Metabolically Healthy Non-obese Research Articles

Metabolically healthy obesity is associated with higher risk of both hyperfiltration and mildly reduced estimated glomerular filtration rate: the role of serum uric acid in a cross-sectional study

BackgroundThe impact of metabolically healthy obesity (MHO) on kidney dysfunction remains debatable. Moreover, few studies have focused on the early stages of kidney dysfunction indicated by hyperfiltration and mildly reduced eGFR. Thus, we aimed to investigate the association between the MHO and early kidney dysfunction, which is represented by hyperfiltration and mildly reduced estimated glomerular filtration rate (eGFR), and to further explore whether serum uric acid affects this association.MethodsThis cross-sectional study enrolled 1188 residents aged ≥ 40 years old from Yonghong Communities. Metabolically healthy phenotypes were categorized based on Adult Treatment Panel III criteria. Obesity was defined as body mass index (BMI) ≥ 25 kg/m2. Mildly reduced eGFR was defined as being in the range 60 < eGFR ≤ 90 ml/min/1.73m2. Hyperfiltration was defined as eGFR > 95th percentile after adjusting for sex, age, weight, and height.ResultsOverall, MHO accounted for 12.8% of total participants and 24.6% of obese participants. Compared to metabolically healthy non-obesity (MHNO), MHO was significantly associated with an increased risk of mildly reduced eGFR (odds ratio [OR] = 1.85, 95% confidence interval [CI] 1.13–3.01) and hyperfiltration (OR = 2.28, 95% CI 1.03–5.09). However, upon further adjusting for uric acid, the association between the MHO phenotype and mildly reduced eGFR was reduced to null. Compared with MHNO/non-hyperuricemia, MHO/non-hyperuricemia was associated with an increased risk of mildly reduced eGFR (OR = 2.04, 95% CI 1.17–3.58), whereas MHO/hyperuricemia was associated with an observably increased risk (OR = 3.07, 95% CI 1.34–7.01).ConclusionsMHO was associated with an increased risk of early kidney dysfunction, and the serum uric acid partially mediated this association. Further prospective studies are warranted to clarify the causality.

All-cause mortality risk with different metabolic abdominal obesity phenotypes: the Rural Chinese Cohort Study.

We aimed to investigate the association of metabolic obesity phenotypes with all-cause mortality risk in a rural Chinese population. This prospective cohort study enrolled 15704 Chinese adults (38·86 % men) with a median age of 51·00 (interquartile range: 41·00-60·00) at baseline (2007-2008) and followed up during 2013-2014. Obesity was defined by waist circumference (WC: ≥ 90 cm for men and ≥ 80 cm for women) or waist-to-height ratio (WHtR: ≥ 0·5). The hazard ratio (HR) and 95 % CI for the risk of all-cause mortality related to metabolic obesity phenotypes were calculated using the Cox hazards regression model. During a median follow-up of 6·01 years, 864 deaths were identified. When obesity was defined by WC, the prevalence of participants with metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO) and metabolically unhealthy obesity (MUO) at baseline was 12·12 %, 2·80 %, 41·93 % and 43·15 %, respectively. After adjusting for age, sex, alcohol drinking, smoking, physical activity and education, the risk of all-cause mortality was higher with both MUNO (HR = 1·20, 95 % CI 1·14, 1·26) and MUO (HR = 1·20, 95 % CI 1·13, 1·27) v. MHNO, but the risk was not statistically significant with MHO (HR = 0·99, 95 % CI 0·89, 1·10). This result remained consistent when stratified by sex. Defining obesity by WHtR gave similar results. MHO does not suggest a greater risk of all-cause mortality compared to MHNO, but participants with metabolic abnormality, with or without obesity, have a higher risk of all-cause mortality. These results should be cautiously interpreted as the representation of MHO is small.

Association of metabolically healthy obesity in young adulthood with myocardial structure and function.

Obesity is major cause of cardiovascular diseases. Metabolically healthy obesity (MHO) may increase heart failure risk early in life, and may be reflected in impaired cardiac structure and function. Therefore, we aimed to examine the relationship between MHO in young adulthood and cardiac structure and function. A total of 3066 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study were included, who completed echocardiography in young adulthood and middle age. The participants were grouped by obesity status (body mass index ≥30 kg/m2) and poor metabolic health (≥2 criteria for metabolic syndrome) into four metabolic phenotypes as follows: metabolically healthy non-obesity (MHN), MHO, metabolically unhealthy non-obesity (MUN), metabolically unhealthy obesity (MUO). The associations of the metabolic phenotypes (MHN serving as the reference) with left ventricular (LV) structure and function were evaluated using multiple linear regression models. At baseline, mean age was 25 years, 56.4% were women, and 44.7% were black. After a follow-up 25 years, MUN in young adulthood was associated with worse LV diastolic function (E/é ratio, β [95% CI], 0.73 [0.18, 1.28]), worse systolic function (global longitudinal strain [GLS], 0.60 [0.08, 1.12]) in comparison with MHN. MHO and MUO were associated with LV hypertrophy (LV mass index, 7.49 g/m2 [4.63, 10.35]; 18.23 g/m2 [12.47, 23.99], respectively), worse diastolic function (E/é ratio, 0.67 [0.31, 1.02]; 1.47 [0.79, 2.14], respectively), and worse systolic function (GLS, 0.72 [0.38, 1.06]; 1.35 [0.64, 2.05], respectively) in comparison with MHN. These results were consistent in several sensitivity analyses. In this community-based cohort using data from the CARDIA study, obesity in young adulthood was significantly associated with LV hypertrophy, worse systolic and diastolic function regardless of metabolic status. Relationship of Baseline Metabolic Phenotypes with Young Adulthood and Midlife Cardiac Structure and Function. Adjusted for year 0 covariates: age, sex, race, educational level, smoking status, drinking status, and physical activity; metabolically healthy non-obesity was used as a reference category for comparison. † Criteria for metabolic syndrome are listed in Supplementary Table S6. MUN metabolically unhealthy non-obesity, MHO metabolically healthy obesity, LVMi left ventricular mass index, LVEF left ventricular ejection fraction, E/A early to late peak diastolic mitral flow velocity ratio, E/é mitral inflow velocity to early diastolic mitral annular velocity, CI confidence interval.

Association between metabolic obesity phenotypes and multiple myeloma hospitalization burden: A national retrospective study.

Obesity and metabolic disorders were associated with increased risk of MM, a disease characterized by high risk of relapsing and require frequent hospitalizations. In this study, we conducted a retrospective cohort study to explore the association of metabolic obesity phenotypes with the readmission risk of MM. We analyzed 34,852 patients diagnosed with MM from the Nationwide Readmissions Database (NRD), a nationally representative database from US. Hospitalization diagnosis of patients were obtained using ICD-10 diagnosis codes. According to obesity and metabolic status, the population was divided into four phenotypes: metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). The patients with different phenotypes were observed for hospital readmission at days 30-day, 60-day, 90-day and 180-day. Multivariate cox regression model was used to estimate the relationship between obesity metabolic phenotypes and readmissions risk. There were 5,400 (15.5%), 7,255 (22.4%), 8,025 (27.0%) and 7,839 (35.6%) unplanned readmissions within 30-day, 60-day, 90-day and 180-day follow-up, respectively. For 90-day and 180-day follow-up, compared with patients with the MHNO phenotype, those with metabolic unhealthy phenotypes MUNO (90-day: P = 0.004; 180-day: P = < 0.001) and MUO (90-day: P = 0.049; 180-day: P = 0.004) showed higher risk of readmission, while patients with only obesity phenotypes MHO (90-day: P = 0.170; 180-day: P = 0.090) experienced no higher risk. However, similar associations were not observed for 30-day and 60-day. Further analysis in 90-day follow-up revealed that, readmission risk elevated with the increase of the combined factor numbers, with aHR of 1.068 (CI: 1.002-1.137, P = 0.043, with one metabolic risk factor), 1.109 (CI: 1.038-1.184, P = 0.002, with two metabolic risk factors) and 1.125 (95% CI: 1.04-1.216, P = 0.003, with three metabolic risk factors), respectively. Metabolic disorders, rather than obesity, were independently associated with higher readmission risk in patients with MM, whereas the risk elevated with the increase of the number of combined metabolic factors. However, the effect of metabolic disorders on MM readmission seems to be time-dependent. For MM patient combined with metabolic disorders, more attention should be paid to advance directives to reduce readmission rate and hospitalization burden.

Association between Metabolic Obesity Phenotypes and the Burden of Hospitalized Postmenopausal Patients Concomitant with Osteoporosis: A Retrospective Cohort Study Based on the National Readmission Database.

The present definition of obesity based on body mass index (BMI) is not accurate and effective enough to identify hospitalized patients with a heavier burden, especially for postmenopausal hospitalized patients concomitant with osteoporosis. The link between common concomitant disorders of major chronic diseases such as osteoporosis, obesity, and metabolic syndrome (MS) remains unclear. Here, we aim to evaluate the impact of different metabolic obesity phenotypes on the burden of postmenopausal hospitalized patients concomitant with osteoporosis in view of unplanned readmissions. Data was acquired from the National Readmission Database 2018. The study population was classified into metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO) patients. We estimated the associations between metabolic obesity phenotypes and 30- and 90-day unplanned readmissions. A multivariate Cox Proportional Hazards (PH) model was used to assess the effect of factors on endpoints, with results expressed as HR and 95% CI. The 30-day and 90-day readmission rates for the MUNO and MUO phenotypes were higher than that of the MHNO group (all p < 0.05), whereas no significant difference was found between the MHNO and MHO groups. For 30-day readmissions, MUNO raised the risk mildly (hazard ratio [HR] = 1.110, p < 0.001), MHO had a higher risk (HR = 1.145, p = 0.002), and MUO further elevated this risk (HR = 1.238, p < 0.001). As for 90-day readmissions, both MUNO and MHO raised the risk slightly (HR = 1.134, p < 0.001; HR = 1.093, p = 0.014, respectively), and MUO had the highest risk (HR = 1.263, p < 0.001). Metabolic abnormalities were associated with elevated rates and risks of 30- or 90-day readmission among postmenopausal hospitalized women complicated with osteoporosis, whereas obesity did not seem to be innocent, and the combination of these factors led to an additional burden on healthcare systems and individuals. These findings indicate that clinicians and researchers should focus not only on weight management but also metabolism intervention among patients with postmenopausal osteoporosis.

Differences in the Impact of Obesity and Metabolic Unhealthiness on the Risk of Gallbladder Polyp.

Differences in the impact of obesity and metabolic health status on the risk of gallbladder polyp (GBP) remain uncertain. Herein, we aimed to compare the risk of GBP ≥5 mm among individuals with different phenotypes based on obesity and metabolic health status. A cohort of 253485 asymptomatic adults who underwent abdominal ultrasonography screening were categorized into the following four groups according to obesity and metabolic health status: 1) metabolically healthy non-obese (MHNO), 2) metabolically unhealthy and non-obese (MUNO), 3) metabolically healthy but obese (MHO), and 4) metabolically unhealthy obese (MUO). The prevalences of GBP ≥5 mm were 2.4%, 3.1%, 3.7%, and 4.0% in the MHNO, MUNO, MHO, and MUO groups, respectively. The multivariable-adjusted odds ratio (OR) values for prevalence of GBP ≥5 mm by comparing the MUNO, MHO, and MUO with the MHNO group were 1.11 [95% confidence interval (CI), 1.04-1.19], 1.30 (95% CI, 1.15-1.47), and 1.37 (95% CI, 1.28-1.45), respectively. The risk of GBP ≥5 mm in the MHO group was significantly higher than that in the MUNO group, but not significantly different from that in the MUO group. Obesity and metabolic unhealthiness appear to be independent risk factors for the prevalence of GBP, and the impact of obesity is greater than that of metabolic unhealthiness, suggesting that maintaining both normal weight and metabolic health may help reduce the risk of GBP.

Metabolically Healthy Obesity and Carotid Plaque among Steelworkers in North China: The Role of Inflammation.

This study aimed to investigate the association between metabolically healthy obesity (MHO) and carotid plaque. In this cross-sectional survey, 3467 steelworkers in North China were surveyed. There are two criteria for defining a carotid plaque: (1) the lesion structure exceeds 50% of the peripheral intima-media thickness value or invades the arterial lumen by at least 0.5 mm; (2) a thickness > 1.5 mm from the intima−lumen interface to the media−adventitia interface. Metabolic health was defined as the nonexistence of one of the metabolic syndrome (MetS) diagnostic criteria for metabolic abnormalities. Obesity was defined as having a BMI ≥ 25 kg/m2. To calculate the odds ratio (OR) for the prevalence carotid plaque, a logistic regression was used for the analysis. The prevalence of carotid plaque in the subjects was 14.3% for metabolically healthy non-obesity (MHNO), 32.4% for MHO, 18.9% for metabolically unhealthy non-obesity (MUNO), and 46.8% for metabolically unhealthy obesity (MUO). The odds ratios for suffering from carotid plaque were 1.27 (95% CI: 0.69 to 2.32) for MHO, 1.83 (95% CI: 1.29 to 2.58) for MUNO, and 1.81 (1.28 to 2.56) for MUO in comparison with MHNO after adjusting for confounders. There was no association between the MHO phenotype and carotid plaque prevalence among steelworkers in North China.

Abstract 13938: Metabolically Healthy Obese and Incident Coronary Heart Disease in Adult Cancer Survivors

Introduction: There is a paucity of data on the combined association of metabolic health status and obesity with coronary heart disease (CHD) in adult cancer survivors who are at excess risk of CHD associated with potentially harmful side effects from some cancer therapies. Long-term cardiovascular health among adult cancer survivors who are metabolically healthy obese (MHO), metabolically unhealthy non-obese (MUN), and metabolically unhealthy obese (MUO) as compared to those who are metabolically healthy non-obese (MHN) remains uncertain. Hypothesis: The hypothesis of this study was that adult cancer survivors who are MHO, MUN, MUO would have higher risk of CHD as compared to those who are MHN. Methods: Data on metabolic health status and incident CHD among adult cancer survivors (n=2,336) were abstracted from the National Health Insurance Service-Health Screening Cohort, 2002-2019 along with information on confounding variables (sociodemographic factors, health status, health behavior, and family history of heart disease). Obesity was defined as body mass index≥25.0 kg/m 2 and the participants were considered metabolically unhealthy if they met more than three out of the five (fasting serum glucose, blood pressure, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol) criteria for worsened metabolic health. Cox proportional hazards model adjusted for the confounding variables was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) for incident CHD according to the metabolic health and obesity categories. Results: Among adult cancer survivors, those who are MHO (HR=2.80; 95% CI: 1.65-4.76), MUN (HR=2.58; 95%: 1.12-5.97), and MUO (HR=4.88; 95% CI: 2.27-10.5) had higher risk of incident CHD as compared to those who are MHN. Conclusions: Adult cancer survivors who are MHO should also be of a clinical concern. Excess body weight and metabolic health status should be concurrently managed to reduce the risk of developing CHD among adult cancer survivors.

Association between obese phenotypes and risk of carotid artery plaque among chinese male railway drivers

BackgroundChina has the world’s highest rail transportation network density, and the prevalence of obesity among railway workers in China is more than twice that of adults in the world. Carotid artery plaque (CAP) is a simple and noninvasive predictor of early atherosclerosis, while the association between different obese phenotypes and CAP risk among Chinese male railway drivers is unclear.MethodsThis cross-sectional study was performed among 8,645 Chinese male railway drivers. Obese phenotypes were assessed based on the obesity status (the body mass index ≥ 28 kg/m2 as obesity vs. < 28 kg/m2 as non-obesity) and metabolic status (metabolically healthy vs. metabolically unhealthy). Metabolically unhealthy was defined as the presence of at least one dysfunction, including elevated blood pressure, elevated fasting blood glucose, elevated triglyceride, and reduced high-density-lipoprotein cholesterol. Four obese phenotypes were defined based on the body mass index and metabolic status, i.e., metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy obesity (MUO), and metabolically unhealthy non-obesity (MUNO). Multivariable logistic regression was employed to estimate the association between different obese phenotypes and the risk of CAP. Subgroup analysis was performed to examine the variation of the association by age, circadian rhythm disorders, and history of smoking and drinking.ResultsThe prevalence of CAP among male railway drivers in MHO, MUO, MUNO, and MHNO was 8.75%, 18.67%, 17.82%, and 5.36%, respectively. Compared to those with MHNO, an increased risk for CAP was observed among those with MHO (OR = 2.18, 95% CI: 0.82, 5.10), MUO (OR = 1.78, 95% CI:1.44, 2.21), and MUNO (OR = 2.20, 95% CI: 1.67, 2.89). The subgroup analysis showed that both of the metabolically unhealthy groups (MUNO and MUO) aged < 45 years were prone to a higher risk of CAP (for the MUNO group, OR = 4.27, 95% CI:2.71, 7.10; for the MUO group, OR = 4.00, 95%CI: 2.26, 7.17).ConclusionThe obese phenotypes are associated with CAP risk in male railway drivers, especially those with metabolically unhealthy conditions aged < 45 years.

Prognostically distinct phenotypes of metabolic health beyond obesity in aortic stenosis

Abstract Background Whilst current evidence are in favour of metabolic health and non-obesity in the reduction of incident cardiovascular disease, little is known regarding the prognosis across the metabolic phenotypes once cardiovascular disease occurs. This study examined the prognosis of patients with significant aortic stenosis (AS) based on the presence of metabolic health and obesity. Methods This retrospective cohort on consecutive patients presenting with moderate-to-severe AS to a tertiary hospital between 2010 and 2015. Patients were allocated into 4 groups based on obesity and metabolic health: metabolically healthy obese (MHO), metabolically healthy non-obese (MHNO), metabolically unhealthy obese (MUO) and metabolically unhealthy non-obese (MUNO). Metabolic health was defined in accordance to Program Adult Treatment Panel III criteria. The primary outcome was all-cause mortality. Cox regression examined independent associations between mortality and metabolic phenotypes, adjusting for aortic valve area, ejection fraction, age, sex, chronic kidney disease and AVR as a time-dependent covariate. Results Of 727 patients, the majority (51.6%) were MUNO, followed by MUO (32.7%), MHNO (11.4%), and MHO (4.3%). MHNO had the highest mortality (43.0%), followed by the MUNO (37.5%), MUO (30.0%) and MHO (6.9%) groups (p=0.001). Compared to MHNO, MHO (HR 0.159, 95% CI 0.038–0.668, p=0.012) and MUO (HR 0.614, 95% CI 0.403–0.937, p=0.024) were independently associated with lower all-cause mortality rates, after adjusting for confounders. In obese patients, metabolic health had favourable survival compared to metabolically unhealthy (p=0.015), but this protective impact of metabolic health was not observed in overweight or normal weight individuals. Obesity had favourable survival compared to overweight and normal weight, in both metabolically health (p=0.002) and unhealthy (p=0.007) patients, Conclusion MHO patients with AS have the most favourable prognosis whilst the seemingly healthy MHNO group had the worst survival. There should be a paradigm shift towards prioritising metabolic health rather than weight reduction in patients with significant AS. Funding Acknowledgement Type of funding sources: None.

The prognostic outcomes of acute myocardial infarction stratified according to metabolic health and obesity status

Abstract Background There has been emerging evidence on the favourable cardiovascular disease incidence in non-obese subjects with healthy metabolism. However, little is known regarding the prognosis across the metabolic phenotypes once cardiovascular disease is established. This study examines the prognosis of patients with acute myocardial infarction (AMI) stratified according to metabolic health and obesity status. Methods A retrospective study conducted in a tertiary hospital between 2014–2021. Consecutive patients with AMI were allocated into 4 groups based on metabolic and obesity profile: metabolically healthy obesity (MHO), metabolically healthy non-obesity (MHNO), metabolically unhealthy obesity (MUO) and metabolically unhealthy non-obesity (MUNO). The primary outcome was all-cause mortality. Cox regression examined the independent association between mortality and metabolic phenotypes, adjusting for age, sex, AMI type and ejection fraction. Results A total of 9958 patients were studied with majority (68.5%) in the MUNO group, followed by MUO (25.1%), MHNO (5.6%), and MHO (0.8%). MHO patients had lowest mortality (7.4%), followed by MHNO (9.7%), MUO (19.2%) and MUNO (22.6%, p&amp;lt;0.001). Relative to MHNO, MUO (HR 1.610, 95% CI 1.198–2.163, p=0.002) and MUNO (HR 1.383, 95% CI 1.043–1.835, p=0.024) had significantly higher mortality risk, but not MHO (HR 1.514, 95% CI 0.649–3.534, p=0.337), after adjusting for confounders. Kaplan-Meier curves showed favourable survival in metabolically healthy groups with clear divergence from metabolically unhealthy groups (p&amp;lt;0.001). There were stepwise increments in mortality with increasing number of metabolic risk factors regardless of obesity status (p&amp;lt;0.001). Favourable survival was observed in overweight and obese versus normal weight patients regardless of metabolic health. Conclusion Metabolically healthy AMI patients had favourable prognosis compared to metabolically unhealthy patients. The obesity paradox was observed in the AMI cohort, but the beneficial effects of obesity appeared not as pronounced in magnitude as in metabolically healthy groups. Funding Acknowledgement Type of funding sources: None.

Metabolic phenotypes and incident type 2 diabetes: Population-based Panasonic cohort study 6.

This study aimed to assess the association between changes in metabolic phenotypes and incident type 2 diabetes. This retrospective cohort study included participants from a medical health checkup program conducted by the Panasonic Corporation, Japan, between 2008 and 2018. The metabolic phenotypes of the participants in 2008 and 2013 were assessed. The association between changes in metabolic phenotypes from 2008 to 2013 and incident type 2 diabetes (n=58,638) were evaluated for a 5-year follow-up using Cox regression analyses. The stable, metabolically healthy obesity group was associated with a higher risk of incident type 2 diabetes than the stable, metabolically healthy nonobesity (MHNO) group (hazard ratio [HR] 3.22, 95% CI: 2.71-3.83). When participants with metabolically healthy obesityexperienced a change to MHNO, their risk of incident type 2 diabetes was similar to that of participants in the stable MHNO group (HR 1.28, 95% CI: 0.78-1.90). Once the participants had metabolic abnormalities, the risk of incident type 2 diabetes was higher than that in the stable MHNO group, even after undergoing a change to MHNO. This study demonstrates that it is important to pay attention to the changes in metabolic phenotypes to prevent incident type 2 diabetes in Japanese populations.

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.

Prognostically Distinct Phenotypes of Metabolic Health Beyond Obesity in Aortic Stenosis

Although current evidence is in favor of metabolic health and nonobesity in the reduction of incident cardiovascular disease, little is known regarding the prognosis across the metabolic phenotypes once cardiovascular disease occurs. This study examined the prognosis of patients with significant aortic stenosis (AS) on the basis of the presence of metabolic health and obesity. This a retrospective cohort study on consecutive patients who presented with moderate-to-severe AS to a tertiary hospital between 2010 and 2015. Patients were allocated into 4 groups on the basis of obesity and metabolic health: metabolically healthy obese (MHO), metabolically healthy nonobese (MHNO), metabolically unhealthy obese (MUO), and metabolically unhealthy nonobese (MUNO). Metabolic health was defined in accordance to the Adult Treatment Panel III criteria. The primary outcome was all-cause mortality. Cox regression examined independent associations between mortality and metabolic phenotypes, adjusting for aortic valve area, ejection fraction, age, gender, chronic kidney disease, and aortic valve replacement as a time-dependent covariate. Of 727 patients, the majority (51.6%) were MUNO, followed by MUO (32.7%), MHNO (11.4%), and MHO (4.3%). MHNO had the highest mortality (43.0%), followed by the MUNO (37.5%), MUO (30.0%), and MHO (6.9%) groups (p=0.001). Compared with MHNO, MHO (hazard ratio 0.159, 95% confidence interval 0.038 to 0.668, p=0.012) and MUO (hazard ratio 0.614, 95% confidence interval 0.403 to 0.937, p=0.024) were independently associated with lower all-cause mortality rates after adjusting for confounders. In patients who are obese, metabolic health had favorable survival compared with metabolically unhealthy (p=0.015), but this protective impact of metabolic health was not observed in patients with overweight or normal weight. Obesity had favorable survival compared with overweight and normal weight in both patients who are metabolically healthy (p=0.002) and unhealthy (p=0.007). In conclusion, patients who are MHO with AS have the most favorable prognosis, whereas the seemingly healthy MHNO group had the worst survival. There should be a paradigm shift toward prioritizing metabolic health rather than weight reduction in patients with significant AS.

Triglyceride-Glucose Index Predicts Cardiovascular Outcome in Metabolically Unhealthy Obese Population: A Nationwide Population-Based Cohort Study.

BackgroundThis study assesses the prognostic value of the triglyceride–glucose (TyG) index for cardiovascular (CV) risk in subgroups based on metabolic health and obesity status.MethodsOriginally, 514,866 participants were enrolled from the Korean National Health Insurance Service-National Health Screening Cohort. The study participants were categorized into four groups: metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). The TyG index was calculated using the following formula: ln (fasting triglyceride [mg/dL]×fasting plasma glucose [mg/dL]/2). Participants were followed from 2009 to 2015 for CV events and CV mortality according to the TyG index.ResultsAfter exclusions, the final study cohort contained 292,206 people. During the follow-up, 9,138 CV events and 1,163 CV deaths were documented. When the high and low TyG groups were compared, the high TyG group had a substantially increased risk of CV events among the MUNO and MUO participants (multivariable-adjusted hazard ratio [HR], 1.18; 95% confidence interval [CI], 1.07–1.30 and 1.27 [1.14–1.42], respectively). In participants with MUO status, CV mortality was also significantly increased in the high TyG group compared with the corresponding low TyG group (multivariable-adjusted HR, 1.48; 95% CI, 1.13–1.93). In contrast, a high TyG index was not related to CV mortality in the MHNO, MHO, and MUNO groups.ConclusionThe predictive value of the TyG index can vary across populations. Among MUO participants, the TyG index was significantly and positively correlated with unfavorable CV outcomes.

Long-Term Prognosis of Acute Myocardial Infarction Associated With Metabolic Health and Obesity Status

ObjectiveEmerging evidence supports the favorable cardiovascular health in nonobese subjects with healthy metabolism. However, little is known regarding the prognosis across the range of metabolic phenotypes once cardiovascular disease is established. We examined the prognosis of patients with acute myocardial infarction (AMI) stratified according to metabolic health and obesity status. MethodsThis is a retrospective study on consecutive patients with AMI admitted to a tertiary hospital between 2014 and 2021. Patients were allocated into the following 4 groups based on metabolic and obesity profile: (1) metabolically healthy obese (MHO), (2) metabolically healthy nonobese (MHNO), (3) metabolically unhealthy obese (MUO), and (4) metabolically unhealthy nonobese (MUNO). Metabolic health was defined in accordance to the Biobank Standardisation and Harmonisation for Research Excellence in the European Union Healthy Obese Project. The primary outcome was all-cause mortality. The Cox regression analysis examined the independent association between mortality and metabolic phenotypes, adjusting for age, sex, AMI type, chronic kidney disease, smoking status, and left ventricular ejection fraction. ResultsOf 9958 patients, the majority (68.5%) were MUNO, followed by MUO (25.1%), MHNO (5.6%), and MHO (0.8%). MHO had the lowest mortality (7.4%), followed by MHNO (9.7%), MUO (19.2%), and MUNO (22.6%) (P < .001). Compared with MHNO, MUO (hazard ratio [HR], 1.737; 95% confidence interval [CI], 1.282-2.355; P < .001) and MUNO (HR, 1.482; 95% CI, 1.108-1.981; P = .008) had a significantly higher mortality risk but not MHO (HR, 1.390; 95% CI, 0.594-3.251; P = .447), after adjusting for confounders. The Kaplan-Meier curves showed favorable survival in the metabolically healthy and obesity groups, with the highest overall survival in the MHO, followed by MHNO, MUO, and MUNO (P < .001). ConclusionMetabolically healthy and obese patients with AMI have favorable prognosis compared with metabolically unhealthy and nonobese patients. It is equally important to prioritize intensive metabolic risk factor management to weight reduction in the early phase after AMI.

Abnormal Obesity Phenotype Is Associated with Reduced eGFR among Diabetes Mellitus and Hypertensive Patients in a Peri-Urban Community in Ghana.

Background Diabetes mellitus (DM) is a chronic disease characterized by hyperglycemia due to obesity and defects in insulin action. Significant complications of DM include kidney disease due to its association with hypertension and obesity. Thus, the contribution of the various obesity phenotypes to the kidney impairment observed among hypertensive and diabetes mellitus patients is of major concern. Aim The study assessed the association between obesity phenotypes and reduced glomerular filtration rate among diabetes mellitus and hypertensive patients. Methods Three hundred and ten (310) adult patients diagnosed with type 2 diabetes mellitus, hypertension, or both who attended the Presbyterian Hospital, Dormaa Ahenkro, from October 2016 to March 2017 were recruited for the study. Blood samples were collected to analyze biochemical parameters (fasting blood glucose (FBG), lipid profile, and creatinine). Questionnaires were used to collect sociodemographic information, and anthropometrics were appropriately measured. The estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI equation, and reduced eGFR was defined as eGFR <90 ml/min/1.73 m2. Results The prevalence of metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically abnormal nonobese (MANO), and metabolically abnormal obese (MAO) phenotypes among the study participants was 30.65%, 4.50%, 52.90%, and 11.94%, respectively. The highest prevalence of reduced eGFR (29/37 (78.38%)) was seen among the MAO group. This was followed by the MANO, MHO, and MHNO with a reduced eGFR prevalence of 62.20%, 57.64%, and 37.89%, respectively. After normalization with MHNO, the reduced eGFR was 1.51, 1.64, and 2.06 times expressed in MHO, MANO, and MAO. For the total samples, when MHNO was maintained as a reference, reduced eGFR was significantly associated with MANO (aOR = 3.07 (95% CI = 1.76–5.35), P < 0.001) and MAO (aOR = 5.67 (95% CI = 2.66–17.27), P < 0.001) even after adjusting for age, gender, smoking, and alcohol intake. This association was maintained among the female study participants when stratified by gender, and in addition, among the female participants, reduced eGFR was also associated with MHO (aOR = 4.19 (95% CI = 1.06–16.53), P=0.041). Conclusion There is a high prevalence of abnormal metabolic phenotypes among diabetes mellitus patients, and these were significantly associated with reduced eGFR among our study participants.

The Relationship Between Obesity and Depression Is Partly Dependent on Metabolic Health Status: A Nationwide Inpatient Sample Database Study.

ObjectiveSome studies have demonstrated a bidirectional association between obesity and depression, whereas others have not. This discordance might be due to the metabolic health status. We aimed to determine whether the relationship between obesity and depression is dependent on metabolic health status.MethodsIn total, 9,022,089 participants were enrolled and classified as one of four obesity phenotypes: metabolically healthy nonobesity (MHNO), metabolically unhealthy nonobesity (MUNO), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). We then divided the population into eight phenotypes based on obesity and the number of metabolic risk factors. Furthermore, the associations of eight phenotypes, based on obesity and specific metabolic risk factors, with depression were assessed.ResultAmong all participants, a higher risk of depression was observed for MUNO, MHO and MUO than for MHNO. The risk was highest for MUO (OR = 1.442; 95% CI = 1.432, 1.451). However, the association between MHO and depression was different for men and women (OR = 0.941, men; OR = 1.132, women). The risk of depression increased as the number of metabolic risk factors increased. Dyslipidemia was the strongest metabolic risk factor. These relationships were consistent among patients ≥ 45 years of age.ConclusionsThe increased risk of obesity-related depression appears to partly depend on metabolic health status. The results highlight the importance of a favorable metabolic status, and even nonobese populations should be screened for metabolic disorders.

Lipoprotein(a) and Cardiovascular Outcomes in Patients With Coronary Artery Disease and Different Metabolic Phenotypes.

BackgroundThe positive relationship between metabolic healthy obesity (MHO) and cardiovascular risk has been under debate in recent years. Previously, strong evidence supported the causal role of increased plasma lipoprotein(a) [Lp(a)] levels in cardiovascular disease (CVD). The current study aimed to investigate the different associations of Lp(a) and cardiovascular events (CVEs) in patients with coronary artery disease (CAD) and different metabolic phenotypes.MethodsA total of 5,089 patients who were angiography-proven CAD were consecutively included and followed up for CVEs. Obesity was defined as a body mass index (BMI) ≥25 kg/m2 according to Asia-specific BMI criteria. Patients were divided into four groups according to metabolic phenotypes, namely metabolically healthy/unhealthy non-obese and metabolically healthy/unhealthy obese [metabolically healthy non-obese (MHN), MHO, metabolically unhealthy non-obese (MUN), and metabolically unhealthy obesity (MUO)]. Comparisons of CAD severity and outcomes were performed among four groups. Cox regression analyses and cubic spline models were used to examine the relationship between Lp(a) and CVEs in patients with different metabolic phenotypes.ResultsDuring a median of 7.5 years’ follow-up, 540 (10.6%) CVEs occurred. MUN and MUO populations had more severe coronary stenosis than MHN ones, while no significant difference in the Gensini score (GS) was observed between MHN and MHO. Patients with MUN and MUO presented a higher risk of CVEs than patients with MHN (hazard ratio [HR]: 1.414, 95% CI: 1.024–1.953–1.556 and HR: 1.747, 95% CI: 1.295–1.363, p < 0.05). In subgroup analysis, restricted cubic spline models showed that there was no association between Lp(a) and CVEs in patients in MHN and MHO, while the MUN and MUO groups presented increasing associations between Lp(a) and CVEs and such association was stronger in the MUO group. In Cox regression analysis, Lp(a) >50 mg/dl was associated with a 2.032- and 2.206-fold higher risk of subsequent CVEs in the MUO and MUN subgroups, respectively.ConclusionAmong patients with angiography-proven stable CAD, Lp(a) had a more significant prognostic value in both MUO and MUN individuals regardless of obesity, suggesting the importance of screening for cardiovascular risk with Lp(a) in metabolically unhealthy patients.

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

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