Obesity Medicine最新文献

{"title":"Elucidating the potential benefit of pump-delivered subcutaneous GLP-1R agonist: an exploratory study in the diet-induced obese mouse","authors":"Elaine Chiquette ,&nbsp;Louise Thisted ,&nbsp;Michael Feigh ,&nbsp;Stephen Daly ,&nbsp;James Besser ,&nbsp;David G. Maggs","doi":"10.1016/j.obmed.2025.100681","DOIUrl":"10.1016/j.obmed.2025.100681","url":null,"abstract":"<div><div>Subcutaneous pump delivery of the GLP1-receptor-agonist exenatide reduced body weight and improved glycemia in the DIO mouse. Basal-bolus administration conferred advantage over basal alone. This mode of incretin-based therapy offers an alternative to conventional intermittent dosing and further examination of this approach is warranted.</div></div>","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"59 ","pages":"Article 100681"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ketosis or calories: The question of diabetes pseudoremission","authors":"Mohammed Abrahim MD CCFP(EM) FCFP ABOM","doi":"10.1016/j.obmed.2025.100677","DOIUrl":"10.1016/j.obmed.2025.100677","url":null,"abstract":"","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"59 ","pages":"Article 100677"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors contributing to non-persistence of glucagon-like peptide-1 agonists: a cross-sectional study","authors":"Shania Liu ,&nbsp;Genieve Wong ,&nbsp;Pavneet Mavi ,&nbsp;Stephanie C. Gysel ,&nbsp;Daniel Burton ,&nbsp;Neire Monteiro ,&nbsp;Derek Durocher ,&nbsp;Arya M. Sharma ,&nbsp;Ross T. Tsuyuki","doi":"10.1016/j.obmed.2025.100674","DOIUrl":"10.1016/j.obmed.2025.100674","url":null,"abstract":"<div><div>Type 2 diabetes and obesity are major public health concerns worldwide. This study examined reasons for stopping GLP-1 agonist therapy. Nearly half discontinued within six months. Key reasons included side effects, shortages, cost, perceived ineffectiveness, and life circumstances.</div></div>","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"59 ","pages":"Article 100674"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning prediction of adolescent obesity using physical fitness data","authors":"Tatiana Sampaio ,&nbsp;Samuel Encarnação ,&nbsp;Bruna Amaro ,&nbsp;Joana Ribeiro ,&nbsp;Luís Branquinho ,&nbsp;António M. Monteiro ,&nbsp;José E. Teixeira ,&nbsp;Soukaina Hattabi ,&nbsp;Andrew Sortwell ,&nbsp;Luciano Bernardes Leite ,&nbsp;Alexandra Malheiro ,&nbsp;Pedro Rodrigues ,&nbsp;Beat Knechtle ,&nbsp;Pedro Flores ,&nbsp;Pedro Forte","doi":"10.1016/j.obmed.2025.100679","DOIUrl":"10.1016/j.obmed.2025.100679","url":null,"abstract":"<div><div>The escalating prevalence of obesity among adolescents has emerged as a critical global public health challenge. Machine learning techniques have been used to predict obesity in adolescents. This study aimed to develop and validate a robust obesity prediction model for adolescents using this hybrid approach, leveraging data from a diverse cross-sectional population-based study. The hybrid method combines statistical inference with non-linear machine learning to enhance prediction accuracy. Physical fitness data were collected from the FITescola® tests. Multiple tests were employed to evaluate physical fitness. Multiple Poisson's multiple regression method was applied to identify the most predictive variables set of the adolescent's body mass index (BMI) classification. The model's goodness-of-fit statistics indicate a strong fit, with a log-likelihood of −8068.6 and a Pseudo R-squared value of 0.8853, where the aerobic fitness (AF), upper limb strength (ULS) and lower limb flexibility (LLF) presented an inverse association with the adolescent's BMI. In contrast the adolescent's core strength presented a positive association with their body mass. The random forest regression showed that an average of 35 repetition on the yo-yo test predicted a healthy BMI percentile [predBMIperc = 0.31]. In addition, the model presented good validity [MAE = 0.36, MSE = 0.20, RMSE = 0.45, R2 = 0.54]. The model's strong fit and accurate random forest regression's predictions suggest that physical fitness components, such as aerobic fitness, upper limb strength, lower limb power, and core strength, play a significant role in obesity risk among adolescents.</div></div>","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"59 ","pages":"Article 100679"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A randomized controlled trial comparing a very low-calorie low-fat ketogenic diet with a standard hypocaloric diet in adults with class I obesity","authors":"Francisco J. Nachon Garcia ,&nbsp;Gabriela E. Saldaña-Davila ,&nbsp;Magdalena Valencia ,&nbsp;Cesar Ochoa-Martínez","doi":"10.1016/j.obmed.2025.100642","DOIUrl":"10.1016/j.obmed.2025.100642","url":null,"abstract":"<div><h3>Background</h3><div>The global rise in obesity, driven by hypercaloric diets and sedentary lifestyles, has intensified interest in novel dietary interventions. Very low-calorie ketogenic diets (VLCKDs) induce rapid weight loss but are typically high in fat. This study assessed the efficacy and safety of a very low-calorie, low-fat, ketogenic diet (VLCLFKD), also known as the Zélé method, versus a standard low-calorie diet (LCD) in adults with class I obesity.</div></div><div><h3>Methods</h3><div>In this 12-week, randomized, double-blind controlled trial (NCT06275347), 88 participants were allocated to VLCLFKD (n = 56) or LCD (n = 32), with 77 completing the protocol. The primary endpoint was weight change; secondary outcomes included body composition, fasting glucose, lipid profile, blood pressure, hepatic and renal function, and acid–base balance. All participants received weekly clinical and dietary support.</div></div><div><h3>Results</h3><div>VLCLFKD led to significantly greater weight loss (−12.4 ± 2.8 kg) than LCD (−7.0 ± 1.9 kg; p &lt; 0.001). Fat mass reduction accounted for 82.1 % of total weight loss in the VLCLFKD group, compared to 38.4 % in the LCD group (p &lt; 0.001), with markedly lower lean mass loss (11.9 % vs. 51.0 %). Significant improvements were observed in fasting glucose (−12.8 mg/dL), total cholesterol (−37.4 mg/dL), triglycerides (−67.4 mg/dL), and blood pressure normalization (88.1 % vs. 71.4 %). Renal and hepatic function and acid–base balance remained stable. No serious adverse events occurred.</div></div><div><h3>Conclusion</h3><div>The VLCLFKD (Zélé method) is a safe, fat-targeted, and metabolically advantageous strategy for class I obesity, delivering superior weight and metabolic outcomes compared with a conventional LCD while preserving lean mass.</div></div>","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"58 ","pages":"Article 100642"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stratification of polycystic ovary syndrome by central adiposity phenotypes: Toward diagnostic precision","authors":"Sulagna Dutta ,&nbsp;Pallav Sengupta","doi":"10.1016/j.obmed.2025.100664","DOIUrl":"10.1016/j.obmed.2025.100664","url":null,"abstract":"<div><div>Polycystic ovary syndrome (PCOS) remains the most common endocrine disorder in reproductive-aged women, yet its diagnosis and classification are inconsistent. Conventional frameworks emphasize reproductive and androgenic features, while relying heavily on body mass index (BMI) as a proxy for adiposity. However, BMI fails to capture visceral fat distribution, which is a stronger determinant of insulin resistance, low-grade inflammation, and cardiovascular risk. Emerging evidence highlights waist-to-height ratio (WHtR) and waist circumference (WC) as superior markers of central adiposity and metabolic dysfunction in PCOS. Based on pooled data from recent studies, consolidated cut-offs for PCOS and insulin-resistant PCOS (PCOS-IR) were derived, allowing phenotype-based stratification according to adiposity patterns. These evidence-based thresholds distinguish the metabolic transition from general to insulin-resistant PCOS, providing practical reference points for clinical use. Based on these insights, we propose a hypothesis-based stratification of PCOS into three adiposity-driven phenotypes: lean PCOS with central adiposity, obese PCOS with predominant central adiposity, and obese PCOS with peripheral adiposity. This stratification framework integrates general and central adiposity measures to identify women at varying metabolic risk levels more accurately. Moving beyond BMI towards adiposity-driven classification is therefore a crucial step toward diagnostic precision in reproductive endocrinology.</div></div>","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"58 ","pages":"Article 100664"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leptin receptor polymorphisms: Unravelling the genetic modulators of metabolically healthy and unhealthy obesity","authors":"Isar Sharma ,&nbsp;Ritu Mahajan ,&nbsp;Nisha Kapoor","doi":"10.1016/j.obmed.2025.100660","DOIUrl":"10.1016/j.obmed.2025.100660","url":null,"abstract":"<div><div>Obesity, a widespread health concern, presents a clinical paradox: not everyone carrying excess weight develops the same metabolic complications. Some individuals remain metabolically healthy (MHO), while others progress to metabolically unhealthy obesity (MUO), facing severe risks like diabetes and heart disease. This critical review assesses the genetic underpinnings of this crucial distinction, focusing on the leptin receptor (LEPR), a key component in the regulation of our body's energy balance. Leptin, a hormone from fat cells, signals satiety through the LEPR. When genetic variations (polymorphisms) in LEPR disrupt this delicate signalling, it can lead to leptin resistance, a state contributing to weight gain and metabolic dysfunction. This review critically evaluates the evidence for how specific LEPR polymorphisms may influence the phenotypic divergence between MHO and MUO, highlighting the complex and population-specific nature of these associations. While variants like Q223R show inconsistent associations, others, such as K656N (rs8179183) and rs3790435, appear to directly contribute to the MUO phenotype by affecting fat distribution and inflammatory pathways. Understanding these genetic influences is paramount, as it shifts our view of obesity from a monolithic condition to a spectrum, revealing how individual genetic predispositions can dictate metabolic resilience or vulnerability. This work is crucial for developing more precise risk assessments and personalized interventions, ultimately paving the way for more effective strategies to promote metabolic health and mitigate the diverse impacts of obesity.</div></div>","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"58 ","pages":"Article 100660"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145417219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-world weight change pattern after glucagon-like peptide-1 receptor agonist discontinuation: A 1-year observational study","authors":"Mona Abdel-Bary ,&nbsp;Andrea Brody ,&nbsp;Jenna Schmitt ,&nbsp;Karen Prieto ,&nbsp;Amy Wetzel ,&nbsp;Yen-Yi Juo","doi":"10.1016/j.obmed.2025.100658","DOIUrl":"10.1016/j.obmed.2025.100658","url":null,"abstract":"<div><h3>Introduction</h3><div>Nearly half of Glucagon-Like Peptide-1 Receptor Agonists (GLP1RA) usage were discontinued within two years. We seek to investigate the reasons and consequences of unplanned GLP1RA discontinuation.</div></div><div><h3>Materials and methods</h3><div>This is a retrospective cohort study of adults who discontinued GLP1RA obesity treatment between 2022 and 2024.</div></div><div><h3>Results</h3><div>A total of 130 patients fitted our inclusion criteria. At the time GLP1RA was discontinued, the mean (Standard Deviation) total weight loss was −2.26 (8.20)%, ranging from −24.52 % to 11.79 %. Over the next twelve months, 85 patients (65.38 %) gained weight, with mean (SD) weight gain percentage at 1, 3, 6, and 12 months being −1.53 (2.33)%, 2.75 (4.19)%, 3.46 (7.38)%, and 24.44 (10.06)%. Of the 75 patients that had previously lost weight, 37 patients (49.33 %) had exceeded their original weight within a year. A significantly higher proportion of patients without T2DM gained weight than those with T2DM (70.75 % vs 41.67 %, p = .007). Besides diabetes, weight again appeared to occur with no association to demographic, socioeconomic and comorbidity factors.</div></div><div><h3>Conclusion</h3><div>Real-world weight gain following GLP1RA discontinuation was common, but neither as rapid nor as consistent as predicted by RCT literature. Developing transitional management strategy is crucial for optimizing these patient's weight outcomes.</div></div>","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"58 ","pages":"Article 100658"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145417220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence for obesity management: A review of applications, opportunities, and challenges","authors":"Jennifer Teke ,&nbsp;Maines Msiska ,&nbsp;Oluronke Abisoye Adanini ,&nbsp;Eghosasere Egbon ,&nbsp;Augustus Osborne ,&nbsp;David B. Olawade","doi":"10.1016/j.obmed.2025.100657","DOIUrl":"10.1016/j.obmed.2025.100657","url":null,"abstract":"<div><div>Traditional obesity management approaches, including dietary interventions, physical activity programmes, pharmacotherapy, and behavioural therapies, face significant limitations in scalability, personalisation, and long-term adherence rates. The emergence of artificial intelligence (AI) technologies, particularly machine learning and deep learning algorithms, has opened new frontiers for transforming obesity prevention, diagnosis, and management strategies. This comprehensive narrative review synthesises current evidence on AI applications in obesity management, examining technological innovations from predictive risk models to personalised digital therapeutics. The review explores AI-based diagnostic tools utilising computer vision for body composition analysis, predictive algorithms identifying high-risk individuals using electronic health records, personalised behavioural interventions powered by reinforcement learning, and remote monitoring systems integrating wearable technologies with intelligent data analytics. Furthermore, it investigates clinical effectiveness of AI-driven digital therapeutics platforms and examines AI integration within clinical decision support systems. The analysis reveals significant benefits including enhanced scalability for population-level interventions, improved personalisation through real-time data integration, increased precision in risk stratification, and potential cost-effectiveness through optimised resource allocation. However, substantial challenges remain, including data privacy and security concerns, algorithmic bias that may exacerbate health disparities, limited large-scale clinical validation, declining user engagement over time, and complex regulatory and ethical considerations. Addressing these challenges through multidisciplinary collaboration, robust validation studies, and ethical frameworks will be critical for successfully integrating AI technologies into routine obesity care and achieving equitable health outcomes across diverse populations.</div></div>","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"58 ","pages":"Article 100657"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Overweight/obesity and sedentary Behavior: Dual modifiable factors associated with Hypertension–diabetes comorbidity among adults in Haiphong, Vietnam","authors":"Thuc Huy Phan ,&nbsp;Kien Trung Dong ,&nbsp;Diem Thi Hong Nguyen ,&nbsp;Hong Thi Nguyen ,&nbsp;Khoa Xuan Tang ,&nbsp;Anh Hai Cao ,&nbsp;Linh Thuy Nguyen ,&nbsp;Tuyet Thi Hong Nguyen ,&nbsp;Duc Minh Cap","doi":"10.1016/j.obmed.2025.100649","DOIUrl":"10.1016/j.obmed.2025.100649","url":null,"abstract":"<div><h3>Aims</h3><div>Hypertension and diabetes are major global public health challenges. This study aimed to assess the prevalence of comorbid hypertension and diabetes and to identify associated factors among adults in Haiphong, Vietnam.</div></div><div><h3>Materials and methods</h3><div>A large-scale cross-sectional screening study involving 2100 adults was conducted. Participants were selected using multistage sampling from November to December 2023. Data were collected through face-to-face interviews, blood pressure measurements, and anthropometric assessments. Fasting plasma glucose levels were determined using venous blood samples. Univariable and multivariable logistic regression analyses were performed to identify factors associated with comorbid hypertension and diabetes.</div></div><div><h3>Results</h3><div>The prevalence of hypertension, diabetes, and their comorbidity was 21.8 %, 10.6 %, and 4.3 %, respectively. In the overall population, comorbidity was significantly associated with age 50–60 years (adjusted odds ratio [aOR], 5.03; 95 % confidence interval [CI], 1.53–16.60), male sex (aOR, 1.84; 95 % CI, 1.06–3.21), overweight/obesity (aOR, 1.98; 95 % CI, 1.17–3.36), and sedentary behavior ≥8 h/day (aOR, 2.37; 95 % CI, 1.26–4.46). Among males, significant factors included age 50–60, sedentary behavior, and high-risk alcohol use. Among females, comorbidity was associated with overweight/obesity and a family history of diabetes.</div></div><div><h3>Conclusion</h3><div>These findings underscore the need for gender-sensitive interventions to reduce the burden of hypertension–diabetes comorbidity in adults. For males, strategies should address sedentary lifestyles, alcohol-related risks, and age-related screening, while in females, efforts should focus on weight management and early identification of individuals with a family history of diabetes.</div></div>","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"58 ","pages":"Article 100649"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145057173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}