Metabolically Healthy Obese Research Articles

Lifestyle intervention improves cardiometabolic profiles among children with metabolically healthy and metabolically unhealthy obesity

BackgroundIn recent years, there has been a surge of interest in the metabolic phenotype among children with obesity characterized by the absence of associated cardiometabolic risk factors (CRFs), known as metabolically healthy obesity (MHO), as opposed to those with metabolically unhealthy obesity (MUO). This study investigated the effect of lifestyle intervention on CRFs among children with MHO and MUO.MethodsA total of 102 school-aged children with obesity (54 girls and 48 boys) aged 8–16 years completed a 16-week school-based lifestyle modification intervention program, MyBFF@school Phase I. The intervention consisted of physical activity, healthy eating promotion, and psychological empowerment. MHO and MUO statuses were defined based on the 2018 consensus-based criteria. Fasting venous blood collection, body composition measurement, clinical assessment and physical fitness testing were conducted at baseline and at the end of week 16.ResultsAfter the intervention, the CRFs of the children with MUO improved with significant decreases in systolic (p < 0.001) and diastolic (p = 0.01) blood pressure and a significant increase in high-density lipoprotein cholesterol (HDL-C) (p = 0.005), while the CRFs of the children with MHO had a significant decrease in uric acid (p = 0.04). Additionally, 51.6% of the children with MHO transitioned to the MUO, while 26.8% of the children with MUO crossed over to the MHO at the end of the intervention. Furthermore, the odds of having high systolic blood pressure among children with MUO were 59% lower at week-16 than at baseline (OR = 0.41 (95% CI = 0.18, 0.92), p = 0.03).ConclusionsOur findings demonstrated that CRFs improved more prominently among children with MUO following the intervention. More importantly, our findings indicate that MHO in children is transient, hence, strategies to protect children against MUO are warranted.Trial registration: ClinicalTrials.gov NCT02212873.

Relationship of different metabolic obesity phenotypes with reflux esophagitis: a propensity score matching analysis

BackgroundObesity is associated with an increased risk of reflux esophagitis (RE). Metabolic abnormalities have been implicated in the pathogenesis of RE. However, the role of metabolic status in the risk of RE among individuals with varying degrees of obesity remains unclear. Therefore, our study aimed to assess the association between metabolic obesity phenotypes and the risk of RE.MethodsThis study included a cohort of 24,368 participants aged 18 years and older who underwent upper gastrointestinal endoscopy at the First Affiliated Hospital of Dalian Medical University during health checkups between January 1, 2008, and December 31, 2021. Among these participants, a total of 9,947 individuals were classified into four groups based on their obesity phenotype: metabolically healthy normal weight (MHNW), metabolically healthy obesity (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy obesity (MUO). To account for potential confounding factors, multivariate logistic regression analysis was applied to examine the association between metabolic obesity phenotypes and the risk of RE, with stratification by sex and age.ResultsAmong all participants, the MUNW, MHO, and MUO groups demonstrated a higher risk of RE when compared to the MHNW group. After controlling for all confounding factors, the MUO group exhibited the highest risk, with an odds ratio (OR) of 3.723 (95% CI: 2.751–5.040) in males and 5.482 (95% CI: 4.080–7.367) in females. The prevalence of RE increased in proportion to the number of metabolic risk factors. Subgroup analyses, which accounted for all confounders, revealed that the MHO, MUNW, and MUO phenotypes were associated with an elevated risk of RE in individuals under 60 years old as well as those over 60 years old. Interestingly, a more comprehensive analysis indicated that obesity may have a greater effect on the risk of RE than metabolic disorders.ConclusionsBoth metabolic disorders and obesity were associated with an increased risk of RE. The effect of obesity on RE prevalence may be stronger than that of metabolic disorders, emphasizing the significance of obesity regardless of metabolic health status. Clinical interventions should address not only obesity but also metabolic disorders in order to reduce the risk of RE.

Body composition differences in patients with Metabolic Dysfunction-Associated Steatotic Liver Disease

BackgroundAlthough body composition (BC) has been associated with Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), there is little evidence of differences in BC in patients with MASLD regarding body mass index (BMI). The aim of this study was to determine differences in BC in terms of BMI and metabolic comorbidities in patients with MASLD.Materials and methodsIt is a cross-sectional study with patients who attended the check-up unit. Liver steatosis was evaluated by controlled attenuation parameter, and patients were classified into five groups according to BMI, presence of MASLD, and metabolic characteristics: &amp;lt;25 kg/m2 non-MASLD; &amp;lt;25 kg/m2-MASLD; Overweight-MASLD; Metabolically Healthy Obese (MHO)-MASLD; and Metabolically Unhealthy Obese (MUO)-MASLD. BC was assessed by bioelectrical impedance and a Bioimpedance Vectorial Analysis (BIVA) was carried out. Differences in BC were analyzed by a One-Way ANOVA test. Univariate and multivariate analyses were performed for factors associated with abnormal BC.ResultsA total of 316 patients were included. 59% (n = 189) were male, with a mean age of 49 ± 10 years. Fat% significantly higher according to BMI was not different between BMI &amp;lt;25 kg/m2-MASLD and Overweight-MASLD groups. Skeletal muscle mass (SMM) was significantly lower in obesity groups with respect to overweight and normal weight groups (p &amp;lt; 0.05); however, no differences were observed in the post-hoc analysis. Extracellular Water/Intracellular Water ratio was significantly higher in the MHO-MASLD group and MUO-MASLD group compared with the BMI &amp;lt;25 kg/m2 non-MASLD group and with the BMI &amp;lt;25 kg/m2-MASLD group. Abnormal Waist Circumference (WC) and liver steatosis were independent factors associated with abnormal BC.ConclusionBC in MASLD patients varies according to BMI increase; changes could be explained by loss of SMM and not necessarily by the presence of metabolic abnormalities. High WC and the presence of steatosis are independent factors associated with altered BC.

Central and Peripheral Sensitivity to Thyroid Hormones Correlate to Metabolically Obesity Phenotypes in Chinese Euthyroid Adults: A Cross-Sectional Study.

Thyroid hormones impact lipid metabolism and glucose homoeostasis through both central and peripheral regulation; however, little research has delved into the association between thyroid hormone sensitivity and metabolically obese phenotypes. We aimed to investigate the correlation between indices of central and peripheral sensitivity to thyroid hormones and metabolically obese phenotypes in euthyroid Chinese adults. This cross-sectional study included 20,084 euthyroid individuals. Central thyroid hormone sensitivity was assessed using the thyroid feedback quantile-based index (TFQI), parametric thyroid feedback quantile-based index (PTFQI), thyroid-stimulating hormone index (TSHI), and thyrotropin thyroxine resistance index (TT4RI), while peripheral thyroid hormone sensitivity was measured by FT3/FT4. Metabolically obesity phenotypes included metabolically healthy non-obesity (MHNO), unhealthy non-obesity (MUNO), metabolically healthy obesity (MHO), and unhealthy obesity (MUO). Multinomial logistic regression and restricted cubic spline analyses were conducted to investigate the association between thyroid hormone sensitivity indices and metabolically obese phenotypes risk. Subgroup analysis was also performed to examine this association stratified by sex and age. Mediation analysis was performed to estimate direct and indirect effects of BMI. Prevalence of MHNO, MUNO, MHO and MUO was 66.1% (n=13,273), 21.3% (n=4271), 5.3% (n=1055), and 7.4% (n=1485) respectively. After adjustment for potential confounders, the odds ratios (ORs) (95% CI) for MUNO and MUO were increased with all elevated thyroid hormones sensitivity indices (per SD increase) [MUNO: TFQI 1.14(1.09-1.19), PTFQI 1.18(1.23-1.23); TSHI 1.26(1.19-1.33), TT4RI 1.41, (1.31-1.53), FT3/FT4 1.20(1.14-1.25) and [MUO: TFQI 1.20(1.11-1.31), PTFQI 1.26(1.16-1.37), TSHI 1.39 (1.26-1.54), TT4RI 1.70(1.48-1.95), FT3/FT4 1.26 (1.16-1.37)] (p value<0.001), and only TSHI and TT4RI (per SD increase) significantly increased the risk of MHO (TSHI: OR=1.12, 95% CI 1.01-1.24; TT4RI: OR=1.25, 95%CI 1.08-1.4) (p value<0.05). Non-linear relationships were observed between central thyroid hormones sensitivity indices and MUNO and MUO(p for nonlinearity<0.05). Conversely, a linear relationship between FT3/FT4 and metabolically obese phenotypes was noted in all subjects (p for nonlinearity>0.05). Besides, subgroup analysis indicated that this association remained consistent among sex and age (p for interaction>0.05). The proportions mediated by BMI on the association of TFQI, PTFQI, TSHI, TT4RI, FT3/FT4 and risk of metabolically unhealthy conditions were 13.73%, 25.38%, 22.75%, 17.94% and 62.28%, respectively. In euthyroid adults, central and peripheral sensitivity to thyroid hormones indices are positively associated with metabolically obese phenotypes risk, especially MUNO and MUO phenotypes.

Telomere length across the spectrum of metabolic health – an analysis from the LIPIDOGEN2015 study

IntroductionBackground: Telomere length is a cellular aging marker and correlates with various cardiovascular disease (CVD) risk factors. The current study assessed the association between obesity, metabolic syndrome (MetS), and telomere length.Material and methodsMaterial and methods: The LIPIDOGRAM&amp;LIPIDOGEN2015 study was conducted in primary care in 2015-2016. Recruited patients to the LIPIDOGEN2015 cohort (n=1788) were a random subset of patients of the LIPIDOGRAM2015 (n=13,724) study. For the aims of this analysis, the recruited patients were divided into four groups based on the presence of MetS: healthy slim (HS), metabolically healthy obese (MHO), non-obese with MetS (NOMS), and metabolically unhealthy obese (MUO). Relative telomere length (RTL) was measured using quantitative polymerase chain reaction (qPCR).ResultsResults: 1516 patients (85%; females - 59.7%, mean age- 50.3 years) were included for final analyses. An increase in body mass index (BMI), waist circumference, prevalence of diabetes mellitus, hypertension, dyslipidemia, and history of myocardial infarction moving from HS to MUO were observed. MUO group exhibited the highest triglycerides and lowest high-density lipoprotein (HDL-C) levels. Univariable regression analyses indicated that NOMS (p=0.038) and MUO (p=0.003) were associated with significantly decreased RTL. After adjustment for age, gender, education, smoking, place of residence, and myocardial infarction, the association was no longer statistically significant.ConclusionsConclusions: Despite the lack of statistical significance in the multivariate analysis, the univariate results suggest that both MUO and NOMS phenotypes contribute to the shortening of telomere length. These results may also indicate that MetS, irrespectively on obesity occurrence, is responsible for the shortened lifespan.

Systemic Inflammation Across Metabolic Obesity Phenotypes: A Cross-Sectional Study of Korean Adults Using High-Sensitivity C-Reactive Protein as a Biomarker.

Chronic systemic inflammation is a hallmark of obesity. This cross-sectional study aimed to investigate the association between metabolic obesity phenotypes and inflammatory markers in Korean adults (N = 21,112; mean age: 50.9 ± 16.6). Metabolic obesity phenotypes were categorized into metabolically healthy non-obesity (MHNO), metabolically unhealthy non-obesity (MUNO), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO) based on body mass index and the presence of any metabolic abnormalities. High-sensitivity C-reactive protein (hs-CRP) levels were measured. Multiple linear regression was used to determine the association between obesity phenotypes and hs-CRP levels. In the male sample, compared to the MHNO type, the MUNO, MHO, and MUO types were associated with a 22.3% (95% confidence interval; CI: 14.7-30.3%), 15.8% (95% CI: 2.6-30.7%), and 12.5% (95% CI: 3.0-22.9%) increase in the hs-CRP levels, respectively. The association between metabolic obesity types and hs-CRP levels was stronger among the female sample; compared to the MHNO type, the MUNO, MHO, and MUO types were associated with a 30.2% (95% CI: 22.8-38.2%), 16.0% (95% CI: 6.5-26.4%), and 22.8% (95% CI: 13.6-32.8%) increase in the hs-CRP levels, respectively. Our findings indicate a varying profile of systemic inflammation across different metabolic obesity phenotypes.

Transitions in metabolic syndrome and metabolic obesity status over time and risk of urologic cancer: A prospective cohort study.

The effects of metabolic obesity (MO) phenotypes status and their dynamic changes on urologic cancer (UC) is ignored. We aimed to investigate the association between metabolic syndrome (MetS) and MO status at baseline, their dynamic changes and UC risk. This paper studied 97,897 subjects who were free of cancers at baseline (2006-2007). Individuals were classified into four MO phenotypes by MetS and obesity at baseline. Transitions in MetS and MO status from 2006-2007 to 2008-2009 were considered. The hazard ratios (HRs) and 95% confidence intervals (CIs) for UC were assessed by multifactorial Cox proportional risk regression models. The main limitations of this study are as follows: the ratio of men to women in the cohort is unbalanced; the impacts of MetS and MO on each cancer type (kidney cancer, prostate cancer, bladder cancer) have not been analyzed separately; the transition intervals of MetS and MO phenotypes are relatively short. From baseline (2006-2007) survey to December 31, 2020, during a median follow-up of 14.02 years, 554 cases of UC were diagnosed. Participants with MetS [HRs (95% CI) = 1.26 (1.06-1.49)] and metabolically unhealthy obesity (MUO) [HRs (95% CI) = 1.49 (1.17-1.89)] had significantly higher risk of UC than those with non-MetS and metabolically healthy normal weight (MHN). Transitions in MetS and MO phenotypes over time were studied. Compared with non-MetS to non-MetS, the risks for UC in MetS to MetS [HRs (95% CI) = 1.45 (1.11-1.88)] was increased. Compared with MHN to MHN, both MUO to metabolically healthy obesity (MHO) [HRs (95% CI) = 2.65 (1.43-4.92)] and MUO to MUO [HRs (95% CI) = 1.60 (1.06-2.42)] had significantly higher UC risk. MetS and MUO increased the UC risk at baseline. Transitions of MetS to MetS, MUO to MUO and even MUO to MHO over time significantly increased the risk of UC development.

Metabolite, Biochemical, and Dietary Intake Alterations Associated with Lifestyle Interventions in Obese and Overweight Malaysian Women.

Differences in metabolic regulation among obesity phenotypes, specifically metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO) women, may lead to varied responses to interventions, which could be elucidated through metabolomics. Therefore, this study aims to investigate the differences in metabolite profiles between MHO and MUO women and the changes following a lifestyle intervention. Serum samples from 36 MHO and 34 MUO women who participated in a lifestyle intervention for weight loss were analysed using untargeted proton nuclear magnetic resonance spectroscopy (1H NMR) at baseline and 6 months post-intervention. Anthropometric, clinical, and dietary intake parameters were assessed at both time points. Both groups showed differential metabolite profiles at baseline and after six months. Seven metabolites, including trimethylamine-N-oxide (TMAO), arginine, ribose, aspartate, carnitine, choline, and tyrosine, significantly changed between groups post-intervention, which all showed a decreasing pattern in MHO. Significant reductions in body weight and body mass index (BMI) in the MUO correlated with changes in the carnitine and tyrosine levels. In conclusion, metabolite profiles differed significantly between MHO and MUO women before and after a lifestyle intervention. The changes in carnitine and tyrosine levels in MUO were correlated with weight loss, suggesting potential targets for therapeutic intervention.

Metabolic obesity phenotypes and the risk of cancer: a prospective study of the Kailuan cohort.

Obesity is as an important risk factor for chronic diseases. Metabolically healthy obesity (MHO) is considered a benign state. The association between metabolic health and obesity categories and cancer risk remains unclear. This study aimed to investigate the relationship between metabolic health status combined with obesity phenotypes and the risk of cancer. Data from 91,834 participants in the Kailuan cohort were analyzed, excluding individuals with a body mass index (BMI) < 18.5 kg/m² and those with a history of cancer. Obesity phenotypes were classified based on BMI and waist circumference (WC) combined with metabolic health status, resulting in six phenotypes. Cox proportional hazard regression models were used to assess the association between metabolic health and obesity phenotypes with cancer risk and all-cause mortality. The prevalence of metabolically healthy obesity and metabolically unhealthy obesity defined by BMI was 6.86% and 12.18%, while that defined by WC was 20.79% and 25.76%, respectively. Compared to metabolically healthy participants, individuals with an unhealthy metabolic status had a significantly higher risk of cancer (HR, 1.09; 95% CI, 1.03-1.15; p=0.004). The hazard ratios for cancer were 1.19, 1.23, 1.20, and 1.55 for individuals with one, two, three, and four metabolic disorders, respectively. Among those classified as metabolically unhealthy, both overweight and obesity were associated with a protective effect on cancer risk (HR, 0.88; 95% CI, 0.80-0.96; p=0.006 for overweight; HR, 0.87; 95% CI, 0.78-0.97; p=0.010 for obesity). However, abdominal obesity significantly increased cancer risk in both metabolically healthy and unhealthy participants. In subgroup analysis, simple obesity showed a protective trend against cancer in those with respiratory cancers, while abdominal obesity consistently posed a risk for various cancer types. Metabolically unhealthy status and abdominal obesity are risk factors for cancer and all-cause mortality, whereas simple obesity offers protective effects against cancer and all-cause mortality in metabolically unhealthy individuals. These findings suggest that maintaining metabolic health and reducing the metabolic risks associated with abdominal obesity should be key targets for cancer prevention.

Genetic influences, lifestyle and psychosocial aspects in relation to metabolically healthy obesity and conversion to a metabolically unhealthy state.

About 10%-30% of individuals with obesity are metabolically healthy, but the specific characteristics of the metabolically healthy obesity (MHO) phenotype remain unclear. We aimed to examine how physical activity, education, depressive symptoms and genetic predisposition to obesity differ between individuals with MHO and those with metabolically unhealthy obesity (MUO), and whether these factors predict stability in MHO or conversion to a metabolically unhealthy state. We retrieved data on 9809 individuals with obesity from the Health and Retirement Study collected between 2006 and 2016. We compared how physical activity, education, depressive symptoms and a polygenic score for higher body mass index (BMI) (PGSBMI) differed cross-sectionally between MHO and MUO using logistic regression. We then examined if the same factors predict conversion to a metabolically unhealthy state over 4 years in individuals with MHO. Individuals with MHO had higher physical activity (odds ratio [OR] = 0.81), higher education (OR = 0.83) and lower depressive symptoms (OR = 1.14) compared to those with MUO but did not differ in the PGSBMI. The associations were slightly attenuated in mutually adjusted models. None of the factors were associated with conversion from MHO to a metabolically unhealthy state. However, a higher PGSBMI indicated 24% lower risk of conversion to a metabolically unhealthy state (p = 0.07). Physical activity, education and depressive symptoms differed between MHO and MUO, even when mutually adjusted for, but did not predict conversion from a metabolically healthy to unhealthy state. Although not statistically significant, the results indicated that those with genetically predicted high BMI are more likely to maintain MHO and not convert to a metabolically unhealthy state.

Association of metabolically healthy obesity with risk of heart failure and left ventricular dysfunction among older adults.

Obesity is major cause of heart failure (HF), but it is related with a better prognosis among the elderly. Therefore, we aimed to examine whether metabolically healthy obesity (MHO) in late life increases HF risk and is reflected in impaired left ventricular (LV) function. The participants were grouped into four metabolic phenotypes based on obesity and metabolic status: metabolically healthy non-obesity (MHN), MHO, metabolically unhealthy non-obesity (MUN), metabolically unhealthy obesity (MUO). Association of metabolic phenotypes with LV function was evaluated using multiple linear regression models. And association between metabolic phenotypes and risk of HF was assessed using multivariable logistic regression models. In addition, we validated the association of metabolic phenotypes and HF risk in a separate longitudinal cohort. In the primary cohort of 6335 participant, there were 434 participants diagnosed with HF. Compared to MHN participants, the risk of HF was higher among older individuals with MUN (OR = 1.51 [95% CI: 1.14-1.99]) and MUO (OR = 2.01 [95% CI: 1.39-2.91]), but not older individuals with MHO (OR = 0.86 [95% CI: 0.30-2.43). Regarding to LV function, worse LV diastolic function was noted among MUN and MUO individuals rather than MHO individuals. Older adults with MHO were also not associated with risk of HF in the validation cohort. Among older individuals, the metabolic health status might modify the association of obesity with risk of HF and LV diastolic dysfunction. Worse LV diastolic function and higher risk of HF were just noted in individuals with MUO, but not in those with MHO.

Prevalence and inequalities of obesity and associated complications in China: A multicentre nationwide survey

ObjectivesObesity is a risk factor for chronic diseases. The prevalence of obesity is rapidly increase and a significant social inequality exists. This study aimed to analyse obesity prevalence and complications in different regions and occupations in China. Study designMulticentre cross-sectional study. MethodsData from 62,893 adults in 10 Chinese provinces were collected in 2022. Measures included body mass index (BMI), metabolic status and complications. Analysis was stratified by gender, age, region and occupation, with results adjusted for age and gender. ResultsThe average BMI was 23.81 ± 3.42 kg/m2, with overweight and obesity prevalence at 34.29 % and 11.24 %, respectively. North China had the highest obesity rate (27.93 %), followed by West (26.64 %), South (25.37 %) and East China (20.06 %). Functionaries (e.g. as civil servants, corporate executives) had higher BMI than employees or intellectual professionals, while workers had higher BMI than farmers. Intellectual professionals had the lowest rates of metabolically healthy obesity (MHO) at 4.90 % and metabolically unhealthy obesity (MUO) at 3.47 %, followed by employees (MHO 6.63 %, MUO 4.45 %) and functionaries (MHO 6.74 %, MUO 4.94 %). Workers had the highest MHO prevalence rate at 8.51 %, while farmers had the highest MUO rate at 6.16 %. Obesity-associated complications were 1.5–3 times more common among obese individuals than those in the normal BMI category, with inequality observed across different occupational groups. ConclusionsIn China, a large number of adults with obesity have poor metabolic health, highlighting the importance of considering metabolic status when addressing obesity-related chronic diseases. Addressing the inequality in obesity rates can inform public health strategies to tackle the increasing problem of obesity and its associated complications in China.

Effect of Obesity and Metabolic Health Status on Metabolic-Associated Steatotic Liver Disease among Renal Transplant Recipients Using Hepatic Steatosis Index

Background/Objectives: Obesity and metabolic conditions increase the risk of metabolic-associated steatotic liver disease (MASLD). This study examined the risk of MASLD in 137 renal transplant recipients (RTRs) from a single-center hospital on the basis of their obesity and metabolic health status. Methods: Participants were categorized into four groups: metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically abnormal nonobese (MANO), and metabolically abnormal obese (MAO). MASLD was assessed using the hepatic steatosis index (HSI), calculated as 8 × (aspartate aminotransferase/alanine aminotransferase ratio) + body mass index + 2 (if diabetic) + 2 (if woman). The HSI scores were 29.50 ± 4.55, 38.08 ± 5.44, 33.61 ± 5.23, and 39.86 ± 4.13 in the MHNO, MHO, MANO, and MAO groups, respectively (p &lt; 0.05). Results: Overall, 25.55% of the participants (57.14% men) were classified as having MASLD (HSI &gt; 36). A multivariate-adjusted regression analysis revealed significantly higher HSI scores in the MAO group than in the MHNO group. Both MHO and MANO groups also had significantly higher HSI scores. The odds ratios for more severe MASLD were 2.74 (95% CI: 0.88–8.52) for the MANO group and 74.59 (95% CI: 13.29–418.68) for the MAO group compared with the MHNO group. Conclusions: These findings suggest that RTRs with obesity have a higher risk of MASLD, but even those with a normal weight and metabolic abnormalities are at increased risk.

Relationship between Body Adiposity Indices and Reversal of Metabolically Unhealthy Obesity 6 Months after Roux-en-Y Gastric Bypass.

The factors determining the reversal of metabolically unhealthy obesity (MUO) to metabolically healthy obesity (MHO) after Roux-en-Y gastric bypass (RYGB) are not completely elucidated. The present study aims to evaluate body adiposity and distribution, through different indices, according to metabolic phenotypes before and 6 months after RYGB, and the relationship between these indices and transition from MUO to MHO. This study reports a prospective longitudinal study on adults with obesity who were evaluated before (T0) and 6 months (T1) after RYGB. Bodyweight, height, waist circumference (WC), BMI, waist-to-height ratio (WHR), total cholesterol (TC), HDL-c, LDL-c, triglycerides, insulin, glucose, HbA1c and HOMA-IR were evaluated. The visceral adiposity index (VAI), the conicity index (CI), the lipid accumulation product (LAP), CUN-BAE and body shape index (ABSI) were calculated. MUO was classified based on insulin resistance. MUO at T0 with transition to MHO at T1 formed the MHO-t group MHO and MUO at both T0 and T1 formed the MHO-m and MUO-m groups, respectively. At T0, 37.3% of the 62 individuals were classified as MHO and 62.7% as MUO. Individuals in the MUO-T0 group had higher blood glucose, HbA1c, HOMA-IR, insulin, TC and LDL-c compared to those in the MHO-T0 group. Both groups showed significant improvement in biochemical and body variables at T1. After RYGB, 89.2% of MUO-T0 became MHO (MHO-t). The MUO-m group presented higher HOMA-IR, insulin and VAI, compared to the MHO-m and MHO-t groups. CI and ABSI at T0 correlated with HOMA-IR at T1 in the MHO-t and MHO-m groups. CI and ABSI, indicators of visceral fat, are promising for predicting post-RYGB metabolic improvement. Additional studies are needed to confirm the sustainability of MUO reversion and its relationship with these indices.

Relationships of Thickness of Perirenal Fat with Urinary Levels of MCP-1 and NGAL in Patients with Hypertension.

We conducted a study to determine the relationships between perirenal fat (PRF) thickness and urinary levels of monocyte chemoattractant protein-1 (MCP-1) and neutrophil gelatinase-associated lipocalin (NGAL) in patients with hypertension (HTN). In 338 HTN patients (aged 63.51±12.3 on average), MCP-1 and NGAL levels were studied using enzyme-linked immunosorbent assay (ELISA). To measure PRF thickness, all patients underwent CT scans. We considered PRF thickness ≥1.91 cm as the diagnostic threshold for perirenal obesity. Patients with excessive PRF thickness exhibited significantly lower levels of MCP-1 and NGAL compared with those with PRF thickness ≥1.91 cm: 0.98 pg/mL (interquartile range, 0.21 to 2.05) vs. 2.35 pg/mL (0.37 to 5.22) for MCP-1 and 50.0 pg/mL (48.9 to 67.8) vs. 98.3 pg/mL (68.4 to 187.1) for NGAL. We found a relationship of PRF thickness with both MCP-1 (r=0.46, P<0.05) and NGAL (r=0.53, P<0.05), the levels of which were significantly different in patients with first- and third-stage chronic kidney disease: 0.33 pg/mL (0.21 to 1.35) vs. 4.47 pg/mL (0.23 to 10.81); 50.0 pg/mL (49.4 to 85.5) vs. 126.45 pg/mL (57.5 to 205.15), respectively (P=0.04). Patients with metabolically healthy obesity (MHO) had significantly lower MCP-1 levels than those with metabolically unhealthy obesity (MUHO): 0.65 pg/mL (0.21 to 2.15) vs. 3.28 pg/mL (2.05 to 5.22) (P=0.014). MHO patients showed significantly lower NGAL levels than MUHO patients: 50.0 pg/mL (49.4 to 62.2) vs. 98.3 pg/mL (50.0 to 174.8) (P=0.04). Multiple linear regression analysis revealed significant relationships of MCP-1 with PRF thickness (β±standard error, 0.41±0.15; P<0.001) and smoking (0.26±0.13; P=0.01) and of NGAL with age (0.45±0.16; P<0.01) and PRF thickness (0.49±0.15; P<0.001). We identified higher concentrations of renal fibrosis markers in patients with perirenal and metabolically unhealthy obesity as well as a link between PRF thickness and MCP-1 and NGAL levels in urine.

Dietary inflammatory index and its relationship with obesity phenotypes: a cross- sectional analysis from RaNCD cohort study

PurposeThe potential dietary inflammatory index (DII) and the phenomenon of obesity have been linked in recent studies, but it is unclear whether this connection is dependent on metabolic status. Therefore, it was thought that this research would be useful in establishing the relationship between obesity phenotypes and DII.MethodsThe 5956 people who took part in the Ravansar non-communicable diseases (RaNCD) cohort research (MHNO) were put into four groups: metabolically unhealthy obesity (MUO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO), and metabolically healthy non-obesity. According to the International Diabetes Federation's criteria, MUO exhibits at least two metabolic disorders and have a body mass index of 30 kg/m2 or higher. DII was extracted from the participant's dietary consumption data.ResultsWhen possible confounders like age, gender, smoking, drinking alcohol, and exercise were taken into account, more adherence to DII was linked to a higher odds of MHO compared to MHNO (OR: 1.44; CI 95% 1.18, 1.75). Additionally, we discovered that greater adherence to DII was significantly related to higher odds for MUO compared to MHNO (OR: 1.67; CI 95% 1.3, 2.15). However, we found no association between adherence to DII and MUNO.ConclusionsOur findings indicated that greater adherence to DII was significantly associated with higher odds of MUO. However, it substantially increased the chances of both phenotypes of obesity.Level of evidence Level V–Cross-sectional observational study.

Impact of bariatric surgery on carotid intima-media thickness and arterial stiffness in metabolically healthy obesity: a prospective study.

Cardiovascular disease is one of the leading causes of mortality in patients with obesity. Metabolically healthy obesity (MHO), in which people do not have metabolic disorders, is a transient state of obesity. However, over the long term, a proportion of individuals with MHO develop metabolic syndrome (MetS). We aimed to investigate the effect of substantial weight loss following bariatric surgery in MHO on carotid intima-media thickness (CIMT) and pulse-wave velocity (PWV), which are independent predictors of subclinical atherosclerosis. This prospective study included 38 patients (34 women, four men) undergoing bariatric surgery who had severe obesity but without comorbidities (hypertension, diabetes, and hyperlipidemia), and 28 control individuals who were matched for age and sex. CIMT and PWV of the left common carotid artery were measured. At 12-month follow-up after bariatric surgery, measurements were repeated in the 38 patients with obesity. Mean baseline body mass index (BMI) in the MHO group was 40.55 ± 3.59kg/m2, which decreased by 33.1% after bariatric surgery. Compared with controls, CIMT and PWV were increased in MHO (543.53 ± 55.29 vs. 407.82 ± 53.09μm, 6.70 ± 1.22 vs. 5.45 ± 0.74m/s, respectively; all P < 0.001). At 12 months post-bariatric surgery, CIMT in MHO was lower than baseline (466.79 ± 53.74 vs. 543.53 ± 55.29μm, P = 0.009), but PWV was not significantly different from baseline (6.27 ± 0.86 vs. 6.70 ± 1.22m/s, P = 0.132). Multivariate regression showed that BMI was an independent predictor of CIMT (β = 0.531, P < 0.001). Carotid artery structure and function were impaired in MHO, and improved carotid artery structure was associated with weight loss in MHO after bariatric surgery.

Metabolically healthy obesity and chronic kidney disease risk: exploring the dynamics.

Obesity represents a prevalent global health concern with significant implications for various diseases, including chronic kidney disease (CKD). Within this landscape, the phenomenon of metabolically healthy obesity has emerged, challenging traditional notions about the health risks associated with excess weight. While traditional CKD risk factors involve obesity, metabolic syndrome, diabetes, and hypertension, the metabolically healthy obese (MHO) subgroup disrupts these assumptions. Our main objective in this study is to integrate existing literature on CKD in MHO individuals. In this endeavor, we delve into the pathophysiological foundations, the transition between obesity phenotypes and their impact on renal health, examine the implications of their metabolic resilience on mortality within a renal context, and explore potential management strategies specifically designed for MHO individuals. Offering a comprehensive overview of the pathophysiology, we cover various factors contributing to the risk of CKD in the metabolically healthy obese setting, including inflammation, cytokines, hemodynamics, and the renin-angiotensin-aldosterone system, gastrointestinal microbiota, diet, exercise, adipose distribution, and lipotoxicity. Through this synthesis, we aim to provide a comprehensive understanding of the risk of CKD in those classified as MHO.

Association between metabolically healthy obesity and carotid intima-media thickness in Korean adolescents with overweight and obesity.

Data regarding the association between metabolically healthy obesity (MHO) and preclinical atherosclerosis in childhood are lacking. Carotid intima-media thickness (cIMT) is a noninvasive method used to assess cardiovascular risk. This study examined the relationships among cIMT, metabolic phenotypes, and cardiometabolic risk factors (CMRFs) in overweight and obese adolescents. Anthropometric, biochemical, and cIMT data were collected. The study participants were categorized as MHO or metabolically unhealthy obesity (MUO) based on insulin resistance. CMRFs were assessed using blood pressure (BP); levels of triglycerides, high-density lipoprotein cholesterol (HDL-C), and fasting plasma glucose; or a diagnosis of diabetes mellitus. Differences in cIMT values were evaluated according to the metabolic phenotype and factors associated with cIMT. Among the 111 participants (80 boys, 72.1%), 23 (20.7%) were classified as MHO and 88 (79.3%) as MUO. The MHO group exhibited lower glycated hemoglobin and triglyceride levels and higher HDL-C levels compared to those exhibited by the MUO group (all P<0.01). The cIMT values did not differ significantly between the MHO and MUO groups. The high cIMT tertile group revealed higher systolic BP compared to that exhibited by the low cIMT tertile group (123.7±2.1 mmHg vs. 116.9±1.6 mmHg, P=0.028). Mean cIMT was positively correlated with age (β=0.009) and body mass index (BMI) (β=0.033) after adjusting for covariates (both P<0.05). In overweight and obese Korean adolescents, cIMT was associated with age and BMI but not with metabolic phenotype or CMRFs. Further research is warranted to determine the relationship between cIMT during adolescence and cardiovascular outcomes during adulthood.

Biomarkers of Intestinal Permeability are Associated with Inflammation in Metabolically Healthy Obesity, but not Normal-Weight Obesity.

Systemic inflammation is reported in normal-weight obesity (NWO) and metabolically healthy obesity (MHO), which may be linked to their increased cardiovascular disease (CVD) risk. Yet, drivers of this inflammation remain unclear. We characterized factors known to influence inflammatory status (i.e., intestinal permeability, adipose tissue, diet quality, microbiota) - and their relationships with measured inflammation - in NWO and MHO, healthy controls (CON) and metabolically unhealthy obesity (MUO; N=80; n=20/group). Serum indicators of intestinal permeability and inflammation were assessed using ELISA and/or multiplex. Total, visceral, and percent body fat were measured with dual-energy X-ray absorptiometry (DXA). Fecal microbiota composition was assessed via 16S rRNA sequencing (n=9-10/group). For C-reactive protein (CRP), MUO > NWO > CON (p<0.0001). In MHO, CRP was intermediate - and similar to - both MUO and NWO. Lipopolysaccharide binding protein (LBP) and the ratio of LBP to soluble CD14 (sCD14) were higher in MHO and MUO versus CON/NWO (p's<0.0001). Across correlation and regression analyses, LBP consistently displayed the strongest relationships with CRP in the entire sample (r=0.78;β = 0.57;p's<0.0001) and in MHO (r=0.74;p<0.01), but not NWO (r=0.37;p = 0.11). Shannon index was higher in CON compared to MUO (p<0.05) and inversely correlated with CRP in the full sample (r=-0.37;p<0.05). These data are consistent with the notion that intestinal permeability is associated with low-grade inflammation in MHO, which could be implicated in this population's reported CVD risk.