Metabolic syndrome and some of its diagnostic components are independent risk factors for NAFLD.

To assess the clustering of modifiable cardiovascular risk factors among Taiwanese adults, we evaluated 579 healthy participants who underwent health examinations between May and December 2007. Exploratory factor analysis was used to examine risk factor clustering. Smoking, alcohol intake, exercise habits, body mass index, waist circumference, total cholesterol, triglycerides, high- and low-density lipoprotein cholesterol, fasting glucose, uric acid, serum hepatic enzymes, and mean arterial pressure were assessed. Separate factor analyses assessed total and low-density lipoprotein cholesterol. Principal components analysis identified five factors for a model without low-density lipoprotein cholesterol and four factors for a model without total cholesterol. Four common factors in both models explained between 51.1 and 51.8% of variance in the original 14 factors. Metabolic factors, hematological factors (white blood cells and platelets), lifestyle factors (smoking and alcohol consumption), and exercise habits and fasting blood glucose explained about 20, 11, 10, 10% of total variance, respectively. In the model without low-density lipoprotein cholesterol, total cholesterol factor explained 8.83% of variance. This study confirmed clustering of established metabolic syndrome components and revealed additional associated cardiovascular disease risk factors, including lifestyle factors, exercise and total cholesterol, which should be targeted in prevention efforts.

BackgroundThe accuracy and precision of the Friedewald formula for estimating low-density lipoprotein cholesterol (LDL-C) is questionable. Although other formulae have been developed, only a few studies compare them. Thus, we compared the efficiencies of various formulae, based on the age and gender of adults, to determine which ones yield more accurate estimations in terms of mean squared error, and which formulae underestimated and overestimated LDL-C performance.MethodsThis study compares various formulae in terms of mean squared error (MSE), as well as underestimation and overestimation of LDL-C concentrations, using subjects of various ages and both genders. Six groups were examined in this study based on age and gender: males 20–44 years old, 45–64, and 65 and above, and females in the same three age ranges.ResultsThe results show that the Friedewald formula has relatively low accuracy, and while its performance among older (aged 45 and above) women with triglyceride concentrations ≤ 400 mg/dL is better than that with other groups, it is still more inaccurate than the other formulae. In terms of prediction errors and mean squared errors, Tsai’s formula (TF) and a calibrated TF provide the most accurate results with regard to the LDL-C concentration. Moreover, based on a cross-validation of age and gender, these two formulae provide highly accurate results for the LDL-C concentrations of all the studied groups, except for women aged 20–44 years.ConclusionsBased on the experimental results, this study provides a set of benchmarks for the formulae used in LDL-C tests when considering the factors of age and gender. Therefore, it is a valuable method for providing formula benchmarking.

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