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An Accurate Risk Score Based on Anthropometric, Dietary, and Lifestyle Factors to Predict the Development of Type 2 Diabetes

¹ Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
² Division of Clinical Epidemiology, German Cancer Research Center, Heidelberg, Germany
³ Department of Clinical Nutrition, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
⁴ Department of Endocrinology, Diabetes and Nutrition, Charite-University Medicine Berlin, Berlin, Germany
⁵ Department of Internal Medicine IV, University of Tübingen, Tübingen, Germany
⁶ Department of Pharmacology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany

Address correspondence and reprint requests to Matthias B. Schulze, German Institute of Human Nutrition Potsdam-Rehbruecke, Department of Epidemiology, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany. E-mail: mschulze{at}dife.de

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 (TÜF), 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 TÜF and –0.45 in the MeSyBePo studies. ROC values for undiagnosed diabetes were 0.83 in the TÜF 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.

Abbreviations: AUC, area under the curve • ARIC, Atherosclerosis Risk in Communities • EPIC, European Prospective Investigation into Cancer and Nutrition • MeSyBePo, Metabolic Syndrome Berlin Potsdam • OGTT, oral glucose tolerance test • ROC, receiver-operator characteristic • TÜF, Tübingen Family Study for Type 2 Diabetes

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