Prediction of visceral adipose tissue magnitude using a new model based on simple clinical measurements.

Aims: Waist circumference (WC) is a reliable obesity surrogate but may not distinguish between visceral and subcutaneous adipose tissue. Our aim was to develop a novel sex-specific model to estimate the magnitude of visceral adipose tissue measured by computed tomography (CT-VAT). Methods: The model was initially formulated through the integration of anthropometric measurements, laboratory data, and CT-VAT within a study group (n=185), utilizing the Multivariate Adaptive Regression Splines (MARS) methodology. Subsequently, its correlation with CT-VAT was examined in an external validation group (n=50). The accuracy of the new model in estimating increased CT-VAT (>130 cm2) was compared with WC, body mass index (BMI), waist-hip ratio (WHR), visceral adiposity index (VAI), a body shape index (ABSI), lipid accumulation product (LAP), body roundness index (BRI), and metabolic score for visceral fat (METS-VF) in the study group. Additionally, the new model's accuracy in identifying metabolic syndrome was evaluated in our Metabolic Healthiness Discovery Cohort (n=430). Results: The new model comprised WC, gender, BMI, and hip circumference, providing the highest predictive accuracy in estimating increased CT-VAT in men (AUC of 0.96 ± 0.02), outperforming other indices. In women, the AUC was 0.94 ± 0.03, which was significantly higher than that of VAI, WHR, and ABSI but similar to WC, BMI, LAP, BRI, and METS-VF. It's demonstrated high ability for identifying metabolic syndrome with an AUC of 0.76 ± 0.03 (p<0.001). Conclusion: The new model is a valuable indicator of CT-VAT, especially in men, and it exhibits a strong predictive capability for identifying metabolic syndrome.

Follistatin as a Potential Biomarker for Identifying Metabolically Healthy and Unhealthy Obesity: A Cross-Sectional Study.

Metabolically healthy obesity (MHO) refers to obese individuals with a favorable metabolic profile, without severe metabolic abnormalities. This study aimed to investigate the potential of follistatin, a regulator of metabolic balance, as a biomarker to distinguish between metabolically healthy and unhealthy obesity. This cross-sectional study included 30 metabolically healthy and 32 metabolically unhealthy individuals with obesity. Blood samples were collected to measure the follistatin levels using an enzyme-linked immunosorbent assay (ELISA). While follistatin did not significantly differentiate between metabolically healthy (median 41.84 [IQR, 37.68 to 80.09]) and unhealthy (median 42.44 [IQR, 39.54 to 82.55]) individuals with obesity (p = 0.642), other biochemical markers, such as HDL cholesterol, triglycerides, C-peptide, and AST, showed significant differences between the two groups. Insulin was the most significant predictor of follistatin levels, with a coefficient of 0.903, followed by C-peptide, which exerted a negative influence at -0.624. Quantile regression analysis revealed nuanced associations between the follistatin levels and metabolic parameters in different quantiles. Although follistatin may not serve as a biomarker for identifying MHO and metabolically unhealthy obesity, understanding the underlying mechanisms that contribute to metabolic dysfunction could provide personalized strategies for managing obesity and preventing associated complications.

Mindful Eating and Current Glycemic Control in Patients With Type 2 Diabetes.

Objective Lifestyle adjustments are essential in the management of type 2 diabetes mellitus (T2DM). Mindful eating involves being more attentive to and aware of meals. This study aimed to investigate the relationship between mindful eating and glycemic control, as well as body mass index (BMI), in people with T2DM. Materials and methods This cross-sectional study included 448 participants who had been diagnosed with T2DM for at least six months. The participants were categorized into three groups based on their HbA1c levels. The Turkish adaptation of the Mindful Eating Questionnaire (MEQ-30) was employed to assess levels of mindful eating behavior. Obesity was defined as a BMI ≥ 30. Anthropometric measurements, laboratory tests, and questionnaire responses were also collected. Results Participants with well-controlled diabetes (HbA1c ≤7%) demonstrated significantly higher scores on the MEQ-30 and its various subgroups in comparison to those with poorly controlled diabetes (HbA1c >9%). The suboptimal glycemic control groups exhibited noticeable variations in mindful eating behaviors. Moreover, participants with lower BMIs displayed stronger inclinations toward mindful eating. Weak negative correlations were observed between BMI and specific MEQ-30 subgroups. Notably, subgroups such as emotional eating, eating control, eating discipline, and interference demonstrated weak negative correlations with the HbA1c levels. Conclusion  Higher levels of mindful eating were associated with lower levels of HbA1c and BMI, indicating that incorporating mindful eating practices may present promising advantages for individuals diagnosed with type 2 diabetes, specifically in terms of glycemic control and weight management.

The effect of close and intensive therapeutic monitoring of patients with poorly controlled type 2 diabetes with different glycemic background.

Patients with type 2 diabetes who have HbA1c values ≥ 10% have different previous glycemic trends, including new diagnosis of diabetes. We aimed to assess the efficacy of 3 months of intensive and facilitated antihyperglycemic treatment in patients with different glycemic backgrounds. In this observational study, patients with type 2 diabetes and poor glycemic control (indicated by an HbA1c level of > = 10%) were divided into groups based on their previous HbA1c levels (group 1; newly diagnosed type 2 diabetics, group 2; patients with previously controlled but now deteriorated HbA1c levels, group 3; patients whose HbA1c was not previously in the target range but was now above 10%, and group 4; patients whose HbA1c was above 10% from the start). Patients received intensive diabetes management with close monitoring and facilitated hospital visits. For further analysis, patients who were known to have previously had good metabolic control (either did not have diabetes or had previously had an HbA1c value < =7) and patients who had prior poor metabolic control were analyzed separately. Of the 195 participants [female, n = 84 (43.1%)], the median age was 54 years (inter-quantile range [IQR] = 15, min = 29, max = 80) and the median baseline HbA1c was 11.8% (IQR = 2.6%, min = 10%, max = 18.3%). The median duration of diabetes was 10 years (IQR = 9, min = 1, max = 35) when newly diagnosed patients were excluded. The ≥ 20% reduction in HbA1c at month 3 was observed in groups 1 to 4 in 97%, 88.1%, 69.1%, and 55.4%, respectively. The percentage of patients who achieved an HbA1c level of 7% or less was 60.6%, 38.1%, 16.4%, and 6.2% in the groups, respectively. The rate of those who achieved an HbA1c of 7% or less was nearly 50% of patients with type 2 diabetes mellitus who had previously had good metabolic control, whereas successful control was achieved in only 1 in 10 patients with persistently high HbA1c levels. Patients' glycemic history played an important role in determining their HbA1c levels at 3 months, suggesting that previous glycemic management patterns may indicate future success in diabetes control.

Is Metabolic Score for Visceral Fat (METS-VF) a Better Index Than Other Adiposity Indices for the Prediction of Visceral Adiposity.

Background: Visceral adiposity is an important risk factor for cardiometabolic diseases. Objective: To determine whether the Metabolic Score for Visceral Fat (METS-VF) is more effective than other adiposity indices in predicting visceral fat area (VFA). Methods: In this single-center and cross-sectional study, we included patients aged 20-50 years, without diabetes and coronary artery disease, who underwent computed tomography (CT) including the third lumbar vertebra. Age, blood pressure, waist circumference (WC), hip circumference, fasting lipids, and glucose were assessed. VFA was measured by cross-sectional examination of CT. The correlation of WC, body mass index (BMI), waist-hip ratio (WHR), lipid accumulation product (LAP), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), and METS-VF with VFA was analyzed by correlation analysis. The cut-off values and area under the curve (AUC) for identifying increased VFA (>130 cm2) were determined. Results: We included 185 individuals with mean age 38.2 ± 8 and female predominance (58.4%). There was a significant positive correlation between all indices and VFA (p<0.001). ROC analysis revealed that METS-VF and WC demonstrated the highest predictive value for identifying increased VFA. In both men (p=0.001) and women (p<0.001), METS-VF (AUC 0.922 and 0.939, respectively) showed a significant superiority over ABSI (AUC 0.702 and 0.658, respectively), and VAI (AUC 0.731 and 0.725, respectively). Additionally, in women, its superiority over WHR (AUC 0.807) was also statistically significant (p=0.003). We identified a METS-VF cut-off point >6.4 in males >6.5 in females and WC cut-off point >88 cm in males (AUC 0.922), >90.5 cm in females (AUC 0.938). Conclusion: METS-VF is strongly associated with visceral adiposity and better to predict increased VFA. However, its superiority over WC, BMI, BRI, and LAP was not significant. The results emphasize that WC is more appealing as screening indicator for visceral adiposity considering its easy use. Clinical Trial Registry Name: Clinicaltrials.gov (http://www.clinicaltrials.gov). Clinical Trial Registry Url: https://clinicaltrials.gov/ct2/show/NCT05648409. Clinical Trial Registry Number: NCT05648409.

Comparison of the Impact of SGLT2-Inhibitors and Exenatide on Body Fat Composition.

OBJECTIVE: To investigate the effect of SGLT2-i and GLP-1RA as an add-on therapy to metformin on weight loss and body composition, and to compare their effects on glucose and lipid parameters. STUDY DESIGN: A descriptive study. Place and Duration of the Study: Goztepe Prof Dr Suleyman Yalcin City Hospital, from January 2016 to May 2021. METHODOLOGY:  The study included 50 patients with diabetes on metformin+SGLT2-i (dapagliflozin or empagliflozin, group 1) and 50 patients with diabetes on metformin+GLP-1 receptor agonist (RA, exenatide, group 2). RESULTS: The reduction in weight, BMI, total body, abdominal, leg, and arm fat percentage, and the improvement in body fat-free and muscle mass percentage were significantly higher in Group 2 (p<0.001, p<0.001, p=0.014; p=0.031, p<0.001; p=0.002 and p=0.014, p=0.014, respectively). The decline in abdominal fat mass in the GLP-1 RA group was also significant (p=0.031). There was a significant decrease in HbA1c, fasting glucose, and triglyceride levels (p<0.001, p<0.001, and p=0.036) with a significant increase in HDL-C (p=0.015). There was no significant difference between groups for glucose, HbA1c, and lipid parameters (p>0.05). CONCLUSION: Both SGLT2 inhibitors and exenatide, when added to metformin therapy, were effective in reducing weight and body fat, more by the GLP-agonist. SGLT2-i had no significant impact on decreasing abdominal fat depicting that these agents do not have any benefit in treating visceral adiposity. KEY WORDS: Type 2 diabetes mellitus, Obesity, GLP-1 receptor, SGLT2 inhibitor, Body fat distribution, Visceral adiposity.

MODY Probability Ratios in Patients Diagnosed with Type 2 Diabetes Mellitus at a Young Age.

OBJECTIVE: Maturity-onset diabetes of the young (MODY) is a non-rare group of monogenic inherited diabetes which is commonly confused with type 1 and type 2 diabetes. Due to high costs of genetic tests that provide a definitive diagnosis, some screening scales are used to identify the high-risk patients. In this study, we aimed to evaluate whether (MODY Probability Calculator [MPC]) which is one of the screening tests will be helpful in identifying our high-risk patients among young patients with type 2 diabetes. METHOD: The patients received the diagnosis of type 2 diabetes aged <35 years were included in the study. The anthropometric characteristics of the patients, the treatments they received at the time of diagnosis, and the current treatments were recorded by retrospectively scanning patient files.The patients with the diagnosis of type 1 diabetes having autoantibodies to the pancreas were excluded from the study. The probability of MODY was calculated using MPC.. RESULTS: The mean age of 72 patients (40% female) was 41.5±7.2 years. Eighteen of the patients (25%) were using insulin at the time of diagnosis. The mean HbA1c was 8.6±2.2% and C-peptide was 2.35±1.52 ng/ml. The mean MODY positive predictive score calculated by MPC for risk of MODY was 11.23 percent. There were 61 patients (84.7%) with a risk of ≤20%, 9 patients (12.5%) with a risk of 20-50%, and 2 patients (2.8%) with ≥50%. In the group with MODY PPV score >20%, the age of onset of diabetes and the body mass index was significantly lower than the others (p<0.05, for both). There was no significant difference between current treatments of both groups. CONCLUSION: It has been reported that MODY risk calculated by MPC may yield different results in different populations. The results of this study showed that 15% of our young-onset diabetes patients had an MPC score above 20 percent. Requesting MODY genetic tests in this 15% of the patient group can be presented as a practical suggestion.

C-peptide concentrations in patients with type 2 diabetes treated with insulin.

AIMS: To determine beta cell reserves of patients with type 2 diabetes who are treated with insulin by using fasting C-peptide concentrations and to investigate the clinical features related to C-peptide concentrations. MATERIALS AND METHODS: Patients with type 2 diabetes, who were using insulin as monotherapy or in combination therapy, were divided into three groups; those with an insufficient beta cell reserve (C-peptide: <0.5 ng/mL), borderline reserve (C-peptide: 0.5-2 ng/mL) and sufficient reserve (C-peptide:> 2 ng/mL). RESULTS: In the 249 patients (mean age, 61.77 ± 9.34 years; 40.6% male), the mean duration of diabetes was 13.9 ± 8.43 years. The mean HbA1c concentrations, fasting glucose and C-peptide concentrations were 8.88 ± 1.87%, 184.29 ± 77.88 mg/dL and 1.95 ± 1.37 ng/mL, respectively. Fifty-seven percent of patients (n = 142) had a borderline beta cell reserve and 37% (n = 92) had high C-peptide concentrations. Only 6% of patients (n = 15) had an insufficient beta cell reserve. C-peptide levels were positively correlated with waist circumference (r: 0.282; p = 0.001), hip circumference (r: 0.251; p = 0.001), body mass index (r: 0.279; p = 0.001), fasting glucose concentrations (r: 0.309; p = 0.001) and triglyceride concentrations (r: 0.358; p = 0.001). CONCLUSION: In this study, almost all patients with type 2 diabetes using insulin were found to have sufficient or borderline beta cell reserves and insulin resistance-related parameters were prominent in those with adequate beta cell reserve. CLINICAL TRIALS NO: NCT04005261.

Inequalities in the use of secondary prevention of cardiovascular disease by socioeconomic status: evidence from the PURE observational study.

BACKGROUND: There is little evidence on the use of secondary prevention medicines for cardiovascular disease by socioeconomic groups in countries at different levels of economic development. METHODS: We assessed use of antiplatelet, cholesterol, and blood-pressure-lowering drugs in 8492 individuals with self-reported cardiovascular disease from 21 countries enrolled in the Prospective Urban Rural Epidemiology (PURE) study. Defining one or more drugs as a minimal level of secondary prevention, wealth-related inequality was measured using the Wagstaff concentration index, scaled from -1 (pro-poor) to 1 (pro-rich), standardised by age and sex. Correlations between inequalities and national health-related indicators were estimated. FINDINGS: The proportion of patients with cardiovascular disease on three medications ranged from 0% in South Africa (95% CI 0-1·7), Tanzania (0-3·6), and Zimbabwe (0-5·1), to 49·3% in Canada (44·4-54·3). Proportions receiving at least one drug varied from 2·0% (95% CI 0·5-6·9) in Tanzania to 91·4% (86·6-94·6) in Sweden. There was significant (p<0·05) pro-rich inequality in Saudi Arabia, China, Colombia, India, Pakistan, and Zimbabwe. Pro-poor distributions were observed in Sweden, Brazil, Chile, Poland, and the occupied Palestinian territory. The strongest predictors of inequality were public expenditure on health and overall use of secondary prevention medicines. INTERPRETATION: Use of medication for secondary prevention of cardiovascular disease is alarmingly low. In many countries with the lowest use, pro-rich inequality is greatest. Policies associated with an equal or pro-poor distribution include free medications and community health programmes to support adherence to medications. FUNDING: Full funding sources listed at the end of the paper (see Acknowledgments).