Abstract

Clustering of risk factors for coronary heart disease and diabetes is well established, particularly in relation to insulin resistance. To determine whether evaluation of risk factor clustering will contribute to risk assessment, it is first necessary to discriminate co-association between risk factors from correlation. We undertook this in a large homogenous group, using a sophisticated measure of insulin sensitivity and a broad range of risk factors. Cross-sectional analysis of an occupational cohort using regression and factor analyses was performed. Subjects were 472 apparently healthy white men. The main outcome measures were insulin sensitivity, S I, by minimal model analysis of the intravenous glucose tolerance test plus liver function and hematologic variables, including the inflammation indices, leukocyte count, and erythrocyte sedimentation rate. The S I correlated independently with serum γ-glutamyl transferase (GGT), aspartate transaminase, and alkaline phosphatase activities; blood pressure; leukocyte count; and erythrocyte sedimentation rate ( P < .01). On factor analysis, the factor that explained the greatest proportion of the variance (56.7%) included, in decreasing order of factor loading, triglycerides, S I (negative), body mass index, high-density lipoprotein cholesterol (negative), insulin, uric acid, and GGT activity (loadings >0.40). Mean arterial pressure was not a feature (loading 0.29), neither were indices of subclinical inflammation. In apparently healthy men, blood pressure and indices of subclinical inflammation do not cluster with other insulin resistance–related risk factors, despite correlating with insulin sensitivity. In contrast, both GGT activity and uric acid concentrations correlated with insulin sensitivity and co-associated with insulin resistance–related risk factors and are therefore components of a true risk factor cluster.

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