Yoxas/statistical_literacy huggingface dataset:
Metabolic syndrome (MetS) has become an issue in the public health discipline. The primary aim of this study is to assess the potential determinants for both knowledge level of metabolic syndrome and health literacy (HL) level among the adult population. The second purpose of this study is to show whether there is a relationship between the MetS knowledge level and the HL level in western Turkey. This cross-sectional study was conducted between October 10, 2017 and November 15, 2017 in western Turkey. The participants of the study were adult population who applied to seven "family health centers". The MetS knowledge level was measured with the Metabolic Syndrome Knowledge Level Scale (MetS-KS). HL level was measured with the HLS-EU-Q16. A General Linear Model was constructed to evaluate the relationship between MetS-KS scores and HLS-EU-Q16 scores. For statistical significance, P < 0.05 was accepted. Younger age, having higher education level, being single, having a high family income, not having a chronic disease, doing regular physical activity, viewing television less than 3 hours a day, previous measurement of waist circumference, previous attempts to lose weight, not being abdominally obese, not being at risk for hypertension and not having optimal body mass index (BMI) were associated with high HL levels (P < 0.05 for each one). According to the general linear model, the level of HL was not related to the level of MetS knowledge level (P > 0.05). Younger age, having a high educational level, high socioeconomic level and positive health behaviors were related with both MetS knowledge level and HL level. However, there was no direct relationship between MetS knowledge level and HL level.
Metabolic syndrome (MetS) is a cluster of clinical syndromes that is closely associated with an elevated risk of developing atherosclerotic cardiovascular disease. In a series of animal experiments and clinical trials, crocus sativus and its component crocin have demonstrated promising hypoglycemic effects. However, there is currently insufficient evidence regarding their impact on cardiometabolic parameters. Our study aimed to assess the impact of Crocus sativus and crocin on glycemic control in individuals with metabolic syndrome and associated disorders, as well as their potential effects on improving cardiometabolic parameters. We searched Cochrane Library, PubMed, Embase, and Web of Science databases to ascertain the pertinent randomized controlled trials (RCTs) until December 30, 2023. Q-test and I2 statistics were utilized to evaluate heterogeneity among the included studies. Data were merged using a random-effects model and presented as (WMD) with a 95% confidence interval (CI). The current comprehensive review and meta-analysis, encompassing 13 RCTs involving a total of 840 patients diagnosed with metabolic syndrome and associated disorders, demonstrates that Crocus sativus was superior to placebo on Hemoglobin A1c(HbA1c) (WMD: -0.31;95% CI [-0.44,-0.19]. P = 0.002) and systolic blood pressure(SBP) (WMD:-7.49;95% CI [-11.67,-3.30]. P = 0.99) respectively. Moreover, Crocus sativus improved fasting blood glucose (FBG) (WMD:-7.25;95% CI [-11.82, -2.57]. P = 0.002) when used crocin and on other chronic diseases. Crocus sativus reduced the total cholesterol (TC) among the metabolic syndromepatients (WMD:-13.64;95%CI [-26.26, -1.03]. P = 0.03). We demonstrated that Crocus sativus exerts beneficial effects on glycemic control and cardiometabolic parameters in individuals with metabolic syndrome and related disorders.
Metabolic syndrome (MetS) is a cluster of medical conditions associated with several health disorders. MetS and frailty can be related to prolonged physical deconditioning. There is a need to know whether there is concordance between the different ways of diagnosing it and to know their prevalence in Spanish older adults. Thus, the aims of this study were to describe the prevalence of MetS; to analyse the concordance between different definitions to diagnose MetS; and to study the associations between MetS, frailty status, and physical activity (PA) in older adults with decreased functional capacity. This report is a cross-sectional study involving 110 Spanish older adults of ages ≥65 years with decreased functional capacity. Clinical criteria to diagnose MetS was defined by different expert groups. Anthropometric measurements, blood biochemical analysis, frailty status, functional capacity, and PA were assessed. The Kappa statistic was used to determine the agreement between the five MetS definitions used. Student's t-test and the Pearson chi-square test were used to examine differences between sex, frailty, and PA groups. The sex-adjusted prevalence of MetS assessed by the National Cholesterol Education Program-Third Adult Treatment Panel was 39.4% in men and 32.5% in women. The International Diabetes Federation and the Harmonized definitions had the best agreement (k = 1.000). The highest odds ratios (ORs) of cardiometabolic risk factors to develop MetS were elevated triglycerides (37.5) and reduced high-density lipoprotein cholesterol (27.3). Central obesity and hypertension prevalence were significantly higher in the non-active group (70.7% and 26.8%, respectively), compared to the active group (50.0% and 7.7%, respectively). Moreover, the active group (OR = 0.85, 95% CI = 0.35, 2.04) and active women group (OR = 0.77, 95% CI = 0.27, 2.20) appeared to show a lower risk of developing this syndrome. MetS is highly prevalent in this sample and changes according to the definition used. It seems that sex and frailty do not influence the development of MetS. However, PA appears to decrease central obesity, hypertension, and the risk of developing MetS.
Metabolic syndrome (MetS) is a group of metabolic abnormalities that include disturbed glucose metabolism, dyslipidemia, abdominal obesity, and arterial hypertension. Nutritional and lifestyle modifications have increased the risk of cardiometabolic disorders among adolescents. Studies conducted in various parts of India have shown a wide range of prevalence among adolescents aged 10-19 years. The various criteria for defining MetS have led to controversial diagnoses, providing inconsistent findings. Additionally, there is a paucity of national-level estimates on the prevalence of MetS in India. Therefore, this systematic review and meta-analysis were conducted to estimate the prevalence of MetS among adolescents. A comprehensive search was conducted to identify studies that reported the prevalence of MetS among adolescents in India. The search was performed using several databases, including PubMed, Embase, ScienceDirect, Scopus, Medline, Web of Science, Google, and Google Scholar. Relevant data were extracted and assessed for quality using the Critical Appraisal Skills Programme (CASP) guidelines. To estimate the pooled prevalence and explore heterogeneity, a random effects model and I2 statistic were used. Subgroup analyses were conducted based on criteria for defining MetS, sex, study setting, and study site. Sensitivity analysis was performed, and publication bias was also explored. A sample size of 19044 adolescents from 16 studies was included in the meta-analysis. The pooled prevalence of Mets among adolescents using the International Diabetes Federation (IDF) criteria was 3.4% (95% CI: 1.1-6.6%, I2=97.1%) and the National Cholesterol Education Program - Adult Treatment Panel III (NCEP-ATP III) criteria were 5.0% (95% CI: 3.3-6.9%, I2=95.9). The subgroup analyses did not reveal the reasons for heterogeneity, but sensitivity analysis showed a substantial change in the pooled estimate. Our study findings show that the prevalence of MetS among Indian adolescents is higher compared to other countries posing a challenge to address the necessity of intervention among adolescents. Standardizing the definition of MetS is necessary to avoid inconsistency in the estimates. The study findings highlight the need to strengthen existing adolescent programs through the encouragement of increased physical activity and the adoption of nutritious well-balanced diets to mitigate the burden of MetS among adolescents in India.
Metabolic syndrome (MetS) is associated with an increased incidence of chronic complications and mortality of diabetes patients. Prevention and treatment of MetS is important means of lowering the risk of cardiovascular diseases and mortality. This study aimed to find out metabolic syndrome and life style factors among diabetes patients. A cross-sectional survey was carried out among 296 patients with type 2 diabetes mellitus attending Chitwan Medical College Teaching Hospital. Consecutive sampling technique was used to select sample. Data were collected from 15th December 2021 to 15th March, 2022 using Interview Schedule, bio-physiological measurement and record review. Obtained data were analysed in SPSS version 20 for window using descriptive and inferential statistics. Chi-square test was applied to measure the association between the variables. Logistic regression analysis was performed to identify the factors associated with metabolic syndrome. Findings revealed that the prevalence of MetS was 66.2% and 58.4% in patients according to International Diabetes Federation (IDF) and National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria respectively. The most common MetS parameters were raised fasting plasma glucose (94.6%) and abnormal waist circumference (78.4% in IDF criteria) while the least prevalent parameter was reduced HDL level (43.2%). Majorities of the patients were non-vegetarian (85.5%), had poor dietary compliance (poor-46.3%, very poor-32.1%), overweight/obese (65.5%), and suffered from moderate stress (90.1%). Bivariate analysis showed that MetS as per NCEP ATP criteria was significantly associated with gender (p = 0.006), occupation (p = 0.007), presence of other co-morbid condition (<0.001) and sleep problem (p = <0.001). However, MetS as per IDF criteria was significantly associated with age (p = <0.028), duration of diabetes (p = <0.001), follow-up visit (p = <0.030), blood sugar monitoring (p = <0.009) and physical activity of diabetes patients (p = <0.001). Further logistic regression analysis revealed that sleep problem (AOR = 21.812;95%CI = 8.512,55.894) and presence of other comorbidities (AOR = 4.024;95%CI = 2.220,7.295) were the significant factors of metabolic syndrome. Metabolic syndrome is high in patients with type 2 diabetes mellitus. Therefore, treating physicians and other health workers need to monitor MetS parameters regularly to reduce the risk of cardiovascular diseases, stroke and premature death.
Metabolic syndrome (MetS), characterized by elevated blood pressure, high blood glucose, excess abdominal fat, and abnormal cholesterol or triglyceride levels, significantly increases the risk of various non-communicable diseases. This study focuses on understanding the sex-specific association between Apolipoprotein E (APOE) polymorphism and MetS among middle-aged and older adults in rural southern India. This cross-sectional study utilized data from the Centre for Brain Research-Srinivaspura Aging, Neuro Senescence, and COGnition (CBR-SANSCOG) study. Participants (n = 3741) underwent comprehensive clinical assessments and blood investigations, including APOE genotyping. MetS was defined using the National Cholesterol Education Program - Adult Treatment Panel III (NCEP ATP III) and the Consensus criteria. Statistical analyses, including chi-square tests, ANCOVA, and logistic regression, were conducted to explore the association of APOE genotype with MetS and its components, stratified by sex. Females carrying the APOE E4 allele had 1.31-fold increased odds of MetS (95 % CI: 1.02,1.69, p = 0.035) according to the NCEP ATP III criteria but not when the Consensus criteria were applied. The study also noted sex-specific differences in the association of APOE with various MetS components, including lipid levels and waist circumference. Our findings reveal a sex-specific association between the APOE E4 allele and MetS, with only females having an increased risk. This study contributes to the understanding of the genetic underpinnings of MetS and highlights the importance of considering sex-specific differences in MetS research and its prevention strategies. This study underscores the complexity of MetS etiology and emphasizes the need for further research to elucidate the role of genetic, environmental, and lifestyle factors in its progression, particularly in sex-specific contexts.
Metabolic syndrome is a complex pathophysiologic state which characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidaemia. The Adult Treatment Panel III report (ATP III) of the National Cholesterol Education Programme identified the metabolic syndrome as a serious public health issue in the modern era. In Western and Asian nations, the frequency of metabolic syndrome is rising, especially in developing regions experiencing rapid socio-environmental changes, in Sub-Saharan Africa; metabolic syndrome may be present in more than 70% of people with type 2 diabetes mellitus. Therefore the objective of our study was to estimate the pooled prevalence of metabolic syndrome and associated factors among type II diabetes mellitus patient. This systematic review and meta-analysis included original articles of cross sectional studies published in the English language. Searches were carried out in PubMed, Web of Science, Google Scholar, and grey literature Journals from 2013 to June 2023. A random-effects model was used to estimate the pooled prevalence of metabolic syndrome among type II Diabetes mellitus patient in Ethiopia. Heterogeneity was assessed using the I2 statistic. Subgroup analysis was also conducted based on study area. Egger's test was used to assess publication bias. Sensitivity analysis was also conducted. Out of 300 potential articles, 8 cross sectional studies were included in this systematic review and meta-analysis study. The pooled prevalence of metabolic syndrome among patient with type II diabetes mellitus in Ethiopia was found to be 64.49% (95% CI: 62.39, 66.59) and 52.38% (95% CI: 50.05, 54.73) by using NCEP/ATP III and IDF criteria, respectively. The weighted pooled prevalence of metabolic syndrome among type II diabetes mellitus patients by sub group analysis based on the study region was 63.79% (95% CI: 56.48, 71.11) and 52.23% (95%CI: 47.37, 57.22) by using NCEP/ATP III and IDF criteria, respectively. Being female and increased body mass index were factors associated with metabolic syndrome among type II diabetes mellitus patients. The prevalence of metabolic syndrome among type II patient is high. Therefore, policymakers, clinicians, and concerned stakeholders shall urge effective strategies in the control, prevention, and management of metabolic syndrome among type II diabetes mellitus.
Metabolomics is an emerging and powerful technology that offers a comprehensive view of an organism's physiological status. Although widely applied in human medicine, it is only recently making its introduction in veterinary medicine. As a result, validated metabolomics protocols in feline medicine are lacking at the moment. Since biological interpretation of metabolomics data can be misled by the extraction method used, species and matrix-specific optimized and validated metabolomic protocols are sorely needed. Systematic optimization was performed using fractional factorial experiments for both serum (n = 57) and urine (n = 24), evaluating dilution for both matrices, and aliquot and solvent volume, protein precipitation time and temperature for serum. For the targeted (n = 76) and untargeted (n = 1949) validation of serum respectively, excellent instrumental, intra-assay and inter-day precision were observed (CV ≤ 15% or 30%, respectively). Linearity deemed sufficient both targeted and untargeted (R2 ≥ 0.99 or 0.90, respectively). An appropriate targeted recovery between 70 and 130% was achieved. For the targeted (n = 69) and untargeted (n = 2348) validation of the urinary protocol, excellent instrumental and intra-assay precision were obtained (CV ≤ 15% or 30%, respectively). Subsequently, the discriminative ability of our metabolomics methods was confirmed for feline chronic kidney disease (CKD) by univariate statistics (n = 41 significant metabolites for serum, and n = 55 for urine, p-value<0.05) and validated OPLS-DA models (R2(Y) > 0.95, Q2(Y) > 0.65, p-value<0.001 for both matrices). This study is the first to present an optimized and validated wholistic metabolomics methods for feline serum and urine using ultra-high performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry. This robust methodology opens avenues for biomarker panel selection and a deeper understanding of feline CKD pathophysiology and other feline applications.
Metabolomics plays a critical role in deciphering metabolic alterations within individuals, demanding the use of sophisticated analytical methodologies to navigate its intricate complexity. While many studies focus on single biofluid types, simultaneous analysis of multiple matrices enhances understanding of complex biological mechanisms. Consequently, the development of data fusion methods enabling multiblock analysis becomes essential for comprehensive insights into metabolic dynamics. This study introduces a novel guideline for jointly analyzing diverse metabolomic datasets (serum, urine, metadata) with a focus on metabolic differences between groups within a healthy cohort. The guideline presents two fusion strategies, 'Low-Level data fusion' (LLDF) and 'Mid-Level data fusion' (MLDF), employing a sequential application of Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS), linking the outcomes of successive analyses. MCR-ALS is a versatile method for analyzing mixed data, adaptable at various stages of data processing-encompassing resonance integration, data compression, and exploratory analysis. The LLDF and MLDF strategies were applied to 1H NMR spectral data extracted from urine and serum samples, coupled with biochemical metadata sourced from 145 healthy volunteers. Both methodologies effectively integrated and analysed multiblock datasets, unveiling the inherent data structure and variables associated with discernible factors among healthy cohorts. While both approaches successfully detected sex-related differences, the MLDF strategy uniquely revealed components linked to age. By applying this analysis, we aim to enhance the interpretation of intricate biological mechanisms and uncover variations that may not be easily discernible through individual data analysis.
Metabolomics, leveraging techniques like NMR and MS, is crucial for understanding biochemical processes in pathophysiological states. This field, however, faces challenges in metabolite sensitivity, data complexity, and omics data integration. Recent machine learning advancements have enhanced data analysis and disease classification in metabolomics. This study explores machine learning integration with metabolomics to improve metabolite identification, data efficiency, and diagnostic methods. Using deep learning and traditional machine learning, it presents advancements in metabolic data analysis, including novel algorithms for accurate peak identification, robust disease classification from metabolic profiles, and improved metabolite annotation. It also highlights multiomics integration, demonstrating machine learning's potential in elucidating biological phenomena and advancing disease diagnostics. This work contributes significantly to metabolomics by merging it with machine learning, offering innovative solutions to analytical challenges and setting new standards for omics data analysis.
Metachromatic leukodystrophy (MLD) is a devastating rare neurodegenerative disease. Typically, loss of motor and cognitive skills precedes early death. The disease is characterised by deficient lysosomal arylsulphatase A (ARSA) activity and an accumulation of undegraded sulphatide due to pathogenic variants in the ARSA gene. Atidarsagene autotemcel (arsa-cel), an ex vivo haematopoietic stem cell gene therapy was approved for use in the UK in 2021 to treat early-onset forms of pre- or early-symptomatic MLD. Optimal outcomes require early diagnosis, but in the absence of family history this is difficult to achieve without newborn screening (NBS). A pre-pilot MLD NBS study was conducted as a feasibility study in Manchester UK using a two-tiered screening test algorithm. Pre-established cutoff values (COV) for the first-tier C16:0 sulphatide (C16:0-S) and the second-tier ARSA tests were evaluated. Before the pre-pilot study, initial test validation using non‑neonatal diagnostic bloodspots demonstrated ARSA pseudodeficiency status was associated with normal C16:0-S results for age (n = 43) and hence not expected to cause false positive results in this first-tier test. Instability of ARSA in bloodspot required transfer of NBS bloodspots from ambient temperature to -20°C storage within 7-8 days after heel prick, the earliest possible in this UK pre-pilot study. Eleven of 3687 de-identified NBS samples in the pre-pilot were positive for C16:0-S based on the pre-established COV of ≥170 nmol/l or ≥ 1.8 multiples of median (MoM). All 11 samples were subsequently tested negative determined by the ARSA COV of <20% mean of negative controls. However, two of 20 NBS samples from MLD patients would be missed by this C16:0-S COV. A further suspected false negative case that displayed 4% mean ARSA activity by single ARSA analysis for the initial test validation was confirmed by genotyping of this NBS bloodspot, a severe late infantile MLD phenotype was predicted. This led to urgent assessment of this child by authority approval and timely commencement of arsa-cel gene therapy at 11 months old. Secondary C16:0-S analysis of this NBS bloodspot was 150 nmol/l or 1.67 MoM. This was the lowest result reported thus far, a new COV of 1.65 MoM is recommended for future pilot studies. Furthermore, preliminary data of this study showed C16:1-OH sulphatide is more specific for MLD than C16:0-S. In conclusion, this pre-pilot study adds to the international evidence that recommends newborn screening for MLD, making it possible for patients to benefit fully from treatment through early diagnosis.