Metabolically Unhealthy Obese Research Articles

Myocardial mechano-energetic efficiency is not impaired in patients with metabolically healthy overweight and obesity.

Reduced myocardial mechano-energetic efficiency (MEE) was associated with BMI. Subgroups of individuals with increased BMI but favorable cardiovascular risk profile were identified as individuals with "metabolically healthy overweight" (MHOW) and "metabolically healthy obesity" (MHO), respectively. We aim to investigate whether those with MHOW/MHO, defined as those having none of the components of metabolic syndrome, exhibit impaired MEE compared with their unhealthy counterparts. Myocardial MEE per gram of left ventricular mass (MEEi) was assessed by echocardiography in 2190 nondiabetic individuals participating in the CATAnzaro MEtabolic RIsk factors (CATAMERI) study who were divided, according to BMI and metabolic status, into groups of individuals with metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), MHOW, metabolically unhealthy overweight (MUOW), MHO, and metabolically unhealthy obesity (MUO). After adjusting for age and sex, no differences in myocardial MEEi were observed among individuals with MHNW, MHOW, and MHO (p = 0.56). Myocardial MEEi was comparable among individuals with MUNW, MUOW, and MUO (p = 0.21). Individuals with MHNW, MHOW, and MHO displayed significantly higher myocardial MEEi compared with their unhealthy counterparts. Increased BMI is not an obligate determinant for reduced myocardial MEEi. Other known components of metabolic syndrome rather than increased BMI contributed to reduced myocardial MEEi.

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.

Low-carbohydrate dietary score and the incidence of metabolically unhealthy phenotype based on BMI status: a cohort study

There is scarce research focusing on the relationship between the low-carbohydrate dietary score and the development of a metabolically unhealthy phenotype. Therefore, this cohort study was designed to assess the association between the low-carbohydrate dietary score and the risk of metabolically unhealthy phenotypes (MUP). This study included 1299 adults with healthy metabolic profiles who were followed for 5.9 years. Results indicated an inverse association between the second tertile of the low-carbohydrate dietary score and the risk of developing metabolically unhealthy obesity (MUO) (HR: 0.76, 95% CI: 0.59–0.98). In addition, we found an inverse association between the healthy low-carbohydrate dietary score and the risk of MUO (HR: 0.77, 95% CI: 0.60–0.99). Our results revealed a nonlinear inverse association between the low-carbohydrate dietary score and the risk of MUP only in subjects with overweight or obesity. This relationship was independent of animal protein and fat intake. Also, we found that a lower intake of unhealthy carbohydrates was associated with a lower risk of MUP only in subjects with overweight or obesity.

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

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

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

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

Association of metabolic health and obesity with coronary heart disease in adult cancer survivors.

The metabolically healthy obese (MHO) phenotype is associated with an increased risk of coronary heart disease (CHD) in the general population. However, association of metabolic health and obesity phenotypes with CHD risk in adult cancer survivors remains unclear. We aimed to investigate the associations between different metabolic health and obesity phenotypes with incident CHD in adult cancer survivors. We used National Health Insurance Service (NHIS) to identify a cohort of 173,951 adult cancer survivors aged more than 20 years free of cardiovascular complications. Metabolically healthy nonobese (MHN), MHO, metabolically unhealthy nonobese (MUN), metabolically unhealthy obese (MUO) phenotypes were created using as at least three out of five metabolic health criteria along with obesity (body mass index ≥ 25.0 kg/m2). We used Cox proportional hazards model to assess CHD risk in each metabolic health and obesity phenotypes. During 1,376,050 person-years of follow-up, adult cancer survivors with MHO phenotype had a significantly higher risk of CHD (hazard ratio [HR] = 1.52; 95% confidence intervals [CI]: 1.41 to 1.65) as compared to those without obesity and metabolic abnormalities. MUN (HR = 1.81; 95% CI: 1.59 to 2.06) and MUO (HR = 1.92; 95% CI: 1.72 to 2.15) phenotypes were also associated with an increased risk of CHD among adult cancer survivors. Adult cancer survivors with MHO phenotype had a higher risk of CHD than those who are MHN. Metabolic health status and obesity were jointly associated with CHD risk in adult cancer survivors.

Association between sugar-free beverage intake and childhood obesity among Chinese children and adolescents.

The relationship between sugar-free beverage (SFB) intake and childhood obesity among Chinese children is unknown. To describe the status of SFB consumption among children and adolescents in China and assess the association between SFB intake and different types of obesity. The study was based on the baseline data of an ongoing cohort project named Evaluation and Monitoring on School-based Nutrition and Growth in Shenzhen (EMSNGS). Food frequency questionnaires were used to collect information on SFB consumption in 3227 students aged 9-17. Physical and clinical examinations were conducted by trained investigators and clinicians. Multivariable binary logistic regression models were performed to assess the association between SFB intake and general obesity, overweight/obesity, abdominal obesity, metabolically unhealthy overweight (MUOW)/metabolically unhealthy obesity (MUO). The median age of the participants was 13.28 years. Among the participants, 55.2% were boys, and 66.1% were adolescents. The median SFB consumption was 16.67 mL/d. After adjusting for potential confounding factors, each 100 mL increase in daily SFB intake was associated with an increased risk of overweight/obesity (OR = 1.14; 95%CI: 1.06-1.23), abdominal obesity (OR = 1.12; 95%CI: 1.03-1.23), and MUOW/MUO (OR = 1.12; 95%CI: 1.02-1.21), respectively. Stratified analyses showed that family income may have an impact on the association between SFB intake and overweight/obesity (P for interaction = 0.021) and abdominal obesity (P for interaction = 0.031). SFB intake was positively associated with childhood obesity in Chinese children, particularly among individuals with high-income families.

MHO or MUO? White adipose tissue remodeling.

In this review, we delve into the intricate relationship between white adipose tissue (WAT) remodeling and metabolic aspects in obesity, with a specific focus on individuals with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). WAT is a highly heterogeneous, plastic, and dynamically secreting endocrine and immune organ. WAT remodeling plays a crucial role in metabolic health, involving expansion mode, microenvironment, phenotype, and distribution. In individuals with MHO, WAT remodeling is beneficial, reducing ectopic fat deposition and insulin resistance (IR) through mechanisms like increased adipocyte hyperplasia, anti-inflammatory microenvironment, appropriate extracellular matrix (ECM) remodeling, appropriate vascularization, enhanced WAT browning, and subcutaneous adipose tissue (SWAT) deposition. Conversely, for those with MUO, WAT remodeling leads to ectopic fat deposition and IR, causing metabolic dysregulation. This process involves adipocyte hypertrophy, disrupted vascularization, heightened pro-inflammatory microenvironment, enhanced brown adipose tissue (BAT) whitening, and accumulation of visceral adipose tissue (VWAT) deposition. The review underscores the pivotal importance of intervening in WAT remodeling to hinder the transition from MHO to MUO. This insight is valuable for tailoring personalized and effective management strategies for patients with obesity in clinical practice.

Relationship of Mitochondrial DNA Oxidation and Content with Metabolic Syndrome and Cardiovascular Risk in Obesity Phenotypes.

Obesity, chronic inflammation, and oxidative stress can influence mitochondrial DNA (mtDNA) content. Our objective was to evaluate the oxidation level and content of mtDNA and its relationship with metabolic parameters in metabolically healthy obese (MHO) compared to metabolically unhealthy obese (MUO) and normal weight (NW) controls. We studied 94 NW, 95 MHO, and 97 MUO individuals between 18 and 80 years old. Relative mtDNA content and mtDNA oxidation level (8-oxoguanine, 8-OxoG) were determined in peripheral blood leukocytes by the SYBR Green method of real-time PCR. One-way ANOVA and Tukey test were used to compare biochemical, clinical, and anthropometric characteristics, as well as mtDNA content and 8-OxoG. A progressive decrease in mtDNA content was observed between NW, MHO, and MUO with significant differences in MUO vs. NW (p: 0.04). An increase in 8-OxoG was observed in MUO patients compared to the other groups (MUO vs. MHO p: 0.01; MUO vs. NW p: 0.04). mtDNA content was directly correlated with HDL-c (p < 0.01) and inversely with waist circumference (p: 0.01) and LDL-c (p: 0.05). mtDNA content decreased, and the oxidation level increased concomitantly with the presence of obesity, the number of MS components, higher coronary risk, and insulin resistance parameters. MHO presented a similar mtDNA oxidation level to NW and mtDNA content to the MUO, placing the MHO individuals as having an intermediate phenotype. Changes in mtDNA content and oxidation were correlated to the lipid profile related to obesity and/or MS presence, probably associated with oxidative stress and chronic low-grade inflammation.

Serum selenium accelerates the development of metabolic disorders in a metabolically healthy obese U.S. population: a retrospective cross-sectional analysis of a population-based study from the NHANES (2011-2018).

Obesity represents a significant risk factor for the development of metabolic abnormalities. However, it is not inevitable that all individuals with obesity will develop these disorders. Selenium has been demonstrated to play a role in maintaining metabolic homeostasis in vivo, with the ability to regulate relevant signaling pathways involved in glucose and lipid metabolism processes. Previous studies have indicated that selenium concentrations in obese individuals are higher than those reported in the general population. These findings the question of whether altered selenium concentrations may act as important triggers for accelerating metabolic imbalances in the obese population. The aim of this study was to examine the potential correlation between serum selenium concentrations and the risk of developing metabolic abnormalities in individuals with obesity. The present study included 6,125 participants from the 2011-2018 National Health and Nutrition Examination Survey (NHANES) who were aged between 20 and 80 years, with a body mass index (BMI) of 30 kg/m2 or greater, and met the inclusion and exclusion criteria. Weighted generalized linear regression analyses were conducted to evaluate the associations between serum selenium concentrations and the conversion of metabolically healthy obesity (MHO) to metabolically unhealthy obesity (MUO). A generalized additive model (GAM) and a two-piecewise linear regression model were employed to investigate the saturation threshold effect between selenium and MUO. The correlation between different selenium concentration intervals and metabolic diseases was evaluated by categorizing selenium concentrations according to the saturation threshold. Furthermore, this study investigated the correlation between serum selenium and lipid concentrations in obese females and between serum selenium and blood pressure in obese males. The weighted prevalence of MUO in the study population was 48.35%. After rigorous adjustment for sociodemographic, physical, and laboratory test covariates, the weighted odds ratio (OR) of MUO increased by 44% for every 1 µM increase (approximately 78.74 µg) in the serum selenium concentration (weighted OR=1.44; 95% CI=1.09 - 1.91; P=0.018). Second, GAM analysis and saturation threshold analyses revealed an inverted U-shaped relationship between serum selenium and metabolic abnormalities in males, with a corresponding inflection point (K) of 2.82 µM. When the serum selenium concentration was below the K-value, the effects of serum selenium were mainly on blood pressure, especially diastolic blood pressure (DBP) (weighted β: 3.34; 95% CI= 0.25 - 6.44; P=0.038). Conversely, the correlation between the serum selenium concentrations and metabolic homeostasis imbalance in females was linear. When the selenium concentration exceeded 2.12 µM, the increase in selenium content was accompanied by increases in total cholesterol (TC, weighted β=0.54, 95% CI=0.32 - 0.76; P=0.000) and triglyceride (TG, weighted β=0.51, 95% CI=0.27 - 0.75; P=0.000) concentrations. The findings of our study indicate that selenium supplementation strategies for individuals with obesity should be tailored to the sex of the individual. In females, serum selenium concentration above the saturation threshold primarily facilitates the transition from MHO to MUO by influencing alterations in serum lipid metabolism. Maintaining selenium concentrations below the threshold levels is highly important for preventing the conversion of MHO to MUO. In males, serum selenium concentrations above the threshold were found to be effective in preventing an elevation in blood pressure, particularly in improving systolic blood pressure (SBP). Nevertheless, serum selenium concentrations below the threshold are linked to an increased risk of hypertension in obese individuals, particularly those with elevated diastolic blood pressure (DBP). Further research is needed to elucidate the optimal serum selenium concentration that exerts deleterious effects on blood pressure.

Exploring metabolically healthy obesity: prevalence, characteristics, and cardiovascular risk in the Iranian population based on the STEPS 2021.

Regarding the rapidly increasing prevalence of obesity throughout the globe, it remains a serious public health concern. A subgroup of obesity that does not meet metabolic syndrome criteria is called metabolically healthy obesity (MHO). However, whether the MHO phenotype increases cardiovascular disease (CVD) risk is controversial. This study aimed to evaluate the prevalence of MHO and its 10-year CVD risk in Iranian populations. Based on the STEPS 2021 project in Iran, we collected data on 18119 Iranians 25 years and older from all 31 provinces after applying many statistical factors. Using the Framingham score, we evaluated the 10-year cardiovascular risk associated with the various MHO definition criteria for Iranian populations. The prevalence of MHO was 6.42% (5.93-6.91) at the national level according to the AHA-NHLBI definition, and 23.29% of obese women and 24.55% of obese men were classified as MHOs. Moreover, the MHO group was younger than the metabolically unhealthy obesity (MUO) group based on all definitions (p < 0.001). The odds ratio of MUO individuals being classified as high-risk individuals by the Framingham criteria for CVD was significantly higher than that of MHO individuals by all definitions, with a crude odds ratio of 3.55:1 based on AHA-NHLBI definition. This study reveals a significant prevalence of MHO in the Iranian population, with approximately 25% of obese individuals classified as MHO. While MHO is associated with a lower risk of cardiovascular disease compared to MUO, MHO carries the potential for transitioning to an unhealthy state. The online version contains supplementary material available at 10.1007/s40200-023-01364-5.

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.

The mediatory role of inflammatory markers on the relationship between the NOVA classification system and obesity phenotypes among obese and overweight adult women: a cross-sectional study.

Diet and inflammation both play important roles in the occurrence of obesity. We aimed to investigate the role of inflammation in the development of both metabolically healthy obese (MHO) and metabolically unhealthy obese (MUHO) individuals. This cross-sectional study included 221 overweight and obese women aged 18-56 years. The study assessed the metabolic health phenotypes of the participants using the Karelis criterion score. Additionally, dietary intakes were evaluated using a 147-item semi-quantitative questionnaire and the NOVA classification system (comprising 37 food groups and beverages). The study also collected and analyzed the blood parameters, as well as biochemical and anthropometric indices, for all participants. Among the women included in the study, 22.9% had MHO phenotypes but 77.1% had MUHO phenotypes. A significant association between the third quartile of the NOVA classification system and the increased likelihood of having the MUHO phenotype was observed (OR = 1.40, 95% CI = 1.09-4.92, p = 0.04). Regarding the potential role of inflammatory markers, high-sensitivity C-reactive protein (hs-CRP) (p = 0.84), transforming growth factor-β (TGF-β) (p = 0.50), monocyte chemoattractant protein-1 (MCP-1) (p = 0.49), plasminogen activator inhibitor-1 (PAI-1) (p = 0.97), and homeostatic model assessment for insulin resistance (HOMA-IR) (p = 0.92) were found to be mediators. We observed a significant positive association between ultra-processed food (UPF) consumption and the MUHO phenotype in overweight and obese women. This association appeared to be mediated by some inflammatory markers, such as hs-CRP, TGF-β, MCP-1, PAI-1, and HOMA-IR. Additional studies are needed to validate these findings.

Single Nucleotide Variants of the VDR Gene and Cardiometabolic Risk in Obesity

BackgroundVitamin D deficiency is associated with impaired glucose tolerance, insulin resistance, metabolic syndrome, and an increased risk of developing type 2 diabetes. Aim: to define the contribution of single nucleotide variants (SNV) of the vitamin D receptor (VDR) gene to the development of metabolically unhealthy obesity (MUO) in children. Materials and Methods200 obese children aged 6-18 years were examined. The main group (n=118) was represented by children with MUO. The control group (n=82) consolidated of children with metabolically healthy obesity (MHO). Whole genome sequencing (CeGat) was performed in 31 children of the main and 21 children of the control group. The level of serum 25-hydroxyvitamin D (Synevo) was measured in all children. Verification of results: calculation of Spearman's correlation coefficient (r) and p-value for each variable. ResultsFive SNVs of the VDR gene were identified: rs2228570 (1 DNA copy number variation (CNV): c.2T>C in 94.23%; rs731236 (2 CNVs: c.11056T>C, c.1206T>C in 65.38%); rs10783218 (2 CNV: c.296+8C>T, c.146+8C>T in 7.69%); rs2228572 (2 CNV: c.57C>T, c.207C>T in 1.92%); rs12721365 (2 CNV: c. 1059C>T, c.909C>T in 1.92% of patients). A correlation between SNV VDR and MUO was observed in the following genotypes: AA rs12721365 (r=0.21), AA rs2228572 (r=0.21) and GG rs2228570 (r= -0.31), p<0.05. A correlation between vitamin D deficiency and SNV VDR was noted for the following genotypes: AA genotype rs12721365 (r= 0.41), AA genotype rs2228572 (r= 0.38) and GG rs 2228570 (r= -0.27), p<0.05. ConclusionsThe development of cardiometabolic risk and vitamin D deficiency in obese children is associated with the presence of AA/AG genotypes SNV VDR rs2228570, rs12721365, rs2228572.

The effects of weight loss and improved metabolic health status on the risk of non-alcoholic fatty liver disease—results from a prospective cohort in China

BackgroundThe impact of weight loss and/or improved metabolic status on the risk of non-alcoholic fatty liver disease (NAFLD) has yet to be determined.MethodsA total of 35,322 participants without NAFLD were followed. NAFLD risk was compared between consistently metabolically healthy non-obese (MHNO) and non-MHNO who lost weight to become non-obese and/or improved their metabolic health, using Cox proportional hazards and logistic regression models.ResultsFollowing 148,186 person-years, 8,409 participants had onset NAFLD, with an incidence rate of 56.75 (95% CI: 55.57, 57.94) per 1,000 person-years. Metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), and metabolically unhealthy non-obese (MUNO) at baseline were associated with increased NAFLD risk, with hazard ratios of 4.48 (95%CI:4.24, 4.73), 8.85 (95%CI:7.95, 9.84), and 10.70 (95%CI:9.73, 11.78). Weight loss and/or metabolic status improvements could significantly reduce NAFLD risk by 79.46 to 41.46%. Specifically, after weight loss from MHO to MHNO, the reduction in NAFLD risk [OR decreased from 12.01 (95%CI:9.40, 15.35) to 4.14 (95%CI:3.08, 5.57)] was greater than that of the MUNO subgroup whose metabolic status improved to MHNO [OR decreased from 5.53 (95%CI:5.15, 5.94) to 2.71 (95%CI:2.50, 3.93)]. In the MUO subgroup, the group with the greatest risk reduction of NAFLD was the weight and metabolic state both improvement group [MUO to MHNO, OR decreased from 22.74 (95%CI:17.61, 29.37) to 4.67 (95%CI:3.05, 7.16)], followed by the weight loss only group [MUO to MUNO, OR decreased to 6.83 (95%CI:4.87, 9.57)], and finally the group with the least and insignificant risk reduction was the metabolic state improvement group [MUO to MHO, OR decreased to 13.38 (95%CI:9.17,19.53)]. NAFLD risk was negatively correlated with the duration of improvement (p &amp;lt; 0.001).ConclusionIndividuals with non-MHNO were more likely to develop NAFLD than those with consistent MHNO, but metabolic improvements and weight loss can alleviate the risk. Their NAFLD risk was negatively correlated with improvement duration. However, it remained higher than in individuals with consistent MHNO at an average follow-up of 4.2 years.

The Role of Adipokines and Myokines in the Pathogenesis of Different Obesity Phenotypes-New Perspectives.

Obesity is a characteristic disease of the twenty-first century that is affecting an increasing percentage of society. Obesity expresses itself in different phenotypes: normal-weight obesity (NWO), metabolically obese normal-weight (MONW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). A range of pathophysiological mechanisms underlie the occurrence of obesity, including inflammation, oxidative stress, adipokine secretion, and other processes related to the pathophysiology of adipose tissue (AT). Body mass index (BMI) is the key indicator in the diagnosis of obesity; however, in the case of the NWO and MONW phenotypes, the metabolic disturbances are present despite BMI being within the normal range. On the other hand, MHO subjects with elevated BMI values do not present metabolic abnormalities. The MUO phenotype involves both a high BMI value and an abnormal metabolic profile. In this regard, attention has been focused on the variety of molecules produced by AT and their role in the development of obesity. Nesfatin-1, neuregulin 4, myonectin, irisin, and brain-derived neurotrophic factor (BDNF) all seem to have protective effects against obesity. The primary mechanism underlying the action of nesfatin-1 involves an increase in insulin sensitivity and reduced food intake. Neuregulin 4 sup-presses lipogenesis, decreases lipid accumulation, and reduces chronic low-grade inflammation. Myonectin lowers the amount of fatty acids in the bloodstream by increasing their absorption in the liver and AT. Irisin stimulates the browning of white adipose tissue (WAT) and consequently in-creases energy expenditure, additionally regulating glucose metabolism. Another molecule, BDNF, has anorexigenic effects. Decorin protects against the development of hyperglycemia, but may also contribute to proinflammatory processes. Similar effects are shown in the case of visfatin and chemerin, which may predispose to obesity. Visfatin increases adipogenesis, causes cholesterol accumulation in macrophages, and contributes to the development of glucose intolerance. Chemerin induces angiogenesis, which promotes the expansion of AT. This review aims to discuss the role of adipokines and myokines in the pathogenesis of the different obesity phenotypes.

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.

Longitudinal association of serum 25-hydroxyvitamin D levels with metabolically healthy body size transition in children and adolescents: A prospective cohort study with 2 years of follow-up

Background and aimsAlthough the associations of vitamin D with obesity and metabolic abnormalities have been reported, the role of vitamin D in the transition of obesity phenotype remains unclear but is highly desired since it is crucial to identify potential methods for obesity management. Therefore, we aimed to investigate the relationship between vitamin D and the risk for metabolically unhealthy obesity (MUO) or metabolically healthy obesity (MHO) in metabolically healthy children with 2 years of follow-up. MethodsData were collected from a population-based cohort consisting of 6424 metabolically healthy children aged 6–16 years at baseline. Metabolic abnormalities including hypertension, high triglycerides (TG), low high-density lipoprotein cholesterol (HDL-C), hyperglycemia, and hyperuricemia were assessed both at baseline and follow-up. Baseline serum 25-hydroxyvitamin D (25[OH]D) concentrations were measured as exposure. The obesity phenotype transition was evaluated by weight status with the combination of metabolic health status from baseline to follow-up. ResultsDuring a 2-year follow-up, 889 (13.8 %) incident MUO cases occurred. For participants with obesity, each 10 nmol/L increment in 25(OH)D concentrations was associated with a 21 % (95%CI: 13 %∼43 %) and a 7 % (95%CI: 1 %∼14 %) decreased risk in high TG and hyperuricemia, respectively. A 51 % (95%CI: 22 %∼69 %) lower risk of MUO was observed in participants with sufficient vitamin D levels (≥50 nmol/L) compared to those with vitamin D deficiency (<30 nmol/L). Besides, among children who were MHO at baseline, those with sufficient vitamin D levels (≥50 nmol/L) were more likely to transition to metabolically healthy normal weight (MHNW) than vitamin D deficient individuals (<30 nmol/L). ConclusionsVitamin D may prevent the development of MUO and help increase the transition from MHO to MHNW. The findings highlight that vitamin D might be an effective nutrient for obesity management.

Risk of incident chronic kidney disease in metabolically healthy obesity and metabolically unhealthy normal weight: A systematic review and meta-analysis.

Studies have reported inconsistent results about the risk of incident chronic kidney disease (CKD) in people with metabolically healthy obesity (MHO). We designed this systematic review and meta-analysis to evaluate the risk of developing CKD in people with MHO and metabolically unhealthy normal weight (MUNW). We used a predefined search strategy to retrieve eligible studies from multiple databases up to June 20, 2022. Random-effects model meta-analyses were implied to estimate the overall hazard ratio (HR) of incident CKD in obesity phenotypes. Eight prospective cohort studies, including approximately 5 million participants with a median follow-up ranging between 3 and 14 years, were included in this meta-analysis. Compared to the metabolically healthy normal weight (MHNW), the mean differences in cardiometabolic and renal risk factors in MHO, MUNW, and metabolically unhealthy obesity (MUO) were evaluated with overall HR of 1.42, 1.49, and 1.84, respectively. Compared to MHNW, the mean estimated glomerular filtration rate (eGFR) and high-density lipoprotein (HDL) were significantly lower, and low-density lipoprotein (LDL), blood pressure, blood glucose, and triglycerides were higher in MHO and MUNW. In conclusion, MHO and MUNW are not benign conditions and pose a higher risk for incident CKD. Obesity, whether in the presence or absence of metabolic health, is a risk factor for CKD.

The short- and long-term readmission of four major categories of digestive system cancers: does obesity or metabolic disorder matter?

Patients with digestive system cancers (DSCs) are at a high risk for hospitalizations; however, the risk factors for readmission remain unknown. Here, we established a retrospective cohort study to assess the association between metabolic obesity phenotypes and readmission risks of DSC. A total of 142,753 and 74,566 patients at index hospitalization were ultimately selected from the Nationwide Readmissions Database (NRD) 2018 to establish the 30-day and 180-day readmission cohorts, respectively. The study population was classified into four groups: metabolically healthy non-obese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO). Multivariate Cox regression analysis was used to estimate the effect of metabolic obesity phenotypes on DSC readmission. The MUNO phenotype had 1.147-fold (95% CI: 1.066, 1.235; p < 0.001) increased 180-day readmission risks in patients with neoplasm of the upper digestive tract. The MUNO phenotype had 1.073-fold (95% CI: 1.027, 1.121; p = 0.002) increased 30-day readmission risks and 1.067-fold (95% CI: 1.021, 1.115; p = 0.004) increased 180-day readmission risks in patients with neoplasm of the lower digestive tract. The MUNO and MUO phenotypes were independent risk factors of readmission in patients with liver or pancreatic neoplasm. Metabolic obesity status was independently associated with a high risk of severe and unplanned hospitalization within 30 days or 180 days. Both obesity and metabolic abnormalities are associated with a high risk for the poor prognosis of DSC patients. The effect of metabolic categories on the short- or long-term readmission of liver or pancreas cancers may be stronger than that of obesity.