An accurate risk score based on anthropometric, dietary, and lifestyle factors to predict the development of type 2 diabetes

Abstract

Objective: We aimed to develop a precise risk score for the screening of large populations for individuals at high risk of developing type 2 diabetes based on noninvasive measurements of major risk factors in German study populations.

Research design and methods: A prospective cohort study (European Prospective Investigation into Cancer and Nutrition [EPIC]-Potsdam study) of 9,729 men and 15,438 women aged 35-65 years was used to derive a risk score predicting incident type 2 diabetes. Multivariate Cox regression model coefficients were used to weigh each variable in the calculation of the score. Data from the EPIC-Heidelberg, the Tübingen Family Study for Type 2 Diabetes (TUF), and the Metabolic Syndrome Berlin Potsdam (MeSyBePo) study were used to validate this score.

Results: Information on age, waist circumference, height, history of hypertension, physical activity, smoking, and consumption of red meat, whole-grain bread, coffee, and alcohol formed the German Diabetes Risk Score (mean 446 points [range 118-983]). The probability of developing diabetes within 5 years in the EPIC-Potsdam study increased from 0.3% for 300 to 23.2% for 750 score points. The area under the receiver-operator characteristic (ROC) curve was 0.84 in the EPIC-Potsdam and 0.82 in the EPIC-Heidelberg studies. Correlation coefficients between the German Diabetes Risk Score and insulin sensitivity in nondiabetic individuals were -0.56 in the TUF and -0.45 in the MeSyBePo studies. ROC values for undiagnosed diabetes were 0.83 in the TUF and 0.75 in the MeSyBePo studies.

Conclusions: The German Diabetes Risk Score (available at www.dife.de) is an accurate tool to identify individuals at high risk for or with undiagnosed type 2 diabetes.