Litcius/Paper detail

<p>Predictors of Comprehensive Knowledge of HIV/AIDS Among People Aged 15–49 Years in Ethiopia: A Multilevel Analysis</p>

Bereket Kefale, Yitayish Damtie, Melaku Yalew, Bezawit Adane, Mastewal Arefaynie

2020HIV/AIDS - Research and Palliative Care17 citationsDOIOpen Access PDF

Abstract

BACKGROUND: HIV/AIDS has been a big public health problem in sub-Saharan African countries including Ethiopia. Comprehensive knowledge is a basis for the prevention, control and treatment of HIV/AIDS. Several studies were focused only on the individual-level characteristics. However, comprehensive knowledge of HIV/AIDS is a multi-factorial understanding on a different level. Thus, the aim of this study was to identify the individual- and community-level factors that determine comprehensive knowledge of HIV/AIDS in Ethiopia. METHODS: This study used data from the 2016 Ethiopian Demographic and Health Survey (EDHS). A total of 25,927 (weighted) people aged 15-49 years were included in the study. A two-stage stratified cluster was used. Data were analyzed using Stata version 14. Multilevel mixed effect logistic regression was used to identify predictors of comprehensive knowledge on HIV/AIDS. RESULTS: Various individual- and community-level factors were associated with comprehensive knowledge of HIV/AIDS. From individual-level factors such as sex (male), educational status (educated), media exposure, and ever been tested for HIV, and from community-level factors such as place of residence (urban) and region (developed region) were predictors of comprehensive knowledge of HIV/AIDS. CONCLUSION: Both individual- and community-level factors were identified as predictors of comprehensive knowledge of HIV/AIDS. The government should design strategies to address the HIV/AIDS knowledge gaps among women and other underprivileged population sub-groups.

Topics & Concepts

ResidenceMedicineLogistic regressionEnvironmental healthPublic healthGerontologyPopulationHuman immunodeficiency virus (HIV)DemographyMultilevel modelFamily medicineNursingSociologyMachine learningInternal medicineComputer scienceAdolescent Sexual and Reproductive HealthHIV/AIDS Impact and ResponsesHIV/AIDS Research and Interventions