Identifying risk factors associated with type 2 diabetes based on data analysis
Waleed Noori Hussein, Zainab Muzahim Mohammed, Amani Naama Mohammed
Abstract
This paper aims to identify risk factors and elements associated with type 2 diabetes. Both quantitative and qualitative approaches were used to collect data. Risk factors for type 2 diabetes are also presented from the systematic literature review to determine the variables and which variable seems to have the greatest impact on type 2 diabetes. Factor analysis of the dataset is used to provide an efficient result to predict and evaluate type 2 diabetes. This paper focused on increasing the accuracy of understanding type 2 diabetes based on data analysis. The results showed that Body Mass Index (BMI) has a strong influence on hemoglobin (A1C) with R-squared (R2) of 78%, and 60% with triglyceride (TG). The outcome of this paper will be a prediction model using a PLC-regression outer model analysis.