Metabolically Healthy Obese Group Research Articles

Impact of bariatric surgery on carotid intima-media thickness and arterial stiffness in metabolically healthy obesity: a prospective study.

Cardiovascular disease is one of the leading causes of mortality in patients with obesity. Metabolically healthy obesity (MHO), in which people do not have metabolic disorders, is a transient state of obesity. However, over the long term, a proportion of individuals with MHO develop metabolic syndrome (MetS). We aimed to investigate the effect of substantial weight loss following bariatric surgery in MHO on carotid intima-media thickness (CIMT) and pulse-wave velocity (PWV), which are independent predictors of subclinical atherosclerosis. This prospective study included 38 patients (34 women, four men) undergoing bariatric surgery who had severe obesity but without comorbidities (hypertension, diabetes, and hyperlipidemia), and 28 control individuals who were matched for age and sex. CIMT and PWV of the left common carotid artery were measured. At 12-month follow-up after bariatric surgery, measurements were repeated in the 38 patients with obesity. Mean baseline body mass index (BMI) in the MHO group was 40.55 ± 3.59kg/m2, which decreased by 33.1% after bariatric surgery. Compared with controls, CIMT and PWV were increased in MHO (543.53 ± 55.29 vs. 407.82 ± 53.09μm, 6.70 ± 1.22 vs. 5.45 ± 0.74m/s, respectively; all P < 0.001). At 12 months post-bariatric surgery, CIMT in MHO was lower than baseline (466.79 ± 53.74 vs. 543.53 ± 55.29μm, P = 0.009), but PWV was not significantly different from baseline (6.27 ± 0.86 vs. 6.70 ± 1.22m/s, P = 0.132). Multivariate regression showed that BMI was an independent predictor of CIMT (β = 0.531, P < 0.001). Carotid artery structure and function were impaired in MHO, and improved carotid artery structure was associated with weight loss in MHO after bariatric surgery.

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.

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.

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.

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.

Computed tomography evaluation of skeletal muscle quality and quantity in people with morbid obesity with and without metabolic abnormality.

We investigated the differences in quantity and quality of skeletal muscle between metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO) individuals using abdominal CT. One hundred and seventy-two people with morbid obesity who underwent bariatric surgery and 64 healthy control individuals participated in this retrospective study. We divided the people with morbid obesity into an MHO and MUO group. In addition, nonobese metabolic healthy people were included analysis to provide reference levels. CT evaluation of muscle quantity (at the level of the third lumbar vertebra [L3]) was performed by calculating muscle anatomical cross-sectional area (CSA), which was normalized to patient height to produce skeletal muscle index (SMI). Muscle quality was assessed as skeletal muscle density (SMD), which was calculated from CT muscle attenuation. To characterize intramuscular composition, muscle attenuation was classified into three categories using Hounsfield unit (HU) thresholds: -190 HU to -30 HU for intermuscular adipose tissue (IMAT), -29 to +29 HU for low attenuation muscle (LAM), and +30 to +150 HU for normal attenuation muscle (NAM). People with morbid obesity comprised 24 (14%) MHO individuals and 148 (86%) MUO individuals. The mean age of the participants was 39.7 ± 12.5 years, and 154 (65%) participants were women. MUO individuals had a significantly greater total skeletal muscle CSA than MHO individuals in the model that adjusted for all variables. Total skeletal muscle SMI, SMD, NAM index, LAM index, and IMAT index did not differ between MHO and MUO individuals for all adjusted models. Total skeletal muscle at the L3 level was not different in muscle quantity, quality, or intramuscular composition between the MHO and MUO individuals, based on CT evaluation. MHO individuals who are considered "healthy" should be carefully monitored and can have a similar risk of metabolic complications as MUO individuals, at least based on an assessment of skeletal muscle.

Abstract 16025: Impact of COVID-19 on Major Adverse Cardiovascular and Cerebrovascular Events in Metabolically Healthy Obese (MHO) Individuals: A National Inpatient Sample Analysis, 2020

Background: The obesity paradox is a phenomenon observed in certain chronic diseases, particularly cardiovascular diseases, where individuals with obesity have better outcomes compared to those of normal weight. We aimed to study how COVID-19 affects MACCE results in metabolically healthy obese (MHO) individuals who have a BMI &gt;30. Methods: Using the National Inpatient Sample (2020) and appropriate ICD-10-CM codes, we identified adult hospitalizations with COVID-19 and grouped them into two cohorts with and without obesity (MHO+ and MHO-, omitting hypertension, diabetes, and hyperlipidemia). MACCE (all-cause inpatient mortality, cardiac arrest, including ventricular fibrillation, and stroke) in COVID-19-related hospitalizations was the primary outcome. Results: 84,145 (21.9%) of 397,040 COVID-19 hospitalizations were MHO+. The MHO+ group was younger (median 43 vs 52 years), female (56.9% vs. 49.4%), black (19.4% vs 15.1%), Hispanic (35.2% vs 30.5%), and Native American (1.5% vs 1.2%) (p&lt;0.001). Tobacco use disorder, past PCI, prior VTE, depression, chronic pulmonary disease, hypothyroidism, and other thyroid problems were more common in MHO+ patients (p&lt;0.05). MHO+ patients were discharged routinely (76% vs. 66.7%) but stayed longer (5 days vs 4 days). After correcting for baseline variables, the MHO+ cohort had a lower rate of MACCE than the MHO- cohort (8% vs. 11.3%, OR 0.81, 95CI 0.74-0.89, p&lt;0.001), and lower all-cause mortality (6.6 % vs 9.4%) compared to the MHO- cohort. On subgroup analysis, females had lower odds (aOR 0.79) than males (aOR 0.82), older individuals ≥65 years old had lower odds (aOR 0.71) vs 45-64 (aOR 0.79), and race- wise comparison, whites had lower odds of MACCE events (aOR 0.76). Conclusions: MHO+ patients had lower odds of MACCE events. The MHO group was younger, suggesting higher cardiorespiratory fitness, which could explain the obesity paradox and reduced odds of MACCE outcomes.

From Metabolically Healthy Obesity to Metabolically Unhealthy Obesity Populations: Decreased Bone Turnover Bioactivity.

A bone turnover marker reflects bone bioactivity. The effects of metabolically healthy compared with metabolically unhealthy obesity phenotypes on bone metabolism are not well understood. The aim of the study was to evaluate differences of bone transformation indexes in these two obesity phenotypes. A total of 419 obese subjects were recruited, 64 with metabolically healthy obesity (MHO) and 351 with metabolically unhealthy obesity (MuHO). BTMs and clinical parameters were measured. Bone metabolism indexes, including tartrate resistant acid phosphatase (TRACP, p < 0.05), β carboxyl terminal peptide of collagen (β-CTX, p < 0.01), and bone alkaline phosphatase (BAP, p < 0.01), were higher in subjects with MHO than MuHO, but parathyroid hormone (PTH) was lower (p < 0.05). The between-group difference in serum calcium was not significant. Low bone turnover activity was associated with significant hyperglycemia, insulin resistance, and body fat index (p < 0.05). Multivariate logistic regression found that TRACP, β-CTX, and BAP were independently associated with the presence of MHO. Receiver operating characteristic curve analysis found that the maximum area under the curve value for the definition of MHO was (0.8221) and was obtained when sex, age, body mass index (BMI), TRACP, β-CTX and BAP were included simultaneously, resulting in a sensitivity of 81.25% and specificity: 72.3%. The MHO group had significantly increased circulating TRACP and β-CTX compared with the MuHO group and BAP levels were within the physiological range. Obesity with the metabolically healthy phenotype had slightly increased bone turnover activity that may be an early compensatory response of skeletal metabolism to the increased BMI.

Correlation analysis of obesity phenotypes with leptin and adiponectin

Obesity can be categorized as metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). However, individuals with MHO are characterized by the absence of metabolic syndrome (MS) and appear to have lower inflammation levels compared to MUO. This study aimed to investigate the association of obesity phenotypes with leptin (LEP) and adiponectin (ADP). According to the inclusion and exclusion criteria, we selected 178 subjects from the previous cross-sectional survey. Based on the body mass index (BMI) and diagnostic criteria of MS, we divided the individuals into three groups, including healthy control group (HC group), metabolically healthy obesity group (MHO group) and metabolically unhealthy obesity group (MUO group). The concentrations of LEP and ADP in serum were measured, and the association of these two cytokines with different obesity phenotypes were subsequently analyzed. Compared to both the HC and MHO groups, the MUO group showed significantly higher BMI, waist circumference (WC), waist-hip ratio (WHR), triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), fasting plasma glucose (FPG), homeostasis model assessment of insulin resistance (Homa-IR) and blood pressure (P < 0.05). In contrast, serum high-density lipoprotein cholesterol (HDL-C) was notably lower in the MUO group (P < 0.05). ADP was found to have a positive correlation with systolic blood pressure (SBP) and a negative correlation with FPG in the MHO group. In the MUO group, LEP demonstrated a positive correlation with fasting insulin (FINS) and Homa-IR, while ADP showed a positive correlation with TC and SBP. Linear regression analysis further indicated that SBP (β = 0.234, P = 0.043), TG (β = − 0.292, P = 0.001) and LDL-C (β = 0.626, P = 0.000) were independently correlated with ADP, and BMI (β = 0.398, P = 0.002) was independently correlated with LEP in obese individuals. In conclusion, ADP and LEP were closely related with glucose and lipid metabolism in obese individuals, these two cytokines might play critical roles in obesity-associated metabolic disorders.

Ceramide d18:1/24:1 as a potential biomarker to differentiate obesity subtypes with unfavorable health outcomes

BackgroundThe criteria for metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) remain controversial. This research aimed to identify a potential biomarker to differentiate the subtypes of obesity.MethodsThe study conducted a lipidomic evaluation of ceramide in the serum of 77 Chinese adults who had undergone hyperinsulinemic-euglycemic clamps. These adults were divided into three groups according to the clinical data: normal weight control group (N = 21), MHO (N = 20), and MUO (N = 36).ResultsThe serum Cer d18:1/24:1 level in the MHO group was lower than that in the MUO group. As the Cer d18:1/24:1 level increased, insulin sensitivity decreased, and the unfavorable parameters increased in parallel. Multivariate logistic regression analysis revealed that serum Cer d18:1/24:1 levels were independently correlated with MUO in obesity. Individuals with higher levels of Cer d18:1/24:1 also had an elevated risk of cardiovascular disease. Most ceramide subtype levels increased in obesity compared to normal-weight individuals, but the levels of serum Cer d18:0/18:0 and Cer d18:1/16:0 decreased in obesity.ConclusionsThe relationships between ceramide subtypes and metabolic profiles might be heterogeneous in populations with different body weights. Cer d18:1/24:1 could be a biomarker that can be used to differentiate MUO from MHO, and to better predict who will develop unfavorable health outcomes among obese individuals.Trial registrationThe First Affiliated Hospital of Nanjing Medical University’s Institutional Review Board authorized this study protocol, and all participants provided written informed consent (2014-SR-003) prior to study entry.

Asociación entre parámetros hematológicos y fenotipos metabólicamente poco saludables en niños y adolescentes

Introduction. Metabolic syndrome has been associated with changes in several hematological parameters, such as red blood cells, platelets, and leucocytes. Therefore, hematologic parameters can be used to identify the subjects at risk of metabolically unhealthy phenotypes (MUP). The current study investigated if hematological parameters can serve as biomarkers to distinguish metabolically healthy phenotype (MHP) from MUP in children and adolescents. Methods. Two hundred ninety-two children and adolescents were enrolled in this cross-sectional study. The MUP was diagnosed using consensus-based criteria. Group comparisons were performed using one-way ANOVA. Multiple logistic regression analysis was used to determine if sex, age group, nutritional status, puberty, hematological parameters, and insulin resistance were associated with MUP. Results. The subject's age mean was 11 years (SD: 2.61). RDW values were significantly lower in children in the metabolically unhealthy normal weight (MUNW) group compared to children with metabolically unhealthy obesity (MUO) group (12.33 ± 0.90 vs. 13.67 ± 0.52; p = 0.01) and in metabolically healthy obesity (MHO) compared to MUO group (13.15 ± 0.53 vs. 13.67 ± 0.52; p = 0.04). In adolescents, the platelet-to-lymphocyte ratio was higher in the MHNW group, with a mean value of 152.60 (SD 62.97) compared to 111.16 (SD 44.12) for the MHO group. However, after adjusting for age, nutritional status, and puberty, hematological indices were not associated with MUP. Conclusions. The study demonstrates that hematologic parameters are not independently associated with the MUP, and it is unlikely that they represent reliable biomarkers for screening for the MUP in the pediatric population.

The triglycerides and glucose index is more strongly associated with metabolically healthy obesity phenotype than the lipid and obesity indices.

The triglycerides and glucose (TyG) index is a reliable biomarker for estimating insulin resistance; however, evidence regarding the use of the TyG index in individuals with metabolically healthy obesity (MHO) is scarce. Thus, we examined the association between the TyG index and the MHO phenotype. Apparently healthy men and women aged 18years or more with obesity (body mass index [BMI] ≥ 30kg/m2) were allocated into the following groups: MHO and metabolically unhealthy obesity (MUO). The MHO phenotype was defined by obesity and the absence of the following metabolic disorders: elevated triglyceride concentrations, elevated glucose levels, elevated blood pressure, and low HDL-C. The MUO was defined by individuals with obesity and at least one of the aforementioned cardiovascular risk factors. A total 827 individuals, 605 (73.1%) women and 222 (26.9%) men were enrolled and allocated into the MHO (n = 104) and MUO (n = 723) groups. The adjusted regression analysis by age, sex, BMI, and waist circumference showed that fasting glucose (OR = 0.90; 95% CI: 0.88-0.93), and triglycerides (OR = 0.97; 95% CI: 0.96-0.98), as well as the triglycerides/HDL-C (OR = 0.18; 95% CI: 0.13-0.26), lipid accumulation product (OR = 0.95; 95% CI: 0.93-0.96), visceral adipose index (OR = 0.38; 95% CI: 0.31-0.46), and TyG index (OR = 0.001; 95% CI: 0.000-0.004) are inversely associated with the MHO, while the HDL-C (OR = 1.10; 95% CI: 1.07-1.12) had a direct association. Our results show that the TyG index is more strongly associated with the MHO phenotype than the lipid and obesity indices.

284-LB: From Metabolically Healthy Obesity (MHO) to Metabolically Unhealthy Obesity (MUHO)—Decreased Thyroid Hormone Sensitivity

Background: To explore the difference of thyroid hormone sensitivity between metabolically healthy and metabolically unhealthy obesity patients and its influence on obesity phenotype. Methods: 10927 euthyroid adults were enrolled, 4 groups based on the presence/absence of metabolic disorders (MD) and BMI were divided: 1) NC (n=1441): no MD and 22≤BMI &amp;lt; 25Kg/m2. 2) NMu (n=3765): MD and 22≤BMI &amp;lt; 25Kg/m2. 3) MHO (n=148): obese with no MD (BMI≥28Kg/m2). 4) MuHO (n=1981): obese with MD (BMI≥28Kg/m2). MD was defined as meeting none of the following criteria: fasted blood glucose ≤6.1 mmol/L; triglycerides ≥1.7 mmol/L; high density lipoprotein (HDL) &amp;lt;1.0 mmol/L (male) and &amp;lt;1.3 mmol/L (female); elevated SBP (≥130 mmHg) or/and DBP (≥85 mmHg). Thyroid hormone central sensitivity indices were calculated by thyroid feedback quantile-based index (TFQI), TSH index (TSHI), Chinese-referenced parametric TFQI (PTFQI) and thyrotropin thyroxine resistance index (TT4RI). Peripheral thyroid hormone sensitivity was evaluated by FT3/FT4 ratio. Results: Compared with MHO group, TFQI, PTFQI and TT4RI elevated in MuHO group, and the trend still existed after adjusting for confounding factors. High FT3/FT4 ratio was an independent risk factor for MuHO (OR = 1.22, 95%CI: 1.13, 1.37, P&amp;lt;0.001). In euthyroid obese patients, decreased TFQI was a protective factor for MHO (OR=0.71, 95%CI 0.51, 0.83, P=0.036), while TSHI (OR= 1.27, 95%CI: 1.11, 1.38, P =0.027) and TT4RI (OR= 1.08, 95%CI: 1.03, 1.16, P =0.022) were significantly correlated with the occurrence of MuHO. Conclusions: Thyroid hormone sensitivity is impaired with elevated BMI. Impaired thyroid hormone sensitivity associated with the development of metabolically unhealthy obesity in patients with similar BMI. Keywords Metabolically Healthy Obesity, Thyroid Hormone Sensitivity Disclosure N. Zhang: None. G. Wang: None. Funding National Natural Science Foundation of China (81770792)

Shared and Distinct Gut Microbial Profiles in Saudi Women with Metabolically Healthy and Unhealthy Obesity.

Mounting evidence suggests a pivotal role for the gut microbiome in energy disequilibrium characteristic of obesity. The clinical utility of microbial profiling for the distinction between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) remains ill-defined. We aim to probe microbial composition and diversity in young adult Saudi females with MHO and MUO. This observational study included anthropometric and biochemical measurements and shotgun sequencing of stool DNA for 92 subjects. α- and β-diversity metrics were calculated to determine the richness and variability in microbial communities, respectively. Results showed that Bacteroides and Bifidobacterium merycicum were less abundant in MUO compared to healthy and MHO groups. BMI was negatively correlated with B. adolescentis, B. longum, and Actinobacteria in MHO, while being positively correlated with Bacteroides thetaiotaomicron in both MHO and MUO. Positive correlations between waist circumference and B. merycicum and B. thetaiotaomicron were observed in MHO and MUO, respectively. Compared to MHO and MUO groups, higher α-diversity was detected in healthy individuals who also had higher β-diversity compared to those with MHO. We conclude that modulation of the gut microbiome cohorts through prebiotics, probiotics, and fecal microbiota transplantation may be a promising preventive and therapeutic approach to obesity-associated disease.

A novel criterion of metabolically healthy obesity could effectively identify individuals with low cardiovascular risk among Chinese cohort.

Obesity has become a serious public health problem and brings a heavy burden of cardiovascular disease. Metabolically healthy obesity (MHO) is defined as individuals with obesity with no or only minor metabolic complications. Whether individuals with MHO have a lower cardiovascular risk remains controversial. In this study, a new criterion was used to define MHO and assess its predictive value for cardiovascular events and death. At the same time, the new criterion and the traditional criterion are compared to analyze the differences between different diagnostic criteria. A prospective cohort was established in northeast rural China from 2012 to 2013. Follow-up was conducted in 2015 and 2018 to investigate the incidence of cardiovascular events and survival. Subjects were grouped according to the metabolic health and obesity status. Kaplan-Meier curves were drawn to describe the cumulative risk of endpoint events in the four groups. Cox regression analysis model was constructed to evaluate the risk of endpoint events. Analysis of variance and post hoc analyses were used to calculate and compare differences in metabolic markers between MHO subjects diagnosed by novel and traditional criteria. A total of 9345 participants 35 years of age or older without a history of cardiovascular disease were included in this study. After a median follow-up of 4.66 years, the data showed that participants in the MHO group had no significant increase in the risk of composite cardiovascular events and stroke, but had a 162% increase in the risk of coronary heart disease (HR: 2.62; 95%CI: 1.21-5.67). However, when using conventional criteria for metabolic health, mMHO group had a 52% increase in combined CVD risk (HR: 1.52; 95%CI: 1.14-2.03). By comparing the differences of metabolic indicators between MHO subjects diagnosed by the two criteria, MHO subjects diagnosed by the new criterion had higher WC, WHR, TG, FPG, and lower HDL-C levels except for lower blood pressure, showing more exposure to cardiovascular risk factors. The risk of combined CVD and stroke was not increased in MHO subjects. The new metabolic health criterion is superior to the traditional criterion and can effectively identify individuals with obesity with a lower risk of combined CVD. Blood pressure levels may be responsible for the inconsistent risk of combined CVD in MHO subjects diagnosed with both criteria.

Association between metabolically healthy obesity and kidney stones: results from the 2011-2018 National Health and Nutrition Examination Survey.

The risk of kidney stones in metabolically healthy obesity (MHO) individuals is largely unexplored. This study using percent body fat (%BF) to categorize obesity, to investigate the association between MHO as well as other metabolic syndrome-obesity combined phenotypes and kidney stones in a national representative population. This cross-sectional study included 4,287 participants in the National Health and Nutrition Examination Survey from 2011 to 2018. Metabolically healthy status was defined as not having any component of metabolic syndrome or insulin resistance. Obesity was identified by %BF, which was measured and assessed by dual-energy x-ray absorptiometry (DXA) scan. Participants were cross-classified by metabolic health and obesity status. The outcome was self-report kidney stones. Multivariable logistic regression model was used to examine the association between MHO and kidney stones. A total of 358 participants had kidney stones [weighted prevalence (SE): 8.61% (0.56%)]. The weighted prevalence (SE) of kidney stones in MHN, MHOW, and MHO groups was 3.13% (1.10%), 4.97% (1.36%), and 8.55% (2.09%), respectively. After adjusting for age, sex, race and ethnicity, education level, smoking status, alcohol consumption, physical activity, daily water intake, CKD stage 3-5, and hyperuricemia, MHO individuals (OR: 2.90, 95% CI: 1.18, 7.0) had a significantly higher risk of kidney stones than those with metabolically healthy normal weight. In metabolically healthy participants, a 5% increment in %BF was associated with a significantly higher risk of kidney stones (OR: 1.60, 95% CI: 1.20, 2.14). Furthermore, a nonlinear dose-response relationship between %BF and the kidney stones was observed in metabolically healthy participants (P for non-linearity = 0.046). Using %BF to define obesity, MHO phenotype was significantly associated with higher risks of kidney stones, suggesting that obesity can independently contribute to kidney stones in the absence of metabolic abnormalities and insulin resistance. Regarding kidney stones prevention, MHO individuals might still benefit from lifestyle interventions aimed at healthy body composition maintenance.

Metabolic phenotypes and risk of end-stage kidney disease in patients with type 2 diabetes.

Obesity often initiates or coexists with metabolic abnormalities. This study aimed to investigate the pathological characteristics and the independent or mutual relations of obesity and metabolic abnormalities with end-stage kidney disease (ESKD) in patients with type 2 diabetes (T2D) and associated diabetic kidney disease (DKD). A total of 495 Chinese patients with T2D and biopsy-confirmed DKD between 2003 and 2020 were enrolled in this retrospective study. The metabolic phenotypes were based on the body weight index (BMI)-based categories (obesity, BMI ≥ 25.0 kg/m2) and metabolic status (metabolically unhealthy status, ≥ 1 criterion National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATP III) excluding waist circumference and hyperglycemia) and were categorized into four types: metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO), and metabolically unhealthy obesity (MUO). The pathological findings were defined by the Renal Pathology Society classification. Cox proportional hazards models were used to estimate hazard ratios (HRs) for ESKD. There are 56 (11.3%) MHNO patients, 28 (5.7%) MHO patients, 176 (35.6%) MUNO patients, and 235 (47.5%) MUO patients. The high prevalence of the Kimmelstiel-Wilson nodule and severe mesangial expansion were associated with obesity, whereas severe IFTA was related to metabolically unhealthy status. In the multivariate analysis, the adjusted HR (aHR) was 2.09 [95% confidence interval (CI) 0.99-4.88] in the MHO group, 2.16 (95% CI 1.20-3.88) in the MUNO group, and 2.31 (95% CI 1.27-4.20) in the MUO group compared with the MHNO group. Furthermore, the presence of obesity was insignificantly associated with ESKD compared with non-obese patients (aHR 1.22, 95% CI 0.88-1.68), while the metabolically unhealthy status was significantly associated with ESKD compared to the metabolically healthy status in the multivariate analysis (aHR 1.69, 95% CI 1.10-2.60). Obesity itself was insignificantly associated with ESKD; however, adding a metabolically unhealthy status to obesity increased the risk for progression to ESKD in T2D and biopsy-proven DKD.

Triglyceride glucose index, pediatric NAFLD fibrosis index, and triglyceride-to-high-density lipoprotein cholesterol ratio are the most predictive markers of the metabolically unhealthy phenotype in overweight/obese adolescent boys.

The prevalence of obesity constantly increases worldwide and definitely increases the risk of premature death in early adulthood. While there is no treatment yet with proven efficacy for the metabolic clamp such as arterial hypertension, dyslipidemia, insulin resistance, diabetes type 2, and fatty liver disease, it is imperative to find a way to decrease cardiometabolic complications. Early prevention strategies beginning in childhood are the most logical step to reduce future cardiovascular morbidity and mortality. Therefore, the aim of the current study is to determine the most sensitive and specific predictive markers of the metabolically unhealthy phenotype with high cardiometabolic risk in overweight/obese adolescent boys. This study was carried out at the Ternopil Regional Children's hospital (Western Ukraine) and involved 254 randomly chosen adolescent overweight or obese boys [median age was 16.0 (15.0,16.1) years]. A control group of 30 healthy children with proportional body weight comparable in gender and age to the main group was presented. A list of anthropometrical markers with biochemical values of carbohydrate and lipid metabolism with hepatic enzymes was determined. All overweight/obese boys were divided into three groups: 51.2% of the boys with metabolic syndrome (MetS) based on the IDF criteria; 19.7% of the boys were metabolically healthy obese (MHO) without hypertension, dyslipidemia, and hyperglycemia; and the rest of the boys (29.1%) were classified as metabolically unhealthy obese (MUO) with only one criterion (hypertension, dyslipidemia, or hyperglycemia). Based on multiple logistic regression analysis that included all anthropometric and biochemical values and calculated indexes in boys from the MHO group and MetS, it was revealed that the maximum likelihood in the prediction of MetS makes the combination of triglyceride glucose index, pediatric nonalcoholic fatty liver disease fibrosis index (PNFI), and triglyceride-to-high-density lipoprotein cholesterol ratio (R2 =0.713, p<0.000). By tracing the receiver operating characteristic curve, the model is confirmed as a good predictor of MetS (AUC=0.898, odds ratio=27.111 percentage correct=86.03%) in overweight and obese boys. Triglyceride glucose index, pediatric NAFLD fibrosis index, and triglyceride-to-high-density lipoprotein cholesterol ratio are a valuable combination of predictive markers of the metabolically unhealthy phenotype in Ukrainian overweight/obese boys.

Metabolome Profiling and Pathway Analysis in Metabolically Healthy and Unhealthy Obesity among Chinese Adolescents Aged 11-18 Years.

The underlying mechanisms of the development of unhealthy metabolic phenotypes in obese children and adolescents remain unclear. We aimed to screen the metabolomes of individuals with the unhealthy obesity phenotype and identify the potential metabolic pathways that could regulate various metabolic profiles of obesity in Chinese adolescents. A total of 127 adolescents aged 11-18 years old from China were investigated using a cross-sectional study. The participants were classified as having metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUO) based on the presence/absence of metabolic abnormalities defined by metabolic syndrome (MetS) and body mass index (BMI). Serum-based metabolomic profiling using gas chromatography-mass spectrometry (GC-MS) was undertaken on 67 MHO and 60 MUO individuals. ROC analyses showed that palmitic acid, stearic acid, and phosphate could predict MUO, and that glycolic acid, alanine, 3-hydroxypropionic acid, and 2-hydroxypentanoic acid could predict MHO (all p < 0.05) from selected samples. Five metabolites predicted MUO, 12 metabolites predicted MHO in boys, and only two metabolites predicted MUO in girls. Moreover, several metabolic pathways may be relevant in distinguishing the MHO and MUO groups, including the fatty acid biosynthesis, fatty acid elongation in mitochondria, propanoate metabolism, glyoxylate and dicarboxylate metabolism, and fatty acid metabolism pathways. Similar results were observed for boys except for phenylalanine, tyrosine and tryptophan biosynthesis, which had a high impact [0.098]. The identified metabolites and pathways could be efficacious for investigating the underlying mechanisms of the development of different metabolic phenotypes in obese Chinese adolescents.

Association between different metabolic phenotypes of obesity and thyroid disorders among Chinese adults: a nationwide cross-sectional study.

Increased body mass index (BMI) and metabolic abnormalities both have potential associations with thyroid disease. The aim of this study was to investigate the correlation between different metabolic phenotypes of obesity and thyroid disorders using nationwide data from China. Data were collected from a cross-sectional survey called the Thyroid Disorders, Iodine Status, and Diabetes Epidemiological Survey conducted between 2015 and 2017 in China. A total of 69007 subjects aged 18 years or older were defined and divided into six groups on the basis of BMI and metabolic health status: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight (MHOW), metabolically unhealthy overweight (MUOW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). We estimated the odds ratios (ORs) and confidence intervals [CIs] for different thyroid disorders according to metabolic phenotypes using multivariate logistic regression models. In our study, we found that the prevalence of subclinical hypothyroidism was almost as high in the MUNW group as in the MUO group, the prevalence of overt hyperthyroidism was highest in the MUNW group and Graves' disease was highest in the MHO group. Our results also suggested that the prevalence of goiter and thyroid nodules increased with increased BMI values and that the MUO group had the highest incidence. Multivariate logistic regression analysis indicated that subjects with unhealthy metabolic phenotypes (MUNW, MUOW, and MUO) all had an increased risk of subclinical hypothyroidism, regardless of their BMI. MUNW subjects had an approximately 1.6-fold higher risk of overt hyperthyroidism and a 1.8-fold higher risk of Graves' disease than their metabolically healthy counterparts (MHNW). The present study also demonstrated that the MUO group had the highest risk of goiter and thyroid nodules among the metabolic phenotypes of obesity. Based on our study, we found that metabolic abnormalities and obesity play different roles in various thyroid diseases. Metabolically unhealthy individuals, both with and without obesity, have a higher risk of thyroid disorders than metabolically healthy individuals without obesity.