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Diabetes 51:3069-3076, 2002
© 2002 by the American Diabetes Association, Inc.

Risk Factor Groupings Related to Insulin Resistance and Their Synergistic Effects on Subclinical Atherosclerosis

The Atherosclerosis Risk in Communities Study

Sherita Hill Golden1, Aaron R. Folsom2, Josef Coresh3, A. Richey Sharrett4, Moyses Szklo3, and Frederick Brancati1,3

1 Department of Medicine, the Johns Hopkins Medical Institutions, Baltimore, Maryland
2 Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis, Minnesota
3 Department of Epidemiology, the Johns Hopkins Medical Institutions, Baltimore, Maryland
4 National Heart, Lung, and Blood Institute, Bethesda, Maryland

The extent to which groupings of insulin resistance-related cardiovascular risk factors synergize to produce atherosclerosis beyond what is expected from their additive effects is uncertain. The objective of this study was to measure interactions among groupings of the features of the insulin resistance syndrome (IRS) on carotid intimal-medial thickness (IMT). This cross-sectional study used baseline data from the Atherosclerosis Risk in Communities Study on 11,790 adults aged 45–64 years without diagnosed diabetes, treated dyslipidemia, or coronary heart disease. The main outcome was carotid IMT, assessed using B-mode ultrasound. The excess carotid IMT attributable to each IRS grouping was determined using multiple linear regression models. There were 57 possible combinations of six IRS components (hypertension, hyperinsulinemia, obesity, hypertriglyceridemia, low HDL cholesterol, and hyperglycemia). In multivariate analysis, 29 of the 57 groupings were associated with excess carotid IMT. Individuals with all six IRS components had the greatest excess IMT compared with those without this grouping (71 µm; 95% CI 40–102 µm). The groupings most strongly associated with excess carotid IMT included hypertension and hypertriglyceridemia. Interventions aimed at ameliorating the IRS may produce reductions in atherosclerotic risk beyond that predicted by treatment of individual IRS-related risk factors.



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