Associations of urinary polycyclic aromatic hydrocarbon (PAH) metabolites and their mixture with thyroid hormone concentration during pregnancy in the LIFECODES cohort: A repeated measures study.

BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) are endocrine disruptors resulting from incomplete combustion. Pregnancy represents a particularly vulnerable period to such exposures, given the significant influence of hormone physiology on fetal growth and pregnancy outcomes. Maternal thyroid hormones play crucial roles in fetal development and pregnancy outcomes. However, limited studies have examined gestational PAH exposure and maternal thyroid hormones during pregnancy. METHODS: Our study included 439 women enrolled in the LIFECODES birth cohort in Boston, aiming to explore the relationship between urinary PAH metabolites and thyroid hormones throughout pregnancy. Urine samples for PAH metabolite analysis and plasma samples for thyroid hormone were measured up to four visits throughout gestation. Single pollutant analyses employed linear mixed effect models to investigate individual associations between each PAH metabolite and thyroid hormone concentration. Sensitivity analyses were conducted to assess potential susceptibility windows and fetal-sex-specific effects of PAH exposure. Mixture analyses utilized quantile g-computation to evaluate the collective impact of eight PAH metabolites on thyroid hormone concentrations. Additionally, Bayesian kernel machine regression (BKMR) was employed to explore potential non-linear associations and interactions between PAH metabolites. Subject-specific random intercepts were incorporated to address intra-individual correlation of serial measurements over time in both single pollutant and mixture analyses. RESULTS: Our findings revealed positive trends in associations between PAH metabolites and thyroid hormones, both individually and collectively as a mixture. Sensitivity analyses indicated that these associations were influenced by the study visit and fetal sex. Mixture analyses suggested non-linear relationships and interactions between different PAH exposures. CONCLUSIONS: This comprehensive investigation underscores the critical importance of understanding the impact of PAH exposures on thyroid hormone physiology during pregnancy. The findings highlight the intricate interplay between environmental pollutants and human pregnancy physiology, emphasizing the need for targeted interventions and public health policies to mitigate adverse outcomes associated with prenatal PAH exposure.

Environmental phenol exposures in 6- to 12-week-old infants: The Infant Feeding and Early Development (IFED) study.

BACKGROUND: Exposure to phenols, endocrine-disrupting chemicals used in personal care and consumer products, is widespread. Data on infant exposures are limited despite heightened sensitivity to endocrine disruption during this developmental period. We aimed to describe distributions and predictors of urinary phenol concentrations among U.S. infants ages 6-12 weeks. METHODS: The Infant Feeding and Early Development (IFED) study is a prospective cohort study of healthy term infants enrolled during 2010-2013 in the Philadelphia region. We measured concentrations of seven phenols in 352 urine samples collected during the 6- or 8- and/or 12-week study visits from 199 infants. We used linear mixed models to estimate associations of maternal, sociodemographic, infant, and sample characteristics with natural-log transformed, creatinine-standardized phenol concentrations and present results as mean percent change from the reference level. RESULTS: Median concentrations (µg/L) were 311 for methylparaben, 10.3 for propylparaben, 3.6 for benzophenone-3, 2.1 for triclosan, 1.0 for 2,5-dichlorophenol, 0.7 for BPA, and 0.3 for 2,4-dichlorophenol. Geometric mean methylparaben concentrations were approximately 10 times higher than published estimates for U.S. children ages 3-5 and 6-11 years, while propylparaben concentrations were 3-4 times higher. Infants of Black mothers had higher concentrations of BPA (83%), methylparaben (121%), propylparaben (218%), and 2,5-dichorophenol (287%) and lower concentrations of benzophenone-3 (-77%) and triclosan (-53%) than infants of White mothers. Triclosan concentrations were higher in breastfed infants (176%) and lower in infants whose mothers had a high school education or less (-62%). Phenol concentrations were generally higher in summer samples. CONCLUSIONS: Widespread exposure to select environmental phenols among this cohort of healthy U.S. infants, including much higher paraben concentrations compared to those reported for U.S. children, supports the importance of expanding population-based biomonitoring programs to infants and toddlers. Future investigation of exposure sources is warranted to identify opportunities to minimize exposures during these sensitive periods of development.

Fetal growth trajectories of babies born large-for-gestational age in the LIFECODES Fetal Growth Study.

BACKGROUND: Babies born large-for-gestational age have an increased risk of adverse health outcomes, including birth injuries, childhood obesity, and cardiometabolic disorders. However, little work has been done to characterize patterns of fetal growth among large-for-gestational age births, which may further elucidate high- and low-risk subgroups. OBJECTIVE: This study aimed to identify subgroups of large-for-gestational age births based on trajectories of fetal growth derived from prenatal ultrasound measurements and explore differences in sociodemographic, pregnancy, and birth outcome characteristics across subgroups. STUDY DESIGN: This study identified and described trajectories of fetal growth among large-for-gestational age births (n=235) in the LIFECODES Fetal Growth Study. Ultrasound measurements of fetal growth in middle to late pregnancy were abstracted from health records. Group-based multi-trajectory modeling was applied to measurements of head circumference, abdominal circumference, and femur length z-scores to identify multivariate trajectories of fetal growth. Moreover, sociodemographic variables, pregnancy characteristics, and birth outcomes based on trajectory membership were summarized. RESULTS: This study identified 4 multivariate trajectories of fetal growth among large-for-gestational age births: catch-up growth (n=28), proportional abdominal circumference-to-femur length growth (n=67), disproportional abdominal circumference-to-femur length growth (n=96), and consistently large (n=44). Fetuses in the "catch-up growth" group exhibited small relative sizes in midpregnancy (ie, below average head circumference, abdominal circumference, and femur length z-scores) and large relative sizes in late pregnancy. Growth among these births was driven by increases in relative abdominal circumference and head circumference sizes. Participants who delivered births assigned to this group were less likely to have normal glucose control (40% vs 65%-75%) and more likely to have pregestational diabetes mellitus (36% vs 10%-17%) than other large-for-gestational age subgroups. In addition, the babies in this trajectory group were more likely to have macrosomia (86% vs 67%-73%) and to be admitted to the neonatal intensive care unit (32% vs 14%-21%) than other large-for-gestational age subgroups. In contrast, babies in the "consistently large" group had the largest relative size for all growth parameters throughout gestation and experienced a lower risk of adverse birth outcomes than other large-for-gestational age subgroups. CONCLUSION: This study characterized several trajectories of fetal growth among large-for-gestational age births, which were related to different pregnancy characteristics and the distribution of adverse birth outcomes. Although the number of individuals within some trajectories was small, a subgroup that exhibited a catch-up growth phenotype during gestation was identified, which may be uniquely associated with exposure to pregestational diabetes mellitus and a higher risk of admission to the neonatal intensive care unit. These results have highlighted that the risk of adverse outcomes may not be evenly distributed across all large-for-gestational age births.

An application of group-based trajectory modeling to define fetal growth phenotypes among small-for-gestational-age births in the LIFECODES Fetal Growth Study.

BACKGROUND: Reductions in fetal growth are associated with adverse outcomes at birth and later in life. However, identifying fetuses with pathologically small growth remains challenging. Definitions of small-for-gestational age are often used as a proxy to identify those experiencing pathologic growth (ie, fetal growth restriction). However, this approach is subject to limitation as most newborns labeled small-for-gestational age are constitutionally, not pathologically, small. Incorporating repeated ultrasound measures to examine fetal growth trajectories may help distinguish pathologic deviations in growth from normal variability, beyond a simple definition of small-for-gestational age. OBJECTIVE: This study aimed to characterize phenotypes of growth using ultrasound trajectories of fetal growth among small-for-gestational-age births. STUDY DESIGN: This study identified and described trajectories of fetal growth among small-for-gestational-age births (<10th percentile weight for gestational age; n=245) in the LIFECODES Fetal Growth Study using univariate and multivariate trajectory modeling approaches. Available ultrasound measures of fetal growth (estimated fetal weight, head circumference, abdominal circumference, and femur length) from health records were abstracted. First, univariate group-based trajectory modeling was used to define trajectories of estimated fetal weight z scores during gestation. Second, group-based multi-trajectory modeling was used to identify trajectories based on concurrent measures of head circumference, abdominal circumference, and femur length z scores. Last, how these trajectories were related to patient demographics, pregnancy characteristics, and birth outcomes compared with those observed among appropriate-for-gestational-age controls was described. RESULTS: Of note, 3 univariate trajectories of estimated fetal weight and 4 multivariate trajectories of fetal growth among small-for-gestational-age births were identified. In our univariate approach, infants with the smallest estimated fetal weight trajectory throughout pregnancy had poorer outcomes, including the highest risk of neonatal intensive care unit admission. The remaining univariate trajectory groups did not have an elevated risk of adverse birth outcomes relative to appropriate-for-gestational-age controls. In our multivariate approach, 2 groups at increased or moderately increased risk of neonatal intensive care unit admission were identified, including infants that remained extremely small for all parameters throughout pregnancy and those who had disproportionately smaller femur length and abdominal circumference compared with head circumference. The remaining multivariate trajectory groups did not have an elevated risk of adverse birth outcome relative to appropriate-for-gestational-age controls. CONCLUSION: Latent class group-based trajectory modeling applied to ultrasound measures of fetal growth may help distinguish pathologic vs constitutional growth profiles among newborns born small-for-gestational age. Although trajectories cannot be fully characterized until delivery, limiting the direct clinical application of these methods, they may still contribute to the development of approaches for separating growth restriction from constitutional smallness.

Urinary oxidative stress biomarkers are associated with preterm birth: an Environmental Influences on Child Health Outcomes program study.

BACKGROUND: Preterm birth is the leading cause of infant morbidity and mortality worldwide. Elevated levels of oxidative stress have been associated with an increased risk of delivering before term. However, most studies testing this hypothesis have been conducted in racially and demographically homogenous study populations, which do not reflect the diversity within the United States. OBJECTIVE: We leveraged 4 cohorts participating in the Environmental Influences on Child Health Outcomes Program to conduct the largest study to date examining biomarkers of oxidative stress and preterm birth (N=1916). Furthermore, we hypothesized that elevated oxidative stress would be associated with higher odds of preterm birth, particularly preterm birth of spontaneous origin. STUDY DESIGN: This study was a pooled analysis and meta-analysis of 4 birth cohorts spanning multiple geographic regions in the mainland United States and Puerto Rico (208 preterm births and 1708 full-term births). Of note, 8-iso-prostaglandin-F2α, 2,3-dinor-5,6-dihydro-8-iso-prostaglandin-F2α (F2-IsoP-M; the major 8-iso-prostaglandin-F2α metabolite), and prostaglandin-F2α were measured in urine samples obtained during the second and third trimesters of pregnancy. Logistic regression was used to calculate adjusted odds ratios and 95% confidence intervals for the associations between averaged biomarker concentrations for each participant and all preterm births, spontaneous preterm births, nonspontaneous preterm births (births of medically indicated or unknown origin), and categories of preterm birth (early, moderate, and late). Individual oxidative stress biomarkers were examined in separate models. RESULTS: Approximately 11% of our analytical sample was born before term. Relative to full-term births, an interquartile range increase in averaged concentrations of F2-IsoP-M was associated with higher odds of all preterm births (odds ratio, 1.29; 95% confidence interval, 1.11-1.51), with a stronger association observed for spontaneous preterm birth (odds ratio, 1.47; 95% confidence interval, 1.16-1.90). An interquartile range increase in averaged concentrations of 8-iso-prostaglandin-F2α was similarly associated with higher odds of all preterm births (odds ratio, 1.19; 95% confidence interval, 0.94-1.50). The results from our meta-analysis were similar to those from the pooled combined cohort analysis. CONCLUSION: Here, oxidative stress, as measured by 8-iso-prostaglandin-F2α, F2-IsoP-M, and prostaglandin-F2α in urine, was associated with increased odds of preterm birth, particularly preterm birth of spontaneous origin and delivery before 34 completed weeks of gestation.

Variability and Longitudinal Trajectories of Phthalate and Replacement Biomarkers across Pregnancy in the Human Placenta and Phthalates Study.

Human exposure to phthalates is widespread, but assessment of variability across pregnancy has been hampered by short half-lives of phthalate biomarkers and a few repeated measures in prior studies. We aimed to characterize the variability and longitudinal profiles of phthalate and replacement biomarkers across pregnancy. Within the Human Placenta and Phthalates Study, 303 pregnant women provided urine samples at up to 8 visits across gestation. Concentrations of 14 metabolites of phthalates and 4 metabolites of replacements were quantified in each sample, and subject-specific averages within each trimester were calculated. We examined variability in individual biomarker concentrations across the 8 visits, within trimesters, and across trimester-specific averages using intraclass correlation coefficients (ICCs). To explore longitudinal exposure biomarker profiles, we applied group-based trajectory modeling to trimester-specific averages over pregnancy. Pooling multiple visits into trimester-specific averages improved the ICCs for all biomarkers. Most biomarkers generally showed stable concentrations across gestation, i.e., high-, medium-, and low-concentration profiles, with small proportions of participants falling into the "high"-exposure groups. Variability over pregnancy is likely attributable to random fluctuations around a baseline exposure rather than true changes in concentrations over time.

Prenatal per- and polyfluoroalkyl substances (PFAS) exposure in relation to preterm birth subtypes and size-for-gestational age in the LIFECODES cohort 2006-2008.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are a group of synthetic chemicals widely used in consumer and industrial products. Numerous studies have linked prenatal PFAS exposures to increased risks of adverse pregnancy outcomes such as preterm birth (PTB) and small-for-gestational age (SGA).However, limited evidence is available for the effects of PFAS on PTB subtypes and large-for-gestational age (LGA). OBJECTIVE: To examine the associations of PFAS with PTB [overall, placental (pPTB), spontaneous (sPTB)], BW Z-score, and size-for-gestational age (SGA, LGA). METHODS: Our nested case-control study included 128 preterm cases and 373 term controls from the LIFECODES cohort between 2006 and 2008 (n = 501). Plasma concentrations of nine PFAS were measured in early pregnancy samples. Logistic regression was used to assess individual PFAS-birth outcome associations, while Bayesian Kernel Machine Regression (BKMR) was used to evaluate the joint effects of all PFAS. Effect modification by fetal sex was examined, and stratified analyses were conducted to obtain fetal sex-specific estimates. RESULTS: Compared to term births, the odds of pPTB were higher from an interquartile range increase in perfluorodecanoic acid (PFDA) (OR = 1.60, 95% CI: 1.00-2.56), perfluorononanoic acid (PFNA) (OR = 1.67, 95% CI: 1.06-2.61), and perfluoroundecanoic acid (PFUA) (OR = 1.77, 95% CI: 1.00-3.12), with stronger associations observed in women who delivered males. BKMR analysis identified PFNA as the most important PFAS responsible for pPTB (conditional PIP = 0.78), with increasing ORs at higher percentiles of PFAS mixture. For LGA, positive associations were observed with PFDA and perfluorooctanoic acid in females only, and with PFUA in males only. BKMR analysis showed increasing, but null effects of PFAS mixture on LGA. CONCLUSIONS: The effect of prenatal exposure to single and multiple PFAS on PTB and LGA depended on fetal sex. Future studies should strongly consider examining PTB subtypes and sex-specific effects of PFAS on pregnancy outcomes.

Early pregnancy phthalates and replacements in relation to fetal growth: The human placenta and phthalates study.

BACKGROUND: Pregnant persons are exposed ubiquitously to phthalates and increasingly to chemicals introduced to replace phthalates. In early pregnancy, exposure to these chemicals may disrupt fetal formation and development, manifesting adverse fetal growth. Previous studies examining the consequences of early pregnancy exposure relied on single spot urine measures and did not investigate replacement chemicals. OBJECTIVE: Characterize associations between urinary phthalate and replacement biomarkers in early pregnancy and fetal growth outcomes. METHODS: Analyses were conducted among 254 pregnancies in the Human Placenta and Phthalates Study, a prospective cohort with recruitment 2017-2020. Exposures were geometric mean concentrations of phthalate and replacement biomarkers quantified in two spot urine samples collected around 12- and 14-weeks of gestation. Outcomes were fetal ultrasound biometry (head and abdominal circumferences, femur length, estimated fetal weight) collected in each trimester and converted to z-scores. Adjusted linear mixed effects (single-pollutant) and quantile g-computation (mixture) models with participant-specific random effects estimated the difference, on average, in longitudinal fetal growth for a one-interquartile range (IQR) increase in individual (single-pollutant) or all (mixture) early pregnancy phthalate and replacement biomarkers. RESULTS: Mono carboxyisononyl phthalate and the sums of metabolites of di-n-butyl, di-iso-butyl, and di-2-ethylhexyl phthalate were inversely associated with fetal head and abdominal circumference z-scores. A one-IQR increase in the phthalate and replacement biomarker mixture was inversely associated with fetal head circumference (ß: -0.36 [95% confidence interval: -0.56, -0.15]) and abdominal circumference (-0.31 [-0.49, -0.12]) z-scores. This association was mainly driven by phthalate biomarkers. CONCLUSIONS: Urine concentrations of phthalate biomarkers, but not replacement biomarkers, in early pregnancy were associated with reductions in fetal growth. Though the clinical implications of these differences are unclear, reduced fetal growth contributes to excess morbidity and mortality across the lifecourse. Given widespread global exposure to phthalates, findings suggest a substantial population health burden resulting from early pregnancy phthalate exposure.

Combining Urinary Biomarker Data From Studies With Different Measures of Urinary Dilution.

BACKGROUND: Guidance is lacking for how to combine urinary biomarker data across studies that use different measures of urinary dilution, that is, creatinine or specific gravity. METHODS: Among 741 pregnant participants from four sites of The Infant Development and Environment Study (TIDES) cohort, we assessed the relation of maternal urinary di-2-ethylhexyl phthalate (DEHP) concentrations with preterm birth. We compared scenarios in which all sites measured either urinary creatinine or specific gravity, or where measure of dilution differed by site. In addition to a scenario with no dilution adjustment, we applied and compared three dilution-adjustment approaches: a standard regression-based approach for creatinine, a standard approach for specific gravity (Boeniger method), and a more recently developed approach that has been applied to both (covariate-adjusted standardization method). For each scenario and dilution-adjustment method, we estimated the association between a doubling in the molar sum of DEHP (∑DEHP) and odds of preterm birth using logistic regression. RESULTS: All dilution-adjustment approaches yielded comparable associations (odds ratio [OR]) that were larger in magnitude than when we did not perform dilution adjustment. A doubling of ∑DEHP was associated with 9% greater odds of preterm birth (OR = 1.09, 95% confidence interval [CI] = 0.91, 1.30) when applying no dilution-adjustment method, whereas dilution-adjusted point estimates were higher, and similar across all scenarios and methods: 1.13-1.20 (regression-based), 1.15-1.18 (Boeniger), and 1.14-1.21 (covariate-adjusted standardization). CONCLUSIONS: In our applied example, we demonstrate that it is possible and straightforward to combine urinary biomarker data across studies when measures of dilution differ.

Design and methods of the Apple Women's Health Study: a digital longitudinal cohort study.

BACKGROUND: Prospective longitudinal cohorts assessing women's health and gynecologic conditions have historically been limited. OBJECTIVE: The Apple Women's Health Study was designed to gain a deeper understanding of the relationship among menstrual cycles, health, and behavior. This paper describes the design and methods of the ongoing Apple Women's Health Study and provides the demographic characteristics of the first 10,000 participants. STUDY DESIGN: This was a mobile-application-based longitudinal cohort study involving survey and sensor-based data. We collected the data from 10,000 participants who responded to the demographics survey on enrollment between November 14, 2019 and May 20, 2020. The participants were asked to complete a monthly follow-up through November 2020. The eligibility included installed Apple Research app on their iPhone with iOS version 13.2 or later, were living in the United States, being of age greater than 18 years (19 in Alabama and Nebraska, 21 years old in Puerto Rico), were comfortable in communicating in written and spoken English, were the sole user of an iCloud account or iPhone, and were willing to provide consent to participate in the study. RESULTS: The mean age at enrollment was 33.6 years old (±standard deviation, 10.3). The race and ethnicity was representative of the US population (69% White and Non-Hispanic [6910/10,000]), whereas 51% (5089/10,000) had a college education or above. The participant geographic distribution included all the US states and Puerto Rico. Seventy-two percent (7223/10,000) reported the use of an Apple Watch, and 24.4% (2438/10,000) consented to sensor-based data collection. For this cohort, 38% (3490/9238) did not respond to the Monthly Survey: Menstrual Update after enrollment. At the 6-month follow-up, there was a 35% (3099/8972) response rate to the Monthly Survey: Menstrual Update. 82.7% (8266/10,000) of the initial cohort and 95.1% (2948/3099) of the participants who responded to month 6 of the Monthly Survey: Menstrual Update tracked at least 1 menstrual cycle via HealthKit. The participants tracked their menstrual bleeding days for an average of 4.44 (25%-75%; range, 3-6) calendar months during the study period. Non-White participants were slightly more likely to drop out than White participants; those remaining at 6 months were otherwise similar in demographic characteristics to the original enrollment group. CONCLUSION: The first 10,000 participants of the Apple Women's Health Study were recruited via the Research app and were diverse in race and ethnicity, educational attainment, and economic status, despite all using an Apple iPhone. Future studies within this cohort incorporating this high-dimensional data may facilitate discovery in women's health in exposure outcome relationships and population-level trends among iPhone users. Retention efforts centered around education, communication, and engagement will be utilized to improve the survey response rates, such as the study update feature.

Semiparametric analysis of a generalized linear model with multiple covariates subject to detection limits.

Studies on the health effects of environmental mixtures face the challenge of limit of detection (LOD) in multiple correlated exposure measurements. Conventional approaches to deal with covariates subject to LOD, including complete-case analysis, substitution methods, and parametric modeling of covariate distribution, are feasible but may result in efficiency loss or bias. With a single covariate subject to LOD, a flexible semiparametric accelerated failure time (AFT) model to accommodate censored measurements has been proposed. We generalize this approach by considering a multivariate AFT model for the multiple correlated covariates subject to LOD and a generalized linear model for the outcome. A two-stage procedure based on semiparametric pseudo-likelihood is proposed for estimating the effects of these covariates on health outcome. Consistency and asymptotic normality of the estimators are derived for an arbitrary fixed dimension of covariates. Simulations studies demonstrate good large sample performance of the proposed methods vs conventional methods in realistic scenarios. We illustrate the practical utility of the proposed method with the LIFECODES birth cohort data, where we compare our approach to existing approaches in an analysis of multiple urinary trace metals in association with oxidative stress in pregnant women.

Associations between mixtures of urinary phthalate metabolite concentrations and oxidative stress biomarkers among couples undergoing fertility treatment.

Phthalate exposure has been associated with adverse reproductive outcomes and oxidative stress is a potential mechanism by which they act. However, few human studies have explored co-exposure confounding or joint effects. Furthermore, most studies examine associations between biomarkers of exposure and oxidative stress from the same urine sample. We investigated single-exposure, co-exposure-adjusted, and joint associations between phthalate metabolites and oxidative stress in the Environment and Reproductive Health (EARTH) study among couples undergoing fertility treatment. We examined cross-sectional associations in both women and men, and longitudinal associations in women. Urine was collected in the follicular phase (women only) and at the time of fertility procedure (women and men), and analyzed for 11 phthalate metabolites. Urine from the time of fertility procedure was analyzed for oxidative stress biomarkers, including free 8-iso-prostaglandin F2α (8-iso-PGF2α), its primary metabolite (2,3-dinor-5,6-dihydro-15-F2t-isoprostane [F2-IsoP-M]), and prostaglandin F2α (PGF2α). Linear mixed effects models were used to estimate single-exposure associations. Bayesian Kernel Machine Regression (BKMR) was used to adjust for co-exposures and to estimate joint effects. Among women, we observed positive associations between all phthalate metabolites and oxidative stress biomarkers in single-exposure models, but there was clear co-exposure confounding. For instance, in a single-exposure model, we estimated a 63% (95% confidence interval: 51, 77) increase in the 8-iso-PGF2α metabolite per interquartile range (IQR) difference in mono-n-butyl phthalate (MBP) versus a 34% (95% credible interval: 12, 60) increase in co-adjusted models. However, several phthalate metabolites remained associated with oxidative stress in co-exposure models, and the joint effects of all exposures were high (e.g., an 114% increase in the 8-iso-PGF2α metabolite per IQR difference in all exposures). Longitudinal results were also attenuated compared to cross-sectional results in women; however, the joint effect of all exposures and the 8-iso-PGF2α metabolite remained positive and statistically significant (11% increase per IQR difference in all exposures, 95% credible interval: 0.2, 23). In men, associations were generally less pronounced, although the joint effect of the mixture on 8-iso-PGF2α was above the null. Because oxidative stress is related to reproductive success among couples seeking fertility treatment, mitigating phthalate exposure should be considered as a potentially beneficial measure.

Urinary glyphosate concentration in pregnant women in relation to length of gestation.

Human exposure to glyphosate-based herbicides (GBH) is increasing rapidly worldwide. Most existing studies on health effects of glyphosate have focused on occupational settings and cancer outcomes and few have examined this common exposure in relation to the health of pregnant women and newborns in the general population. We investigated associations between prenatal glyphosate exposure and length of gestation in The Infant Development and the Environment Study (TIDES), a multi-center US pregnancy cohort. Glyphosate and its primary degradation product [aminomethylphosphonic acid (AMPA)] were measured in urine samples collected during the second trimester from 163 pregnant women: 69 preterm births (<37 weeks) and 94 term births, the latter randomly selected as a subset of TIDES term births. We examined the relationship between exposure and length of gestation using multivariable logistic regression models (dichotomous outcome; term versus preterm) and with weighted time-to-event Cox proportional hazards models (gestational age in days). We conducted these analyses in the overall sample and secondarily, restricted to women with spontaneous deliveries (n = 90). Glyphosate and AMPA were detected in most urine samples (>94 %). A shortened gestational length was associated with maternal glyphosate (hazard ratio (HR): 1.31, 95 % confidence interval (CI) 1.00-1.71) and AMPA (HR: 1.32, 95%CI: 1.00-1.73) only among spontaneous deliveries using adjusted Cox proportional hazards models. In binary analysis, glyphosate and AMPA were not associated with preterm birth risk (<37 weeks). Our results indicate widespread exposure to glyphosate in the general population which may impact reproductive health by shortening length of gestation. Given the increasing exposure to GBHs and the public health burden of preterm delivery, larger confirmatory studies are needed, especially in vulnerable populations such as pregnant women and newborns.

Fetal Growth Trajectories Among Small for Gestational Age Babies and Child Neurodevelopment.

BACKGROUND: Being born small for gestational age (SGA, <10th percentile) is a risk factor for worse neurodevelopmental outcomes. However, this group is a heterogeneous mix of healthy and growth-restricted babies, and not all will experience poor outcomes. We sought to determine whether fetal growth trajectories can distinguish who will have the worst neurodevelopmental outcomes in childhood among babies born SGA. METHODS: The present analysis was conducted in Generation R, a population-based cohort in Rotterdam, the Netherlands (N = 5,487). Using group-based trajectory modeling, we identified fetal growth trajectories for weight among babies born SGA. These were based on standard deviation scores of ultrasound measures from mid-pregnancy and late pregnancy in combination with birth weight. We compared child nonverbal intelligence quotient (IQ) and attention deficit hyperactivity disorder (ADHD) symptoms at age 6 between SGA babies within each growth trajectory to babies born non-SGA. RESULTS: Among SGA individuals (n = 656), we identified three distinct fetal growth trajectories for weight. Children who were consistently small from mid-pregnancy (n = 64) had the lowest IQ (7 points lower compared to non-SGA babies, 95% confidence interval [CI] = -11.0, -3.5) and slightly more ADHD symptoms. Children from the trajectory that started larger but were smaller at birth showed no differences in outcomes compared to children born non-SGA. CONCLUSIONS: Among SGA children, those who were smaller beginning in mid-pregnancy exhibited the worst neurodevelopmental outcomes at age 6. Fetal growth trajectories may help identify SGA babies who go on to have poor neurodevelopmental outcomes.

Prenatal Exposure to Nonpersistent Chemical Mixtures and Offspring IQ and Emotional and Behavioral Problems.

Prenatal exposure to nonpersistent chemicals such as phthalates, bisphenols, and organophosphate (OP) pesticides is ubiquitous and occurs in mixtures. So far, epidemiological studies investigating neurodevelopmental consequences of these exposures have mainly been restricted to single-pollutant models. Thus, we studied the association between prenatal exposure to nonpersistent chemical mixtures and child IQ and emotional and behavioral problems. Data came from 782 mother-child pairs. Eleven phthalate, one bisphenol, and five OP pesticide urinary exposure biomarkers were measured three times during pregnancy and averaged. Nonverbal IQ, internalizing and attention problems, aggressive behavior, and autistic traits were assessed at child age 6 years. We used quantile g-computation to estimate the change in each outcome per quartile increase in all chemicals within the mixture. Higher exposure to the mixture was associated with lower nonverbal IQ (-4.0 points (95%CI = -7.0, -1.0), -5.5 points (95%CI = -10.2, -0.9), and -4.6 points (95%CI = -10.8, 1.5) for the second, third, and fourth quartile, respectively, compared to the first quartile). These results were mainly driven by the phthalate mixture. No association was observed with emotional and behavioral problems. Prenatal exposure to nonpersistent chemical mixtures was associated with lower nonverbal IQ in children. Exposure to chemical mixtures during gestation is universal and may impact neurodevelopment.

A prospective study of maternal 25-hydroxyvitamin D (25OHD) in the first trimester of pregnancy and second trimester heavy metal levels.

BACKGROUND: Vitamin D facilitates the absorption of calcium but may also increase absorption of other metals; the literature is conflicting. OBJECTIVE: To examine whether 25OHD in the first trimester of pregnancy was associated with subsequent metals levels in the late second trimester of pregnancy. METHODS: We used data from a sample of women in the LIFECODES pregnancy cohort (N = 381). 25-hydroxyvitamin D (25OHD) was measured with a chemiluminescence immunoassay in plasma samples drawn at 10 weeks of gestation. A panel of 17 metals and elements was measured in urine collected at 26 weeks of gestation. We used linear or logistic regression to estimate associations between 25OHD (dichotomous, linear, and in tertiles) and either urinary metal concentrations or the proportion of samples below the limit of detection, respectively. Multivariable models included urinary specific gravity, age, race/ethnicity, education, body mass index, insurance type, gestational age, and season. RESULTS: After multivariable adjustment, low 25OHD was associated with a 47% increase in lead level, a 60% increase in tin level, and 1.58 times the odds of detectable tungsten. A 10 ng/ml increase in 25OHD was associated with a 12% decrease in tin and an 8% increase in molybdenum. While we had a small sample size, we found some evidence of effect modification by race. Women who reported their race as Black or were classified in the other race category, who also had low 25OHD, had 40% higher thallium than women with higher 25OHD and were more likely to have detectable beryllium and tungsten. These metals were not associated with low 25OHD in women who reported their race as White. Tin and lead were higher in women with low 25OHD in all race groups. DISCUSSION: In total, further research is warranted to determine if vitamin D levels alter metal levels, and to elucidate the shape of the association for each metal across a range of corresponding 25OHD levels, and longitudinally, across pregnancy. This is especially true for pregnant people as exposure to metals during pregnancy has health consequences for the fetus.

A hierarchical integrative group least absolute shrinkage and selection operator for analyzing environmental mixtures.

Environmental health studies are increasingly measuring multiple pollutants to characterize the joint health effects attributable to exposure mixtures. However, the underlying dose-response relationship between toxicants and health outcomes of interest may be highly nonlinear, with possible nonlinear interaction effects. Existing penalized regression methods that account for exposure interactions either cannot accommodate nonlinear interactions while maintaining strong heredity or are computationally unstable in applications with limited sample size. In this paper, we propose a general shrinkage and selection framework to identify noteworthy nonlinear main and interaction effects among a set of exposures. We design hierarchical integrative group least absolute shrinkage and selection operator (HiGLASSO) to (a) impose strong heredity constraints on two-way interaction effects (hierarchical), (b) incorporate adaptive weights without necessitating initial coefficient estimates (integrative), and (c) induce sparsity for variable selection while respecting group structure (group LASSO). We prove sparsistency of the proposed method and apply HiGLASSO to an environmental toxicants dataset from the LIFECODES birth cohort, where the investigators are interested in understanding the joint effects of 21 urinary toxicant biomarkers on urinary 8-isoprostane, a measure of oxidative stress. An implementation of HiGLASSO is available in the higlasso R package, accessible through the Comprehensive R Archive Network.

Longitudinal profiles of plasma eicosanoids during pregnancy and size for gestational age at delivery: A nested case-control study.

BACKGROUND: Inflammation during pregnancy is hypothesized to influence fetal growth. Eicosanoids, an important class of lipid mediators derived from polyunsaturated fatty acids, can act as both direct influences and biomarkers of inflammation through a variety of biological pathways. However, quantifying these distinct inflammatory pathways has proven difficult. We aimed to characterize a comprehensive panel of plasma eicosanoids longitudinally across gestation in pregnant women and to determine whether levels differed by infant size at delivery. METHODS AND FINDINGS: Our data come from a case-control study of 90 pregnant women nested within the LIFECODES prospective birth cohort study conducted at Brigham and Women's Hospital in Boston, Massachusetts. This study included 31 women who delivered small for gestational age (SGA) babies (SGA, ≤10th percentile), 28 who delivered large for gestational age (LGA) babies (≥90th percentile), and 31 who delivered appropriate for gestational age (AGA) babies (controls, >10th to <90th percentile). All deliveries occurred between 2010 and 2017. Most participants were in their early 30s (median age: 33 years), of white (60%) or black (20%) race/ethnicity, and of normal pre-pregnancy BMI (median BMI: 23.5 kg/m2). Women provided non-fasting plasma samples during 3 prenatal study visits (at median 11, 25, and 35 weeks gestation) and were analyzed for a panel of eicosanoids. Eicosanoids were grouped by biosynthetic pathway, defined by (1) the fatty acid precursor, including linoleic acid (LA), arachidonic acid (AA), docosahexaenoic acid (DHA), or eicosapentaenoic acid (EPA), and (2) the enzyme group, including cyclooxygenase (COX), lipoxygenase (LOX), or cytochrome P450 (CYP). Additionally, the concentrations of the 4 fatty acids (LA, AA, DHA, and EPA) were measured in maternal plasma. Analytes represent lipids from non-esterified plasma. We examined correlations among eicosanoids and trajectories across pregnancy. Differences in longitudinal concentrations between case groups were examined using Bayesian linear mixed effects models, which included participant-specific random intercepts and penalized splines on gestational age. Results showed maternal plasma levels of eicosanoids and fatty acids generally followed U-shaped curve patterns across gestation. Bayesian models showed that associations between eicosanoids and case status varied by biosynthetic pathway. Eicosanoids derived from AA via the CYP and LOX biosynthetic pathways were positively associated with SGA. The adjusted mean concentration of 12-HETE, a LOX pathway product, was 56.2% higher (95% credible interval 6.6%, 119.1%) among SGA cases compared to AGA controls. Eicosanoid associations with LGA were mostly null, but negative associations were observed with eicosanoids derived from AA by LOX enzymes. The fatty acid precursors had estimated mean concentrations 41%-97% higher among SGA cases and 33%-39% lower among LGA cases compared to controls. Primary limitations of the study included the inability to explore the potential periods of susceptibility of eicosanoids on infant size due to limited sample size, along with the use of infant size at delivery instead of longitudinal ultrasound measures to estimate fetal growth. CONCLUSIONS: In this nested case-control study, we found that eicosanoids and fatty acids systematically change in maternal plasma over pregnancy. Eicosanoids from specific inflammation-related pathways were higher in mothers of SGA cases and mostly similar in mothers of LGA cases compared to controls. These findings can provide deeper insight into etiologic mechanisms of abnormal fetal growth outcomes.

Prenatal exposure to organophosphate pesticides and brain morphology and white matter microstructure in preadolescents.

BACKGROUND: Prenatal exposure to organophosphate (OP) pesticides associate with impaired neurodevelopment in humans and animal models. However, much uncertainty exists about the brain structural alterations underlying these associations. The objective of this study was to determine whether maternal OP pesticide metabolite concentrations in urine repeatedly measured during gestation are associated with brain morphology and white matter microstructure in 518 preadolescents aged 9-12 years. METHOD: Data came from 518 mother-child pairs participating in the Generation R Study, a population-based birth cohort from Rotterdam, the Netherlands. Maternal urine concentrations were determined for 6 dialkylphosphates (DAPs) including 3 dimethyl (DM) and 3 diethyl (DE) alkyl phosphate metabolites, collected at early, mid, and late pregnancy. At child's age 9-12 years, magnetic resonance imaging was performed to obtain T1-weighted images for brain volumes and surface-based cortical thickness and cortical surface area, and diffusion tensor imaging was used to measure white matter microstructure through fractional anisotropy (FA) and mean diffusivity (MD). Linear regression models were fit for the averaged prenatal exposure across pregnancy. RESULTS: DM and DE metabolite concentrations were not associated with brain volumes, cortical thickness, and cortical surface area. However, a 10-fold increase in averaged DM metabolite concentrations across pregnancy was associated with lower FA (B = -1.00, 95%CI = -1.80, -0.20) and higher MD (B = 0.13, 95%CI = 0.04, 0.21). Similar associations were observed for DE concentrations. CONCLUSIONS: This study provides the first evidence that OP pesticides may alter normal white matter microstructure in children, which could have consequences for normal neurodevelopment. No associations were observed with structural brain morphology, including brain volumes, cortical thickness, and cortical surface area.

Association of urinary levels of bisphenols F and S used as bisphenol A substitutes with asthma and hay fever outcomes.

BACKGROUND: Bisphenols F (BPF) and S (BPS) are bisphenol A (BPA) analogs used as substitutes in consumer products. Despite previous reports of BPA's association with asthma, no studies have examined its structural analogs in relation to asthma and allergy outcomes. OBJECTIVE: To examine the association of urinary BPF, BPS, and BPA with asthma and hay fever in a US representative sample. METHODS: We analyzed data from 3,538 participants aged 12 years or older in the 2013-2016 National Health and Nutrition Examination Survey (NHANES). Children aged 6-11 years (N = 738), who did not have all covariate data available, were analyzed separately. Covariate-adjusted logistic regression was used to assess the association of the exposures with the outcomes. RESULTS: BPF, BPS, and BPA were detected in 57.1%, 88.4%, and 94.8% of the urine samples, respectively. Urinary BPF detection was positively associated with current asthma (odds ratio [OR]: 1.54, 95% confidence interval [CI]: 1.16-2.04) and hay fever (OR: 1.66, 95% CI: 1.12-2.46). Urinary BPS was associated with increased odds of current asthma in men (OR: 1.64, 95% CI: 1.13-2.40) and urinary BPA was associated with increased odds of asthma without hay fever in children aged 6-11 years (OR: 2.65, 95% CI: 1.05-6.68). CONCLUSION: Our nationally-representative findings document that BPF and BPS exposure is common in the US and that exposure to these BPA analogs is associated with asthma and/or hay fever. Our results suggest that BPF and BPS may not be safe alternatives to BPA; however, prospective studies should be conducted to confirm these results.