Simple Tool Predicts Diabetes Risk

Doctors can use basic information, like body weight and waist size, to identify individuals at high risk of developing diabetes within 10 years, and adding some lab test values identifies those at very high risk.

U.S. researchers report the development of the two risk scoring systems in the latest issue of Annals of Internal Medicine.

Use of these two scoring systems "would help to bring adults at greatest need into appropriate modes of preventive care," Dr. Henry S. Kahn and colleagues from the Centers for Disease Control and Prevention, Atlanta, Georgia, write.

"Perhaps the most appealing feature of our two scoring systems," they note, "is their ease of use in a clinical or public health setting." An individual's risk score can be calculated "using only a pencil and paper."

The scoring systems were derived and validated using nearly 15 years of long-term data from 12,729 adults who were between 45 and 64 years old when they entered a research study. Nearly 19 percent of them developed diabetes at some point during follow-up.

The basic scoring system includes increased body weight and waist circumference, age 55 or older, black race, short stature, high blood pressure, rapid pulse, smoking history, and family history of diabetes.

The enhanced scoring system includes these same variables plus high blood sugar and abnormal results on other analytes commonly assessed in a fasting blood sample such as cholesterol levels and uric acid levels.

According to the investigators, ascending "quintiles" of the basic system were associated with a 10-year incidence of diabetes of 5.3 percent, 8.7 percent, 15.5 percent, 24.5 percent and 33.0 percent, respectively.

Ascending quintiles of the enhanced system were associated with a 10-year incidence of 3.5 percent, 6.4 percent, 11.5 percent, 19.3 percent, and 46.1 percent, respectively.

In a commentary published with the study, Dr. William H. Herman of the University of Michigan, Ann Arbor, notes that the proposed scoring systems "clearly advance the cause of identifying persons at risk for diabetes who are likely to benefit from focused clinical interventions."