Obesity

Current recommendations suggest that women achieve a healthy weight before becoming pregnant, but evidence supporting the benefits of preconception weight loss are limited and inconsistent, with some evidence of risks. The Maternal Preconception Weight Trajectory (MatTrack) study will evaluate the impact of preconception weight change on maternal, pregnancy, and child outcomes. In this paper, we present methods used to construct the cohort and evaluate baseline characteristics. The MatTrack cohort was derived from electronic health record data from four Kaiser Permanente regions. Inclusion criteria addressed data quality, availability, and enrollment; maternal age ([≥]18 years); and date (pregnancy onset date in 2006-2020, delivery [≤]12/31/2020). Starting body mass index (BMI) was calculated using weight closest to 24 months prior to pregnancy onset date and adult height. Preconception weight change rates from 24 months prior to and through pregnancy onset date were estimated using linear mixed effects models. Descriptive analyses characterized the baseline characteristics of the cohort. The cohort includes 297,592 pregnancies with the full spectrum of starting BMI: underweight (2.3%), normal weight (41.8%), overweight (28.4%); and obesity class I (15.3%), II (7.4%), and III (5.0%). The cohort is demographically diverse, with 8.3% covered by Medicaid; and 44.5%, 9.2%, and 10.9% Hispanic, non-Hispanic Black, or non-Hispanic Asian, respectively. Preconception weight change rates (kg/year) span weight loss to gain, with the greatest loss in those with obesity class III [median (10th, 90th percentile): -0.8 (-9.5, 4.9)] and the greatest gain in those with underweight [median (10th, 90th percentile): 1.1 (-0.7, 3.6)]. Longitudinal data from this cohort of nearly 300,000 linked maternal-child dyads will enable examination of associations between preconception weight loss and pregnancy, maternal, and child health outcomes. Findings will strengthen the evidence base for preconception weight management guidelines.

Background Lifestyle interventions are central to obesity prevention and management, yet interindividual variability in response remains incompletely understood. Here, we leveraged genetically defined, distinct obesity endotypes to examine lifestyle-body mass index (BMI) associations across biological pathways. Methods In the UK Biobank, we analyzed 305,713 participants with partitioned polygenic scores (pPSs) representing 10 obesity endotypes. We evaluated interactions between endotype-specific genetic susceptibility and physical activity, diet, sedentary behavior, and sleep on BMI using multivariable linear regression. Primary findings were externally evaluated in the All of Us Research Program using Fitbit-derived lifestyle measures. Results Favorable lifestyle behaviors were associated with lower BMI for all obesity endotypes, but the magnitude of these associations varied significantly across endotypes. Higher endotype-specific pPSs strengthened the benefits of physical activity (7 endotypes), healthy diet (3 endotypes), nonsedentary behavior (5 endotypes), and adequate sleep (7 endotypes) on BMI. Distinct endotypes demonstrated the greatest responsiveness to different lifestyle domains, with the metabolically unhealthy endotype showing the strongest interaction with physical activity, metabolically healthy endotype with sedentary behavior, hypothalamic dysregulation endotype with diet, and hypoinsulin 2 endotype with sleep, corresponding to differences in BMI of 0.22-0.49 kg/m2 between the highest and lowest pPS deciles. These interaction patterns were consistent in the All of Us cohort. Conclusions Obesity endotypes modify the association between lifestyle behaviors and BMI, demonstrating that responsiveness to lifestyle behaviors is heterogeneous and pathway dependent. These findings provide a framework for precision obesity prevention by identifying individuals who may derive greater benefit from specific lifestyle interventions.

Background: Early postoperative weight loss may help predict later outcomes, but its reliability for longer-term weight loss and regain remains unclear. We assessed whether the percentage total weight loss (%TWL) 3 months after metabolic/bariatric surgery predicted later %TWL weight change/regain. Methods: This retrospective observational cohort study included 216 patients from a prospectively pre-recruited multicentre bariatric surgery cohort who underwent sleeve gastrectomy or Roux-en-Y gastric bypass and had 3-month %TWL and at least one later outcome. Linear regression assessed associations between 3-month %TWL and later %TWL plus weight change/regain outcomes. Adjusted incremental R2 quantified the additional variance explained by 3-month %TWL. Secondary procedure-stratified, diabetes-stratified, and baseline BMI comparator analyses are reported in the Supplementary Material. Results: Greater 3-month %TWL was associated with higher 1-year and 2-year %TWL in adjusted models (both p < 0.001) but not longer-term %TWL (p = 0.078). Incremental R2 was 38.23% for 1-year, 11.75% for 2-year %TWL and 2.25% for long-term %TWL. Greater 3-month %TWL was also associated with greater recurrent weight gain from 1 to 2 years and from 1 year to long-term follow-up. In secondary analyses, findings were broadly consistent across procedure and diabetes subgroups, while 3-month %TWL explained more additional variance in 1-year %TWL than baseline BMI Conclusion: 3-month %TWL predicted 1-year and 2-year outcomes but not longer-term %TWL, supporting its value as an early marker of postoperative weight trajectory. Heterogeneity in recurrent weight stability may contribute to weaker long-term prediction and warrants further study to determine whether early weight-loss patterns can identify patients requiring closer long-term weight management support.

Aims To characterize adults with obesity in a large integrated health system. Methods We created a cross-sectional cohort of adults with at least one body mass index (BMI) value >=30 kg/m2 in the prior 18 months, a recent in-person outpatient visit, and an assigned primary care provider. Electronic health record data were transformed into a patient-level analytic dataset and linked to neighborhood-level social determinants of health. Diagnoses, laboratory values, vital signs, and prescriptions were curated using reproducible phenotype definitions and internally reviewed vocabularies. Results The registry included 284,143 adults, of whom 48% had class I obesity. The cohort was 63% female, 27% black, and 48% lived in areas with high or very high social vulnerability. Common comorbidities included hypertension, type 2 diabetes, depression, and anxiety. HbA1c and cholesterol measurements were absent in more than 40% of the cohort during the prior two years. Overall, 22% of patients received a prescription for at least one weight loss drug in the past 2 years, including 18% who received a GLP-1 agonist approved for weight management. Conclusions This care-engaged obesity cohort was characterized by high representation of women and socially vulnerable populations, substantial cardiometabolic screening gaps, and broad adoption of GLP-1 agonists.

Background: Heat-inactivated postbiotics derived from Lactiplantibacillus plantarum have been proposed to support weight management and metabolic health by acting on the gut-metabolic axis, including endogenous glucagon-like peptide-1 (GLP-1) signaling. resM is an orally delivered formulation combining heat-inactivated L. plantarum RSB11 (RSB11-HI) with vitamin D3, vitamin B12, chromium picolinate, white mulberry (Morus alba) leaf, and fenugreek (Trigonella foenum-graecum) seed extracts. We tested the effects of resM on body weight and a panel of metabolic outcomes in adults with overweight or obesity. Methods: In a randomized, double-blind, placebo-controlled, parallel-group trial (NCT06911073), 80 adults with overweight or obesity were allocated 1:1 to oral resM or matched placebo for 8 weeks. The trial was conducted in a fully remote, direct-to-consumer setting. The primary outcome was absolute change in body weight at the final scheduled weekly assessment, Week 7, corresponding to completion of the 8-week intervention. Secondary outcomes included body-mass index; fasting insulin, HbA1c, and HOMA-IR; serum active GLP-1; strain-specific stool quantitative PCR for L. plantarum RSB11; food cravings measured using the Food Craving Questionnaire-Trait-reduced; depressive symptoms measured using the PHQ-9; safety laboratory measures; and adverse-event surveillance. Between-group differences were evaluated using independent-samples t-tests and baseline-adjusted ANCOVA, and within-group changes were evaluated using paired tests. Results: Body weight decreased by 2.6 kg, or 3.0%, in the resM group and increased by 0.5 kg, or 0.6%, in the placebo group. Food-craving scores fell by 15.1 points within the resM arm during the 8-week intervention (p<0.001), as did depression scores. Active GLP-1 approximately doubled among participants treated with resM and increased more than in the placebo group. Serum GLP-1 levels correlated with L. plantarum RSB11 levels in stool samples in the resM arm. Safety laboratory values remained within reference ranges, gastrointestinal symptoms were reported more frequently with placebo than with resM, and no serious adverse events were reported in either group. Conclusions: Over 8 weeks, resM produced clinically meaningful weight loss within the intervention group and compared with placebo, together with reductions in food cravings and depression scores and an approximately two-fold increase in active GLP-1. Larger and longer-duration trials are needed to confirm the persistence and generalizability of these findings.

Purpose: Nighttime fasting intervals (NFIs; i.e., the longest period between the last eating episode of the day and the first of the next day) are associated with depressive symptoms in non-pregnant populations. However, this chrono-nutrition indicator has rarely been explored in the perinatal period, when individuals experience dramatic physiological and psychological changes. We explored potential associations between NFIs and depressive symptoms during the perinatal period. Methods: This secondary analysis included 232 individuals with pre-pregnancy body mass index (BMI) [&ge;]25 kg/m2. Participants were assessed during early-pregnancy, mid-pregnancy, and at 6-months postpartum. NFIs and breakfast time were estimated from 24-hour dietary recall interviews, and depressive symptoms were self-reported using the Center for Epidemiologic Studies Depression Scale. NFIs were categorized into three classifications to represent short, middle, and long NFIs. Longitudinal associations were evaluated using mixed effects linear models with interaction terms between NFIs and each timepoint. Results: NFIs remained largely stable at the group level across the three study visits (M [SD] = 12.7 [2.75] hours). Although NFIs were not significantly associated with depressive symptoms, long NFIs showed geometric mean ratio of 0.84 (95% CI: 0.64 to1.11) relative to middle NFIs at mid-pregnancy. Conclusions: NFIs and depression were not associated among this perinatal sample. Future studies should explore circadian eating patterns (e.g., the timing of the last eating episode relative to dim-light melatonin onset), different timepoints (e.g., late pregnancy), and pregnant individuals across the weight spectrum.

The satiety cascade includes post-prandial increases in plasma glucose and insulin, and changes in appetitive gut hormones, including decreases in orexigenic stomach-derived ghrelin, and increases in liver-foregut-derived LEAP2 hormone, a ghrelin antagonist. However, which contribute to post-prandial attenuation of eating behaviour with increasing preload meal size is unclear. In a randomised, single-blinded study, adults without obesity attended four visits, consuming 750mL liquid preloads 0, 600, 900, 1200 kcal, with assay of plasma glucose, acyl ghrelin (AG), LEAP2 and serum insulin over 0-3h with appetite ratings (n=17, 65 visits). At 2h a virtual portion size creation task measured desired food intake (n=15, 58 visits, after data exclusion), and at 3h an ad libitum meal measured actual food intake (n=11, 43 visits). The greater the pre-load meal size, the greater the post-prandial increase in plasma glucose and serum insulin, and greater the decrease in plasma AG and AG/LEAP2 ratio, associated with greater attenuation of eating behaviour (appetite ratings, desired/actual food intake). The strongest correlations of eating behaviour with blood measures were for serum insulin, plasma AG and AG/LEAP2 ratio, with weaker results for plasma glucose. Although there was a weak correlation of post-prandial plasma LEAP2 with pre-load meal size but not with eating behaviour. Post-prandial increases in serum insulin and decreases in plasma AG and AG/LEAP2 ratio appear part of the satiety cascade related to preload meal size in adults without obesity. Future studies should investigate potential mediation of satiety in this context via other appetitive gut hormones, and in obesity.

Objective. This systematic review and meta-analysis synthesised the global prevalence of overweight and obesity in people with Down syndrome (DS) across the lifespan, characterised determinants of excess adiposity, and examined associations with adverse cardiometabolic outcomes. Methods. Six databases were searched without date or language restriction. Two independent reviewers screened studies, extracted data, and assessed quality using the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies. Prevalence was pooled using a random-effects logit model. A pre-specified subgroup analysis by age band was conducted. Publication bias was assessed with Egger's test and certainty of evidence with Grading of Recommendations Assessment, Development and Evaluation (GRADE). Results. Twenty-six studies (7,840 individuals; 14 countries) were included. The pooled prevalence was 18% (95% CI 15-22%) in children and adolescents, 36% (95% CI 26-47%) in adults, and 30% (95% CI 20-43%) in mixed-age cohorts; the test for subgroup differences was significant. The overall pooled prevalence was 22% (95% CI 18-26%; prediction interval 7-53%; I^2 = 95.3%). No publication bias was detected (Egger's t = 0.39, p = 0.6964). DS-specific growth charts yielded estimates 14-37 percentage points lower than general-population references applied to the same cohorts. Obesity more than doubled obstructive sleep apnea risk (RR 2.4; 95% CI 1.34-4.34) and non-alcoholic fatty liver disease was present in 82% of obese versus 45% of non-obese children with DS. GRADE certainty was Moderate for prevalence estimates. Conclusions. Overweight and obesity in DS are highly prevalent, age-progressive, and substantially exceed general-population rates at every life stage. Roughly one in five people with DS is affected overall, rising to more than one in three adults. The reference chart applied is the single largest source of heterogeneity in reported estimates. Cardiometabolic surveillance, adapted lifestyle interventions, and primary prevalence research from low- and middle-income countries are the highest-priority gaps.

Background & Aims: Childhood obesity is a complex, heterogeneous disease. Children with obesity are often grouped into metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) phenotypes, although this classification may oversimplify the underlying metabolic diversity. We aimed to characterise the metabolic profiles associated with the conventional MHO/MUO classification and to identify data-driven metabolic profiles in 267 children and adolescents with obesity. Methods: In this cross-sectional study, we used serum 1H-NMR spectroscopy to quantify lipoproteins, glycoproteins, low-molecular-weight metabolites, and lipid fractions. Univariate comparisons and partial least squares discriminant analysis (PLS-DA) were used to characterise NMR-derived variables associated with MHO and MUO groups. We applied unsupervised k-means clustering based on principal component scores to identify data-driven metabolic profiles independent of the predefined clinical phenotypes. Results: Forty-one NMR-derived variables differed between MUO and MHO (FDR q-value < 0.05), predominantly in the triglyceride-rich lipoprotein and glycoprotein profiles, of which 31 were elevated in MUO. PLS-DA discriminated between MHO and MUO (AUC = 0.84, Q2 = 0.33; permutation p < 0.001). Unsupervised clustering identified two data-driven metabotypes that only partially overlapped with the clinical phenotypes: 27% of children with MHO clustered within the adverse metabolic profile (Cluster 2), characterised by a triglyceride-rich and inflammation-associated profile, whereas 41% of children with MUO were assigned to the comparatively favourable profile (Cluster 1). Clustering further revealed additional differences in lipoprotein subclasses and lipid composition that the MHO/MUO classification did not capture. Conclusions: The conventional MHO/MUO classification captures an important component of metabolic variation in childhood obesity but does not fully capture cardiometabolic heterogeneity. Quantitative 1H-NMR metabolomics identified putative metabotypes characterised by differences in lipoprotein composition and cholesterol distribution beyond clinical phenotypes. These findings support the potential value of metabolomic profiling to refine cardiometabolic risk stratification in children with obesity; however, the relevance of these data-driven metabotypes requires confirmation in independent cohorts and longitudinal follow-up studies.

Background: Real-world evidence on food-as-medicine programs for irritable bowel syndrome (IBS) is scarce, and single-arm evaluations overstate improvement because of regression to the mean (RTM). We estimated change in the IBS Symptom Severity Scale (IBS-SSS, 0-500) in a multi-omics personalized digital health food-as-medicine program, unadjusted and RTM-corrected. Methods: Retrospective single-arm cohort. Of 15,933 members with a valid baseline, 2,254 had a follow-up reading and 1,683 one at least 14 days after baseline. Change at 4, 12 (primary) and 26 weeks was estimated by baseline severity stratum, unadjusted and RTM-corrected by analysis of covariance. A responder fell by at least 50 points (the minimal clinically important difference benchmark). Sensitivity analyses covered equity, inverse-probability weighting and tipping-point analyses for members without a reading in each landmark window, a negative-control stratum and medication. The association of weight loss and dietary nutrient density with symptom change was evaluated within and between members. Results: At 12 weeks (n = 430) IBS-SSS fell by 43.88 points unadjusted (95% confidence interval [CI] -52.44 to -35.32; p < 0.001) and by 47.73 RTM-corrected (-55.48 to -39.98; p < 0.001); 720 of 1,339 symptomatic members (53.8%; 95% CI 51.1 to 56.4) fell by at least 50 points. Larger improvement in more severe members persisted after RTM correction (severe stratum, n = 37: unadjusted -127.43, RTM-corrected -60.71, 95% CI -97.75 to -23.68, p = 0.001). A higher meal nutrient density was associated with lower IBS-SSS within a member's own trajectory (p = 0.018) while weight change was not (p = 0.361). Improvement was similar across groups in spite of baseline differences by age and sex: RTM-corrected 12-week change did not differ by age (p = 0.458), body-mass index (p = 0.328), sex (p = 0.749), income (p = 0.486) or ethnicity (p = 0.170). Estimates were robust to weighting for members without a reading in the landmark window (RTM-corrected estimates moved by less than 2 points), and the change of those members would have had to be 39 to 73 points worse than observed before the mean change reached zero. Baseline medication use and starting a GLP-1 receptor agonist did not explain symptom changes. Conclusions: IBS-SSS fell significantly among program participants, with steeper improvement in the more severe group, even after RTM correction. The improvement was comparable across socioeconomic characteristics, age and sex and robust to the confounders and missing-data assumptions evaluated. These associations from a self-selected single-arm cohort warrant replication in independent studies.

Background: Tirzepatide is conventionally initiated at 2.5 mg weekly and titrated to approved maintenance doses. Evidence describing weight change at injectable starting doses below 2.5 mg/week is limited. Methods: We conducted a retrospective, single-organization observational study of adults documented as new GLP-1 starts, with baseline body mass index (BMI) [&ge;]27 kg/m2, who initiated compounded injectable tirzepatide at a microdose of 1 or 2 mg/week (below the standard 2.5 mg/week starting dose). Source records were reviewed for baseline validity, prior treatment, weight consistency, and treatment exposure. The main descriptive analysis selected the latest eligible measurement per patient within observation windows of 14-35, 36-59, and 60-89 days of adjudicated treatment exposure, excluding observations after escalation above 2 mg/week. All 93 eligible measurements were included in a supporting random-intercept model. Analyses were retrospective and hypothesis-generating; no formal sample-size calculation was performed. Results: Sixty patients contributed 93 eligible follow-up measurements, of which 84 were selected for patient-window summaries. Mean age was 47.3 years, 81.7% were female, and mean baseline BMI was 33.3 kg/m2. Mean body-weight loss was 2.18% (95% CI 1.61-2.76; n=57) in the 14-35-day window at a median 21 days, 3.58% (95% CI 2.43-4.72; n=19) in the 36-59-day window at a median 48 days, and 6.10% (95% CI 4.60-7.60; n=8) in the 60-89-day window at a median 65.5 days. The adjusted model estimated 2.16 percentage points greater loss per 30 days of treatment exposure (95% CI 1.69-2.63). Conclusions: Weight loss was observed within the 14-35-, 36-59-, and 60-89-day observation windows among evaluable adults initiating compounded injectable tirzepatide at 1-2 mg/week. These uncontrolled findings are hypothesis-generating; the 36-59- and 60-89-day estimates are particularly limited by sparse follow-up.

Body mass index (BMI) alone may underestimate clinically relevant obesity because it does not capture central fat distribution. We compared obesity prevalence in Mexico using BMI-only criteria, adiposity-confirmed criteria, and the clinical obesity definition proposed by the Lancet Diabetes and Endocrinology Commission. We conducted a population-based, cross-sectional study of 13,160 adults aged 18 years or older who participated in the 2018-2019 Mexican National Health and Nutrition Survey (ENSANUT). Obesity prevalence was estimated through survey-weighted analyses that accounted for the complex sampling design. The weighted prevalence of obesity based on BMI was 34.5% (95% CI, 33.1-35.9), while 30.9% (95% CI, 29.6-32.2) met criteria for clinical obesity. One quarter of individuals with clinical obesity had a BMI under 30 kg/m2, a phenotype more common among older adults. Half of adults with a BMI under 30 kg/m2 showed elevated central adiposity. BMI alone underestimates clinically relevant obesity in Mexican adults. Adding waist-based measurements could improve the identification of individuals with excess fat and metabolic risk, both in clinical settings and population monitoring.

Purpose: In high-income countries, lower socioeconomic position (SEP) is linked to higher childhood obesity prevalence but its association with cardiometabolic risk in those presenting in pediatric weight management services remain underexplored. Methods: In the Bern Obesity in Childhood and Adolescence Biorepository (BOCAB), we used the Swiss neighborhood index of SEP (0-100, 100=highest SEP) to assess cross-sectional associations with obesity severity and cardiometabolic risk factors, mediation by behavioral lifestyle factors and longitudinal associations between SEP and percentage of the 95th BMI percentile (%BMIp95) and waist circumference-to-height ratio (WHtR), adjusted for age and sex. Results: Among 886 participants (52% male, mean age 11.2 years [SD 3.1]), mean %BMIp95 was 124% (SD 17%). A 10-unit higher SEP was associated with lower %BMIp95 ({beta} -2.57; 95% CI -3.84 to -1.31) and lower WHtR ({beta} -0.006; -0.010 to -0.001), both partially mediated by weekly physical activity and screen time. Higher SEP was also associated with lower odds of insulin resistance (OR 0.80; 0.65 to 0.98), low HDL-cholesterol (OR 0.81; 0.67 to 0.98), elevated non-HDL-cholesterol (OR 0.74; 0.59 to 0.92) and elevated triglycerides (OR 0.83; 0.70 to 0.98). Among 419 participants with longitudinal data, annual reduction in %BMIp95 and WHtR did not differ by SEP. Conclusion: Lower SEP is associated with greater obesity severity and cardiometabolic risk among children and adolescents with obesity presenting at specialized tertiary care. Screening and early referral of lower-SEP children and adolescents with obesity should be encouraged, before cardiometabolic risk accumulates, particularly since treatment response did not differ once enrolled.

Background: Both fetal and maternal genomes contribute to birthweight, but the timing and relative magnitude of their effects during gestation remain unclear. Polygenic risk scores (PRSs), constructed from genome-wide association studies (GWAS), capture the cumulative influence of common birthweight-associated variants to quantify genetic predisposition to fetal growth. We constructed fetal and maternal PRSs for birthweight in two UK birth cohorts, the Pregnancy Outcome Prediction Study (POPS) and Born in Bradford (BiB), to evaluate their associations with estimated fetal weight (EFW) throughout pregnancy and with birthweight at delivery. We also investigated whether PRSs could improve risk stratification of infants born below the 10th centile by distinguishing those with pathological intrauterine growth restriction (IUGR) from those who are constitutionally small-for-gestational-age (SGA). Methods: In POPS and BiB, we used LDpred2-auto to estimate PRSs based on the largest available maternal and fetal GWAS for birthweight. We longitudinally assessed EFW associations with PRSs using linear mixed effects models in POPS and BiB. We evaluated birthweight associations with PRSs using linear models, where birthweight was adjusted for gestational age and fetal sex. We estimated R2 and conducted variance decomposition analyses for all models. Genetically-predicted birthweights were estimated from joint models of fetal and maternal PRSs plus ten genetic principal components (PCs). BiB analyses were conducted separately for genetically-inferred European (EUR) and South Asian (SAS) ancestry. Results: While PRSfetus was significantly associated with EFW at baseline ([~]22 weeks gestation) across cohorts, PRSmother was not. Both the interaction of PRSfetus and PRSmother with gestational age (GA) were significantly associated with EFW. The effect of PRSmother on EFW increased more quickly across gestation than the effect of PRSfetus in POPS, but this finding was not replicated in BiB. Jointly, fetal and maternal polygenic risk explained 4% of variance in EFW in POPS and 1% in BiB-EUR. In POPS, fetal and maternal PRSs showed independent contributions to EFW variance of 3% and 0.5%, respectively. Joint and univariable linear models showed significant positive associations of PRSfetus and PRSmother with observed birthweight. In POPS, PRSfetus and PRSmother accounted for [~]10% and [~]4% of variance in birthweight over covariates alone, respectively, which was replicated in BiB-EUR. Maternal and fetal genetic effects jointly explained 11% of birthweight variance in POPS, similar to BiB-EUR, at 12%; however, the variance explained was reduced by half in BiB-SAS, at 6%. Among POPS babies born <10th birthweight centile, the magnitude of the difference between observed and genetically-predicted birthweight was greater in the group judged clinically to be IUGR vs. SGA (p=0.008; point estimate=0.29, 95%CI: 0.12, 0.47). Conclusions: Maternal and fetal PRSs jointly account for [~]11-12% of birthweight variance in European ancestry groups, but much less in a South Asian cohort. In POPS, the effect of birthweight-associated SNPs on estimated fetal weight increases more rapidly across pregnancy for maternal than for fetal genetic effects. Deviation from genetically-predicted birthweight may be a useful metric to help distinguish growth-restricted from constitutionally small babies.

The prevalence of obesity is increasing worldwide, especially amongst younger populations. As both brain and body are still under development, numerous studies have shown that adolescence is an especially sensitive period for the impact of external insults including unbalanced diets. To better understand and prevent the vulnerability to obesity and maladaptive food choice, it is crucial to explore the long-term impact of adolescent exposure to obesogenic diets on different feeding behaviours. To address this, we gave mice access to an obesogenic diet with a very high-fat content (vHFD) specifically during adolescence and investigated the long-lasting impact on feeding at adulthood months after a switch to a healthy diet. Using specific feeding tests, we found that both males and females vHFD-exposed mice exhibited an increased intake of both standard food and palatable high-fat foods, without impacting preference for non-caloric food rewards. Importantly, these sex-dependent alterations are not fully correlated with diet-induced weight gain but may support long-term vulnerability to overeating and the development or maintenance of obesity.

Postmenopausal women are vulnerable to metabolic dysfunction. Compelling evidence suggests this is because they lack the protective effects of estrogens. We have shown that circulating estrogens regulate daily eating and activity rhythms in female mice and protect them from obesity and metabolic dysfunction. However, few studies have investigated whether postmenopausal women have disrupted eating and sleep-activity rhythms that could contribute to metabolic dysfunction. The purpose of this cross-sectional study was to investigate the relationship between sleep and eating rhythms and metabolic risk in postmenopausal women with overweight or obesity. Seven days of sleep and food intake behavior data were collected from postmenopausal women with overweight or obesity. Sleep timing was assessed using wrist-worn actigraphy and sleep logs. First and last calorie intake times were collected daily using text messaging. Visceral adipose tissue (DXA), insulin resistance (Matsuda index), blood pressure, and triglycerides were analyzed as markers of metabolic risk. In 122 postmenopausal women (mean {+/-} SD: 58.1 {+/-} 3.6 yr, 33.2 {+/-} 5.2 kg/m2 BMI), we found that later sleep onset was associated with greater visceral adipose tissue (p=0.0007), but not insulin resistance, blood pressure, or triglycerides. Next, we used a random forest model to quantify the relative contributions of sleep and meal timing variables to predict visceral adipose tissue. The top predictors of visceral adipose tissue were time of sleep onset, sleep duration, and time of last caloric intake. These data suggest that interventions that advance sleep onset may reduce metabolic risk in postmenopausal women.

BackgroundObesity is a complex multifactorial disease associated with chronic low grade inflammation, gut microbiota dysbiosis, and impaired gut-brain communication. Oligomeric procyanidins from grape seed extracts (GSE) are promising prebiotic candidates, capable of modulating host metabolism through interactions with the gut microbiota. MethodsC57Bl/6J male mice were rendered obese by feeding them a high fat, high sucrose diet and were orally administered GSE at a dose of 1or 2 g/kg/day for 12 weeks. We assessed body weight, adiposity, glucose tolerance, insulin sensitivity, circulating hormones, brain homeostasis markers, colonic and liver gene expression, 16S rRNA gene sequencing of the gut microbiota profiles, and untargeted cecal metabolomics. ResultsGSE reduced body weight gain, visceral adiposity, adipocyte hypertrophy, and improved oral glucose tolerance and insulin sensitivity. It normalized circulating lipid and glucose levels and lowered fasting insulin and leptin while increasing endogenous GLP-1. Hepatic gene expression analysis revealed a dose-dependent restoration of antioxidant defenses (SOD, CAT) and lipogenic transcription factors (SREBP, ChREBP). In the colon, GSE attenuated pro-inflammatory IL6 cytokine expression and strikingly upregulated GLP-1 and GLP-1 receptor expression. Microbiota analysis revealed a profound, dose-dependent remodeling of gut microbiota composition and diversity, with an expansion of health-associated taxa, such as Akkermansia muciniphila. Brain analyses revealed restoration of NAA and BDNF levels together with markers consistent with improved mitochondrial function. Cecal metabolomics revealed normalization of secondary bile acid metabolism, restoration of arginine bioavailability, and reduction in the accumulation of L-DOPA and spermidine. ConclusionsAn oligomeric procyanidin-rich grape seed extract acts as a multitarget prebiotic that alleviates diet-induced obesity and is associated with coordinated restoration of gut microbiota composition, GLP-1 signaling, and gut-brain and gut-liver communication pathways. Convergent dose-dependent effects on Akkermansia muciniphila abundance, GLP-1, NAA, and BDNF identify key mechanisms underlying its metabolic benefits.

Background: Vietnam and similar low-middle-income countries face a double/triple burden of overweight-obesity, thinness, and stunting. We examined how pre-pubertal BMI affects longitudinal height trajectories in a large Vietnamese cohort. Methods: We analyzed annual school health data from Hanoi, Ho Chi Minh City, and Haiphong (2018-2025). Children with greater than or equal to 3 visits (n = 40,887) were classified by WHO BMI category (thinness, normal, overweight, obesity) at sex-specific pre-pubertal index ages (males 11 years, females 9 years). Height trajectories were visualized via LOESS smoothing. Between-group differences were tested using Kruskal-Wallis with Dunn post-hoc tests and bootstrap median differences. BMI transitions assessed whether weight-status normalization recovered height potential. Results: At index ages, obese children were taller than normal-BMI peers (+5.1 cm at 11 years, peaking at +5.8 cm at 12 years for males and +4.0 cm at 9 years for females), while thin children were shorter (-3.0 to -4.2 cm). Differences narrowed progressively, becoming non-significant by 15 years in females (p = 0.885) and 17 years in males (p = 0.201). BMI normalization was associated with convergence toward normal-weight peers while persistent thinness showed no recovery. Results were consistent across ages, cities, and sensitivity analyses. Conclusions: Pre-pubertal BMI shapes the tempo, not outcome, of pubertal height gain, supporting early, sex-specific nutritional intervention without compromising adult height.

Omega-3 polyunsaturated fatty acids (n-3 PUFA) influence white adipose tissue (WAT) lipid buffering capacity; however, sex-specific regulation remains understudied. We recently reported that male mice fed a diet containing high alpha-linolenic acid (ALA) had increased WAT mass, reduced serum triglycerides and elevated lipolysis compared to mice fed a diet containing recommended levels of ALA, independent of background dietary protein. The current study examined whether subcutaneous and visceral WAT (scWAT, vWAT) lipolytic activity was altered in female C57BL/6N mice (n=16/group) fed low-ALA (1% energy) or high-ALA (3% energy) diets containing skim milk protein (SMP) or soy protein isolate (SPI) for 8 weeks. Body weight, WAT depot weights and serum triglycerides were unchanged in response to ALA content. Lipolytic markers were mostly unchanged by ALA content except for an increase in adipose triglyceride lipase (ATGL) in vWAT, while diets containing SPI modestly reduced serum cholesterol levels and increased total hormone-sensitive lipase (HSL) content in vWAT. Collectively, WAT lipolytic markers in female mice showed minimal response to diets containing high ALA content, unlike that previously reported in male mice. These results highlight the importance of considering both sexes to ensure generalizability of findings when investigating diet regulation of WAT lipid metabolism.

Background: Yoga may support changes in dietary intake and/or physical activity levels, supporting sustainable weight loss. However, previous research has focused on yoga postures (asanas) rather than breathing practices (pranayama). This study used the proof-of-concept stage in the ORBIT model to evaluate feasibility, acceptability, and preliminary efficacy of a breath-based yoga program integrated within a behavioral weight loss (BWL) intervention. Methods: Fifteen participants with overweight or obesity (BMI: 31.3 +/- 4.3, 80% female) were enrolled in a 16-week, single-arm, group-based BWL intervention which included four breath-based yoga sessions/week, individualized daily goals for energy intake reduction, and progressive aerobic exercise recommendations. Primary outcomes included prespecified benchmarks enrollment, retention, adherence, and acceptability. Secondary outcomes included changes in body weight and composition, metabolic health indices (e.g., blood pressure, fasting glucose, abdominal obesity), physical activity, appetite, and dietary intake. Results: Mean percent weight loss was 6.5 +/- 6.0%, exceeding the pre-defined proof-of-concept benchmark. Recruitment and adherence exceeded established benchmarks, with mean in-class attendance of 84.1 +/- 14.6% and adherence to the prescribed duration of at-home yoga sessions averaging 85.5 +/- 38.4%. However, retention was lower than the pre-specified benchmark (73% vs 80%). Positive changes were observed in waist circumference, blood pressure, and appetite traits. Self-reported satisfaction with the program and outcomes were acceptable (mean ratings >6/10). Conclusions: A BWL with a breath-based, low-intensity yoga can lead to acceptable weight loss with potential benefits in key behavioral and metabolic health indices. Recruitment, high adherence, and satisfaction demonstrated feasibility.