Factor analysis, a multivariate correlation technique, has been used to provide insight into the underlying structure of the
metabolic syndrome. The majority of previous factor analyses, however, have used only surrogate measures of
insulin sensitivity; very few have included nontraditional
cardiovascular disease (CVD) risk factors such as
plasminogen activator inhibitor (PAI)-1,
fibrinogen, and
C-reactive protein (CRP); and only a limited number have assessed the ability of factors to predict
type 2 diabetes. The objective of this study was to investigate, using factor analysis, the clustering of metabolic and
inflammation variables using data from 1,087 nondiabetic participants in the
Insulin Resistance Atherosclerosis Study (IRAS) and to determine the association of these clusters with risk of
type 2 diabetes at follow-up. This study includes information on directly measured
insulin sensitivity (S(i)) from the frequently sampled intravenous
glucose tolerance test among African-American, Hispanic, and non-Hispanic white subjects aged 40-69 years. Principal factor analysis of data from nondiabetic subjects at baseline (1992-1994) identified three factors, which explained 28.4, 7.4, and 6% of the total variance in the dataset, respectively. Based on factor loadings of >or= 0.40, these factors were interpreted as 1) a "metabolic" factor, with positive loadings of BMI, waist circumference, 2-h
glucose, log
triglyceride, and log PAI-1 and inverse loadings of log S(i) + 1 and
HDL; 2) an "
inflammation" factor, with positive loadings of BMI, waist circumference,
fibrinogen, and log CRP and an inverse loading of log S(i) + 1; and 3) a "blood pressure" factor, with positive loadings of systolic and diastolic blood pressure. The results were similar within strata of ethnicity, and there were only subtle differences in sex-specific analyses. In a prospective analysis, each of the factors was a significant predictor of diabetes after a median follow-up period of 5.2 years, and each factor remained significant in a multivariate model that included all three factors, although this three-factor model was not significantly more predictive than models using either
impaired glucose tolerance or conventional CVD risk factors. Factor analysis identified three underlying factors among a group of
inflammation and
metabolic syndrome variables, with
insulin sensitivity loading on both the metabolic and
inflammation variable clusters. Each factor significantly predicted diabetes in multivariate analysis. The findings support the emerging hypothesis that chronic subclinical
inflammation is associated with
insulin resistance and comprises a component of the
metabolic syndrome.