AzoresDiab model: the risk prediction of type 2 diabetes in the Azores

Abstract

Introduction: The incidence of type 2 diabetes mellitus is increasing in the Azores. The Azorean population has unique health-related characteristics that emphasize the necessity of developing a predictive model, namely the double insularity phenomena and consanguinity marriages. Therefore, the authors aimed to develop a model, the AzoresDiab model, that assesses the risk of type 2 diabetes for residents of the Azores. Methods: The variables used for developing the model included the history of cardiovascular disease, hypertension, sex, body mass index, triacylglycerol level, glucose level, and age. This model was developed using binary logistic regression wherein the dependent variable was considered 0 if the patient had type 2 diabetes and 1 if the patient did not. The sample comprised 6834 individuals who were Azores residents, aged over 18 years and who were not missing values for the covariates under study; individuals were included regardless of whether they had a previous diagnosis of type 2 diabetes. Participants were considered to have type 2 diabetes if they had been previously diagnosed with type 2 diabetes or had been prescribed at least one antidiabetic drug listed in the norms of the Portuguese General Directorate of Health and the Portuguese Medical Association. Results: This model showed an area under the receiver operating characteristic curve of 0.863 based on internal validation performed with bootstrapping. Conclusion: The AzoresDiab model exhibited excellent discrimination of patients with and without type 2 diabetes. The use of predictive risk models will enable the early implementation of disease prevention programs in medium- and high-risk individuals, and public health policies to prevent the onset of the disease in these populations.

Keywords

• Azores
• personalized medicine
• preventive medicine
• risk predictor model
• type 2 diabetes.