Metabolically Unhealthy Obese Research Articles

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.

The joint associations of high birth weight and not having siblings with metabolic obesity phenotype among school-aged children and adolescents: A National Survey in China.

Birth weight (BW) and sibling's status are two important indicators of early intrauterine environment and subsequent living environment, but no evidence has emerged on their joint associations on metabolic obesity phenotype. To determine the joint associations between BW and single-child status with childhood metabolic obesity phenotype was our purpose. A cross-sectional assessment of children and adolescents aged 7-18 years was performed in Chinese seven provinces in 2013. We obtained anthropometric, blood pressure and biochemical measurements, and distributed questionnaires covering demographic, neonatal and lifestyle characteristics. The metabolic obesity phenotype was defined by 2018 consensus-based criteria. Logistic regression and restricted cubic spline models were applied to evaluate the associations of BW and metabolic obesity phenotype, and estimate the multiplicative interactions and the combined associations of BW and single-child status with metabolic obesity phenotype. Of enrolled 12 346 children and adolescents, the prevalence of metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) was 1.96% and 3.03%. There were 8.95% and 4.03% children with high BW or low BW, and 67.55% did not have siblings. High BW was positively associated with MHO (OR=1.94, 95%CI=1.28-2.94). Single-child also had increased odds of MHO and MUO (p < 0.05), and it had joint associations with high BW showing 0.85- to 2.58-fold higher odds of MUO and MHO. High BW and single-child status have joint positive associations with the subsequent odds of MHO and MUO, which should be jointly prevented through earlier screening and subsequent preventive strategies.

Association between different metabolic phenotypes and the development of hypothyroidism: 9 years follow-up of Tehran thyroid study.

The association between metabolic phenotypes and thyroid function has not yet been established; therefore, this study examined whether different metabolic phenotypes are associated with the development of hypothyroidism. Study participants were selected from the Tehran Thyroid Study (TTS). A total of 3338 euthyroid adults were included and categorized into four obesity phenotype groups: metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy obese (MUO). The participants were assessed at baseline and during three follow-up studies at three-year intervals. Multiple logistic regression analysis was used to examine the relationship between metabolic phenotypes and the development of hypothyroidism. In the total population, the chi-square test was only significant (P=0.008) in 3rd year with a higher prevalence of hypothyroidism in the MUNW phenotype, followed by MHO, MUO, and MHNW. Moreover, in the 3rd and 9th years of follow-up, hypothyroidism was more prevalent in MUO only in male subjects (P=0.002 and 0.035, respectively). In the unadjusted model, the MHO phenotype increased the odds of hypothyroidism compared with the MHNW phenotype (OR=1.51; 95% CI=1.04, 2.18; P-value=0.031). After adjusting for confounding factors, the odds of hypothyroidism were higher in the MUNW (OR=1.86; 95% CI=1.17, 2.96; P-value=0.008), MHO (OR=1.71; 95% CI=1.09, 2.67; P-value=0.018), and MUO (OR=1.64; 95% CI=1.03, 2.62; P-value=0.036) phenotypes than in the MHNW group. The MUNW phenotype increased the risk of hypothyroidism compared to MHNW, only in males. However, in females, the MHO phenotype increased the risk of hypothyroidism compared to MHNW. Both obesity and metabolic abnormalities are associated with hyperthyroidism. Healthy metabolic and weight maintenance were associated with a lower risk of hypothyroidism in males and females.

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.

Prevalence and Predictive Clinical Characteristics of Metabolically Healthy Obesity in Obese Children and Adolescents.

The increasing prevalence of childhood obesity and accompanying comorbidities all over the world constitutes one of the most important public health problems of the changing world. The frequency and causes of the metabolically healthy obesity (MHO) phenotype in children is not clear. The objective is to determine the prevalence of the MHO phenotype in obese Turkish children and adolescents and to identify clinical and biochemical indicators for this phenotype. Eight hundred forty-seven obese children and adolescents, aged 3-18 years with BMI-SDS >+2 SD from the obesity outpatient clinic were included. Demographic, anthropometric, and physical examination information was collected from patient medical files. In addition, obesity-related comorbidities and results of laboratory tests were obtained. For study purposes, obese patients with no cardiometabolic risk factors were accepted as MHO, and those with ≥1 cardiometabolic risk factor were considered metabolically unhealthy obese (MUO). MHO was defined according to Damanhoury's criteria. Out of 847 children (mean age 10.6±3.4 years) who met the study criteria, 289 (34.1%) were diagnosed with MHO. Being younger, prepubertal, having relatively low BMI, low waist/hip ratio, low insulin resistance (HOMA-IR) index, high high-density lipoprotein, low triglyceride, low fasting insulin and glucose levels, low uric acid and low alanine transaminase (ALT) levels were associated with MHO. The MHO phenotype was present in just over a third of this obese pediatric cohort. The most important factors associated with MHO; age, waist-hip ratio, and BMI were determined.

RELATIONSHIP OF THE LEVELS OF TRYPTOFAN METABOLITES WITH ADIPOKINES AND MYOKINES IN PATIENTS WITH VARIOUS OBESITY PHENOTYPES

Relevance. In the last 10 years, there has been an active study of the system of conjugation of the metabolism of a macroorganism and its microbiome. The microbiotic conversion of tryptophan into biologically active signaling molecules is a potential regulatory mechanism by which the intestinal microbiota can change the metabolism of both intestinal cells and the entire macroorganism. However, the content of tryptophan metabolism metabolites in patients with metabolically healthy (MHO) and metabolically unhealthy obesity (MUHO), as well as the relationship of these metabolites with adipokines and myokines, has not yet been studied. Purpose of the study. To study the content of metabolites of tryptophan metabolism in the blood serum of obese patients and to evaluate the relationship between the content of adipokines and myokines and the content of tryptophan metabolism metabolites of bacterial and non-bacterial origin in the blood serum of patients with MSO and MNSO. Material and methods. 266 patients were examined, including 138 healthy non-obese volunteers and 128 obese patients, of whom two subgroups were formed: 30 patients with MHO and 41 patients with MUHO. Metabolite concentrations in blood and feces were determined using high performance liquid chromatography. Quantitative analysis of adipokines and myokines was performed by multiplex enzyme immunoassay. The content of metabolites of tryptophan metabolism in blood serum was assessed by high performance liquid chromatography with mass spectrometric detection. Results. For patients with obesity, an increase in the serum concentration of kynurenine, kynurenic and quinoline acids, indole-3-lactate, indole-3-butyrate and indole-3-acetate was established. Patients with MHO and MUHO were statistically significantly different only in terms of serum tryptamine concentration. Regardless of the presence/absence of metabolic disorders in obese patients, it has been established that xanthurenic and quinoline acids are interrelated with the concentration of myostatin in the blood serum. At the same time, for patients with MHO, it was shown that the serum concentration of the dominant catabolite of the indole pathway, indole-3-acetate, is interconnected with the content of insulin and leptin in the blood serum. Whereas in patients with MUHO, leptinemia is consistent with a high concentration of anthranilic acid in the blood serum, and hyperinsulinemia, on the contrary, is associated with a low concentration of indole-3-propionate in the blood serum

Role of genetic modification of the PNPLA3 gene in predicting metabolically unhealthy obesity and metabolic associated fatty liver disease in children

Introduction and aim. Single nucleotide variants (SNV) of the patatin‐like phospholipase domain‐containing protein 3 (PNP-LA3) gene play an important role in hepatic lipid remodeling and lipogenesis de novo, which is associated with the development of metabolically unhealthy obesity (MUO) and metabolic associated fatty liver disease (MAFLD). The aim of the study was to define the contribution of SNV PNPLA3 gene to the development of MUO, complicated by MAFLD in children. Material and methods. 200 obese children aged 6-18 years were examined. The main group (n=118) was represented by children with MUO. The control group (n=82) consolidated of children with metabolically healthy obesity (MHO). Whole genome sequencing (CeGat) was performed in 31 children of the main and 21 children of the control group. Results. Among obese children, 14 variants of SNV PNPLA3 (rs139051, rs34179073, rs2294918, rs139047, rs779127153, rs2076212, rs738409, rs738408, rs4823173, rs2072906, rs2076213, rs141106484, rs138736228) were identified, including SNV PNPLA3 g.44322818, not described in the dbSNP core database. The role of the following SNV PNPLA3 genotypes in the development of MUO complicated by MAFLD was revealed: rs738409 C/G (Relative risk (RR)=1.71); rs738408 C/T (RR=1.71); rs4823173 G/A (RR=1.57); rs2072906 A/G (RR=1.57) with Sensitivity (Se)=0.63 and Specificity (Sp)=0.72. Conclusion. The contribution to the development of MUO complicated by MAFLD in children is made by the linked association of genotypes: rs738409 C/G, rs738408 C/T, rs4823173 G/A and rs2072906 A/G out of 14 PNPLA3 SNVs diagnosed by us.

Abstract MP31: Serum Metabolite Signatures for Metabolic Healthy and Unhealthy Obesity: The Bogalusa Heart Study

Introduction: Mechanisms for metabolically healthy obesity (MHO) are not well studied. Methods: We performed cross-sectional analyses among 1,261 participants of the Bogalusa Heart Study 2013-2016 survey. A total of 887 known serum metabolites were profiled using an untargeted approach. Participants who met all the following five criteria were considered metabolically healthy, otherwise, unhealthy: 1) SBP &lt;130 mm Hg and DBP &lt;85 mm Hg; 2) fasting glucose &lt;100 mg/dl; 3) triglycerides &lt;150 mg/dl; 4) HDL ≥40 mg/dl in men and ≥50 mg/dl in women; and 5) not taking medications for hypertension, diabetes, or dyslipidemia. We tested associations of metabolites with metabolic health status, controlling for age, sex, race, education, smoking, drinking, and kidney function. Results: Among 648 obese participants (BMI≥30 kg/m 2 ), 66 (10.2%) had MHO. After Bonferroni correction, 26 metabolites differed between MHO and metabolically unhealthy obesity (MUO) groups. Amino acids serine , glycine, and histidine , fatty acid N-linoleoylserine , 4 sphingolipids, and 3 plasmalogens were significantly higher among MHO individuals. These metabolites are functionally relevant to metabolic health ( Table ). Carbohydrates mannose , lactate, and pyruvate , urate , amino acids glutamate , 1-carboxyethylvaline , 1-carboxyethylleucine , 3-methyl-2-oxovalerate , and 3-methyl-2-oxobutyrate , PE(18:0/18:2(9Z,12Z)) , and 5 diacylglycerols were significantly higher in the MUO group. These metabolites are mostly food additives or reduce gut microbiota diversity ( Table ). Furthermore, histidine was associated with metabolic health only among overweight and obese participants. Odds ratios of being metabolically healthy per SD increase of histidine among normal weight, overweight, and obese participants were 1.05 (95% CI: 0.83-1.32), 1.54 (95% CI: 1.10-2.14), and 2.12 (95% CI: 1.56-2.89), respectively (P for group difference=1.41E-4). Conclusion: We identified potential intervention targets to improve metabolic health in obesity.

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.

The association between egg consumption and metabolic health status in overweight and obese adolescents

Existing evidence examining the relation between egg consumption and metabolic health of overweight/obese adolescents is scarce. We examined the association between egg consumption and metabolic status in Iranian overweight/obese adolescents. Using multistage cluster random sampling approach, overweight/obese adolescents (n = 203) with ages from 12 to 18 years old were selected for the present cross-sectional study. A validated 147-item food frequency questionnaire was adopted to determine usual dietary intakes. Blood pressure and anthropometric data and were assessed, and levels of lipid profile, insulin, and glucose were measured by collecting fasting blood samples. Participants were classified into metabolically healthy obese (MHO) or metabolically unhealthy obese (MUO) based on two methods of International Diabetes Federation (IDF) and the combination of IDF with Homeostasis Model Assessment Insulin Resistance (HOMA-IR). In total, 67 (33.0%) and 79 (38.9%) adolescents were classified as MUO based on IDF/HOMA and IDF definitions, respectively. Considering IDF criteria, the highest intake of egg was related to decreased chance of MUO, in crude (OR 0.22; 95% CI 0.10–0.48) and maximally-adjusted model (OR 0.25; 95% CI 0.10–0.59). Considering IDF/HOMA-IR criteria, similar results were obtained (crude model: OR 0.24; 95% CI 0.11–0.52; fully-adjusted model: OR 0.28; 95% CI 0.11–0.69). Stratified analyses found stronger relation among boys (vs. girls) and overweight (vs. obese) individuals. In conclusion, higher egg consumption was negatively related to decreased chance of being MUO in overweight/obese adolescents, especially in boys and overweight individuals, regardless of MUO definitions. Prospective studies are required to support our results.

Nonalcoholic Fatty Liver Disease Severity Is Related to Plasma Pro-Oxidative Biomarkers Rather Than Liver Tissue-Measured Nitrogen Metabolism Biomarkers in Population with Obesity and Metabolic Syndrome.

Background: The metabolic syndrome (MS) is associated with an increased production of nitrogen metabolites and elevated oxidative stress, which favors progression of nonalcoholic fatty liver disease (NAFLD). Subjects with the phenotype known as metabolically unhealthy obese (MUO) meet most of the MS cardiometabolic risk criteria and show a higher risk of advanced NAFLD severity, compared with the so-widely known metabolically healthy obese (MHO). Obese individuals with MS are more susceptible to abnormal lipid accumulation in different tissues, whereas oxidative stress and nitrogen metabolites are increased in MS and/or obesity. This study aimed to explore whether plasma- or liver tissue-determined biomarkers of nitrogen metabolism and oxidative stress relate to NAFLD severity and/or metabolic phenotype. Methods: This cross-sectional study included candidates for bariatric surgery with biopsy-proven NAFLD diagnosis and staging. For comparison, the study population was divided according to NAFLD damage (steatohepatitis F0-F1 vs. steatohepatitis F2-F4) and metabolic phenotype (MHO vs MUO, based on the MS criteria). Hepatic and plasma concentrations of nitrogen metabolites and oxidative stress biomarkers were determined by enzymatic kinetics assays, enzyme-linked immunosorbent assay, and Greiss reaction. Results: The study population (N = 45) was constituted by patients with obesity and higher prevalence of dyslipidemia, diabetes mellitus, and hypertension. According to plasma biomarkers, MUO phenotype was related to higher cardiometabolic risk; meanwhile, advanced NAFLD damage was related to higher glycated hemoglobin (HbA1c) and triglycerides. Elevated hepatic concentrations of ammonium, nitrites, arginine, and citrulline were found in MUO phenotype, but only higher plasma concentration of malondialdehyde was found as specifically related to advanced NAFLD damage. Conclusions: Circulating biomarkers of redox state were selectively related to advanced NAFLD damage, suggesting prognostic and therapeutic targets. Hepatic concentrations of nitrogen metabolism biomarkers may be more related to cardiometabolic risk.

Identification of Biomarkers Related to Metabolically Unhealthy Obesity in Korean Obese Adolescents: A Cross-Sectional Study

The current study aimed to screen for relationships and different potential metabolic biomarkers involved between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) in adolescents. The study included 148 obese adolescents aged between 14 and 16. The study participants were divided into MUO and MHO groups based on the age-specific adolescent metabolic syndrome (MetS) criteria of the International Diabetes Federation. The current study was conducted to investigate the clinical and metabolic differences between the MHO and MUO groups. Multivariate analyses were conducted to investigate the metabolites as independent predictors for the odds ratio and the presence of the MetS. There were significant differences in the three acylcarnitines, five amino acids, glutamine/glutamate ratio, three biogenic amines, two glycerophospholipids, and the triglyceride-glucose index between the MUO group and those in the MHO group. Moreover, several metabolites were associated with the prevalence of MUO. Additionally, several metabolites were inversely correlated with MHO in the MUO group. In this study, the biomarkers found in this study have the potential to reflect the clinical outcomes of the MUO group. These biomarkers will lead to a better understanding of MetS in obese adolescents.

Адипокины и миокины как индикаторы фенотипов ожирения и их связь с показателями разнообразия микробиома кишечника

Today, metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) are distinguished. Adipose and muscle tissues can determine the obese phenotype due to adipokine and myokine production. Gut microbial community is also involved in MHO. The study was aimed to reveal the features of adipokine and myokine levels and their association with the gut microbiome alpha diversity in patients with MHO and MUO. A total of 265 subjects were divided into two groups: healthy individuals and obese patients. The latter were divided into two subgroups: patients with MHO and patients with MUO. Body mass index, waist circumference, HOMA-IR, adipokine and myokine levels, gut microbiome taxonomic composition, alpha diversity indices were defined in all the surveyed individuals, lipid and carbohydrate metabolism was also assessed. Significant differences in the adipokine and myokine levels and their association with the gut microbiome diversity indicators were revealed in patients with different obese phenotypes. Patients with MHO and MUO showed significantly lower adiponectin levels (р &lt; 0.05) and significantly higher leptin and asprosin levels (р &lt; 0.05) than healthy individuals. Patients with MUO had lower adiponectin and leptin levels (p &lt; 0.05) than patients with MHO. Significantly higher FGF21 levels were observed in patients with MUO. Large-scale correlation analysis revealed the relationship between the glucose levels and the gut microbiome diversity indices that was missing in patients with MUO. This indicated the loss of the microbiota diversity effects on the blood glucose control in individuals with MUO, as well as different regulatory roles in the gut microbiome‒liver‒muscle/adipose tissue axes of individuals with MHO and MUO played by gut microbiota. The findings show the relationship between the gut microbiome diversity and the obese phenotype.

Increased intestinal-fatty acid binding protein in obesity-associated type 2 diabetes mellitus.

Obesity is a traditional risk factor for type 2 diabetes mellitus (T2DM). However, recent studies reported that metabolically unhealthy obesity (MUO) exerts a higher risk of developing T2DM than metabolically healthy obesity (MHO) because of its higher state of insulin resistance. This may happen due to metabolic endotoxemia through gut dysbiosis and increased intestinal permeability. Our study aimed to know the association of intestinal permeability using intestinal fatty acid-binding protein (I-FABP) with obesity-related T2DM patients in Indonesia. This was a cross-sectional study that recruited 63 participants with obesity defined using body mass index (BMI) classification for the Asia-Pacific population (BMI ≥25 kg/m2). All participants were then grouped into T2DM and non-T2DM based on American Diabetes Association (ADA) diagnostic criteria. The I-FABP levels were measured using the enzyme-linked immunosorbent assay method. The I-FABP level of T2DM group was higher compared to non-T2DM group, namely 2.82 (1.23) ng/mL vs. 1.78 (0.81) ng/mL (p<0.001; mean difference 1.033 with 95% CI 0.51-1.55). This difference was not attenuated even after adjustment for age. The fitted regression model using linear regression was: i-FABP = 1.787+1.034*(DM) (R2 = 18.20%, standardized ß = 0.442, p<0.001). This study underscores the association of intestinal permeability with T2DM in people with obesity and supports the evidence of the potential role of intestinal permeability in the pathogenesis of obesity-related T2DM.

Nutrient patterns in relation to metabolic health status in overweight and obese adolescents

The association between dietary nutrient patterns (NPs) and metabolic health status has not been investigated in adolescents. This study aimed to evaluate the relationship between NPs and metabolic health status in Iranian adolescents with overweight and obesity. In this cross-sectional study, 203 obese/overweight adolescents were selected using a multistage mass random sampling method. To assess usual dietary intakes, a validated food frequency questionnaire was applied. Data of anthropometric and blood pressure were collected. Insulin, lipid profile, and glucose levels were determined using fasting blood samples. Two approaches [International Diabetes Federation (IDF) and a combination of IDF with Homeostasis Model Assessment Insulin Resistance (HOMA-IR)] were applied to identify metabolically healthy obese and metabolically unhealthy obese (MUO) adolescents. Participants had a mean age of 13.9 ± 1.61 years and 52.2% of them were girls. Three NPs were identified and labeled as "high minerals and vitamins" (NP1), "high carbohydrate" (NP2) and "high fat and sodium" (NP3). After adjustments for all potential confounders, no significant association was observed between higher adherence to NP1 and NP2 and odds of MUO; however, greater adherence to "high fat and sodium" NP was associated with higher odds of being MUO based on IDF (OR = 3.12; 95% CI 1.19, 8.09) and IDF/HOMA-IR (OR = 2.81; 95% CI 1.02, 7.74) definitions. Stratified analysis revealed that these associations were stronger in boys (versus girls) and obese (versus overweight) adolescents. In conclusion, high adherence to a "high fat and sodium" nutrient pattern was related to elevated chance of being MUO in Iranian adolescents, especially in boys and obese individuals. Therefore, less consumption of trans fatty acids, saturated fatty acids and sodium could be recommended to prevent MUO prevalence especially in boys with obesity.

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.

Is there a link between obesity phenotype and thyroid diseases? A mini-review of current concepts

Abstract Obesity is a chronic, relapsing, and progressive disease that leads to negative health consequences. Excessive adiposity frequently coexists with metabolic and nonmetabolic complications, deteriorating health and reducing quality of life and life span. Individuals with obesity are not a homogenous group and can present different obesity phenotypes. The most common obesity phenotypes include: metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO). The latter category involves those with developed metabolic syndrome (MetS) and non-fully-developed metabolic syndrome (pre-MetS). The fundamental factor leading to obesity is imbalance between energy uptake and expenditure. From this perspective the thyroid gland plays the pivotal role in metabolism regulation and obesity development. The thyroid regulates thermogenesis, appetite, and lipids turnover. Clinically, hypothyroid patients have decreased metabolic rate and subsequently experience increase of BMI and excess adiposity. The interaction between the thyroid gland and obesity is bidirectional. Several mechanisms of alteration of the hypothalamus-pituitary-thyroid axis in obesity are proposed. Excessive adiposity and dysfunction of adipose tissue may contribute to the development of thyroid functional and structural impairment, such as autoimmunity, thyroid nodules, and thyroid cancer. The prevalence of certain thyroid disorders in obese individuals is higher than in nonobese subjects and this trend is more pronounced in unhealthy obesity phenotypes. The aim of this mini-review is to present the current knowledge on the interaction between thyroid gland disorders and obesity, with special focus on obesity phenotypes.

Evaluating the Impact of Obesity and Different Metabolic Statuses on the Prognosis of Hospitalized Patients with Inflammatory Bowel Disease: A Cohort Study

Introduction: Obesity is associated with an increased risk of inflammatory bowel disease (IBD), whereas not all obese individuals have the same effect. In individuals with obesity, the role of metabolic status in the readmission of IBD remains unclear. Our study aimed to evaluate the association between different obesity metabolic phenotypes and the prognosis of IBD patients. Methods: We conducted a longitudinal cohort study using Nationwide Readmissions Database (NRD) (2018 sample). Out of 12,928,231 discharge records, 63,748 records with a discharge diagnosis of IBD were identified for analysis. Cox proportional hazard ratio (HR) with 95% confidence interval (CI) was calculated, adjusting for potential confounders. Results: During a 180-day follow-up in IBD patients with different obesity metabolic phenotypes, all-cause readmission rate, inpatient mortality rate, unplanned readmission rate, total charge, hospitalized length of stay were statistically different (all p < 0.001). After multivariate Cox regression analysis, IBD patients with metabolically unhealthy nonobese (MUNO) had higher risk of readmission (all-cause and unplanned) (HR 1.04, 95% CI: 1.00–1.08 and HR 1.06, 95% CI: 1.02–1.10), and those with metabolically unhealthy obesity (MUO) had higher risk of unplanned readmission (HR 1.08, 95% CI: 1.02–1.15). In subgroup analysis, both the MUNO group and MUO group had higher risk of readmission (all-cause and unplanned) in the ulcerative colitis (UC) subgroup, but only the MUNO group had higher risk of readmission (all-cause and unplanned) (HR 1.05, 95% CI: 1.00–1.10 and HR 1.06, 95% CI: 1.01–1.12) in the Crohn’s disease (CD) subgroup. Conclusion: Metabolic abnormalities were associated with an increased risk of readmission in patients with IBD, regardless of obesity.

Differences in metabolic characteristics between Metabolically Healthy Obesity (MHO) and Metabolically Unhealthy Obesity (MUO) in weight reduction therapy.

Metabolically Healthy Obesity (MHO) is generally recognized as the absence of any metabolic disorders and cardiovascular diseases, including type 2 diabetes, dyslipidemia, and hypertension, in obese individuals; however, it is not clearly defined. Therefore, the present study investigated differences in metabolic characteristics between individuals with MHO and Metabolically Unhealthy Obesity (MUO) during weight reduction therapy. The key factors defining MHO and the importance of weight reduction therapy for MHO were also examined. Cohort data from the Japan Obesity and Metabolic Syndrome (JOMS) study were analyzed. Subjects were divided into the MHO (n = 25) and MUO (n = 120) groups. Prior to weight reduction therapy, serum adiponectin levels were significantly higher in the MHO group than in the MUO group. Serum adiponectin levels also negatively correlated with the area of subcutaneous adipose tissue (SAT) and Homeostasis model assessment (HOMA)-R in the MHO group, but not in the MUO group. Collectively, the present results suggest the importance of adiponectin for maintaining metabolic homeostasis in the MHO group. On the other hand, no significant differences were observed in inflammatory markers between the MHO and MUO groups, suggesting the presence of chronic inflammation in both groups. Furthermore, a positive correlation was noted between changes in serum cystatin C levels and waist circumference in the MHO group, which indicated that despite the absence of metabolic disorders, the MHO group exhibited anti-inflammatory responses during weight reduction therapy. These results underscore the significance of weight reduction even for individuals with MHO.