Simple model predicts diabetes in middle-age

NEW YORK, June 14 (Reuters)- Obesity, other cardiovascular risk factors and parents with diabetes predict the development of type 2 diabetes in middle-aged adults, according to findings published in the Archives of Internal Medicine.

''Prediction of chronic conditions like type 2 diabetes mellitus that have a definable onset can help to guide interventions and healthy policy development,'' Dr. Peter W. F. Wilson, of Emory University School of Medicine, A tlanta, and colleagues write.

''Prediction rules for type 2 diabetes have been developed, but we lack consensus for the most effective approach.'' In the current study, the researchers estimated the 7-year risk of type 2 diabetes in 3,140 middle-age subjects who were an average of 54 years old. Most subjects were overweight, but not obese, and 12.7 per cent had impaired glucose tolerance at the beginning of the study, indicating ''pre-diabetic'' blood sugar irregularities.

There were160 cases of new type 2 diabetes. Using a number of parameters, the team developed prediction models for type 2 diabetes that started simply and progressed to greater levels of complexity.

They started with a personal model using characteristics known to each subject (age, sex, weight, height and parental history of diabetes).

They then developed a clinical model by adding measurements such as metabolic syndrome traits. The metabolic syndrome is a cluster of conditions, including overweight or obesity, high blood pressure and high cholesterol, which increase the risk of having a cardiovascular event, such as a heart attack.

Finally, the researchers developed complex clinical models that included all of the previous elements plus a variety of tests, such as the 2-hour post-oral glucose tolerance test, fasting insulin, C-reactive protein levels and the Gutt insulin sensitivity index.

The personal model variables, with the exception of sex, were significantly predictive of type 2 diabetes, the researchers report.

Parental history of diabetes and obesity remained significant predictors in the simple clinical model.

No further improvements were provided by the complex clinical models in predicting diabetes risk.

''We found that complex models are not needed to predict type 2 diabetes and that information from a typical clinic visit adds to type 2 diabetes prediction beyond personal awareness of diabetes risk factors,'' Wilson's team concludes.

''The simple clinical model we developed should be tested in other population samples to validate our approach, as has been done for prediction of coronary heart disease events.'' REUTERS SG VC1006