Urinary phenols and parabens and diabetes among US adults, NHANES 2005-2014

Journal Pre-proof Urinary phenols and parabens and diabetes among US adults, NHANES 2005-2014 Julia B. Ward, PhD, MPH, Sarah S. Casagrande, PhD, Catherine C. Cowie, PhD, MPH PII:

S0939-4753(20)30021-1

DOI:

https://doi.org/10.1016/j.numecd.2020.01.005

Reference:

NUMECD 2210

To appear in:

Nutrition, Metabolism and Cardiovascular Diseases

Received Date: 14 June 2019 Revised Date:

11 December 2019

Accepted Date: 4 January 2020

Please cite this article as: Ward JB, Casagrande SS, Cowie CC, Urinary phenols and parabens and diabetes among US adults, NHANES 2005-2014, Nutrition, Metabolism and Cardiovascular Diseases, https://doi.org/10.1016/j.numecd.2020.01.005. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

Urinary phenols and parabens and diabetes among US adults, NHANES 2005-2014 Julia B. Ward, PhD, MPH ([email protected])a,b Sarah S. Casagrande, PhD ([email protected])c Catherine C. Cowie, PhD, MPH ([email protected])d a

Social & Scientific Systems 4505 Emperor Boulevard, Suite 400 Durham, NC 27703

b

Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill 135 Dauer Drive 2101 McGavran-Greenberg Hall, CB #7435 Chapel Hill, NC 27599-7435

c

Social & Scientific Systems 8757 Georgia Avenue, 12th Floor Silver Spring, MD 20910

d

National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health 6707 Democracy Boulevard Bethesda, MD 20892

Corresponding author: Julia B. Ward Social & Scientific Systems 4505 Emperor Boulevard, Suite 400 Durham, NC 27703 [email protected] Phone: (919) 287-4327

Word Count: 3,852 Abstract: 248 Tables/figures: 4 References: 45

Keywords: phenols; triclosan; benzophenone-3; parabens; diabetes; United States

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Abbreviations BMI: body mass index BP-3: benzophenone-3 BPA: Bisphenol A CDC: Centers for Disease Control and Prevention CI: confidence interval eGFR: estimated glomerular filtration rate FPG: fasting plasma glucose HbA1c: Hemoglobin A1c LOD: limit of detection NHANES: National Health and Nutrition Examination Surveys OR: odds ratios US: United States

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ABSTRACT Background and Aims: Phenols and parabens are ubiquitous and have been associated with markers of cardiovascular health. However, the literature lacks population-based studies examining the link between these endocrine disruptors and diabetes. We examined the association between paraben/phenol concentrations and diabetes among a nationally representative sample of US adults. Methods and Results: We utilized data from the 2005-2014 National Health and Nutrition Examination Surveys (N=8,498). Total urinary concentrations of BPA, triclosan, BP-3, and propyl-, butyl-, ethyl-, and methyl parabens were measured from urine specimens collected during the examination session. Diabetes status was based on self-report of a previous diagnosis or HbA1c≥6.5%. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CI) associated with the difference in log-transformed values of the 75th and 25th percentiles for each phenol/paraben, adjusting for potential confounders. The adjusted ORs (95% CI) of diabetes comparing the 75th to 25th percentiles of each paraben/phenol were 1.09 (0.961.23) for BPA, 0.84 (0.72-0.98) for triclosan, 0.69 (0.61-0.79) for BP-3, 0.71 (0.61-0.83) for propyl paraben, 0.66 (0.54-0.80) for butyl paraben, 0.60 (0.51-0.71) for ethyl paraben, and 0.79 (0.68-0.91) for methyl paraben. Conclusions: Higher concentrations of triclosan, BP-3, and propyl, butyl, ethyl, and methyl parabens were associated with lower odds of diabetes. These findings warrant further investigation into the potential mechanism behind the observed associations and the temporal direction of the associations, given that we cannot rule out reverse causation. Future studies of these endocrine disruptors may improve the understanding of their relationship with diabetes.

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Introduction Endocrine-disrupting chemicals have been shown to disturb hormonal balance and have been associated with obesity, metabolic syndrome, and type 2 diabetes[1]. Most studies have focused on Bisphenol A (BPA), an endocrine disruptor that has been linked to chronic health problems, including diabetes[1]. However, a large proportion of the United States (US) population has demonstrated measurable urinary concentrations of other endocrine-disrupting chemicals, including triclosan, benzophenone-3 (BP-3), and methyl, ethyl, propyl, and butyl parabens[2, 3], and these concentrations have remained relatively steady over the last decade[3]. Phenols and parabens can be found in a variety of commonly used consumer products including toothpaste, cosmetics, cleaning products, plastic materials, paint, food, pharmaceuticals, sunscreens, and other personal care products[2, 3]. Although the US population experiences high levels of exposure to these endocrine-disrupting phenols and parabens, few studies have examined their potential health impact. Several animal studies suggest that endocrine-disrupting chemicals may impact health by influencing thyroid hormones, estrogenic signaling, androgenic activity, and the hypothalamic pituitary axis[4]. Human studies have also shown associations between endocrine disruptors and markers of cardiovascular health that are often comorbid with diabetes. For example, triclosan and various parabens have been associated with oxidative stress and inflammation[5], and triclosan and BP-3 have been shown to influence adipogenesis[6, 7]. Triclosan and parabens have additionally been associated with body mass index (BMI), obesity, and waist circumference, although the direction of these associations has been inconsistent[8-12]. While prior studies have assessed the association between endocrine disruptors and conditions that are often comorbid with or predispose to diabetes, the literature lacks large

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population-based studies examining the association with diabetes. Given that a large proportion of the US population is exposed to endocrine disruptors, an assessment conducted in a nationally representative population is warranted. The objective of this study was to determine the association between urine concentrations of phenols and parabens (BPA, triclosan, BP-3, propyl paraben, butyl paraben, ethyl paraben, and methyl paraben) and diabetes using data from a nationally representative sample of the non-institutionalized civilian population in the US.

Methods Study population The National Health and Nutrition Examination Surveys (NHANES) is a series of crosssectional multistage, stratified probability surveys that are designed to represent the US civilian, non-institutionalized population[13]. We utilized data from 2005-2014, which were collected in 5 phases (2005-2006, 2007-2008, 2009-2010, 2011-2012, and 2013-2014). Urine samples were collected from a random nationally representative subset of approximately one third of NHANES participants[13]. Of 28,461 adults age ≥20 years who participated in the interview and examination, 8,738 were included in the urine phenols/parabens subset with no missing phenols/parabens data. We excluded pregnant women (N=240), resulting in a final sample of 8,498 participants. The Institutional Review Board of the National Center for Health Statistics of the Centers for Disease Control and Prevention (CDC) reviewed and approved the protocol for the 20052014 NHANES surveys. All participants gave written informed consent. Data collection

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Data collection for each wave consisted of a standardized interview in the participant’s home, detailed physical examination, and subsequent visit to a mobile examination center[13]. Standardized questionnaires utilized during the in-home interview collected data regarding age, race/ethnicity, sex, education, household income, smoking status, and alcohol consumption. During the visit to the mobile examination center, height and weight were measured by a trained interviewer and BMI (weight[kg]/height[m2]) was calculated. Participants provided a casual urine specimen during the examination session. The samples were shipped on dry ice to the CDC’s National Center for Environmental Health and stored at temperatures below −20°C until analyzed. The total urinary concentrations (free plus conjugated species) of BPA; triclosan; BP-3; and propyl-, butyl-, ethyl-, and methyl parabens were measured using online solid-phase extraction coupled with high-performance liquid chromatography-tandem mass spectrometry, described in detail elsewhere[14]. The limit of detection (LOD) for each phenol and paraben was calculated as 3S0, where S0 is the standard deviation as the concentration approaches zero[14]. The LODs for BP-3, ethyl paraben, and methyl paraben were 0.4, 1.0, and 1.0 ng/mL, respectively. The LODs for BPA, triclosan, propyl paraben, and butyl paraben varied by year and ranged 0.2-0.4, 1.7-2.3, 0.1-0.2, and 0.1-0.2 ng/mL, respectively. Table 1 displays the LODs, percentage below the LOD, and percentiles. Participants with values below the LOD were assigned a value equal to the LOD divided by the square root of 2, as recommended by the CDC when examining NHANES data[15]. Further, for each phenol and paraben, low-concentration and high-concentration quality control materials, prepared with pooled human urine spiked with the analytes of interest, were analyzed with standard, reagent blank, and NHANES samples.

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Diabetes was defined as self-report of a previous diagnosis of diabetes or hemoglobin A1c≥6.5% (48 mmol/mol). Hemoglobin A1c (HbA1c) was measured using 2.2 Plus Glycohemoglobin Analyzer (Tosoh Medics, Inc., San Francisco, CA) in the 2005-2006 NHANES and the HPLC Glycohemoglobin Analyzer (Tosoh Medics, Inc., San Francisco, CA) in the 2007-2014 NHANES. Although different equipment was used over time, we did not calibrate these data as the National Center for Health Statistics does not recommend calibrating HbA1c data[13]. Prediabetes was defined as HbA1c 5.7-6.4% (39-47 mmol/mol) among those without diabetes. We recognize that use of HbA1c alone to determine undiagnosed diabetes may result in underestimation of diabetes prevalence in the population. While NHANES also measured fasting plasma glucose (FPG) in a subsample of participants, the resultant loss in sample size were we to include this variable precluded our considering a broader definition of diabetes. Further, in the NHANES population strong overlap has been found in undiagnosed diabetes prevalence as defined by FPG or HbA1c, separately, mitigating concerns of extensive underestimation of undiagnosed diabetes by using HbA1c alone[16]. Statistical analysis Descriptive statistics of participant sociodemographic and health characteristics were assessed overall, by diabetes status, and by prediabetes status. As done in previous studies, we created log-transformed paraben and phenol values given the right skewness of the distribution in the NHANES population[17, 18]. For our primary analyses, we included each paraben and phenol, in separate models, as a continuous log-transformed variable. We then obtained the odds ratios (OR) and 95% confidence intervals (CI) associated with the difference in the logtransformed values of the 75th and 25th percentiles of the overall weighted sample distribution. Models were adjusted for potential confounders based on mechanisms studied in previous

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literature[19]. Initial models were adjusted for urinary creatinine, time of venipuncture, age, race/ethnicity, and sex (Model 2). Subsequent models were additionally adjusted for education, income, smoking status, and alcohol use (Model 3). An additional model was adjusted for BMI, given its strong influence on diabetes (Model 4). However, BMI may be a mediator between paraben/phenol concentration and diabetes[8, 9], thus we interpreted Model 3 as the final fully adjusted model. Correlations between the biomarkers (Table S1) were similar to those seen in previous studies[11, 20]. As done in previous studies of parabens/phenols, analyses for each paraben/phenol were conducted separately and not mutually adjusted given the potential for issues with collinearity and positivity. However, in sensitivity analyses, we included all four parabens in a single model given that they had slightly higher correlations than the other biomarkers. In additional analyses, urinary paraben/phenol concentrations were categorized in quartiles based on the weighted sample distribution. We then used logistic regression to estimate ORs and 95% CIs for diabetes comparing each quartile to the lowest quartile for each phenol/paraben, separately. For propyl paraben and butyl paraben, ~50% of the participants were under the LOD; consequently, the first quartile for these two parabens was comprised entirely of participants under the LOD. We next tested for linear trends across quartiles of urinary phenols/parabens by including the median of each quartile as a continuous variable in logistic regression models. This modeling strategy was also employed by several previous studies examining these biomarkers in the NHANES population[18, 21, 22]. We repeated all analyses with prediabetes as the outcome, excluding those with diabetes.

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To investigate whether the associations between phenols/parabens and diabetes varied by sex or BMI, we examined models including interaction terms between phenols/parabens and sex and obesity status. We additionally examined associations stratified by sex and obesity status. Finally, we carried out an additional sensitivity analysis excluding participants with a low estimated glomerular filtration rate (eGFR), defined as eGFR<60 mL/min/1.73m2, an indication of chronic kidney disease, given its link with abnormalities in paraben/phenol metabolism and excretion (N=789 excluded)[23]. All data analyses were conducted using SUDAAN (version 9.0; Research Triangle Institute, Research Triangle Park, NC) and incorporated sampling weights to account for the complex NHANES sampling design, including unequal probabilities of selection, oversampling, and nonresponse.

Results Participant characteristics Compared to those without diabetes, participants with diabetes were older and more likely to be non-Hispanic Black, to have less than a high school education, to have an annual household income <$20,000, to be a former smoker, and to have a BMI≥30 kg/m2 (Table 2). Participants with diabetes were also less likely to be current smokers and to consume alcohol. A similar pattern was found for those with prediabetes compared to those without prediabetes (Table S2). Logistic regression for the difference in the 75th and 25th percentiles of paraben/phenol Table 3 displays the multivariable adjusted ORs (95% CI) of diabetes, modeling the parabens/phenols as log-transformed continuous variables such that one unit was equivalent to

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the difference between the 75th and 25th percentiles of the paraben or phenol distribution. While the ORs for BPA suggested that higher urinary BPA concentrations were associated with increased odds of diabetes, the CIs included the null (OR: 1.09; 95% CI: 0.96-1.23). The ORs and tests for trend for triclosan, BP-3, and propyl, butyl, ethyl, and methyl parabens indicated that higher urinary concentrations of these phenols/parabens were associated with significantly decreased odds of diabetes (Model 3, Table 3). The ORs comparing the 75th to the 25th percentile ranged from 0.84 (0.72-0.98) for triclosan to 0.60 (0.51-0.71) for ethyl paraben. Adjusting for the potential mediator of BMI did attenuate to some degree almost all of the associations; however, the direction of the associations remained unchanged, and only the associations with propyl and methyl parabens became non-significant (Model 4, Table 3). Sensitivity analyses that included all four parabens in a single model attenuated the paraben results, and only ethyl paraben remained significant. Logistic regression for paraben/phenol quartiles Table 4 displays the tests for trend and multivariable adjusted ORs of diabetes, comparing each quartile of phenol/paraben concentration with the lowest quartile. The patterns observed were similar to those reported for the log-linear analysis. Higher BPA concentration was associated with increased odds of diabetes, although the CI included the null and the test for trend was non-significant (p=0.1842; Model 3, Table 4). Conversely, higher concentrations of triclosan, BP-3, and propyl, butyl, ethyl, and methyl parabens were associated with lower odds of diabetes. The ORs comparing the highest concentration quartile to the lowest quartile ranged from 0.74 (0.57-0.96) for triclosan to 0.47 (0.34-0.63) for BP-3. Thus, the results observed in this table differed from the adjusted analysis only in that BP-3 replaced ethyl paraben as having the effect estimate with the greatest magnitude. Adjusting for BMI attenuated the associations;

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however, as with the log-linear analysis, the direction and the magnitude of the associations were mostly stable, and only the association with methyl paraben became non-significant (Model 4, Table 4). The associations of parabens/phenols with prediabetes showed similar patterns to the associations with diabetes; however, the magnitude and strength of the associations were largely attenuated (Table S3). Sensitivity analyses by sex, BMI, and eGFR The analyses stratified by sex suggested that the inverse associations between concentrations of triclosan, BP-3, and propyl-, butyl-, and methyl parabens and diabetes were stronger among females than males (Table S4). However, inclusion of interaction terms between phenols/parabens and sex demonstrated that these apparent sex differences in the associations were non-significant at the P<0.05 significance level. When stratifying by obesity status, we found that the directions of the associations were similar for those with BMI<30 kg/m2 and those with BMI≥30 kg/m2 (Table S5). The associations for BP-3, triclosan, butyl paraben, ethyl paraben, and methyl paraben did appear to be stronger among those with BMI<30 vs. BMI≥30 kg/m2 and for propyl paraben stronger among those with BMI≥30 kg/m2. However, there was still a large amount of CI overlap between the obesity status strata, whereby for all of the paraben/phenol analyses, the stratum-specific estimate for at least one, if not both, of the strata were contained within the CI of the other stratum-specific estimate. Further, the interaction terms for all models, with the exception of that for methyl paraben, were non-significant. Finally, when we repeated the analyses excluding those with chronic kidney disease, the results remained unchanged (Table S6).

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Discussion This study assessed the association between urinary phenol/paraben concentrations and diabetes among the 2005-2014 NHANES population. In contrast with some previous studies, we did not observe a strong association between BPA and diabetes[1]. In particular, our findings conflict with those using data from the 2003-2004 NHANES cycle[17, 22]. However, past studies of the 2005-2006 and 2007-2008 waves had findings consistent with our study results, which also included data from these two waves[17]. Additionally, longitudinal analyses of urinary BPA and incident diabetes in the Nurses’ Health Study supported the non-significant findings in the later NHANES waves[24]. Given that urinary BPA concentrations have decreased over time among the US population, the non-significant association found in our study could be a result of lack of variability of this exposure in the more recent NHANES waves[25]. Studies of the biological mechanism underlying the influence of BPA on diabetes have primarily been conducted among animals[26]. While these studies demonstrate the estrogenic properties of BPA among rodents, it remains unclear if the findings apply to humans. Few previous studies have examined the association between parabens/phenols, other than BPA, and diabetes. One previous study of endocrine-disrupting chemicals and diabetes among 101 individuals in Saudi Arabia reported higher odds of diabetes among those with higher concentrations of these chemicals[27]. However, due to the small sample size, the confidence limits for the ORs were exceedingly wide, with confidence limit ratios reaching up to 186.0. Further, although the authors reported that endocrine-disrupting chemicals were associated with increased diabetes odds, effect estimates for methyl paraben, propyl paraben, triclosan, and BP-3

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suggested lower diabetes odds among those in higher concentration quartiles. These findings were in fact consistent with our results. There is a growing body of literature examining the association between triclosan and factors related to cardiovascular health, including BMI and waist circumference. Previous studies of the 2003-2010 NHANES demonstrated inverse associations between urinary triclosan and BMI and waist circumference[8, 9]. Our findings are consistent with these studies given the strong association between increased waist circumference, BMI, and diabetes[28]. Further, triclosan in toothpaste has been associated with improved oral health[29], and oral health may reduce risk of diabetes[30]. In addition, it has been hypothesized that triclosan may impact cardiovascular health by influencing thyroid hormones. Hypothyroidism has been shown to impact insulin resistance and thereby increase diabetes risk[31], and increased urinary triclosan concentration has been associated with increased serum levels of thyroid hormone[21]. Our analysis found that increased BP-3 concentration was associated with decreased diabetes odds. A small previous study (N=76) among children in India found no association between urinary BP-3 and obesity, a significant risk factor for diabetes[32]. However, other studies have shown an association between BP-3 and reduced body weight, possibly because the chemical structure of BP-3 is similar to that of antiobesogenic chemicals such as adiporon[18, 33-35]. Consistent with our findings, a study among pregnant women in Puerto Rico found that increased BP-3 concentration was associated with lower C-reactive protein, a measure of systemic inflammation associated with diabetes[5, 36]. The high BP-3 exposure in the US warrants further research into its association with diabetes. Our study found that increased paraben concentrations were associated with decreased diabetes odds. Consistent with our findings, several studies, including a recent study among

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2007-2014 NHANES participants, found inverse associations between butyl, ethyl, methyl, and propyl parabens and various adiposity measures that may predispose to diabetes, including obesity, BMI, and waist circumference[10-12]. Additionally, parabens may impact thyroid function which, as previously noted, may affect diabetes risk by influencing glucose transport and insulin resistance[21], although previous results have been inconsistent and limited mostly to animal models[37, 38]. Stratification by sex demonstrated that the inverse associations between triclosan and propyl, butyl, and methyl parabens and diabetes were stronger among females than among males, although inclusion of interaction terms indicated that these differences were non-significant. Nevertheless, it has been hypothesized that the potential stronger associations in women may be due to sex differences in use of products containing the various phenols/parabens[21]. Although our study can only demonstrate associations and not prove causality, if a causal link does exist between parabens/phenols and diabetes, various biological mechanisms could explain the inverse associations observed for the majority of the examined endocrine disruptors. First, phenols have demonstrated antioxidant and anti-inflammatory properties, which may have benefits for cardiovascular health[39]. Second, the antiadipogenic activity of endocrine disruptors may mediate their association with diabetes. Endocrine disruptors have been associated with lower body fat in several studies[8, 34, 35] and potentially interfere with fat development[6, 7, 33]. For example, triclosan has been shown to inhibit adipocyte differentiation of human mesenchymal stem cells[6], and BP-3 has been shown to influence paratibial fat depot size and serum leptin levels and thereby result in body weight reductions in animal models[7]. These studies may also provide insight into our finding of a stronger association between methyl paraben and diabetes among those with BMI<30 kg/m2 than among those with BMI≥30 kg/m2. If

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certain endocrine disruptors are antiobesogenic and thereby decrease the risk of diabetes development due to obesity, those who are already obese or predisposed to obesity may be immune to this benefit. Nevertheless, while there is a growing body of literature demonstrating the potential antiobesogenic properties of endocrine disruptors, the underlying mechanisms for the observed inverse association between urinary endocrine disruptor concentrations and diabetes have not been fully elucidated. Unmeasured confounding also may have influenced our results. For example, endocrine disruptor concentrations have been found to be lower in low socioeconomic categories compared to high socioeconomic categories[3], and low socioeconomic populations tend to be at greater risk for diabetes[30]. While our analyses adjusted for education and income, these variables may not fully capture the potential confounding effects of socioeconomic position. Additionally, it is worth noting that past studies demonstrating a positive association between endocrine disruptors and diabetes or oxidative stress have frequently adjusted for the potential mediator of BMI[5, 17, 22, 24]. Adjusting for the mediator of BMI has been shown in other situations to reverse the true association as a result of collider stratification bias[40]. For this reason, we chose to interpret our models prior to BMI adjustment. We did however examine the effect of BMI adjustment in our modeling, which attenuated most of the associations but did not change the direction of any association. Future analyses could utilize a formal mediation approach (e.g. decomposition methods, inverse odds ratio weighting, etc.) to evaluate the degree to which BMI may mediate the observed associations[41, 42]. It is important to note that the cross-sectional nature of NHANES data precludes a causal interpretation of our results. We utilized single spot urine samples as a proxy for past paraben/phenol exposure, however, many of these chemicals are rapidly metabolized and have

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short half-lives[43]. We therefore cannot conclude that observed paraben/phenol concentrations accurately indicate accumulation of prior exposure, nor can we rule out that diabetes diagnosis occurred before the paraben/phenol exposure. At the same time, several studies have indicated that spot urine samples of parabens/phenols reflect ongoing average exposure on a population level and that a spot urine sample can reasonably represent an individual's exposure over several months[12, 44]; however, diabetes develops over the course of many years. Consequently, our findings may be a result of reverse causality and reflect altered use patterns due to diabetes diagnosis. Individuals with diabetes may have different exposure profiles with regard to the pharmaceuticals, personal care products, and food containing the examined parabens/phenols. Future longitudinal studies measuring paraben/phenol concentrations at multiple time points will be required to disentangle the temporal direction of the observed associations. Our study had several strengths. NHANES is a large study that collects data utilizing a standardized study protocol, employs extensive quality control measures, and utilizes technicians who are trained and certified in data collection procedures. Additionally, NHANES is nationally representative, which allows our results to be generalizable to the noninstitutionalized US civilian population. However, as previously mentioned, causal interpretation of our findings is not possible given the cross-sectional nature of NHANES. Additionally, diabetes may influence paraben/phenol concentration due to impaired kidney function, which impacts excretion of urinary parabens/phenols among those with diabetes. Nevertheless, exclusion of individuals with chronic kidney disease did not alter our results. Further, NHANES does not distinguish between type 1 and type 2 diabetes. However, given that our study sample comprised a general adult population, the vast majority of people with diabetes in our analysis are likely to have type 2 diabetes[45]. To conserve sample size, our diabetes definition was also based on HbA1c values

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and self-report of previous diagnosis alone and did not include measurements of FPG or 2-hour plasma glucose. However, extensive overlap has been found in undiagnosed diabetes prevalence as defined by FPG or HbA1c, separately[16]. Our study was the first to examine the association between several endocrine disruptors and the odds of diabetes among a large-scale nationally representative US population. Our results suggested that increased urinary concentrations of triclosan, BP-3, and propyl, butyl, ethyl, and methyl parabens were associated with decreased diabetes odds. Our findings warrant further investigation into the temporal direction and mechanism behind these associations. Given the ubiquitous nature of many phenols and parabens and their continued presence in commonly used products, future studies of these endocrine disruptors may allow for a more comprehensive understanding of their relationship with diabetes.

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Acknowledgements The authors thank Laura Fang, Social & Scientific Systems, for computer programming, and Keith Rust, PhD, Westat, for assistance with the statistical analysis. Funding: This work was supported by a contract from the National Institute of Diabetes and Digestive and Kidney Diseases [GS10F0381L]. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the National Institute of Diabetes and Digestive and Kidney Diseases. Competing Interests: The authors have no conflicts of interest to disclose.

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Table 1. Means (ng/mL) and interquartile range of phenols and parabens among adults ≥20 years of age, National Health and Nutrition Examination Survey, 2005-2014* LOD Percent Mean 25th 50th 75th Standard percentile percentile percentile deviation
Table 2. Weighted means or percentages (standard error) of participant characteristics by diabetes status, National Health and Nutrition Examination Survey, 2005-2014 Overall Diabetes status (N=8,498) Yes (N=1,325) No (N=6,859) Age, years 47.4 (0.3) 59.2 (0.5) 45.8 (0.3)* Women, % 51.0 (0.6) 49.0 (2.0) 51.3 (0.7) Non-Hispanic White, % 69.3 (1.6) 64.2 (2.1) 70.0 (1.6)* Non-Hispanic Black, % 10.9 (0.8) 16.4 (1.5) 10.1 (0.8)* Mexican-American, % 8.1 (0.8) 8.1 (1.1) 8.1 (0.8)* < high school education, % 17.7 (0.8) 26.1 (1.9) 16.6 (0.8)* Household income <$20,000, % 17.8 (0.8) 20.8 (1.5) 17.4 (0.8)* Current smokers, % 21.6 (0.8) 18.1 (1.6) 22.0 (0.9)* Former smokers, % 24.2 (0.5) 33.7 (1.7) 22.9 (0.6)* Consume alcohol, % 77.5 (0.8) 66.6 (1.8) 79.0 (0.8)* Body mass index ≥30 kg/m2, % 35.7 (0.7) 64.0 (2.0) 31.8 (0.7)* Diabetes, %† 12.1 (0.4) Prediabetes, %‡ 20.0 (0.5) 22.7 (0.6) *p-value <0.05, comparing those with and without diabetes †Diabetes defined as self-report of a previous diagnosis of diabetes or hemoglobin HbA1c ≥6.5% (48 mmol/mol) ‡Prediabetes defined as HbA1c 5.7-6.4% (39-47 mmol/mol) among those without diabetes

Table 3. Odds ratios of diabetes associated with log-transformed urinary phenols and parabens modeled continuously, phenols and parabens modeled such that one unit is equivalent to the difference between the 75th and 25th percentiles, National Health and Nutrition Examination Survey, 2005-2014 Odds ratio (95% confidence interval) Bisphenol A Model 1* 0.96 (0.88-1.06) Model 2† 1.10 (0.98-1.24) Model 3‡ 1.09 (0.96-1.23) Model 4§ 1.05 (0.93-1.19) Triclosan Model 1* 0.75 (0.65-0.86) Model 2† 0.82 (0.71-0.94) Model 3‡ 0.84 (0.72-0.98) Model 4§ 0.85 (0.73-0.99) Benzophenone-3 Model 1* 0.57 (0.51-0.64) Model 2† 0.68 (0.60-0.76) Model 3‡ 0.69 (0.61-0.79) Model 4§ 0.74 (0.65-0.86) Propyl paraben Model 1* 0.75 (0.66-0.85) Model 2† 0.73 (0.63-0.85) Model 3‡ 0.71 (0.61-0.83) Model 4§ 0.85 (0.72-1.01) Butyl paraben Model 1* 0.64 (0.53-0.77) Model 2† 0.68 (0.57-0.82) Model 3‡ 0.66 (0.54-0.80) Model 4§ 0.78 (0.63-0.95) Ethyl paraben Model 1* 0.59 (0.51-0.69) Model 2† 0.61 (0.52-0.71) Model 3‡ 0.60 (0.51-0.71) Model 4§ 0.74 (0.63-0.87) Methyl paraben Model 1* 0.87 (0.78-0.98) Model 2† 0.81 (0.70-0.93) Model 3‡ 0.79 (0.68-0.91) Model 4§ 0.90 (0.76-1.07) *Model 1 is the bivariate association between each phenol/paraben and diabetes †Model 2 adjusted for urinary creatinine, time of venipuncture, age, sex, and race/ethnicity ‡Model 3 adjusted for variables in Model 2 plus education, income, smoking status, and alcohol consumption §Model 4 adjusted for variables in Model 3 plus BMI

Table 4. Odds ratios (95% confidence intervals) of diabetes associated with quartile of phenol or paraben, modeled separately, National Health and Nutrition Examination Survey, 2005-2014 Quartile 1 Quartile 2 Quartile 3 Quartile 4 p-trend Bisphenol A Model 1* 1.00 1.03 (0.80-1.33) 1.02 (0.81-1.29) 0.94 (0.78-1.14) 0.3685 Model 2† 1.00 1.14 (0.86-1.51) 1.27 (0.97-1.66) 1.27 (0.97-1.66) 0.0886 Model 3‡ 1.00 1.19 (0.88-1.60) 1.29 (0.98-1.70) 1.25 (0.94-1.66) 0.1842 Model 4§ 1.00 1.08 (0.79-1.46) 1.18 (0.89-1.55) 1.14 (0.86-1.52) 0.4095 Triclosan Model 1* 1.00 0.80 (0.66-0.96) 0.83 (0.69-1.00) 0.60 (0.48-0.75) 0.0002 Model 2† 1.00 0.92 (0.76-1.11) 0.99 (0.81-1.22) 0.71 (0.56-0.91) 0.0035 Model 3‡ 1.00 0.92 (0.76-1.13) 1.02 (0.82-1.27) 0.74 (0.57-0.96) 0.0131 Model 4§ 1.00 0.92 (0.75-1.14) 0.98 (0.78-1.22) 0.76 (0.58-0.99) 0.0334 Benzophenone-3 Model 1* 1.00 0.58 (0.48-0.70) 0.49 (0.39-0.61) 0.33 (0.26-0.44) <0.0001 Model 2† 1.00 0.69 (0.56-0.85) 0.66 (0.53-0.83) 0.45 (0.34-0.59) <0.0001 Model 3‡ 1.00 0.68 (0.53-0.86) 0.68 (0.54-0.88) 0.47 (0.34-0.63) 0.0002 Model 4§ 1.00 0.65 (0.52-0.82) 0.71 (0.55-0.91) 0.54 (0.39-0.74) 0.0087 Propyl paraben Model 1* 1.00 0.78 (0.59-1.04) 0.74 (0.58-0.94) 0.62 (0.50-0.78) 0.0007 Model 2† 1.00 0.85 (0.62-1.16) 0.75 (0.57-0.99) 0.59 (0.46-0.75) 0.0001 Model 3‡ 1.00 0.84 (0.61-1.16) 0.76 (0.57-1.01) 0.56 (0.43-0.73) <0.0001 Model 4§ 1.00 0.91 (0.65-1.29) 0.92 (0.69-1.23) 0.73 (0.55-0.96) 0.0250 Butyl paraben Model 1* 1.00 0.62 (0.49-0.80) 0.60 (0.46-0.80) 0.51 (0.37-0.69) 0.0002 Model 2† 1.00 0.71 (0.54-0.94) 0.69 (0.52-0.93) 0.53 (0.39-0.74) 0.0009 Model 3‡ 1.00 0.71 (0.53-0.94) 0.66 (0.50-0.89) 0.52 (0.37-0.72) 0.0006 Model 4§ 1.00 0.76 (0.57-1.01) 0.81 (0.61-1.08) 0.67 (0.48-0.96) 0.0519 Ethyl paraben Model 1* 1.00 0.71 (0.60-0.84) 0.39 (0.31-0.50) 0.49 (0.40-0.61) <0.0001 Model 2† 1.00 0.74 (0.61-0.89) 0.42 (0.32-0.53) 0.50 (0.39-0.63) <0.0001 Model 3‡ 1.00 0.75 (0.62-0.91) 0.42 (0.32-0.56) 0.48 (0.37-0.62) <0.0001 Model 4§ 1.00 0.82 (0.68-1.00) 0.50 (0.38-0.66) 0.67 (0.52-0.86) 0.0202 Methyl paraben Model 1* 1.00 0.86 (0.68-1.07) 0.84 (0.67-1.06) 0.75 (0.59-0.96) 0.0378 Model 2† 1.00 0.83 (0.65-1.06) 0.80 (0.62-1.04) 0.64 (0.49-0.85) 0.0040 Model 3‡ 1.00 0.81 (0.63-1.04) 0.81 (0.62-1.06) 0.61 (0.46-0.82) 0.0024 Model 4§ 1.00 0.83 (0.63-1.08) 0.99 (0.75-1.32) 0.75 (0.54-1.05) 0.1279 *Model 1 is the bivariate association between each phenol/paraben and diabetes †Model 2 adjusted for urinary creatinine, time of venipuncture, age, sex, and race/ethnicity ‡Model 3 adjusted for variables in Model 2 plus education, income, smoking status, and alcohol consumption §Model 4 adjusted for variables in Model 3 plus BMI

Highlights • • •

BPA was not associated with diabetes in a nationally representative sample Triclosan, BP-3, and parabens were associated with lower odds of diabetes The association of parabens/phenols was similar among those with prediabetes