Binary Logistic Regression Analysis on Risk Factors Associated with Hepatitis B Disease in Gusau Local Government Zamfara State, Nigeria

Abstract

This study focused on creating a binary logistic regression model to evaluate the risk factors for hepatitis B viral disease in the Gusau Local Government of Zamfara State, Nigeria. Secondary data was utilised, and the model identified independent predictors of hepatitis-b disease based on variables with a P-value < 0.05 and a 95% confidence interval for the odds ratio not less than 1. The results indicated that marital status, history of blood transfusion, multiple sex partners, and alcohol consumption were statistically associated with hepatitis-B virus infection, while gender and having an infected family member were not. Model selection criteria, including Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), favoured a model with only significant predictors, revealing the existence of Hepatitis-B virus infection risk factors in patients from Gusau Local Government of Zamfara State.