Transition from metabolically benign to metabolically unhealthy obesity and 10-year cardiovascular disease incidence: The ATTICA cohort study

The transition of metabolic phenotypes and cardiovascular events: Panasonic cohort study 16

OBJECTIVE

The study objective was to investigate whether changes in metabolic phenotype affect the risk of cardiovascular events.

METHODS

All 117,589 participants were included in this retrospective cohort study. The metabolic phenotypes of the participants were assessed at two points (the second evaluation was set 2 years after the first evaluation), and the incidence rate of cardiovascular events was observed for 11 years. The main outcome was 3-point major adverse cardiac events (MACE), which comprises cardiovascular death, nonfatal coronary artery disease, and nonfatal stroke incidence.

RESULTS

Of the participants, 2748 (2.3%) cases of 3-point MACE were identified during follow-up. The stable metabolically healthy obesity group had a higher risk of 3-point MACE than those with stable metabolically healthy nonobesity (MHNO). Additionally, the change from metabolically healthy obesity to MHNO for 2 years decreased the risk of 3-point MACE (hazard ratio [HR], 1.12: 95% CI: 0.84-1.47) to the same level as stable MHNO. However, the change from metabolically abnormal nonobesity and metabolically abnormal obesity to MHNO for 2 years maintained a higher risk of 3-point MACE (HR, 1.66 [95% CI: 1.36-2.01]; HR, 1.91 [95% CI: 1.22-2.81]) than those with stable MHNO.

CONCLUSIONS

Change in metabolic phenotype is associated with incident 3-point MACE.

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.

Atherosclerosis and the Bidirectional Relationship between Cancer and Cardiovascular Disease: From Bench to Bedside-Part 1

Atherosclerosis, a complex metabolic-immune disease characterized by chronic inflammation driven by the buildup of lipid-rich plaques within arterial walls, has emerged as a pivotal factor in the intricate interplay between cancer and cardiovascular disease. This bidirectional relationship, marked by shared risk factors and pathophysiological mechanisms, underscores the need for a comprehensive understanding of how these two formidable health challenges intersect and influence each other. Cancer and its treatments can contribute to the progression of atherosclerosis, while atherosclerosis, with its inflammatory microenvironment, can exert profound effects on cancer development and outcomes. Both cancer and cardiovascular disease involve intricate interactions between general and personal exposomes. In this review, we aim to summarize the state of the art of translational data and try to show how oncologic studies on cardiotoxicity can broaden our knowledge of crucial pathways in cardiovascular biology and exert a positive impact on precision cardiology and cardio-oncology.

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.

Metabolic-associated fatty liver disease and sarcopenia: A double whammy

The prevalence of metabolic-associated fatty liver disease (MAFLD) has increased substantially in recent years because of the global obesity pandemic. MAFLD, now recognized as the number one cause of chronic liver disease in the world, not only increases liver-related morbidity and mortality among sufferers but also worsens the complications associated with other comorbid conditions such as cardiovascular disease, type 2 diabetes mellitus, obstructive sleep apnoea, lipid disorders and sarcopenia. Understanding the interplay between MAFLD and these comorbidities is important to design optimal therapeutic strategies. Sarcopenia can be either part of the disease process that results in MAFLD (e.g., obesity or adiposity) or a consequence of MAFLD, especially in the advanced stages such as fibrosis and cirrhosis. Sarcopenia can also worsen MAFLD by reducing exercise capacity and by the production of various muscle-related chemical factors. Therefore, it is crucial to thoroughly understand how we deal with these diseases, especially when they coexist. We explore the pathobiological interlinks between MAFLD and sarcopenia in this comprehensive clinical update review article and propose evidence-based therapeutic strategies to enhance patient care.

Phenotyping obesity: A focus on metabolically healthy obesity and metabolically unhealthy normal weight

Over the past 4 decades, research has shown that having a normal body weight does not automatically imply preserved metabolic health and a considerable number of lean individuals harbour metabolic abnormalities typically associated with obesity. Conversely, excess adiposity does not always equate with an abnormal metabolic profile. In fact, evidence exists for the presence of a metabolically unhealthy normal weight (MUHNW) and a metabolically healthy obese (MHO) phenotype. It has become increasingly recognised that different fat depots exert different effects on the metabolic profile of each individual by virtue of their location, structure and function, giving rise to these different body composition phenotypes. Furthermore, other factors have been implicated in the aetiopathogenesis of the body composition phenotypes, including genetics, ethnicity, age and lifestyle/behavioural factors. Even though to date both MHO and MUHNW have been widely investigated and documented in the literature, studies report different outcomes on long-term cardiometabolic morbidity and mortality. Future large-scale, observational and population-based studies are required for better profiling of these phenotypes as well as to further elucidate the pathophysiological role of the adipocyte in the onset of metabolic disorders to allow for better risk stratification and a personalised treatment paradigm.

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

AIMS

The aim of this study was to systematically review and analyze differences in the levels of C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) comparing metabolically healthy but obese (MHO) with metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO) subjects.

DATA SYNTHESIS

We searched PubMed, Embase, Web of Science, and Scopus for studies that matched the relevant search terms. Differences in inflammatory marker levels between MHO and the other three phenotypes were pooled as standardized mean differences (SMD) or differences of medians (DM) using a random-effects model. We included 91 studies reporting data on 435,007 individuals. The CRP levels were higher in MHO than in MHNO subjects (SMD = 0.63, 95% CI: 0.49, 0.76; DM = 0.83 mg/L, 95% CI: 0.56, 1.11). The CRP levels were higher in MHO than in MUNO subjects (SMD = 0.16, 95% CI: 0.05, 0.28; DM = 0.39 mg/L, 95% CI: 0.09, 0.69). The CRP levels were lower in MHO than in MUO individuals (SMD = -0.43, 95% CI: -0.54, -0.31; DM = -0.82 mg/L, 95% CI: -1.16, -0.48). The IL-6 levels in MHO were higher than in MHNO while lower than in MUO subjects. The TNF-α levels in MHO were higher than in MHNO individuals.

CONCLUSIONS

This review provides evidence that CRP levels in MHO are higher than in MHNO and MUNO subjects but lower than in MUO individuals. Additionally, IL-6 levels in MHO are higher than in MHNO but lower than in MUO subjects, and TNF-α levels in MHO are higher than in MHNO individuals.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO number: CRD42021234948.

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.

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.

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

OBJECTIVES

Endothelial dysfunction, the earliest vascular alteration, is a consequence of metabolic disorders associated with obesity. However, it is still unclear whether a proportion of obese individuals without metabolic alterations associated with obesity, defined as "metabolically healthy obesity (MHO)", exhibit better endothelial function. We therefore aimed to investigate the association of different metabolic obesity phenotypes with endothelial dysfunction.

METHODS

The obese participants without clinical cardiovascular disease from the MESA (Multi-Ethnic Study of Atherosclerosis) were allocated to the different metabolic obesity phenotypes based on their metabolic status, including MHO and metabolically unhealthy obesity (MUO). Associations of metabolic obesity phenotypes with the biomarkers of endothelial dysfunction, including soluble intercellular adhesion molecule-1 (sICAM-1) and soluble E-selectin (sE-selectin), were evaluated using multiple linear regression models.

RESULTS

Plasma levels of sICAM-1 and sE-selectin were respectively measured in 2371 and 968 participants. Compared to the non-obese participants, those with MUO were associated with higher concentrations of sICAM-1 (β 22.04, 95% CI 14.33-29.75, P < 0.001) and sE-selectin (β 9.87, 95% CI 6.00-13.75, P < 0.001) after adjusting for confounders. However, no differences were found for the concentrations of sICAM-1 (β 0.70, 95% CI - 8.91 to 10.32, P = 0.886) and sE-selectin (β 3.69, 95% CI - 1.13 to 8.51, P = 0.133) in the participants with MHO compared to the non-obese participants.

CONCLUSIONS

Individuals with MUO were associated with elevated biomarkers of endothelial dysfunction, but the association with endothelial dysfunction was not found in those with MHO, indicating that the individuals with MHO might exhibit better endothelial function.

Obesity phenotypes and cardiovascular risk: From pathophysiology to clinical management

Obesity epidemic reached the dimensions of a real global health crisis with more than one billion people worldwide living with obesity. Multiple obesity-related mechanisms cause structural, functional, humoral, and hemodynamic alterations with cardiovascular (CV) deleterious effects. A correct assessment of the cardiovascular risk in people with obesity is critical for reducing mortality and preserving quality of life. The correct identification of the obesity status remains difficult as recent evidence suggest that different phenotypes of obesity exist, each one associated with different degrees of CV risk. Diagnosis of obesity cannot depend only on anthropometric parameters but should include a precise assessment of the metabolic status. Recently, the World Heart Federation and World Obesity Federation provided an action plan for management of obesity-related CV risk and mortality, stressing for the instauration of comprehensive structured programs encompassing multidisciplinary teams. In this review we aim at providing an updated summary regarding the different obesity phenotypes, their specific effects on CV risk and differences in clinical management.

Cognitive Functions, Neurotransmitter Alterations, and Hippocampal Microstructural Changes in Mice Caused by Feeding on Western Diet

Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD) is the most common chronic liver disease in Western countries. It is becoming increasingly evident that peripheral organ-centered inflammatory diseases, including liver diseases, are linked with brain dysfunctions. Therefore, this study aims to unravel the effect of MASLD on brain histology, cognitive functions, and neurotransmitters. For this purpose, mice fed for 48 weeks on standard (SD) or Western diet (WD) were evaluated by behavioral tests, followed by sacrifice and analysis of the liver-brain axis including histopathology, immunohistochemistry, and biochemical analyses. Histological analysis of the liver showed features of Metabolic Dysfunction-Associated Steatohepatitis (MASH) in the WD-fed mice including lipid droplet accumulation, inflammation, and fibrosis. This was accompanied by an elevation of transaminase and alkaline phosphatase activities, increase in inflammatory cytokine and bile acid concentrations, as well as altered amino acid concentrations in the blood. Interestingly, compromised blood capillary morphology coupled with astrogliosis and microgliosis were observed in brain hippocampus of the WD mice, indicating neuroinflammation or a disrupted neurovascular unit. Moreover, attention was impaired in WD-fed mice along with the observations of impaired motor activity and balance, enhanced anxiety, and stereotyped head-twitch response (HTR) behaviors. Analysis of neurotransmitters and modulators including dopamine, serotonin, GABA, glutamate, and acetylcholine showed region-specific dysregulation in the brain of the WD-fed mice. In conclusion, the induction of MASH in mice is accompanied by the alteration of cellular morphology and neurotransmitter expression in the brain, associated with compromised cognitive functions.

Association of metabolically unhealthy non-obese and metabolically healthy obese individuals with arterial stiffness and 10-year cardiovascular disease risk: a cross-sectional study in Chinese adults

BACKGROUND

The relationship between metabolically healthy obese individuals (MHO) and cardiovascular disease (CVD) risk is disputed. This study investigated the association of metabolically unhealthy non-obese(MUNO) individuals and MHO with arterial stiffness and 10-year CVD risk.

METHODS

A total of 13,435 participants were enrolled and further divided into the metabolically healthy non-obese (MHNO) phenotype (n = 4927), MUNO phenotype (n = 1971), MHO phenotype (n = 2537) and metabolically unhealthy obese (MUO) phenotype (n = 4000) according to body mass index (BMI) and metabolic status. We used brachial ankle pulse wave velocity (baPWV) to measure arterial stiffness and the Framingham risk score (FRS) to evaluate the 10-year CVD risk.

RESULTS

The MUO and MUNO phenotypes had higher mean baPWV values than the MHO and MHNO phenotypes, regardless of age (1446.19 ± 233.65 vs. 1423.29 ± 240.72 vs. 1283.57 ± 213.77 vs. 1234.08 ± 215.99 cm/s, P < 0.001). Logistic regression analysis indicated that the MUNO and MUO phenotypes were independently correlated with elevated baPWV and 10-year CVD risk, while the MHO phenotype was independently associated with only the 10-year CVD risk. In metabolically healthy subjects, BMI showed a dose-dependent increase in the risk of elevated baPWV, with an adjusted OR of 1.007 (95% CI 1.004-1.010, P < 0.001). However, in metabolically unhealthy participants, the estimate for the relationship between elevated baPWV and BMI was nonsignificant.

CONCLUSIONS

The MUNO phenotype exhibits increased arterial stiffness and 10-year CVD risk. However, BMI is positively and dose-dependently correlated with arterial stiffness only in metabolically healthy subjects. We speculate that metabolic status may be a strong confounder in the obesity-elevated baPWV association.

Adipose Tissue and Metabolic Health

In this review, we provide a brief synopsis of the connections between adipose tissue and metabolic health and highlight some recent developments in understanding and exploiting adipocyte biology. Adipose tissue plays critical roles in the regulation of systemic glucose and lipid metabolism and secretes bioactive molecules possessing endocrine, paracrine, and autocrine functions. Dysfunctional adipose tissue has a detrimental impact on metabolic health and is intimately involved in key aspects of metabolic diseases such as insulin resistance, lipid overload, inflammation, and organelle stress. Differences in the distribution of fat depots and adipose characteristics relate to divergent degrees of metabolic dysfunction found in metabolically healthy and unhealthy obese individuals. Thermogenic adipocytes increase energy expenditure via mitochondrial uncoupling or adenosine triphosphate-consuming futile substrate cycles, while functioning as a metabolic sink and participating in crosstalk with other metabolic organs. Manipulation of adipose tissue provides a wealth of opportunities to intervene and combat the progression of associated metabolic diseases. We discuss current treatment modalities for obesity including incretin hormone analogs and touch upon emerging strategies with therapeutic potential including exosome-based therapy, pharmacological activation of brown and beige adipocyte thermogenesis, and administration or inhibition of adipocyte-derived factors.

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 the expression of TLR4, TLR2, and MyD88 with low-grade chronic inflammation in individuals with metabolically healthy obesity

BACKGROUND

Among the Toll-like receptors (TLR) that are dependent of myeloid response protein (MyD88), the TLR4 and TLR2 are directly associated with low-grade chronic inflammation; however, they are not been investigated in subjects with metabolically healthy obesity (MHO). Thus, the objective of this study was to determine the association between the expression of TLR4, TLR2, and MyD88 with low-grade chronic inflammation in individuals with MHO.

METHODS AND RESULTS

Men and women with obesity aged 20 to 55 years were enrolled in a cross-sectional study. Individuals with MHO were allocated into the groups with and without low-grade chronic inflammation. Pregnancy, smoking, alcohol consumption, intense physical activity or sexual intercourse in the previous 72 h, diabetes, high blood pressure, cancer, thyroid disease, acute or chronic infections, renal impairment, and hepatic diseases, were exclusion criteria. The MHO phenotype was defined by a body mass index (BMI ≥ 30 kg/m²) plus one or none of the following cardiovascular risk factors: hyperglycemia, elevated blood pressure, hypertriglyceridemia, and low high-density lipoprotein cholesterol. A total of 64 individuals with MHO were enrolled and allocated into the groups with (n = 37) and without (n = 27) inflammation. The multiple logistic regression analysis indicated that TLR2 expression is significantly associated with inflammation in individuals with MHO. In the subsequent analysis adjusted by BMI, TLR2 expression remained associated with inflammation in individuals with MHO.

CONCLUSION

Our results suggest that overexpression of TLR2, but not TLR4 and MyD88, is associated with low-grade chronic inflammation in subjects with MHO.

D’Cunha N, Tsiampalis T, Zec M, Sergi D, Travica N, Marx W, McKune AJ, Panagiotakos DB, Naumovski N. Metabolically Healthy Overweight and Obesity, Transition to Metabolically Unhealthy Status and Cognitive Function: Results from the Framingham Offspring Study

AIMS

To evaluate the association between metabolically healthy overweight/obesity (MHO) status and longitudinal cognitive function while also considering the stability of the condition.

METHODS

In total, 2892 participants (mean age 60.7 (9.4) years) from Framingham Offspring Study completed health assessments every four years since 1971. Neuropsychological testing was repeated every four years starting from 1999 (Exam 7) to 2014 (Exam 9) (mean follow-up: 12.9 (3.5) years). Standardized neuropsychological tests were constructed into three factor scores (general cognitive performance, memory, processing speed/executive function). Healthy metabolic status was defined as the absence of all NCEP ATP III (2005) criteria (excluding waist circumference). MHO participants who scored positively for one or more of NCEP ATPIII parameters in the follow-up period were defined as unresilient MHO.

RESULTS

No significant difference on the change in cognitive function over time was observed between MHO and metabolically healthy normal weight (MHN) individuals (all p > 0.05). However, a lower processing speed/executive functioning scale score was observed in unresilient MHO participants compared to resilient MHO participants (β = -0.76; 95% CI = -1.44, -0.08; p = 0.030).

CONCLUSIONS

Retaining a healthy metabolic status over time represents a more important discriminant in shaping cognitive function compared to body weight alone.

Trends in the Prevalence of Metabolically Healthy Obesity Among US Adults, 1999-2018

IMPORTANCE

Improved understanding of trends in the proportion of individuals with metabolically healthy obesity (MHO) may facilitate stratification and management of obesity and inform policy efforts.

OBJECTIVES

To characterize trends in the prevalence of MHO among US adults with obesity, overall and by sociodemographic subgroups.

DESIGN, SETTING, AND PARTICIPANTS

This survey study included 20 430 adult participants from 10 National Health and Nutrition Examination Survey (NHANES) cycles between 1999-2000 and 2017-2018. The NHANES is a series of cross-sectional and nationally representative surveys of the US population conducted continuously in 2-year cycles. Data were analyzed from November 2021 to August 2022.

EXPOSURES

National Health and Nutrition Examination Survey cycles from 1999-2000 to 2017-2018.

MAIN OUTCOMES AND MEASURES

Metabolically healthy obesity was defined as a body mass index of 30.0 (calculated as weight in kilograms divided by height in meters squared) without any metabolic disorders in blood pressure, fasting plasma glucose (FPG), high-density lipoprotein cholesterol (HDL-C), or triglycerides based on established cutoffs. Trends in the age-standardized prevalence of MHO were estimated using logistic regression analysis.

RESULTS

This study included 20 430 participants. Their weighted mean (SE) age was 47.1 (0.2) years; 50.8% were women, and 68.8% self-reported their race and ethnicity as non-Hispanic White. The age-standardized prevalence (95% CI) of MHO increased from 3.2% (2.6%-3.8%) in the 1999-2002 cycles to 6.6% (5.3%-7.9%) in the 2015-2018 cycles (P < .001 for trend). There were 7386 adults with obesity. Their weighted mean (SE) age was 48.0 (0.3) years, and 53.5% were women. The age-standardized proportion (95% CI) of MHO among these 7386 adults increased from 10.6% (8.8%-12.5%) in the 1999-2002 cycles to 15.0% (12.4%-17.6%) in the 2015-2018 cycles (P = .02 for trend). Substantial increases in the proportion of MHO were observed for adults aged 60 years or older, men, non-Hispanic White individuals, and those with higher income, private insurance, or class I obesity. In addition, there were significant decreases in the age-standardized prevalence (95% CI) of elevated triglycerides (from 44.9% [40.9%-48.9%] to 29.0% [25.7%-32.4%]; P < .001 for trend) and reduced HDL-C (from 51.1% [47.6%-54.6%] to 39.6% [36.3%-43.0%]; P = .006 for trend). There was also a significant increase in elevated FPG (from 49.7% [95% CI, 46.3%-53.0%] to 58.0% [54.8%-61.3%]; P < .001 for trend) but no significant change in elevated blood pressure (from 57.3% [53.9%-60.7%] to 54.0% [50.9%-57.1%]; P = .28 for trend).

CONCLUSIONS AND RELEVANCE

The findings of this cross-sectional study suggest that the age-standardized proportion of MHO increased among US adults from 1999 to 2018, but differences in trends existed across sociodemographic subgroups. Effective strategies are needed to improve metabolic health status and prevent obesity-related complications in adults with obesity.

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.

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 four 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 (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 occurred in MUOO reduced the risk of diabetes compared to stable MUOO, changing from MUOO to MHNW, MUNW, and MHOO resulted in HRs (95% CI) of 0.57 (0.37, 0.87), 0.68 (0.50, 0.93), and 0.45 (0.34, 0.60), respectively.

CONCLUSIONS

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.

Association of Metabolically Healthy Obesity and Risk of Cardiovascular Disease Among Adults in China: A Retrospective Cohort Study

PURPOSE

Previous studies have shown that metabolically healthy obesity (MHO) and changes in its status are connected to an increased incidence of cardiovascular disease (CVD). Yet, fewer studies have been conducted in China, especially for the middle-aged and elderly population, a high-risk group. The purpose of the study was to investigate the association between metabolic health status and CVD events.

PATIENTS AND METHODS

A total of 46,055 participants were categorized into 6 subgroups with different metabolic states according to the existence of metabolic syndrome and body mass index (BMI). The changes in obesity and metabolic health status were defined from baseline to follow-up outcomes with a combination of overweight and obesity. Cox proportional hazards models estimated the association of CVD events and each BMI-metabolic groups.

RESULTS

MHO and metabolic abnormality normal weight (MANW) subjects had a higher HR of CVD, 1.62 (95% CI, 1.36-1.92) and 1.24 (95% CI, 1.07-1.44), respectively, than their metabolically healthy normal weight (MHNW) counterparts. Then, more than 50% and 30% of the metabolically healthy overweight or obesity (MHOO) populations maintained their status and converted to a metabolically unhealthy state, respectively. Stable MANW, MHOO and metabolically abnormal obesity (MAO) were associated with a higher risk for CVD, 1.68 (95% CI, 1.37-2.05),1.26 (95% CI, 1.08-1.47) and 1.65 (95% CI, 1.45-1.88), respectively, than stable MHNW.

CONCLUSION

Despite being of normal weight, MANW status is in fact a risk factor for CVD, as well as MHO, especially for the Chinese middle-aged and elderly population. Furthermore, metabolic health is a transient state for partial middle-aged and elderly Chinese individuals, and MAO has the highest risk of CVD, including coronary heart disease (CHD) and stroke.

Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China

Background

A change in weight or metabolic status is a dynamic process, yet most studies have focused on metabolically healthy obesity (MHO) and the transition between MHO and metabolically unhealthy obesity (MUO); therefore, they have not fully revealed the nature of all possible transitions among metabolism-weight phenotypes over the years.

Methods

This was a longitudinal study based on a retrospective health check-up cohort. A total of 9,742 apparently healthy individuals aged 20-60 years at study entry were included and underwent at least two health check-ups. Six metabolism-weight phenotypes were cross-defined by body mass index (BMI) categories and metabolic status as follows: metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), MHO, metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW), and MUO. A multistate Markov model was used to analyse all possible transitions among these phenotypes and assess the effects of demographic and blood indicators on the transitions.

Results

The transition intensity from MUNW to MHNW was the highest (0.64), followed by the transition from MHO to MUO (0.56). The greatest sojourn time appeared in the MHNW state (3.84 years), followed by the MUO state (2.34 years), and the shortest sojourn time appeared in the MHO state (1.16 years). Transition intensities for metabolic improvement gradually decreased with BMI level as follows: 0.64 for MUNW to MHNW, 0.44 for MUOW to MHNW, and 0.27 for MUO to MHO; however, transition intensities for metabolic deterioration, including MHNW to MUNW, MHOW to MUOW, and MHO to MUO, were 0.15, 0.38, and 0.56, respectively. In the middle-aged male group, elevated alanine aminotransferase (ALT), aspartate aminotransferase (AST), and uric acid (UA) increased the risk of deterioration in weight and metabolic status and decreased the possibility of improvement.

Conclusion

Maintaining a normal and stable BMI is important for metabolic health. More attention should be given to males and elderly people to prevent their progression to an unhealthy metabolic and/or weight status. MHO is the most unstable phenotype and is prone to convert to the MUO state, and individuals with abnormal ALT, AST and UA are at an increased risk of transitioning to an unhealthy weight and/or metabolic status; therefore, we should be alert to abnormal indicators and MHO. Intervention measures should be taken early to maintain healthy weight and metabolic status.

Assessment of a consensus definition of obesity and metabolic health phenotypes in children at different pubertal stages

Not all individuals with obesity develop metabolic complications, which has brought about the concepts of metabolically healthy and unhealthy obesity (MHO/MUO). However, inconsistent definitions of these conditions have limited their understanding. We assessed whether a recently-proposed consensus definition for MHO/MUO correlates with adiposity and reflects metabolic risk parameters during puberty. Low-middle income children from the Growth and Obesity Cohort Study (Santiago, Chile) were included (n = 949; 1692 visits at Tanner (T)2, T4 and/or one-year post menarche (1YPM)). Anthropometry, body composition and metabolic parameters were compared between MUO and MHO, and also in children without obesity. The risk for presenting MUO phenotype was significantly elevated with higher waist-height ratio (T2), zBMI (T2, T4), trunk fat, and C-reactive protein (T4). Elevated cardiometabolic indices were important predictors of the "unhealthy" phenotype allocation in children with or without obesity. Our observations suggest that the consensus definition in children at T2, T4 and 1YPM reflects metabolic risk and central obesity. Metabolic health phenotype allocation by this equation enables easy detection of risk factors that call for action to prevent long-term metabolic derangements in children with obesity and, importantly, also those without obesity.

Long-term metabolic fate and mortality in obesity without metabolic syndrome

BACKGROUND

Obesity and metabolic syndrome (MetS) are known to expose to atrial fibrillation (AF), cardiovascular diseases (CVD) and mortality. Metabolically healthy obesity refers to obesity without MetS. This study aimed to investigate how obesity and MetS modify the risk of CVD, AF and mortality in very long-time follow-up.

METHODS

Finnish middle-aged subjects (n = 1045) were grouped into four subgroups according to the presence of obesity and MetS. CVD events and AF were followed for 24 years and total mortality for 30 years. Moreover, 600 available patients had a follow-up visit for metabolic examinations after approximately 22 years.

RESULTS

One-hundred and sixty-two (30%) subjects without obesity or MetS died during the follow-up. Ninety-two (17%) of the patients in this group had a CVD event and 58 (11%) were diagnosed with AF. As compared to them, obese subjects without MetS had similar metabolic fate and mortality (mortality 26 (38%), p = .143; CVD event 12 (18%), p = .858 and AF 7 (10%), p = .912, respectively), whereas subjects with obesity and MetS had greater mortality (102 (49%), p < .001), more CVD (71 (34%), p < .001) and AF (49 (23%), p < .001). Non-obese individuals with MetS had greater rates of mortality (96 (44%), p < .001) and CVD (80 (37%), p < .001), but not of AF (26 (12%), p = .606). Of the 40 subjects with obesity but without MetS at baseline and available for the follow-up visit, 15 (38%) were metabolically healthy at the follow-up visit.

CONCLUSIONS

In the present long-term follow-up study, the presence of MetS, but not obesity only, implies a greater risk of mortality and CVD. The risk of AF is increased only in subjects with both obesity and MetS. However, obesity without MetS tends to progress eventually to obesity with MetS. Key messagesThe presence of metabolic syndrome (MetS), but not obesity only, entails a greater risk of mortality and cardiovascular diseases.The risk of atrial fibrillation is increased only in subjects with both obesity and MetS.Obesity without MetS tends to progress eventually to obesity with MetS.

Association between metabolic obesity phenotype, transition of metabolic phenotypes and the risk of hyperuricemia in Chinese adults: A cohort study

Prospective evidence on the association of obesity and metabolic health status and its transition over time with the risk of hyperuricemia in the Chinese population is limited. This study aims to investigate the phenotypic transition characteristics of metabolic obesity in Chinese adults and its association with hyperuricemia. Using the China Health and Retirement Longitudinal Survey (CHARLS) survey data in 2011 and 2015, 6059 adults aged ≥ 18 years were selected as the research people. The participants' general information, living habits, blood sample testing, and blood uric acid testing data during follow-up were extracted. According to body weight and metabolic health status, obesity phenotypes were divided into: metabolically normal weight group (MHNW), metabolically normal overweight/obesity group (MHOWO); metabolically abnormal normal weight group (MUNW); metabolically abnormal overweight/obese group (MUHOWO). Multiple linear regression was used to evaluate the correlation between metabolic obesity phenotype and serum uric acid level, and logistic regression model was used to analyze the association of metabolic obesity phenotype and transition with the risk of hyperuricemia. The average age of all subjects was (58.62 ± 8.93) years old, and 42.1% were male. The MHOWO phenotype was present in 19.2% of the general population and 48.6% of the baseline who were overweight or obese population. During the 4-year follow-up period, only 10.7% of participants with MHNW at baseline converted to MHOWO. Among MHOWO participants, 21.2% converted to MUHOWO. MHOWO also increased the risk of hyperuricemia (OR, 1.57; 95% CI 1.15-2.13; P = .004), both in obese and normal-weight individuals, even when metabolic status changed from unhealthy to healthy. Risk of hyperuricemia was high among those who remained metabolically unhealthy but of normal weight (OR, 3.09; 95% CI 1.51-6.30; P = .001). MHOWO also increases the risk of hyperuricemia, and MHOWO remains stable or changes to MUHOWO, which increases the risk of hyperuricemia. Therefore, close attention should be paid to the transition of metabolic health status over time, and individualized prevention strategies should be focused on metabolically unhealthy and obese individuals.

HOMA-IR as a predictor of Health Outcomes in Patients with Metabolic Risk Factors: A Systematic Review and Meta-analysis

INTRODUCTION

There exists clinical interest in the following question: Is there an association between HOMA-IR and the risk of developing metabolic diseases?

AIMS

Assessing the association between high values of HOMA-IR with the incidence of T2DM, MACE, essential hypertension, dyslipidemia, NASH, and cancer in healthy participants and participants with a component of metabolic syndrome.

METHODS

Databases were searched by an experienced librarian to find eligible studies. Observational cohort studies enrolling healthy adults and adults with metabolic syndrome components that evaluated HOMA as a marker of IR were considered for inclusion. Eligibility assessment, data extraction and risk of bias assessment were performed independently and in duplicate. Baseline characteristics of patients, cutoff values of HOMA-IR to predict metabolic events were extracted independently and in duplicate.

RESULTS

38 studies (215,878 participants) proved eligible. A higher HOMA-IR value had a significant effect on the risk of developing T2DM (HR 1.87; CI 1.40-2.49), presenting non-fatal MACE (HR 1.46; CI 1.08-1.97) and hypertension (HR 1.35; CI 1.15-1.59). No association was found regarding cancer mortality and fatal MACE with higher HOMA-IR values, there was not enough information to carry out a meta-analysis to establish an association between higher values of HOMA with cancer incidence, dyslipidemia, and NASH.

CONCLUSIONS

High values of HOMA were associated with an increased risk of diabetes, hypertension, and non-fatal MACE; yet, not for cardiovascular or cancer mortality. More research is needed to determine the value of the HOMA index in metabolic and cardiovascular outcomes.

PROSPERO REGISTRATION NUMBER

CRD42020187645.

The Association Between Metabolic Derangement and Wound Complications in Elective Plastic Surgery

INTRODUCTION

The incidence of metabolically unhealthy obesity is rising nationally. In this study, we compare wound and overall complications between metabolically unhealthy obese and healthy patients undergoing elective plastic surgery and model how operative time influences a complication risk.

METHODS

Patients undergoing elective breast and body plastic surgery procedures in the 2009-2019 National Surgical Quality Improvement Program (NSQIP) dataset were identified. Complications were compared between metabolically unhealthy obese (body mass index [BMI] > 30 with diabetes and/or hypertension) versus metabolically healthy obese patients (BMI > 30 without diabetes or hypertension). Logistic regression was used to model the probability of wound complications across operative times stratified by metabolic status.

RESULTS

Of 139,352 patients, 13.4% (n = 18,663) had metabolically unhealthy obesity and 23.8% (n = 33,135) had metabolically healthy obesity. Compared to metabolically healthy patients, metabolically unhealthy patients had higher incidence of wound complications (6.9% versus 5.6%; P < 0.001) and adverse events (12.4% versus 9.6%; P < 0.001), in addition to higher 30-d readmission, returns to the operating room, and length of stay (all P < 0.001). After adjustment, BMI (Odds ratio [OR] 7.86), hypertension (OR 1.15), and diabetes (OR 1.25) were independent risk factors for wound complications (all P < 0.001). Among metabolically unhealthy patients, the operative time was log-linear with a wound complication risk (OR 1.21; P < 0.001).

CONCLUSIONS

Diabetes and hypertension are additive risk factors with obesity for wound complications in elective plastic surgery. Among patients with metabolically unhealthy obesity, a risk of wound complications increases logarithmically with operative time. This distinction with regard to metabolic state might explain the unclear impact of obesity on surgical outcomes within existing surgical literature.

Transition from metabolically healthy to unhealthy overweight/obesity and risk of cardiovascular disease incidence: A systematic review and meta-analysis

AIMS

Discrepant results have been demonstrated regarding the cardiovascular (CV) risk of populations with metabolically healthy overweight/obesity (MHO) who were transitioned into metabolically unhealthy states. So, the objective of this systematic review and meta-analysis was to estimate the risk of cardiovascular diseases (CVD) incidence in individuals with transitional MHO phenotype.

DATA SYNTHESIS

A literature review was done in PubMed, Scopus, EMBASE, and google scholar databases. Pooled HRs for all fatal and nonfatal CV events were computed using random-effect models for transitional MHOs in general as well as for each sex subgroup separately. This systematic review and meta-analysis included a total of 7 prospective observational studies with a total of 7,720,165 participants, published between 2018 and 2020. The mean follow-up duration of participants was 11.7 (5.5) years. Overall, the transitional MHO individuals had a significant risk of CVD incidence [HR = 1.42, 95% CI (1.24-1.60)]. In addition, in both male and female subgroups, unstable MHO phenotype demonstrated a significant CVD risk and HRs for incident CVD in males and females were 1.51 (1.07-1.96) and 1.71 (1.08-2.34), respectively.

CONCLUSION

Transition from MHO to unhealthy state throughout follow-up elevated the risk of CVD in both male and female groups. This can explain the association between MHO and incidence of CV events especially with longer follow up period.

REGISTRATION CODE IN PROSPERO

CRD42021270225.

Pathogenesis, Murine Models, and Clinical Implications of Metabolically Healthy Obesity

Although obesity is commonly associated with numerous cardiometabolic pathologies, some people with obesity are resistant to detrimental effects of excess body fat, which constitutes a condition called “metabolically healthy obesity” (MHO). Metabolic features of MHO that distinguish it from metabolically unhealthy obesity (MUO) include differences in the fat distribution, adipokine types, and levels of chronic inflammation. Murine models are available that mimic the phenotype of human MHO, with increased adiposity but preserved insulin sensitivity. Clinically, there is no established definition of MHO yet. Despite the lack of a uniform definition, most studies describe MHO as a particular case of obesity with no or only one metabolic syndrome components and lower levels of insulin resistance or inflammatory markers. Another clinical viewpoint is the dynamic and changing nature of MHO, which substantially impacts the clinical outcome. In this review, we explore the pathophysiology and some murine models of MHO. The definition, variability, and clinical implications of the MHO phenotype are also discussed. Understanding the characteristics that differentiate people with MHO from those with MUO can lead to new insights into the mechanisms behind obesity-related metabolic derangements and diseases.

Acute Myocardial Infarction in Young Patients and its Correlation with Obesity Status at Pre-adolescent Stage: A Narrative Review

Background:

Cardiovascular diseases (CVD), especially acute myocardial infarction (AMI), remain a worldwide major cause of premature morbidity and mortality, with considerable health care costs. Metabolic, behavioural, environmental, and social risk factors are significant drivers of AMI, with obesity being a key determinant among them. Childhood obesity constitutes a major health threat that is considered a global epidemic of the 21st century.

Objective:

To assess whether excess weight from the first years of life acts as a predisposing factor in increasing the risk of AMI in young adults.

Methods:

This is a narrative review of the evidence concerning the epidemiology of early AMI and obesity, using PubMed and Google Scholar.

Results:

There is substantial evidence showing that excess weight during childhood multiplies the risk of AMI at an early age.

Conclusion:

Premature AMI seems to have significant drivers related to lifestyle factors, such as childhood obesity. In the era of a childhood obesity epidemic, the aforementioned relationship underlines the need for early prevention and management.

Metabolic obesity phenotypes: a friend or foe of digestive polyps?-An observational study based on National Inpatient Database

OBJECTIVE

Obesity is associated with an increased risk of digestive polyps, whereas all obesity are not created equally. The role of metabolic states in occurrence risks of polyps among individuals with varying degrees of obesity remains unknown. Our study aimed to evaluate the association between metabolic obesity phenotypes and the occurrence of digestive polyps.

RESEARCH DESIGN AND METHODS

Data from 9,278,949 patients between 2016 and 2018 from the National Inpatient Sample (NIS) database, a nationally representative database of all discharges from US health-care hospitals, were analyzed. According to obesity phenotype, the study population was classified into four groups: metabolically healthy nonobese (MHNO), metabolically unhealthy nonobese (MUNO), metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO). We calculated the incidence rates of various digestive polyps (stomach/duodenum, colon and rectum polyps) among these participants by searching the hospital records for ICD-10 diagnosis codes indicating each gastric, duodenum, colon or rectal polyps. The multiple stepwise regression analysis and further in-depth subgroup analysis were used to determine the associations between metabolic obesity phenotypes and the occurrence of digestive polyps.

RESULTS

In the total or female population, those with the MUNO and MUO phenotypes had significantly higher prevalence of digestive polyps compared with individuals with the MHNO or MHO phenotypes (all p < 0.05) and a significant difference was not found between MUNO and MUO phenotypes (p > 0.05). Obese subjects seem to be more likely to develop stomach and duodenum polyps or colon polyps than non-obese subjects in metabolically healthy people of males (MHO vs. MHNO, p < 0.05), whereas obesity status seems to have little effect on the occurrence of digestive polyps in metabolically healthy people of females (MHO vs. MHNO, p>0.05). After adjusting for the potential confounders, the MHO, MUNO and MUO phenotypes were all risk factors for stomach and duodenum polyps (OR = 1.46, 95% CI: 1.36-1.58, p< 0.01; OR = 1.19, 95% CI: 1.14-1.25, p< 0.01; OR = 1.44, 95% CI: 1.35-1.55, p< 0.01, respectively) or colon polyps (OR = 1.28, 95% CI: 1.21-1.35, p< 0.01; OR = 1.18, 95% CI: 1.14-1.22, p< 0.01; OR = 1.46, 95% CI: 1.38-1.54, p< 0.01, respectively) compared with the MHNO phenotype，especially in menopausal female. Interestingly, we also observed in further in-depth subgroup analysis that metabolic abnormalities may have a greater impact on the occurrence of digestive polyps than obesity (all p < 0.05).

CONCLUSIONS

Both metabolic abnormities and obesity were associated with a higher risk of digestive polyps. The effect of metabolism on digestive polyp occurrence may be stronger than that of obesity, highlighting the importance of abnormal metabolic status modification regardless of obesity status. Clinical intervention should not only focus on obesity, but also on metabolic abnormalities to decrease digestive polyp risk.

Transition of Metabolic Phenotypes and Risk of Atrial Fibrillation According to BMI: Kailuan Study

Objective

Atrial fibrillation (AF) is associated with both obesity and its metabolic consequences. However, there is a paucity of information on whether the dynamic change of metabolic health and obesity phenotypes affect the risk of AF. We aimed to prospectively examine the association between metabolic health and its change over time and AF risk across body mass index (BMI) categories.

Methods

A total of 58,483 participants without history of cancer, and cardiovascular diseases from the Kailuan study were included in the present study. Transition of metabolic phenotypes was evaluated between 1st survey (2006–2007) and the 2nd survey (2008–2009). The hazard ratios (HRs) and 95% confidence intervals (CIs) for AF were assessed by Cox proportional hazards regression.

Results

During a median follow-up of 3 years, we documented 580 cases of AF. Compared with metabolically healthy individuals with normal weight, the multivariable-adjusted hazard ratios for metabolically healthy and unhealthy overweight/obese were 1.27 (95% CI: 1.01, 1.59) and 1.37 (95% CI: 1.09, 1.72), respectively. However, when transition was taken into account, overweight/obese people who maintained metabolically healthy status were not associated with increased long-term risk (HR, 1.11;95% CI: 0.70, 1.78), whereas participants who converted from metabolically healthy overweight/obese status to an unhealthy phenotype had higher AF risk than those who maintained metabolically healthy normal weight (HR 1.59, 95% CI: 1.11, 2.26). When BMI and metabolically healthy status were updated over the course of the study, significant short-term elevations in AF risk were associated with individuals with stable MU-OW/OB status.

Conclusion

In this community-based cohort study, metabolically healthy overweight/obese individuals have increased risks of AF. Obesity remains a risk factor for AF independent of major metabolic factors. Our data further suggested that metabolic phenotype was a dynamic condition, and maintenance of metabolic health and normal weight might alleviate the risk of AF.

Prolonged or Transition to Metabolically Unhealthy Status, Regardless of Obesity Status, Is Associated with Higher Risk of Cardiovascular Disease Incidence and Mortality in Koreans

The risk of chronic disease and mortality may differ by metabolic health and obesity status and its transition. We investigated the risk of cardiovascular disease (CVD) and cancer incidence and mortality according to metabolic health and obesity status and their transition using the nationally representative Korea National Health and Nutrition Examination Survey (KNHANES) and the Ansan-Ansung (ASAS) cohort of the Korean Genome and Epidemiology Study. Participants that agreed to mortality linkage (n = 28,468 in KNHANES and n = 7530 adults in ASAS) were analyzed (mean follow-up: 8.2 and 17.4 years, respectively). Adults with no metabolic risk factors and BMI <25 or ≥25 kg/m2 were categorized as metabolically healthy non-obese (MHN) or metabolically healthy obese (MHO), respectively. Metabolically unhealthy non-obese (MUN) and metabolically unhealthy obese (MUO) adults had ≥1 metabolic risk factor and a BMI < or ≥25 kg/m2, respectively. In KNHANES participants, MUN, and MUO had higher risks for cardiovascular mortality, but not cancer mortality, compared with MHN adults. MHO had 47% and 35% lower risks of cancer mortality and all-cause mortality, respectively, compared to MHN. Similar results were observed in the ASAS participants. Compared to those persistently MHN, the risk of CVD was greater when continuously MUN or MUO. Transitioning from a metabolically healthy state to MUO also increased the risk of CVD. Few associations were found for cancer incidence. Using a nationally representative cohort and an 18-year follow-up cohort, we observed that the risk of CVD incidence and mortality and all-cause mortality, but not cancer incidence or mortality, increases with a continuous or a transition to an unhealthy metabolic status in Koreans.

The presence of NAFLD influences the transition of metabolically healthy to metabolically unhealthy obesity and the ten-year cardiovascular disease risk: A population-based cohort study

BACKGROUND/OBJECTIVES

We evaluated the role of the presence of non-alcoholic fatty liver disease (NAFLD) at baseline in the transition from metabolically healthy to metabolically unhealthy obesity (MHO to MUO) ten years later.

METHODS

A prospective cohort study (ATTICA study, Greece) was performed between 2002 and 2012 studying a sample from the greater metropolitan Athens area. In total, 1514 (49·8%) men and 1528 (50.2%) women (aged >18 years old) free-of-CVD were included. Healthy metabolic status was defined as absence of all NCEP ATP III (2005) metabolic syndrome components. NAFLD was defined according to validated liver steatosis indices. Follow-up CVD assessment (2011-2012) was achieved in n = 2020 participants (n = 317 cases).

RESULTS

NAFLD prevalence among MHO participants ranged from 29% to 39% according to the specific NAFLD score used. MHO participants who developed metabolically unhealthy status had about two times higher odds to have NAFLD at baseline compared with their metabolically healthy normal weight counterparts whereas stable MHO was not associated significantly with NAFLD. Moreover, MHO status accompanied by NAFLD was associated with increased CVD risk (Hazard Ratio = 2.90 95% Confidence Interval (1.35, 5.40)) in comparison to their non-NAFLD MHO counterparts. Further analysis revealed that in the obese, NAFLD indices and not simply visceral adiposity increased significantly the ability of metabolic status (using standard definition) to predict long-term CVD incidence.

CONCLUSIONS

Considering NAFLD, even when assessed using validated indices only, in the clinical assessment of apparently healthy obese individuals predicts who is to develop MUO and contributes independently and more accurately to defining future cardiometabolic risk.

Metabolically healthy obesity: Is it really healthy for type 2 diabetes mellitus?

Metabolically healthy obese (MHO) individuals are reported to have a lower risk of developing cardiovascular diseases in comparison with individuals with metabolic syndrome. However, the association between MHO and type 2 diabetes (T2DM) is still controversial. Some studies indicated that MHO is a favorable phenotype for T2DM, but more studies showed that MHO individuals have an increased risk of developing T2DM compared with metabolically healthy normal-weight individuals, especially among those who would acquire metabolically unhealthy obesity. This has been supported by finding insulin resistance and low-grade inflammatory responses in MHO individuals with a tendency for impaired beta-cell dysfunction. Studies also showed that liver fat accumulation increased the risk of incidence of T2DM in MHO. Here, we reviewed current literature on the relationship between MHO and T2DM, discussed the determinants for the development of diabetes in MHO, and summarized the measures for the prevention of T2DM in MHO.

Insulin resistance persists despite a metabolically healthy obesity phenotype

OBJECTIVE

Metabolically healthy obesity (MHO) is often defined as the absence of metabolic syndrome in the presence of obesity. However, phenotypic features of MHO are unclear. Insulin sensitivity in MHO was cross-sectionally compared with metabolically unhealthy obesity (MUO) and a reference group of young healthy participants without obesity.

METHODS

Sedentary adults (n = 96) undergoing anthropometric, blood chemistries, maximal aerobic capacity, and euglycemic-hyperinsulinemic clamp measurements were classified by BMI (<25 and ≥30 kg/m2 ). MUO was defined as having obesity with metabolic syndrome (≥2 additional risk factors). Data were analyzed using a linear mixed models approach.

RESULTS

Body weight was similar between MHO and MUO. Body fat (percentage) and high-density lipoprotein cholesterol were higher (p < 0.001), and systolic blood pressure, triglycerides, glucose, and insulin were lower in MHO versus MUO (p < 0.03, all). The MHO group also had lower high-density lipoprotein cholesterol and higher low-density lipoprotein cholesterol, diastolic blood pressure, and insulin compared with the reference. Both the MHO and MUO groups displayed impaired insulin sensitivity compared with the reference control (p < 0.001).

CONCLUSIONS

Participants with MHO had distinct clinical measures related to hypertension, lipid metabolism, and glycemic control compared with a healthy reference group. Peripheral insulin resistance in obesity independent of metabolic status portends increased risk for type 2 diabetes in the MHO patient population.

Wrist circumference as a novel predictor of transition from metabolically healthy to unhealthy phenotype in overweight/obese adults: a gender-stratified 15.5-year follow-up

BACKGROUND

Individuals with transition from metabolically healthy overweight/obese (MHO) to metabolically unhealthy overweight/obese (MUO) phenotype are significantly predisposed to greater risks of cardiovascular events compared to those with a persistent MHO phenotype. The aim of this study was to evaluate the predictive performance of wrist circumference for this transition in adults over a 15.5-year follow-up.

METHODS

We included 309 males and 821 females with the age of ≥18 years old, body mass index ≥25 kg/m², and metabolically healthy status according to the criteria of the Joint Interim Statement. The incidence of MUO phenotype was evaluated for each gender, across tertiles wrist circumference, using Cox-proportional hazard models.

RESULTS

The overall rate of transition from MHO to MUO phenotype was 87.1% in males and 77.5% in females. The hazard ratios (HRs) with 95% CI across second and third tertiles of wrist circumference were 0.89 (0.64-1.24) and 1.31 (0.99-1.73) in men (P for trend =0.027); and 1.34 (1.09-1.66) and 1.61 (1.30-2.00) in women (P for trend <0.001), respectively. After multivariable adjustment, HRs across second and third tertiles of wrist circumference were 0.92 (0.64-1.32) and 1.18 (0.83-1.67) in males (p for trend =0.352), and 1.32 (1.05-1.65) and 1.34 (1.06-1.96) in females (p for trend =0.025), respectively.

CONCLUSIONS

Wrist circumference significantly predicts the transition from MHO to MUO phenotype in adults of both genders. However, it is an independent predictor of the transition only in females. Future studies are warranted to clarify the role of wrist circumference mechanisms on metabolic risk deterioration.

Evolution of Metabolic Phenotypes of Obesity in Coronary Patients after 5 Years of Dietary Intervention: From the CORDIOPREV Study

Background: Obesity phenotypes with different metabolic status have been described previously. We analyzed metabolic phenotypes in obese coronary patients during a 5-year follow-up, and examined the factors influencing this evolution. Methods: The CORDIOPREV study is a randomized, long-term secondary prevention study with two healthy diets: Mediterranean and low-fat. All obese patients were classified as either metabolically healthy obese (MHO) or metabolically unhealthy obese (MUO). We evaluated the changes in the metabolic phenotypes and related variables after 5 years of dietary intervention. Results: Initially, 562 out of the 1002 CORDIOPREV patients were obese. After 5 years, 476 obese patients maintained their clinical and dietary visits; 71.8% of MHO patients changed to unhealthy phenotypes (MHO-Progressors), whereas the MHO patients who maintained healthy phenotypes (MHO-Non-Progressors) lost more in terms of their body mass index (BMI) and had a lower fatty liver index (FLI-score) (p < 0.05). Most of the MUO (92%) patients maintained unhealthy phenotypes (MUO-Non-Responders), but 8% became metabolically healthy (MUO-Responders) after a significant decrease in their BMI and FLI-score, with improvement in all metabolic criteria. No differences were found among dietary groups. Conclusions: A greater loss of weight and liver fat is associated with a lower progression of the MHO phenotype to unhealthy phenotypes. Likewise, a marked improvement in these parameters is associated with regression from MUO to healthy phenotypes.

Influence of dietary patterns on the metabolically healthy obesity phenotype: A systematic review

AIMS

In many individuals (35%) obesity is not accompanied by cardiometabolic disorders, a condition referred to as metabolically healthy obesity. Since the effectiveness of dietary interventions for this condition is not well established, this study reviews the influence of dietary patterns on the phenotype of metabolically healthy obesity in adults and elderly.

DATA SYNTHESIS

The review was carried out following the PRISMA guidelines and registered in the PROSPERO. The search was conducted in the MEDLINE, SCOPUS, Web of Science, Science Direct, LILACS, and SciELO databases. A total of 236 articles were identified, seven of which were selected for synthesis after application of the eligibility criteria.

CONCLUSIONS

The overall result found out in this synthesis was that the greater adherence to healthy eating patterns was considered a preventive to the transition from metabolically healthy obesity to metabolic unhealthy obese phenotypes, by improving metabolic health, and reducing the risk of cardiovascular disease and mortality from all causes. In contrast, unhealthy eating patterns resulted in increased inflammation and risks of developing noncommunicable diseases. This review indicates that adherence to healthy eating patterns may interfere with metabolic phenotypes of obesity and positively affect metabolically healthy obesity.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number CRD42020159783.

Obesity, metabolic syndrome, and inflammation: an update for anaesthetists caring for patients with obesity

Our understanding of chronic inflammation in obesity is evolving. Suggested mechanisms include hypoxia of adipose tissue and a subsequent increase in circulating cytokines. It is now known that adipose tissue, far from being an inert tissue, produces and secretes multiple peptides that influence inflammation and metabolism, including substrates of the renin-angiotensin-aldosterone system (RAAS). RAAS blocking antihypertensive medication and cholesterol-lowering agents are now being evaluated for their metabolic and inflammation-modulating effects. Surgery also has pro-inflammatory effects, which may be exacerbated in patients with obesity. This narrative review will summarise the recent literature surrounding obesity, metabolic syndrome, inflammation, and interplay with the RAAS, with evidence-based recommendations for the optimisation of patients with obesity, prior to surgery and anaesthesia.

Selected 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitors. A look into their use and potential in pre-diabetes and type 2 diabetes

Objectives. This review assesses the comparative safety and efficacy of selected 3-hydroxy-3-methylglutaric acid coenzyme A inhibitors (statins, cinnamic acids. 3-hydroxy-3-methyl glutaric acid) on the pre-onset type 2 diabetes (PT2D) and post-onset type 2 diabetes (T2D)-related cluster of seven features (central obesity, hyperglycemia, hypertension, dyslipidemia, pro-thrombosis, oxidation and inflammation). Methods. Google scholar and PubMed were searched for statin*, flaxseed lignan complex (FLC), cinnamic acid (CA)*, and 3-hydroxy-3-methylglutaric acid (HMGA) in conjunction with each of PT2D, T2D and the cluster of seven. An introduction was followed by findings or absence thereof on the impacts of each of statins, FLC, CAs and HMGA on each member of the cluster of seven. Results. Pravastatin manages three features in PT2D, while a number of the statins improve five in T2D. FLC is negative in PT2D but controls four in T2D; it is not clear if the CAs and HMGA in FLC play a role in this success. CAs have potential in six and HMGA has potential in three of the cluster of seven though yet CAs and HMGA are untested in PT2D and T2D in humans. There are safety concerns with some statins and HMGA but FLC and CAs appear safe in the doses and durations tested. Conclusions. Selected statins, FLC, CAs and HMGA can manage or have a potential to manage at least three features of the cluster of seven. Most of the literature-stated concerns are with select statins but there are concerns (one actual and two potential) with HMGA.

Transitions in Metabolic Health and Associations With Arterial Stiffness Progression Across Body Mass Index Categories

[Figure: see text].

Metabolic Constellations, Clusters, and Renal Function: Findings from the 2013-2018 National Health and Nutrition Examination Surveys

Metabolic syndrome (MetS) is associated with decreased renal function and chronic kidney disease (CKD). To date, no research regarding the sixteen possible constellations resulting in the diagnosis of MetS has been elucidated. The purpose of this study is to report renal function in sixteen metabolic constellations grouped into four metabolic clusters. Individuals (n = 2767; representing 86,652,073 individuals) from the 2013-2018 National Health and Nutrition Examination Surveys who met the criteria for MetS were included. Sixteen possible constellations of three or more risk factors were analyzed for renal function. Four metabolic clusters representing MetS with hyperglycemia (Cluster I), MetS with hypertension (Cluster II), MetS with hyperglycemia and hypertension (Cluster III), or MetS with normoglycemia and normotension (Cluster IV) were assessed for renal function and CKD status. Cluster III had the highest odds of CKD (OR = 2.57, 95% CL = 1.79, 3.68). Clusters II and III had the lowest renal function and were not different from one another (87.82 and 87.28 mL/min/1.73 m2, p = 0.71). The constellation with the lowest renal function consisted of hypertension, high triglycerides, and a large waist circumference (82.86 mL/min/1.73 m2), whereas the constellation with the highest renal function consisted of hyperglycemia, low HDL, and a large waist circumference (107.46 mL/min/1.73 m2). The sixteen constellations of MetS do not have the same effects on renal function. More research is needed to understand the relationship between the various iterations of MetS and renal function.

Metabolic Health, Obesity, and Renal Function: 2013-2018 National Health and Nutrition Examination Surveys

Rising rates of metabolic syndrome, obesity, and mortality from chronic kidney disease (CKD) have prompted further investigation into the association between metabolic phenotypes and CKD. Purpose: To report the frequency of strictly defined metabolic phenotypes, renal function within each phenotype, and individual risk factors associated with reduced renal function. We utilized the 2013-2018 National Health and Nutrition Examination Surveys (NHANES) and complex survey sample weighting techniques to represent 220 million non-institutionalized U.S. civilians. Metabolic health was defined as having zero of the risk factors defined by the National Cholesterol Education Program with the exception of obesity, which was defined as BMI ≥ 30 kg/m2 in non-Asians and BMI ≥ 25 kg/m2 in Asians. The metabolically healthy normal (MUN) phenotype comprised the highest proportion of the population (38.40%), whereas the metabolically healthy obese (MHO) was the smallest (5.59%). Compared to the MHN reference group, renal function was lowest in the strictly defined MUN (B = -9.60, p < 0.001) and highest in the MHO (B = 2.50, p > 0.05), and this persisted when an increased number of risk factors were used to define metabolic syndrome. Systolic blood pressure had the strongest correlation with overall eGFR (r = -0.25, p < 0.001), and individuals with low HDL had higher renal function compared to the overall sample. The MUN phenotype had the greatest association with poor renal function. While the MHO had higher renal function, this may be due to a transient state caused by renal hyperfiltration. Further research should be done to investigate the association between dyslipidemia and CKD.

Transitions in metabolic health status over time and risk of heart failure: a prospective study

AIMS

- Evidence for the effects of metabolically healthy obese (MHO) status on heart failure (HF) is limited and ignores the dynamic change of metabolic health and obesity phenotypes. We aimed to investigate the associations of metabolic health and its transition with HF across body mass index (BMI) and waist circumference (WC) categories.

METHODS

- This prospective cohort study was conducted with 93,288 Chinese adults who were free of cardiovascular disease, cancer or HF at baseline (2006-2007). Metabolic health was defined as having no or only one abnormality in blood pressure, glucose, high-density lipoprotein cholesterol, or triglyceride levels. Participants were cross-classified at baseline by metabolic health and obesity (defined by BMI and WC criteria). Transitions in metabolic health status from 2006-2007 to 2010-2011 were considered. The hazard ratios (HRs) and 95% confidence intervals (CIs) for HF were assessed by Cox proportional hazards regression.

RESULTS

- During a mean ± standard deviation follow-up of 9.7 ± 1.5 years, 1,628 participants developed HF. Individuals with MHO (HR: 1.78, 95% CI: 1.45, 2.19 for BMI criteria; HR: 1.51, 95% CI: 1.30, 1.76 for WC criteria) had higher risk of HF than those with metabolically healthy normal weight (MH-NW). Individuals with initial MHO who shifted to metabolically unhealthy phenotype during follow-up had higher risk of HF compared with stable MH-NW individuals (HR 3.12; 95% CI: 2.01, 4.85 for BMI categories; HR 1.98; 95% CI: 1.42, 2.77 for WC categories). Even stable MHO individuals were at an increased risk of HF compared with stable MH-NW individuals (HR: 2.17; 95% CI: 1.39, 3.39 for BMI categories; HR: 1.33; 95% CI: 0.96, 1.85 for WC categories).

CONCLUSIONS

- MHO phenotype is dynamic and its transition to metabolically unhealthy phenotype or even stable MHO is associated with increased risk of HF. Maintaining metabolic health may provide a clue for preventing HF.

Risk of arterial stiffness according to metabolically healthy obese phenotype: a combined cross-sectional and longitudinal study in kailuan cohort

We aim to investigate the risk of incident arterial stiffness according to metabolically healthy obese (MHO) phenotype in Chinese population. 37,180 participants with at least one-time measurement of branchial-ankle pulse wave velocity (baPWV) were included in the cross-sectional analysis, and 16,236 participants with repeated measurement of baPWV during the follow-ups were included in the longitudinal study. Cross-classification of body mass index (BMI) categories and metabolic health status created six groups. Linear and logistic regression analyses were used. The results of cross-sectional and longitudinal investigation were essentially the same, as the abnormality of baPWV increased with BMI categories in metabolically healthy participants, while the increasing tendency disappeared in metabolically unhealthy participants. A 1.4-fold, 2.2-fold increased risk for the new occurrence of arterial stiffness were documented in MHO and metabolically unhealthy obese participants compared to metabolically healthy normal-weight controls in the fully adjusted model. Further stratified analysis showed that metabolic health status was an interaction factor between BMI and arterial stiffness in all study populations (P=0.0001 for cross-sectional study and P=0.0238 for longitudinal study). In conclusion, metabolic health status and BMI categories contribute to the progression of arterial stiffness, while BMI is positively associated with arterial stiffness only in metabolically healthy participants.

Association between Dietary Patterns and Serum Hepatic Enzyme Levels in Adults with Dyslipidemia and Impaired Fasting Plasma Glucose

We investigated the association between dietary patterns and serum hepatic enzyme levels in adults with dyslipidemia and impaired fasting glucose in Taiwan. A total of 15,005 subjects (5452 men and 9553 women) aged 35–69 years were selected. Two major dietary patterns were identified by principal component analysis: Western dietary pattern and Mediterranean dietary pattern. Subjects in the highest quartile (Q4) of the Western dietary pattern showed an increased risk of elevated serum alanine aminotransferase (ALT) levels (OR: 1.24, 95% CI: 1.06–1.45, p-trend = 0.01). Fur-thermore, in the highest quartile of the Western dietary pattern, subjects with high waist circum-ference were observed to have a greater risk for developing abnormal serum ALT levels compared to those in the lowest quartile (Q1) (OR: 1.43, 95% CI: 1.04–1.97, p-trend = 0.01). In the highest quartile of the Western dietary pattern, only women were at an increased risk for having abnormal serum ALT levels (OR: 1.28, 95% CI: 1.04–1.59, p-trend = 0.03). By contrast, in the highest quartile of the Mediterranean dietary pattern, only men were at a reduced risk for having abnormal serum gamma-glutamyl transferase (GGT) levels (OR: 0.72, 95% CI: 0.53–0.97, p-trend = 0.048). We report a positive association between the Western dietary pattern and abnormal serum ALT levels.

Differences in body composition between metabolically healthy and unhealthy midlife women with respect to obesity status

Body composition (BC) characteristics across metabolic health-by-body mass index categories were examined. Metabolic health (MH) was defined by five biomarkers: waist circumference, blood pressure, levels of triglycerides, high density lipoprotein cholesterol, and fasting glucose. Potential differences in BC characteristics between metabolically healthy obese (MH-O) and metabolically unhealthy obese (MUH-O) women, and between MH normal weight (MH-NW) and MUH normal weight (MUH-NW) women were explored in 276 Slovak midlife women (39-65 years). Body composition parameters were measured with bioimpedance analyzer (BIA 101, Akern, S. r. l.). A simple comparison of the BC data between the subgroups showed significant differences in resistance (Rz, ohm) (p=0.035), muscle mass (MM, kg) (p=0.044), and total body water (TBW, kg) (p=0.047) between MH-O and MUH-O women. However, we did not observe any significant differences in BC characteristics between MH-NW and MUHNW. Specific logistic regression models were used to determine differences in BC characteristics between various obesity phenotypes, with controlling for age, menopausal status, smoking status and sport activity. Our results indicated that increasing age and decreasing Rz were statistically significantly associated with an increased likelihood of exhibiting MUH-O (p=0.031 for age; p=0.032 for Rz). Moreover, other logistic models which included age, menopausal status, biochemical variables and life style factors such as covariates, showed that increasing alanine aminotransferase (ALT) and uric acid (UA) were statistically significantly associated with an increased likelihood of exhibiting MUH-O (p=0.023 for ALT, p=0.010 for UA). In conclusion, MUH-O and MH-O cardiometabolic profiles are characterized by differences in the value of resistance and plasma levels of ALT and UA.

Leukocyte related parameters in older adults with metabolically healthy and unhealthy overweight or obesity

It remains unclear whether leukocyte-related parameters could be used as biomarkers to differentiate metabolically unhealthy overweight/obesity (MUO) from metabolically healthy overweight/obesity (MHO). We aimed to examine the differences in the distribution of leukocyte-related parameters between older adults with MHO and MUO and the correlations of leukocyte-related parameters with individual components of metabolic abnormality. In the Weitang Geriatric Diseases Study on older Chinese adults aged 60 years or above, 404 individuals with MHO and 480 with MUO contributed to the analysis. Overweight/obesity was defined as body mass index (BMI) of 25 kg/m² or more. MHO and MUO were discriminated based on the Adult Treatment Panel III (ATP III) criteria. Leukocyte-related parameters were assessed using an automated hematology analyzer. All leukocyte-related parameters except monocytes were elevated in MUO group compared with MHO group (all P < 0.05). The prevalence of MUO increased by 24% with each 10⁹/L increase of leukocytes after adjusting for confounders in the multiple-adjusted model (P < 0.01) and each unit elevation of other parameters except lymphocytes and monocytes were significantly associated with the presence of MUO (all P < 0.01). Trend tests revealed a linear trend for the association between MUO and all the leukocyte-related parameters (all P for trend < 0.05). Significant interactions between leukocyte-related parameters and sex on the presence of MUO were observed (all P value for interaction < 0.05). Higher leukocyte-related parameters were found in patients with MUO than those with MHO and were associated with higher prevalence of MUO which seems to be sex-dependent. Further studies are needed to see whether these parameters could be used as biomarkers for the screening or diagnosis for MUO in clinical or public health practice.