Introduction: The purpose of this study was to determine the possible differences in genetic polymorphisms and serum levels of chromogranin A (CgA), according to age and sex, in subjects with and without metabolic syndrome (MetS). Methodology: The genotyping and serum level of CgA and biochemical parameters were measured by the T-ARMS-PCR and PCR-RFLP and ELISA and spectrophotometer methods, respectively. Results: A comparison of males with and without MetS showed significantly lower high-density lipoprotein-cholesterol (HDL-C) levels than those of females. At ages 30-70 years, both sexes showed significant differences in triglycerides (TG), fasting blood sugar (FBS), CgA levels and waist circumference (WC) when compared to the two groups. Both sexes with MetS indicated significant differences in systolic blood pressure (SBP) at ages 40-70 years, while at ages 40-59 years, there was a significant difference in HDL-C level in males. There was a significant correlation between serum levels of FBS, TG, SBP and WC (in both sexes), and CgA in subjects with MetS. Significant correlation was found between HDL-C level and diastolic blood pressure (DBP), and CgA level in males and females, respectively. CgA genotype frequency (T-415C and C+87T polymorphisms) showed no significant differences between males and females with and without MetS, while there was only a significant difference in frequency of the genotypes T-415C when compared to males with and without MetS. Conclusion The CgA appears to be strongly associated with MetS components in both sexes. Variation in CgA gene expression may affect the T–415C polymorphism in males. This may mean that the structure of CgA genetics differs in different ethnic groups. Differences in the serum level and expression of CgA gene may show valuable study results that it may be expected a relationship between these variables and the MetS.
Sex ; Chromogranin A ; Genotype ; Metabolic Syndrome

Objectives: We determined the clinical characteristics and prevalence of metabolic syndrome among adult Filipinos with overt hypothyroidism. Methodology: This is a cross-sectional study of 151 adults. Patients were recruited by sequential enrollment. Anthropometric and blood pressure measurements were performed followed by blood extraction for metabolic parameters and thyroid function tests. Clinical and laboratory characteristics were compared between patients with and without metabolic syndrome. Results: The prevalence of metabolic syndrome is 40.4% (95%CI: 32.5%, 48.7%). Patients with metabolic syndrome have a waist circumference of 88.4 ± 7.7 cm in females and 93.3 ± 9.0 cm in males. The median fasting blood glucose was 111.4 (52.2) mg/dL, median systolic blood pressure of 120 (30) mm Hg and diastolic blood pressure of 80 (20) mmHg, median serum triglycerides of 174.3 (114.2) mg/dL, median HDL-C of 42.3 (19.2) mg/dL and a proportion of patients with diabetes (23.0%) and hypertension (44.3%), respectively. The presence of increased waist circumference is the most prevalent component seen among hypothyroid patients. There were no differences in terms of age, sex, etiology of hypothyroidism and anti-TPO levels in those with and without metabolic syndrome. Conclusion The prevalence of metabolic syndrome in adult Filipinos with hypothyroidism is high. Emphasis must be placed on early screening using waist circumference and metabolic parameters among hypothyroid patients who are at high risk of developing metabolic syndrome.
Dyslipidemias ; Hypothyroidism ; Metabolic Syndrome ; Prevalence

BACKGROUND: It is crucial to understand the seasonal variation of Metabolic Syndrome (MetS) for the detection and management of MetS. Previous studies have demonstrated the seasonal variations in MetS prevalence and its markers, but their methods are not robust. To clarify the concrete seasonal variations in the MetS prevalence and its markers, we utilized a powerful method called Seasonal Trend Decomposition Procedure based on LOESS (STL) and a big dataset of health checkups. METHODS: A total of 1,819,214 records of health checkups (759,839 records for men and 1,059,375 records for women) between April 2012 and December 2017 were included in this study. We examined the seasonal variations in the MetS prevalence and its markers using 5 years and 9 months health checkup data and STL analysis. MetS markers consisted of waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG). RESULTS: We found that the MetS prevalence was high in winter and somewhat high in August. Among men, MetS prevalence was 2.64 ± 0.42 (mean ± SD) % higher in the highest month (January) than in the lowest month (June). Among women, MetS prevalence was 0.53 ± 0.24% higher in the highest month (January) than in the lowest month (June). Additionally, SBP, DBP, and HDL-C exhibited simple variations, being higher in winter and lower in summer, while WC, TG, and FPG displayed more complex variations. CONCLUSIONS This finding, complex seasonal variations of MetS prevalence, WC, TG, and FPG, could not be derived from previous studies using just the mean values in spring, summer, autumn and winter or the cosinor analysis. More attention should be paid to factors affecting seasonal variations of central obesity, dyslipidemia and insulin resistance.
Male ; Female ; Humans ; Metabolic Syndrome/epidemiology* ; Seasons ; Prevalence ; Climate ; Insulin Resistance ; Triglycerides

Background and Objective: Dyslipidemia in hypothyroidism results from the effects of thyroid hormones on lipid metabolism. These, in combination with hypothyroidism-induced hemodynamic changes, are risk factors for cardiometabolic diseases. We determined the prevalence of metabolic syndrome (MS) among adult Filipinos with hypothyroidism and compared clinical and laboratory characteristics of those with versus without MS. Methods: This is a retrospective study of 105 patients with biochemically confirmed hypothyroidism. A review of records obtained anthropometric measurements, blood pressure, fasting blood glucose, lipid profile, and thyroid hormones. Clinical and laboratory characteristics were then compared between MS and those without. Significant differences were determined by two-way ANOVA, while heterogeneity of categorical variables was determined by chi-square or Fisher exact test. All data analyses were performed using Stata version 17.0 with a significance level of p<0.05. Results: The prevalence of MS is 36.19% (95%CI: 27.04%,46.15%). Body mass index (BMI) peaks at obese class I among those with MS. There is a significantly higher proportion of patients diagnosed to have diabetes (28.95% vs. 7.46%; p=0.003) and hypertension (52.63% vs. 14.93%; p<0.001) in the MS group. No significant differences were noted between groups regarding age, sex, etiology of hypothyroidism, blood pressure, fasting glucose, lipid profile, and thyroid hormone levels. Conclusion Our study showed that the prevalence of MS in adult Filipinos with hypothyroidism is increased at 36.19%. Only BMI, presence of diabetes, and hypertension were shown to be significantly higher. Emphasis must be placed on early screening among hypothyroid patients at high risk of developing MS. A prospective study using waist circumference and clinical and metabolic parameters is needed to validate these findings.
dyslipidemia ; hypothyroidism ; metabolic syndrome ; prevalence

Obesity and overweight are considered health risks for non-communicable diseases. Most clinical practice guidelines suggest lifestyle modification as the primary management and as an adjunct to pharmacologic treatment. Using the SMART-EST goaloriented action plan and lifestyle medicine may improve weight reduction outcomes. The case presented had clinical criteria (3/5) for metabolic syndrome, diagnosed previously as obese stage II, asthma moderately uncontrolled, prediabetes, and mild dyslipidemia. Baseline weight and waist-to-hip ratio were taken and interpreted as obese stage II with a very severe risk for comorbidity. The diagnostics used were fasting plasma glucose, lipid profile, HbA1c, and 2-D echocardiography on the eight months of intervention only. Using the SMART-EST action plan plus Lifestyle medicine approaches as non-pharmacologic management for metabolic syndrome. There was an 11.4 % reduction in weight, improved fasting glucose, lipid profile, and 2-D echocardiography within the eight months of intervention.
Metabolic syndrome

Objective: To explore the relationship between sleep/physical activity and metabolic syndrome (MS) in urban population of Xinjiang. Methods: This is a prospective, cross-sectional study. From July 2019 to September 2021, a two-stage random sampling method was used to randomly select residents aged 30-74 years from two communities in Urumqi of northern Xinjiang and Korla of southern Xinjiang. General situation questionnaire, Pittsburgh Sleep Quality Index Scale (PSQI) survey, International Physical Activity Questionnaire (IPAQ) survey, physical examination, physiological and biochemical indicators were obtained and analyzed. The dose-response curves of healthy sleep score and physical activity with metabolic syndrome were plotted using restricted cubic spline curves. Multivariate logistic regression model was used to analyze the independent and combined effects of sleep quality and physical activity on MS risk. Results: A total of 10 209 participants were included. The mean age of the subjects was (47.1±9.1) years, and males accounted for 51.3% (5 275/10 209). The prevalence of MS was significantly associated with the healthy sleep score and physical activity. Compared to the subjects with healthy sleep, OR (95%CI) of MS with intermediate, and poor sleep were 1.20(1.06-1.35), 1.23(1.04-1.45), respectively. Compared to the subjects with high physical activity, OR (95%CI) of MS with medium, low physical activity was 1.34(1.15-1.56), 1.42(1.19-1.70), respectively. There was a significant interaction between sleep and physical activity in MS (P for interaction=0.002). Compared to the subjects with high physical activity and healthy sleep, OR (95%CI) of MS with poor sleep and high physical activity was 2.03 (1.24-3.33, P for trend=0.016). Conclusion: Poor sleep quality and lack of physical activity are not only independent risk factors for an increased risk of MS but also have a combined effect with an increased risk of MS.
Male ; Humans ; Adult ; Middle Aged ; Sleep Quality ; Metabolic Syndrome/epidemiology* ; Urban Population ; Cross-Sectional Studies ; Prospective Studies ; Exercise

Objective: By identifying different metabolites in the serum and clarifying the potential metabolic disorder pathways in metabolic syndrome (MS) and stable coronary artery disease patients, to evaluate the predictive value of specific metabolites based on serum metabolomics for the occurrence of MS and coronary heart disease in overweight or obese populations. Methods: This is a retrospective cross-sectional study. Patients with Metabolic Syndrome (MS group), patients with stable coronary heart disease (coronary heart disease group), and overweight or obese individuals (control group) recruited from the Central District of the First Affiliated Hospital of Zhengzhou University from 2017 to 2019 were assigned to the training set, meanwhile, the corresponding three groups of people recruited from the East District of the hospital during the same period were assigned to the validation test. The serum metabolomics profiles were determined by ultra-performance liquid chromatography-quadrupole/orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS). Clinical characteristics (age, gender, body mass index (BMI), blood pressure, fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c), alanine aminotransferase (ALT), aspartate transaminase (AST), total cholesterol (TC), triacylglycerol (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), glomerular filtration rate (eGFR), creatinine (CR)) were also collected. Based on the orthogonal partial least-squares discrimination analysis (OPLS-DA) model, the significantly changed metabolites for MS and coronary artery disease patients were screened according to variable important in projection (VIP), and the receiver operating characteristic (ROC) analysis was evaluated for the risk prediction values of changed metabolites. Results: A total of 488 subjects were recruited in this study, the training set included 40 MS, 249 coronary artery disease patients and 148 controls, the validation set included 16 MS, 18 coronary artery disease patients and 17 controls. We made comparisons of the serum metabolites of coronary artery disease vs. controls, MS vs. controls, and coronary artery disease vs. MS, and a total of 22 different metabolites were identified. The disturbed metabolic pathways involved were phospholipid metabolism, amino acid metabolism, purine metabolism and other pathways. Through cross-comparisons, we identified 2 specific metabolites for MS (phosphatidylcholine (18∶1(9Z)e/20) and pipecolic acid), 4 specific metabolites for coronary artery disease (lysophosphatidylcholine (17∶0), PC(16∶0/16∶0), hypoxanthine and histidine), and 4 common metabolites both for MS and coronary artery disease (isoleucine, phenylalanine, glutathione and LysoPC(14∶0)). Based on the cut-off values from ROC curve, the predictive value of the above metabolites for the occurrence of MS in overweight or obese populations is 100%, the predictive value for the occurrence of coronary heart disease is 87.5%, and the risk predictive value for coronary heart disease in MS patients is 82.1%. Conclusions: The altered serum metabolites suggest that MS and coronary heart disease may involve multiple metabolic pathway disorders. Specific metabolites based on serum metabolomics have good predictive value for the occurrence of MS and coronary heart disease in overweight or obese populations.
Humans ; Metabolic Syndrome ; Overweight ; Coronary Artery Disease ; Retrospective Studies ; Cross-Sectional Studies ; Obesity ; Cholesterol, HDL ; Biomarkers

Background: Cardiovascular diseases are the leading causes of deaths among adults in the Philippines, and this is true also among older persons aged 60 years and above. Identification of risk factors and diseases that lead to cardiovascular mortality among the elderly is important to have an impact on longevity. Objective: This study aimed to determine the prevalence of metabolic syndrome and specific cardiovascular risk factors among older persons in the Philippines. Methods: A cross sectional design was used, with data taken from the results of the 8th Philippine National Nutrition Survey (NNS) Clinical and Health Survey done in 2013. Although there is a more recent survey, only the 2013 data is complete and available for secondary analyses. Results: There were 1,835 older persons who were participants in the 8th Philippine NNS who had complete clinical data. The prevalence of Metabolic Syndrome was 52.6% in this population with the distribution of the components as follows: 33.5% have elevated waist circumference; 59.25 had elevated BP >130/85 mm Hg; 30.1% had fasting blood glucose ≥100 mg/dL (includes prediabetes and diabetes); 63% have low HDL, and 39% have elevated triglycerides ≥150 mg/dL. The results for other cardiovascular diseases and risk factors are as follows: 44% had hypertension using the criterion of the JNC VII report (BP ≥140/90 mm Hg); 85% had LDL cholesterol ≥100 mg/dL; 31% are current alcohol drinkers; 22% are current smokers; 53.7% have low physical activity; and 82% have an unhealthy diet. Conclusions Fifty-two percent (52%) of older Filipinos have metabolic syndrome and have a high prevalence of cardiovascular risk factors, foremost of which are elevated LDL-cholesterol at 85%, hypertension at 44% based on JNC VII, approximately 10% with diabetes mellitus, but with a double burden of overweight/obesity and undernutrition. This data can help plan for public health approaches to improve quality of life and increase longevity of Filipinos.
Metabolic Syndrome ; Heart Disease Risk Factors

Background: As the prevalence of metabolic syndrome, obesity and diabetes increase worldwide, the need to identify modifiable lifestyle risk factors also increases, especially those that may be relatively unique to a specific population. To explore a possible association between betel quid chewing and metabolic syndrome, a community-based cross-sectional study was conducted. Methodology: Three hundred ninety-one (391) adults were interviewed and the following parameters were measured: triglycerides, HDL-cholesterol, glucose, waist circumference, body mass index and blood pressure. Multiple logistic regression was used to determine the association between betel quid chewing and metabolic syndrome while controlling for confounders. Results: The prevalence of metabolic syndrome was similar in chewers and non-chewers, 50% and 49%, respectively. After controlling for other factors, development of metabolic syndrome was positively associated with number of betel quid chewed per day, age greater than 40 years , and a positive family history of hypertension and diabetes. Regarding the duration of betel chewing, when analyzed by sex, the risk was doubled in men compared to non-chewers (OR 2.15; 95% CI = 1.21, 3.84]). As a result, a man chewing more than 10 pieces (OR 2.49; 95% CI = 1.36, 4.57]) of betel quids per day for more than 10 years had a two-fold increased chance of developing the metabolic syndrome. Conclusions Frequency and duration of betel quid chewing may represent a behavioral lifestyle target for approaches to reduce the incidence of metabolic syndrome.
Metabolic Syndrome

Animals ; Metabolic Syndrome/therapy* ; Probiotics/therapeutic use* ; Models, Animal