Science of the Total Environment 470–471 (2014) 726–732

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Bisphenol A and cardiometabolic risk factors in obese children

Naila Khalil a,⁎,1, James R. Ebert b,1, Lei Wang c, Scott Belcher d, Miryoung Lee e,Stefan A. Czerwinski f, Kurunthachalam Kannan c

a 3123 Research Blvd, Suite #200, Center for Global Health, Department of Community Health, Boonshoft School of Medicine, Wright State, University, Dayton, OH, USAb The Pediatric Lipid Clinic, the Children's Medical Center of Dayton, One Children's Plaza, Dayton, OH 45404, USAc Wadsworth Center, New York State Department of Health and Department of Environmental Health Sciences, State University of New York, Albany, NY 12201-0509, USAd 231 Albert Sabin Way, University of Cincinnati, Cincinnati, OH 45267-0575, USAe Community Health and Pediatrics, Wright State University, 3171 Research Blvd. Dayton, OH 45420-4006, USAf Community Health, Wright State University, 3171 Research Blvd. Dayton, OH 45420, USA

H I G H L I G H T S

• Cross sectional study of 39 obese and overweight children aged 3–8 years• Urinary BPA (u-BPA) measured by liquid chromatography-tandem mass spectrometry• Association between u-BPA and obesity analyzed by linear regression, spline analyses• U-BPA concentration in male obese children was associated with adverse liver and metabolic effects and high diastolic blood pressure

⁎ Corresponding author. Tel.: +1 937 258 5559; fax: +E-mail addresses: naila.khalil@wright.edu (N. Khalil),

(J.R. Ebert), Scott.Belcher@uc.edu (S. Belcher), miryoung.lstefan.czerwinski@wright.edu (S.A. Czerwinski), kkannan

1 Both authors contributed equally to the manuscript.

0048-9697/$ – see front matter © 2013 Elsevier B.V. All rihttp://dx.doi.org/10.1016/j.scitotenv.2013.09.088

a b s t r a c t

a r t i c l e i n f o

Article history:

Received 11 July 2013Received in revised form 26 September 2013Accepted 26 September 2013Available online xxxx

Editor: Frank Riget

Keywords:Bisphenol AEndocrine disruptorNon-monotonic dose responseChildhood obesityNonalcoholic fatty liver diseaseSpline analysis

Background and objective: Bisphenol-A (BPA) is an endocrinedisruptor (ED) that has been associatedwith obesityand metabolic changes in liver in humans. Non-alcoholic fatty liver disease (NAFLD) affects 40% of all obesechildren in the United States. Association of BPA with NAFLD in children is poorly understood. We investigatedif BPA might play a role.Methods: In a cross sectional study of 39 obese and overweight children aged 3–8 years enrolled from theChildrenMedical Center of Dayton, Ohio, anthropometric, clinical and biochemical assessment of serum sampleswere conducted. Urinary BPAwasmeasured by liquid chromatography-tandemmass spectrometry (LC-MS/MS)and was adjusted for urinary creatinine BPA (creatinine) using linear regression and spline analyses.Results:Higher urinary BPA (creatinine) concentration in overweight and obese children was associatedwith in-creasing free thyroxine. In male children BPA (creatinine) decreased with age, and was associated with elevatedliver enzyme aspartate aminotransferase and diastolic blood pressure. The association of BPA (creatinine)persisted even after adjusting for age and ethnicity. Also in males, BPA concentration unadjusted for creatininewas significantly associated with serum fasting insulin and homeostasis model assessment for insulin resistance(HOMA-IR) showing non-monotonic exposure–response relationship.

Conclusion:Urinary BPA in obese children, at least inmales is associatedwith adverse liver andmetabolic effects,and high diastolic blood pressure.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

Obesity in children is amajor public health concern. Early life obesitynot only tracks to adulthood, increasing the risk of metabolic and car-diovascular disease (CVD) but also is associatedwith liver abnormalities

1 937 258 5544.James.Ebert@wright.eduee@wright.edu (M. Lee),@wadsworth.org (K. Kannan).

ghts reserved.

including non-alcoholic fatty liver disease (NAFLD). NAFLD affects 40% ofobese children (Schwimmer et al., 2006). In addition to lifestyle factors,environmental chemicals acting as endocrine disruptors have beenthought to play a role in childhood obesity (Newbold et al., 2009;DiVall, 2013) and NAFLD (Polyzos et al., 2012).

Bisphenol A (BPA), a high production industrial chemical and com-ponent of polycarbonate plastics is ubiquitous in the environment(CDC, 2013). BPA is considered an endocrine-disrupting chemical(EDC) with estrogenic and thyroid hormone effects observed in experi-mental and epidemiological studies (Melzer et al., 2010; Moriyamaet al., 2002; Vandenberg et al., 2009). According to 2003–2004 National

727N. Khalil et al. / Science of the Total Environment 470–471 (2014) 726–732

Health and Nutrition Examination Survey (NHANES), 93% of the UnitedStates population sampled had measurable urinary BPA (Calafat et al.,2008), and children aged between 6 and 11 years had the highest uri-nary creatinine corrected BPA concentrations compared to other agecategories (CDC, 2013). Furthermore, in other NHANES studies in chil-dren aged 6 to 19 years, urinary BPA concentration was associatedwith increased risk of obesity (Trasande et al., 2013a) and albuminuria(Trasande et al., 2013b). In children, major exposure to BPA occursthrough food and water intake, although dental sealants, inhalation ofhouse dust, and dermal absorption are considerable sources of BPAexposure (CDC, 2013).

Epidemiological studies have linked BPA exposure in adults withobesity (Carwile and Michels, 2011; Shankar et al., 2012b) and insulinresistance (IR) (T. Wang et al., 2012), diabetes (Lang et al., 2008;Silver et al.), hypertension (Shankar and Teppala, 2012), peripheral ar-tery disease (Shankar et al., 2012a), and risk of CVD (Melzer et al.,2010, 2012; Lang et al., 2008). Evidence is emerging regarding theunderlying pathophysiology of BPA and metabolic dysregulation.Population based studies demonstrate that BPA is also associatedwith elevated serum liver enzymes in men (F. Wang et al., 2012)and with inflammatory biomarkers, fatty liver disease and IR in women(Tarantino et al., 2013). In particular both fatty liver disease and IR arethought to be related to BPA mediated inflammation (Ben-Jonathanet al., 2009;Hugo et al., 2008). In laboratory animals environmentally rel-evant doses of BPA influenced lipid metabolism in liver contributing tohepatic steatosis (Ronn et al., 2013). Kandaraki et al. (2011) describedpositive correlation between BPA and IR in women (Kandaraki et al.,2011). This association corroborates evidence from in vitro and in vivoexperiments in which BPA exposure induced insulin secretion andIR (Alonso-Magdalena et al., 2006, 2010). Endocrine hormones andendocrine disruptors often exhibit non-monotonic dose responseassociation (NMDR) (Vandenberg et al., 2012; Beausoleil et al., inpress) as U-shaped, inverted U-shaped, or W-shaped curves re-ported in animal models (Cabaton et al., 2011; Markey et al., 2001)and limited epidemiological studies (reviewed in Vandenberg et al.,2012). The present exploratory study aimed to examine the relation-ship of urinary BPA, with anthropometric, clinical, hormonal and meta-bolic measures in a cohort of obese and overweight children. Wehypothesized that urinary BPA will have a significant association withadiposity, serum lipids and metabolic panel. Further we hypothesizedthat association of BPA with the above parameters will differ by sexand exhibit non-linear exposure–response relationship.

2. Methods

2.1. Study population

The study population comprised of 39 obese or overweight childrenaged 3–8years (50% females, 62% Caucasians), whowere enrolled fromthe Lipid Clinic at Children's Medical Center of Dayton (CMC) Ohio. TheLipid Clinic at CMC was established in 2001. It is a referral facility withexpertise in diagnosing and managing children and adolescents pre-senting with obesity related metabolic diseases. The interdisciplinaryteam includes physicians, nurses, and dieticians. Children were invitedto participate in this study from April to August 2012, if they werebetween 3 and 8 years of age, were not suffering from thyroid disease,diabetes (Type 1 or 2) or other chronic diseases (e.g., asthma). Thestudy protocol was approved by the institutional review boards of theCMC, and Wright State University, and written informed consent wasobtained from parents or guardians of all the participants.

2.2. Demographic and anthropometric measures

Age and ethnicity of children were self-reported by parents. Anthro-pometric data included measurements of weight, stature, and waistcircumference using a standardized protocol (Lohman et al., 1988).

Weight was measured to nearest 0.1 kg on a Detecto-6550 balancescale in street clothes. Height in meters was measured without shoesusing a stadiometer (SECA-216). BMI was calculated as weight/height2

(kg/m2). Age- and sex-standardized BMI z scores are calculatedaccording to 2000 Centers for Disease Control and Prevention (CDC)year growth charts (Ogden et al., 2002). Overweight and obese werecategorized as BMI z score of 1.036 or greater (85th percentile for ageand sex) and 1.64 or greater (95th percentile), respectively (Trasandeet al., 2012). In this group except one, all children were obese. Waistcircumference (WC) was obtained from iliac crest to iliac crest withstandard tape measure in standing position without any clothes cover-ing the abdomen. Seated systolic (SBP) and diastolic blood pressure(DBP) inmillimeters ofmercury (mmHg)were obtained using a sphyg-momanometer (Dinamap Pro-100 model 400v2) using 2 cuffs sizes of17–25cm, or 23–33 cm based on the age of the child.

2.3. Biochemical assays

Blood samples are obtained after an overnight fast by venipunctureinto BPA free Vacutainer tubes. Biochemical data of interest includedfasting insulin (FI), glucose, glycated hemoglobin (HbA1C), low densitylipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol(HDL-C), total cholesterol (TC), and triglycerides (TG). Liver profilecomprised of alanine aminotransferase (ALT) and aspartate amino-transferase (AST). Thyroid profile included thyroid stimulating hor-mone (TSH) and free thyroxine (FT4).

The lipid and thyroid assays were performed on-site by the CMClaboratory, certified by the College of American Pathologists. BeckmanCoulter DxC600i/Synchron was used for assay of plasma glucose,LDL-C, HDL-C, TC, TG, ALT and AST (normal range for both liver en-zymes 0–45 IU/L). Serum insulin, TSH and FT4 were measured utilizingBeckman Coulter DxC600i/Access 2. HbA1C was measured by SiemensDCAVantage Analyzer. Homeostasismodel assessment for insulin resis-tance (HOMA-IR) was calculated using the formula: fasting plasmaglucose (mmol/l)× fasting insulin (mIU) / 22.5.

2.4. Bisphenol-A assay

Spot sample of urine was collected in sterile polypropylene (PP),BPA-free urine cups. Ten milliliters of urine was transferred into BPAfree glass tubes and frozen at −40 °C until shipment on dry ice toWadsworth Center, Albany, New York for analysis (Fig. 1).

Urine (500 μL) was transferred into a 15 mL PP tube (afterthawing at room temperature for 30min), and 10 ng of 13C12-bisphenolA (13C12-BPA)was added as an internal standard. Three hundredmicro-liters of 1.0M ammonium acetate containing 44 units of glucuronidasewas added to each sample and the mixture was shaken in an orbitalshaker at 37°C for 12h (Zhang et al., 2011). Then 0.5mL of 1.0M formicacid was added to stop the enzyme activity, and then 0.2mL of Milli-Qwater was added. The digested sample was extracted twice by ethyl ac-etate (5+4mL), and then the extractswere separated by centrifugation(5000 ×g, 5 minutes) and washed by 0.5 mL of Milli-Q water. Theextracts were concentrated to near dryness by a gentle stream of N2,and then dissolved in 0.5mL ofmethanol before analysis by liquid chro-matography-tandem mass spectrometry (LC-MS/MS).

Analyte levels in samples were quantified using a high-performanceliquid chromatography (HPLC) coupled with API 2000 electrospraytriple-quadrupole mass spectrometer (ESI-MS/MS). The analyticalmethod is similar to that described earlier (Kunisue et al., 2012). A 10μL of the extract was injected onto an analytical column (Betasil® C18,100 × 2.1 mm column; Thermo Electron Corporation, Waltham, MA),which was connected to a Javelin® guard column (Betasil® C18,20 × 2.1 mm). The mobile phase was comprised of methanol andwater containing 0.01 M ammonium acetate at a gradient startingfrom 25% methanol to 99% methanol in 4 minutes and held for

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Creatinine adjusted Urinary BPA (ug/g) in Children by Sex

Male Female

p-value: 0.723

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Urinary BPA (ng/mL) in Children by Sex

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p-value: 0.079

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Fig. 1. a, b: Bisphenol analyte distribution in obese and overweight children by sex. a) BPA,b) Creatinine corrected urinary BPA.

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10minutes before it was reversed to initial condition. The flow rate andthe column temperature were 300 μL/min and 25°C respectively.

To confirm that glass tubes were free from BPA contamination, andfor quality assurance, procedural blanks were used and no backgroundcontaminationwas found. Quality assurance and quality control param-eters also included validation of the method by spiking BPA into thesample matrices and passing through the entire analytical procedureto calculate recoveries of analytes through the analytical method.Reported concentrations were corrected for the recoveries of surro-gate standard (isotopic dilution method). The BPA standards spikedto selected sample matrices and passed through the entire analyticalprocedure yielded a recovery of 98%. An external calibration curvewas prepared by injecting 10 μL of 0.01, 0.02, 0.05, 0.10, 0.20, 0.5,1, 2, 5, 10, and 20 ng/mL standards and regression coefficient was0.99.

For the analysis of creatinine, an aliquot of urine (10μL) was diluted(160-fold) withMilli-Q water, and 800ng of d3-creatininewas added. Amixture of methanol/Milli-Q water (50:50, v/v) containing 0.1% formicacid was used as the isocratic mobile phase. The positive ion MRMtransitions monitored were 114 N 44 for creatinine and 117 N 47 ford3-creatinine. The MS/MS collision energy was 25 eV, ion source tem-perature was 400 °C, and cone voltage was 4500 V. The BPA limit ofdetection (LOD) was 0.1 ng/mL. For one child (n=1 [2.5% of the sam-ple]), urinary BPA concentrations below LOD, a value of 0.07 ng/mLwas substituted for statistical analysis following usual practice (LODdivided by the square root of 2) (CDC, 2013). To correct for urinary dilu-tion, all analyses were repeated with urinary creatinine adjusted BPA(BPA(creatinine)) concentration.

2.5. Statistical analysis

The association of BPA with demographic, clinical and biochemicalvariables was analyzed in overall sample, as well as by sex. Assumptionof normality was tested graphically and by using the Shapiro–Wilkstatistic available in SAS as part of the basic descriptive analysis. Thenull hypothesis of a Shapiro–Wilk test explores if there is no significantdeparture fromnormality.When the p-value associatedwith goodness-of-fit statistic was more than 0.05, the null hypothesis was not rejected,concluding normal distribution. If the p-value was less than thepredetermined critical value (b0.05), the null hypothesis was rejected,concluding non-normal distribution.

Variables with non-normal distribution were log transformed. STATAprogramoptions “Gladder” (graphical representation of distribution) and“Ladder” (statistical test of distribution) procedures were used to choosethe most appropriate of several possible transformations of each non-normal variable. These STATA functions provide not only goodness-of-fit statistics upon which to evaluate transformations, but also superim-pose plots of the transformed variable upon a normal curve to illustratethe goodness of fit. We chose the log transformation out of those withthe best scores because it provided results that were easier for the audi-ence to interpret. Sex differences were analyzed by t-tests and Mann–Whitney U tests. To assess univariate relationship of BPA (independentvariable) with parameters of interest (dependent variable) linear regres-sion was performed separately for each dependent variable.

The association between log transformedBPA andmetabolic variablesHOMA-IR, FI and TSH was tested using cubic spline in regression modelsas reported in epidemiology literature for BPA (Braun et al., 2011) andother toxic environmental exposures including lead (Jemal et al., 2002),perfluoroalkyl surfactants (PFASs) (Lopez-Espinosa et al., 2011), atrazine,dioxin, and perchlorate (Vandenberg et al., 2012). Cubic polynomialsplines allow the shape of the relationship between the exposure andoutcome to be flexible and can show non-monotonic exposure–responserelationship (Desquilbet and Mariotti, 2010). For 3 knot regressionsplines knots were located at 0.1, 0.5, and 0.9 percentile distribution ofBPA. For 4 knot regression splines, knots were placed at 0.5, 0.35, 0.65,and 0.95 percentile distribution of BPA. Exposure–response associationbetween BPA and metabolic outcome variables HOMA-IR, FI and TSHwas tested with Wald test in separate regression models. Wald test wasused to test if the slope of three segments of BPAwas significantly differ-ent from zero. STATA software was used for spline analysis (Edition 9,StataCorp, College Station, Texas, USA). Other analyses were performedusing SAS 9.2 (SAS Institute, Cary, NC, USA). In all analyses, a two-sidedp-value of b0.05 was considered statistically significant.

3. Results

3.1. Characteristics of participants

The characteristics of participants overall, and by sex arepresented in Table 1. Median (inter-quartile range) of urinary BPAconcentration was 1.37 (1.2) ng/mL, and urinary BPA adjusted forcreatinine (BPA(creatinine)) was 1.82μg/g (2.6) (Table 1). Anthropomet-ric, clinical and metabolic characteristics were comparable by sex withthe exception of BMI z score which was significantly higher (p=0.04)and serum FT4 concentration that was lower in males (p = 0.04)(Fig. 1). Neither urinary BPA nor BPA(creatinine), or urinary creatinineclearance was different in children across ethnicity (Table 1). However,in sex specific analysis only females (n=9) of African American/otherethnicity had significantly higher urinary BPA compared to males(n=6) of African American/other ethnicity.

3.2. Linear regression results

Although separate models were run for all anthropometric, clinicaland metabolic (dependent) variables shown in Table 1, only selected

Table 1Anthropometric, metabolic characteristics of study participants, overall and by sex.

Characteristic, Mean (SD) n Overall n Female n Male p-Valuea

Age (year) 39 6.6 (1.5) 22 6.7 (1.3) 17 6.4 (1.7) 0.58Weight (kg) 39 46.3 (14.7) 22 43.9 (12.8) 17 49.5 (16.8) 0.24Height (cm) 39 129 (12.4) 22 128 (10.9) 17 130 (14.5) 0.66Waist circumference (cm) 36 83.3 (11.1) 19 84.2 (10.8) 17 82.2 (11.6) 0.60BMI (kg/m2) 39 27.2 (5.4) 22 26.1 (5.0) 17 28.7 (5.8) 0.15BMI z scoreb 39 2.6 (0.7) 22 2.4 (0.8) 17 2.7 (0.6) 0.04Diastolic BP (mm Hg) 39 64.4 (6.8) 22 63.4 (6.7) 17 65.7 (7) 0.32Systolic BP (mm Hg) 39 113.3 (11.0) 22 110 (12) 17 116.2 (11) 0.15LDL-C (mg/mL) 32 107 (25.4) 17 108 (30) 15 106 (20) 0.81HDL-C (mg/mL) 33 42 (11.6) 18 43.6 (11) 15 40.1 (12.8) 0.39Triglycerides (mg/mL)b 33 85 (96) 18 87 (108) 15 85 (67) 0.68c

Total Cholesterol (mg/mL) b 33 167 (52) 18 175 (61) 15 163 (47) 0.85c

AST (μ/L) 31 30.5 (6.7) 16 30.1 (5.5) 15 30.9 (8.0) 0.74ALT (μ/L)b 31 23 (9) 16 23 (9) 15 23 (17) 0.80c

Fasting insulin (Uiu/mL)b 34 8.0 (6.5) 19 7.3 (7.9) 15 8.0 (5.0) 0.89c

Fasting glucose (mg/mL) 35 89.6 (8) 19 88 (7.4) 16 91.5 (8.4) 0.20A1C (mmol/mol) 27 5.3 (0.4) 14 5.3 (0.4) 13 5.3 (0.5) 0.83HOMA (mmol/L)b 32 1.78 (1.5) 18 1.7 (2.2) 14 1.8 (1.2) 0.72c

FT4 (pmol/L)b 32 0.87 (0.3) 15 0.98 (0.4) 17 0.80 (1.0) 0.04c

TSH (μIU/mL)b 33 2.5 (1.6) 20 2.5 (1.9) 13 2.5 (1.4) 0.87c

Bisphenol A (ng/mL)b 39 1.37 (2.2) 22 1.74 (3.3) 17 1.12 (1.2) 0.07c

Caucasians 24 1.31d (2.5) 13 1.41 (2.9) 11 1.19 (1.4) 0.78c

Others 15 1.40d (2.0) 9 2.11(2.5) 6 0.90 (0.9) 0.04c

BPA (creatinine) (μg/g)b 39 1.82 (2.6) 22 2.52 (3.1) 17 1.20 (1.9) 0.06c

Caucasians 24 1.71e (2.3) 13 1.90 (2.9) 11 1.23 (1.8) 0.49c

Others 15 2.26e (6.2) 9 3.45 (4.8) 6 1.05 (1.0) 0.11c

Urinary creatinine (μg/mL)b 39 932 (578) 22 871 (591) 17 1067 (588) 0.46c

Caucasians 24 930f (822) 13 857 (684) 11 1283 (799) 0.23c

Others 15 930f (347) 9 931 (304) 6 757 (309) 0.86c

a p-Value tests mean/median differences between males and female.b Median (Inter-quartile range).c Mann–Whitney U test.d, e, f p-Value tests median overall analyte difference between participants of Caucasian and others ethnicities (d 0.785, e 0.466, f 0.502).

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models that were significantly associated with BPA or BPA (creatinine) arepresented in Table 2.

3.2.1. BPA overall and sex specific modelsIn overall linear regression analysis andwhen analyzed by sex, in fe-

males BPA did not show any significant association with anthropomet-ric andmetabolic characteristics. However inmales, BPAwas significantin predicting decrease in serum FI (β Standard Error (SE))=−0.36, =0.10, p=0.022 and HOMA-IR (β=−0.39 SE (0.10), p=0.006).

3.2.2. In BPA (creatinine) and sex specific modelsIn overall model serum FT4 was significantly associated with

BPA(creatinine) (β (SE)=0.26, SE (0.1), p=0.028). In sex specific univar-iate regression analysis, in males BPA(creatinine) was a negative predictor

Table 2Simple linear regression between log transformed bisphenol A (BPA) and log transformed BPA

Characteristics Overall Femal

β (SE)b p-Value R2 β (SE

Age BPA −0.01 (0.2) 0.629 0.0 −0.14BPA Cr −0.37 (0.2) 0.051 0.10 −0.18

AST BPA 1.95 (1.1) 0.262 0.04 0.30 (BPA Cr 1.48 (0.9) 0.116 0.08 −0.04

FI a BPA −0.11 (0.1) 0.407 0.02 0.00 (BPA Cr −0.04 (0.1) 0.696 0.00 −0.01

HOMA-IR a BPA −0.13 (0.1) 0.345 0.30 −0.00BPA Cr −0.05 (0.1) 0.656 0.00 −0.00

Diastolic BP BPA −0.61 (0.1) 0.543 0.01 −0.58BPA Cr 1.05 (0.9) 0.238 0.04 −0.25

FT4a BPA 0.15 (0.1) 0.290 0.04 0.08 (BPA Cr 0.26 (0.1) 0.028 0.18 0.33 (

a Log transformed variables.b SE: standard error.

of age (β=−0.71, SE (0.2), p=0.029), positive predictor of serum AST(β=3.35, SE (1.4), p=0.032) and diastolic blood pressure (β=3.34,SE (1.1), p=0.011).

3.2.3. Adjusted regression analysis for diastolic blood pressureAssociation between BPA(creatinine) and diastolic blood pressure

(outcome variable) in males was significant when adjusted for age,and ethnicity (β=4.01, SE (1.41), pb0.014, adjusted R2=0.38, Table 3).

3.2.4. Spline analysisIn spline analysis a non-monotonic exposure–response association

between urinary BPA, serum TSH was noted. In addition, in males, uri-nary BPA concentration had significant non-linear relationship withHOMA-IR and FI (Fig. 2). Wald test was significant which indicated

(creatinine) and selected characteristics of study participants, overall and by sex.

e Male

) p-Value R2 β (SE) p-Value R2

(0.2) 0.530 0.02 −0.12 (0.5) 0.815 0.00(0.2) 0.442 0.03 −0.71 (0.2) 0.029 0.28

1.3) 0.812 0.00 5.05 (2.4) 0.058 0.25(1.2) 0.991 0.00 3.35 (1.4) 0.032 0.31

0.2) 0.992 0.00 −0.36 (0.1) 0.022 0.34(0.2) 0.948 0.00 −0.08 (0.1) 0.501 0.04(0.2) 0.992 0.00 −0.39 (0.12) 0.006 0.48(0.2) 0.963 0.00 −0.08 (0.1) 0.439 0.05(0.1) 0.617 0.01 0.20 (2.2) 0.927 0.00(1.2) 0.837 0.00 3.34 (1.1) 0.011 0.36

0.2) 0.727 0.00 0.06 (0.1) 0.318 0.100.2) 0.121 0.18 0.04 (0.1) 0.931 0.00

Table 3Parameter estimates of simple (Model 1) and multivariable linear regression (Model 2)between log BPA (creatinine) and diastolic bloodpressure inmale obese and overweight chil-dren (n=17).

Parameter estimates β SE p

Model 1, diastolic blood pressureIntercept 64.92 1.44 b0.001Log BPA (creatinine), μg/g 3.34 1.16 0.011R2= 0.36

Model 2, diastolic blood pressureIntercept 64.37 6.78 b0.001Log BPA (creatinine), μg/g 4.01 1.41 0.014Age, years 0.67 1.14 0.566Ethnicity: Caucasian versus others −6.07 3.35 0.093R2= 0.49, Adjusted R2=0.38.

Fig. 2. a, b, c: Non-linear association of BPA analytes with a) FI and b) HOMA-IR in males,and c) with TSH overall (all variables log transformed). p-Value for Wald test in A, B, C:b0.001.

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that the slope of three segments of BPA was different from zero for FI(pb0.0001), HOMA-IR (pb0.006), TSH (pb0.0001) and showed variablepatterns of increase and decrease at different exposure levels of BPA.

4. Discussion

The results of this study suggest that higher urinary BPA(creatinine)

concentration in overweight and obese children is associated withincreasing FT4. In male children BPA(creatinine) decreased with age, andwas associatedwith elevated liver enzymeAST anddiastolic blood pres-sure. BPA concentration unadjusted for creatinine was associated withdecreasing serum FI and HOMA-IR levels in linear regression andshowed NMDR association. These results are suggestive that BPA expo-sure in obese children at least in males can lead to adverse liver, andmetabolic effects and high diastolic blood pressure.

Themedian urinary BPA concentration observed in obese children inthe current study was lower than 2.8 ng/mL (4.4) as compared to thatreported in US population based sample of children aged 6–19years in2009–2010 NHANES (Trasande et al., 2012). In the current analysis,even at comparatively lower BPA concentration, significant associationswith several metabolic outcomes were observed.

4.1. BPA and thyroid hormone

In this study, male obese children had significantly lower FT4 com-pared to female children. In overall linear regression BPA(creatinine)

predicted higher FT4. In overall correlation analysis TSH was inverselyassociated with BPA which on spline analysis showed a NMDR associa-tion, suggesting that as concentration of BPA increased TSH hormonesdid not exhibit a linear pattern of increase. Thyroid hormone is essentialfor prenatal and post natal growth and brain development. BPA hasbeen associated with potentially adverse effects on cognition andbehavior in humans (Braun et al., 2011) which may be attributable todisruption of thyroid function. Limited human evidence shows thatBPA exposure during pregnancy is inversely related to total T4 in preg-nant women and decreased TSH in male infants (Chevrier et al., 2013).These associations may have implications in children during rapidgrowth phases of childhood and puberty.

4.2. BPA and age

Prenatal growth, infancy, and childhood when rapid developmentoccurs, are periods of highest vulnerability to adverse effects of BPAexposure (Chevrier et al., 2013). In the current study in male childrenurinary BPA concentration decreased significantly with age (only inBPA(creatinine)). As reported in 2009–2010NHANESdata inwhich children6–11years of age had significantly higher urinary BPA (2.25ng/mL) con-centration compared to ages 12–19 years (1.76 ng/mL) (p b 0.016)(Trasande et al., 2013b) (both sexes). According to 2003–2004 NHANES

children aged 6–11 years of age had the highest urinary BPA(creatinine)

compared to other age categories (2012). In an epidemiological studyof younger children aged 1, 2, and 3 years, median urinary BPA(creatinine)

decreased from 18.0 ug/g, 9.6 ug/g, to 5.3 ug/g with age respectively(Braun et al., 2011).

4.3. BPA in males

In the current analysis in male children serum FI and HOMA-IRshowed a non-linear associationwith increasing urinary BPA concentra-tion. This observation is consistent with evidence from in-vitro and in-vivo models, however human studies are non-existent. Estrogens (E2)and BPA have insulinotropic effects on pancreatic islets of Langerhans

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in male mice which indicate that E2, and BPA increases insulin con-tent and secretion (Alonso-Magdalena et al., 2008). When Islets ofLangerhans were cultured in the presence of glucose and increasingdosage of E2 (physiological dose of E2) for 48hours, insulin secretion in-creased in an inverted-U dose-dependent response pattern. When BPAwas substituted for E2, increase of insulin secretion showed a similarinverted U-shaped dose response curve. This indicates that BPA as axenoestrogenmaymimic the effect of E2 on insulin secretion pathways,and increases pancreatic insulin content in a non-monotonic manner(Alonso-Magdalena et al., 2008).

In animalmodels, prenatal BPA exposure disturbed pancreatic β-cellresponse and stimulated IR in male mice offspring (Alonso-Magdalenaet al., 2006, 2010). On the contrary, female offspring displayed normalglucose and insulin parameters. Females are protected against IR morethan aremales, as in female presence of estrogenswithin the physiolog-ical range protect against diabetes in mice (Louet et al., 2004). Thesexually dimorphic relationship suggests an association of BPA actingas an estrogen with obesity and glucose homeostasis in males but notin females (Mauvais-Jarvis, 2011). Further, data from animal studiessuggest that males may not metabolize BPA as efficiently as femalesandmay be at higher risk of BPA exposure because of delayed excretionand metabolism (Takeuchi et al., 2004).

4.4. BPA and liver

Hepatotoxic effect of BPA has been described in animal modelswhere BPA concentration lower than human protective dose No Ob-served Adverse Effect Level (NOAEL) can induce hepatic damage andmitochondrial dysfunction by increasing oxidative stress in the liver(Ronn et al., 2013). Based on hepatotoxic potential of BPA in rodentmodels, the U.S. Environmental Protection Agency derived a tolerabledaily intake (TDI) of 50 μg/kg/day for humans after applying an uncer-tainty factor of 100 to the NOAEL of 5000 μg/kg/day (5000/100= 50)(Marmugi et al., 2012). In rodents, BPA at TDI doses showed non-monotonic dose response with liver enzymes that control fat synthesis(Marmugi et al., 2012). BPAmay induce fat deposition in liver, either di-rectly through a hepatotoxic effect and/or indirectly by promoting IRand inflammation (Moon et al., 2012) as shown in an increase in pro-inflammatory cytokines interleukin-6 (IL-6) and tumor necrosisfactor-alpha (TNF-α) (Moon et al., 2012). In rats exposure to BPA atTDI dose, magnetic resonance imaging showed that liver fat contentwas significantly increased compared to controls (p = 0.04) (Ronnet al., 2013). In premenopausalwomenwith poly cystic ovary syndrome(PCOS), serum BPA levels were related to HOMA-IR, markers of low-grade inflammation including C-reactive protein (CRP), IL-6, and ultra-sound quantification of hepatic steatosis (Tarantino et al., 2013).

4.5. BPA and non-monotonic exposure–response

Endocrine hormones and endocrine disruptors such as BPA rarelydisplay linear dose response association (Vandenberg et al., 2012). Thereason being that after a hormone binds and saturates its receptorsites; excess hormone does not produce further response (Vandenberget al., 2012). Alternatively, high doses can down regulate responsesinitiated at lower doses such that different effects can appear anddisappear at different exposure concentrations. These non-monotonicexposure–response curves are commonly accepted in endocrinology(Vandenberg et al., 2012). BPA exposure has been associated with vari-ous health outcomes in a non-monotonic fashion displayed as U-shapedor inverted U-shaped, W-shaped curves. As reported in literature, whenhuman fat explants was treated with BPA (0.1–10 nM) the adiponectinsecretion response was a U-shaped curve; at low dose of BPAadiponectin secretion was lower, whereas at elevated BPA dosesadiponectin secretion increased (Hugo et al., 2008). In animal exper-iments, when BPA was added in 1 or 10 μg BPA/L doses in drinkingwater during early development, 1 μg dose but not 10 μg of BPA/L

induced significant weight gain (Miyawaki et al., 2007). Variousdoses of BPA may function in distinctly different sometimes oppos-ing manner.

4.6. BPA and diastolic blood pressure

In this study, BPA was significantly related to diastolic blood pres-sure in male children even after adjusting for confounding effects ofage and ethnicity. BPA at environmentally relevant doses inhibits the re-lease of adiponectin, a key adipokine protective against hypertensionand other components of metabolic syndrome (abdominal obesity, glu-cose intolerance, hyper-insulinemia, hyper-triglyceremia) (Hugo et al.,2008). As discussed above, in epidemiological studies, BPA exposurewas associated with abnormal liver and thyroid function, higher levelsof fasting glucose, estrogen-mimetic effects, IR, and HOMA-IR whichare considered risk factors for hypertension. Furthermore, BPA can in-duce endothelial cell injury mediated through oxidative stress (Ooeet al., 2005) and elevations in lipids in animal models (Marmugi et al.,2012). Emerging evidence in human population also supports that asso-ciation between BPA, hypertension (Shankar and Teppala, 2012) andperipheral arterial disease is plausible as noted in adults in NHANES2003–2004 (Shankar et al., 2012a).

4.7. Strengths and limitations

The main strengths of our study include its representation of youngchildren from both sexes and the availability of extensive data onmetabolic and hormonal parameters. To our knowledge this is the firststudy to report a non-monotonic exposure–response relationship be-tween metabolic and hormonal effects of BPA in children. Howeverthere are several study limitations, including the small sample size, itscross-sectional design which does not allow establishing cause–effectassociations.

5. Conclusions

In obese and overweightmale children BPA(creatinine) decreasedwithage, and was associated with elevated liver enzyme AST and diastolicblood pressure. BPA concentration unadjusted for creatinine showednon-linear association with decreasing serum FI and HOMA-IR. Furtherresearch to explore environmental exposure to BPA and obesity relatedhealth outcome in children is warranted.

Grant support and institutional review for human subjects' research

Theworkwasnot grant supported. The study protocolwas approvedby the institutional review boards of the Children's Medical Center ofDayton, and Wright State University. Written informed consent wasobtained from parents or guardians of all the participants. The approvalof research protocol is appended (Appendices 1–3).

Conflict of interest statement

All authors declare that they do not have any actual or potential con-flict of interest including any financial, personal or other relationshipswith other people or organizations within three years of beginning thesubmitted work that could inappropriately influence, or be perceivedto influence, their work.

We assure you that all of the authors have read and approved thepaper. The content has not been published previously nor is it beingconsidered by any other peer-reviewed journal. We have not usedanimals in this research. Written informed consent was obtained fromthe participants before the start of the study.

732 N. Khalil et al. / Science of the Total Environment 470–471 (2014) 726–732

Acknowledgments

The contribution of study participants and Lipid Clinic staff includingChristie Bernard, Gail Keys, DeniseMullins, andKris Ramdat is gratefullyacknowledged.

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