Metabolically healthy obesity: what's in a name?

Physical activity in relation to metabolic health and obesity: The Feel4Diabetes study

AIM

To examine physical activity levels in association with metabolic health and estimate the stability of metabolically healthy obese (MHO) phenotypes over a 2-year period.

METHODS

In total, 2848 men and women from families at risk of the development of diabetes were recruited. Participants were classified as obese or non-obese and metabolic health was defined using five existing definitions. Physical activity was estimated with the International Physical Activity Questionnaire and pedometers.

RESULTS

Prevalence of the MHO phenotype varied among definitions (0% to 20.2%). Overall, the MHO were more active than the metabolically unhealthy obese (MUO). Daily sitting hours (odds ratio [OR] = 1.055, 95% confidence interval [CI]: 1.009-1.104) and daily steps (per 500; OR = 0.934, 95% CI: 0.896-0.973) were remarkable predictors of metabolic health in individuals with obesity; and likewise, in individuals without obesity. After 2 years, 44.1% of baseline MHO adults transitioned to MUO, while 84.0% of the MUO at baseline remained at the same phenotype. Although physical activity was not a major determinant in phenotype transitioning, daily steps were associated with the maintenance of metabolic health over time in the non-obese group.

CONCLUSION

A universally accepted definition for MHO is needed. Being physically active can contribute to a metabolically healthy profile even in the presence of obesity; still, MHO is a transient condition and physical activity alone may not be an adequate factor for its maintenance.

Rethinking weight loss treatments as cardiovascular medicine in obesity, a comprehensive review

The global escalation of obesity has made it a worldwide health concern, notably as a leading risk factor for cardiovascular disease (CVD). Extensive evidence corroborates its association with a range of cardiac complications, including coronary artery disease, heart failure, and heightened vulnerability to sudden cardiac events. Additionally, obesity contributes to the emergence of other cardiovascular risk factors including dyslipidaemia, type 2 diabetes, hypertension, and sleep disorders, further amplifying the predisposition to CVD. To adequately address CVD in patients with obesity, it is crucial to first understand the pathophysiology underlying this link. We herein explore these intricate mechanisms, including adipose tissue dysfunction, chronic inflammation, immune system dysregulation, and alterations in the gut microbiome.Recent guidelines from the European Society of Cardiology underscore the pivotal role of diagnosing and treating obesity to prevent CVD. However, the intricate relationship between obesity and CVD poses significant challenges in clinical practice: the presence of obesity can impede accurate CVD diagnosis while optimizing the effectiveness of pharmacological treatments or cardiac procedures requires meticulous adjustment, and it is crucial that cardiologists acknowledge the implications of excessive weight while striving to enhance outcomes for the vulnerable population affected by obesity. We, therefore, sought to overcome controversial aspects in the clinical management of heart disease in patients with overweight/obesity and present evidence on cardiometabolic outcomes associated with currently available weight management interventions, with the objective of equipping clinicians with an evidence-based approach to recognize and address CVD risks associated with obesity.

Metabolically healthy obesity: from epidemiology and mechanisms to clinical implications

The concept of metabolic health, particularly in obesity, has attracted a lot of attention in the scientific community, and is being increasingly used to determine the risk of cardiovascular diseases and diabetes mellitus-related complications. This Review assesses the current understanding of metabolically healthy obesity (MHO). First, we present the historical evolution of the concept. Second, we discuss the evidence for and against its existence, the usage of different definitions of MHO over the years and the efforts made to provide novel definitions of MHO. Third, we highlight epidemiological data with regard to cardiovascular risk in MHO, which is estimated to be moderately elevated using widely used definitions of MHO when compared with individuals with metabolically healthy normal weight, but potentially not elevated using a novel definition of MHO. Fourth, we discuss novel findings about the physiological mechanisms involved in MHO and how such knowledge helps to identify and characterize both people with MHO and those with metabolically unhealthy normal weight. Finally, we address how the concept of MHO can be used for risk stratification and treatment in clinical practice.

Risk of Cardiovascular Events in Metabolically Healthy Overweight or Obese Adults: Role of LDL-Cholesterol in the Stratification of Risk

The objective of this study was to investigate the longitudinal association of metabolically healthy overweight/obese adults with major adverse cardiovascular events (MACE) and the effect of LDL-cholesterol levels on this association. This study was conducted with 15,904 participants from the URRAH study grouped according to BMI and metabolic status. Healthy metabolic status was identified with and without including LDL-cholesterol. The risk of MACE during 11.8 years of follow-up was evaluated with multivariable Cox regressions. Among the participants aged <70 years, high BMI was associated with an increased risk of MACE, whereas among the older subjects it was associated with lower risk. Compared to the group with normal weight/healthy metabolic status, the metabolically healthy participants aged <70 years who were overweight/obese had an increased risk of MACE with an adjusted hazard ratio of 3.81 (95% CI, 1.34-10.85, p = 0.012). However, when LDL-cholesterol < 130 mg/dL was included in the definition of healthy metabolic status, no increase in risk was found in the overweight/obese adults compared to the normal weight individuals (hazard ratio 0.70 (0.07-6.71, p = 0.75). The present data show that the risk of MACE is increased in metabolically healthy overweight/obese individuals identified according to standard criteria. However, when LDL-cholesterol is included in the definition, metabolically healthy individuals who are overweight/obese have no increase in risk.

Genetic Evidence for Distinct Biological Mechanisms That Link Adiposity to Type 2 Diabetes: Toward Precision Medicine

We aimed to unravel the mechanisms connecting adiposity to type 2 diabetes. We used MR-Clust to cluster independent genetic variants associated with body fat percentage (388 variants) and BMI (540 variants) based on their impact on type 2 diabetes. We identified five clusters of adiposity-increasing alleles associated with higher type 2 diabetes risk (unfavorable adiposity) and three clusters associated with lower risk (favorable adiposity). We then characterized each cluster based on various biomarkers, metabolites, and MRI-based measures of fat distribution and muscle quality. Analyzing the metabolic signatures of these clusters revealed two primary mechanisms connecting higher adiposity to reduced type 2 diabetes risk. The first involves higher adiposity in subcutaneous tissues (abdomen and thigh), lower liver fat, improved insulin sensitivity, and decreased risk of cardiometabolic diseases and diabetes complications. The second mechanism is characterized by increased body size and enhanced muscle quality, with no impact on cardiometabolic outcomes. Furthermore, our findings unveil diverse mechanisms linking higher adiposity to higher disease risk, such as cholesterol pathways or inflammation. These results reinforce the existence of adiposity-related mechanisms that may act as protective factors against type 2 diabetes and its complications, especially when accompanied by reduced ectopic liver fat.

ARTICLE HIGHLIGHTS

Follistatin as a Potential Biomarker for Identifying Metabolically Healthy and Unhealthy Obesity: A Cross-Sectional Study

Metabolically healthy obesity (MHO) refers to obese individuals with a favorable metabolic profile, without severe metabolic abnormalities. This study aimed to investigate the potential of follistatin, a regulator of metabolic balance, as a biomarker to distinguish between metabolically healthy and unhealthy obesity. This cross-sectional study included 30 metabolically healthy and 32 metabolically unhealthy individuals with obesity. Blood samples were collected to measure the follistatin levels using an enzyme-linked immunosorbent assay (ELISA). While follistatin did not significantly differentiate between metabolically healthy (median 41.84 [IQR, 37.68 to 80.09]) and unhealthy (median 42.44 [IQR, 39.54 to 82.55]) individuals with obesity (p = 0.642), other biochemical markers, such as HDL cholesterol, triglycerides, C-peptide, and AST, showed significant differences between the two groups. Insulin was the most significant predictor of follistatin levels, with a coefficient of 0.903, followed by C-peptide, which exerted a negative influence at -0.624. Quantile regression analysis revealed nuanced associations between the follistatin levels and metabolic parameters in different quantiles. Although follistatin may not serve as a biomarker for identifying MHO and metabolically unhealthy obesity, understanding the underlying mechanisms that contribute to metabolic dysfunction could provide personalized strategies for managing obesity and preventing associated complications.

Associations between residential greenness and obesity phenotypes among adults in Southwest China

BACKGROUND

Although exposure to greenness has generally benefited human metabolic health, the association between greenness exposure and metabolic obesity remains poorly studied. We aimed to investigate the associations between residential greenness and obesity phenotypes and the mediation effects of air pollutants and physical activity (PA) level on the associations.

METHODS

We used the baseline of the China Multi-Ethnic Cohort (CMEC) study, which enrolled 87,613 adults. Obesity phenotypes were defined based on obesity and metabolic status, including metabolically unhealthy obesity (MUO), non-obesity (MUNO), metabolically healthy obesity (MHO), and non-obesity (MHNO). Greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 500-m buffer zones around the participants' residence. Multivariable logistic regression was used to estimate the associations between greenness and obesity phenotypes. Stratified analyses by age, sex, educational level, and urbanicity were performed to identify how the effect varies across different subgroups. Causal mediation analysis was used to examine the mediation effects of air pollutants and PA level.

RESULTS

Compared with MHNO, each interquartile range (IQR) increase in greenness exposure was associated with reduced risks of MHO (ORNDVI [95% CI] = 0.87 [0.81, 0.93]; OREVI = 0.91 [0.86, 0.97]), MUO (ORNDVI = 0.83 [0.78, 0.88]; OREVI = 0.86 [0.81, 0.91]), and MUNO (ORNDVI = 0.88 [0.84, 0.91]; OREVI = 0.89 [0.86, 0.92]). For each IQR increase in both NDVI and EVI, the risks of MHO, MUO, and MUNO were reduced more in men, participants over 60 years, those with a higher level of education, and those living in urban areas, compared to their counterparts. Concentrations of particulate matter (PM) and PA level partially mediated the associations between greenness exposure and obesity phenotypes.

CONCLUSIONS

Exposure to residential greenness was associated with decreased risks of MHO, MUO, and MUNO, which was mediated by concentrations of PM and PA level, and modified by sex, age, educational level, and urbanicity.

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

AIMS

To investigate the prevalence of metabolically healthy overweight/obesity and to study its longitudinal association with major adverse cardiovascular and renal events (MARCE).

METHODS AND RESULTS

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

CONCLUSION

The present data show that the risk of MARCE is not increased in young metabolically healthy overweight/obesity suggesting that the clinical approach to people with high BMI should focus on parameters of metabolic health rather than on BMI.

Instability of Healthy Overweight and Obesity Phenotypes over the Long Term in Young Participants in the HARVEST Study: Influence of Sex

BACKGROUND

Whether healthy metabolic status is stable or only temporary is still controversial. The aim of the present study was to determine the frequency of the transition from metabolically healthy to metabolically unhealthy status, or vice versa, over the long term.

METHODS

We examined 970 individuals of 18 to 45 years of age. The participants' mean age was 33.1 ± 8.6 years and mean BP was 145.5 ± 10.6/93.5 ± 5.7 mmHg. Participants were classified into four groups according to whether they had normal weight or overweight/obesity (OwOb) and were metabolically healthy or unhealthy. After 7.5 years, 24.3% of men and 41.9% of women in the metabolically healthy normal-weight group remained metabolically healthy (p < 0.0001). Among the metabolically healthy OwOb participants, 31.9% remained metabolically healthy, with a similar frequency in men and women. However, more OwOb women (19.1%) than men (5.7%) achieved normal weight (p < 0.0001). Among the metabolically unhealthy OwOb subjects, 81.8% of men and 69.3% of women remained metabolically unhealthy, 7.4% of men and 12.0% of women transitioned to OwOb healthy status, and 10.7% of men and 18.7% of women achieved normal weight (men versus women, p < 0.0001). Predictors of transition to unhealthy status were high BP, high BMI, and smoking. Male sex was a borderline predictor of progression to unhealthy status in OwOb participants (p = 0.073).

CONCLUSION

These data show that metabolically healthy status is a highly unstable condition in both normal-weight and OwOb individuals. The impairment of metabolic status was more frequent in men than in women. Lifestyle counseling produced beneficial effects in almost one-third of metabolically unhealthy OwOb women and in less than one-fifth of men.

Association between alternative healthy eating index (AHEI) with metabolic health status in adolescents with overweight and obesity

BACKGROUND

There has been lack of evidence on the association between healthy dietary patterns and metabolic health status of adolescents. The present study aimed to evaluate the association between alternative healthy eating index (AHEI) and metabolic health status among a relatively representative sample of Iranian adolescents with overweight/obesity.

METHODS

Adolescents with extra body weight (n = 203, aged 12-18 y), were selected for this cross-sectional study by a multistage cluster random-sampling method. Habitual dietary intakes and diet quality of individuals were assessed using validated food frequency questionnaire and AHEI-2010, respectively. Data on other covariates were also gathered by pre-tested questionnaires. To determine fasting glucose, insulin and lipid profiles, fasting blood samples were collected. Participants were categorized as having metabolically healthy overweight/obesity (MHO) or metabolically unhealthy overweight/obesity (MUO) phenotypes, based on two approaches (International Diabetes Federation (IDF) and combination of IDF with Homeostasis Model Assessment Insulin Resistance (HOMA-IR)).

RESULTS

The overall prevalence of MUO was 38.9% (based on IDF criteria) and 33.0% (based on IDF/HOMA-IR criteria). After considering all potential confounders, participants in highest tertiles of AHEI-2010 had lower odds of MUO profile according to both IDF (OR = 0.05; 95% CI: 0.01-0.15) and IDF/HOMA-IR (OR = 0.05; 95% CI: 0.02-0.19) definitions. This association was stronger in adolescents with overweight compared with obese ones and also among girls than boys. Moreover, each unit increase in AHEI-2010 score was associated with lower risk of MUO based on both criteria.

CONCLUSIONS

Higher adherence to AHEI-2010 was inversely associated with odds of MUO in Iranian adolescents with overweight/obesity.

Transitions in Metabolic Health and Onset Age of Cardiovascular Diseases

INTRODUCTION

The cardiometabolic risk associated with metabolically healthy obesity remains the subject of debate. It is unclear whether changes in metabolically healthy obesity status affect premature cardiovascular disease (CVD) risk. Authors aimed to investigate the association of metabolically healthy obesity and its transition over time with incident CVD by age at onset.

METHODS

In a community-based, prospective cohort study, 54,441 adults without CVD in or before 2010 were followed for incident CVD until 2020. This sample was analyzed in 2022. Four age groups were examined (<55, 55-65, 65-75, and ≥75 years) for CVD onset. In each age group, participants were cross-classified by BMI categories and metabolic health. The Cox proportional hazards model with age as the underlying time scale was used to examine the associations of metabolic health status and its transition with CVD across BMI categories.

RESULTS

During a median follow-up of 9.59 years, 3,038 participants developed CVD. Individuals with metabolically unhealthy obesity at baseline had the highest hazard ratio for CVD onset at any age, ranging from 2.68 (95% CI=2.02, 3.55) for CVD onset in those aged <55 years to 1.55 (95% CI=1.09, 2.10) for CVD onset in those aged ≥75 years. Individuals who had metabolically healthy obesity at baseline or even remained metabolically healthy during 2006-2010 were still at increased risk of premature CVD, and the association attenuated with increasing age of CVD onset.

CONCLUSIONS

The metabolically healthy obesity phenotype is dynamic and its transition to a metabolically unhealthy phenotype or even stable metabolically healthy obesity is associated with an increased risk of CVD. The associations were more evident for CVD onset at younger ages.

A data-driven computational model for obesity-driven diabetes onset and remission through weight loss

Obesity is a major risk factor for the development of type 2 diabetes (T2D), where a sustained weight loss may result in T2D remission in individuals with obesity. To design effective and feasible intervention strategies to prevent or reverse T2D, it is imperative to study the progression of T2D and remission together. Unfortunately, this is not possible through experimental and observational studies. To address this issue, we introduce a data-driven computational model and use human data to investigate the progression of T2D with obesity and remission through weight loss on the same timeline. We identify thresholds for the emergence of T2D and necessary conditions for remission. We explain why remission is only possible within a window of opportunity and the way that window depends on the progression history of T2D, individual's metabolic state, and calorie restrictions. These findings can help to optimize therapeutic intervention strategies for T2D prevention or treatment.

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

BACKGROUND

A variable percentage of children and adolescents with obesity do not have cardiometabolic comorbidities. A phenotype called metabolically healthy obese (MHO) has emerged to describe this population subgroup. Early identification of this condition may prevent the progression to metabolically unhealthy obesity (MUO).

MATERIAL AND METHODS

A cross-sectional descriptive study of 265 children and adolescents from Cordoba (Spain) conducted in 2018. The outcome variables were MHO, established based on three criteria: International Criterion, HOMA-IR, and a combination of the previous two.

RESULTS

The prevalence of MHO ranged from 9.4% to 12.8% of the study population, between 41% and 55.7% of the sample with obesity. The highest agreement was reached between the HOMA-IR definitions and the combined criteria. The waist-to-height ratio (WHtR) was the indicator with the highest discriminant capacity for MHO in 2 of the three criteria, with its best cut-off point at 0.47 for both.

CONCLUSION

The prevalence of MHO in children and adolescents differed according to the criteria used for diagnosis. The anthropometric variable with the most remarkable discriminating capacity for MHO was WHtR, with the same cut-off point in the three criteria analysed.

IMPACT STATEMENT

This research work defines the existence of metabolically healthy obesity through anthropometric indicators in children and adolescents. Definitions that combine cardiometabolic criteria and insulin resistance are used to identify metabolically healthy obesity, as well as the prediction of this phenomenon through anthropometric variables. The present investigation helps to identify metabolically healthy obesity before metabolic abnormalities begin.

ZFYVE28 mediates insulin resistance by promoting phosphorylated insulin receptor degradation via increasing late endosomes production

Insulin resistance is associated with many pathological conditions, and an in-depth understanding of the mechanisms involved is necessary to improve insulin sensitivity. Here, we show that ZFYVE28 expression is decreased in insulin-sensitive obese individuals but increased in insulin-resistant individuals. Insulin signaling inhibits ZFYVE28 expression by inhibiting NOTCH1 via the RAS/ERK pathway, whereas ZFYVE28 expression is elevated due to impaired insulin signaling in insulin resistance. While Zfyve28 overexpression impairs insulin sensitivity and causes lipid accumulation, Zfyve28 knockout in mice can significantly improve insulin sensitivity and other indicators associated with insulin resistance. Mechanistically, ZFYVE28 colocalizes with early endosomes via the FYVE domain, which inhibits the generation of recycling endosomes but promotes the conversion of early to late endosomes, ultimately promoting phosphorylated insulin receptor degradation. This effect disappears with deletion of the FYVE domain. Overall, in this study, we reveal that ZFYVE28 is involved in insulin resistance by promoting phosphorylated insulin receptor degradation, and ZFYVE28 may be a potential therapeutic target to improve insulin sensitivity.

Normal-weight central obesity: implications for diabetes mellitus

Background

Current guidelines for obesity prevention and control focus on body mass index (BMI) and rarely address central obesity. Few studies have been conducted on the association between normal-weight central obesity and the risk of diabetes mellitus (DM).

Methods

26,825 participants from the National Health and Nutrition Examination Survey (NHANES) were included in our study. A weighted multivariate logistic regression model was used to analyze the relationship between different obesity patterns and the risk of DM.

Results

Our results suggest that normal-weight central obesity is associated with an increased risk of DM (OR: 2.37, 95% CI: 1.75-3.23) compared with normal-weight participants without central obesity. When stratified by sex, men with normal-weight central obesity, obesity and central obesity were found to have a similar risk of DM (OR: 3.83, 95% CI: 2.10-5.97; OR: 4.20, 95% CI: 3.48-5.08, respectively) and a higher risk than all other types of obesity, including men who were overweight with no central obesity (OR: 1.21, 95% CI: 0.96-1.51) and obese with no central obesity (OR: 0.53, 95% CI: 0.30-0.91).

Conclusion

Our results highlight the need for more attention in people with central obesity, even if they have a normal BMI.

Transitions in Metabolic Health Status and Obesity Over Time and Risk of Diabetes: The Dongfeng-Tongji Cohort Study

CONTEXT

Evidence regarding the association between metabolically healthy overweight or obesity (MHOO) and diabetes is controversial, and mostly ignores the dynamic change of metabolic health status and obesity.

OBJECTIVE

To explore the association between transitions of metabolic health status and obesity over 5 years and diabetes incidence.

METHODS

We examined 17 309 participants derived from the Dongfeng-Tongji cohort and followed from 2008 to 2018 (median follow-up 9.9 years). All participants were categorized into 4 phenotypes based on body mass index (BMI) and metabolic health status: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), MHOO, and metabolically unhealthy overweight or obesity (MUOO). The associations of changes in BMI-metabolic health status (2008-2013) with diabetes incidence (2018) were performed among 12 206 individuals with 2 follow-up examinations.

RESULTS

Compared with stable MHNW, stable MHOO (hazard ratio [HR] 1.76; 95% CI 1.26, 2.45) and transition from MHOO to metabolically unhealthy phenotypes were associated with higher risk for diabetes (HR 2.97; 95% CI 1.79, 4.93 in MHOO to MUNW group and HR 3.38; 95% CI 2.54, 4.49 in MHOO to MUOO group). Instead, improvements to metabolic healthy phenotypes or weight loss occurring in MUOO reduced the risk of diabetes compared with stable MUOO, changing from MUOO to MHNW, MUNW, and MHOO resulted in HRs of 0.57 (95% CI 0.37, 0.87), 0.68 (95% CI 0.50, 0.93), and 0.45 (95% CI 0.34, 0.60), respectively.

CONCLUSION

People with MHOO, even stable MHOO, or its transition to metabolically unhealthy phenotypes were at increased risk of diabetes. Metabolic improvements and weight control may reduce the risk of diabetes.

Obesity and metabolic state are associated with increased healthcare resource and medication use and costs: a Finnish population-based study

AIM

To characterize healthcare resource (HCRU) and medication use and associated costs in individuals with obesity compared with individuals with normal weight or overweight in a population-based cohort of Finnish adults. The association between metabolic state and direct costs was also assessed.

METHODS

The study cohort included 5587 randomly selected individuals who participated in the national FinHealth 2017 health examination survey. Data on healthcare visits and hospital stays, including diagnoses (ICD-10), and purchases and costs of prescription medicines were collected from the nationwide registers by the Finnish Institute for Health and Welfare and Social Insurance Institution of Finland. The healthcare costs were calculated based on standard unit costs reported by the Finnish Institute for Health and Welfare.

RESULTS

The total annual direct costs were €2665 (SD €5673) and €1799 (SD €3874) per person with obesity and with normal weight or overweight, respectively. Obesity was associated with significantly increased total direct (age- and sex-adjusted cost rate ratio, RR, 1.356; p < 0.001), HCRU-related (1.273; p = 0.002), and medication (1.669; p < 0.001) costs. A vast majority (90%) of individuals with obesity were classified as metabolically unhealthy based on clinical measurements. The metabolically unhealthy state was associated with increased costs in individuals with obesity but not in individuals with normal weight or overweight.

CONCLUSION

Obesity is associated with a significant and complex direct cost burden to society, arising primarily from increased comorbidity. Metabolically healthy obesity is uncommon and obesity prevention and timely treatment should be of high priority to tackle the increasing burden of obesity.

Tirzepatide and potential use for metabolically healthy obesity

Metabolically healthy obesity or metabolically healthy overweight (MHO) is best described as being absent of any major metabolic disorder or cardiovascular diseases such as type 2 diabetes mellitus, dyslipidemia, hypertension, and atherosclerotic cardiovascular disease despite being obese or overweight. Nevertheless, MHO is being recognized as an important risk factor for the development of cardiovascular, cerebrovascular, and peripheral artery disease. In addition, these patients are at a high risk of conversion to the metabolically unhealthy phenotype. Tirzepatide is a newly developed glucose-lowering agent which acts on the glucose-dependent insulinotropic peptide (GIP) and glucagon-like peptide-1 (GLP-1) receptors. It has been shown to result in several highly beneficial outcomes including weight loss and a significant improvement in important metabolic parameters such as HbA1c, fasting serum glucose, and triglyceride/lipoprotein levels. These findings suggest that tirzepatide could potentially be beneficial to metabolically healthy obese or metabolically healthy overweight patients in reducing their risk of adverse cardiovascular outcomes and conversion to the metabolically unhealthy phenotype. In this review, we aim to discuss the potential benefits of using the novel anti-diabetic tirzepatide in the management of MHO to prevent the development of cardiovascular events and to decrease the likelihood of conversion to the unhealthy phenotype. We initially describe the clinical outcomes of MHO as well as the association of MHO with developing future cardiovascular events. We then delineate the currently available evidence behind the clinical effects of tirzepatide. We finally discuss the potential advantages of using tirzepatide in the management of MHO.

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.

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

BACKGROUND

Metabolically healthy obesity (MHO), a phenotype of obesity considered to be of lower cardiovascular risk, is still a controversial concept. This study aimed to investigate the presence of subclinical systemic microvascular dysfunction in individuals with MHO.

METHODS

This was a cross-sectional study in which 112 volunteers were allocated into three groups: metabolically healthy normal weight (MHNW), MHO, or metabolically unhealthy obesity (MUO). Obesity was defined as a body mass index (BMI) ≥ 30 kg/m². MHO was defined as the absence of any component of metabolic syndrome, except waist circumference. Microvascular reactivity was evaluated using cutaneous laser speckle contrast imaging.

RESULTS

Mean age was 33.2 ± 7.66 years. The median BMI in the MHNW, MHO and MUO groups was 23.6, 32.8, and 35.8 kg/m², respectively. Baseline microvascular conductance values were lower in the MUO group (0.25 ± 0.08 APU/mmHg) than in MHO (0.30 ± 0.10 APU/mmHg) and MHNW groups (0.33 ± 0.12 APU/mmHg) (P = 0.0008). There were no significant differences regarding endothelial-dependent (acetylcholine stimulation or postocclusive reactive hyperemia) or endothelial-independent (sodium nitroprusside stimulation) microvascular reactivity among the groups.

CONCLUSIONS

Individuals with MUO had lower baseline systemic microvascular flow than those with MHNW or MHO, but endothelium-dependent or endothelium-independent microvascular reactivity were not changed in any of the groups. The relatively young age of the study population, the low frequency of class III obesity, or the strict definition of MHO (absence of any metabolic syndrome criteria) might account for the lack of difference of microvascular reactivity among MHNW, MHO or MUO.

U-shaped association between the triglyceride-glucose index and atrial fibrillation incidence in a general population without known cardiovascular disease

OBJECTIVE

The triglyceride-glucose (TyG) index has been shown to be a new alternative measure for insulin resistance. However, no study has attempted to investigate the association of the TyG index with incident atrial fibrillation (AF) in the general population without known cardiovascular diseases.

METHODS

Individuals without known cardiovascular diseases (heart failure, coronary heart disease, or stroke) from the Atherosclerosis Risk in Communities (ARIC) cohort were recruited. The baseline TyG index was calculated as the Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. The association between the baseline TyG index and incident AF was examined using Cox regression.

RESULTS

Of 11,851 participants, the mean age was 54.0 years; 6586 (55.6%) were female. During a median follow-up of 24.26 years, 1925 incidents of AF cases (0.78/per 100 person-years) occurred. An increased AF incidence with a graded TyG index was found by Kaplan‒Meier curves (P < 0.001). In multivariable-adjusted analysis, both < 8.80 (adjusted hazard ratio [aHR] = 1.15, 95% confidence interval [CI] 1.02, 1.29) and > 9.20 levels (aHR 1.18, 95% CI 1.03, 1.37) of the TyG index were associated with an increased risk of AF compared with the middle TyG index category (8.80-9.20). The exposure-effect analysis confirmed the U-shaped association between the TyG index and AF incidence (P = 0.041). Further sex-specific analysis showed that a U-shaped association between the TyG index and incident AF still existed in females but not in males.

CONCLUSIONS

A U-shaped association between the TyG index and AF incidence is observed in Americans without known cardiovascular diseases. Female sex may be a modifier in the association between the TyG index and AF incidence.

Metabolically healthy obesity: Misleading phrase or healthy phenotype?

Obesity is a heterogenous condition with multiple different phenotypes. Among these a particular subtype exists named as metabolically healthy obesity (MHO). MHO has multiple definitions and its prevalence varies according to study. The potential mechanisms underlying the pathophysiology of MHO include the different types of adipose tissue and their distribution, the role of hormones, inflammation, diet, the intestinal microbiota and genetic factors. In contrast to the negative metabolic profile associated with metabolically unhealthy obesity (MUO), MHO has relatively favorable metabolic characteristics. Nevertheless, MHO is still associated with many important chronic diseases including cardiovascular disease, hypertension, type 2 diabetes, chronic kidney disease as well as certain types of cancer and has the risk of progression into the unhealthy phenotype. Therefore, it should not be considered as a benign condition. The major therapeutic alternatives include dietary modifications, exercise, bariatric surgery and certain medications including glucagon-like peptide-1 (GLP-1) analogs, sodium-glucose cotransporter-2 (SGLT-2) inhibitors and tirzepatide. In this review, we discuss the significance of MHO while comparing this phenotype with MUO.

Association between metabolically obese but normal weight and cardiovascular diseases in Korean menopausal women

OBJECTIVE

The aim of this study was to present useful data for developing effective health management strategies for cardiovascular disease (CVD) prevention in postmenopausal women by investigating health-related behaviors and the prevalence of CVD for different types of obesity classified according to metabolic health status and body mass index criteria.

METHODS

Using the 2016 Korean National Health and Nutrition Examination Survey VII-1 data, 1,190 menopausal women aged 50 years or older were analyzed in this cross-sectional study. The participants were divided into four groups as follows: metabolically healthy and normal weight (MHNW), metabolically obese but normal weight (MONW), metabolically healthy but obese, and metabolically obese and obese. Complex-samples general linear analysis, t tests, and logistic regression analysis were used to compare the differences in health-related behaviors and the risk of CVD among the four groups.

RESULTS

The risk for stroke was 3.61 times higher (95% CI, 1.18-11.03) in the MONW group than in the MHNW group.

CONCLUSIONS

We found a strong association between the MONW group of obesity and the risk for CVD, particularly stroke, in postmenopausal women. These findings would serve as valuable evidence for developing and implementing interventions to prevent stroke in postmenopausal women in the MONW group.

Association of legumes and nuts consumption with metabolic health status in Iranian overweight and obese adolescents

Limited data are available on the association of legumes and nuts consumption with health status in pediatrics. So, we assessed the relation of legumes and nuts intake with metabolic health status in Iranian adolescents. A random sample of overweight/obese adolescents aged 12 to 18 years was included in this cross-sectional study. Dietary intakes were gathered using a validated 147-item food frequency questionnaire (FFQ). We measured metabolic indices including blood pressure, lipid profile, glycemic and anthropometrics indices. Two strategies were used for classification of adolescents to metabolically healthy obese (MHO) or unhealthy obese (MUO): International Diabetes Federation (IDF) and combination of IDF with Homeostasis Model Assessment Insulin Resistance (HOMA-IR). Information on 203 overweight/obese adolescents (50.2% girls and 49.8% boys) with an average age of 13.98 (± 1.61) years and a mean weight of 73.48 (± 11.60) kg/m² was evaluated. Based on the IDF and IDF/HOMA-IR definition, higher consumption of legumes and nuts consumption was related to a 66% and 61% decreased odds of MUO in crude model (OR = 0.34, 95%CI 0.17-0.69), (OR = 0.39, 95%CI 0.19-0.80); but in fully-adjusted model, these relations disappeared. After adjustment for potential cofounders, an inverse association was found between legumes and nuts consumption and odds of hyperglycemia (OR = 0.35, 95%CI 0.16-0.78). Moreover, although inverse significant associations were found between legumes and nuts consumption and odds of MUO in girls and overweight subjects in crude models, these associations disappeared after adjustment for all confounders. After taking potential confounders into account, no significant association was found between consumption of legumes and nuts and MUO in Iranian adolescents. The findings should be affirmed by further prospective studies.

An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case-control study

OBJECTIVES

To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways.

METHODS

We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications.

RESULTS

We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome.

CONCLUSIONS

The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications.

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.

The association between egg consumption and metabolic health status in overweight and obese adolescents

Existing evidence examining the relation between egg consumption and metabolic health of overweight/obese adolescents is scarce. We examined the association between egg consumption and metabolic status in Iranian overweight/obese adolescents. Using multistage cluster random sampling approach, overweight/obese adolescents (n = 203) with ages from 12 to 18 years old were selected for the present cross-sectional study. A validated 147-item food frequency questionnaire was adopted to determine usual dietary intakes. Blood pressure and anthropometric data and were assessed, and levels of lipid profile, insulin, and glucose were measured by collecting fasting blood samples. Participants were classified into metabolically healthy obese (MHO) or metabolically unhealthy obese (MUO) based on two methods of International Diabetes Federation (IDF) and the combination of IDF with Homeostasis Model Assessment Insulin Resistance (HOMA-IR). In total, 67 (33.0%) and 79 (38.9%) adolescents were classified as MUO based on IDF/HOMA and IDF definitions, respectively. Considering IDF criteria, the highest intake of egg was related to decreased chance of MUO, in crude (OR 0.22; 95% CI 0.10-0.48) and maximally-adjusted model (OR 0.25; 95% CI 0.10-0.59). Considering IDF/HOMA-IR criteria, similar results were obtained (crude model: OR 0.24; 95% CI 0.11-0.52; fully-adjusted model: OR 0.28; 95% CI 0.11-0.69). Stratified analyses found stronger relation among boys (vs. girls) and overweight (vs. obese) individuals. In conclusion, higher egg consumption was negatively related to decreased chance of being MUO in overweight/obese adolescents, especially in boys and overweight individuals, regardless of MUO definitions. Prospective studies are required to support our results.

Whole-Genome Transcriptomics of PBMC to Identify Biomarkers of Early Metabolic Risk in Apparently Healthy People with Overweight-Obesity and in Normal-Weight Subjects

SCOPE

Peripheral blood mononuclear cells (PBMC) provide a useful and minimally invasive source of biomarkers. Here to identify PBMC transcriptomic biomarkers predictive of metabolic impairment related to increased adiposity is aimed.

METHODS AND RESULTS

The study analyzed the global PBMC transcriptome in metabolically healthy (normoglycemic) volunteers with overweight-obesity (OW-OB, n = 12), and in subjects with metabolically obese normal-weight (MONW, n = 5) phenotype, in comparison to normal-weight (NW, n = 12) controls. The study identifies 1072 differentially expressed genes (DEGs) in OW-OB versus NW and 992 in MONW versus NW. Hierarchical clustering of the top 100 DEGs clearly distinguishes OW-OB and MONW from NW. Remarkably, the OW-OB and MONW phenotypes share 257 DEGs regulated in the same direction. The top up-regulated gene CXCL8, coding for interleukin 8, with a role in obesity-related pathologies, is of special interest as a potential marker for predicting increased metabolic risk. CXCL8 expression is increased mainly in the MONW group and correlated directly with C-reactive protein levels.

CONCLUSIONS

PBMC gene expression analysis of CXCL8 or a pool of DEGs may be used to identify early metabolic risk in an apparently healthy population regardless of their BMI, i.e., subjects with OW-OB or MONW phenotype and to apply adequate and personalized nutritional preventive strategies.

The risk for chronic kidney disease in metabolically healthy obese patients: A systematic review and meta-analysis

BACKGROUND

Chronic kidney disease (CKD) is associated with obesity and metabolic syndrome. Nevertheless, the association of CKD with phenotype referred as metabolically healthy obese or overweight is unclear. In this this systematic review and meta-analysis, we investigate the relationships between obesity and CKD independent of metabolic syndrome by appraising published evidence in studies focusing on metabolically healthy obese people.

MATERIALS AND METHODS

We performed a literature search through three databases Embase (Elsevier), the Cochrane Central Register of Controlled Trials (Wiley) and PubMed/Medline Web of Science up to March 2022 with the following terms: "chronic kidney disease", "kidney function", "obesity", "metabolic syndrome", "metabolically healthy obesity", "metabolically healthy overweight". Metabolically unhealthy was defined an individual having at least 3 of the following: abdominal obesity, high blood pressure, hypertriglyceridemia, low HDL cholesterol and hyperglycaemia. We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for reporting. Prospective, retrospective, randomized and nonrandomized studies fitting the search criteria were included in our results.

RESULTS

Our final analysis included 16 studies with a total number of 4.965.285 participants. There is considerable heterogeneity in terms of study design, participant characteristics and number of participants across individual studies. In comparison to healthy normal weight patients, the risk was progressively higher in overweight (RR 1.29, 95% CI 1.27 to 1.32, p < 0.001) and obese patients (RR 1.47, 95% CI 1.31 to 1.65, p < 0.001).

CONCLUSION

Metabolically healthy overweight and obese individuals have higher risk of CKD compared to individuals without weight excess.

Evolution of the diagnostic value of "the sugar of the blood": hitting the sweet spot to identify alterations in glucose dynamics

In this paper, we provide an overview of the evolution of the definition of hyperglycemia during the past century and the alterations in glucose dynamics that cause fasting and postprandial hyperglycemia. We discuss how extensive mechanistic, physiological research into the factors and pathways that regulate the appearance of glucose in the circulation and its uptake and metabolism by tissues and organs has contributed knowledge that has advanced our understanding of different types of hyperglycemia, namely prediabetes and diabetes and their subtypes (impaired fasting plasma glucose, impaired glucose tolerance, combined impaired fasting plasma glucose, impaired glucose tolerance, type 1 diabetes, type 2 diabetes, gestational diabetes mellitus), their relationships with medical complications, and how to prevent and treat hyperglycemia.

Association of dietary patterns with obesity and metabolically healthy obesity phenotype in Chinese population: a cross-sectional analysis of China Multi-Ethnic Cohort Study

Metabolically healthy obesity (MHO) might be an alternative valuable target in obesity treatment. We aimed to assess whether alternative Mediterranean (aMED) diet and Dietary Approaches to Stop Hypertension (DASH) diet were favourably associated with obesity and MHO phenotype in a Chinese multi-ethnic population. We conducted this cross-sectional analysis using the baseline data of the China Multi-Ethnic Cohort study that enrolled 99 556 participants from seven diverse ethnic groups. Participants with self-reported cardiometabolic diseases were excluded to eliminate possible reverse causality. Marginal structural logistic models were used to estimate the associations, with confounders determined by directed acyclic graph (DAG). Among 65 699 included participants, 11·2 % were with obesity. MHO phenotype was present in 5·7 % of total population and 52·7 % of population with obesity. Compared with the lowest quintile, the highest quintile of DASH diet score had 23 % decreased odds of obesity (OR = 0·77, 95 % CI 0·71, 0·83, P_trend < 0·001) and 27 % increased odds of MHO (OR = 1·27, 95 % CI 1·10, 1·48, P_trend = 0·001) in population with obesity. However, aMED diet showed no obvious favourable associations. Further adjusting for BMI did not change the associations between diet scores and MHO. Results were robust to various sensitivity analyses. In conclusion, DASH diet rather than aMED diet is associated with reduced risk of obesity and presents BMI-independent metabolic benefits in this large population-based study. Recommendation for adhering to DASH diet may benefit the prevention of obesity and related metabolic disorders in Chinese population.

Role of physical activity and cardiorespiratory fitness in metabolically healthy obesity: a narrative review

Obesity has been associated with a multitude of metabolic disorders, often clustering with risk factors of cardiovascular disease and type 2 diabetes mellitus, hypertension, dyslipidaemia. Overall, obesity is a worldwide, growing health concern. However, a subgroup of obese individuals with a low burden of metabolic abnormalities have been identified and described as metabolically healthy obese (MHO). Whether the MHO phenotype is protective against obesity-related metabolic disorders in the long-term is presently unclear, and current research examining the potential transition has yielded inconsistent results. In this current narrative review, we aim to provide insights on the role of physical activity (PA) and cardiorespiratory fitness (CRF) in MHO. Lifestyle factors such as PA and CRF may influence the MHO phenotype. Limited studies have characterised energy expenditure and CRF in MHO and metabolically unhealthy obese. However, higher levels of PA, less sedentary behaviour and higher CRF have been observed in MHO individuals. Considering the multiple benefits of PA, it is high time to advocate this lifestyle change beyond its influence on energy balance in a weight loss programme to improve cardiovascular and metabolic risk factors irrespective of body weight and fat mass changes. Improved CRF via increased PA, especially exercise participation, while avoiding weight gain is not only a realistic goal, but should be the primary intervention for MHO populations to prevent the transition to an abnormal metabolic state.

Diagnostic accuracy of the waist-to-height ratio and other anthropometric indices for metabolically healthy obesity in the working population

Approximately one-third of overweight individuals, and half of those with obesity, do not have cardiometabolic disorders. For this reason, a phenotype called metabolically healthy obese (MHO) has emerged to describe this population group. The early detection of this situation could save costs associated with the development of comorbidities or pharmacological interventions. Therefore, the aim is to know the prevalence of MHO in the working population and propose variables for its detection. Cross-sectional descriptive study of 635 workers of the Cordoba City Council was carried out based on the results of the 2016 health surveillance. The outcome variables were the MHO, established based on the criteria of the IDF, NCEP—ATP III, and Aguilar—Salinas. In addition, the degree of agreement between the different MHO criteria was studied using Cohen's kappa (k), and the predictive capacity of the anthropometric variables was assessed with Receiver Operator Curves. The prevalence of MHO ranged from 6.6 to 9%. The highest agreement was reached between the IDF and NCEP-ATP III definitions (k = 0.811; 95% CI 0.724–0.898; p &lt; 0.001). The waist-to-height ratio (WHtR) showed the highest discriminant capacity for MHO, with its best cut-off point at 0.55 for all criteria used. Sensitivity ranged from 84 to 93%. The prevalence of MHO in the working population differed according to the criteria used for diagnosis. The anthropometric variable with the highest discriminant capacity for MHO was WHtR, presenting the same cut-off point in the three criteria analyzed. Therefore, WHtR is the variable that best detects the presence of MHO.

Integrated Care Model of Adiposity-Related Chronic Diseases

PURPOSE OF REVIEW

Although obesity is a disease, most patients with obesity do not undergo effective treatment nor adhere to long-term care. We examine the barriers that patients with obesity confront when searching for effective treatment and propose an integrated care model of adiposity-related chronic diseases in a cardio-renal metabolic unit.

RECENT FINDINGS

The current care of obesity is fragmented between primary care providers, medical specialists and metabolic bariatric surgeons with little or no coordination of care between these providers. The current care of obesity heavily focuses on weight loss as the primary aim of treatment thereby reenforcing the weight stigma and turning patients away from effective therapy like metabolic bariatric surgery. An interdisciplinary cardio-renal metabolic unit that, besides weight loss, emphasizes prevention/remission of adiposity-related chronic diseases may deliver thorough and rewarding care to most patients with obesity.

The evolving view of thermogenic fat and its implications in cancer and metabolic diseases

The incidence of metabolism-related diseases like obesity and type 2 diabetes mellitus has reached pandemic levels worldwide and increased gradually. Most of them are listed on the table of high-risk factors for malignancy, and metabolic disorders systematically or locally contribute to cancer progression and poor prognosis of patients. Importantly, adipose tissue is fundamental to the occurrence and development of these metabolic disorders. White adipose tissue stores excessive energy, while thermogenic fat including brown and beige adipose tissue dissipates energy to generate heat. In addition to thermogenesis, beige and brown adipocytes also function as dynamic secretory cells and a metabolic sink of nutrients, like glucose, fatty acids, and amino acids. Accordingly, strategies that activate and expand thermogenic adipose tissue offer therapeutic promise to combat overweight, diabetes, and other metabolic disorders through increasing energy expenditure and enhancing glucose tolerance. With a better understanding of its origins and biological functions and the advances in imaging techniques detecting thermogenesis, the roles of thermogenic adipose tissue in tumors have been revealed gradually. On the one hand, enhanced browning of subcutaneous fatty tissue results in weight loss and cancer-associated cachexia. On the other hand, locally activated thermogenic adipocytes in the tumor microenvironment accelerate cancer progression by offering fuel sources and is likely to develop resistance to chemotherapy. Here, we enumerate current knowledge about the significant advances made in the origin and physiological functions of thermogenic fat. In addition, we discuss the multiple roles of thermogenic adipocytes in different tumors. Ultimately, we summarize imaging technologies for identifying thermogenic adipose tissue and pharmacologic agents via modulating thermogenesis in preclinical experiments and clinical trials.

Koyanagi Y, Matsuo K, Mikami H, Kusakabe M, Takeuchi K, Wakai K. Associations of metabolic syndrome and metabolically unhealthy obesity with cancer mortality: The Japan Multi-Institutional Collaborative Cohort (J-MICC) study

Purpose

The association between metabolic syndrome (MetS) and the risk of death from cancer is still a controversial issue. The purpose of this study was to examine the associations of MetS and metabolically unhealthy obesity (MUHO) with cancer mortality in a Japanese population.

Methods

We used data from the Japan Multi-Institutional Collaborative Cohort Study. The study population consisted of 28,554 eligible subjects (14,103 men and 14,451 women) aged 35–69 years. MetS was diagnosed based on the criteria of the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) and the Japan Society for the Study of Obesity (JASSO), using the body mass index instead of waist circumference. The Cox proportional hazards analysis was used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for total cancer mortality in relation to MetS and its components. Additionally, the associations of obesity and the metabolic health status with cancer mortality were examined.

Results

During an average 6.9-year follow-up, there were 192 deaths from cancer. The presence of MetS was significantly correlated with increased total cancer mortality when the JASSO criteria were used (HR = 1.51, 95% CI 1.04–2.21), but not when the NCEP-ATP III criteria were used (HR = 1.09, 95% CI 0.78–1.53). Metabolic risk factors, elevated fasting blood glucose, and MUHO were positively associated with cancer mortality (P <0.05).

Conclusion

MetS diagnosed using the JASSO criteria and MUHO were associated with an increased risk of total cancer mortality in the Japanese population.

Long-term Prognosis of Acute Myocardial Infarction Associated with Metabolic Health and Obesity Status

BACKGROUND

Emerging evidence supports the favourable cardiovascular health in non-obese subjects with healthy metabolism. However, little is known regarding the prognosis across the range of metabolic phenotypes once cardiovascular disease is established. We examined the prognosis of patients with acute myocardial infarction (AMI) stratified according to metabolic health and obesity status.

METHODS

This is a retrospective study on consecutive patients with AMI admitted to a tertiary hospital between 2014-2021. Patients were allocated into 4 groups based on metabolic and obesity profile: metabolically healthy obese (MHO), metabolically healthy non-obese (MHNO), metabolically unhealthy obese (MUO) and metabolically unhealthy non-obese (MUNO). Metabolic health was defined in accordance to the BioSHARE-EU Healthy Obese Project. The primary outcome was all-cause mortality. Cox regression analysis examined the independent association between mortality and metabolic phenotypes, adjusting for age, sex, AMI type, chronic kidney disease, smoking status and left ventricular ejection fraction.

RESULTS

Of 9958 patients, the majority (68.5%) were MUNO, followed by MUO (25.1%), MHNO (5.6%), and MHO (0.8%). MHO had the lowest mortality (7.4%), followed by MHNO (9.7%), MUO (19.2%) and MUNO (22.6%) (p<0.001). Compared to MHNO, MUO (HR 1.737, 95%CI 1.282-2.355, p<0.001) and MUNO (HR 1.482, 95%CI 1.108-1.981, p=0.008) had significantly higher mortality risk, but not MHO (HR 1.390, 95%CI 0.594-3.251, p=0.447), after adjusting for confounders. Kaplan-Meier curves showed favourable survival in the metabolically healthy and obesity groups, with the highest overall survival in the MHO followed by MHNO, MUO and MUNO (p<0.001).

CONCLUSION

Metabolically healthy and obese AMI patients have favourable prognosis compared to metabolically unhealthy and non-obese patients. It is equally important to prioritize intensive metabolic risk factor management to weight reduction in the early phase after AMI.

Impaired Metabolic Health and Low Cardiorespiratory Fitness Independently Associate With Subclinical Atherosclerosis in Obesity

CONTEXT

For a given body mass index (BMI), both impaired metabolic health (MH) and reduced cardiorespiratory fitness (CRF) associate with increased risk of cardiovascular disease (CVD).

OBJECTIVE

It remains unknown whether both risk phenotypes relate to CVD independently of each other, and whether these relationships differ in normal weight, overweight, and obese subjects.

METHODS

Data from 421 participants from the Tübingen Diabetes Family Study, who had measurements of anthropometrics, metabolic parameters, CRF (maximal aerobic capacity [VO2max]) and carotid intima-media thickness (cIMT), an early marker of atherosclerosis, were analyzed. Subjects were divided by BMI and MH status into 6 phenotypes.

RESULTS

In univariate analyses, older age, increased BMI, and a metabolic risk profile correlated positively, while insulin sensitivity and VO2max negatively with cIMT. In multivariable analyses in obese subjects, older age, male sex, lower VO2max (std. ß -0.21, P = 0.002) and impaired MH (std. ß 0.13, P = 0.02) were independent determinants of increased cIMT. After adjustment for age and sex, subjects with metabolically healthy obesity (MHO) had higher cIMT than subjects with metabolically healthy normal weight (MHNW; 0.59 ± 0.009 vs 0.52 ± 0.01 mm; P < 0.05). When VO2max was additionally included in this model, the difference in cIMT between MHO and MHNW groups became statistically nonsignificant (0.58 ± 0.009 vs 0.56 ± 0.02 mm; P > 0.05).

CONCLUSION

These data suggest that impaired MH and low CRF independently determine increased cIMT in obese subjects and that low CRF may explain part of the increased CVD risk observed in MHO compared with MHNW.

Dietary and lifestyle indices for hyperinsulinemia with the risk of obesity phenotypes: a prospective cohort study among Iranian adult population

BACKGROUND

Previous studies have cited insulin-related disorders, including hyperinsulinemia, as one of the main causes of obesity risk and metabolic disorders. We aimed to investigate the association of the Empirical Dietary Index for Hyperinsulinemia (EDIH) and Empirical Lifestyle Index for Hyperinsulinemia (ELIH) with the risk of obesity phenotypes among Iranian adults.

METHODS

Present study was conducted on 2705 subjects, including 1604 metabolically healthy normal weights (MHNW) and 1101 metabolically healthy obesity (MHO) individuals. Obesity phenotypes, including MHNW, MHO, metabolically unhealthy normal weights (MUNW), and metabolic unhealthy obesity (MUO), were determined using the criteria of the Joint International statement (JIS) for metabolic syndrome. Dietary intake data from the previous year was gathered using a food frequency questionnaire. Cox proportional hazard regression was used to estimate the hazard ratio and 95% confidence intervals (HRs and 95% CIs) of obesity phenotypes incident across tertiles of EDIH and ELIH scores.

RESULTS

The mean ± SD of age and BMI of all participants were 33.5 ± 12.2 years and 24.3 ± 3.8 kg/m2, respectively. In the multivariable-adjusted model, a higher ELIH score was associated with a greater risk for incidence of MUO (HR: 3.47, 95%CI: 2.54-4.74; Ptrend =  < 0.001) and MHO (HR: 3.61, 95%CI: 2.73-4.77; Ptrend =  < 0.001). Also, a higher score of EDIH was related to an increased risk of MUO incidence (HR: 1.35, 95%CI: 1.02-1.79; P for trend = 0.046). However, there was no significant association between a higher score of EDIH and the risk of MHO.

CONCLUSION

Our findings revealed that a high insulinemic potential of diet and lifestyle, determined by EDIH and ELIH indices, may be related to an increase in the simultaneous occurrence of obesity with metabolic disorders in Iranian adults.

Clinical monitored in subjects metabolically healthy and unhealthy before and during a SARS-CoV-2 infection- A cross-sectional study in Mexican population

The COVID-19 disease has forced us to consider the physiologic role of obesity and metabolically healthy and unhealthy status in response to SARS-CoV-2 infection. Hematological, coagulation, biochemical, and immunoinflammatory changes have been informed with a disparity in morbidity and mortality. Therefore, we aimed to investigate the influence of metabolic health on clinical features in a cross-sectional study in Mexican subjects with and without SARS-CoV-2 infection in non-severe stages after a rigorous classification of obese and non-obese subjects who were metabolically healthy and unhealthy. Four groups were formed: 1) metabolically healthy with normal BMI (MHN); 2) metabolically unhealthy with normal BMI (MUN); 3) metabolically healthy obese (MHO); 4) metabolically unhealthy obese (MUO). Serum proinflammatory (TNF-α, MCP-1, IL-1β, and IL-6) and anti-inflammatory (TGF-β, IL-1Ra, IL-4, and IL-10) cytokines, hematological parameters, coagulation, and acute phase components were evaluated. Our results showed that MHO people live with inflammaging. Meanwhile, MUN and MUO subjects develop metaflammation. Both inflammaging and metaflammation cause imperceptible modifications on hematological parameters, mainly in leukocyte populations and platelets, as well as acute phase and coagulation components. The statistical analysis revealed that many clinical features are dependent on metabolic health. In conclusion, MHO subjects seem to be transitioning from metabolically healthy to unhealthy, which is accelerated in acute processes, such as SARS-CoV-2 infection. Meanwhile, metabolically unhealthy subjects independently of BMI have a deteriorating immunometabolic status associated with a hyperinflammatory state leading to multi-organ dysfunction, treatment complications, and severe COVID-19 disease.

Prevalence of liver cirrhosis based on the metabolic health and weight criteria: Report from the Korea National Health and Nutrition Examination Survey (KNHANES) data analysis

BACKGROUND

Recent studies have proposed two distinctive types of obesity, metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO), based on various physiological factors. This study sought to explore the relationship between the metabolic obesity types and the incidence of liver cirrhosis (LC) in a large nationally-representative population.

METHODS

Data on 27,629 adults with MHO or MUHO, were analyzed from the Korea National Health and Nutrition Examination Survey (KNHANES) obtained from 2015 through 2019. Four categories of metabolic health and weight (MHW) were generated for analysis: (1) MHO, (2) MUHO, (3) Metabolically unhealthy normal weight (MUHNW), and (4) Metabolically healthy normal weight (MHNW). Statistical analyzes were performed with univariate and multivariate logistic regression.

RESULTS

The prevalence of LC did not show statistically significant differences among the MHW categories: 0.5% in MHO, 0.4% in MUHO, 0.2% in MHNW, and 0.3% in MUHNW. The unadjusted analysis showed a significant association between self-reported LC and MUHO, but this association was not evident in the adjusted analysis. In the adjusted analysis of the prevalence of laboratory LC, a significant association emerged in the MUHO group, followed in descending order of magnitude by the MHO and MUHNW groups. A favorable fasting blood glucose level was the only factor associated with increased prevalence of reported LC in MUHO.

CONCLUSIONS

The study demonstrated a difference in the prevalence of LC between MHO and MUHO. Our study concludes that the MHO phenotype is a transient status with regard to metabolic abnormalities, and caution is necessary when evaluating MHO.

The Metabolic Profiles of Metabolically Healthy Obese and Metabolically Unhealthy Obese South African Adults over 10 Years

Obesity is associated with an increased cardiometabolic risk, but some individuals maintain metabolically healthy obesity (MHO). The aims were to follow a cohort of black South African adults over a period of 10 years to determine the proportion of the group that maintained MHO over 10 years, and to compare the metabolic profiles of the metabolically healthy and metabolically unhealthy groups after the follow-up period. The participants were South African men (n = 275) and women (n = 642) from the North West province. The prevalence of obesity and the metabolic syndrome increased significantly. About half of the metabolically healthy obese (MHO) adults maintained MHO over 10 years, while 46% of the women and 43% of men became metabolically unhealthy overweight/obese (MUO) at the end of the study. The metabolic profiles of these MHO adults were similar to those of the metabolically healthy normal weight (MHNW) group in terms of most metabolic syndrome criteria, but they were more insulin resistant; their CRP, fibrinogen, and PAI-1act were higher and HDL-cholesterol was lower than the MHNW group. Although the metabolic profiles of the MUO group were less favourable than those of their counterparts, MHO is a transient state and is associated with increased cardiometabolic risk.

2022 Prevention of chronic non-communicable diseases in Of the Russian Federation. National guidelines

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Independent and joint effects of body mass index and metabolic health in mid- and late-life on all-cause mortality: a cohort study from the Swedish Twin Registry with a mean follow-up of 13 Years

BACKGROUND

There is robust evidence that in midlife, higher body mass index (BMI) and metabolic syndrome (MetS), which often co-exist, are associated with increased mortality risk. However, late-life findings are inconclusive, and few studies have examined how metabolic health status (MHS) affects the BMI-mortality association in different age categories. We, therefore, aimed to investigate how mid- and late-life BMI and MHS interact to affect the risk of mortality.

METHODS

This cohort study included 12,467 participants from the Swedish Twin Registry, with height, weight, and MHS measures from 1958-2008 and mortality data linked through 2020. We applied Cox proportional hazard regression with age as a timescale to examine how BMI categories (normal weight, overweight, obesity) and MHS (identification of MetS determined by presence/absence of hypertension, hyperglycemia, low HDL, hypertriglyceridemia), independently and in interaction, are associated with the risk of all-cause mortality. Models were adjusted for sex, education, smoking, and cardiovascular disease.

RESULTS

The midlife group included 6,252 participants with a mean age of 59.6 years (range = 44.9-65.0) and 44.1% women. The late-life group included 6,215 participants with mean age 73.1 years (65.1-95.3) and 46.6% women. In independent effect models, metabolically unhealthy status in midlife increased mortality risks by 31% [hazard ratio 1.31; 95% confidence interval 1.12-1.53] and in late-life, by 18% (1.18;1.10-1.26) relative to metabolically healthy individuals. Midlife obesity increased the mortality risks by 30% (1.30;1.06-1.60) and late-life obesity by 15% (1.15; 1.04-1.27) relative to normal weight. In joint models, the BMI estimates were attenuated while those of MHS were less affected. Models including BMI-MHS categories revealed that, compared to metabolically healthy normal weight, the metabolically unhealthy obesity group had increased mortality risks by 53% (1.53;1.19-1.96) in midlife, and across all BMI categories in late-life (normal weight 1.12; 1.01-1.25, overweight 1.10;1.01-1.21, obesity 1.31;1.15-1.49). Mortality risk was decreased by 9% (0.91; 0.83-0.99) among those with metabolically healthy overweight in late-life.

CONCLUSIONS

MHS strongly influenced the BMI-mortality association, such that individuals who were metabolically healthy with overweight or obesity in mid- or late-life did not carry excess risks of mortality. Being metabolically unhealthy had a higher risk of mortality independent of their BMI.

Association of Dietary Insulin Index and Dietary Insulin Load With Metabolic Health Status in Iranian Overweight and Obese Adolescents

Background

Limited data are available on the association of dietary insulin load (DIL) and dietary insulin index (DII) with health status in pediatrics. We aimed to investigate the relationship of DIL and DII with metabolic health status in Iranian overweight/obese adolescents.

Methods

In this cross-sectional study, using a multistage cluster random-sampling method, 203 overweight/obese adolescents (aged 12 to <18 years) were included. A validated 147-item food frequency questionnaire (FFQ) was used for a dietary intake assessment. Glycemic and lipid profile, blood pressure (BP), and anthropometric indices were measured. Participants were categorized as metabolically healthy obese (MHO) or metabolically unhealthy obese (MUO) using the two methods of the International Diabetes Federation (IDF) and a combination of IDF with Homeostasis Model Assessment Insulin Resistance (HOMA-IR).

Results

According to IDF and IDF/HOMA-IR strategies, 38.9% (n = 79) and 33.0% (n = 67) of participants belonged to MUO category. After adjustments for potential confounders, subjects in the highest tertile of DIL in comparison with those in the lowest tertile had the odds ratio (OR) values of 8.44 (95% CI: 2.24-31.78) and 5.86 (95% CI: 1.39-24.58) for MUO based on IDF and IDF/HOMA-IR definitions, respectively. Moreover, after considering potential confounders, adolescents in the highest tertile of DII, compared to the lowest tertile, were, respectively, 6.93 (OR: 6.93; 95% CI: 2.59-18.57) and 5.26 (OR: 5.26; 95% CI: 1.85-14.97) times more likely to be MUO, based on IDF and IDF/HOMA-IR definitions. A significant decreasing trend was observed for OR of MUO in tertiles of DIL and DII. The stratified analysis revealed that these associations were stronger in obese participants; in overweight subjects, the association was not independent of confounders.

Conclusion

This population-based study revealed that higher DIL and DII were strongly related to increased OR of MUO in Iranian adolescents, especially in obese participants. Further investigations, especially with a prospective design, are needed to affirm these findings.

The Interplay of Obesity, Dyslipidemia and Immune Dysfunction: A Brief Overview on Pathophysiology, Animal Models, and Nutritional Modulation

Obesity has emerged as a leading global health concern. It is characterized by chronic low-grade inflammation, which impairs insulin signaling, lipid metabolism and immune function. Recent findings from animal and clinical studies have begun to elucidate the underlying mechanisms of immune dysfunction seen in the context of obesity. Here, we provide a brief review on the current understanding of the interplay between obesity, dyslipidemia and immunity. We also emphasize the advantages and shortcomings of numerous applicable research models including rodents and large animal swine that aim at unraveling the molecular basis of disease and clinical manifestations. Although there is no perfect model to answer all questions at once, they are often used to complement each other. Finally, we highlight some emerging nutritional strategies to improve immune function in the context of obesity with a particular focus on choline and foods that contains high amounts of choline.

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.