Obesity最新文献

{"title":"Does deciding not to participate in a lifestyle intervention for children with obesity affect the long-term weight change?","authors":"Rasmus M. Jørgensen,&nbsp;Jane N. Østergaard,&nbsp;Mette Fogh,&nbsp;Rachael W. Taylor,&nbsp;Henrik Støvring,&nbsp;Jens M. Bruun","doi":"10.1002/oby.24231","DOIUrl":"10.1002/oby.24231","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The objective of this study was to investigate whether long-term weight change in children with obesity is affected after deciding not to participate in a lifestyle intervention.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This observational study included 713 children (aged 5–8 years) with obesity living in Aarhus, Denmark, of whom 157 decided not to participate in a community-based lifestyle intervention between 2010 and 2020, and 556 were never invited to participate (i.e., no-intervention group). Height and weight measurements were combined with socioeconomic information from national registers. A mixed-effects model with splines was used to model changes in BMI <i>z</i> score and stratification to investigate effect modifications.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We observed a median follow-up of 3.6 years (quartile [Q]₁;Q₃: 0.4;5.1) for the decided-not-to-participate group. No difference was observed in annual change in BMI <i>z</i> score between the decided-not-to-participate and no-intervention groups (0.00 per year, 95% CI: −0.03 to 0.03; <i>p</i> = 0.90). No effect modifications were observed between the two groups concerning highest completed household education (<i>p</i> = 0.59), household income (<i>p</i> = 0.72), or immigration status (<i>p</i> = 0.17).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Children deciding not to participate in an intervention did not increase their weight compared with children who were never invited, indicating that treatment could be briefly postponed until families are able to participate. Additionally, socioeconomic status or immigration background did not modify the weight change.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 7","pages":"1334-1343"},"PeriodicalIF":4.2,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24231","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143470361","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":"Global cancer burden attributable to excess body weight, 1990 to 2021, decomposed by population size, aging, and epidemiological change","authors":"Xiaoru Feng,&nbsp;Ruoqian Li,&nbsp;Hang Yi,&nbsp;Shuyi Chen,&nbsp;Meng Liu,&nbsp;You Wu","doi":"10.1002/oby.24219","DOIUrl":"10.1002/oby.24219","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The objective of this study was to estimate cancer burden attributable to excess body weight (EBW) and identify its main source.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We obtained relative risks from meta-analyses, cancer and population data from the Global Burden of Disease Study (GBD) 2021, and BMI prevalence data from the NCD Risk Factor Collaboration (NCD-RisC). We calculated the incidence of 11 cancers attributable to high BMI from 1990 to 2021, analyzed trends using joinpoint regression, and assessed cohort effects with the age-period-cohort model. Decomposition analysis was conducted by cancer-specific risk factors and by population size, aging, and epidemiological changes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The incidence of 11 EBW-related cancers has increased from 1990 to 2021. Later-born cohorts and older age groups had higher cancer incidence rates. High BMI was the top contributor to changes in cancer burden (15.96% of all disability-adjusted life years [DALYs]), particularly in high Sociodemographic Index (SDI) regions. Colorectal, esophageal, and liver cancer had the highest burden due to high BMI (1,349,622; 1,284,385; and 944,616 DALYs, respectively). Epidemiological changes in BMI contributed to the rising DALY burden, ranging from 7.88% for postmenopausal breast cancer to 49.20% for liver cancer.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The rising prevalence of EBW contributed to the global cancer burden, showing a significant birth cohort effect. High BMI was the top contributing factor to obesity-related cancers, surpassing other epidemiological risk factors.</p>\u0000 \u0000 <div>\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":"33 3","pages":"567-577"},"PeriodicalIF":4.2,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143470363","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":"Time-restricted eating, caloric reduction, and unrestricted eating effects on weight and metabolism: a randomized trial","authors":"Niki Oldenburg,&nbsp;Douglas G. Mashek,&nbsp;Lisa Harnack,&nbsp;Qi Wang,&nbsp;Emily N. C. Manoogian,&nbsp;Nicholas Evanoff,&nbsp;Donald R. Dengel,&nbsp;Abdisa Taddese,&nbsp;Brad P. Yentzer,&nbsp;Lesia Lysne,&nbsp;Alison Wong,&nbsp;Michelle Hanson,&nbsp;Julie D. Anderson,&nbsp;Alison Alvear,&nbsp;Nicole LaPage,&nbsp;Justin Ryder,&nbsp;Krista Varady,&nbsp;Zan Gao,&nbsp;Suryeon Ryu,&nbsp;Patrick J. Bolan,&nbsp;Bryan Bergman,&nbsp;Erika Helgeson,&nbsp;Satchidananda Panda,&nbsp;Lisa S. Chow","doi":"10.1002/oby.24252","DOIUrl":"10.1002/oby.24252","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Metabolic improvements may precede weight loss. We compared the effects of self-selected 8-h time-restricted eating (TRE), 15% caloric restriction (CR), and unrestricted eating (UE) on weight, body composition, caloric intake, glycemic measures, and metabolic flexibility.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In this 12-week randomized-controlled trial, we measured weight (primary outcome), body composition (dual-energy x-ray absorptiometry/magnetic resonance imaging), caloric intake (24-h recall), metabolic flexibility (indirect calorimetry during hyperinsulinemic-euglycemic clamp), and glycemic measures (hemoglobin A1c, hyperinsulinemic-euglycemic clamp, continuous glucose monitoring).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of the 88 enrolled participants, 81 (92%) completed the trial (mean [SD], age, 43.2 [10.5] years, BMI, 36.2 [5.1] kg/m²; 54.5% female, 84.1% White). Final eating windows were 9.8 h (95% CI: 9.0 to 10.6) for TRE, 12.9 h (95% CI: 11.9 to 13.9) for CR, and 11.8 h (95% CI: 11.0 to 12.7) for UE. Compared with UE (<i>n</i> = 29), weight changes were −1.4 kg (95% CI: −4.5 to 1.7; <i>p</i> = 0.53) with TRE (<i>n</i> = 30) and −2.5 kg (95% CI: −5.8 to 0.8; <i>p</i> = 0.18) with CR (<i>n</i> = 29). TRE showed lower metabolic flexibility than CR (−0.041 [95% CI: −0.080 to −0.002]). Weight, body composition, caloric intake, and glycemic measures were similar among groups. Eating window reduction correlated with decreased caloric intake and visceral fat.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In a 12-week intervention, TRE did not lead to significant improvements in weight, average body composition, or glycemic or metabolic measures compared with CR or UE.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 4","pages":"671-684"},"PeriodicalIF":4.2,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24252","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143461080","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":"Associations between obesity class and ambulatory blood pressure curves in African American women","authors":"Raphiel J. Murden,&nbsp;Nicole D. Fields,&nbsp;Zachary T. Martin,&nbsp;Benjamin B. Risk,&nbsp;Alvaro Alonso,&nbsp;Amita Manatunga,&nbsp;Christy L. Erving,&nbsp;Reneé Moore,&nbsp;Shivika Udaipuria,&nbsp;Arshed Quyyumi,&nbsp;Viola Vaccarino,&nbsp;Tené T. Lewis","doi":"10.1002/oby.24230","DOIUrl":"10.1002/oby.24230","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Studies of body size and blood pressure (BP) in African American women typically focus on obesity overall or collapse obesity classes II and III into a single subgroup, ignoring potential heterogeneity in associations across categories. Moreover, ambulatory BP outcomes are primarily analyzed as mean daytime and/or nighttime BP, without examination of circadian changes during the day-to-night transition or the full 24-h cycle.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Functional data analysis methods were used to examine whether obesity categories modified ambulatory monitoring-assessed BP circadian rhythm in a cohort of 407 African American women.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Age-adjusted systolic BP (SBP) was 4 mm Hg (95% CI: 0.4–8.4) higher among women with class I or II obesity than those with normal weight or overweight from 12:30 p.m. through 8:00 a.m. Age-adjusted differences in SBP among women with class III obesity versus those with normal weight or overweight were 6 mm Hg (95% CI: 0.7–10.8) during daytime hours and increased to 11 mm Hg (95% CI: 5.8–16.0) overnight. Compared with all other BMI categories, SBP of women with class III obesity declined more slowly from day to night.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Circadian BP among African American women was distinct among those with class III obesity compared with those with other body weight categories, suggesting that intervention efforts in African American women should target this group.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 3","pages":"589-598"},"PeriodicalIF":4.2,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24230","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143461079","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":"Adherence to self-monitoring and behavioral goals is associated with improved weight loss in an mHealth randomized-controlled trial","authors":"Lora E. Burke,&nbsp;Zhadyra Bizhanova,&nbsp;Molly B. Conroy,&nbsp;Jessica Cheng,&nbsp;Britney Beatrice,&nbsp;Jacob K. Kariuki,&nbsp;Bambang Parmanto,&nbsp;Susan M. Sereika","doi":"10.1002/oby.24234","DOIUrl":"10.1002/oby.24234","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The SMARTER mobile health (mHealth) weight-loss trial compared adherence to self-monitoring (SM) of diet, physical activity (PA), and weight and adherence to study-prescribed diet and PA goals between SM + feedback (SM + FB) and SM-only arms over 12 months.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Participants used digital tools to monitor their dietary intake, PA, and weight. We applied generalized linear mixed modeling to compare patterns of monthly adherence to SM and behavioral goals between groups over time and examine the association of adherence to SM and behavioral goals with ≥5% weight loss.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The sample (<i>N</i> = 502) was 80% female and 82% White, with a mean (SD) BMI of 33.7 (4.0) kg/m². Adherence to SM and fat, calorie, and PA goals declined nonlinearly over time, with the SM + FB group displaying less of a decline compared with the SM-only group. Higher adherence to diet, PA, and weight SM and to calorie and PA goals was associated with greater odds of achieving ≥5% weight loss. A higher monthly probability of achieving ≥5% weight loss was associated with greater adherence to diet, PA, and weight SM and to calorie and PA goals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These results suggest that future research should examine the mechanisms underlying tailored FB to improve the effect of FB intervention strategies that can lead to improved weight loss.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 3","pages":"478-489"},"PeriodicalIF":4.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24234","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443136","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":"Trends in educational inequalities in obesity-attributable mortality in England and Wales, Finland, and Italy","authors":"Fanny Janssen,&nbsp;Rolando Gonzales Martinez,&nbsp;Nicolás Zengarini,&nbsp;Pekka Martikainen,&nbsp;Anton Kunst","doi":"10.1002/oby.24225","DOIUrl":"10.1002/oby.24225","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>We assessed trends in educational inequalities in obesity-attributable mortality (OAM) and their contribution to educational inequalities in all-cause mortality for people aged 30 years and older, in England and Wales (1991–2017), Finland (1978–2017), and Italy (1990–2018).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In our population-level study, we estimated the shares of all-cause mortality due to OAM by educational level (i.e., low, middle, and high) by applying the population-attributable fraction formula to harmonized obesity prevalence data by educational level, along with sex- and age-specific relative risks of dying from obesity. We obtained OAM rates by multiplying the shares with individually linked all-cause mortality data by educational level. We measured absolute inequalities in OAM and all-cause mortality by the slope index of inequality.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>OAM largely increased for the different sex- and education-specific populations and increased most strongly for those with low educational level up to 2010 to 2015. Educational inequalities in OAM initially increased but stabilized or declined from at least 2008 onward. Obesity contributed, on average, 15% to absolute educational inequalities in all-cause mortality in 1991 through 2017.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The mortality impact of the obesity epidemic by educational level changed over time. Although the observed change from increasing to declining or stable educational inequalities is encouraging, reducing OAM in all socioeconomic groups remains a challenge.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 3","pages":"578-588"},"PeriodicalIF":4.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24225","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443137","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":"Loss of VSTM2A promotes adipocyte hypertrophy and disrupts metabolic homeostasis","authors":"Manal Al Dow,&nbsp;Blandine Secco,&nbsp;Mathilde Mouchiroud,&nbsp;Marianne Rochette,&nbsp;Gustavo R. Gilio,&nbsp;Mickael Massicard,&nbsp;Marilou Hardy,&nbsp;Yves Gélinas,&nbsp;William T. Festuccia,&nbsp;Mathieu C. Morissette,&nbsp;Venkata S. K. Manem,&nbsp;Mathieu Laplante","doi":"10.1002/oby.24224","DOIUrl":"10.1002/oby.24224","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Adipose tissue expands through hyperplasia and hypertrophy to store excess lipids, a process that is essential for the maintenance of metabolic homeostasis. The mechanisms regulating adipocyte recruitment from progenitors remain unclear. We have previously identified V-set and transmembrane domain-containing protein 2A (VSTM2A) as a factor promoting fat cell development in vitro. Whether VSTM2A impacts adipose tissue and systemic metabolism in vivo is still unknown.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We generated VSTM2A knockout mice (<i>Vstm2a</i>^{<i>−/−</i>}) using clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) and fed them either a chow or high-fat diet. These mice were evaluated for body weight, adiposity, blood parameters, and glucose homeostasis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p><i>Vstm2a</i>^{<i>−/−</i>} mice were viable and showed no body weight differences. Although adipose mass was similar, <i>Vstm2a</i>^{<i>−/−</i>} mice had larger adipocytes, an effect linked to inflammation, ectopic lipid deposition, and impaired glucose and lipid metabolism. Transcriptomic analysis revealed that VSTM2A loss affects the expression of several genes in adipose tissue, including some related to the lysosome. Interestingly, acute lysosomal inhibition early in life is sufficient to cause adipocyte hypertrophy in adults.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>VSTM2A is dispensable for adipose tissue formation, but its loss causes adipocyte hypertrophy and impairs glucose and lipid homeostasis. Our study also underscores a critical role of the lysosome in initiating adipogenesis.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 3","pages":"522-536"},"PeriodicalIF":4.2,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24224","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143434635","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":"Pretreatment predictors of weight loss in a 12-month behavioral obesity treatment: a signal detection analysis of DIETFITS","authors":"Michele L. Patel,&nbsp;Matthew J. Landry,&nbsp;Astrid N. Zamora,&nbsp;Priya Fielding-Singh,&nbsp;Abby C. King,&nbsp;Christopher D. Gardner","doi":"10.1002/oby.24226","DOIUrl":"10.1002/oby.24226","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The objective of this study was to identify pretreatment predictors of weight loss in a 12-month behavioral obesity treatment that restricted either fat or carbohydrates.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Participants were 436 adults with overweight or obesity from the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) trial. Signal detection analysis was used to identify which combinations of 51 pretreatment demographic, clinical, behavioral, and psychosocial variables, along with diet type (healthy low-fat vs. healthy low-carbohydrate), formed subgroups that varied in proportion of those achieving at least 5% weight loss at 12 months.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Overall, 51% of participants achieved at least 5% weight loss at 12 months, with eight subgroups identified through signal detection. Diet type was not a key factor. Among racial and ethnic minority participants, the best predictors of weight loss were lower levels of emotional eating, less friend discouragement, and presence of metabolic syndrome. Among non-Hispanic White participants, the best predictors were high confidence in participating fully in the intervention, more family encouragement, and lower outcome expectations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We found that psychosocial and clinical factors, along with race and ethnicity, successfully differentiated subgroups that varied in their 12-month weight loss. Given the heterogeneity in response to behavioral obesity treatment, these results can help generate hypotheses to move intervention science toward a precision medicine approach by matching individuals to their most suitable obesity treatments.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 3","pages":"463-477"},"PeriodicalIF":4.2,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24226","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143416395","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":"Metabolically unhealthy adipose tissue is characterized by reductions in mitochondrial size and function","authors":"Darla DeStephanis,&nbsp;Masha R. Long,&nbsp;Abigail G. Williams,&nbsp;McKinley Santiago,&nbsp;Jack Tonkin,&nbsp;Christina M. Stevens,&nbsp;Matthew A. Davis,&nbsp;Alistaire D. Ruggiero,&nbsp;Darren C. Henstridge,&nbsp;Dino Premilovac,&nbsp;Kylie Kavanagh","doi":"10.1002/oby.24221","DOIUrl":"10.1002/oby.24221","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Adipose function, not mass, underpins metabolic health. Lean and obese nonhuman primates (NHPs) naturally develop metabolic syndrome. Mitochondria-related measures in subcutaneous adipose tissue (SQ AT) and peripheral blood mononuclear cells may elucidate differences that transcend adiposity measures.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Obesity statuses ranged from very lean to severely obese (&lt;9%–&gt;50%, <i>n</i> = 44), which were equivalent in healthy or unhealthy NHPs (metabolic syndrome score difference, <i>p</i> &lt; 0.001). We evaluated SQ AT histology, electron microscopy, tissue proteins, and bioenergetics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Unhealthy adipocytes had mitochondria one-half the size of healthy adipocytes (<i>p</i> &lt; 0.01), whereas adipocyte cell sizes were comparable. Consistent with small mitochondria, we saw deficiencies in mitochondrial fusion and quality-control proteins in SQ AT from unhealthy NHPs (all <i>p</i> &lt; 0.05). Smaller mitochondria in unhealthy adipocytes were consistent with low SQ AT tissue respiration (<i>p</i> &lt; 0.05). Mitochondrial size was specifically reduced with unhealthiness, as mitochondrial abundance, size, and related metrics were unrelated to adiposity. Isolated stromal vascular cells showed comparable respirometry profiles, substantiating specificity of adipocyte-related mitochondrial defects. Peripheral blood mononuclear cell bioenergetic indices were increased in unhealthy NHPs, indicative of immune cell activation, and correlated to SQ AT inflammatory cytokines.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We conclude that targeting mitochondrial fusion processes would be a rational strategy to improve metabolic health, independent of total fat mass.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 3","pages":"537-547"},"PeriodicalIF":4.2,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24221","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143416112","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":"Mitigating muscle loss during weight loss: can nutritional ketosis make a difference? A call for more research","authors":"Shaminie J. Athinarayanan,&nbsp;Jeff S. Volek","doi":"10.1002/oby.24235","DOIUrl":"10.1002/oby.24235","url":null,"abstract":"<p>Weight loss (WL) has an important role in managing obesity and type 2 diabetes, but preserving lean body mass (LBM) during WL is essential for maintaining muscle function and metabolic health. Significant WL with incretin mimetic-based therapies, similar to bariatric surgery, raises concerns regarding disproportionate LBM loss, which may lead to physical frailty. Recent analyses have suggested that high adherence to a ketogenic diet may mitigate LBM loss while improving physical function, even with substantial WL. However, more research is needed to understand the mechanisms behind LBM preservation in nutritional ketosis and the role of other lifestyle interventions. Future studies of pharmacological, surgical, and lifestyle-driven WL interventions should also assess LBM, physical function, and frailty. Research in this area is essential for developing strategies that optimize patient outcomes, especially for those who are considering their options for the treatment of obesity.</p>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 3","pages":"431-434"},"PeriodicalIF":4.2,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24235","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143416389","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}