
Table 1. General characteristics of study participants.
Table 1. General characteristics of study participants.
CharacteristicsN (%)
Total1865 (100.0)
Women1063 (57.0)
Age (years)
 18–29247 (13.2)
 30–39412 (22.1)
 40–49454 (24.3)
 50–59430 (23.1)
 60–69322 (17.3)
Body mass index (BMI), kg/m2
 <18.556 (3.0)
 18.5–22.9816 (43.7)
 23.0–24.9453 (24.3)
 ≥25.0540 (29.0)
Education
 <High school529 (28.4)
 High school705 (37.8)
 >High school631 (33.8)
Income, U.S. $/month
 <910399 (21.4)
 910–2729894 (47.9)
 2730–4550423 (22.7)
 >4550149 (8.0)
Cigarette smoking status
 Never1232 (66.1)
 Former228 (12.2)
 Current405 (21.7)
Place of residence
 Rural448 (24.0)
 Urban1417 (76.0)
Table 2. Selected urine concentration percentiles of 4-nonylphenol in the Korean population aged 18–69 years, by sex and age subgroups.
Table 2. Selected urine concentration percentiles of 4-nonylphenol in the Korean population aged 18–69 years, by sex and age subgroups.
VariableN% > LOD *PercentileMax
25th50th75th90th95th
All186583.21.02 (0.96)8.10 (7.5021.9 (23.0)61.7 (64.1)137.4 (145.6)4477.0 (10,435.8)
Sex
 Male80282.90.95 (0.72)7.94 (6.27)20.9 (17.0)66.3 (56.3)150.9 (132.1)781.8 (1541.9)
 Female106383.41.02 (1.08)8.19 (8.62)22.9 (28.2)58.3 (72.2)128.0 (156.5)4477.0 (10,435.8)
Age (years)
 18–2924782.60.64 (0.41)9.83 (6.62)22.7 (20.6)78.8 (61.4)182.4 (131.6)658.0 (974.8)
 30–3941283.01.79 (1.46)8.99 (8.99)24.9 (24.9)62.5 (82.4)186.0 (176.2)1039.1 (1135.7)
 40–4945482.60.35 (0.44)6.42 (6.46)17.2 (18.9)49.1 (52.2)110.0 (111.3)781.8 (1541.9)
 50–5943083.51.02 (1.08)8.19 (7.76)22.9 (25.8)60.2 (63.1)117.0 (152.6)4477.0 (10,435.8)
 60–6932284.51.10 (1.28)8.50 (8.47)23.0 (29.3)66.0 (71.1)140.0 (149.8)654.6 (944.1)
* Limit of detection (LOD) = 0.05 ng/mL; Percentile values are expressed as volume-based concentrations (ng/mL), and creatinine-adjusted concentrations (μg/g creatinine) are in parentheses.
Table 3. Selected urine concentration percentiles of 4-t-octylphenol in the Korean population aged 18–69 years, by sex and age subgroups.
Table 3. Selected urine concentration percentiles of 4-t-octylphenol in the Korean population aged 18–69 years, by sex and age subgroups.
VariableN% > LOD *PercentileMax
25th50th75th90th95th
All186591.80.17 (0.17)0.77 (0.71)1.80 (1.94)4.40 (4.86)8.00 (8.64)988.7 (645.4)
Sex
 Male80292.60.16 (0.15)0.74 (0.56)1.80 (1.39)4.10 (3.60)8.20 (6.89)356.3 (240.3)
 Female106391.30.18 (0.20)0.81 (0.87)1.90 (2.37)4.70 (5.69)7.80 (10.22)988.7 (645.4)
Age (years)
 18–2924790.70.14 (0.12)0.83 (0.60)1.70 (1.29)3.80 (3.50)7.40 (5.73)47.1 (24.3)
 30–3941291.30.19 (0.18)0.81 (0.69)1.96 (2.04)4.19 (5.31)7.61 (8.38)988.7 (645.4)
 40–4945489.90.15 (0.15)0.86 (0.84)1.91 (2.07)5.13 (5.69)9.22 (8.54)356.3 (144.6)
 50–5943093.30.13 (0.15)0.66 (0.65)1.60 (1.84)3.80 (4.05)6.50 (6.97)73.1 (104.8)
 60–6932294.40.20 (0.22)0.77 (0.76)2.04 (2.06)5.44 (6.30)9.66 (13.37)336.8 (232.7)
* LOD = 0.05 ng/mL; Percentile values are expressed as volume-based concentrations (ng/mL), and creatinine-adjusted concentrations (μg/g creatinine) are in parentheses.
Table 4. Population-weighted geometric means and adjusted proportional changes in urinary 4-nonylphenol concentrations by demographic characteristics in the Korean population aged 18–69 years.
Table 4. Population-weighted geometric means and adjusted proportional changes in urinary 4-nonylphenol concentrations by demographic characteristics in the Korean population aged 18–69 years.
Variable NGeometric Mean (95% CI), ng/mLp-Value aAdjusted Proportional Change (95% CI) bp-Value
Total 3.70 (3.20–4.27) -
Sex
 Male8023.67 (2.97–4.54)0.92530.65 (0.42–1.00)0.052
 Female10633.72 (3.06–4.53) 1.00 (reference)
Age (years)
 18–292473.50 (2.40–5.10)0.787 1.00 (reference)0.073
 30–394124.36 (3.27–5.81) 1.32 (0.82–2.11)
 40–494543.08 (2.35–4.04) 1.04 (0.64–1.70)
 50–594303.91 (2.96–5.15) 1.44 (0.83–2.49)
 60–693223.98 (2.91–5.43) 1.83 (1.00–3.33)
BMI
 <18.5563.78 (1.53–9.37)0.838 1.00 (reference)0.974
 18.5–22.98163.65 (2.93–4.56) 1.00 (0.41–2.44)
 23.0–24.94534.53 (3.39–6.05) 1.29 (0.52–3.19)
 ≥25.05403.20 (2.47–4.13) 0.91 (0.37–2.21)
Education
 <High school5293.48 (2.69–4.51)0.268 1.00 (reference)0.349
 High school7053.21 (2.53–4.07) 0.91 (0.61–1.37)
 >High school6314.24 (3.35–5.36) 1.27 (0.77–2.11)
Income (U.S. $/month)
 <9103992.64 (1.87–3.72)0.068 1.00 (reference)0.122
 910–27298943.99 (3.26–4.89) 1.53 (0.98–2.39)
 2730–45504233.65 (2.72–4.90) 1.40 (0.83–2.36)
 >45501494.84 (2.92–8.01) 1.77 (0.91–3.41)
Cigarette smoking status
 Never12323.34 (2.79–4.00)0.136 1.00 (reference)0.023
 Former2284.25 (2.99–6.03) 1.61 (0.99–2.63)
 Current4054.39 (3.21–5.99) 1.73 (1.08–2.76)
Place of residence
 Rural4482.49 (1.85–3.35)0.005 0.66 (0.47–0.93)0.020
 Urban14174.03 (3.42–4.75) 1.00 (reference)
a p determined by survey t-test or linear trend test; b The exponentiated β-coefficient from a log-linear multiple regression that included all covariates in the table and urinary creatinine concentration.
Table 5. Population-weighted geometric means and adjusted proportional changes in urinary 4-t-octylphenol concentrations by demographic characteristics in the Korean population aged 18–69 years.
Table 5. Population-weighted geometric means and adjusted proportional changes in urinary 4-t-octylphenol concentrations by demographic characteristics in the Korean population aged 18–69 years.
VariableNGeometric Mean (95% CI), ng/mLp-Value aAdjusted Proportional Change (95% CI) bp-Value
Total 0.60 (0.55–0.66) -
Sex
 Male8020.57 (0.50–0.65)0.193 0.77 (0.59–1.01)0.057
 Female10630.64 (0.57–0.72) 1.00 (reference)
Age (years)
 18–292470.57 (0.45–0.72)0.551 1.00 (reference)0.189
 30–394120.63 (0.53–0.75) 1.22 (0.91–1.64)
 40–494540.63 (0.52–0.75) 1.27 (0.92–1.77)
 50–594300.52 (0.45–0.61) 1.09 (0.77–1.54)
 60–693220.69 (0.57–0.84) 1.44 (0.98–2.11)
BMI
 <18.5560.97 (0.57–1.63)0.087 1.00 (reference)0.107
 18.5–22.98160.58 (0.51–0.66) 0.63 (0.38–1.03)
 23.0–24.94530.63 (0.52–0.76) 0.67 (0.40–1.14)
 ≥25.05400.59 (0.50–0.70) 0.63 (0.37–1.06)
Education
 <High school5290.61 (0.52–0.71)0.759 1.00 (reference)0.234
 High school7050.57 (0.50–0.67) 1.04 (0.80–1.35)
 >High school6310.63 (0.54–0.73) 1.22 (0.88–1.70)
Income (U.S. $/month)
 <9103990.63 (0.51–0.80)0.426 1.00 (reference)0.525
 910–27298940.60 (0.53–0.68) 0.96 (0.72–1.29)
 2730–45504230.54 (0.45–0.64) 0.85 (0.60–1.21)
 >45501490.78 (0.55–1.12) 1.21 (0.77–1.91)
Cigarette smoking status
 Never12320.61 (0.55–0.69)0.569 1.00 (reference)0.638
 Former2280.62 (0.50–0.78) 1.17 (0.86–1.60)
 Current4050.57 (0.48–0.69) 1.07 (0.80–1.44)
Place of residence
 Rural4480.70 (0.59–0.83)0.076 1.21 (0.98–1.48)0.075
 Urban14170.58 (0.53–0.65) 1.00 (reference)
a p determined by survey t-test or linear trend test; b The exponentiated β-coefficient from a log-linear multiple regression that included all covariates in the table and urinary creatinine concentration.

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MDPI and ACS Style

Park, H.; Kim, K. Urinary Levels of 4-Nonylphenol and 4-t-Octylphenol in a Representative Sample of the Korean Adult Population. Int. J. Environ. Res. Public Health 2017, 14, 932. https://doi.org/10.3390/ijerph14080932

AMA Style

Park H, Kim K. Urinary Levels of 4-Nonylphenol and 4-t-Octylphenol in a Representative Sample of the Korean Adult Population. International Journal of Environmental Research and Public Health. 2017; 14(8):932. https://doi.org/10.3390/ijerph14080932

Chicago/Turabian Style

Park, Hyejin, and Kisok Kim. 2017. "Urinary Levels of 4-Nonylphenol and 4-t-Octylphenol in a Representative Sample of the Korean Adult Population" International Journal of Environmental Research and Public Health 14, no. 8: 932. https://doi.org/10.3390/ijerph14080932

APA Style

Park, H., & Kim, K. (2017). Urinary Levels of 4-Nonylphenol and 4-t-Octylphenol in a Representative Sample of the Korean Adult Population. International Journal of Environmental Research and Public Health, 14(8), 932. https://doi.org/10.3390/ijerph14080932

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