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Refined Definition of Metabolic Syndrome Better Predicts Future Diabetes

Dec 5, 2006
 

A newly validated definition of metabolic syndrome that uses continuous rather than categorical variables has better predictive power for future diabetes. "The diagnosis of the metabolic syndrome should not be managed as a categorical variable; a ‘yes or no’ approach is not valid in chronic-degenerative disorders such as this," Dr. Rosalba Rojas told Reuters Health. A continuous variable concept "results in a group of subjects with a spectrum of long-term risk for having the final outcomes."

Dr. Rojas from the National Institute of Public Health, Cuernavaca, Morelos, Mexico and colleagues developed a definition that gave one point per population decile for every component of the National Cholesterol Education Program (NCEP) definition of the metabolic syndrome, and tested the ability of the definition to predict diabetes in a Hispanic population.

More than 60% of the patients identified by NCEP criteria as having metabolic syndrome were in the upper quintile of the new definition’s scale, the authors report. However, 147 of 559 individuals in the upper quintile had an adverse metabolic profile but met only two NCEP criteria.

"Therefore," the investigators assert, "the population-based method provides complementary information for individuals with no more than 2 NCEP components."

The prevalence of hyperinsulinemia increased as the total number of points increased, the results indicate, and the incidence of diabetes was directly proportional to the total number of points accumulated.

"The clinical application of our method may be limited by the necessity for a decile distribution of the variables," the researchers admit. "The main value of this report may be in research studies."

Meanwhile, "a large cohort study is under way to assess the performance of our definition (and other prognostic scales) for the prediction of cardiovascular outcomes," Dr. Rojas said. "In addition, we are applying our population-based definition in several genetic studies designed to identify type 2 diabetes susceptibility genes."

Diabetes Care 2006;29:2420-2426.