Metabolically Unhealthy Research Articles

Association Between Dietary Magnesium Intake with Serum Brain-Derived Neurotrophic Factor (BDNF) and Adropin Levels and Metabolic Health Status in Iranian Adults.

Given the sparse conclusive findings regarding the association of magnesium intake with metabolic health status and limited evidence relating magnesium intake to metabolic biomarkers, our objective was to evaluate the association of metabolic health status, adropin, and brain-derived neurotrophic factor (BDNF) in relation to dietary magnesium intake. In this cross-sectional study, 527 male and female adults were investigated in Isfahan City. The data regarding usual dietary intakes were gathered using a valid and reliable 168-item food frequency questionnaire. Biochemical variables, anthropometric indices, and blood pressure were assessed following standard methods. The criteria suggested by Wildman et al. were used to classify participants as metabolically unhealthy (MU) and metabolically healthy (MH). Moderate magnesium intake was associated with 71% reduced odds of MU (OR T2 vs. T1 = 0.29; 95% CI: 0.12-0.70). In the stratified analysis, the inverse association between moderate intake of magnesium and MU was seen only in overweight/obese subjects but not in normal-weight ones. A significant difference was found in serum levels of adropin between the first and second tertile of dietary magnesium intake among overweight/obese subjects (62.74 ± 4.99 vs. 50.13 ± 2.54, P = 0.03). After adjustment for potential covariates, this association became attenuated (59.06 ± 3.47 vs. 50.02 ± 3.64, P = 0.20). No statistically significant link was obtained between dietary intake of magnesium and circulating BDNF levels. Moderate dietary intake of magnesium may exert beneficial effects on metabolic health and serum levels of adropin, especially in obese/overweight individuals. Further prospective studies will be required to approve our findings.

Systemic Inflammatory Indicators and Risk of Incident Metabolically Unhealthy Phenotype.

This retrospective cohort study was designed to evaluate the association between eight systemic inflammation indicators at baseline and the metabolically unhealthy (MU) phenotype after two years of follow-up. Participants were defined as metabolically healthy (MH) if they met 0-2 of the criteria and metabolically unhealthy (MU) if they met ≥ 3 of the criteria. A many of 4175 subjects aged 20-80 years with a metabolically healthy (MH) phenotype at baseline were enrolled in the study. We compared the clinical characteristics between women and men enrolled at baseline according to the metabolic phenotype at follow-up. The associations between baseline inflammation indicators and MU status at follow-up were evaluated using logistic regression analysis. 922 (22.08%) developed new-onset MU symptoms during follow-up. Logistic regression analysis found that most inflammation indicators were significantly associated with MU phenotype at follow-up, aside from the LMR and SII. After adjusting for potential confounders, only the correlations between CRP level, neutrophil count, and MU phenotype reached significance. In comparison to the control group with a CRP of <0.50 mg/L, the odds ratios (ORs) and 95% confidence intervals (CIs) were 1.61 (1.25-2.09), 1.49 (1.15-1.94), and 1.68 (1.30-2.18) for individuals with CRP levels of 0.50-0.90 mg/L, 0.91-1.72 mg/L, and above 1.72 mg/L, respectively. In the population with a neutrophil count <5.00 ×109 cells/L, the neutrophil count correlated positively and significantly with the MU phenotype. In comparison to the control group with a neutrophil count of <2.75 × 109 cells/L, the ORs and 95% CIs were 1.65 (1.30-2.09) in the population with neutrophil count >4.17 × 109 cells/L. CRP and neutrophil counts positively correlated with the risk of MU phenotype in Chinese subjects. These composite inflammatory markers (NLR, PLR, LMR, and SII) provide limited advantages for predicting MU risks compared to CRP.

Multifaceted association of overweight and metabolically unhealthy with the risk of Barrett's esophagus in the UK Biobank cohort

The association of overweight/obesity and metabolically unhealthy (MU) with the risk of developing Barrett's esophagus (BE) remains uncertain. We evaluated whether MU and overweight/obesity are associated with increased BE incidence and whether they have a synergistic impact on BE development. We analyzed the body mass index (BMI) and metabolic indicators at baseline of 402,510 individuals from the UK Biobank with no history of BE. Overweight/obesity and MU were defined as BMI ≥ 25.0 kg/m2 and presence of ≥ 1 MU indicators, respectively. Accordingly, the participants were categorized into four groups: (1) metabolically healthy non-overweight/obesity (MHNO), (2) metabolically unhealthy non-overweight/obesity (MUNO), (3) metabolically healthy overweight/obesity (MHO), and (4) metabolically unhealthy overweight/obesity (MUO). During a median follow-up of 13.5 years, 6195 (1.5%) individuals were newly diagnosed with BE. Among them, 39,281 (9.8%), 92,000 (22.9%), 25,297 (6.3%), and 245,932 (61.1%) individuals were classified as MHNO, MUNO, MHO, and MUO, respectively. In Cox regression analyses, both MU and overweight/obesity were independently associated with BE incidence. Moreover, BE incidence was significantly higher in the MUNO, MHO, and MUO groups, compared to the MHNO group. MU and overweight/obesity are independent risk factors for BE and have a synergistic effect on BE development.

Association betweentransitions in metabolic health and colorectal cancer across categories of body size phenotype: a prospective cohort study.

We aimed to investigate the associations of changes in metabolic health across categories of body size phenotype with the risk of colorectal cancer in a community-based prospective cohort. In the current study, a total of 70,987 participants were included. Changes in metabolic health across categories of body size phenotype were assessed between the health examination for the first time in the years 2006 through 2009 and a 2010/2011 health examination. A multivariate Cox proportional hazards model was used to assess the associations of changes in metabolic health across body size phenotype categories with risk of colorectal cancer. During the median follow-up time of 11.04 years, 428 (0.60%) participants developed colorectal cancer. Compared with metabolically healthy normal-weight (MHNW) participants who remained MH, the risk of colorectal cancer was increased by 144% (95% CI: 1.21-4.95) for participants with metabolically healthy obesity (MHO) who converted to a metabolically unhealthy (MU) phenotype. Participants who were MU at baseline were still at increased risk of colorectal cancer, regardless of obesity status. The MHO phenotype was a dynamic status over time, and converting to MU during follow-up and being initially MU were associated with having an increased risk of colorectal cancer, regardless of degree of obesity and body size phenotype.

Nutrient patterns in relation to metabolic health status and serum levels of brain-derived neurotrophic factor (BDNF) and adropin in adults

The present study aimed to investigate the association of nutrient patterns (NPs) with metabolic health status and serum levels of brain-derived neurotrophic factor (BDNF) and adropin in Iranian adults. This cross-sectional survey was performed on 527 adults aged 20–60 years in Isfahan, Iran. To evaluate dietary intake, a validated 168-item semi-quantitative food frequency questionnaire (FFQ) was used. Participants were categorized as metabolically healthy (MH) and metabolically unhealthy (MU) according to their glycemic and lipid profile, insulin resistance (IR), and inflammation status. An overnight fasting blood sample was collected from each participant and serum levels of BDNF and adropin were assessed. A total of 42.50% of participants were recognized as MU. Three NPs were recognized by factor analysis that labeled as “high animal protein” (NP1), “high vegetable” (NP2), and “high carbohydrate” (NP3) patterns. Moderate adherence to NP2 was related to a lower risk of MU (ORT2 vs. T1 = 0.38, 95% CI: 0.18–0.76). Moreover, high adherence of NP2 (T3 vs. T1) was inversely associated with hypertriglyceridemia (OR = 0.27, 95% CI: 0.11–0.65; P-trend < 0.001) and high hs-CRP values (OR = 0.29, 95% CI: 0.09–1.00; P-trend = 0.03). No significant association was observed between adherence of NP1 and NP3 with MU in crude and adjusted models. However, negative associations were found between moderate adherence to NP3 and insulin resistance (IR) (OR = 0.23, 95% CI: 0.06–0.91) as well as high adherence to NP1 and hypertension (OR = 0.23, 95% CI: 0.09–0.61; P-trend < 0.001). NPs were not associated with serum BDNF and adropin values.

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

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

Adherence to Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay Diet in Relation to Serum Brain-Derived Neurotrophic Factor Concentrations and Metabolic Health Status in Adults

BackgroundThere is a lack of data regarding the Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) diet and metabolic health. ObjectivesThis study assessed the relation between MIND diet and metabolic health status relative to serum brain-derived neurotrophic factor (BDNF) concentrations. MethodsThis was a cross-sectional study of 527 adults (286 males and 241 females) recruited from 20 schools in 6 different educational districts of Isfahan, Iran. Dietary intakes of participants were collected by a validated 168-item food frequency questionnaire, and MIND diet score was estimated. Anthropometric indices, blood pressure, biochemical parameters, and BDNF concentrations were assessed for all participants. The metabolically unhealthy (MU) phenotype was determined based on blood pressure, glycemic and lipid profiles, chronic inflammation, and insulin resistance. ResultsThe frequency of MU phenotype among obese/overweight and normal-weight individuals was 79.5 % and 20.5 %, respectively. After adjustment for confounders, individuals in the top tertile of the MIND diet scores had 58 % lower odds of having the MU phenotype than individuals in the bottom tertile (odds ratios [ORs]: 0.42; 95 % confidence interval [CI]: 0.20, 0.90). In the fully adjusted model, females and normal-weight individuals had 81 % (OR: 0.19; 95 % CI: 0.04, 0.83) and 89 % (OR: 0.11; 95 % CI: 0.02, 0.69) lower chance of developing the MU phenotype, respectively. In addition, significant inverse associations between adherence to the MIND diet and high-blood pressure and hypertriglyceridemia were found. No significant association was found between adherence to MIND diet and odds of low BDNF concentrations. ConclusionsAdherence to MIND diet is inversely associated with odds of MU phenotype, especially among women and normal-weight individuals. BDNF concentration is not associated with MIND diet and MU status.

Early prediction of body composition parameters on metabolically unhealthy in the Chinese population via advanced machine learning.

Metabolic syndrome (Mets) is considered a global epidemic of the 21st century, predisposing to cardiometabolic diseases. This study aims to describe and compare the body composition profiles between metabolic healthy (MH) and metabolic unhealthy (MU) phenotype in normal and obesity population in China, and to explore the predictive ability of body composition indices to distinguish MU by generating machine learning algorithms. A cross-sectional study was conducted and the subjects who came to the hospital to receive a health examination were enrolled. Body composition was assessed using bioelectrical impedance analyser. A model generator with a gradient-boosting tree algorithm (LightGBM) combined with the SHapley Additive exPlanations method was adapted to train and interpret the model. Receiver-operating characteristic curves were used to analyze the predictive value. We found the significant difference in body composition parameters between the metabolic healthy normal weight (MHNW), metabolic healthy obesity (MHO), metabolic unhealthy normal weight (MUNW) and metabolic unhealthy obesity (MUO) individuals, especially among the MHNW, MUNW and MUO phenotype. MHNW phenotype had significantly lower whole fat mass (FM), trunk FM and trunk free fat mass (FFM), and had significantly lower visceral fat areas compared to MUNW and MUO phenotype, respectively. The bioimpedance phase angle, waist-hip ratio (WHR) and free fat mass index (FFMI) were found to be remarkably lower in MHNW than in MUNW and MUO groups, and lower in MHO than in MUO group. For predictive analysis, the LightGBM-based model identified 32 status-predicting features for MUNW with MHNW group as the reference, MUO with MHO as the reference and MUO with MHNW as the reference, achieved high discriminative power, with area under the curve (AUC) values of 0.842 [0.658, 1.000] for MUNW vs. MHNW, 0.746 [0.599, 0.893] for MUO vs. MHO and 0.968 [0.968, 1.000] for MUO and MHNW, respectively. A 2-variable model was developed for more practical clinical applications. WHR > 0.92 and FFMI > 18.5 kg/m2 predict the increased risk of MU. Body composition measurement and validation of this model could be a valuable approach for the early management and prevention of MU, whether in obese or normal population.

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

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

FAAH Pro129Thr Variant Is Associated with Increased Cholesterol Levels in Normal-Weight Metabolically Unhealthy Subjects.

Introduction: The endocannabinoid system (ECS) plays an integral role in maintaining metabolic homeostasis, where an hyperactivation has been related with serum lipid alterations. The biological effects of ECS are limited by the activation of the endocannabinoid-degrading enzyme fatty acid amide hydrolase (FAAH) and by polyunsaturated fatty acid (PUFA) intake as precursors. The FAAH Pro129Thr variant has been associated with obesity in some populations. However, the association with metabolic phenotypes in the Mexican population has not been studied. This study aimed to analyze the association of the FAAH Pro129Thr variant with serum lipids and diet in Mexican adults with different metabolic phenotypes. Methods: This is a cross-sectional study with 306 subjects between 18 and 65 years of age. They were classified with normal weight (NW) or excess weight (EW) according to their body mass index (BMI). The EW group included individuals with overweight or obesity (BMI 25-39.9 kg/m2). The individuals were classified into two metabolic phenotypes, metabolically healthy and metabolically unhealthy (MUH), using the homeostatic model assessment of insulin resistance and the National Cholesterol Education Program-adenosine triphosphate III cutoff points for blood pressure, triglycerides, high-density lipoprotein cholesterol, and fasting glucose. Subjects with ≥2 of 5 altered parameters were classified as MUH. The FAAH Pro129Thr variant was determined by allelic discrimination with TaqMan® probes. Results: The total cholesterol and very low-density lipoprotein cholesterol levels were associated with the FAAH Pro129Thr variant in NW-MUH subjects. Moreover, a lower PUFA intake was found in EW-MUH subjects with the FAAH variant. Conclusions: FAAH Pro129Thr variant has an important role in lipid metabolism, especially in NW-MUH subjects. By contrast, a low dietary intake of endocannabinoid PUFA precursors may partly counteract the development of the altered lipid profile associated with overweight/obesity.

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

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

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

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

Differences in the Impact of Obesity and Metabolic Unhealthiness on the Risk of Gallbladder Polyp.

Differences in the impact of obesity and metabolic health status on the risk of gallbladder polyp (GBP) remain uncertain. Herein, we aimed to compare the risk of GBP ≥5 mm among individuals with different phenotypes based on obesity and metabolic health status. A cohort of 253485 asymptomatic adults who underwent abdominal ultrasonography screening were categorized into the following four groups according to obesity and metabolic health status: 1) metabolically healthy non-obese (MHNO), 2) metabolically unhealthy and non-obese (MUNO), 3) metabolically healthy but obese (MHO), and 4) metabolically unhealthy obese (MUO). The prevalences of GBP ≥5 mm were 2.4%, 3.1%, 3.7%, and 4.0% in the MHNO, MUNO, MHO, and MUO groups, respectively. The multivariable-adjusted odds ratio (OR) values for prevalence of GBP ≥5 mm by comparing the MUNO, MHO, and MUO with the MHNO group were 1.11 [95% confidence interval (CI), 1.04-1.19], 1.30 (95% CI, 1.15-1.47), and 1.37 (95% CI, 1.28-1.45), respectively. The risk of GBP ≥5 mm in the MHO group was significantly higher than that in the MUNO group, but not significantly different from that in the MUO group. Obesity and metabolic unhealthiness appear to be independent risk factors for the prevalence of GBP, and the impact of obesity is greater than that of metabolic unhealthiness, suggesting that maintaining both normal weight and metabolic health may help reduce the risk of GBP.

Macrophage Phenotypes and Gene Expression Patterns Are Unique in Naturally Occurring Metabolically Healthy Obesity.

Obesity impacts 650 million individuals globally, often co-occurring with metabolic syndrome. Though many obese individuals experience metabolic abnormalities (metabolically unhealthy obese [MUO]), ~30% do not (metabolically healthy obese [MHO]). Conversely, >10% of lean individuals are metabolically unhealthy (MUL). To evaluate the physiologic drivers of these phenotypes, a 44-animal African green monkey cohort was selected using metabolic syndrome risk criteria to represent these four clinically defined health groups. Body composition imaging and subcutaneous adipose tissue (SQ AT) biopsies were collected. Differences in adipocyte size, macrophage subtype distribution, gene expression, vascularity and fibrosis were analyzed using digital immunohistopathology, unbiased RNA-seq, endothelial CD31, and Masson’s trichrome staining, respectively. MHO AT demonstrated significant increases in M2 macrophages (p = 0.02) and upregulation of fatty acid oxidation-related terms and transcripts, including FABP7 (p = 0.01). MUO AT demonstrated downregulation of these factors and co-occurring upregulation of immune responses. These changes occurred without differences in AT distributions, adipocyte size, AT endothelial cells, collagen I deposition, or circulating cytokine levels. Without unhealthy diet consumption, healthy obesity is defined by an increased SQ AT M2/M1 macrophage ratio and lipid handling gene expression. We highlight M2 macrophages and fatty acid oxidation as targets for improving metabolic health with obesity.

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

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

Body fat and muscle were associated with metabolically unhealthy phenotypes in normal weight and overweight/obesity in Yi people: A cross-sectional study in Southwest China.

This study aimed to determine the association between the absolute mass, distribution, and relative ratio of body fat and muscle with the metabolically unhealthy (MU) phenotypes in normal weight and overweight/obesity in Yi people in China. The cross-sectional data from the Yi Migrants Study was used, which included 3,053 Yi people aged 20–80 years from the rural and urban sets. Participants were classified according to body mass index and metabolic status. Body composition including body fat percentage (BFP), fat mass index (FMI), visceral fat grade (VFG), muscle mass index (MMI), and muscle/fat ratio (M/F) were measured by bioelectrical impedance analysis. Restricted cubic spline and logistics regression models were used to test the associations between body composition parameters with MU phenotypes. Receiver-operating characteristic curves (ROC) were used to analyze the predictive value of MU phenotypes. Among the normal weight and overweight/obesity, 26.31% (497/1,889) and 52.15% (607/1,164) were metabolically unhealthy. Stratified by BMI, covariance analysis showed higher body fat (BFP, FMI, and VFG) and MMI in MU participants than in healthy participants. BFP, FMI, VFG, and MMI were positively associated with MU phenotypes both in normal weight and overweight/obesity after adjustment. M/F was significantly lower than MU participants and was negatively associated with MU phenotypes. BFP, FMI, VFG, and M/F could better predict MU phenotypes than BMI. We concluded that BFP, FMI, and VFG were positively associated with MU phenotypes, while M/F was negatively associated with MU phenotypes across the BMI categories in Yi people. Body fat and muscle measurement could be a valuable approach for obesity management.

The Spectrum and Impact of Metabolic Dysfunction in MAFLD: A Longitudinal Cohort Analysis of 32,683 Overweight and Obese Individuals

Metabolic associated fatty liver disease (MAFLD) was recently proposed as an alternative name change for better encapsulation of disease. However, there exists a spectrum of MAFLD where both metabolically healthy (MH) and metabolically unhealthy (MU) individuals are included. In view of limited evidence, we sought to examine the prevalence, clinical characteristics, and differences in outcomes of MH-MAFLD at the population level. Data were used from the United States National Health and Nutrition Examination Survey 1999 to 2018. Multivariate logistic regression analysis was used to obtain odds ratios for the estimation of events. Survival analysis was conducted with Cox regression and the Fine-Gray subdistribution model. There were 32,683 overweight and obese individuals included in the analysis. In MAFLD patients, the prevalence of MH-MAFLD was 6.92% (95% confidence interval [CI], 6.58%-7.27%), and 93.08% (95% CI, 92.73%-93.42%) were considered as MU-MAFLD. Multivariate analysis found a significantly higher risk of MACE (odds ratio, 1.38; 95% CI, 1.28-1.49; P < .01), all-cause (hazard ratio, 1.24; 95% CI, 1.17-1.32; P < .01), cardiovascular disease (SHR, 1.20; 95% CI, 1.02-1.42; P = .03), and cancer mortality (SHR, 1.24; 95% CI, 1.07-1.44; P < .01) in MU-MAFLD relative to non-MAFLD. However, MH-MAFLD individuals were not associated with a statistically significant increased risk of these adverse outcomes compared with non-MAFLD. MU-MAFLD diabetics were also at a higher risk of adverse events compared with non-diabetics. This study reports on the heterogeneity and spectrum of metabolic dysfunction that exists in overweight and obese MAFLD. Although MAFLD may potentially be advantageous in improving awareness and patient outcomes, there remains substantial heterogeneity within patients included in MAFLD on the basis of the underlying metabolic burden.

Metabolically healthy transition and its association with body size change patterns among different adult age groups

ObjectiveTo explore the metabolically healthy (MH) to metabolically unhealthy (MU) transition and its association with body size change patterns according to age. MethodsIn total, 12,910 MH subjects were evaluated in 2013 and reevaluated in 2020. A MH state was defined as a score ≤ 1, and a MU state was defined as a score > 1 on the National Cholesterol Education Program-Adult Treatment Panel III criteria. ResultsApproximately 27.0% of MH individuals converted to MU status over the follow-up. Compared with young adults, middle adulthood individuals had a 1.33-fold (95% CI: 1.21–1.46) and late adulthood individuals had a 1.55-fold (95% CI: 1.41–1.70) risk of transition. The body mass index (BMI)/waist circumference (WC)-value change was positively associated with metabolic deterioration; the association weakened with age. With stable normal body size (defined by BMI) as a reference, changing phenotype categories of maximum overweight [hazard ratio (HR): 1.75; 95% CI: 1.56–1.95], non-obesity to general obesity (HR: 2.96; 95% CI: 2.47–3.54) and stable general obesity (HR: 2.44; 95% CI: 1.92–3.10) conferred a higher risk of metabolic deterioration. ConclusionsMH status is a transient state, especially in late and middle adulthood. Individuals transitioning to an obese phenotype should receive attention for concomitant metabolic deterioration.

Association of Lifelines Diet Score (LLDS) and metabolically unhealthy overweight/obesity phenotypes in women: a cross-sectional study

BackgroundPrevious studies have shown the association of a number of dietary quality scores with metabolically phenotypes of obesity. Recently, the Lifelines Diet Score (LLDS), which is a fully food-based score based on the 2015 Dutch dietary guidelines and underlying international literature, has been proposed as a tool for assessing the quality of the diet. Therefore, this study was performed to investigate the association between LLDS and metabolically healthy/unhealthy overweight and obesity (MHO/MUHO) phenotypes.MethodsThis study was performed on 217 women, aged 18–48 years old. For each participant anthropometric values, biochemical test and body composition were evaluated by standard protocols and methods. The LLDS was determined based on 12 components using a valid and reliable food frequency questionnaire (FFQ) containing 147 items. The metabolically healthy (MH) was evaluated using the Karelis criteria.ResultsAmong the total participants in this study, 31.3% of the subjects were MHO while 68.7% were MUHO. After adjustment for potential confounding variables (age, energy intake, and physical activity), participants in highest LLDS tertile had a lower odds of MUHO compared with those in the lowest tertile (OR: 1.18; 95% CI: 0.23, 5.83; P-trend = 0.03). Also, after further adjustment with BMI, provided only small changes in "OR" and did not attenuate the significance (OR: 1.28; 95% CI: 0.23, 6.91; P-trend = 0.02).ConclusionsThe present evidence indicates that individuals with higher adherence to the LLDS had lower odds of metabolically unhealthy (MUH).

Association between non-alcoholic fatty liver disease and metabolically healthy deterioration across different body shape phenotypes at baseline and change patterns

Non-alcoholic fatty liver disease (NAFLD) is a hepatic manifestation of metabolic syndrome (MetS), and the relationship between NAFLD and metabolic deterioration remains unclear. This study aimed to investigate dynamic changes in metabolically healthy phenotypes and to assess the impact of non-alcoholic fatty liver disease (NAFLD) on the conversion from metabolically healthy (MH) to metabolically unhealthy (MU) phenotypes across body shape phenotypes and phenotypic change patterns. We defined body shape phenotypes using both the body mass index (BMI) and waist circumference (WC) and defined metabolic health as individuals scoring ≤ 1 on the NCEP-ATP III criteria, excluding WC. A total of 12,910 Chinese participants who were MH at baseline were enrolled in 2013 and followed-up in 2019 or 2020. During a median follow-up of 6.9 years, 27.0% (n = 3,486) of the MH individuals developed an MU phenotype. According to the multivariate Cox analyses, NAFLD was a significant predictor of conversion from the MH to MU phenotype, independent of potential confounders (HR: 1.12; 95% confidence interval: 1.02–1.22). For the MH-normal weight group, the relative risk of NAFLD in phenotypic conversion was 1.21 (95% CI 1.03–1.41, P = 0.017), which was relatively higher than that of MH-overweight/obesity group (HR: 1.14, 95% CI 1.02–1.26, P = 0.013). Interestingly, the effect of NAFLD at baseline on MH deterioration was stronger in the “lean” phenotype group than in the “non-lean” phenotype group at baseline and in the “fluctuating non-lean” phenotype change pattern group than in the “stable non-lean” phenotype change pattern group during follow-up. In conclusion, lean NAFLD is not as benign as currently considered and requires more attention during metabolic status screening.