Fasting triglyceride is a major determinant of postprandial triglyceride response in postmenopausal women.

OBJECTIVE: The purpose of the study was to examine the relative influences of fasting lipids, insulin resistance, and waist circumference (WC) on postprandial lipemia in postmenopausal women. DESIGN: Forty-nine naturally postmenopausal women were recruited for the study. Each woman underwent a 75-g oral glucose tolerance test to measure insulin resistance and a 1,000-kcal high-fat mixed meal test for postprandial triglyceride (TG) response. RESULTS: The participants were divided into three groups by tertiles of incremental TG response in the mixed meal test. The three groups were comparable in weight, WC, and fasting high-density lipoprotein cholesterol (HDL-C) levels. There were significant differences in fasting TG and non-HDL-C concentrations among the three groups. The women in the high-tertile group were more insulin resistant than those in the low-tertile group, indicated by higher homeostasis model assessment for insulin resistance (HOMA-IR) values. The postprandial TG response was significantly correlated with Log(fasting TG), fasting non-HDL-C and Log(HOMA-IR), but not with WC, in univariate regression analyses. Log(fasting TG) was the only variable that remained significantly related to incremental TG response when all the above were entered into multiple regression models. Subsequently, we found that Log(HOMA-IR) and fasting non-HDL-C independently predicted the variance of Log(fasting TG) in stepwise multiple regression. CONCLUSIONS: Our data demonstrated that the fasting TG level is a major determinant of postprandial TG response in postmenopausal women. Insulin resistance and non-HDL-C may contribute independently to the fasting TG level. The influences of WC on postprandial lipemia seemed to be insignificant.

Is hyperuricemia another facet of the metabolic syndrome?

BACKGROUND: Hyperuricemia is commonly associated with obesity, glucose intolerance, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. The resemblance of the metabolic syndrome and hyperuricemia has led to the suggestion that hyperuricemia is a part of the metabolic syndrome. The purpose of this study is to examine the contribution of uric acid (UA) as an additional component of the metabolic syndrome in middle-aged men. METHODS: In total, 393 male participants, aged 45-60 years, were recruited from a professional health evaluation program. Anthropometric measurements and blood pressure (BP) were taken after an overnight fast. Fasting blood samples were collected for the measurements of glucose, UA, and lipid profile. Logistic regression models were fitted to examine the relationship between UA and the diagnosis of metabolic syndrome. Factor analysis was performed to explore the relationship between UA and the components of the metabolic syndrome. RESULTS: The diagnosis of the metabolic syndrome was significantly associated with waist circumference (WC), glucose, triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), systolic BP, and liver enzyme levels, but not associated with UA levels. The sensitivity of hyperuricemia (serum UA > or = 7.0 mg/dL) for the diagnosis of the metabolic syndrome was 58.0% and the specificity was 55.3%. In factor analysis, UA aggregated with body mass index, WC, glucose, log TG, and HDL-C as a metabolic factor. Systolic and diastolic BP were loaded on a second factor separately. The model loaded with UA explained a similar proportion of the total variance (56.9%), as did the model loaded without UA (62.5%). CONCLUSION: Our results suggest that the contribution of UA as an additional component of the syndrome seems to be insignificant. We propose that hyperuricemia might not be an important facet for the understanding of the underlying structure of the metabolic syndrome.