The Associations of Maternal Health Characteristics, Newborn Metabolite Concentrations, and Child Body Mass Index among US Children in the ECHO Program

We aimed first to assess associations between maternal health characteristics and newborn metabolite concentrations and second to assess associations between metabolites associated with maternal health characteristics and child body mass index (BMI). This study included 3492 infants enrolled in three birth cohorts with linked newborn screening metabolic data. Maternal health characteristics were ascertained from questionnaires, birth certificates, and medical records. Child BMI was ascertained from medical records and study visits. We used multivariate analysis of variance, followed by multivariable linear/proportional odds regression, to determine maternal health characteristic-newborn metabolite associations. Significant associations were found in discovery and replication cohorts of higher pre-pregnancy BMI with increased C0 and higher maternal age at delivery with increased C2 (C0: discovery: aβ 0.05 [95% CI 0.03, 0.07]; replication: aβ 0.04 [95% CI 0.006, 0.06]; C2: discovery: aβ 0.04 [95% CI 0.003, 0.08]; replication: aβ 0.04 [95% CI 0.02, 0.07]). Social Vulnerability Index, insurance, and residence were also associated with metabolite concentrations in a discovery cohort. Associations between metabolites associated with maternal health characteristics and child BMI were modified from 1–3 years (interaction: p < 0.05). These findings may provide insights on potential biologic pathways through which maternal health characteristics may impact fetal metabolic programming and child growth patterns

Maternal tobacco smoking and offspring autism spectrum disorder or traits in ECHO cohorts

Given inconsistent evidence on preconception or prenatal tobacco use and offspring autism spectrum disorder (ASD), this study assessed associations of maternal smoking with ASD and ASD-related traits. Among 72 cohorts in the Environmental Influences on Child Health Outcomes consortium, 11 had ASD diagnosis and prenatal tobaccosmoking (n = 8648). and 7 had Social Responsiveness Scale (SRS) scores of ASD traits (n = 2399). Cohorts had diagnoses alone (6), traits alone (2), or both (5). Diagnoses drew from parent/caregiver report, review of records, or standardized instruments. Regression models estimated smoking-related odds ratios (ORs) for diagnoses and standardized mean differences for SRS scores. Cohort-specific ORs were meta-analyzed. Overall, maternal smoking was unassociated with child ASD (adjusted OR, 1.08; 95% confidence interval [CI], 0.72–1.61). However, heterogeneity across studies was strong: preterm cohorts showed reduced ASD risk for exposed children. After excluding preterm cohorts (biased by restrictions on causal intermediate and exposure opportunity) and small cohorts (very few ASD cases in either smoking category), the adjusted OR for ASD from maternal smoking was 1.44 (95% CI, 1.02–2.03). Children of smoking (versus non-smoking) mothers had more ASD traits (SRS T-score + 2.37 points, 95% CI, 0.73–4.01 points), with results homogeneous across cohorts. Maternal preconception/prenatal smoking was consistently associated with quantitative ASD traits and modestly associated with ASD diagnosis among sufficiently powered United States cohorts of non-preterm children. Limitations resulting from self-reported smoking and unmeasured confounders preclude definitive conclusions. Nevertheless, counseling on potential and known risks to the child from maternal smoking is warranted for pregnant women and pregnancy planners. Lay Summary: Evidence on the association between maternal prenatal smoking and the child's risk for autism spectrum disorder has been conflicting, with some studies reporting harmful effects, and others finding reduced risks. Our analysis of children in the ECHO consortium found that maternal prenatal tobacco smoking is consistently associated with an increase in autism-related symptoms in the general population and modestly associated with elevated risk for a diagnosis of autism spectrum disorder when looking at a combined analysis from multiple studies that each included both pre- and full-term births. However, this study is not proof of a causal connection. Future studies to clarify the role of smoking in autism-like behaviors or autism diagnoses should collect more reliable data on smoking and measure other exposures or lifestyle factors that might have confounded our results

Combining Effect Estimates Across Cohorts and Sufficient Adjustment Sets for Collaborative Research: A Simulation Study.

BackgroundCollaborative research often combines findings across multiple, independent studies via meta-analysis. Ideally, all study estimates that contribute to the meta-analysis will be equally unbiased. Many meta-analyses require all studies to measure the same covariates. We explored whether differing minimally sufficient sets of confounders identified by a directed acyclic graph (DAG) ensures comparability of individual study estimates. Our analysis applied four statistical estimators to multiple minimally sufficient adjustment sets identified in a single DAG.MethodsWe compared estimates obtained via linear, log-binomial, and logistic regression and inverse probability weighting, and data were simulated based on a previously published DAG.ResultsOur results show that linear, log-binomial, and inverse probability weighting estimators generally provide the same estimate of effect for different estimands that are equally sufficient to adjust confounding bias, with modest differences in random error. In contrast, logistic regression often performed poorly, with notable differences in effect estimates obtained from unique minimally sufficient adjustment sets, and larger standard errors than other estimators.ConclusionsOur findings do not support the reliance of collaborative research on logistic regression results for meta-analyses. Use of DAGs to identify potentially differing minimally sufficient adjustment sets can allow meta-analyses without requiring the exact same covariates

Perspectives of peripartum people on opportunities for personal and collective action to reduce exposure to everyday chemicals: Focus groups to inform exposure report-back.

Participants in biomonitoring studies who receive personal exposure reports seek information to reduce exposures. Many chemical exposures are driven by systems-level policies rather than individual actions; therefore, change requires engagement in collective action. Participants' perceptions of collective action and use of report-back to support engagement remain unclear. We conducted virtual focus groups during summer 2020 in a diverse group of peripartum people from cohorts in the Environmental influences on Child Health Outcomes (ECHO) Program (N&nbsp;=&nbsp;18). We assessed baseline exposure and collective action experience, and report-back preferences. Participants were motivated to protect the health of their families and communities despite significant time and cognitive burdens. They requested time-conscious tactics and accessible information to enable action to reduce individual and collective exposures. Participant input informed the design of digital report-back in the cohorts. This study highlights opportunities to shift responsibility from individuals to policymakers to reduce chemical exposures at the systems level

A review of maternal prenatal exposures to environmental chemicals and psychosocial stressors-implications for research on perinatal outcomes in the ECHO program.

Exposures to environmental chemicals and psychosocial stressors during pregnancy have been individually associated with adverse perinatal outcomes related to birthweight and gestational age, but are not often considered in combination. We review types of psychosocial stressors and instruments used to assess them and classes of environmental chemical exposures that are known to adversely impact perinatal outcomes, and identify studies relevant studies. We discuss the National Institutes of Health's Environmental influences on Child Health Outcomes (ECHO) program that has combined existing longitudinal cohorts that include more than 50,000 children across the U.S. We describe future opportunities for investigators to use this important new resource for addressing relevant and critical research questions to maternal health. Of the 84 cohorts in ECHO, 38 collected data on environmental chemicals and psychosocial stressors and perinatal outcomes. The diverse ECHO pregnancy cohorts provide capacity to compare regions with distinct place-based environmental and social stressors

A review of maternal prenatal exposures to environmental chemicals and psychosocial stressors-implications for research on perinatal outcomes in the ECHO program.

Exposures to environmental chemicals and psychosocial stressors during pregnancy have been individually associated with adverse perinatal outcomes related to birthweight and gestational age, but are not often considered in combination. We review types of psychosocial stressors and instruments used to assess them and classes of environmental chemical exposures that are known to adversely impact perinatal outcomes, and identify studies relevant studies. We discuss the National Institutes of Health's Environmental influences on Child Health Outcomes (ECHO) program that has combined existing longitudinal cohorts that include more than 50,000 children across the U.S. We describe future opportunities for investigators to use this important new resource for addressing relevant and critical research questions to maternal health. Of the 84 cohorts in ECHO, 38 collected data on environmental chemicals and psychosocial stressors and perinatal outcomes. The diverse ECHO pregnancy cohorts provide capacity to compare regions with distinct place-based environmental and social stressors

A framework for assessing the impact of chemical exposures on neurodevelopment in ECHO: Opportunities and challenges.

The Environmental influences on Child Health Outcomes (ECHO) Program is a research initiative funded by the National Institutes of Health that capitalizes on existing cohort studies to investigate the impact of early life environmental factors on child health and development from infancy through adolescence. In the initial stage of the program, extant data from 70 existing cohort studies are being uploaded to a database that will be publicly available to researchers. This new database will represent an unprecedented opportunity for researchers to combine data across existing cohorts to address associations between prenatal chemical exposures and child neurodevelopment. Data elements collected by ECHO cohorts were determined via a series of surveys administered by the ECHO Data Analysis Center. The most common chemical classes quantified in multiple cohorts include organophosphate pesticides, polychlorinated biphenyls, polybrominated diphenyl ethers, environmental phenols (including bisphenol A), phthalates, and metals. For each of these chemicals, at least four ECHO cohorts also collected behavioral data during infancy/early childhood using the Child Behavior Checklist. For these chemicals and this neurodevelopmental assessment (as an example), existing data from multiple ECHO cohorts could be pooled to address research questions requiring larger sample sizes than previously available. In addition to summarizing the data that will be available, the article also describes some of the challenges inherent in combining existing data across cohorts, as well as the gaps that could be filled by the additional data collection in the ECHO Program going forward

A framework for assessing the impact of chemical exposures on neurodevelopment in ECHO: Opportunities and challenges

The Environmental influences on Child Health Outcomes (ECHO) Program is a research initiative funded by the National Institutes of Health that capitalizes on existing cohort studies to investigate the impact of early life environmental factors on child health and development from infancy through adolescence. In the initial stage of the program, extant data from 70 existing cohort studies are being uploaded to a database that will be publicly available to researchers. This new database will represent an unprecedented opportunity for researchers to combine data across existing cohorts to address associations between prenatal chemical exposures and child neurodevelopment. Data elements collected by ECHO cohorts were determined via a series of surveys administered by the ECHO Data Analysis Center. The most common chemical classes quantified in multiple cohorts include organophosphate pesticides, polychlorinated biphenyls, polybrominated diphenyl ethers, environmental phenols (including bisphenol A), phthalates, and metals. For each of these chemicals, at least four ECHO cohorts also collected behavioral data during infancy/early childhood using the Child Behavior Checklist. For these chemicals and this neurodevelopmental assessment (as an example), existing data from multiple ECHO cohorts could be pooled to address research questions requiring larger sample sizes than previously available. In addition to summarizing the data that will be available, the article also describes some of the challenges inherent in combining existing data across cohorts, as well as the gaps that could be filled by the additional data collection in the ECHO Program going forward

Association between Quality of Maternal Prenatal Food Source and Preparation and Breastfeeding Duration in the Environmental Influences on Child Health Outcome (ECHO) Program

This study examined the relationship between maternal food source and preparation during pregnancy and the duration of breastfeeding among 751 mother–child dyads in the United States. The data collected from the Environmental influences on Child Health Outcomes (ECHO) Program included twelve cohorts of mothers (age ≥ 18) who delivered infant(s). Three categories of maternal food source and preparation including, High, Moderate, or Low Food Source Quality were derived from the mother report. The mean duration of breastfeeding differed strongly across the three categories. The High Food Source Quality group breastfed an average of 41 weeks, while shorter durations were observed for the Moderate (26 weeks) and Low (16 weeks) Food Source Quality groups. Cox proportional hazards models were used to estimate the relative hazard of time to breastfeeding cessation for each participant characteristic. The full model adjusted for clustering/cohort effect for all participant characteristics, while the final model adjusted for the subset of characteristics identified from variable reduction modeling. The hazard of breastfeeding cessation for those in the High Food Source Quality group was 24% less than the Moderate group (RH = 0.76; 95% CI, 0.63–0.92). Pregnant women in the High Food Source Quality group breastfed longer than the Moderate and Low groups. We encourage more detailed studies in the future to examine this relationship longitudinally

Associations of Gestational Perfluoroalkyl Substances Exposure with Early Childhood BMI z-Scores and Risk of Overweight/Obesity: Results from the ECHO Cohorts.

BackgroundGestational per- and polyfluoroalkyl substances (PFAS) exposure may be associated with adiposity and increased risk of obesity among children and adolescents. However, results from epidemiological studies evaluating these associations are inconsistent.ObjectivesWe estimated the associations of pregnancy PFAS concentrations with child body mass index (BMI) z-scores and risk of overweight/obesity in eight U.S. cohorts.MethodsWe used data from 1,391 mother-child pairs who enrolled in eight Environmental influences on Child Health Outcomes (ECHO) cohorts (enrolled: 1999-2019). We quantified concentrations of seven PFAS in maternal plasma or serum in pregnancy. We measured child weight and height between the ages of 2 and 5 y and calculated age- and sex-specific BMI z-scores; 19.6% children had more than one BMI measurement. We estimated covariate-adjusted associations of individual PFAS and their mixture with child BMI z-scores and risk of overweight/obesity using linear mixed models, modified Poisson regression models, and Bayesian approaches for mixtures. We explored whether child sex modified these associations.ResultsWe observed a pattern of subtle positive associations of PFAS concentrations in pregnancy with BMI z-scores and risk of overweight/obesity. For instance, each doubling in perfluorohexane sulfonic acid concentrations was associated with higher BMI z-scores (β=0.07; 95% CI: 0.01, 0.12). Each doubling in perfluroundecanoic acid [relative risk (RR)=1.10; 95% CI: 1.04, 1.16] and N-methyl perfluorooctane sulfonamido acetic acid (RR=1.06; 95% CI: 1.00, 1.12) was associated with increased risk of overweight/obesity, with some evidence of a monotonic dose-response relation. We observed weaker and more imprecise associations of the PFAS mixture with BMI or risk of overweight/obesity. Associations did not differ by child sex.DiscussionIn eight U.S.-based prospective cohorts, gestational exposure to higher levels of PFAS were associated with slightly higher childhood BMI z-score and risk of overweight or obesity. Future studies should examine associations of gestational exposure to PFAS with adiposity and related cardiometabolic consequences in older children. https://doi.org/10.1289/EHP11545