ANALYSIS ON THE PREVALENCE OF HEPATITIS B USING BINARY LOGISTIC REGRESSION: A CASE STUDY OF FEDERAL TEACHING HOSPITAL GOMBE.

Abstract This rescarch investigates the prevalence of Hepatitis B cases over age and gender, using Federal Teaching Hospital Gombe as a case study. The study identifies patterns and provides insights into the distribution of cases, which will contribute to understanding the disease dynamics and informing prevention strategies. Data was collected from hospital records and analyzed using binary logistic regression methods. The results suggest that hepatitis B affects all age groups but is more prone to the middle age group, reinforcing the need for targeted interventions across different age categories. Also, liver tests showed ALT levels have a positive trend (0.0062,p=0.091),indicating that higher ALT levels may be linked to complications, and AST levels (-0.0004,p=0.901)did not have a significant relationship with complications, suggesting that AST alone may not be a strong predictor of treatment outcomes. Based on the findings of this study, it is evident that hepatitis B affects a diverse demographic, encompassing individuals of varying ages,genders,and vaccination statuses. The nearly equal distribution of treatment outcomes between those who experienced complications and those who did not suggests that factors beyond those analyzed in this study may contribute to disease progression and treatment efficacy. The study further found that complications were present in both vaccinated and unvaccinated individuals. This indicates that while vaccination is essential, other factors such as the stage of infection at diagnosis,co-existing health conditions, and individual immune response may also play a crucial role in treatment outcomes. Based on the results, we suggest further research to incorporate additional variables such as lifestyle factors,socioeconomic status, and genetic predispositions to obtain a more comprehensive understanding of the disease dynamics.