Obesity最新文献

{"title":"Weight Loss Before Basic Combat Training and Musculoskeletal Injuries Among U.S. Army Trainees: The ARMI Study","authors":"Vy T. Nguyen,&nbsp;Ashley A. Donovan,&nbsp;Kathryn M. Taylor,&nbsp;Katelyn Guerriere Aaron,&nbsp;Leila A. Walker,&nbsp;Vincent P. Pecorelli,&nbsp;David J. Zeppetelli,&nbsp;Colleen M. Castellani,&nbsp;Susan P. Proctor,&nbsp;Julie M. Hughes,&nbsp;Stephen A. Foulis","doi":"10.1002/oby.24364","DOIUrl":"10.1002/oby.24364","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To investigate the association between weight loss before joining the U.S. Army and rates of musculoskeletal injury (MSKI) during physically demanding Basic Combat Training (BCT).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Self-reported weight loss was collected on 3168 Army trainees who were followed through electronic medical records for diagnosis of any and region-specific MSKI. Cox regression models were stratified by sex and COVID-19 pandemic and adjusted for age, height, maximum-ever BMI, race/ethnicity, smoking history, prior physical activity, and history of injury.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 829 trainees (26.16%) reported losing weight to enter the Army with mean (SD) weight loss of 9.06 (8.62) kg, most commonly through exercise (83.72%). Trainees who lost weight to enter the Army had lower rates of any (HR: 0.86; 95% CI: 0.74, 0.99) and lower extremity (HR: 0.84; 95% CI: 0.72, 0.98) MSKI during BCT compared to trainees who did not lose weight. Rate of weight loss (mean [SD]: 1.27 [1.06] kg/week) was not associated with any or region-specific MSKI.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Results indicate that losing excess weight before military training may minimize injuries during training and the relatively gradual rate of weight loss in these trainees did not pose a higher risk of injury.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 10","pages":"1977-1983"},"PeriodicalIF":4.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24364","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144755528","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":"BMI, Sleep Architecture, and Glucose Metabolism: Insights From the Baependi Heart Study","authors":"Carolina Mendes Pessoa,&nbsp;Tâmara P. Taporoski,&nbsp;Felipe Beijamini,&nbsp;Shaina J. Alexandria,&nbsp;Jose E. Krieger,&nbsp;Malcolm von Schantz,&nbsp;Alexandre C. Pereira,&nbsp;Kristen L. Knutson","doi":"10.1002/oby.24359","DOIUrl":"10.1002/oby.24359","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To examine whether (1) sleep architecture is associated with BMI groups in the absence of sleep apnea and (2) BMI group modified associations between sleep architecture and markers of glucose metabolism.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The Baependi Heart Study (BHS) is a family-based observational study of adults that assessed sleep using at-home polysomnography (PSG) and collected anthropometric and fasting blood measures. BMI was classified into: 18.5 to &lt; 25, 25 to &lt; 30, and ≥ 30 kg/m². People with moderate–severe sleep apnea and taking diabetes-related medication were excluded. Cross-sectional associations were examined (<i>n</i> = 1014).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Individuals with BMI ≥ 30 kg/m² had less REM sleep (−7.8 min, <i>p</i> = 0.003) and the groups with BMI 25 to &lt; 30 kg/m² and ≥ 30 kg/m² had higher apnea-hypopnea index than individuals with BMI 18.5 to &lt; 25 kg/m² (by 0.8 and 1.4 events per hour, respectively, <i>p</i> &lt; =0.002). Wake after sleep onset (WASO) was associated with higher fasting glucose levels in participants with BMI ≥ 30 kg/m² only; 10 min more WASO was associated with ~1% higher fasting glucose (<i>p</i> = 0.002).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>After exclusion of participants with moderate–severe sleep apnea, there was no difference in non-REM sleep and only a small difference in REM sleep between BMI groups, suggesting that BMI does not substantially impair sleep unless sleep apnea is present.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 10","pages":"1849-1854"},"PeriodicalIF":4.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12404664/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144984504","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":"Cardiovascular Indexes and Oxidative Balance in Advanced Cardiovascular–Kidney–Metabolic Syndrome","authors":"Zhaoqi Yan,&nbsp;Xiangyi Pu,&nbsp;Xing Chang,&nbsp;Ruxiu Liu","doi":"10.1002/oby.24356","DOIUrl":"10.1002/oby.24356","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The cardiovascular–kidney–metabolic (CKM) syndrome lacks clear strategies for risk reduction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study utilized data from NHANES focusing on adults with CKM. Participants were categorized into early and advanced CKM. A multivariable logistic regression model evaluated the relationship between oxidative balance score (OBS) levels—total, dietary, and lifestyle—and advanced CKM. The mediating effects of cardiovascular indexes, atherogenic index of plasma (AIP), and cardiac metabolic index (CMI) were also analyzed. The SHapley Additive exPlanations (SHAP) in machine learning interpret the importance of indexes' components.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Higher OBS levels were significantly associated with a lower risk of advanced CKM. Specifically, a total OBS ≥ 28 correlated with a 36% reduced risk compared to scores ≤ 16. AIP and CMI were linked to increased advanced CKM risk at levels &gt; 0.56 and &gt; 0.57, respectively. Mediation analysis showed AIP and CMI potentially mediated 0.68% and 4.08% of the OBS-advanced CKM risk association. SHAP highlighted the importance of carotene and niacin.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study is the first to identify an inverse association between higher OBS and advanced CKM risk, with cardiovascular indexes emerging as potential mediators, which lay the groundwork for future longitudinal and interventional studies to elucidate potential causal pathways.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 9","pages":"1791-1801"},"PeriodicalIF":4.7,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144746674","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":"Family Considerations in the Treatment of Adult Obesity With Antiobesity Medications","authors":"Keeley J. Pratt,&nbsp;David B. Sarwer,&nbsp;Joseph A. Skelton","doi":"10.1002/oby.24355","DOIUrl":"10.1002/oby.24355","url":null,"abstract":"<p>Adult weight management guidelines recommend offering antiobesity medications (AOMs) as an adjunct to lifestyle modification approaches. Consequently, prescriptions for AOMs are at an unprecedented high, with some estimates suggesting that one in eight US adults report ever taking an AOM. AOMs induce clinically meaningful weight loss for many; concerns about accessibility, cost, long-term efficacy and safety, and changes in eating behavior and psychosocial functioning remain unanswered. A question that has not been asked pertains to the family system. Family members' acceptability and perception of AOMs may dictate adherence, and established family and household routines and dynamics may influence individual behavior change during or after AOM use. This Perspective considers aspects of the family context with health behavior change and weight loss. The paper concludes with suggestions for future research to explore positive ripple effects and unintended consequences that AOMs could have on individual family members and family dynamics.</p>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 9","pages":"1619-1621"},"PeriodicalIF":4.7,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24355","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144736373","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":"Early-Onset Obesity and Tirzepatide Treatment: A Post Hoc Analysis of the SURMOUNT Clinical Trials","authors":"Evgenia Gourgari,&nbsp;Gitanjali Srivastava,&nbsp;Aaron S. Kelly,&nbsp;Donna Mojdami,&nbsp;Dachuang Cao,&nbsp;Madhumita A. Murphy,&nbsp;Chrisanthi A. Karanikas,&nbsp;Clare J. Lee","doi":"10.1002/oby.24348","DOIUrl":"10.1002/oby.24348","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>People with early-onset obesity (diagnosed at age &lt; 25 years) may present with more cardiometabolic abnormalities and obesity-related complications. This post hoc analysis assessed baseline characteristics and body weight (BW) changes with tirzepatide in people with early- versus later-onset obesity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Participants (<i>N</i> = 3782) from SURMOUNT-1, SURMOUNT-3, and SURMOUNT-4 randomized to tirzepatide or placebo were included. Baseline characteristics and changes in BW and cardiometabolic risk factors at 72/88 weeks were assessed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In SURMOUNT-1, participants with early- versus later-onset obesity had longer mean obesity duration (20 ± 12 vs. 11 ± 8 years), higher BMI (40 ± 7 vs. 37 ± 6 kg/m²) and waist circumference (WC, 118 ± 16 vs. 112 ± 14 cm), and lower HbA1c (5.48% ± 0.4% vs. 5.60% ± 0.4%), triglycerides (median 120 vs. 130 mg/dL), and systolic blood pressure (SBP; 121 ± 13 vs. 125 ± 13 mmHg) at baseline (all <i>p</i> ≤ 0.004). At 72 weeks, improvements with tirzepatide in BW (−23% vs. −22%), WC (−22 vs. −19 cm), HbA1c (−0.51% vs. −0.52%), triglycerides (−32% vs. −31%), and SBP (−8 vs. −8 mmHg) were similar between subgroups. Similar improvements were observed in SURMOUNT-3 and SURMOUNT-4.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In this post hoc analysis, participants with early- versus later-onset obesity exhibited a mixed profile of metabolic health at baseline, including a higher degree of central adiposity and lower HbA1c and SBP. Improvements in BW and cardiometabolic markers with tirzepatide were similar between subgroups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Trial Registration</h3>\u0000 \u0000 <p>\u0000 ClinicalTrials.gov identifiers: NCT04184622, NCT04657016, NCT04660643</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":"33 9","pages":"1668-1679"},"PeriodicalIF":4.7,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24348","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144736372","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":"Investigating shared genetic architecture between major depressive disorder and central obesity","authors":"Ya Zhan,&nbsp;Na Zhao,&nbsp;Qi-Gang Zhao,&nbsp;Cheng-Xi Wu,&nbsp;Shan-Juan Yuan,&nbsp;Xiu-Juan Yu,&nbsp;Xiao Zheng,&nbsp;Chao-Jie Liu,&nbsp;Rong Hai,&nbsp;Zheng-Qing Liu,&nbsp;Yu-Fang Pei","doi":"10.1002/oby.24333","DOIUrl":"10.1002/oby.24333","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study investigated the shared genetic architecture between major depressive disorder (MDD) and waist-hip ratio (WHR) to provide insights into the biological mechanisms underlying their comorbidity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using large-scale genome-wide association study summary statistics, we performed cross-trait genetic correlation and pleiotropic variant discovery analyses and bidirectional Mendelian randomization analysis, as well as drug target prioritization analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified significant genetic correlation between MDD and WHR (<i>r</i>\u0000 _g = 0.11, <i>p</i> = 4.18 × 10⁻⁵). Cross-trait analysis identified 26 pleiotropic loci, including a novel variant (rs2855812, intronic to <i>MICB</i>). Colocalization analysis confirmed six pleiotropic loci. Forward Mendelian randomization analysis demonstrated MDD is associated with increased WHR (<i>β</i> = 0.079, 95% CI: 0.014–0.143; <i>p</i> = 0.017), with no reverse causation. Drug prioritization identified agents able to be repurposed targeting <i>MICB</i>, <i>PSORS1C1</i>, and <i>C6orf15</i>. Enrichment analyses highlighted immune pathways.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our findings establish pleiotropy between MDD and WHR, implicating dysregulated immunometabolic pathways as shared mechanisms. Prioritized drug targets represent translatable opportunities for comorbidity management.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 9","pages":"1745-1755"},"PeriodicalIF":4.7,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144736374","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 Impact of Eating Behaviors on Ultraprocessed Food Consumption Over 12 Months in Children","authors":"Dabin Yeum,&nbsp;Shuxian Hua,&nbsp;Gita Thapaliya,&nbsp;Sarah Ann Duck,&nbsp;Susan J. Melhorn,&nbsp;Christian L. Roth,&nbsp;Ellen A. Schur,&nbsp;Susan Carnell,&nbsp;Leticia E. Sewaybricker","doi":"10.1002/oby.24361","DOIUrl":"10.1002/oby.24361","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Ultraprocessed foods (UPF) are often energy-dense and nutrient-poor, and excess consumption can increase the risk of child obesity. Eating behaviors in childhood may influence future dietary patterns. This study examined the relationships of baseline eating behaviors with baseline UPF intake and 12-month changes in UPF intake in children.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Children aged 9–11 years were recruited (<i>N</i> = 101; 53% female). Parents reported on children's eating behaviors via the Child Eating Behavior Questionnaire (CEBQ). Children's dietary intake was captured with three automated dietary recalls. Daily average kilocalories of unprocessed/minimally processed foods (MPF) and UPF were extracted using the NOVA Food Classification System to calculate a UPF/MPF ratio.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Mean age and BMI <i>z</i>-score were 10.5 years (SD 0.88) and 0.97 (SD 1.07), respectively. Linear regressions controlling for sex and pubertal stage found that CEBQ-food fussiness was associated with a higher UPF/MPF intake ratio (<i>p</i> = 0.02) at baseline and an increase in UPF/MPF intake ratio (<i>p</i> = 0.04) over 1 year. CEBQ-enjoyment of food was associated with a decrease in UPF/MPF intake ratio (<i>p</i> = 0.03) over 1 year.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Child eating behaviors predict changes in UPF intake over 1 year. These results advocate for longitudinal research to examine dynamic relationships between eating behaviors, UPF intake, and body weight.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 9","pages":"1704-1712"},"PeriodicalIF":4.7,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144736375","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":"Placental Gene Expression Associated With Early Childhood Growth Trajectories and Obesity Risk","authors":"Hyo Young Choi,&nbsp;Luhang Han,&nbsp;Alison G. Paquette,&nbsp;James MacDonald,&nbsp;Theo Bammler,&nbsp;Christine Loftus,&nbsp;Daniel A. Enquobahrie,&nbsp;Kaja Z. LeWinn,&nbsp;Nicole R. Bush,&nbsp;Catherine J. Karr,&nbsp;Sheela Sathyanarayana,&nbsp;Qi Zhao","doi":"10.1002/oby.70000","DOIUrl":"10.1002/oby.70000","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study aimed to investigate the association of placental gene expression with early childhood growth trajectories and obesity risk.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We analyzed 794 children from the Conditions Affecting Neurocognitive Development and Learning in Early Childhood study. Placental samples collected at delivery underwent RNA sequencing to obtain transcriptome data. BMI trajectories from birth to 4 years (rising-high-, moderate-, and low-BMI) and overweight/obesity at 4 years were the childhood outcomes of interest. Differentially expressed genes (DEGs) associated with the outcomes were identified using DESeq2. Pathway enrichment analysis was performed on DEGs. Their causal relationships with outcomes were explored using the Mendelian randomization (MR) approach.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified 22 and 23 DEGs associated with BMI trajectories and overweight/obesity, respectively, with false discovery rates (FDR) &lt; 0.05. Pathway analysis of these DEGs identified 26 biological pathways, primarily related to the immune system. MR analysis suggested that one (<i>SSX2B</i>) and eight DEGs (e.g., <i>HSPA1A</i>, <i>DNAJB1</i>) might be causally associated with the BMI trajectories and overweight/obesity (FDR &lt; 0.05), respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study identified placental gene expression associated with early childhood growth outcomes. These findings suggest the potential important role of placental immune system genes in the development of childhood obesity.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 9","pages":"1713-1724"},"PeriodicalIF":4.7,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144710415","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":"Effect of unprocessed red meat on obesity and related factors: A systematic review and meta-analysis","authors":"Md Akheruzzaman,&nbsp;Marleigh Hefner,&nbsp;Daniel Baller,&nbsp;Shane Clark,&nbsp;Zahra Feizy,&nbsp;Diana M. Thomas,&nbsp;Nikhil V. Dhurandhar","doi":"10.1002/oby.24322","DOIUrl":"10.1002/oby.24322","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The objective of this study was to conduct a systematic review and meta-analysis of intervention trials that have determined the effect of unprocessed red meat (URM) intake on obesity-related outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The populations, interventions, controls, and outcomes (PICO) framework was used to create questions to search seven databases from July 29, 2020, to August 21, 2020. Two reviewers independently screened 5630 references. English-language intervention trials in adults testing the effect of URM on obesity-related outcomes were included. Twenty-four studies met selection criteria. A random-effects model was developed to calculate pooled effect sizes. The DerSimonian-Laird estimator was used to estimate the variance of the true effect sizes. An interactive dashboard was published to provide transparent analysis and data presentation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We found no significant effect of URM for BMI, body weight, or percent body fat based on unfiltered pooled effect sizes. Filtered pooled effect size analysis showed a slight adverse effect of URM for total cholesterol and low-density lipoprotein cholesterol.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Studies did not show an effect of URM on weight gain, obesity, or related metabolic conditions. This may help clinicians when considering the use of URM for patients. Longer studies may be needed for observing obesity development in case the effect of URM on weight gain is small and needs a much longer time to express.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 9","pages":"1627-1636"},"PeriodicalIF":4.7,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24322","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144710414","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":"Timing Matters: Early Eating Mitigates Genetic Susceptibility for Obesity","authors":"Divya Joshi,&nbsp;Marie Pigeyre","doi":"10.1002/oby.24350","DOIUrl":"10.1002/oby.24350","url":null,"abstract":"&lt;p&gt;Obesity is a multifactorial and highly heritable condition, influenced by the interplay between genetic predisposition and modifiable lifestyle behaviors. While the contribution of diet composition and physical activity to energy balance is well established, growing evidence highlights the role of circadian rhythms, particularly meal timing, in regulating metabolic health [&lt;span&gt;(1)&lt;/span&gt;]. Disruptions in the synchrony between endogenous biological rhythms and external behavioral cues, such as the timing of food intake, have been associated with increased risk of obesity, insulin resistance, and related cardiometabolic disorders. However, the mechanisms and the extent to which timing of meal intake interacts with genetic susceptibility to influence obesity-related outcomes remain not fully clear.&lt;/p&gt;&lt;p&gt;In this issue of &lt;i&gt;Obesity&lt;/i&gt;, a study by Rocío De la Peña-Armada et al. [&lt;span&gt;(2)&lt;/span&gt;], conducted in the Obesity, Nutrigenetics, Timing, and Mediterranean (ONTIME) cohort, addresses this gap by examining the independent and interactive effects of meal timing and polygenic risk for body mass index (BMI) on weight-related outcomes. The authors included 1195 adults with overweight or obesity who were participating in a standardized, multimodal weight loss intervention in Spain. The intervention comprised dietary counseling, physical activity, and behavioral therapy but notably did not advise on meal timing, thereby allowing for natural variation in chrononutritional behavior.&lt;/p&gt;&lt;p&gt;Meal timing was assessed via self-reported usual times for breakfast and dinner, from which the midpoint of food intake was calculated and used as a marker of chrononutritional behavior [&lt;span&gt;(2)&lt;/span&gt;]. Participants were classified as early or late eaters based on the tertiles of this midpoint. Genetic predisposition to obesity was quantified using a genome-wide polygenic score for BMI (PGS-BMI), generated through the polygenic scores of continuous shrinkage (PGS-CS) method, which modeled the effects of ~900,000 single-nucleotide polymorphisms (SNPs) using a Bayesian framework [&lt;span&gt;(3)&lt;/span&gt;]. This approach offers improved prediction of complex traits over traditional polygenic risk scoring methods by accounting for the continuous shrinkage of SNP effects and linkage disequilibrium.&lt;/p&gt;&lt;p&gt;The study reports robust and clinically relevant findings [&lt;span&gt;(2)&lt;/span&gt;]. Later meal timing was independently associated with higher baseline BMI, slower weight loss during intervention, and poorer long-term weight maintenance. Specifically, each 1-h delay in meal intake midpoint was associated with nearly a 1-kg/m&lt;sup&gt;2&lt;/sup&gt; increase in BMI, a slower weight loss rate of 0.05 kg/week, and a 3% increase in weight regained after an average of 12 years. These associations persisted even after adjusting for potential confounders, such as total energy intake, macronutrient distribution, sleep duration, physical activity, and educational level. Notably, the authors observed","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 8","pages":"1414-1415"},"PeriodicalIF":4.2,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24350","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144710416","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}