Epidemiology & Institute of Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.
[show abstract][hide abstract] ABSTRACT: Factor analysis has emerged as a useful method for understanding patterns underlying the co-occurrence of metabolic risk factors for both type 2 diabetes and atherosclerosis--often referred to as "insulin resistance syndrome." In factor analysis of data on 322 healthy elderly people from the Cardiovascular Health Study, Sakkinen et al. (Am J Epidemiol 2000;152:897-907) confirmed findings from a dozen prior studies that as many as four distinct physiologic domains comprise the syndrome, with a unifying role for markers of insulin resistance. With the addition of markers of hemostasis and inflammation, they also found that impaired fibrinolysis and endothelial dysfunction are central features of the syndrome, while inflammation is only weakly linked to insulin resistance through associations with obesity.
American Journal of Epidemiology 12/2000; 152(10):908-11; discussion 912. · 4.78 Impact Factor
[show abstract][hide abstract] ABSTRACT: Various subclinical disease indicators can be used as an early stage marker of atherosclerosis. Left ventricular (LV) mass has been related to cardiovascular morbidity and mortality. The distribution of LV mass in Chinese is rarely studied and nothing is known about its relationships with various atherosclerotic risk factors in young teenagers, in particular, aspects of lipid profiles. We performed a community-based survey of 523 males and 555 females, aged 12-15, in Chin-Shan, a suburb area near Taipei, Taiwan. LV mass was calculated from the Penn convention. Normalized LV mass by height with power of 2.7 was defined. LV mass and normalized LV mass were significantly greater in males than in females. There were significant positive correlation coefficients between LV mass and age, blood pressure, body mass index, low density lipoprotein cholesterol (LDL-C), apolipoprotein (Apo) B, fasting insulin levels and significant negative correlation coefficients between LV mass and high density lipoprotein cholesterol (HDL-C) and Apo A1 level in both genders. Multiple linear regression models showed gender and body mass index (BMI) were important factors associated with LV mass or normalized values for adolescents. Age and systolic blood pressure were also significant predictors of LV mass, but not of normalized LV mass values. LV mass values were found to be negatively associated with HDL-C values at marginal statistically significant level. Age and BMI are the most significant factors of echocardiographic LV mass distributions in young adolescent in Taiwan. LV mass may also be associated with atherosclerotic risk factors.
[show abstract][hide abstract] ABSTRACT: Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor.
Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models.
The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome.
These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.
Diabetes Care 02/2006; 29(1):113-22. · 7.74 Impact Factor
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