Metabolically Healthy Obese Research Articles

Association between the transition to metabolically unhealthy obesity and lifestyle behavior: A nationwide cohort study.

To identify the characteristics of individuals transitioning from metabolically healthy obesity (MHO) to unhealthy obesity and the factors influencing the change. This is a nationwide cohort study using data from the National Health Insurance Service in South Korea. Individuals with obesity but metabolically healthy in 2009 and 2010 and those still obese 4 years later were selected. Sociodemographic, physical, metabolic, and health behavior variables were collected, and logistic regression was used to find an association with the transition. We analyzed 1,564,467 individuals, observing significant differences in all variables and the transition from MHO to unhealthy obesity. Among males, the transition was associated with smoking and drinking positively and physical activity negatively. Among females, drinking demonstrated a negative correlation. Regardless of age, regular exercise was negatively associated with the transition for all individuals. Except for older adults, all age groups showed a positive correlation with smoking and drinking. Considering the significant factors in the transition, it is essential to develop and implement interventions varied by gender and age to delay and prevent the change in metabolic status. The necessity of developing interventions enables individuals to engage in regular exercise, regardless of age and gender.

Rising Trends in Metabolically Healthy Obesity in Cancer Patients and Its Impact on Cardiovascular Events: Insights from a Contemporary Nationwide Analysis in the USA (2016-2020).

Background: Obesity or overweight raises the risk of developing 13 types of cancer, representing 40% of all cancers diagnosed in the United States annually. Given the ongoing debate surrounding the impact of metabolically healthy obesity (MHO) on cardiovascular outcomes, it is crucial to comprehend the incidence of Major Adverse Cardiovascular and Cerebrovascular Events (MACCEs) and the influence of MHO on these outcomes in cancer patients. Methods: Data of hospitalized cancer patients with and without obesity were analyzed from the National Inpatient Sample 2016-2020. Metabolically healthy patients were identified by excluding diabetes, hypertension, and hyperlipidemia using Elixhauser comorbidity software, v.2022.1. After that, we performed a multivariable regression analysis for in-hospital MACCEs and other individual outcomes. Results: We identified 3,111,824 cancer-related hospitalizations between 2016 and 2020. The MHO cohort had 199,580 patients (6.4%), whereas the MHnO (metabolically healthy non-obese) cohort had 2,912,244 patients (93.6%). The MHO cohort had a higher proportion of females, Blacks, and Hispanics. Outcomes including in-hospital MACCEs (7.9% vs. 9.5%; p < 0.001), all-cause mortality (6.1% vs. 7.5%; p < 0.001), and acute myocardial infarction (AMI) (1.5% vs. 1.6%; p < 0.001) were lower in the MHO cohort compared to the MHnO cohort. Upon adjusting for the baseline characteristics, the MHO group had lower odds of in-hospital MACCEs [adjusted odds ratio (AOR) = 0.93, 95% CI (0.90-0.97), p < 0.001], all-cause mortality [AOR = 0.91, 95% CI (0.87-0.94); p < 0.001], and acute ischemic stroke (AIS) [AOR = 0.76, 95% CI (0.69-0.84); p < 0.001], whereas there were higher odds of acute myocardial infarction (AMI) [AOR = 1.08, 95% CI (1.01-1.16); p < 0.001] and cardiac arrest (CA) [AOR = 1.26, 95% CI (1.01-1.57); p = 0.045] in the MHO cohort compared to the MHnO cohort. Conclusions: Hospitalized cancer patients with MHO exhibited a lower prevalence of in-hospital MACCEs than those with MHnO. Additional prospective studies and randomized clinical trials are imperative to validate these findings, particularly in stratifying MHO across various cancer types and their corresponding risks of in-hospital MACCEs.

Frequency of prediabetes in individuals with increased adiposity and metabolically healthy or unhealthy phenotypes.

To utilize the estimated glucose disposal rate (eGDR) index of insulin sensitivity, which is based on readily available clinical variables, namely, waist circumference, hypertension and glycated haemoglobin, to discriminate between metabolically healthy and unhealthy phenotypes, and to determine the prevalence of prediabetic conditions. Non-diabetic individuals (n = 2201) were stratified into quartiles of insulin sensitivity based on eGDR index. Individuals in the upper quartiles of eGDR were defined as having metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW) or metabolically healthy obesity (MHO) according to their body mass index, while those in the lower quartiles were classified as having metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW) and metabolically unhealthy obesity (MUO), respectively. The frequency of impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and IFG + IGT status was comparable among the MHNW, MHOW and MHO groups, while it increased from those with MUNW status towards those with MUOW and MUO status. As compared with participants with MHNW, the odds ratio of having IFG, IGT, or IFG + IGT was significantly higher in participants with MUOW and MUO but not in those with MUNW, MHOW and MHO, respectively. A metabolically healthy phenotype is associated with lower frequency of IFG, IGT, and IFG + IGT status across all body weight categories.

Follistatin as a Potential Biomarker for Identifying Metabolically Healthy and Unhealthy Obesity: A Cross-Sectional Study.

Metabolically healthy obesity (MHO) refers to obese individuals with a favorable metabolic profile, without severe metabolic abnormalities. This study aimed to investigate the potential of follistatin, a regulator of metabolic balance, as a biomarker to distinguish between metabolically healthy and unhealthy obesity. This cross-sectional study included 30 metabolically healthy and 32 metabolically unhealthy individuals with obesity. Blood samples were collected to measure the follistatin levels using an enzyme-linked immunosorbent assay (ELISA). While follistatin did not significantly differentiate between metabolically healthy (median 41.84 [IQR, 37.68 to 80.09]) and unhealthy (median 42.44 [IQR, 39.54 to 82.55]) individuals with obesity (p = 0.642), other biochemical markers, such as HDL cholesterol, triglycerides, C-peptide, and AST, showed significant differences between the two groups. Insulin was the most significant predictor of follistatin levels, with a coefficient of 0.903, followed by C-peptide, which exerted a negative influence at -0.624. Quantile regression analysis revealed nuanced associations between the follistatin levels and metabolic parameters in different quantiles. Although follistatin may not serve as a biomarker for identifying MHO and metabolically unhealthy obesity, understanding the underlying mechanisms that contribute to metabolic dysfunction could provide personalized strategies for managing obesity and preventing associated complications.

Resistance training and cardiometabolic risk in women with metabolically healthy and unhealthy obesity.

Despite some reported benefits, there is a low quality of evidence for resistance training (RT) improving metabolic health of individuals with overweight or obesity. We evaluated the impact of RT on body composition, cardiorespiratory fitness (CRF) and physical performance, lipid-lipoprotein profile, inflammation, and glucose-insulin homeostasis in 51 postmenopausal women versus 29 controls matched for age, obesity, and physical activity. Exercised women were further subdivided for comparison of RT effects into those presenting metabolically healthy obesity (MHO) and those with metabolically unhealthy obesity (MUHO) classified according to Karelis and Rabasa-Lhoret or an approach based on adipose tissue secretory dysfunction using the plasma adiponectin(A)/leptin (L) ratio. Participants followed a 4-month weekly RT program targeting major muscle groups (3 × 10 repetitions at 80% one repetition maximum (1-RM)). Percent fat marginally decreased and lean body mass increased (0.01<p<0.05) while CRF and muscular strength improved in all women, after RT (effect size (ES): 0.11-1.21 (trivial to large effects), p ˂ 0.01). Fasting plasma triacylglycerol and high-density lipoprotein-cholesterol levels slightly increased and decreased, respectively, in participants with MHO using the A/L ratio approach (ES: -0.47 to 1.07 (small to large effects), p ˂ 0.05). Circulating interleukin-6 soluble receptor decreased in both groups and soluble tumor necrosis factor receptor-1/soluble tumor necrosis factor receptor-2 in women with MUHO only, irrespective of definition (ES: -0.42 to-0.84 (small to large effects), p ˂ 0.05). Glucose-insulin homeostasis was unchanged regardless of group or definition. RT improved physical performance and body composition but had a lesser impact on cardiometabolic risk in women with obesity, irrespective of their metabolic phenotype.

Distinguishing health-related parameters between metabolically healthy and metabolically unhealthy obesity in women.

Obesity represents a global health crisis, yet a dichotomy is emerging with classification according to the metabolic state into metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). This study aimed to identify distinctive systemic clinical/endocrinological parameters between MHO individuals, employing a comprehensive comparative analysis of 50 biomarkers. Our emphasis was on routine analytes, ensuring cost-effectiveness for widespread use in diagnosing metabolic health. The study included 182 women diagnosed with obesity referred for bariatric surgery at the Endocrinology, Diabetes, and Metabolism Service of São João Hospital and University Centre in Portugal. MUO was defined by the presence of at least one of the following metabolic disorders: diabetes, hypertension, or dyslipidemia. Patients were stratified based on the diagnosis of these pathologies. Significantly divergent health-related parameters were observed between MHO and MUO patients. Notable differences included: albumin (40.1 ± 2.2 vs 40,98 ± 2.6 g/L, p value = 0.017), triglycerides (110.7 ± 51.1 vs 137.57 ± 82.6 mg/dL, p value = 0.008), glucose (99.49 ± 13.0 vs 119.17 ± 38.9 mg/dL, p value < 0.001), glycated hemoglobin (5.58 ± 0.4 vs 6.15 ± 1.0%, p value < 0.001), urea (31.40 ± 10.0 vs 34.61 ± 10.2 mg/dL, p value = 0.014), total calcium (4.64 ± 0.15 vs 4.74 ± 0.17 mEq/L, 1 mEq/L = 1 mg/L, p value < 0.001), ferritin (100.04 ± 129.1 vs 128.55 ± 102.1 ng/mL, p value = 0.005), chloride (104.68 ± 1.5 vs 103.04 ± 2.6 mEq/L, p value < 0.001), prolactin (13.57 ± 6.3 vs 12.47 ± 7.1 ng/mL, p value = 0.041), insulin (20.36 ± 24.4 vs 23.87 ± 19.6 μU/mL, p value = 0.021), c peptide (3.78 ± 1.8 vs 4.28 ± 1.7 ng/mL, p value = 0.003), albumin/creatinine ratio (15.41 ± 31.0 vs 48.12 ± 158.7 mg/g creatinine, p value = 0.015), and whole-body mineral density (1.27 ± 0.1 vs 1.23 ± 0.1 g/cm2, p value = 0.016). Our findings highlight potential additional parameters that should be taken into consideration alongside the commonly used biomarkers for classifying metabolic health in women. These include albumin, urea, total calcium, ferritin, chloride, prolactin, c-peptide, albumin-creatinine ratio, and whole-body mineral density. Moreover, our results also suggest that MHO may represent a transitional phase preceding the development of the MUO phenotype.

Metabolic Obesity Phenotypes and Incident Cardiovascular Outcomes in Middle-Aged and Older Korean Adults: A Longitudinal 10-Year Analysis of the Korean Genome and Epidemiology Study.

Background: This study investigated the association of four metabolic obesity phenotypes with incident coronary artery disease and stroke in a large-scale, community population-based, prospective Korean cohort observed for over 10 years. Methods: The study participants included 7374 adults aged 40-69 years, drawn from the Korean Genome and Epidemiology Study. Participants with different metabolic obesity phenotypes were categorized according to body weight and metabolic health status into four groups: metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy nonobese (MUHNO), and metabolically unhealthy obese (MUHO). Combined cardiovascular events were defined as coronary artery disease and stroke. We used multivariate Cox proportional hazards regression models to prospectively assess hazard ratios (HRs) with 95% confidence intervals (CIs) for incident coronary artery disease or stroke over 10 years after the baseline survey. Results: During the follow-up period, newly developed coronary artery disease, stroke, and combined cardiovascular events were diagnosed in 151 (2.0%), 137 (1.9%), and 283 (3.8%) participants, respectively. After adjusting for confounding variables, the HRs (95% CIs) for incident combined cardiovascular events were 1.81 (1.34-2.46) in the MUHO group, 1.29 (0.92-1.81) in the MUHNO group, and 1.21 (0.81-1.79) in the MHO group compared with those in the MHNO group. Conclusions: This study revealed distinct risks associated with four metabolic obesity phenotypes concerning incident coronary artery disease and stroke. After adjusting for potential confounding variables, the results indicated that MUHO, but not MUHNO or MHO, showed a higher risk of developing coronary artery disease and stroke than MHNO.

Significance of single-nucleotide variants of anorexigenic hormone genes in childhood obesity

Obesity-induced dysregulation of hypothalamic neurons is not completely eliminated by restoring body weight, therefore the most urgent task of modern precision medicine is to predict the trajectory of development of metabolic disorders associated with obesity in children. The aim of the study was to determine the level of association of single-nucleotide variants of genes that determine eating behavior – Neuronal growth regulator 1, Fat mass and obesity associated gene, Glucagon-like peptide-1 receptor, ghrelin, leptin receptor, cholecystokinin, in the development of metabolically unhealthy obesity. 252 obese children aged 6-18 years were examined. The main group (n=152) consisted of children with metabolically unhealthy obesity (MUO) according to Identification and prevention of Dietary- and Lifestyle-induced Health Effects in Children and Infants 2014 criteria. The control group (n=100) consisted of children with metabolically healthy obesity (MHO). All children underwent a general clinical, immunobiochemical examination at the Synevo laboratory (Ukraine). Whole-genome sequencing (CeGat, Germany) was performed in 31 children of the primary and 21 children of the control group. Static analysis: variance analysis ANOVA, method of estimating data dispersion, ROC-analysis, method of testing statistical hypotheses. The level of single nucleotide variants association of anorexigenic hormone genes with MUO that exceeded the threshold accepted by 75% of the available data was, respectively, in ascending order: leptin receptor (LEPR) rs1137101 (40.38%), Glucagon-like peptide-1 receptor (GLP1R) rs1126476 (40.38%), GLP1R rs2235868 (42.31%), GLP1R rs1042044 (42.31%), LEPR rs3790435 (48.08%), cholecystokinin (CCK) rs754635 (50%), LEPR rs2186248 (55.76%), GLP1R rs6918287 (55.76%). Genotypes of the GLP1R gene, such as CC rs10305421 determine insulin resistance (F=5.6); GA/AA rs3765468 – meta-inflammation (F=5.8); AA rs6918287 – basal hyperglycemia (F=6.3) and triglyceridemia (F=51.3), p&lt;0.05. Single-nucleotide variants of the gene GLP1R rs6918287, LEPR rs2186248, CCK rs754635 of the anorexic hormones that control eating behavior are highly associated with the presence of metabolically unhealthy obesity in children.

Cardiometabolic profiles and proteomics associated with obesity phenotypes in a longitudinal cohort of young adults

To assess cardiometabolic profiles and proteomics to identify biomarkers associated with the metabolically healthy and unhealthy obesity. Young adults (N = 156) enrolled were classified as not having obesity, metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO) based on NCEP ATP-III criteria. Plasma proteomics at study entry were measured using Olink Cardiometabolic Explore panel. Linear regression was used to assess associations between proteomics and obesity groups as well as cardiometabolic traits of glucose, insulin, and lipid profiles at baseline and follow-up visits. Enriched biological pathways were further identified based on the significant proteomic features. Among the baseline 95 (61%) and 61 (39%) participants classified as not having obesity and having obesity (8 MHO and 53 MUHO), respectively. Eighty of the participants were followed-up with an average 4.6 years. Forty-one proteins were associated with obesity (FDR < 0.05), 29 of which had strong associations with insulin-related traits and lipid profiles (FDR < 0.05). Inflammation, immunomodulation, extracellular matrix remodeling and endoplasmic reticulum lumen functions were enriched by 40 proteins. In this study population, obesity and MHO were associated with insulin resistance and dysregulated lipid profiles. The underlying mechanism included elevated inflammation and deteriorated extracellular matrix remodeling function.

Prevalence, Risk Factors, and Metabolic Characteristics of Metabolically Healthy Obesity in Patients Seeking Bariatric Surgery: A Cohort Study.

Bariatric surgery is an effective treatment for morbid obesity. However, a subset of individuals seeking bariatric surgery may exhibit a metabolically healthy obesity (MHO) phenotype, suggesting that they may not experience metabolic complications despite being overweight. This study aimed to determine the prevalence and metabolic features of MHO in a population undergoing bariatric surgery. A representative sample of 665 participants aged 14 or older who underwent bariatric surgery at our center from January 1, 2010 to January 1, 2020 was included in this cohort study. MHO was defined based on specific criteria, including blood pressure, waist-to-hip ratio, and absence of diabetes. Among the 665 participants, 80 individuals (12.0%) met the criteria for MHO. Female gender (P = .021) and younger age (P < .001) were associated with a higher likelihood of MHO. Smaller weight and BMI were observed in individuals with MHO. However, a considerable proportion of those with MHO exhibited other metabolic abnormalities, such as fatty liver (68.6%), hyperuricemia (55.3%), elevated lipid levels (58.7%), and abnormal lipoprotein levels (88%). Approximately 1 in 8 individuals referred for bariatric surgery displayed the phenotype of MHO. Despite being metabolically healthy based on certain criteria, a significant proportion of individuals with MHO still exhibited metabolic abnormalities, such as fatty liver, hyperuricemia, elevated lipid levels, and abnormal lipoprotein levels, highlighting the importance of thorough metabolic evaluation in this population.

Metabolic Health, Overweight or Obesity, and Depressive Symptoms among Older Australian Adults.

The relationship between overweight or obesity and depressive symptoms in individuals with or without cardio-metabolic abnormalities is unclear. In a cross-sectional study we examined the odds of experiencing depressive symptoms in overweight or obese older adults with or without metabolic abnormalities. The participants included 3318 older adults from the Hunter Community Study Cohort with a Body Mass Index (BMI) ≥ 18.5 kgm2, stratified by BMI and metabolic health risk. Obesity was defined as BMI ≥ 30 kgm2 and metabolically healthy as the absence of metabolic risk factors, according to International Diabetic Federation criteria for metabolic syndromes. Moderate to severe depressive symptoms were defined as a Centre for Epidemiological Studies Depression Scale (CES-D) score ≥ 16. Compared to the metabolically healthy normal weight (MHNW) group, the odds of experiencing moderate/severe depressive symptoms were higher in those classified as a metabolically unhealthy normal weight (MUNW) (odds ratio (OR) = 1.25, 95% Confidence Interval (CI): 0.76-2.06) or metabolically unhealthy obesity (MUO) (OR = 1.48, 95% CI: 1.00-2.19), but not in those classified as metabolically unhealthy overweight (MUOW) (OR = 0.96, 95% CI: 0.63-1.45), metabolically healthy overweight (MHOW) (OR = 0.80, 95% CI: 0.51-1.26), and metabolically healthy obesity (MHO) (OR = 1.03, 95% CI: 0.65-1.64). Compared with MHNW males, the odds of moderate/severe depressive symptoms were increased in all other BMI category-metabolic health groups for males and females. Our relatively small sample size and cross-sectional design did not allow us to robustly establish causality. The odds of experiencing moderate/severe depressive symptoms were increased in metabolically unhealthy older adults regardless of normal weight or obesity, with the odds of having moderate/severe depressive symptoms being higher in females than in males.

Abstract P332: Metabolically Healthy Obesity is Associated With Higher Levels of Executive Function in Middle-Aged Adults: The Bogalusa Heart Study

Introduction: Obesity in midlife is associated with an increased risk of cognitive decline. It remains unclear if there is a difference in cognitive function between individuals with obesity and metabolic dysfunction (metabolically abnormal obesity - MAO) versus those with metabolically healthy obesity (MHO). We assessed the relationship between MHO (vs MAO) and cognitive function in mid-life among Black and White individuals in the Bogalusa Heart Study. Methods: The Bogalusa Heart Study is a longitudinal cohort exploring the natural history of cardiovascular disease among Black and White individuals in Bogalusa, Louisiana. This cross-sectional analysis included 659 participants with obesity, defined as BMI ≥ 30 kg/m 2 . Metabolic abnormality was defined as the presence of one or more of the following: systolic blood pressure ≥ 130 mm Hg, diastolic blood pressure ≥ 85 mm Hg, taking blood pressure lowering medication, triglycerides ≥ 150 mg/dL, HDL-C &lt; 40 mg/dL (men) or &lt; 50 mg/dL (women), taking lipid-lowering medication, fasting plasma glucose ≥ 100 mg/dL, or taking diabetes medication. Healthy metabolic status was defined as the absence of blood pressure, lipid, and glycemic abnormalities. Cognitive function was measured using a total of 9 neuropsychological tests assessing attention/information processing speed, executive function, and episodic memory. Linear regression models were used to determine the association between MHO and a demographically standardized global cognitive score and individual domain-based z-scores adjusting for smoking status and education. Results: Participants had a mean age of 47.8 ± 5.3 years, 42.7% self-identified as Black, and 64.1% were female. The prevalence of MHO was 9.9%. MHO was associated with higher levels of executive function compared with MAO (β=0.46; SE=0.19; p=0.0145). No significant differences were observed between MHO and MAO participants on global cognitive score, processing speed, or episodic memory. Conclusions: Our study found that MHO is associated with better levels of executive function in midlife. While additional studies are needed, these findings suggest that interventions that reduce metabolic abnormalities related to blood pressure, lipids, and glucose may reduce obesity-related decreases in executive function among middle-aged individuals with obesity.

Vitamin D and the Metabolic Phenotype in Weight Loss After Bariatric Surgery: A Longitudinal Study.

To evaluate the influence of vitamin D (VD) concentrations coupled with metabolic phenotypes preoperatively and 6months after Roux-en-Y gastric bypass (RYGB) on body variables and weight loss. A longitudinal, retrospective, analytical study comprising 30 adult individuals assessed preoperatively (T0) and 6months (T1) after undergoing Roux-en-Y gastric bypass. The participants were distributed preoperatively into metabolically healthy obese (MHO) and metabolically unhealthy obese individuals (MUHO) according to the HOMA-IR classification, as well as the adequacy and inadequacy of vitamin D concentrations in the form of 25(OH)D. All participants were assessed for weight, height, body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), visceral adiposity index (VAI), body circularity index (BCI), body adiposity index (BAI), weight loss, and assessment of 25(OH)D and 1,25(OH)2D concentrations using high-performance liquid chromatography with an ultraviolet detector (HPLC-UV). The statistical program used was SPSS version 21. VD adequacy and a healthy phenotype in the preoperative period may play an important role concerning body fat distribution, as the body averages for WHtR (0.020*) and BCI (0.020*) were lower in MHO participants. In comparison, those with VD inadequacy and MUHOs had higher BAI averages (0.000*) in the postoperative period. Furthermore, it is possible that VD inadequacy before and after RYGB, even in the presence of an unhealthy phenotype, may contribute to the increase in VAI values (0.029*) after this surgery. Only those with inadequate VD and MUHOs had higher 25(OH)D concentrations. Besides, this unhealthy phenotype had a greater reduction in BMI in the early postoperative period (p < 0.001). This study suggests that VD adequacy and the presence of a healthy phenotype appear to have a positive impact on the reduction of visceral fat in the context of pre- and postoperative obesity. In addition, there was a greater weight reduction in those with VD inadequacy and in MUHO, which suggests that the volumetric dilution effect of VD and catabolism after bariatric surgery is more pronounced in this specific metabolic phenotype.

Assessment of the role of albuminuria and uromodulin in the early diagnosis of renal function disorders in some types of obesity phenotypes

The aim: to study of the relationship of biological markers reflecting damage of the kidneys with its functional state, as well as with clinical, metabolic, hormonal parameters and immunoinflammatory processes in obesity phenotypes.Patients and Methods: The study involved 224 obese Uzbek women who were divided into 2 groups according to the recommended criteria for metabolic syndrome: group 1 consisted of 133 women diagnosed with metabolic complicated obesity, average age 42.0±0.5; Group 2 consisted of 91 women diagnosed with metabolic healthy obesity, average age 41.7±0.7. The control group consisted of 45 healthy volunteers (women, mean age 43.2±0.8, body mass index ˂ 30 kg/m2, waist circumference less than 80 cm). In the observation groups, anthropometric indicators, blood pressure, biochemical tests and blood lipid spectrum, levels of leptin, insulin, cystatin C and uromodulin in the blood serum, gradations of microalbuminuria in urine were determined, the glomerular filtration rate was calculated for cystatin C and creatinine and the obtained indicators were compared.Results. In both obesity phenotypes, the amount of microalbuminuria and cystatin C significantly increased in group 1 compared to these indicators in group 2 and the control group, and the amount of uromodulin in the blood serum, on the contrary, decreased compared to the indicators in group 2 and control group (r ˂ 0.001) . An increase in the gradation of microalbuminuria and cystatin C and a decrease in the amount of uromodulin in the blood serum in both groups was expressed by a decrease in the estimated glomerular filtration rate, which was clearly expressed in group 1 (χ2 = 4.5, r = 0.034). Also, an increase in body mass index was characterized by an increase in cardiometabolic disorders, an increase in the gradation of microalbuminuria, a decrease in the level of uromodulin in the blood serum and cytokinemia (p ˂ 0.001).Conclusion. In both obesity phenotypes, an increase in the degree of obesity was manifested by an increase in the level of cardiometabolic risk, as well as an increase in subclinical kidney damage. It is considered appropriate to determine the amount of uromodulin and cystatin C in blood serum and assess the gradation of microalbuminuria in the early diagnosis of renal dysfunction in obesity.

Metabolic health's central role in chronic kidney disease progression: a 20-year study of obesity-metabolic phenotype transitions

This study investigates the risk of chronic kidney disease (CKD) across four metabolic phenotypes: Metabolically Healthy-No Obesity (MH-NO), Metabolically Unhealthy-No obesity (MU-NO), Metabolically Healthy-Obesity (MH-O), and Metabolically Unhealthy-Obesity (MU-O). Data from the Tehran Lipid and Glucose Study, collected from 1999 to 2020, were used to categorize participants based on a BMI ≥ 30 kg/m2 and metabolic health status, defined by the presence of three or four of the following components: high blood pressure, elevated triglycerides, low high-density lipoprotein, and high fasting blood sugar. CKD, characterized by a glomerular filtration rate < 60 ml/min/1.72 m2. The hazard ratio (HR) of CKD risk was evaluated using Cox proportional hazard models. The study included 8731 participants, with an average age of 39.93 years, and identified 734 incidents of CKD. After adjusting for covariates, the MU-O group demonstrated the highest risk of CKD progression (HR 1.42–1.87), followed by the MU-NO group (HR 1.33–1.67), and the MH-O group (HR 1.18–1.54). Persistent MU-NO and MU-O posed the highest CKD risk compared to transitional states, highlighting the significance of exposure during early adulthood. These findings emphasize the independent contributions of excess weight and metabolic health, along with its components, to CKD risk. Therefore, preventive strategies should prioritize interventions during early-adulthood.

Joint effect of BMI and metabolic status on mortality among adults: a population-based longitudinal study in United States

We explored the joint effects of different metabolic obesity phenotypes on all-cause and disease-specific mortality risk among the American population. Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 1999–2018. Mortality outcome data were from mortality files linked to National Death Index record and follow-up information was up to December 31, 2019. 50,013 participants were finally included. Four metabolic obesity phenotypes were defined based on obesity and metabolic status: metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), metabolically healthy non-obese (MHNO), and metabolically unhealthy non-obese (MUNO). Population-weighted Cox proportional hazards models were used to explore the all-cause and disease-specific mortality risk of metabolic obesity phenotypes. The all-cause mortality risk of MUO and MUNO was significantly higher than MHNO. MUNO was associated with a significantly increased risk of death from heart disease (HR: 1.40, 95% CI 1.16–1.70), hypertension (HR: 1.68, 95% CI 1.34–2.12), diabetes (HR: 2.29, 95% CI 1.67–3.15), and malignant neoplasms (HR:1.29, 95% CI 1.09–1.53). Metabolic unhealth significantly increased the risk of all-cause mortality, regardless of obesity status. Among individuals with metabolic unhealthy status, obesity significantly reduced the risk of all-cause mortality (HR: 0.91, 95% CI 0.85–0.98). Our study highlights the importance of identifying and characterizing metabolic obesity phenotypes in obese and metabolically abnormal patients, as well as healthy adults. Comprehensive evaluation of obesity and metabolic status is necessary to adopt appropriate interventions and treatment measures and maximize patient benefit.

Abstract TP262: Trends, Odds, Burdens and Outcomes of Metabolically Healthy Obesity in Stroke Related Hospitalizations of Elderly Patients - A Nationwide Analysis, 2016-2019

Background: Obesity has been associated with an increase in the risk of stroke and poor outcomes. Meanwhile, Metabolically healthy obesity (MHO) trends are understudied in association with stroke. In this study, we aim to analyze the MHO trends and outcomes with respect to Stroke. Methods: We queried the National Inpatient Sample (2016-2019) to identify Stroke hospitalizations in the elderly population (%E2%89%A565 years) with vs without MHO by using ICD-10 codes after excluding patients with Hypertension, analyze, and Diabetes Mellitus. Patients were categorized into a metabolically healthy obese MHO+ve cohort, BMI&gt; 30, and MHO-ve cohort, BMI&lt;30. Trends, demographics, comorbidities, and outcomes were then compared between the two cohorts. Results: Overall Prevalence of stroke was higher in the MHO-ve cohort (2.4% vs 1.4% p&lt;0.001) compared to the MHO+ve cohort. MHO-ve cohort often consisted of higher median age (78 vs 73 years), Males (48.2% vs 36.4%), Hispanics (5.1% vs 4.7%), whites (83.8% vs 82.3%), Asians (2.4% vs 1.1%) vs MHO +ve cohort (p&lt;0.001). The rate of death (15.9% vs 14.4%), Home health care requirements (16.6% vs 12.4%) was also higher in the MHO-ve cohort vs MHO+ve cohort. Conversely, the MHO+ve cohort had higher rates of smokers, Prior MI, Hypothyroidism, CKD, and OSA in comparison to the MHO-ve cohort. Univariate and Multivariate regression analysis adjusted for confounders did not show any significant association between Stroke and MHO. Conclusion: Excluding other cardiovascular disease risk factors such as hypertension, diabetes mellitus, and hyperlipidemia, the non-significant difference in in-hospital mortality between elderly stroke patients with vs without MHO suggests that MHO might not be a significant independent predictor of short-term mortality. Other factors likely influence this relationship. Further research is warranted for the investigation of the factors influencing the absence of a relationship between stroke and MHO.

Abstract TMP100: Acute Ischemic Stroke in Young Adults: A Comparative Analysis of Outcomes and Mortality in Metabolically Healthy Obese vs. Normal Weight Individuals, 2016-2019 Cohort

Introduction: Rising obesity rates and the increasing prevalence of stroke in the metabolically healthy obese (MHO) necessitate examining its association in younger (18-44 year) populations. Analyzing acute ischemic stroke (AIS) trends and outcomes in MHO vs. metabolically healthy normal weight (MH-NW). Methods: Data from the National Inpatient Sample (2016-2019) was analyzed to identify young MHO and MH-NW AIS patients using ICD-10 codes. Demographics, trends, and outcomes were compared using multivariable statistical approaches. Results: Of 26,949,310 young metabolically healthy individuals studied between 2016 and 2019, 47,795 had AIS, 4,985 were MHO, and 42,810 were MH-NW. The median AIS patient age was 35. The MHO cohort was primarily female, white, in the lowest income quartile, with private insurance. Most were hospitalized in southern US urban teaching hospitals. Notably, the MHO cohort had higher rates of specific comorbidities like depression, chronic pulmonary disease, and obstructive sleep apnea but lower rates of drug abuse and peripheral vascular disease. The in-hospital mortality rate was significantly lower in MHO patients (6.0% vs. 8.6%). Hospitalization length and cost did not significantly differ between groups. From 2016 to 2019, AIS incidence rose slightly, significant only for the MH-NW cohort. Adjusted multivariable odds ratios revealed no significant difference in AIS occurrence between MHO and MH-NW overall (aOR: 1.02, p=0.701), in males (aOR: 0.88, p=0.161) or females (aOR: 1.06, p=0.363). However, MHO-associated AIS had lower odds of in-hospital mortality than MH-NW (aOR: 0.60, p=0.021). Conclusion: AIS incidence was consistent across young metabolically healthy groups regardless of obesity status. However, we noted a paradoxical 40% reduction in in-hospital mortality in the MHO cohort. This underscores the complex MHO-stroke relationship in young adults, signaling a need for in-depth research and tailored interventions.

Prevalence of metabolically healthy obesity and healthy overweight and the associated factors in southern Iran: A population-based cross-sectional study.

Obesity is considered a major growing threat to public health which could negatively affect the quality of life. The current cross-sectional study was conducted to investigate the population-based prevalence of metabolically healthy obesity (MHO) and healthy overweight (MHOW) and associated factors in southern Iran. Baseline data from the Pars Cohort Study was analyzed. Metabolically healthy participants were identified based on the definition of the American Heart Association for the metabolic syndrome. The prevalence of MHOW and MHO and their 95% confidence intervals were estimated. Poisson regression was applied for the calculation of prevalence ratios (PRs). Gender- and age-standardized prevalences of MHOW and MHO were 6.3% (6.0%-6.6%) and 2.3% (2.1%-2.5%), respectively. The following factors were associated with being MHOW compared with those with normal weight: Being younger, female gender (1.31, 1.20-1.43), higher socioeconomic status, being noncurrent cigarette smoker (1.27, 1.11-1.45), low level of physical activity (1.14, 1.03-1.25), having normal overweight during adolescence, and overweight (1.35, 1.24-1.48) or obesity (1.68, 1.53-1.86) during young adulthood. We also found strong associations between MHO and younger age groups, female gender (2.87, 2.40-3.42), being married (1.57, 1.08-2.27), Fars ethnicity (1.25, 1.10-1.43), higher socioeconomic status, ever use of tobacco (1.14, 1.00-1.30), never use of opium (1.85, 1.19-2.86), lower physical activity (1.45, 1.20-1.72), being normal weight in 15-year body pictogram and being overweight (1.87, 1.59-2.20) or obese (3.20, 2.74-3.72) in 30-year body pictogram when considering those with normal weight or MHO. Potentially modifiable factors including physical activity should be more emphasized. Furthermore, our study issued that it would be more reasonable that the prevention of unhealthy obesity be initiated before the development of MHO, where there are more protective factors and they could be more effective.

Body Composition Indicators Jointly Predict Metabolic Unhealthy Phenotypes in Young and Middle-Aged Obese Individuals: A Cross-Sectional Quantitative Computed Tomography Study.

The main aim of this study is to analyze the relationship between body composition indices and metabolic unhealthy phenotypes in young and middle-aged obese patients and to assess their joint predictive ability. A cross-sectional study method was used to select 207 patients who were proposed to undergo weight loss surgery for morbid obesity from March to November 2022. Total adipose tissue (TAT), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), liver fat content (LFC), cross-sectional area (CSAmuscle), and intermuscular adipose tissue (CSAIMAT) of paraspinal muscles were measured using quantitative computed tomography. Participants were categorized into two groups: metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). The receiver operating characteristic curve comprised body composition variables that correlated with MUO, and the area under the curve (AUC) was calculated to compare their prediction capacity for MUO. There were 71 patients with MHO (34.3%) and 136 patients with MUO (65.7%). The VAT, VAT/TAT ratio, LFC, and CSAmuscle was higher in MUO patients than in MHO (all P < 0.001), and SAT was lower than in MHO (P = 0.008). And all of these metrics were correlated with MUO (all P < 0.05). Inclusion of these body composition metrics in the ROC analysis showed that the AUC values for SAT, VAT, VAT/TAT ratio, LFC and CSAmuscle were 0.615, 0.663, 0.727, 0.694, 0.671, respectively, and the combination of the VAT/TAT ratio and the LFC had the ability to predict MUO best (AUC=0.746, P = 0.025). The combined use of VAT/TAT ratio and LFC is superior to the use of these two metrics alone in terms of their ability to predict the MUO, providing a more accurate approach to the management and prevention of obesity-related metabolic risk.