Development of type 2 diabetes risk assessment model for Turkish society.

Abstract

The study was conducted to develop a risk assessment tool to determine the Turkish population's risk of undiagnosed type 2 diabetes. The study was carried out in a methodological design. A total of 610 individuals, including those diagnosed with diabetes (321) and not diagnosed with diabetes (289), who applied to the internal medicine and diabetes outpatient clinics of a public hospital, were included in the study. The sample of patients with diabetes was created with the individuals who applied to diabetes outpatient clinics, were 40 years of age and older, and had the values of FPG ≥ 126mg/dl and HbA1C ≥ 6.5%. The sample of healthy individuals consisted of people over the age of 40 who were not diagnosed with diabetes or prediabetes. Logistic regression and random forest algorithms were used to evaluate the diabetes risk of individuals. The performance of the models was evaluated with sensitivity, specificity, accuracy, and area under the ROC (AUC). In the study, the variables of exercise in daily routines, presence of prediabetes, getting angry, feeling hungry frequently, and excessive thirst formed the diabetes risk assessment model with Sensitivity 0.983 and Specificity 0.984 according to the logistic regression model obtained. Body mass index, physical activity, age, gender, and family history of diabetes were not found to be significant in differentiating cases with diabetes (0.05 < p). This diabetes risk assessment tool is a reliable tool for Turkish society to identify individuals at high risk for diabetes and to raise awareness of the importance of modifiable risk factors.