Healthy overweight and obesity in the young: Prevalence and risk of major adverse cardiovascular events.

AIMS: To investigate the prevalence of metabolically healthy overweight/obesity and to study its longitudinal association with major adverse cardiovascular and renal events (MARCE). METHODS AND RESULTS: The study was conducted in 1210 young-to-middle-age subjects grouped according to their BMI and metabolic status. The risk of MARCE was evaluated during 17.4 years of follow-up. Forty-eight-percent of the participants had normal weight, 41.9% had overweight, and 9.3% had obesity. Metabolically healthy status was found in 31.1% of subjects with normal weight and in 20.0% of those with overweight/obesity. During the follow-up, there were 108 MARCE. In multivariate Cox analysis adjusted for confounders and risk factors, no association was found between MARCE and overweight/obesity (p = 0.49). In contrast, metabolic status considered as a two-class variable (0 versus at least one metabolic abnormality) was a significant predictor of MARCE (HR, 2.11; 95%CI, 1.21-3.70, p = 0.009). Exclusion of atrial fibrillation from MARCE (N = 87) provided similar results (HR, 2.11; 95%CI, 1.07-4.16, p = 0.030). Inclusion of average 24 h BP in the regression model attenuated the strength of the associations. Compared to the group with healthy metabolic status, the metabolically unhealthy overweight/obesity participants had an increased risk of MARCE with an adjusted HR of 2.33 (95%CI, 1.05-5.19, p = 0.038). Among the metabolically healthy individuals, the CV risk did not differ according to BMI group (p = 0.53). CONCLUSION: The present data show that the risk of MARCE is not increased in young metabolically healthy overweight/obesity suggesting that the clinical approach to people with high BMI should focus on parameters of metabolic health rather than on BMI.

Integrated genetic and epigenetic analyses uncovered GLP1R association with metabolically healthy obesity.

BACKGROUND: Both genetic and epigenetic variations of GLP1R influence the development and progression of obesity. However, the underlying mechanism remains elusive. This study aims to explore the mediation roles of obesity-related methylation sites in GLP1R gene variants-obesity association. METHODS: A total of 300 Chinese adult participants were included in this study and classified into two groups: 180 metabolically healthy obesity (MHO) cases and 120 metabolically healthy normal-weight (MHNW) controls. Questionnaire investigation, physical measurement and laboratory examination were assessed in all participants. 18 single nucleotide polymorphisms (SNPs) and 31 CpG sites were selected for genotype and methylation assays. Causal inference test (CIT) was performed to evaluate the associations between GLP1R genetic variation, DNA methylation and MHO. RESULTS: The study found that rs4714211 polymorphism of GLP1R gene was significantly associated with MHO. Additionally, methylation sites in the intronic region of GLP1R (GLP1R-68-CpG 7.8.9; GLP1R-68-CpG 12.13; GLP1R-68-CpG 17; GLP1R-68-CpG 21) were associated with MHO, and two of these methylation sites (GLP1R-68-CpG 7.8.9; GLP1R-68-CpG 17) partially mediated the association between genotypes and MHO. CONCLUSIONS: Not only the gene polymorphism, but also the DNA methylation of GLP1R was associated with MHO. Epigenetic changes in the methylome may in part explain the relationship between genetic variants and MHO.

Differences in the levels of inflammatory markers between metabolically healthy obese and other obesity phenotypes in adults: A systematic review and meta-analysis.

AIMS: The aim of this study was to systematically review and analyze differences in the levels of C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) comparing metabolically healthy but obese (MHO) with metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO) subjects. DATA SYNTHESIS: We searched PubMed, Embase, Web of Science, and Scopus for studies that matched the relevant search terms. Differences in inflammatory marker levels between MHO and the other three phenotypes were pooled as standardized mean differences (SMD) or differences of medians (DM) using a random-effects model. We included 91 studies reporting data on 435,007 individuals. The CRP levels were higher in MHO than in MHNO subjects (SMD = 0.63, 95% CI: 0.49, 0.76; DM = 0.83 mg/L, 95% CI: 0.56, 1.11). The CRP levels were higher in MHO than in MUNO subjects (SMD = 0.16, 95% CI: 0.05, 0.28; DM = 0.39 mg/L, 95% CI: 0.09, 0.69). The CRP levels were lower in MHO than in MUO individuals (SMD = -0.43, 95% CI: -0.54, -0.31; DM = -0.82 mg/L, 95% CI: -1.16, -0.48). The IL-6 levels in MHO were higher than in MHNO while lower than in MUO subjects. The TNF-α levels in MHO were higher than in MHNO individuals. CONCLUSIONS: This review provides evidence that CRP levels in MHO are higher than in MHNO and MUNO subjects but lower than in MUO individuals. Additionally, IL-6 levels in MHO are higher than in MHNO but lower than in MUO subjects, and TNF-α levels in MHO are higher than in MHNO individuals. SYSTEMATIC REVIEW REGISTRATION: PROSPERO number: CRD42021234948.

Predictive markers of metabolically healthy obesity in children and adolescents: can AST/ALT ratio serve as a simple and reliable diagnostic indicator?

This study aimed to estimate the prevalence of metabolically healthy obesity (MHO) according to two different consensus-based criteria and to investigate simple, measurable predictive markers for the diagnosis of MHO. Five hundred and ninety-three obese children and adolescents aged 6-18 years were included in the study. The frequency of MHO was calculated. ROC analysis was used to estimate the predictive value of AST/ALT ratio, waist/hip ratio, MPV, TSH, and Ft4 cut-off value for the diagnosis of MHO. The prevalence of MHO was 21.9% and 10.2% according to 2018 and 2023 consensus-based MHO criteria, respectively. AST/ALT ratio cut-off value for the diagnosis of MHO was calculated as ≥ 1 with 77% sensitivity and 52% specificity using Damanhoury et al.'s criteria (AUC = 0.61, p = 0.02), and 90% sensitivity and 51% specificity using Abiri et al.'s criteria (AUC = 0.70, p = 0.01). Additionally, using binomial regression analysis, only the AST/ALT ratio is independently and significantly associated with the diagnosis of MHO (p = 0.03 for 2018 criteria and p = 0.04 for 2023 criteria). CONCLUSION: The ALT/AST ratio may be a useful indicator of MHO in children and adolescents. WHAT IS KNOWN: • Metabolically healthy obesity refers to people who are obese but do not have any of the standard cardio-metabolic risk factors. • Metabolically healthy obesity is not entirely harmless; the metabolic characteristics of individuals with this phenotype are less favorable than those of healthy lean groups. Moreover, it is not a constant state, and there may be a transition to metabolically unhealthy phenotypes over time. WHAT IS NEW: • The prevalence of MHO is 21.9% and 10.2% according to 2018 and 2023 consensus-based metabolically healthy obesity criteria, respectively. • The ALT/AST ratio may be a useful indicator of metabolically healthy obesity in children and adolescents.

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

Background and objective: 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. Methods: 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. Results: 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. Conclusions: 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.

[Relationship between skeletal muscle mass index and metabolic phenotypes of obesity in adolescents]. / é’å°‘å¹´éª¨éª¼è‚Œè´¨é‡æŒ‡æ•°ä¸Žè‚¥èƒ–ä»£è°¢è¡¨åž‹çš„å ³ç³».

OBJECTIVES: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: Increasing SMI can reduce the risk of the development of metabolic unhealthy/obesity.

Diagnostic accuracy of anthropometric indices for metabolically healthy obesity in child and adolescent population.

BACKGROUND: A variable percentage of children and adolescents with obesity do not have cardiometabolic comorbidities. A phenotype called metabolically healthy obese (MHO) has emerged to describe this population subgroup. Early identification of this condition may prevent the progression to metabolically unhealthy obesity (MUO). MATERIAL AND METHODS: A cross-sectional descriptive study of 265 children and adolescents from Cordoba (Spain) conducted in 2018. The outcome variables were MHO, established based on three criteria: International Criterion, HOMA-IR, and a combination of the previous two. RESULTS: The prevalence of MHO ranged from 9.4% to 12.8% of the study population, between 41% and 55.7% of the sample with obesity. The highest agreement was reached between the HOMA-IR definitions and the combined criteria. The waist-to-height ratio (WHtR) was the indicator with the highest discriminant capacity for MHO in 2 of the three criteria, with its best cut-off point at 0.47 for both. CONCLUSION: The prevalence of MHO in children and adolescents differed according to the criteria used for diagnosis. The anthropometric variable with the most remarkable discriminating capacity for MHO was WHtR, with the same cut-off point in the three criteria analysed. IMPACT STATEMENT: This research work defines the existence of metabolically healthy obesity through anthropometric indicators in children and adolescents. Definitions that combine cardiometabolic criteria and insulin resistance are used to identify metabolically healthy obesity, as well as the prediction of this phenomenon through anthropometric variables. The present investigation helps to identify metabolically healthy obesity before metabolic abnormalities begin.

Evaluation of systemic endothelial-dependent and endothelial-independent microvascular reactivity in metabolically healthy obesity: An observational study.

BACKGROUND: Metabolically healthy obesity (MHO), a phenotype of obesity considered to be of lower cardiovascular risk, is still a controversial concept. This study aimed to investigate the presence of subclinical systemic microvascular dysfunction in individuals with MHO. METHODS: This was a cross-sectional study in which 112 volunteers were allocated into three groups: metabolically healthy normal weight (MHNW), MHO, or metabolically unhealthy obesity (MUO). Obesity was defined as a body mass index (BMI) ≥ 30 kg/m2. MHO was defined as the absence of any component of metabolic syndrome, except waist circumference. Microvascular reactivity was evaluated using cutaneous laser speckle contrast imaging. RESULTS: Mean age was 33.2 ± 7.66 years. The median BMI in the MHNW, MHO and MUO groups was 23.6, 32.8, and 35.8 kg/m2, respectively. Baseline microvascular conductance values were lower in the MUO group (0.25 ± 0.08 APU/mmHg) than in MHO (0.30 ± 0.10 APU/mmHg) and MHNW groups (0.33 ± 0.12 APU/mmHg) (P = 0.0008). There were no significant differences regarding endothelial-dependent (acetylcholine stimulation or postocclusive reactive hyperemia) or endothelial-independent (sodium nitroprusside stimulation) microvascular reactivity among the groups. CONCLUSIONS: Individuals with MUO had lower baseline systemic microvascular flow than those with MHNW or MHO, but endothelium-dependent or endothelium-independent microvascular reactivity were not changed in any of the groups. The relatively young age of the study population, the low frequency of class III obesity, or the strict definition of MHO (absence of any metabolic syndrome criteria) might account for the lack of difference of microvascular reactivity among MHNW, MHO or MUO.

Myocardial Tissue-Level Characteristics of Adults With Metabolically Healthy Obesity.

BACKGROUND: It remains unclear whether adults with metabolically healthy obesity (MHO) have altered myocardial tissue-level characteristics. OBJECTIVES: This study aims to assess the subclinical myocardial tissue-level characteristics of adults with MHO. METHODS: The 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. RESULTS: A 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). CONCLUSIONS: This 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).

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

BACKGROUND: A 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. METHODS: This 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. RESULTS: Of 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). CONCLUSIONS: Individuals 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.

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

BACKGROUND AND AIMS: Metabolically 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 RESULTS: We 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). CONCLUSION: The 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.

Inflammation biomarkers and inflammatory genes expression in metabolically healthy obese patients.

BACKGROUND AND AIMS: Obesity without metabolic alterations (Metabolically Healthy Obesity, MHO) is a condition with a risk of death and cardiovascular disease lower than that of obesity associated with metabolic alterations (Metabolically Unhealthy Obesity, MUO) and similar to that of healthy non obese individuals. Inflammation is considered as a key risk factor mediating the adverse health outcomes in obesity. METHODS AND RESULTS: We compared circulating levels of thirteen major cytokines and adipokines and the expression profiles of fifteen pro-inflammatory and two anti-inflammatory genes in visceral and subcutaneous adipose tissue in a series of 16 MHO patients and in 32 MUO patients that underwent bariatric surgery. MHO was defined according to the most applied definition in current literature. Serum levels of a large set of major cytokines and adipokines did not differ between MHO and MUO patients (p ≥ 0.15). Analyses of the expression profile of pro-inflammatory and anti-inflammatory genes in subcutaneous and visceral adipose tissue failed to show differences between MHO and MUO patients (p ≥ 0.07). Sensitivity analyses applying two additional definitions of MHO confirmed the results of the primary analysis. CONCLUSION: In a series of metabolically healthy obese patients neither circulating levels of major cytokines and adipokines nor the gene expression profile of a large set of pro-inflammatory and anti-inflammatory genes in subcutaneous and visceral fat differed from those in metabolically unhealthy obese patients.

Risk factors, cutoff points, and definition of metabolically healthy/unhealthy obesity in children and adolescents: A scoping review of the literature.

Diagnosis of metabolically healthy obesity (MHO) and its definition do not have universal criteria in the pediatric age group. Hence, this scoping review aims to identify the components, the cutoff points, and the definition of MHO in children and adolescents. A comprehensive, systematic search was conducted in PubMed, Scopus, EMBASE, and Google Scholar databases. A consensus-based definition of MHO was developed through a Delphi process involving an international panel of 23 experts. This review included a total of 63 non-randomized studies, published between 2007 and 2022. According to our consensus (≥80% agreement), the proposed definition for MHO included the following components: high-density lipoprotein cholesterol >40 mg/dl (or >1.03 mmol/l), triglycerides ≤150 mg/dl (or ≤1.7 mmol/l), fasting plasma glucose <100 mg/dl (or <5.6 mmol/l), a measure of insulin, and systolic and diastolic blood pressure ≤90th percentile. Therefore, MHO was defined as the absence of the above metabolic risk factors; and those children and adolescents with one or more criteria were considered as metabolically unhealthy. A universal definition of MHO will allow comparisons between studies in the field of childhood obesity and can be useful in clinical practice.

Hyperuricemia as an effect modifier of the association between metabolic phenotypes and nonalcoholic fatty liver disease in Chinese population.

BACKGROUND: Different metabolic phenotypes may be related to nonalcoholic fatty liver disease (NAFLD), but such association whether modified by serum uric acid levels is unknown. We examined the association between different metabolic phenotypes and NAFLD and further explore whether hyperuricemia could modify this association. METHODS: A total of 2959 participants (mean age: 55.02 years) with medical checkups were recruited from Tianjin Medical University General Hospital. Participants were categorized into four groups according to their BMI levels and metabolically healthy status: metabolically healthy normal weight (MHNW), metabolically healthy overweight or obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy overweight or obese (MUO). Blood samples (including serum uric acid) were collected from participants after an overnight fast. NAFLD was diagnosed based on abdominal ultrasonography scanning. Data were analyzed using logistic regression models and the interaction effect model. RESULTS: The prevalence of NAFLD in MHNW, MHO, MUNW, and MUO groups was 9.9% (7.9-12.0%), 42.8% (39.5-46.1%), 36.5% (31.2-41.9%), and 69.7% (66.8-72.6%), respectively. In multi-adjusted logistic models, the ORs (95% CIs) of NAFLD were 5.32 (4.01-7.04) for participants with MHO, 4.51 (3.17-6.40) for those with MUNW, and 13.68 (10.23-18.30) for those with MUO compared to those with MHNW. In the stratified analysis by uric acid levels, the prevalence of NAFLD was significantly higher in participants with MHO, MUNW, and MUO in the hyperuricemia group than those in the normal uric acid group, and the interaction effect of metabolic phenotypes and uric acid on NAFLD was statistical significant (P < 0.05). CONCLUSIONS: MHO, MUNW, and MUO were associated with higher prevalence of NAFLD. Serum uric acid levels may modify the association between metabolically phenotypes and NAFLD.

Relationship between skeletal muscle mass index and metabolic phenotypes of obesity in adolescents / 中国当代儿科杂志

OBJECTIVES@#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.@*METHODS@#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.@*RESULTS@#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).@*CONCLUSIONS@#Increasing SMI can reduce the risk of the development of metabolic unhealthy/obesity.

Association between Metabolic Phenotypes of Body Fatness and Incident Stroke: A Prospective Cohort Study of Chinese Community Residents.

This study aimed to assess the association of body mass index (BMI)-based and waist circumference (WC)-based metabolic phenotypes with the risk of stroke among Chinese community residents. A total of 34,294 participants (mean ± standard deviation age: 56.05 ± 11.26 years) with no previous stroke diagnosis history were included in this cohort study. BMI-based metabolic phenotypes were classified into eight groups: metabolically healthy and normal weight (MHNW), metabolically healthy and underweight (MHUW), metabolically healthy and overweight (MHOW), metabolically healthy and obese (MHO), metabolically unhealthy and normal weight (MUNW), metabolically unhealthy and underweight (MUUW), metabolically unhealthy and overweight (MUOW), and metabolically unhealthy and obese (MUO). WC-based metabolic phenotypes were classified into four groups: metabolically healthy and normal WC (MHNWC), metabolically healthy and oversized WC (MHOWC), metabolically unhealthy and normal WC (MUNWC), and metabolically unhealthy and oversized WC (MUOWC). The association of these phenotypes with developing stroke events was examined using proportional hazards models. A total of 546 cases of first-stroke onset were recorded over a median follow-up time of 4.97 years. Compared with the reference group, the obesity phenotypes showed higher risks for stroke. The adjusted HRs (95% CIs) of MHUW, MHOW, MHO, MUNW, MUUW, MUOW, and MUO phenotypes were 1.01 (0.41, 2.49), 1.47 (1.09, 2.00), 1.33 (0.80, 2.22), 2.49 (1.87, 3.30), 3.92 (1.44, 10.72), 2.14 (1.64, 2.79), and 2.60 (1.91, 3.55), respectively. The adjusted HRs (95% CIs) of MHOWC, MUNWC, and MUOWC were 1.41 (1.02, 1.94), 2.25 (1.76, 2.87), and 2.16 (1.63, 2.87), respectively. The metabolic phenotypes defined by an alternative definition all showed significant positive associations (except for MHUW), with the adjusted HR ranging from 1.51 to 3.08 based on BMI and from 1.68 to 2.24 based on WC. The risk of stroke increased with the increase in metabolic abnormality numbers in different BMI and WC groups (all p trend < 0.001). The present study suggests that maintaining normal body weight or WC and improving metabolic health are of great significance in preventing cerebrovascular diseases.