Risk Of MetS Research Articles

Identification of nutrition factors in the metabolic syndrome and its progression over time in older adults: analysis of the TUDA cohort

BackgroundNutrition is recognized as playing an important role in the metabolic syndrome (MetS), but the dietary components involved are unclear. We aimed to investigate nutrition factors in relation to MetS and its progression in older adults over a follow-up period of 5.4 years.MethodsCommunity-dwelling adults (≥ 60y) from the Trinity-Ulster-Department-of-Agriculture study, sampled at baseline (2008–12) and follow-up (2014–18; n 953), were classified as ‘with MetS’ by having three or more of: waist circumference (≥ 102 cm, males; ≥ 88 cm, females); HDL-cholesterol (< 1.0 mmol/L, males; < 1.3 mmol/L, females); triglycerides (≥ 1.7 mmol/L); blood pressure (systolic ≥ 130 and/or diastolic ≥ 85 mmHg); and hemoglobin A1c (≥ 39 mmol/mol).ResultsMetS was identified in 67% of participants, increasing to 74% at follow-up. Predictors at baseline for the development of metabolic syndrome (MetS) at follow-up were higher waist circumference (odds ratio [95%CI]; 1.06 [1.01–1.11]), but not BMI, and increased triglyceride concentrations (2.01 [1.29–3.16]). In dietary analysis (at follow-up), higher protein (g/kg bodyweight/day) and monounsaturated fatty acid (g/day) intakes were each associated with lower risk of MetS (0.06 [0.02–0.20] and 0.88 [0.78–1.00], respectively), whilst higher protein was also associated with lower abdominal obesity (0.10 [0.02–0.51]) and hypertension (0.22 [0.00–0.80]). Furthermore, participants with, compared to without, MetS consumed less high-quality protein foods (P = 0.006) and more low-quality protein foods (P < 0.001), as defined by the protein digestibility-corrected amino acid score.ConclusionsDietary interventions targeting protein quantity and quality may have specific benefits in preventing or delaying the progression of MetS in at-risk older people, but this requires investigation in the form of randomized trials.

Screen Time and Hours of Sleep Influence the Estimate Risk of Diabetes Mellitus and Metabolic Syndrome in Healthy Young Males.

Objective: Screen time (ST) has shown negative effects on physical and mental health, with an increase in the prevalence of overweight, metabolic syndrome (MetS), and obesity. The time spent in front of the screens was also associated with higher odds of selecting indicators of cardiometabolic disease in adulthood. In view of this, the aim of this study was to identify the risk of MetS and type 2 diabetes mellitus (T2DM) in healthy young males and relate it to ST and sleep time. Methods: We evaluated physical and laboratory characteristics, dichotomous diagnosis criteria, and continuous scores to assess MetS and Finnish Diabetes Risk Score questionnaire to measure the T2DM risk. Results: The means of MetS dichotomous and continuous severity criteria, among individuals with <7 hr of sleep, were higher than those with adequate sleep. We did not observe a direct impact of ST on the risk of MetS; nevertheless, >8 hr of ST increased 1.22 points in the T2DM risk. Conclusion: Excessive ST increased the risk of T2DM, but not of MetS. Moreover, sleeping <7 hr was associated with a higher mean of dichotomous and continuous severity criteria for MetS.

Relationship between Life's Essential 8 and metabolic syndrome among older Americans (NHANES, 2007-2010): navigating biological aging and inflammation.

Metabolic syndrome (MetS) is a global health concern, and it is particularly harmful to middle-aged and elderly individuals. Life Element Eight (LE8), a measure to improve cardiovascular health, may offer benefits for MetS. Herein, we examined the relationship between LE8 and MetS among middle-aged and elderly individuals, and elucidated the role of biological aging and inflammation in this process. We obtained the LE8 scores of 2,901 Americans, along with their biological aging indicators (Biological age, Phenotypic age, Serum Klotho), and computed their inflammatory indicators SII, DII. Using logistic regression model, we assessed the association among inflammatory markers, Biological aging, LE8 and MetS. Additionally, we generated restricted cubic spline (RCS) plots to display trends in significant variables in logistic regression. Using parallel mediation analysis, we evaluated the possible mediating role of various factors in the risk relationship between LE8 and MetS. Our examination revealed that higher LE8 scores were associated with a lower incidence of MetS in a fully adjusted model. The high LE8 subgroup had a 79.73% reduction in the risk of MetS compared to the low subgroup with an OR = 0.2027 (95% Cl 0.0871, 0.4714), with similar correlations between health factor scores and MetS risk. Biological aging mediated the associations between LE8, health behaviors and health factor scores and MetS risk. A rise in the LE8 score among middle-aged and elderly individuals is a protective factor for MetS, and this association may be partially mediated by biological aging, suggesting that LE8 may reduce the risk of MetS by ameliorating aging.

Substance use and incidence of metabolic syndrome before midlife among military adults: the CHIEF cohort study.

Habitual substance use, i. e., alcohol, tobacco and betel nut, has been found with an increased risk of metabolic syndrome (MetS) in the general population, whereas the association remains unclear in physically fit military personnel. This study aimed to investigate the combination of these substances use and their associations with new-onset MetS in the military. A total of 2,890 military men and women, aged 18-39 years, without MetS were obtained from the cardiorespiratory fitness and health in eastern armed forces study (CHIEF) in Taiwan and followed for incident MetS from baseline (2014) through the end of 2020. Incident MetS event was defined by the International Diabetes Federation guideline and confirmed in the annual health examinations. A self-report was used to assess the alcohol, tobacco and betel nut use status (active vs. former/never). Multivariable Cox regression model was performed to determine the association with adjustments for sex, age, body mass index and physical activity at baseline. At baseline, there were 279 active betel nut chewers (9.7%), 991 active smokers (34.3%) and 1,159 active alcohol consumers (40.1%). During a mean follow-up of 6.0 years, 673 incident MetS (23.3%) were observed. As compared to no substance users, only one substance, and two and three substances users had a greater risk of incident MetS [hazard ratios (HRs) and 95% confidence intervals: 1.27 (1.06-1.54), 1.38 (1.12-1.69) and 1.78 (1.37-2.32), respectively]. In subgroup analyses, the risk of incident MetS in two and three substances users was significantly greater in those free of baseline low high-density lipoprotein [HRs: 1.54 (1.21-1.95) and 2.57 (1.92-3.46), respectively], as compared to their counterparts (both p for interactions <0.05). A dose-response association of more substances use for new-onset MetS was noted in military personnel. This finding suggests that the combined alcohol, tobacco and betel nut use may play a role in the development of MetS. Further study is required to establish causation and to investigate the potential benefits of substance use cessation in reducing the risk of MetS.

Individual and joint exposure to PM2.5 constituents and incident risk of metabolic syndrome: A national cohort study

Cohort evidence linking fine particulate matter (PM2.5) constituents to metabolic syndrome (MetS) was extensively scarce. A nationwide MetS-free cohort of 3658 participants aged 45 and above, followed up from 2011 to 2015, were enrolled from 125 cities across China's mainland. Cox proportional hazards models and quantile-based g-computation were adopted to investigate individual and joint effects of exposure to PM2.5 constituents with MetS and its components. Monte Carlo simulations (n = 1000) were utilized to generate quasi-concentration-response (C-R) curve of joint exposure. A total of 633 MetS events occurred during 14,766.5 person-years follow-up (median 4.1 years). An estimated excess risk of 33 %−51 % in MetS incidence was linked to per interquartile range (IQR) increase in individual exposure to PM2.5 constituents. For an IQR-equivalent increase in joint exposure, we estimated a hazard ratio of 1.45 (95 % confidence internal: 1.23−1.69) for MetS, 1.49 (1.31−1.69) for central obesity, 1.19 (1.06−1.34) for high BP, 1.57 (1.34−1.84) for low HDL-C, 1.31 (1.14−1.51) for high TG, and 1.23 (1.02−1.48) for elevated FBG, respectively. Approximately linear or J-shaped C-R curves were consistently observed in individual and joint associations of PM2.5 constituents with MetS and its components. Joint-exposure analyses provided consistent evidence for the greatest contribution of SO42− in triggering PM2.5-associated risks of overall MetS and its components. Stratified analysis suggested higher PM2.5-related MetS risks among older participants and urban residents. These findings added longitudual population-based evidence for increased incident risks of MetS and its components associated with long-term exposures to PM2.5 constituents in middle-aged and older adults.

Real-world ctDNA testing patterns, associated biomarkers and sites of metastasis in early stage colorectal cancer.

3610 Background: There is a growing body of evidence to support the prognostic and predictive relevance of ctDNA in patients (pts) with early stage colorectal cancer (CRC). Relatively little is known about the real-world (rw) utilization of tumor-informed, personalized ctDNA assays in this population. We described the uptake of ctDNA testing over time as well as how results correlate with other biomarkers and the development of specific sites of metastasis (SOM). Methods: Pts with stage I-III CRC diagnosed after 1/1/2018 and a commercial ctDNA test in the early stage setting were selected using machine learning models from the Flatiron Health nationwide EHR-derived, de-identified database with a data cutoff of 10/31/23. Pts were considered ctDNA positive (ctDNA+) if they had at least one positive test. Odds ratios (OR) were calculated using logistic regression, adjusting for age, race, stage, practice type, insurance, and adjuvant treatment. Median time to metastasis (mets) for the ctDNA+ cohort (indexed to first positive test) was estimated using the Kaplan Meier estimator. Differences in minimal residual disease (MRD) in MTM/mL were compared using a Wilcox rank-sum test using maximum MRD. Results: In a cohort of 78,046 pts with stage I-III disease, 17,209 ctDNA tests were performed in 5,005 pts (median 3 per pt) with the majority in stage III pts (54.2%). 11% of pts (1652 / 14803) diagnosed between 1/1/21 and 4/1/22 received ctDNA testing compared to 14% of pts (1610 / 11412) diagnosed between 4/1/22 and 4/1/23. Among tested pts, 1,729 (34.5%) had at least one positive test. Pts with ctDNA+ tests were more likely to have tumor mutations in TP53 (OR: 1.69 [95% CI: 1.37, 2.08]) and KRAS (OR: 1.78 [95% CI: 1.10, 1.72]) than pts with ctDNA- tests. No differences were found in NRAS, BRAF or HER2. Progression to metastatic disease was observed in 365 (21.1%) pts with ctDNA+ tests vs 93 (2.8%) pts with ctDNA- tests (OR: 8.84 [95% CI: 6.95, 11.26]). The median time from first ctDNA+ to mets was 24.2 [95% CI: 21.7, NR] months. In those who developed mets, pts with ctDNA+ tests were significantly more likely to have liver mets compared to pts with ctDNA- tests (OR: 1.89 [95% CI: 1.12, 3.19]). Pts with liver mets had higher levels of MRD compared to non-liver SOM. (p &lt;0.001). Conclusions: This is the largest study to date of early stage CRC ctDNA testing in routine practice. Results suggest that pairing ctDNA and NGS testing has the potential to predict risk for liver mets and other pt outcomes. Future work is needed to translate these findings into clinically actionable insights and treatment strategies. [Table: see text]

Cardiorespiratory Fitness Decreases High-Sensitivity C-Reactive Protein and Improves Parameters of Metabolic Syndrome.

To evaluate the relationship between cardiorespiratory fitness (CRF), expressed as maximal oxygen uptake (ml.kg-1.min-1), metabolic syndrome (MetS), and high-sensitivity C-reactive protein (hs-CRP), a marker of systemic inflammation. The relationship between CRF, MetS, and hs-CRP was examined in a cohort of 173 men and women. CRF was evaluated using a Bruce protocol treadmill test and measured as estimated maximal oxygen uptake (VO2 max). Participants' physical activity status was self-reported. Plasma hs-CRP levels were measured using a standardized immunoassay, and the diagnostic criteria for MetS were based on guidelines established by the International Diabetes Federation (IDF). An inverse association was observed between hs-CRP levels and estimated VO2 max (p<0.01). Additionally, hs-CRP increased linearly with the number of MetS criteria present (p<0.01), while the estimated VO2 max decreased as the number of MetS criteria increased (p<0.01). Moreover, higher estimated VO2 max correlated with increased self-reported physical activity levels (p<0.01). Notably, participants engaging in two to three hours of exercise per week had hs-CRP levels ≤2.5 mg/L (p=0.018), considered a low-to-moderate risk range. Higher CRF, reflected by an estimated VO2 max, ≥45 ml/kg/min, is associated with lower hs-CRP levels and fewer MetS criteria. Additionally, regular physical activity, corresponding to higher VO2 max, appears to reduce systemic inflammation and ameliorate MetS risk factors. These findings support the mechanisms by which improved CRF and exercise may lower the risk of cardiovascular diseases (CVD) and type 2 diabetes (T2DM).

Predicting the onset of metabolic syndrome in a cohort study using a logistic regression model

Introduction: Metabolic syndrome (MetS) is a complex condition manifested as a group of metabolic disorders and is associated with the prevalence of certain diseases. Early prediction of MetS risk in the middle-aged population can be effective in controlling and preventing cardiovascular diseases. This study aimed to use logistic regression to predict metabolic syndrome and identify risk factors related to this condition. Method: This cohort study investigated factors associated with metabolic syndrome in the Mashhad study, which included a total of 11,570 participants. Factors that increase the relative risk of metabolic syndrome were evaluated using logistic regression, and predictive modeling was performed using logistic regression. Results: The results of the analysis using the logistic regression model showed that some factors, such as body mass index, history of high blood lipids, history of high blood pressure, and diabetes, increased the risk of metabolic syndrome. Various indicators, such as inactivity, high blood urea level, red blood cell hemoglobin content, aging, female gender, high levels of liver gamma-glutamyl transferase, and blood uric acid increase the risk of developing metabolic syndrome. Conclusion: It seems that body mass index, history of diabetes, and heart disease are related to the relative risk of developing the MetS syndrome compared to the other indicators, such as history of blood lipids, sedentary blood pressure, blood urea, uric acid, and hemoglobin content of red blood cells. These findings were obtained using the logistic regression model.

Machine Learning Identification of Nutrient Intake Variations across Age Groups in Metabolic Syndrome and Healthy Populations.

This study undertakes a comprehensive examination of the intricate link between diet nutrition, age, and metabolic syndrome (MetS), utilizing advanced artificial intelligence methodologies. Data from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2018 were meticulously analyzed using machine learning (ML) techniques, specifically extreme gradient boosting (XGBoost) and the proportional hazards model (COX). Using these analytic methods, we elucidated a significant correlation between age and MetS incidence and revealed the impact of age-specific dietary patterns on MetS. The study delineated how the consumption of certain dietary components, namely retinol, beta-cryptoxanthin, vitamin C, theobromine, caffeine, lycopene, and alcohol, variably affects MetS across different age demographics. Furthermore, it was revealed that identical nutritional intakes pose diverse pathogenic risks for MetS across varying age brackets, with substances such as cholesterol, caffeine, and theobromine exhibiting differential risks contingent on age. Importantly, this investigation succeeded in developing a predictive model of high accuracy, distinguishing individuals with MetS from healthy controls, thereby highlighting the potential for precision in dietary interventions and MetS management strategies tailored to specific age groups. These findings underscore the importance of age-specific nutritional guidance and lay the foundation for future research in this area.

Correlation between remnant cholesterol and hyperuricemia in patients with type 2 diabetes mellitus: a cross-sectional study

BackgroundRemnant cholesterol (RC) has been known as an important factor for the assessment of the metabolic syndrome (Mets) risk. However, the correlation between RC and hyperuricemia (HUA) in type 2 diabetes mellitus (T2DM) remains unclear. This study aims to explore the correlation between RC and HUA in patients with T2DM.MethodsA total of 2956 patients with T2DM admitted to the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University from 2020 to 2022 were included. The correlation between RC and HUA was evaluated with Spearman’s correlation, multiple logistic regression, subgroup analyses, receiver operating characteristic (ROC) curves analyses and generalized smooth curve fitting. Total cholesterol (TC) < 5.18mmol/L was defined as normal TC.ResultsRC was correlated with uric acid in patients with T2DM (Spearman’s correlation coefficient = 0.279, P < 0.001). According to the multiple logistic regression analyses, there was an independent positive correlation between RC and HUA (OR = 1.63, 95%CI = 1.40, 1.90). In addition, a non-linear correlation between RC and HUA was identified. The area under the ROC curve (AUC) of RC (0.658, 95%CI = 0.635, 0.681) was the largest compared with those of low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and TC. Subgroup analyses showed a more significant positive correlation among females or normal TC groups.ConclusionElevated RC is correlated with HUA in patients with T2DM significantly and positively. RC is better in its predictability for HUA than that of conventional lipid indexes.

Prenatal Exposure to Chemical Mixtures and Metabolic Syndrome Risk in Children

Prenatal exposure to ubiquitous endocrine-disrupting chemicals (EDCs) may increase the risk of metabolic syndrome (MetS) in children, but few studies have studied chemical mixtures or explored underlying protein and metabolic signatures. To investigate associations of prenatal exposure to EDC mixtures with MetS risk score in children and identify associated proteins and metabolites. This population-based, birth cohort study used data collected between April 1, 2003, and February 26, 2016, from the Human Early Life Exposome cohort based in France, Greece, Lithuania, Norway, Spain, and the UK. Eligible participants included mother-child pairs with measured prenatal EDC exposures and complete data on childhood MetS risk factors, proteins, and metabolites. Data were analyzed between October 2022 and July 2023. Nine metals, 3 organochlorine pesticides, 5 polychlorinated biphenyls, 2 polybrominated diphenyl ethers (PBDEs), 5 perfluoroalkyl substances (PFAS), 10 phthalate metabolites, 3 phenols, 4 parabens, and 4 organophosphate pesticide metabolites measured in urine and blood samples collected during pregnancy. At 6 to 11 years of age, a composite MetS risk score was constructed using z scores of waist circumference, systolic and diastolic blood pressures, triglycerides, high-density lipoprotein cholesterol, and insulin levels. Childhood levels of 44 urinary metabolites, 177 serum metabolites, and 35 plasma proteins were quantified using targeted methods. Associations were assessed using bayesian weighted quantile sum regressions applied to mixtures for each chemical group. The study included 1134 mothers (mean [SD] age at birth, 30.7 [4.9] years) and their children (mean [SD] age, 7.8 [1.5] years; 617 male children [54.4%] and 517 female children [45.6%]; mean [SD] MetS risk score, -0.1 [2.3]). MetS score increased per 1-quartile increase of the mixture for metals (β = 0.44; 95% credible interval [CrI], 0.30 to 0.59), organochlorine pesticides (β = 0.22; 95% CrI, 0.15 to 0.29), PBDEs (β = 0.17; 95% CrI, 0.06 to 0.27), and PFAS (β = 0.19; 95% CrI, 0.14 to 0.24). High-molecular weight phthalate mixtures (β = -0.07; 95% CrI, -0.10 to -0.04) and low-molecular weight phthalate mixtures (β = -0.13; 95% CrI, -0.18 to -0.08) were associated with a decreased MetS score. Most EDC mixtures were associated with elevated proinflammatory proteins, amino acids, and altered glycerophospholipids, which in turn were associated with increased MetS score. This cohort study suggests that prenatal exposure to EDC mixtures may be associated with adverse metabolic health in children. Given the pervasive nature of EDCs and the increase in MetS, these findings hold substantial public health implications.

#1358 The association between TNFRSF1B rs1061624 polymorphism and hypertension in end-stage kidney disease patients on dialysis

Abstract Background and Aims In chronic kidney disease (CKD), hypertension (HT) is commonly found during its development and is a leading cause for its progression. HT, dyslipidemia and visceral obesity are among the components of metabolic syndrome (MetS) and seem to associate with progression of CKD to end-stage kidney disease (ESKD). Enhanced levels of soluble tumor necrosis factor receptor 2 (sTNFR2) are known to associate with progressive CKD; and this biomarker was reported as an independent predictor of all-cause mortality in ESKD patients under dialysis. Concerning the TNFRSF1B gene, the polymorphism rs1061624 (A &amp;gt; G), located in the 3′-untranslated region (3′-UTR), was associated with the development of HT in men and with increased risk of MetS. The aim of this study was to determine the genotype frequencies of TNFRSF1B rs1061624 in ESKD patients with and without HT, and to evaluate its relationship with the circulating levels of some MetS biomarkers. Method We studied 277 ESKD patients on dialysis (recruited between 2016-2019), 170 diagnosed with HT and 107 without HT (no-HT group); age, sex, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP) and statin therapy were recorded. Real time PCR TaqMan SNP genotyping assay was used to assess genotype frequencies of TNFRSF1B rs1061624. We also evaluated the conventional lipid profile and the levels of oxidized low-density lipoprotein, adiponectin and leptin. Results The genotype frequencies in patients with and without HT were different (P = 0.002); the AA genotype was less frequent in HT than in no-HT group, while GG and AG genotypes were more frequent. Considering the AA genotype carriers, HT ESKD patients (n = 23), compared to the no-HT group (n = 33), presented lower adiponectin levels (P = 0.025); for the AG genotype carriers, HT group (n = 89) presented a trend towards lower adiponectin concentrations (P = 0.055), and were younger than no-HT patients (n = 48; P&amp;lt;0.001); in both comparisons, groups were matched for sex, BMI and number of patients under statins treatment, and in the first case also for age. Considering GG genotype, HT patients (n = 58) only differed from no-HT subjects (n = 26) in SBP, that was higher (P&amp;lt;0.001). Among HT patients, AG genotype carriers presented higher DBP (P = 0.004), lower values of leptin (P = 0.012) and leptin/adiponectin ratio (P = 0.022) and were younger (P&amp;lt;0.001) than GG genotype patients; compared to AA carriers, cholesterol levels were lower (P = 0.012). For the no-HT group, AG genotype patients presented lower DBP (P = 0.008) than AA genotype carriers. Conclusion The genotype frequencies were different in ESKD patients with and without HT, being G allele more frequent in HT. The HT ESKD patients with the AA or the AG genotypes seem to present lower adiponectin levels than the ESKD no-HT patients with the same genotypes. Acknowledgements This work was financed by CESPU, through the project SNPsCKD-GI2-CESPU-2022; FCT, in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences—UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy—i4HB.

Unraveling the Link: Mendelian Randomization Reveals Causal Relationship Between Selenium and Metabolic Syndrome.

Observational studies have linked selenium and metabolic syndrome (MetS), but the causality remains unclear. Therefore, this study intends to determine the causal relationship between selenium and the risk of MetS and its component features [body mass index (BMI), waist circumference adjusted for BMI (WCadjBMI), triglycerides (TC), HDL-cholesterol (HDL-C), fasting blood glucose (FBG), fasting blood insulin (FBI), systolic blood pressure (SBP), and diastolic blood pressure (DBP)]. This study was designed as the two-sample Mendelian randomization (MR), and genetic variants were obtained from the genome-wide association studies. The inverse variance weighted (IVW) was applied as the primary method, and the MR-Egger, weighted median, and MR-PRESSO were supplemented to assess its robustness. The Bonferroni method was used to correct p-values for multiple tests. Genetically incremented selenium level was related to higher odds ratios of developing the MetS (OR = 1.054, 95% CI = 1.016-1.094, p = 0.0049). As for components, significant causal links were identified between selenium and BMI (β = 0.015, p = 1.321 × 10-5), WCadjBMI (β = 0.033, p = 2.352 × 10-4), HDL-C (β = -0.036, p = 1.352 × 10-8), FBG (β = 0.028, p = 0.001), and FBI (β = 0.028, p = 0.002). No significant association was discovered for SBP (β = -0.076, p = 0.218) and DBP (β = 0.054, p = 0.227). These results were generally supported by the weighted median and MR-PRESSO methods. Our study provided evidence of the causal effect of selenium on MetS risk from the genetic perspective in the European population, and further investigation across diverse populations was warranted.

Correlation between Metabolic Syndrome and Gastric Cancer: Results of an Evidence-Based Strategy in Oriental Populations.

Metabolic syndrome (MetS) is a cluster of cardiovascular risk factors, including abdominal obesity, hyperglycemia, hypertension, and dyslipidemia. Gastric cancer (GC) is a common malignancy with significant mortality rates. The relationship between MetS and GC risk remains controversial. This systematic review and meta-analysis aimed to evaluate the correlation between MetS and GC. Case-control studies investigating the association between MetS and GC were obtained from various databases, including China National Knowledge Infrastructure (CNKI), SinoMed, Embase, Web of Science, The Cochrane Library, and PubMed. The search was performed from the inception of each database up until September, 2023. Two researchers independently screened the literature, extracted data, and assessed the quality of the included studies. A meta-analysis of the included literature was conducted using Stata 12.0 software. The study protocol is registered in PROSPERO (CRD42023490410). A total of eight studies involving a combined sample size of forty-four thousand eight hundred and seventy participants were included in the meta-analysis. The findings revealed that the risk of developing GC was not significantly associated with body mass index, triglycerides, hypertension, high fasting glucose, or MetS. However, it was found to be positively correlated with high-density lipoprotein cholesterol (OR = 1.69, 95%CI: 1.35-2.12). This meta-analysis suggests that MetS is not significantly associated with an increased risk of GC. The risk of GC increases with the presence of individual MetS components, such as high-density lipoprotein cholesterol. Therefore, GC prevention strategies should include lifestyle modifications and targeted interventions to manage MetS and its components. CRD42023490410 (PROSPERO).

Association between metabolic syndrome and kidney cancer risk: a prospective cohort study

BackgroundKidney cancer has become known as a metabolic disease. However, there is limited evidence linking metabolic syndrome (MetS) with kidney cancer risk. This study aimed to investigate the association between MetS and its components and the risk of kidney cancer.MethodsUK Biobank data was used in this study. MetS was defined as having three or more metabolic abnormalities, while pre-MetS was defined as the presence of one or two metabolic abnormalities. Hazard ratios (HRs) and 95% confidence intervals (CIs) for kidney cancer risk by MetS category were calculated using multivariable Cox proportional hazards models. Subgroup analyses were conducted for age, sex, BMI, smoking status and drinking status. The joint effects of MetS and genetic factors on kidney cancer risk were also analyzed.ResultsThis study included 355,678 participants without cancer at recruitment. During a median follow-up of 11 years, 1203 participants developed kidney cancer. Compared to the metabolically healthy group, participants with pre-MetS (HR= 1.36, 95% CI: 1.06-1.74) or MetS (HR= 1. 70, 95% CI: 1.30-2.23) had a significantly greater risk of kidney cancer. This risk increased with the increasing number of MetS components (P for trend < 0.001). The combination of hypertension, dyslipidemia and central obesity contributed to the highest risk of kidney cancer (HR= 3.03, 95% CI: 1.91-4.80). Compared with participants with non-MetS and low genetic risk, those with MetS and high genetic risk had the highest risk of kidney cancer (HR= 1. 74, 95% CI: 1.41-2.14).ConclusionsBoth pre-MetS and MetS status were positively associated with kidney cancer risk. The risk associated with kidney cancer varied by combinations of MetS components. These findings may offer novel perspectives on the aetiology of kidney cancer and assist in designing primary prevention strategies.

Dietary patterns and metabolic syndrome in patients with premature heart disease: a cross-sectional study

PurposeDue to the increase in the prevalence of other risk factors of heart diseases, the age of heart disease has decreased and it has led to premature heart disease. One of the main risk factors of this disease is metabolic syndrome (MetS). One of the key ways to control MetS is dietary modification. The purpose of this study is to investigate the relationship between dietary patterns and MetS in patients with premature heart disease.Design/methodology/approachThis study was conducted on 409 people with premature heart disease. The diagnosis of MetS was made based on the ATP III criteria. Dietary intake for the past year was collected using the validated semi-quantitative food frequency questionnaire. Dietary patterns were determined by factor analysis with principal components approach.FindingsThree dietary patterns were identified, including the healthy, western and traditional patterns. The findings showed that people who followed the traditional pattern more than those who followed less had a lower risk of MetS. (OR:0.23; 95% CI: 0.11–0.52). But, no relation was observed between healthy (OR:1.45; 95% CI:0.64–3.25) and western (OR:1.04; 95% CI:0.51–2.13) patterns with MetS.Originality/valueThe findings of this study showed that following a traditional dietary pattern based on high consumption of whole grains, red meat, viscera, fish, eggs, high-fat dairy products, soft drinks, mayonnaise and solid oil was associated with a lower risk of MetS.

Relationship between Circulating 25-Hydroxyvitamin D and Metabolic Syndrome in Chinese Adults: A Large Nationwide Longitudinal Study.

This study investigated the association of circulating levels of 25-hydroxyvitamin D (25[OH]D) with the risk of metabolic syndrome (MetS) and its components in adults. This nationwide cohort involved 23,810 Chinese adults attending annual health evaluations. Serum 25(OH)D levels, MetS status, and covariates were determined at each examination. Among them, 8146, 3310, and 1971 completed two, three, and more than three evaluations, respectively. A hybrid mixed-effects and Cox regression model was employed to determine the cross-sectional and longitudinal relationships. The odds ratios (ORs) and 95% confidence intervals (CIs) of MetS were significantly lower in individuals within quartile 4 (vs. 1) of serum 25(OH)D for both between-individual (0.43 [0.35, 0.52]) and within-individual comparisons (0.60 [0.50, 0.73]), respectively (all p-trends < 0.001). Among the MetS components, the corresponding ORs (95% CI) in between- and within-individual comparisons were 0.40 (0.29, 0.54) and 0.26 (0.19, 0.36) for abdominal obesity, 0.49 (0.41, 0.58) and 0.78 (0.66, 0.93) for high triglycerides, 0.70 (0.59, 0.82) and 0.75 (0.64, 0.87) for hypertriglyceridemia, 0.48 (0.39, 0.59) and 0.87 (0.71, 1.07) for low HDL cholesterol, and 0.92 (0.76, 1.12) and 0.49 (0.41, 0.59) for hypertension, respectively. Decreased hazard ratios (95% CIs) in quartile 4 (vs. 1) of 25(OH)D were found for MetS (0.80 [0.65, 1.00]), high triglycerides (0.76 [0.62, 0.92]), abdominal obesity (0.77 [0.63, 0.96]), and low HDL cholesterol (0.64 [0.50, 0.81]). Decreased concentrations of serum 25(OH)D correlate significantly to a heightened MetS risk and specific components. Our findings underscore the potential preventive function of circulating vitamin D concerning metabolic disorders.

Prevalence of metabolic sy ndrome and its risk factors among medical undergraduates at Northern Border University, Arar, Saudi Arabia

Purpose: To determine the prevalence of metabolic syndrome (MetS) and its associated factors among medical undergraduates of Northern Border University. Methods: This cross-sectional study was performed on 200 medical undergraduates of Northern Border University, Arar, Saudi Arabia from August 2023 to October 2023. Data on demographic details and anthropometric measurements were collected. Complete lipid profile and blood glucose levels were measured after at least 8-h fast. The International Diabetes Federation (IDF) recommendations were utilized for diagnosing MetS. The data obtained were analyzed using Statistical Package for Social Sciences (SPSS), version 20.0. Group differences were analyzed using Chi-square test and Post hoc analysis. Results: The estimated overall prevalence of MetS was 21.5 %. Metabolic syndrome (MetS) was more prevalent among older students (37.36 %) and obese students (45.28 %) than among younger and non-obese students. Female students had a higher prevalence of MetS (29 %) than their male counterparts (14 %). The most frequent risk factors for MetS were elevated waist circumference (36 %) and low HDL levels (33 %). The majority of students (76.7 %) with high waist circumference had 2 or more risk factors for MetS. Students with a positive family history of hypertension and obesity showed greater prevalence of MetS. Conclusion: The study has demonstrated a high prevalence of MetS among young adults in Arar, Saudi Arabia. High prevalence of obesity and elevated waist circumference suggests that early and targeted interventions are required to prevent the development of MetS and cardiovascular risk in later life.

Risk prediction model of metabolic syndrome in perimenopausal women based on machine learning

IntroductionMetabolic syndrome (MetS) is considered to be an important parameter of cardio-metabolic health and contributing to the development of atherosclerosis, type 2 diabetes. The incidence of MetS significantly increases in postmenopausal women, therefore, the perimenopausal period is considered a critical phase for prevention. We aimed to use four machine learning methods to predict whether perimenopausal women will develop MetS within 2 years. MethodsWomen aged 45–55 years who underwent 2 consecutive years of physical examinations in Ninth Clinical College of Peking University between January 2021 and December 2022 were included. We extracted 26 features from physical examinations, and used backward selection method to select top 10 features with the largest area under the receiver operating characteristic curve (AUC). Extreme gradient boosting (XGBoost), Random forest (RF), Multilayer perceptron (MLP) and Logistic regression (LR) were used to establish the model. Those performance were measured by AUC, accuracy, precision, recall and F1 score. SHapley Additive exPlanation (SHAP) value was used to identify risk factors affecting perimenopausal MetS. ResultsA total of 8700 women had physical examination records, and 2,254 women finally met the inclusion criteria. For predicting MetS events, RF and XGBoost had the highest AUC (0.96, 0.95, respectively). XGBoost has the highest F1 value (F1 = 0.77), followed by RF, LR and MLP. SHAP value suggested that the top 5 variables affecting MetS in this study were Waist circumference, Fasting blood glucose, High-density lipoprotein cholesterol, Triglycerides and Diastolic blood pressure, respectively. ConclusionWe’ve developed a targeted MetS risk prediction model for perimenopausal women, using health examination data. This model enables early identification of high MetS risk in this group, offering significant benefits for individual health management and wider socio-economic health initiatives.

Women with a history of gestational diabetes mellitus present an accumulation of cardiovascular risk factors at age 46-A birth cohort study.

The incidence of gestational diabetes mellitus (GDM) is globally increasing, and it has been associated with later type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease (CVD). However, long-term population-based studies investigating common CVD risk factors years after pregnancy are lacking. To evaluate the future mortality and morbidity in cardiovascular and metabolic diseases, we conducted a thorough investigation of midlife risk factors in women with and without previous GDM. A prospective population-based cohort study was conducted of 3173 parous women from the Northern Finland Birth Cohort, 1966. Study participants were obtained from the national register or patient records. Those with a GDM diagnosis formed the GDM cohort (n = 271), and those without a previous GDM diagnosis formed the control cohort (n = 2902). Clinical examinations were performed on participants at the age of 46 and included anthropometric measurements, oral glucose tolerance test (OGTT), biochemical measurements, and cardiovascular assessment. At the age of 46, women in the GDM cohort had a higher body mass index (BMI, 29.0 kg/m2 vs 26.3 kg/m2, p < 0.001) and greater waist circumference (94.1 cm vs 86.5 cm, p < 0.001) than the control cohort. In the GDM cohort, a higher incidence of impaired glucose tolerance (12.6% vs 7.3%, p = 0.002), more previously diagnosed and OGTT-detected type 2 diabetes (23.3% vs 3.9%, p < 0.001), lower high-density lipoprotein (1.53 mmol/L vs 1.67 mmol/L, p = 0.011), higher triglycerides (1.26 mmol/L vs 1.05 mmol/L, p = 0.002) and a higher fatty liver index (6.82 vs 2.47, p < 0.001), were observed even after adjusting for BMI, polycystic ovary syndrome, parity, level of education, physical activity, smoking, and alcohol consumption. The women in the GDM cohort also had more MetS (42.6% vs 21.9%, p < 0.001) and higher risk scores for CVD and fatal events (Framingham 4.95 vs 3.60, p < 0.001; FINRISK 1.71 vs 1.08, p < 0.001). Women with a previous diagnosis of GDM exhibit more risk factors for CVD in midlife and are at a higher risk for cardiovascular events later in life.