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. Author manuscript; available in PMC: 2024 Mar 1.
Published in final edited form as: Int J Hyg Environ Health. 2022 Dec 14;248:114104. doi: 10.1016/j.ijheh.2022.114104

Associations of Maternal Gestational Urinary Environmental Phenols Concentrations with Bone Mineral Density Among 12-year-old Children in the HOME Study

Jordan R Kuiper a,*, Shudi Pan b,*, Bruce P Lanphear c, Antonia M Calafat d, Aimin Chen e, Kim M Cecil f, Yingying Xu g, Kimberly Yolton h, Heidi J Kalkwarf i, Joseph M Braun j, Jessie P Buckley k
PMCID: PMC9898141  NIHMSID: NIHMS1858427  PMID: 36525700

Abstract

Background:

Early life environmental exposures may affect bone mass accrual in childhood, but only one study has assessed the role of environmental phenols on child bone health.

Methods:

We used data from 223 mother-child dyads enrolled in the Health Outcomes and Measures of the Environment (HOME) Study (Cincinnati, OH; 2003–2006). We quantified benzophenone-3, bisphenol A (BPA), 2,5-dichlorophenol, and triclosan in maternal urine collected at 16- and 26-weeks gestation and calculated the average of creatinine-adjusted concentrations. We performed dual x-ray absorptiometry at age 12 years and calculated Z-scores for whole body (less head), total hip, femoral neck, and 1/3rd distal radius bone mineral content (BMC) and areal bone mineral density (aBMD) as well as ultra-distal radius aBMD and spine BMC and bone mineral apparent density (BMAD). We estimated covariate-adjusted associations per doubling of maternal urinary environmental phenol concentrations in linear regression models. We also examined effect measure modification by child’s sex and estimated associations of the environmental phenol mixture with BMC and aBMD using quantile g-computation.

Results:

We observed generally null associations for all analytes and bone measures. Yet, in adjusted models, higher urinary 2,5-dichlorophenol concentrations were associated with higher 1/3rd distal radius BMC (β: 0.09; 95% CI: 0.02, 0.17) and aBMD (β: 0.09; 95% CI: 0.02, 0.17) Z-scores in the overall sample. In sex-stratified analyses, the magnitude of the BMC association was positive for females (β: 0.16; 95% CI: 0.06, 0.26) and null for males (β: 0.02; 95% CI: −0.08, 0.13). The environmental phenol mixture was associated with greater 1/3rd distal radius BMC and aBMD Z-scores in both sexes, which was mostly driven by benzophenone-3 in males and 2,5-dichlorophenol in females.

Conclusion:

In this prospective cohort study, we observed generally null associations for environmental phenols with BMC and aBMD at age 12 years. While there was a positive association of 2,5-dichlorophenol concentrations during fetal development with distal radius BMC and aBMD at age 12 years, future studies utilizing methods capable of differentiating cortical and trabecular bone are needed to elucidate potential mechanisms and implications for bone strength and microarchitecture.

Keywords: Bisphenol A; bone mineral density; children; environmental phenols; 2,5-dichlorophenol

Introduction

Bone mass accrual during early childhood is critical for lifelong bone health (Weaver et al., 2016). Bone mass accretion begins during fetal growth, increases slowly during childhood, and bone mass accretion velocity peaks during puberty (Bailey et al., 1999; Weaver et al., 2016). Although bone accrual continues after puberty, 95% of adult bone mass is achieved within four years following the peak velocity (Baxter-Jones et al., 2011). Low bone mineral density (BMD) during childhood is linked with lower peak bone mass in young adulthood (Wren et al., 2014), with low peak bone mass being a major factor in the development of bone fractures and osteoporosis in older adults (Bonjour et al., 1994). Osteoporosis, characterized by low BMD (T-score < −2), affects more than 10 million adults over age 50 years (10.3%) in the USA (Wright et al., 2014). Thus, determining whether environmental exposures affect optimal bone accrual in early life has long-lasting implications for reducing risk of fractures and osteoporosis later in life.

Environmental phenols (including bactericides, benzophenones, and bisphenols) are ubiquitous endocrine-disrupting chemicals found in personal care products, plastics, and cleaning supplies (Diamanti-Kandarakis et al., 2009). Although environmental phenols are non-persistent chemicals excreted within 24 hours (Völkel et al., 2002; Weatherly and Gosse, 2017), the ubiquity of exposure sources leads to ongoing exposures that may have a profound health effect (Jeon et al., 2008). Environmental phenols have been shown to affect skeletal formation and remodeling (Agas et al., 2018; Agas et al., 2013; Chin et al., 2018; Smith et al., 2017; Thent et al., 2018; Turan, 2021; Vitku et al., 2018). While the exact mechanisms are not known, environmental phenols may disrupt bone metabolism through binding with estrogen receptors α and β, or by inducing inflammation and oxidative stress (Chin et al., 2018; Yang et al., 2009).

Most human epidemiologic studies of environmental phenols and bone health have been cross-sectional and among adult populations, and they have reported inconsistent associations (Cai et al., 2019; Vitku et al., 2018; Wang et al., 2020). One cross-sectional study of postmenopausal women using 2005–2010 National Health and Nutrition Examination Survey (NHANES) data found a positive association of urinary 2,5-dicholorophenol concentrations with greater femoral neck areal BMD (aBMD) as well as an association of urinary triclosan concentrations with lower femoral neck aBMD (Wang et al., 2020). Similarly, Cai et al. (2019) reported an association of higher urinary triclosan concentrations with lower total femur, intertrochanteric region (i.e., where the thigh and hip muscles attach to the femur), and lumbar spine aBMD among women aged ≥20 years in 2005–2010 NHANES. Additionally, women in the highest tertile of triclosan concentration had elevated prevalence of osteoporosis compared with women in the lowest tertile (Cai et al., 2019).

The developing fetus may be particularly susceptible to endocrine-disrupting chemicals because many of them, including environmental phenols, cross the placenta (Balakrishnan et al., 2010; Schönfelder et al., 2002). Further, given their abilities to disrupt key hormones involved in ossification (i.e., bone formation) and remodeling/mineralization, such as estrogen and thyroid stimulating hormone (Aker et al., 2019; Delitala et al., 2020; Versonnen et al., 2003; Völkel et al., 2002), fetal exposure to environmental phenols may impact skeletal health in later life. Despite this, we are aware of only one epidemiologic study focused on gestational exposures to environmental phenols and bone health in children (van Zwol-Janssens et al., 2020). Among 1,362 offspring enrolled in the Generation R cohort, no associations were observed between maternal urinary bisphenol A (BPA) concentrations in the first, second, or third trimester and children’s whole body aBMD at age 6 or 10 years (van Zwol-Janssens et al., 2020). However, no population-based studies of children have assessed relations of other phenolic compounds such as benzophenone-3, triclosan, and 2,5-dichlorophenol with bone health in children, nor has any study examined phenol mixtures, and no studies have evaluated other skeletal sites.

Our goal was to examine associations of maternal urinary concentrations of four phenolic compounds (benzophenone-3, BPA, 2,5-dichlorophenol, triclosan) during pregnancy with bone mineral content (BMC) and aBMD at six skeletal sites among adolescents in the Health Outcomes and Measures of the Environment (HOME) Study. We also evaluated effect measure modification by child’s sex and estimated effects of the environmental phenol mixture on bone health outcomes.

Material and methods

Study population

We used data from the HOME Study, a prospective pregnancy and birth cohort study conducted in greater Cincinnati, Ohio from March 2003–January 2006. Detailed information regarding this cohort has been described previously (Braun et al., 2020; Braun et al., 2017). Pregnant women were eligible if they were aged 18 years or older; HIV negative; not receiving seizure, thyroid or chemotherapy/radiation medications; and living in a home built prior to 1978. Of the 1263 eligible participants, 468 were initially enrolled and 398 delivered live-born singleton infants (389 remained enrolled until delivery, 9 dropped out prior to delivery but re-enrolled at a later visit). In this study, we include 223 singleton children with at least one maternal urinary environmental phenol measure during pregnancy and bone outcome measurements at age 12 years.

The institutional review boards (IRBs) of Cincinnati Children’s Hospital Medical Center (CCHMC), and the participating hospitals, reviewed the study. The Centers for Disease Control and Prevention (CDC) deferred to CCHMC IRB as the IRB of record. Participants provided written informed consent. At the 12-year follow-up visit, children also provided informed assent.

Urinary biomarker quantification

Urine samples were collected in polyethylene containers and stored at −20 °C before shipping them overnight on dry ice to the CDC Division of Laboratory Sciences. We quantified concentrations of benzophenone-3, BPA, 2,5-dichlorophenol, and triclosan (hereafter referred to collectively as “environmental phenols”) in maternal urine samples collected at 16 weeks gestation (range: 11.3–21.4) and 26 weeks gestation (range: 21.6–34.6) using high-performance liquid chromatography–isotope-dilution tandem mass spectrometry (Ye et al., 2005a). We quantified at least one environmental phenol biomarker for 222 women at the 16-week visit and 207 women at the 26-week visit. One urine sample collected at the 16-week visit did not have a quantifiable creatinine concentration and was excluded from further analyses. Creatinine was measured by an enzyme reaction using a Roche Hitachi 912 chemistry analyzer (Roche Hitachi, Basel, Switzerland). Additional methodological details regarding the quantification of environmental phenols have been published previously (Ye et al., 2005a, b).

Outcome assessment

During the 12-year follow-up visit, trained research staff measured children’s standing height to the nearest 0.1 cm, in triplicate, with an Ayrton Stadiometer Model S100 (Prior Lake, MN). Technicians performed dual energy x-ray absorptiometry (DXA) scans of the whole-body, lumbar spine, hip, and radius with a Hologic Horizon densitometer (Marlborough, MA). We assessed the long-term calibration stability of our DXA scanner by daily scanning of the Hologic anthropomorphic spine phantom. Scans were analyzed using Apex 5.5 software to estimate BMC (g) and areal BMD (aBMD; g/cm2) = BMC (g) / projected area (cm2) for the whole body (less head), total hip, femoral neck, 1/3rd distal radius, ultra-distal radius, and lumbar spine. We excluded the head from whole body measures since the proportion of BMC contained in the skull varies relative to a child’s body size in an inconsistent manner (Taylor et al., 1997). Whereas BMC is a measure of bone mass, BMD is a measure of bone density, and is less affected by bone size (Zemel et al., 2010). We also calculated spine bone mineral apparent density (BMAD = BMC/bone area1.5) as an estimated measure of spine volumetric BMD (g/cm3) not affected by height (Kindler et al., 2019). For all skeletal sites, we calculated Z-scores using reference ranges from the Bone Mineral Density in Childhood Study (Kindler et al., 2020a; Kindler et al., 2019; Zemel et al., 2011). We calculated height-for-age adjusted age-, sex-, and race-specific whole body (excluding head), total hip, femoral neck, and 1/3rd distal radius BMC and aBMD Z-scores as well as lumbar spine BMC Z-scores. Because DXA provides 2-dimensional scans of bone, it does not account for bone depth, and therefore resulting BMC and BMD Z-scores may be confounded due to short or tall stature. We used height-for-age Z-scores to account for this artifact (Zemel et al., 2010). We also calculated age-, sex-, and race-specific ultra-distal radius aBMD and spine BMAD Z-scores, which were not height-for-age adjusted as these outcomes are weakly correlated with height-for-age (Kindler et al., 2020b; Kindler et al., 2019).

Covariates

We identified and selected covariates for our adjusted regression models based on a directed acyclic graph (DAG) (Supplemental Material Figure S1). Maternal characteristics included race and ethnicity, mid-pregnancy body mass index (BMI), height, household income level, age at delivery, prenatal vitamin use, average maternal blood lead concentrations during pregnancy, average serum cotinine concentrations during pregnancy, and self-reported frequency of fruit and vegetable consumption during pregnancy (≥ 4 days per week vs. < 4 days per week). We also adjusted for child’s age in months at follow-up and sex assigned at birth. We collected sociodemographic characteristics using standardized, computer-assisted interviews and medical chart reviews by trained research assistants. Lead was measured via inductively coupled plasma mass spectrometry (Jones et al., 2017) in whole blood samples collected at up to three time points (16 weeks gestation, 26 weeks gestation, and delivery) and stored at −80°C until shipment on dry ice to the CDC for analysis. We adjusted for lead exposure using the average of maternal blood lead concentrations as a measure of gestational lead exposure because the HOME Study was initially designed as a randomized trial of lead and injury hazard controls to reduce children’s blood lead levels (Braun et al., 2017).

Statistical methods

We singly-imputed biomarker concentrations below the limit of detection (LOD) using LOD/2 (Hornung and Reed, 1990). We calculated Spearman’s rank correlations between environmental phenol biomarkers using average biomarker concentrations during pregnancy, and also using concentrations from individual timepoints during pregnancy. After visually examining distributions, we log2-transformed concentration to reduce the influence of outliers and because of positive-skewness of their distributions. We applied covariate-adjusted creatinine standardization to adjust for the influence of urine dilution on environmental phenol concentrations (O’Brien et al., 2016) as described in detail previously (Kuiper et al., 2022). Briefly, we fitted a linear model of urinary creatinine values (at 16 weeks or 26 weeks) based on maternal age, maternal mid-pregnancy BMI, maternal height, maternal race/ethnicity, household income, hypertension status, and gestational diabetes status; then, we multiplied each biomarker concentration by the ratio of fitted to observed creatinine values, resulting in covariate-adjusted creatinine-standardized biomarker concentrations.

We assessed associations between creatinine-standardized urinary environmental phenol biomarker concentrations with bone outcome Z-scores by constructing linear regression models with and without covariates. Adjusted models included midpoint of reported household income range category (continuous), age at delivery (continuous), prenatal vitamin use (dichotomous: ever, never), average maternal lead concentration (continuous), self-reported frequency of fruit and vegetable consumption during pregnancy (dichotomous: ≥ 4 days per week, < 4 days per week), self-reported maternal race and/or ethnicity (dichotomous: non-Hispanic White; non-Hispanic Black or any other race or ethnicity), maternal mid-pregnancy BMI (continuous), maternal height (cm; continuous), child’s sex assigned at birth (dichotomous: male, female), and child age at follow-up (continuous). Our primary models used the average of available log2-transformed concentrations from 16- and 26-weeks gestation because repeated measures can reduce exposure measurement error for non-persistent chemicals (Calafat et al., 2015). For this averaged variable, we used a single concentration if only one time point was available (n = 16 with only 16-week and n = 1 with only 26-week concentrations). As an exploratory analysis, we evaluated potential periods of heightened susceptibility to exposure by estimating associations for each timepoint (16- or 26-weeks of gestation) in separate linear regression models. We used an alpha level of 0.05 for hypothesis testing and full information maximum likelihood to account for missing covariate information.

Environmental phenols, which are endocrine disrupting chemicals, might have sexually-dimorphic relations with bone mineral accrual and strength. Thus, we evaluated sex as an effect measure modifier by stratifying models by child’s sex and calculating p-values for the difference in sex-specific estimates via two-sample Z-tests (Buckley et al., 2017). For analyses of effect measure modification, we used an alpha level of 0.1 as indication of effect measure modification by child’s sex. While there is no standard alpha threshold for evaluation of effect measure modification, we chose a less conservative value since we were likely underpowered to detect underlying sex-differences in associations.

We used quantile-based g-computation to estimate the overall effect of the environmental phenol mixture and individual contributions of each biomarker in the mixture to the overall effect. This method categorizes the continuous biomarker concentrations into quantiles to estimate the overall effect of increasing all biomarkers by one quantile and defines weights for each biomarker as a measure of their contributions to the overall associations with bone outcomes (Keil et al., 2020). With this model, we estimated 1) differences (95% confidence interval, CI) in outcome Z-score per quartile increase in all environmental phenols (ψ), 2) differences in bone outcome Z-score per quartile increase in environmental phenols with estimated effects in either the positive direction or the negative direction (i.e., directional scaled effects), and 3) weights for the percent contribution of each environmental phenol to the overall mixture effect. We also assessed the potential for effect measure modification of the overall mixture effect by child’s sex via inclusion of a product term between ψ and child’s sex. For these mixture models, we restricted analysis to participants with all biomarkers quantified (n = 212), and we accounted for missing covariate data using a single stochastic imputation to address potential bias due to missing covariate data. We fit overall models using the R package qgcomp and obtained sex-specific estimates using qgcompint.

We conducted all single-biomarker analyses using Stata (version 15.1, College Station, TX: StataCorp LP) and all mixtures analyses using R (version 4.0.2, R Core Team 2020).

Results

Study Sample Characteristics

Most mothers were between 25 and 35 years of age (60%), more than half were non-Hispanic White (57%), and 59% had an annual household income more than $40,000 at baseline (Table 1). We observed no systematic differences in sociodemographics between the study sample (n = 223) and full sample of mothers with singleton pregnancies (n = 398) (Table 1). The average child age at follow-up was 12.4 (0.7) years (Table 2). Geometric mean maternal urinary concentrations were 23.0 ng/mL for benzophenone-3, 2.1 ng/mL for BPA, 8.0 ng/mL for 2,5-dichlorophenol, and 19 ng/mL for triclosan (Table 3). Spearman’s rank correlations between environmental phenols were low for most pairwise combinations, except for 2,5-dichlorophenol and BPA (ρ = 0.42) (Supplemental Material Figure S2). Correlations between concentrations of the same biomarker measured at 16- and 26-weeks of gestation ranged from 0.27 for BPA to 0.71 for 2,5-dichlorophenol (Supplemental Material Figure S3).

Table 1.

Baseline characteristics of HOME Study participants included in the study sample and full sample. All statistics are n (%) unless otherwise stated.

Variables Study sample,
n = 223a 		Full sample,
n = 398
Maternal age
 < 25 years 59 (26) 100 (25)
 25 – 35 years 133 (60) 236 (59)
 > 35 years 31 (14) 62 (16)
Maternal mid-pregnancy BMI (kg/m2)
 < 18.5 (underweight) 3 (1) 3 (1)
 18.5 to < 25 (normal weight) 85 (41) 153 (41)
 25 to < 30 (overweight) 69 (33) 125 (34)
 ≥ 30 (obese) 51 (25) 88 (24)
 Missing 15 29
Maternal height (cm)
 < 152.4 (< 5 feet) 7 (3) 15 (4)
 152.4 to < 167.6 (≥ 5 feet < 5.5 feet) 133 (64) 230 (62)
 167.6 to < 182.9 (≥ 5.5 feet < 6 feet) 64 (31) 120 (33)
 ≥ 182.9 (≥ 6 feet) 4 (2) 4 (1)
 Missing 15 29
Maternal race/ethnicity
 Non-Hispanic White 127 (57) 241 (61)
 Non-Hispanic Black 84 (38) 129 (33)
 Other 12 (5) 25 (6)
 Missing 0 3
Household income
 < $20,000 57 (26) 88 (22)
 $20,000 – < $40,000 35 (16) 67 (17)
 $40,000 – < $80,000 77 (35) 140 (35)
 ≥ $80,000 54 (24) 103 (26)
Parity
 Nulliparous 90 (42) 171 (44)
 Primiparous 72 (33) 124 (32)
 Multiparous 54 (25) 92 (24)
 Missing 7 11
Prenatal vitamin use
 Never used 27 (13) 46 (12)
 Ever used 188 (87) 340 (88)
 Missing 8 12
Fruit and vegetable consumption during pregnancy
 < 4 days per week 50 (23) 81 (21)
 ≥ 4 days per week 165 (77) 305 (79)
 Missing 8 12
Maternal blood lead concentration during pregnancy (μg/dL)b 3
 < 0.50 39 (18) 59 (15)
 ≥ 0.50 – < 1.00 154 (69) 283 (71)
 ≥ 1.00 30 (13) 56 (14)
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Abbreviations: BMI = body mass index; cm = centimeter; dL = deciliter; mL = milliliter; ng = nanogram; μg = microgram

a

Participants with at least one urinary environmental phenol biomarker quantified during gestation

b

Average of up to three timepoints: 16 weeks gestation, 26 weeks gestation, and delivery

Table 2.

Characteristics of HOME Study participants in the study sample at follow-up. Statistics are mean (SD) unless otherwise stated.

Variable Overall
(n=223)		 Males
(n=99)		 Females
(n=124)
Age at visit (years) 12.4 (0.70) 12.4 (0.74) 12.4 (0.67)
Pubertal stagea (n, %)
 1 23 (10) 17 (17) 6 (5)
 2 56 (25) 31 (31) 25 (20)
 3 65 (29) 26 (26) 39 (32)
 4 45 (20) 16 (16) 29 (24)
 5 33 (15) 9 (9) 24 (20)
 Missing 1 0 1
BMC measures (g)
 Whole body (excluding head) 1228 (325) 1174 (328) 1272 (318)
 Total hip 25.2 (6.69) 25.6 (7.62) 24.8 (5.86)
 Femoral neck 3.69 (0.78) 3.68 (0.77) 3.70 (0.80)
 1/3rd Distal radius 1.45 (0.28) 1.42 (0.27) 1.47 (0.28)
 Spine 38.9 (11.8) 35.7 (11.1) 41.5 (11.8)
BMC Z-scoreb
 Whole body (excluding head) −0.05 (0.82) −0.16 (0.78) 0.04 (0.85)
 Total hip −0.08 (0.92) −0.12 (0.94) −0.06 (0.90)
 Femoral neck 0.23 (0.97) 0.13 (0.93) 0.31 (0.99)
 1/3rd Distal radius 0.10 (0.98) −0.02 (0.93) 0.19 (1.01)
 Spine 0.09 (0.86) 0.06 (0.87) 0.12 (0.85)
aBMD measures (g/cm2)
 Whole body (excluding head) 0.826 (0.094) 0.809 (0.092) 0.841 (0.093)
 Total hip 0.853 (0.137) 0.838 (0.130) 0.866 (0.142)
 Femoral neck 0.798 (0.136) 0.782 (0.122) 0.810 (0.145)
 1/3rd Distal radius 0.603 (0.064) 0.592 (0.062) 0.612 (0.063)
 Ultra-distal radius 0.350 (0.056) 0.347 (0.047) 0.352 (0.063)
 Spine (BMAD, g/cm3) 0.228 (0.036) 0.209 (0.026) 0.244 (0.036)
aBMD Z-scoreb
 Whole body (excluding head) −0.38 (0.90) −0.43 (0.89) −0.34 (0.92)
 Total hip −0.02 (1.07) −0.06 (1.10) 0.02 (1.05)
 Femoral neck −0.02 (1.07) −0.10 (1.10) 0.05 (1.04)
 1/3rd Distal radius 0.23 (0.96) 0.22 (0.91) 0.23 (1.00)
 Ultra-distal radiusc 0.28 (1.17) 0.18 (1.00) 0.36 (1.29)
 Spine (BMAD)c 0.33 (1.02) 0.32 (1.02) 0.34 (1.02)
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Abbreviations: cm = centimeter; g = grams; kg = kilograms; aBMD = areal bone mineral density; BMAD = bone mineral apparent density; BMC = bone mineral content

a

Tanner stage self-assessment

b

Height-for-age adjusted age-, sex-, and population ancestry-specific Z-scores

c

Age-, sex-, and population ancestry-specific Z-score

Table 3.

Covariate-adjusted, creatinine-standardizeda maternal gestational urinary environmental phenol concentrations (ng/mL), 2003–2006.

Visit Sample size LOD N (%) > LODb GM (GSD) 25th Percentile 50th Percentile 75th percentile 95th percentile
Benzophenone-3 16 Weeks 190 0.4 188 (99) 22.4 (6.3) 5.63 16.9 72.5 703
26 Weeks 197 0.4 196 (99) 23.1 (6.1) 5.90 15.7 76.4 646
Averagec 215 NA NA 23.0 (5.3) 5.95 18.2 70.3 569
BPA 16 Weeks 221 0.4 203 (92) 2.14 (2.7) 1.06 1.91 3.79 15.5
26 Weeks 207 0.4 189 (91) 1.98 (2.7) 1.01 1.68 3.08 9.13
Averagec 223 NA NA 2.10 (2.2) 1.15 1.92 3.34 7.15
2,5-Dichlorophenol 16 Weeks 217 0.2 216 (99) 9.03 (4.5) 3.12 6.41 22.0 193
26 Weeks 177 0.2 176 (99) 5.84 (4.7) 2.01 4.16 14.0 135
Averagec 219 NA NA 7.99 (4.2) 2.71 5.71 20.3 136
Triclosan 16 Weeks 218 2.3 206 (95) 21.8 (4.8) 6.26 17.7 57.6 459
26 Weeks 204 2.3 178 (87) 15.8 (4.7) 5.10 12.5 38.3 447
Averagec 222 NA NA 18.7 (3.8) 6.79 16.9 42.1 237
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Abbreviations: BPA = bisphenol A; GM = geometric mean; GSD = geometric standard deviation; LOD = limit of detection; NA = not applicable; ng/mL = nanogram per milliliter

a

Raw analyte concentrations were multiplied by the ratio of fitted to observed creatinine concentration. Fitted creatinine was estimated from a linear regression model that included maternal age, maternal mid-pregnancy BMI, maternal height, maternal race/ethnicity, household income, hypertension status, and gestational diabetes status.

b

Concentrations < LOD replaced by LOD/√2.

c

Average of 16- and 26-week measures or a single measure if only one is available.

Multivariable Linear Regression

In unadjusted (Supplemental Material Table S1) and adjusted (Supplemental Material Table S3) analyses of the overall study sample, a doubling in average 2,5-dichlorophenol concentration was associated with greater BMC and aBMD Z-scores for most bone sites. Associations were greatest in magnitude for 2,5-dichlorophenol with aBMD (β = 0.09; 95% CI: 0.02, 0.17) and BMC (β = 0.09; 95% CI: 0.02, 0.17) at the 1/3rd distal radius (Figure 1; Supplemental Material Table S3). Associations with other environmental phenols were generally null, though associations for BPA and triclosan were often positively associated with BMC and aBMD Z-scores but with wide confidence intervals (Supplemental Material Table S3). In our exploratory analysis of periods of susceptibility, all associations were comparable for concentrations measured during 16- and 26-weeks of gestation (Supplemental Material Table S4).

Figure 1.

Figure 1.

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Adjusted associations of average covariate-adjusted, creatinine-standardizeda maternal gestational urinary 2,5-dichlorophenol concentration (ng/mL) with BMD Z-scores. Difference (95% confidence interval) in outcome Z-score per doubling in environmental phenol concentration estimated in separate linear regression models adjusted for maternal age at delivery, mid-gestation BMI, height, race/ethnicity, household income, prenatal vitamin use, average blood lead concentration during pregnancy, average serum cotinine concentration during pregnancy, fruit and vegetable consumption during pregnancy, and age at follow-up. Overall models additionally adjusted for child’s sex. All outcomes are aBMD Z-scores, except spine which is BMAD Z-score. aBMD, areal bone mineral density; BMAD, bone mineral apparent density. a Urinary dilution was accounted for using covariate-adjusted, creatinine-standardization. Raw analyte concentrations were multiplied by the ratio of fitted to observed creatinine concentration. Fitted creatinine was estimated from a linear regression model that included maternal age, maternal mid-pregnancy BMI, maternal height, maternal race/ethnicity, household income, hypertension status, and gestational diabetes status.

We found limited evidence of effect measure modification by child’s sex in unadjusted (Supplemental Material Tables S1 and S2) and adjusted (Supplemental Material Table S5) analyses. Only 2,5-dichlorophenol and triclosan showed evidence of differential associations between sexes, and only at the 1/3rd distal radius and total hip, respectively. A doubling of average 2,5-dichlorophenol concentration was associated with higher 1/3rd distal radius BMC Z-scores among females (β = 0.16; 95% CI: 0.06, 0.26), but not males (β = 0.02, 95% CI = −0.08, 0.13) (Supplemental Material Table S5). Conversely, a doubling in average triclosan concentration was associated with lower total hip aBMD (β = −0.05; 95% CI: −0.13, 0.03) and BMC (β = −0.06; 95% CI: −0.13, 0.02) Z-scores among females, whereas among males triclosan was associated with higher aBMD (β = 0.07; 95% CI: −0.02, 0.16) Z-scores (Supplemental Material Table S5).

Quantile g-computation

Similar to the single-biomarker models, we observed the strongest association of the environmental phenol mixture with aBMD and BMC at the 1/3rd distal radius. For the overall mixture effect (ψ), a quartile increase in the mixture was associated with a 0.16 (95% CI: −0.04, 0.37) greater aBMD and 0.23 (95% CI: 0.02, 0.44) greater BMC Z-score at the 1/3rd distal radius (Table 4). Associations of the environmental phenol mixture with aBMD and BMC were weaker and not statistically significant for other skeletal sites (Table 4). While associations with BMC and aBMD were generally comparable between males and females, the contributions of individual biomarkers to the overall mixture effect often differed by sex (Supplemental Material Table S6 and Table S7). For example, among males, the overall positive association for the mixture with 1/3rd distal radius aBMD was driven primarily by benzophenone-3 (positive weight = 56.2%); whereas among females, the overall positive mixture effect was driven by 2,5-dichlorophenol (positive weight = 100%) (Supplemental Material Table S6).

Table 4.

Adjusted associations of the maternal urinary environmental phenol mixture with bone outcome Z-scores at age 12 years estimated using quantile g-computation, overall and by child sex.

Outcome Overall
(n = 212)		 Males
(n = 93)		 Females
(n = 119)
BMD Z-score
 Whole-body aBMD 0.11 (−0.06, 0.29) 0.07 (−0.21, 0.35) 0.14 (−0.08, 0.36)
 Total hip aBMD 0.07 (−0.13, 0.28) 0.12 (−0.23, 0.47) 0.05 (−0.20, 0.30)
 Femoral neck aBMD 0.05 (−0.15, 0.25) 0.09 (−0.23, 0.40) 0.04 (−0.20, 0.28)
 1/3rd Distal radius aBMD 0.16 (−0.04, 0.37) 0.21 (−0.11, 0.52) 0.13 (−0.11, 0.37)
 Ultra-distal radius aBMD 0.03 (−0.22, 0.25) 0.02 (−0.33, 0.37) 0.06 (−0.23, 0.36)
 Spine BMAD −0.03 (−0.24, 0.18) −0.13 (−0.42, 0.17) 0.03 (−0.25, 0.31)
BMC Z-score
 Whole-body 0.08 (−0.08, 0.23) 0.09 (−0.16, 0.34) 0.07 (−0.12, 0.26)
 Total hip 0.06 (−0.12, 0.24) 0.16 (−0.12, 0.44) −0.01 (−0.23, 0.22)
 Femoral neck 0.12 (−0.07, 0.31) 0.13 (−0.16, 0.42) 0.11 (−0.13, 0.35)
 1/3rd Distal radius 0.23 (0.02, 0.44) 0.24 (−0.10, 0.58) 0.22 (−0.04, 0.47)
 Spine 0.07 (−0.10, 0.24) −0.08 (−0.36, 0.20) 0.16 (−0.05, 0.38)
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Note: Difference (95% confidence interval) in outcome Z-score per quartile increase in all average covariate-adjusted, creatinine-standardizeda maternal gestational urinary environmental phenols estimated using quantile g-computation. Adjusted for maternal age at delivery, mid-gestation BMI, height, race/ethnicity, household income, prenatal vitamin use, average blood lead concentration during pregnancy, average serum cotinine concentration during pregnancy, fruit and vegetable consumption during pregnancy, and child’s age at follow-up. Overall models were additionally adjusted for child’s sex. Missing covariate information accounted for using single stochastic imputation by chained equations. BMC, bone mineral content; aBMD, areal bone mineral density; BMAD, bone mineral apparent density.

a

Raw analyte concentrations were multiplied by the ratio of fitted to observed creatinine concentration. Fitted creatinine was estimated from a linear regression model that included maternal age, maternal mid-pregnancy BMI, maternal height, maternal race/ethnicity, household income, hypertension status, and gestational diabetes status.

Discussion

In this prospective cohort, we observed mostly null associations of urinary environmental phenol concentrations during fetal development with BMC and aBMD Z-scores at six skeletal sites at age 12 years. However, we did find that higher concentrations of 2,5-dichlorophenol and the environmental phenol mixture were associated with higher BMC and aBMD Z-scores, particularly at the 1/3rd distal radius and among females. The mixture effect was primarily driven by benzophenone-3 among males and 2,5-dichlorophenol among females. Magnitudes of the mixture associations were as high as 0.24 standard deviation per quartile increase in all environmental phenols. To place this into context, vigorous physical activity (each additional hour per day) was associated with a 0.05 greater whole body (less head) BMC and total hip aBMD Z-score in the Bone Mineral Density in Childhood Study (Mitchell et al., 2016). Additionally, a standard deviation decrease in either BMC or aBMD has been associated with a 30–40% increase in odds of forearm fracture in children (Kalkwarf et al., 2011).

Compared with other studies of gestational environmental phenols exposures during the same general time-period, median uncorrected (i.e., not adjusted for urinary dilution) average pregnancy concentrations in our study were similar for BPA (1.90 ng/mL) and triclosan (15.1 ng/mL) (Berger et al., 2021; Buckley et al., 2018; van Zwol-Janssens et al., 2020; Wolff et al., 2008). The median concentration of 2,5-dichlorophenol (6.15 ng/mL) was comparable to those reported in a French cohort of mother-child dyads (EDEN cohort) (Philippat et al., 2014) but also lower than those reported in the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) study- (Berger et al., 2021) and the Children’s Environmental Health Study (Wolff et al., 2008). The median concentration of benzophenone-3 (22.4 ng/mL) was both lower (Wolff et al., 2008) and higher (Berger et al., 2021; Philippat et al., 2014) compared to these other studies.

To date, only one epidemiologic study assessed the associations between fetal exposure to environmental phenols and child bone health (van Zwol-Janssens et al., 2020). Among 1,362 participants of the Generation R Study, maternal urinary BPA concentrations in pregnant women were not associated with their children’s BMD or area-adjusted BMC at age 6 and 10 years, similar to null findings observed in our study. Importantly, van Zwol-Janssens et al. only examined exposure to bisphenols, and no previous studies have explored associations of maternal urinary 2,5-dichlorophenol, triclosan, and benzophenone-3 concentrations or their mixture with child bone health.

2,5-dichlorophenol has been used as an intermediate in dye production, pharmaceuticals, and agricultural products (Ye et al., 2005b) and is also a metabolite of paradichlorobenzene (also known as 1,4-dichlorobenzene), a disinfectant chemical used in products such as mothballs and deodorizing agents and with demonstrated clastogenic activity in vitro (Mohtashamipur et al., 1987). In our study, we observed a positive association between 2,5-dichlorophenol and 1/3rd distal radius bone mineral content and density among females, but not males, at age 12 years. We are not aware of any other studies evaluating associations with gestational urinary 2,5-dichlorophenol concentrations. This sex-difference might be due to sexually-dimorphic endocrine-disrupting actions of 2,5-dichlorophenol (Brouwer et al., 1999; Völkel et al., 2002), potentially by affecting pubertal timing and development (Bigambo et al., 2020). A previous systematic review and meta-analysis of four environmental phenols in 4,737 children from nine studies, showed that 2,5-dichlorophenol was the only chemical associated with the risk of early puberty (OR: 1.13; 95% CI: 1.06, 1.20) (Bigambo et al., 2020). Relatedly, three prior studies have found that greater urinary childhood 2,5-dichlorophenol concentrations were associated with earlier menarche among girls (Binder et al., 2018; Buttke Danielle et al., 2012; Wolff et al., 2017). Mechanisms of 2,5-dichlorophenol may also be independent of puberty; 2,5-dichlorophenol exhibits estrogenic activity in vitro (Versonnen et al., 2003), and estrogen regulates bone formation and inhibit bone resorption (Khosla et al., 2012). Moreover, short-term exposure to estrogen during fetal development is positively associated with peak bone mass in animal models (Migliaccio et al., 1996; Migliaccio et al., 2000).

Experimental studies have shown that gestational exposures to BPA may adversely affect bone development (Huang et al., 2021; Hwang et al., 2013; Kanno et al., 2004; Lejonklou et al., 2016; Lind et al., 2019; Pelch et al., 2012; Toda et al., 2002). However, our study and van Zwol Janssen et al. (2020) did not find evidence to support an association. Similarly, four prior epidemiologic studies have investigated associations of BPA exposure on BMD among adult populations, with mostly null findings (Gu et al., 2022; Kim et al., 2012; Wang et al., 2020; Zhao et al., 2012).

In a study investigating the effect of triclosan on sea urchin embryos, exposure to triclosan (1 μM) decreased the expression of several genes related to skeletal development, including bone morphogenic proteins, a group of growth factors that are critical to chondrogenesis and osteogenesis (Hwang et al., 2017). In our study, though associations were imprecise, we observed sex differences in associations of triclosan with total hip bone mineral content and density. Specifically, higher triclosan concentrations were associated with lower total hip aBMD and BMC Z-scores among females but lower Z-scores among males. We are not aware of other epidemiologic studies evaluating gestational exposures to triclosan with offspring skeletal development, though two cross-sectional studies of adults observed that greater triclosan exposure was associated with lower BMD in the total femur, intertrochanteric region of the femur, femoral neck, and lumbar spine as well as greater odds of osteoporosis, among females (Cai et al., 2019; Wang et al., 2020).

As with 2,5-dichlorophenol and triclosan, no studies have evaluated the impact of gestational exposure to benzophenone-3, an ultraviolet filter used in sunscreen and other products, on offspring bone outcomes. We are aware of only one experimental study of benzophenone-3 and bone relevant outcomes, an in vitro study that evaluated the effects of benzophenone-3 exposure (0.1 nM to 10μM) on rat calvarial osteoblast-like cells (Ziolkowska et al., 2006). This study found significantly reduced proliferative activity among cells treated with the highest dose of benzophenone-3; though, this was suspected to be from cytotoxicity independent from endocrine-disrupting mechanisms (Ziolkowska et al., 2006).

Since fractures in children and adolescents most frequently occur at the forearm (containing two long bones, the ulna and the radius), our findings suggests that fetal exposure to certain environmental phenols could affect fracture risk (Jones et al., 2002; Kalkwarf et al., 2011; Korup et al., 2022). Still, greater bone content and density does not necessarily equate to greater bone strength. Additionally, any deviations from normal-for-age bone development may be considered as potentially adverse for health.

Lack of consistent associations across skeletal sites in our study may reflect differences in microarchitecture, composition of bone (i.e., dense cortical vs. spongy trabecular bone), and distribution of mineral within the bone at these sites. As such, environmental chemical exposures may not necessarily be expected to exert effects equally on all skeletal sites. In our study, 2,5-dichlorophenol was almost universally associated with higher bone mineral content and density at all skeletal sites. This suggests that perhaps its parent compound, paradichlorobenzene, is able to affect both cortical and trabecular bone. However, DXA is not able to differentiate bone composition and would instead require the use of peripheral quantitative computed tomography. Taken together, we found little evidence that gestational exposure to environmental phenols affected skeletal development in offspring.

This study contributes to the few studies of environmental phenols and bone health in early adolescence. Our study has several strengths, including the measurement of BMC and BMD at multiple skeletal sites, adjustment for many potential confounders, and consideration of chemical mixtures. We quantified phenols concentrations in two spot urine samples (16 weeks and 26 weeks gestation). Environmental phenols have short biological half-lives (e.g., < 24 hours) (Völkel et al., 2002; Weatherly and Gosse, 2017) and reliance on only two urinary measurements during pregnancy may result in bias from exposure misclassification (Perrier et al., 2016). However, using the average of available concentrations during pregnancy may better approximate of usual exposure to these compounds (or their parent compounds) during gestation. Additionally, while our study focused on frequently detected environmental phenols (or their metabolites), other compounds may impact bone development. Future studies should consider a wider array of phenolic compounds, especially increasingly utilized replacements for legacy compounds, e.g., bisphenol F and bisphenol S (Lehmler et al., 2018; van Zwol-Janssens et al., 2020). Our relatively modest sample size of 223 mother-and-child pairs limited our statistical power, especially for sex-specific associations. Additionally, we conducted multiple hypothesis tests given the array of exposures and outcomes evaluated. As such, our findings could be due to chance, though we have focused on patterns of associations, broadly, as opposed to individual statistical tests. While there was loss to follow-up in our cohort, baseline characteristics of sample participants were similar to the full cohort. Lastly, childhood exposures and other postnatal factors may also be important for early adolescent bone health. Future studies should assess exposures occurring across childhood and possible modification by postnatal factors, e.g., physical activity, diet, and breastfeeding.

Conclusions

In this prospective study, gestational environmental phenol exposures were not consistently associated with measures of early adolescent bone health. 1,4-paradichlorobenzene (the precursor of 2,5-dichlorophenol) and the environmental phenol mixture were associated with greater distal radius bone mineral content and density at age 12 years, especially among females. Yet, further studies on exposures and bone outcomes, particularly those utilizing methods capable of differentiating cortical and trabecular bone, are needed to confirm these findings and further determine effects of 1,4-paradichlorobenzene on cortical and trabecular bone strength and microarchitecture.

Supplementary Material

1

Highlights.

  • Gestational urinary 2,5-dichlorophenol concentrations were positively associated with distal radius bone mineral density at age 12 years, especially among females.

  • Gestational urinary benzophenone-3, bisphenol A, and triclosan were not significantly associated with bone mineral measurements.

  • The environmental phenol mixture was positively associated with distal radius bone mineral content in quantile g-computation models.

Acknowledgments

This work was supported by grants from the National Institutes of Health Center for Advancing Translational Sciences Clinical Translational Science Award program (UL1TR001425), National Institute of Environmental Health Sciences of the National Institutes of Health (R01ES033252, R01ES030078, R01ES025214, R01ES020349, R01 ES024381, R01ES027224, R01ES028277, P01ES011261) and U.S. Environmental Protection Agency (P01R829389). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. We are grateful to the participants for the time they have given to the HOME Study.

Declaration of competing financial interests

Dr. Braun and his institution were financially compensated for his services as an expert witness for plaintiffs in litigation related to PFAS-contaminated drinking water. Dr. Lanphear served as an expert witness in cases related to childhood lead poisoning, but he was not personally compensated. The other authors declare they have no actual or potential competing financial interests.

Abbreviations

BPA

bisphenol A

BMD

Bone mineral density

BMI

Bone Mass Index

CDC

The Centers for Disease Control and Prevention

DAG

Directed acyclic graph

DXA

Dual-energy X-ray absorptiometry

GM

Geometric Mean

HOME

Health Outcomes and Measures of the Environment

NHANES

National Health and Nutrition Examination Survey

Footnotes

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Disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. Use of trade names is for identification only and does not imply endorsement by the CDC, the Public Health Service, or the US Department of Health and Human Services.

Data sharing

Data from the HOME Study is available upon request. The HOME Study principal investigators have actively engaged in collaborative data-sharing projects. We welcome new collaborations with other investigators. Investigators interested in HOME Study data can explore options at the following location: https://homestudy.research.cchmc.org/ and use the available link to contact the investigators to discuss collaborative opportunities. The Data Sharing Committee meets regularly to review proposed research projects and ensure they do not overlap with extant projects and are an efficient use of scarce resources (e.g., biological samples). Funds to support staff efforts in the assembly of data sets are required.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1858427-supplement-1.docx (1.3MB, docx)

Data Availability Statement

Data from the HOME Study is available upon request. The HOME Study principal investigators have actively engaged in collaborative data-sharing projects. We welcome new collaborations with other investigators. Investigators interested in HOME Study data can explore options at the following location: https://homestudy.research.cchmc.org/ and use the available link to contact the investigators to discuss collaborative opportunities. The Data Sharing Committee meets regularly to review proposed research projects and ensure they do not overlap with extant projects and are an efficient use of scarce resources (e.g., biological samples). Funds to support staff efforts in the assembly of data sets are required.

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