Evaluation of Fasting Glucose-Insulin-C-Peptide-Derived Metabolic Indices for Identifying Metabolic Syndrome in Young, Healthy Adults.

Metabolic syndrome (MetS) is a condition defined by a cluster of symptoms, including excessive adipose tissue, impaired glucose homeostasis, dyslipidemia, and high blood pressure (BP). We aimed to evaluate the correlation between the MetS criteria (IDF) and fasting glucose-insulin-C-peptide-derived indices in a cohort of 128 healthy young adults who were 20-35 years old at the time of this study. We measured fasting serum glucose, insulin, C-peptide (CP), HDL-cholesterol, triglycerides, and hsCRP; HOMA-IR INS, HOMA-IR CP1, HOMA-IR CP2, HOMA-BETA, HOMA-BETA CP, QUICKI, disposition index (DI), CP index (CPI), and 20/C-peptide*glucose. Significant correlations were found between BMI and all HOMA indices, QUICKI, and CPI; waist circumferences and HOMA-IR INS, HOMA-BETA, and QUICKI (for both sexes); glucose and HOMA-IR INS/CP1/CP2, HOMA-BETA CP, DI, and QUICKI; HDL-cholesterol and HOMA-IR INS, HOMA-BETA, and QUICKI for males and females only with QUICKI; triglycerides and HOMA-IR INS, HOMA-BETA, and QUICKI; systolic BP and HOMA-IR INS, HOMA-BETA; diastolic BP and DI. The cut-off values for HOMA-IR INS, HOMA-BETA, and QUICKI in the combined group (females + males) were 1.855, 82.250, 0.355; 2.115, 106.370, 0.345 for males; 1.805, 71.305, 0.355 for females. A stronger correlation was found between males' indices and hsCRP. In conclusion, CP-derived indices do not add significant information, and the male sex is more predisposed to MetS.

Risk of Cardiovascular Events Associated with Chronic Obstructive Pulmonary Disease and/or Metabolic Syndrome: A Large-Scale Nationwide Population-Based Cohort Study.

Purpose: Chronic obstructive pulmonary disease (COPD) and metabolic syndrome (MetS) are among the most prevalent conditions that might predispose individuals to life-threatening events. We aimed to examine their associations with cardiovascular (CV) events and mortality using a large-scale population dataset from the National Health Information Database in Korea. Patients and Methods: This population-based cohort study enrolled adults aged ≥40 years who had undergone more than two health examinations between 2009 and 2011. They were divided into four groups based on the presence of COPD and MetS. Analysis of the outcomes and CV events or deaths was performed from 2014 to 2019. We compared CV event incidence and mortality rates using a multivariate Cox proportional hazards model and Kaplan-Meier curves. Results: Totally, 5,101,810 individuals were included, among whom 3,738,458 (73.3%) had neither COPD nor MetS, 1,193,014 (23.4%) had only MetS, 125,976 (2.5%) had only COPD, and 44,362 (0.9%) had both. The risk of CV events was significantly higher in individuals with both COPD and MetS than in those with either COPD or MetS alone (HRs: 2.4 vs 1.6 and 1.8, respectively; all P <0.001). Similarly, among those with both COPD and MetS, all-cause and CV mortality risks were also elevated (HRs, 2.9 and 3.0, respectively) compared to the risks in those with either COPD (HRs, 2.6 and 2.1, respectively) or MetS (HRs, 1.7 and 2.1, respectively; all P <0.001). Conclusion: The comorbidity of MetS in patients with COPD increases the incidence of CV events and all-cause and cardiovascular mortality rates.

Alanine aminotransferase predicts incident steatotic liver disease of metabolic etiology: Long life to the old biomarker!

Alanine aminotransferase (ALT) serum levels increase because of hepatocellular damage. Metabolic dysfunction-associated fatty liver disease (MAFLD), which identifies steatotic liver disease (SLD) associated with ≥ 2 metabolic abnormalities, has prominent sexual differences. The Metabolic Syndrome defines a cluster comprising abdominal obesity, altered glucose metabolism, dyslipidemia, and hypertension. Male sex, body mass index, glucose, lipids, ferritin, hypertension, and age independently predict ALT levels among blood donors. Over the last few decades, the reference range of ALT levels has been animatedly debated owing to attempts to update sex-specific reference ranges. With this backset, Chen et al have recently published a study which has two main findings. First, > 80% of individuals with MAFLD had normal ALT levels. Second, there was a linear increasing trend in the association between cumulative excess high-normal ALT levels and the rate of incident MAFLD. This study has biologically credible findings. However, it inaccurately considered sex differences in the MAFLD arena. Therefore, future studies on SLD owing to metabolic dysfunction should adopt locally determined and prospectively validated reference ranges of ALT and carefully consider sex differences in liver enzymes and MAFLD pathobiology.

Superiority of the triglyceride glucose index over the homeostasis model in predicting metabolic syndrome based on NHANES data analysis.

The triglyceride-glucose (TyG) index is a simple and inexpensive new marker of insulin resistance that is being increasingly used for the clinical prediction of metabolic syndrome (MetS). Nevertheless, there are only a few comparative studies on its predictive capacity for MetS versus those using the traditional homeostasis model assessment (HOMA). We conducted a cross-sectional study using a database from the National Health and Nutrition Examination Survey (1999 March to 2020 pre-pandemic period). Using statistical methods, we compared the predictive abilities of the TyG index and HOMA (including HOMA of insulin resistance [HOMA-IR] and HOMA of beta-cell function [HOMA-ß]) for MetS. A total of 34,195 participants were enrolled and divided into the MetS group (23.1%) or no MetS group (76.9%) according to the International Diabetes Federation (IDF) diagnostic criteria. After applying weighted data, the baseline characteristics of the population were described. Following the exclusion of medication influences, the final count was 31,304 participants. Receiver operating characteristic curve analysis revealed that while distinguishing between MetS and no MetS, the TyG index had an area under the curve (AUC) of 0.827 (sensitivity = 71.9%, specificity = 80.5%), and the cutoff was 8.75, slightly outperforming HOMA-IR (AUC = 0.784) and HOMA-ß (AUC = 0.614) with a significance of P < 0.01. The prevalence of MetS in the total population calculated using the TyG index cutoff value was 30.9%, which was higher than that reported in the IDF diagnostic criteria. Weighted data analysis using univariate and multivariate logistic regression displayed an independent association between elevated TyG and HOMA-IR with the risk of MetS. Subgroup analysis further revealed differences in the predictive ability of the TyG index among adult populations across various genders and ethnicities, whereas such differences were not observed for children and adolescents. The TyG index is slightly better than HOMA in predicting MetS and may identify more patients with MetS; thus, its applications in a clinical setting can be appropriately increased.

Metabolic score for insulin resistance (METS-IR) predicts all-cause and cardiovascular mortality in the general population: evidence from NHANES 2001-2018.

BACKGROUND: The prevalence of obesity-associated insulin resistance (IR) is increasing along with the increase in obesity rates. In this study, we compared the predictive utility of four alternative indexes of IR [triglyceride glucose index (TyG index), metabolic score for insulin resistance (METS-IR), the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio and homeostatic model assessment of insulin resistance (HOMA-IR)] for all-cause mortality and cardiovascular mortality in the general population based on key variables screened by the Boruta algorithm. The aim was to find the best replacement index of IR. METHODS: In this study, 14,653 participants were screened from the National Health and Nutrition Examination Survey (2001-2018). And TyG index, METS-IR, TG/HDL-C and HOMA-IR were calculated separately for each participant according to the given formula. The predictive values of IR replacement indexes for all-cause mortality and cardiovascular mortality in the general population were assessed. RESULTS: Over a median follow-up period of 116 months, a total of 2085 (10.23%) all-cause deaths and 549 (2.61%) cardiovascular disease (CVD) related deaths were recorded. Multivariate Cox regression and restricted cubic splines analysis showed that among the four indexes, only METS-IR was significantly associated with both all-cause and CVD mortality, and both showed non-linear associations with an approximate "U-shape". Specifically, baseline METS-IR lower than the inflection point (41.33) was negatively associated with mortality [hazard ratio (HR) 0.972, 95% CI 0.950-0.997 for all-cause mortality]. In contrast, baseline METS-IR higher than the inflection point (41.33) was positively associated with mortality (HR 1.019, 95% CI 1.011-1.026 for all-cause mortality and HR 1.028, 95% CI 1.014-1.043 for CVD mortality). We further stratified the METS-IR and showed that significant associations between METS-IR levels and all-cause and cardiovascular mortality were predominantly present in the nonelderly population aged < 65 years. CONCLUSIONS: In conjunction with the results of the Boruta algorithm, METS-IR demonstrated a more significant association with all-cause and cardiovascular mortality in the U.S. population compared to the other three alternative IR indexes (TyG index, TG/HDL-C and HOMA-IR), particularly evident in individuals under 65 years old.

The predictive capability of several anthropometric indices for identifying the risk of metabolic syndrome and its components among industrial workers.

Metabolic syndrome (MetS) is closely associated with adverse cardiometabolic outcomes. The objective of this study was to identify practical methods that could enable the effective identification of MetS based on anthropometric indices. The basis of our study involved retrospective database obtained from routine medical prophylactic examinations. This was a cross-sectional study on the health status of male workers employed in hazardous working conditions at industrial enterprises in the Ural region conducted in 2019. A total of 347 male workers employed under hazardous working conditions were investigated. The presence of MetS was established by a healthcare professional in accordance with the guidelines of the International Diabetes Federation (IDF). Simple linear regression was used to evaluate the associations between anthropometric indices and MetS incidence. Logistic regression was used to determine the odds ratios of MetS in relation to increases in anthropometric indices. ROC curves were calculated to compare the ability of each anthropometric index to predict MetS and to determine the diagnostic thresholds of the indicators considered. According to the IDF criteria, 36.3% of the workers had MetS. A direct relationship was found between the individual components of MetS and the anthropometric indices studied. The highest OR was shown by the Body Roundness Index (BRI) of 2.235 (95% CI 1.796-2.781). For different age quartiles, the optimal cut-off values for predicting MetS were as follows: BRI, 4.1-4.4 r.u.; body shape index (ABSI), 0.080-0.083 m11/6 kg-2/3; and lipid accumulation product (LAP), 49.7-70.5 cm mmol/l. The most significant associations with MetS were observed where the values were greater than these cut-off points (Se = 97.4%). The results of this study demonstrated the rapid use of new anthropometric indicators, which have shown good predictive ability and are quite easy to use.

The discriminative ability of the triglyceride-glucose index to identify metabolic syndrome among adults of the northern Sri Lankan population.

BACKGROUND: The triglyceride-glucose index (TyG index) is a simple surrogate marker for Insulin Resistance (IR). However, the relationship between the TyG index and Metabolic Syndrome (MetS) remains unknown in the Northern Sri Lankan population. METHODS: This was a descriptive, cross-sectional study of adults aged between 18 and 65 years living in Jaffna, Sri Lanka. This study aimed to verify the discriminative ability of the TyG index to identify MetS using the International Diabetes Federation (IDF-2006) criteria and to determine the gender-specific TyG index cut-off values for better prediction of MetS in Northern Sri Lankan adults. TyG index was calculated as Ln[Triglycerides (TG) (mg/dl) × Fasting plasma glucose (FPG) (mg/dl)/2]. RESULTS: A total of 540 individuals were included in this study, with a mean age of 42.18 (± 13.89) years for males and 43.80 (± 12.56) years for females. The mean value of the TyG index in the total study population was 8.54 (± 0.53). Individuals in the higher quartiles of the TyG index had a significantly increased risk of MetS compared with those in the lowest quartile (p < 0.01). TyG index showed a stronger association with MetS than the FPG and all the conventional lipid components and the unadjusted odds ratio was 5.47. The area under the curve (AUC) of ROC revealed values of 0.914 (95% confidence interval (CI): 0.884, 0.944) for females, 0.881 (95% CI: 0.830, 0.932) for males and 0.897 (95% CI: 0.870, 0.924) for the total study population. TyG index had a stronger discriminative ability to identify MetS as per IDF criteria in the study population with a cut-off value of 8.60. The mean level of the TyG index significantly increased with the increasing number of MetS components. CONCLUSIONS: The mean value of the TyG index increased as the number of MetS components in the study population increased. Individuals with a higher TyG index had a significantly increased risk of having MetS compared with the lowest quartile of the TyG index. TyG index had a good discriminative ability to diagnose MetS as per IDF criteria among the northern Sri Lankan population.

Correlation of anthropometric measurements with body mass index and estimation of the proportion of metabolic syndrome among overweight and obese children: a hospital-based cross-sectional study.

BACKGROUND: Early identification of overweight and obesity with the help of simple anthropometric tests can prevent from development of metabolic complications in these children. Body mass index (BMI) is the most commonly used parameter but, measurements such as waist circumference (WC), waist-to-height ratio (WHtR) and wrist circumference (WrC) have also been studied and found to have a better correlation with visceral fat. OBJECTIVE: To correlate WC, WHtR and WrC with BMI among overweight and obese children. The secondary objective was to estimate the proportion of metabolic syndrome among obese and overweight children. METHODS: A single-centre, cross-sectional study involving 80 overweight and obese children aged 3-15 years. Anthropometric measures such as WC, WHtR and WrC of the study subjects were correlated with BMI and investigated for metabolic syndrome. RESULTS: Statistically significant and moderate positive correlation was found between BMI and WC, r (80)=0.45 and p<0.001 with WC explaining 20% of the variation of BMI. There was a statistically significant, moderate positive correlation between WHtR and BMI r (80)=0.34 and p<0.001 with 11% of the variation in BMI. There was a statistically significant strong positive correlation between WC and WrC (80)=0.61 and p<0.001, and WrC explains 37.2% of the variation in WC. However, there was no statistically significant correlation between BMI and WrC. Metabolic syndrome was found in 13 (16.25%) children. CONCLUSION: Alternative anthropometric measurements such as WC and WHtR have a significant correlation with BMI and may be of help in defining overweight and obesity in children. There was a statistically significant strong positive correlation between WC and WrC among obese children. Metabolic syndrome is common in these children.

Diagnosis of metabolic syndrome in nursing professionals: An accuracy study.

Metabolic Syndrome (MetS) represents a group of cardiovascular risk factors. This article aims to evaluate the accuracy of the tools of MetS diagnosis in Nursing professionals from Primary Health Care (PHC) in Bahia, Brazil. A cross-sectional study with a random sample selected according to essential health information for the diagnostic of MetS. For MetS diagnostic, we used EGIR, NCEP-ATPIII, AACE, IDF, Barbosa et al. (2006), and IDF/AHA/NHLBI (defined as gold standard) definition. Sensitivity, specificity, predictive values, and likelihood ratio were estimated for each diagnostic tool and compared with the gold standard. Kappa statistic was used to determine the agreement between the diagnostic methods. One thousand one hundred and eleven nursing professionals were included in this study. Sensitivity varied from 15% to 95.1%, and specificity varied between 99.5% and 100%. IDF and Barbosa et al. (2006) definitions were more sensitive (95.1% and 92.8%, respectively), and EGIR, NCEP, ATP III, and IDF showed 100% specificity. IDF and Barbosa et al. (2006) use suitable metabolic syndrome identification and confirmation criteria. The highest agreement was found in the definition of the IDF, Barbosa et al. (2006) and the NCEP ATP III. Defining metabolic syndrome with a higher diagnostic accuracy could contribute to the screening and the early identification of nursing professionals with cardiovascular disease risk factors, which provide opportunities for appropriate prevention and treatment.

Estimated pulse wave velocity as a forefront indicator of developing metabolic syndrome in Korean adults.

BACKGROUND/AIMS: The predictive value of the estimated pulse wave velocity (ePWV) for the development of metabolic syndrome has not yet been extensively explored. This study aimed to fill this gap by evaluating ePWV as a potential predictor of metabolic syndrome development in middle-aged Korean adults. METHODS: Using prospective data obtained from the Ansan-Ansung cohort database, participants without metabolic syndrome at baseline were studied. ePWV was calculated using specific equations based on age and blood pressure. The primary outcome was the incidence of metabolic syndrome during a median follow-up period of 187 months. RESULTS: Among the 6,186 participants, 2,726 (44.1%) developed metabolic syndrome during the follow-up period. ePWV methvalues were categorized into tertiles to assess their predictive value for the development of metabolic syndrome. An ePWV cut-off of 7.407 m/s was identified as a predictor of metabolic syndrome development, with a sensitivity of 0.743 and a specificity of 0.464. Participants exceeding this cut-off, especially those in the third tertile (8.77-14.63 m/s), had a notably higher risk of developing metabolic syndrome. Specifically, the third tertile exhibited a 52.8% cumulative incidence compared with 30.8% in the first tertile. After adjustments, those in the third tertile faced a 1.530-fold increased risk of metabolic syndrome (95% confidence interval, 1.330-1.761). CONCLUSION: ePWV is a significant predictor of the development of metabolic syndrome. This finding underscores the potential of ePWV as a cardiometabolic risk assessment tool and can thus provide useful information for primary prevention strategies.

Gender-specific accuracy of lipid accumulation product index for the screening of metabolic syndrome in general adults: a meta-analysis and comparative analysis with other adiposity indicators.

BACKGROUND: Lipid accumulation product (LAP) is a novel predictor index of central lipid accumulation associated with metabolic and cardiovascular diseases. This study aims to investigate the accuracy of LAP for the screening of metabolic syndrome (MetS) in general adult males and females and its comparison with other lipid-related indicators. METHODS: A systematic literature search was conducted in PubMed, Scopus, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and ProQuest for eligible studies up to May 8, 2024. Outcomes were pooled mean difference (MD), odds ratio (OR), and diagnostic accuracy parameters (sensitivity, specificity, and area under the summary receiver operating characteristic [AUSROC] curve). Comparative analysis was conducted using Z-test. RESULTS: Forty-three studies involving 202,313 participants (98,164 males and 104,149 females) were included. Pooled MD analysis showed that LAP was 45.92 (P < 0.001) and 41.70 units (P < 0.001) higher in men and women with MetS, respectively. LAP was also significantly associated with MetS, with pooled ORs of 1.07 (P < 0.001) in men and 1.08 (P < 0.001) in women. In men, LAP could detect MetS with a pooled sensitivity of 85% (95% CI: 82%-87%), specificity of 81% (95% CI: 80%-83%), and AUSROC curve of 0.88 (95% CI: 0.85-0.90), while in women, LAP had a sensitivity of 83% (95% CI: 80%-86%), specificity of 80% (95% CI: 78%-82%), and AUSROC curve of 0.88 (95% CI: 0.85-0.91). LAP had a significantly higher AUSROC curve (P < 0.05) for detecting MetS compared to body mass index (BMI), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), body roundness index (BRI), a body shape index (ABSI), body adiposity index (BAI), conicity index (CI) in both genders, and waist circumference (WC) and abdominal volume index (AVI) in females. CONCLUSION: LAP may serve as a simple, cost-effective, and more accurate screening tool for MetS in general adult male and female populations.

Presence of metabolic syndrome markers in very low birth weight ex-premature infants during early adolescence.

OBJECTIVES: To investigate the association of growth patterns with overweight/obesity and markers of metabolic syndrome in ex-premature adolescents; to assess the relationship between the increase (1 SD) in Z-score weight at term and at 2 years with outcomes in adolescents with or without intrauterine growth restriction; and to evaluate the association between the Cook criteria and overweight/obesity according to body mass index. METHODS: Cohort, retrospective, analytical study. Population: adolescents born weighting<1,500 g. RESULTS: One hundred twenty-seven adolescents (11.3 years) were included. There is an association between the 1 SD increase in the percentile (Pc) of weight at 40 weeks and at 2 years in the population with adequate birth weight (PCA) with insulin levels, resistance, and sensitivity at 11 years. Catch-up at 2 years was associated with significantly higher proportion of HDL value<41 (18.75 vs. 5.36 %) OR 4.08 95% CI (1.04-16.05) p=0.031. Overweight/obesity was associated with waist circumference index>0.5, HDL<41, and with blood pressure greater than Pc 90 for sex and height. CONCLUSIONS: In preterm infants, a 1 SD increase in weight Z score at 40 weeks and 2 years was predictive of metabolic and cardiovascular disorders in adolescence.

The role of small dense LDL-C/large buoyant LDL-C ratio as an independent risk factor in patients with type 2 diabetes mellitus and metabolic syndrome

Dyslipidemia plays a key role in metabolic syndrome (MS), intricately linked to type 2 diabetes mellitus (T2DM). This study aimed to investigate the differences in low-density lipoprotein cholesterol (LDL-C) subfraction levels between T2DM and T2DM with MS, and identify the risk factors associated with the disease. A total of 246 individuals diagnosed with T2DM, including 144 T2DM patients with MS, and 147 healthy subjects were recruited. All participants underwent a comprehensive clinical evaluation. Lipoprotein subfraction analysis was performed using the Lipoprint LDL system. Multivariate logistic regression analysis revealed that several lipid markers, including triglyceride (TG), LDL-C, large buoyant LDL-C (lbLDL-C), small dense LDL-C (sdLDL-C), LDLC2-5, and sdLDL-C/lbLDL-C ratio, were identified as independent risk factors for T2DM. Additionally, TG, sdLDL-C, LDLC-4, LDLC-5, and sdLDL-C/lbLDL-C ratio were found to be independent risk factors for T2DM with MS. Furthermore, the results of the receiver operating characteristic (ROC) curves demonstrated that sdLDL-C, LDLC-4, LDLC-3, and sdLDL-C/lbLDL-C ratio exhibited excellent predictive performance for the risk of T2DM (AUC > 0.9). The sdLDL-C/lbLDL-C ratio emerges as a shared independent risk factor for T2DM and MS complications. Furthermore, sdLDL-C/lbLDL-C ratio, along with LDL-4 and LDL-3, exhibits noteworthy predictive capabilities for T2DM.

A Study of Prevalence of Renal Function Abnormalities and Their Association with the Individual Components of Metabolic Syndrome.

INTRODUCTION: Metabolic syndrome (MetS) is one of the most important emerging pandemics of the 21st century and is associated with renal dysfunction in a significant number of subjects, the association of which is shown to be of greater significance in the South Asian population. AIMS AND OBJECTIVES: The prevalence of renal dysfunction in patients with MetS is the primary outcome. The secondary outcome is to assess the strength and significance of the association between the individual components of MetS and the presence of renal dysfunction. MATERIALS AND METHODS: This is a hospital-based cross-sectional observational study conducted for 2 years in a tertiary care hospital in India. A total of 100 diagnosed subjects of MetS were taken as cases and underwent relevant blood tests. Data were collected and analyzed in a Statistical Package for the Social Sciences (SPSS) v29 sheet. RESULTS: Over a period of 18 months, 100 subjects with MetS were documented, among which 66% had albuminuria, with microalbuminuria being 24% and the rest being macroalbuminuria. Among the same subjects, 30% had an estimated glomerular filtration rate (eGFR) <60 mL/minute/1.73m2. Waist circumference (WC) [measured by the National Institutes of Health (NIH) protocol] had the strongest association with increased albuminuria (r = 0.540; p-value < 0.001) as well as reduced eGFR (r = 0.460; p-value < 0.001). CONCLUSION: All the components of MetS, for example, increased WC, hypertension, increased fasting glucose, raised triglyceride (TG), and low high-density lipoprotein (HDL), have statistically significant correlations with increased urine albumin-to-creatinine ratio (ACR) and decreased eGFR, signifying glomerular injury and renal dysfunction, respectively.

Evolution of Metabolic Syndrome in Newly Diagnosed Type 2 Diabetes Mellitus Asian-Indian Patients Over the Last 15 Years using Adult Treatment Panel III of the National Cholesterol Education Program, World Health Organization, and International Diabetes Federation Criterion.

AIM: A retrospective observational study was undertaken to assess the changing trends in the incidence of metabolic syndrome (MetS) in Asian-Indian patients with newly diagnosed type 2 diabetes (T2D) using Adult Treatment Panel III of the National Cholesterol Education Program (NCEP-ATP III), World Health Organization (WHO), and the International Diabetes Federation (IDF) criteria. The overall and gender-wise pattern of MetS and its components were also evaluated. MATERIALS AND METHODS: Newly diagnosed T2D patients (n = 10,950)visiting Dr Panikar's Diabetes Care Centre from 2004 to 2019 with retrievable electronic medical records were selected. The incidence of MetS in these patients was studied using NCEP-ATP III, WHO, and IDF criteria in three separate timelines, namely, group I (2004-2008), group II (2009-2013), and group III (2014-2019). Overall and gender-wise, the incidence of various components of the MetS was also studied and compared across the three groups. All data were analyzed by using the Statistical Software Statistical Package for the Social Sciences (SPSS) version 10.0. Continuous variables were summarized by the number of observations (mean, standard deviation or median with minimum and maximum) and categorical values (calculating frequencies with percentages). Chi-square was used to estimate the incidence of MetS using different criteria and gender-wise patterns of the MetS components for the three periods. Other variables, such as mean body mass index (BMI), were assessed by applying variance analysis (ANOVA test). All values were reported based on a two-sided ANOVA test, and all the statistical tests were interpreted at a 5% level of significance. RESULTS: In the current study, the overall incidence of MetS observed among the study population was 80.9, 65.4, and 69.8% using NCEP-ATP III, WHO, and IDF criteria, respectively. The incidence of MetS across the three timelines (i.e., from 2004 to 2019) with all the diagnostic criteria showed a steady increase. An analysis of the individual components of MetS revealed a high incidence of central obesity across all subgroups, followed by hypertension and dyslipidemia. Central obesity was prevalent in nearly 85.9% of patients in 2014-2019 vs 78.6% in the 2004-2008 subgroup. Similarly, the incidence of hypertension and overall dyslipidemia [i.e., high triglycerides (TGs) and low high-density lipoprotein-cholesterol (HDL-C)] was 77.8% and 68.2% in the former vs 67.9% and 59.6% in the latter, respectively. The incidence of all three MetS components, along with fasting sugar, showed a statistically significant and progressive increase over the years, with prevalence in group III (2014-2019) being the highest. Women were found to be more centrally obese and more dyslipidemic compared to men, whereas men were found to be more hypertensive. CONCLUSION: The study shows a high incidence of MetS in Asian-Indian patients with newly diagnosed T2D. The incidence of MetS was significantly higher with the NCEP-ATP III diagnostic criteria than with WHO and IDF criteria. A steady rise in the incidence of MetS was observed over the study period of 2004-2019. Among the components of MetS, the incidence of central obesity, elevated TG levels, and low HDL-C were found to be higher in the female population than in males, whereas the incidence of hypertension was higher in males. Stringent lifestyle measures, along with appropriate pharmacological management, might help mitigate the risks associated with MetS.

Assessment of the appropriate cutoff points for anthropometric indices and their relationship with cardio-metabolic indices to predict the risk of metabolic associated fatty liver disease.

BACKGROUND: Research on Metabolic Associated Fatty Liver Disease (MAFLD) is still in its early stages, with few studies available to identify and predict effective indicators of this disease. On the other hand, early diagnosis and intervention are crucial to reduce the burden of MAFLD. Therefore, the aim of this research was to investigate the effectiveness of eleven anthropometric indices and their appropriate cut-off values as a non-invasive method to predict and diagnose MAFLD in the Iranian population. METHODS: In this cross-sectional study, we analyzed baseline data from the Hoveyzeh Cohort Study, a prospective population-based study conducted in Iran that enrolled a total of 7836 subjects aged 35 to 70 years from May 2016 through August 2018. RESULTS: The optimal cut-off values of anthropometric indices for predicting MAFLD risk were determined for waist circumference(WC) (102.25 cm for males and 101.45 cm for females), body mass index (BMI) (27.80 kg/m2 for males and 28.75 kg/m2 for females), waist-to-hip ratio (WHR) (0.96 for both males and females), waist-to-height ratio (WHtR) (0.56 for males and 0.63 for females), body adiposity index (BAI) (23.24 for males and 32.97 for females), visceral adiposity index (VAI) (1.64 for males and 1.88 for females), weight-adjusted waist index (WWI) (10.63 for males and 11.71 for females), conicity index (CI) (1.29 for males and 1.36 for females), body roundness index (BRI) (4.52 for males and 6.45 for females), relative fat mass (RFM) (28.18 for males and 44.91 for females) and abdominal volume index (AVI) (18.85 for males and for 21.37 females). VAI in males (sensitivity: 77%, specificity: 60%, Youden's Index: 0.37) and RFM in females (sensitivity: 76%, specificity: 59%, Youden's Index: 0.35) were found to have higher sensitivity and specificity compared to other anthropometric indices. Furthermore, anthropometric indices demonstrated statistically significant correlations with various hepatic and cardiometabolic indices. Among these, the strongest positive correlations were observed between WC, BMI, BAI, BRI, and AVI with the Hepatic Steatosis Index (HSI), TyG-BMI, and TyG-WC, as well as between VAI and the Atherogenic Index of Plasma (AIP), Lipid Accumulation Product (LAP), Cardiometabolic Index (CMI), and the Triglyceride and Glucose (TyG) Index. CONCLUSION: Anthropometric indices are effective in predicting MAFLD risk among Iranian adults, with WWI, VAI, and RFM identified as the strongest predictors. The proposed cutoff values could serve as a straightforward and non-invasive methods for the early diagnosis of MAFLD.

Metabolic syndrome parameters' variability and stroke incidence in hypertensive patients: evidence from a functional community cohort.

BACKGROUND: Stroke is a common complication of hypertension, but the predictive value of metabolic syndrome parameters' variability on stroke risk in individuals with hypertension remains unclear. Therefore, our objective was to investigate the relationship between metabolic syndrome parameters' variability and the risk of total stroke and its subtypes in hypertensive patients. METHODS: This prospective cohort study included 17,789 individuals with hypertension from the Kailuan study since 2006. Metabolic syndrome parameters, including waist circumference (WC), fasting blood glucose (FBG), systolic blood pressure (SBP), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG), were collected at three follow-up visits in the 2006, 2008, and 2010 surveys. We assess the variability utilizing the coefficient of variation (CV), standard deviation (SD), average real variation (ARV), and variability independent of the mean (VIM), with CV initially assessed. Participants were categorized based on the number of high-variability metabolic syndrome parameters (0, 1, 2, ≥ 3). Stroke cases were identified by reviewing medical records. The associations between variability in metabolic syndrome parameters and the risk of total stroke and its subtypes were analyzed using Cox proportional hazard regression models. RESULTS: During a median follow-up of 9.32 years, 1223 cases of stroke were recorded. Participants with ≥ 3 high-variability metabolic syndrome parameters had an increased risk of total stroke (HR: 1.29, 95%CI 1.09-1.52), as well as an increased risk of ischemic stroke (HR: 1.31, 95%CI 1.05-1.63) compared to those without high-variability parameters. The study also examined variability in each metabolic syndrome parameter, and significant associations with an increased risk of total stroke were observed for variability in SBP (HR: 1.24, 95%CI 1.05-1.46) and HDL-C (HR: 1.34, 95%CI 1.09-1.64). CONCLUSIONS: Long-term fluctuations in metabolic syndrome parameters significantly increase the risk of total stroke, especially ischemic stroke. Maintaining low variability in metabolic syndrome parameters could benefit health, and hypertensive individuals must be regularly monitored.

Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening.

Infrared spectroscopy is a powerful technique for probing the molecular profiles of complex biofluids, offering a promising avenue for high-throughput in vitro diagnostics. While several studies showcased its potential in detecting health conditions, a large-scale analysis of a naturally heterogeneous potential patient population has not been attempted. Using a population-based cohort, here we analyze 5,184 blood plasma samples from 3,169 individuals using Fourier transform infrared (FTIR) spectroscopy. Applying a multi-task classification to distinguish between dyslipidemia, hypertension, prediabetes, type 2 diabetes, and healthy states, we find that the approach can accurately single out healthy individuals and characterize chronic multimorbid states. We further identify the capacity to forecast the development of metabolic syndrome years in advance of onset. Dataset-independent testing confirms the robustness of infrared signatures against variations in sample handling, storage time, and measurement regimes. This study provides the framework that establishes infrared molecular fingerprinting as an efficient modality for populational health diagnostics.