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Research Articles August 2016 | Volume 124 | Issue 8

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Children's Health
Environ Health Perspect; DOI:10.1289/ehp.1510065

Relation between in Utero Arsenic Exposure and Birth Outcomes in a Cohort of Mothers and Their Newborns from New Hampshire

Diane Gilbert-Diamond,1,2* Jennifer A. Emond,3* Emily R. Baker,2,4 Susan A. Korrick,2,5,6 and Margaret R. Karagas1,2

Author Affiliations open
1Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA; 2Children’s Environmental Health and Disease Prevention Center at Dartmouth, Hanover, New Hampshire, USA; 3Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA; 4Department of Obstetrics and Gynecology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA; 5Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA; 6Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA

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  • Background: Studies suggest that arsenic exposure influences birth outcomes; however, findings are mixed.

    Objective: We assessed in utero arsenic exposure in relation to birth outcomes and whether maternal prepregnancy weight and infant sex modified the associations.

    Methods: Among 706 mother–infant pairs exposed to low levels of arsenic through drinking water and diet, we assessed in utero arsenic exposure using maternal second-trimester urinary arsenic, maternal prepregnancy weight through self-report, and birth outcomes from medical records.

    Results: Median (interquartile range) of total urinary arsenic [tAs; inorganic arsenic (iAs) + monomethylarsonic acid (MMA) + dimethylarsinic acid (DMA)] was 3.4 μg/L (1.7–6.0). In adjusted linear models, each doubling of tAs was associated with a 0.10-cm decrease (95% CI: –0.19, –0.01) in head circumference. Results were similar for MMA and DMA. Ln(tAs) and ln(DMA) were positively associated with birth length in infant males only; among males, each doubling of tAs was associated with a 0.28-cm increase (95% CI: 0.09, 0.46) in birth length (pinteraction = 0.04). Results were similar for DMA. Additionally, arsenic exposure was inversely related to ponderal index, and associations differed by maternal weight. Each ln(tAs) doubling of tAs was associated with a 0.55-kg/m3 lower (95% CI: –0.82, –0.28, p < 0.001) ponderal index for infants of overweight/obese, but not normal-weight, mothers (pinteraction < 0.01). Finally, there was a significant interaction between maternal weight status, infant sex, and arsenic exposure on birth weight (pinteraction = 0.03). In girls born of overweight/obese mothers, each doubling of tAs was associated with a 62.9-g decrease (95% CI: –111.6, –14.2) in birth weight, though the association was null in the other strata.

    Conclusions: Low-level arsenic exposure may affect fetal growth, and the associations may be modified by maternal weight status and infant sex.

  • Citation: Gilbert-Diamond D, Emond JA, Baker ER, Korrick SA, Karagas MR. 2016. Relation between in utero arsenic exposure and birth outcomes in a cohort of mothers and their newborns from New Hampshire. Environ Health Perspect 124:1299–1307; http://dx.doi.org/10.1289/ehp.1510065

    *These authors contributed equally to this work.

    Address correspondence to D. Gilbert-Diamond, Hinman 7927, Geisel School of Medicine at Dartmouth, Hanover, NH 03755 USA. Telephone: (603) 653-3362. E-mail: Diane.Gilbert-Diamond@Dartmouth.edu

    We thank the study participants and our sources of funding.

    Funding was provided by the National Institutes of Health (NIH) National Institute of Environmental Health Sciences (P42ES007373, P01ES022832, and P42ES004940), the NIH National Institute of General Medical Sciences (P20GM104416), and the U.S. Environmental Protection Agency (RD83544201).

    No funding bodies had any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

    The authors declare they have no actual or potential competing financial interests.

    Received: 10 April 2015
    Revised: 25 August 2015
    Accepted: 12 February 2016
    Published: 8 March 2016

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Introduction

Fetal development is a period marked by rapid cell division, differentiation, and tissue growth and is therefore highly sensitive to the negative effects of toxic exposures. Arsenic is a naturally occurring chemical element found in bedrock and soil and it readily dissolves into surrounding groundwater that may be used for drinking (Smedley and Kinniburgh 2002). There is also growing awareness that people are exposed to arsenic through consumption of rice and other foods (Gilbert-Diamond et al. 2011Meharg et al. 2009). Arsenic crosses the placenta (Concha et al. 1998), and experimental studies suggest that arsenic may have reproductive toxicity (Ahmed et al. 2011Davey et al. 2007Tsang et al. 2012), though the epidemiological evidence relating arsenic exposure to fetal growth has been mixed. Three prospective studies have found negative associations between arsenic exposure biomarkers and birth weight (Claus Henn et al. 2016Laine et al. 2015Rahman et al. 2009Yang et al. 2003), and a third found a suggestive negative association (Hopenhayn et al. 2003). In contrast, two large cross-sectional studies did not find any association between arsenic and birth weight (Kwok et al. 2006Myers et al. 2010). Almost all of these studies were performed in arsenic-endemic regions with generally high water arsenic (e.g., > 50 μg/L), and few studies have examined arsenic–birth outcome relationships in areas with predominantly lower levels of arsenic exposure (e.g., drinking-water arsenic < 10 μg/L).

After ingestion, inorganic arsenic (iAs) is methylated into monomethylarsonic acid (MMAV), which is then reduced to monomethylarsonous acid (MMAIII) (Vahter 2002). In a second methylation step, MMAIII is converted to dimethylarsinic acid (DMAV), which is then reduced to dimethylarsinous acid (DMAIII). This biotransformation of iAs is incomplete and iAs, MMAV, and DMAV are all excreted in the urine (Francesconi et al. 2002Watanabe and Hirano 2013). Although the reduced methylated forms, MMAIII and DMAIII, have also been found in urine of people exposed to high levels of iAs (Mandal et al. 2001Valenzuela et al. 2005), they have not been observed in urine samples from populations exposed to lower levels of arsenic (Lindberg et al. 2006Rivera-Núñez et al. 2012). MMAV and DMAV are generally considered less toxic than iAs (Gebel 2002Moore et al. 1997); however, some animal studies suggest that MMAIII and DMAIII may be even more toxic than iAs (Styblo et al. 2000).

Weight status may affect the efficiency of arsenic metabolism (Gomez-Rubio et al. 2011Li et al. 2008), although findings have been mixed. For example, a study among 624 adult women in the southern United States and northern Mexico (Gomez-Rubio et al. 2011) where 68.9% of women were overweight or obese, documented that the efficiency of arsenic metabolism increased with maternal body mass index (BMI). In contrast, a study among 442 Bangladeshi pregnant women (Li et al. 2008) documented no statistical differences in arsenic methylation rates by maternal weight status during the first trimester; however, only 5.4% of the women in that sample were overweight (BMI ≥ 25 kg/m2). Given the importance of maternal weight status in fetal growth (Hull et al. 2008King 2006Sewell et al. 2006Wu et al. 2004) and maternal weight status’s potential role in arsenic metabolism, it is important to understand if maternal weight status modifies arsenic’s association with fetal growth outcomes.

The aims of this study were to assess the associations between in utero arsenic exposure and birth size among a cohort of U.S. pregnant women with low-level arsenic exposure from diet and drinking water, and to determine whether maternal prepregnancy weight modified that association.

Methods

Source Population

The New Hampshire Birth Cohort Study (NHBCS) is a prospective study designed to examine the associations of arsenic exposure on fetal growth and development during early childhood (Gilbert-Diamond et al. 2011). In the state of New Hampshire, residents commonly use unregulated private water supplies, and it is estimated that more than 1 in 10 homes have drinking-water wells with water arsenic concentrations that exceed the U.S. Environmental Protection Agency’s recommended maximum of 10 μg/L (Karagas et al. 1998). Pregnant women 18–45 years old between 24 and 28 weeks of gestation were recruited from prenatal clinics in New Hampshire beginning in January 2009. Eligibility criteria included English literacy, the use of a private, unregulated water system (e.g., private well) at home, and a singleton pregnancy. The NHBCS enrolled 1,033 pregnant women by 30 September 2013. At the time of the analysis there were 1,020 live singleton births. Of those, prepregnancy weight status was not available for 111 women, maternal second-trimester spot urine samples were not available for an additional 151 women, and newborn anthropometric data were not available for 27 newborns. Of the remaining 731 mother–child dyads, 25 were excluded because the mother had a prepregnancy BMI < 18.5 kg/m2. Thus the final sample size of the analysis was 706 dyads. When comparing women who were included in the analysis with the entire population-based cohort, there were no significant differences related to baseline characteristics, arsenic exposures, or birth outcomes (data not shown). Participants provided informed consent, and all study procedures were approved by the Internal Review Board at Dartmouth College.

Primary Outcomes: Measures of Infant Size at Birth

Infant length, weight, head circumference, gestational age (weeks), and sex at birth were collected from a medical record review by trained study staff. Ponderal index at birth was computed as kg/m3, and age- and sex-adjusted birth lengths and birth weight percentiles were computed per the methods of Fenton (Fenton et al. 2013). Age- and sex-adjusted birth weight percentiles were used to classify infants’ size-for-gestational age, which included small (≤ 10th percentile) (SGA), average (11–89th percentile) (AGA), and large-for-gestational age (≥ 90th percentile) (LGA) (Lesseur et al. 2013Wilhelm-Benartzi et al. 2012).

Primary Exposure: in Utero Arsenic Exposure

Using previously described methods (Gilbert-Diamond et al. 2011), we collected and analyzed maternal second-trimester urinary arsenic. Women provided a spot urine sample collected at approximately 24–28 weeks of gestation that was analyzed for iAs (AsIII and AsV), MMAV, and DMAV (hereafter MMA and DMA) using a high-performance liquid chromatography inductively coupled plasma mass spectrometry system (Larsen et al. 1993). The limits of detection (LODs) ranged from 0.01 to 0.39 μg/L for the individual arsenic species across the analysis batches. The average LOD for iAs was 0.15 μg/L, and the average LOD for both MMA and DMA was 0.06 μg/L. Measurements below the detection limit were set to half the LOD. Total urinary arsenic concentrations (tAs) were determined by summing those four metabolites and excluding arsenobetaine, an organoarsenic compound that is unmetabolized and is thought to be nontoxic (Francesconi et al. 2002). Inorganic arsenic, MMAV, DMAV, and tAs concentrations were right-skewed, so values were natural log (ln)–transformed for analysis. In addition, we divided MMAV by iAs and DMAV by MMAV to calculate the primary and secondary methylation indices (PMI and SMI), respectively (Chen et al. 2003Gilbert-Diamond et al. 2013Tseng 2009). The PMI and SMI were analyzed as continuous predictors. Urinary creatinine, a marker of urinary dilution, was measured using a calorimetric assay (Assay #500701; Cayman Chemical, Ann Arbor, MI).

In addition to providing urine samples, women also provided drinking-water samples that were analyzed for arsenic as previously described (Gilbert-Diamond et al. 2011). Because rice (Cascio et al. 2011Gilbert-Diamond et al. 2011Meharg et al. 2009) and seafood (Adams et al. 1994Francesconi 2010) are also known sources of arsenic exposure in the United States, women also reported their rice and seafood intake for the 3 days before the urine sample collection on a brief questionnaire.

Maternal Weight Status

Women were asked to report their usual weight when not pregnant as part of the enrollment questionnaire. Those values were combined with height abstracted from the medical records to compute prepregnancy BMI (kg/m2). Prepregnancy weight status was categorized as normal weight (18.5–25 kg/m2), or overweight or obese (≥ 25 kg/m2). Twenty-five women who were classified as underweight (< 18.5 kg/m2) before the current pregnancy were excluded from this analysis.

Other Measures

Demographics and lifestyle characteristics and medical history were collected via prenatal and postpartum questionnaires. Trained study staff also conducted a medical record review to collect results of gestational blood glucose testing. As part of routine prenatal care, women typically completed a nonfasting glucose challenge test (GCT) between 24 and 28 weeks gestation, where blood was sampled 1 hr after ingestion of 50 g of glucose. For those with a 1-hr GCT result of 140–199 mg/dL an additional, fasting oral glucose tolerance test (OGTT) was performed, where blood was sampled hourly for 3 hr after ingesting 100 g of glucose. Because women with a 1-hr GCT result ≥ 200 mg/dL were considered to have had gestational diabetes, they did not undergo a subsequent OGTT. For this analysis, results from both the GCT and OGTT were used to define maternal gestational hyperglycemia. Specifically, gestational diabetes mellitus (GDM) was defined as a 1-hr GCT result ≥ 200 mg/dL or failing the 1-hr GCT (140–199 mg/dL) with two or more high values on the OGTT based on the American Diabetes Association criteria for a normal OGTT (Committee on Practice Bulletins—Obstetrics 2013) of blood glucose ≤ 95 mg/dL at baseline, ≤ 180 mg/dL at 1 hr, ≤ 155 mg/dL at 2 hr, and ≤ 140 mg/dL at 3 hr. Impaired glucose tolerance (IGT) was defined as failing the 1-hr GCT (140–199 mg/dL) and having one high value on the OGTT. For two participants, results from 1-hr GCT were not available, yet a diagnosis of GDM was included in the medical record. Therefore, data on IGT status were available for 680 participants, and data on GDM status were available for 682 participants.

Statistical Analyses

All analyses were completed using R: A Language and Environment for Statistical Computing, version 3.0.2 (R Core Team 2013). A threshold of p < 0.05 was used to define associations as statistically significant. Baseline characteristics, maternal urinary arsenic concentrations, infant gestational age, and infant birth size measures were summarized overall and compared by maternal prepregnancy weight status using chi-square test for categorical measures, t-tests for normally distributed continuous measures, and Wilcoxon rank-sum tests for non-normally distributed continuous measures.

We assessed the linearity of each dose–response relationship between each arsenic exposure (ln-transformed) and each outcome using generalized additive models (GAMs). GAMs were fit using the R language gam function included in the mgcv package. In our analyses, the shape of dose–repose relationship was estimated using thin plate splines (Wood 2004). The quasi-Akaike Information Criteria (qAIC) is an indicator of model fit, with lower values indicating a better-fitting model (Wood 2004). When considering the inclusion of a nonlinear term in each model, the criterion of a change in qAIC of ≥ 10 (Burnham and Anderson 2002) was considered evidence of an improved model fit over a linear model. Per that criterion, we did not find evidence of any nonlinear dose–response relationships between total arsenic (ln-transformed) and each outcome.

Models were fit in the overall sample and stratified by maternal prepregnancy weight status and infant sex. In all models, variables associated with maternal prepregnancy weight status or birth size at the p < 0.10 level in bivariate analyses were included as covariates. In this study, we explored arsenic’s association with birth anthropometric outcomes while controlling for gestational age, and did not explore potential mediation of any associations by gestational age. The models for the head circumference, birth length, birth weight, and ponderal index outcomes were adjusted for maternal age at enrollment (continuous), maternal education (ordinal, with the five categories listed in Table 1 assigned values of 1–5, respectively), maternal parity (continuous), infant sex, and gestational age (continuous). Models for the gestational age outcome were similar except they did not adjust for gestational age. Models for the sex- and age-specific birth length or weight percentiles were also similar but they did not adjust for gestational age or infant sex. Models with PMI and SMI as the main predictors were additionally adjusted for tAs. For each outcome, models for the overall sample also included maternal prepregnancy weight status (dichotomous: BMI < 25 kg/m2, BMI ≥ 25 kg/m2) as a covariate.

Table 1 - Select View Table (HTML Version) for a 508-conformant versionTable 1 – Selected characteristics of 706 mothers and their infants from a New Hampshire pregnancy cohort for all participants and by maternal prepregnancy weight status.a

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Models with multiplicative interaction terms between the urinary As exposure and maternal prepregnancy weight status were used to formally assess modification by maternal prepregnancy weight status; a Wald test was used to determine statistical significance of the multiplicative terms. In addition, because other studies report potential sex-specific effects of arsenic exposure (Davis et al. 2015Kippler et al. 2012Pilsner et al. 2012), we conducted similar interaction analyses to test for effect modification by infant sex on the relationships between arsenic and birth outcomes. For birth outcomes that showed evidence of effect modification (either statistically significant or suggestive) by either maternal weight status or infant sex, we estimated the associations with each arsenic exposure stratified by both maternal weight status and infant sex. To test for the significance of a three-way interaction between maternal weight status, infant sex, and each arsenic exposure, we fit a multivariable regression with main effect terms, two-way multiplicative interaction terms, and a three-way multiplicative interaction term, adjusted for covariates; we assessed the statistical significance of each three-way multiplicative interaction term using a Wald’s test.

Several sensitivity analyses were completed to assess the robustness of the results. All multivariate regression models were repeated: a) excluding women who reported any seafood intake within the 2 days before the urine sample collection, b) excluding any women who reported any rice intake within the 2 days before the urine sample collection, and c) adjusted for creatinine for the subset of women with urinary creatinine concentrations available. We also repeated the analysis with the head circumference outcome additionally adjusting for a) vaginal or cesarean birth and b) birth weight. Finally, because prepregnancy weight status is positively associated with risk of developing GDM (Torloni et al. 2009), we completed exploratory analyses to determine if there was a multiplicative interaction between maternal hyperglycemia and arsenic exposure on infant birth size using a Wald test to determine statistical significance of the interaction terms.

Results

Among the 706 included participants, 300 (42.5%) were overweight or obese before their current pregnancy, and specifically 113 (16.0%) were obese. Table 1 presents baseline characteristics by maternal prepregnancy weight status. Three women were missing education data, 2 women were missing parity data, and 67 women were missing gestational weight gain data. In addition, 25 women were missing data on GDM status, and 27 women were missing data on IGT and their 1-hr blood glucose screening. Women who were overweight or obese were younger, more likely to have a lower level of education, and less likely to be nulliparous. Home water arsenic concentrations and any intake of seafood or rice did not differ significantly by prepregnancy weight status. Rates of IGT and GDM did not differ significantly by prepregnancy weight status, nor did mean screening blood glucose. Urinary iAs was correlated with MMA and DMA (Spearman’s ρ = 0.71, 0.59, respectively; both p < 0.001) and tAs was most strongly correlated with DMA (Spearman’s ρ = 0.98, p < 0.001). Unadjusted concentrations of maternal urinary arsenic did not differ by prepregnancy weight status, nor did the PMI and SMI.

Infant birth characteristics by maternal prepregnancy weight status are presented in Table 1. Maternal overweight or obese weight status was associated with an earlier gestational age at birth, though there was no difference in the proportion of births before 37 weeks by weight status (5.4% overall, p = 0.43). Overweight or obese status was also associated with a larger head circumference at birth. When considering age- and sex-adjusted size at birth (data not shown), the average (SD) birth length percentile was 57 (29) among all infants and did not differ by maternal weight status (p = 0.12). The average (SD) birth weight percentile was significantly higher for infants whose mothers were overweight or obese compared to normal weight prepregnancy [57 (27) vs. 51 (26); p = 0.001]. Additionally, mothers who were overweight or obese gave birth to children with a 0.5 kg/m3 higher ponderal index, on average, though this difference was only marginally statistically significant (p = 0.07).

Results from the adjusted generalized additive models supported linear dose–response relationships between maternal urinary arsenic concentrations and gestational age, head circumference, birth length, birth weight, ponderal index, birth length percentile, and birth weight percentile (data not shown). Table 2 presents the adjusted parameter estimates from a series of linear regression models fitting those infant birth characteristics on natural log–transformed maternal urinary arsenic concentrations, overall and stratified by maternal prepregnancy weight status. Maternal urinary MMA and tAs were negatively associated with infant head circumference at birth. After holding all other covariates constant, each doubling of tAs was associated with a 0.10-cm decrease [95% confidence interval (CI): –0.19, –0.01, p = 0.03] in head circumference. The association was not modified by maternal weight status and did not change after further adjustment for delivery mode and/or birth weight (see Table S1). Results were also consistent in unadjusted models (data not shown). The negative associations between maternal urinary iAs and DMA and head circumference were similar in magnitude to those for MMA and tAs, though they did not reach statistical significance.

Table 2 - Select View Table (HTML Version) for a 508-conformant versionTable 2 – Adjusted parameter estimates (95% confidence interval) for the change in birth outcomes with each unit increase in natural log–transformed maternal 2nd trimester urinary arsenic for all participants and by maternal prepregnancy weight status (n = 706).a,b

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Maternal urinary DMA and tAs were positively associated with infant birth length. After holding all other covariates constant, each doubling of tAs was associated with a 0.15-cm increase (95% CI: 0.01, 0.28, p = 0.04) in birth length. Although the estimates of association were larger and only statistically significant in the overweight/obese stratum, the statistical test for interaction by maternal weight status did not reach statistical significance. The results for birth length percentile were qualitatively similar to those for birth length (see Table S2); birth length percentile was positively associated with ln(DMA) and ln(tAs) in the stratum of overweight/obese women, though only the ln(DMA) association was statistically significant.

Maternal urinary arsenic was inversely associated with infant adiposity measured as ponderal index, and the associations appeared limited to women who were overweight or obese prepregnancy. Among children of those women, each doubling of tAs was associated with a 0.55-kg/m3 lower (95% CI: –0.82, –0.28, p < 0.001) ponderal index. Additionally among those women, decreases in mean ponderal index also were observed with increases in urinary iAs, MMA, and DMA. In contrast, there were not any statistically significant associations between maternal arsenic concentrations and infant ponderal index among normal weight women.

Maternal urinary arsenic was not significantly associated with gestational age, absolute birth weight (Table 2), or birth weight percentiles (see Table S2). The PMI and SMI were not significantly associated with gestational age or any birth anthropometric measures (data not shown).

In analyses that examined effect modification by infant sex (see Table S3), arsenic exposure was positively and significantly related to birth length in male infants but showed no association in females [p for interaction for ln(tAs) = 0.04]; among male infants, each doubling of tAs was associated with a 0.28-cm increase (95% CI: 0.09, 0.46, p < 0.01) in birth length. Results were similar for DMA and MMA. There was also a suggestive interaction between arsenic exposure and infant sex on the birth weight outcome; arsenic appeared negatively associated with birth weight in girls and positively associated with birth weight in boys, though none of the point estimates were statistically significant, nor were any of the interaction tests.

In analyses stratified by both maternal weight status and infant sex (Table 3), the positive association between arsenic exposure and infant length appeared limited to the stratum of boys born of overweight/obese mothers, though the test for three-way interaction was only marginally significant (p = 0.13). In the stratum of boys born of overweight/obese mothers, each doubling of tAs was associated with a 0.51-cm increase (95% CI: 0.21, 0.82) in birth length. When looking at the birth weight outcome, there was a strong, statistically significant negative association between arsenic exposure and birth weight in the stratum of girls born of overweight/obese mothers, whereas associations in the other strata were largely positive and not statistically significant; the test for three-way interaction was significant (p = 0.03). In the stratum of girls born of overweight/obese mothers, each doubling of tAs was associated with a 62.9-g decrease (95% CI: –111.6, –14.2) in birth weight.

Table 3 - Select View Table (HTML Version) for a 508-conformant versionTable 3 – Adjusted parameter estimates (95% CI) for the change in birth outcomes with each unit increase in natural log–transformed maternal 2nd-trimester urinary arsenic by maternal prepregnancy weight statusa and infant sex strata.b

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Results were consistent in analyses limited to the subset of women who did not consume seafood (n = 594) or rice (n = 543) in the previous 2 days, with additional adjustment for creatinine (data available for 520 participants; data not shown), or with additional adjustment for gestational weight gain (data available for 639 participants; data not shown). Also, we did not find evidence that the results of the maternal glucose challenge test or maternal hyperglycemia status modified the association between maternal urinary tAs and infant ponderal index (data not shown).

Discussion

In this U.S. sample of women and their newborn infants, we found that second-trimester maternal urinary arsenic concentration, a measure of fetal in utero arsenic exposure, was negatively associated with infant head circumference, positively associated with infant length and, negatively associated with adiposity at birth. We further observed that the associations between arsenic exposure and birth length were observed only in males, and the associations with adiposity were only observed in the overweight/obese stratum and not in the normal weight stratum. Finally, we observed a significant three-way interaction between maternal weight status, infant sex, and arsenic exposure on the birth weight outcome; specifically, arsenic exposure is related to lower birth weight in females born to overweight/obese mothers, but the association appears null, or possibly in the opposite direction, for all males and for females born of healthy weight mothers.

Our findings relating arsenic exposure and head circumference at birth agree with those from a large prospective analysis by Rahman et al. (2009). In that study of 805 Bangladeshi mothers with urinary arsenic in the lower range of exposure (< 100 μg/L) and their children, 1 μg/L of maternal tAs (average from samples taken around gestational weeks 8 and 30) was associated with a 0.05-mm (SE = 0.03, p = 0.04) lower newborn head circumference after adjustment for maternal BMI and socioeconomic status. An analysis of ultrasound measurements from the Bangladeshi cohort (n = 1,929) found that arsenic may influence head circumference before the third trimester and in a sex-specific manner (Kippler et al. 2012); maternal urinary arsenic was negatively associated with ultrasound measures of head circumference in males and positively associated with head circumference in females. Our previous analysis of 223 ultrasound reports from our cohort also suggests that this arsenic-related reduced head circumference may be present as early as the second trimester, though we observed a stronger negative association in female fetuses (Davis et al. 2015). In the present study, we did not observe any significant effect modification of the associations between arsenic and head circumference by infant sex.

In contrast to our results, Rahman et al. (2009) did not observe an association between arsenic exposure and birth length. They did observe a negative association between maternal urinary arsenic and birth weight; each 1 μg/L of urinary tAs was associated with an adjusted –1.68 g (SE = 0.62, p < 0.01) difference in birth weight when examining infants born of mothers with urinary arsenic concentrations < 100 μg/L. In contrast, we only observed a negative association between arsenic and birth weight in girls born of overweight/obese mothers.

Three other prospective studies have examined maternal urinary arsenic in relation to birth outcomes (Chou et al. 2014Laine et al. 2015Shirai et al. 2010). A study of 299 mother–child pairs from a non–arsenic-endemic region of Taiwan (Chou et al. 2014) and a study of 78 low-exposure mother–child pairs from Tokyo (Shirai et al. 2010), did not find any associations between maternal urinary arsenic and head circumference, birth length, or birth weight. In a study of 200 mother–child pairs from an arsenic-endemic region in Mexico, maternal urinary MMA was negatively associated with birth weight and gestational age, and iAs was negatively associated with birth length and gestational age (Laine et al. 2015). In a small study that compared 19 mothers from a city with high water arsenic to 19 mothers from a city with low water arsenic in Chile, there were no significant urinary arsenic–birth weight associations in (Hopenhayn et al. 2003).

The results are also mixed from other studies that relied on maternal hair (Huyck et al. 2007), maternal blood (Claus Henn et al. 2016Guan et al. 2012), infant meconium (Vall et al. 2012), and drinking-water (Hopenhayn et al. 2003Kwok et al. 2006Myers et al. 2010Yang et al. 2003) arsenic levels to examine the association between arsenic and birth weight (Claus Henn et al. 2016Huyck et al. 2007Guan et al. 2012Hopenhayn et al. 2003Kwok et al. 2006Myers et al. 2010Vall et al. 2012Yang et al. 2003); length (Claus Henn et al. 2016Guan et al. 2012Vall et al. 2012); and head circumference (Claus Henn et al. 2016Guan et al. 2012Vall et al. 2012).

Several population characteristics could lead to the heterogeneity of study findings. Our research differs from the bulk of previous research on arsenic and fetal growth because of the relatively low levels of arsenic exposure in our population; for example, participants in the study by Rahman et al. (2009) had a median concentration of 95 μg/L of total urinary arsenic compared with our median of 3.4 μg/L. In addition, almost half of our study population was overweight or obese. In contrast, only 5% of the mothers in the Rahman et al. (2009) study were overweight or obese and 30% were underweight. We were unable to explore the relation between arsenic and fetal growth in underweight women because only 25 women in our sample met this criterion. In addition to weight status, other nutritional factors such as folate (Gamble et al. 2007Hall et al. 2009) and protein intake (Heck et al. 2009Milton et al. 2004) could modify the associations between arsenic and fetal growth; thus nutritional factors may lead to heterogeneity in study findings and should be explored in future research.

Fetal growth is a complicated process that is affected by several factors including maternal nutrition, genetics, and toxic exposures (Kramer 1987). Although the mechanism by which arsenic might affect fetal growth is unknown, several possibilities have been proposed. Our previous work suggests that increased maternal arsenic exposure may lead to increased expression of the arsenic transporter AQP9 in placental tissue, which, in turn, may decrease expression of the adipose tissue–derived ENPP2 (Fei et al. 2013), a phospholipase that is purported to regulate adipose tissue growth (Nishimura et al. 2014). In addition, there is evidence that arsenic increases oxidative stress (Xu et al. 2008) and inflammatory processes (Ahmed et al. 2011Fry et al. 2007), factors associated with growth restriction (Biri et al. 2007Challis et al. 2009). Given that excess adiposity is also known to increase oxidative stress and systemic inflammation (Vincent and Taylor 2006), it is feasible that arsenic exposure may differentially impact fetal growth depending on maternal weight status. In addition, arsenic could influence fetal growth through other mechanisms such as endocrine disruption (Bodwell et al. 2004Davey et al. 2007), epigenetic modification (Koestler et al. 2013), and/or altered transcription (Kumagai and Sumi 2007) and it is plausible that effects could differ by infant sex.

Opposite effects of in utero arsenic exposure on fetal length at lower and higher exposure doses is plausible given the findings of an in vitro study of arsenic trioxide (ATO) and the growth of osteoblasts—the specialized cells in the bone that secrete collagen and a calcium- and phosphate-containing mineral to form the bone matrix (Xu et al. 2014). In that study, a low-dose (0.25, 0.5, and 1 μM) of ATO, an oxide of inorganic arsenic, greatly enhanced the viability of cultured osteoblasts and promoted collagen synthesis and secretion, and a high-dose (5, 10, and 20 μM) of ATO led to a significant reduction in osteoblast viability and induced osteoblast apoptosis. Although we did not observe an inverse association between arsenic and birth length at any part of the dose–response curves in the stratified or total samples, this may be attributable to the relatively low range of arsenic exposure in our population.

Alterations of fetal growth related to in utero arsenic exposure may have important public health implications. Head circumference closely correlates to brain volume (Cooke et al. 1977Wickett et al. 2000), and some research suggests that head circumference at birth is associated with later intellectual function (Gale et al. 2006). Additionally, the persistence of the negative association between arsenic and head circumference after adjusting for birth weight suggests that the reduction in head circumference is independent of birth size, as has been observed with other toxicant exposure (Fein et al. 1984Hernandez-Avila et al. 2002). Thus, our findings of increased arsenic exposure related to decreased head circumference are consistent with laboratory studies that find that arsenic has neurotoxic effects (Chaudhuri et al. 1999), and epidemiological studies that suggest that arsenic exposure is related to decreased intellectual function (Hamadani et al. 2011Roy et al. 2011). Other studies suggest that postnatal head growth is also important in determining later cognitive function (Gale et al. 2004Smithers et al. 2013), so it is important to further explore arsenic’s relationship with postnatal head circumference growth and ultimately cognitive function in future studies.

The influence of fetal growth on later risk of adiposity (Curhan et al. 1996a1996b) and metabolic disease (Barker et al. 1989a1989b) is well recognized. Studies suggest a U-shaped relationship with both high birth weight/adiposity (Eriksson et al. 2001) and low birth weight/adiposity (Barker et al. 1993Bhargava et al. 2004) and later adiposity and metabolic disease. Studies additionally suggest that low size at birth may be related to accelerated weight gain (catch up growth) in infancy (Barker et al. 1993Bhargava et al. 2004) which is in turn related to later obesity (Hack et al. 1984Ong et al. 2000Victora et al. 2001). Interestingly, our observed negative association between arsenic exposure and ponderal index in the overweight/obese stratum seems to be driven by longer birth length in boys, but by lower birth weight in girls. Such possible mechanistic differences in adiposity at birth could have important ramifications for later growth trajectories. Ongoing follow-up of our longitudinal cohort will allow us to examine weight and adiposity trajectories in early infancy, and ultimately childhood overweight or obesity status, in relation to in utero arsenic exposure in our population. We will also be able to explore whether early childhood arsenic exposure is related to early childhood growth, as has been done in more highly exposed populations (Gardner et al. 2013). A study of 1,505 mother–infant pairs in rural Bangladesh found an inverse relationship between children’s weight, height, and growth velocity and concurrent arsenic exposure at 5 years of age (Gardner et al. 2013).

Unlike the majority of epidemiological studies on arsenic exposure, this population-based prospective study explores arsenic exposures at levels commonly encountered in the United States through water and food sources. Our study is strengthened by using sensitive biomarkers of in utero exposure to both inorganic arsenic and its metabolites as well as clinically measured anthropometry at birth. Although we have only a single measure of maternal urinary arsenic during pregnancy, a study in American-Indian communities suggests that urinary arsenic is relatively stable over time (Navas-Acien et al. 2009). Our study was also limited by our use of self-reported prepregnancy weight, which is likely slightly underreported (Holland et al. 2013Russell et al. 2013); this may have led to some women who were overweight/obese being misclassified as healthy weight. In this analysis, we explored only arsenic species and did not examine arsenic’s correlation with other metals, so we cannot rule out the potential for confounding by those factors. In addition, we did not adjust for micronutrient status, which may relate to arsenic metabolism; however, we believe it is unlikely that this would have substantially influenced our results, beacause all women received prenatal care at study clinics and approximately 92% of women in the cohort report taking prenatal vitamins. A further limitation is that we were underpowered to explore arsenic’s association specifically with risk for being born SGA or LGA, given the small number of infants born with these outcomes.

Our study, in a U.S. cohort of mothers and infants, suggest that arsenic exposure, even at low levels, may affect fetal growth, and that associations may be modified by maternal weight status and infant sex. The health implications of our findings will be elucidated by future longitudinal studies in our cohort and others that explore the impact of prenatal and postnatal arsenic exposure on growth and neurodevelopmental outcomes.


References

Adams MA, Bolger PM, Gunderson EL. 1994. Dietary intake and hazards of arsenic. In: Arsenic: Exposure and Health, Science Technology Letters (Chapell WR, Abernathy CO, Cothern CR, eds). London, UK:Northwood, 41–49.

Ahmed S. 2011. Arsenic-associated oxidative stress, inflammation, and immune disruption in human placenta and cord blood. Environ Health Perspect 119:258–264, doi: 10.1289/ehp.1002086.

Barker DJ, Hales CN, Fall CH, Osmond C, Phipps K, Clark PM. 1993. Type 2 (non-insulin-dependent) diabetes mellitus, hypertension and hyperlipidaemia (syndrome X): relation to reduced fetal growth. Diabetologia 36:62–67.

Barker DJ, Osmond C, Golding J, Kuh D, Wadsworth ME. 1989a. Growth in utero, blood pressure in childhood and adult life, and mortality from cardiovascular disease. BMJ 298:564–567, doi: 10.1136/bmj.298.6673.564.

Barker DJP, Osmond C, Winter PD, Margetts B, Simmonds SJ. 1989b. Weight in infancy and death from ischaemic heart disease. Lancet 334:577–580, doi: 10.1016/S0140-6736(89)90710-1.

Bhargava SK, Sachdev HS, Fall CHD, Osmond C, Lakshmy R, Barker DJP, et al. 2004. Relation of serial changes in childhood body-mass index to impaired glucose tolerance in young adulthood. N Engl J Med 350:865–875, doi: 10.1056/NEJMoa035698.

Biri A, Bozkurt N, Turp A, Kavutcu M, Himmetoglu O, Durak I. 2007. Role of oxidative stress in intrauterine growth restriction. Gynecol Obstet Invest 64:187–192, doi: 10.1159/000106488.

Bodwell JE, Kingsley LA, Hamilton JW. 2004. Arsenic at very low concentrations alters glucocorticoid receptor (GR)-mediated gene activation but not GR-mediated gene repression: complex dose-response effects are closely correlated with levels of activated GR and require a functional GR DNA binding domain. Chem Res Toxicol 17:1064–1076, doi: 10.1021/tx0499113.

Burnham KP, Anderson DR. 2002. Model Selection and Multimodel Inference: A Practical Information-Theoretical Approach. 2d ed. New York: Springer-Verlag.

Cascio C, Raab A, Jenkins RO, Feldmann J, Meharg AA, Haris PI. 2011. The impact of a rice based diet on urinary arsenic. J Environ Monit 13:257–265, doi: 10.1039/c0em00482k.

Challis JR, Lockwood CJ, Myatt L, Norman JE, Strauss JF III, Petraglia F. 2009. Inflammation and pregnancy. Reprod Sci 16:206–215, doi: 10.1177/1933719108329095.

Chaudhuri AN, Basu S, Chattopadhyay S, Das Gupta S. 1999. Effect of high arsenic content in drinking water on rat brain. Indian J Biochem and Biophys 36:51–54.

Chen YC, Su HJJ, Guo YLL, Hsueh YM, Smith TJ, Ryan LM, et al. 2003. Arsenic methylation and bladder cancer risk in Taiwan. Cancer Causes Control 14:303–310.

Chou WC, Chung YT, Chen HY, Wang CJ, Ying TH, Chuang CY, et al. 2014. Maternal arsenic exposure and DNA damage biomarkers, and the associations with birth outcomes in a general population from Taiwan. PLoS One 9:e86398, doi: 10.1371/journal.pone.0086398.

Claus Henn B, Ettinger AS, Hopkins MR, Jim R, Amarasiriwardena C, Christiani DC, et al. 2016. Prenatal arsenic exposure and birth outcomes among a population residing near a mining-related Superfund site. Environ Health Perspect 124:1308–1315, doi: 10.1289/ehp.1510070.

Committee on Practice Bulletins—Obstetrics. 2013. ACOG Practice Bulletin no. 137: Clinical Management Guidelines for Obstetrician-Gynecologists. Gestational diabetes, Obstet Gynecol 122(2 pt 1):406–416, doi: 10.1097/01.AOG.0000433006.09219.f1.

Concha G, Vogler G, Lezcano D, Nermell B, Vahter M. 1998. Exposure to inorganic arsenic metabolites during early human development. Toxicol Sci 44:185–190, doi: 10.1006/toxs.1998.2486.

Cooke RWI, Lucas A, Yudkin PL, Pryse-Davies J. 1977. Head circumference as an index of brain weight in the fetus and newborn. Early Hum Dev 1:145–149, doi: 10.1016/0378-3782(77)90015-9.

Curhan GC, Chertow GM, Willett WC, Spiegelman D, Colditz GA, Manson JE, et al. 1996a. Birth weight and adult hypertension and obesity in women. Circulation 94:1310–1315, doi: 10.1161/01.CIR.94.6.1310.

Curhan GC, Willett WC, Rimm EB, Spiegelman D, Ascherio AL, Stampfer MJ. 1996b. Birth weight and adult hypertension, diabetes mellitus, and obesity in US men. Circulation 94:3246–3250, doi: 10.1161/01.CIR.94.12.3246.

Davey JC, Bodwell JE, Gosse JA, Hamilton JW. 2007. Arsenic as an endocrine disruptor: effects of arsenic on estrogen receptor-mediated gene expression in vivo and in cell culture. Toxicol Sci 98:75–86, doi: 10.1093/toxsci/kfm013.

Davis MA, Higgins J, Li Z, Gilbert-Diamond D, Baker ER, Das A, et al. 2015. Preliminary analysis of in utero low-level arsenic exposure and fetal growth using biometric measurements extracted from fetal ultrasound reports. Environ Health 14:12, doi: 10.1186/1476-069X-14-12.

Eriksson J, Forsén T, Tuomilehto J, Osmond C, Barker D. 2001. Size at birth, childhood growth and obesity in adult life. Int J Obes Relat Metab Disord 25:735–740, doi: 10.1038/sj.ijo.0801602.

Fei DL, Koestler DC, Li Z, Giambelli C, Sanchez-Mejias A, Gosse JA, et al. 2013. Association between in utero arsenic exposure, placental gene expression, and infant birth weight: a US birth cohort study. Environ Health 12:58, doi: 10.1186/1476-069X-12-58.

Fein GG, Jacobson JL, Jacobson SW, Schwartz PM, Dowler JK. 1984. Prenatal exposure to polychlorinated biphenyls: effects on birth size and gestational age. J Pediatr 105:315–320.

Fenton TR, Nasser R, Eliasziw M, Kim JH, Bilan D, Sauve R. 2013. Validating the weight gain of preterm infants between the reference growth curve of the fetus and the term infant. BMC Pediatr 13:92, doi: 10.1186/1471-2431-13-92.

Francesconi KA. 2010. Arsenic species in seafood: origin and human health implications. Pure Appl Chem 82:373–381, doi: 10.1351/PAC-CON-09-07-01.

Francesconi KA, Tanggaar R, McKenzie CJ, Goessler W. 2002. Arsenic metabolites in human urine after ingestion of an arsenosugar. Clin Chem 48:92–101.

Fry RC, Navasumrit P, Valiathan C, Svensson JP, Hogan BJ, Luo M, et al. 2007. Activation of inflammation/NF-κB signaling in infants born to arsenic-exposed mothers. PLoS Genet 3:e207, doi: 10.1371/journal.pgen.0030207.

Gale CR, O’Callaghan FJ, Bredow M, Martyn CN, Avon Longitudinal Study of Parents and Children Study Team. 2006. The influence of head growth in fetal life, infancy, and childhood on intelligence at the ages of 4 and 8 years. Pediatrics 118:1486–1492, doi: 10.1542/peds.2005–2629.

Gale CR, O’Callaghan FJ, Godfrey KM, Law CM, Martyn CN. 2004. Critical periods of brain growth and cognitive function in children. Brain 127:321–329, doi: 10.1093/brain/awh034.

Gamble MV, Liu X, Slavkovich V, Pilsner JR, Ilievski V, Factor-Litvak P, et al. 2007. Folic acid supplementation lowers blood arsenic. Am J Clin Nutr 86:1202–1209.

Gardner RM, Kippler M, Tofail F, Bottai M, Hamadani J, Grandér M, et al. 2013. Environmental exposure to metals and children’s growth to age 5 years: a prospective cohort study. Am J Epidemiol 177:1356–1367, doi: 10.1093/aje/kws437.

Gebel TW. 2002. Arsenic methylation is a process of detoxification through accelerated excretion. Int J Hyg Environ Health 205:505–508, doi: 10.1078/1438-4639-00177.

Gilbert-Diamond D, Cottingham KL, Gruber JF, Punshon T, Sayarath V, Gandolfi AJ, et al. 2011. Rice consumption contributes to arsenic exposure in US women. Proc Natl Acad Sci USA 108:20656–20660, doi: 10.1073/pnas.1109127108.

Gilbert-Diamond D, Li Z, Perry AE, Spencer SK, Gandolfi AJ, Karagas MR. 2013. A population-based case–control study of urinary arsenic species and squamous cell carcinoma in New Hampshire, USA. Environ Health Perspect 121:1154–1160, doi: 10.1289/ehp.1206178.

Gomez-Rubio P, Roberge J, Arendell L, Harris RB, O’Rourke MK, Chen Z, et al. 2011. Association between body mass index and arsenic methylation efficiency in adult women from southwest U.S. and northwest Mexico. Toxicol Appl Pharmacol 252:176–182, doi: 10.1016/j.taap.2011.02.007.

Guan H, Piao F, Zhang X, Li X, Li Q, Xu L, et al. 2012. Prenatal exposure to arsenic and its effects on fetal development in the general population of Dalian. Biol Trace Elem Res 149:10–15, doi: 10.1007/s12011-012-9396-7.

Hack M, Merkatz IR, McGrath SK, Jones PK, Fanaroff AA. 1984. Catch-up growth in very-low-birth-weight infants. Clinical correlates. Am J Dis Child 138:370–375.

Hall MN, Liu X, Slavkovich V, Ilievski V, Pilsner JR, Alam S, et al. 2009. Folate, cobalamin, cysteine, homocysteine, and arsenic metabolism among children in Bangladesh. Environ Health Perspect 117:825–831, doi: 10.1289/ehp.0800164.

Hamadani JD, Tofail F, Nermell B, Gardner R, Shiraji S, Bottai M, et al. 2011. Critical windows of exposure for arsenic-associated impairment of cognitive function in pre-school girls and boys: a population-based cohort study. Int J Epidemiol 40:1593–1604, doi: 10.1093/ije/dyr176.

Heck JE, Nieves JW, Chen Y, Parvez F, Brandt-Rauf PW, Graziano JH, et al. 2009. Dietary intake of methionine, cysteine, and protein and urinary arsenic excretion in Bangladesh. Environ Health Perspect 117:99–104, doi: 10.1289/ehp.11589.

Hernandez-Avila M, Peterson KE, Gonzalez-Cossio T, Sanin LH, Aro A, Schnaas L, et al. 2002. Effect of maternal bone lead on length and head circumference of newborns and 1-month-old infants. Arch Environ Health 57:482–488, doi: 10.1080/00039890209601441.

Holland E, Moore Simas TA, Doyle Curiale DK, Liao X, Waring ME. 2013. Self-reported pre-pregnancy weight versus weight measured at first prenatal visit: effects on categorization of pre-pregnancy body mass index. Matern Child Health J 17:1872–1878, doi: 10.1007/s10995-012-1210-9.

Hopenhayn C, Ferreccio C, Browning SR, Huang B, Peralta C, Gibb H, et al. 2003. Arsenic exposure from drinking water and birth weight. Epidemiology 14:593–602, doi: 10.1097/01.ede.0000072104.65240.69.

Hull HR, Dinger MK, Knehans AW, Thompson DM, Fields DA. 2008. Impact of maternal body mass index on neonate birthweight and body composition. Am J Obstet Gynecol 198:416.e1–6, doi: 10.1016/j.ajog.2007.10.796.

Huyck KL, Kile ML, Mahiuddin G, Quamruzzaman Q, Rahman M, Breton CV, et al. 2007. Maternal arsenic exposure associated with low birth weight in Bangladesh. J Occup Environ Med 49:1097–104, doi: 10.1097/JOM.0b013e3181566ba0.

Karagas MR, Tosteson TD, Blum J, Morris JS, Baron JA, Klaue B. 1998. Design of an epidemiologic study of drinking water arsenic exposure and skin and bladder cancer risk in a U.S. population. Environ Health Perspect 106(suppl 4):1047–1050.

King JC. 2006. Maternal obesity, metabolism, and pregnancy outcomes. Annu Rev Nutr 26:271–291, doi: 10.1146/annurev.nutr.24.012003.132249.

Kippler M, Wagatsuma Y, Rahman A, Nermell B, Persson LÅ, Raqib R, et al. 2012. Environmental exposure to arsenic and cadmium during pregnancy and fetal size: a longitudinal study in rural Bangladesh. Reprod Toxicol 34:504–511, doi: 10.1016/j.reprotox.2012.08.002.

Koestler DC, Avissar-Whiting M, Houseman EA, Karagas MR, Marsit CJ. 2013. Differential DNA methylation in umbilical cord blood of infants exposed to low levels of arsenic in utero. Environ Health Perspect 121:971–977, doi: 10.1289/ehp.1205925.

Kramer MS. 1987. Determinants of low birth weight: methodological assessment and meta-analysis. Bull World Health Organ 65:663–737.

Kumagai Y, Sumi D. 2007. Arsenic: signal transduction, transcription factor, and biotransformation involved in cellular response and toxicity. Annu Rev Pharmacol Toxicol 47:243–262, doi: 10.1146/annurev.pharmtox.47.120505.105144.

Kwok RK, Kaufmann RB, Jakariya M. 2006. Arsenic in drinking-water and reproductive health outcomes: a study of participants in the Bangladesh Integrated Nutrition Programme. J Health Popul Nutr 24:190–205.

Laine JE, Bailey KA, Rubio-Andrade M, Olshan AF, Smeester L, Drobná Z, et al. 2015. Maternal arsenic exposure, arsenic methylation efficiency, and birth outcomes in the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort in Mexico. Environ Health Perspect 123:186–192, doi: 10.1289/ehp.1307476.

Larsen EH, Pritzl G, Hansen SH. 1993. Speciation of eight arsenic compounds in human urine by high-performance liquid chromatography with inductively coupled plasma mass spectrometric detection using antimonate for internal chromatographic standardization. J Anal At Spectrom 8:557–563, doi: 10.1039/ja9930800557.

Lesseur C, Armstrong DA, Paquette AG, Koestler DC, Padbury JF, Marsit CJ. 2013. Tissue-specific leptin promoter DNA methylation is associated with maternal and infant perinatal factors. Mol Cell Endocrinol 381:160–167, doi: 10.1016/j.mce.2013.07.024.

Li L, Ekström EC, Goessler W, Lönnerdal B, Nermell B, Yunus M, et al. 2008. Nutritional status has marginal influence on the metabolism of inorganic arsenic in pregnant Bangladeshi women. Environ Health Perspect 116:315–321, doi: 10.1289/ehp.10639.

Lindberg AL, Goessler W, Gurzau E, Koppova K, Rudnai P, Kumar R, et al. 2006. Arsenic exposure in Hungary, Romania and Slovakia. J Environ Monit 8:203–208, doi: 10.1039/b513206a.

Mandal BK, Ogra Y, Suzuki KT. 2001. Identification of dimethylarsinous and monomethylarsonous acids in human urine of the arsenic-affected areas in West Bengal, India. Chem Res Toxicol 14:371–378, doi: 10.1021/tx000246h.

Meharg AA, Williams PN, Adomako E, Lawgali YY, Deacon C, Villada A, et al. 2009. Geographical variation in total and inorganic arsenic content of polished (white) rice. Environ Sci Technol 43:1612–1617.

Milton AH, Hasan Z, Shahidullah SM, Sharmin S, Jakariya MD, Rahman M, et al. 2004. Association between nutritional status and arsenicosis due to chronic arsenic exposure in Bangladesh. Int J Environ Health Res 14:99–108, doi: 10.1080/0960312042000209516.

Moore MM, Harrington-Brock K, Doerr CL. 1997. Relative genotoxic potency of arsenic and its methylated metabolites. Mutat Res Rev Mutat Res 386:279–290, doi: 10.1016/S1383-5742(97)00003-3.

Myers SL, Lobdell DT, Liu Z, Xia Y, Ren H, Li Y, et al. 2010. Maternal drinking water arsenic exposure and perinatal outcomes in inner Mongolia, China. J Epidemiol Community Health 64:325–329, doi: 10.1136/jech.2008.084392.

Navas-Acien A, Umans JG, Howard BV, Francesconi KA, Crainiceanu CM, Silbergeld EK, et al. 2009. Urine arsenic concentrations and species excretion patterns in American Indian communities over a 10-year period: the Strong Heart Study. Environ Health Perspect 117:1428–1433, doi: 10.1289/ehp.0800509.

Nishimura S, Nagasaki M, Okudaira S, Aoki J, Ohmori T, Ohkawa R, et al. 2014. ENPP2 contributes to adipose tissue expansion and insulin resistance in diet-induced obesity. Diabetes 63:4154–4164, doi: 10.2337/db13-1694.

Ong KK, Ahmed ML, Emmett PM, Preece MA, Dunger DB. 2000. Association between postnatal catch-up growth and obesity in childhood: prospective cohort study. BMJ 320:967–971.

Pilsner JR, Hall MN, Liu X, Ilievski V, Slavkovich V, Levy D, et al. 2012. Influence of prenatal arsenic exposure and newborn sex on global methylation of cord blood DNA. PLoS One 7:e37147, doi: 10.1371/journal.pone.0037147.

R Core Team. 2013. R: A Language and Environment for Statistical Computing. Vienna, Austria:R Foundation for Statistical Computing. Available: http://www.R-project.org [accessed 30 September 2013].

Rahman A, Vahter M, Smith AH, Nermell B, Yunus M, Arifeen SE, et al. 2009. Arsenic exposure during pregnancy and size at birth: a prospective cohort study in Bangladesh. Am J Epidemiol 169:304–312, doi: 10.1093/aje/kwn332.

Rivera-Núñez Z, Meliker JR, Meeker JD, Slotnick MJ, Nriagu JO. 2012. Urinary arsenic species, toenail arsenic, and arsenic intake estimates in a Michigan population with low levels of arsenic in drinking water. J Expo Sci Environ Epidemiol 22:182–190, doi: 10.1038/jes.2011.27.

Roy A, Kordas K, Lopez P, Rosado JL, Cebrian ME, Vargas GG, et al. 2011. Association between arsenic exposure and behavior among first-graders from Torreón, Mexico. Environ Res 111:670–676, doi: 10.1016/j.envres.2011.03.003.

Russell A, Gillespie S, Satya S, Gaudet LM. 2013. Assessing the accuracy of pregnant women in recalling pre-pregnancy weight and gestational weight gain. J Obstet Gynaecol Can 35:802–809.

Sewell MF, Huston-Presley L, Super DM, Catalano P. 2006. Increased neonatal fat mass, not lean body mass, is associated with maternal obesity. Am J Obstet Gynecol 195:1100–1103, doi: 10.1016/j.ajog.2006.06.014.

Shirai S, Suzuki Y, Yoshinaga J, Mizumoto Y. 2010. Maternal exposure to low-level heavy metals during pregnancy and birth size. J Environ Sci Health A Tox Hazard Subst Environ Eng 45:1468–1474.

Smedley PL, Kinniburgh DG. 2002. A review of the source, behaviour and distribution of arsenic in natural waters. Appl Geochem 17:517–568, doi: 10.1016/S0883-2927(02)00018-5.

Smithers LG, Lynch JW, Yang S, Dahhou M, Kramer MS. 2013. Impact of neonatal growth on IQ and behavior at early school age. Pediatrics 132:e53–e60, doi: 10.1542/peds.2012–3497.

Styblo M, Del Razo LM, Vega L, Germolec DR, LeCluyse EL, Hamilton GA, et al. 2000. Comparative toxicity of trivalent and pentavalent inorganic and methylated arsenicals in rat and human cells. Arch Toxicol 74:289–299.

Torloni MR, Betrán AP, Horta BL, Nakamura MU, Atallah AN, Moron AF, et al. 2009. Prepregnancy BMI and the risk of gestational diabetes: a systematic review of the literature with meta-analysis. Obes Rev 10:194–203, doi: 10.1111/j.1467-789X.2008.00541.x.

Tsang V, Fry RC, Niculescu MD, Rager JE, Saunders J, Paul DS, et al. 2012. The epigenetic effects of a high prenatal folate intake in male mouse fetuses exposed in utero to arsenic. Toxicol Appl Pharmacol 264:439–450, doi: 10.1016/j.taap.2012.08.022.

Tseng CH. 2009. A review on environmental factors regulating arsenic methylation in humans. Toxicol Appl Pharmacol 235:338–350.

Vahter M. 2002. Mechanisms of arsenic biotransformation. Toxicology 181–182:211–217.

Valenzuela OL, Borja-Aburto VH, Garcia-Vargas GG, Cruz-Gonzalez MB, Garcia-Montalvo EA, Calderon-Aranda ES, et al. 2005. Urinary trivalent methylated arsenic species in a population chronically exposed to inorganic arsenic. Environ Health Perspect 113:250–254, doi: 10.1289/ehp.7519.

Vall O, Gómez-Culebras M, Garcia-Algar O, Joya X, Velez D, Rodriquez-Carrasco E, et al. 2012. Assessment of prenatal exposure to arsenic in Tenerife Island. PLoS One 7:e50463, doi: 10.1371/journal.pone.0050463.

Victora CG, Barros FC, Horta BL, Martorell R. 2001. Short-term benefits of catch-up growth for small-for-gestational-age infants. Int J Epidemiol 30:1325–1330.

Vincent HK, Taylor AG. 2006. Biomarkers and potential mechanisms of obesity-induced oxidant stress in humans. Int J Obes (Lond) 30:400–418, doi: 10.1038/sj.ijo.0803177.

Watanabe T, Hirano S. 2013. Metabolism of arsenic and its toxicological relevance. Arch Toxicol 87:969–979, doi: 10.1007/s00204-012-0904-5.

Wickett JC, Vernon PA, Lee DH. 2000. Relationships between factors of intelligence and brain volume. Pers Individ Dif 29:1095–1122, doi: 10.1016/S0191-8869(99)00258-5.

Wilhelm-Benartzi CS, Houseman EA, Maccani MA, Poage GM, Koestler DC, Langevin SM, et al. 2012. In utero exposures, infant growth, and DNA methylation of repetitive elements and developmentally related genes in human placenta. Environ Health Perspect 120:296–302, doi: 10.1289/ehp.1103927.

Wood SN. 2003. Thin plate regression splines. J R Stat Soc Ser B Stat Methodol 65(1):95–114, doi: 10.1111/1467-9868.00374.

Wu G, Bazer FW, Cudd TA, Meininger CJ, Spencer TE. 2004. Maternal nutrition and fetal development. J Nutr 134:2169–2172.

Xu WX, Liu Y, Liu SZ, Zhang Y, Qiao GF, Yan J. 2014. Arsenic trioxide exerts a double effect on osteoblast growth in vitro. Environ Toxicol Pharmacol 38:412–419, doi: 10.1016/j.etap.2014.07.010.

Xu Y, Wang Y, Zheng Q, Li X, Li B, Jin Y, et al. 2008. Association of oxidative stress with arsenic methylation in chronic arsenic-exposed children and adults. Toxicol Appl Pharmacol 232:142–149, doi: 10.1016/j.taap.2008.06.010.

Yang CY, Chang CC, Tsai SS, Chuang HY, Ho CK, Wu TN. 2003. Arsenic in drinking water and adverse pregnancy outcome in an arseniasis-endemic area in northeastern Taiwan. Environ Res 91:29–34.


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