Obesity最新文献

{"title":"Multidimensional Analysis of Early Adiposity Rebound Determinants in Children: Two Key “1000 Days”","authors":"Ling Luo,&nbsp;Xing Wang,&nbsp;Juan Tong,&nbsp;Yongkang Liu,&nbsp;Ping Lv,&nbsp;Qizheng Huang,&nbsp;Jie Wang,&nbsp;Cong Geng,&nbsp;Hong Gan,&nbsp;Menglong Geng,&nbsp;Beibei Zhu,&nbsp;Shuman Tao,&nbsp;Hui Gao,&nbsp;Xiulong Wu,&nbsp;Kun Huang,&nbsp;Shuangqin Yan,&nbsp;Fangbiao Tao","doi":"10.1002/oby.70278","DOIUrl":"10.1002/oby.70278","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Adiposity rebound (AR), the second rise in BMI during growth, increases the risk of obesity and metabolic diseases when it occurs early. We aimed to identify key factors influencing early AR (EAR) within two critical 1000-day periods and develop a predictive model.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Based on the Ma'anshan Birth Cohort (MABC), we collected serial BMI from birth through school age and applied linear mixed models to construct individual growth curves for determining AR. EAR was defined as AR timing at or below the sex-specific 25th percentile (≤ 55.46 months in boys and ≤ 60.54 months in girls) in MABC. Among the 2072 parent-offspring trios included, 65 potential factors were collected from maternal, pregnancy, paternal, and offspring sources. Ten machine learning techniques and SHAP were used to evaluate feature importance.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Multimethod screening identified EAR determinants, including paternal and maternal pre-pregnancy overweight/obesity, pregnancy organic phosphate esters (OPE) exposures, offspring high genetic risk (the predominant contributor), catch-up BMI trajectory, and high waist circumference trajectory. The categorical boosting model demonstrated the best performance among 10 machine learning models for predicting EAR (AUC_training = 0.764, 95% CI = 0.733–0.795; AUC_testing = 0.721, 95% CI = 0.669–0.773).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>EAR determinants may inform future interventions, including weight management, prenatal OPE exposure reduction, and early screening for genetically high-risk individuals.</p>\u0000 \u0000 <div>\u0000 \u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"34 10","pages":"1915-1935"},"PeriodicalIF":4.9,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148803894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neighborhood-Level Variation in the Effectiveness of Intensive Health Behavior and Lifestyle Treatment for Pediatric Obesity","authors":"Grace Wang,&nbsp;Stephanie Samuels,&nbsp;Kaitlin R. Maciejewski,&nbsp;Pamela Hu,&nbsp;Mary Savoye,&nbsp;Mona Sharifi","doi":"10.1002/oby.70292","DOIUrl":"10.1002/oby.70292","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study assessed variation in BMI change by neighborhood characteristics of participants in Bright Bodies, a family-based intensive health behavior and lifestyle treatment for pediatric obesity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>For first-time participants (2008–2018) with initial BMI ≥ 85th percentile, we geocoded addresses and assigned Child Opportunity Index (COI) and COI-Healthy Environment (COI-HE) scores (Low/Moderate/High). Using multivariable mixed effect linear regression, we assessed monthly change in BMI percent of the 95th percentile (%BMIp95) and extended BMI <i>z</i> score by COI and COI-HE.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of 391 youth (mean ± SD age 11.7 ± 2.8 years, 60.1% female), 80.8% resided in Low COI and 66.5% in Low COI-HE neighborhoods. Monthly %BMIp95 change differed by COI (<i>p</i> = 0.039 for interaction) and COI-HE (<i>p</i> = 0.004). Mean %BMIp95 decreased in all subgroups; greatest reductions were in High COI (−1.86 [95% CI: −2.40, −1.33]) and High COI-HE groups (−2.32 [−2.78, −1.85]) and lowest in Moderate COI (−1.17 [−1.59, −0.75]) and Low COI-HE groups (−1.53 [−1.75, −1.32]). Change in extended BMI <i>z</i> score differed significantly between COI-HE subgroups only (<i>p</i> &lt; 0.001).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Bright Bodies participation was associated with BMI reduction among all COI/COI-HE subgroups, but the highest COI/COI-HE groups had the greatest reductions. Modifications to intensive health behavior and lifestyle treatments should address inequities in access to built environments that facilitate healthy, active living.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"34 10","pages":"1936-1944"},"PeriodicalIF":4.9,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.70292","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148993303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Major Adverse Liver Outcomes With Tirzepatide and Injectable Semaglutide in Adults With Overweight or Obesity and Type 2 Diabetes","authors":"Mainak Banerjee,&nbsp;Ajitesh Roy,&nbsp;Vivek Mohan Sharma,&nbsp;Abhishek Das","doi":"10.1002/oby.70277","DOIUrl":"10.1002/oby.70277","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study aimed to compare the effectiveness of tirzepatide versus injectable semaglutide in preventing major adverse liver outcomes (MALO) among adults with overweight or obesity and type 2 diabetes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective target trial emulation utilized the TriNetX global network to analyze new users of tirzepatide and semaglutide. The primary outcome was time-to-first MALO (a composite of cirrhosis, decompensated events, and hepatocellular carcinoma). Propensity score matching balanced baseline covariates.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Over a median follow-up of ~17 months, no significant difference in MALO risk was observed between tirzepatide and semaglutide initiators (estimated incidence rate [IR] 4.05 vs. 4.04 per 1000 person-years [PY]; hazard ratio [HR] 1.04, 95% CI 0.88–1.23). This comparable risk profile was maintained across sensitivity analyses, including people with MASLD (IR 9.97 vs. 10.03 per 1000 PY; HR 1.03, 95% CI: 0.75–1.42) and “as treated” analysis (HR 0.98, 95% CI: 0.80–1.21). Tirzepatide achieved greater BMI reduction (mean difference ~1.1 kg/m², <i>p</i> &lt; 0.001). Internal validation confirmed both agents significantly outperformed sitagliptin.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In this high-risk population with type 2 diabetes, tirzepatide and injectable semaglutide offered comparable effectiveness in mitigating liver disease progression and MALO in the short- to medium-term follow-up.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"34 10","pages":"1958-1966"},"PeriodicalIF":4.9,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148803891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond BMI: Genome-Wide Associations of Visceral Fat, Fat Mass, and Fat-Free Mass in Eastern Asian Populations","authors":"Hsin-Ming Lu,&nbsp;Shun-Jen Chang,&nbsp;Kuei-Hau Luo,&nbsp;Yun-Shiuan Chuang,&nbsp;Fu-Wen Liang,&nbsp;Hung-Yi Chuang","doi":"10.1002/oby.70276","DOIUrl":"10.1002/oby.70276","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>BMI is widely used to define obesity and may not capture heterogeneity in body fat distribution. Genetic studies of obesity have largely focused on BMI but not visceral fat and fat-free mass, which is particularly limited in East Asian populations. This study aimed to explore the genetic associations among body composition traits.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted genome-wide association studies (GWAS) of fat composition traits, including visceral fat, fat mass, and fat-free mass, in 14,121 adults from a population-based biobank. Bioelectrical impedance analysis was used for standardized body composition. GWAS were performed, followed by multinomial logistic regressions for associations across phenotype strata, adjusting for BMI and confounders.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>GWAS identified multiple SNPs significantly associated with visceral fat, fat mass, and fat-free mass. A variant within the TTN-rs794727539 was inversely associated with visceral fat and positively associated with fat-free mass, independent of BMI. Additional loci showed trait-specific associations, while many fat-mass-associated variants were attenuated after BMI adjustment, highlighting different genetic regulation of fat distribution.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We found that visceral fat, fat mass, and fat-free mass were governed by partially distinct genetic mechanisms not fully captured by BMI. These results underscore the importance of incorporating fat composition phenotypes into genetic studies in East Asian populations.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"34 10","pages":"1967-1978"},"PeriodicalIF":4.9,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.70276","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148842637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hepatic FMO3 Downregulation Contributes to the Metabolic Benefits of Vertical Sleeve Gastrectomy","authors":"Hai Yan,&nbsp;Chong Cao,&nbsp;Xiaozhuo Tan,&nbsp;Xianjue Huang,&nbsp;Yanyang Liu,&nbsp;Yuxiao Chu,&nbsp;Mengcheng He,&nbsp;Qiyuan Yao,&nbsp;Rong Hua,&nbsp;Yikai Shao","doi":"10.1002/oby.70281","DOIUrl":"10.1002/oby.70281","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Metabolic bariatric surgery, such as vertical sleeve gastrectomy (VSG), is the most effective treatment for obesity, yet the molecular mechanisms remain incompletely defined. This study aims to explore the role of hepatic flavin monooxygenase 3 (FMO3) in the metabolic improvements of VSG.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Hepatic FMO3 was assessed in liver biopsies from human patients. Diet-induced obese mice underwent VSG, targeted hepatic FMO3 inhibition with antisense oligonucleotides, or VSG with concurrent FMO3 knockdown. Outcomes included weight loss, glucose tolerance, insulin sensitivity, serum lipids, hepatic steatosis, circulating bile acid profiling, hepatic gene expression involved in the FXR pathway, and bile acid synthesis/transport.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In mouse models, VSG suppressed hepatic FMO3 expression, leading to significant weight loss, enhanced glucose and lipid metabolism, and reduced hepatic steatosis. Inhibition of FMO3 using antisense oligonucleotides recapitulated many of these effects, while silencing FMO3 diminished VSG's metabolic benefits. Clinical data revealed elevated hepatic FMO3 expression in patients with obesity and its downregulation after VSG, correlating with metabolic improvements. Additionally, FMO3 downregulation was associated with alterations in bile acid metabolism and FXR signaling.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <div>Hepatic FMO3 downregulation contributes importantly to the metabolic benefits of VSG. Targeting hepatic FMO3 may offer a nonsurgical strategy to reproduce key clinical benefits of metabolic bariatric surgery.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"34 10","pages":"1880-1891"},"PeriodicalIF":4.9,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148681629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Forcing Factors That Predict Obesity: A Cross-Sectional Multilevel Machine Learning Model of US County-Level Prevalence","authors":"Nicolaas P. Pronk,&nbsp;Shuaijie Wang,&nbsp;Colin Woodard,&nbsp;Ross Arena","doi":"10.1002/oby.70283","DOIUrl":"10.1002/oby.70283","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Variables predicting obesity are not limited to individual-level risk factors. The purpose of this study is to assess multilevel predictors of obesity prevalence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>US county-level datasets incorporating 34 variables were analyzed cross-sectionally using explainable artificial intelligence (XAI) analytical methods. A Light Gradient Boosting Machine Model was trained to predict obesity prevalence, after which model performance and feature importance were evaluated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Optimal model performance included 29 features and explained 78% of the variance in county-level obesity prevalence. The dominant predictor of obesity prevalence was physical inactivity. Additional highly important variables include smoking, excessive drinking, political ideology, and regional culture.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study used XAI methods to predict obesity, explaining 78% of the variance at the granular county level. Inclusion of both upstream and downstream factors in multisectoral and multidisciplinary approaches to predicting population-level obesity prevalence is warranted.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"34 10","pages":"1945-1957"},"PeriodicalIF":4.9,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148842712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Dietetic Counseling Combined With Digital Tools on Obesity-Related Indices in Greek Adults: The GATEKEEPER Study","authors":"Rafaela Makri,&nbsp;Iliana Evangelou,&nbsp;Eva Karaglani,&nbsp;Maria Vlachava,&nbsp;George E. Dafoulas,&nbsp;Ioanna Drympeta,&nbsp;Konstantinos Votis,&nbsp;Eleni I. Georga,&nbsp;Dimitrios I. Fotiadis,&nbsp;Francisco Lupiáñez-Villanueva,&nbsp;Frans Folkvord,&nbsp;Leandro Pecchia,&nbsp;Giuseppe Fico,&nbsp;Demosthenes Panagiotakos,&nbsp;Odysseas Androutsos,&nbsp;Yannis Manios,&nbsp;GATEKEEPER study (Greek Use Case 1) group","doi":"10.1002/oby.70284","DOIUrl":"10.1002/oby.70284","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study aimed to evaluate the effectiveness of dietetic counseling with digital tools on obesity-related and metabolic outcomes in adults aged ≥ 55 years at high risk for metabolic syndrome (MetS).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In this 3-month randomized controlled trial, 984 adults aged ≥ 55 years with ≥ 1 MetS risk factor were randomized (1:1:1) to: standard care (monthly dietetic counseling), standard care plus web-based platform, or standard care plus platform and digital devices. Analyses included 954 participants and used linear mixed-effect models under a missing-at-random assumption adjusted for age and sex. The primary outcome was change in waist circumference. Secondary outcomes included BMI, body composition indices, physical activity, and glycemic markers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Waist circumference decreased in all groups (−6.29, −4.92, −4.69 cm), with smaller reductions in the platform (MD −1.38 cm; 95% CI −2.37 to −0.38) and platform + devices groups (MD −1.61 cm; 95% CI −2.61 to −0.60). BMI, body composition indices, and glycemic markers improved similarly across groups. Physical activity increased more in the platform + devices group (MD +55.52 MET-min/week; 95% CI 15.32 to 95.72).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Dietetic counseling improved anthropometric and metabolic outcomes in adults at risk for MetS. Digital tools enhanced physical activity but did not provide additional short-term metabolic benefits.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Trial Registration</h3>\u0000 \u0000 <p>ClinicalTrials.gov identifier: NCT05031299</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"34 10","pages":"1849-1859"},"PeriodicalIF":4.9,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.70284","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149003143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Navigating the Numerous Frameworks for Obesity Care","authors":"Priya Sumithran,&nbsp;Louise A. Baur","doi":"10.1002/oby.70273","DOIUrl":"10.1002/oby.70273","url":null,"abstract":"&lt;p&gt;More than 30 years ago, the World Health Organization (WHO) defined obesity as “the degree of fat storage associated with clearly elevated health risks.” However, a lack of agreement about cutoff points for the percentage of body fat that defines obesity, and the difficulty of measuring fat mass under field conditions, led the WHO Expert Committee to propose classifying adults according to body mass index (BMI) [&lt;span&gt;1&lt;/span&gt;]. While acknowledging that BMI does not measure fat mass or distribution, provide an indication of health, or account for the heterogeneity of obesity, it was considered “the most useful, albeit crude, population-level measure” to estimate the prevalence of obesity and its associated risks [&lt;span&gt;2&lt;/span&gt;] because height and weight are robust measurements and routinely included in population health surveys.&lt;/p&gt;&lt;p&gt;Decades later, BMI remains the most practicable measure for population descriptions and monitoring, especially in low-resource settings, although appropriate cut points will vary with ethnicity. However, recent therapeutic advances have encouraged rethinking of our approach to obesity in individuals. A profusion of new frameworks for definition, categorization, staging, and management has been put forward [&lt;span&gt;3-5&lt;/span&gt;], leading to understandable confusion about which to use and when. As practicing clinicians, we propose that some clarity may emerge from considering the scope of the issues each framework seeks to address and their common features.&lt;/p&gt;&lt;p&gt;Essential steps in obesity management include establishing the presence and impact of excess adiposity. Three prominent recent frameworks—the Lancet Commission on Clinical Obesity [&lt;span&gt;3&lt;/span&gt;], the European Association for the Study of Obesity (EASO) framework for the diagnosis, staging, and management of obesity in adults [&lt;span&gt;4&lt;/span&gt;], and the American Association of Clinical Endocrinology (AACE) 2025 algorithm for the evaluation and treatment of adults with obesity/adiposity-based chronic disease [&lt;span&gt;5&lt;/span&gt;]—concur that at an individual level, BMI alone is insufficient for these purposes. All three frameworks recommend confirmation of excess adiposity with an anthropometric measure, particularly to reduce the risk of under-detection of abdominal fat accumulation (and consequently, under-investigation and management of its sequelae) in adults with BMI &lt; 30 kg/m&lt;sup&gt;2&lt;/sup&gt;. The Lancet Commission framework also includes recommendations for children and adolescents.&lt;/p&gt;&lt;p&gt;All frameworks recommend thorough evaluation of obesity's impact on health and well-being through history taking, physical examination, and investigations as relevant. Obesity is a major risk factor for many noncommunicable diseases (NCDs), such as type 2 diabetes, atherosclerotic disease, and several cancers. However, even in the absence of such NCDs, excess adiposity may impair a person's health or functioning (represented in the Lancet Commission's diagnostic criteria for “","PeriodicalId":215,"journal":{"name":"Obesity","volume":"34 10","pages":"1847-1848"},"PeriodicalIF":4.9,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.70273","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148633311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Responses to GLP-1RA in White and Black Adults With Obesity: Insights From Generalized Additive Mixed Models of EHR Data","authors":"Jordan H. Mallette,&nbsp;Joshua S. Speed,&nbsp;Seth T. Lirette,&nbsp;Daniel Moore,&nbsp;John S. Clemmer","doi":"10.1002/oby.70180","DOIUrl":"10.1002/oby.70180","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study examined racial differences in weight loss and clinical response to glucagon-like peptide-1 receptor agonist (GLP-1RA) therapy among adults with obesity using real-world data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We retrospectively analyzed our institution's Research Data Warehouse (RDW) containing deidentified data from electronic health records (EHRs) from adults aged 18 years and older. EHR data from the University of Mississippi Medical Center RDW were analyzed for 7214 adults (2182 White; 5032 Black) prescribed injectable GLP-1RA between 2015 and 2025. Inclusion criteria were BMI ≥ 30 kg/m² and ≥ 1 GLP-1RA. Longitudinal changes in patient data were modeled using generalized additive mixed models.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>At 2.5 years, White individuals experienced significantly greater body weight loss than Black individuals: −7.1% (95% CI −8.0%, −6.2%) versus −4.9% (95% CI −5.4%, −4.3%), as well as significantly larger reductions in estimated glomerular filtration rate, systolic blood pressure, and HbA1c. Semaglutide and tirzepatide were associated with the greatest improvements. Renal function decline was attenuated in both groups after therapy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In a large, diverse EHR cohort, GLP-1RA therapy was associated with significant weight, glycemic, and renal benefits that were attenuated in Black adults. These findings highlight the urgent need to understand mechanisms contributing to variable GLP-1RA outcomes among different populations.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"34 S2","pages":"109-118"},"PeriodicalIF":4.9,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13191755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147597214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sex, Not Age, Predicts Weight Loss Outcomes With Tirzepatide: A Retrospective Analysis","authors":"Regina Castaneda,&nbsp;Dima Bechenati,&nbsp;Rene de J. Rivera Gutierrez,&nbsp;Maria A. Espinosa,&nbsp;Jose Villamarin,&nbsp;Elif Tama,&nbsp;Nancy Safwan,&nbsp;Sima Fansa,&nbsp;Alfredo Verastegui,&nbsp;Allyson W. McNally,&nbsp;Jesse L. Meek,&nbsp;Kristin C. Cole,&nbsp;Stacey J. Winham,&nbsp;Tamim I. Rajjo,&nbsp;Andres Acosta,&nbsp;Stephanie S. Faubion,&nbsp;Chrisandra L. Shufelt,&nbsp;Maria D. Hurtado Andrade","doi":"10.1002/oby.70231","DOIUrl":"10.1002/oby.70231","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study assessed the impact of sex and age on weight loss outcomes in patients receiving tirzepatide in real-world clinical practice.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a retrospective cohort study of adults with overweight or obesity who initiated tirzepatide at Mayo Clinic between June 2022 and May 2024 and completed ≥ 12 months of continuous therapy. Primary outcome was total body weight loss percentage (TBWL%) at 15 months, stratified by sex and age groups (≤ 45, 46–59, ≥ 60 years).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among 1039 patients (57% women; mean age 56 ± 11 years), women achieved significantly greater TBWL% than men after 15 months of treatment (15.1% vs. 10.7%, <i>p</i> &lt; 0.001). Patients aged ≤ 45 years had greater weight loss than those ≥ 60 years (15.1% vs. 12.3%, <i>p</i> = 0.024). In multivariable analyses, greater weight loss was independently associated with female sex, absence of type 2 diabetes, no prior obesity medication use, no concomitant weight gain-promoting medications, and higher tirzepatide dosage. Age was not an independent predictor.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Sex, but not age, predicted weight loss with tirzepatide among individuals using the medication continuously for ≥ 12 months. These findings underscore the importance of incorporating sex-specific considerations into personalized obesity treatment strategies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"34 S2","pages":"132-145"},"PeriodicalIF":4.9,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148255229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}