Kristine J. Steffen, Alicia A. Sorgen, Anthony A. Fodor, Ian M. Carroll, Ross D. Crosby, James E. Mitchell, Dale S. Bond, Leslie J. Heinberg
Objective
Metabolic and bariatric surgery (MBS) is associated with substantial, but variable, weight outcomes. The gut microbiome may be a factor in determining weight trajectory, but examination has been limited by a lack of longitudinal studies with robust microbiome sequencing. This study aimed to describe changes in the microbiome and associations with weight outcomes more than 2 years post surgery.
Methods
Data were collected at two Midwestern U.S. centers. Adults undergoing primary MBS were assessed before and 1, 6, 12, 18, and 24 months after surgery. BMI and metagenomic sequencing occurred at each assessment. A linear growth mixture model determined class structure for weight trajectory.
Results
A linear growth mixture model of participants (N = 124) revealed a two-class structure; one class had greater sustained weight loss relative to the other. Greater genus-level taxonomic changes in the microbiome composition at each time point were associated with being in the more favorable weight trajectory class, after controlling for surgery type. Higher Proteobacteria relative abundance at 1 month was predictive of percentage weight change at 6, 12, 18, and 24 months (p < 0.05 for all).
Conclusions
Greater genus-level taxonomic changes in the gut microbiota are associated with improved weight trajectory. Early changes in the gut microbiota may be an important indicator of MBS outcomes and durability.
{"title":"Early changes in the gut microbiota are associated with weight outcomes over 2 years following metabolic and bariatric surgery","authors":"Kristine J. Steffen, Alicia A. Sorgen, Anthony A. Fodor, Ian M. Carroll, Ross D. Crosby, James E. Mitchell, Dale S. Bond, Leslie J. Heinberg","doi":"10.1002/oby.24168","DOIUrl":"10.1002/oby.24168","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Metabolic and bariatric surgery (MBS) is associated with substantial, but variable, weight outcomes. The gut microbiome may be a factor in determining weight trajectory, but examination has been limited by a lack of longitudinal studies with robust microbiome sequencing. This study aimed to describe changes in the microbiome and associations with weight outcomes more than 2 years post surgery.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Data were collected at two Midwestern U.S. centers. Adults undergoing primary MBS were assessed before and 1, 6, 12, 18, and 24 months after surgery. BMI and metagenomic sequencing occurred at each assessment. A linear growth mixture model determined class structure for weight trajectory.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A linear growth mixture model of participants (<i>N</i> = 124) revealed a two-class structure; one class had greater sustained weight loss relative to the other. Greater genus-level taxonomic changes in the microbiome composition at each time point were associated with being in the more favorable weight trajectory class, after controlling for surgery type. Higher Proteobacteria relative abundance at 1 month was predictive of percentage weight change at 6, 12, 18, and 24 months (<i>p</i> < 0.05 for all).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Greater genus-level taxonomic changes in the gut microbiota are associated with improved weight trajectory. Early changes in the gut microbiota may be an important indicator of MBS outcomes and durability.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"32 11","pages":"1985-1997"},"PeriodicalIF":4.2,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24168","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577322","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}
Visceral adiposity is associated with increased proinflammatory activity, insulin resistance, diabetes risk, and mortality rate. Numerous individual genes have been associated with obesity, but studies investigating gene regulatory networks in human visceral obesity have been lacking.
Methods
We analyzed gene regulatory networks in human visceral adipose tissue (VAT) from 48 and 11 Chinese patients with and without obesity, respectively, using gene coexpression and gene regulatory network construction from RNA-sequencing data. We also conducted RNA interference-based functional tests on selected genes for effects on adipocyte differentiation.
Results
A scale-free gene coexpression network was constructed from 360 differentially expressed genes between VAT samples from patients with and without obesity (absolute log fold change > 1, false discovery rate [FDR] < 0.05), with edge probability > 0.8. Gene regulatory network analysis identified candidate transcription factors associated with differentially expressed genes. A total of 15 subnetworks (communities) displayed altered connectivity patterns between obesity and nonobesity networks. Genes in proinflammatory pathways showed increased network connectivity in VAT samples with obesity, whereas the oxidative phosphorylation pathway displayed reduced connectivity (enrichment FDR < 0.05). Functional screening via RNA interference identified genes such as SOX30, SIRPB1, and OSBPL3 as potential network-derived candidates influencing adipocyte differentiation.
Conclusions
This approach highlights the network architecture in human obesity, identifies novel candidate genes, and generates new hypotheses regarding network-assisted gene regulation in VAT.
{"title":"In silico and functional analysis identifies key gene networks and novel gene candidates in obesity-linked human visceral fat","authors":"Lijin Wang, Pratap Veerabrahma Seshachalam, Ruiming Chua, Hongwen Zhou, Sun Lei, Sujoy Ghosh","doi":"10.1002/oby.24161","DOIUrl":"10.1002/oby.24161","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Visceral adiposity is associated with increased proinflammatory activity, insulin resistance, diabetes risk, and mortality rate. Numerous individual genes have been associated with obesity, but studies investigating gene regulatory networks in human visceral obesity have been lacking.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We analyzed gene regulatory networks in human visceral adipose tissue (VAT) from 48 and 11 Chinese patients with and without obesity, respectively, using gene coexpression and gene regulatory network construction from RNA-sequencing data. We also conducted RNA interference-based functional tests on selected genes for effects on adipocyte differentiation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A scale-free gene coexpression network was constructed from 360 differentially expressed genes between VAT samples from patients with and without obesity (absolute log fold change > 1, false discovery rate [FDR] < 0.05), with edge probability > 0.8. Gene regulatory network analysis identified candidate transcription factors associated with differentially expressed genes. A total of 15 subnetworks (communities) displayed altered connectivity patterns between obesity and nonobesity networks. Genes in proinflammatory pathways showed increased network connectivity in VAT samples with obesity, whereas the oxidative phosphorylation pathway displayed reduced connectivity (enrichment FDR < 0.05). Functional screening via RNA interference identified genes such as <i>SOX30</i>, <i>SIRPB1</i>, and <i>OSBPL3</i> as potential network-derived candidates influencing adipocyte differentiation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This approach highlights the network architecture in human obesity, identifies novel candidate genes, and generates new hypotheses regarding network-assisted gene regulation in VAT.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"32 11","pages":"1998-2011"},"PeriodicalIF":4.2,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11548800/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577323","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}
Julia M. P. Bittner, Stephen E. Gilman, Zhen Chen, Neil J. Perkins, Bobby K. Cheon
Objective
Socioeconomic mobility, i.e., changing socioeconomic status (SES) between adolescence and adulthood, may impact health through changing resources, social status, and health-related behaviors. This analysis examined whether subjective SES contributes to associations of mobility with metabolic health (BMI and metabolic syndrome) and unhealthy diets (fast-food consumption and sugar-sweetened beverage [SSB] consumption).
Methods
National Longitudinal Study of Adolescent to Adult Health data were used (n = 4132). Mobility was defined as the difference between adolescent (collected 1994–1995, ages 11–19 years) and adult (collected 2016–2018, ages 33–43 years) SES. Linear and logistic regressions examined associations of mobility with metabolic and dietary outcomes and mediation by subjective SES.
Results
Substantial upward mobility was associated with lower risk of high SSB consumption compared with stable disadvantaged SES (risk difference: −0.10 [95% CI: −0.16 to −0.041]). Subjective SES mediated associations of upward, but not downward, mobility with risks of developing metabolic syndrome, high fast-food consumption, and high SSB consumption; upward mobility was associated with higher subjective SES and lower risks of poor metabolic and dietary outcomes.
Conclusions
The finding that subjective SES contributed to associations between upward mobility and better health may inform development of interventions designed to promote healthier diets and reduce socioeconomic disparities in metabolic health.
{"title":"Socioeconomic mobility, metabolic health, and diet: mediation via subjective socioeconomic status","authors":"Julia M. P. Bittner, Stephen E. Gilman, Zhen Chen, Neil J. Perkins, Bobby K. Cheon","doi":"10.1002/oby.24148","DOIUrl":"10.1002/oby.24148","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Socioeconomic mobility, i.e., changing socioeconomic status (SES) between adolescence and adulthood, may impact health through changing resources, social status, and health-related behaviors. This analysis examined whether subjective SES contributes to associations of mobility with metabolic health (BMI and metabolic syndrome) and unhealthy diets (fast-food consumption and sugar-sweetened beverage [SSB] consumption).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>National Longitudinal Study of Adolescent to Adult Health data were used (<i>n</i> = 4132). Mobility was defined as the difference between adolescent (collected 1994–1995, ages 11–19 years) and adult (collected 2016–2018, ages 33–43 years) SES. Linear and logistic regressions examined associations of mobility with metabolic and dietary outcomes and mediation by subjective SES.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Substantial upward mobility was associated with lower risk of high SSB consumption compared with stable disadvantaged SES (risk difference: −0.10 [95% CI: −0.16 to −0.041]). Subjective SES mediated associations of upward, but not downward, mobility with risks of developing metabolic syndrome, high fast-food consumption, and high SSB consumption; upward mobility was associated with higher subjective SES and lower risks of poor metabolic and dietary outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The finding that subjective SES contributed to associations between upward mobility and better health may inform development of interventions designed to promote healthier diets and reduce socioeconomic disparities in metabolic health.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"32 11","pages":"2035-2044"},"PeriodicalIF":4.2,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540334/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577334","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}
Mohammad Y. Anwar, Heather Highland, Victoria Lynn Buchanan, Mariaelisa Graff, Kristin Young, Kent D. Taylor, Russell P. Tracy, Peter Durda, Yongmei Liu, Craig W. Johnson, Francois Aguet, Kristin G. Ardlie, Robert E. Gerszten, Clary B. Clish, Leslie A. Lange, Jingzhong Ding, Mark O. Goodarzi, Yii-Der Ida Chen, Gina M. Peloso, Xiuqing Guo, Maggie A. Stanislawski, Jerome I. Rotter, Stephen S. Rich, Anne E. Justice, Ching-ti Liu, Kari North
Objective
Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi-omics approach might improve identification of subgroups of individuals with obesity who have distinct cardiometabolic disease patterns.
Methods
We performed machine learning-based, integrative unsupervised clustering to identify proteomics- and metabolomics-defined subpopulations of individuals living with obesity (BMI ≥ 30 kg/m2), leveraging data from 243 individuals in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort. Omics that contributed to the observed clusters were functionally characterized. We performed multivariate regression to assess whether the individuals in each cluster demonstrated differential patterns of cardiometabolic traits.
Results
We identified two distinct clusters (iCluster1 and 2). iCluster2 had significantly higher average BMI values, fasting blood glucose, and inflammation. iCluster1 was associated with higher levels of total cholesterol and high-density lipoprotein cholesterol. Pathways mediating cell growth, lipogenesis, and energy expenditures were positively associated with iCluster1. Inflammatory response and insulin resistance pathways were positively associated with iCluster2.
Conclusions
Although the two identified clusters may represent progressive obesity-related pathologic processes measured at different stages, other mechanisms in combination could also underpin the identified clusters given no significant age difference between the comparative groups. For instance, clusters may reflect differences in dietary/behavioral patterns or differential rates of metabolic damage.
{"title":"Machine learning-based clustering identifies obesity subgroups with differential multi-omics profiles and metabolic patterns","authors":"Mohammad Y. Anwar, Heather Highland, Victoria Lynn Buchanan, Mariaelisa Graff, Kristin Young, Kent D. Taylor, Russell P. Tracy, Peter Durda, Yongmei Liu, Craig W. Johnson, Francois Aguet, Kristin G. Ardlie, Robert E. Gerszten, Clary B. Clish, Leslie A. Lange, Jingzhong Ding, Mark O. Goodarzi, Yii-Der Ida Chen, Gina M. Peloso, Xiuqing Guo, Maggie A. Stanislawski, Jerome I. Rotter, Stephen S. Rich, Anne E. Justice, Ching-ti Liu, Kari North","doi":"10.1002/oby.24137","DOIUrl":"10.1002/oby.24137","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi-omics approach might improve identification of subgroups of individuals with obesity who have distinct cardiometabolic disease patterns.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We performed machine learning-based, integrative unsupervised clustering to identify proteomics- and metabolomics-defined subpopulations of individuals living with obesity (BMI ≥ 30 kg/m<sup>2</sup>), leveraging data from 243 individuals in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort. Omics that contributed to the observed clusters were functionally characterized. We performed multivariate regression to assess whether the individuals in each cluster demonstrated differential patterns of cardiometabolic traits.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified two distinct clusters (iCluster1 and 2). iCluster2 had significantly higher average BMI values, fasting blood glucose, and inflammation. iCluster1 was associated with higher levels of total cholesterol and high-density lipoprotein cholesterol. Pathways mediating cell growth, lipogenesis, and energy expenditures were positively associated with iCluster1. Inflammatory response and insulin resistance pathways were positively associated with iCluster2.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Although the two identified clusters may represent progressive obesity-related pathologic processes measured at different stages, other mechanisms in combination could also underpin the identified clusters given no significant age difference between the comparative groups. For instance, clusters may reflect differences in dietary/behavioral patterns or differential rates of metabolic damage.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"32 11","pages":"2024-2034"},"PeriodicalIF":4.2,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540333/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577327","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}
Maya-Jean Hilaire, Annelise Babcock, Glenn White, Cynthia F. Masson, Rany M. Salem, Uma M. Reddy, Dympna Gallagher, Charles A. LeDuc, Vidhu V. Thaker
Objective
The objective of this study was to assess maternal gestational outcomes and offspring growth trajectories following prepregnancy metabolic and bariatric surgery (MBS) compared with non-MBS controls.
Methods
Single-center deliveries between January 2020 and March 2023 with prepregnancy Roux-en-Y gastric bypass (herein referred to as “bypass”), sleeve gastrectomy (herein referred to as “sleeve”), and non-MBS controls were included. Offspring growth trajectories were compared with the World Health Organization child growth standards. Linear mixed models assessed MBS-bypass and MBS-sleeve offspring weight, length, and BMI trajectories with a prepregnancy BMI 27 to 37 kg/m2 and propensity score-matched controls.
Results
The study included 440 participants with prepregnancy MBS (MBS-bypass, 185; MBS-sleeve, 225; 76% Hispanic/Latino) and 13,434 non-MBS controls. Gestational weight gain and gestational diabetes mellitus were similar, whereas hypertensive disorders of pregnancy were more common after MBS. The post-MBS offspring had lower birth weight but higher weight gain at 24 months (sleeve, +1.4 kg [95% CI: 1.0–1.9]; bypass, +0.5–0.7 kg [95% CI: 0.0–1.2]) compared with non-MBS groups. Male children had higher weight gain than females. The post-MBS-sleeve but not the post-MBS-bypass offspring had higher BMI z scores.
Conclusions
The higher early-life weight gain and sex differences in the post-MBS-sleeve group compared with the post-MBS-bypass group provide a window toward elucidating pathways to mitigate intergenerational metabolic risk transfer.
{"title":"The association of higher offspring early-childhood weight gain with prepregnancy metabolic and bariatric surgery","authors":"Maya-Jean Hilaire, Annelise Babcock, Glenn White, Cynthia F. Masson, Rany M. Salem, Uma M. Reddy, Dympna Gallagher, Charles A. LeDuc, Vidhu V. Thaker","doi":"10.1002/oby.24166","DOIUrl":"10.1002/oby.24166","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The objective of this study was to assess maternal gestational outcomes and offspring growth trajectories following prepregnancy metabolic and bariatric surgery (MBS) compared with non-MBS controls.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Single-center deliveries between January 2020 and March 2023 with prepregnancy Roux-en-Y gastric bypass (herein referred to as “bypass”), sleeve gastrectomy (herein referred to as “sleeve”), and non-MBS controls were included. Offspring growth trajectories were compared with the World Health Organization child growth standards. Linear mixed models assessed MBS-bypass and MBS-sleeve offspring weight, length, and BMI trajectories with a prepregnancy BMI 27 to 37 kg/m<sup>2</sup> and propensity score-matched controls.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The study included 440 participants with prepregnancy MBS (MBS-bypass, 185; MBS-sleeve, 225; 76% Hispanic/Latino) and 13,434 non-MBS controls. Gestational weight gain and gestational diabetes mellitus were similar, whereas hypertensive disorders of pregnancy were more common after MBS. The post-MBS offspring had lower birth weight but higher weight gain at 24 months (sleeve, +1.4 kg [95% CI: 1.0–1.9]; bypass, +0.5–0.7 kg [95% CI: 0.0–1.2]) compared with non-MBS groups. Male children had higher weight gain than females. The post-MBS-sleeve but not the post-MBS-bypass offspring had higher BMI <i>z</i> scores.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The higher early-life weight gain and sex differences in the post-MBS-sleeve group compared with the post-MBS-bypass group provide a window toward elucidating pathways to mitigate intergenerational metabolic risk transfer.</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":"32 11","pages":"2012-2023"},"PeriodicalIF":4.2,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577337","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}
Jinchen Xie, Peng Nie, Mengzi Sun, Xinguang Chen, Tingling Xu, Zumin Shi, Chuntian Lu, Youfa Wang
Objective
Obesity has become a major public health problem worldwide and particularly in China. This study examined the secular trend of overweight and obesity in China over the past 100 years.
Methods
Nationwide data from the China Health and Nutrition Survey and the Chinese General Social Survey were used. A generalized binary mixed-effects model and a weighted quantile sum model were applied.
Results
From 1909 to 2021, the prevalence of overweight and obesity remained stable from 1909 to 1944, experienced a smooth increase from 1945 to 1959 followed by a decline between 1960 and 1974, continued to rise after 1975, and peaked in 2003. The prevalence of overweight (obesity) among Chinese adults increased by 2.68 (6.21) times, from 20.65% (3.10%) in 1993 to 55.33% (19.26%) in 2021, and cohorts born during the Chinese Cultural Revolution (1960–1974) exhibited the lowest risk of overweight and obesity, associated with low protein intake and high physical activity. Cohorts born during the Reform and Opening-Up period (1975–2003) showed a high risk of overweight and obesity related to favorable socioeconomic status and rapid urbanization. Persistent differences by sex and emerging differences by socioeconomic status in overweight and obesity prevalence were captured.
Conclusions
Overweight and obesity trends in China have shown a distinctive increasing–decreasing–increasing pattern over the past 100 years. These patterns exhibit unique characteristics and are influenced by discernible social forces.
{"title":"One hundred-year secular trends of overweight and obesity in China: effects of age, period, and cohort","authors":"Jinchen Xie, Peng Nie, Mengzi Sun, Xinguang Chen, Tingling Xu, Zumin Shi, Chuntian Lu, Youfa Wang","doi":"10.1002/oby.24134","DOIUrl":"10.1002/oby.24134","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Obesity has become a major public health problem worldwide and particularly in China. This study examined the secular trend of overweight and obesity in China over the past 100 years.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Nationwide data from the China Health and Nutrition Survey and the Chinese General Social Survey were used. A generalized binary mixed-effects model and a weighted quantile sum model were applied.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>From 1909 to 2021, the prevalence of overweight and obesity remained stable from 1909 to 1944, experienced a smooth increase from 1945 to 1959 followed by a decline between 1960 and 1974, continued to rise after 1975, and peaked in 2003. The prevalence of overweight (obesity) among Chinese adults increased by 2.68 (6.21) times, from 20.65% (3.10%) in 1993 to 55.33% (19.26%) in 2021, and cohorts born during the Chinese Cultural Revolution (1960–1974) exhibited the lowest risk of overweight and obesity, associated with low protein intake and high physical activity. Cohorts born during the Reform and Opening-Up period (1975–2003) showed a high risk of overweight and obesity related to favorable socioeconomic status and rapid urbanization. Persistent differences by sex and emerging differences by socioeconomic status in overweight and obesity prevalence were captured.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Overweight and obesity trends in China have shown a distinctive increasing–decreasing–increasing pattern over the past 100 years. These patterns exhibit unique characteristics and are influenced by discernible social forces.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"32 11","pages":"2186-2197"},"PeriodicalIF":4.2,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577332","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}
Alison Z. Swartz, Kathryn Wood, Eric Farber-Eger, Alexander Petty, Heidi J. Silver
Objective
The objective of this study was to determine the unique clinical and cardiometabolic risk characteristics of weight-cyclers and identify differences between weight-cyclers and individuals with other weight-change trajectories.
Methods
A deidentified database of 1,428,204 Vanderbilt University Medical Center patients from 1997 to 2020 was included based on having ≥5 years of recorded weights. Patients with a history of malignant neoplasm, bariatric surgery, implausible BMI (e.g., <15 or >80 kg/m2), or missing documented height were excluded, yielding 83,261 participants categorized by weight trajectory, i.e., weight-stable, weight-gainer, weight-loser, or weight-cycler, based on criteria of ≥5% weight-change thresholds. Additionally, quartiles of average successive weight variability were evaluated to determine the effect of absolute differences among successive weight values.
Results
Over half (55%) of participants were weight-cyclers, 23% were weight-gainers, 12% were weight-losers, and 10% were weight-stable over 5 years. Although baseline BMI did not differ among groups, weight-cyclers were more likely to have lower high-density lipoprotein cholesterol and higher blood glucose and triglyceride levels and to have been prescribed antihypertensive, dyslipidemia, and/or antidiabetic therapies. They were also younger and more likely to be smokers. Participants with the greatest weight variability (i.e., highest quartile of average successive weight variability) had higher cardiometabolic risk scores.
Conclusions
Weight cycling was highly prevalent but yielded no meaningful overall change in body weight after 5 years. These findings support a paradigm shift in weight management in individuals with overweight/obesity toward reducing cardiometabolic risk with or without weight loss.
{"title":"Cardiometabolic characteristics of weight cycling: results from a mid-South regional comprehensive health care system","authors":"Alison Z. Swartz, Kathryn Wood, Eric Farber-Eger, Alexander Petty, Heidi J. Silver","doi":"10.1002/oby.24163","DOIUrl":"10.1002/oby.24163","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The objective of this study was to determine the unique clinical and cardiometabolic risk characteristics of weight-cyclers and identify differences between weight-cyclers and individuals with other weight-change trajectories.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A deidentified database of 1,428,204 Vanderbilt University Medical Center patients from 1997 to 2020 was included based on having ≥5 years of recorded weights. Patients with a history of malignant neoplasm, bariatric surgery, implausible BMI (e.g., <15 or >80 kg/m<sup>2</sup>), or missing documented height were excluded, yielding 83,261 participants categorized by weight trajectory, i.e., weight-stable, weight-gainer, weight-loser, or weight-cycler, based on criteria of ≥5% weight-change thresholds. Additionally, quartiles of average successive weight variability were evaluated to determine the effect of absolute differences among successive weight values.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Over half (55%) of participants were weight-cyclers, 23% were weight-gainers, 12% were weight-losers, and 10% were weight-stable over 5 years. Although baseline BMI did not differ among groups, weight-cyclers were more likely to have lower high-density lipoprotein cholesterol and higher blood glucose and triglyceride levels and to have been prescribed antihypertensive, dyslipidemia, and/or antidiabetic therapies. They were also younger and more likely to be smokers. Participants with the greatest weight variability (i.e., highest quartile of average successive weight variability) had higher cardiometabolic risk scores.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Weight cycling was highly prevalent but yielded no meaningful overall change in body weight after 5 years. These findings support a paradigm shift in weight management in individuals with overweight/obesity toward reducing cardiometabolic risk with or without weight loss.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"32 11","pages":"2045-2059"},"PeriodicalIF":4.2,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540335/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577307","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}
Jessica A. Roekenes, Marthe I. Aukan, Ola Jakob Bomo, Ingeborg Brechan, Katarina A. Knudsen, Jonas G. Hansen, Sílvia R. Coutinho, Jens F. Rehfeld, Helen Truby, Amanda Sainsbury, Mette Svendsen, Catia Martins
Objective
This trial aimed to compare three low-energy diets (LEDs) with different amounts of carbohydrates (CHO) on ketosis and changes in hunger feelings in adults with obesity.
Methods
A total of 101 adults (51 female) with obesity (BMI, mean [SEM], 34.7 [0.4] kg/m2) were randomized to follow three isocaloric LEDs (1000 kcal/day) for 8 weeks, containing either low, medium, or high CHO (70, 100, and 130 g/day, respectively), and 4 weeks of refeeding and weight stabilization. Body weight (BW) and composition, hunger and other appetite ratings, concentrations of β-hydroxybutyrate (βHB), and appetite-related hormones were measured at baseline and at the end of weeks 8 and 12.
Results
At week 8, weight loss and βHB concentrations were significantly different among groups: Low CHO group versus Medium CHO group (BW: 2.32 [0.95] kg, 95% CI: 0.44 to 4.21, p = 0.016; βHB: −0.40 [0.09] mM, 95% CI: −0.67 to −0.09, p < 0.001); Low CHO group versus High CHO group (BW: 2.29 [0.96] kg, 95% CI: 0.39 to 4.19, p = 0.016; βHB: −0.644 [0.10] mM, 95% CI: −0.84 to −0.44, p < 0.001); and Medium CHO group versus High CHO group (BW: −0.03 [0.94] kg, 95% CI: −1.89 to 1.84, p = 0.977; βHB: −0.15 [0.08] mM, 95% CI: −0.30 to 0.002, p = 0.054). No significant differences in hunger were found among groups: Low CHO group versus Medium CHO group (−10.87 [5.92] mm, 95% CI: −0.82 to 22.57, p = 0.068); Low CHO group versus Medium CHO group (7.74 [7.36] mm, 95% CI: −6.77 to 22.26, p = 0.294); and Medium CHO group versus High CHO group (−3.13 [7.48] mm, 95% CI: −17.89 to 11.63, p = 0.676).
Conclusions
Although the findings of this trial are not definitive, changes in hunger ratings with weight loss did not differ among groups. Additional studies with CHO intake of up to 130 g in 1000-kcal/day LEDs are warranted to replicate these findings.
{"title":"Is severe carbohydrate restriction necessary for appetite suppression? The ASKED randomized controlled trial","authors":"Jessica A. Roekenes, Marthe I. Aukan, Ola Jakob Bomo, Ingeborg Brechan, Katarina A. Knudsen, Jonas G. Hansen, Sílvia R. Coutinho, Jens F. Rehfeld, Helen Truby, Amanda Sainsbury, Mette Svendsen, Catia Martins","doi":"10.1002/oby.24133","DOIUrl":"10.1002/oby.24133","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This trial aimed to compare three low-energy diets (LEDs) with different amounts of carbohydrates (CHO) on ketosis and changes in hunger feelings in adults with obesity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A total of 101 adults (51 female) with obesity (BMI, mean [SEM], 34.7 [0.4] kg/m<sup>2</sup>) were randomized to follow three isocaloric LEDs (1000 kcal/day) for 8 weeks, containing either low, medium, or high CHO (70, 100, and 130 g/day, respectively), and 4 weeks of refeeding and weight stabilization. Body weight (BW) and composition, hunger and other appetite ratings, concentrations of β-hydroxybutyrate (βHB), and appetite-related hormones were measured at baseline and at the end of weeks 8 and 12.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>At week 8, weight loss and βHB concentrations were significantly different among groups: Low CHO group versus Medium CHO group (BW: 2.32 [0.95] kg, 95% CI: 0.44 to 4.21, <i>p</i> = 0.016; βHB: −0.40 [0.09] mM, 95% CI: −0.67 to −0.09, <i>p</i> < 0.001); Low CHO group versus High CHO group (BW: 2.29 [0.96] kg, 95% CI: 0.39 to 4.19, <i>p</i> = 0.016; βHB: −0.644 [0.10] mM, 95% CI: −0.84 to −0.44, <i>p</i> < 0.001); and Medium CHO group versus High CHO group (BW: −0.03 [0.94] kg, 95% CI: −1.89 to 1.84, <i>p</i> = 0.977; βHB: −0.15 [0.08] mM, 95% CI: −0.30 to 0.002, <i>p</i> = 0.054). No significant differences in hunger were found among groups: Low CHO group versus Medium CHO group (−10.87 [5.92] mm, 95% CI: −0.82 to 22.57, <i>p</i> = 0.068); Low CHO group versus Medium CHO group (7.74 [7.36] mm, 95% CI: −6.77 to 22.26, <i>p</i> = 0.294); and Medium CHO group versus High CHO group (−3.13 [7.48] mm, 95% CI: −17.89 to 11.63, <i>p</i> = 0.676).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Although the findings of this trial are not definitive, changes in hunger ratings with weight loss did not differ among groups. Additional studies with CHO intake of up to 130 g in 1000-kcal/day LEDs are warranted to replicate these findings.</p>\u0000 </section>\u0000 </div>","PeriodicalId":215,"journal":{"name":"Obesity","volume":"32 11","pages":"2087-2099"},"PeriodicalIF":4.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/oby.24133","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484516","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}
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