METHODS: Six hundred and thirty-six adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from two independent Asian cohorts were enrolled in our study. Liver stiffness measurement (LSM) was assessed by vibration-controlled transient elastography (Fibroscan). Fibrotic NASH was defined as NASH with a NAFLD activity score (NAS) ≥ 4 and F ≥ 2 fibrosis.
RESULTS: Metabolic syndrome (MetS), platelet count and MACK-3 were independent predictors of fibrotic NASH. On the basis of their regression coefficients, we developed a novel nomogram showing a good discriminatory ability (area under receiver operating characteristic curve [AUROC]: 0.79, 95% confidence interval [CI 0.75-0.83]) and a high negative predictive value (NPV: 94.7%) to rule out fibrotic NASH. In the validation set, this nomogram had a higher AUROC (0.81, 95%CI 0.74-0.87) than that of MACK-3 (AUROC: 0.75, 95%CI 0.68-0.82; P
CONCLUSION: In this review, we will discuss the possible mechanisms which may relate the association between MetS and cognitive decline which include vascular damages, elevation of reactive oxygen species (ROS), insulin resistance and low-grade inflammation.
MATERIALS AND METHODS: This cross sectional study involved 123 subjects from Temiar subtribe in Kuala Betis, Gua Musang, Kelantan. MetS criteria were measured according to standard protocol by modified National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) guideline. Anthropometric and biochemical measurements were performed including serum adiponectin and resistin for every study subjects.
RESULTS: Serum adiponectin was significantly lower in MetS subjects (7.98 ± 5.65 ng/ml) but serum resistin was found to be significantly higher in MetS subjects (11.22 ± 6.34 ng/ml) compared to non-MetS subjects with p
METHODS AND RESULTS: Blood pressures, fasting lipid profile and fasting glucose were measured, and DASH score was computed based on a 22-item food frequency questionnaire. Older individuals, women, those not consuming alcohol and those undertaking regular physical activity were more likely to have higher DASH scores. In the Malaysian cohort, while total DASH score was not significantly associated with cardio-metabolic risk factors after adjusting for confounders, significant associations were observed for intake of green vegetable [0.011, standard error (SE): 0.004], and red and processed meat (-0.009, SE: 0.004) with total cholesterol. In the Philippines cohort, a 5-unit increase in total DASH score was significantly and inversely associated with systolic blood pressure (-1.41, SE: 0.40), diastolic blood pressure (-1.09, SE: 0.28), total cholesterol (-0.015, SE: 0.005), low-density lipoprotein cholesterol (-0.025, SE: 0.008), and triglyceride (-0.034, SE: 0.012) after adjusting for socio-demographic and lifestyle groups. Intake of milk and dairy products, red and processed meat, and sugared drinks were found to significantly associated with most risk factors.
CONCLUSIONS: Differential associations of DASH diet and dietary components with cardio-metabolic risk factors by country suggest the need for country-specific tailoring of dietary interventions to improve cardio-metabolic risk profiles.
METHODS: Using a randomized, crossover and double-blinded design, 15 men and 15 women with metabolic syndrome consumed high-fat meals enriched with SFA, MUFA or n-6 PUFA, or a low-fat/high-sucrose (SUCR) meal. C-peptide, insulin, glucose, gastrointestinal peptides and satiety were measured up to 6 h.
RESULTS: As expected, SUCR meal induced higher C-peptide (45 %), insulin (45 %) and glucose (49 %) responses compared with high-fat meals regardless of types of fatty acids (P < 0.001). Interestingly, incremental area under the curve (AUC0-120min) for glucagon-like peptide-1 was higher after SUCR meal compared with MUFA (27 %) and n-6 PUFA meals (23 %) (P = 0.01). AUC0-120min for glucose-dependent insulinotropic polypeptide was higher after SFA meal compared with MUFA (23 %) and n-6 PUFA meals (20 %) (P = 0.004). Significant meal x time interaction (P = 0.007) was observed for ghrelin, but not cholecystokinin and satiety.
CONCLUSIONS: The amount of fat regardless of the types of fatty acids affects insulin and glycemic responses. Both the amount and types of fatty acids acutely affect the gastrointestinal peptide release in metabolic syndrome subjects, but not satiety.
SUBJECTS/METHODS: Thirty metabolic syndrome subjects (15 men and 15 women) were recruited to a randomized, double-blinded and crossover study. The subjects were administered a single dose of 200 mg or 400 mg γδ-T3 emulsions or placebo incorporated into a glass of strawberry-flavored milkshake, consumed together with a high-fat muffin. Blood samples were collected at 0, 5, 15, 30, 60, 90, 120, 180, 240, 300 and 360 min after meal intake.
RESULTS: Plasma vitamin E levels reflected the absorption of γδ-T3 after treatments. Postprandial changes in serum C-peptide, serum insulin, plasma glucose, triacylglycerol, non-esterified fatty acid and adiponectin did not differ between treatments, with women displaying delayed increase in the aforementioned markers. No significant difference between treatments was observed for plasma cytokines (interleukin-1 beta, interleukin-6 and tumor necrosis factor alpha) and thrombogenic markers (plasminogen activator inhibitor type 1 and D-dimer).
CONCLUSIONS: Supplementation of a single dose of γδ-T3 did not change the insulinemic, anti-inflammatory and anti-thrombogenic responses in metabolic syndrome subjects.
METHODS: Data from the first wave Malaysian Elders Longitudinal Research (MELoR) study comprising urban dwellers aged 55 years and above were utilized. Twelve-month fall histories were established during home-based, computer-assisted interviews which physical performance, anthropometric and laboratory measures were obtained during a hospital-based health check. Gait speed, exhaustion, weakness, and weight loss were employed as frailty markers.
RESULTS: Data were available for 1415 participants, mean age of 68.56 ± 7.26 years, 57.2% women. Falls and metabolic syndrome were present in 22.8% and 44.2%, respectively. After adjusting for age, sex, and multiple comorbidities, metabolic syndrome was significantly associated with falls in the sample population [odds ratio (OR): 1.33, 95% confidence interval (CI): 1.03; 1.72]. This relationship was attenuated by the presence of slow gait speed, but not exhaustion, weakness, or weight loss.
CONCLUSION: Metabolic syndrome was independently associated with falls among older adults, and this relationship was accounted for by the presence of slow gait speed. Future studies should determine the value of screening for frailty and falls with gait speed in older adults with metabolic syndrome as a potential fall prevention measure.