Are metabolically healthy obese individuals really healthy?

Waist-height ratio highlights detrimental risk for olanzapine associated weight gain earlier than body mass index

OBJECTIVE

The objective of the current study was to compare the level of sensitivity of body mass index (BMI) or waist-height ratio (WHtR) in identifying physically determinable adiposity levels that are considered to be landmarks for commencing intervention to prevent more sinister cardio-metabolic risks among schizophrenia patients receiving olanzapine.

METHODS

The study was a descriptive crossectional one among patients with schizophrenia recieving olanzapine and healthy volunteers as controls. Key measurement of anthropological parameters were compared between the population.

RESULTS

Our findings revealed significantly higher rates of abnormal body mass index (BMI) (X2=17.06, p=0.000036; OR=4.58, CI=2.16-9.74) and abnormal waist-height ratio (WHtR) (X2=35.57, p=2.46E-9; OR=6.37, CI=3.39-12.00) among the schizophrenia patients compared to the healthy volunteers. Notably, BMI identified 43.3 % of the schizophrenia patients as having concerning weight changes, whereas WHtR identified 64.7 %, indicating that WHtR is a more sensitive measure. This discrepancy means that an additional 21.4 % of schizophrenia patients would benefit from weight management guidance based on WHtR rather than BMI.

CONCLUSION

Our results underscore the critical importance of WHtR in assessing adiposity among schizophrenia patients treated with olanzapine, highlighting its value as a tool for monitoring and managing cardiometabolic risks in this population.

Lifestyle intervention improves cardiometabolic profiles among children with metabolically healthy and metabolically unhealthy obesity

BACKGROUND

In recent years, there has been a surge of interest in the metabolic phenotype among children with obesity characterized by the absence of associated cardiometabolic risk factors (CRFs), known as metabolically healthy obesity (MHO), as opposed to those with metabolically unhealthy obesity (MUO). This study investigated the effect of lifestyle intervention on CRFs among children with MHO and MUO.

METHODS

A total of 102 school-aged children with obesity (54 girls and 48 boys) aged 8-16 years completed a 16-week school-based lifestyle modification intervention program, MyBFF@school Phase I. The intervention consisted of physical activity, healthy eating promotion, and psychological empowerment. MHO and MUO statuses were defined based on the 2018 consensus-based criteria. Fasting venous blood collection, body composition measurement, clinical assessment and physical fitness testing were conducted at baseline and at the end of week 16.

RESULTS

After the intervention, the CRFs of the children with MUO improved with significant decreases in systolic (p < 0.001) and diastolic (p = 0.01) blood pressure and a significant increase in high-density lipoprotein cholesterol (HDL-C) (p = 0.005), while the CRFs of the children with MHO had a significant decrease in uric acid (p = 0.04). Additionally, 51.6% of the children with MHO transitioned to the MUO, while 26.8% of the children with MUO crossed over to the MHO at the end of the intervention. Furthermore, the odds of having high systolic blood pressure among children with MUO were 59% lower at week-16 than at baseline (OR = 0.41 (95% CI = 0.18, 0.92), p = 0.03).

CONCLUSIONS

Our findings demonstrated that CRFs improved more prominently among children with MUO following the intervention. More importantly, our findings indicate that MHO in children is transient, hence, strategies to protect children against MUO are warranted.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02212873.

Stratification of Atherosclerosis based on Plasma Metabolic States

CONTEXT

Atherosclerosis is a dominant cause of cardiovascular disease (CVD), including myocardial infarction and stroke.

OBJECTIVE

To investigate metabolic states that are associated with the development of atherosclerosis.

METHODS

Cross-sectional cohort study at a university hospital in the Netherlands. A total of 302 adult subjects with a body mass index (BMI) ≥ 27 kg/m2 were included. We integrated plasma metabolomics with clinical metadata to quantify the "atherogenic state" of each individual, providing a continuous spectrum of atherogenic states that ranges between nonatherogenic states to highly atherogenic states.

RESULTS

Analysis of groups of individuals with different clinical conditions-such as metabolically healthy individuals with obesity, and individuals with metabolic syndrome-confirmed the generalizability of this spectrum; revealed a wide variation of atherogenic states within each condition; and allowed identification of metabolites that are associated with the atherogenic state regardless of the particular condition, such as gamma-glutamyl-glutamic acid and homovanillic acid sulfate. The analysis further highlighted metabolic pathways such as catabolism of phenylalanine and tyrosine and biosynthesis of estrogens and phenylpropanoids. Using validation cohorts, we confirmed variation in atherogenic states in healthy subjects (before atherosclerosis plaques become visible), and showed that metabolites associated with the atherogenic state were also associated with future CVD.

CONCLUSION

Our results provide a global view of atherosclerosis risk states using plasma metabolomics.

From Beats to Metabolism: the Heart at the Core of Interorgan Metabolic Cross Talk

The heart, once considered a mere blood pump, is now recognized as a multifunctional metabolic and endocrine organ. Its function is tightly regulated by various metabolic processes, at the same time it serves as an endocrine organ, secreting bioactive molecules that impact systemic metabolism. In recent years, research has shed light on the intricate interplay between the heart and other metabolic organs, such as adipose tissue, liver, and skeletal muscle. The metabolic flexibility of the heart and its ability to switch between different energy substrates play a crucial role in maintaining cardiac function and overall metabolic homeostasis. Gaining a comprehensive understanding of how metabolic disorders disrupt cardiac metabolism is crucial, as it plays a pivotal role in the development and progression of cardiac diseases. The emerging understanding of the heart as a metabolic and endocrine organ highlights its essential contribution to whole body metabolic regulation and offers new insights into the pathogenesis of metabolic diseases, such as obesity, diabetes, and cardiovascular disorders. In this review, we provide an in-depth exploration of the heart's metabolic and endocrine functions, emphasizing its role in systemic metabolism and the interplay between the heart and other metabolic organs. Furthermore, emerging evidence suggests a correlation between heart disease and other conditions such as aging and cancer, indicating that the metabolic dysfunction observed in these conditions may share common underlying mechanisms. By unraveling the complex mechanisms underlying cardiac metabolism, we aim to contribute to the development of novel therapeutic strategies for metabolic diseases and improve overall cardiovascular health.

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.

Metabolic phenotyping in people living with obesity: Implications for dietary prevention

Given the increasing number of people living with obesity and related chronic metabolic disease, precision nutrition approaches are required to increase the effectiveness of prevention strategies. This review addresses these approaches in different metabolic phenotypes (metabotypes) in obesity. Although obesity is typically associated with an increased cardiometabolic disease risk, some people with obesity are relatively protected against the detrimental effects of excess adiposity on cardiometabolic health, also referred to as 'metabolically healthy obesity' (MHO). Underlying mechanisms, the extent to which MHO is a transient state as well as lifestyle strategies to counteract the transition from MHO to metabolically unhealthy obesity (MUO) are discussed. Based on the limited resources that are available for dietary lifestyle interventions, it may be reasonable to prioritize interventions for people with MUO, since targeting high-risk patients for specific nutritional, lifestyle or weight-loss strategies may enhance the cost-effectiveness of these interventions. Additionally, the concept of tissue insulin resistant (IR) metabotypes is discussed, representing distinct etiologies towards type 2 diabetes (T2D) as well as cardiovascular disease (CVD). Recent evidence indicates that these tissue IR metabotypes, already present in individuals with obesity with a normal glucose homeostasis, respond differentially to diet. Modulation of dietary macronutrient composition according to these metabotypes may considerably improve cardiometabolic health benefits. Thus, nutritional or lifestyle intervention may improve cardiometabolic health, even with only minor or no weight loss, which stresses the importance of focusing on a healthy lifestyle and not on weight loss only. Targeting different metabotypes towards T2D and cardiometabolic diseases may lead to more effective lifestyle prevention and treatment strategies. Age and sex-related differences in tissue metabotypes and related microbial composition and functionality (fermentation), as important drivers and/or mediators of dietary intervention response, have to be taken into account. For the implementation of these approaches, more prospective trials are required to provide the knowledge base for precision nutrition in the prevention of chronic metabolic diseases.

Inflammatory markers may mediate the relationship between processed meat consumption and metabolic unhealthy obesity in women: a cross sectional study

Metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO) are known to be affected by diet and inflammatory factors (such as TGF-β1, IL-β1, MCP1). We sought to survey that consume of processed meat could effect on MHO and MUHO phenotypes, mediated through inflammatory markers, in overweight and obese Iranian women. The current cross-sectional study was done on 224 women 18-48 years, with a body mass index (BMI) ≥ 25 kg/m². A 147- item food frequency questionnaire (FFQ) was used to evaluate dietary intake. In all participants, anthropometric indices and biochemical factors, as well as metabolic health phenotypes based on Karelis score, were evaluated. According to results, 22.6% of participants had MHO and 75.7% had MUHO phenotypes. There was an association between higher adherence to processed meats and increasing odds of MUHO phenotype in Iranian women (OR:2.54; 95% CI 0.009, 7.51; P = 0.05). Moreover, we found that the relation can be affected by agents such as TGF-β1, IL-β1, and MCP1; however, more research is needed to confirm these results and finding.

Role of obesity related inflammation in pathogenesis of peripheral artery disease in patients of type 2 diabetes mellitus

Objective

Type 2 diabetes mellitus (T2DM) has emerged as one of the greatest global health challenges of twenty-first century. Visceral obesity is one of the most important determinant of insulin resistance (IR) as well as T2DM complications. Therefore this review focuses on the molecular mechanism of obesity induced inflammation, signaling pathways contributing to diabetes, as well as role of lifestyle interventions and medical therapies in the prevention and management of T2DM.

Method

Articles were searched on digital data base PubMed, Cochrane Library, and Web of Science. The key words used for search included Type 2 diabetes mellitus, obesity, insulin resistance, vascular inflammation and peripheral arterial disease.

Result

Visceral obesity is associated with chronic low grade inflammation and activation of immune systems which are involved in pathogenesis of obesity related IR and T2DM.

Conclusion

Metabolic dysregulation of adipose tissue leads to local hypoxia, misfolded/unfolded protein response and increased circulating free fatty acids, which in turn initiate inflammatory signaling cascades in the population of infiltrating cells. Mechanism that relates the role of adipocytokines with insulin sensitivity and glucose homeostasis might throw a light on the development of therapeutic interventions and subsequently might result in the reduction of vascular complications.

The Correlation of Apolipoprotein B with Alterations in Specific Fat Depots Content in Adults

Body mass index (BMI) and blood biomarkers are not enough to predict cardiovascular disease risk. Apolipoprotein B was identified to be associated with cardiovascular disease (CVD) progression. The Dual-energy X-ray Absorption (DXA) results could be considered as a predictor for cardiovascular disease in a more refined way based on fat distribution. The prediction of CVD risk by simple indicators still cannot meet clinical needs. The association of ApoB with specific fat depot features remains to be explored to better co-predict cardiovascular disease risk. An amount of 5997 adults from National Health and Nutrition Examination Survey (NHANES) were enrolled. Their demographic information, baseline clinical condition, blood examination, and DXA physical examination data were collected. Multivariate regression was used to assess the correlation between ApoB and site-specific fat characteristics through different adjusted models. Smooth curve fittings and threshold analysis were used to discover the turning points with 95% confidence intervals. ApoB is positively correlated with arms percent fat, legs percent fat, trunk percent fat, android percent fat, gynoid percent fat, arm circumference and waist circumference after adjustment with covariates for age, gender, race, hypertension, diabetes, hyperlipidemia, coronary heart disease, smoking status and vigorous work activity. The smooth curve fitting and threshold analysis also showed that depot-specific fat had lower turning points of ApoB in both males and females within the normal reference range of ApoB. Meanwhile, females have a lower increase in ApoB per 1% total percent fat and android percent fat than males before the turning points, while females have a higher growth of ApoB per 1% gynoid percent fat than males. The combined specific fat-depot DXA and ApoB analysis could indicate the risk of CVD in advance of lipid biomarkers or DXA alone.

Metabolically unhealthy phenotype in adults with normal weight: Is cardiometabolic health worse off when compared to adults with obesity?

The concept of metabolically healthy vs. unhealthy obese (MHO vs. MUO) was expanded to non-obese individuals as obesity-related comorbidities exist in a sub-group of normal weight (NW), i.e., MHNW vs. MUNW. It is unclear if MUNW differs from MHO with respect to cardiometabolic health.

PURPOSE

The purpose of this study was to compare cardiometabolic disease risk factors between MH vs. MU across weight status, NW, and obesity.

METHOD

A total of 8160 adults were included in the study from both the 2019 and 2020 Korean National Health and Nutrition Examination Surveys. Individuals with NW vs. obesity were further stratified as MH vs. MU by using AHA/NHLBI criterion for metabolic syndrome. A retrospective pair-matched analysis with respect to sex (male/female) and age ( ± 2 years) was performed to verify our total cohort analyses/results.

RESULTS

Despite a gradual increase in BMI and waist circumference from MHNW to MUNW to MHO to MUO, the surrogate estimates of insulin resistance and arterial stiffness were higher in MUNW vs. MHO. When compared to the MHNW, MUNW and MUO showed higher odds of hypertension (MUNW: 512%, MUO: 784%), dyslipidemia (MUNW: 210%, MUO: 245%), and diabetes (MUNW: 920%, MUO: 4012%), with no difference between MHNW and MHO.

CONCLUSION

Individuals with MUNW vs. MHO have greater vulnerability to cardiometabolic disease. Our data indicate that cardiometabolic risk is not solely dependent on adiposity, suggesting that early preventive efforts for chronic disease are needed for individuals with NW yet MU.

Anthropometric estimators of abdominal fat volume in adults with overweight and obesity

BACKGROUND/OBJECTIVES

To evaluate anthropometric measures for the prediction of whole-abdominal adipose tissue volumes V_XAT (subcutaneous V_SAT, visceral V_VAT and total V_TAT) in patients with obesity.

SUBJECTS/METHODS

A total of 181 patients (108 women) with overweight or obesity were analyzed retrospectively. MRI data (1.5 T) were available from independent clinical trials at a single institution (Integrated Research and Treatment Center of Obesity, University of Leipzig). A custom-made software was used for automated tissue segmentation. Anthropometric parameters (AP) were circumferences of the waist (WC) and hip (HC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and the (hypothetical) hip-to-height ratio (HHtR). Agreement was evaluated by standard deviations s_d% of percent differences between estimated volumes (using results of linear AP-V_XAT regression) and measured ones as well as Pearson's correlation coefficient r.

RESULTS

For SAT volume estimation, the smallest s_d% for all patients was seen for HC (25.1%) closely followed by HHtR (25.2%). Sex-specific results for females (17.5% for BMI and 17.2% for HC) and males (20.7% for WC) agreed better. VAT volumes could not be estimated reliably by any of the anthropometric measures considered here. TAT volumes in a mixed population could be best estimated by BMI closely followed by WC (roughly 17.5%). A sex-specific consideration reduced the deviations to around 16% for females (BMI and WC) and below 14% for males (WC).

CONCLUSIONS

We suggest the use of sex-specific parameters-BMI or HC for females and WC for males-for the estimation of abdominal SAT and TAT volumes in patients with overweight or obesity.

Visceral fat and attribute-based medicine in chronic kidney disease

Visceral adipose tissue plays a central role in obesity and metabolic syndrome and is an independent risk factor for both cardiovascular and metabolic disorders. Increased visceral adipose tissue promotes adipokine dysregulation and insulin resistance, leading to several health issues, including systemic inflammation, oxidative stress, and activation of the renin-angiotensin-aldosterone system. Moreover, an increase in adipose tissue directly and indirectly affects the kidneys by increasing renal sodium reabsorption, causing glomerular hyperfiltration and hypertrophy, which leads to increased proteinuria and kidney fibrosis/dysfunction. Although the interest in the adverse effects of obesity on renal diseases has grown exponentially in recent years, the relationship between obesity and renal prognosis remains controversial. This may be attributed to the long clinical course of obesity, numerous obesity-related metabolic complications, and patients' attributes. Multiple individual attributes influencing the pathophysiology of fat accumulation make it difficult to understand obesity. In such cases, it may be effective to elucidate the pathophysiology by conducting research tailored to individual attributes from the perspective of attribute-based medicine/personalized medicine. We consider the appropriate use of clinical indicators necessary, according to attributes such as chronic kidney disease stage, level of visceral adipose tissue accumulation, age, and sex. Selecting treatments and clinical indicators based on individual attributes will allow for advancements in the clinical management of patients with obesity and chronic kidney disease. In the clinical setting of obesity-related nephropathy, it is first necessary to accumulate attribute-based studies resulting from the accurate evaluation of visceral fat accumulation to establish evidence for promoting personalized medicine.

Risk of Heart Failure between Different Metabolic States of Health and Weight: A Meta-Analysis of Cohort Studies

We conducted a systematic review of cohort studies comparing the risk of heart failure in people with differing metabolic health and obesity statuses. We searched three electronic databases (PubMed, Web of Science, Scopus), where the studies of the relationships of metabolic health and obesity statuses with heart failure were included. Fixed-effects or random-effects models were used to estimate the summary relative risks [RRs]. Ten cohort studies were selected. Compared with individuals with normal metabolic health and body mass, the pooled RRs (95% confidence intervals) for heart failure were 1.23 (1.17, 1.29) for metabolic healthy overweight individuals, 1.52 (1.40, 1.64) for metabolic healthy individuals with obesity, 1.56 (1.30, 1.87) for metabolically unhealthy normal-weight individuals, 1.75 (1.55, 1.98) for metabolically unhealthy overweight individuals, and 2.28 (1.96, 2.66) for metabolic unhealthy individuals with obesity. A sensitivity analysis suggested that no single study had a substantial effect on the results. The Egger's and Begg's tests showed no evidence of publication bias. People with overweight or obesity were at a higher risk of heart failure, even if metabolically healthy. In addition, compared with metabolically healthy normal-weight individuals; metabolically unhealthy normal-weight individuals, and those with overweight or and obesity, were at higher risk of heart failure.

Metabolic Obesity Phenotypes and Risk of Lung Cancer: A Prospective Cohort Study of 450,482 UK Biobank Participants

(1) Background: The association between metabolic obesity phenotypes and incident lung cancer (LC) remains unclear. (2) Methods: Based on the combination of baseline BMI categories and metabolic health status, participants were categorized into eight groups: metabolically healthy underweight (MHUW), metabolically unhealthy underweight (MUUW), metabolically healthy normal (MHN), metabolically unhealthy normal (MUN), metabolically healthy overweight (MHOW), metabolically unhealthy overweight (MUOW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). The Cox proportional hazards model and Mendelian randomization (MR) were applied to assess the association between metabolic obesity phenotypes with LC risk. (3) Results: During a median follow-up of 9.1 years, 3654 incident LC patients were confirmed among 450,482 individuals. Compared with participants with MHN, those with MUUW had higher rates of incident LC (hazard ratio (HR) = 3.24, 95% confidence interval (CI) = 1.33-7.87, p = 0.009). MHO and MHOW individuals had a 24% and 18% lower risk of developing LC, respectively (MHO: HR = 0.76, 95% CI = 0.61-0.95, p = 0.02; MHO: HR = 0.82, 95% CI = 0.70-0.96, p = 0.02). No genetic association of metabolic obesity phenotypes and LC risk was observed in MR analysis. (4) Conclusions: In this prospective cohort study, individuals with MHOW and MHO phenotypes were at a lower risk and MUUW were at a higher risk of LC. However, MR failed to reveal any evidence that metabolic obesity phenotypes would be associated with a higher risk of LC.

Risk factors in adolescence as predictors of trajectories of somatic symptoms over 27 years

BACKGROUND

Somatic symptoms among adolescents are common, yet little is known about long-term trajectories of somatic symptoms and the factors in adolescence that shape them. We examined individual, family and school-based factors at age 16 as predictors of trajectories of somatic symptoms over 27 years.

METHODS

Participants from the Northern Swedish Cohort (n = 1001) responded to questions about individual factors (e.g. health behaviours), family factors (e.g. contact with parents, social and material adversity) and school satisfaction at age 16; as well as 10 somatic symptoms at ages 16, 18, 21, 30 and 43. Teacher assessments at age 16 included overall ability at school and peer relations. Age 16 predictors of somatic symptom trajectory group membership were analysed using multinomial logistic regression.

RESULTS

Poor contact with mother and poor school satisfaction were significant predictors of adverse symptom trajectories among both men and women. Low birth weight and low parental academic involvement were contributing factors for women, while smoking and social adversity were more relevant factors for men.

CONCLUSIONS

Our findings emphasize the importance of a holistic approach that considers the unique contributions of individual, family and school-based factors in the development of trajectories of somatic symptoms from adolescence to middle age.

Metabolic inflexibility in youth with obesity: Is it a feature of obesity or distinctive of youth who are metabolically unhealthy?

Individuals with obesity have metabolic inflexibility with diminished fasting fat oxidation and blunted increase in respiratory quotient (RQ) in insulin-stimulated states. However, it is unclear if metabolic inflexibility is a characteristic of obesity per se or is unique to youth who have metabolically unhealthy obesity (MUO) compared with metabolically healthy obesity (MHO). We investigated metabolic flexibility in youth with MUO, MHO and normal weight (NW) and compared their metabolic characteristics. Youth (n = 188) were divided, based on cut-off points for in vivo insulin sensitivity (IS) of adolescents with NW, into 137 with MUO and 51 with MHO. Fasting hepatic IS (HIS) from hepatic glucose production by [6,6-² H₂ ]glucose, adipose tissue IS (ATIS) from whole-body lipolysis by [² H₅ ]glycerol, RQ (indirect calorimetry) during fasting and a hyperinsulinemic (80 mU/m² /min)-euglycemic clamp were measured. Youth with MUO versus MHO had blunted ΔRQ (p = .035) and lower HIS and ATIS (both p < .0001), while ΔRQ, HIS and ATIS were not different between youth with MHO and NW. In a pair-matched sub-analyses of 30 MUO and 30 MHO the results were similar to the total cohort. Metabolic inflexibility, does not appear to be a feature of obesity per se rather distinctive of youth with MUO, who also have worse HIS and ATIS compared with youth with MHO.

Hormonal and metabolic profiles of obese and nonobese type 2 diabetes patients: implications of plasma insulin, ghrelin, and vitamin D levels

Type 2 diabetes (T2D) is associated with obesity whereas loss of weight is a feature of the disease; however, the two states are not mutually exclusive. Obesity is linked with changes in hormonal activity and overall body metabolism.

MATERIALS AND METHODS

In this study, 408 T2D patients were recruited in three distinct studies conducted in Bahrain, Saudi Arabia, and Kuwait in three different intervals between 2001 and 2019. In addition to demographics, glycemic and lipid profiles were obtained in all studies, whereas plasma insulin and HOMA-IR, vitamin D, and ghrelin were analyzed in Saudi Arabia. Different techniques such as chemical auto-analyzer, ELISA, chemiluminescent immunoassay, radioimmunoassay were used.

RESULTS

The obese (BMI ≥ 30 kg/m2) compared with nonobese (BMI 18.5 to <30) patients with diabetes were more likely to be women (P < 0.001), smaller in age (P = 0.028), and with shorter disease duration (P = 0.018). Unexpectedly, the glycemic and lipid profiles were consistently comparable between the two groups in the three sites. Furthermore, vitamin D was strikingly lower in obese patients with diabetes (P = 0.007). Finally, plasma ghrelin (P = 0.163), insulin (P = 0.063), and HOMA-IR (P = 0.166) were comparable between obese and nonobese patients with diabetes.

CONCLUSION

Diabetic obesity was significantly associated with female sex, young age, short disease duration, and noticeably low vitamin D, and a trend of high insulin levels. However, the obese and nonobese patients had comparable metabolic profiles with no differences in insulin resistance and ghrelin levels. Further studies, especially at a molecular level, are needed to explore this topic which is barely investigated.

Metabolically healthy obesity in children enrolled in the CANadian Pediatric Weight management Registry (CANPWR): An exploratory secondary analysis of baseline data

Our study purpose was to determine the prevalence of metabolically healthy obesity (MHO) and examine factors associated with MHO in children with obesity. This cross-sectional study was a secondary, exploratory analysis of data that included 2-17 years old with a body mass index (BMI) ≥85th percentile from the CANadian Pediatric Weight management Registry. Children were classified as having MHO or metabolically unhealthy obesity (MUO) using consensus-based criteria. Those with MHO had normal triglycerides, high-density lipoprotein cholesterol, blood pressure, and fasting glucose. Logistic regression was used to examine factors associated with MHO, which included calculating odds ratios (ORs) and 95% confidence intervals (CIs). In total, 945 children were included (mean age: 12.3 years; 51% female). The prevalence of MHO was 31% (n = 297), with lower levels across increasing age categories (2-5 years [n = 18; 43%], 6-11 years [n = 127; 35%], 12-17 years [n = 152; 28%]). Children with MHO were younger, weighed less, and had lower BMI z-scores than their peers with MUO (all p < 0.01). MHO status was positively associated with physical activity (OR: 1.18; 95% CI: 1.01-1.38), skim milk intake (OR: 1.10; 95% CI: 1.01-1.19), and fruit intake (OR: 1.12; 95% CI: 1.01-1.24) and negatively associated with BMI z-score (OR: 0.69; 95% CI: 0.60-0.79), total screen time in hours (OR: 0.79; 96% CI: 0.68-0.92), and intake of fruit flavoured drinks (OR: 0.91; 95% CI: 0.84-0.99). These findings may help guide clinical decision-making regarding obesity management by focusing on children with MUO who are at relatively high cardiometabolic risk.

Prevalence and clinical characteristics of metabolically healthy obese versus metabolically unhealthy obese school children

INTRODUCTION

Children with obesity in the absence of traditional cardiometabolic risk factors (CRF) have been described as metabolically healthy obese (MHO). Children with MHO phenotype has a favorable metabolic profile with normal glucose metabolism, lipids, and blood pressure compared to children with metabolically unhealthy obese (MUO) phenotype. This study aimed to compare several parameters related to obesity between these two groups and to examine the predictors associated with the MHO phenotype.

METHODS

This study included a cross-sectional baseline data of 193 children with obesity (BMI z-score > +2 SD) aged 8-16 years enrolled in MyBFF@school program, a school-based intervention study conducted between January and December 2014. Metabolic status was defined based on the 2018 consensus-based criteria with MHO children had no CRF (HDL-cholesterol > 1.03 mmol/L, triglycerides ≤ 1.7 mmol/L, systolic and diastolic blood pressure ≤ 90^th percentile, and fasting plasma glucose ≤ 5.6 mmol/L). Those that did not meet one or more of the above criteria were classified as children with MUO phenotype.

RESULTS

The prevalence of MHO was 30.1% (95% CI 23.7 - 37.1) among schoolchildren with obesity and more common in younger and prepubertal children. Compared to MUO, children with MHO phenotype had significantly lower BMI, lower waist circumference, lower uric acid, higher adiponectin, and higher apolipoprotein A-1 levels (p < 0.01). Multivariate logistic regression showed that adiponectin (OR: 1.33, 95% CI 1.05 - 1.68) and apolipoprotein A-1 (OR: 1.02, 95% CI 1.01 - 1.03) were independent predictors for MHO phenotype in this population.

CONCLUSIONS

MHO phenotype was more common in younger and prepubertal children with obesity. Higher serum levels of adiponectin and apolipoprotein A-1 increased the possibility of schoolchildren with obesity to be classified into MHO phenotype.

Reduced leukocyte mitochondrial copy number in metabolic syndrome and metabolically healthy obesity

OBJECTIVE

This study aimed to investigate the associations between peripheral blood leukocyte mitochondrial copy number, metabolic syndrome, and adiposity-related body composition phenotypes in a high prevalence population.

METHODS

A single center cross-sectional study was conducted, consisting of 521 middle-aged subjects of Maltese-Caucasian ethnicity. Participants were stratified according to the presence of metabolic syndrome and different metabolic health definitions based on NCEP-ATP III criteria. Relative leukocyte mitochondrial DNA copy number was determined by quantitative polymerase chain reaction and corrected for leukocyte and platelet count. The associations between mitochondrial copy number and metabolic syndrome components was evaluated and adjusted for age and gender.

RESULTS

Significant negative correlations between mtDNA copy number and BMI, waist circumference, triglyceride levels, fasting plasma glucose, HbA1c, HOMA-IR and hsCRP were observed, along with a positive correlation with HDL-C levels. Mitochondrial copy number was lower in individuals with metabolic syndrome. When compared to metabolically healthy normal weight subjects, a reduction in mtDNA copy number was observed in both the metabolically healthy and unhealthy obese categories.

CONCLUSION

Our data supports the association between reduced leukocyte mtDNA copy number, obesity, and metabolic syndrome. This investigation expands on the spectrum of associations between mtDNA copy number and metabolic phenotypes in different populations and underpins the role of mitochondrial dysfunction in the development and progression of metabolic syndrome and its components.

Visceral adiposity index performed better than traditional adiposity indicators in predicting unhealthy metabolic phenotype among Chinese children and adolescents

The relationship between visceral adiposity index (VAI) and unhealthy metabolic phenotype remained unclear in children and adolescents. This study aimed to investigate their association and compared the ability of VAI and traditional adiposity indicators (body mass index, waist circumference and waist-to-height ratio) to predict metabolically unhealthy phenotype among normal-weight, overweight and obese children and adolescents. In this cross-sectional study, 1722 children and adolescents aged 12-18 years were selected by cluster random sampling, underwent a questionnaire survey, physical examination and biochemical tests. Participants were divided into four phenotypes according to the combination of the weight status determined by body mass index (BMI) and metabolic syndrome components. Receiver operating characteristic (ROC) analysis and multivariate logistic regression were used to compare the predictive capacity between VAI and traditional adiposity indicators and their relationship with metabolically unhealthy phenotype. We found that VAI had better performance in predicting metabolically unhealthy phenotype than traditional adiposity indicators, the area under the receiver-operating characteristic curve (AUC) were 0.808 and 0.763 for boys and girls with normal-weight, 0.829 and 0.816 for boys and girls with overweight and obese (all P < 0.001). VAI was most strongly related to metabolically unhealthy phenotype whether or not to adjust the age, the adjusted OR and 95%CI was 6.15 (4.13-9.14) in boys with normal weight, and 5.90 (3.06-11.36), 4.95 (2.35-10.41) in boys and girls with overweight and obese, respectively (all P < 0.001). Our findings suggested VAI could be used as a comprehensive predictor to identify unhealthy metabolic phenotype in children and adolescents.

Association of Metabolically Healthy and Unhealthy Obesity Phenotype with Markers Related to Obesity, Diabetes among Young, Healthy Adult Men. Analysis of MAGNETIC Study

Adipose tissue secretes many regulatory factors called adipokines. Adipokines affect the metabolism of lipids and carbohydrates. They also influence the regulation of the immune system and inflammation. The current study aimed to evaluate the association between markers related to obesity, diabesity and adipokines and metabolically healthy and unhealthy obesity in young men. The study included 98 healthy participants. We divided participants into three subgroups based on body mass index and metabolic health definition: 49 metabolically healthy normal-weight patients, 27 metabolically healthy obese patients and 22 metabolically unhealthy obese patients. The 14 metabolic markers selected were measured in serum or plasma. The analysis showed associations between markers related to obesity, diabesity and adipokines in metabolically healthy and unhealthy obese participants. The decreased level of adipsin (p < 0.05) was only associated with metabolically healthy obesity, not with metabolically unhealthy obesity. The decreased level of ghrelin (p < 0.001) and increased level of plasminogen activator inhibitor-1 (p < 0.01) were only associated with metabolically unhealthy obesity, not with metabolically healthy obesity. The decreased level of adiponectin and increased levels of leptin, c-peptide, insulin and angiopoietin-like 3 protein were associated with metabolically healthy and unhealthy obesity. In conclusion, our data show that metabolically healthy obesity was more similar to metabolically unhealthy obesity in terms of the analyzed markers related to obesity and diabesity.

Children's Lipid Accumulation Product Combining Visceral Adiposity Index is a Novel Indicator for Predicting Unhealthy Metabolic Phenotype Among Chinese Children and Adolescents

PURPOSE

The predictive capacity between children's lipid accumulation product (CLAP) combining visceral adiposity index (VAI), CLAP, and VAI with metabolically unhealthy phenotype remained unclear. This study aimed to compare the ability of CLAP combining VAI, CLAP, VAI and traditional adiposity indicators (body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and waist-to-hip ratio (WHR)) to predict metabolically unhealthy phenotype among Chinese children and adolescents.

PATIENTS AND METHODS

In the cross-sectional study, 1714 children and adolescents aged 12 to 18 were selected by random cluster sampling, underwent a questionnaire survey, physical examination, biochemical tests and body composition was measured by bioelectrical impedance analysis (BIA). Participants were divided into four phenotypes according to BMI and metabolic syndrome components. The logarithmic CLAP (LnCLAP), VAI, BMI, WC, WHtR and WHR were standardized for sex and age using the z-score method (standardized variables: LnCLAP-z, VAI-z, BMI-z, WC-z, WHtR-z and WHR-z).

RESULTS

LnCLAP-z ≥ 1, VAI-z ≥ 1, WC-z ≥ 1, and WHR-z ≥ 1 increased the risk of metabolically unhealthy normal-weight phenotype (the OR and 95% CI were 4.18 (1.75-10.02), 24.05 (12.79-45.21), 6.17 (1.14-33.51), 2.69 (1.07-6.72), respectively), LnCLAP-z ≥ 1, VAI-z ≥ 1 and WC-z ≥ 1 increased the risk of metabolically unhealthy overweight or obese phenotype (the OR and 95% CI were 2.67 (1.40-5.09), 10.30 (3.03-35.03), 2.19 (1.18-4.09), respectively). The area under the ROC curve (AUC) for CLAP combining VAI in the prediction of the metabolically unhealthy phenotype were 0.837 (0.776-0.899) and 0.876 (0.834-0.918) for boys and girls with normal-weight, 0.853 (0.803-0.903) and 0.794 (0.711-0.878) for boys and girls with overweight and obese (all P < 0.001), which were higher than CLAP, VAI, BMI, WC, WHtR and WHR.

CONCLUSION

Among Chinese children and adolescents, CLAP combining VAI was a more effective indicator than CLAP, VAI and traditional adiposity indicators in predicting unhealthy metabolic phenotype.

Metabolically Abnormal But Normal-Weight Individuals Had a Higher Risk of Type 2 Diabetes Mellitus in a Cohort Study of a Chinese Population

Aims

Obesity is a heterogeneous disease in terms of body mass index (BMI) and metabolic status. The purpose of this study was to investigate the risk of type 2 diabetes mellitus (T2DM) in subjects with metabolically abnormal but normal weight (MANW) in China.

Materials and Methods

A prospective cohort with a total of 17,238 participants of the Zhejiang metabolic syndrome cohort was recruited. According to the standard of the Working Group on Obesity in China, general obesity is defined. Metabolic abnormality was defined as two or more abnormal components (elevated triglycerides (TG), low high-density lipoprotein cholesterol (HDL-C), elevated systolic blood pressure (SBP) or diastolic blood pressure (DBP) or use of antihypertensive therapy, and elevated fasting plasma glucose or antidiabetic treatment). The hazard ratio (HR) and its 95% CI were calculated using a multiple regression model, adjusted for the potential confounding factors.

Results

Compared with metabolically normal and normal weight (MNNW) subjects, the metabolically abnormal and obesity/overweight (MAO) subjects had the highest risk of T2DM disease, with an HR of 4.67 (95% CI: 3.23-6.76), followed by MANW subjects (HR = 2.61, 95% CI: 1.74-3.92) and metabolically normal but obesity/overweight (MNO) subjects (HR = 2.09, 95% CI: 1.29-3.38) after adjusting for age, sex, smoking, drinking, physical activity, and family history of diabetes. Compared with that in the MNNW subjects, the HR in MANW subjects was significantly higher than that in MNO subjects. In normal-weight subjects, the HR of T2DM was significantly positively correlated with the number of components with metabolic abnormalities.

Conclusions

MANW subjects had a higher risk of T2DM. MANW subjects should be given more attention in the prevention and control of common chronic diseases.

Are overweight and obesity risk factors for invasive mechanical ventilation in severe coronavirus disease 2019 pneumonia?

OBJECTIVE

Describe the demographic, clinical, and biochemical characteristics of overweight or obese people with severe COVID-19 pneumonia and evaluate its association with mechanical ventilation requirements in a Mexican cohort.

METHODS

Data were obtained from medical electronic records. Patients were divided in three groups according to the World Health Organization (WHO) classification of body mass index (BMI): lean, overweight and obese. Baseline characteristics and clinical course were compared among these 3 groups.

RESULTS

The study included a total of 355 patients with confirmed COVID-19 diagnoses. Patients with obesity and overweigh, according to the WHO classification, had no significantly increased risk of requiring intubation and invasive mechanical ventilation (IMV) compared to lean subjects, with an odds ratio (OR) of 1.82 (95% CI, 0.94-3.53). A post hoc and multivariate analysis using a BMI > 35 kg/m2 to define obesity revealed that subjects above this cut off had as significantly increased risk of requiring IMV after with an OR of 2.86 (95% CI, 1.09-7.05).

CONCLUSION

We found no higher risk of requiring IMV in patients with overweight or obesity while using conventional BMI cutoffs. According to our sensitivity analyses, the risk of IMV increases in patients with a BMI over 35 kg/m2.

Metabolically healthy obesity and risk of non-alcoholic fatty liver disease severity independent of visceral fat

BACKGROUND AND AIM

Obesity and metabolic conditions may be related to non-alcoholic fatty liver disease (NAFLD). The study assesses the risk of NAFLD according to obesity and metabolic health status in a community-based population.

METHODS

A total of 1651 subjects were recruited from the community. Individuals were categorized into four groups according to obesity status (defined as a body mass index ≥ 25 kg/m² ) and metabolically healthy status: metabolically healthy nonobesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy nonobesity (MUHNO), and metabolically unhealthy obesity (MUHO). NAFLD was diagnosed based on a semiquantitative ultrasonography measurement. Visceral fat was assessed through bioelectrical impedance analysis and is shown by tertile (T1, T2, and T3). A proportional odds model was used to assess the cumulative risk of NAFLD.

RESULTS

The NAFLD prevalence was 26.7%, 62.8%, 47.0%, and 76.7% in subjects with MHNO, MHO, MUHNO, and MUHO, respectively (P < 0.0001). After adjustment for age, sex, exercise habits, alcohol consumption, cigarette smoking, and visceral fat, the odds ratios for more severe NAFLD were 2.44 (95% confidence interval [CI]: 1.64-3.65), 2.75 (95% CI: 1.91-3.94), and 7.41 (95% CI: 4.94-11.12) in the MHO, MUHNO, and MUHO groups, respectively, compared with the MHNO group. In addition, the odds ratios for more severe NAFLD significantly increased with the increase in visceral fat level (T2 vs T1: 3.83, 95% CI: 2.65-5.53; T3 vs T1: 9.17, 95% CI: 5.33-15.79).

CONCLUSION

Both obesity and metabolically unhealthy status were associated with a higher risk of NAFLD independent of visceral fat level.

The Role of Gut Microbiota and Its Produced Metabolites in Obesity, Dyslipidemia, Adipocyte Dysfunction, and Its Interventions

Obesity is becoming an increasing problem worldwide and is often, but not invariably, associated with dyslipidemia. The gut microbiota is increasingly linked to cardiovascular disease, nonalcoholic fatty liver disease, and type 2 diabetes mellitus. However, relatively little focus has been attributed to the role of gut-microbiota-derived metabolites in the development of dyslipidemia and alterations in lipid metabolism. In this review, we discuss current data involved in these processes and point out the therapeutic potentials. We cover the ability of gut microbiota metabolites to alter lipoprotein lipase action, VLDL secretion, and plasma triglyceride levels, and its effects on reverse cholesterol transport, adipocyte dysfunction, and adipose tissue inflammation. Finally, the current intervention strategies for treatment of obesity and dyslipidemia is addressed with emphasis on the role of gut microbiota metabolites and its ability to predict treatment efficacies.

Joint associations of metabolically healthy abdominal obesity and non-alcoholic fatty liver disease with prediabetes and diabetes in Chinese adults

INTRODUCTION

We aimed to evaluate the joint associations of metabolically healthy abdominal obesity (MHAO) with non-alcoholic fatty liver disease (NAFLD) on risks of diabetes and prediabetes.

RESEARCH DESIGN AND METHODS

Baseline information of 1318 adults with abdominal obesity (waist circumference ≥90 cm for men and 80 cm for women) from an ongoing cohort study in Xiamen, China were analyzed. Metabolic health was identified as none of the criteria of metabolism syndrome, except for obesity, was met.

RESULTS

MHAO and metabolically unhealthy abdominal obesity (MUAO) were identified on 173 (13.1%) and 1145 (86.9%) subjects. NAFLD was further diagnosed on 60 (34.7%) in MHAO and 721 (63.0%) in MUAO groups (p<0.001). Both MUAO (vs MHAO) and NAFLD (vs non-NAFLD) were independently associated with increased risks of diabetes as well as prediabetes plus diabetes, with the adjusted ORs (95% CIs) of 9.40 (3.38 to 26.14) and 2.02 (1.47 to 2.77), respectively. Compared with MHAO and non-NAFLD, MHAO and NAFLD showed significantly increased risks of prediabetes plus diabetes with the adjusted ORs (95% CIs) of 2.87 (1.32 to 6.27, p=0.008). And there were significantly positive trends between increasing categories jointly by MHAO and NAFLD (from MHAO and non-NAFLD, MHAO and NAFLD, MUAO and non-NAFLD to MUAO and NAFLD) with risks of diabetes and prediabetes plus diabetes (both trend tests: p<0.001).

CONCLUSIONS

About 35% of subjects with MHAO accompanied by NAFLD showed excessive risk of prediabetes plus diabetes compared with MHAO and non-NAFLD. Thus, NAFLD should be screened and intervened even for those subjects with metabolically healthy obesity (MHO) and should be considered as one additional criterion when defining and diagnosing MHO.

A genetic analysis identifies haplotype at adiponectin locus: Association with the metabolic health and obesity phenotypes

BACKGROUND

Obesity and metabolic syndrome frequently co-exist and define obese individuals into different obesity phenotypes, such as metabolically healthy obese (MHO), metabolically unhealthy obese (MUO) and metabolically unhealthy normal weight (MUNW). Growing evidence suggests that genetic predisposition and environmental factors can explain the heterogeneity among these phenotypes.

METHODS

We conducted a case-control study including 130 MHO, 251 MUNW, 208 MUO and 336 health controls by genotyping 2 SNPs (rs2241766, rs1501299) in ADIPOQ to investigate possible associations between SNPs in the ADIPOQ gene with susceptibility to three obese phenotypes respectively in Chinese Han population. Unconditional logistic regressions were used to detect the association between ADIPOQ SNPs and MHO/MUNW/MUO risks.

RESULTS

Variant G allele of rs2241766 was associated with a reduced odds of MUO (additive model: Adjusted OR = 0.55; 95% CI = 0.40-0.75; P < 0.001) and no evidence of any significant association between rs2241766 and MHO phenotype (additive model: Adjusted OR = 0.84; 95% CI = 0.61-1.16; P = 0.306) or MUNW phenotype (additive model: Adjusted OR = 0.95; 95% CI = 0.73-1.24; P = 0.720) was found. Minor allele T of rs1501299 were significantly associated with decreased risk of MHO (Adjusted OR = 0.53; 95% CI = 0.37-0.76; P < 0.001) and MUNW (Adjusted OR = 0.63; 95% CI = 0.48-0.83; P = 0.001) in additive genetic model after correction for multiple testing.

CONCLUSIONS

The variant G allele of rs2241766 was negatively associated with risk of MUO and variant T allele of rs1501299 exhibited reduced odds for MHO and MUNW. Beyond that, future studies are warranted to validate and extend our findings.

Metabolically healthy obesity and metabolically obese normal weight: a review

Despite the general relationship between obesity and its co-morbidities, there are both obese individuals who scarcely present the associated pathologies (metabolically healthy obese; MHO) and individuals who present obesity alterations despite having normal weight (metabolically obese normal weight; MONW). It is still difficult to define metabolically MHO and MONW individuals because different classifications have been used in the studies reported. Indeed, different inclusion criteria have been used to discriminate between metabolically healthy and metabolically unhealthy subjects. Due to this and other reasons, such as differences in ethnicity, genetics, and lifestyle of the populations, data concerning the prevalence of MHO and MONW are very variable. The main determinants of MHO are type of growth (hypertrophy or hyperplasia), anatomical location, inflammation of adipose tissue, ectopic fat accumulation, genetic factors, and lifestyles factors. In the case of MONW, the main determinants are genetic background and lifestyle factors. With regard to treatment, it is not clear whether MHO subjects would benefit from traditional lifestyle interventions, based on diet energy restriction and increased physical activity. For MONW subjects, there is still no specialized treatment, and the therapies are the same as those used in obese subjects.

Does Proteomic Mirror Reflect Clinical Characteristics of Obesity?

Obesity is a frightening chronic disease, which has tripled since 1975. It is not expected to slow down staying one of the leading cases of preventable death and resulting in an increased clinical and economic burden. Poor lifestyle choices and excessive intake of “cheap calories” are major contributors to obesity, triggering type 2 diabetes, cardiovascular diseases, and other comorbidities. Understanding the molecular mechanisms responsible for development of obesity is essential as it might result in the introducing of anti-obesity targets and early-stage obesity biomarkers, allowing the distinction between metabolic syndromes. The complex nature of this disease, coupled with the phenomenon of metabolically healthy obesity, inspired us to perform data-centric, hypothesis-generating pilot research, aimed to find correlations between parameters of classic clinical blood tests and proteomic profiles of 104 lean and obese subjects. As the result, we assembled patterns of proteins, which presence or absence allows predicting the weight of the patient fairly well. We believe that such proteomic patterns with high prediction power should facilitate the translation of potential candidates into biomarkers of clinical use for early-stage stratification of obesity therapy.

Effect of Metabolic Health and Obesity Phenotype on Risk of Diabetes Mellitus: A Population-Based Longitudinal Study

BACKGROUND

Epidemiologic evidence on body mass index (BMI)-metabolic status phenotypes and diabetes risk remains controversial, especially for metabolically healthy obesity (MHO). We aimed to examine the effect of metabolic health and obesity phenotype on diabetes risk in the Chinese population.

METHODS

A population-based cohort study was carried out. The baseline survey was conducted in 2017, with two follow-up visits in 2018 and 2020. Diabetes was defined based on the criteria of the World Health Organization. Robust generalized estimating equation models with a binary distribution using a log link and exchange structure were applied for the pooled analysis sample.

RESULTS

A total sample of 9623 observations was pooled for the longitudinal data analysis. The average follow-up time was 1.64 years per person and the overall incidence density of diabetes was 6.94% person-years. Decreased diabetes risk was found in metabolically healthy overweight phenotype (RR = 0.65; 95% CI = 0.47-0.90) and no significant associations were detected for the MHO individuals (RR = 0.99; 95% CI = 0.63-1.53) compared with those of metabolically healthy normal weight, in contrast to metabolically unhealthy normal weight (MU-NW) (RR = 1.81; 95% CI = 1.28-2.55), metabolically unhealthy overweight (MU-OW) (RR = 2.02; 95% CI = 1.57-2.61) and metabolically unhealthy obesity (MUO) (RR = 2.48; 95% CI = 1.89-3.26) phenotypes. Significant associations between BMI-metabolic status phenotypes and diabetes were found in both males and females.

CONCLUSION

The MUO phenotype needs to be accorded much more importance. MU-NW and MU-OW are also important component for targeted prevention. Our findings can be targeted for optimizing preventive strategies to mitigate the obviously increased prevalence of diabetes.

Metabolic healthy obesity is associated with higher incidence of mild decrease estimate glomerular rate in rural northeast Chinese

BACKGROUND

Metabolic healthy obesity (MHO), a phenotype of obesity, seems to be associated with a lower risk of cardiovascular disease. However, MHO has a close relationship with a higher incidence of metabolic syndrome and diabetes. This study aimed to investigate the prevalence of MHO at baseline, the changes in the obese metabolic phenotype at follow-up and the relationship of this phenotype with the incidence of mildly reduced estimated glomerular filtration rate (eGFR) in rural Northeast Chinese.

METHODS

The Chronic Kidney Disease Epidemiology (CKD-EPI) equation was used to calculate eGFR. A total of 4903 participants aged ≥35 years with eGFR > 90 ml/min/1.73 m² at baseline were enrolled and successfully followed. All participants completed the questionnaires, anthropometric measurements, and blood tests during baseline and follow-up. Mild renal dysfunction was defined as mildly reduced eGFR between 60 and 90 ml/min/1.73 m².

RESULTS

The prevalence of MHO was 20.0% at baseline (19.0% for women and 21.1% for men), which was secondary to metabolic abnormal obesity (MAO) (24.4, 27.2% for women and 21.5% for men). A total of 38.4% of women and 38.9% of men experienced phenotypic changes during follow-up. The cumulative incidence of mildly reduced eGFR in the MHO group was 20.1% (17.7% for women and 22.3% for men), which was also secondary to the incidence in the MAO group (20.8, 18.6% for women and 23.5% for men). After adjusting for age, current smoking, current drinking, chronic diseases, LDL-C, ALT, and AST, MHO was associated with a higher incidence of mildly reduced eGFR among women [OR (95% CI) =1.6 (1.2, 2.3)] and men [OR (95% CI) =1.6(1.2, 2.1)], whereas MAO was related to a higher incidence of mildly reduced eGFR among men only [OR (95% CI) =1.7 (1.3, 2.3)].

CONCLUSION

MHO was associated with a higher incidence of mildly reduced eGFR in both sexes; however, there was a specific relationship between MAO and mildly reduced eGFR in men only. Therefore, it is necessary to monitor kidney function among participants with both MHO and MAO.

Abdominal subcutaneous fat quantification in obese patients from limited field-of-view MRI data

Different types of adipose tissue can be accurately localized and quantified by tomographic imaging techniques (MRI or CT). One common shortcoming for the abdominal subcutaneous adipose tissue (ASAT) of obese subjects is the technically restricted imaging field of view (FOV). This work derives equations for the conversion between six surrogate measures and fully segmented ASAT volume and discusses the predictive power of these image-based quantities. Clinical (gender, age, anthropometry) and MRI data (1.5 T, two-point Dixon sequence) of 193 overweight and obese patients (116 female, 77 male) from a single research center for obesity were analyzed retrospectively. Six surrogate measures of fully segmented ASAT volume (V_ASAT) were considered: two simple ASAT lengths, two partial areas (A_p-FH, A_p-ASIS) and two partial volumes (V_p-FH, V_p-ASIS) limited by either the femoral heads (FH) or the anterior superior iliac spine (ASIS). Least-squares regression between each measure and V_ASAT provided slope and intercept for the computation of estimated ASAT volumes (V^~_ASAT). Goodness of fit was evaluated by coefficient of determination (R²) and standard deviation of percent differences (s_d%) between V^~_ASAT and V_ASAT. Best agreement was observed for partial volume V_p-FH (s_d% = 14.4% and R² = 0.78), followed by V_p-ASIS (s_d% = 18.1% and R² = 0.69) and AWF_ASIS (s_d% = 23.9% and R² = 0.54), with minor gender differences only. Other estimates from simple lengths and partial areas were moderate only (s_d% > 23.0% and R² < 0.50). Gender differences in R² generally ranged between 0.02 (d_ven) and 0.29 (A_p-FH). The common FOV restriction for MRI volumetry of ASAT in obese subjects can best be overcome by estimating V_ASAT from V_p-FH using the equation derived here. The very simple AWF_ASIS can be used with reservation.

Increased Stroke Risk in Metabolically Abnormal Normal Weight: a 10-Year Follow-up of 102,037 Participants in China

The purpose of this study was to investigate the risks of stroke in subjects with metabolically abnormal normal weight (MANW) in China. We recruited 102,037 participants from the Zhejiang Metabolic Syndrome Cohort and the Kailuan cohort. The mean years of follow-up were 9.9 years. General obesity was defined by body mass index (BMI) ≥ 28, overweight by BMI < 28 and ≥ 24, and normal weight by BMI < 24 and ≥ 18.5. Metabolic abnormality was defined as two or more abnormal components (elevated triglycerides, low high-density lipoprotein cholesterol, elevated systolic blood pressure or diastolic blood pressure, or use of antihypertensive drug therapy, elevated fasting plasma glucose, or antidiabetic treatment). A multiple Cox regression model was used to calculate hazard ratio (HR) and its 95% confidence interval (CI), adjusted by potential confounding factors. Overall HR of the risks in two cohorts was calculated by a meta-analysis. Compared with the subjects who were metabolically normal with normal weight (MNNW), the pooled HR for stroke in MANW subjects was 1.82 (95% CI, 1.59-2.07). The risks of stroke in MANW subjects were significantly lower than that in subjects with metabolically abnormal obesity (MAO), but higher than that in those with metabolically normal obesity (MNO) (P < 0.05). These associations remained in the subtypes of cerebral infarction and cerebral hemorrhage. In normal-weight subjects, the HR for stroke was significantly positively correlated with the number of abnormal metabolic components (P_trend < 0.001). In brief, metabolic abnormality increased the risk of stroke irrespective of obesity status. MANW individuals showed a greater risk of stroke, and this risk was positively correlated with the number of abnormal metabolic components.

Metabolically Healthy Obesity: Presence of Arterial Stiffness in the Prepubescent Population

Aim: Arteriosclerotic cardiovascular disease, one of the world’s leading causes of death, first manifests itself at an early age. The identification of children who may have increased cardiovascular risk in the future could be an important prevention strategy. Our aim was to assess the clinical, analytical, and dietary variables associated with arterial stiffness (AS), measured by carotid-femoral pulse wave velocity (cfPWV) in a prepubescent population with metabolically healthy obesity (MHO). Subjects and Methods: A cross-sectional study in prepubescent subjects with obesity who had ≤1 metabolic syndrome criteria (abdominal perimeter and blood pressure ≥90th percentile, triglycerides >150 mg/dL, HDL-cholesterol <40 mg/dL, fasting plasma glucose ≥100 mg/dL) was conducted. Adherence to Mediterranean Diet, blood pressure, BMI, waist/height ratio (WHtR), glycemic status, lipid profile, and cfPWV were analyzed. 75 MHO children (boys: 43; girls: 32; p = 0.20) (age = 10.05 ± 1.29 years; BMI = 25.29 ± 3.5 kg/m2) were included. Results: We found a positive correlation between cfPWV and weight (r = 0.51; p < 0.0001), BMI (r = 0.44; p < 0.0001), WHtR (r = 0.26; p = 0.02), fasting insulin levels (r = 0.28; p = 0.02), and insulin resistance (Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) index) (r = 0.25; p = 0.04). Multiple linear regression analysis identified BMI and HOMA-IR as independent parameters associated with cfPWV. Conclusions: Prepubescent children with obesity who were shown to be metabolically healthy presented with arterial stiffness, which is closely related to BMI and the state of insulin resistance.

Are young Iranian women with metabolically healthy obesity at increased risk of CVD incidence?

Background

The association between the Metabolically Healthy Obese (MHO) phenotype in the absence of metabolic syndrome and subsequent cardiovascular disease remains unclear.

Objectives

We examined the association between MHO and CVD risk in young Iranian women.

Methods

We studied 183 women aged 20-35 years from a population of 308 candidates. We classified participants into 4 phenotypes. We measured body composition, blood pressure, and biochemical factors in all participants.

Results

The Metabolically Healthy Normal Weight (MHNW) and Normal Weight Obese (NWO) phenotypes had no statistical differences in any biochemistry variables. FBS, TG, LDL/HDL, Cholesterol/HDL, hs-CRP, and atherogenic index of plasma (AIP) were all higher in Metabolically Unhealthy Obese (MUO) than MHO individuals, whereas HDL was higher in MHO than in MUO individuals. LDL/HDL and hs-CRP were higher in MHO participants than MHNW participants, whereas HDL-c was higher in MHNW than MHO.

Conclusions

Results of the present study demonstrate that young women displaying the MHO phenotype have a favorable metabolic profile as shown by lower FBS, TG, LDL-c/HDL, Cho/HDL, hs-CRP, and AIP and higher HDL levels than the MUO phenotype. However, MHO individuals were still at greater risk of CVD incidence (lower HDL and higher hs-CRP levels) than MHNW individuals.

Association Metabolic Obesity Phenotypes with Cardiometabolic Index, Atherogenic Index of Plasma and Novel Anthropometric Indices: A Link of FTO-rs9939609 Polymorphism

BACKGROUND

The role of metabolic states in cardiovascular risks among individuals with varying degrees of obesity is unknown. The study aimed to compare cardiometabolic index (CMI), atherogenic index of plasma (AIP), lipid accumulation product (LAP) and novel anthropometric indices in metabolic and non-metabolically obese individual with regard to the role of FTO gene in Iranian adults.

METHODS

In total, 165 individuals were recruited into this cross-sectional study. Individuals grouped into four groups: metabolic healthy normal-weight (MHNW) individuals, metabolically unhealthy normal-weight (MUNW) individuals, metabolically healthy obese (MHO) individuals and metabolic unhealthy obese (MUO) individuals. The dietary intake was evaluated by food frequency questionnaire (FFQ). The cardiovascular indices (CMI, AIP and LAP) were calculated. A variety of anthropometric indices were calculated, including body adiposity Index (BAI), weight-adjusted-waist index (WWI), A body shape index (ABSI) and waist-height ratio (WHR). The genotypes of FTO-rs9939609 subjects were detected by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP).

RESULTS

The individuals with metabolically unhealthy phenotypes (MUO, MUNW) have higher levels of triglyceride and cardiovascular indices (AIP, LAP and CMI) than the individuals with metabolic healthy phenotypes (MHO, MHNW). With a similar degree of obesity, the anthropometric indices (BAI, WWI and WHR) levels were higher in metabolic unhealthy groups than metabolically healthy groups. The highest frequency of obesity-risk allele AA of FTO gene was observed in MUO, MHO, MUNW and MHNW, respectively.

CONCLUSION

Normal-weight individuals with metabolic unhealthy status are at higher risk for cardiovascular diseases than obese individuals with metabolically healthy status. The genotype frequencies of obesity-risk allele AA of FTO gene were higher in obesity phenotypes than metabolic phenotypes.

Sociodemographic and metabolic risk characteristics associated with metabolic weight categories in the Women's Health Initiative

To identify sociodemographic and metabolic correlates of weight categories in postmenopausal women.

Methods

The Women's Health Initiative enrolled 161 808 postmenopausal women ages 50-79. We included those free of cardiovascular disease (CVD) and with CVD risk factors and biomarkers (n = 19 412). Normal weight was defined as a BMI ≥18.5 and <25 kg/m² and waist circumference <88 cm and overweight/obesity as a BMI ≥25 kg/m² or waist circumference ≥88 cm. Metabolically healthy was based on <2 and metabolically unhealthy ≥2 traits: triglycerides ≥150 mg/dl, systolic blood pressure (BP) ≥130 mmHg or diastolic BP ≥85 mmHg or antihypertensives or diuretics, fasting glucose ≥100 mg/dl or diabetes medication, and high-density lipoprotein cholesterol <50 mg/dl. Polytomous multinomial logistic regression with generalized link logit function provided the odds of metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUHNW), metabolically healthy overweight/obese (MHO), and metabolically unhealthy overweight/obese (MUHO) according to demographic and risk factor measures.

Results

Among the 19 412 postmenopausal women, 2369 (12.2%) participants had prevalent diabetes. Advanced age was associated with an increased odds of MUHNW as compared with the MHNW after adjusting for covariates [odds ratio (OR) 1.04, P < 0.0001]. Black/African American ethnicity was associated with a decreased odds of MUHNW (OR 0.64, P < 0.0001) and MUHO (OR 0.77, P = 0.0004), while an increased odds for MHO (OR 1.50, P < 0.0001) as compared with White MHNW.

Conclusions

Advanced age and ethnicity are important indicators of metabolic weight categories among postmenopausal women.

Preoperative intragastric balloon in morbid obesity is unable to decrease early postoperative morbidity of bariatric surgery (sleeve gastrectomy and gastric bypass): a clinical assay

INTRODUCTION

There are few studies that investigate the usefulness of the preoperative intragastric balloon (IGB). This study will evaluate if pre-surgical weight loss with IGB reduces morbidity and mortality after surgery.

METHOD

Prospective randomised study of patients with morbid obesity treated with gastric bypass or vertical gastrectomy, with two arms: the balloon arm (B-arm), where an IGB was inserted within the 6 months before surgery, and the control arm (C-arm).

RESULTS

The study included 66 patients: 65.6% women, 69.6% with bypass. Age: 43 years (SD 10.2) B-arm and 42.6 years (SD 9.2) in the C-arm. We found 34.4% therapeutic failures in IGB. The mean body weight loss, %EWL and BMI reduction before surgery was 16.2 kg (SD 9.84) B-arm versus 4.7 (SD 8.70) in the C-arm, 23.6% versus 4.7% (p < 0.001) and 6.04 versus 1 (p < 0.001), respectively. The hospital stay was 7 days (p25-75: 5-8) B-arm and 7 days (p25-75: 5-9) in the C-arm (p = 0.937). Post-surgical morbidity with IGB was 25% versus 29.5% in the C-arm, p = 0.689. The number needed to treat (NNT) to prevent of post-surgical morbidity was 23 patients. The B-arm presented 54.5% moderate-severe post-surgical adverse events (12.5%) versus 82.6% in the C-arm (23.5%), p = 0.111. The cost of placing a balloon was more than 4000 Euros each.

CONCLUSIONS

The preoperative balloon does not achieve a reduction in the post-surgical morbidity, nor does it reduce the hospital stay or rate of re-operations. The balloon achieves a higher weight loss result when compared to a diet programme, its added cost must also be given due consideration.

TRAIL REGISTRY

This study has been registered on ClinicalTrials.gov with the Identifier: NCT01998243 (November 28, 2013).

Obesity and Breast Cancer: The Role of Crown-Like Structures in Breast Adipose Tissue in Tumor Progression, Prognosis, and Therapy

Obesity is associated with increased risk and aggressiveness of many types of cancer. Women with obesity and breast cancer are more likely to be diagnosed with larger and higher-grade tumors and have higher incidence of metastases than lean individuals. Increasing evidence indicates that obesity includes systemic, chronic low-grade inflammation, and that adipose tissue can act as an important endocrine site, secreting a variety of substances that may regulate inflammation, immune response, and cancer predisposition. Obesity-associated inflammation appears to be initially mediated by macrophage infiltration into adipose tissue. Macrophages can surround damaged or necrotic adipocytes, forming "crown-like" structures (CLS). CLS are increased in breast adipose tissue from breast cancer patients and are more abundant in patients with obesity conditions. Moreover, the CLS index-ratio from individuals with obesity seems to influence breast cancer recurrence rates and survival. In this review, we discuss the most recent cellular and molecular mechanisms involved in CLS establishment in the white adipose tissue of women with obesity and their implications for breast cancer biology. We also explain how CLS influence the tumor microenvironment and affect breast cancer behavior. Targeting breast adipose tissue CLS can be a crucial therapeutic tool in cancer treatment, especially in patients with obesity.

Effects of metformin in obesity treatment in different populations: a meta-analysis

OBJECTIVE

Some studies have shown that metformin can reduce body weight. However, metformin has not been officially approved as a medicine for weight loss because its effect on different populations remains inconsistent. This meta-analysis aimed to summarize the weight loss effect of metformin quantitatively.

METHOD

The randomized controlled and high-quality case-control trials of metformin monotherapy in obesity treatment were eligible. Baseline body mass index (BMI) was chosen as a self-control to compare the changes in BMI of different populations before and after treatment. All changes were calculated as differences between the final and initial BMI values (with negative values indicating a decrease). Results were presented as weighted mean difference (WMD) with a 95% confidence interval (CI 95%). Subgroup analysis was performed based on baseline BMI, age, daily dose, and duration of medication.

RESULTS

A total of 21 trials (n = 1004) were included, and the meta-analysis of metformin treatment in different populations showed that metformin has a modest reduction in the BMI of included participants (WMD -0.98; 95% CI, -1.25 to -0.72), and the reduction of BMI was most significant in the simple obesity population (WMD -1.31; 95% CI, -2.07 to -0.54). The subgroup analysis showed that metformin treatment significantly reduced BMI in obesity patients with a BMI >35kg/m2 (WMD -1.12; 95% CI, -1.84 to -0.39) compared with before treatment. BMI in the high dose group decreased by 1.01 units (WMD-1.01; 95% CI, -1.29 to -0.73) and BMI did not continue to decrease significantly after treatment of more than 6 months.

CONCLUSION

Patients treated with metformin experienced about a one-unit reduction in BMI at the end of treatment. But whether this decreased value produced enough weight loss (5% of baseline body weight) to qualify as a "weight loss drug" as current guidelines require, requires larger specific randomized control trials.

Metabolically Healthy Obesity and Bariatric Surgery

A peculiar category of persons with obesity lacking common metabolic disturbances has been depicted and termed as metabolically healthy obesity (MHO). Yet, although MHO patients are free of obesity-associated complications, they might not be entirely precluded from developing cardio-metabolic disorders. Among patients with morbid obesity (MO) who are referred to bariatric surgery, a subset of metabolically healthy MO (MHMO) has been identified and the question arises if these patients would benefit from surgery in terms of mitigating the peril of cardio-metabolic complications. We revisited the pathophysiological mechanisms that define MHO, the currently available data on the cardio-metabolic risk of these patients and finally we reviewed the benefits of bariatric surgery and the urge to better characterize MHMO before submission to surgery.

[Diagnostic accuracy of the tri-ponderal mass index in identifying the unhealthy metabolic obese phenotype in obese patients]

INTRODUCTION

The metabolically healthy obese (MHO) phenotype defines obese patients who have preserved insulin sensitivity and absence of metabolic complications. This phenotype is associated with a lower risk of cardiovascular disease and type2 diabetes in adulthood.

OBJECTIVES

To determine the prevalence of MHO and the metabolically unhealthy obesity (MUO) phenotype in a cohort of obese children and adolescents and to establish the predictive capacity of the tri-ponderal mass index (TMI) and other anthropometric parameters in order to identify these patients.

PATIENTS AND METHODS

A cross-sectional study was conducted on 239 obese patients (125males) from 8 to 18years of age. Grade3 obesity was present in 45.9% of the patients. ROC curves were used to find the best cut-off point for: TMI, body mass index (BMI), BMI z-score (BMIzs), and waist/height index (WHI). MHO components: plasma blood glucose, plasma triglycerides, HDL-cholesterol, and blood pressure.

RESULTS

The prevalence of MUO in the study cohort was 62.4%. No differences between genders were observed, and it was increasing with the age and obesity degree. The TMI has a sensitivity of 75.8 and a specificity of 42.2 to identify the MUO patients. The best cut-off point for TMI is 18.7kg/m³, for BMI it was 30.4kg/m², for BMIzs +3.5SD, and 0.62 for WHI.

CONCLUSIONS

The diagnostic accuracy of TMI in identifying obese adolescents with metabolic risk was similar to BMI and WHI. However, the TMI is much simpler to use and simplifies the categorization of the obesity in both genders.

Impact of the Definition of Metabolically Healthy Obesity on the Association with Incident Cardiovascular Disease

Background: Whether subjects with metabolically healthy obesity (MHO) have an increased risk of cardiovascular disease (CVD) is controversial. Some of this discrepancy could be due to differences in the definition of MHO. Therefore, we investigated how the definition of MHO affected the risk of CVD. Methods: In the Uppsala Longitudinal Study of Adult Men (ULSAM) cohort (total n = 2122, mean age 50 years), obese (n = 134), overweight (n = 845), and normal weight (n = 1143) individuals were subdivided according to the number of Metabolic Syndrome (MetS) risk factors (excluding waist circumference). During a median follow-up of 28.0 years, 877 individuals experienced a CVD event (defined as fatal or nonfatal myocardial infarction, stroke, or heart failure). Results: All obese groups, except that without any MetS risk factors (n = 3), showed an increased risk compared to the control group of normal weight without any MetS risk factors (n = 235), ranging from a hazard ratio (HR) of 3.0 (95% confidence interval [CI] 1.7-5.3, P = 0.0002) in those with one MetS risk factor to HR 5.5 (95% CI 3.0-9.8, P < 0.00001) in those with four MetS risk factors. The overweight group without any MetS risk factor (n = 74) showed a similar risk of incident CVD as the normal weight group, whereas all other overweight groups showed an increased risk with increasing number of MetS risk factors. Conclusions: The results suggest that the definition of MHO played a major role on the risk of CVD. No increased risk was seen in overweight/obese individuals with no MetS risk factor, but they were very rare.

Does healthy obesity exist in the elderly? Findings from the Northern Shanghai Study

BACKGROUND AND AIMS

Metabolic unhealthiness and obesity are both associated with an increased risk of cardiovascular disease. We aimed to investigate the significance of metabolic unhealthiness and obesity in organ damages in a community-based elderly cohort.

METHODS AND RESULTS

A total of 3325 elderly participants (>65 years old) were recruited in northern Shanghai. Associations of metabolic status and obesity with organ damages were investigated. In all, 1317 (39.6%) participants were metabolically unhealthy and 481 (14.5%) were obese. Compared with metabolically healthy nonobese (MH-nonobese) individuals, metabolically healthy obese subjects had a greater left ventricular mass index (LVMI) and pulse wave velocity (PWV). Metabolically unhealthy subjects, regardless of their obesity status, had greater organ damage parameters including E/Ea, LVMI, PWV, and urine albumin-creatinine ratio (UACR) than MH-nonobese subjects (all P < 0.05). After multivariate adjustments, both metabolic unhealthiness and obesity increased the risk of left ventricular hypertrophy (LVH) (OR 1.31, 95% CI 1.10-1.57 and OR 1.63, 95% CI 1.30-2.04), diastolic dysfunction (OR 1.33, 95% CI 1.06-1.67 and OR 1.51, 95% CI 1.14-1.99), and lower extremity atherosclerosis (OR 1.44, 95% CI 1.11-1.85 and OR 2.01, 95% CI 1.49-2.70). Metabolic unhealthiness was also associated with arterial stiffness, microalbuminuria and chronic kidney disease (all P < 0.05). In a subgroup analysis, metabolic unhealthiness was associated with more organ damages in nonobese subjects, and obesity was associated with LVH and lower extremity atherosclerosis regardless of metabolic status.

CONCLUSION

Both obesity and metabolic unhealthiness were associated with organ damages. Metabolic unhealthiness was associated with more organ damages, especially in nonobese individuals. Even healthy obesity was significantly associated with cardiac and vascular impairment.

REGISTRATION NUMBER FOR CLINICAL TRIALS

NCT02368938.

Metabolically Healthy Obesity

Obesity contributes to reduced life expectancy, impaired quality of life, and disabilities, mainly in those individuals who develop cardiovascular diseases, type 2 diabetes, osteoarthritis, and cancer. However, there is a large variation in the individual risk to developing obesity-associated comorbid diseases that cannot simply be explained by the extent of adiposity. Observations that a proportion of individuals with obesity have a significantly lower risk for cardiometabolic abnormalities led to the concept of metabolically healthy obesity (MHO). Although there is no clear definition, normal glucose and lipid metabolism parameters-in addition to the absence of hypertension-usually serve as criteria to diagnose MHO. Biological mechanisms underlying MHO lower amounts of ectopic fat (visceral and liver), and higher leg fat deposition, expandability of subcutaneous adipose tissue, preserved insulin sensitivity, and beta-cell function as well as better cardiorespiratory fitness compared to unhealthy obesity. Whereas the absence of metabolic abnormalities may reduce the risk of type 2 diabetes and cardiovascular diseases in metabolically healthy individuals compared to unhealthy individuals with obesity, it is still higher in comparison with healthy lean individuals. In addition, MHO seems to be a transient phenotype further justifying therapeutic weight loss attempts-even in this subgroup-which might not benefit from reducing body weight to the same extent as patients with unhealthy obesity. Metabolically healthy obesity represents a model to study mechanisms linking obesity to cardiometabolic complications. Metabolically healthy obesity should not be considered a safe condition, which does not require obesity treatment, but may guide decision-making for a personalized and risk-stratified obesity treatment.

Increased incidence of bladder cancer with metabolically unhealthy status: analysis from the National Health Checkup database in Korea

We assessed the association between metabolic health status and the incidence of bladder cancer using nationally representative data from the National Health Insurance System and National Health Checkups (NHC) databases in South Korea. Data for 11,781,768 men who participated in the NHC between 2009 and 2012 were analysed. The normal-weight and physically obese categories were defined as body mass indexes (BMI) < 25 and ≥25 kg/m², respectively. Metabolically obese was defined as the presence of ≥3 components of metabolic syndrome. The participants were stratified into metabolically healthy, normal-weight (MHNW); metabolically obese, normal-weight (MONW); metabolically healthy, obese (MHO); metabolically obese, obese (MOO). Multivariate-adjusted Cox regression analysis was conducted to examine the association between metabolic health status and the incidence of bladder cancer. The study participants included 17,777 men newly registered with bladder cancer. Analysis according to metabolic health status classification revealed a higher multivariable-adjusted hazard ratio in the MOO, MONW group than in the MHO group (1.307 [95% CI: 1.258–1.358], 1.183 [95% CI: 1.137–1.231] and 1.066 [95% CI: 1.017–1.119], respectively; hazard ratios given relative to MHNW group) We found an association between metabolic health status and the incidence of bladder cancer, with an increasing risk according to the number of metabolic health status components.