Background: Inadequate or excessive gestational weight gain (GWG) is associated with adverse pregnancy outcomes. Less is known about how GWG and post-partum weight retention impact women’s long-term cardiovascular health (CVH). Methods: Participants are from Project Viva, a prospective cohort of pregnant women and their offspring. We defined GWG as the last clinically measured pre-delivery weight from clinical records minus pre-pregnancy weight (from self-report). We defined post-partum weight retention as post-partum weight (measured at 6 months; self-reported at 1 and 2 years) minus pre-pregnancy weight. At the Mid-life Visit (2017-2021), we measured blood pressure, body mass index (BMI), glucose, hemoglobin A1c, cholesterol, and participants self-reported health behaviors (sleep, diet, physical activity, smoking). We derived American Heart Association Life’s Essential 8 (LE8) scores (0-100, higher=better) and used linear regression to examine associations of overall and trimester-specific GWG and post-partum weight retention at 6 months, 1, and 2 years post-partum with overall LE8, its biomedical and behavioral domains, and individual metrics. Models were adjusted for pre-pregnancy body mass index, age of mother at enrollment, and mother’s educational attainment at enrollment. Results: Among 819 women (mean [SD] age 32.6 [5.0] years at enrollment and 51.0 [5.1] years at mid-life; 68% Non-Hispanic White, 15% Non-Hispanic Black), pre-pregnancy BMI was 24.6 (5.1) kg/m 2 ( Table 1 ). Higher GWG (per 1 kg) was associated with a worse BMI score at mid-life for pregnancy overall (β = -0.71, 95% CI: -1.02, -0.39), and for the 1 st (β = -1.07, 95% CI: -1.67, -0.48), 2 nd (β = -1.14, 95% CI: -1.89, -0.40) and 3 rd (β = -0.72, 95% CI: -1.31, -0.13) trimesters individually ( Table 2 ). Higher post-partum weight retention (per 1 kg) at all time points was associated with a worse LE8 biomedical domain (indicating worse CVH), a worse BMI score, and a worse BP score ( Table 3 ). Higher post-partum weight retention at 6 months (β = -0.36, 95% CI: -0.68, -0.04) and 2 years (β = -0.36, 95% CI: -0.67, -0.05) was also associated with a worse blood glucose score. Conclusion: In this prospective cohort, higher GWG was associated with higher mid-life BMI, and higher post-partum weight retention was associated with higher BMI, BP, and worse overall CVH. Minimizing post-partum weight retention may be an important target for optimizing women’s long-term CVH.

We estimated sex-specific population effects of hypothetical interventions to limit sugar sweetened-beverages (SSBs) and 100% fruit juice throughout childhood on central adiposity, insulin resistance, and glycemic outcomes in adolescence in Project Viva prebirth cohort. Among 481 females and 491 males, mothers reported beverage intake from 3 to 10 years from a food frequency questionnaire. The primary outcome was the homeostatic model assessment for insulin resistance (HOMA-IR), and secondary outcomes were waist circumference, truncal fat mass, fasting glucose, and glycated hemoglobin in late adolescence. We applied inverse probability weighting of longitudinal marginal structural models to account for baseline and time-varying confounding, and censoring. We estimated that limiting SSBs to 1 serving weekly across childhood would reduce HOMA-IR by 0.28 units (95% confidence interval [CI], -0.61 to 0.02), waist circumference by 1.91 cm (95% CI, -3.79 to -0.05), truncal fat mass by 0.64 kg (95% CI, -1.33 to 0.05), and fasting glucose by 1.02 mg/dL (95% CI, -2.40 to 0.35) in males compared to no intervention. In females, effect estimates were near 0 and less precise than males. Effect estimates for 100% fruit juice were small, with imprecise CI in both sexes. Overall, limiting SSBs in childhood may have small effects on insulin resistance, central adiposity, and glycemia in males in this population of low consumers. Trial registration: NCT02820402; https://clinicaltrials.gov/study/NCT02820402.

Introduction and Objective: We examined whether associations of physical activity and dietary habits in early adolescence with glycemic traits 5 years later were modified by type 2 diabetes (T2D) polygenic risk scores (PRS). Methods: We calculated a PRS for T2D, derived from the most recent adult T2D genome-wide association study, in a cohort of white non-Hispanic youth from Project Viva (MA, USA). At a median age 13y we assessed moderate-to-vigorous physical activity (MVPA, min/d) by accelerometry, and sugary drink, fast-food, and fruit and vegetable intakes by diet screener. At follow-up (median age 18y), we measured fasting glucose, insulin, and HbA1c. We estimated exposure by PRS interaction terms with linear regression models, adjusting for baseline age, sex, the first 3 genetic principal components, and socioeconomic factors. Results: In 516 youth (50% female), higher MVPA was associated with lower HOMA-IR and fasting glucose, with stronger associations among those at higher T2D-PRS (Figure). Consuming fast-food at least (vs. <) 1x/week was associated with 14.20% (95% CI: 0.05, 28.35) higher HOMA-IR, without evidence of interaction by T2D-PRS. We did not detect interactions between other dietary habits and T2D-PRS on glycemic markers. Conclusion: Youth at higher genetic risk for T2D may benefit more from increasing MVPA for T2D prevention, while limiting fast-food could be favourable irrespective of genetics. Disclosure S. Harnois-Leblanc: None. I. Aris: None. S. Rifas-Shiman: None. E. Oken: None. D. Manousaki: Research Support; Current; Sanofi. Speaker's Bureau; Current; Sanofi. Advisory Panel; Current; Sanofi. W. Perng: None. J. Merino: None. M. Hivert: None. Funding American Diabetes Association (7-23-PDFT2DY-03), National Institutes of Health (R01034568, R24ES030894)

Background/Objectives: We aimed to identify eating habits associated with hepatic fat fraction (HFF) and assess effect modification by an established genetic variant for fatty liver disease, PNPLA3 rs738409, among 381 general-risk adolescents. Methods: Dietary intake was assessed using the Block Kids Food Frequency Questionnaire and HFF was measured via magnetic resonance imaging (MRI) at age ~16 years. We first characterized naturally occurring dietary patterns using principal component analysis followed by reduced-rank regression with HFF as the response variable to identify a dietary pattern that is both relevant to the population and associated with HFF. Next, we investigated associations of the dietary pattern with HFF using linear regression models that accounted for maternal gestational diabetes, education, and prenatal smoking and child sex, age, Tanner stage, and BMI. Finally, we tested for a dietary pattern and PNPLA3 rs738409 interaction and stratified by genotype if P-interaction < 0.05. Results: The participants were 16.7 ± 1.2 years (range: 12.6-19.6 years). Half were female (50.4%) and 52.0% identified as non-Hispanic White. The dietary pattern of interest was composed of vegetables, fruit, nuts and seeds, oatmeal, sports bars, crackers and sandwiches, and beef, and was inversely associated with HFF (-0.48 [95% CI: -0.81, -0.16]). Stratified analyses revealed the strongest inverse association observed between the diet pattern score and HFF in the high-risk-variant (GG) group (-2.19 [-4.35, -0.03]), followed by the intermediate-risk (CG) group (-0.43 [-0.77, -0.10]), but not the low-risk (CC) group (-0.32 [-0.77, 0.13]). Conclusions: A diet high in vegetables, fruit, nuts and seeds, oatmeal, sports bars, crackers and sandwiches, and beef-potentially capturing an active, on-the-go lifestyle-is associated with lower HFF during adolescence, especially among individuals at genetic risk.

OBJECTIVE:Although polycystic ovary syndrome (PCOS) is associated with high body mass index (BMI), less is known about the cardiometabolic manifestations of PCOS without excess adiposity. Among female adolescents enrolled in the Project Viva longitudinal prebirth cohort, we characterized growth, adiposity, and cardiometabolic biomarkers among those with vs without PCOS, stratified by BMI category. METHODS:We defined PCOS at the mid-teen visit (mean age 17.7 years) as self-reported diagnosis or oligo-anovulation with clinical/biochemical hyperandrogenism. We obtained anthropometric and dual x-ray absorptiometry measurements. Within each BMI category (≥85th percentile vs < 85th percentile), we used unadjusted linear regression to compare growth trajectories, adiposity, and cardiometabolic biomarkers among those with vs without PCOS. We used mixed effects models to visually represent estimated BMI and linear growth trajectories. RESULTS:Among 358 females with data at the mid-teen visit, n = 51 (14%) participants met our criteria for PCOS. Among females with BMI <85th percentile, those with PCOS (n = 27) had earlier age at peak height velocity [β = -.57 years; 95% confidence interval (CI) -0.96, -0.18], higher Homeostatic Model Assessment of Insulin Resistance (β = .77, 95% CI 0.23, 1.30), and lower adiponectin-leptin ratio (β = -.35, 95% CI -0.65, -0.06) vs without PCOS. Females with BMI ≥85th percentile had similar biomarkers by PCOS status. Adiposity measures did not differ by PCOS status within either BMI category. CONCLUSION:Within this population-based cohort, adolescents with PCOS and BMI <85th percentile had greater insulin resistance and adipose tissue dysfunction vs without PCOS. PCOS-associated metabolic dysfunction exist even among adolescents with BMI <85th percentile.

BACKGROUND:Sugar-sweetened beverages (SSBs) have been linked to obesity and metabolic dysfunction in youth; whereas the effects of 100% fruit juice, which is also high in free sugar, remain debated. OBJECTIVE:To compare metabolomic profiles of SSB versus 100% fruit juice intake across childhood and adolescence. METHODS:Data were from 593 youth in the EPOCH cohort collected during childhood (6-14 years) and adolescence (12-19 years). A food frequency questionnaire assessed total-energy-adjusted SSB and fruit juice intakes over the past week and fasting serum samples were assayed by untargeted metabolomics profiling. Least Absolute Shrinkage and Selection Operator (LASSO) regression with bootstrapping identified metabolites associated with each beverage at each visit. Metabolites consistently selected across visits were retained and compared. RESULTS:Mean (SD) SSB intake was 6.9 (4.9) and 5.2 (3.7) servings/week in childhood and adolescence, respectively, and mean fruit juice intake was 2.4 (2.6) and 1.7 (2.0) servings/week. Of 767 metabolites, 40 were associated with SSB intake and 39 were associated with fruit juice intake at both visits. Only three metabolites were associated with SSB and fruit juice intake (argininate, cortisone, quinate); all others were unique. Both beverages were linked to metabolites of amino acid, xenobiotic, lipid, and carbohydrate metabolism (10, 11, 8 and 1 metabolites, respectively, for SSB; 7, 8, 8 and 3 metabolites, respectively, for juice intake). CONCLUSIONS:SSB and 100% fruit juice intake are associated with largely distinct metabolomic profiles, suggesting some degree of beverage-specific metabolic effects in youth. Future studies are needed to replicate these findings, explore the role of common endogenous pathways and characterise mechanisms.

AIMS:The American Heart Association's Life's Essential 8 cardiovascular health (CVH) construct strongly predicts cardiovascular disease (CVD), yet biological processes associated with early-life CVH trajectories are unclear. We examined associations of CVH score and trajectory parameters across childhood with cardiovascular-related proteins. METHODS AND RESULTS:We derived CVH scores (0-100 points) in 424 children at median ages 3.2, 7.7, 13, and 17.5y. Segmented mixed-effect models estimated three CVH trajectory parameters: timing of inflection when CVH declines and slope before and after inflection. We assayed 92 proteins from plasma samples in late adolescence (17.5y). Linear regression models assessed cross-sectional (CVH in late adolescence) and longitudinal (CVH trajectory parameters) associations with proteins, with false discovery rate correction via Benjamini-Hochberg method. Mean (SD) late-adolescent CVH was 75.5 (10.5) points. Cardiovascular health slope before inflection was 0.6 (1.4) points/y, timing of inflection was 10.1y (0.7), and slope after inflection was -1.2 (1.2) points/y. Cross-sectionally, a 1-SD higher CVH was associated with 29 differentially abundant proteins (DAPs); five showed robust associations with log2-fold change ≥|0.2| (higher FGF-21, HAOX1, IL-1ra, LEP, and lower GH). Longitudinally, 1-SD increments in CVH trajectory parameters were associated with up to 13 DAPs; specifically, we observed robust associations of timing of CVH inflection with higher LEP and CVH slope after inflection with higher IL-1ra, LEP, and SERPINA12. These DAPs implicated lipid metabolism, inflammation, and glyoxylate/oxalate production pathways. CONCLUSION:We identified novel protein biomarkers reflecting adolescent CVH and cumulative impact of childhood CVH trajectories, which may inform preventive strategies early in life to alter CVD progression.

Objective:Attention-deficit/hyperactivity disorder (ADHD) affects an increasing number of children in the United States. Identifying risk factors is paramount to decreasing ADHD burden in the population. This study sought to examine the prospective association between maternal prenatal perceived stress and ADHD diagnosis in offspring. Method:A diverse subset of 6,080 mother-child dyads from the Environmental Influences on Child Health Outcomes (ECHO) cohort study met our analytic inclusion criteria. Child age ranged from 3 to 15 years. Associations between maternal perceived stress during pregnancy and prospective offspring were as follows: (1) ADHD diagnosis, by a health care provider, or (2) ADHD symptoms, assessed with the Child Behavior Checklist. These associations were evaluated using generalized regression models, adjusted for sociodemographic and lifestyle covariates. Sex- and age-stratified models assessed possible effect measure modification. Results:High maternal perceived stress during pregnancy was associated with increased odds of offspring ADHD diagnosis (adjusted odds ratio [aOR] = 2.46 [1.47, 4.15]) and higher scores on CBCL ADHD-related subscales (aORADHD DSM-5 clinical vs normal = 5.14 [2.44, 10.86] and βexternalizing problems = 7.66 [6.57, 8.75] among preschool-aged children, and aOR ADHD DSM-5 clinical vs normal = 4.94 [1.22, 20.03] and βexternalizing problems = 7.04 [4.34, 9.75] among school-aged children). Conclusion:Findings suggest that maternal prenatal perceived stress is associated with increased ADHD diagnosis risk and symptoms in offspring. Minimizing stress during pregnancy through stress management or other programs may facilitate improved management of ADHD symptoms in youth.

Introduction and Objective: Childhood adiposity is a risk factor for chronic disease development. While maternal obesity has been linked to higher offspring body mass index, there is limited data on associations with adiposity trajectories. We assessed % fat mass (%FM) trajectories from birth to adolescence by maternal pre-pregnancy body mass index (ppBMI). Methods: We used data from 1,270 mother-child pairs in the Healthy Start Study, a Colorado pre-birth cohort. Maternal ppBMI values were categorized as pre-pregnancy healthy weight (<25 kg/m2), overweight (25-30 kg/m2), or obesity (≥30 kg/m2). Offspring %FM was measured with air displacement plethysmography at birth (~2 days), infancy (~5 months), early-childhood (~5 years), mid-childhood (~9 years) and adolescence (~11 years). Longitudinal mean response profile models, adjusted for maternal factors and child sex, were used to assess offspring %FM by ppBMI category. Results: Offspring of mothers with pre-pregnancy overweight or obesity had consistently higher mean %FM from early-childhood onward compared with offspring of mothers with pre-pregnancy healthy weight. Adiposity trajectories further diverged between groups over time (Figure). Conclusion: Maternal overweight and obesity are associated with higher offspring adiposity trajectories from early-childhood through adolescence. Efforts addressing maternal pre-pregnancy obesity status may reduce childhood adiposity. Disclosure M. Farron: None. D. Glueck: None. W. Perng: None. C. Friedman: None. C.C. Cohen: None. M. Kelsey: Research Support; Current; Rhythm Pharmaceuticals, Inc. D. Dabelea: None. Funding National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases (R01DK076648, UH3OD023248/UG3OD023248, R01DK133235)

BACKGROUND:Diet is a source of environmental toxicants; however, chemical exposures are not considered in the United States Dietary Guidelines for Americans (DGA). OBJECTIVES:We tested whether higher DGA adherence was associated with gestational chemical exposures. METHODS:Pregnant participants in the Environmental influences on Child Health Outcomes Cohort completed a food frequency questionnaire or 24-h recall at a median of 21 wk of gestation, which we used to calculate the Healthy Eating Index (HEI)-2015 total and individual component scores to assess DGA adherence. In spot urine samples collected at a median of 22 wk of gestation, we measured 113 analytes representing 10 chemical classes, including insecticides, fungicides/herbicides, organophosphate esters (OPEs), halogenated phenols, benzophenones, bisphenols, parabens, antimicrobials, phthalates/alternatives, and polycyclic aromatic hydrocarbons (PAHs). Using Bayesian generalized linear mixed-effects regression, we estimated covariate-adjusted percentage differences (β; biomarkers with ≥70% detection) or detection risk ratios (biomarkers with 30%-69% detection) and 95% credible intervals (CrIs) in urinary chemical biomarker concentrations for each 10-point increase in HEI-2015 total score. We used quantile-based g-computation to identify the top HEI-2015 component contributors to associations. RESULTS:Most participants (n = 1492) self-identified as non-Hispanic White (40%) or Black (36%), and 50% had incomes ≥$50,000. The median (25th, 75th percentile) HEI-2015 score was 61.9 points (53.6, 70.2; of 100). We detected 53 analytes, representing biomarkers of 45 chemical parent compounds, in >30% of participants. Higher HEI-2015 scores were associated with lower OPE, halogenated phenol, bisphenol, phthalate, and PAH biomarker concentrations, most notably monobenzyl phthalate (β: -13.5%; 95% CrI: -21.0%, -5.8%). However, higher HEI-2015 scores were also associated with higher insecticide, paraben, and benzophenone biomarker concentrations, most notably benzophenone-3 (β: 16.2%; 95% CrI: 5.9%, 26.8%). Lower added sugar and higher protein, vegetable, fruit, and whole-grain intake were consistent predictors of lower or higher chemical biomarker concentrations. CONCLUSIONS:Greater DGA adherence may minimize exposure to some, but not all, toxicants.

PURPOSE:To examine factors associated with moving during pregnancy and impacts of assigning nSES at enrollment, delivery, or a time-weighted average on birth outcomes (birthweight, birthweight-for-gestational-age z-score, low birthweight, gestational age, small-for-gestational age, preterm birth). METHODS:We used data from the Environmental influences on Child Health Outcomes (ECHO) Cohort Study (2010-2019) with nSES data from the American Community Survey (ACS) matched by time and location to monthly residential histories. We used multivariable logistic models with Generalized Estimating Equations to identify factors associated with moving and quantify exposure misclassification in model estimates. RESULTS:Approximately 7 % of 15,376 participants moved at least once during pregnancy. Maternal age (OR: 0.97, 95 % CI: 0.95, 0.98) and other race vs. White (OR: 0.39, 95 % CI: 0.20, 0.80) were associated with lower odds of moving; lower neighborhood-level education (OR: 1.34, 95 % CI: 1.11, 1.62) and living in urban neighborhoods (OR: 3.03, 95 % CI: 1.39, 6.59) were associated with higher odds. Among movers, estimates between nSES and birth outcomes changed ≥ 16 % by address assignment; birthweight-for-gestational-age z-score was significant only when using nSES at delivery. CONCLUSION:Sociodemographic and nSES characteristics are associated with moving during pregnancy; movers may experience exposure misclassification and underestimated effects on birth outcomes.

INTRODUCTION:While inflammation is a normal physiological process of pregnancy, exposure to excess inflammation in utero may have unfavourable consequences for the offspring's health. This analysis investigated associations of prenatal inflammation with offspring adiposity in early childhood. METHODS:Among 555 mother-offspring pairs in the Healthy Start Study, we measured three inflammation biomarkers-C-reactive protein, interleukin-6 and tumour necrosis factor-α-at ~28 gestational weeks. We internally standardised each biomarker and took its average as an indicator of overall exposure to prenatal inflammation. When offspring were 4-6 years old, we measured weight and height for body mass index (BMI) z-score calculation; waist circumference; and % fat mass (%FM) using air displacement plethysmography. In the analysis, we used linear regression to examine associations of the prenatal inflammation z-score with offspring outcomes. As an exploratory analysis, we conducted stratified analysis by maternal race/ethnicity, which is known to modify associations in maternal-child health studies. RESULTS:After adjusting for offspring age and sex, each increment in the prenatal inflammation z-score corresponded with 0.31 (95% CI: 0.14, 0.48) higher BMI z-score, 1.43 (0.61, 2.25) cm higher waist circumference and 1.47 (0.43, 2.51) higher %FM in offspring. Further adjustment for maternal pre-pregnancy BMI attenuated estimates to the null for BMI z-score and waist circumference, but less for %FM (0.77 [-0.39, 1.94]; p = 0.19). These associations were driven by Hispanic mother-offspring pairs. CONCLUSIONS:Prenatal inflammation may predispose offspring to greater adiposity during early childhood. This association is partially explained by maternal BMI and driven by participants of Hispanic ethnicity. TRIAL REGISTRATION:NCT #002273297.

Cesarean sections (CS) create unnecessary health risks for mothers and newborns in low-risk contexts. In the United States, low-risk CS prevalence is higher among people of color, though this may vary across regions. We investigated low-risk CS prevalence by race and ethnicity in a Colorado pregnancy cohort comprising primarily Hispanic and non-Hispanic White mother-offspring pairs. Pregnant women in Denver, Colorado were enrolled (2009–2014, n = 1,410). 904 mother-offspring pairs met the criteria for low-risk birth and were included in this analysis. Low-risk CS was based on (1) Society for Maternal-Fetal Medicine criteria and (2) nulliparous, term, singleton, vertex (NTSV) criteria. Demographic and clinical characteristics were self-reported or extracted from medical records and included in statistical models as potential confounders. Poisson regression assessed relative risk of delivering via low-risk CS by race and ethnicity independent of demographic and clinical characteristics. A sensitivity analysis excluded non-nulliparous births. Participants self-identified as non-Hispanic White (58

Psychosocial distress is associated with adverse perinatal outcomes, yet its biological correlates remain incompletely understood. We evaluated associations of prenatal psychosocial distress with allopregnanolone (ALLO) and related steroids, and assessed race/ethnicity as a potential effect modifier, using data from 237 participants from the Healthy Start Study. We selected participants based on high distress (Edinburgh Perinatal Depression Scale [EPDS] ≥13 or EPDS-3A ≥7; n = 57) or low distress (EPDS <4 and EPDS-3A <2; n = 180). We quantified ALLO, progesterone, pregnanolone, cortisol, and cortisone in maternal serum using HPLC-MS/MS at two timepoints in pregnancy for each participant, (median ∼17 and ∼27 weeks' gestation; range: 10-34 weeks). We modeled the relationship between high vs. low prenatal distress with repeated measures of the steroid hormones using linear mixed-effects models. We found that ALLO was 20.6% lower (95% CI: -30.9%, -8.7%) in high-distress individuals after adjusting for maternal age, fetal sex, smoking and gestational age at blood draw, with no evidence of effect modification by race/ethnicity. However, this association attenuated after additional adjustment for sociodemographic characteristics. Several ALLO-related ratios were lower with high distress, but only ALLO-to-progesterone remained significant across models. These findings suggest that associations between psychosocial distress and circulating ALLO concentrations during pregnancy are influenced by social and structural factors, with the exception of the ALLO-to-progesterone ratio, which may capture aspects of neurosteroid metabolism more closely linked to prenatal psychosocial distress.

Introduction: Physical activity, sedentary time and sleep are determinants of adolescent cardiometabolic health. However, few studies have examined the interrelatedness of these behaviors in a 24h period, which is more applicable to the real world and could better inform public health policies. Hypothesis: Reallocation of time from sedentary behaviors to physical activity over 24h in early adolescence is associated with the most cardiometabolic health benefits in late adolescence. Methods: We used data from the ongoing Project Viva prebirth cohort (Eastern Massachusetts, USA, births 1999-2002). In early adolescence (median age 12.9 years), participants wore a wrist accelerometer for 7-10 consecutive days and completed sleep logs. We determined the average minutes spent in sleep, sedentary time, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) using validated cut points. In late adolescence (median age 17.5 years), we collected fasting blood for adiponectin, glucose, and insulin and calculated HOMA-IR. We analyzed how proportion of time spent in each of the four activity categories in early adolescence was associated with glucose, insulin, and adiponectin in late adolescence using compositional data analysis, adjusting for participants’ age, sex, and season of actigraphy in early adolescence and maternal education and household income at enrollment. Results: A total of 802 adolescents (n=394 with outcome data) had valid accelerometer data, with 51.9% female and 63.7% non-Hispanic white (Table). The sample average 24h time composition was 33% for sleep, 48% for sedentary activities, 17% for LPA and 2% for MVPA. Allocating time towards sleep or MVPA at the expense of sedentary time in early adolescence was associated with lower HOMA-IR in late adolescence (Figure). More specifically, reallocating 30 minutes of sedentary time to MVPA or to sleep was associated with a 14.8% (95%CI: -23.3; -5.1) and 4.7% (95%CI: -7.8; -0.6) reduction in HOMA-IR, respectively, while reallocating to LPA would yield no significant change in HOMA-IR (2.9%, 95%CI: -0.9; 7.4). Our results did not support associations of activity 24h composition with adiponectin or fasting glucose. Conclusions: Allocating more time in MVPA and sleep on a 24h period in early adolescence is associated with lower insulin resistance in late adolescence. Public health strategies should focus on promoting MVPA and sleep to preserve optimal cardiometabolic health in adolescents.

BACKGROUND:Many women have suboptimal cardiovascular health (CVH), which declines during midlife. Few studies have characterized CVH across the menopausal transition or identified its sociodemographic and neighborhood determinants. METHODS:We analyzed a prospective cohort of women in eastern Massachusetts enrolled during pregnancy (1999-2002) and followed to midlife (2019-2024). Exposures included household income, education, race and ethnicity, and neighborhood Social Vulnerability Index (categorized from very low [<20th percentile] to very high [≥80th percentile]; higher categories=greater neighborhood vulnerability). Women self-reported their menopause status using questionnaires. Using Life's Essential 8, we derived CVH scores (0-100 points; higher score=better CVH) at 3-, 8-, 13-, 18-, and 23-year follow-up visits. Linear spline mixed-effect models examined associations of sociodemographics and neighborhood Social Vulnerability Index with differences in CVH across different menopause stages (premenopause, perimenopause, and postmenopause). RESULTS:Among 1200 women (mean enrollment age, 32.1 years; 67.5% Non-Hispanic White), 15.4% had household incomes ≤$40 000/y, 8.8% had ≤high school education, and 17.4% resided in very high Social Vulnerability Index neighborhoods. After covariate adjustment, women with lower income, lower education, or identifying as Non-Hispanic Black exhibited lower CVH across follow-up. Independent of individual sociodemographics, continued residence in vulnerable neighborhoods over time was associated with lower CVH and unfavorable CVH trajectories across follow-up. For example, residence in very high (versus very low) Social Vulnerability Index neighborhoods from enrollment to 3-year follow-up corresponded to mean CVH differences of -6.7 (95% CI, -12.3 to -1.2) at 3-year, -9.8 (95% CI, -15.6 to -4.0) at 8-year, -8.9 (95% CI, -13.9 to -3.9) at 13-year, -6.7 (95% CI, -12.9 to -0.5) at 18-year, and -7.2 (95% CI, -12.5 to -1.9) at 23-year follow-up, and with faster CVH score decline during premenopause (-0.62 points/y; 95% CI, -1.22 to -0.02). CONCLUSIONS:Women from disadvantaged sociodemographic backgrounds or residing in vulnerable neighborhoods exhibit poorer CVH across the menopausal transition, highlighting opportunities to optimize long-term CVH and mitigate cardiovascular disease risk.