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Diabetes Care. 2005 Aug;28(8):2013-8.

Identifying individuals at high risk for diabetes: The Atherosclerosis Risk in Communities study.

Author information

  • 1Graduate Studies Program in Epidemiology, School of Medicine, Federal University of Rio Grande do Sul, Porto Alegre, Brazil. mischmidt@orion.ufrgs.br

Abstract

OBJECTIVE:

To develop and evaluate clinical rules to predict risk for diabetes in middle-aged adults.

RESEARCH DESIGN AND METHODS:

The Atherosclerosis Risk in Communities is a cohort study conducted from 1987-1989 to 1996-1998. We studied 7,915 participants 45-64 years of age, free of diabetes at baseline, and ascertained 1,292 incident cases of diabetes by clinical diagnosis or oral glucose tolerance testing.

RESULTS:

We derived risk functions to predict diabetes using logistic regression in a random half of the sample. Rules based on these risk functions were evaluated in the other half. A risk function based on waist, height, hypertension, blood pressure, family history of diabetes, ethnicity, and age was performed similarly to one based on fasting glucose (area under the receiver-operating characteristic curve [AUC] 0.71 and 0.74, respectively; P = 0.2). Risk functions composed of the clinical variables plus fasting glucose (AUC 0.78) and additionally including triglycerides and HDL cholesterol (AUC 0.80) performed better (P < 0.001). Evaluation of scores based on the metabolic syndrome as defined by the National Cholesterol Education Program or with slight variations showed AUCs of 0.75 and 0.78, respectively. Rules based on all these approaches, while identifying 20-56% of the sample as screen positive, achieved sensitivities of 40-87% and specificities of 50-86%.

CONCLUSIONS:

Rules derived from clinical information, alone or combined with simple laboratory measures, can characterize degrees of diabetes risk in middle-aged adults, permitting preventive actions of appropriate intensity. Rules based on the metabolic syndrome are reasonable alternatives to rules derived from risk functions.

PMID:
16043747
[PubMed - indexed for MEDLINE]
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