Association of serum calcium and metabolically healthy obese in US adults: a cross-sectional study.

OBJECTIVES: The relationship between serum calcium and occurrence of MHO (metabolically healthy obesity) and MUNO (metabolically unhealthy non-obesity) remains unclear, and distinguishing these two phenotypes is difficult within primary healthcare units. This study explores that relationship. METHODS: This survey included 28590 adults from the National Health and Nutrition Examination Survey (NHANES) 2001-2018. Obesity phenotypes were categorized based on BMI and presence or absence of metabolic syndrome components. Weighted multivariate logistic regression analyses were used to assess the association between serum calcium levels and the obesity phenotype. Restricted cubic spline analysis characterized dose-response relationships, and stratified analyses explored these relationships across sociodemographic and lifestyle factors. RESULTS: The overall prevalence of MHO and MUNO were 2.6% and 46.6%, respectively. After adjusting for covariates, serum calcium exhibited a negative association with MHO [OR (95%): 0.49 (0.36,0.67), p < 0.001], while exhibiting a positive association with MUNO [OR (95%): 1.48 (1.26,1.84), p < 0.001]. Additionally, we found a non-linear association between serum calcium levels and the incidences of MHO and MUNO. Stratified analyses demonstrated a strong negative correlation between serum calcium levels and MHO occurrence across various subgroups. There was no significant interaction between calcium and stratified variables except sex; the association between calcium and the occurrence of MHO was remarkable in female patients. Meanwhile, the predictive ability of serum calcium level for the occurrence of MUNO among all patients was consistent across various subgroups. There was a significant interaction between calcium level and stratified variables based on age, sex, race, and smoking status; the association was remarkable in older (≥ 40 years old), white, none or less smoking, and female patients. CONCLUSIONS: A significant correlation was identified between serum calcium levels and MHO or MUNO. The findings suggest that serum calcium levels may serve as an indicator for more accurate assessment and diagnosis of MUNO and MHO, especially among individuals with abdominal obesity.

Serum calcium levels exhibited an inverse relationship with metabolically healthy obesity (MHO) and a positive relationship with metabolically unhealthy non-obese (MUNO).A nonlinear association exists between serum calcium levels and the incidence of both MHO and MUNO.Serum calcium has the potential to enhance evaluation and screening for MUNO or MHO in the general US adult population.

Dietary inflammatory index and its relationship with obesity phenotypes: a cross- sectional analysis from RaNCD cohort study.

PURPOSE: The potential dietary inflammatory index (DII) and the phenomenon of obesity have been linked in recent studies, but it is unclear whether this connection is dependent on metabolic status. Therefore, it was thought that this research would be useful in establishing the relationship between obesity phenotypes and DII. METHODS: The 5956 people who took part in the Ravansar non-communicable diseases (RaNCD) cohort research (MHNO) were put into four groups: metabolically unhealthy obesity (MUO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO), and metabolically healthy non-obesity. According to the International Diabetes Federation's criteria, MUO exhibits at least two metabolic disorders and have a body mass index of 30 kg/m2 or higher. DII was extracted from the participant's dietary consumption data. RESULTS: When possible confounders like age, gender, smoking, drinking alcohol, and exercise were taken into account, more adherence to DII was linked to a higher odds of MHO compared to MHNO (OR: 1.44; CI 95% 1.18, 1.75). Additionally, we discovered that greater adherence to DII was significantly related to higher odds for MUO compared to MHNO (OR: 1.67; CI 95% 1.3, 2.15). However, we found no association between adherence to DII and MUNO. CONCLUSIONS: Our findings indicated that greater adherence to DII was significantly associated with higher odds of MUO. However, it substantially increased the chances of both phenotypes of obesity. Level of evidence Level V-Cross-sectional observational study.

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

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

Association between transitions in metabolic health and colorectal cancer across categories of body size phenotype: a prospective cohort study.

OBJECTIVE: We aimed to investigate the associations of changes in metabolic health across categories of body size phenotype with the risk of colorectal cancer in a community-based prospective cohort. METHODS: In the current study, a total of 70,987 participants were included. Changes in metabolic health across categories of body size phenotype were assessed between the health examination for the first time in the years 2006 through 2009 and a 2010/2011 health examination. A multivariate Cox proportional hazards model was used to assess the associations of changes in metabolic health across body size phenotype categories with risk of colorectal cancer. RESULTS: During the median follow-up time of 11.04 years, 428 (0.60%) participants developed colorectal cancer. Compared with metabolically healthy normal-weight (MHNW) participants who remained MH, the risk of colorectal cancer was increased by 144% (95% CI: 1.21-4.95) for participants with metabolically healthy obesity (MHO) who converted to a metabolically unhealthy (MU) phenotype. Participants who were MU at baseline were still at increased risk of colorectal cancer, regardless of obesity status. CONCLUSIONS: The MHO phenotype was a dynamic status over time, and converting to MU during follow-up and being initially MU were associated with having an increased risk of colorectal cancer, regardless of degree of obesity and body size phenotype.

Metabolically healthy obesity and left ventricular geometric remodelling in Chinese children.

AIM: To investigate the association between metabolically healthy obesity (MHO) and left ventricular geometric remodelling in Chinese children. MATERIALS AND METHODS: This cross-sectional study used data from two population-based samples in China, including 2871 children aged 6-11 years. Weight status was defined based on body mass index according to the World Health Organization growth chart. Metabolic status was defined based on the 2018 consensus-based criteria proposed by Damanhoury et al. Obes Rev 2018;19:1476-1491 (blood pressure, lipids and glucose). Left ventricular geometric remodelling was determined as concentric remodelling, eccentric hypertrophy, and concentric hypertrophy. Multinomial logistic regression analysis was used to determine odds ratios (ORs) and 95% confidence intervals (CIs) for the association between categories of weight and metabolic status and left ventricular geometric remodelling. RESULTS: Compared with children with metabolically healthy normal weight, those with MHO had higher odds of left ventricular geometric remodelling, with adjusted ORs (95% CIs) of 2.01 (1.23-3.28) for concentric remodelling, 6.36 (4.03-10.04) for eccentric hypertrophy, and 17.07 (7.97-36.58) for concentric hypertrophy. Corresponding ORs (95% CIs) were 2.35 (1.47-3.75), 10.85 (7.11-16.55), and 18.56 (8.63-39.94), respectively, for children with metabolically unhealthy obesity. In contrast, metabolically unhealthy normal weight was not associated with higher odds of left ventricular geometric remodelling. Findings were consistent in sensitivity analyses that used different definitions of weight and metabolic status and left ventricular geometric remodelling. CONCLUSIONS: Children with MHO had higher odds of left ventricular geometric remodelling than their metabolically healthy normal weight counterparts. Our findings suggest MHO may not be a benign condition for cardiac health in children.

Association between metabolic phenotypes of overweight/obesity and cardiovascular diseases in postmenopausal women.

BACKGROUND AND AIM: Obesity and metabolic abnormalities were associated with an increased risk of cardiovascular disease. However, it is unclear how metabolic weight phenotypes relate to cardiovascular diseases in postmenopausal women. This study aimed to explore the relationships in postmenopausal women. METHODS AND RESULTS: We included 15,575 postmenopausal women aged 35-75 years (median age, 60.6) without cardiovascular disease at baseline from a subcohort of the China Patient-centered Evaluative Assessment of Cardiac Events Million Persons Project. Metabolically unhealthy phenotype was defined as having ≥2 risk factors of metabolic syndrome: blood pressure ≥130/85 mm Hg or current use of antihypertensive drugs, fasting glucose ≥5.6 mmol/L or current use of antidiabetic agents, triglycerides ≥1.7 mmol/L, and high-density lipoprotein cholesterol <1.3 mmol/L. Cox regression analysis was used to evaluate the risks of cardiovascular diseases. Over a median follow-up period of 3.55 (interquartile range, 2.59-4.44) years, a total of 1354 cardiovascular events occurred. Compared to metabolically healthy normal weight, the multivariate-adjusted hazard ratios and their 95% confidence intervals were 1.41 (1.16-1.72) for metabolically unhealthy normal weight, 1.42 (1.16-1.73) for metabolically healthy overweight/obesity, and 1.75 (1.48-2.08) for metabolically unhealthy overweight/obesity. Subdividing overweight/obesity into separate groups revealed higher total cardiovascular disease risk only in metabolically unhealthy individuals across body mass index categories. CONCLUSION: In postmenopausal women, both metabolically healthy overweight/obesity and metabolically unhealthy normal weight were associated with a higher risk of cardiovascular disease compared to metabolically healthy normal weight, and the greatest risk was observed in the metabolically unhealthy overweight/obesity category.

Trends and characteristics of the metabolically healthy obese phenotype in an Arab population.

The metabolically healthy obesity (MHO) phenotype represents a complex and distinctive trait, the trends and characteristics of which remain unknown in the Saudi Arabian adult population. The present study aims to fill that gap. A combined total of 10,220 Saudi adults from 2 independent cohorts [2008-2019, N = 7,896 (2,903 males and 4,993 females), and 2021-2023, N = 2,324 (830 males and 1,494 females)] aged 19-70 years old was screened, of whom 9,631 (3,428 males and 6,203 females) were included. Anthropometric data were measured, and fasting blood samples were collected to assess glucose, lipids, adipocytokines and inflammatory markers using routine methods and commercially available assays. Obesity was defined as a body mass index (BMI) ≥30 kg/m2. Screening for MHO was done using the empiric definition proposed by Zembic and colleagues and the by the National Cholesterol Education Program's Adult Treatment Panel III (NCEP ATPIII). Of the 3,949 (41.0%) participants with obesity, 33.4% (95% confidence interval, CI, 32-35) were considered MHO using the empiric definition, and 32.8% (95% CI, 31-34) using NCEP-ATPIII. The overall age and gender adjusted prevalence of MHO in the Saudi adult population was 31.6% (95% CI, 30-33) and 30.1% (29-31) by the two definitions, respectively. Females had a higher age-adjusted prevalence of MHO than males (OR = 1.22, 95% CI 1.1-1.4, p = 0.009) as per the ATPIII criteria. MHO prevalence substantially increased over time from 2008 to 2023 (p < 0.001) for both definitions. Circulating leptin levels and insulin resistance were significantly higher in the MUO group than the MHO group independent of the definition used, suggesting the presence of a more severe form of leptin resistance in the MUO group which may explain the worse cardiometabolic profile as compared to the MHO group. In summary, the study highlights the first time the characteristics and trends of the MHO phenotype among Saudi Arabian adults. The pluripotent effects of leptin and its resistance may be central to MHO's progression, or lack thereof, to the MUO phenotype, and this needs further investigation.

Metabolically healthy obesity in adults with X-linked hypophosphatemia.

OBJECTIVES: X-linked hypophosphatemia (XLH) is characterized by increased concentrations of circulating fibroblast growth factor 23 (FGF-23) resulting in phosphate wasting, hypophosphatemia, atypical growth plate and bone matrix mineralization. Epidemiologic studies suggest a relationship between FGF-23, obesity, and metabolic dysfunction. The prevalence of overweight and obesity is high in children with XLH. We aimed to evaluate the prevalence of obesity and metabolic complications in adults with XLH. METHODS: We conducted a prospective cohort study in adult XLH patients from a single tertiary referral center. The proportion of patients with a BMI >25 kg/m2 was the main outcome measure. Body fat mass percentage (FM%) and adipose tissue surfaces were secondary outcome measures. Glucose homeostasis (plasma glucose and insulin concentrations after fasting and 2 hours after an oral glucose tolerance test) was explored in a subgroup of patients and compared with age-, sex-, and BMI-matched healthy controls. RESULTS: Among 113 evaluated patients, 85 (75%) were female and 110 (97%) carried a PHEX mutation. Sixty-three (56%) patients were overweight or obese, with a median BMI of 25.3 [IQR, 22.7; 29.2] kg/m2. BMI was correlated with FM%, abdominal and thigh subcutaneous and intra-abdominal adipose tissue surfaces. The prevalence of impaired fasting glucose, impaired glucose tolerance, and diabetes was not different between XLH patients and matched controls. CONCLUSION: The prevalence of overweight and obesity is high among XLH patients and is associated with excess fat mass. However, the prevalence of glucose homeostasis abnormalities is not increased in patients compared to healthy controls, suggesting that metabolically healthy overweight or obesity predominates.

Acute ischemic stroke in young adults: comparative analysis of outcomes and mortality in metabolically healthy obese or overweight vs. non-obese or overweight hospitalizations, 2016-2019 cohort.

INTRODUCTION: Rising obesity rates and the increasing prevalence of stroke in the metabolically healthy obese and overweight (MHOO) necessitate examining its association in younger (18-44 year) populations and analyzing acute ischemic stroke (AIS) trends and outcomes in MHOO vs. metabolically healthy non-obese or overweight (MHnOO). METHODS: Data from the United States National Inpatient Sample (2016-2019) was analyzed to identify young MHOO and MHnOO AIS patients using ICD-10-CM codes. Metabolically healthy status was defined by excluding hospitalization records with diagnostic codes for hypertension, diabetes, and dyslipidemia. Demographics, trends, and outcomes were compared using appropriate statistical approaches. RESULTS: Of 26,949,310 young metabolically healthy hospitalizations between 2016 and 2019, 47,795 had AIS, of which 4,985 were MHOO and 42,810 were MHnOO. The median age of AIS hospitalization was 35 years, and primarily female and white. From 2016 to 2019, AIS incidence rose slightly, which was significant only for the MHnOO cohort. The in-hospital mortality rate was significantly lower in the MHOO cohort (6.0 % vs. 8.6 %, p < 0.001). Hospitalization length and cost did not differ substantially between groups. Adjusted multivariable analysis revealed no significant difference in AIS hospitalization risk between MHOO and MHnOO (aOR: 1.02, p=0.701), with subgroup analysis in males (aOR: 0.88, p=0.161) or females (aOR: 1.06, p=0.363). However, all-cause in-hospital mortality (ACIHM) in AIS had lower odds in the MHOO vs. MHnOO cohorts (aOR: 0.60, p=0.021). CONCLUSION: Our study finds a rising trend of AIS hospitalizations in young metabolically healthy adults, with obesity or overweight status not being associated with AIS hospitalization. We identify an "obesity paradox" of lower odds for ACIHM for AIS hospitalizations in the MHOO cohort.

Metabolically healthy obesity and chronic kidney disease risk: exploring the dynamics.

Obesity represents a prevalent global health concern with significant implications for various diseases, including chronic kidney disease (CKD). Within this landscape, the phenomenon of metabolically healthy obesity has emerged, challenging traditional notions about the health risks associated with excess weight. While traditional CKD risk factors involve obesity, metabolic syndrome, diabetes, and hypertension, the metabolically healthy obese (MHO) subgroup disrupts these assumptions. Our main objective in this study is to integrate existing literature on CKD in MHO individuals. In this endeavor, we delve into the pathophysiological foundations, the transition between obesity phenotypes and their impact on renal health, examine the implications of their metabolic resilience on mortality within a renal context, and explore potential management strategies specifically designed for MHO individuals. Offering a comprehensive overview of the pathophysiology, we cover various factors contributing to the risk of CKD in the metabolically healthy obese setting, including inflammation, cytokines, hemodynamics, and the renin-angiotensin-aldosterone system, gastrointestinal microbiota, diet, exercise, adipose distribution, and lipotoxicity. Through this synthesis, we aim to provide a comprehensive understanding of the risk of CKD in those classified as MHO.

Neurological-related proteomic profiling in plasma of children with metabolic healthy and unhealthy overweight/obesity.

OBJECTIVE: Children with overweight/obesity (OW/OB) exhibit poor cardiometabolic health, yet mechanisms influencing brain health remain unclear. We examined the differences in neurological-related circulating proteins in plasma among children with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) and the association with metabolic syndrome markers. METHODS: In this cross-sectional study, we included 84 Caucasian children (39% girls), aged 10.1 ± 1.1 years, from the ActiveBrains project (NCT02295072). A ninety-two-protein targeted approach using Olink's® technology was used. RESULTS: We identified distinct concentrations of CD38, LAIR2, MANF and NRP2 proteins in MHO compared with MUO. Moreover, individual metabolic syndrome (MS) markers were linked to nine proteins (CD38, CPM, EDA2R, IL12, JAMB, KYNU, LAYN, MSR1 and SMOC2) in children with OW/OB. These proteins play crucial roles in diverse biological processes (e.g., angiogenesis, cholesterol transport, nicotinamide adenine dinucleotide (NAD+) catalysis and maintenance of blood-brain barrier) related to brain health. CONCLUSION: Our proteomics study suggests that cardiometabolic health (represented by MHO/MUO or individual MS markers) is associated with the concentration in plasma of several proteins involved in brain health. Larger-scale studies are needed to contrast/confirm these findings, with CD38 standing out as a particularly noteworthy and robust discovery.

Associations of metabolic changes and polygenic risk scores with cardiovascular outcomes and all-cause mortality across BMI categories: a prospective cohort study.

BACKGROUND: Associations between metabolic status and metabolic changes with the risk of cardiovascular outcomes have been reported. However, the role of genetic susceptibility underlying these associations remains unexplored. We aimed to examine how metabolic status, metabolic transitions, and genetic susceptibility collectively impact cardiovascular outcomes and all-cause mortality across diverse body mass index (BMI) categories. METHODS: In our analysis of the UK Biobank, we included a total of 481,576 participants (mean age: 56.55; male: 45.9%) at baseline. Metabolically healthy (MH) status was defined by the presence of < 3 abnormal components (waist circumstance, blood pressure, blood glucose, triglycerides, and high-density lipoprotein cholesterol). Normal weight, overweight, and obesity were defined as 18.5 ≤ BMI < 25 kg/m2, 25 ≤ BMI < 30 kg/m2, and BMI ≥ 30 kg/m2, respectively. Genetic predisposition was estimated using the polygenic risk score (PRS). Cox regressions were performed to evaluate the associations of metabolic status, metabolic transitions, and PRS with cardiovascular outcomes and all-cause mortality across BMI categories. RESULTS: During a median follow-up of 14.38 years, 31,883 (7.3%) all-cause deaths, 8133 (1.8%) cardiovascular disease (CVD) deaths, and 67,260 (14.8%) CVD cases were documented. Among those with a high PRS, individuals classified as metabolically healthy overweight had the lowest risk of all-cause mortality (hazard ratios [HR] 0.70; 95% confidence interval [CI] 0.65, 0.76) and CVD mortality (HR 0.57; 95% CI 0.50, 0.64) compared to those who were metabolically unhealthy obesity, with the beneficial associations appearing to be greater in the moderate and low PRS groups. Individuals who were metabolically healthy normal weight had the lowest risk of CVD morbidity (HR 0.54; 95% CI 0.51, 0.57). Furthermore, the inverse associations of metabolic status and PRS with cardiovascular outcomes and all-cause mortality across BMI categories were more pronounced among individuals younger than 65 years (Pinteraction < 0.05). Additionally, the combined protective effects of metabolic transitions and PRS on these outcomes among BMI categories were observed. CONCLUSIONS: MH status and a low PRS are associated with a lower risk of adverse cardiovascular outcomes and all-cause mortality across all BMI categories. This protective effect is particularly pronounced in individuals younger than 65 years. Further research is required to confirm these findings in diverse populations and to investigate the underlying mechanisms involved.

Predicting the Transition to Metabolically Unhealthy Obesity Among Young Adults With Metabolically Healthy Obesity in South Korea: Nationwide Population-Based Study.

BACKGROUND: Globally, over 39% of individuals are obese. Metabolic syndrome, usually accompanied by obesity, is regarded as a major contributor to noncommunicable diseases. Given this relationship, the concepts of metabolically healthy and unhealthy obesity, considering metabolic status, have been evolving. Attention is being directed to metabolically healthy people with obesity who have relatively low transition rates to noncommunicable diseases. As obesity rates continue to rise and unhealthy behaviors prevail among young adults, there is a growing need for obesity management that considers these metabolic statuses. A nomogram can be used as an effective tool to predict the risk of transitioning to metabolically unhealthy obesity from a metabolically healthy status. OBJECTIVE: The study aimed to identify demographic factors, health behaviors, and 5 metabolic statuses related to the transition from metabolically healthy obesity to unhealthy obesity among people aged between 20 and 44 years and to develop a screening tool to predict this transition. METHODS: This secondary analysis study used national health data from the National Health Insurance System in South Korea. We analyzed the customized data using SAS (SAS Institute Inc) and conducted logistic regression to identify factors related to the transition from metabolically healthy to unhealthy obesity. A nomogram was developed to predict the transition using the identified factors. RESULTS: Among 3,351,989 people, there was a significant association between the transition from metabolically healthy to unhealthy obesity and general characteristics, health behaviors, and metabolic components. Male participants showed a 1.30 higher odds ratio for transitioning to metabolically unhealthy obesity than female participants, and people in the lowest economic status were also at risk for the transition (odds ratio 1.08, 95% CI 1.05-1.1). Smoking status, consuming >30 g of alcohol, and insufficient regular exercise were negatively associated with the transition. Each relevant variable was assigned a point value. When the nomogram total points reached 295, the shift from metabolically healthy to unhealthy obesity had a prediction rate of >50%. CONCLUSIONS: This study identified key factors for young adults transitioning from healthy to unhealthy obesity, creating a predictive nomogram. This nomogram, including triglycerides, waist circumference, high-density lipoprotein-cholesterol, blood pressure, and fasting glucose, allows easy assessment of obesity risk even for the general population. This tool simplifies predictions amid rising obesity rates and interventions.

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.

Frequency of prediabetes in individuals with increased adiposity and metabolically healthy or unhealthy phenotypes.

AIMS: To utilize the estimated glucose disposal rate (eGDR) index of insulin sensitivity, which is based on readily available clinical variables, namely, waist circumference, hypertension and glycated haemoglobin, to discriminate between metabolically healthy and unhealthy phenotypes, and to determine the prevalence of prediabetic conditions. METHODS: Non-diabetic individuals (n = 2201) were stratified into quartiles of insulin sensitivity based on eGDR index. Individuals in the upper quartiles of eGDR were defined as having metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW) or metabolically healthy obesity (MHO) according to their body mass index, while those in the lower quartiles were classified as having metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW) and metabolically unhealthy obesity (MUO), respectively. RESULTS: The frequency of impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and IFG + IGT status was comparable among the MHNW, MHOW and MHO groups, while it increased from those with MUNW status towards those with MUOW and MUO status. As compared with participants with MHNW, the odds ratio of having IFG, IGT, or IFG + IGT was significantly higher in participants with MUOW and MUO but not in those with MUNW, MHOW and MHO, respectively. CONCLUSIONS: A metabolically healthy phenotype is associated with lower frequency of IFG, IGT, and IFG + IGT status across all body weight categories.

Association between the transition to metabolically unhealthy obesity and lifestyle behavior: A nationwide cohort study.

OBJECTIVES: To identify the characteristics of individuals transitioning from metabolically healthy obesity (MHO) to unhealthy obesity and the factors influencing the change. DESIGN: This is a nationwide cohort study using data from the National Health Insurance Service in South Korea. SAMPLE: Individuals with obesity but metabolically healthy in 2009 and 2010 and those still obese 4 years later were selected. MEASUREMENTS: Sociodemographic, physical, metabolic, and health behavior variables were collected, and logistic regression was used to find an association with the transition. RESULTS: We analyzed 1,564,467 individuals, observing significant differences in all variables and the transition from MHO to unhealthy obesity. Among males, the transition was associated with smoking and drinking positively and physical activity negatively. Among females, drinking demonstrated a negative correlation. Regardless of age, regular exercise was negatively associated with the transition for all individuals. Except for older adults, all age groups showed a positive correlation with smoking and drinking. CONCLUSIONS: Considering the significant factors in the transition, it is essential to develop and implement interventions varied by gender and age to delay and prevent the change in metabolic status. The necessity of developing interventions enables individuals to engage in regular exercise, regardless of age and gender.

Metabolically healthy obesity and risks of cardiovascular disease and all-cause mortality, a matched cohort study: the Shizuoka study.

BACKGROUND: Metabolically healthy obesity is not always a benign condition. It is associated with an increased incidence of cardiovascular disease and all-cause mortality. We investigated the prognostic significance of metabolically healthy obesity by comparing clinical profile-matched metabolically healthy obesity and non-obesity groups. METHODS: We analyzed a health insurance dataset with annual health checkup data from Japan. The analyzed data included 168,699 individuals aged <65 years. Obesity was defined as ≥25 kg/m2 body mass index. Metabolically healthy was defined as ≤1 metabolic risk factor (high blood pressure, low high-density lipoprotein cholesterol, high low-density lipoprotein cholesterol, or high hemoglobin A1c). Incidence rates of stroke, myocardial infarction, and all-cause mortality identified from the insurance data were compared between metabolically healthy obesity and non-obesity groups (n = 8644 each) using a log-rank test. RESULTS: The stroke (obesity: 9.2 per 10,000 person-years; non-obesity: 10.5; log-rank test p = 0.595), myocardial infarction (obesity: 3.7; non-obesity: 3.1; p = 0.613), and all-cause mortality (obesity: 26.6; non-obesity: 23.2; p = 0.304) incidence rates did not differ significantly between the metabolically healthy obesity and non-obesity groups, even when the abdominal obesity was considered in the analysis. The lack of association was also observed in the comparison between the metabolically unhealthy obesity and non-obesity groups (n = 10,965 each). The population with metabolically healthy obesity reported negligibly worse metabolic profiles than the population with non-obesity at the 5.6-year follow-up. CONCLUSION: Obesity, when accompanied by a healthy metabolic profile, did not increase the risk of cardiovascular outcomes and all-cause mortality.

Cardiometabolic characteristics of people with metabolically healthy and unhealthy obesity.

There is considerable heterogeneity in the cardiometabolic abnormalities associated with obesity. We evaluated multi-organ system metabolic function in 20 adults with metabolically healthy obesity (MHO; normal fasting glucose and triglycerides, oral glucose tolerance, intrahepatic triglyceride content, and whole-body insulin sensitivity), 20 adults with metabolically unhealthy obesity (MUO; prediabetes, hepatic steatosis, and whole-body insulin resistance), and 15 adults who were metabolically healthy lean. Compared with MUO, people with MHO had (1) altered skeletal muscle biology (decreased ceramide content and increased expression of genes involved in BCAA catabolism and mitochondrial structure/function); (2) altered adipose tissue biology (decreased expression of genes involved in inflammation and extracellular matrix remodeling and increased expression of genes involved in lipogenesis); (3) lower 24-h plasma glucose, insulin, non-esterified fatty acids, and triglycerides; (4) higher plasma adiponectin and lower plasma PAI-1 concentrations; and (5) decreased oxidative stress. These findings provide a framework of potential mechanisms responsible for MHO and the metabolic heterogeneity of obesity. This study was registered at ClinicalTrials.gov (NCT02706262).

Distinguishing health-related parameters between metabolically healthy and metabolically unhealthy obesity in women.

BACKGROUND: Obesity represents a global health crisis, yet a dichotomy is emerging with classification according to the metabolic state into metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). This study aimed to identify distinctive systemic clinical/endocrinological parameters between MHO individuals, employing a comprehensive comparative analysis of 50 biomarkers. Our emphasis was on routine analytes, ensuring cost-effectiveness for widespread use in diagnosing metabolic health. SUBJECTS/METHODS: The study included 182 women diagnosed with obesity referred for bariatric surgery at the Endocrinology, Diabetes, and Metabolism Service of São João Hospital and University Centre in Portugal. MUO was defined by the presence of at least one of the following metabolic disorders: diabetes, hypertension, or dyslipidemia. Patients were stratified based on the diagnosis of these pathologies. RESULTS: Significantly divergent health-related parameters were observed between MHO and MUO patients. Notable differences included: albumin (40.1 ± 2.2 vs 40,98 ± 2.6 g/L, p value = 0.017), triglycerides (110.7 ± 51.1 vs 137.57 ± 82.6 mg/dL, p value = 0.008), glucose (99.49 ± 13.0 vs 119.17 ± 38.9 mg/dL, p value < 0.001), glycated hemoglobin (5.58 ± 0.4 vs 6.15 ± 1.0%, p value < 0.001), urea (31.40 ± 10.0 vs 34.61 ± 10.2 mg/dL, p value = 0.014), total calcium (4.64 ± 0.15 vs 4.74 ± 0.17 mEq/L, 1 mEq/L = 1 mg/L, p value < 0.001), ferritin (100.04 ± 129.1 vs 128.55 ± 102.1 ng/mL, p value = 0.005), chloride (104.68 ± 1.5 vs 103.04 ± 2.6 mEq/L, p value < 0.001), prolactin (13.57 ± 6.3 vs 12.47 ± 7.1 ng/mL, p value = 0.041), insulin (20.36 ± 24.4 vs 23.87 ± 19.6 µU/mL, p value = 0.021), c peptide (3.78 ± 1.8 vs 4.28 ± 1.7 ng/mL, p value = 0.003), albumin/creatinine ratio (15.41 ± 31.0 vs 48.12 ± 158.7 mg/g creatinine, p value = 0.015), and whole-body mineral density (1.27 ± 0.1 vs 1.23 ± 0.1 g/cm2, p value = 0.016). CONCLUSIONS: Our findings highlight potential additional parameters that should be taken into consideration alongside the commonly used biomarkers for classifying metabolic health in women. These include albumin, urea, total calcium, ferritin, chloride, prolactin, c-peptide, albumin-creatinine ratio, and whole-body mineral density. Moreover, our results also suggest that MHO may represent a transitional phase preceding the development of the MUO phenotype.

Resistance training and cardiometabolic risk in women with metabolically healthy and unhealthy obesity.

Despite some reported benefits, there is a low quality of evidence for resistance training (RT) improving metabolic health of individuals with overweight or obesity. We evaluated the impact of RT on body composition, cardiorespiratory fitness (CRF) and physical performance, lipid-lipoprotein profile, inflammation, and glucose-insulin homeostasis in 51 postmenopausal women versus 29 controls matched for age, obesity, and physical activity. Exercised women were further subdivided for comparison of RT effects into those presenting metabolically healthy obesity (MHO) and those with metabolically unhealthy obesity (MUHO) classified according to Karelis and Rabasa-Lhoret or an approach based on adipose tissue secretory dysfunction using the plasma adiponectin(A)/leptin (L) ratio. Participants followed a 4-month weekly RT program targeting major muscle groups (3 × 10 repetitions at 80% one repetition maximum (1-RM)). Percent fat marginally decreased and lean body mass increased (0.01 < p < 0.05) while CRF and muscular strength improved in all women, after RT (effect size (ES): 0.11-1.21 (trivial to large effects), p ˂ 0.01). Fasting plasma triacylglycerol and high-density lipoprotein-cholesterol levels slightly increased and decreased, respectively, in participants with MHO using the A/L ratio approach (ES: -0.47 to 1.07 (small to large effects), p ˂ 0.05). Circulating interleukin-6 soluble receptor decreased in both groups and soluble tumor necrosis factor receptor-1/soluble tumor necrosis factor receptor-2 in women with MUHO only, irrespective of definition (ES: -0.42 to -0.84 (small to large effects), p ˂ 0.05). Glucose-insulin homeostasis was unchanged regardless of group or definition. RT improved physical performance and body composition but had a lesser impact on cardiometabolic risk in women with obesity, irrespective of their metabolic phenotype.