Prevalence and relationship between metabolic syndrome and risk of cardiovascular disease: Evidence from two population-based studies

Aggregation of type-2 diabetes, prediabetes, and metabolic syndrome in German couples

We aimed to examine the concordance of type-2 diabetes, prediabetes and the metabolic syndrome in couples. In cross-sectional analyses, we used data from 1173 couples with index persons from the Heinz Nixdorf Recall Study (2011-2015), a population-based cohort study in Western Germany, and partners from the associated Heinz Nixdorf Multigeneration Study (2013-2016). Mean age (standard deviation) was 67.2 (6.6) years in index persons, and 67.8 (7.7) years in partners. The exposure was the presence of diabetes, prediabetes or metabolic syndrome in index persons, the outcome was the presence of the same health status in partners. Diabetes was defined by either self-reported diagnosis, intake of antidiabetic drugs or insulin, or HbA1c ≥ 6.5%. If the index person had prediabetes or diabetes, the partner was 1.46 (95% CI 1.07-2.00) times more likely to have diabetes than partners of index persons without the condition in the crude model (adjusted model: 1.33 (0.97-1.83)). For self-reported diabetes and for the metabolic syndrome, the corresponding prevalence ratios were 1.33 (0.90-1.97) and 1.17 (1.03-1.32), respectively (adjusted models: 1.23 (0.77-1.94), 1.04 (0.91-1.18)). In German couples, there was weak to moderate concordance of type-2 diabetes, prediabetes and the metabolic syndrome in crude, but poor concordance in adjusted models.

Exercise-induced effects on asprosin and indices of atherogenicity and insulin resistance in males with metabolic syndrome: a randomized controlled trial

Metabolic syndrome (MetS) development is associated with insulin resistance and obesity, with the progression of visceral adipose tissue playing a crucial role. Excessive adipose tissue is accompanied by an increase in the asprosin (ASP), which is responsible for carbohydrate metabolism and the regulation of hunger and satiety. Exercise affects the release of ASP, which may regulate metabolism accordingly. Due to the inconclusive results of the effect of exercise on ASP concentration in men with MetS, 12-week interventions were carried out in the following groups: EG1-aerobic training (n = 21, age: 34.21 ± 6.06, WC; waist circumference: 114.7 ± 10.93) and EG2-a combination of aerobic and resistance training (n = 21, age: 37.37 ± 7.08, WC: 114.8 ± 11.64) and compared with a control group (CG) of men with MetS without any intervention (n = 20, age: 38.26 ± 7.43, WC: 115.3 ± 10.54). Body composition, indicators of carbohydrate-lipid metabolism, and ASP were assessed four times: before the intervention, at 6 and 12 weeks of training, and 4 weeks after the training sessions. A comparison of the intervention influence on changes in the analyzed variables between the groups was performed using ANOVA test for dependent groups with post-hoc comparison. The effect size (ES) was also assessed using squared eta (η2). The implementation of aerobic training resulted in a decrease in ASP concentration (p = 0.03) within 6 weeks of the intervention, while in the CG a gradual increase in ASP was confirmed (p < 0.001). Aerobic-resistance training did not induce significant changes in ASP concentration but resulted in an increase in fat-free mass/fat mass (FFM/FM) ratio (p < 0.001), and a decrease (p = 0.04) in Homeostasis Model Assessment of Insulin Resistance (HOMA-IR). Changes in the visceral adipose tissue level indicate a gradual decrease in both the EG1 (p = 0.01) and EG2 (p = 0.04) groups. Both aerobic and aerobic-resistance exercises may have a regulatory effect, mainly by reducing visceral adipose tissue, on the improvement of metabolic disorders.

Cardiovascular disease risk stratification in the Pakistani population with and without metabolic syndrome: A single centre cross-sectional study

Existing atherosclerotic cardiovascular disease (ASCVD) risk stratification algorithms are predominantly validated only for Western populations, and do not include parameters of metabolic syndrome (MetS) which may increase the relative risk for cardiovascular disease in South Asians. This study aimed to compare the differences between 10-year ASCVD risk by the Framingham Risk Score (FRS), Pooled Cohort Risk Equations (PCE), and QRISK3 calculators in a cohort of apparently healthy Pakistani adults and stratify the ASCVD risk by MetS status.A cross-sectional study recruited 179 subjects between the ages of 40 to 74 years from the outpatient department of the Aga Khan University Hospital between May 2019 to November 2022. Anthropometry, demography, and blood samples were collected from each subject after informed consent. The IDF criteria were used to categorize subjects as MetS positive (n = 122) and MetS negative (n = 57). The mean age of study participants was 51.07±7.38 years. The average 10-year ASCVD risk (%) for our cohort was calculated to be 15.34 ± 11.60, 9.66 ± 10.87, and 17.02 ± 14.66 using the FRS algorithm, PCE calculator, and QRISK3 calculator respectively. MetS status did not show a statistically significant association with the risk categories determined by any of the calculators, although numerical ASCVD risk estimates were significantly higher in the MetS positive group for all calculators.Although ASCVD risk is a useful way to reduce CVD burden by identifying asymptomatic individuals at the highest risk of developing ASCVD, a high proportion of individuals with MetS may still be identified as low risk by the current risk stratification algorithms in South Asians. Powered validation studies with larger sample sizes and longitudinal follow-up are needed in South Asians to modify existing calculators to make them more applicable to South Asian populations.

Gender differences in metabolic syndrome and its components in southern china using a healthy lifestyle index: a cross-sectional study

BACKGROUND

Lifestyle changes are important for the prevention and management of metabolic syndrome (MetS), but studies that focus on gender differences in the lifestyle risk factors of MetS are limited in China. This research aimed to generate a healthy lifestyle index (HLI) to assess the behavioral risk factors of MetS and its components, and to explore the gender differences in HLI score and other influencing factors of MetS.

METHODS

A convenience sample of 532 outpatients were recruited from a general hospital in Changsha, China. The general information and HLI scores [including physical activity (PA), diet, smoking, alcohol use, and body mass index (BMI)] of the subjects were collected through questionnaires, and each patient's height, weight, waist circumference, and other physical signs were measured. Logistic regression analysis was used to analyze the risk factors of MetS and its components.

RESULTS

The prevalence of MetS was 33.3% for the whole sample (46.3% in males and 23.3% in females). The risk of MetS increased with age, smoking, unhealthy diet, and BMI in males and with age and BMI in females. Our logistic regression analysis showed that lower HLI (male: OR = 0.838,95%CI = 0.757-0.929; female: OR = 0.752, 95%CI = 0.645-0.876) and older age (male: OR = 2.899, 95%CI = 1.446-5.812; female: OR = 4.430, 95%CI = 1.640-11.969) were independent risk factors of MetS, for both sexes.

CONCLUSION

Low levels of HLI and older ages were independent risk factors of MetS in both males and females. The association between aging and MetS risk was stronger in females, while the association between unhealthy lifestyles and MetS risk was stronger in males. Our findings reinforced the expected gender differences in MetS prevalence and its risk factors, which has implications for the future development of gender-specific MetS prevention and intervention programs.

Effects of sea buckthorn (Hippophae rhamnoides L.) on factors related to metabolic syndrome: A systematic review and meta-analysis of randomized controlled trial

The purpose of this meta-analysis is to explore whether the supplement of sea buckthorn affects the factors related to metabolic syndrome. The related RCTs from five databases were systematically searched and comprehensively random effects model was used to calculate SMD and 95% CI. The Cochrane deviation risk tool was used to evaluate the deviation risk. Fifteen studies were involved in the meta-analysis. First, sea buckthorn supplementation reduced triglycerides [-0.722 (-1.129, -0.316); p < .001], total cholesterol [-0.345 (-0.639, -0.051); p = .021], low density lipoprotein cholesterol [-0.396 (-0.755, -0.037); p = .031], and increased high density lipoprotein cholesterol [0.370 (0.056, 0.684); p = .021] in overall subjects. Second, subgroup analysis showed that sea buckthorn supplementation reduced lipids only in people with abnormal lipid metabolism. Third, sea buckthorn had no effect on blood sugar, blood pressure, and BMI of the overall subjects. Sea buckthorn may affect the lipid metabolism in circulation, but it cannot affect blood glucose, blood pressure, and BMI. These indicators are closely associated with metabolic syndrome. This study may contribute to the development and utilization of sea buckthorn, and may provide a new and safer way for the prevention and treatment of metabolic syndrome. The limitation of this study is high heterogeneity, even if subgroup analysis is used. However, more clinical studies are needed to determine the real effect of sea buckthorn on metabolic syndrome.

Can Fasting Curb the Metabolic Syndrome Epidemic?

Metabolic syndrome (MetS) represents a cluster of metabolic abnormalities that includes hypertension, central obesity, insulin resistance, and atherogenic dyslipidemia. Due to the high prevalence (around 1/3 of the world population) economic burden of MetS, there is a need for new dietary, lifestyle, and therapeutic options. Recently, fasting emerged as a dietary method proposed for controlling metabolic risk factors. Intermittent fasting (IF), or time-restricted feeding (TRF), describes an array of feeding patterns in which calorie intake is restricted to a specific time period. Hence, this review aimed to elucidate the latest data on MetS and explore the viability of simple management options, such as IF and TRF. Preclinical studies have shown how IF/TRF exerts beneficial effects on the gut microbiota, glucose and insulin metabolism, weight and visceral fat, and lipid metabolism. However, the results obtained from human studies are somewhat conflicting, as weight loss was achieved in all studies, whereas in some studies, there was no significant effect on insulin resistance, cholesterol/lipid metabolism, or blood pressure. Nevertheless, as only very few human studies were performed, there is a need for more randomized control trials on larger cohorts of patients with MetS to gather higher-yield evidence to clarify whether IF/TRF are suitable dietary patterns for this population.

Integrative Analysis of Multi-Omics and Genetic Approaches-A New Level in Atherosclerotic Cardiovascular Risk Prediction

Genetics and environmental and lifestyle factors deeply affect cardiovascular diseases, with atherosclerosis as the etiopathological factor (ACVD) and their early recognition can significantly contribute to an efficient prevention and treatment of the disease. Due to the vast number of these factors, only the novel "omic" approaches are surmised. In addition to genomics, which extended the effective therapeutic potential for complex and rarer diseases, the use of "omics" presents a step-forward that can be harnessed for more accurate ACVD prediction and risk assessment in larger populations. The analysis of these data by artificial intelligence (AI)/machine learning (ML) strategies makes is possible to decipher the large amount of data that derives from such techniques, in order to provide an unbiased assessment of pathophysiological correlations and to develop a better understanding of the molecular background of ACVD. The predictive models implementing data from these "omics", are based on consolidated AI best practices for classical ML and deep learning paradigms that employ methods (e.g., Integrative Network Fusion method, using an AI/ML supervised strategy and cross-validation) to validate the reproducibility of the results. Here, we highlight the proposed integrated approach for the prediction and diagnosis of ACVD with the presentation of the key elements of a joint scientific project of the University of Milan and the Almazov National Medical Research Centre.