Predictors Of Metabolic Syndrome Research Articles

Metabolic Outcomes of Changing From Rilpivirine/Tenofovir Disoproxil Fumarate/Emtricitabine to Rilpivirine/Tenofovir Alafenamide/Emtricitabine: A Longitudinal Study.

People living with human immunodeficiency virus (HIV, PLWH) are aging, and there are growing concerns regarding combined antiretroviral therapy (cART)-associated negative metabolic consequences. We aimed to investigate the metabolic outcomes of PLWH by replacing rilpivirine (RPV)/tenofovir disoproxil fumarate (TDF)/emtricitabine (FTC) with RPV/tenofovir alafenamide (TAF)/FTC. This retrospective study enrolled PLWH who changed from RPV/TDF/FTC to RPV/TAF/FTC between January 2019 and September 2023. Metabolic profiles were compared 1 year before and 3 years after changing cART using Cochran's Q and one-way ANOVA. The independent risk factors for metabolic syndrome were analyzed using logistic regression. A total of 182 patients were enrolled. The prevalence of metabolic syndrome has increased from 28% to 40.7%. The prevalence of hypertension and abnormal lipid levels significantly increased in the first year after changing cART, but the prescription of medicine for dyslipidemia increased in the second year (p = 0.025) and that for hypertension increased in the third year (p < 0.001). In addition to the criteria, body mass index (BMI) before changing cART was the only predictor of metabolic syndrome in the third year (OR 1.36; 95% CI 1.19-1.55; p < 0.001). The prevalence of metabolic syndrome and BMI did not increase significantly during the second and third years. A gradually higher prevalence of metabolic syndrome among PLWH occurred with changes from RPV/TDF/FTC to RPV/TAF/FTC but plateaued beyond 2 years. However, fewer drugs for dyslipidemia, diabetes, and hypertension were prescribed within the first year after changing cART.

Perirenal fat thickness is an independent predictor for metabolic syndrome in steatotic liver disease

The objective of our study is to measure perirenal fat thickness using MRI in individuals with steatotic liver disease and investigate the relationship between perirenal fat thickness and metabolic syndrome. This retrospective study included consecutive patients with steatotic liver disease who underwent magnetic resonance imaging-proton density fat fraction from October 2018 to February 2020. Among them, patients with crossed fused kidneys or who underwent nephrectomy were excluded. The metabolic abnormalities were reviewed; presence of hypertension, type 2 diabetes, abdominal circumference, triglyceride, and high-density lipoprotein. Perirenal fat was measured in four directions in both kidneys and the total sum of them was calculated. A total of 250 patients (140 males and 110 females) were included. Perirenal fat thickness showed a moderate correlation with waist circumference, creatinine, and hepatic fat fraction (all p < 0.001). Perirenal fat thickness was significantly higher in patients with metabolic syndrome than in patients without (76.8 mm vs. 65.1 mm, p = 0.004). In multivariable regression analysis, the group with high perirenal fat thickness had as significantly higher odd ratio of 2.71 compared to the low group. The perirenal fat thickness is independently associated with metabolic syndrome in patients with steatotic liver disease.

Triglyceride and Glucose Index as an Optimal Predictor of Metabolic Syndrome in Lebanese Adults.

Background: Globally, the prevalence of metabolic syndrome (MetS) is on the rise, especially in Arab countries, which emphasizes the need for reliable ethnic-specific biochemical screening parameters. Methods: Two hundred twenty-one Lebanese adults were enrolled in this cross-sectional study. Biochemical parameters including Homeostasis Model Assessment (HOMA), Triglyceride and Glucose index (TyG), ratio of Triglycerides to High-Density Lipoprotein Cholesterol (TG/HDL-C), Atherogenic Index of Plasma (AIP), and Visceral Adiposity Index (VAI) were assessed for their prediction of MetS. Analysis of covariance, logistic regression, expected-versus-observed case ratio were used to determine model calibration, concordance statistic, area under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CIs), sensitivity, specificity, and negative and positive predictive values (PPV, NPV). Results: The prevalence of MetS was 44.3%. All biochemical parameters were significantly associated with MetS, with a strong model discrimination (c-statistic between 0.77 and 0.94). In both sex categories, TyG best predicted MetS (females: cut-off value, 8.34; males: cut-off value, 8.43) and showed good estimation among females, but overestimation among males. HOMA had the lowest discriminatory power in both sex categories. Conclusions: This study suggests that TyG best predicts MetS, while HOMA has the lowest predictive power. Future larger studies need to focus on harmonizing ethnic specific cut-offs and further validating our results.

Assessment and Predictors of Metabolic Syndrome in Patients of Xanthelasma Palpebrarum: An Observational Study.

Xanthelasma palpebrarum is considered to be a cutaneous marker for cardiovascular diseases, and there is a known association with hypertension, insulin resistance, diabetes mellitus, obesity, and stroke. Our aim was to study the association and identify the predictors of metabolic syndrome in patients with xanthelasma palpebrarum. An observational study was conducted on 55 patients in which patients of both sexes ages 20-70 years without any other skin condition were included after written informed consent. After history and examination, blood pressure and waist circumference were measured in all the subjects. Investigations were sent for fasting blood sugar levels and serum lipid profile. The 2006 IDF Definition of metabolic syndrome was used as assessment criteria. Among the 55 patients, metabolic syndrome was present in 23 patients (41.82%). There was a statistically significant (P<0.05) difference in the values of waist circumference (100% vs. 59.38%, P=0.0003), elevated blood pressure (82.61% vs. 9.38%, P<.0001), raised fasting blood sugar (47.83% vs. 18.75%, P=0.021), and raised triglyceride levels (56.52% vs. 25%, P=0.018) between patients with metabolic syndrome and those without. However, HDL cholesterol levels (34.78% vs. 50%, P=0.262) were comparable between groups. Also, a patient aged 41 years or more with even a single xanthelasma of more than one year's duration has a 76.1% chance of developing metabolic syndrome. Metabolic syndrome develops in a sizeable number of xanthelasma palpebrarum patients, and this therefore gives us an opportunity for early diagnosis and intervention to prevent the development of cardiovascular complications.

Relationship Between Serum Uromodulin as a Marker of Kidney Damage and Metabolic Status in Patients with Chronic Kidney Disease of Non-Diabetic Etiology.

Chronic kidney disease (CKD) is often associated with dyslipidemia, marked by lipid abnormalities that can worsen kidney function and increase cardiovascular risk. A promising biomarker for evaluating kidney function and metabolic status in chronic kidney disease (CKD) is serum uromodulin (sUmod). This study sought to further investigate the relationship between sUmod levels and metabolic status in non-diabetic CKD patients. A sensitive ELISA method was used to determine sUmod levels in 90 adults with obstructive nephropathy and 30 healthy controls. Kidney function was assessed using the measured glomerular filtration rate (mGFR) through renal clearance of 99mTc-diethylenetriamine penta-acetic acid, along with cystatin C levels. Additionally, glycemic and lipid statuses were evaluated. sUmod concentrations showed a significant association with High-density lipoprotein (HDL) levels. Furthermore, CKD patients with lower sUmod levels had significantly lower Apolipoprotein A-I (Apo A-I) values compared to the control group. Significant predictors of lower sUmod concentrations identified in this study were higher glycemia (B = -15.939; p = 0.003) and lower HDL cholesterol levels (B = 20.588; p = 0.019). We conclude that, in addition to being significantly reduced in CKD patients, sUmod is a potential predictor of metabolic syndrome (MS) in this population. Lower sUmod concentrations, independent of mGFR, predict lower HDL cholesterol levels and higher glycemia values.

Relationship between Parathyroid Hormone Level and Degree of Hepatic Steatosis by Fibroscan among Prevalent Hemodialysis Patients

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is the hepatic manifestation of metabolic syndrome (MS) which may be related to cardiovascular mortality among hemodialysis (HD) patients. Hepatic steatosis contributed to many factors related to MS, atherogenic dyslipidemia, insulinresistance, and adipose tissue hormones. Elevated parathyroid hormone is associated with insulin resistance and atherosclerosis and may be considered an independent predictor of metabolic syndrome. some studies reported an association between elevated PTH and non-alcoholic steatohepatitis. However, the relationship between hyperparathyroidism and NAFLD in HD patients is not well defined. Aims of the Study To test the hypothesis of a possible association between hyperparathyroidism and the presence of hepatic steatosis and fibrosis by transient elastography and to evaluate the possible risk factors of NAFLD among hemodialysis patients. Patients and Methods This is a Case-control study included: Group I: (30) chronic HD patients with NAFLD, Group II: (25) chronic HD patients without NAFLD, and Group III: 30 healthy volunteers as a control group. Infection with a hepatotropic virus, Diabetes mellitus (DM), patients with a history of recent hepatobiliary surgery, Abdominal Ascites, Active infection, fever, Active malignancy, drugs induce hepatic steatosis, or Alcohol abuse were excluded. All subjects were subjected to full history and clinical examination. Laboratory tests: Complete blood count (CBC), Iron profile, Serum creatinine, Urea, Calcium (Ca), phosphorus, Intact parathyroid hormone (iPTH), Serum Alkaline phosphatase (ALP), γ-glutamyl transferase (GGT), Serum Aspartate aminotransferase (AST), Alanine aminotransferase (ALT), Albumin, Total bilirubin, Total cholesterol, High-density lipoprotein cholesterol (HDL), Low-density Lipoprotein cholesterol (LDL), Triglycerides (TG), C -reactive protein (CRP) Titre, HBsAg, HCV Ab and Urea reduction ratio (URR). Transient elastography Fibroscan® for assessment of Controlled attenuation parameter (CAP) to detect liver steatosis grades and liver stiffness measurement to quantitate liver fibrosis was done. Results The mean ±SD values of CAP of liver steatosis (263.7 ± 52.7, 181.3 ± 23, 210.8 ± 33.7) (dB/m) in group I, II and control group respectively (P &amp;lt; 0.001). There were significant differences between the studied group as regard body mass index (BMI), serum Ca, phosphorus, ALP and GGT and CRP titer, PTH and liver function tests, and lipid profile (P &amp;lt; 0.001). Post Hoc analysis revealed a significant statistical difference between group I and II groups as regard ALT, AST, Bilirubin level and serum albumin, CRP titer, and lipid profile (P &amp;lt; 0.5). In HD patients studied groups, the CAP value of liver steatosis was statistically significantly correlated to BMI ALT (r = 0.387, P=0.004), AST (r = 0.365, P = 0.006), Cholesterol (r = 0.785, P &amp;lt; 0.001), LDL (r = 0.692, P &amp;lt; 0.001), TG (r = 0.668, P &amp;lt;0.001), CRP Titre (r=0.384, P=0.004), but not correlated to PTH or other studied parameters (P &amp;gt; 0.05). In control group III, there was a significant correlation between the measured CAP Value of liver steatosis and BMI, PTH, CRP titer, ALT, AST, cholesterol, LDL, and a negative correlation between HDL and CAP value (P &amp;lt; 0.05). liver stiffness /fibrosis was observed in 18 (60.0%) of HD patients in group I versus 8 (32%) patients in group II (P &amp;lt; 0.05). The mean value of liver stiffness (Kpa) was (6.73 ± 6.08, 6.39 ± 5.65, 4.57 ± 0.75) in groups I, II, and the control group respectively (P &amp;lt; 0.001) and post hoc analysis showed a significant difference between Group I and Group II (P = 0.04) and between group I and control group p (&amp;lt;0.001). There was a significant difference between group I and group II and between group I and the control group regarding mean values of liver stiffness (Kpa) (P &amp;lt; 0.05) Conclusions Non-alcoholic liver disease (NAFLD) in prevalent hemodialysis patients is significantly correlated to high cholesterol, LDL, triglycerides, low HDL, increased body mass index, and CRP titer as a marker of inflammation, but not significantly correlated to elevated parathyroid hormone level. NAFLD is a risk for liver stiffness /fibrosis among chronic hemodialysis patients.

The Association of the HEPAKID Index with Insulin Sensitivity Index in Obese Adolescents with Metabolic Syndrome.

Objective: The HEPAKID index, a novel diagnostic tool with a sensitivity of 82% and specificity of 62% for detecting nonalcoholic fatty liver disease in obese adolescents. Our study aimed to explore the potential relationship between the HEPAKID index and risk factors contributing to the development of cardiovascular disease in obese adolescents with metabolic syndrome. Methods: This prospective cross-sectional study, conducted at two medical centers from December 2023 to March 2024, included 208 obese adolescents, with a median age of 14.5 years and an average body mass index (BMI) of 30.57 kg/m2. Results: Elevated HEPAKID index values were found in obese adolescents with metabolic syndrome, showing positive associations with BMI, waist and hip circumferences, alanine aminotransferase level, fasting insulin, and homeostasis model assessment for insulin resistance. In those with metabolic syndrome, waist circumference (WC) and homeostasis model assessment for insulin resistance were significant independent variables linked to the HEPAKID index, while WC was the sole influencer in the nonmetabolic syndrome group. Multivariate logistic regression highlighted systolic and diastolic blood pressures, triglycerides, high-density lipoprotein cholesterol, and the HEPAKID index as reliable predictors of metabolic syndrome. A predictive cutoff value of 60.84 for the HEPAKID index showed 61.7% sensitivity and 59.1% specificity in identifying metabolic syndrome. Conclusions: Our study highlighted the potential value of the HEPAKID index in combination with other clinical parameters for predicting metabolic syndrome in obese adolescents, underscoring its role as a valuable screening tool. Furthermore, our findings revealed a correlation between the HEPAKID index and insulin sensitivity in this high-risk population.

Using weight-for-age as a screening tool for metabolic syndrome in apparently healthy adolescents.

The increasing prevalence of metabolic syndrome (MetS) among adolescents necessitates a simple and easy-to-use screening tool. This study aimed to develop and validate a simple model based on age, sex, race, and weight-for-age or BMI-for-age to identify adolescents with MetS. A cross-sectional study of adolescents (aged 12-18 years) who participated in the American National Health and Nutrition Examination Survey (NHANES) was performed. Participants with pre-existing hypertension, diabetes or dyslipidemia were excluded. Data from 2005-2018 were randomly divided into training (70%) and validation (30%) sets. Anthropometric, demographic data, and MetS criteria were extracted. The training group included 1974 adolescents (52% boys, median age 15 years), and the validation group included 848 adolescents (50% boys, median age 14 years). Both weight- and BMI-for-age demonstrated good discrimination ability in the training group (AUC = 0.897 and 0.902, respectively), with no significant difference between them (p = 0.344). Multivariable models showed similar discrimination ability. Therefore, weight-for-age was chosen and using Youden's index, the 93rd weight-for-age percentile (SDS 1.5) was identified as the optimal cut-off value for MetS. Similar values were observed in the validation group. Among adolescents aged 12-18 years, weight-for-age percentiles are an easy-to-use primary screening indicator for the presence of MetS. The prevalence of metabolic syndrome in adolescents is increasing. An early detection screening tool is required to prevent related adulthood morbidity. Screening adolescents for metabolic syndrome is challenging. This study suggests the use of weight-for-age as a single criterion for primary screening of adolescents aged 12-18. Using weight-for-age as a single predictor of metabolic syndrome is expected to increase screening rates compared to using BMI-for-age, due to its simplicity.

Chemotherapy and Metabolic Syndrome: A Comprehensive Review of Molecular Pathways and Clinical Outcomes.

Cancer therapies, notably chemotherapy, have significantly improved survival rates and quality of life for many patients. However, chemotherapy's cytotoxic effects also impact normal cells, leading to adverse effects, including metabolic disturbances. This paper explores the link between chemotherapy and metabolic syndrome, a cluster of metabolic abnormalities that increase the risk of cardiovascular diseases and type 2 diabetes. Understanding the predictors, such as specific chemotherapy regimens, patient characteristics, comorbid conditions, lifestyle factors, and genetic variations, is crucial for formulating personalized care plans and preventive strategies. Research indicates that older age, female gender, pre-existing diabetes, and baseline obesity are significant predictors of metabolic syndrome in cancer patients. Chemotherapy-induced molecular changes, including insulin resistance, dyslipidemia, chronic inflammation, oxidative stress, and tissue fibrosis, contribute to the development of this syndrome. Effective management strategies require a multidisciplinary approach, incorporating lifestyle interventions, pharmacological treatments, and regular monitoring. This paper underscores the importance of personalized medicine in mitigating the risks associated with metabolic syndrome and improving long-term health outcomes for cancer survivors. Future research directions include longitudinal studies to track metabolic health over time, mechanistic studies to uncover the molecular pathways involved, and the development of integrative therapies. By adopting comprehensive care models, healthcare providers can enhance the overall quality of life for cancer survivors, addressing both cancer and metabolic health challenges.

Visceral Adiposity Index as a Predictor for Metabolic Syndrome in a Cohort of Older Adults With Obesity

Visceral Adiposity Index as a Predictor for Metabolic Syndrome in a Cohort of Older Adults With Obesity

Depression Symptom Patterns as Predictors of Metabolic Syndrome and Cardiac Events in Symptomatic Women with Suspected Myocardial ischemia: The Women’s Ischemia Syndrome Evaluation (WISE and WISE-CVD) Projects

Depression Symptom Patterns as Predictors of Metabolic Syndrome and Cardiac Events in Symptomatic Women with Suspected Myocardial ischemia: The Women’s Ischemia Syndrome Evaluation (WISE and WISE-CVD) Projects

Hematological Predictors of Antipsychotic-induced Metabolic Syndrome in a Female Patient with Schizophrenia: Case Report

Schizophrenia is a chronic mental disorder. It is treated with antipsychotics, which have a high risk of adverse reactions. One of these adverse reactions is metabolic syndrome, which increases the risk of cardiovascular diseases and the mortality rate of patients with schizophrenia. Various studies have shown an association between hematological parameters and metabolic syndrome. In this regard, the use of hematological predictors as a diagnostic tool can help identify risks and timely correct antipsychotic therapy for preventing metabolic syndrome. One of the most promising predictors are hematological inflammation coefficients obtained on the basis of a clinical blood test. The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and the index of systemic immune inflammation (SII), are inexpensive, easy-to-detect markers of systemic inflammation. This case report of a 48-year-old female patient with paranoid schizophrenia, hematological inflammation coefficients were increased during antipsychotic therapy compared to the baseline. At the start of clozapine therapy, the highest levels of systemic inflammatory markers were recorded, after which the patient developed metabolic syndrome. In this case, stopping clozapine therapy when the level of hematological inflammatory coefficients increases would prevent the development of metabolic syndrome in the patient. Markers of systemic inflammation can help doctors diagnose metabolic syndrome early. This may reduce rates of cardiovascular disease and type 2 diabetes and thus reduce mortality in patients with schizophrenia. This case report demonstrates that wider implementation of hematological predictors of metabolic syndrome into real clinical practice could help significantly improve the safety of antipsychotic therapy.

Aspartate Aminotransferase to Platelet Ratio Index (APRI) as a Predictor of Metabolic Syndrome (MetS) Development in Individuals With Type 2 Diabetes Mellitus.

Despite ongoing findings on the relationship between liver fibrosis in nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome (MetS), this association in diabetic patients remains unclear. Early diagnosis of liver fibrosis is important due to the easily available diagnostic tools, such as noninvasive indices that combine clinical and laboratory variables, and the possibility of preventing its complications in type 2 diabetes mellitus (T2DM) patients with MetS. This study examines the potential predictive values of non-invasive liver fibrosis indices for MetS in T2DM patients. Over the course of a two-year prospective, observational, clinical study, 80 individuals with T2DMrandomly selected from the Diabetes Counseling Centers of the Public Institution Health Center of Sarajevo Canton were divided into two groups: T2DM-MetS and T2DM-non-MetS, based on the development of MetS. The studyincludedindividuals with T2DM aged30 to 60who were clinically diagnosed without MetS, voluntarily agreed to participate, and provided complete data in the collection forms. Serum samples from the patients were assessed for levels of liver enzymes, platelet counts, total cholesterol, high-density lipoprotein cholesterol, fasting glucose, and triglycerides. Various equations were utilized to calculate liver fibrosis indices, including the Aspartate Aminotransferase to Platelet Ratio Index (APRI), Aspartate Aminotransferase to Gamma-Glutamyl Transferase to Platelet Ratio (AGPR), Aspartate Aminotransferase to Alanine Aminotransferase Ratio to Platelet Ratio Index (AARPRI), Fibrosis-4 (FIB-4) Index, Forns Index, and Gamma-Glutamyl Transpeptidase to Platelet Ratio (GPR). Receiver operating characteristic (ROC) analysis was utilized to determine the usefulness of noninvasive liver fibrosis indices for diagnosing MetS in individuals with T2DM. Logistic regression analysis was used to predict the onset of MetS in T2DM patients. Significant differences in the values of APRI (p<0.001), AGPR (p<0.05), AARPRI (p<0.001), and the FIB-4 index (p=0.001) were observed in T2DM-MetS individuals compared to T2DM-non-MetS. According to ROC analysis, the area under the curve (AUC) was found to be highest for APRI (0.84), followed by FIB-4 (0.783) and AARPRI (0.747). Logistic regression analysis identified APRI as an independent positive predictor of MetS (OR 18.179, 95% CI 6.035-24.58, p=0.015). This research highlights the effectiveness of the APRI index as a reliable predictor of MetS development in individuals with T2DM.

Dapagliflozin added to metformin reduces perirenal fat layer in type 2 diabetic patients with obesity

Sodium-glucose co-transporters type 2 inhibitors (SLGT2i) are highly effective in controlling type 2 diabetes, but reported beneficial cardiovascular effects suggest broader actions on insulin resistance. Weight loss may be initially explained by glycosuria-induced net caloric output and secondary volumetric reduction, but its maintenance could be due to loss of visceral fat mass. Structured ultrasound (US) imaging of abdominal adipose tissue (“eco-obesity”) is a recently described methodology used to measure 5 consecutive layers of abdominal fat, not assessable by DEXA or CT scan: superficial subcutaneous (SS), deep subcutaneous (DS), preperitoneal (PP), omental (Om) and right perirenal (RK). PP, Om and RK are predictors of metabolic syndrome (MS) with defined cut-off points. To assess the effect of SLGT2i on every fat depot we enrolled 29 patients with type 2 Diabetes (HbA1c 6.5–9%) and Obesity (IMC > 30 kg/m2) in an open-label, randomized, phase IV trial (EudraCT: 2019-000979-16): the Omendapa trial. Diabetes was diagnosed < 12 months before randomization and all patients were treatment naïve. 14 patients were treated with metformin alone (cohort A) and 15 were treated with metformin + dapaglifozin (cohort B). Anthropometric measures and laboratory tests for glucose, lipid profile, insulin, HOMA, leptin, ultrasensitive-CRP and microalbuminuria (MAL) were done at baseline, 3rd and 6th months. At 6th month, weight loss was −5.5 ± 5.2 kg (5.7% from initial weight) in cohort A and −8.4 ± 4.4 kg (8.6%) in cohort B. Abdominal circumference showed a −2.7 ± 3.1 cm and −5.4 ± 2.5 cm reduction, respectively (p = 0.011). Both Metformin alone (−19.4 ± 20.1 mm; −21.7%) or combined with Dapaglifozin (−20.5 ± 19.4 mm; −21.8%) induced significant Om fat reduction. 13.3% of cohort A patients and 21.4% of cohort’s B reached Om thickness below the cut-off for MS criteria. RK fat loss was significantly greater in cohort B group compared to cohort A, at both kidneys. Only in the Met + Dapa group, we observed correlations between Om fat with leptin/CRP/MAL and RK fat with HOMA-IR. US is a useful clinical tool to assess ectopic fat depots. Both Metformin and Dapaglifozin induce fat loss in layers involved with MS but combined treatment is particularly effective in perirenal fat layer reduction. Perirenal fat should be considered as a potential target for cardiovascular dapaglifozin beneficial effects.

Resting metabolic rate in children with obesity: a predictor of metabolic syndrome

Resting metabolic rate in children with obesity: a predictor of metabolic syndrome

Sedentary Lifestyle and Dietary Habits as Predictors of Metabolic Syndrome amongst Middle-aged Adults: A Cross-sectional Analysis

Abstract Introduction: The metabolic syndrome characterised by obesity, dyslipidaemia, hypertension and hyperglycaemia increases risk factors for cardiovascular diseases and diabetes. The purpose of this study is to ascertain the effect of sedentary behaviour and diet in the prevalence of metabolic syndrome in middle-aged adults. Methods: Data collection was done using an online survey amongst 624 Saudi adults aged between 18 and 54 years. Sedentary behaviour and dietary patterns were measured, and metabolic syndrome was defined by two or more of the following: high waist circumference and high blood pressure. Results: Physical inactivity was evident, with 41% of the participants having metabolic syndrome. The results also revealed that the odds of having metabolic syndrome raised to 2 if one spends over 6 h per day sedentary. Threefold (95% confidence interval 1. 3, 3 times, P = 0. 04) as compared to infrequent consumers of sugary beverages, the risk of having the disease was increased by 1. Conclusion: Physical inactivities and wrong dietary patterns greatly increase one’s chances of developing metabolic syndrome. Encouraging exercise and proper diets may help to alleviate this burden in middle-aged individuals.

Baseline urinary osteopontin levels are associated with the improvement of metabolic syndrome

Background and aimsWhile serum osteopontin (OPN)'s established role in cardiometabolic risk is recognized, its potential as a predictor of metabolic syndrome (MetS) improvement through a urine assay has not yet been demonstrated. In this study, we propose its potential predictive role over a 12-month period of standard care, with the ability to complement anthropometric measures. Methods and resultsHierarchical clustering revealed a notable association of urinary OPN (uOPN) with MetS criteria and overcame anthropometric measures in predicting the improvement at 12 months (OR of 2.74 [95% CI 1.32 to 6.29]). uOPN significantly contributed to the homogeneity of the nodes in the random forest and ultimately enhanced the performance of anthropometric measures when assessed for accuracy and area under the curve (AUC). ConclusionOur findings offer insights into potential applications in cardiometabolic medicine for uOPN, which is easily detectable in non-invasive biological samples through an affordable assay.

Sagittal Abdominal Diameter as the Best Predictor of Metabolic Syndrome in HIV-Infected Men on Antiretroviral Therapy.

The interaction of human immunodeficiency virus (HIV), host and antiretroviral therapy (ART) causes a range of metabolic disorders that can be characterized as a metabolic syndrome (MetS) that increases the cardiovascular risk. MetS involves central obesity, which can be detected using different anthropometric parameters. To assess the abilities of different anthropometric parameters in the prediction of MetS in HIV-infected men on ART. The study involved 92 male participants (mean age 44.46±10.38 years), divided into two groups: with and without MetS. All subjects underwent biochemical evaluation (triglycerides, HDL-cholesterol, fasting glucose), blood pressure measurement and anthropometric assessment: body mass, body height, body mass index (BMI), body fat mass, body circumferences (chest, upper arm, forearm, waist, hip, proximal and middle thigh and calf), sagittal abdominal diameter (SAD), skinfold thicknesses (subscapular, anterior and posterior upper arm, anterior and lateral forearm, abdominal, supraspinal, thigh and calf), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), waist-to-thigh ratio (WTR), sagittal abdominal diameter-to-body height ratio (SADH), body adiposity index (BAI) and conicity index. MetS was specified according to IDF criteria. Subjects with MetS had statistically significant higher values of all anthropometric parameters except middle thigh circumference, calf skinfold and body height. According to ROC analysis and Binary Logistic Regression, SAD has been shown as the best predictor of MetS with a predictive value of 21.40 cm (AUC:0.91), followed by WHR with a predictive value of 0.93. Sagittal abdominal diameter is the strongest anthropometric indicator of MetS in HIV-infected patients on ART.

Machine learning analysis for the association between breast feeding and metabolic syndrome in women

This cross-sectional study aimed to develop and validate population-based machine learning models for examining the association between breastfeeding and metabolic syndrome in women. The artificial neural network, the decision tree, logistic regression, the Naïve Bayes, the random forest and the support vector machine were developed and validated to predict metabolic syndrome in women. Data came from 30,204 women, who aged 20 years or more and participated in the Korean National Health and Nutrition Examination Surveys 2010–2019. The dependent variable was metabolic syndrome. The 86 independent variables included demographic/socioeconomic determinants, cardiovascular disease, breastfeeding duration and other medical/obstetric information. The random forest had the best performance in terms of the area under the receiver-operating-characteristic curve, e.g., 90.7%. According to random forest variable importance, the top predictors of metabolic syndrome included body mass index (0.1032), medication for hypertension (0.0552), hypertension (0.0499), cardiovascular disease (0.0453), age (0.0437) and breastfeeding duration (0.0191). Breastfeeding duration is a major predictor of metabolic syndrome for women together with body mass index, diagnosis and medication for hypertension, cardiovascular disease and age.

A Novel Clinical Predictor of Metabolic Syndrome: Vascular Risk Age

A Novel Clinical Predictor of Metabolic Syndrome: Vascular Risk Age