A Predictive Model for Hepatitis B Infection Among High-Risk Adults Using a Community-Based Sample in Greater Philadelphia.
Liver cancer is the 3 deadliest cancer worldwide, with 5-year survival rates of only 15%. In the U.S., liver cancer incidence and death rates are increasing at a faster rate than any other cancer and are projected to continue to rise through at least 2030. A significant proportion of these liver cancer cases are due to hepatitis B virus (HBV). Community-based screening is a public health practice working to identify individuals who are living with HBV in underserved communities, particularly Asian American, Pacific Islander and African immigrant populations. This dataset includes a total of 3,019 individuals considered high-risk for HBV tested at community-based testing events between 2008-2019. Descriptive results revealed HBV infection rate was 7.9% (N=229), and 59% (N=1,704) had protective antibodies against HBV. To account for missingness in the data, multiple imputation was preformed and followed by logistic regression to create a predictive model. The results support an association between insurance status and HBV infection in the predictive model. Participant region of origin was also significantly related to HBV infection, and participants who immigrated from the Western Pacific and African World Health Organization designated regions had higher odds of infection compared to participants from the Americas. Results emphasize the need to continue to expand testing in high-risk populations for HBV.This article is protected by copyright. All rights reserved.