Multilevel analysis of factors associated with HIV among women of reproductive age (15-49 years old) in Ethiopia: Bayesian approach

Womens Health (Lond). 2021 Jan-Dec;17:17455065211067638. doi: 10.1177/17455065211067638.

Abstract

Background: Human immunodeficiency virus remains the leading cause of morbidity and mortality throughout the world. Sub-Saharan Africa regions are the most affected regions and accounted for 67% of HIV infections worldwide, and 72% of the world's AIDS-related deaths.

Objective: To estimate the prevalence of HIV and identify factors associated with it among women of reproductive age in Ethiopia.

Methods: This study was conducted based on the 2016 Ethiopian Demographic and Health Surveys data. The data were weighted using sampling weight for probability sampling and non-response to restore the representativeness of the data and get valid statistical estimates. Then, a total of 14,161 weighted sample women were used to investigate the study. Finally, a multilevel analysis was done based on the Bayesian approach to identify factors associated with HIV among women of reproductive age in Ethiopia.

Results: This study showed the prevalence of HIV among reproductive age group women was 0.85%. Being rural resident (adjusted odds ratio = 0.20; 95% CrI = 0.1-0.4), secondary education level (adjusted odds ratio = 0.20; 95% CrI = 0.1-0.4), rich wealth status (adjusted odds ratio = 4; 95% CrI = 3-6), married women but living separately (adjusted odds ratio = 2.3; 95% CrI = 1.2-4.5), long distance from the health facility (adjusted odds ratio = 0.4; 95% CrI = 0.3-0.5), and exposure to media (adjusted odds ratio = 2.9; 95% CrI = 1.8-4.7) were significantly associated with HIV.

Conclusion: Being rural residents, women whose marital status is separated, wealthy, travel a long distance to get health facility, and are exposed to media are risky to be infected by HIV. Whereas being a rural resident and educated are preventive factors for HIV. Therefore, the government of Ethiopia and the ministry of health should consider those factors when they design HIV prevention and control strategies.

Keywords: Ethiopia; HIV; demographic health survey; women.

MeSH terms

  • Adolescent
  • Adult
  • Bayes Theorem
  • Ethiopia / epidemiology
  • Female
  • HIV Infections* / epidemiology
  • Health Surveys
  • Humans
  • Middle Aged
  • Multilevel Analysis
  • Rural Population
  • Young Adult