Metabolically Healthy Non-obese Research Articles

Rising Trends in Metabolically Healthy Obesity in Cancer Patients and Its Impact on Cardiovascular Events: Insights from a Contemporary Nationwide Analysis in the USA (2016-2020).

Background: Obesity or overweight raises the risk of developing 13 types of cancer, representing 40% of all cancers diagnosed in the United States annually. Given the ongoing debate surrounding the impact of metabolically healthy obesity (MHO) on cardiovascular outcomes, it is crucial to comprehend the incidence of Major Adverse Cardiovascular and Cerebrovascular Events (MACCEs) and the influence of MHO on these outcomes in cancer patients. Methods: Data of hospitalized cancer patients with and without obesity were analyzed from the National Inpatient Sample 2016-2020. Metabolically healthy patients were identified by excluding diabetes, hypertension, and hyperlipidemia using Elixhauser comorbidity software, v.2022.1. After that, we performed a multivariable regression analysis for in-hospital MACCEs and other individual outcomes. Results: We identified 3,111,824 cancer-related hospitalizations between 2016 and 2020. The MHO cohort had 199,580 patients (6.4%), whereas the MHnO (metabolically healthy non-obese) cohort had 2,912,244 patients (93.6%). The MHO cohort had a higher proportion of females, Blacks, and Hispanics. Outcomes including in-hospital MACCEs (7.9% vs. 9.5%; p < 0.001), all-cause mortality (6.1% vs. 7.5%; p < 0.001), and acute myocardial infarction (AMI) (1.5% vs. 1.6%; p < 0.001) were lower in the MHO cohort compared to the MHnO cohort. Upon adjusting for the baseline characteristics, the MHO group had lower odds of in-hospital MACCEs [adjusted odds ratio (AOR) = 0.93, 95% CI (0.90-0.97), p < 0.001], all-cause mortality [AOR = 0.91, 95% CI (0.87-0.94); p < 0.001], and acute ischemic stroke (AIS) [AOR = 0.76, 95% CI (0.69-0.84); p < 0.001], whereas there were higher odds of acute myocardial infarction (AMI) [AOR = 1.08, 95% CI (1.01-1.16); p < 0.001] and cardiac arrest (CA) [AOR = 1.26, 95% CI (1.01-1.57); p = 0.045] in the MHO cohort compared to the MHnO cohort. Conclusions: Hospitalized cancer patients with MHO exhibited a lower prevalence of in-hospital MACCEs than those with MHnO. Additional prospective studies and randomized clinical trials are imperative to validate these findings, particularly in stratifying MHO across various cancer types and their corresponding risks of in-hospital MACCEs.

Metabolic Obesity Phenotypes and Incident Cardiovascular Outcomes in Middle-Aged and Older Korean Adults: A Longitudinal 10-Year Analysis of the Korean Genome and Epidemiology Study.

Background: This study investigated the association of four metabolic obesity phenotypes with incident coronary artery disease and stroke in a large-scale, community population-based, prospective Korean cohort observed for over 10 years. Methods: The study participants included 7374 adults aged 40-69 years, drawn from the Korean Genome and Epidemiology Study. Participants with different metabolic obesity phenotypes were categorized according to body weight and metabolic health status into four groups: metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy nonobese (MUHNO), and metabolically unhealthy obese (MUHO). Combined cardiovascular events were defined as coronary artery disease and stroke. We used multivariate Cox proportional hazards regression models to prospectively assess hazard ratios (HRs) with 95% confidence intervals (CIs) for incident coronary artery disease or stroke over 10 years after the baseline survey. Results: During the follow-up period, newly developed coronary artery disease, stroke, and combined cardiovascular events were diagnosed in 151 (2.0%), 137 (1.9%), and 283 (3.8%) participants, respectively. After adjusting for confounding variables, the HRs (95% CIs) for incident combined cardiovascular events were 1.81 (1.34-2.46) in the MUHO group, 1.29 (0.92-1.81) in the MUHNO group, and 1.21 (0.81-1.79) in the MHO group compared with those in the MHNO group. Conclusions: This study revealed distinct risks associated with four metabolic obesity phenotypes concerning incident coronary artery disease and stroke. After adjusting for potential confounding variables, the results indicated that MUHO, but not MUHNO or MHO, showed a higher risk of developing coronary artery disease and stroke than MHNO.

The transition of metabolic phenotypes and cardiovascular events: Panasonic cohort study 16.

The study objective was to investigate whether changes in metabolic phenotype affect the risk of cardiovascular events. All 117,589 participants were included in this retrospective cohort study. The metabolic phenotypes of the participants were assessed at two points (the second evaluation was set 2 years after the first evaluation), and the incidence rate of cardiovascular events was observed for 11 years. The main outcome was 3-point major adverse cardiac events (MACE), which comprises cardiovascular death, nonfatal coronary artery disease, and nonfatal stroke incidence. Of the participants, 2748 (2.3%) cases of 3-point MACE were identified during follow-up. The stable metabolically healthy obesity group had a higher risk of 3-point MACE than those with stable metabolically healthy nonobesity (MHNO). Additionally, the change from metabolically healthy obesity to MHNO for 2 years decreased the risk of 3-point MACE (hazard ratio [HR], 1.12: 95% CI: 0.84-1.47) to the same level as stable MHNO. However, the change from metabolically abnormal nonobesity and metabolically abnormal obesity to MHNO for 2 years maintained a higher risk of 3-point MACE (HR, 1.66 [95% CI: 1.36-2.01]; HR, 1.91 [95% CI: 1.22-2.81]) than those with stable MHNO. Change in metabolic phenotype is associated with incident 3-point MACE.

Joint effect of BMI and metabolic status on mortality among adults: a population-based longitudinal study in United States

We explored the joint effects of different metabolic obesity phenotypes on all-cause and disease-specific mortality risk among the American population. Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 1999–2018. Mortality outcome data were from mortality files linked to National Death Index record and follow-up information was up to December 31, 2019. 50,013 participants were finally included. Four metabolic obesity phenotypes were defined based on obesity and metabolic status: metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), metabolically healthy non-obese (MHNO), and metabolically unhealthy non-obese (MUNO). Population-weighted Cox proportional hazards models were used to explore the all-cause and disease-specific mortality risk of metabolic obesity phenotypes. The all-cause mortality risk of MUO and MUNO was significantly higher than MHNO. MUNO was associated with a significantly increased risk of death from heart disease (HR: 1.40, 95% CI 1.16–1.70), hypertension (HR: 1.68, 95% CI 1.34–2.12), diabetes (HR: 2.29, 95% CI 1.67–3.15), and malignant neoplasms (HR:1.29, 95% CI 1.09–1.53). Metabolic unhealth significantly increased the risk of all-cause mortality, regardless of obesity status. Among individuals with metabolic unhealthy status, obesity significantly reduced the risk of all-cause mortality (HR: 0.91, 95% CI 0.85–0.98). Our study highlights the importance of identifying and characterizing metabolic obesity phenotypes in obese and metabolically abnormal patients, as well as healthy adults. Comprehensive evaluation of obesity and metabolic status is necessary to adopt appropriate interventions and treatment measures and maximize patient benefit.

Association of metabolic health and obesity with coronary heart disease in adult cancer survivors.

The metabolically healthy obese (MHO) phenotype is associated with an increased risk of coronary heart disease (CHD) in the general population. However, association of metabolic health and obesity phenotypes with CHD risk in adult cancer survivors remains unclear. We aimed to investigate the associations between different metabolic health and obesity phenotypes with incident CHD in adult cancer survivors. We used National Health Insurance Service (NHIS) to identify a cohort of 173,951 adult cancer survivors aged more than 20 years free of cardiovascular complications. Metabolically healthy nonobese (MHN), MHO, metabolically unhealthy nonobese (MUN), metabolically unhealthy obese (MUO) phenotypes were created using as at least three out of five metabolic health criteria along with obesity (body mass index ≥ 25.0 kg/m2). We used Cox proportional hazards model to assess CHD risk in each metabolic health and obesity phenotypes. During 1,376,050 person-years of follow-up, adult cancer survivors with MHO phenotype had a significantly higher risk of CHD (hazard ratio [HR] = 1.52; 95% confidence intervals [CI]: 1.41 to 1.65) as compared to those without obesity and metabolic abnormalities. MUN (HR = 1.81; 95% CI: 1.59 to 2.06) and MUO (HR = 1.92; 95% CI: 1.72 to 2.15) phenotypes were also associated with an increased risk of CHD among adult cancer survivors. Adult cancer survivors with MHO phenotype had a higher risk of CHD than those who are MHN. Metabolic health status and obesity were jointly associated with CHD risk in adult cancer survivors.

The classification of obesity based on metabolic status redefines the readmission of non-Hodgkin’s lymphoma—an observational study

BackgroundThe relationship between obesity and non-Hodgkin’s lymphoma (NHL) was controversial, which may be due to the crudeness definition of obesity based on body mass index (BMI). As obesity and metabolic abnormalities often coexist, we aimed to explore whether the classification of obesity based on metabolic status can help to evaluate the real impact of obesity on the readmission of NHL.MethodsIn this retrospective cohort study, utilizing the 2018 Nationwide Readmissions Database, we identified NHL-related index hospitalizations and followed them for non-elective readmission. The patients with NHL were classified as metabolically healthy non-obese (MHNO) and obese (MHO) and metabolically unhealthy non-obese (MUNO) and obese (MUO). Readmission rates for each phenotype were calculated at 30-day intervals. Multiple COX regression was used to analyze the association of metabolic-defined obesity with 30-day, 90-day, and 180-day readmission rates in patients with NHL.ResultsThere were 22,086 index hospitalizations with NHL included. In the multivariate COX regression, MUNO was associated with increased 30-day (HR = 1.113, 95% CI 1.036–1.195), 90-day (HR = 1.148, 95% CI 1.087–1.213), and 180-day readmission rates (HR = 1.132, 95% CI 1.077–1.189), and MUO was associated with increased 30-day (HR=1.219, 95% CI: 1.081-1.374), 90-day (HR = 1.228, 95% CI 1.118–1.348), and 180-day readmission rates (HR = 1.223, 95% CI 1.124–1.33), while MHO had no associations with readmission rates.ConclusionsThe presence of metabolic abnormalities with or without obesity increased the risk of non-selective readmission in patients with NHL. However, obesity alone had no associations with the risk of non-selective readmission, suggesting that interventions for metabolic abnormalities may be more important in reducing readmissions of NHL patients.

The effects of weight loss and improved metabolic health status on the risk of non-alcoholic fatty liver disease—results from a prospective cohort in China

BackgroundThe impact of weight loss and/or improved metabolic status on the risk of non-alcoholic fatty liver disease (NAFLD) has yet to be determined.MethodsA total of 35,322 participants without NAFLD were followed. NAFLD risk was compared between consistently metabolically healthy non-obese (MHNO) and non-MHNO who lost weight to become non-obese and/or improved their metabolic health, using Cox proportional hazards and logistic regression models.ResultsFollowing 148,186 person-years, 8,409 participants had onset NAFLD, with an incidence rate of 56.75 (95% CI: 55.57, 57.94) per 1,000 person-years. Metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), and metabolically unhealthy non-obese (MUNO) at baseline were associated with increased NAFLD risk, with hazard ratios of 4.48 (95%CI:4.24, 4.73), 8.85 (95%CI:7.95, 9.84), and 10.70 (95%CI:9.73, 11.78). Weight loss and/or metabolic status improvements could significantly reduce NAFLD risk by 79.46 to 41.46%. Specifically, after weight loss from MHO to MHNO, the reduction in NAFLD risk [OR decreased from 12.01 (95%CI:9.40, 15.35) to 4.14 (95%CI:3.08, 5.57)] was greater than that of the MUNO subgroup whose metabolic status improved to MHNO [OR decreased from 5.53 (95%CI:5.15, 5.94) to 2.71 (95%CI:2.50, 3.93)]. In the MUO subgroup, the group with the greatest risk reduction of NAFLD was the weight and metabolic state both improvement group [MUO to MHNO, OR decreased from 22.74 (95%CI:17.61, 29.37) to 4.67 (95%CI:3.05, 7.16)], followed by the weight loss only group [MUO to MUNO, OR decreased to 6.83 (95%CI:4.87, 9.57)], and finally the group with the least and insignificant risk reduction was the metabolic state improvement group [MUO to MHO, OR decreased to 13.38 (95%CI:9.17,19.53)]. NAFLD risk was negatively correlated with the duration of improvement (p &amp;lt; 0.001).ConclusionIndividuals with non-MHNO were more likely to develop NAFLD than those with consistent MHNO, but metabolic improvements and weight loss can alleviate the risk. Their NAFLD risk was negatively correlated with improvement duration. However, it remained higher than in individuals with consistent MHNO at an average follow-up of 4.2 years.

The short- and long-term readmission of four major categories of digestive system cancers: does obesity or metabolic disorder matter?

Patients with digestive system cancers (DSCs) are at a high risk for hospitalizations; however, the risk factors for readmission remain unknown. Here, we established a retrospective cohort study to assess the association between metabolic obesity phenotypes and readmission risks of DSC. A total of 142,753 and 74,566 patients at index hospitalization were ultimately selected from the Nationwide Readmissions Database (NRD) 2018 to establish the 30-day and 180-day readmission cohorts, respectively. The study population was classified into four groups: metabolically healthy non-obese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO). Multivariate Cox regression analysis was used to estimate the effect of metabolic obesity phenotypes on DSC readmission. The MUNO phenotype had 1.147-fold (95% CI: 1.066, 1.235; p < 0.001) increased 180-day readmission risks in patients with neoplasm of the upper digestive tract. The MUNO phenotype had 1.073-fold (95% CI: 1.027, 1.121; p = 0.002) increased 30-day readmission risks and 1.067-fold (95% CI: 1.021, 1.115; p = 0.004) increased 180-day readmission risks in patients with neoplasm of the lower digestive tract. The MUNO and MUO phenotypes were independent risk factors of readmission in patients with liver or pancreatic neoplasm. Metabolic obesity status was independently associated with a high risk of severe and unplanned hospitalization within 30 days or 180 days. Both obesity and metabolic abnormalities are associated with a high risk for the poor prognosis of DSC patients. The effect of metabolic categories on the short- or long-term readmission of liver or pancreas cancers may be stronger than that of obesity.

Association of metabolically unhealthy non-obese and metabolically healthy obese individuals with arterial stiffness and 10-year cardiovascular disease risk: a cross-sectional study in Chinese adults

BackgroundThe relationship between metabolically healthy obese individuals (MHO) and cardiovascular disease (CVD) risk is disputed. This study investigated the association of metabolically unhealthy non-obese(MUNO) individuals and MHO with arterial stiffness and 10-year CVD risk.MethodsA total of 13,435 participants were enrolled and further divided into the metabolically healthy non-obese (MHNO) phenotype (n = 4927), MUNO phenotype (n = 1971), MHO phenotype (n = 2537) and metabolically unhealthy obese (MUO) phenotype (n = 4000) according to body mass index (BMI) and metabolic status. We used brachial ankle pulse wave velocity (baPWV) to measure arterial stiffness and the Framingham risk score (FRS) to evaluate the 10-year CVD risk.ResultsThe MUO and MUNO phenotypes had higher mean baPWV values than the MHO and MHNO phenotypes, regardless of age (1446.19 ± 233.65 vs. 1423.29 ± 240.72 vs. 1283.57 ± 213.77 vs. 1234.08 ± 215.99 cm/s, P < 0.001). Logistic regression analysis indicated that the MUNO and MUO phenotypes were independently correlated with elevated baPWV and 10-year CVD risk, while the MHO phenotype was independently associated with only the 10-year CVD risk. In metabolically healthy subjects, BMI showed a dose-dependent increase in the risk of elevated baPWV, with an adjusted OR of 1.007 (95% CI 1.004–1.010, P < 0.001). However, in metabolically unhealthy participants, the estimate for the relationship between elevated baPWV and BMI was nonsignificant.ConclusionsThe MUNO phenotype exhibits increased arterial stiffness and 10-year CVD risk. However, BMI is positively and dose-dependently correlated with arterial stiffness only in metabolically healthy subjects. We speculate that metabolic status may be a strong confounder in the obesity–elevated baPWV association.

Differences in the levels of inflammatory markers between metabolically healthy obese and other obesity phenotypes in adults: A systematic review and meta-analysis

AimsThe aim of this study was to systematically review and analyze differences in the levels of C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) comparing metabolically healthy but obese (MHO) with metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO) subjects. Data synthesisWe searched PubMed, Embase, Web of Science, and Scopus for studies that matched the relevant search terms. Differences in inflammatory marker levels between MHO and the other three phenotypes were pooled as standardized mean differences (SMD) or differences of medians (DM) using a random-effects model. We included 91 studies reporting data on 435,007 individuals. The CRP levels were higher in MHO than in MHNO subjects (SMD = 0.63, 95% CI: 0.49, 0.76; DM = 0.83 mg/L, 95% CI: 0.56, 1.11). The CRP levels were higher in MHO than in MUNO subjects (SMD = 0.16, 95% CI: 0.05, 0.28; DM = 0.39 mg/L, 95% CI: 0.09, 0.69). The CRP levels were lower in MHO than in MUO individuals (SMD = −0.43, 95% CI: −0.54, −0.31; DM = −0.82 mg/L, 95% CI: −1.16, −0.48). The IL-6 levels in MHO were higher than in MHNO while lower than in MUO subjects. The TNF-α levels in MHO were higher than in MHNO individuals. ConclusionsThis review provides evidence that CRP levels in MHO are higher than in MHNO and MUNO subjects but lower than in MUO individuals. Additionally, IL-6 levels in MHO are higher than in MHNO but lower than in MUO subjects, and TNF-α levels in MHO are higher than in MHNO individuals. Systematic review registrationPROSPERO number: CRD42021234948.

Metabolic phenotypes and risk of end-stage kidney disease in patients with type 2 diabetes.

Obesity often initiates or coexists with metabolic abnormalities. This study aimed to investigate the pathological characteristics and the independent or mutual relations of obesity and metabolic abnormalities with end-stage kidney disease (ESKD) in patients with type 2 diabetes (T2D) and associated diabetic kidney disease (DKD). A total of 495 Chinese patients with T2D and biopsy-confirmed DKD between 2003 and 2020 were enrolled in this retrospective study. The metabolic phenotypes were based on the body weight index (BMI)-based categories (obesity, BMI ≥ 25.0 kg/m2) and metabolic status (metabolically unhealthy status, ≥ 1 criterion National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATP III) excluding waist circumference and hyperglycemia) and were categorized into four types: metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO), and metabolically unhealthy obesity (MUO). The pathological findings were defined by the Renal Pathology Society classification. Cox proportional hazards models were used to estimate hazard ratios (HRs) for ESKD. There are 56 (11.3%) MHNO patients, 28 (5.7%) MHO patients, 176 (35.6%) MUNO patients, and 235 (47.5%) MUO patients. The high prevalence of the Kimmelstiel-Wilson nodule and severe mesangial expansion were associated with obesity, whereas severe IFTA was related to metabolically unhealthy status. In the multivariate analysis, the adjusted HR (aHR) was 2.09 [95% confidence interval (CI) 0.99-4.88] in the MHO group, 2.16 (95% CI 1.20-3.88) in the MUNO group, and 2.31 (95% CI 1.27-4.20) in the MUO group compared with the MHNO group. Furthermore, the presence of obesity was insignificantly associated with ESKD compared with non-obese patients (aHR 1.22, 95% CI 0.88-1.68), while the metabolically unhealthy status was significantly associated with ESKD compared to the metabolically healthy status in the multivariate analysis (aHR 1.69, 95% CI 1.10-2.60). Obesity itself was insignificantly associated with ESKD; however, adding a metabolically unhealthy status to obesity increased the risk for progression to ESKD in T2D and biopsy-proven DKD.

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.