Definitions Of Metabolic Health Research Articles

Abstract 4870: Defining metabolically healthy and unhealthy obesity in relation to cancer risk: A prospective cohort study by using a machine learning approach in comparison with conventional definitions in the UK Biobank

Abstract Background: The definition of metabolically healthy and unhealthy obesity for cancer risk remains uncertain and controversial. This study proposed a novel classifier based on biomarkers selected using machine learning (ML) and compared its risk stratification with the conventional definition. Methods: A prospective cohort study was conducted of 317,569 UK Biobank participants who were free of cancer and with body mass index (BMI) ≥18.5 kg/m2 at baseline. Individuals were classified into metabolically healthy and non-obese (MHNO), metabolically unhealthy and non-obese (MUNO), metabolically healthy and obese (MHO), and metabolically unhealthy and obese (MUO), according to body mass index (BMI) and six metabolic criteria. For the ML approach, LASSO regularization was used to select a subset from seventeen metabolic biomarkers to optimize C index. Clinical cut-off value was applied to this subset to define MHO. Multivariable Cox proportional hazards models were used to estimate hazard ratios (HRs) of total, obesity-related, type two diabetes (T2D)-related, and 23 site-specific cancers according to the conventional and ML definitions. Findings: Of 21 biomarkers, 17 were selected using LASSO. Compared with MHNO, individuals with MHO had higher risk of obesity-related cancer (HRconventional 1.22, 95% CI 1.15-1.29; HRML 1.23, 95% CI 1.16-1.30) and T2D-related cancer (HRconventional 1.25, 95% CI 1.19-1.39; HRML 1.27, 95% CI 1.20-1.34) after adjusting for sociodemographic and lifestyle factors. ML-defined metabolic status better-stratified individuals with normal weight for risk of total cancer (HRconventional1.02, 95% CI 0.99 -1.06; HRML 1.06, 95% CI 1.02 - 1.10) and some site-specific cancers, e.g., hepatocellular carcinoma (HRconventional 0.89, 95% CI, 0.53-1.48; HRML 2.52, 95% CI, 1.85-3.45). Interpretation: Compared with the conventional definition of metabolic health, a broader array of metabolic markers may help better stratify individuals for cancer risk. Keywords: Obesity, cancer, metabolically healthy obesity, hepatocellular carcinoma. Citation Format: Ziyi Zhou, Solange Parra-Soto, Yujia Lu, Zhe Fang, Kai Wang, Alaina Bever, Liyuan Tao, Fanny Petermann-Rocha, Jirapitcha Boonpor, Naveed Sattar, Carlos Celis-Morales, Jill P. Pell, Frederick K. Ho, Mingyang Song. Defining metabolically healthy and unhealthy obesity in relation to cancer risk: A prospective cohort study by using a machine learning approach in comparison with conventional definitions in the UK Biobank [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4870.

Body size, insulin sensitivity, metabolic health and risk of cardiovascular disease in Chinese adults: Insights from the China Cardiometabolic Disease and Cancer Cohort (4C) study.

To assess the excess risk of cardiovascular disease (CVD) associated with different criteria for metabolic health, and the interplay of body size, insulin sensitivity and metabolic health with CVD risk. We conducted a prospective study involving 115 638 participants from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. Metabolic health was defined using three different definitions: (1) insulin sensitivity defined by homeostatic model assessment of insulin resistance index; (2) absence of metabolic syndrome according to the National Cholesterol Education Program Adult Treatment Panel III criteria; and (3) simultaneous absence of metabolic abnormalities (diabetes, hypertension, dyslipidaemia). The primary endpoint was a composite of incident CVD events comprising the first occurrence of myocardial infarction, stroke, heart failure, or cardiovascular death. During a mean 3.61-year follow-up period, obese individuals with insulin sensitivity (multivariable-adjusted hazard ratio [HR] 1.69, 95% confidence interval [CI] 1.37-2.08), or without metabolic syndrome (HR 1.46, 95% CI 1.13-1.89) still exhibited increased CVD risks, when compared to their normal-weight counterparts. Otherwise, those with obesity but simultaneous absence of metabolic abnormalities demonstrated similar CVD risk compared to normal-weight individuals (HR 0.91, 95% CI 0.53-1.59). CVD risk increased with the number of abnormalities across body mass index categories, regardless of insulin sensitivity. This study emphasizes the need for refined definitions of metabolic health and advocates for meticulous screening for metabolic abnormalities to reduce cardiovascular risks, even in individuals with normal weight and insulin sensitivity.

Metabolic Health and Carotid Intima-Media Thickness: Association of Different Definitions in Women

The concept of metabolic health and the metabolic syndrome is to identify subjects at a higher cardiovascular risk. However, many definitions are currently in use, and it is uncertain which is the best in identifying at-risk subjects. We performed a cross-sectional study whereby women were invited to participate and were assessed for several anthropometric and biochemical parameters. Carotid intima-media thickness (CIMT) was measured in both common carotid arteries in each participant. The study cohort consisted of 203 white premenopausal women with a mean age of 38.3 ± 5.4years. The prevalence of the metabolically unhealthy varied from 7.3% to 61.6%, according to the definition used. The prevalence of the metabolic syndrome, as defined by the International Diabetes Federation, was 20.7%. Women with a metabolically unhealthy phenotype had a higher referent CIMT for all definitions of metabolic health. Defining metabolically unhealthy phenotype as having <2 abnormalities using the National Cholesterol Education Program Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (NCEP-ATPIII) cutoffs had the highest odds ratio for an abnormal CIMT. In conclusion, we found that in a contemporary cohort of middle-aged women, the NCEP-ATPIII definition of the metabolic syndrome was more strongly associated with atherosclerosis as determined by the CIMT than the International Diabetes Federation definition or other definitions of metabolic health; it was also more strongly associated than body mass index or waist circumference. Our results need to be validated by other investigators in other populations.

PS-BPP03-3: CARDIOVASCULAR RISK AND METABOLIC CHARACTERIZATION OF METABOLICALLY HEALTHY OBESITY CLASSIFIED BY THE NEWLY PROPOSED DEFINITION: A PROSPECTIVE STUDY

Objective: The varying definition of metabolic health is responsible for the debate about whether metabolically healthy obesity (MHO) is associated with increased cardiovascular risk. An empirically derived definition of metabolic health has been newly proposed to identify individuals with obesity but without excess mortality risk. This study aimed to evaluate the association of MHO classified by the new definition with cardiovascular events and to reveal the metabolic characterization of MHO. Design and method: We classified 1331 Flemish people (mean age: 51.3 years; women: 50.3%) by their metabolic health status (systolic blood pressure &lt; 130 mmHg, waist-to-hip ratio &lt; 0.95 for women or 1.03 for men, and absence of antihypertensives and diabetes) and obesity status (body mass index &gt; = 25 kg/m2). Plasma 44 metabolites were measured by nuclear magnetic resonance spectroscopy at baseline. Hazard ratios (HRs), odds ratios, and 95% confidence intervals (95% CI) were calculated using Cox proportional hazard regressions and logistic regressions, accounting for sex, age, sex, smoking, alcohol, and physical activity. Results: During 5.6 years of follow-up, 111 cardiovascular events and 33 diabetes incidents occurred. MHO was not associated with cardiovascular events (HR 1.61, 95% CI: 0.49–5.27) compared with metabolically healthy normal weight. The HRs were 3.19 (95% CI: 1.07–9.53) and 3.27 (95% CI: 1.15–9.32) for metabolically unhealthy normal weight and obesity, respectively. Individuals with metabolic health had a lower risk of diabetes (HR: 0.22, 95%CI: 0.06–0.77). Compared with metabolically unhealthy obesity, MHO was associated with eight metabolites, including six with positive association (2-aminobutyrate, 4-aminobutyrate, alanine, leucine, 4-hydroxybutyrate, and acetate) and two with negative association (valerate and lactate). Metabolites positively associated with MHO showed inverse associations with diabetes risk, while metabolites negatively associated with MHO showed positive associations with diabetes risk. The associations of these metabolites with MHO reversed their directions compared with metabolically healthy normal weight. None of the eight metabolites was associated with cardiovascular events. Conclusion: This new definition of metabolic health can be replicated to stratify cardiovascular risk for individuals with or without obesity. The metabolic characterization of MHO was not completely ‘healthy’, which might help to identify novel targets for intervention.

Association of Metabolically Healthy Obesity and Glomerular Filtration Rate among Male Steelworkers in North China.

This study aims to investigate the association between metabolically healthy obesity (MHO) and the early stages of renal dysfunction and whether systemic inflammation affects the study’s outcome. Male steelworkers in northern China were investigated in this cross-sectional survey (n = 6309). A decrease in estimated glomerular filtration rate (eGFR) was used as the primary outcome, which was defined as an eGFR of ≤89 mL/min/1.73 m2. A BMI ≥ 25 kg/m2 was used to determine obesity. In the definition of metabolic health, the absence of metabolic syndrome components is considered metabolically healthy. An assessment of inflammation was carried out using a surrogate marker called high-sensitivity C-reactive protein (hs-CRP). The adjusted odds ratio (OR) and confidence intervals (CIs) were estimated using the multivariable logistic regression model. After adjusting for hs-CRP, MHO (OR = 1.97; 95% CI: 1.21 to 3.21) was significantly associated with decreased eGFR compared to metabolically healthy non-obesity (MHNO). With the MHNO/hs-CRP ≤ 0.01 mg/dL group as a reference, the OR was 2.17 (95% CI: 1.17 to 4.02) for decreased eGFR in the group with MHO/hs-CRP > 0.01 mg/dL. MHO is associated with renal dysfunction at an early stage. To some degree, this risk can be explained by the level of inflammation.

Prevalence rates of metabolic health and body size phenotypes by different criteria and association with insulin resistance in a Maltese Caucasian population

IntroductionHyperinsulinemia and insulin resistance are known to be associated with increased cardiovascular morbidity and mortality. A metabolically unhealthy phenotype is frequently used as a surrogate marker for insulin resistance. The aims of the current study were to compare the prevalence of the body size phenotypes using different definitions of metabolic health and to investigate which one of them is most strongly associated with insulin resistance in men and women.MethodsWe conducted a cross-sectional study in a middle-aged cohort of Maltese Caucasian non-institutionalized population. Metabolic health was defined using the various currently used definitions.ResultsThere were significant differences in the prevalence of body size phenotypes according to the different definitions. We also found significant sex differences in the predictive value of the various definitions of the metabolically unhealthy phenotype to predict insulin resistance. The strongest association was for the definition of having >2 NCEP-ATPIII criteria to characterize the metabolic unhealthy phenotype in women (odds ratio of 19.7). On the other hand, the Aguilar-Salinas et al. definition had the strongest association in men (odds ratio of 18.7).ConclusionsWe found large differences in the prevalence of the various body size phenotypes when using different definitions, highlighting the need for having standard criteria. Our data also suggest the need for sex-specific definitions of metabolic health.

1236-P: Cardiometabolic Disease Risk in Metabolically Unhealthy vs. Healthy in Normal Weight and Obesity: Results from 2015 and 20KNHNES Data

The concept of metabolically unhealthy vs. healthy obese (MUO vs. MHO) was expanded to non-obese individuals as obesity-related comorbidities exist in a subgroup of metabolically unhealthy vs. healthy normal-weight (MUNW vs. MHNW) . It is unclear if MUNW differs from MHO with respect to cardiometabolic health. Here, we applied a widely accepted definition of metabolic health (JAMA 20285: 2486) and examined differences in cardiometabolic risk factors among 4 subgroups of Korean adults (N=7,594) . Individuals with NW vs. obesity (BMI ≥25 kg/m2) were categorized as either MU or MH if those met one or more of the following criteria: triglyceride ≥150 mg/dl; fasting glucose ≥100 mg/dl; HDL &amp;lt;40 mg/dl in men or &amp;lt;50 mg/dl in women; and SBP ≥130 mmHg or DBP ≥85 mmHg. Despite a gradual increase in BMI and visceral adiposity index from MHNW to MUNW to MHO to MUO, surrogates of insulin resistance (TG/HDL) and arterial stiffness (estimated pulse wave velocity) were higher in MUNW vs. MHO (Table) . HOMA-IR was highest in MUO with no difference between MUNW and MHO (Table) . Individuals with MUNW vs. MHO are at least similar to or more vulnerable 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 normal-weight, yet metabolically unhealthy. Disclosure M.Seo: None. W.Cho: None. J.Rosenberg: None. L.White: None. J.Kim: n/a.

Association between Metabolically Healthy Obesity and Subclinical Atherosclerosis in the Cardiovascular and Metabolic Diseases Etiology Research Center (CMERC) Cohort.

We aimed to investigate the association between a new definition of metabolic health (MH) and subclinical atherosclerosis in a cohort of patients without previous cardiovascular disease (CVD). In total, 7824 community-dwelling adults were categorized as normal weight, overweight, or obese. Metabolically healthy obesity (MHO) was defined as obesity accompanied by all of the following criteria: systolic blood pressure (BP) < 130 mmHg, no use of BP-lowering medication, waist-hip ratio <0.832 (women) and <0.887 (men), and no prevalent diabetes. Carotid atherosclerosis was defined as carotid plaque or mean carotid intima-media thickness ≥ 1.1 mm. The prevalence of carotid atherosclerosis was 8.3% and 1113 (14.2%) patients were classified as having MHO. All individuals classified as metabolically unhealthy were at an increased risk of carotid atherosclerosis independent of body mass index categories. Conversely, the risk of carotid atherosclerosis in individuals with MHO was not significantly increased compared to that in metabolically healthy normal weight participants (hazard ratio 1.20, 95% confidence interval 0.87–1.67). This new definition of MH was able to identify people with MHO without an increased risk of CVD in an Asian community cohort.

Abstract P175: Combined Metabolic Health And Obesity Status Is Associated With Markers Of High-Density Lipoprotein Metabolism: Dallas Heart Study

Introduction: While high-density lipoprotein (HDL) cholesterol is a component of metabolic syndrome, an ASCVD risk factor, other markers of HDL metabolism better associate with ASCVD. However, it is unclear whether these markers better discriminate between metabolic health and obese groups. Hypothesis: We hypothesized that higher cholesterol efflux capacity (CEC) and a favorable HDL profile would be associated with metabolically healthy profiles within each weight category. Methods: Data from the second phase of the Dallas Heart Study were used to classify participants (n=2156) into four groups based on a harmonized definition of metabolic health and obesity status: Metabolically Healthy, Normal Weight (MHNW); Metabolically Unhealthy, Normal Weight (MUNW); Metabolically Healthy, Obese (MHO); Metabolically Unhealthy, Obese (MUO). MU was classified as having one or more of the following: elevated blood pressure (SBP/DBP ≥130/85 mmHg), fasting glucose (≥100 mg/dL), or fasting triglycerides (≥150 mg/dL); a history of CVD or diabetes; or any medications for these conditions. Obesity was defined as BMI ≥ 30kg/m 2 . CEC was measured using J774 macrophages, BODIPY- and radio-labeled cholesterol, and apoB-precipitated plasma. HDL particle (HDL-P) subfractions were quantified by NMR spectroscopy. Generalized linear models were used to compare paired means of CEC and HDL traits between groups controlling for age, sex, race, and smoking. Results: Small HDL-P concentration was higher in MU groups regardless of weight status. Total and medium HDL-P concentrations and radio-labeled CEC were higher in NW groups, regardless of metabolic health status. Mean HDL-P size and large HDL-P concentrations were different across all groups, with the rank order being MHNW, MUNW, MHO, MUO (Table 1). Conclusions: In conclusion, associations between HDL subfractions, CEC and metabolic/weight status are heterogeneous, highlighting the complexity of HDL physiology as it pertains to body weight and metabolic disease.

Prognostic Value of Triglyceride and Glucose Index for Incident Type 2 Diabetes beyond Metabolic Health and Obesity.

BackgroundMetabolically healthy obese (MHO) phenotype is metabolically heterogeneous in terms of type 2 diabetes (T2D). Previously, the triglyceride and glucose (TyG) index has been considered for identifying metabolic health and future risk of T2D. This study aimed to evaluate the risk of incident T2D according to obesity status and metabolic health, categorized by four different criteria and the TyG index.MethodsThe study included 39,418 Koreans without T2D at baseline. The risk of T2D was evaluated based on four different definitions of metabolic health and obesity status and according to the baseline TyG index within each metabolic health and obesity group.ResultsDuring the median follow-up at 38.1 months, 726 individuals developed T2D. Compared with the metabolically healthy non-obese (MHNO) group with low TyG index, the MHO group with high TyG index showed increased risk of T2D in all four definitions of metabolic health with multivariate-adjusted hazard ratios of 2.57 (95% confidence interval [CI], 1.76 to 3.75), 3.72 (95% CI, 2.15 to 6.43), 4.13 (95% CI, 2.67 to 6.38), and 3.05 (95% CI, 2.24 to 4.15), when defined by Adult Treatment Panel III, Wildman, Karelis, and homeostasis model assessment (HOMA) criteria, respectively.ConclusionMHO subjects with high TyG index were at an increased risk of developing T2D compared with MHNO subjects, regardless of the definition of metabolic health. TyG index may serve as an additional factor for predicting the individual risk of incident T2D in MHO subjects.

An Empirically Derived Definition of Metabolically Healthy Obesity Based on Risk of Cardiovascular and Total Mortality

People classified by a priori definitions as having metabolically healthy obesity have frequently been found to be at increased risk of mortality, compared with individuals with metabolically healthy normal weight, suggesting these definitions may be insufficient. To systematically derive a new definition of metabolic health (MH) and investigate its association with cardiovascular disease (CVD) mortality and total mortality. In a cohort study using data from the third National Health and Nutrition Examination Survey (NHANES-III), a representative survey using complex multistage probability sampling, anthropometric factors, biomarkers, and blood pressure (BP) associated with total and CVD mortality among participants with obesity were identified with Cox proportional hazards regression. Area under the receiver operating characteristic was calculated to identify predictive factors for mortality to be used to define MH, cutoff levels were determined by the Youden index, and the findings were validated through comparison with the independent UK Biobank cohort, a population-based prospective study. All nonpregnant participants in the databases aged 18 to 75 years with no history of CVD, body mass index greater than or equal to 18.5, and who fasted 6 or more hours before examination in NHANES-III were included; participants in the UK Biobank cohort who did not have blood measurements were excluded. The study was conducted from 2015 to 2020. Body mass index and MH were defined by the new definition and compared with 3 a priori definitions. Cardiovascular disease mortality and total mortality. Within the NHANES-III (n = 12 341) cohort, mean (SD) age was 41.6 (29.2) years, 50.7% were women, and mean follow-up was 14.5 (2.7) years. Within the UK Biobank (n = 374 079) cohort, mean (SD) age was 56.2 (8.1) years, 55.1% were women, and mean follow-up was 7.8 (1.0) years. Use of blood pressure (BP)-lowering medication (hazard ratio [HR] for CVD mortality, 2.41; 95% CI, 1.50-3.87 and total mortality, 2.05; 95% CI, 1.47-2.84), diabetes, and several continuous factors were associated with mortality. Of all significant continuous factors, the combination of systolic BP and waist-to-hip ratio showed the highest area under the receiver operating characteristic (CVD mortality: 0.775; 95% CI, 0.770-0.781; total mortality: 0.696; 95% CI, 0.694-0.699). Thus, MH was defined as systolic BP less than 130 mm Hg, no BP-lowering medication, waist-to-hip ratio less than 0.95 for women and less than 1.03 for men, and no self-reported (ie, prevalent) diabetes. In both cohorts, metabolically healthy obesity was not associated with CVD and total mortality compared with metabolically healthy normal weight. For NHANES-III, the hazard ratio was 0.68 (95% CI, 0.30-1.54) for CVD mortality and 1.03 (95% CI, 0.70-1.51) for total mortality. For UK Biobank, the hazard ratio was 1.17 (95% CI, 0.81-1.69) for CVD mortality and 0.98 (95% CI, 0.87-1.10) for total mortality. Regardless of body mass index, all metabolically unhealthy groups displayed increased risks. This newly proposed definition of MH may identify a subgroup of people with obesity without increased risk of mortality and stratify risks in people who are overweight or normal weight.

Metabolically Healthy Obesity: Criteria, Epidemiology, Controversies, and Consequences.

To present a comprehensive overview regarding criteria, epidemiology, and controversies that have arisen in the literature about the existence and the natural course of the metabolic healthy phenotype. The concept of metabolically healthy obesity (MHO) implies that a subgroup of obese individuals may be free of the cardio-metabolic risk factors that commonly accompany obese subjects with adipose tissue dysfunction and insulin resistance, known as having metabolic syndrome or the metabolically unhealthy obesity (MUO) phenotype. Individuals with MHO appear to have a better adipose tissue function, and are more insulin sensitive, emphasizing the central role of adipose tissue function in metabolic health. The reported prevalence of MHO varies widely, and this is likely due the lack of universally accepted criteria for the definition of metabolic health and obesity. Also, the natural course and the prognostic value of MHO is hotly debated but it appears that it likely evolves towards MUO, carrying an increased risk for cardiovascular disease and mortality over time. Understanding the pathophysiology and the determinants of metabolic health in obesity will allow a better definition of the MHO phenotype. Furthermore, stratification of obese subjects, based on metabolic health status, will be useful to identify high-risk individuals or subgroups and to optimize prevention and treatment strategies to compact cardio-metabolic diseases.

Risk of type 2 diabetes in metabolically healthy people in different categories of body mass index: an updated network meta-analysis of prospective cohort studies.

Introduction: Risk of diabetes mellitus type 2 (T2DM) is variable between individuals due to different metabolic phenotypes. In present network meta-analysis, we aimed to evaluate the risk of T2DM related with current definitions of metabolic health in different body mass index (BMI) categories. Methods: Relevant articles were collected by systematically searching PubMed and Scopus databases up to 20 March 2018 and for analyses we used a random-effects model. Nineteen prospective cohort studies were included in the analyses and metabolically healthy normal weight (MHNW) was considered as the reference group in direct comparison for calculating indirect comparisons in difference type of BMI categories. Results: Total of 199403 participants and 10388 cases from 19 cohort studies, were included in our network meta-analysis. Metabolically unhealthy obesity (MUHO) group poses highest risk for T2DM development with 10 times higher risk when is compared with MHNW (10.46 95% CI; 8.30, 13.18) and after that Metabolically unhealthy overweight (MUOW) individuals were at highest risk of T2DM with 7 times higher risk comparing with MHNW (7.25, 95% CI; 5.49, 9.57). Metabolically healthy overweight and obese (MHOW/MHO) individuals have (1.77, 95% CI; 1.33, 2.35) and (3.00, 95% CI; 2.33, 3.85) risk ratio for T2DM development in comparison with MHNW respectively. Conclusion: In conclusion we found that being classified as overweight and obese increased the risk of T2DM in comparison with normal weight. In addition, metabolically unhealthy (MUH) individuals are at higher risk of T2DM in all categories of BMI compared with metabolically healthy individuals.

Early determinants of metabolically healthy obesity in young adults: study of the Northern Finland Birth Cohort 1966.

A body of literature suggests a metabolically healthy phenotype in individuals with obesity. Despite important clinical implications, the early origins of metabolically healthy obesity (MHO) have received little attention. To assess the prevalence of MHO among the Northern Finland Birth Cohort 1966 (NFBC1966) at 31 years of age, examine its determinants in early life taking into account the sex specificity. We studied 3205 term-born cohort participants with data available for cardio-metabolic health outcomes at 31 years, and longitudinal height and weight data. After stratifying the population by sex, adult BMI and a strict definition of metabolic health (i.e., no risk factors meaning metabolic health), we obtained six groups. Repeated childhood height and weight measures were used to model early growth and early adiposity phenotypes. We employed marginal means adjusted for mother and child covariates including socio-economic status, birth weight and gestational-age, to compare differences between the groups. The prevalence of adult MHO was 6% in men and 13.5% in women. Differences in adult metabolic status were linked to alterations in BMI and age at adiposity peak in infancy (p < 0.0003 in men and p = 0.027 in women), and BMI and age at adiposity rebound (AR) (p < 0.0001 irrespective of sex). Compared to MHO, metabolically unhealthy obese (MUO) women were five and a half months younger at AR (p = 0.007) with a higher BMI while MUO men were four months older (p = 0.036) with no difference in BMI at AR. At the time of AR, MHO women appeared to be older than their MUO counterparts while MHO men were younger. These original results support potential risk factors at the time of adiposity rebound linked to metabolic health in adulthood. These variations by sex warrant independent replication.

Physical Activity and Sedentary Time Associations with Metabolic Health Across Weight Statuses in Children and Adolescents

The aim of this study was to examine the prevalence of metabolic health across weight statuses and the associations of physical activity and sedentary time within and across metabolic health-weight status groups. Six studies (n = 4,581) from the International Children's Accelerometry Database were used. Sedentary time, light physical activity, and moderate to vigorous physical activity (MVPA) were accelerometer derived. Individuals were classified with normal weight (NW), overweight, or obesity. Strict and lenient composite definitions of metabolic health were created. Binomial and multinomial logistic regressions controlling for age, sex, study, and accelerometer wear time were conducted. The metabolically unhealthy (MU) prevalence was 26.4% and 45.6% based on two definitions. Across definitions, more sedentary time was associated with higher odds of MU classification compared with metabolically healthy (MH) classification for the NW group. More MVPA was associated with lower odds of MU classification than MH classification for NW and overweight groups. For multinomial logistic regressions, more MVPA was associated with lower odds of MH-obesity classification, as well as MU-NW, -overweight, and -obesity classifications, compared with the MH-NW group. Furthermore, more sedentary time was associated with higher odds of MU-NW classification compared with the MH-NW group. More MVPA was beneficial for metabolic health and weight status, whereas lower sedentary time was beneficial for metabolic health alone, although associations were weak.

Risk of incident hypertension according to metabolic health and obesity: Definition of metabolic health does not matter

Risk of incident hypertension according to metabolic health and obesity: Definition of metabolic health does not matter

The association of incident hypertension with metabolic health and obesity status: definition of metabolic health does not matter.

Metabolically healthy obese (MHO) phenotype refers to obese individuals with a favourable metabolic profile. Its prognostic value remains controversial and may partly depend on differences in how the phenotype is defined. We aimed to investigate whether the MHO phenotype is associated with future development of incident hypertension in a Korean population according to various definitions of metabolic health. The study population comprised 31 033 Koreans without hypertension. Participants were stratified into metabolically healthy nonobese (MHNO), metabolically unhealthy nonobese (MUNO), metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO) by body mass index (cut-off value, 25·0 kg/m(2) ) and metabolic health state, using four different definitions: Adult Treatment Panel (ATP)-III, Wildman, Karelis and the homoeostasis model assessment (HOMA) criteria. Over the median follow-up period of 35·0 months (range, 4·5-81·4 months), 4589 of the 31 033 individuals (14·8%) developed incident hypertension. Compared with the MHNO group, the MHO group showed increased association with incident hypertension with multivariate-adjusted odds ratios of 1·56 (95% confidence interval [CI], 1·41-1·72), 1·58 (95% CI 1·42-1·75), 1·52 (95% CI 1·35-1·71) and 1·46 (95% CI 1·33-1·61), when defined by ATP-III, Wildman, Karelis and HOMA criteria, respectively. MUO individuals showed the highest association with the incident hypertension (adjusted odds ratios up to 2·00). MHO subjects showed an approximately 1·5-fold higher association with incident hypertension than their nonobese counterpart regardless of the definition of metabolic health used. Thus, considering both metabolic health and obesity is important for the assessment of potential cardiovascular outcomes.

Abstract 13300: The Risk of Incident Hypertension According to the Metabolic Health and Obesity: Definition of Metabolic Health Does Not Matter

Background: Obesity is considered to be an important risk factor for hypertension. The metabolically healthy obese (MHO) phenotype refers to obese individuals with a favorable metabolic profile. Its prognostic value remains controversial and may partly depend on differences in defining methods. We examined the risk of MHO phenotype with incident hypertension in a Korean population using four representative criteria to define metabolic health status. Design and methods: The study population comprised of 31,033 Koreans without hypertension. Participants were stratified by body mass index (BMI) (cut-off value, 25.0 kg/m2) and metabolic health state, according to four defining methods; Adult Treatment Panel (ATP)-III criteria, Wildman criteria, Karelis criteria, and Homeostasis Model Assessment (HOMA) criteria. Results: Over the median follow-up period of 35.0 months (range, 4.5-81.4 months), 4,589 of the 31,033 individuals (14.8%) developed incident hypertension. Compared with the metabolically healthy nonobese (MHNO) group, the MHO group showed increased risk of incident hypertension with a multivariate-adjusted hazard ratio (HR) of 1.42 (95% confidence interval [CI], 1.30-1.54), 1.43 (95% CI 1.31-1.57), 1.41 (95% CI 1.27-1.56), and 1.33 (95% CI 1.23-1.45), when defined by ATP-III criteria, Wildman criteria, Karelis criteria, and HOMA criteria, respectively. Metabolically unhealthy obese (MUO) individuals were at the highest risk of incident hypertension. Conclusions: MHO subjects showed a substantially higher risk of incident hypertension regardless of the definition for metabolic health. Thus, it is important to consider both metabolic health and obesity when evaluating risk of hypertension.

Definitions of Metabolic Health and Risk of Future Type 2 Diabetes in BMI Categories: A Systematic Review and Network Meta-analysis.

Various definitions of metabolic health have been proposed to explain differences in the risk of type 2 diabetes within BMI categories. The goal of this study was to assess their predictive relevance. We performed systematic searches of MEDLINE records for prospective cohort studies of type 2 diabetes risk in categories of BMI and metabolic health. In a two-stage meta-analysis, relative risks (RRs) specific to each BMI category were derived by network meta-analysis and the resulting RRs of each study were pooled using random-effects models. Hierarchical summary receiver operating characteristic curves were used to assess predictive performance. In a meta-analysis of 140,845 participants and 5,963 incident cases of type 2 diabetes from 14 cohort studies, classification as metabolically unhealthy was associated with higher RR of diabetes in all BMI categories (lean RR compared with healthy individuals 4.0 [95% CI 3.0-5.1], overweight 3.4 [2.8-4.3], and obese 2.5 [2.1-3.0]). Metabolically healthy obese individuals had a high absolute risk of type 2 diabetes (10-year cumulative incidence 3.1% [95% CI 2.6-3.5]). Current binary definitions of metabolic health had high specificity (pooled estimate 0.88 [95% CI 0.84-0.91]) but low sensitivity (0.40 [0.31-0.49]) in lean individuals and satisfactory sensitivity (0.81 [0.76-0.86]) but low specificity (0.42 [0.35-0.49]) in obese individuals. However, positive (<3.3 in all BMI categories) and negative (>0.4) likelihood ratios were consistent with insignificant to small improvements in prediction. Although individuals classified as metabolically unhealthy have a higher RR of type 2 diabetes compared with individuals classified as healthy in all BMI categories, current binary definitions of metabolic health have limited relevance to the prediction of future type 2 diabetes.

Changes in Metabolic Health Status Over Time and Risk of Developing Type 2 Diabetes: A Prospective Cohort Study.

Metabolic health and obesity are not stable conditions, and changes in the status of these conditions might lead to different clinical outcomes. We aimed to determine whether changes in metabolic health status or obesity over time have any effect on the risk of future diabetes. Nondiabetic individuals (n = 2692) from a population-based prospective cohort study with baseline and 2 follow-up examinations at 4-year intervals were included. Being "metabolically obese" (MO) was defined as being in the highest quartile of the TyG index (ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]), whereas falling into the lower 3 quartiles was regarded as being "metabolically healthy" (MH). Individuals were classified as "obese" (O) or "nonobese" (NO) using a body mass index of 25 kg/m2 as a cut-off. The risk of diabetes at year 8 was assessed according to changes of metabolic health status between year 0 and 4. Multivariate-adjusted relative risks (RRs) (95% confidence interval [CI]) of diabetes were significantly higher in individuals who retained the MONO phenotype (RR 3.72, 95% CI 2.10, 6.60) or who had progressed to MONO from the MHNO phenotype (RR 1.96, 95% CI 1.06, 3.61), whereas it was not significant in individuals who had improved to MHNO from the MONO phenotype (RR 0.67, 95% CI 0.26, 1.74) compared with individuals who retained the MHNO phenotype. In contrast, obese individuals had significantly higher RRs for diabetes, independent of changes in metabolic health status, whereas weight reduction resulted in a decreased risk of diabetes. Sensitivity analysis using the presence or absence of the metabolic syndrome as a definition of metabolic health revealed similar results. Changes in metabolic health status were an independent risk factor for future diabetes in nonobese individuals, whereas general obesity had a greater contribution to the risk of obese individuals developing diabetes. These observations might imply a different intervention strategy for diabetes prevention according to obesity status.