Metabolic and inflammation variable clusters and prediction of type 2 diabetes: Factor analysis using directly measured insulin sensitivity

• Published in: Diabetes (New York, N.Y.) Vol. 53; no. 7; pp. 1773 - 1781
• Main Authors: HARTLEY, Anthony J. G, FESTA, Andreas, D'AGOSTINO, Ralph B, WAGENKNECHT, Lynne E, SAVAGE, Peter J, TRACY, Russell P, SAAD, Mohammed F, HAFFNER, Steven M
• Format: Journal Article
• Language: English
• Published: Alexandria, VA American Diabetes Association 01.07.2004
• Subjects: Adult; African Americans; Aged; Associated diseases and complications; Atherosclerosis; Biological and medical sciences; Blood pressure; Cardiovascular disease; Cardiovascular diseases; Cardiovascular Diseases - etiology; Care and treatment; Diabetes; Diabetes Mellitus, Type 2 - etiology; Diabetes. Impaired glucose tolerance; Endocrine pancreas. Apud cells (diseases); Endocrinopathies; Ethnicity; Etiopathogenesis. Screening. Investigations. Target tissue resistance; European Continental Ancestry Group; Factor Analysis, Statistical; Glucose; Glucose Tolerance Test; Health aspects; Health maintenance organizations; Hispanic Americans; Hispanic people; HMOs; Humans; Inflammation; Inflammation - complications; Insulin; Insulin Resistance; Medical sciences; Metabolic syndrome; Middle Aged; Multivariate Analysis; Physiology; Prospective Studies; Risk Assessment - methods; Risk Factors; Type 2 diabetes; Variables; United States; San Luis Valley; Type 2 diabetes; Endocrinopathy; Pancreatic hormone; Sensitivity; Factor analysis; Prediction; Inflammation; Insulin
• ISSN: 0012-1797; 1939-327X
• DOI: 10.2337/diabetes.53.7.1773

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.