Healthy Obesity Research Articles

Relationship between skeletal muscle mass index and metabolic phenotypes of obesity in adolescents

To study the relationship between skeletal muscle mass index (SMI) and metabolic phenotypes of obesity in adolescents, and to provide a basis for the prevention and control of adolescent obesity and related metabolic diseases. A total of 1 352 adolescents aged 12 to 18 years were randomly selected by stratified cluster sampling in Yinchuan City from October 2017 to September 2020, and they were surveyed using questionnaires, physical measurements, body composition measurements, and laboratory tests. According to the diagnostic criteria for metabolic abnormalities and the definition of obesity based on the body mass index, the subjects were divided into four metabolic phenotypes: metabolically healthy normal weight, metabolically healthy obesity, metabolically unhealthy normal weight, and metabolically unhealthy obesity. The association between SMI and the metabolic phenotypes was analyzed using multivariate logistic regression. The SMI level in the metabolically unhealthy normal weight, metabolically healthy obesity, and metabolically unhealthy obesity groups was lower than that in the metabolically healthy normal weight group (P<0.001). Multivariate logistic regression analysis showed that after adjusting for gender and age, a higher SMI level was a protective factors for adolescents to develop metabolic unhealthy normal weight, metabolically healthy obesity, and metabolically unhealthy obesity phenotypes (OR=0.74, 0.60, and 0.54, respectively; P<0.001). Increasing SMI can reduce the risk of the development of metabolic unhealthy/obesity.

Metabolically Healthy Obesity Is a Misnomer: Components of the Metabolic Syndrome Linearly Increase with BMI as a Function of Age and Gender.

We aimed to examine the relationships between body mass index (BMI) and metabolic syndrome (MS) components as a function of age and gender across weight categories. This cross-sectional study included 19,328 subjects who participated in a health-screening program. We analyzed 14,093 apparently healthy subjects with a BMI ≥ 18.5 kg/m2 (ranging from 18.5 to 46 kg/m2). At a BMI of 18.5 kg/m2, 16% of subjects had one or more MS components (MS ≥ 1). The number of MS components increased linearly with BMI. The most prevalent components for MS1-4 were hypertension (in men) and increased waist circumference (in women). Among 6391 non-obese subjects with MS = 0, there was a linear increase in blood pressure, glucose, and triglycerides, as well as a decline in high-density lipoprotein cholesterol, as BMI increased. In 2087 subjects with a BMI ≥ 30 kg/m2, a true normometabolic state (MS = 0) was observed in only 7.5%, declining to less than 1% at a BMI ≥ 36 kg/m2 (ATP criteria). Women were metabolically protected relative to men between the ages of 30 and 50 years. (A) MS components increase linearly with BMI from the lowest normal BMI and continue to increase with age and BMI; (B) metabolically healthy obesity is rare in subjects with a high BMI and declines with age; (C) hypertension is the most common component in men; and (D) in women, MS components are seen at older ages than in men for the same BMI. Metabolic health declines with age and BMI in nearly all subjects with obesity.

Integrated microbiome-metabolome-genome axis data of Laiwu and Lulai pigs

Excessive fat deposition can trigger metabolic diseases, and it is crucial to identify factors that can break the link between fat deposition and metabolic diseases. Healthy obese Laiwu pigs (LW) are high in fat content but resistant to metabolic diseases. In this study, we compared the fecal microbiome, fecal and blood metabolome, and genome of LW and Lulai pigs (LU) to identify factors that can block the link between fat deposition and metabolic diseases. Our results show significant differences in Spirochetes and Treponema, which are involved in carbohydrate metabolism, between LW and LU. The fecal and blood metabolome composition was similar, and some anti-metabolic disease components of blood metabolites were different between the two breeds of pigs. The predicted differential RNA is mainly enriched in lipid metabolism and glucose metabolism, which is consistent with the functions of differential microbiota and metabolites. The down-regulated gene RGP1 is strongly negatively correlated with Treponema. Our omics data would provide valuable resources for further scientific research on healthy obesity in both human and porcine.

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.

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.

Emotional eating among adults with healthy weight, overweight and obesity: a systematic review and meta-analysis.

Emotional eating (EE) is a disordered eating behaviour which may lead to overeating. It is not clear whether EE presents to an equal degree among adults, regardless of their BMI status. The aim of this study was to assess whether there is a difference in degree of EE between adults with healthy weight, overweight and obesity. MEDLINE and APA PsycINFO databases were searched from inception up to January 2022 for studies that reported EE scores from validated questionnaires. The quality of all included studies was assessed using the AXIS tool. Meta-analysis used random effects and standardised mean difference (SMD). Heterogeneity was investigated using I2 statistics and sensitivity analyses. A total of 11 studies with 7207 participants were included in the meta-analysis. Degree of EE was greater in adults with a BMI above the healthy range, compared to adults with a healthy BMI (SMD 0.31, 95% CI 0.17 to 0.45; I2 = 85%). However, subgroup analysis found that degree of EE was only greater in adults with obesity (SMD 0.61, 95% CI 0.41 to 0.81; I2 = 62%) and there was no difference in degree of EE between adults with overweight, compared to those with a healthy BMI. Degree of EE is greater among adults living with obesity, compared to adults with a healthy BMI, indicating a need for behavioural support to support EE among people living with obesity seeking weight management. Future research should examine the long-term effectiveness of interventions for EE. This article is protected by copyright. All rights reserved.

Association of Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet and metabolically unhealthy overweight/obesity phenotypes among Iranian women: a cross sectional study

PurposeParadoxes have been found in obesity, including individuals with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO), and diet may be one of the reasons for the creation of these metabolic phenotypes. Hence, the purpose of the present study was to investigate the association of the Mediterranean-DASH intervention for neurodegenerative delay (MIND) diet with metabolically unhealthy overweight/obesity (MUHOW/O) phenotypes.MethodsIn this cross-sectional study, 229 overweight and obese women (body mass index (BMI) ≥ 25 kg/m2) aged 18–48 years were examined. Anthropometric measures and biochemical parameters were collected from all participants. The body composition of each participant was assessed using a bioelectrical impedance analyzer (BIA). The MIND diet score was determined based on 15 components using a valid and reliable food frequency questionnaire (FFQ) containing 147 items. Karelis criteria was used to determine metabolically healthy/unhealthy phenotype (MH/MUH).ResultsAmong the participants, 72.5% of individuals were identified as MUH and 27.5% as MH, with a mean ± standard deviation (SD) age of 36.16 (8.33) years. The results of our analysis showed that after controlling for age, energy intake, BMI, and physical activity, there was no significant association observed between overweight/obesity phenotypes with tertile 2 (T2) (OR: 2.01, 95% CI: 0.86–4.17, P-value = 0.10), T3 (OR: 1.89, 95% CI: 0.86–4.17, P-value = 0.11) of MIND score, and only the odds of MUH relative to MH with a marginal significant decreasing trend was observed from the second to the third tertile (1.89 vs. 2.01) (P − trend = 0.06). Also, after additional adjustment for marital status, the nonsignificant association between overweight/obesity phenotypes with tertile 2 (T2) (OR: 2.13, 95% CI: 0.89−5.10, P-value = 0.08), T3 (OR: 1.87, 95% CI: 0.83−4.23, P-value = 0.12) of MIND score remained, and the odds of MUH relative to MH with a significant decreasing trend was observed with increasing tertiles (P-trend = 0.04).ConclusionsIn conclusion, no significant associations were found between adherence to MIND diet with MUH, and only a significant downward trend in the odds of MUH was observed with increasing tertiles. We suggest further studies in this field.

The Composition of Small Extracellular Vesicles (sEVs) in the Blood Plasma of Colorectal Cancer Patients Reflects the Presence of Metabolic Syndrome and Correlates with Angiogenesis and the Effectiveness of Thermoradiation Therapy.

The majority of colorectal cancer patients (CRCPs) develop tumors on the background of "metabolically healthy obesity" or metabolic syndrome. The aim of the work was to study the levels of matrix metalloproteinases (MMPs) and heat shock proteins (HSPs) on the surface of blood plasma CD9-positive and FABP4-positive small extracellular vesicles (sEVs) from CRCPs depending on metabolic status and tumor angiogenesis, as well as to evaluate the sEVs markers as predictors of the effectiveness of thermoradiotherapy. In CRCPs, compared with patients with colorectal polyps (CPPs), the proportion of triple positive EVs and EVs with the MMP9+MMP2-TIMP1+ phenotype increased significantly among FABP4-positive EVs (adipocyte-derived EVs), which in general may indicate the overexpression of MMP9 and TIMP1 by adipocytes or adipose tissue macrophages in CRCPs. The results obtained have prospects for use as markers to clarify cancer risk in CPPs. One can assume that for CRCPs with metabolic syndrome or metabolically healthy obesity, it is the FABP4+MMP9+MMP2-TIMP1- population of circulating sEVs that is the most optimal biomarker reflecting tumor angiogenesis. Determining this population in the blood will be useful in monitoring patients after treatment for the early detection of tumor progression. CD9+MMP9+MMP2-TIMP1- and MMP9+MMP2-TIMP1+ subpopulations of circulating sEVs are the most promising predictors of the efficacy of thermoradiation therapy because their levels at baseline differ significantly in CRCPs with different tumor responses.

Expression of ICAM-1 and E-selectin in different metabolic obesity phenotypes: discrepancy for endothelial dysfunction.

Endothelial dysfunction, the earliest vascular alteration, is a consequence of metabolic disorders associated with obesity. However, it is still unclear whether a proportion of obese individuals without metabolic alterations associated with obesity, defined as "metabolically healthy obesity (MHO)", exhibit better endothelial function. We therefore aimed to investigate the association of different metabolic obesity phenotypes with endothelial dysfunction. The obese participants without clinical cardiovascular disease from the MESA (Multi-Ethnic Study of Atherosclerosis) were allocated to the different metabolic obesity phenotypes based on their metabolic status, including MHO and metabolically unhealthy obesity (MUO). Associations of metabolic obesity phenotypes with the biomarkers of endothelial dysfunction, including soluble intercellular adhesion molecule-1 (sICAM-1) and soluble E-selectin (sE-selectin), were evaluated using multiple linear regression models. Plasma levels of sICAM-1 and sE-selectin were respectively measured in 2371 and 968 participants. Compared to the non-obese participants, those with MUO were associated with higher concentrations of sICAM-1 (β 22.04, 95% CI 14.33-29.75, P < 0.001) and sE-selectin (β 9.87, 95% CI 6.00-13.75, P < 0.001) after adjusting for confounders. However, no differences were found for the concentrations of sICAM-1 (β 0.70, 95% CI -8.91 to 10.32, P = 0.886) and sE-selectin (β 3.69, 95% CI -1.13 to 8.51, P = 0.133) in the participants with MHO compared to the non-obese participants. Individuals with MUO were associated with elevated biomarkers of endothelial dysfunction, but the association with endothelial dysfunction was not found in those with MHO, indicating that the individuals with MHO might exhibit better endothelial function.

Exploring the controversies surrounding metabolically healthy obesity

Exploring the controversies surrounding metabolically healthy obesity

Myocardial Tissue-Level Characteristics of Adults With Metabolically Healthy Obesity

BackgroundIt remains unclear whether adults with metabolically healthy obesity (MHO) have altered myocardial tissue-level characteristics. ObjectivesThis study aims to assess the subclinical myocardial tissue-level characteristics of adults with MHO. MethodsThe EARLY-MYO-OBESITY (EARLY Assessment of MYOcardial Tissue Characteristics in OBESITY; NCT05277779) registry was a prospective, 3-center, cardiac imaging study of obese nondiabetic individuals without cardiac symptoms who underwent cardiac magnetic resonance. Myocardial tissue-level characteristics, including extracellular volume fraction (ECV) and native T2 values, were measured as indicators of myocardial fibrosis and edema. Global longitudinal peak systolic strain and early diastolic longitudinal strain rate were assessed by tissue tracking analysis to detect subclinical systolic and diastolic dysfunction. ResultsA total of 120 participants were included: MHO (n = 32; mean age, 38 years; 41% men), metabolically healthy controls without obesity (n = 32; mean age: 37 years; 41% men), and metabolically unhealthy obesity (MUHO) (n = 56; mean age: 37 years; 55% men). The MHO group had higher ECV and native T2 values than healthy controls (both P < 0.001); furthermore, the ECV was higher in the MUHO group than in the MHO group (P = 0.002). The prevalence of myocardial fibrosis was 44% (14 of 32) in the MHO group and 71% (40 of 56) in the MUHO group. Although there was no intergroup difference in left ventricular ejection fraction, the MHO group had reduced global longitudinal peak systolic and early diastolic longitudinal strain rates, indicating subclinical systolic and diastolic dysfunction. Multivariate regression analysis identified increased body mass index to be an independent risk factor for myocardial fibrosis (OR: 6.28 [95% CI: 3.17-12.47]; P < 0.001). ConclusionsThis study provides the first evidence of subclinical myocardial tissue-level remodeling in adults with obesity, regardless of metabolic health. Early identification of cardiac impairment may facilitate preventive strategies against heart failure in the MHO population. (EARLY Assessment of MYOcardial Tissue Characteristics in OBESITY [EARLY-MYO-OBESITY]; NCT05277779)

Metabolic syndrome is associated with similar long-term prognosis in those living with and without obesity: an analysis of 45 615 patients from the nationwide LIPIDOGRAM 2004-2015 studies.

We aimed to evaluate the association between metabolic syndrome (MetS) and long-term all-cause mortality. The LIPIDOGRAM studies were carried out in the primary care in Poland in 2004, 2006, and 2015. MetS was diagnosed based on the National Cholesterol Education Program, Adult Treatment Panel III (NCEP/ATP III), and Joint Interim Statement (JIS) criteria. The cohort was divided into four groups: non-obese patients without MetS, obese patients without MetS, non-obese patients with MetS, and obese patients with MetS. Differences in all-cause mortality were analysed using Kaplan-Meier and Cox regression analyses. A total of 45 615 participants were enrolled (mean age 56.3, standard deviation: 11.8 years; 61.7% female). MetS was diagnosed in 14 202 (31%) by NCEP/ATP III criteria and 17 216 (37.7%) by JIS criteria. Follow-up was available for 44 620 (97.8%, median duration 15.3 years) patients. MetS was associated with increased mortality risk among the obese {hazard ratio, HR: 1.88 [95% confidence interval (CI) 1.79-1.99] and HR: 1.93 [95% CI 1.82-2.04], according to NCEP/ATP III and JIS criteria, respectively} and non-obese individuals [HR: 2.11 (95% CI 1.85-2.40) and 1.7 (95% CI 1.56-1.85) according to NCEP/ATP III and JIS criteria, respectively]. Obese patients without MetS had a higher mortality risk than non-obese patients without MetS [HR: 1.16 (95% CI 1.10-1.23) and HR: 1.22 (95% CI 1.15-1.30), respectively in subgroups with NCEP/ATP III and JIS criteria applied]. MetS is associated with increased all-cause mortality risk in non-obese and obese patients. In patients without MetS, obesity remains significantly associated with mortality. The concept of metabolically healthy obesity should be revised.

Variable dysregulation of circulating lipocalin-2 in different obese phenotypes: Association with vasodilator dysfunction.

Obesity is linked with heightened cardiovascular risk, especially when accompanied by metabolic abnormalities. Lipocalin (LCN) 2 and retinol-binding protein (RBP) 4, two members of the lipocalin family, may be upregulated in insulin resistance and atherosclerosis. We analyzed whether changes in circulating LCN2 and RBP4 in obese individuals relate with impaired vasodilator reactivity, an early stage in atherosclerosis. Obese individuals (n = 165), without (n = 48) or with (n = 117) metabolic abnormalities, and lean subjects (n = 42) participated in this study. LCN2 and RBP4 were measured by Luminex assay. Endothelium-dependent and -independent vasodilation to acetylcholine and sodium nitroprusside, respectively, was assessed by strain-gauge plethysmography. Circulating LCN2 was higher in obese than in lean subjects (p < 0.001), whereas RBP4 was not different between the two groups (p = 0.12). The vasodilator responses to both acetylcholine and nitroprusside were impaired in obese individuals (p < 0.001 vs lean subjects), with no difference between those with metabolically healthy or unhealthy obesity (p > 0.05). In the whole population, vasodilator responses to acetylcholine (R = 0.23, p = 0.01) and nitroprusside (R = 0.38, p < 0.001) had an inverse, linear relationship with circulating LCN2; no correlation, by contrast, was observed between circulating RBP4 and vasodilator reactivity (both p > 0.05). In a subgroup of obese patients with diabetes (n = 20), treatment with metformin (n = 10) or pioglitazone (n = 10) did not modify circulating LCN2 and RBP4 or vascular reactivity (all p > 0.05). Circulating LCN2, but not RBP4, is higher in obese than in lean individuals. Interestingly, changes in LCN2 inversely relate to those in vasodilator function, thereby making this protein a potential biomarker for risk stratification in obesity.

Cardiovascular risk of metabolically healthy obesity in two european populations: Prevention potential from a metabolomic study

BackgroundA new definition of metabolically healthy obesity (MHO) has recently been proposed to stratify the heterogeneous mortality risk of obesity. Metabolomic profiling provides clues to metabolic alterations beyond clinical definition. We aimed to evaluate the association between MHO and cardiovascular events and assess its metabolomic pattern.MethodsThis prospective study included Europeans from two population-based studies, the FLEMENGHO and the Hortega study. A total of 2339 participants with follow-up were analyzed, including 2218 with metabolomic profiling. Metabolic health was developed from the third National Health and Nutrition Examination Survey and the UK biobank cohorts and defined as systolic blood pressure < 130 mmHg, no antihypertensive drugs, waist-to-hip ratio < 0.95 for women or 1.03 for men, and the absence of diabetes. BMI categories included normal weight, overweight, and obesity (BMI < 25, 25–30, ≥ 30 kg/m2). Participants were classified into six subgroups according to BMI category and metabolic healthy status. Outcomes were fatal and nonfatal composited cardiovascular events.ResultsOf 2339 participants, the mean age was 51 years, 1161 (49.6%) were women, 434 (18.6%) had obesity, 117 (5.0%) were classified as MHO, and both cohorts had similar characteristics. Over a median of 9.2-year (3.7–13.0) follow-up, 245 cardiovascular events occurred. Compared to those with metabolically healthy normal weight, individuals with metabolic unhealthy status had a higher risk of cardiovascular events, regardless of BMI category (adjusted HR: 3.30 [95% CI: 1.73–6.28] for normal weight, 2.50 [95% CI: 1.34–4.66] for overweight, and 3.42 [95% CI: 1.81–6.44] for obesity), whereas those with MHO were not at increased risk of cardiovascular events (HR: 1.11 [95% CI: 0.36–3.45]). Factor analysis identified a metabolomic factor mainly associated with glucose regulation, which was associated with cardiovascular events (HR: 1.22 [95% CI: 1.10–1.36]). Individuals with MHO tended to present a higher metabolomic factor score than those with metabolically healthy normal weight (0.175 vs. -0.057, P = 0.019), and the score was comparable to metabolically unhealthy obesity (0.175 vs. -0.080, P = 0.91).ConclusionsIndividuals with MHO may not present higher short-term cardiovascular risk but tend to have a metabolomic pattern associated with higher cardiovascular risk, emphasizing a need for early intervention.

Comparative analyses of surrogates of metabolic syndrome in children and adolescents with metabolically healthy obesity vs. metabolically unhealthy obesity according to Damanhoury's criteria.

Metabolically healthy obesity (MHO) has been reported with varying frequencies in children. The reasons of metabolically healthy phenotype in some obese subjects are unclear. Our aim was to identify the frequency of MHOinobese subjects, to assess the potential associations ofdemographic characteristics, serum uric acid, alanine transaminase (ALT), pediatric nonalcoholic fatty liver disease fibsosis score probability (PNFS p) with MHO statusand to evaluate the differences between MHO and metabolically unhealthy obesity (MUO) with regard to metabolic syndrome surrogates. 251 consecutive obese subjects (125 females) aged7-18 years were included. Subjects were classified as having MHO according to Damanhoury's criteria. Several metabolic variables were measured, PNFS p was calculated by using the formula: z=1.1+(0.34*sqrt(ALT))+ (0.002*ALP)-(1.1*log(platelets)-(0.02*GGT). Median age of the subjects was 12.5yr (range: 7.0-17.0yr). The frequency of MHO was 41%. Subjects withMHO were significantly younger, had lower waist circumference (WC) and waist height ratio (WHtR) and lowerHOMA-IR than those without MHO(p<0.05 for all). Frequencies of hyperuricemia, hypertransaminasemia, hepatosteatosis and PNFS p values≥8 were similar betwen the groups. When putatively influential factors associated with MHO status were assessed with logistic regression analysis, only WC(β=1.03) and HOMA-IR(β=1.166) emerged assignificant factors(Nagelkerke R2=0.142). None of the investigated demographic factors were associated with MHOstatus. We found a remarkably high frequency of MHO status. Nevertheless, the absence of decreased frequencies of hyperuricemia, hypertransaminasemia andPNFS in subjects with MHO may suggest the need to reconsider the validity of the criteria defining MHO.

Adiposity, hepatic steatosis, and metabolic health transitions in people with obesity: Influences of age and sex

Background and aimsMetabolically healthy (MHO) and unhealthy obesity (MUO) may be transient conditions. This study aimed to quantify and identify predictive factors of metabolic transitions in obesity, exploring influences of age and sex. Methods and resultsWe retrospectively evaluated adults with obesity who underwent routine health evaluation. In a cross-sectional analysis of 12,118 individuals (80% male, age 44.3 ± 9.9 years), 16.8% had MHO. In a longitudinal evaluation of 4483 participants, 45.2% of individuals with MHO at baseline had dysmetabolism after a median follow-up of 3.0 (IQR 1.8–5.2) years, whereas 13.3% MUO participants became metabolically healthy (MH). Development of hepatic steatosis (HS, ultrasound) was an independent predictor of MHO conversion to dysmetabolism (OR 2.36; 95% CI 1.43, 3.91; p < 0.001), while HS persistence was inversely associated with transition from MUO to MH status (OR 0.63; 95% CI 0.47, 0.83; p = 0.001). Female sex and older age were associated with a lower chance of MUO regression. A 5% increment in body mass index (BMI) over time increased the likelihood of metabolic deterioration by 33% (p = 0.002) in females and 16% (p = 0.018) in males with MHO. A 5% reduction in BMI was associated with a 39% and 66% higher chance of MUO resolution in females and males, respectively (both p < 0.001). ConclusionThe findings support a pathophysiological role of ectopic fat depots in metabolic transitions in obesity and identify female sex as an aggravating factor for adiposity-induced dysmetabolism, which has implications for personalized medicine.

Metabolically healthy and unhealthy obesity and the development of lung dysfunction

We investigated the association of metabolically healthy (MH) and unhealthy (MU) obesity with incident lung dysfunction. This cohort study included 253,698 Korean lung disease-free adults (mean age, 37.4 years) at baseline. Spirometry-defined lung dysfunction was classified as a restrictive pattern (RP) or obstructive pattern (OP). We defined obesity as BMI ≥ 25 kg/m2 and MH as the absence of any metabolic syndrome components with a homeostasis model assessment of insulin resistance < 2.5: otherwise, participants were considered MU. During a median follow-up of 4.9 years, 10,775 RP cases and 7140 OP cases develped. Both MH and MU obesity showed a positive association with incident RP, with a stronger association in the MU than in the MH group (Pinteraction = 0.001). Multivariable-adjusted hazard ratios (95% CI) for incident RP comparing obesity to the normal-weight category was 1.15 (1.05–1.25) among the MH group and 1.38 (1.30–1.47) among MU group. Conversely, obesity was inversely associated with OP because of a greater decline in forced vital capacity than forced expiratory volume in 1 s. Both MH and MU obesity were positively associated with RP. However, the associations between obesity, metabolic health, and lung functions might vary depending on the type of lung disease.

Metabolically healthy obesity is associated with higher risk of both hyperfiltration and mildly reduced estimated glomerular filtration rate: the role of serum uric acid in a cross-sectional study

BackgroundThe impact of metabolically healthy obesity (MHO) on kidney dysfunction remains debatable. Moreover, few studies have focused on the early stages of kidney dysfunction indicated by hyperfiltration and mildly reduced eGFR. Thus, we aimed to investigate the association between the MHO and early kidney dysfunction, which is represented by hyperfiltration and mildly reduced estimated glomerular filtration rate (eGFR), and to further explore whether serum uric acid affects this association.MethodsThis cross-sectional study enrolled 1188 residents aged ≥ 40 years old from Yonghong Communities. Metabolically healthy phenotypes were categorized based on Adult Treatment Panel III criteria. Obesity was defined as body mass index (BMI) ≥ 25 kg/m2. Mildly reduced eGFR was defined as being in the range 60 < eGFR ≤ 90 ml/min/1.73m2. Hyperfiltration was defined as eGFR > 95th percentile after adjusting for sex, age, weight, and height.ResultsOverall, MHO accounted for 12.8% of total participants and 24.6% of obese participants. Compared to metabolically healthy non-obesity (MHNO), MHO was significantly associated with an increased risk of mildly reduced eGFR (odds ratio [OR] = 1.85, 95% confidence interval [CI] 1.13–3.01) and hyperfiltration (OR = 2.28, 95% CI 1.03–5.09). However, upon further adjusting for uric acid, the association between the MHO phenotype and mildly reduced eGFR was reduced to null. Compared with MHNO/non-hyperuricemia, MHO/non-hyperuricemia was associated with an increased risk of mildly reduced eGFR (OR = 2.04, 95% CI 1.17–3.58), whereas MHO/hyperuricemia was associated with an observably increased risk (OR = 3.07, 95% CI 1.34–7.01).ConclusionsMHO was associated with an increased risk of early kidney dysfunction, and the serum uric acid partially mediated this association. Further prospective studies are warranted to clarify the causality.

Quality of life and psychosocial outcomes among children with metabolically healthy and unhealthy obesity.

Obesity and obesity-related morbidities are associated with poor psychosocial adjustment and health-related quality of life (HRQoL). This study aims to examine HRQoL and psychosocial outcomes in children with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO), and the effects of familial health on these outcomes. Four hundred and six children with BMI for age ≥ 97th percentile were classified as having MHO and MUO based on the absence or presence of metabolic abnormalities. HRQoL and psychosocial outcomes were assessed using validated questionnaires such as PedsQL and DASS-21. There were no significant differences in HRQoL and psychosocial outcomes between children with MHO and children with MUO. Children with MUO and prior knowledge of existing metabolic conditions reported significantly lower total HRQoL (71.18 ± 17.42 vs. 75.34 ± 15.33), and higher depression (12.16 ± 11.80 vs. 8.95 ± 8.52) and stress (12.11 ± 8.21 vs. 10.04 ± 7.92) compared to children with MHO. Children with MUO who had fathers with metabolically unhealthy phenotype reported significantly lower total HRQoL (72.41 ± 15.67 vs. 76.82 ± 14.91) compared to children with MUO who had fathers with metabolically healthy phenotype. Prior knowledge of existing metabolic abnormalities was associated with poorer HRQoL and mental health in children with obesity. Paternal metabolic health status influenced HRQoL in children with MUO. First study that compared health-related quality of life (HRQoL) and psychosocial outcomes between children with metabolically healthy obesity (MHO) and children with metabolically unhealthy obesity (MUO). No significant differences in HRQoL and psychosocial outcomes between children with metabolically healthy obesity (MHO) and children with metabolically unhealthy obesity (MUO). Children with MUO who had prior knowledge of existing metabolic conditions reported lower HRQoL, higher depression and stress compared to children with MHO. Paternal metabolic health status was found to influence HRQoL in children with MUO. Mental health support intervention with paternal involvement should be provided for children with MUO.