The 25-year national trends in prevalence of metabolic phenotypes among iranian adults: from 2000 to 2025 using STEPS studies.

Metabolic abnormalities, but not obesity per se, associated with chronic kidney disease in a Taiwanese population

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. 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. 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. 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.

BackgroundIncreased body mass index (BMI) and metabolic abnormalities both have potential associations with thyroid disease. The aim of this study was to investigate the correlation between different metabolic phenotypes of obesity and thyroid disorders using nationwide data from China.MethodsData were collected from a cross-sectional survey called the Thyroid Disorders, Iodine Status, and Diabetes Epidemiological Survey conducted between 2015 and 2017 in China. A total of 69007 subjects aged 18 years or older were defined and divided into six groups on the basis of BMI and metabolic health status: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight (MHOW), metabolically unhealthy overweight (MUOW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). We estimated the odds ratios (ORs) and confidence intervals [CIs] for different thyroid disorders according to metabolic phenotypes using multivariate logistic regression models.ResultsIn our study, we found that the prevalence of subclinical hypothyroidism was almost as high in the MUNW group as in the MUO group, the prevalence of overt hyperthyroidism was highest in the MUNW group and Graves’ disease was highest in the MHO group. Our results also suggested that the prevalence of goiter and thyroid nodules increased with increased BMI values and that the MUO group had the highest incidence. Multivariate logistic regression analysis indicated that subjects with unhealthy metabolic phenotypes (MUNW, MUOW, and MUO) all had an increased risk of subclinical hypothyroidism, regardless of their BMI. MUNW subjects had an approximately 1.6-fold higher risk of overt hyperthyroidism and a 1.8-fold higher risk of Graves’ disease than their metabolically healthy counterparts (MHNW). The present study also demonstrated that the MUO group had the highest risk of goiter and thyroid nodules among the metabolic phenotypes of obesity.ConclusionBased on our study, we found that metabolic abnormalities and obesity play different roles in various thyroid diseases. Metabolically unhealthy individuals, both with and without obesity, have a higher risk of thyroid disorders than metabolically healthy individuals without obesity.

Evaluating the risk of hypertension according to the metabolic health status stratified by degree of obesity

Although obesity is clearly identified as a risk factor for diabetes, the relationship between diabetes and metabolically healthy status of obesity is less clear. This study was aimed to evaluate the incidental risk of diabetes according to metabolically healthy status of obesity. 31,834 Korean men without diabetes categorized into six groups according to their metabolically healthy status stratified by degree of obesity were followed up for 5 years: metabolically healthy normal weight (MH-NW), metabolically healthy overweight (MH-OW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MU-NW), metabolically unhealthy overweight (MU-OW), and metabolically unhealthy obese (MUO). Cox proportional hazards analysis was used to measure the risk for diabetes according to their categories. While overall incidence was 9.0 %, incidence of diabetes was in proportion to the degree of obesity and metabolically healthy status (MH-NW: 6.3 %, MH-OW: 7.5 %, MHO: 9.2 %, MU-NW: 11.8 %, MU-OW: 14.9 %, MUO: 20.1 %). When MH-NW was set as reference, the adjusted HRs (95 % CI) for diabetes of the MH-OW, MHO, MU-NW, MU-OW, MUO compared to MH-NW were 1.18 (1.06-1.32), 1.58 (1.03-2.41), 1.81 (1.61-2.04), 2.36 (2.11-2.63), and 3.47 (2.84-4.24), respectively. In conclusion, risk for diabetes was in proportion to the degree of obesity in both metabolically healthy and unhealthy group. Metabolically healthy status was more significant determinant for incident diabetes than obesity itself.

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. 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. 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. A metabolically healthy phenotype is associated with lower frequency of IFG, IGT, and IFG + IGT status across all body weight categories.

BackgroundUrinary albumin‐creatinine ratio (UACR) is a sensitive marker of kidney injury. This study analyzed the prevalence of different metabolic phenotypes and investigated their relationship with UACR in Chinese community adults.MethodsThis study involved 33 303 participants over 40 years old from seven centers across China. They were stratified into six groups according to their body mass index (BMI) and metabolic status: metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), metabolically healthy obesity (MHO), metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW), and metabolically unhealthy obesity (MUO). Increased albuminuria was defined as a UACR ≥30 mg/g.ResultsThe percentages of MHNW, MHOW, MHO, MUNW, MUOW, and MUO were 27.6%, 15.9%, 4.1%, 19.8%, 22.5%, and 9.6%, respectively. Multiple logistic regression analysis showed that the MHO group (odds ratio [OR] 1.205; 95% CI, 1.081‐1.343), MUNW group (OR 1.232; 95% CI, 1.021‐1.486), MUOW group (OR 1.447; 95% CI, 1.303‐1.607), and MUO group (OR 1.912; 95% CI, 1.680‐2.176) were at higher risk of increased albuminuria compared to the MHNW group. Subgroup analysis indicated that the risk of increased albuminuria was further elevated among regular smokers in men aged 40 to 55 years old with abdominal obesity.ConclusionsAmong Chinese community adults, increased albuminuria was associated with increased BMI whether metabolism was normal or not, and those with abnormal metabolism were at greater risk of increased albuminuria than those with normal metabolism. These findings suggest that overweight or obesity or metabolic abnormalities are risk factors for chronic kidney disease.

Associations between metabolic phenotypes and diabetes risk: A systematic review and meta-analysis

<b>OBJECTIVE: </b>It is controversial whether adults who are obese, but "metabolically healthy" have cardiovascular disease (CVD) risk comparable to normal weight adults. High-sensitivity cardiac troponin T(hs-cTnT), a biomarker of myocardial damage, is useful in characterizing subclinical CVD. We categorized obesity phenotypes and studied their associations with subclinical and clinical CVD and CVD subtypes, including heart failure (HF). <p><b>RESEARCH DESIGN AND METHODS: </b>We conducted cross-sectional and prospective analyses of<b> </b>9,477 adults in the Atherosclerosis Risk in Communities (ARIC) Study. We used the Adult Treatment Panel III criteria and body mass index (BMI) to define obesity phenotypes as metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOv), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOv), and metabolically unhealthy obese (MUO). </p> <p><b>RESULTS: </b>At baseline<b> </b>(1990-1992), mean age was 56 years, 56% were female, 23% Black, 25% detectable hs-cTnT(≥ 6 ng/L).<b> </b>Over a median 17 years of follow-up, there were 2,603 clinical CVD events. The MHO (HR 1.38, 95%CI:1.15-1.67), MUNW (HR 1.51, 95%CI:1.30-1.76), MUOv (HR 1.60, 95%CI:1.41-1.82) and MUO (HR 2.14, 95%CI: 1.88-2.44) phenotypes had higher CVD risks than the MHNW. Detectable hs-cTnT(≥ 6 ng/L) was associated with higher CVD risk, even among MHNW adults. MHO adults had higher HF risk (HR 1.65, 95%CI:1.30-2.09) than the MHNW. </p> <p><b>CONCLUSIONS: </b>The MHO phenotype was associated with excess burden of clinical CVD, primarily driven by an excess risk of HF. Hs-cTnT was useful in stratifying CVD risk across all obesity phenotypes, even among obese persons who appear otherwise metabolically healthy. </p>

<b>OBJECTIVE: </b>It is controversial whether adults who are obese, but "metabolically healthy" have cardiovascular disease (CVD) risk comparable to normal weight adults. High-sensitivity cardiac troponin T(hs-cTnT), a biomarker of myocardial damage, is useful in characterizing subclinical CVD. We categorized obesity phenotypes and studied their associations with subclinical and clinical CVD and CVD subtypes, including heart failure (HF). <p><b>RESEARCH DESIGN AND METHODS: </b>We conducted cross-sectional and prospective analyses of<b> </b>9,477 adults in the Atherosclerosis Risk in Communities (ARIC) Study. We used the Adult Treatment Panel III criteria and body mass index (BMI) to define obesity phenotypes as metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOv), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOv), and metabolically unhealthy obese (MUO). </p> <p><b>RESULTS: </b>At baseline<b> </b>(1990-1992), mean age was 56 years, 56% were female, 23% Black, 25% detectable hs-cTnT(≥ 6 ng/L).<b> </b>Over a median 17 years of follow-up, there were 2,603 clinical CVD events. The MHO (HR 1.38, 95%CI:1.15-1.67), MUNW (HR 1.51, 95%CI:1.30-1.76), MUOv (HR 1.60, 95%CI:1.41-1.82) and MUO (HR 2.14, 95%CI: 1.88-2.44) phenotypes had higher CVD risks than the MHNW. Detectable hs-cTnT(≥ 6 ng/L) was associated with higher CVD risk, even among MHNW adults. MHO adults had higher HF risk (HR 1.65, 95%CI:1.30-2.09) than the MHNW. </p> <p><b>CONCLUSIONS: </b>The MHO phenotype was associated with excess burden of clinical CVD, primarily driven by an excess risk of HF. Hs-cTnT was useful in stratifying CVD risk across all obesity phenotypes, even among obese persons who appear otherwise metabolically healthy. </p>

Risk of diabetes according to the metabolic health status and degree of obesity

Metabolically unhealthy individuals, either with obesity or not, have a higher risk of critical coronavirus disease 2019 outcomes than metabolically healthy individuals without obesity

Association of metabolic health phenotypes, obesity, and hepatocellular carcinoma risk.

PurposeThe association between metabolic phenotypes and thyroid function has not yet been established; therefore, this study examined whether different metabolic phenotypes are associated with the development of hypothyroidism.MethodsStudy participants were selected from the Tehran Thyroid Study (TTS). A total of 3338 euthyroid adults were included and categorized into four obesity phenotype groups: metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy obese (MUO). The participants were assessed at baseline and during three follow-up studies at three-year intervals. Multiple logistic regression analysis was used to examine the relationship between metabolic phenotypes and the development of hypothyroidism.ResultsIn the total population, the chi-square test was only significant (P=0.008) in 3rd year with a higher prevalence of hypothyroidism in the MUNW phenotype, followed by MHO, MUO, and MHNW. Moreover, in the 3rd and 9th years of follow-up, hypothyroidism was more prevalent in MUO only in male subjects (P=0.002 and 0.035, respectively). In the unadjusted model, the MHO phenotype increased the odds of hypothyroidism compared with the MHNW phenotype (OR=1.51; 95% CI=1.04, 2.18; P-value=0.031). After adjusting for confounding factors, the odds of hypothyroidism were higher in the MUNW (OR=1.86; 95% CI=1.17, 2.96; P-value=0.008), MHO (OR=1.71; 95% CI=1.09, 2.67; P-value=0.018), and MUO (OR=1.64; 95% CI=1.03, 2.62; P-value=0.036) phenotypes than in the MHNW group. The MUNW phenotype increased the risk of hypothyroidism compared to MHNW, only in males. However, in females, the MHO phenotype increased the risk of hypothyroidism compared to MHNW.ConclusionBoth obesity and metabolic abnormalities are associated with hyperthyroidism. Healthy metabolic and weight maintenance were associated with a lower risk of hypothyroidism in males and females.

The global increase in obesity, driven by socioeconomic development, poses significant public health challenges owing to its phenotypic heterogeneity. Individuals with obesity, according to body mass index (BMI) and metabolism health, are classified into six common subgroups: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUHNW), metabolically healthy overweight (MHOW), metabolically unhealthy overweight (MUHOW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUHO). Populations with MHO exhibit high BMI but maintain normal glucose, lipid, and insulin levels. However, their long-term risks and mechanisms remain unclear. The relationship between MHO, its biomarkers, and disease risks was examined in this review, emphasizing its clinical significance. Adipose tissue dysfunction driven by chronic inflammation, oxidative stress, and adipokine imbalance underlies metabolic dysregulation. BMI remains widely used as a primary diagnostic tool; nevertheless, its limitation in differentiating MHO from MUHO highlights the importance of incorporating more precise biomarkers, including inflammatory markers, adipokines, myokines, epigenetic regulators, and other clinical indices. Individuals with MHO may initially exhibit a relatively benign metabolic profile; however, they remain at an increased risk of developing type 2 diabetes, cardiovascular diseases, and other cardiometabolic conditions. We propose risk factors for predicting MHO progression, providing critical insights for early intervention and personalized management.