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AIMS/HYPOTHESIS: We compared the ability of genetic (established type 2 diabetes, fasting glucose, 2 h glucose and obesity variants) and modifiable lifestyle (diet, physical activity, smoking, alcohol and education) risk factors to predict incident type 2 diabetes and obesity in a population-based prospective cohort of 3,444 Swedish adults studied sequentially at baseline and 10 years later. METHODS: Multivariable logistic regression analyses were used to assess the predictive ability of genetic and lifestyle risk factors on incident obesity and type 2 diabetes by calculating the AUC. RESULTS: The predictive accuracy of lifestyle risk factors was similar to that yielded by genetic information for incident type 2 diabetes (AUC 75% and 74%, respectively) and obesity (AUC 68% and 73%, respectively) in models adjusted for age, age(2) and sex. The addition of genetic information to the lifestyle model significantly improved the prediction of type 2 diabetes (AUC 80%; p = 0.0003) and obesity (AUC 79%; p < 0.0001) and resulted in a net reclassification improvement of 58% for type 2 diabetes and 64% for obesity. CONCLUSIONS/INTERPRETATION: These findings illustrate that lifestyle and genetic information separately provide a similarly high degree of long-range predictive accuracy for obesity and type 2 diabetes.

Original publication




Journal article



Publication Date





462 - 471


Environment, Genes, Obesity, Predictors, Type 2 diabetes, Blood Glucose, Diabetes Mellitus, Type 2, Exercise, Humans, Life Style, Logistic Models, Obesity, Prospective Studies