Factor Analysis of Metabolic Syndrome Using Directly Measured Insulin Sensitivity
The Insulin Resistance Atherosclerosis Study
- Anthony J.G. Hanley12,
- Andrew J. Karter3,
- Andreas Festa1,
- Ralph D’Agostino, Jr.4,
- Lynne E. Wagenknecht4,
- Peter Savage5,
- Russell P. Tracy6,
- Mohammed F. Saad7 and
- Steven Haffner1
- 1Division of Clinical Epidemiology, University of Texas Health Sciences Center at San Antonio, San Antonio, Texas
- 2Division of Epidemiology and Biostatistics, Samuel Lunenfeld Research Institute, Mt. Sinai Hospital, Toronto, Canada
- 3Division of Research, Kaiser Permanente, Oakland, California
- 4Department of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, North Carolina
- 5Division of Epidemiology and Clinical Applications, National Heart, Lung and Blood Institute, Bethesda, Maryland
- 6Departments of Pathology and Biochemistry, College of Medicine, University of Vermont, Burlington, Vermont
- 7Department of Medicine, University of Southern California School of Medicine, Los Angeles, California
Abstract
Factor analysis, a multivariate correlation technique, has been used to provide insight into the underlying structure of metabolic syndrome, which is characterized by physiological complexity and strong statistical intercorrelation among its key variables. The majority of previous factor analyses, however, have used only surrogate measures of insulin sensitivity. In addition, few have included members of multiple ethnic groups, and only one has presented results separately for subjects with impaired glucose tolerance. The objective of this study was to investigate, using factor analysis, the clustering of physiologic variables using data from 1,087 nondiabetic participants in the Insulin Resistance Atherosclerosis Study (IRAS). This study includes information on the directly measured insulin sensitivity index (SI) from intravenous glucose tolerance testing among African-American, Hispanic, and non-Hispanic white subjects aged 40–69 years at various stages of glucose tolerance. Principal factor analysis identified two factors that explained 28 and 9% of the variance in the dataset, respectively. These factors were interpreted as 1) a “ metabolic” factor, with positive loadings of BMI, waist, fasting and 2-h glucose, and triglyceride and inverse loadings of log(SI+1) and HDL; and 2) a “blood pressure” factor, with positive loadings of systolic and diastolic blood pressure. The results were unchanged when surrogate measures of insulin resistance were used in place of log(SI+1). In addition, the results were similar within strata of sex, glucose tolerance status, and ethnicity. In conclusion, factor analysis identified two underlying factors among a group of metabolic syndrome variables in this dataset. Analyses using surrogate measures of insulin resistance suggested that these variables provide adequate information to explore the underlying intercorrelational structure of metabolic syndrome. Additional clarification of the physiologic characteristics of metabolic syndrome is required as individuals with this condition are increasingly being considered candidates for behavioral and pharmacologic intervention.
Footnotes
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Address correspondence and reprint requests to Dr. Steven Haffner, Division of Clinical Epidemiology, University of Texas Health Science Center at San Antonio, mail code 7873, 7703 Floyd Curl Dr., San Antonio, TX 78229-3900. E-mail: haffner{at}uthscsa.edu.
Received for publication 6 January 2002 and accepted in revised form 9 May 2002.
R.P.T. has been on advisory panels for Monsanto/Seale, Bio-Tek, and Dade/Behring; holds stock in COR Therapeutics and Haematologic Technologies; has received honoraria and/or consulting fees from Genentech, Pfizer, Merck, Parke-Davis, Bristol-Myers Squibb, Wyeth-Ayerst, Organon, Diagnostic Products, and Diagnostica Stago; and has received grant/research support from Eli Lilly, Genentech, Bristol-Myers Squibb, Unilever, and Pfizer.
FSIGTT, frequently sampled intravenous glucose tolerance test; HOMA-IR, homeostasis model assessment index of insulin resistance; IGT, impaired glucose tolerance; IRAS, Insulin Resistance Atherosclerosis Study; NGT, normal glucose tolerance; SI, insulin sensitivity index.
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