Birth outcomes in relation to neighborhood food access and individual food insecurity during pregnancy in the Environmental Influences on Child Health Outcomes (ECHO)-wide cohort study.

BACKGROUND: Limited access to healthy foods, resulting from residence in neighborhoods with low-food access or from household food insecurity, is a public health concern. Contributions of these measures during pregnancy to birth outcomes remain understudied. OBJECTIVES: We examined associations between neighborhood food access and individual food insecurity during pregnancy with birth outcomes. METHODS: We used data from 53 cohorts participating in the nationwide Environmental Influences on Child Health Outcomes-Wide Cohort Study. Participant inclusion required a geocoded residential address or response to a food insecurity question during pregnancy and information on birth outcomes. Exposures include low-income-low-food-access (LILA, where the nearest supermarket is >0.5 miles for urban or >10 miles for rural areas) or low-income-low-vehicle-access (LILV, where few households have a vehicle and >0.5 miles from the nearest supermarket) neighborhoods and individual food insecurity. Mixed-effects models estimated associations with birth outcomes, adjusting for socioeconomic and pregnancy characteristics. RESULTS: Among 22,206 pregnant participants (mean age 30.4 y) with neighborhood food access data, 24.1% resided in LILA neighborhoods and 13.6% in LILV neighborhoods. Of 1630 pregnant participants with individual-level food insecurity data (mean age 29.7 y), 8.0% experienced food insecurity. Residence in LILA (compared with non-LILA) neighborhoods was associated with lower birth weight [ß -44.3 g; 95% confidence interval (CI): -62.9, -25.6], lower birth weight-for-gestational-age z-score (-0.09 SD units; -0.12, -0.05), higher odds of small-for-gestational-age [odds ratio (OR) 1.15; 95% CI: 1.00, 1.33], and lower odds of large-for-gestational-age (0.85; 95% CI: 0.77, 0.94). Similar findings were observed for residence in LILV neighborhoods. No associations of individual food insecurity with birth outcomes were observed. CONCLUSIONS: Residence in LILA or LILV neighborhoods during pregnancy is associated with adverse birth outcomes. These findings highlight the need for future studies examining whether investing in neighborhood resources to improve food access during pregnancy would promote equitable birth outcomes.

Prevalence of maternal hyperglycemic subtypes by race/ethnicity and associations between these subtypes with adverse pregnancy outcomes: Findings from a large retrospective multi-ethnic cohort in the United States.

AIMS: With the two-step gestational diabetes mellitus (GDM) screening approach, hyperglycemic subtypes can be identified. We aimed to investigate racial/ethnic differences in the prevalence of hyperglycemic subtypes and to examine the associations between these subtypes and adverse pregnancy outcomes. METHODS: In this retrospective cohort, 11,405 pregnancies were screened using the two-step approach. Hyperglycemic subtypes included: pregnancy-impaired glucose intolerance-I (PIGT-I), PIGT-II, GDM-I (abnormal post-load glucose only), and GDM-II (abnormal fasting & post-load glucose). Modified Poisson regressions with robust error variance were used to estimate age-adjusted prevalence ratios (PR) of hyperglycemic subtypes and multivariable-adjusted risk ratios (RR) of adverse pregnancy outcomes. RESULTS: The prevalence of hyperglycemic subtypes was higher in Asians (PIGT-I: 1.51 [95% confidence interval 1.35-1.69]; PIGT-II: 2.18 [1.78-2.68]; GDM-I: 2.55 [2.10-3.10]; GDM-II: 1.55 [1.08-2.21]) and Hispanics (PIGT-I: 1.32 [1.16-1.50]; PIGT-II: 2.07 [1.67-2.57]; GDM-I: 1.69 [1.35-2.13]; GDM-II: 2.68 [1.93-3.71]) than non-Hispanic Whites (NHW). Despite low GDM prevalence, Japanese and Koreans had higher PIGT prevalence than NHW. PIGT-II was positively associated with hypertensive disorders of pregnancy (1.19 [1.02-1.38]), large-for-gestational age (1.73 [1.37-2.18]), and preterm birth (PB, 1.33 [1.05-1.68]). PIGT-I (1.23 [1.04-1.45]) and GDM-I (1.56 [0.87-1.71]) were positively related to PB. CONCLUSIONS: The prevalence of hyperglycemic subtypes varies by race/ethnicity and they have distinct health implications.

Associations of Organophosphate Ester Flame Retardant Exposures during Pregnancy with Gestational Duration and Fetal Growth: The Environmental influences on Child Health Outcomes (ECHO) Program.

BACKGROUND: Widespread exposure to organophosphate ester (OPE) flame retardants with potential reproductive toxicity raises concern regarding the impacts of gestational exposure on birth outcomes. Previous studies of prenatal OPE exposure and birth outcomes had limited sample sizes, with inconclusive results. OBJECTIVES: We conducted a collaborative analysis of associations between gestational OPE exposures and adverse birth outcomes and tested whether associations were modified by sex. METHODS: We included 6,646 pregnant participants from 16 cohorts in the Environmental influences on Child Health Outcomes (ECHO) Program. Nine OPE biomarkers were quantified in maternal urine samples collected primarily during the second and third trimester and modeled as log2-transformed continuous, categorized (high/low/nondetect), or dichotomous (detect/nondetect) variables depending on detection frequency. We used covariate-adjusted linear, logistic, and multinomial regression with generalized estimating equations, accounting for cohort-level clustering, to estimate associations of OPE biomarkers with gestational length and birth weight outcomes. Secondarily, we assessed effect modification by sex. RESULTS: Three OPE biomarkers [diphenyl phosphate (DPHP), a composite of dibutyl phosphate and di-isobutyl phosphate (DBUP/DIBP), and bis(1,3-dichloro-2-propyl) phosphate] were detected in >85% of participants. In adjusted models, DBUP/DIBP [odds ratio (OR) per doubling=1.07; 95% confidence interval (CI): 1.02, 1.12] and bis(butoxyethyl) phosphate (OR for high vs. nondetect=1.25; 95% CI: 1.06, 1.46), but not other OPE biomarkers, were associated with higher odds of preterm birth. We observed effect modification by sex for associations of DPHP and high bis(2-chloroethyl) phosphate with completed gestational weeks and odds of preterm birth, with adverse associations among females. In addition, newborns of mothers with detectable bis(1-chloro-2-propyl) phosphate, bis(2-methylphenyl) phosphate, and dipropyl phosphate had higher birth weight-for-gestational-age z-scores (ß for detect vs. nondetect=0.04-0.07); other chemicals showed null associations. DISCUSSION: In the largest study to date, we find gestational exposures to several OPEs are associated with earlier timing of birth, especially among female neonates, or with greater fetal growth. https://doi.org/10.1289/EHP13182.

Metabolomic data presents challenges for epidemiological meta-analysis: a case study of childhood body mass index from the ECHO consortium.

INTRODUCTION: Meta-analyses across diverse independent studies provide improved confidence in results. However, within the context of metabolomic epidemiology, meta-analysis investigations are complicated by differences in study design, data acquisition, and other factors that may impact reproducibility. OBJECTIVE: The objective of this study was to identify maternal blood metabolites during pregnancy (> 24 gestational weeks) related to offspring body mass index (BMI) at age two years through a meta-analysis framework. METHODS: We used adjusted linear regression summary statistics from three cohorts (total N = 1012 mother-child pairs) participating in the NIH Environmental influences on Child Health Outcomes (ECHO) Program. We applied a random-effects meta-analysis framework to regression results and adjusted by false discovery rate (FDR) using the Benjamini-Hochberg procedure. RESULTS: Only 20 metabolites were detected in all three cohorts, with an additional 127 metabolites detected in two of three cohorts. Of these 147, 6 maternal metabolites were nominally associated (P < 0.05) with offspring BMI z-scores at age 2 years in a meta-analytic framework including at least two studies: arabinose (Coefmeta = 0.40 [95% CI 0.10,0.70], Pmeta = 9.7 × 10-3), guanidinoacetate (Coefmeta = - 0.28 [- 0.54, - 0.02], Pmeta = 0.033), 3-ureidopropionate (Coefmeta = 0.22 [0.017,0.41], Pmeta = 0.033), 1-methylhistidine (Coefmeta = - 0.18 [- 0.33, - 0.04], Pmeta = 0.011), serine (Coefmeta = - 0.18 [- 0.36, - 0.01], Pmeta = 0.034), and lysine (Coefmeta = - 0.16 [- 0.32, - 0.01], Pmeta = 0.044). No associations were robust to multiple testing correction. CONCLUSIONS: Despite including three cohorts with large sample sizes (N > 100), we failed to identify significant metabolite associations after FDR correction. Our investigation demonstrates difficulties in applying epidemiological meta-analysis to clinical metabolomics, emphasizes challenges to reproducibility, and highlights the need for standardized best practices in metabolomic epidemiology.

Gestational diabetes mellitus and risk of neurodevelopmental disorders in young offspring: does the risk differ by race and ethnicity?

BACKGROUND: Previous studies examined the associations of gestational diabetes mellitus with autism spectrum disorder and attention deficit hyperactivity disorder. However, the associations between gestational diabetes mellitus and other neurodevelopmental disorders, such as the common speech/language disorder and developmental coordination disorder, are rarely studied, and whether the associations vary by race/ethnicity remains unknown. OBJECTIVE: This study aimed to examine the associations of gestational diabetes mellitus with individual neurodevelopmental disorders in young offspring, and to investigate whether the associations vary by race/ethnicity. STUDY DESIGN: This retrospective cohort study (Glucose in Relation to Women and Babies' Health [GrownB]) included 14,480 mother-offspring pairs in a large medical center in the United States from March 1, 2013 to August 31, 2021. We ascertained gestational diabetes mellitus using the validated ICD (International Classification of Diseases) codes (ICD-9: 648.8x; ICD-10: O24.4x), and identified neurodevelopmental disorders (speech/language disorder, developmental coordination disorder, autism spectrum disorder, and other neurodevelopmental disorders [attention deficit hyperactivity disorder, behavioral disorder, intellectual disability, and learning difficulty]) and their combinations using validated algorithms. We compared the hazard of neurodevelopmental disorders during the entire follow-up period between offspring born to mothers with and without gestational diabetes mellitus using multivariable Cox regression models. RESULTS: Among all mothers, 19.9% were Asian, 21.8% were Hispanic, 41.0% were non-Hispanic White, and 17.3% were of other/unknown race/ethnicity. During the median follow-up of 3.5 years (range, 1.0-6.3 years) after birth, 8.7% of offspring developed at least 1 neurodevelopmental disorder. Gestational diabetes mellitus was associated with a higher risk of speech/language disorder (adjusted hazard ratio, 1.59 [95% confidence interval, 1.07-2.35]), developmental coordination disorder (2.36 [1.37-4.04]), autism spectrum disorder (3.16 [1.36-7.37]), other neurodevelopmental disorders (3.12 [1.51-6.47]), any neurodevelopmental disorder (1.86 [1.36-2.53]), the combination of speech/language disorder and autism spectrum disorder (3.79 [1.35-10.61]), and the combination of speech/language disorder and developmental coordination disorder (4.22 [1.69-10.51]) among offspring born to non-Hispanic White mothers. No associations between gestational diabetes mellitus and any neurodevelopmental disorders or their combinations were observed among offspring born to mothers of other racial/ethnic groups. CONCLUSION: We observed an elevated risk of neurodevelopmental disorders among young offspring born to non-Hispanic White mothers with gestational diabetes mellitus, but not among other racial/ethnic groups.

Maternal Pre-Pregnancy BMI, Breastfeeding, and Child BMI.

OBJECTIVES: Breastfeeding practices may protect against offspring obesity, but this relationship is understudied among women with obesity. We describe the associations between breastfeeding practices and child BMI for age z-score (BMIz), stratified by maternal BMI. METHODS: We analyzed 8134 dyads from 21 cohorts in the Environmental Influences on Child Health Outcomes Program. Dyads with data for maternal pre-pregnancy BMI, infant feeding practices, and ≥1 child BMI assessment between the ages of 2 and 6 years were included. The associations between breastfeeding practices and continuous child BMIz were assessed by using multivariable linear mixed models. RESULTS: Maternal pre-pregnancy BMI category prevalence was underweight: 2.5%, healthy weight: 45.8%, overweight: 26.0%, and obese: 25.6%. Median child ages at the cessation of any breastfeeding and exclusive breastfeeding across the 4 BMI categories were 19, 26, 24, and 17 weeks and 12, 20, 17, and 12 weeks, respectively. Results were in the hypothesized directions for BMI categories. Three months of any breastfeeding was associated with a lower BMIz among children whose mothers were a healthy weight (-0.02 [-0.04 to 0.001], P = .06), overweight (-0.04 [-0.07 to -0.004], P = .03), or obese (-0.04 [-0.07 to -0.006], P = .02). Three months of exclusive breastfeeding was associated with a lower BMIz among children whose mothers were a healthy weight (-0.06 [-0.10 to -0.02], P = .002), overweight (-0.05 [-0.10 to 0.005], P = .07), or obese (-0.08 [-0.12 to -0.03], P = .001). CONCLUSIONS: Human milk exposure, regardless of maternal BMI category, was associated with a lower child BMIz in the Environmental Influences on Child Health Outcomes cohorts, supporting breastfeeding recommendations as a potential strategy for decreasing the risk of offspring obesity.

Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis.

BACKGROUND: Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM. METHODS: Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA). RESULTS: A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers. CONCLUSIONS: Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

Gestational Diabetes (GDM) is high blood sugar that develops during pregnancy and may cause complications. GDM diagnosis is centered on blood sugar levels. Despite everyone receiving standard treatment, the clinical outcomes may vary from one individual to another. This indicates a need to identify factors that may help GDM diagnosis and result in improved classification of those at greatest risk for complications. Here, we systematically analyzed all published evidence for potential markers that could identify those with GDM who have greater risk of complications. We find that high maternal weight is a risk factor for offspring born larger for their gestational age. Other promising markers were identified, but further analysis is needed before they can be applied in the clinic.

Opportunities for Examining Child Health Impacts of Early-Life Nutrition in the ECHO Program: Maternal and Child Dietary Intake Data from Pregnancy to Adolescence.

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.

Intrinsic motivation for physical activity, healthy eating, and self-weighing in association with corresponding behaviors in early pregnancy.

Healthy lifestyle behaviors influence maternal cardiovascular health, but motivation for them in pregnancy is poorly understood. We examined whether intrinsic motivation (assessed on 5-point scales for each behavior) is associated with three lifestyle behaviors in early pregnancy: physical activity, by intensity level; healthy eating, quantified with the Alternate Healthy Eating Index for Pregnancy (AHEI-P); and weight self-monitoring, a standard weight management technique. Participants in the Northern California Pregnancy, Lifestyle and Environment Study (PETALS) population-based cohort completed validated surveys in early pregnancy (2017-18; N = 472; 22 % Asian, 6 % Black, 30 % Hispanic, 13 % multiracial, 30 % White). Cross-sectional data were analyzed in 2021-22. Overall, 40.7 % (n = 192) met United States national physical activity guidelines; the average AHEI-P score was 62.3 out of 130 (SD 11.4); and 36.9 % reported regular self-weighing (≥once/week; n = 174). In models adjusted for participant characteristics, 1-unit increases in intrinsic motivation were associated with increased likelihood of meeting physical activity guidelines (risk ratio [95 % CI]: 1.66 [1.48, 1.86], p < 0.0001); meeting sample-specific 75th percentiles for vigorous physical activity (1.70 [1.44, 1.99], p < 0.0001) and AHEI-P (1.75 [1.33, 2.31], p < 0.0001); and regular self-weighing (2.13 [1.92, 2.37], p < 0.0001). A 1-unit increase in intrinsic motivation lowered the risk of meeting the 75th percentile for sedentary behavior (0.79 [0.67, 0.92], p < 0.003). Intrinsic motivation was not associated with reaching 75th percentiles for total, light, or moderate activity. Intrinsic motivation is associated with physical activity, healthy eating, and self-weighing among diverse individuals in early pregnancy. Results can inform intervention design to promote maternal health via increased enjoyment of lifestyle behaviors.

PFAS concentrations in early and mid-pregnancy and risk of gestational diabetes mellitus in a nested case-control study within the ethnically and racially diverse PETALS cohort.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are persistent synthetic chemicals and are commonly found in everyday items. PFAS have been linked to disrupting glucose homeostasis, however, whether they are associated with gestational diabetes mellitus (GDM) risk remains inconclusive. We examined prospective associations of PFAS concentrations measured twice in pregnancy with GDM risk. METHODS: In the PETALS pregnancy cohort, a nested case-control study which included 41 GDM cases and 87 controls was conducted. PFAS analytes were measured in blood serum collected in both early and mid-pregnancy (mean [SD]: 13.9 [2.2] and 20.2 [2.2] gestational weeks, respectively), with cumulative exposure calculated by the area-under-the-curve (AUC) to integrate both the PFAS concentration and the timing of the exposure. Individual adjusted weighted unconditional logistic regression models examined seven PFAS in association with GDM risk. P-values were corrected using the false-discovery-rate (FDR). Mixture models were analyzed with Bayesian kernel machine regression (BKMR). RESULTS: PFDA, PFNA and PFOA were individually associated with higher GDM risk per interquartile range (IQR) in early pregnancy (OR [95% CI]: 1.23 [1.09, 1.38]), 1.40 [1.24, 1.58]), and 1.15 [1.04, 1.27], respectively), mid-pregnancy (1.28 [1.15, 1.43], 1.16 [1.05, 1.28], and 1.20 [1.09, 1.33], respectively), and with cumulative exposure (1.23 [1.09, 1.38], 1.21 [1.07, 1.37], and 1.19 [1.09, 1.31], respectively). PFOS in mid-pregnancy and with cumulative exposure was associated with increased GDM risk (1.41 [1.17, 1.71] and 1.33 [1.06, 1.58], respectively). PFUnDA in early pregnancy was associated with lower GDM risk (0.79 [0.64, 0.98]), whereas mid-pregnancy levels were associated with higher risk (1.49 [1.18, 1.89]). PFHxS was associated with decreased GDM risk in early and mid-pregnancy (0.48 [0.38, 0.60] and 0.48 [0.37, 0.63], respectively) and with cumulative exposure (0.49 [0.38,0.63]). PFPeA was not associated with GDM. Similar conclusions were observed in BKMR models; however, overall associations in these models were not statistically significant. CONCLUSIONS: Higher risk of GDM was consistently observed in association with PFDA, PFNA, and PFOA exposure in both early and mid-pregnancy. Results should be corroborated in larger population-based cohorts and individuals of reproductive age should potentially avoid known sources of PFAS.

Prenatal depression and risk of child autism-related traits among participants in the Environmental influences on Child Health Outcomes program.

This study evaluated the association between prenatal depression and offspring autism-related traits. The sample comprised 33 prenatal/pediatric cohorts participating in the Environmental influences on Child Health Outcomes program who contributed information on prenatal depression and autism-related traits. Autism-related traits were assessed continuously and at the diagnostic cut-off using the Social Responsiveness Scale for children up to 12 years of age. Main analyses included 3994 parent-child pairs with prenatal depression diagnoses data; secondary analyses included 1730 parent-child pairs with depression severity data. After confounder adjustment, we observed an increase in autism-related traits among children of individuals with prenatal depression compared to those without (adjusted ß = 1.31 95% CI: 0.65, 1.98). Analyses stratified by child sex documented a similar significant association among boys (aß = 1.34 95%CI: 0.36, 2.32) and girls (aß = 1.26 95% CI: 0.37, 2.15). Prenatal depression was also associated with increased odds of moderate to severe autism-related traits (adjusted odds ratio: 1.64, 95%CI: 1.09, 2.46), the screening threshold considered high risk of autism spectrum disorder (ASD) diagnosis. Findings highlight the importance of prenatal depression screening and preventive interventions for children of pregnant individuals with depression to support healthy development. Future research is needed to clarify whether these findings reflect overlap in genetic risk for depression and ASD-related traits or another mechanism.

Prenatal Health Care Outcomes Before and During the COVID-19 Pandemic Among Pregnant Individuals and Their Newborns in an Integrated US Health System.

Importance: The COVID-19 pandemic accelerated the use of telemedicine. However, data on the integration of telemedicine in prenatal health care and health outcomes are sparse. Objective: To evaluate a multimodal model of in-office and telemedicine prenatal health care implemented during the COVID-19 pandemic and its association with maternal and newborn health outcomes. Design, Setting, and Participants: This cohort study of pregnant individuals using longitudinal electronic health record data was conducted at Kaiser Permanente Northern California, an integrated health care system serving a population of 4.5 million people. Individuals who delivered a live birth or stillbirth between July 1, 2018, and October 21, 2021, were included in the study. Data were analyzed from January 2022 to May 2023. Exposure: Exposure levels to the multimodal prenatal health care model were separated into 3 intervals: unexposed (T1, birth delivery between July 1, 2018, and February 29, 2020), partially exposed (T2, birth delivery between March 1, 2020, and December 5, 2020), and fully exposed (T3, birth delivery between December 6, 2020, and October 31, 2021). Main Outcomes and Measures: Primary outcomes included rates of preeclampsia and eclampsia, severe maternal morbidity, cesarean delivery, preterm birth, and neonatal intensive care unit (NICU) admission. The distributions of demographic and clinical characteristics, care processes, and health outcomes for birth deliveries within each of the 3 intervals of interest were assessed with standardized mean differences calculated for between-interval contrasts. Interrupted time series analyses were used to examine changes in rates of perinatal outcomes and its association with the multimodal prenatal health care model. Secondary outcomes included gestational hypertension, gestational diabetes, depression, venous thromboembolism, newborn Apgar score, transient tachypnea, and birth weight. Results: The cohort included 151 464 individuals (mean [SD] age, 31.3 [5.3] years) who delivered a live birth or stillbirth. The mean (SD) number of total prenatal visits was similar in T1 (9.41 [4.75] visits), T2 (9.17 [4.50] visits), and T3 (9.15 [4.66] visits), whereas the proportion of telemedicine visits increased from 11.1% (79 214 visits) in T1 to 20.9% (66 726 visits) in T2 and 21.3% (79 518 visits) in T3. NICU admission rates were 9.2% (7014 admissions) in T1, 8.3% (2905 admissions) in T2, and 8.6% (3615 admissions) in T3. Interrupted time series analysis showed no change in NICU admission risk during T1 (change per 4-week interval, -0.22%; 95% CI, -0.53% to 0.09%), a decrease in risk during T2 (change per 4-week interval, -0.91%; 95% CI, -1.77% to -0.03%), and an increase in risk during T3 (change per 4-week interval, 1.75%; 95% CI, 0.49% to 3.02%). There were no clinically relevant changes between T1, T2, and T3 in the rates of risk of preeclampsia and eclampsia (change per 4-week interval, 0.76% [95% CI, 0.39% to 1.14%] for T1; -0.19% [95% CI, -1.19% to 0.81%] for T2; and -0.80% [95% CI, -2.13% to 0.55%] for T3), severe maternal morbidity (change per 4-week interval , 0.12% [95% CI, 0.40% to 0.63%] for T1; -0.39% [95% CI, -1.00% to 1.80%] for T2; and 0.99% [95% CI, -0.88% to 2.90%] for T3), cesarean delivery (change per 4-week interval, 0.06% [95% CI, -0.11% to 0.23%] for T1; -0.03% [95% CI, -0.49% to 0.44%] for T2; and -0.05% [95% CI, -0.68% to 0.59%] for T3), preterm birth (change per 4-week interval, 0.23% [95% CI, -0.11% to 0.57%] for T1; -0.37% [95% CI, -1.29% to 0.55%] for T2; and -0.15% [95% CI, -1.41% to 1.13%] for T3), or secondary outcomes. Conclusions and Relevance: These findings suggest that a multimodal prenatal health care model combining in-office and telemedicine visits performed adequately compared with in-office only prenatal health care, supporting its continued use after the pandemic.

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

BACKGROUND: Gestational 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. OBJECTIVES: We 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. METHODS: We 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. RESULTS: We 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 (ß=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. DISCUSSION: In 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.

Birth Outcomes in Relation to Prenatal Exposure to Per- and Polyfluoroalkyl Substances and Stress in the Environmental Influences on Child Health Outcomes (ECHO) Program.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are persistent and ubiquitous chemicals associated with risk of adverse birth outcomes. Results of previous studies have been inconsistent. Associations between PFAS and birth outcomes may be affected by psychosocial stress. OBJECTIVES: We estimated risk of adverse birth outcomes in relation to prenatal PFAS concentrations and evaluate whether maternal stress modifies those relationships. METHODS: We included 3,339 participants from 11 prospective prenatal cohorts in the Environmental influences on the Child Health Outcomes (ECHO) program to estimate the associations of five PFAS and birth outcomes. We stratified by perceived stress scale scores to examine effect modification and used Bayesian Weighted Sums to estimate mixtures of PFAS. RESULTS: We observed reduced birth size with increased concentrations of all PFAS. For a 1-unit higher log-normalized exposure to perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), perfluorononanoic acid (PFNA), and perfluorohexane sulfonic acid (PFHxS), we observed lower birthweight-for-gestational-age z-scores of ß=-0.15 [95% confidence interval (CI): -0.27, -0.03], ß=-0.14 (95% CI: -0.28, -0.002), ß=-0.22 (95% CI: -0.23, -0.10), ß=-0.06 (95% CI: -0.18, 0.06), and ß=-0.25 (95% CI: -0.37, -0.14), respectively. We observed a lower odds ratio (OR) for large-for-gestational-age: ORPFNA=0.56 (95% CI: 0.38, 0.83), ORPFDA=0.52 (95% CI: 0.35, 0.77). For a 1-unit increase in log-normalized concentration of summed PFAS, we observed a lower birthweight-for-gestational-age z-score [-0.28; 95% highest posterior density (HPD): -0.44, -0.14] and decreased odds of large-for-gestational-age (OR=0.49; 95% HPD: 0.29, 0.82). Perfluorodecanoic acid (PFDA) explained the highest percentage (40%) of the summed effect in both models. Associations were not modified by maternal perceived stress. DISCUSSION: Our large, multi-cohort study of PFAS and adverse birth outcomes found a negative association between prenatal PFAS and birthweight-for-gestational-age, and the associations were not different in groups with high vs. low perceived stress. This study can help inform policy to reduce exposures in the environment and humans. https://doi.org/10.1289/EHP10723.

Metabolomic biomarkers of the mediterranean diet in pregnant individuals: A prospective study.

BACKGROUND AND AIMS: Metabolomic profiling is a systematic approach to identifying biomarkers for dietary patterns. Yet, metabolomic markers for dietary patterns in pregnant individuals have not been investigated. The aim of this study was to identify plasma metabolomic markers and metabolite panels that are associated with the Mediterranean diet in pregnant individuals. METHODS: This is a prospective study of 186 pregnant individuals who had both dietary intake and metabolomic profiles measured from the Fetal Growth Studies-Singletons cohort. Dietary intakes during the peri-conception/1st trimester and the second trimester were accessed at 8-13 and 16-22 weeks of gestation, respectively. Adherence to the Mediterranean diet was measured by the alternate Mediterranean Diet (aMED) score. Fasting plasma samples were collected at 16-22 weeks and untargeted metabolomics profiling was performed using the mass spectrometry-based platforms. Metabolites individually or jointly associated with aMED scores were identified using linear regression and least absolute shrinkage and selection operator (LASSO) regression models with adjustment for potential confounders, respectively. RESULTS: Among 459 annotated metabolites, 64 and 41 were individually associated with the aMED scores of the diet during the peri-conception/1st trimester and during the second trimester, respectively. Fourteen metabolites were associated with the Mediterranean diet in both time windows. Most Mediterranean diet-related metabolites were lipids (e.g., acylcarnitine, cholesteryl esters (CEs), linoleic acid, long-chain triglycerides (TGs), and phosphatidylcholines (PCs), amino acids, and sugar alcohols. LASSO regressions also identified a 10 metabolite-panel that were jointly associated with aMED score of the diet during the peri-conception/1st trimester (AUC: 0.74; 95% CI: 0.57, 0.91) and a 3 metabolites-panel in the 2nd trimester (AUC: 0.68; 95% CI: 0.50, 0.86). CONCLUSION: We identified plasma metabolomic markers for the Mediterranean diet among pregnant individuals. Some of them have also been reported in previous studies among non-pregnant populations, whereas others are novel. The results from our study warrant replication in pregnant individuals by future studies. CLINICAL TRIAL REGISTRATION NUMBER: This study was registered at ClinicalTrials.gov.

Trends in Screen Time Use Among Children During the COVID-19 Pandemic, July 2019 Through August 2021.

Importance: The COVID-19 pandemic led to widespread lockdowns and school closures that may have affected screen time among children. Although restrictions were strongest early in the pandemic, it is unclear how screen time changed as the pandemic progressed. Objective: To evaluate change in children's screen time from before the pandemic to during the pandemic, from July 2019 through August 2021. Design, Setting, and Participants: This is a longitudinal cohort study with repeated measures of screen time collected before the pandemic and during 2 pandemic periods. Children aged 4 to 12 years and their parent were enrolled in 3 pediatric cohorts across 3 states in the US participating in the Environmental Influences of Child Health Outcomes (ECHO) Program. Data analysis was performed from November 2021 to July 2022. Exposures: COVID-19 pandemic period: prepandemic (July 2019 to March 2020), pandemic period 1 (December 2020 to April 2021), and pandemic period 2 (May 2021 to August 2021). Main Outcomes and Measures: The primary outcomes were total, educational (not including remote school), and recreational screen time assessed via the ECHO Child Media Use questionnaire. Linear mixed-effects models were used for screen time adjusted for child's age, number of siblings, sex, race, ethnicity, and maternal education. Results: The cohort included 228 children (prepandemic mean [SD] age, 7.0 [2.7] years; 100 female [43.9%]) with screen time measured during the prepandemic period and at least once during the pandemic period. Prepandemic mean (SD) total screen time was 4.4 (3.9) hours per day and increased 1.75 hours per day (95% CI, 1.18-2.31 hours per day) in the first pandemic period and 1.11 hours per day (95% CI, 0.49-1.72 hours per day) in the second pandemic period, in adjusted models. Prepandemic mean (SD) recreational screen time was 4.0 (3.5) hours per day and increased 0.89 hours per day (95% CI, 0.39-1.39 hours per day) in the first pandemic period and 0.70 hours per day (95% CI, 0.16-1.25 hours per day) in the second pandemic period. Prepandemic mean (SD) educational screen time was 0.5 (1.2) hours per day (median [IQR], 0.0 [0.0-0.4] hours per day) and increased 0.93 hours per day (95% CI, 0.67-1.19 hours per day) in the first pandemic period and 0.46 hours per day (95% CI, 0.18-0.74 hours per day) in the second pandemic period. Conclusions and Relevance: These findings suggest that screen time among children increased during the COVID-19 pandemic and remained elevated even after many public health precautions were lifted. The long-term association of increased screen time during the COVID-19 pandemic with children's health needs to be determined.

Dietary Quality Indices in Early Pregnancy and Rate of Gestational Weight Gain among a Prospective Multi-Racial and Ethnic Cohort.

Meeting the Institute of Medicine (IOM) gestational weight gain (GWG) guidelines is associated with a reduced risk of adverse perinatal outcomes. Overall diet quality comprehensively assesses dietary components and accounts for interactions between them. While GWG is influenced by maternal diet, its association with overall diet quality-measured by various dietary quality indices-is not well-defined. We prospectively estimated the relationship between four established dietary quality indices and the risk of GWG rate above (excessive) or below (inadequate) IOM guidelines in a multi-racial and ethnic cohort of 2914 pregnant people from the Pregnancy Environment and Lifestyle Study (2014-2019). We assessed diet quality using the Healthy Eating Index 2010 (HEI-2010), alternate Mediterranean Diet (aMED), Dietary Approaches to Stop Hypertension (DASH), and Empirical Dietary Inflammatory Index (EDIP). Following the first trimester, 56% of the cohort had excessive GWG, and 14% had inadequate GWG. Poor diet quality (below the 75th percentile), measured by HEI-2010, was associated with a higher risk of excessive GWG in the second and third trimesters [RR = 1.03 (1.00, 1.06)]. Effect modification of this relationship by race and ethnicity and pre-pregnancy BMI was assessed. We found poor diet quality to be associated with elevated risk of excessive GWG among Black participants [RR = 1.14 (1.02, 1.28)] and White participants [RR 1.07 (1.01, 1.12)]. This was also the case for participants with pre-pregnancy BMI < 25.0 [RR 1.05 (1.00, 1.10)]. These results suggest that diet quality measured by the HEI-2010 is associated with excessive GWG, and the associations appear to be stronger among pregnant people without overweight or obesity and pregnant people who identify as Black or White race and ethnicity.

In utero metabolomic signatures of refined grain intake and risk of gestational diabetes: A metabolome-wide association study.

BACKGROUND: Epidemiologic evidence has linked refined grain intake to a higher risk of gestational diabetes (GDM), but the biological underpinnings remain unclear. OBJECTIVES: We aimed to identify and validate refined grain-related metabolomic biomarkers for GDM risk. METHODS: In a metabolome-wide association study of 91 cases with GDM and 180 matched controls without GDM (discovery set) nested in the prospective Pregnancy Environment and Lifestyle Study (PETALS), refined grain intake during preconception and early pregnancy and serum untargeted metabolomics were assessed at gestational weeks 10-13. We identified refined grain-related metabolites using multivariable linear regression and examined their prospective associations with GDM risk using conditional logistic regression. We further examined the predictivity of refined grain-related metabolites selected by least absolute shrinkage and selection operator regression in the discovery set and validation set (a random PETALS subsample of 38 individuals with and 336 without GDM). RESULTS: Among 821 annotated serum (87.4% fasting) metabolites, 42 were associated with refined grain intake, of which 17 (70.6% in glycerolipids, glycerophospholipids, and sphingolipids clusters) were associated with subsequent GDM risk (all false discovery rate-adjusted P values <0.05). Adding 7 of 17 metabolites to a conventional risk factor-based prediction model increased the C-statistic for GDM risk in the discovery set from 0.71 (95% CI: 0.64, 0.77) to 0.77 (95% CI: 0.71, 0.83) and in the validation set from 0.77 (95% CI: 0.69, 0.86) to 0.81 (95% CI: 0.74, 0.89), both with P-for-difference <0.05. CONCLUSIONS: Clusters of glycerolipids, glycerophospholipids, and sphingolipids may be implicated in the association between refined grain intake and GDM risk, as demonstrated by the significant associations of these metabolites with both refined grains and GDM risk and the incremental predictive value of these metabolites for GDM risk beyond the conventional risk factors. These findings provide evidence on the potential biological underpinnings linking refined grain intake to the risk of GDM and help identify novel disease-related dietary biomarkers to inform diet-related preventive strategies for GDM.

Prenatal Exposure to Per- and Polyfluoroalkyl Substances and Childhood Autism-related Outcomes.

BACKGROUND: Epidemiologic evidence linking prenatal exposure to per- and polyfluoroalkyl substances (PFAS) with altered neurodevelopment is inconclusive, and few large studies have focused on autism-related outcomes. We investigated whether blood concentrations of PFAS in pregnancy are associated with child autism-related outcomes. METHODS: We included 10 cohorts from the National Institutes of Health (NIH)-funded Environmental influences on Child Health Outcomes (ECHO) program (n = 1,429). We measured 14 PFAS analytes in maternal blood collected during pregnancy; eight analytes met detection criteria for analysis. We assessed quantitative autism-related traits in children via parent report on the Social Responsiveness Scale (SRS). In multivariable linear models, we examined relationships of each PFAS (natural log-transformed) with SRS scores. We further modeled PFAS as a complex mixture using Bayesian methods and examined modification of these relationships by child sex. RESULTS: Most PFAS in maternal blood were not associated with child SRS T-scores. Perfluorononanoic acid (PFNA) showed the strongest and most consistent association: each 1-unit increase in ln-transformed PFNA was associated with greater autism-related traits (adjusted ß [95% confidence interval (CI)] = 1.5 [-0.1, 3.0]). The summed mixture, which included six PFAS detected in >70% of participants, was not associated with SRS T-scores (adjusted ß [95% highest posterior density interval] = 0.7 [-1.4, 3.0]). We did not observe consistent evidence of sex differences. CONCLUSIONS: Prenatal blood concentrations of PFNA may be associated with modest increases in child autism-related traits. Future work should continue to examine the relationship between exposures to both legacy and emerging PFAS and additional dimensional, quantitative measures of childhood autism-related outcomes.