Definition Of Metabolic Syndrome Research Articles

Dietary intake, obesity, and metabolic risk factors among children and adolescents in the SEACO-CH20 cross-sectional study

We investigated the association between dietary intake and metabolic risk factors in children and adolescents within a semi-rural Malaysian community. Using an interviewer-led questionnaire, we surveyed 623 participants aged 7–18 from the South East Asia Community Observatory (SEACO). Anthropometric and blood pressure data were collected from all participants, while a subset (n = 162) provided blood samples for biomarker analysis, including fasting blood glucose (FBG), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Metabolic syndrome was determined using the International Diabetes Federation’s Definition of Metabolic Syndrome in Children and Adolescents. Most participants were Malay (66.8%), with a median household income of MYR1,500 and a balanced sex distribution. Cereals, processed foods, beverages, fruits, and vegetables were commonly consumed. Obesity and abdominal obesity were prevalent, affecting more than a third of participants. Adherence to dietary recommendations was generally poor (ranging from 19.9 to 58.1%) and varied across age, sex, and ethnicity. Notably, some food groups displayed unexpected associations with health markers; for instance, fruit consumption was linked to abdominal obesity in children (abdominal obesity vs. normal: 2.4 servings/day vs. 1.6 servings/day). These findings emphasise the necessity of longitudinal studies to explore the complex relationship between diet and long-term health outcomes, including cardiometabolic diseases, while acknowledging the unique challenges posed by the COVID-19 pandemic on data collection and analysis.

Deep learning imaging phenotype can classify metabolic syndrome and is predictive of cardiometabolic disorders

BackgroundCardiometabolic disorders pose significant health risks globally. Metabolic syndrome, characterized by a cluster of potentially reversible metabolic abnormalities, is a known risk factor for these disorders. Early detection and intervention for individuals with metabolic abnormalities can help mitigate the risk of developing more serious cardiometabolic conditions. This study aimed to develop an image-derived phenotype (IDP) for metabolic abnormality from unenhanced abdominal computed tomography (CT) scans using deep learning. We used this IDP to classify individuals with metabolic syndrome and predict future occurrence of cardiometabolic disorders.MethodsA multi-stage deep learning approach was used to extract the IDP from the liver region of unenhanced abdominal CT scans. In a cohort of over 2,000 individuals the IDP was used to classify individuals with metabolic syndrome. In a subset of over 1,300 individuals, the IDP was used to predict future occurrence of hypertension, type II diabetes, and fatty liver disease.ResultsFor metabolic syndrome (MetS) classification, we compared the performance of the proposed IDP to liver attenuation and visceral adipose tissue area (VAT). The proposed IDP showed the strongest performance (AUC 0.82) compared to attenuation (AUC 0.70) and VAT (AUC 0.80). For disease prediction, we compared the performance of the IDP to baseline MetS diagnosis. The models including the IDP outperformed MetS for type II diabetes (AUCs 0.91 and 0.90) and fatty liver disease (AUCs 0.67 and 0.62) prediction and performed comparably for hypertension prediction (AUCs of 0.77).ConclusionsThis study demonstrated the superior performance of a deep learning IDP compared to traditional radiomic features to classify individuals with metabolic syndrome. Additionally, the IDP outperformed the clinical definition of metabolic syndrome in predicting future morbidities. Our findings underscore the utility of data-driven imaging phenotypes as valuable tools in the assessment and management of metabolic syndrome and cardiometabolic disorders.

Prevalence and Associations Between Metabolic Syndrome Components and Hyperuricemia by Race: Findings From US Population, 2011-2020.

We explored the trend in prevalence of hyperuricemia and metabolic syndrome in US populations and investigated associations between components of metabolic syndrome and hyperuricemia by race. We analyzed data from the four most recent National Health and Nutrition Examination Survey (NHANES) cycles (2011 to March 2020), comprising 10,175 participants. Hyperuricemia is defined as serum urate >7.0 mg/dL (men) or >5.7 mg/dL (women), following the NHANES-III guideline. The definition of metabolic syndrome follows the National Cholesterol Education Program's Adult Treatment Panel III guideline. We estimated the prevalence of metabolic syndrome and hyperuricemia in each cycle and performed subgroup analyses with logistic regression to investigate the patterns of associated components of metabolic syndrome with hyperuricemia. In the most recent cycle (2017 to March 2020), the prevalence of metabolic syndrome was 45.9% and that of hyperuricemia was 20.7%. Over the 2011 to 2020 period, a significant rise in metabolic syndrome prevalence was observed among Hispanic and Asian populations, and the prevalence of hyperuricemia has increased significantly only in the Hispanic population. After adjustment for confounding factors, patients with metabolic syndrome exhibited a higher hyperuricemia in women than in men. Elevated blood pressure was the strongest factor with hyperuricemia. The association was the weakest in the Asian population. Waist circumference was the only significant factor associated with hyperuricemia in the Asian population. The prevalence of metabolic syndrome has an increasing pattern, but there was no specific decadal trend in prevalence of hyperuricemia. There is an ethnicity-specific association of metabolic syndrome and hyperuricemia, especially among Asians.

Metabolic Syndrome Prevalence in Women with Gestational Diabetes Mellitus in the Second Trimester of Gravidity.

Background: Women with gestational diabetes (GDM) have an increased risk of metabolic syndrome (MS) after delivery. MS could precede gravidity. The aims of this study were (i) to detect the prevalence of MS in women at the time of GDM diagnosis, (ii) to detect the prevalence of MS in the subgroup of GDM patients with any form of impaired glucose tolerance after delivery (PGI), and (iii) to determine whether GDM women with MS have a higher risk of peripartal adverse outcomes. Methods: A cross-sectional observational study comprised n = 455 women with GDM. International Diabetes Federation (IDF) criteria for MS definition were modified to the pregnancy situation. Results: MS was detected in 22.6% of GDM patients in those with PGI 40%. The presence of MS in GDM patients was associated with two peripartal outcomes: higher incidence of pathologic Apgar score and macrosomia (p = 0.01 resp. p = 0.0004, chi-square). Conclusions: The presence of MS in GDM patients is a statistically significant risk factor (p = 0.04 chi-square) for PGI. A strong clinical implication of our findings might be to include MS diagnostics within GDM screening using modified MS criteria in the second trimester of pregnancy.

Cutoffs of different body measurement indexes of central obesity in patients with type 2 diabetes

Few research discuss whether the body measurement indexs of obesity in general populations is applicable to patients with type 2 diabetes. We explore the optimal cutoffs of visceral fat area (VFA) and subcutaneous fat area (SFA) in the diagnosis of central obesity and the cutoffs of corresponding waist circumference (WC) and body mass index (BMI) in patients with Type 2 Diabetes (T2D). Cross-sectional cohort study. 1057 patients with T2D (550 males and 507 females) aged 18 or above that satisfied the criteria were included. The definition and diagnostic criteria of Metabolic syndrome (Mets) were analyzed according to the 2020 Chinese Diabetes Society (CDS) Guideline. The VFA and SFA were measured by bioelectrical impedance analysis (BIA). The optimal VFA and SFA cutoffs and corresponding WC and BMI when two or more nonadipose components of MetS (without central obesity) were met were analyzed by ROC curve. Among all of the T2D patients, the optimal VFA cutoff for identifying two or more nonadipose components of MetS was 73.30 cm2 for females and 69.20 cm2 for males, while the optimal SFA cutoff was 186.70 cm2 for females and 123.30 cm2 for males. The ROC area under curve (AUC) of VFA for identifying two or more nonadipose components of MetS was higher than that of SFA (Female: 0.65 vs. 0.58, P = 0.01). The VFA cutoff of newly diagnosed T2D patients (females = 86.10 cm2, males = 69.00 cm2) was higher than that of non-newly diagnosed T2D patients (females = 73.30 cm2, males = 65.40 cm2). A stratification analysis of gender and whether newly diagnosed with T2D or not showed that the WCs corresponding to VFA were 85.00 cm and BMI was about 24.00 kg/m2. VFA measured by BIA can be a non-invasive method to detect central obesity in patients with T2D, the corresponding WC were 85.00 cm and BMI was 24.00 kg/m2.

Comparing the association of two metabolic syndrome definitions, NCEP ATP III and IDF, with the risk of developing atherosclerotic cardiovascular disease: An analytical cross-sectional study.

Atherosclerotic cardiovascular diseases (ASCVD) are significant sources of mortality and morbidity with substantial economic implications and preventive measures play key roles in this regard. Metabolic syndrome (MetS) is a common condition, and its association with ASCVD and mortality has made it clinically important. However, controversies persist regarding the best definition for MetS. Here in, we investigated the ability of the International Diabetes Federation (IDF) and the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) in the prediction of ASCVD incidence. We conducted an investigation on individuals diagnosed with MetS as part of the "Kerman Coronary Artery Diseases Risk Factor Study" (KERCADRS). This study was a cohort study conducted on a population aged 15-75 years residing in Kerman, Iran to assess the risk of ASCVD. We employed ACC/AHA ASCVD Risk Estimator for predicting ASCVD occurrence in the future and then compared the results with different definitions of MetS including IDF and NCEP ATP III. Patients with MetS consistent with NCEP ATP III had higher ASCVD risk scores than those with IDF (10.63 ± 10.989 vs. 9.50 ± 9.357). NCEP ATP III had better overall performance in terms of specificity, accuracy, sensitivity and positive and negative predictive values especially in higher ASCVD risk score categories. The agreement between IDF and NCEP ATP III was none to slight (Cohen's Kappa <0.2) except for IDF in the group of ASCVD >30%, which revealed no agreement (Cohen's Kappa = 0). NCEP ATP III has better overall performance compared to IDF. The ability of NCEP ATP III increases as the ASCVD risk score goes higher. IDF may be useful in primary screening and patients with lower ASCVD risk scores.

Emerging Perspectives on the Set of Conditions That Lead to the Emergence of Metabolic Syndrome.

Metabolic syndrome, as a medical condition, presents multifactorial complexity that is characterized by the resulting damage from genetic, environmental, and lifestyle factors (presence or absence of physical activity, food choices). Thus, metabolic syndrome qualifies unequivocally as a medical condition in which there are, simultaneously, several independent metabolic risk factors, namely, abdominal obesity, high triglyceride level, low HDL cholesterol level, arterial hypertension, and high glycemic level. Although age, sex, socio-economic status, and the precise definition of metabolic syndrome all influence the prevalence and risk of developing the condition, clinical and epidemiological studies clearly show that central obesity, as measured by an increased abdominal circumference, is the main risk factor. Thus, due to the growing global incidence of obesity, there has been an increase in the incidence of metabolic syndrome. Starting with obesity, all other metabolic risk factors are influenced: for example, as a result of insulin resistance with hyperglycemia, diabetes is linked to an increased risk of cardiovascular disease due to increased abdominal circumference. Through this review, we aimed to highlight the latest research studies and dietary nutritional interventions useful in the prevention of this disease but also implementation strategies for primary prevention among the healthy population.

Evaluating metabolic syndrome criteria in gabonese type 2 diabetes patients

Background : Metabolic syndrome (MS) is the association of several cardiovascular risk factors. It aggravates cardiovascular complications, in diabetic subjects. Its prevalence depends on the definition used to describe it. This study aimed to compare four definitions of metabolic syndrome in type 2 diabetic subjects in Gabon.&#x0D; Materials And Methods : It was a prospective, observational study of type 2 diabetic subjects, followed at the University Hospital of Libreville. The MS was defined according to the criteria of the WHO, the National Education Program on NCEP ATP III Cholesterol, those of the International Diabetes Federation FID and the harmonized definition. Cohen's Kappa test was used to assess the two-to-two concordance between definitions and differences were significant for a p value&lt; 0.05.&#x0D; Results : The panel was composed of 100 diabetics. The 4 definitions, showed the respective SM values of 41%, 71%, 64% and 78%. All methods showed that women were more affected and that abdominal obesity was the most common metabolic abnormality. The best concordance was found between the NCEP definition and the harmonized one (k= 0.82 p=0.000).&#x0D; Conclusion : The prevalence of metabolic syndrome showed female predominance according to the 4 definitions. The NCEP ATP III and harmonized definitions gave the most consistent results within this population.

Personal exposure of PM2.5 and metabolic syndrome markers of pregnant women in South Korea: APPO study

We examined the association between exposure to PM2.5, focused on individual exposure level, and metabolic dysfunction during pregnancy. APPO study (Air Pollution on Pregnancy Outcome) was a prospective, multicenter, observational cohort study conducted from January 2021 to March 2023. Individual PM2.5 concentrations were calculated using a time-weighted average model. Metabolic dysfunction during pregnancy was assessed based on a modified definition of metabolic syndrome and its components, accounting for pregnancy-specific criteria. Exposure to PM2.5 during pregnancy was associated with worsened metabolic parameters especially glucose metabolism. In comparison to participants exposed to the low PM2.5 group, those exposed to high PM2.5 levels exhibited increased odds of gestational diabetes mellitus (GDM) after adjusting for confounding variables in different adjusted models. Specifically, in model 1, the adjusted odds ratio (aOR) was 3.117 with a 95% confidence interval (CI) of 1.234–7.870; in model 2, the aOR was 3.855 with a 95% CI of 1.255–11.844; in model 3, the aOR was 3.404 with a 95% CI of 1.206–9.607; and in model 4, the aOR was 2.741 with a 95% CI of 0.712–10.547. Exposure to higher levels of PM2.5 during pregnancy was associated with a tendency to worsen metabolic dysfunction markers specifically in glucose homeostasis. Further research is needed to investigate the mechanisms underlying the effects of ambient PM2.5 on metabolic dysfunction during pregnancy.

Unsupervised identification of cardiometabolic profiles among adolescents: findings from the PARIS birth cohort study

Metabolic syndrome (MetS) is known as a risk factor in cardiometabolic morbidity but there is no consensus on its definition for teenagers. We aimed to identify cardiometabolic health profiles and which parameters best discriminate them. K-means partitioning identified cardiometabolic profiles by sex using data on health measurements of 530 adolescents from the PARIS birth cohort. A discriminant analysis was performed. Cardiometabolic risk score and handgrip strength were also measured. Depending on definitions, MetS prevalence ranged from 0.2% to 1.3%. Two profiles were identified for the entire group and by sex: “healthy” and “at cardiometabolic risk.” Weight and waist-to-height ratio or waist circumference explained more than 87% of the variance in the profile differentiation. The “at cardiometabolic risk” profiles included adolescents with overweight, a waist-to-height ratio over 0.5, and prehypertension. They had higher cardiometabolic risk scores and parents who were more likely to be overweight and have cardiometabolic diseases themselves. They also had higher birthweights, earlier adiposity-rebound and puberty ages, and lower relative handgrip strength. Conclusion: The two profiles identified, based on cardiometabolic health, were associated with early indicators and handgrip strength. Results suggest that the waist-to-height ratio is a useful clinical tool for screening individuals at cardiometabolic risk and who therefore require clinical follow-up.What is Known:• Although there is a need for tools to assess cardiometabolic health during adolescence, there is no consensus on the definition of metabolic syndrome for this age group.What is Knew:• The findings suggest that waist-to-height ratio can serve as a simple and valuable clinical tool for screening individuals at cardiometabolic risk who may require clinical monitoring for early prevention of cardiovascular diseases.

Comparison of different definitions of metabolic syndrome and their associations with non-alcoholic fatty liver disease: a retrospective study.

Metabolic syndrome (MetS) is considered an important risk factor for non-alcoholic fatty liver disease (NAFLD). The aim of this study was to measure the prevalence of MetS based on six different MetS definitions and compare the performance of various definitions for identifying diabetes, hypertension, and dyslipidemia among NAFLD patients. The definitions compared were those developed by the World Health Organization (WHO), National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III), International Diabetes Federation (IDF), American Association of Clinical Endocrinologists (AACE), American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI), and Interim Joint Statement "harmonized" criteria. Receiver operator characteristic (ROC) curves were plotted for the six MetS definitions with NAFLD diagnosis. The diagnosis for NAFLD was established based on liver imaging or biopsy compatible with fatty liver disease. A total of 500 NAFLD patients were analyzed. The mean age was 61.2 (SD 13.2) years, and BMI was 32.7 (SD 8.0) kg/m2. The most prevalent MetS component was dyslipidemia (83%), followed by hypertension (60%), obesity (61%), and diabetes (57%). The prevalence of MetS according to the WHO, NCEP/ATP-III, IDF, AACE, AHA/NHLBI, and harmonized criteria was 69%, 59%, 54%, 64%, 78%, and 79%, respectively. The highest area under the ROC curve for diabetes and hypertension was with the WHO definition (0.7405) and (0.8120), respectively. The prevalence of MetS in NAFLD patients varies according to the definitions of MetS employed. The modified WHO definition appeared to be most useful for the screening of MetS in NAFLD patients.

Insulin resistance and central obesity determine hepatic steatosis and explain cardiovascular risk in steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has recently been proposed to replace non-alcoholic fatty liver disease and focus on patients with progressive disease due to the presence of metabolic dysfunction. However, it is unclear whether the new definition actually identifies patients with hepatic steatosis at increased cardiovascular risk. A total of 4,286 asymptomatic subjects from the SAKKOPI study aged 45-80 years undergoing screening colonoscopy were analyzed. Steatosis was diagnosed by abdominal ultrasound. MASLD was diagnosed according to the recent expert consensus. Insulin resistance was assessed by homeostasis model assessment-insulin resistance score (HOMA-IR) (cutoff: ≥2.5), subclinical inflammation was estimated by ferritin/CRP/uric acid, and cardiovascular risk was assessed using SCORE2/ASCVD. Mean age was 59.4 ± 8.5 years, 51.6% were male; mean BMI was 27.0 ± 4.5 kg/m², 9.2% had type 2 diabetes mellitus. In total, 1,903 (44.4%) were diagnosed with hepatic steatosis and were characterized by more severe metabolic dysfunction including insulin resistance (47.1% vs. 12.2%, p < 0.001) and central obesity (waist circumference ≥102/88 cm, 71.8% vs. 37.1%, p < 0.001). This translated into higher (subclinical) inflammation (ferritin 153 vs. 95 mg/dL, p < 0.001, uric acid 6.3 mg/dL vs. 5.2 mg/dL, p < 0.001) and 10-year cardiovascular risk (SCORE2 7.8 points vs. 5.1 points, p < 0.001, ASCVD 17.9 points vs. 10.8 points, p < 0.001). 99.0% of subjects with steatosis met the MASLD definition, 95.4% met the MAFLD definition, and 53.6% met the definition of metabolic syndrome, while 95.4% of subjects without steatosis also met the MASLD criteria for metabolic dysfunction compared to 69.0% and 17.4% who met the MAFLD and metabolic syndrome criteria, respectively. Forward stepwise regression indicated that waist circumference, HOMA-IR, and triglycerides were most relevant in explaining the presence of hepatic steatosis across all subgroups of increasing metabolic dysfunction. At the same time, hepatic steatosis was not associated with cardiovascular risk in the overall cohort (SCORE2: B = 0.060, 95% CI: -0.193-0.314, and p = 0.642) and in patients with metabolic dysfunction after adjusting for age, sex, and these three metabolic dysfunction components. Although hepatic steatosis is associated with increased central obesity and insulin resistance, metabolic dysfunction per se rather than hepatic steatosis explains cardiovascular risk in these patients.

Metabolic syndrome, adiposity, diet, and emotional eating are associated with oxidative stress in adolescents.

Metabolic syndrome (MS), a condition related to adiposity and oxidative stress, can develop in adolescence, a critical stage in life that impacts health in adulthood. However, there is scarce scientific research about the relationship between lifestyle factors, emotion management, and oxidative stress in this phase of life. To analyze whether nutritional parameters, lifestyle factors, emotion management, and MS in adolescents are associated with oxidative stress measured by the biomarker 8-isoprostane. A cross-sectional study was carried out in 132 adolescents (48.5% girls, aged 12 ± 0.48 years) and data were collected on nutritional parameters (anthropometric measurements, biochemical analyzes, and blood pressure), lifestyle factors (physical activity, sleep, and diet), and emotion management (self-esteem, emotional eating, and mood). 8-isoprostane was analyzed in spot urine samples. The study population was categorized in three groups (healthy, at-risk, and with MS) using the International Diabetes Federation definition of MS in adolescents. To capture more complex interactions, a multiple linear regression was used to analyze the association between 8-isoprostane and the aforementioned variables. Urinary 8-isoprostane levels were significantly higher in the MS group compared to the healthy group (1,280 ± 543 pg./mg vs. 950 ± 416 pg./mg respectively). In addition, univariable analysis revealed positive significant associations between 8-isoprostane and body mass index, waist circumference, waist-to-height ratio, body fat percentage, blood lipid profile and glucose, emotional eating, and refined cereal intake. Conversely, a negative significant association was found between 8-isoprostane and sleep duration and fish intake. The multiple linear regression analysis revealed associations between 8-isoprostane and LDL-c (β = 0.173 value of p = 0.049), emotional eating (low β = 0.443, value of p = 0.036; high β = 0.152, value of p = 0.470), refined cereal intake (β =0.191, value of p = 0.024), and fish intake (β = -0.187, value of p = 0.050). The MS group, LDL-c, emotional eating, and high refined cereals and low fish intakes were associated with higher levels of oxidative stress in an adolescent population.

METABOLİK SENDROM

Metabolic syndrome is a common health problem, is an important cause of mortality and morbidity. Metabolic syndrome is a type of disorder that occurs as a result of the coexistence of insulin resistance and obesity-like findings, hipertriglisemi, hypertension, Type 2 diabetes mellitus, dyslipidemia and non-alcoholic fatty liver disease, stress, low HDL, hyperglycemia, inflammation, adipocyte-derived aldosterone-releasing factors, sleep apnea, etc. The same criteria and symptoms are valid for the disease in animals, and similar definitions are made for animals. In recent years, interest in metabolic syndrome, its causes and consequences has increased in veterinary medicine as well as in human medicine. In the formation of the disease, with the development of industry and technology, besides genetic factors urbanization, sedentary life, fast and high-calorie food consumption and many environmental factors such as smoking and alcohol use play role. In addition to this, many situations are shown in animals such as breed, neutralism, relationship with the owner, ration content, loss of hunter, catcher, etc. characteristics by assimilating to today's conditions. Many internationally recognized institutions such as the National Cholesterol Education Program (NCEP) ATPIII, the International Diabetes Federation (IDF), the World Health Organization (WHO), the Turkish Society of Endocrinology and Metabolism have made definitions for metabolic syndrome. In this article, metabolic syndrome, which has a significant impact on human and animal life, is examined in general terms.

Investigating Adiposity-Related Metabolic Health Phenotypes in Patients with Hidradenitis Suppurativa: A Cross-Sectional Study.

Obesity and hidradenitis suppurativa (HS) are related through meta-inflammation and are both associated with increased cardiometabolic risk. Notwithstanding, cardiometabolic pathology is not uniform in obesity and a subset of individuals with excess adiposity exhibit a healthy metabolic profile. Whilst the incidence of cardiometabolic endpoints and transitions across different adiposity-related body composition phenotypes within several populations and across different ethnicities have been investigated, data regarding metabolic health (MetH) and body composition phenotypes in individuals with HS are lacking. The objective of this study was to evaluate the relationship between different body composition phenotypes in individuals with HS. This was a cross-sectional study of 632 individuals with and without HS from a population with a high prevalence of both obesity and HS. A total of four body composition phenotypes were generated based on BMI and metabolic status (defined using either the metabolic syndrome definition or the homeostasis model of insulin resistance (HOMA-IR)): metabolically healthy overweight/obese (MHOWOB), metabolically unhealthy overweight/obese (MUOWOB), metabolically healthy normal weight (MHNW), and metabolically unhealthy normal weight (MUNW). Generally, subjects with HS exhibited a worse metabolic profile with higher levels of indices of central adiposity measures (including Visceral Adiposity Index and waist circumference), systolic blood pressure and markers of insulin resistance, as well as a higher prevalence of the metabolic syndrome. Moreover, when sub-stratified into the different body composition phenotypes, individuals with HS typically also demonstrated adverse metabolic characteristics relative to controls matched for both adiposity and metabolic health, particularly in the normal weight category and despite being classified as metabolically healthy. Being metabolically unhealthy in addition to being overweight/obese increases an individual's risk of HS. Metabolic risk-assessment should be prioritized in the clinical management of individuals with HS even in those who are lean. Patients attending HS clinics provide a valuable opportunity for targeted cardiovascular risk reduction with respect to the management of both obesity and metabolic health.

Predictive estimation of the Visceral Adiposity Index (VAI) and Dysfunctional Adiposity Index (DAI) for metabolic syndrome in a working population

To evaluate metabolic syndrome using three methodsproposed by recognizedinternational institutions, and the visceraladiposity (VAI)anddysfunctionaladiposity (DAI)indices for prediction and prevalence estimation in working populations. Cross-sectional study in workers from different Spanish autonomous communities who underwent a health examination between January 2019 and September 2021 at four occupational risk prevention services. Metabolic syndrome was evaluated according to criteria from the National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATP-III), the International Diabetes Federation (IDF) and the Joint Interim Statement (JIS). VAI and DAI values were calculated using their specific formulas and their predictive capacity was measured using ROC curves. The SPSS 27.0 program was used, with statistical significance level set at p< 0.05. 418 343 workers were included, mostly men (58.8%), average age between 30 and 49 years (58.0%), social class III, mostly manual workers (75.9%) and nonsmokers (66.9%). The prevalence of metabolic syndrome differed depending on the criteria used, being higher in men with IDF and JIS, and in women with ATPIII. For the three definitions of metabolic syndrome, the values of the area under the curve were > 0.8 (>80%). The highest VAI was obtained with the JIS, and the highest DAI with the ATPIII. The highest confidence index was for ATPIII and JIS. The VAI and ICD adiposity indices show high predictive capacity in metabolic syndrome with all three criteria used and can be useful for prevention activities in occupational health.

Association between Menopause, Postmenopausal Hormone Therapy and Metabolic Syndrome.

(1) Background: We aimed to explore the associations between menopause, postmenopausal hormone therapy, and metabolic syndrome in a large community-based group of Asian women. (2) Methods: This is a cross-sectional study in which we enrolled women aged 30 to 70 years with sufficient information about menopausal status from the Taiwan Biobank. The definition for metabolic syndrome used in this study aligns with the Bureau of Health Promotion's (Taiwan) proposed definition. (3) Results: A total of 17,460 women were recruited. The postmenopausal group had a higher metabolic syndrome prevalence (30% vs. 14%) and 1.17 times higher odds ratio (OR) than the premenopausal group (95% confidence interval [CI] = 1.02 to 1.33). Regarding the types of menopause, surgical menopause was associated with metabolic syndrome (OR = 1.40; 95% CI = 1.20 to 1.63); however, natural menopause was not associated with metabolic syndrome. Interestingly, postmenopausal hormone therapy was associated with a lower risk of metabolic syndrome in the women with natural menopause (OR = 0.79; 95% CI = 0.70 to 0.89), but not in those with surgical menopause. (4) Conclusions: Our results suggest that menopause is associated with an increased prevalence of metabolic syndrome, while postmenopausal hormone therapy is associated with a lower prevalence of metabolic syndrome in women with natural menopause.

#4869 ULTRASOUND IMAGING PATTERNS OF KIDNEY DISEASE IN PATIENTS WITH METABOLIC SYNDROME

Abstract Background and Aims Meeting definition of metabolic syndrome (MetS) requires detection of central obesity (increasing waist circumference, WC) plus any two of the other four factors (hyperglycemia, dyslipidemia, cardiovascular disease, hypertension) [1]. Up to date, kidney evaluation is not fully reflected in MetS evaluation. Multiparameter ultrasound (US) can provide accurate information on every MetS sign [2] and for specific detecting type of chronic kidney disease (CKD) [3]. The Aim was to study added diagnostic value of ultrasound diagnosis of chronic kidney disease in patients with MetS for precise diagnosis and patients stratification. Method We included 48 overweight subjects patients (27-75 years; 25 women) with signs of MetS, BMI &amp;gt; 30, waist circumference (WC) &amp;gt; 110. The control group included 50 healthy individuals (26 women), mean age 43 ± 7 years without clinical, laboratory signs of MetS, nephropathy and liver pathology. All patients underwent general clinical, lab tests; abdominal US including precise multiparameter US of kidneys as in [3] measuring shear wave elastography (SWE), Doppler in parenchyma and vessels. We determined fat accumulations measuring VF and subcutaneous (SF) fat thickness (cm) and areas (cm2) on US. Results We detected hypertension (in 62%); hypercholesterolemia (in 45%); hyperuricemia (in 28%); hyperglycemia (in 32%); nephropathy (in 37%), portal hypertension (in 32%) in obese individuals (vs controls p &amp;lt; 0.05). In all patients we found increasing of visceral fat and various abnormalities in kidneys on US, we distinguished patterns in according to constituents of MetS by its definition s follows: Diabetic nephropathy included mild decresing or normal kidneys size, thinning parenchyma, low differentiation, clear smooth margings, Doppler showed mild decreasing velocities, increasing of RI in segmental arteries over 0.7 (Figure 1). Ischemic pattern associated with advanced atherosclerosis included severe decreasing of size, thinned, hyperechoic parenchyma; decreasing velocities under 25 cm/s., severe increasing of RI over 0.8. Hypertension associated nephropathy: mild changes in structure, normal velocities, increased RI (Figure 2). Hypertension correlated with levels of RI. Nephropathy in hyperuricemia and gout: signs as in [3] included thinning, increasing echogenicity of kidney parenchyma (P &amp;lt; 0.05), detection of fibrotic changes and small hyperechoic inclusions, hilly margins, anaechoic strips under the capsule, RI increasing in segmental arteries over 0.7. “Circular pyramyds pattern” included hyoerechoic circles around pyramids (white pyramid sign, hyperdense renal pyramids sign) with normal size, normal / mild increase of RI. SWE showed increased parenchyma stiffness to 10 ± 1.7 kPa (6–17 kPa) versus 4.2 ± 1.2 kPa (P &amp;lt; .05), showed differences among patterns, highest values were in nephropathy in gout and ischemia. Conclusion Multiparameter ultrasound is effective for detecting and distinguishing patterns of kidney disease in MetS provides additional value for differentiation and modification treatment and targeted prevention. Kidney involvement should be considered in management of MetS.

Critical assessment of the metabolic syndrome definitions in the adult general population of the United States - the Multi-Ethnic Study of Atherosclerosis (MESA).

Metabolic syndrome (MetS) consists of a cluster of cardiometabolic risk factors and is an important determining factor for cardiovascular diseases (CVDs). We intended to use latent class analysis to classify the study population into several clusters. The baseline information of 6,814 participants of the Multi-Ethnic Study of Atherosclerosis (MESA) aged 45-84 years in 2000-2002 was used. The latent class analysis was conducted to extract different patterns of components. SAS 9.2 and Stata 12 software were used for analysis. The components of MetS tend to accumulate, hence it would be feasible to categorize the population into three classes: [1] Non-Metabolic Syndrome Latent Class (NonMetS-LC), [2] Low Risk Latent Class (LowR-LC), and [3] Metabolic Syndrome Latent Class (MetS-LC). In women, adding high-density lipoprotein (HDL) component to the two-component combinations of NonMetS-LC will transfer the individual to MetS-LC, and it was found in 100% of combinations of MetS-LC. However, in men, blood pressure (BP) played such a similar role, which was found in 97.36% of combinations of MetS-LC. Results showed that clinical value of each MetS component is different by gender. The main component in men was elevated BP; while low HDL and elevated fasting blood sugar (FBS) were in next ranks. However, the main component in women was low HDL; while elevated BP and FBS were in next ranks. Special attention should be paid to BP and HDL components, because these can be useful for clinicians and health policy-makers in diagnosis and screening. In conclusion, this study showed that revisions might be needed for the MetS definitions.

Metabolic syndrome in patients with gout

Introduction. The definition of metabolic syndrome is not yet consistent. However, many studies have been conducted in the latest decades about the effect of increased uric acid on metabolic syndrome development. Large epidemiological studies on the association between hyperuricemia and MS showed that increased concentration of serum urea is often observed in subjects with metabolic syndrome. The aim of the study was to characterize specific dysmetabolic changes and features of extraarticular evolution in patients with gout. Materials and methods. A descriptive study was conducted that included 501 patients with gout. The mean age of gout (423 men and 78 women) was 49.2 (36.9; 59.9). The diagnosis of gout was established according to the classification criteria for gout ACR/EULAR 2015. The raw data was processed in SPSS version 26.0. Results. According to our data, the highest severity of obesity and LDL-cholesterol was detected in those with tophaceous gout, which also caused an increase in the frequency of high blood pressure and type 2 diabetes, with age differences in the frequency of detection of metabolic syndrome and insulin resistance. Our data have noted that serum levels of uric acid correlated with the risk of developing both metabolic syndrome as well as its components - obesity, hypertension, and dyslipidemia, but inversely correlated with hyperglycemia. Conclusions. Gout is associated with a severe lipid metabolism dysfunction, significantly increasing the rate of metabolic syndrome especially among patients with chronic tophaceous gout, than in the group of patients with gout under the age of 59 years. On the other hand, in patients with the onset of gout who are ≤59 years lipid metabolism disorders occur significantly earlier than in patients with the onset of gout at the age of ≥60 years.