Insulin resistance has been hypothesized to unify the clustering of hypertension, glucose intolerance, hyper-insulinemia, increased levels of triglyceride and decreased HDL cholesterol, and central and overall obesity. We tested this hypothesis with factor analysis, a statistical technique that should identify one factor if a single process underlies the clustering of these risk variables. From 2,458 nondiabetic subjects of the Framingham Offspring Study, we collected clinical data, fasting and 2-h postchallenge glucose and insulin levels, and fasting lipid levels. We performed factor analyses separately for men and women in the entire population and among subgroups with features of the insulin resistance syndrome. Subjects ranged in age from 26 to 82 years (mean age 54); 53% were women, 13.4% had impaired glucose tolerance, 27.6% had hypertension, 40% were obese, and 11.6% were hyperinsulinemic, defined by elevated fasting insulin levels. Underlying the clustering of these risk variables were three factors. Fasting and 2-h postchallenge insulin levels, fasting triglyceride and HDL cholesterol levels, BMI, and waist-to-hip ratio were associated with one factor. Fasting and 2-h levels of glucose and insulin were associated with a second factor. Systolic blood pressure, diastolic blood pressure, and BMI were associated with a third factor. Results were similar for men and women and for all subgroups. These results were consistent with more than one independent physiological process underlying risk variable clustering: a central metabolic syndrome (characterized by hyperinsulinemia, dyslipidemia, and obesity), glucose intolerance, and hypertension. Glucose intolerance and hypertension were linked to the central syndrome through shared correlations with insulin levels and obesity. Insulin resistance (reflected by hyperinsulinemia) alone did not appear to underlie all features of the insulin resistance syndrome.
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Original Articles|
October 01 1997
Risk Variable Clustering in the Insulin Resistance Syndrome: The Framingham Offspring Study
James B Meigs;
James B Meigs
General Internal Medicine Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School
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Ralph B D'Agostino, Sr;
Ralph B D'Agostino, Sr
Department of Mathematics, Statistics, and Consulting Unit, Boston University
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Peter WF Wilson;
Peter WF Wilson
Framingham Heart Study, National Heart, Lung and Blood Institute, National Institutes of Health
Framingham, Massachusetts
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L Adrienne Cupples;
L Adrienne Cupples
Department of Epidemiology and Biostatistics, Boston University School of Public Health and School of Medicine
Boston
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David M Nathan;
David M Nathan
Diabetes Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School
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Daniel E Singer
Daniel E Singer
General Internal Medicine Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School
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Address correspondence and reprint requests to James B. Meigs, MD MPH, General Internal Medicine Unit S50-9, Massachusetts General Hospital, Boston, MA 02114. E-mail: [email protected]
Diabetes 1997;46(10):1594–1600
Article history
Received:
March 18 1997
Revision Received:
June 20 1997
Accepted:
June 20 1997
PubMed:
9313755
Citation
James B Meigs, Ralph B D'Agostino, Peter WF Wilson, L Adrienne Cupples, David M Nathan, Daniel E Singer; Risk Variable Clustering in the Insulin Resistance Syndrome: The Framingham Offspring Study. Diabetes 1 October 1997; 46 (10): 1594–1600. https://doi.org/10.2337/diacare.46.10.1594
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