International Journal of Obesity最新文献

Background: The effects of resveratrol supplementation on anthropometric indices, adiponectin, and leptin levels remain inconclusive in individuals with overweight and obesity.

Method: This systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to evaluate the effects of resveratrol supplementation on anthropometric indices, adiponectin, and leptin levels. We searched electronic databases, including Scopus, Web of Science, and PubMed, up to September 2025, to identify eligible RCTs.

Results: A total of 23 RCTs, involving 1005 participants, met the inclusion criteria for the meta-analysis. Resveratrol supplementation did not significantly affect body weight (WMD: -1.42 kg; 95% CI: -3.19, 0.35; P = 0.117), body mass index (BMI) (WMD: -0.47 kg/m²; 95% CI: -0.96, 0.01; P = 0.055), fat mass (FM) (WMD: 0.47 kg; 95% CI: -1.75, 2.69; P = 0.679), body fat percentage (BFP) (WMD: -0.88%; 95% CI: -1.91, 0.15; P = 0.094), fat-free mass (FFM) (WMD: 1.42 kg; 95% CI: -1.04, 3.89; P = 0.257), waist-hip ratio (WHR) (WMD: -0.00; 95% CI: -0.01, 0.00; P = 0.436), adiponectin (WMD: 1.84 µg/mL; 95% CI: -2.25, 5.95; P = 0.378), or leptin (WMD: 1.87 ng/mL; 95% CI: -3.84, 7.60; P = 0.521). However, resveratrol supplementation significantly reduced waist circumference (WC) (WMD: -1.93 cm; 95% CI: -3.10, -0.76; P = 0.001). Subgroup analyses revealed significant reductions in body weight and BMI with doses <1000 mg/day, longer interventions (≥12 weeks), and in females. Additionally, FFM increased significantly among participants aged <50 years, and leptin levels were significantly elevated in both sexes.

Conclusion: This meta-analysis showed that resveratrol supplementation did not significantly impact most anthropometric measures and serum leptin and adiponectin in individuals with overweight and obesity. However, it led to a significant reduction in waist circumference. The PROSPERO registration number: is CRD42024497932.

Background: Childhood obesity and iodine deficiency are prevalent in developed countries and are linked to adverse health outcomes in adulthood. Mild-to-moderate iodine deficiency and insufficient maternal iodine intake during pregnancy may increase the risk of large-for-gestational-age newborns, which are associated with childhood obesity. Despite this, predicting childhood obesity during pregnancy remains a challenge. We assessed and evaluated machine learning algorithms predicting childhood obesity risk using maternal anthropometrics, thyroid function and iodine intake; and identified key prenatal factors contributing to childhood obesity.

Methods: A diagnostic accuracy study was conducted based on 87 parameters collected from a mother-newborn-offspring prospective cohort (N = 191) in a mild-to-moderate iodine deficiency region. Maternal iodine status and thyroid function, including serum free tri-iodo-thyronine (FT3) concentrations, were assessed during the second half of pregnancy. Iodine intake was evaluated using a semi-quantitative food frequency questionnaire. Anthropometric measurements were obtained from mothers during pregnancy, from newborns at birth, and from children at 2 years of age. An outcome of overweight at 2 years was defined as a gender-adjusted weight percentile >85%. The dataset was split into training (80%) and test (20%) sets. Synthetic datasets were created to evaluate the performance of six machine learning models, including artificial neural networks (Nnet) that trained and evaluated the model using 5-fold cross-validation.

Results: The best-performing model was Nnet, which achieved the highest accuracy (1500 instances with a balanced predicted outcome). On the unseen test data, accuracy, Kappa, outcome F1-score and weighted F1 were 0.743, 0.347, 0.500 and 0.769 (respectively). Significant predictors included gravidity, maternal-newborn anthropometrics (height and head circumference, respectively), maternal consumption and dietary intake of iodine-rich foods (popsicle, selected fish, and yogurt) and FT3.

Conclusions: Machine learning approaches show promise in predicting childhood obesity risk using maternal and dietary factors during pregnancy. If validated, these findings could support interventions to reduce childhood obesity rates.

Introduction: Genetic and environmental factors contribute to weight gain, but how these effects change over adulthood is largely unknown. We examined how genetic factors influence BMI changes from young adulthood to old age and how this change relates to BMI in early adulthood.

Data and methods: Data from 16 longitudinal twin cohorts, including 111,370 adults (56% women) and 55,657 complete twin pairs (42% monozygotic), were pooled. The data were divided into three stages (young adulthood-early middle age, late middle age, and old age). BMI changes were calculated via linear mixed effects and delta slope methods. Genetic and environmental contributions to these changes and their correlations with BMI in early young adulthood were estimated through structural equation modeling.

Results: The average BMI increase per year was 0.18 kg/m² in men and 0.15 kg/m² in women during young adulthood-early middle age (18-50 years), decreasing to ≤0.07 kg/m² at older ages. Genetic effects contributed to variance of BMI changes during young adulthood-early middle age (men a² = 0.29; women a² = 0.26) and less so in late middle age (51-64 years) (men a² = 0.05; women a² = 0.16) and old age ( > 65 years) (men a² = 0.13; women a² = 0.18). Most variation was explained by non-shared environmental effects (e² = 0.71-0.95 in men and e²= 0.74-0.84 in women). In men, greater BMI during early young adulthood (18-30 years) was associated with lower BMI changes later in life (r = -0.22 to -0.13), and the association was driven by genetic (r_A = -0.27) and non-shared environmental (r_E = -0.22 to -0.14) factors. In contrast, the association was positive in women (r = 0.05-0.28) and was explained by genetic factors (r_A=0.27-0.51).

Conclusion: Genotype influences BMI changes across adulthood, with its effect varying by age and sex. Environmental effects are the main drivers of adult BMI changes, highlighting the role of modifiable factors in long-term weight regulation.

Obesity is a growing global health issue, leading to complications such as cardiovascular diseases, type 2 diabetes, non-alcoholic fatty liver disease (NAFLD), and chronic inflammation. Existing treatments for people with obesity, including lifestyle changes, pharmaceutical interventions, and surgical procedures, have certain limitations, highlighting the need for alternative therapies. Postbiotics, as inanimate microbial metabolites, offer a novel therapeutic approach. This review discusses how postbiotics exert anti-obesity effects through various mechanisms, including regulation of lipid metabolism and energy homeostasis, gut microbiota modulation, endogenous systemic regulation, inflammatory immunomodulation and intestinal barrier function enhancement, along with other synergistic effects. Our work also evaluates their clinical application potential, emphasizing the safety, efficacy, and advantages over traditional treatments like pharmaceuticals and surgery. Despite promising early clinical trial results, challenges remain in translating postbiotics into clinical practice, including the need for long-term studies to assess their sustained efficacy and safety, standardized production processes, scalability, and addressing individual variability in treatment responses. Overall, postbiotics represent a sustainable and personalized therapeutic strategy for managing obesity and its complications.

Background: The burden of obesity may be compounded by disparities in the quality of cardiovascular care across racial and ethnic groups. We aimed to examine racial and ethnic differences in the control of risk factors for cardiovascular disease (CVD) among adults with obesity.

Methods: We included nonpregnant US adults with obesity aged ≥20 years who participated in the National Health and Nutrition Examination Survey. Participants from a total of 11 survey cycles between 1999-2000 and 2021-2023 were included. Primary outcome was racial and ethnic differences in controlling all risk factors for CVD (including glycemic, blood pressure and lipid control) among participants, where the risk factor targets were glycated hemoglobin <7.0%, systolic and diastolic blood pressure <140/90 mmHg, and non-high-density lipoprotein cholesterol <3.4 mmol/L, respectively. Multivariable logistic regression models were used for analyses.

Results: A total of 21,982 participants with obesity (mean age: 48.4 years, body mass index: 36.0 kg/m², 53.4% females) were included. Across racial and ethnic groups, most participants were young adults aged <65 years, women, and in low education level. All racial and ethnic groups had a significant improvement of all risk factor control temporally (p values for trend <0.01), with the prevalence ranging from 17.1% in 1999-2004 to 31.4% in 2017-2023 for non-Hispanic White (NHW), from 21.7% to 36.1% for non-Hispanic Black (NHB), and from 19.9% to 35.5% for Mexican American (MA). Relative to other groups throughout the survey cycles, NHW had the highest prevalence of glycemic (ranging from 92.1% to 94.2%) and blood pressure (from 77.5% to 83.9%) control, and NHB had the greatest control of lipids (from 32.0% to 54.2%). NHW demonstrated higher medication use than MA in participants whose risk factor targets were not achieved across the survey cycles.

Conclusions: Across racial and ethnic groups, the majority of participants with obesity were young adults, women, and those in low education. While temporal improvement was found in all groups, racial and ethnic differences in the control of CVD risk factors in adults with obesity still remained. Efforts are required to further explore and confirm these results to help reduce the obesity and CVD burden.

Background: A healthy low-fat (HLF) and healthy low-carbohydrate (HLC) diet are common strategies for weight loss that vary in their effects on adiposity and metabolism. Visceral adipose tissue (VAT) is the major contributor to metabolism deregulation, beyond subcutaneous adipose tissue (SAT). Despite strong biological evidence that a HLC diet preferentially decreases VAT, the difficulty measuring it has impeded diet trials. We estimated VAT and SAT in the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) weight loss trial to compare the effects of HLF and HLC diets and effect modification by sex and insulin resistance.

Methods: In a 1-year weight loss trial, DIETFITS, we compared VAT loss between HLF and HLC diets by randomizing N = 609 adults to either diet. VAT was estimated using dual-energy x-ray absorptiometry at baseline, 6 months, and 12 months. Linear mixed models analyzed associations between diet and VAT. We built separate models to evaluate effect modification by sex and insulin resistance.

Results: Among 449 participants (60% women; mean age 39 years), VAT loss was significantly greater for those eating the HLC diet compared to the HLF diet at 6 months [10.6 cm²; 95% confidence interval (CI): 5,16.2] and 12 months (6.3 cm²; 95% CI: 0.6,12). VAT relative to SAT loss estimates were greater in the HLC diet at 6 months only. Men experienced greater HLC diet-induced VAT loss than did women. Insulin secretion status did not modify VAT loss.

Conclusions: The HLC diet was associated with greater VAT loss compared to the HLF diet over 12 months. The loss of metabolically harmful VAT was independent from SAT over 6 months. Direct estimation of adipose sub-types provides strong evidence that insulin resistance does not modulate diet response. Sex differences should be considered in effective dietary interventions targeting VAT reduction and metabolic health.

Background/objectives: A concern with intentional weight loss among middle-aged and older adults with obesity and type 2 diabetes mellitus (T2DM) is the loss of lean mass, which may lead to declining physical function. However, the association between changes in body composition with intentional weight loss and physical function over the long-term is unknown. Thus, we examined the association between changes in body composition and physical function 8 years following an intensive lifestyle intervention (ILI).

Subjects/methods: We conducted a secondary analysis of participants at the Baton Rouge site within the Look AHEAD study. Participants (n = 220) were middle-aged and older adults with overweight/obesity and T2DM randomized to an ILI or diabetes support and education (DSE). Body composition was measured by dual-energy X-ray absorptiometry at baseline and Year 8. Physical performance (expanded Short Physical Performance Battery [SPPB_exp], 20- and 400-m walk) and strength (grip and knee extensor) were assessed at Year 8.

Results: Percent change (mean ± SD) from baseline in weight, fat and lean mass over 8 years were -4.0 ± 7.3%, 0.2 ± 12.5% and -6.5 ± 5.3% in ILI and -3.0 ± 9.7%, 1.2 ± 17.1% and -5.8 ± 6.6% in DSE, respectively. ILI had better SPPB_exp scores and faster gait speed than DSE at 8-year follow-up (p < 0.05). Increases in fat mass were associated with worse SPPB_exp scores in ILI and DSE (p = 0.03) and with slower gait speed in DSE (p = 0.01). Decreases in lean mass were associated with weaker grip strength in ILI (p = 0.04) and knee extensor strength in ILI and DSE (p < 0.05). There were no significant interactions by intervention group.

Conclusions: Although the overall intervention effect on physical function was positive, increases in fat mass were associated with poorer physical performance while lean mass loss was associated with weaker strength 8 years post-randomization. Findings highlight the importance of minimizing fat mass gain/regain and loss of lean mass during intentional weight loss.

Background: Shorter sleep duration and longer screen time are established risk factors for adolescent obesity. However, the extent to which these behaviors are prospectively associated with the transition back from overweight/obesity to a healthy status remains unclear. We examined whether sleep duration and screen time among adolescents with overweight/obesity are associated with the likelihood of transitioning to a normal body mass index (BMI).

Methods: We used data from 3498 U.S. adolescents aged 9-11 years with overweight/obesity (45.1% female), from the Adolescent Brain Cognitive Development (ABCD) Study. Cox proportional hazards models examined the prospective associations of parent-reported sleep duration (9-11, 8-9, 7-8, and <7 h/day) and screen time (hours/day) with a shift from overweight/obesity (BMI percentile ≥85) to a normal (BMI percentile <85) accounting for key covariates including pubertal status.

Results: Over a median 657 days of follow-up, 643 (18.4%) adolescents transitioned from overweight/obesity to a normal BMI percentile. Compared with those sleeping 9-11 h, adolescents sleeping 7-8 h were less likely to transition to a normal BMI percentile (hazard ratio [HR]: 0.60, 95% CI 0.44, 0.82), with significant dose-response trend (p for trend = 0.003). The association remained significant in sex-stratified analyses for both females (HR: 0.55, 95% CI 0.30, 0.98) and males (HR: 0.59, 95% CI 0.41, 0.86), with similar significant trend in both groups (p for trend <0.05). Higher screen time was not associated with transitioning to a normal BMI overall (HR: 0.99, 95% CI 0.96, 1.02) or by sex (females, HR: 1.00, 95% CI 0.95, 1.05; males, HR: 0.99, 95% CI 0.95, 1.02).

Conclusion: Short sleep duration was prospectively associated with a lower likelihood of transitioning to a normal BMI among adolescents with overweight/obesity. This association warrants further investigation as a potential intervention target.

Background: Rapid infant weight gain (RIWG) and infant social withdrawal are important early markers of risk of subsequent overweight/obesity and mental health problems, respectively. While overweight and mental health problems are linked later in life, it remains unclear if this association is present already in infancy.

Objective: We examine if infant social withdrawal is associated with subsequent RIWG independently of an array of known risk factors (gestational age, birth weight, sex, parity, breastfeeding, maternal postpartum depressive symptoms, maternal smoking during pregnancy, maternal age at birth and pre-pregnancy BMI, family educational level, and employment status).

Methods: In a cohort of 12,468 children born 2015-19 in Copenhagen, we analyzed the association between infant social withdrawal around age 3 months, measured with the Alarm Distress Baby Scale (ADBB)-a validated screening tool, and subsequent RIWG. We retrieved information on social withdrawal and weight during infancy from health visitors' records and linked these to register data. Multivariate logistic regression was used to estimate adjusted odds ratios (aOR) and 95% confidence intervals (CI) for RIWG, adjusting for the known risk factors outlined above.

Results: Children showing signs of social withdrawal had 1.19 higher odds of RIWG compared to children showing no signs of social withdrawal (aOR 1.19; 95% CI: 1.03, 1.37, p = 0.017). RIWG was also more likely among boys, firstborns, children born small-for-gestational age, and those with mothers who smoked during pregnancy or had higher pre-pregnancy BMI. In contrast, higher birth weight and breastfeeding >4 months were protective factors. No associations were found with maternal postpartum depression, low education, parental labor market status, or maternal age.

Conclusions: We found an association between infant social withdrawal and subsequent rapid infant weight gain independently of an array of known risk factors, which may expand our understanding of the developmental origins of excess weight gain and its association with early childhood mental health.