Title: Risk Analysis of Diabetes Mellitus and Hypertension Using Biresponse Binary Logistic Regression
Authors: Marisa Rifada Elly Ana Cynthia Anggelyn Siburian Amanda Gita Safitri
Volume: 8
Issue: 12
Pages: 82-88
Publication Date: 2024/12/28
Abstract:
This study aims to analyze risk factors for diabetes mellitus and hypertension using a biresponse binary logistic regression model, enabling simultaneous analysis of two dependent binary variables. Secondary data were obtained from the Kaggle platform, involving 574 individuals with non-alcoholic fatty liver disease (NAFLD) and several health variables, including age, gender, Body Mass Index (BMI), ALT levels, LDL cholesterol levels, hyperlipidemia status, metabolic syndrome, and smoking habits. The results indicate that diabetes is more prevalent among individuals aged 55-64, while hypertension is more common in those aged 65 and older. Key findings identify risk factors such as a BMI over 30, low ALT levels, hyperlipidemia, and metabolic syndrome as significantly associated with both conditions. The logistic regression results reveal an odds ratio of 1.123, indicating a dependent relationship between diabetes and hypertension. This study underscores the importance of understanding these risk factors for more effective health interventions in addressing both diseases simultaneously. The application of this model is expected to serve as a foundation for developing more comprehensive health policies to reduce the risk of complications associated with diabetes and hypertension.