Metabolically Unhealthy Obese Phenotype Research Articles

The Relationship between Dietary Patterns and Metabolic Phenotypes: A Cross-Sectional Study in a Representative Sample of Iranian Industrial Employees.

Background and Aim: There is limited evidence to support the relationship between dietary patterns and metabolic phenotypes. Therefore, this study aimed to assess the association of dietary patterns with metabolic phenotypes among a large sample of Iranian industrial employees. Methods: This cross-sectional study was conducted among 3,063 employees of Esfahan Steel Company, Iran. Using exploratory factor analysis, major dietary patterns were obtained from a validated short form of food frequency questionnaire. The metabolic phenotypes were defined according to Adult Treatment Panel III guidelines. The independent-sample t-test, one-way analysis of variance, χ2 test, and multivariable logistic regression were applied to analyze data. Results: Three major dietary patterns were identified by factor analysis: the Western dietary pattern, the healthy dietary pattern, and the traditional dietary pattern. After controlling for potential confounders, subjects in the highest tertile of Western dietary pattern score had a higher odds ratio (OR) for metabolically healthy obese (MHO; OR 1.58, 95% confidence interval [CI]: 1.29-1.94), metabolically unhealthy normal weight (OR 1.93, 95% CI 1.08-3.45), and metabolically unhealthy obese (MUHO) phenotypes (OR 2.87, 95% CI 2.05-4.03) than those in the lowest tertile. Also, higher adherence to traditional dietary pattern was positively associated with a higher risk of MHO (OR 1.91, 95% CI 1.56-2.34) and MUHO phenotypes (OR 2.33, 95% CI 1.69-3.22) in the final model. Conclusion: There were significant associations between dietary patterns and metabolic phenotypes, suggesting the necessity of nutritional interventions in industrial employees to improve metabolic phenotype, health outcomes, and, therefore, job productivity in the workforce population.

Distinguishing health-related parameters between metabolically healthy and metabolically unhealthy obesity in women.

Obesity represents a global health crisis, yet a dichotomy is emerging with classification according to the metabolic state into metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). This study aimed to identify distinctive systemic clinical/endocrinological parameters between MHO individuals, employing a comprehensive comparative analysis of 50 biomarkers. Our emphasis was on routine analytes, ensuring cost-effectiveness for widespread use in diagnosing metabolic health. The study included 182 women diagnosed with obesity referred for bariatric surgery at the Endocrinology, Diabetes, and Metabolism Service of São João Hospital and University Centre in Portugal. MUO was defined by the presence of at least one of the following metabolic disorders: diabetes, hypertension, or dyslipidemia. Patients were stratified based on the diagnosis of these pathologies. Significantly divergent health-related parameters were observed between MHO and MUO patients. Notable differences included: albumin (40.1 ± 2.2 vs 40,98 ± 2.6 g/L, p value = 0.017), triglycerides (110.7 ± 51.1 vs 137.57 ± 82.6 mg/dL, p value = 0.008), glucose (99.49 ± 13.0 vs 119.17 ± 38.9 mg/dL, p value < 0.001), glycated hemoglobin (5.58 ± 0.4 vs 6.15 ± 1.0%, p value < 0.001), urea (31.40 ± 10.0 vs 34.61 ± 10.2 mg/dL, p value = 0.014), total calcium (4.64 ± 0.15 vs 4.74 ± 0.17 mEq/L, 1 mEq/L = 1 mg/L, p value < 0.001), ferritin (100.04 ± 129.1 vs 128.55 ± 102.1 ng/mL, p value = 0.005), chloride (104.68 ± 1.5 vs 103.04 ± 2.6 mEq/L, p value < 0.001), prolactin (13.57 ± 6.3 vs 12.47 ± 7.1 ng/mL, p value = 0.041), insulin (20.36 ± 24.4 vs 23.87 ± 19.6 μU/mL, p value = 0.021), c peptide (3.78 ± 1.8 vs 4.28 ± 1.7 ng/mL, p value = 0.003), albumin/creatinine ratio (15.41 ± 31.0 vs 48.12 ± 158.7 mg/g creatinine, p value = 0.015), and whole-body mineral density (1.27 ± 0.1 vs 1.23 ± 0.1 g/cm2, p value = 0.016). Our findings highlight potential additional parameters that should be taken into consideration alongside the commonly used biomarkers for classifying metabolic health in women. These include albumin, urea, total calcium, ferritin, chloride, prolactin, c-peptide, albumin-creatinine ratio, and whole-body mineral density. Moreover, our results also suggest that MHO may represent a transitional phase preceding the development of the MUO phenotype.

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 mediatory role of inflammatory markers on the relationship between the NOVA classification system and obesity phenotypes among obese and overweight adult women: a cross-sectional study.

Diet and inflammation both play important roles in the occurrence of obesity. We aimed to investigate the role of inflammation in the development of both metabolically healthy obese (MHO) and metabolically unhealthy obese (MUHO) individuals. This cross-sectional study included 221 overweight and obese women aged 18-56 years. The study assessed the metabolic health phenotypes of the participants using the Karelis criterion score. Additionally, dietary intakes were evaluated using a 147-item semi-quantitative questionnaire and the NOVA classification system (comprising 37 food groups and beverages). The study also collected and analyzed the blood parameters, as well as biochemical and anthropometric indices, for all participants. Among the women included in the study, 22.9% had MHO phenotypes but 77.1% had MUHO phenotypes. A significant association between the third quartile of the NOVA classification system and the increased likelihood of having the MUHO phenotype was observed (OR = 1.40, 95% CI = 1.09-4.92, p = 0.04). Regarding the potential role of inflammatory markers, high-sensitivity C-reactive protein (hs-CRP) (p = 0.84), transforming growth factor-β (TGF-β) (p = 0.50), monocyte chemoattractant protein-1 (MCP-1) (p = 0.49), plasminogen activator inhibitor-1 (PAI-1) (p = 0.97), and homeostatic model assessment for insulin resistance (HOMA-IR) (p = 0.92) were found to be mediators. We observed a significant positive association between ultra-processed food (UPF) consumption and the MUHO phenotype in overweight and obese women. This association appeared to be mediated by some inflammatory markers, such as hs-CRP, TGF-β, MCP-1, PAI-1, and HOMA-IR. Additional studies are needed to validate these findings.

The Role of Adipokines and Myokines in the Pathogenesis of Different Obesity Phenotypes-New Perspectives.

Obesity is a characteristic disease of the twenty-first century that is affecting an increasing percentage of society. Obesity expresses itself in different phenotypes: normal-weight obesity (NWO), metabolically obese normal-weight (MONW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). A range of pathophysiological mechanisms underlie the occurrence of obesity, including inflammation, oxidative stress, adipokine secretion, and other processes related to the pathophysiology of adipose tissue (AT). Body mass index (BMI) is the key indicator in the diagnosis of obesity; however, in the case of the NWO and MONW phenotypes, the metabolic disturbances are present despite BMI being within the normal range. On the other hand, MHO subjects with elevated BMI values do not present metabolic abnormalities. The MUO phenotype involves both a high BMI value and an abnormal metabolic profile. In this regard, attention has been focused on the variety of molecules produced by AT and their role in the development of obesity. Nesfatin-1, neuregulin 4, myonectin, irisin, and brain-derived neurotrophic factor (BDNF) all seem to have protective effects against obesity. The primary mechanism underlying the action of nesfatin-1 involves an increase in insulin sensitivity and reduced food intake. Neuregulin 4 sup-presses lipogenesis, decreases lipid accumulation, and reduces chronic low-grade inflammation. Myonectin lowers the amount of fatty acids in the bloodstream by increasing their absorption in the liver and AT. Irisin stimulates the browning of white adipose tissue (WAT) and consequently in-creases energy expenditure, additionally regulating glucose metabolism. Another molecule, BDNF, has anorexigenic effects. Decorin protects against the development of hyperglycemia, but may also contribute to proinflammatory processes. Similar effects are shown in the case of visfatin and chemerin, which may predispose to obesity. Visfatin increases adipogenesis, causes cholesterol accumulation in macrophages, and contributes to the development of glucose intolerance. Chemerin induces angiogenesis, which promotes the expansion of AT. This review aims to discuss the role of adipokines and myokines in the pathogenesis of the different obesity phenotypes.

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.

Circulating MicroRNA-30a, Beclin1 and Their Association with Different Variables in Females with Metabolically Healthy /Unhealthy Obesity.

Obesity is associated with metabolic and cardiovascular co-morbidities. It is important to determine the factors associated with metabolic derangement in obesity. Autophagy plays a major role in the pathogenesis of metabolic syndrome. MicroRNA-30a targets beclin1, the main regulator of autophagy. We assess circulating microRNA-30a and serum beclin1 in women with metabolically unhealthy obesity (MUO), women with metabolically healthy obesity (MHO) and non-obese healthy control and determine their relationship with different clinical and metabolic variables in women with obesity. This cross-sectional study included 34 women with MHO, 34 with MUO, and 20 healthy non-obese women. Blood pressure, body mass index (BMI), and waist circumference were recorded. Glycemic and lipid indices, urinary albumin-to-creatinine ratio, ALT, AST, microRNA-30a expression in serum were measured using real-time polymerase chain reaction and beclin1 by enzyme-linked immunosorbent assay were measured. The expression of microRNA-30a was significantly higher, and beclin1 level was significantly lower in women with MUO compared to those in women with MHO (P<0.001; for both). People with MUO were significantly older (P<0.001) and had higher TSH (P=0.006), HbA1c (P<0.001), triglyceride (P<0.001), and ALT (P<0.001) compared to women with MHO. However, there was no significant difference between the two groups in any anthropometric measurements, HDL-C or LDL-C. In univariate analyses, age, ALT, TSH, microRNA-30a, and beclin1 were significantly correlated with the MUO phenotype (P<0.001; for all). Significance was confirmed in the multivariate analysis for microRNA-30a (95% CI 1.317-28.252; P=0.021). MicroRNA-30a, beclin1, age, and ALT and TSH levels were significantly associated with the MUO phenotype, among which microRNA-30a was the best indicator of metabolic syndrome in women with obesity.

Adherence to the Mediterranean diet as a possible additional tool to be used for screening the metabolically unhealthy obesity (MUO) phenotype

BackgroundThe terms metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) categorize subjects with obesity based on the presence or absence of cardio-metabolic risk factors. Detecting MUO phenotype is crucial due to the high risk of cardio-metabolic complications, requiring tailored and intensive follow-up. However, diagnosing MUO is time-consuming and costly. Thus, we aimed to investigate the role of Mediterranean diet (MD) in determining MHO/MUO phenotypes and whether adherence to MD could serve as an additional screening tool for MUO phenotype.MethodsThe study population of this cross-sectional observational study consisted of 275 subjects with obesity. We assessed their lifestyle habits (physical activity and smoking habits), anthropometric measurements (weight, height, waist circumference, body mass index), blood pressure, metabolic parameters, inflammatory marker (high sensitivity C reactive protein levels), adherence to MD (by PREvención con DIetaMEDiterránea (PREDIMED) questionnaire), and MHO/MUO phenotypes.ResultsThe study included 275 individuals with obesity (256F/19M; 34.0 ± 10.5 years; BMI 38.3 ± 5.95 kg/m2). Among them, 114 (41.5%) exhibited MHO phenotype, while 161 (58.5%) had MUO phenotype. MHO phenotype exhibited favorable anthropometric and cardio-metabolic profiles, characterized by lower waist circumference (p < 0.001), BMI (p < 0.001), insulin resistance (p < 0.001), blood pressure (p < 0.001), inflammation (p < 0.001), and lipid levels (p < 0.001) compared to MUO phenotype. Notably, we found that MHO phenotype had higher adherence to MD (p < 0.001) and consumed more extra virgin olive oil (EVOO) (p < 0.001), vegetables (p < 0.001), fruits (p < 0.001), legumes (p = 0.001), fish (p < 0.001), wine (p = 0.008), and nuts (p = 0.001), while reporting lower intake of red/processed meats (p < 0.001), butter, cream, margarine (p = 0.008), soda drinks (p = 0.006), and commercial sweets (p = 0.002) compared to MUO phenotype. Adherence to MD (p < 0.001) and EVOO (p = 0.015) intake were identified as influential factors in determining the presence of MUO/MHO phenotypes. Furthermore, a PREDIMED score < 5 proved to be the most sensitive and specific cut-point value for predicting the presence of MUO phenotype (p < 0.001).ConclusionHigh adherence to MD was associated with MHO phenotype. Moreover, we suggest that a specific cut-off of the PREDIMED score could be an indicator to discriminate patients with MUO/MHO phenotypes and therefore help in identifying patients at higher cardiovascular risk who will require specific dietary intervention.

Significance of the rs754635 variant of the cholecystokinin gene in the development of obesity in children

So far, the possible influence of single nucleotide variants (SNV) of the cholecystokinin (CCK) gene on the likelihood of developing obesity and metabolic disorders in children has not been demonstrated. The aim of the study SNV associations of the CSK gene to predict the probability of obesity and personalize the development trajectory of various metabolic disorders associated with obesity in children. Materials and methods. 252 obese children aged 6-18 years were examined. The main group (n=152) was represented by children with metabolically unhealthy obesity (MUO). The control group (n=100) consolidated of children with metabolically healthy obesity (MHO). Whole genome sequencing (CeGat, Germany) was performed in 31 children of the main and 21 children of the control group. Serum levels of interleukin-1β were measured using a chemiluminescent immunoassay (CLIA) method, interleukin-6 - by enzyme-linked immunosorbent assay (ELISA), Synevo, Ukraine. Results. The G allele of SNV rs754635 of the CCK gene was significantly more frequent among children with both MHO (t=10.93; p&lt;0.05) and MUO (t=12.96; p&lt;0.05) compared to healthy individuals. The G allele of SNV rs754635 of the CCK gene was associated with basal hyperglycemia (r=0.44) and impaired carbohydrate tolerance (r=0.33) in the MHO phenotype and with the atherogenicity index of the lipid spectrum (r=0.40) and was inversely correlated with the level of high-density lipoproteins (HDL) (r=-0.58) in children with MUO phenotype, p&lt;0.05. Conclusions. The G allele SNV rs754635 of the CCK gene is associated with obesity and the development of metabolic disorders. The research was carried out in accordance with the principles of the Declaration of Helsinki. The research protocol was approved by the Local Ethics Committee of the institution mentioned in the work. Informed consent of parents or their guardians was obtained for conducting research. No conflict of interests was declared by the author.

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.

Associations of Fruit and Vegetable Intake with Metabolic Health Status in Overweight and Obese Youth

Introduction: The objective of this study was to assess the relationship between fruit and vegetable intake with metabolic health status among overweight and obese Iranian youth. Methods: In total, 203 obese and overweight youth including 101 boys and 102 girls, 12–18 years, were randomly recruited through a multistage cluster sampling approach in this study. A validated Persian format of food frequency questionnaire was used to estimate participants’ usual food intake. Adolescents were categorized in accordance with the International Diabetes Federation (IDF) criteria as well as IDF plus insulin resistance (HOMA-IR) definition into metabolically healthy obese and metabolically unhealthy obese (MUO). Results: Based on IDF criteria, youth in the third tertile of vegetable and the combination of fruit and vegetable intake had 66% (odds ratio = 0.34, 95% CI: 0.12–0.95) and 73% (odds ratio = 0.27, 95% CI: 0.09–0.81) lower odds of MUO compared to those in the first tertile, in the fully-adjusted model. According to IDF plus HOMA-IR definition, inverse associations were also found between vegetable (odds ratio = 0.36, 95% CI: 0.12–1.02) and the combination of fruit and vegetable (odds ratio = 0.25, 95% CI: 0.08–0.79) intake with MUO phenotype. Stratified analysis indicated inverse associations between intake of vegetables and the combination of fruits and vegetables with MUO phenotype (based on IDF definition) in overweight, but not obese subjects. Conclusion: The current study demonstrated that greater consumption of vegetables as well as the combination of fruits and vegetables was related to a lower risk of MUO phenotype, particularly in overweight youth.

Inflammatory markers may mediate the relationship between processed meat consumption and metabolic unhealthy obesity in women: a cross sectional study

Metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO) are known to be affected by diet and inflammatory factors (such as TGF-β1, IL-β1, MCP1). We sought to survey that consume of processed meat could effect on MHO and MUHO phenotypes, mediated through inflammatory markers, in overweight and obese Iranian women. The current cross-sectional study was done on 224 women 18–48 years, with a body mass index (BMI) ≥ 25 kg/m2. A 147- item food frequency questionnaire (FFQ) was used to evaluate dietary intake. In all participants, anthropometric indices and biochemical factors, as well as metabolic health phenotypes based on Karelis score, were evaluated. According to results, 22.6% of participants had MHO and 75.7% had MUHO phenotypes. There was an association between higher adherence to processed meats and increasing odds of MUHO phenotype in Iranian women (OR:2.54; 95% CI 0.009, 7.51; P = 0.05). Moreover, we found that the relation can be affected by agents such as TGF-β1, IL-β1, and MCP1; however, more research is needed to confirm these results and finding.

Healthy eating index and bone health markers in adults with metabolically healthy and unhealthy obese phenotypes

The Healthy Eating Index (HEI) estimates the diet quality, and low HEI scores are associated with adverse bone outcomes. However, the relationship between HEI scores and bone health in individuals who are obese but otherwise healthy or obese with comorbidities remains unclear. We aimed to evaluate the association of HEI scores with bone mineral density (BMD), bone regulating hormones and bone turnover markers in individuals with metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO) phenotypes. This was a cross-sectional analysis of 122 adults who were overweight or obese. A questionnaire was completed to obtain demographic data. Body composition and BMD were assessed by a Dual Energy X-Ray Absorptiometry (DXA) exam. The HEI scores and dietary components were calculated using a 24-h dietary recall. Blood samples were collected for the analysis of serum 25-hydroxyvitamin D (s25OHD), total osteocalcin (OC), parathyroid hormone (PTH), and C-terminal telopeptide (CTx) concentrations. The MHO and MUO phenotypes were classified according to the absence or presence of metabolic abnormalities. The sample mean age was 37.91 ± 12.66 years, 50.8% were men, mean body mass index (BMI) was 30.01 ± 4.63 kg/m2, and 45.9% were classified as the MUO phenotype. The mean HEI scores were 54.42 ± 16.25 and 61.48% had low-diet quality. HEI scores were positively associated with s25OHD in the MUO phenotype group (β = 0.194, 95%CI = 0.038–0.350, p = 0.016). Certain dietary score components, such as fruits, seafood and plant protein, added sugars, whole grains, and fatty acids were also associated with bone health markers. However, HEI scores were not associated with BMD measures, neither with other bone regulating hormones and turnover markers. There was a positive association between HEI scores and s25OHD in adults who were overweight or obese with MUO phenotype. Additionally, the adequate consumption of specific food groups may benefit bone mass and metabolism. These results emphasize the importance of lifestyle interventions encouraging healthy eating habits to prevent s25OHD deficiency, poor bone health, and cardiometabolic complications.

RELATIONSHIP BETWEEN SKELETAL MASS INDEX AND DIFFERENT OBESITY METABOLIC PHENOTYPES AMONG ADOLESCENTS IN CHINA

Objective: To explore the relationship between skeletal mass index (SMI) and different obesity metabolic phenotypes among adolescents,and to provide a theoretical basis for the prevention and control of obesity and related metabolic diseases in adolescents. Design and method: A total of 1352 adolescents aged 12-18 were randomly selected for questionnaire survey,physical measurements,body composition determination and laboratory testing. Multiple logistic regression analysis was used to analyze the correlation intensity between SMI and different metabolic phenotypes of obesity. Results: The metabolically unhealthy normal weight (MUNW) phenotype, metabolically healthy obesity(MHO) phenotype and metabolically unhealthy obesity(MUO) phenotype had lower levels of SMI compared to the metabolically healthy normal weight(MHNW) phenotype among adolescents,with all differences being statistically significant(P-values were all less than 0.001). Similar results were found after stratification by sex. Multiple logistic regression analysis showed that after adjusting for sex, SMI were protective factors for MUNW phenotype, MHO phenotype and MUO phenotype in adolescents(P-values were all less than 0.001),with the 0.86(95%CI:0.85,0.92),0.78(0.75,0.82) and 0.73(0.70,0.76) increased risks of MUNW phenotype, MHO phenotype and MUO phenotype associated with each unit rise in SMI, similar results were found after stratification by sex. Conclusions: SMI were protective factors for MUNW phenotype, MHO phenotype and MUO phenotype among adolescents. Attention should be paid to the assessment and supervision of adolescent skeletal muscle quality when prevented obesity and related metabolic risks,reducing the risk of abnormal cardiovascular metabolism in adolescents.

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 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.

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.

The relationship between different metabolic phenotypes and bone indices in Chinese children and adolescents aged 12-18 years old.

Data regarding different metabolic phenotypes and bone markers including bone mineral content (BMC) and osteocalcin (OCN) among children and adolescents are very limited. Hence, the purpose of this investigation was to explore the relationship between different metabolic phenotypes and BMC or OCN among Chinese children and adolescents. This cross-sectional study included 1,328 children and adolescents aged between 12 and 18 years who were selected from four schools in Yinchuan city from 2018 to 2020 by stratified cluster random sampling. Subjects were divided into four groups according to BMI and metabolic status, as follows: metabolically healthy obesity (MHO), metabolically unhealthy obesity (MUO), metabolically unhealthy normal weight (MUNW), and metabolically healthy normal weight (MHNW). The MHNW, MUNW, MHO, and MUO phenotypes in boys were 48.4%, 30.5%, 6.7%, and 14.4%, respectively, and were 47.8%, 33.6%, 6.6%, and 12.1% in girls, respectively. The MHO and MUO phenotypes had higher BMC than the MHNW or MUNW phenotype (all p < 0.05), and the MUO phenotype with BMC was significantly higher than MHO group in boys (p < 0.05). We discovered a significant positive correlation between BMC and the MHO (OR = 8.82, 95% CI = 2.04-38.16), MUO phenotypes (OR = 13.53, 95% CI = 4.10-44.70), while no association was found between OCN and metabolic phenotypes in neither boys nor girls. Overweight/obese children and adolescents had higher BMC, and there existed sex differences in the effect of metabolic status on BMC among them. OCN was not supposed to be an index of bone health in this study.

Dietary Intakes and Eating Behavior between Metabolically Healthy and Unhealthy Obesity Phenotypes in Asian Children and Adolescents.

Diet plays a critical role in the development of obesity and obesity-related morbidities. Our study aimed to evaluate the dietary food groups, nutrient intakes and eating behaviors of metabolically healthy and unhealthy obesity phenotypes in an Asian cohort of children and adolescents. Participants (n = 52) were asked to record their diet using a 3-day food diary and intakes were analyzed using a nutrient software. Eating behavior was assessed using a validated questionnaire. Metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUO) were defined based on criteria of metabolic syndrome. Children/adolescents with MUO consumed fewer whole grains (median: 0.00 (interquartile range: 0.00-0.00 g) vs. 18.5 g (0.00-69.8 g)) and less polyunsaturated fat (6.26% kcal (5.17-7.45% kcal) vs. 6.92% kcal (5.85-9.02% kcal)), and had lower cognitive dietary restraint (15.0 (13.0-17.0) vs. 16.0 (14.0-19.0)) compared to children/adolescents with MHO. Deep fried food, fast food and processed convenience food were positively associated with both systolic (β: 2.84, 95%CI: 0.95-6.62) and diastolic blood pressure (β: 4.83, 95%CI: 0.61-9.04). Higher polyunsaturated fat intake (OR: 0.529, 95%CI: 0.284-0.986) and cognitive dietary restraint (OR: 0.681, 95%CI: 0.472-0.984) were associated with a lower risk of the MUO phenotype. A healthier diet composition and positive eating behavior may contribute to favorable metabolic outcomes in children and adolescents with obesity.

The metabolic phenotype of the patient influences the reduction in carotid intima-media thickness achieved following metabolic surgery.

To determine whether metabolic phenotype is associated with the change in carotid intima-media thickness (CIMT) in patients undergoing bariatric /metabolic surgery (BMS). We performed a case-control study of BMS candidates who had metabolically unhealthy obesity (MUO) or metabolically healthy obesity (MHO). We measured the change in CIMT during the 9 months following BMS. The plasma tumor necrosis factor-α, interleukin-1β, adiponectin, leptin, nitric oxide (NO), vascular endothelial growth factor A (VEGF-A), and malondialdehyde concentrations were determined, adipocyte area was measured histologically, and adipose tissue area was estimated using computed tomography. Fifty-six patients (mean age 44.5 years, mean body mass index 44.9 kg/m2, 53% women, and 53% had MUO) were studied. Nine months following BMS, the MUO phenotype was not associated with a significant reduction in CIMT, and that of the MHO group was larger. In addition, fewer participants achieved a 10% reduction in CIMT in the MUO group. A CIMT reduction was associated with lower VEGF-A and NO in the MUO group, while that in the MHO group was associated with a higher NO concentration. The metabolic phenotype of patients may influence their change in CIMT following BMS, probably through circulating vasodilatory and pro-inflammatory molecules.