Hepatitis B knowledge among women and men in the upper west region of Ghana: What sources of health information matter?
Florence Wullo AnfaaraKilian Nasung AtuoyeRoger AntabeYujiro SanoIsaac LuginaahPublished in: The International journal of health planning and management (2020)
Despite the vital role of accurate health information in reducing the spread of Hepatitis B virus (HBV) in endemic contexts such as Ghana, little is known about how health information sources may influence disparities in the knowledge of HBV transmission among women and men. This study examines the association between sources of health information and knowledge of HBV transmission in the Upper West Region (UWR) of Ghana. Data from a cross-sectional survey (n = 1061) was analyzed using gender-specific multivariate ordered logistic regression models. The results show that, women who obtained health information from religious-based programs (OR = 4.04, P < .05), higher-level facilities (OR = 2.37, P < .05), and primary health facilities (OR = 1.83, P < .1) were more likely to have good knowledge of HBV transmission compared to non-facility-based programs. Similarly, men who accessed health information from religious-based programs only, were more likely to have good knowledge of HBV transmission (OR = 2.14, P < .05) compared to non-facility-based programs. The results demonstrate the importance of health information sources on knowledge of disease transmission and prevention in a resource-poor context. Based on our findings, we suggest the scaling-up of information programs at health facilities in rural areas and the expansion of HBV services in the UWR in contribution towards the attainment of SDG #3.3.
Keyphrases
- health information
- hepatitis b virus
- healthcare
- social media
- liver failure
- public health
- drinking water
- polycystic ovary syndrome
- mental health
- primary care
- middle aged
- type diabetes
- pregnancy outcomes
- pregnant women
- insulin resistance
- risk assessment
- climate change
- electronic health record
- cervical cancer screening
- deep learning
- human health