Logo image
A predictive model for hepatitis B infection among high-risk adults using a community-based sample in greater Philadelphia
Journal article   Peer reviewed

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

Catherine Freeland, Daniel Vader, Chari Cohen and Brandon George
Journal of viral hepatitis, v 27(12), pp 1319-1325
01 Dec 2020
PMID: 32702781

Abstract

Gastroenterology & Hepatology Infectious Diseases Life Sciences & Biomedicine Science & Technology Virology
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.

Metrics

10 Record Views
5 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Gastroenterology & Hepatology
Infectious Diseases
Virology
Logo image