A predictive model for hepatitis B infection among high-risk adults using a community-based sample in greater Philadelphia

J Viral Hepat. 2020 Dec;27(12):1319-1325. doi: 10.1111/jvh.13365. Epub 2020 Aug 10.

Abstract

Liver cancer is the 3rd deadliest cancer worldwide, with 5-year survival rates of only 15%. In the United States, 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 data set includes a total of 3019 individuals considered high risk for HBV tested at community-based testing events between 2008 and 2019. Descriptive results revealed HBV infection rate was 7.9% (N = 229), and 59% (N = 1704) 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 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.

Keywords: community-based testing; health disparities; hepatitis B; liver cancer; population health; public health; viral hepatitis.