Components of the “Metabolic Syndrome” and Incidence of Type 2 Diabetes

Abstract

The combination of insulin resistance, dyslipidemia, hypertension, and obesity has been described as a "metabolic syndrome" that is a strong determinant of type 2 diabetes. Factor analysis was used to identify components of this syndrome in 1,918 Pima Indians. Prospective analyses were conducted to evaluate associations of identified factors with incidence of diabetes. Factor analysis identified 4 factors that accounted for 79% of the variance in the original 10 variables. Each of these factors reflected a proposed component of the metabolic syndrome: insulinemia, body size, blood pressure, and lipid metabolism. Among 890 originally nondiabetic participants with follow-up data, 144 developed diabetes in a median follow-up of 4.1 years. The insulinemia factor was strongly associated with diabetes incidence (incidence rate ratio [IRR] for a 1-SD difference in factor scores ‫؍‬ 1.81, P < 0.01). The body size and lipids factors also significantly predicted diabetes (IRR 1.52 and 1.37, respectively, P < 0.01 for both), whereas the blood pressure factor did not (IRR 1.11, P ‫؍‬ 0.20). Identification of four unique factors with different associations with incidence of diabetes suggests that the correlations among these variables reflect distinct metabolic processes, about which substantial information may be lost in the attempt to combine them into a single entity. Diabetes 51:3120 -3127, 2002 T ype 2 diabetes and cardiovascular disease have many risk factors in common, and many of these risk factors are highly correlated with one another (1-3). The relationships among these risk factors may be attributable to a small number of physiological phenomena, perhaps even a single phenomenon. The combination of hypertension, dyslipidemia, insulin resistance, hyperinsulinemia, glucose intolerance, and obesity, particularly central obesity, has been termed the "metabolic syndrome." It has been proposed that this syndrome is a powerful determinant of diabetes and cardiovascular disease (3-6). There are few prospective data, however, on the extent to which this syndrome or its constituent components predict incidence of type 2 diabetes.Factor analysis is a mathematical technique by which a large number of correlated variables can be reduced to fewer "factors" that represent distinct attributes that account for a large proportion of the variance in the original variables. Thus, factor analysis is well suited for identifying components of the metabolic syndrome, and several analyses have been undertaken for this purpose (7-26). Prospective epidemiological studies of factor "scores" from these analyses can further determine relations between components of the metabolic syndrome and incidence of diabetes. In the present study, factor analysis is used to identify components of the metabolic syndrome in Pima Indians, an American Indian population with a high prevalence of type 2 diabetes and obesity (27,28), and relations of these components to incidence of diabetes are examined. RESEARCH DESIGN AND METHODSParticipants and measurements...

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