Estimating prevalence of type 1 and type 2 diabetes in a population of African Americans with diabetes mellitus.

Abstract

The pathogenesis, treatment, and outcomes of type 1 and type 2 diabetes differ. Current surveys derive population-based estimates of diabetes prevalence by type using limited clinical information and applying classification rules developed in white populations. How well these rules perform when deriving similar estimates in African American populations is unknown. For this study, data were collected on a group of African Americans with diabetes who enrolled at the Diabetes Unit of Grady Memorial Hospital in Atlanta, Georgia, from April 16, 1991, to November 1, 1996. The data were used to develop some simple classification rules for African Americans based on a classification tree and a logistic regression model. Sensitivities and specificities, in which fasting C-peptide was used as the gold standard, were determined for these rules and for two current rules developed in mostly white, non-Hispanic populations. Rules that yielded precise (minimum variance unbiased) estimates of the prevalence of type 1 diabetes were preferred. The authors found that a rule based on the logistic regression model was best for estimating type 1 prevalences ranging from 1% to 17%. They concluded that simple classification rules can be used to estimate prevalence of diabetes by type in African American populations and that the optimal rule differs somewhat from the current rules.