Metabolic Unhealthiness Research Articles

Impact of metabolic unhealthiness and its changes on the risk of erosive esophagitis: a cohort study.

We aimed to compare the risk of erosive esophagitis (EE) among individuals with different phenotypes based on metabolic health status and obesity and investigate the role of changes in metabolic health in EE risk. A cohort of 258 892 asymptomatic adults without EE at baseline who underwent ollow-up esophagogastroduodenoscopy (EGD) were categorized into the following four groups according to metabolic health and obesity status: (i) metabolically healthy (MH) non-obese; (ii) metabolically unhealthy (MU) non-obese; (iii) MH obese; and (iv) MU obese. EE was defined as the presence of grade A or higher mucosal breaks on EGD. During a median follow-up of 4.5years, the incidence rates of EE were 0.6/103 person-years (PY), 1.7/103 PY, 1.7/103 PY, and 3.1/103 PY in the MH non-obese, MU non-obese, MH obese, and MU obese groups, respectively. The multivariable-adjusted hazard ratio (HR) (95% confidence intervals [CI]) for developing EE comparing the MH obese, MU non-obese, and MU obese groups with the MH non-obese group were 1.49 (1.29-1.71), 1.56 (1.25-1.94), and 2.18 (1.90-2.49), respectively. The multivariable-adjusted HR (95% CI) comparing the progression of MH to MU, regression of MU to MH, and persistent MU with the persistent MH group were 1.39 (1.10-1.76), 1.39 (1.09-1.77), and 1.86 (1.56-2.21), respectively. The increased risk of EE among the persistent MU group was consistently observed in individuals without obesity or abdominal obesity. Metabolic unhealthiness and obesity were independent risk factors for the development of EE, suggesting that maintaining both normal weight and metabolic health may help reduce the risk of EE.

Metabolic Unhealthiness is Associated With Increased Risk of Critical COVID-19 Pneumonia and Inpatient Mortality in Hospitalized Patients with Obesity or Overweight.

Background and aims Being metabolically unhealthy (MU) is defined as having either hypertension, hyperlipidemia, type 2 diabetes mellitus/pre-diabetes, or fatty liver disease. We aimed to determine if MU was associated with severe COVID-19 pneumonia (severe disease). Methods We performed a single-center retrospective study between March 2020 and August 2021 for patients with overweight or obesity hospitalized with COVID-19 pneumonia. Logistic regression analysis was utilized to derive a risk score for severe disease. The accuracy of the model was assessed using the area under the receiver operating characteristic curve (AUROCC) and bootstrap resampling. Results A total of 334 of 450 patients hospitalized with COVID-19 pneumonia (74.2%) were MU. Patients who were MU had higher in-hospital mortality (10.5% vs. 2.6%) and longer length of hospitalization (median 6 vs. 4 days). MU was not associated with severe disease, p=0.311. On multivariable analysis, older age, male sex, and Asian race were associated with severe disease. Not being vaccinated was associated with doubled odds of severe disease. The AUROCC of the final model was 0.66 (95% CI: 0.60 to 0.71). The risk score at the lowest quintile had a 33.1% to 65.5% predicted risk and a 58.7% observed risk of severe disease, whereas, at the highest quintile, there was an 85.7% to 97.7% predicted risk and an 89.7% observed risk of severe disease. Conclusion Being MU was not a predictor of severe disease, even though mortality was higher despite having higher rates of vaccination. This risk score may help to predict severe disease in hospitalized patients with obesity or overweight. External validation is recommended.

Stepwise evaluation for the risk of metabolic unhealthiness and significant non-alcoholic fatty liver disease in India

Non-communicable diseases including metabolic health disorders are becoming area of concern for low/middle income countries with poor health-care resources. Present study was planned to assess the prevalence of metabolically unhealthy (MU) subjects in the community and proportion of the MU subjects having the risk of significant Non-alcoholic Fatty Liver Disease (NAFLD) using a step-wise evaluation strategy in a resource-poor setting. Study was performed in 19 community development blocks of Birbhum district, West Bengal, India. Every fifth member in the electoral list was included for the first step evaluation (n = 79,957/1,019,365, 7.8%) to detect any metabolic risk. Subjects with any metabolic risk in the first step (n = 9819/41,095, 24%) were taken for second step evaluation with Fasting blood glucose (FBG) and ALT. Subjects with elevated FBG and/or ALT in the second step (n = 1403/5283, 27%) were taken into third step evaluation. At least one risk factor was found in 51.4% (n = 41,095/79,957). 63% (n = 885/1403) of the subjects with metabolic abnormality (third step) had MU state making its overall prevalence of 1.1% (n = 885/79,957). 53% of MU subjects (n = 470/885) had ‘persistently elevated ALT’ suggesting the risk of having significant NAFLD. Step-wise evaluation strategy could detect the subjects at risk, actually having MU state and proportion of MU subjects at risk of having ‘persistently elevated ALT’ (surrogate of significant NAFLD) in the community with minimum utilization of scarce resources. This study was funded by Bristol Myers Squibb Foundation, USA, under the program ‘Together on Diabetes Asia’ (Project Number: 1205 – LFWB).

Underestimation of metabolic unhealthiness and overestimation of non-alcoholic fatty liver disease.

Underestimation of metabolic unhealthiness and overestimation of non-alcoholic fatty liver disease.

Effect of metabolic health and obesity on all-cause death and CVD incidence in Korean adults: a retrospective cohort study

This study aimed to investigate the risk of all-cause mortality and incidence of CVD according to metabolic health and body mass index (BMI) in Korean adults. This study was retrospectively designed using the National Health Insurance Service-National Health Screening Cohort data. Participants were divided into six groups according to two category of metabolic syndrome and three categories of BMI. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the composite outcome (all-cause mortality and incidence of CVDs) were estimated using multivariable Cox proportional hazards regression models. 151,706 participants aged ≥ 40 years were enrolled; median follow-up period was 9.7 years in the study. Compared to metabolically healthy normal weight, the fully adjusted HRs (95% CIs) of metabolically healthy overweight, metabolically healthy obese, metabolically unhealthy normal weight, metabolically unhealthy overweight, and metabolically unhealthy obese for composite outcome were 1.07 (1.03–1.12), 1.12 (1.07–1.17), 1.33 (1.25–1.41), 1.28 (1.22–1.34), and 1.31 (1.26–1.37), respectively, in men, and 1.10 (1.05–1.16), 1.22 (1.16–1.29), 1.34 (1.26–1.43), 1.27 (1.19–1.34), and, 1.40 (1.34–1.47), respectively, in women. High BMI and metabolic unhealthiness were associated with an increased risk on the composite of all-cause mortality and incidence of CVD in both sexes.

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.

СООТНОШЕНИЕ ТАЛИИ К РОСТУ – ВАЖНЫЙ АНТРОПОМЕТРИЧЕСКИЙ ДИСКРИМИНАТОР МЕТАБОЛИЧЕСКИХ НАРУШЕНИЙ У ПОДРОСТКОВ С ИЗБЫТОЧНОЙ МАССОЙ ТЕЛА И ОЖИРЕНИЕМ: ПИЛОТНОЕ ИССЛЕДОВАНИЕ

The purpose of the research was to describe the most informative anthropometric indicator for identifying a metabolically unhealthy phenotype in Caucasian adolescents with overweight and obesity. Materials and methods of the research: single-center cross-sectional study. The studies were carried out in Feb. 2015 - Oct. 2016 in the regions Republic of Buryatia and Irkutsk Oblast. At the first stage, the study included data from 1356 adolescents aged from 10 years to 17 years 11 months 29 days old obtained during a dispensary examination: anthropometric examination and determination of the level of blood glycemia. The second stage, which includes lipid profile analysis, calipometry and measurement of circumferential parameters, included adolescents with overweight and obesity, adolescents with a morning glycemia level exceeding 5.6 mmol/l, and adolescents who wished to participate in the study and met the inclusion criteria. A total of 219 children were included in the study: 99 (45.2%) boys (age 13 [12-15]) and 120 (54.8%) girls (age 14 [12-16]). There was no statistically significant age difference between boys and girls (p=0.093). Results: when comparing the analyzed parameters in the group of adolescents with overweight and obesity, but with different metabolic phenotypes, statistically significant differences were revealed: waist circumference (WC)/height ratio - 0.54 [0.50:0.58] in boys without metabolic disorders vs. 0.58 [0.54:0.62] with metabolic disorders (p=0.042); roundness index - 4.08 [3.30:4.92] vs. 4.97 [4.13:5.78], respectively (p=0.042); hip volume - 97.64 [92.25:98.75] versus 99.15 [97.00:99.80], respectively (p=0.040). In girls, a similar pattern of differences in anthropometric parameters in the sample of girls without metabolic disorders and with those: WC/height - 0.52 [0.47:0.59] vs. 0.60 [0.54:0.69] (p=0.012); roundness index 3.78 [2.92:5.13] vs. 1.19 [1.14:1.29] (p=0.039). When comparing anthropometric parameters in adolescents with normal weight, but with different metabolic phenotypes, no statistically significant differences were found. The most informative parameters of the metabolically unhealthy phenotype in both boys and adolescent girls are the WC/height ratio and roundness index. Threshold values for predicting metabolic unhealthiness in boys are WC/height ratios greater than 0.53 (AUC=0.69, 95% Cl=0.54-0.84, sensitivity=0.632, specificity=0.731), roundness index greater than 3.96 (AUC=0.69, 95% Cl=0.54-0.84, sensitivity=0.632, specificity=0.731); in girls -WC/height ratio greater than 0.50 (AUC=0.75, 95% Cl=0.60–0.90, sensitivity=0.833, specificity=0.670), roundness index greater than 3.38 (AUC=0.75, 95 % Cl=0.60-0.90, sensitivity=0.833, specificity=0.670). Both parameters were calculated using WC and height, but the complexity of calculating the roundness index (in the absence of an available Russian-language online calculator) compared to calculating the WC/height ratio makes it difficult to use in clinical practice. Conclusion: the WC/height ratio in both boys and girls is the best indicator in clinical practice for verifying a metabolically unhealthy phenotype in overweight and obese adolescents. The optimal threshold value of this indicator for predicting two or more components of metabolic disorders that are not related to WC is 0.50 in girls and 0.53 in boys.

Relations of Metabolic Health and Obesity to Brain Aging in Young to Middle-Aged Adults.

BackgroundWe aimed to evaluate the association between metabolic health and obesity and brain health measured via magnetic resonance imaging and neurocognitive testing in community dwelling adults.Methods and ResultsFramingham Heart Study Third Generation Cohort members (n=2170, 46±9 years of age, 54% women) without prevalent diabetes, stroke, dementia, or other neurologic conditions were grouped by metabolic unhealthiness (≥2 criteria for metabolic syndrome) and obesity (body mass index ≥30 kg/m2): metabolically healthy (MH) nonobese, MH obese, metabolically unhealthy (MU) nonobese, and MU obese. We evaluated the relationships of these groups with brain structure (magnetic resonance imaging) and function (neurocognitive tests). In multivariable‐adjusted analyses, metabolically unhealthy individuals (MU nonobese and MU obese) had lower total cerebral brain volume compared with the MH nonobese referent group (both P<0.05). Additionally, the MU obese group had greater white matter hyperintensity volume (P=0.004), whereas no association was noted between white matter hyperintensity volume and either groups of metabolic health or obesity alone. Obese individuals had less favorable cognitive scores: MH obese had lower scores on global cognition, Logical Memory‐Delayed Recall and Similarities tests, and MU obese had lower scores on Similarities and Visual Reproductions‐Delayed tests (all P≤0.04). MU and obese groups had higher free water content and lower fractional anisotropy in several brain regions, consistent with loss of white matter integrity.ConclusionsIn this cross‐sectional cohort study of younger to middle‐aged adults, poor metabolic health and obesity were associated with structural and functional evidence of brain aging. Improvement in metabolic health and obesity may present opportunities to improve long‐term brain health.

Association between being metabolically healthy/unhealthy and metabolic syndrome in Iranian adults.

IntroductionThe prevalence of metabolically healthy obesity (MHO) varies based on different criteria. We assessed the prevalence of MHO and metabolic unhealthiness based on body mass index (BMI) and their association with metabolic syndrome (MetS) in a nation-wide study.MethodsData were taken from the STEPs 2016 study, from 18,459 Iranians aged ≥25 years. Demographic, metabolic, and anthropometric data were collected. Subjects were stratified by BMI, metabolic unhealthiness, and having MetS. The latter was defined based on National Cholesterol Education Program Adult Treatment Panel III 2004 (NCEP ATP III), was then assessed.ResultsThe prevalence of MHO and metabolic unhealthiness in obese subjects was 7.5% (about 3.6 million) and 18.3% (about 8.9 million), respectively. Most of the metabolic unhealthy individuals were female (53.5%) or urban residents (72.9%). Low physical activity was significantly and positively associated (Odds Ratio: 1.18, 95% CI: 1.04–1.35) with metabolic unhealthiness, while being a rural residence (0.83, 0.74–0.93), and having higher education (0.47, 0.39–0.58) significantly but negatively affected it. Dyslipidemia was the most frequent MetS component with a prevalence rate of 46.6% (42.1–51.1), 62.2% (60.8–63.6), 76.3% (75.1–77.5), and 83.4% (82.1–84.6) among underweight, normal weight, overweight and obese phenotypes, respectively.ConclusionBMI aside, an additional set of criteria such as metabolic markers should be taken into account to identify normal weight but metabolically unhealthy individuals. Given the highest prevalence of dyslipidemia among obese subjects, further interventions are required to raise public awareness, promote healthy lifestyles and establish lipid clinics.

Stepwise Evaluation for the Risk of Metabolic Unhealthiness and Significant Non-Alcoholic Fatty Liver Disease in the Community of a Lower Income Country

Stepwise Evaluation for the Risk of Metabolic Unhealthiness and Significant Non-Alcoholic Fatty Liver Disease in the Community of a Lower Income Country

A Study on Metabolic Health Status as a Risk Factor for Female Bladder Cancer Incidence: Analysis From the National Health Checkups Database of Korea

Purpose: This study investigated metabolic health status as a risk factor for female bladder cancer using the National Health Checkups databases of Korea.Materials and Methods: We defined obesity if body mass index was ≥25 kg/m&lt;sup&gt;2&lt;/sup&gt; and normal weight as &lt;25 kg/m&lt;sup&gt;2&lt;/sup&gt;. Metabolic unhealthiness was defined when 3 or more criteria of metabolic syndrome were met. A total of 11,461,618 women who took National health Checkups between 2009 and 2012 were categorized as metabolic healthy normal weight (MHNW), metabolic unhealthy normal weight (MuHNW), metabolic health obese (MHO), and metabolic unhealthy obese (MuHO). Multivariable-adjusted Cox regression was done to analyze the hazard ratio of bladder cancer.Results: The mean age was 48±11.55 years and body mass index was 23.19±2.13 kg/m&lt;sup&gt;2&lt;/sup&gt;. During 5.4±1.1 years of follow-up, 3,893 patients were newly diagnosed with bladder cancer. Compared to MHNW group, the hazard ratio of MuHNW group and MuHO group were 1.237 and 1.288, respectively, while 0.997 in the MHO group. As the number of metabolic unhealthy criteria increased, the cumulative incidence of bladder cancer increased.Conclusions: As a result of a large-scale study conducted on the female population in Korea, the risk of bladder cancer increased with metabolic unhealthiness. Even with normal weight, if metabolically unhealthy, the risk of bladder cancer increased. The greater the degree of metabolic unhealthiness, the higher the risk of bladder cancer. Education on metabolic healthiness concerning female bladder cancer is necessary.

Does healthy obesity exist in the elderly? Findings from the Northern Shanghai Study

Background and aimsMetabolic unhealthiness and obesity are both associated with an increased risk of cardiovascular disease. We aimed to investigate the significance of metabolic unhealthiness and obesity in organ damages in a community-based elderly cohort. Methods and resultsA total of 3325 elderly participants (>65 years old) were recruited in northern Shanghai. Associations of metabolic status and obesity with organ damages were investigated. In all, 1317 (39.6%) participants were metabolically unhealthy and 481 (14.5%) were obese. Compared with metabolically healthy nonobese (MH-nonobese) individuals, metabolically healthy obese subjects had a greater left ventricular mass index (LVMI) and pulse wave velocity (PWV). Metabolically unhealthy subjects, regardless of their obesity status, had greater organ damage parameters including E/Ea, LVMI, PWV, and urine albumin-creatinine ratio (UACR) than MH-nonobese subjects (all P < 0.05). After multivariate adjustments, both metabolic unhealthiness and obesity increased the risk of left ventricular hypertrophy (LVH) (OR 1.31, 95% CI 1.10–1.57 and OR 1.63, 95% CI 1.30–2.04), diastolic dysfunction (OR 1.33, 95% CI 1.06–1.67 and OR 1.51, 95% CI 1.14–1.99), and lower extremity atherosclerosis (OR 1.44, 95% CI 1.11–1.85 and OR 2.01, 95% CI 1.49–2.70). Metabolic unhealthiness was also associated with arterial stiffness, microalbuminuria and chronic kidney disease (all P < 0.05). In a subgroup analysis, metabolic unhealthiness was associated with more organ damages in nonobese subjects, and obesity was associated with LVH and lower extremity atherosclerosis regardless of metabolic status. ConclusionBoth obesity and metabolic unhealthiness were associated with organ damages. Metabolic unhealthiness was associated with more organ damages, especially in nonobese individuals. Even healthy obesity was significantly associated with cardiac and vascular impairment. Registration number for clinical trialsNCT02368938.

Metabolically Healthy Obesity and the Risk of Erosive Esophagitis: A Cohort Study.

OBJECTIVES:Obesity is an established risk factor of erosive esophagitis, and metabolic unhealthiness has been implicated in the pathogenesis of erosive esophagitis. Yet, the risk of erosive esophagitis among obese individuals without obesity-related metabolic unhealthiness, a condition referred to as “metabolically healthy obese (MHO)”, remains unclear. We examined the association between body mass index (BMI) categories and the development of erosive esophagitis in a cohort of metabolically healthy individuals.METHODS:We conducted a cohort study of 14,725 asymptomatic adults free of erosive esophagitis and metabolic abnormalities, who underwent repeated health checkups including screening endoscopy. A metabolically healthy state was defined as having no metabolic syndrome components and a homeostasis model assessment of insulin resistance <2.5. The presence of erosive esophagitis was determined using endoscopy.RESULTS:During 81,385.2 person-years of follow-up, 1,865 participants developed erosive esophagitis (incidence rate, 22.9 per 1,000 person-years). The multivariable adjusted hazard ratios (95% confidence intervals) for incident erosive esophagitis comparing overweight (BMI 23.0–24.9) and obese (≥25) with normal-weight participants (18.5–22.9) were 1.12 (1.00–1.25) and 1.29 (1.14–1.47), respectively. In dose-response analyses, increasing BMI also showed positive association with overall and LA-B grade or higher. The association persisted in MHO individuals without central obesity. The association between waist circumference categories and the development of erosive esophagitis was also evident.DISCUSSION:In a large cohort of strictly defined metabolically healthy men and women, the MHO phenotype was associated with an increased incidence of erosive esophagitis, providing evidence that the MHO phenotype is not protective from gastroesophageal reflux disease.

Metabolic Unhealthiness Increases the Likelihood of Having Metabolic Syndrome Components in Normoweight Young Adults.

Findings on risk detection for having metabolic syndrome (MetS) components, each of which may individually increase the risk of disease and mortality, are limited in young adults. In this study, we aimed to calculate the likelihood of having ≥1 MetS component in normoweight young adults using two different metabolic health criteria. We recruited 1182 normoweight young adults from the Taiwan Survey on the Prevalence of Hypertension, Hyperglycemia, and Hyperlipidemia and the National Health Interview Survey (aged 16–45 years, 39% male, body mass index = 18.5–22.99, all without MetS) and followed them for 5 years. Metabolic health criteria were derived from the Harmonized criteria (unhealthy if showing abnormality in one or two MetS components) and the triglyceride-glucose index (TyG-i; unhealthy if TyG-i was in the >75th percentile). Odds ratio (OR) and 95% confidence interval (CI) estimations for having ≥1 MetS component and for having each MetS component in 5 years were assessed using multivariable-adjusted logistic regression. We observed a significantly increased likelihood of the presence of ≥1 MetS component in the unhealthy group by using the Harmonized criteria and TyG-i (adjusted OR (aOR); 95%CI: 2.64; 2.02–3.45 and 2.1; 1.57–2.82, respectively). The areas under the receiver-operating characteristics curves were 0.679 and 0.652 for the final models using Harmonized and TyG-i criteria, respectively. These findings support the recommendation of treating any metabolic component abnormality, even in young adults without a MetS diagnosis.

ASSOCIATION OF METABOLIC HEALTH AND OBESITY WITH HYPERTENSIVE MEDIATED ORGAN DAMAGE IN THE ELDERLY

Objective:Metabolic syndrome and obesity is associated with increased risk of cardiovascular disease. We aimed at investigating the significance of metabolic unhealthiness and obesity in hypertensive mediated organ damage (HMOD) in a community-based elderly cohort.Design and method:2830 elderly part

Optimal Starting Age for Colorectal Cancer Screening in an Era of Increased Metabolic Unhealthiness: A Nationwide Korean Cross-Sectional Study.

Background/AimsThe association between metabolic syndrome and colorectal cancer (CRC) has been suggested as one of causes for the increasing incidence of CRC, particularly in younger age groups. The present study examined whether the current age threshold (50 years) for CRC screening in Korea requires modification when considering increased metabolic syndrome.MethodsWe analyzed data from the National Health Insurance Corporation database, which covers ~97% of the population in Korea. CRC risk was evaluated with stratification based on age and the presence/absence of relevant metabolic syndrome components (diabetes, dyslipidemia, and hypertension).ResultsA total of 51,612,316 subjects enrolled during 2014 to 2015 were analyzed. Among them, 19.3% had diabetes, hypertension, dyslipidemia, or some combination thereof. This population had a higher incidence of CRC than did those without these conditions, and this was more prominent in subjects <40 years of age. The optimal cutoff age for detecting CRC, based on the highest Youden index, was 45 years among individuals without diabetes, dyslipidemia, and hypertension. Individuals with at least one of these components of metabolic syndrome had the highest Youden index at 62 years old, but the value was only 0.2. Resetting the cutoff age from 50 years to 45 years achieved a 6% increase in sensitivity for CRC detection among the total population.ConclusionsStarting CRC screening earlier, namely, at 45 rather than at 50 years of age, may improve secondary prevention of CRC in Korea.

Obesity increases the risk of erosive esophagitis but metabolic unhealthiness alone does not: a large-scale cross-sectional study

BackgroundObesity is a known risk factor for erosive esophagitis (EE) and metabolic unhealthiness has been implicated in EE pathogenesis. However, obesity and metabolic unhealthiness are not synonymous and the associations between obesity, metabolic health, and EE are unclear. Therefore, our aim was to investigate the relationship between EE, obesity, and metabolic health.MethodsWe performed a retrospective cross-sectional study of subjects undergoing health screening at a university hospital. Subjects were classified into 4 groups based on metabolic and obesity criteria: metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy nonobese (MUNO), and metabolically unhealthy obese (MUO). Multivariable analysis was used to identify EE risk factors with MHNO subjects as reference. To determine if there were synergistic interactions between metabolic health and obesity status, the Rothman’s synergy index and attributable proportion of risk were also calculated.ResultsWe included 10,338 subjects (5448 MHNO, 1605 MHO, 1600 MUNO, 1685 MUO). The prevalence of EE was 6.5% in MHNO, 12.6% in MHO, 9.3% in MUNO, and 14.3% in MUO. EE risk was increased significantly by obesity (MHO: OR, 1.589, 95% CI, 1.314–1.921, P < 0.001; MUO: OR, 1.734, 95% CI, 1.441–2.085, P < 0.001), but not in MUNO subjects (OR, 1.224, 95% CI, 0.991–1.511, P = 0.060). Male sex, blood leukocyte count, alcohol, and smoking significantly increased EE risk, but H. pylori infection was protective. Replacement of obesity with abdominal obesity gave similar results. The Rothman’s synergy index was 0.920 (95% CI, 0.143–5.899) and the attributable proportion of risk was − 0.051 (95% CI, − 1.206–1.105), indicating no interaction between metabolic and obesity status on EE risk.ConclusionsWe demonstrated that obesity increased the risk of EE, regardless of metabolic health status. However, EE risk was not significantly increased in MUNO subjects, suggesting that metabolic unhealthiness may not be involved in EE pathogenesis. As observational cross-sectional studies cannot prove causality, prospective longitudinal studies involving obesity and metabolic treatment should be performed to further investigate the association between obesity, metabolic health, and EE risk.

Risk of ischemic stroke in metabolically healthy obesity: A nationwide population-based study.

BackgroundWhether metabolically healthy obese (MHO) individuals are at increased risk of ischemic stroke is not well known. We investigated the association of the MHO phenotype with ischemic stroke.MethodsA total of 354,083 adults (age 45.8 ± 14.2 years) from the Korean National Health Insurance Service–National Sample Cohort enrolled in 2004–2008 were followed-up for incident ischemic stroke until 2013. Subjects meeting none of the metabolic syndrome criteria were classified as ‘metabolically healthy’. The cohort was categorized into four groups according to obesity and metabolic status: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), MHO, and metabolically unhealthy obese (MUO).ResultsIschemic stroke was newly diagnosed in 4,884 (1.4%) individuals during a mean follow-up of 7.4 ± 1.5 years. Stroke incidence rates for the MHNW, MUNW, MHO, and MUO groups were 0.56, 2.61, 0.61, and 2.76 per 1,000 person-years, respectively. While risk for stroke increased significantly in metabolically unhealthy groups, it was not increased in MHO compared to the MHNW group on multivariate analysis. In metabolically healthy individuals, obesity did not increase the risk for ischemic stroke, regardless of the severity of obesity. Meanwhile, in metabolically unhealthy individuals, being obese was significantly associated with increased risk of stroke.ConclusionsMHO individuals were not at increased risk for ischemic stroke. However, obesity increased risk for ischemic stroke in persons with metabolic risk factors; therefore, maintaining normal weight may be more important for this population. Also, metabolic unhealthiness showed greater association than obesity with stroke.

Interaction of Metabolic Health and Obesity on Subclinical Target Organ Damage.

Metabolically healthy obese (MHO) individuals generally show better cardiovascular prognosis compared with metabolically unhealthy counterparts, which may be related to different patterns of target organ damage (TOD). We aimed to investigate the patterns of TOD related to obesity and metabolic unhealthiness. A total of 659 Korean adults (mean age, 60.0 ± 11.8 years; male, 51.1%) undergoing health examinations were stratified into four groups according to obesity (body mass index ≥25.0 kg/m2) and metabolic healthiness (meeting ≤1 criteria of metabolic syndrome excluding abdominal circumference): metabolically healthy nonobese (MHNO), metabolically unhealthy nonobese (MUNO), MHO, and metabolically unhealthy obese (MUO). Four measures of TOD were evaluated: arterial stiffness, renal dysfunction, left ventricular (LV) diastolic dysfunction, and LV hypertrophy (LVH). In multivariable analyses, compared with the MHNO group, the MHO group showed 2.31 times higher odds for LVH, whereas, the MUNO group showed 3.14 and 6.28 times higher odds for increased arterial stiffness and renal dysfunction, respectively. Metabolic unhealthiness was associated with increased arterial stiffness [odds ratio (OR) 2.73; confidence interval (95% CI) 1.72-4.34], renal dysfunction (OR 4.02; 95% CI 1.54-10.49), and LV diastolic dysfunction (OR 2.28; 95% CI 1.14-4.55). Meanwhile, obesity showed weaker association with LVH and LV diastolic dysfunction, and was not associated with increased arterial stiffness and renal dysfunction in multivariable analyses. Metabolic unhealthiness shows more association with TOD than obesity, which may contribute to the higher risk of cardiometabolic abnormalities in MUNO compared with MHO.

Metabolic unhealthiness is an important predictor for the development of advanced colorectal neoplasia

Obesity is a well-known risk factor for colorectal neoplasia. Yet, the associations of both metabolic and obesity status with metachronous colorectal neoplasia remain unclear. We conducted a cohort study of 9,331 adults who underwent screening colonoscopy and surveillance colonoscopy. Participants were classified as metabolically healthy if they had no metabolic syndrome component. Participants were categorized into four groups according to body mass index and metabolic status: metabolically healthy non-obese (MHNO; n = 2,745), metabolically abnormal non-obese (MANO; n = 3,267), metabolically healthy obese (MHO; n = 707), and metabolically abnormal obese (MAO; n = 2,612). MAO individuals [n = 159 advanced colorectal neoplasia (AN) cases, 6.1%] and MANO individuals (n = 167 AN cases, 5.1%) had a higher incidence of AN compared with MHNO individuals (n = 79 AN cases, 2.9%). In a multivariable model, the risk of metachronous AN was higher in MANO (hazard ratio [HR] 1.43, 95% confidence interval [CI] 1.12–1.84) and MAO (HR 1.52, 95% CI 1.18–1.96) than in MHNO. In contrast, the risk of metachronous AN was not significantly elevated in MHO. In subgroup analyses, with or without adenoma at baseline, MAO was a risk group for metachronous AN, and MHO was not. Our findings suggest that metabolic unhealthiness is a significant predictor for metachronous AN.