Metabolic Syndrome Risk Factors Research Articles

Metabolic syndrome in children and adolescents

Background: Metabolic syndrome is a serious condition associated with multiple diseases. The prevalence of metabolic syndrome is increasing caused by an increase in obesity rates among children and adolescents.Current Concepts: Owing to the various definitions used, there is lack of consensus regarding the diagnostic criteria for metabolic syndrome in children and adolescents. Although the exact pathogenesis remains unclear, insulin resistance and subsequent inflammation are key mechanistic contributors. Metabolic syndrome is characterized by overweight and obesity accompanied by abnormalities in glucose metabolism, dyslipidemia, and hypertension and is associated with other conditions such as fatty liver, polycystic ovary syndrome, and a pro-inflammatory state. Prevention and management of metabolic syndrome can be achieved through lifestyle modifications, behavioral interventions, pharmacotherapy, and surgical interventions.Discussion and Conclusion: Childhood and adolescent obesity serves as a risk factor for metabolic syndrome during later life. Early identification and intervention are important to prevent the progression of metabolic syndrome. Clinicians must identify at-risk children and adolescents and provide guidance for the prevention and management of metabolic syndrome.

Metabolic Syndrome in people treated with Antipsychotics (RISKMet): A multimethod study protocol investigating genetic, behavioural, and environmental risk factors.

The RISKMet project aims to: (1) identify risk factors for metabolic syndrome (MetS) by comparing patients with and without MetS; (2) characterise patients treated with second-generation antipsychotics (SGAs) about MetS diagnosis; (3) study behavioural patterns, including physical activity (PA) and dietary habits, in patients and healthy individuals using a prospective cohort design. The RISKMet project investigates MetS in individuals treated with SGAs, focusing on both adult and paediatric populations. The study utilizes a case-control design to examine potential risk factors for MetS, categorizing participants as MetS+ considered as "Cases" and MetS- considered as "Controls" matched by sex and age. The evaluation of factors such as MetS, lifestyle habits, and environmental influences is conducted at two time points, T0 and T3, after 3 months. Subsequently, the project aims to assess body parameters, including physical examinations, and blood, and stool sample collection, to evaluate metabolic markers and the impact of SGAs. The analysis includes pharmacological treatment data and genetic variability. Behavioural markers related to lifestyle, eating behaviour, PA, and mood are assessed at both T0 and T3 using interviews, accelerometers, and a mobile app. The study aims to improve mental and physical well-being in SGA-treated individuals, establish a biobank for MetS research, build an evidence base for physical health programs, and develop preventive strategies for SGA-related comorbidities. This project innovates MetS monitoring in psychiatry by using intensive digital phenotyping, identifying biochemical markers, assessing familial risks, and including genetically similar healthy controls. ISRCTN18419418 at www.isrctn.com.

Unraveling the Complexities of Polycystic Ovarian Syndrome: A Comprehensive Review

Polycystic Ovarian Syndrome (PCOS) is a complex endocrine disorder affecting reproductive-age women, characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology. This comprehensive review delves into the multifaceted nature of PCOS, exploring its etiology, pathophysiology, clinical manifestations, diagnostic criteria, and management strategies. Key topics include the role of insulin resistance and hyperinsulinemia in PCOS pathogenesis, the impact of hormonal imbalances on menstrual irregularities and fertility, and the association of PCOS with metabolic syndrome and cardiovascular risk factors. Furthermore, the review discusses current diagnostic criteria and controversies surrounding PCOS diagnosis, as well as evidence-based approaches to treatment, encompassing lifestyle modifications, pharmacological interventions, and assisted reproductive technologies. By synthesizing current knowledge and emerging research findings, this review aims to provide a comprehensive overview of PCOS for clinicians, researchers, and individuals affected by this prevalent endocrine disorder.

A meta-analysis of the association between RBP4 rs3758539 genotype and metabolic syndrome factors.

To explore the link between the RBP4 rs3758539 genotype and metabolic syndrome risk factors and whether the impact of this genetic variation displays any potential race discrepancy. This meta-analysis followed the PRISMA guidelines and was registered with PROSPERO (registration no. CRD42023407999). PubMed, Web of Science, Embase, Cochrane Library, Google Scholar, Airiti Library and CINAHL databases were used for the study search until October 2023. We evaluated the methodological quality using the Joanna Briggs Institute checklist and determined the correlation using a random-effects meta-analysis. The results indicated that individuals with the rs3758539 GA/AA genotype had a higher risk profile, including lower high-density lipoprotein levels [correlation: -0.045, 95% confidence interval (CI): -0.080 to -0.009, p = .015, I2 = 46.9%] and higher body mass index (correlation: 0.117, 95% CI: 0.036-0.197, p = .005, I2 = 82.0%), body fat (correlation: 0.098, 95% CI: 0.004-0.191, p = .041, I2 = 64.0%), and low-density lipoprotein levels (correlation: 0.074, 95% CI: 0.010-0.139, p = .024, I2 = 0%), of developing metabolic syndrome than those with the GG genotype. The subgroup analysis maintained a significantly positive correlation between the rs3758539 GA/AA genotype and body mass index (correlation: 0.163, 95% CI: 0.031-0.289, p = .016, I2 = 88.9%) but a negative correlation with high-density lipoprotein levels (correlation: -0.047, 95% CI: -0.087 to -0.006, p = .025, I2 = 65.7%) in the Asian group only. The current meta-analysis supports a significant link between the RBP4 rs3758539 GA/AA genotype and the metabolic syndrome.

Analyzing Longitudinal Health Screening Data with Feature Ensemble and Machine Learning Techniques: Investigating Diagnostic Risk Factors of Metabolic Syndrome for Chronic Kidney Disease Stages 3a to 3b.

Longitudinal data, while often limited, contain valuable insights into features impacting clinical outcomes. To predict the progression of chronic kidney disease (CKD) in patients with metabolic syndrome, particularly those transitioning from stage 3a to 3b, where data are scarce, utilizing feature ensemble techniques can be advantageous. It can effectively identify crucial risk factors, influencing CKD progression, thereby enhancing model performance. Machine learning (ML) methods have gained popularity due to their ability to perform feature selection and handle complex feature interactions more effectively than traditional approaches. However, different ML methods yield varying feature importance information. This study proposes a multiphase hybrid risk factor evaluation scheme to consider the diverse feature information generated by ML methods. The scheme incorporates variable ensemble rules (VERs) to combine feature importance information, thereby aiding in the identification of important features influencing CKD progression and supporting clinical decision making. In the proposed scheme, we employ six ML models-Lasso, RF, MARS, LightGBM, XGBoost, and CatBoost-each renowned for its distinct feature selection mechanisms and widespread usage in clinical studies. By implementing our proposed scheme, thirteen features affecting CKD progression are identified, and a promising AUC score of 0.883 can be achieved when constructing a model with them.

The relationship between heavy metals and metabolic syndrome using machine learning.

Exposure to high levels of heavy metals has been widely recognized as an important risk factor for metabolic syndrome (MetS). The main purpose of this study is to assess the associations between the level of heavy metal exposure and Mets using machine learning (ML) method. The data used in this study are from the national health and nutrition examination survey 2003-2018. According to the demographic information and heavy metal exposure level of participants, a total of 22 variables were included. Lasso was used to screen out the key variables, and 9 commonly used ML models were selected to establish the associations with the 5-fold cross validation method. Finally, we choose the SHapley Additive exPlanations (SHAP) method to explain the prediction results of Adaboost model. 11,667 eligible individuals were randomly divided into two groups to train and verify the prediction model. Through lasso, characteristic variables were selected from 24 variables as predictors. The AUC (area under curve) of the models selected in this study were all greater than 0.7, and AdaBoost was the best model. The AUC value of AdaBoost was 0.807, the accuracy was 0.720, and the sensitivity was 0.792. It is noteworthy that higher levels of cadmium, body mass index, cesium, being female, and increasing age were associated with an increased probability of MetS. Conversely, lower levels of cobalt and molybdenum were linked to a decrease in the estimated probability of MetS. Our study highlights the AdaBoost model proved to be highly effective, precise, and resilient in detecting a correlation between exposure to heavy metals and MetS. Through the use of interpretable methods, we identified cadmium, molybdenum, cobalt, cesium, uranium, and barium as prominent contributors within the predictive model.

New paradigms in the study of the cholinergic system and metabolic diseases: Acetyl-and-butyrylcholinesterase.

Acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) are enzymes that belong to the neuromuscular cholinergic system, their main function is to hydrolyze the neurotransmitter acetylcholine (ACh), through their hydrolysis these enzymes regulate the neuronal and neuromuscular cholinergic system. They have recently attracted considerable attention due to the discovery of new enzymatic and nonenzymatic functions. These discoveries have aroused the interest of numerous scientists, consolidating the relevance of this group of enzymes. Recent investigations have revealed a positive correlation between several risk factors for metabolic syndrome (MetS) and the expression of cholinesterases (ChE's), which underscore the impact of high ChE's activity on the pro-inflammatory state associated with MetS. In addition, the excessive hydrolysis of ACh and other choline esters (succinylcholine, propionylcholine, butyrylcholine, etc.) by both ChE's results in the overproduction of fatty acid precursor metabolites, which facilitate the synthesis of very low-density lipoproteins and triacylglycerols. Participation in these processes may represent the link between ChE's and metabolic disorders. However, further scientific research is required to fully elucidate the involvement of ChE's in metabolic diseases. This review aims to collect recent research studies that contribute to understanding the association between the cholinergic system and metabolic diseases.

Prevalence of cardiometabolic risk factors according to urbanization level, gender and age, in apparently healthy adults living in Gabon, Central Africa.

The prevalence of cardiometabolic risk factors (CMRFs) is increasing in sub-Saharan Africa and represents a serious public health issue. Accurate data are required to implement adapted prevention programs and healthcare strategies. Thus, the aim of this study was to estimate the prevalence rates of CMRFs according to the level of urbanization, age and gender in Gabon. A cross-sectional study was conducted in northern (Bitam), western coast (Libreville, Melen) and southeast (Koulamoutou) areas of Gabon using the World Health Organization's (WHO) stepwise approach for the surveillance of chronic disease risk factors. Participants over 18 years of age, without known underlying disease, living in rural and urban areas of Gabon were included. Sociodemographic, biological, and behavioral data were collected. Univariate and multivariate analysis were used to identify the CMRFs. Of the 978 participants, 499 lived in urban and 479 in rural areas. Their median age was 38[28-50] years. Tobacco (26.1% vs 6.2%; p < 0.01) and excessive alcohol consumption (19.4% vs 9.6%; p < 0.01) predominated in rural than in urban areas, respectively. Urban dwellers had more often insufficient physical activity than rural people (29.5% vs 16.3%; p < 0.01). In total, 79.9% of participants aged under 54 years had a high blood pressure;10.6% of the younger participants had pre-hypertension. Metabolic syndrome was more frequent in women (21.7%) than in men (10.0%) (p < 0.01); 6.4% of men and 2.5% of women had a high Framingham score (p = 0.03). Finally, 54.0% of the participants had three or four CMRFs. The multivariate analysis showed that men were more likely to be smokers and to be at risk of pre-hypertension or high blood pressure (p < 0.01). Women were more likely to be obese or to have a metabolic syndrome (p < 0.01). Living in urban areas was also a risk factor for hypertension, diabetes, metabolic syndrome and high LDL cholesterol level. The prevalence of CMRFs was high in the study population. Disparities were observed according to urban and rural areas, gender and age. National prevention and healthcare strategies for cardiometabolic diseases in Gabon should consider these observed differences.

Association between dental scaling and metabolic syndrome and lifestyle.

Periodontal disease is a risk factor for diabetes and metabolic syndrome, and non-surgical periodontal treatment has been shown to help maintain stable blood sugar in diabetic patients. Determining the level of preventive scaling in patients with metabolic syndrome will help manage the disease. The purpose of this study was to investigate the extent to which people with metabolic syndrome or bad lifestyle performed scaling and the association between preventive scaling and metabolic syndrome or lifestyle in a large population. This study was conducted on adults aged 20 years or older from January 2014 to December 2017 in the National Health Insurance System (NHIS) database. Among 558,067 people who underwent health checkups, 555,929 people were included. A total of 543,791 people were investigated for preventive scaling. Metabolic syndrome components were abdominal obesity, lower high density lipoprotein cholesterol (HDL)-C, high triglycerides, high blood pressure and hyperglycemia. Unhealthy lifestyle score was calculated by assigning 1 point each for current smokers, drinkers, and no performing regular exercise. When multiple logistic regression analysis was performed after adjusting for age, sex, income, body mass index (BMI), smoking, drinking and regular exercise, the Odds ratios (OR) and 95% confidence intervals (CI) of the group with 5 metabolic syndrome components were 0.741 (0.710, 0.773) (p<0.0001). After adjustment for age, sex, income, BMI, smoking, drinking, regular exercise, diabetes, hypertension and dyslipidemia, the OR (95% CI) of the group with unhealthy lifestyle score = 3 was 0.612 (0.586, 0.640) (p<0.0001). The more metabolic syndrome components, and the higher unhealthy lifestyle score, the less scaling was performed.

Cost-effectiveness of behavioural counselling intervention compared with non-intervention for adult patients with metabolic syndrome to prevent cardiovascular diseases and type 2 diabetes in Japan: a microsimulation modelling study

ObjectivesNationwide lifestyle intervention—specific health guidance (SHG) in Japan—employs counselling and education to change unhealthy behaviours that contribute to metabolic syndrome, especially obesity or abdominal obesity. We aimed to perform a...

Association between metabolic phenotypes of overweight/obesity and cardiovascular diseases in postmenopausal women

Background and aimObesity and metabolic abnormalities were associated with an increased risk of cardiovascular diseases. However, it is unclear how metabolic weight phenotypes relate to cardiovascular diseases in postmenopausal women. This study aimed to explore the relationships in postmenopausal women. Methods and resultsWe included 15,575 postmenopausal women aged 35–75 years (median age, 60.6) without cardiovascular disease at baseline from a subcohort of the China Patient-centered Evaluative Assessment of Cardiac Events Million Persons Project. Metabolically unhealthy phenotype was defined as having ≥2 risk factors of metabolic syndrome: blood pressure ≥130/85 mm Hg or current use of antihypertensive drugs, fasting glucose ≥5.6 mmol/L or current use of antidiabetic agents, triglycerides ≥1.7 mmol/L, and high-density lipoprotein cholesterol <1.3 mmol/L. Cox regression analysis was used to evaluate the risks of cardiovascular diseases. Over a median follow-up period of 3.55 (interquartile range, 2.59–4.44) years, a total of 1354 cardiovascular events occurred. Compared to metabolically healthy normal weight, the multivariate-adjusted hazard ratios and their 95% confidence intervals were 1.41 (1.16–1.72) for metabolically unhealthy normal weight, 1.42 (1.16–1.73) for metabolically healthy overweight/obesity, and 1.75 (1.48–2.08) for metabolically unhealthy overweight/obesity. Subdividing overweight/obesity into separate groups revealed higher total cardiovascular disease risk only in metabolically unhealthy individuals across body mass index categories. ConclusionIn postmenopausal women, both metabolically healthy overweight/obesity and metabolically unhealthy normal weight were associated with a higher risk of cardiovascular disease compared to metabolically healthy normal weight, and the greatest risk was observed in the metabolically unhealthy overweight/obesity category.

Dietary Habit and Physical Activity as Risk Factors of Metabolic Syndrome among Civil Servants in Jambi City

The prevalence of Metabolic Syndrome (MetS) is an important health problem due to the association with increased cardiovascular disease as the main cause of death. Approximately 20-25% of the global adult population including Indonesia suffers from MetS. The high prevalence is attributed to several factors namely lifestyle changes such as dietary habit and physical activity. Therefore, this study aimed to investigate the relationship between dietary habit and physical activity with MetS incidence among civil servant employees in Jambi City, Indonesia. A cross-sectional design was used to assess the proportion of MetS, dietary habit, and physical activity. A total of 108 civil servant employees were selected as respondents from six agencies using a multistage random sampling technique. Data collection was carried out through physical examination and interviews using a questionnaire. The results showed that the prevalence of MetS was 60.2%, with three risk indicators, namely central obesity (74.1%), blood pressure (66.7%), and HDL (63%). Based on the chi-square test, dietary habit (OR=2.571, 95%CI=1.151-5.744) and physical activity (OR=3.692, 95%CI=1.625-8.388) were significantly related to MetS. The persistently high prevalence of MetS was significantly related to dietary habit and physical activity among civil servant employees in Jambi City-Indonesia. These results underscored the need to improve understanding of healthy diets by adopting a balanced nutritional intake, increasing the intensity of physical activity according to age, and engaging in regular exercise.

Prevalence and risk factors of metabolic syndrome among female university students: A cross-sectional study

Metabolic syndrome (MetS) encompasses various metabolic abnormalities linked to type 2 diabetes and cardiovascular diseases. The study is aimed to assess the prevalence of Metabolic Syndrome (MetS) among female university students, by gathering anthropometric data including Body Mass Index (BMI), Waist Circumference (WC), and Blood Pressure (BP) and evaluating biochemical data including total Cholesterol (TC), Fasting Plasma Glucose (FPG), High-Density Lipoprotein (HDL), and Triglycerides. This study done at Legacy University Okija assessed MetS prevalence among female students, gathering anthropometric (BMI, waist circumference (WC), blood pressure (BP)) and biochemical data (total cholesterol (TC), fasting plasma glucose (FBS), HDL, triglycerides) after an 8-hour fast. The tests were done using standard laboratory procedures. One-way analysis of variance (ANOVA) was used to assess differences in BMI groups and MetS components. The results showed that 2(2.9%) students were underweight, 49(70%) had ideal body weight, 12(17.1%) were overweight and 7(10%) were obese. The prevalence of the risk factors were: 7.1% for obesity according to WC, 7.1 % (high) and 1.4%(very high) for systolic BP, 18% for diastolic BP, 48.6% for triglyceride, and 7.1%(pre-diabetic) and 1.4%(diabetic) for FPG. Low HDL-C was absent. The highest prevailing risk factor was triglyceride. The variables with statistical significance were WC(p&lt;0.05), FPG(p&lt;0.05), and diastolic BP(p&lt;0.05). Overall MetS prevalence was 1.4%. MetS is present, especially among the obese, but risk factors are also evident in other groups.

A Holistic Review of Rosacea and Its Association with Cardiovascular Diseases

Rosacea is a chronic inflammatory dermatological condition with different clinical phenotypes, usually diagnosed clinically and treated with systemic and topical medications. Rosacea is one of the skin conditions that is often believed to just have cutaneous manifestation, but it is actually a systemic condition that affects many different systems. The correlation between rosacea and a variety of comorbidities, including depression, gastrointestinal disorders, migraines, autoimmune conditions, and cardiovascular diseases (CVD) are noted in many different studies. There are numerous risk factors for CVD, including hypertension (HTN), diabetes mellitus (DM), metabolic syndrome (MS), and dyslipidemia. CVD has a high mortality rate and should not be overlooked. Rosacea patients must receive the appropriate education regarding the management of CVD risk factors in addition to rosacea. We thought it was important to conduct a literature review to investigate the association between rosacea and the risk factors associated with CVDs, since both conditions are chronic and involve the interaction of genetic and inflammatory factors. The purpose of this narrative review is to overview rosacea, draw attention to the cardiovascular risk that rosacea patients face, and alert dermatologists, cardiologists, and primary care physicians to the need for immediate risk factor treatment.

Factors predicted metabolic syndrome among health care workers exposed to coronavirus disease 2022 in Erbil, Iraq

Background and objective: There have been a recent concern about life style and stress exposure among health care workers during corona virus infection pandemic. This study aimed to investigate the lifestyle of the staff working in public hospitals in Erbil city during the years of 2021-2022. Methods: This is a survey involving data of the available hospital staff from 1st of January 2021 to 1st of April 2022. The hospital staff were including the reception staff, logistic staff, doctors and medical assistances working at the hospitals during the COVID-19 pandemic. In this study, 313 hospital staff are taken conveniently from the working hospitals. Demographic data and laboratory investigations were taken from all the participants. Results: During COVID19 metabolic syndrome was high among staffs. Females shown to have higher prevalence of metabolic syndrome (28.9%) than males (12%). Have a car (19.9%), living in rural area (21.7%) primary education (33.3%) have highest prevalence of metabolic syndrome. Furthermore, regarding the occupation of staffs, operation assistants have highest prevalence of metabolic syndrome (37.2%) followed by reception staff (28.6%) and pharmacists (25%). Association with male sex (p value&lt;0.001), marriage (p value=0.01) with metabolic syndrome was statistically significant. Conclusions: During COVID19 pandemic metabolic syndrome was common among staffs. Aging, sex, education, occupation, smoking, fatty diet, marriage, family history of diabetes and cardiac disease are the main risk factors for metabolic syndrome. People with these risk factors should be assessed for metabolic syndrome and educated about the risks and possible consequences in the future.

Arthritis prevalence is associated with metabolic syndrome risk factors but not with physical activity in middle-aged and older patients - a cross-sectional study

BackgroundIn light of the aging population, increasingly suffering from the metabolic syndrome (MS), strategies need to be developed to address global public health challenges known to be associated with MS such as arthritis. As physical activity (PA) may play a crucial role in tackling those challenges, this study aimed to determine the association between the number of MS risk factors, PA and arthritis in people ≥ 50 years old.MethodsData from the Survey of Health, Ageing, and Retirement in Europe (SHARE) were used to estimate the prevalence of arthritis and MS risk factors in the European population ≥ 50 years and to evaluate the associations between MS risk factors, PA and arthritis. Binary logistic regression was performed to calculate the odds ratio of different factors.Results73,125 participants were included in the analysis. 55.75% of patients stated at least one of the three MS risk factors. The prevalence of rheumatoid arthritis (RA) and osteoarthritis (OA)/other rheumatism among ≥ 50 years population was 10.19% and 19.32% respectively. Females showed a higher prevalence of arthritis than males. Prevalence did not differ between groups with different levels of PA. Arthritis prevalence was positively correlated with the number of MS risk factors (P < 0.01) but not with PA (P > 0.05).ConclusionMiddle-aged and older Europeans with multiple comorbidities suffered from RA, OA or other rheumatism more frequently than participants with fewer comorbidities, while the level of physical activity was not associated with the number of metabolic risk factors in patients with RA and OA/other rheumatism.

Non-alcoholic fatty liver disease and psoriasis: mechanisms of comorbidity and approaches to therapy

Psoriasis is a chronic immune-mediated skin disease of a multifactorial nature, characterized by accelerated proliferation of keratinocytes and impaired differentiation, an imbalance between pro-inflammatory and anti-inflammatory cytokines, with frequent involvement of the musculoskeletal system in the pathological process. The etiology of psoriasis is unknown, but several risk factors have been identified, including family history, smoking and obesity. The high prevalence of obesity, diseases of the cardiovascular system and digestive organs in patients with psoriasis allows us to consider it as an indicator of the patient’s metabolic disorders. In the structure of comorbidity of patients with psoriasis, special attention is drawn to non-alcoholic fatty liver disease (NAFLD), which occupies a leading position in the structure of the incidence of chronic diffuse liver diseases among the adult population in many countries of the world, including Russia. Patients with psoriasis are more often diagnosed with NAFLD, regardless of the presence of metabolic syndrome and other traditional risk factors. The presence of NAFLD is associated with more severe psoriasis and worse outcomes. On the other hand, a negative effect of psoriasis on the course of liver pathology has been noted. In this regard, it seems particularly relevant to study the etiological factors and pathogenetic links underlying this comorbidity, as potential targets for targeted therapy, which can improve the effectiveness of treatment for this cohort of patients. The purpose of this review publication is to summarize and systematize the available data on the prevalence of comorbidity of psoriasis and NAFLD in the population, the mechanisms of its formation and approaches to patient management.

Dysregulation of miR-335-5p in People with Obesity and its Predictive Value for Metabolic Syndrome.

The epidemic of obesity and metabolic syndrome has become the most serious global public health problem. The part played by microRNA (miRNA) in the onset and progression of obesity and metabolic syndrome has been increasingly focused upon. The goal of this study was to explore miR-335-5p as a potential predictive biomarker or therapeutic target for obesity and metabolic syndrome. The expression level of miR-335-5p was detected by qRT-PCR. The diagnostic value of miR-335-5p was evaluated by ROC curve. The association between serum miR-335-5p levels and various clinical parameters was assessed using the chi-square test. Logistic regression analysis was used to evaluate the risk factors of metabolic syndrome in obese population. The biological processes and molecular mechanisms are studied through GO and KEGG enrichment analysis. The ROC curve analysis revealed that miR-335-5p could serve as a predictive indicator for the development of obesity accompanied by metabolic syndrome. Logistic regression analysis revealed that BMI, TG, FBG, HOMA-IR, and miR-335-5p expression represent independent risk factors of metabolic syndrome occurrence. Chi-square test analysis revealed that patients with higher values of BMI, SBP, DBP, TG, FBG, and HOMA-IR exhibited a more significantly increased expression of miR-335-5p in their serum. In conclusion, miR-335-5p holds predictive and diagnostic value for obesity and metabolic syndrome and has potential to serve as a biomarker for these conditions.

Body mass index as a dominant risk factor for metabolic syndrome among indonesian adults: a 6-year prospective cohort study of non-communicable diseases

BackgroundNon-communicable diseases (NCDs), notably cardiovascular disease and type 2 diabetes mellitus, are largely driven by metabolic syndrome (MetS), a cluster of critical risk factors. Despite extensive research, the progression of MetS, especially in Indonesia, has received limited attention. This research tracks adult MetS risk dynamics in a populous Bogor District cohort, providing crucial insights into its evolving nature.MethodsThis prospective open cohort study analysed secondary data from the Special Research - Cohort Study of Non-Communicable Diseases by the Ministry of Health, Republic of Indonesia from 2011 to 2018. The final sample was 1,376 Indonesian adult participants, all residents of Bogor District. MetS outcome, dietary assessment, physical activity, and biomarkers were analysed every two consecutive years.ResultsThe risk of overweight and obese participants developing MetS was 2.4 and 4.4 times higher, respectively (95% CI: 1.176–3.320 and 3.345–5.740) than those with body mass index (BMI) in the normal range. Participants who reported less intentional physical exercise had a MetS risk 1.5 times higher (95% CI: 1.034–2.109) than those with more intentional physical exercise. The role of diet is also significant, evidenced by a 30% reduction in MetS risk for people with fat intakes in the 2nd quartile compared to the 1st quartile (95% CI: 0.505–0.972). Meanwhile, a carbohydrate intake in the 2nd quartile increased the risk of MetS 1.5 times (95% CI: 1.063–2.241) in comparison with the 1st quartile.ConclusionsNotably, participants with underweight BMI exhibited the highest cumulative survival of MetS, while those with obese BMI recorded the lowest cumulative survival. There is an urgent need for strategic interventions to enhance the existing early detection and NCD monitoring program. This involves a targeted focus on promoting a community-based healthy lifestyle in the Bogor District. The study emphasizes the importance of tailored public health measures to address specific risk factors identified in the local context, aiming to mitigate the prevalence and impact of MetS in the population.

Metabolic syndrome traits exhibit genotype-by-environment interaction in relation to socioeconomic status in the Mexican American family heart study.

Background: Socioeconomic Status (SES) is a potent environmental determinant of health. To our knowledge, no assessment of genotype-environment interaction has been conducted to consider the joint effects of socioeconomic status and genetics on risk for metabolic disease. We analyzed data from the Mexican American Family Studies (MAFS) to evaluate the hypothesis that genotype-by-environment interaction (GxE) is an essential determinant of variation in risk factors for metabolic syndrome (MS). Methods: We employed a maximum likelihood estimation of the decomposition of variance components to detect GxE interaction. After excluding individuals with diabetes and individuals on medication for diabetes, hypertension, or dyslipidemia, we analyzed 12 MS risk factors: fasting glucose (FG), fasting insulin (FI), 2-h glucose (2G), 2-h insulin (2I), body mass index (BMI), waist circumference (WC), leptin (LP), high-density lipoprotein-cholesterol (HDL-C), triglycerides (TG), total serum cholesterol (TSC), systolic blood pressure (SBP), and diastolic blood pressure (DBP). Our SES variable used a combined score of Duncan's socioeconomic index and education years. Heterogeneity in the additive genetic variance across the SES continuum and a departure from unity in the genetic correlation coefficient were taken as evidence of GxE interaction. Hypothesis tests were conducted using standard likelihood ratio tests. Results: We found evidence of GxE for fasting glucose, 2-h glucose, 2-h insulin, BMI, and triglycerides. The genetic effects underlying the insulin/glucose metabolism component of MS are upregulated at the lower end of the SES spectrum. We also determined that the household variance for systolic blood pressure decreased with increasing SES. Conclusion: These results show a significant change in the GxE interaction underlying the major components of MS in response to changes in socioeconomic status. Further mRNA sequencing studies will identify genes and canonical gene pathways to support our molecular-level hypotheses.