Para-dichlorobenzene (p-DCB) products are widely used in the home and public buildings, leading to exposure to this chemical in indoor environments. In this study, we explored potential relationships between p-DCB exposure and diabetes in US adults by analyzing a nationally representative subsample of 3063 adult participants aged 20–79 years randomly selected for measurement of urinary concentrations of 2,5-dichlorophenol (2,5-DCP), the major metabolite of p-DCB, in the 2007–2010 National Health and Nutrition Examination Survey. Median urinary 2,5-DCP concentration was 7.0 μg/l (interquartile range: 2.1–29.9). Of the participants, 560 (13.6%) were diabetic. A dose-dependent increase in the prevalence of diabetes was observed in the study participants across quartiles of urinary 2,5-DCP (P-trend<0.0001). After adjusting for potential confounders, individuals in the highest quartile of urinary 2,5-DCP had an increased odds of diabetes (OR=1.59 (95% CI: 1.06, 2.40)) compared with individuals with the lowest quartile. The highest quartile of urinary 2,5-DCP was also positively associated with insulin resistance (adjusted β=0.75; 95% CI: 0.27, 1.24). This study demonstrated a potential association between exposure to p-DCB, measured as urinary concentrations of 2,5-DCP, and diabetes in US adults. Additional epidemiologic and mechanistic studies would further explore these interactions.
The prevalence of diagnosed diabetes in the United States has risen sharply since 1990 among all age groups.1 It was estimated that a total of 21.0 million children and adults in the United States had diagnosed diabetes, with 1.7 million new cases in people aged 20 years and older in 2012.2 In adults, type 2 diabetes accounts for about 90–95% of all diagnosed cases of diabetes. Multiple risk factors are known to contribute to the development of type 2 diabetes, including obesity, sedentary lifestyle, poor diet, and genetic factors. Among these known risk factors, obesity is the primary risk factor, as the increase in adipose tissue is associated with increased resistance to insulin and other metabolic syndrome. In recent years, a growing body of evidence from epidemiologic and experimental studies has suggested roles of environmental chemicals, the so called “obesogens”, in the development of obesity and diabetes.3, 4, 5, 6, 7, 8, 9 Certain types of environmental chemicals, such as organochlorine pesticides, phthalate plasticizers, and phenolic compounds, are endocrine-disrupting agents that could alter metabolic processes and predispose some people to gain weight.5, 7, 8
The environmental chemical of our particular concern is para-dichlorobenzene (p-DCB), found in indoor environments. p-DCB that has been used in moth balls, some air fresheners, toilet-deodorizer blocks, and previously, as a fumigant insecticide, is highly volatile, and was detected in the air of households, restrooms, and new buildings.10, 11 People could be exposed to this compound by breathing vapors from products used in the home or in buildings on a daily basis. Exposure to p-DCB is usually measured as urinary concentrations of 2,5-dichlorophenol (2,5-DCP), the major metabolite of p-DCB.12, 13 Urinary 2,5-DCP was reported to be suitable as an index for monitoring low-level exposure of p-DCB in the general population.14 Owing to the widespread exposure to p-DCB in humans, 2,5-DCP was detected in urine of 98.5% of the study participants, aged 6 years and above, in the 2007–2010 U.S. National Health and Nutrition Examination Survey (NHANES). In our recent studies by analyzing the 2005–2008 NHANES data, we found a significant and dose-dependent association between urinary concentrations of 2,5-DCP and obesity in children and adolescents as well as in adults after adjustment for urine creatinine and potential confounders.15, 16 Our finding was supported by a study in which only urinary concentrations of 2,5-DCP, among several endocrine-disrupting chemicals examined, was found to be associated with earlier age of menarche in the US female participants of 12–16 years of age.17
In this study, we explored relationships between exposure to p-DCB, measured as urinary concentrations of 2,5-DCP, and diabetes in US adults by analyzing the 2007–2010 NHANES data. Type 2 diabetes is characterized by insulin resistance. The association between urinary 2,5-DCP and insulin resistance was also evaluated. In addition, the study examined whether differences in urinary 2,5-DCP concentrations exist among individuals with various demographic and social or behavioral characteristics. This study would contribute to the prevention of obesity and diabetes by providing more scientific evidence on potential roles of environmental chemical exposure in metabolic risks, and thus reducing environmental exposures, especially during sensitive windows of development.
Data Source and Study Population
NHANES is an ongoing survey of a nationally representative sample of the non-institutionalized US civilian population conducted by the National Center for Health Statistics of CDC. Data from the NHANES were obtained online.18 To obtain survey estimates with greater precision, the adjacent two data collection cycles of 2007–2008 and 2009–2010 were combined to create the analytical data file for this study. Data from different components of the NHANES, including questionnaire, laboratory, dietary, and physical examination, were used in the study. Participants are selected using a complex multistage probability sampling design. The NHANES obtained informed consent from all participants.
Measurement of Urinary Concentrations of 2,5-DCP
Urinary concentrations of 2,5-DCP were used to determine the level of exposure to p-DCB. 2,5-DCP was measured in a random one-third subsample of the NHANES participants. Spot urine samples were collected from study participants and stored at −20 °C until analysis. The urine samples were measured for chlorophenols by solid phase extraction coupled on-line to high-performance liquid chromatography and tandem mass spectrometry. Details on the sample collection and analyses are shown in the document published by CDC.19 We evaluated outliers by their sampling weight20 and excluded those values that were substantially outside of range (>99th percentile; n=35). For urinary 2,5-DCP concentrations below the limit of detection (1.5% of participants), the value of 0.14 μg/l was assigned in the NHANES. The urinary concentrations of 2,5-DCP were categorized into quartiles, with the lowest quartile used as the reference group.
Both diagnosed and undiagnosed diabetic individuals were identified in the study. Participants who met any of the following criteria were classified as having diabetes: (i) participants who responded “yes” to the question “Other than during pregnancy, have you ever been told by a doctor or health professional that you have diabetes or sugar diabetes?”; (ii) participants who responded “yes” to the question “Are you now taking diabetic pills to lower your blood sugar?”; (iii) participants who responded “yes” to the question “Are you now taking insulin?”; (iv) fasting blood glucose is ≥126 mg/dl; (v) 2-h glucose tolerance test is ≥200 mg/dl; (vi) hemoglobin A1c is ≥6.5%.21
As type II diabetes is charaterized by insulin resistance, we conducted a secondary analysis for the association of urinary 2,5-DCP with insulin resistance in the study participants. The homeostatic model assessment (HOMA) is a method for assessing insulin resistance (IR) and beta-cell function from fasting glucose and insulin concentrations. The HOMA-IR was calculated as blood glucose (mmol/l) × insulin level (μIU/ml)/22.5 for each participant in the study.
We considered the age, gender, race/ethnicity, poverty status, education, cigarette smoking, alcohol consumption, physical activity, total caloric, and total fat intake of the participants as potential confounders. Age was categorized as 20–29, 30–39, 40–49, 50–59, 60–69, and 70–79 years. Race/ethnicity was categoriaed as non-Hispanic white, non-Hispanic black, Hispanic (Mexican American and other Hispanic), and Other (Asian and other, including multi-racial). Education was categorized as less than high school and high school graduate or higher. Poverty status was classified as family income to poverty ratio<1 versus≥1. Physical activity was categorized as self-reported moderate or vigorous physical recreational activity versus none. Total caloric intake and total fat intake for 24 h was grouped into quartiles. For cigarette smoking, participants were classified as never, current, or past smokers, based on the questioniare data. Alcohol consumption was classified into “yes” or “no” based on the question “In any one year, have you had at least 12 alcohol drinks?”.
Statistical analyses were performed using SAS 9.3 software (SAS Institute Inc., Cary, NC, USA). As the population was selected using a complex probability sample procedure, sample weights were incorporated into the analysis to get proper estimates and confidence intervals of estimates. The Cochran–Armitage trend test was performed to evaluate whether there was a linear trend in the prevalence of diabetes in adults across increasing levels of 2,5-DCP. A multivariate logistic regression was conducted to evaluate the association between urinary 2,5-DCP and diabetes. Three regression models were constructed in the study. To control for urine dilution in spot urine samples, all models were adjusted for urine creatinine as a covariate. Model 1 was adjusted for urine creatinine only; Model 2 adjusted for urine creatinine and demographic variables (age, gender, race/ethnicity, education, and poverty status); Model 3 adjusted for model two variables, and behavioral variables (total caloric intake, total fat intake, physical activity, cigarette smoking, and alcohol consumption). Given the highly skewed distribution of HOMA-IR values, we conducted median regression analysis (quantreg) to explore the relationship between urinary levels of 2,5-DCP and HOMA-IR. For this secondary analysis, sample weights were not used. Results were considered statistically significant at α level of 0.05 and all statitical tests were two-sided.
Analysis for Specificity of Association
We also examined associations of urinary concentrations of another dichlorophenol compound, 2,4-dichlorophenol (2,4-DCP), that is chemically similar to 2,5-DCP, with diabetes in the logistic regression models. 2,4-DCP is used primarily as an intermediate in the manufacturing of the herbicide 2,4-dichlorophenoxyacetic acid. 2,4-DCP was detected in urine of 89.7% of the 2007–2010 NHANES participants. The value of 0.14 μg/l was assigned to those whose urinary 2,4-DCP was below the limit of detection (10.3% of participants). Analyses for 2,4-DCP were conducted using multivariate logistic regression models as described in the section of Statistical Analysis for 2,5-DCP.
During the study period of 2007–2010, a total of 3465 adult participants aged 20–79 years had available data on both diabetes and 2,5-DCP. After excluding women who were pregnant (n=40), and participants with missing covariates included in our models (n=362), a total of 3063 participants were included in the analyses. The median level of urinary 2,5-DCP was 7.0 μg/l (range: 0.14–3700; interquartile range: 2.1–29.9). Of the participants, 560 (13.6%) were diabetic.
Table 1 presents descriptive analyses of urinary concentrations of 2,5-DCP (weighted geometric means (95% CI)) by demographic and behavioral variables, as well as the primary study outcome. Geometric means of urinary concentations of 2,5-DCP differed by gender, race/ethnicity, poverty status, and educational level, with statistically significantly higher concentrations in male adults, in non-Hispanic black and Hispanic, and in the individuals living below poverty and with an education level of less than high school. In particular, much higher concentrations of urinary 2,5-DCP were found in non-Hispanic black (geometric mean, 22.20 μg/l; 95% CI: 18.92, 26.05) and Hispanic (14.59 μg/l; 95% CI: 12.55, 16.78), compared with non-Hispanic white (4.81 μg/l; 95% CI: 4.39, 5.31). Participants who did moderate or vigorous physical activity had significantly lower concentrations of urinary 2,5-DCP as compared with the ones who did not. No statistically significant differences in urinary concentrations of 2,5-DCP were seen among different age groups, with different smoking status and alcohol consumption, and among quartiles of total caloric or total fat intake. As expected, diabetic adults had a significantly higher geometric mean of urinary concentrations of 2,5-DCP (9.87 μg/l; 95% CI: 7.92, 12.43), compared with that in non-diabetic adults (6.30 μg/l; 95% CI: 5.75, 6.82).
A higher prevalence of diabetes was found in the study participants who had higher urinary concentrations of 2,5-DCP in a dose-dependent manner (Table 2). The weighted prevalence of diabetes in Q1 was 11.0%, in Q2 was 12.7%, in Q3 was 14.5%, and in Q4 was 17.8%. A linear trend in the prevalence of diabetes in adults across increasing levels of urinary 2,5-DCP was revealed by the trend test (P<0.0001).
We examined the relation between urinary quartiles of 2,5-DCP and diabetes by logistic regression analyses in three models (Table 3). A dose-dependent association with diabetes was observed across quartiles of urinary 2,5-DCP in all three models. Statistically significant crude associations (model 1, adjusted for urine creatinine only) were found in the third and fourth quartiles of 2,5-DCP with a 1.55 (95% CI: 1.05, 2.29) and 2.00 (95% CI: 1.37, 2.93) increased odds of diabetes, respectively. After adjusting for potential confounders, the highest quartile of urinary 2,5-DCP was significantly associated with diabetes with a 1.65 (95% CI: 1.09, 2.49) increased odds of diabetes in model 2 (adjusted for urine creatinine, age, gender, race/ethnicity, poverty status, and education) and a 1.59 (95% CI: 1.06, 2.40) increased odds of diabetes in model 3 (additionally adjusted for total caloric and total fat intake, physical activity, cigarette smoking, and alcohol consumption). When the analysis was done with urinary 2,5-DCP concentrations (log-transformed) as continuous variable, statistically significant associations with diabetes were also seen in all three models. The odds ratio was 1.15 (95% CI: 1.08, 1.22) in model 1 (adjusting for urine creatinine only), 1.11 (95% CI: 1.03, 1.19) in model 2 (adjusting for urine creatinine and demographic variables), and 1.10 (95% CI: 1.03, 1.18) after additionally adjusting for behavioral variables (model 3).
To address the specificity of the association between urinary 2,5-DCP and diabetes, we conducted logistic regression analyses for 2,4-DCP, a reference compound that is excreted from urine and chemically similar to 2,5-DCP (Table 3). A statistically significant association was only seen for the fourth quartile of 2,4-DCP in crude regression model (model 1) with a crude OR of 1.78 (95% CI: 1.22, 2.60). No statistically significant associations with diabetes were found after adjusting for demographic variables (model 2) or for demographic and behavioral variables (model 3). The adjusted OR for the fourth quartile of 2,4-DCP was 1.37 (95% CI: 0.92, 2.05) and 1.35 (95% CI: 0.90, 2.03) for model 2 and model 3, respectively.
The descriptive statistical analysis showed that the median value of HOMA-IR was 2.7, with a range of 0.20–113.21, among adult participants (n=1402) (excluding 1661 missing data on blood glucose or insulin values from the total sample size of 3063). Median regression analyses were conducted to estimate the relation between urinary 2,5-DCP and insulin resistence, presented as regression coefficient β. Urinary 2,5-DCP showed an increasing monotonic association with HOMA-IR in all three models (Table 4). Participants with higher urinary levels of 2,5-DCP had higher median HOMA-IR levels. The highest quartile of urinary 2,5-DCP had a significantly higher median level of HOMA-IR in all models as compared with participants in the lowest quartile, with an adjusted β of 0.75 (95% CI: 0.27, 1.24) after adjusting for urine creatinine and demographic and behavioral variables.
Finally, we conducted sensitivity analyses with two additional sets of data. The first set of data excluded participants with 2,5-DCP outliers and with 2,5-DCP below the limit of detection (n=3008); and the second set included all of the study participants with 2,5-DCP data (including 2,5-DCP outliers and 2,5-DCP below the limit of detection; n=3088). Statistically significant associations with diabetes were also seen in the fourth quartile of 2,5-DCP after adjusting for covariates in the analyses of these two additional sets of data (results not shown), as it was seen in the analysis of the original set of data.
This study explored relationships between p-DCB exposure and diabetes in US adults by analyzing the 2007–2010 NHANES data. To our knowledege, it is the first report characterizing a potential role of exposure to p-DCB in diabetes. We found that urinary concentrations of 2,5-DCP were significantly associated with diabetes and insulin resistence in the study population, after adjustment for urine creatinine and potential confounders. Obesity has been identified as the major risk factor for type 2 diabetes. The results of this study were consistent with our earlier findings on the association between urinary 2,5-DCP and obesity.15, 16
The development of diabetes is the interaction between genetic predisposition and the environment. Exposure to environmental chemicals is widespread, and many of these chemicals are considered endocrine-disrupting agents that can damage the body’s natural weight-control mechanisms at much lower levels of exposure. Recent reports have shown that obesogens could stimulate adipogenesis in vitro and in vivo by activating peroxisome proliferator-activated receptor gamma (PPARγ),22, 23 a key regulator of obesity. Different obesogenic compounds may have different mechanisms of actions. Limited information is available on the metabolic effect of p-DCB. Up to date, p-DCB has been found to possess estrogenic activity in vitro and in vivo24 and alter thyroid gland functions in rats,25, 26 which might link p-DCB exposure to the development of diabetes. The mechanisms underlying the effect of p-DCB on obesity and diabetes remain to be discovered.
The wide use of p-DCB products in the home and public buildings leads to potential high exposure to this chemical in indoor environments.27, 28 The distribution of indoor concentrations of p-DCB was large and highly skewed.27 Our study shows a wide range of urinary levels of 2,5-DCP (0.14–3700 μg/l) among the NHANES participants with a right-skewed distribution. This could be largely due to significant variations in indoor concentrations of p-DCB in homes and public buildings. Individuals’ susceptibility to p-DCB metabolism and excretion would also be taken into account. Interestingly, we found that significantly higher geometric means of urinary concentrations of 2,5-DCP occur in males, in racial groups of non-Hispanic black and Hispanic, and in participants with lower levels of education and family income, suggesting that biological mechanisms and social or behavioral factors are related to the exposure. Social and behavioral factors might significantly contribute to p-DCB exposure, which is supported by the study conducted by Chin et al.27 in which p-DCB concentrations in indoors was found differed among households and the cities studied. In accordance with our findings, Ye et al.29 found that household income and race/ethnicity were significant predictors of urinary concentrations of DCP above the 95th percentile. Furthermore, our study shows that the geometric mean of urinary concentrations of 2,5-DCP in US adult participants (20–79 years of age, n=3063) was much higher than that in the German population (18–69 years of age, n=692), based on the 1998 German Environmental Survey.30
The NHANES is a national survey to assess the health and nutritional status of adults and children in the United States with a cross-sectional design. Owing to the nature of a cross-sectional study, a causal relationship cannot be made between exposure to p-DCB and diabetes in adults. The lack of information on the etiology of the interaction between p-DCB and diabetes prevents inference on causality. We cannot rule out the possibility of reverse causality in this study. Obese and diabetic individuals might have physiological characteristics that could lead to higher urinary levels of pesticides. To explore this, we analyzed 2,4-DCP that is chemically similar to 2,5-DCP and the results showed that the association with diabetes was only seen in urinary 2,5-DCP, but not in 2,4-DCP, which indicates that the observed association is less likely to be a reverse causality and supports our hypothesis that exposure to p-DCB, measured as urinary 2,5-DCP, could lead to metabolic disorders and diabetes. However, prospective epidemiological studies measuring exposure during etiologically relevant periods are needed to prove this causal relationship.
In the NHANES, only one urine sample was collected from each survey participant at different times of the day. To control for urine dilution in spot urine samples for a better assessment of exposure, we analyzed the association between urinary 2,5-DCP and diabetes adjusting for urinary creatinine as an independent variable in the regression models, as it was recommended by Barr et al.31 Although urinary levels of 2,5-DCP reflect recent exposure, the measurement could represent long-term exposure because the p-DCB-containing products, such as room and toilet deodorizers, are widely and frequently used in households and people can be exposed by inhaling contaminated air in indoor environments on a daily basis. Studies showed urinary levels of compounds measured at one time point to be fairly predictive of levels measured over time.17, 32 However, this type of measurement would likely lead to misclassifications of exposure. Further studies should examine multiple urine samples taken over time to better assess long-term exposure to p-DCB.
Additionally, self-reported diabetes may be subjected to report bias, which might be related to participants’ education and socioeconomic status, and other factors. Type of diabetes was not differentiated between type 1 and type 2 diabetes; however, we believe most (90–95%) of the cases had type 2 diabetes.33 Type 2 diabetes is characterized by insulin resistance. Our study also examined the association between urinary 2,5-DCP and HOMA-IR and found that the highest quartile of urinary 2,5-DCP was significantly associated with both diabetes and insulin resistance.
Despite the limitations of this study, there are a number of strengths. First, we explored the association between urinary concentrations of 2,5-DCP and diabetes in a large study population consisting of representative sample of US adults who participated in the NHANES over a 4-year period. Second, we were able to control for a number of potential confounders, including demographic, dietary, and behavioral factors. Third, as approximately 30% of diabetes was undiagnosed,2, 34 we included both diagnosed and undiagnosed diabetes in the study. Fourth, we examined the association between urinary 2,5-DCP and HOMA-IR, which provided more evidence on the association with type 2 diabetes.
In conclusion, our findings suggest a potential association between exposure to p-DCB, measured as urinary concentrations of 2,5-DCP, and diabetes in adults. Additional epidemiologic and mechanistic studies would further explore these interactions. Significant variations in the levels of p-DCB exposure among individuals or households indicate that social and behavioral factors play an important role in the patterns of using this chemical, suggesting the need for policies and actions to reduce exposures.
CDC. Number (in millions) of civilian, noninstitutionalized persons with diagnosed diabetes, United States, 1980-2011 http://www.cdc.gov/diabetes/statistics/prev/national/figpersons.htm. Accessed September 25, 2013.
American Diabetes Association. Statistics about diabetes http://www.diabetes.org/diabetes-basics/statistics/. Accessed July 20, 2014.
Baillie-Hamilton PF . Chemical toxins: A hypothesis to explain the global obesity epidemic. J Altern Complement Med 2002; 8: 185–192.
Heindel JJ, vom Saal FS . Role of nutrition and environmental endocrine disrupting chemicals during the perinatal period on the aetiology of obesity. Mol Cell Endocrinol 2009; 304: 90–96.
Holtcamp W . Obesogens: an environmental link to obesity. Environ Health Perspect 2012; 120: A62–A68.
McClafferty H . Interactions between environmental health and pediatric obesity. Explore 2008; 4: 328–332.
La Merrill M, Birnbaum LS . Childhood obesity and environmental chemicals. Mt Sinai J Med 2011; 78: 22–48.
Thayer KA, Heindel JJ, Bucher JR, Gallo MA . Role of environmental chemicals in diabetes and obesity: a National Toxicology Program Workshop Review. Environ Health Perspect 2012; 120: 779–789.
Trasande L, Attina TM, Blustein J . Association between urinary bisphenol A concentration and obesity prevalence in children and adolescents. JAMA 2012; 308: 1113–1121.
Brown SK, Sim MR, Abramson MJ, Gray CN . Concentrations of volatile organic compounds in indoor air: a review. Indoor Air 1994; 4: 123–134.
Saijo Y, Kishi R, Sata F, Katakura Y, Urashima Y, Hatakeyama A et al. Symptoms in relation to chemicals and dampness in newly built dwellings. Int Arch Occup Environ Health 2004; 77: 461–470.
Hill RH, Ashley DL, Head SL, Needham LL, Pirkle JL . P-dichlorobenzene exposure among 1000 adults in the United States. Arch Environ Health 1995; 50: 277–280.
Hill RH, Head SL, Baker S, Gregg M, Shealy DB, Bailey SL et al. Pesticide residues in urine of adults living in the United States: reference range concentrations. Environ Res 1995; 71: 99–108.
Yoshida T, Andoh K, Fukuhara M . Urinary 2,5-dichlorophenol as biological index for p-dichlorobenzene exposure in the general population. Arch Environ Contam Toxicol 2002; 43: 481–485.
Twum C, Wei Y . The association between urinary concentrations of dichlorophenol pesticides and obesity in children. Rev Environ Health 2011; 26: 215–219.
Wei Y, Zhu J, Nguyen A . Urinary concentrations of dichlorophenol pesticides and obesity among adult participants in the U.S. National Health and Nutrition Examination Survey (NHANES) 2005-2008. Int J Hyg Environ Health 2014; 217: 294–299.
Buttke DE, Sircar K, Martin C . Exposures to endocrine-disrupting chemicals and age of menarche in adolescent girls in NHANES (2003-2008). Environ Health Perspect 2012; 120: 1613–1618.
CDC. National Health and Nutrition Examination Survey http://www.cdc.gov/nchs/nhanes/nhanes_questionnaires.htm. Accessed March 28, 2014.
CDC. Laboratory Procedure Manual. Method No: 6301.01. 2010 http://www.cdc.gov/nchs/nhanes/nhanes2009-2010/lab_methods_09_10.htm. Accessed August 15, 2014.
CDC. Task 3a: How to identify outliers and evaluate their impact using SAS http://www.cdc.gov/nchs/tutorials/nhanes/Preparing/CleanRecode/Task3.htm. Accessed September 5, 2014.
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Diagnosis of diabetes and prediabetes http://diabetes.niddk.nih.gov/dm/pubs/diagnosis/. Accessed September 25, 2013.
Janesick A, Blumberg B . Minireview: PPARγ as the target of obesogens. J Steroid Biochem Mol Biol 2011; 127: 4–8.
Riu A, Grimaldi M, le Maire A, Bey G, Phillips K, Boulahtouf A et al. Peroxisome proliferator-activated receptor γ is a target for halogenated analogs of bisphenol A. Environ Health Perspect 2011; 119: 1227–1232.
Versonnen BJ, Arijs K, Verslycke T, Lema W, Janssen CR . In vitro and in vivo estrogenicity and toxicity of o-, m-, and p-dichlorobenzene. Environ Toxicol Chem 2003; 22: 329–335.
Elcombe CR, Odum J, Foster JR, Stone S, Hasmall S, Soames AR et al. Prediction of rodent nongenotoxic carcinogenesis: evaluation of biochemical and tissue changes in rodents following exposure to nine nongenotoxic NTP carcinogens. Environ Health Perspect 2002; 110: 363–375.
National Toxicology Program. NTP toxicology and carcinogenesis studies of 1,4-dichlorobenzene (CAS No. 106-46-7) in F344/N rats and B6C3F1 mice (gavage studies). Natl Toxicol Program Tech Rep Ser 1987; 319: 1–198.
Chin J-Y, Godwin C, Jia C, Robins T, Lewis T, Parker E et al. Concentrations and risks of p-dichlorobenzene in indoor and outdoor air. Indoor Air 2013; 23: 40–49.
Guerrero PA, Corsi RL . Emissions of p-dichlorobenzene and naphthalene from consumer products. J Air Waste Manag Assoc 2012; 62: 1075–1084.
Ye X, Wong L-Y, Zhou X, Calafat AM . Urinary concentrations of 2,4-dichlorophenol and 2,5-dichlorophenol in the U.S. population (National Health and Nutrition Examination Survey, 2003-2010): trends and predictors. Environ Health Perspect 2014; 122: 351–355.
Becker K, Schulz C, Kaus S, Seiwert M, Seifert B . German Environmental Survey 1998 (GerES III): environmental pollutants in the urine of the German population. Int J Hyg Environ Health 2003; 206: 15–24.
Barr DB, Wilder LC, Caudill SP, Genzalez AJ, Needham LL, Pirkle JL et al. Urinary creatinine concentrations in the U.S. population: implications for urinary biologic monitoring measurements. Environ Health Perspect 2005; 113: 192–200.
Hoppin JA, Brock JW, Davis BJ, Baird DD . Reproducibility of urinary phthalate metabolites in first morning urine samples. Environ Health Perspect 2002; 110: 515–518.
Harris MI . Classification, diagnosis criteria, and screening for diabetes. In: Diabetes in America. Publication No. 95-1468. National Institute of Diabetes and Digestive and Kidney Diseases: Bethesda, MD. 1995, 15–36.
Danaei G, Friedman AB, Oza S, Murray CJ, Ezzati M . Diabetes prevalence and diagnosis in US states: analysis of health surveys. Popul Health Metr 2009; 7: 16.
The authors declare no conflict of interest.
About this article
Cite this article
Wei, Y., Zhu, J. Urinary concentrations of 2,5-dichlorophenol and diabetes in US adults. J Expo Sci Environ Epidemiol 26, 329–333 (2016). https://doi.org/10.1038/jes.2015.19
- insulin resistance
- urinary 2,5-dichlorophenol
Associations between urinary concentrations of 2,5-dichlorophenol and metabolic syndrome among non-diabetic adults
Environmental Science and Pollution Research (2016)