Janaki M. Nair, Ganesh Chauhan, Gauri Prasad, Khushdeep Bandesh, Anil K. Giri, Shraddha Chakraborty, Raman K. Marwaha, Sandeep Mathur, Devapriya Choudhury, Nikhil Tandon, Analabha Basu, Dwaipayan Bharadwaj
Objective
Childhood obesity (OB) is influenced by complex gene–environmental interaction. While genetics of adult OB have been extensively studied, polygenic childhood OB in non-European populations is still underexplored. Furthermore, in a developing nation such as India, how the environmental component strongly modulated by the socioeconomic status (SES) shapes the genetic susceptibility is crucial to understand.
Methods
A two-staged genome-wide association study (GWAS; N = 5673) and an independent exome-wide association study (ExWAS; N = 4963) were performed using a generalized linear model assuming additive effect to identify the common and rare genetic variants respectively associated with childhood OB. Rare-variant burden testing was also performed. We used the gene expression profiles and regulatory data from public databases to explain the novel associations. The implications of SES as a potential modifier of genetic susceptibility were evaluated.
Results
GWAS identified novel associations in TCF7L2, IMMP2L, IPMK, CDC5L, SNTG1, and MX1, whereas ExWAS uncovered CNTN4, COQ4, TNFRSF10D, FLG-AS1, and BMP3. Both GWAS and ExWAS validated known associations in FTO and MC4R. Furthermore, rare-variant testing highlighted the role of 101 genes. We also observed that SES can modulate the inherent susceptibility to OB.
Conclusions
Our study identified genetic variants associated with childhood OB and highlighted the gene–environmental interaction in childhood OB.
{"title":"Mapping the landscape of childhood obesity: genomic insights and socioeconomic status in Indian school-going children","authors":"Janaki M. Nair, Ganesh Chauhan, Gauri Prasad, Khushdeep Bandesh, Anil K. Giri, Shraddha Chakraborty, Raman K. Marwaha, Sandeep Mathur, Devapriya Choudhury, Nikhil Tandon, Analabha Basu, Dwaipayan Bharadwaj","doi":"10.1002/oby.24248","DOIUrl":"10.1002/oby.24248","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Childhood obesity (OB) is influenced by complex gene–environmental interaction. While genetics of adult OB have been extensively studied, polygenic childhood OB in non-European populations is still underexplored. Furthermore, in a developing nation such as India, how the environmental component strongly modulated by the socioeconomic status (SES) shapes the genetic susceptibility is crucial to understand.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A two-staged genome-wide association study (GWAS; <i>N</i> = 5673) and an independent exome-wide association study (ExWAS; <i>N</i> = 4963) were performed using a generalized linear model assuming additive effect to identify the common and rare genetic variants respectively associated with childhood OB. Rare-variant burden testing was also performed. We used the gene expression profiles and regulatory data from public databases to explain the novel associations. The implications of SES as a potential modifier of genetic susceptibility were evaluated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>GWAS identified novel associations in <i>TCF7L2</i>, <i>IMMP2L</i>, <i>IPMK</i>, <i>CDC5L</i>, <i>SNTG1</i>, and <i>MX1</i>, whereas ExWAS uncovered <i>CNTN4</i>, <i>COQ4</i>, <i>TNFRSF10D</i>, <i>FLG-AS1</i>, and <i>BMP3</i>. Both GWAS and ExWAS validated known associations in <i>FTO</i> and <i>MC4R</i>. Furthermore, rare-variant testing highlighted the role of 101 genes. We also observed that SES can modulate the inherent susceptibility to OB.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our study identified genetic variants associated with childhood OB and highlighted the gene–environmental interaction in childhood OB.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 4","pages":"754-765"},"PeriodicalIF":4.2,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143506716","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}
Marian L. Yurchishin, Lauren A. Fowler, Amy M. Goss, William T. Garvey, Barbara A. Gower
Objective
The study objective was to determine whether associations between a genetic risk score (GRS) for insulin resistance (IR) and measures of insulin sensitivity differ by race and/or BMI status in African American (AA) and European American (EA) adults without diabetes.
Methods
Fifty-three AA and 54 EA participants were classified into “high” or “low” BMI groups using the sample median (25.9 kg/m2) as the cut point. The GRS was derived from 52 previously identified genetic variants. Skeletal muscle insulin sensitivity was measured with the hyperinsulinemic-euglycemic clamp. The homeostasis model assessment of insulin resistance (HOMA-IR) and the Matsuda index of insulin sensitivity were calculated from oral glucose tolerance test values to determine hepatic and whole-body insulin sensitivity, respectively. Linear regression models, stratified by race, assessed interactions between BMI status and GRS on measures of insulin sensitivity.
Results
In EA participants, associations of GRS with HOMA-IR and the Matsuda index differed by BMI status, where the GRS was associated with IR in the high-BMI group only. In AA participants, associations from the clamp differed by BMI status, but an association was observed only in the low-BMI group.
Conclusions
These results highlight the heterogeneity of IR and support the hypothesis that the relationship between genetic predisposition for IR and obesity is race- and tissue-specific.
研究目的研究目的是确定胰岛素抵抗(IR)遗传风险评分(GRS)与胰岛素敏感性指标之间的关联是否因种族和/或体重指数状况而异,研究对象为非裔美国人(AA)和无糖尿病的欧洲裔美国人(EA)成年人:以样本中位数(25.9 kg/m2)为切点,将 53 名 AA 和 54 名 EA 参与者分为 "高 "或 "低 "BMI 组。GRS是从之前确定的52个基因变异中得出的。骨骼肌胰岛素敏感性通过高胰岛素血糖钳夹法进行测量。胰岛素抵抗稳态模型评估(HOMA-IR)和松田胰岛素敏感性指数是根据口服葡萄糖耐量试验值计算得出的,分别用于确定肝脏和全身的胰岛素敏感性。按种族分层的线性回归模型评估了体重指数状况和胰岛素敏感性测量值之间的相互作用:结果:在 EA 参与者中,GRS 与 HOMA-IR 和松田指数的关系因 BMI 状态而异,其中只有高 BMI 组的 GRS 与 IR 相关。在 AA 参与者中,夹钳的关联因 BMI 状态而异,但只在低 BMI 组中观察到关联:这些结果凸显了IR的异质性,并支持了IR遗传易感性与肥胖之间的关系具有种族和组织特异性的假设。
{"title":"Predictability of genetic risk score for insulin resistance is influenced by both BMI and race","authors":"Marian L. Yurchishin, Lauren A. Fowler, Amy M. Goss, William T. Garvey, Barbara A. Gower","doi":"10.1002/oby.24238","DOIUrl":"10.1002/oby.24238","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The study objective was to determine whether associations between a genetic risk score (GRS) for insulin resistance (IR) and measures of insulin sensitivity differ by race and/or BMI status in African American (AA) and European American (EA) adults without diabetes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Fifty-three AA and 54 EA participants were classified into “high” or “low” BMI groups using the sample median (25.9 kg/m<sup>2</sup>) as the cut point. The GRS was derived from 52 previously identified genetic variants. Skeletal muscle insulin sensitivity was measured with the hyperinsulinemic-euglycemic clamp. The homeostasis model assessment of insulin resistance (HOMA-IR) and the Matsuda index of insulin sensitivity were calculated from oral glucose tolerance test values to determine hepatic and whole-body insulin sensitivity, respectively. Linear regression models, stratified by race, assessed interactions between BMI status and GRS on measures of insulin sensitivity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In EA participants, associations of GRS with HOMA-IR and the Matsuda index differed by BMI status, where the GRS was associated with IR in the high-BMI group only. In AA participants, associations from the clamp differed by BMI status, but an association was observed only in the low-BMI group.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These results highlight the heterogeneity of IR and support the hypothesis that the relationship between genetic predisposition for IR and obesity is race- and tissue-specific.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 4","pages":"788-795"},"PeriodicalIF":4.2,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24238","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143495124","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}
Søren Gam, Simon Lysdahlgaard, Bibi Gram, Martin Weber Kusk, Anne Pernille Hermann, Claus Bogh Juhl, Stinus Gadegaard Hansen
Objective
The aim of this study was to investigate the effects of zoledronic acid for the prevention of bone loss after bariatric surgery.
Methods
In this randomized, double-blinded study, 59 patients undergoing Roux-en-Y gastric bypass or sleeve gastrectomy (mean [SD], age: 48.9 [6.3] years, BMI: 42.3 [5.3], 73% female) were randomly assigned (1:1) to receive either zoledronic acid (5 mg; intervention [INT]) or placebo (control [CON]) preoperatively. The primary endpoint was the change in spine volumetric bone mineral density (vBMD) at 12 months after surgery. Secondary outcomes included changes in hip and femoral neck vBMD and areal BMD.
Results
The estimated mean treatment effects of zoledronic acid on the spine and total hip were 6.8 mg/cm3 (95% CI 1.9–11.7; p = 0.003) and 5.0 mg/cm3 (95% CI: 1.4–8.5; p = 0.006), respectively. Bone mass in the spine increased by 2.6% in INT, whereas no changes were observed in CON. Additionally, bone loss in the total hip was prevented in INT compared with CON (vBMD: −0.6% vs. −3.6%; p = 0.006).
Conclusions
Zoledronic acid increases bone mass in the spine and prevents bone loss in the hip region after bariatric surgery compared with placebo.
研究目的本研究旨在探讨唑来膦酸预防减肥手术后骨质流失的效果:在这项随机双盲研究中,59 名接受 Roux-en-Y 胃旁路手术或袖状胃切除术的患者(平均 [SD] 年龄:48.9 [6.3] 岁,BMI:42.3 [5.3],73% 为女性)被随机分配(1:1)至术前接受唑来膦酸(5 毫克;干预 [INT])或安慰剂(对照 [CON])治疗。主要终点是术后12个月时脊柱体积骨密度(vBMD)的变化。次要结果包括髋关节和股骨颈vBMD以及骨密度分布的变化:唑来膦酸对脊柱和全髋的估计平均治疗效果分别为 6.8 mg/cm3 (95% CI 1.9-11.7; p = 0.003) 和 5.0 mg/cm3 (95% CI: 1.4-8.5; p = 0.006)。在 INT 中,脊柱的骨量增加了 2.6%,而在 CON 中未观察到任何变化。此外,与CON相比,INT可防止全髋部骨质流失(vBMD:-0.6% vs. -3.6%;p = 0.006):结论:与安慰剂相比,唑来膦酸可增加减肥手术后脊柱的骨量并防止髋部骨质流失。
{"title":"Zoledronic acid increases spine bone mass and prevents hip bone loss after bariatric surgery: a randomized placebo-controlled study","authors":"Søren Gam, Simon Lysdahlgaard, Bibi Gram, Martin Weber Kusk, Anne Pernille Hermann, Claus Bogh Juhl, Stinus Gadegaard Hansen","doi":"10.1002/oby.24214","DOIUrl":"10.1002/oby.24214","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The aim of this study was to investigate the effects of zoledronic acid for the prevention of bone loss after bariatric surgery.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In this randomized, double-blinded study, 59 patients undergoing Roux-en-Y gastric bypass or sleeve gastrectomy (mean [SD], age: 48.9 [6.3] years, BMI: 42.3 [5.3], 73% female) were randomly assigned (1:1) to receive either zoledronic acid (5 mg; intervention [INT]) or placebo (control [CON]) preoperatively. The primary endpoint was the change in spine volumetric bone mineral density (vBMD) at 12 months after surgery. Secondary outcomes included changes in hip and femoral neck vBMD and areal BMD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The estimated mean treatment effects of zoledronic acid on the spine and total hip were 6.8 mg/cm<sup>3</sup> (95% CI 1.9–11.7; <i>p</i> = 0.003) and 5.0 mg/cm<sup>3</sup> (95% CI: 1.4–8.5; <i>p</i> = 0.006), respectively. Bone mass in the spine increased by 2.6% in INT, whereas no changes were observed in CON. Additionally, bone loss in the total hip was prevented in INT compared with CON (vBMD: −0.6% vs. −3.6%; <i>p</i> = 0.006).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Zoledronic acid increases bone mass in the spine and prevents bone loss in the hip region after bariatric surgery compared with placebo.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 4","pages":"659-670"},"PeriodicalIF":4.2,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24214","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143470365","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}
Elortegui Pascual, P, Rolands, MR, Eldridge, AL, Kassis, A, Mainardi, F, Lê, KA, Karagounis, LG, Gut, P, Varady, KA. A meta-analysis comparing the effectiveness of alternate day fasting, the 5:2 diet, and time-restricted eating for weight loss. Obesity (Silver Spring). 2023; 31(S1): 9–21. doi:10.1002/oby.23568
In Figure 1, there is a miscount error in the “Records excluded based on title” box. “Records excluded based on title (n = 1748)” was incorrect. The number of articles should be n = 1747. The error occurred during the reporting of the number and does not affect the selection process or the validity of the final papers selected and analyzed.
We apologize for this error.
{"title":"Correction to “A meta-analysis comparing the effectiveness of alternate day fasting, the 5:2 diet, and time-restricted eating for weight loss”","authors":"","doi":"10.1002/oby.24266","DOIUrl":"10.1002/oby.24266","url":null,"abstract":"<p>\u0000 <span>Elortegui Pascual, P</span>, <span>Rolands, MR</span>, <span>Eldridge, AL</span>, <span>Kassis, A</span>, <span>Mainardi, F</span>, <span>Lê, KA</span>, <span>Karagounis, LG</span>, <span>Gut, P</span>, <span>Varady, KA</span>. <span>A meta-analysis comparing the effectiveness of alternate day fasting, the 5:2 diet, and time-restricted eating for weight loss</span>. <i>Obesity (Silver Spring)</i>. <span>2023</span>; <span>31</span>(<span>S1</span>): <span>9</span>–<span>21</span>. doi:10.1002/oby.23568\u0000 </p><p>In Figure 1, there is a miscount error in the “Records excluded based on title” box. “Records excluded based on title (<i>n</i> = 1748)” was incorrect. The number of articles should be <i>n</i> = 1747. The error occurred during the reporting of the number and does not affect the selection process or the validity of the final papers selected and analyzed.</p><p>We apologize for this error.</p>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"33 5","pages":"1011"},"PeriodicalIF":4.2,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24266","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143470359","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}
Xiaoru Feng, Ruoqian Li, Hang Yi, Shuyi Chen, Meng Liu, You Wu
Objective
The objective of this study was to estimate cancer burden attributable to excess body weight (EBW) and identify its main source.
Methods
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.
Results
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.
Conclusions
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.
{"title":"Global cancer burden attributable to excess body weight, 1990 to 2021, decomposed by population size, aging, and epidemiological change","authors":"Xiaoru Feng, Ruoqian Li, Hang Yi, Shuyi Chen, Meng Liu, 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}
Raphiel J. Murden, Nicole D. Fields, Zachary T. Martin, Benjamin B. Risk, Alvaro Alonso, Amita Manatunga, Christy L. Erving, Reneé Moore, Shivika Udaipuria, Arshed Quyyumi, Viola Vaccarino, Tené T. Lewis
Objective
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.
Methods
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.
Results
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.
Conclusions
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.
{"title":"Associations between obesity class and ambulatory blood pressure curves in African American women","authors":"Raphiel J. Murden, Nicole D. Fields, Zachary T. Martin, Benjamin B. Risk, Alvaro Alonso, Amita Manatunga, Christy L. Erving, Reneé Moore, Shivika Udaipuria, Arshed Quyyumi, Viola Vaccarino, 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}
Niki Oldenburg, Douglas G. Mashek, Lisa Harnack, Qi Wang, Emily N. C. Manoogian, Nicholas Evanoff, Donald R. Dengel, Abdisa Taddese, Brad P. Yentzer, Lesia Lysne, Alison Wong, Michelle Hanson, Julie D. Anderson, Alison Alvear, Nicole LaPage, Justin Ryder, Krista Varady, Zan Gao, Suryeon Ryu, Patrick J. Bolan, Bryan Bergman, Erika Helgeson, Satchidananda Panda, Lisa S. Chow
Objective
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.
Methods
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).
Results
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 (n = 29), weight changes were −1.4 kg (95% CI: −4.5 to 1.7; p = 0.53) with TRE (n = 30) and −2.5 kg (95% CI: −5.8 to 0.8; p = 0.18) with CR (n = 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.
Conclusions
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.
{"title":"Time-restricted eating, caloric reduction, and unrestricted eating effects on weight and metabolism: a randomized trial","authors":"Niki Oldenburg, Douglas G. Mashek, Lisa Harnack, Qi Wang, Emily N. C. Manoogian, Nicholas Evanoff, Donald R. Dengel, Abdisa Taddese, Brad P. Yentzer, Lesia Lysne, Alison Wong, Michelle Hanson, Julie D. Anderson, Alison Alvear, Nicole LaPage, Justin Ryder, Krista Varady, Zan Gao, Suryeon Ryu, Patrick J. Bolan, Bryan Bergman, Erika Helgeson, Satchidananda Panda, 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/m<sup>2</sup>; 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}
Lora E. Burke, Zhadyra Bizhanova, Molly B. Conroy, Jessica Cheng, Britney Beatrice, Jacob K. Kariuki, Bambang Parmanto, Susan M. Sereika
Objective
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.
Methods
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.
Results
The sample (N = 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.
Conclusions
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.
{"title":"Adherence to self-monitoring and behavioral goals is associated with improved weight loss in an mHealth randomized-controlled trial","authors":"Lora E. Burke, Zhadyra Bizhanova, Molly B. Conroy, Jessica Cheng, Britney Beatrice, Jacob K. Kariuki, Bambang Parmanto, 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/m<sup>2</sup>. 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}
Fanny Janssen, Rolando Gonzales Martinez, Nicolás Zengarini, Pekka Martikainen, Anton Kunst
Objective
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).
Methods
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.
Results
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.
Conclusions
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.
{"title":"Trends in educational inequalities in obesity-attributable mortality in England and Wales, Finland, and Italy","authors":"Fanny Janssen, Rolando Gonzales Martinez, Nicolás Zengarini, Pekka Martikainen, 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}
Manal Al Dow, Blandine Secco, Mathilde Mouchiroud, Marianne Rochette, Gustavo R. Gilio, Mickael Massicard, Marilou Hardy, Yves Gélinas, William T. Festuccia, Mathieu C. Morissette, Venkata S. K. Manem, Mathieu Laplante
Objective
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.
Methods
We generated VSTM2A knockout mice (Vstm2a−/−) 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.
Results
Vstm2a−/− mice were viable and showed no body weight differences. Although adipose mass was similar, Vstm2a−/− 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.
Conclusions
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.
{"title":"Loss of VSTM2A promotes adipocyte hypertrophy and disrupts metabolic homeostasis","authors":"Manal Al Dow, Blandine Secco, Mathilde Mouchiroud, Marianne Rochette, Gustavo R. Gilio, Mickael Massicard, Marilou Hardy, Yves Gélinas, William T. Festuccia, Mathieu C. Morissette, Venkata S. K. Manem, 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><sup><i>−/−</i></sup>) 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><sup><i>−/−</i></sup> mice were viable and showed no body weight differences. Although adipose mass was similar, <i>Vstm2a</i><sup><i>−/−</i></sup> 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}