RESUMO
The factors determining the reversal of metabolically unhealthy obesity (MUO) to metabolically healthy obesity (MHO) after Roux-en-Y gastric bypass (RYGB) are not completely elucidated. The present study aims to evaluate body adiposity and distribution, through different indices, according to metabolic phenotypes before and 6 months after RYGB, and the relationship between these indices and transition from MUO to MHO. This study reports a prospective longitudinal study on adults with obesity who were evaluated before (T0) and 6 months (T1) after RYGB. Bodyweight, height, waist circumference (WC), BMI, waist-to-height ratio (WHR), total cholesterol (TC), HDL-c, LDL-c, triglycerides, insulin, glucose, HbA1c and HOMA-IR were evaluated. The visceral adiposity index (VAI), the conicity index (CI), the lipid accumulation product (LAP), CUN-BAE and body shape index (ABSI) were calculated. MUO was classified based on insulin resistance. MUO at T0 with transition to MHO at T1 formed the MHO-t group MHO and MUO at both T0 and T1 formed the MHO-m and MUO-m groups, respectively. At T0, 37.3% of the 62 individuals were classified as MHO and 62.7% as MUO. Individuals in the MUO-T0 group had higher blood glucose, HbA1c, HOMA-IR, insulin, TC and LDL-c compared to those in the MHO-T0 group. Both groups showed significant improvement in biochemical and body variables at T1. After RYGB, 89.2% of MUO-T0 became MHO (MHO-t). The MUO-m group presented higher HOMA-IR, insulin and VAI, compared to the MHO-m and MHO-t groups. CI and ABSI at T0 correlated with HOMA-IR at T1 in the MHO-t and MHO-m groups. CI and ABSI, indicators of visceral fat, are promising for predicting post-RYGB metabolic improvement. Additional studies are needed to confirm the sustainability of MUO reversion and its relationship with these indices.
RESUMO
BACKGROUND: The association between dietary nutritional patterns, psychological factors, and metabolic health status has not been investigated in university students. There are studies that include numerous variables to test hypotheses from various theoretical bases, but due to their complexity, they have not been studied in combination. The scientific community recognizes the use of Gaussian graphical models (GGM) as a set of novel methods capable of addressing this. OBJECTIVE: To apply GGMs to derive specific networks for groups of healthy and unhealthy obese individuals that represent nutritional, psychological, and metabolic patterns in an Ecuadorian population. METHODOLOGY: This was a quantitative, non-experimental, cross-sectional, correlational study conducted on a sample of 230 obese/overweight university students, selected through a multi-stage random sampling method. To assess usual dietary intake, a Food Frequency Questionnaire (FFQ) was used; to evaluate psychological profiles (anxiety, depression, and stress), the DASS-21 scale was employed; blood pressure and anthropometric data were collected; and insulin levels, lipid profiles, and glucose levels were determined using fasting blood samples. The International Diabetes Federation (IDF) criteria were applied to identify metabolically healthy and unhealthy individuals. Statistical analysis relied on univariate methods (frequencies, measures of central tendency, and dispersion), and the relationships were analyzed through networks. The Mann-Whitney U test was used to analyze differences between groups. RESULTS: In metabolically unhealthy obese individuals, GGMs identified a primary network consisting of the influence of waist circumference on blood pressure and insulin levels. In the healthy obese group, a different network was identified, incorporating stress and anxiety variables that influenced blood pressure, anthropometry, and insulin levels. Other identified networks show the dynamics of obesity and the effect of waist circumference on triglycerides, anxiety, and riboflavin intake. CONCLUSIONS: GGMs are an exploratory method that can be used to construct networks that illustrate the behavior of obesity in the studied population. In the future, the identified networks could form the basis for updating obesity management protocols in Primary Care Units and supporting clinical interventions in Ecuador.
Assuntos
Dieta , Obesidade , Sobrepeso , Estudantes , Humanos , Equador/epidemiologia , Masculino , Feminino , Estudos Transversais , Estudantes/psicologia , Universidades , Adulto Jovem , Obesidade/psicologia , Sobrepeso/psicologia , Adulto , Comportamento Alimentar/psicologia , Estado Nutricional , Nível de Saúde , AdolescenteRESUMO
INTRODUCTION AND OBJECTIVES: Recent studies have proposed two distinctive types of obesity, metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO), based on various physiological factors. This study sought to explore the relationship between the metabolic obesity types and the incidence of liver cirrhosis (LC) in a large nationally-representative population. MATERIALS AND METHODS: Data on 27,629 adults with MHO or MUHO, were analyzed from the Korea National Health and Nutrition Examination Survey (KNHANES) obtained from 2015 through 2019. Four categories of metabolic health and weight (MHW) were generated for analysis: (1) MHO, (2) MUHO, (3) Metabolically unhealthy normal weight (MUHNW), and (4) Metabolically healthy normal weight (MHNW). Statistical analyzes were performed with univariate and multivariate logistic regression. RESULTS: The prevalence of LC did not show statistically significant differences among the MHW categories: 0.5% in MHO, 0.4% in MUHO, 0.2% in MHNW, and 0.3% in MUHNW. The unadjusted analysis showed a significant association between self-reported LC and MUHO, but this association was not evident in the adjusted analysis. In the adjusted analysis of the prevalence of laboratory LC, a significant association emerged in the MUHO group, followed in descending order of magnitude by the MHO and MUHNW groups. A favorable fasting blood glucose level was the only factor associated with increased prevalence of reported LC in MUHO. CONCLUSIONS: The study demonstrated a difference in the prevalence of LC between MHO and MUHO. Our study concludes that the MHO phenotype is a transient status with regard to metabolic abnormalities, and caution is necessary when evaluating MHO.
Assuntos
Obesidade Metabolicamente Benigna , Obesidade , Humanos , Prevalência , Inquéritos Nutricionais , Obesidade/diagnóstico , Obesidade/epidemiologia , Fenótipo , Cirrose Hepática/diagnóstico , Cirrose Hepática/epidemiologia , República da Coreia/epidemiologia , Índice de Massa Corporal , Fatores de RiscoRESUMO
BACKGROUND: Whether the metabolically healthy obese (MHO) phenotype is a single, stable or a transitional, fluctuating state is currently unknown. The Mexican-Mestizo population has a genetic predisposition for the development of type 2 diabetes (T2D) and other cardiometabolic complications. Little is known about the natural history of metabolic health in this population. The aim of this study was to analyze the transitions over time among individuals with different degrees of metabolic health and body mass index, and evaluate the incidence of cardiometabolic outcomes according to phenotype. METHODS: The study population consisted of a metabolic syndrome cohort with at least 3 years of follow up. Participants were apparently-healthy urban Mexican adults ≥20 years with a body mass index (BMI) ≥20 kg/m2. Metabolically healthy phenotype was defined using the criteria of the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) metabolic syndrome criteria and the subjects were stratified into 4 groups according to their BMI and metabolic health. For cardiometabolic outcomes we estimated the incidence of cardiometabolic outcomes and standardized them per 1, 000 person-years of follow-up. Finally, to evaluate the risk for transition and development of cardiometabolic outcomes, we fitted Cox Proportional Hazard regression models. RESULTS: Amongst the 5541 subjects, 54.2% were classified as metabolically healthy and 45.8% as unhealthy. The MHO prevalence was 39.3%. Up to a third of the population changed from their initial category to another and the higher transition rate was observed in MHO (42.9%). We also found several novel factors associated to transition to metabolically unhealthy phenotype; socioeconomic status, number of pregnancies, a high carbohydrate intake, history of obesity and consumption of sweetened beverages. Similarly, visceral adipose tissue (VAT) was a main predictor of transition; loss of VAT ≥5% was associated with reversion from metabolically unhealthy to metabolically healthy phenotype (hazard ratio (HR) 1.545, 95%CI 1.266-1.886). Finally, we observed higher incidence rates and risk of incident T2D and hypertension in the metabolically unhealthy obesity (MUHO) and metabolically unhealthy lean (MUHL) phenotypes compared to MHO. CONCLUSIONS: Metabolic health is a dynamic and continuous process, at high risk of transition to metabolically unhealthy phenotypes over time. It is imperative to establish effective processes in primary care to prevent such transitions.
Assuntos
Fatores de Risco Cardiometabólico , Obesidade Metabolicamente Benigna/epidemiologia , Obesidade Metabolicamente Benigna/patologia , Adulto , Índice de Massa Corporal , Doenças Cardiovasculares/epidemiologia , Doenças Cardiovasculares/etiologia , Estudos de Coortes , Diabetes Mellitus Tipo 2/epidemiologia , Diabetes Mellitus Tipo 2/etiologia , Progressão da Doença , Feminino , Seguimentos , Humanos , Hipertensão/epidemiologia , Hipertensão/etiologia , Masculino , Síndrome Metabólica/epidemiologia , Síndrome Metabólica/etiologia , México/epidemiologia , Pessoa de Meia-Idade , Obesidade Metabolicamente Benigna/complicações , Obesidade Metabolicamente Benigna/diagnóstico , Fenótipo , Prevalência , Prognóstico , Fatores de Risco , População Urbana/estatística & dados numéricosRESUMO
PURPOSE: Job stress has proven to be a relevant cause of stress for adults, but its effect on the development of metabolic alterations in individuals with obesity is still poorly explored. We aimed to investigate the association between job stress and metabolically unhealthy obesity (MUO) phenotype in participants with obesity at the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) baseline assessment. METHODS: This study analyzed data collected at the baseline examination between 2008 and 2010. A total of 2371 individuals with obesity were included. Two metabolic phenotypes were characterized based on the US National Health and Nutrition Examination Survey criteria. The job stress scale was based on the Brazilian version of the Swedish Demand-Control-Support Questionnaire. The association between job stress domains and MUO phenotype was assessed by binary logistic models. RESULTS: In our sample, 1297 (54.7%) participants were women, mean age was 49.6 ± 7.1 years and 1696 (71.5%) had MUO. Low skill discretion was associated with MUO after adjustment for age, sex and race. However, in fully-adjusted models, the MUO phenotype was not associated with high job demand (odds ratio [OR] = 1.05; 95% confidence interval [95%CI] 0.82-1.35), low skill discretion (OR = 1.26; 95%CI 0.95-1.68), low decision authority (OR = 0.94; 95%CI 0.70-1.25) nor low social support (OR = 0.93; 95%CI 0.71-1.20). CONCLUSION: We found a significant association between low skill discretion and an adverse metabolic profile in models adjusted for age, sex and race. No associations were significant between job stress domains and the metabolic profile of individuals with obesity in full models.