Birth hospitalization length of stay (LOS) is extended for infants with neonatal opioid withdrawal syndrome (NOWS),1 raising health care costs and complicating efforts to promote maternal-infant bonding.1–2 However, many infants exposed to opioids do not develop NOWS. The overall costs of intrauterine opioid exposure may be significantly greater if infants who do not develop withdrawal symptoms also have an increased LOS due to observation for the emergence of NOWS or other medical or social complications. Using data from the Environmental influences on Child Health Outcomes (ECHO)-wide cohort study funded by the National Institutes of Health, we evaluated whether opioid exposure not resulting in NOWS was associated with a longer LOS. We also performed similar evaluations of tobacco, alcohol, and cannabis, and considered the effect of combined exposures.

Background In the United States, disparities in gestational age at birth by maternal race, ethnicity, and geography are theorized to be related, in part, to differences in individual- and neighborhood-level socioeconomic status (SES). Yet, few studies have examined their combined effects or whether associations vary by maternal race and ethnicity and United States Census region. Methods We assembled data from 34 cohorts in the Environmental influences on Child Health Outcomes (ECHO) program representing 10,304 participants who delivered a liveborn, singleton infant from 2000 through 2019. We investigated the combined associations of maternal education level, neighborhood deprivation index (NDI), and Index of Concentration at the Extremes for racial residential segregation (ICERace) on gestational weeks at birth using linear regression and on gestational age at birth categories (preterm, early term, post–late term relative to full term) using multinomial logistic regression. Results After adjustment for NDI and ICERace, gestational weeks at birth was significantly lower among those with a high school diploma or less (−0.31 weeks, 95% CI: −0.44, −0.18), and some college (−0.30 weeks, 95% CI: −0.42, −0.18) relative to a master’s degree or higher. Those with a high school diploma or less also had an increased odds of preterm (aOR 1.59, 95% CI: 1.20, 2.10) and early term birth (aOR 1.26, 95% CI: 1.05, 1.51). In adjusted models, NDI quartile and ICERace quartile were not associated with gestational weeks at birth. However, higher NDI quartile (most deprived) associated with an increased odds of early term and late term birth, and lower ICERace quartile (least racially privileged) associated with a decreased odds of late or post-term birth. When stratifying by region, gestational weeks at birth was lower among those with a high school education or less and some college only among those living in the Northeast or Midwest. When stratifying by race and ethnicity, gestational weeks at birth was lower among those with a high school education or less only for the non-Hispanic White category. Conclusion In this study, maternal education was consistently associated with shorter duration of pregnancy and increased odds of preterm birth, including in models adjusted for NDI and ICERace.

Background: Heightened exposure to racial/ethnic discrimination is associated with poorer sleep health among non-pregnant adults. This relationship has received limited research attention among pregnant women, despite the importance of prenatal sleep quality for optimal maternal and child health outcomes. Methods: We utilized perinatal data from a sample of Black American women (n = 600) participating in a cohort study who reported their lifetime experiences of racial/ethnic discrimination and gendered racial stress during early pregnancy and reported on their sleep quality and depressive symptoms during early and mid-pregnancy. Hierarchical multiple linear regression models were fit to examine associations between lifetime experiences of racial/ethnic discrimination or gendered racial stress and sleep quality during early and mid-pregnancy. We also adjusted for women’s concurrent depressive symptoms and tested whether the discrimination/sleep quality association varied by socioeconomic status. Results: Greater exposure to racial/ethnic discrimination was associated with poorer sleep quality during early (ΔR2 = 0.04, ΔF = 26.08, p < 0.001) and mid-pregnancy (ΔR2 = 0.02, ΔF = 9.88, p = 0.002). Similarly, greater gendered racial stress was associated with poorer sleep quality during early (ΔR2 = 0.10, ΔF = 65.72, p < 0.001) and mid-pregnancy (ΔR2 = 0.06, ΔF = 40.43, p < 0.001. These findings largely held after adjustment for concurrent prenatal depressive symptoms. Socioeconomic status did not modify the observed relationships. Conclusions: Efforts to decrease institutional and interpersonal experiences of racial/ethnic discrimination and gendered racism would benefit the sleep quality of pregnant Black American women, particularly during early pregnancy.

Prenatal exposure to single chemicals belonging to the per- and polyfluoroalkyl substances (PFAS) family is associated with biological perturbations in the mother, fetus, and placenta, plus adverse health outcomes. Despite our knowledge that humans are exposed to multiple PFAS, the potential joint effects of PFAS on the metabolome remain largely unknown. Here, we leveraged high-resolution metabolomics to identify metabolites and metabolic pathways perturbed by exposure to a PFAS mixture during pregnancy. Targeted assessment of perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorooctanesulfonic acid (PFOS), and perfluorohexanesulfonic acid (PFHxS), along with untargeted metabolomics profiling, were conducted on nonfasting serum samples collected from pregnant African Americans at 6–17 weeks gestation. We estimated the overall mixture effect and partial effects using quantile g-computation and single-chemical effects using linear regression. All models were adjusted for maternal age, education, parity, early pregnancy body mass index, substance use, and gestational weeks at sample collection. Our analytic sample included 268 participants and was socioeconomically diverse, with the majority receiving public health insurance (78%). We observed 13.3% of the detected metabolic features were associated with the PFAS mixture (n = 1705, p < 0.05), which was more than any of the single PFAS chemicals. There was a consistent association with metabolic pathways indicative of systemic inflammation and oxidative stress (e.g., glutathione, histidine, leukotriene, linoleic acid, prostaglandins, and vitamins A, C, D, and E metabolism) across all metabolome-wide association studies. Twenty-six metabolites were validated against authenticated compounds and associated with the PFAS mixture (p < 0.05). Based on quantile g-computation weights, PFNA contributed the most to the overall mixture effect for γ-aminobutyric acid (GABA), tyrosine, and uracil. In one of the first studies of its kind, we demonstrate the feasibility and utility of using methods designed for exposure mixtures in conjunction with metabolomics to assess the potential joint effects of multiple PFAS chemicals on the human metabolome. We identified more pronounced metabolic perturbations associated with the PFAS mixture than for single PFAS chemicals. Taken together, our findings illustrate the potential for integrating environmental mixture analyses and high-throughput metabolomics to elucidate the molecular mechanisms underlying human health.

Background Longitudinal measures of diet spanning pregnancy through adolescence are needed from a large, diverse sample to advance research on the effect of early-life nutrition on child health. The Environmental influences on Child Health Outcomes (ECHO) Program, which includes 69 cohorts, >33,000 pregnancies, and >31,000 children in its first 7-y cycle, provides such data, now publicly available. Objectives This study aimed to describe dietary intake data available in the ECHO Program as of 31 August, 2022 (end of year 6 of Cycle 1) from pregnancy through adolescence, including estimated sample sizes, and to highlight the potential for future analyses of nutrition and child health. Methods We identified and categorized ECHO Program dietary intake data, by assessment method, participant (pregnant person or child), and life stage of data collection. We calculated the number of maternal-child dyads with dietary data and the number of participants with repeated measures. We identified diet-related variables derived from raw dietary intake data and nutrient biomarkers measured from biospecimens. Results Overall, 66 cohorts (26,941 pregnancies, 27,103 children, including 22,712 dyads) across 34 US states/territories provided dietary intake data. Dietary intake assessments included 24-h recalls (1548 pregnancies and 1457 children), food frequency questionnaires (4902 and 4117), dietary screeners (8816 and 23,626), and dietary supplement use questionnaires (24,798 and 26,513). Repeated measures were available for ∼70%, ∼30%, and ∼15% of participants with 24-h recalls, food frequency questionnaires, and dietary screeners, respectively. The available diet-related variables describe nutrient and food intake, diet patterns, and breastfeeding practices. Overall, 17% of participants with dietary intake data had measured nutrient biomarkers. Conclusions ECHO cohorts have collected longitudinal dietary intake data spanning pregnancy through adolescence from a geographically, socioeconomically, and ethnically diverse US sample. As data collection continues in Cycle 2, these data present an opportunity to advance the field of nutrition and child health.

Background Studies have reported mixed findings regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on pregnant women and birth outcomes. This study used a quasi-experimental design to account for potential confounding by sociodemographic characteristics. Methods Data were drawn from 16 prenatal cohorts participating in the Environmental influences on Child Health Outcomes (ECHO) program. Women exposed to the pandemic (delivered between 12 March 2020 and 30 May 2021) (n = 501) were propensity-score matched on maternal age, race and ethnicity, and child assigned sex at birth with 501 women who delivered before 11 March 2020. Participants reported on perceived stress, depressive symptoms, sedentary behavior, and emotional support during pregnancy. Infant gestational age (GA) at birth and birthweight were gathered from medical record abstraction or maternal report. Results After adjusting for propensity matching and covariates (maternal education, public assistance, employment status, prepregnancy body mass index), results showed a small effect of pandemic exposure on shorter GA at birth, but no effect on birthweight adjusted for GA. Women who were pregnant during the pandemic reported higher levels of prenatal stress and depressive symptoms, but neither mediated the association between pandemic exposure and GA. Sedentary behavior and emotional support were each associated with prenatal stress and depressive symptoms in opposite directions, but no moderation effects were revealed. Conclusions There was no strong evidence for an association between pandemic exposure and adverse birth outcomes. Furthermore, results highlight the importance of reducing maternal sedentary behavior and encouraging emotional support for optimizing maternal health regardless of pandemic conditions.

Background Prenatal exposure to phthalates, a group of synthetic chemicals widely used in consumer products, has previously been associated with adverse infant and child development. Studies also suggest that maternal depression and anxiety, may amplify the harmful effects of phthalates on infant and child neurodevelopment. Study design Our analysis included a subset of dyads enrolled in the Atlanta African American Maternal-Child Cohort (N = 81). We measured eight phthalate metabolites in first and second trimester (8–14 weeks and 24–32 weeks gestation) maternal urine samples to estimate prenatal exposures. Phthalate metabolite concentrations were averaged across visits and natural log-transformed for analysis. Maternal symptoms of depression and anxiety were assessed using validated questionnaires (Edinberg Postnatal Depression Scale and State Trait Anxiety Inventory, respectively) and the total score on each scale was averaged across study visits. The NICU Network Neurobehavioral Scale (NNNS) was administered at two weeks of age. Our primary outcomes included two composite NNNS scores reflecting newborn attention and arousal. Linear regression was used to estimate associations between individual phthalate exposures and newborn attention and arousal. We assessed effect modification by maternal depression and anxiety. Results Higher levels of urinary phthalate metabolites were not associated with higher levels of infant attention and arousal, but true associations may still exist given the limited power of this analysis. In models examining effect modification by maternal depression, we observed that an interquartile range increase in mono (2-ethlyhexyl) phthalate (MEHP), mono (2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono (2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) was associated with a significant increase in newborn arousal only among those with high depressive symptoms (MEHP: β = 0.71, 95% confidence interval [CI] = 0.10, 1.32 for high, β = −0.30, 95% CI = −0.73, 0.12 for low; MEOHP: β = 0.60, 95% CI = −0.03, 1.23 for high, β = −0.12, 95% CI = −0.58, 0.33 for low; MEHHP: β = 0.54, 95% CI = −0.04, 1.11 for high, β = −0.11, 95% CI = −0.54, 0.32 for low). Similar patterns were observed in models stratified by maternal anxiety, although CIs were wide. Conclusion Our results suggest maternal anxiety and depression symptoms may exacerbate the effect of phthalates on infant neurodevelopment. Future studies are needed to determine the optimal levels of attention and arousal in early infancy.

Background Epigenetic clocks are promising tools for assessing biological age. We assessed the accuracy of pediatric epigenetic clocks in gestational and chronological age determination. Results Our study used data from seven tissue types on three DNA methylation profiling microarrays and found that the Knight and Bohlin clocks performed similarly for blood cells, while the Lee clock was superior for placental samples. The pediatric-buccal-epigenetic clock performed the best for pediatric buccal samples, while the Horvath clock is recommended for children's blood cell samples. The NeoAge clock stands out for its unique ability to predict post-menstrual age with high correlation with the observed age in infant buccal cell samples. Conclusions Our findings provide valuable guidance for future research and development of epigenetic clocks in pediatric samples, enabling more accurate assessments of biological age.

Although offspring of women exposed to childhood trauma exhibit elevated rates of psychopathology, many children demonstrate resilience to these intergenerational impacts. Among the variety of factors that likely contribute to resilience, epigenetic processes have been suggested to play an important role. The current study used a prospective design to test the novel hypothesis that offspring epigenetic aging – a measure of methylation differences that are associated with infant health outcomes – moderates the relationship between maternal exposure to childhood adversity and offspring symptomatology. Maternal childhood adversity was self-reported during pregnancy via the ACEs survey and the CTQ, which assessed total childhood trauma as well as maltreatment subtypes (i.e., emotional, physical, and sexual abuse). Offspring blood samples were collected at or shortly after birth and assayed on a DNA methylation microarray, and offspring symptomatology was assessed with the CBCL/1.5–5 when offspring were 2–4 years old. Results indicated that maternal childhood trauma, particularly sexual abuse, was predictive of offspring symptoms (ps = 0.003–0.03). However, the associations between maternal sexual abuse and offspring symptomatology were significantly attenuated in offspring with accelerated epigenetic aging. These findings further our understanding of how epigenetic processes may contribute to and attenuate the intergenerational link between stress and psychopathology.

Background: Few standardized and open-source tools exist for calculating dietary pattern indexes from dietary intake data in epidemiological and clinical studies. Miscalculations of dietary indexes, with suspected erroneous findings, are occasionally noted in the literature. Objective: The primary aim is to develop and validate dietaryindex, a user-friendly and versatile R package that standardizes the calculation of dietary indexes. Methods: Dietaryindex utilizes a two-step process: an initial calculation of serving size for each food and nutrient category, followed by the calculation of individual dietary indexes. It includes generic functions that accept any preprocessed serving sizes of food groups and nutrients, with the standard serving sizes defined according to the methodologies used in well-known prospective cohort studies. For ease of use, dietaryindex also offers one-step functions that directly reference common datasets and tools, including the National Health and Nutrition Examination Survey (NHANES) and Block Food Frequency Questionnaire, eliminating the need for data preprocessing. At least two independent researchers validated the serving size definitions and scoring algorithms of dietaryindex. Results: Dietaryindex can calculate multiple dietary indexes of high interest in research, including Healthy Eating Index (HEI) - 2020, Alternative Healthy Eating Index 2010, Dietary Approaches to Stop Hypertension Index, Alternate Mediterranean Diet Score, Dietary Inflammatory Index, American Cancer Society 2020 dietary index, and Planetary Health Diet Index from the EAT-Lancet Commission. In our validation process, dietaryindex demonstrated full accuracy (100%) in all generic functions with two-decimal rounding precision in comparison to hand-calculated results. Similarly, using NHANES 2017–2018 data and ASA24 and DHQ3 example data, the HEI2015 outputs from dietaryindex aligned (99.95%–100%) with results using the SAS codes from the National Cancer Institute. Conclusions: Dietaryindex is a user-friendly, versatile, and validated informatics tool for standardized dietary index calculations. We have open-sourced all the validation files and codes with detailed tutorials on GitHub (https://github.com/jamesjiadazhan/dietaryindex).