Socioeconomic Inequalities in Human Immunodeficiency Virus (HIV) Sero-Prevalence among Women in Namibia: Further Analysis of Population-Based Data

Abstract

Socioeconomic inequality is a major factor to consider in the prevention of human immunodeficiency virus (HIV) transmission. The aim of this study was to investigate socioeconomic inequalities in HIV prevalence among Namibian women. Data from a population-based household survey with multistage-stratified sample of 6501 women were used to examine the link between socioeconomic inequalities and HIV prevalence. The weighted HIV prevalence was 13.2% (95% CI: 12.1–14.3%). The HIV prevalence among the poorest, poorer, middle, richer, and richest households was 21.4%, 19.7%, 16.3%, 11.0%, and 3.7%, respectively. Similarly, 21.2%, 21.7%, 11.8%, and 2.1% HIV prevalence was estimated among women with no formal education and primary, secondary, and higher education, respectively. Women from poor households (Conc. Index = −0.258; SE = 0.017) and those with no formal education (Conc. Index = −0.199; SE = 0.015) had high concentration of HIV infection, respectively. In light of these findings, HIV prevention strategies must be tailored to the specific drivers of transmission in low socioeconomic groups, with special attention paid to the vulnerabilities faced by women and the dynamic and contextual nature of the relationship between socioeconomic status and HIV infection.

Association between socio-economic factors and HIV self-testing knowledge amongst South African women

“…26,34,35 Education assists with knowing one's HIV status: lower levels of education correlate with less knowledge of HIV infection and a lower uptake of HIV services. 12,35,36,37 Wealth is correlated with greater knowledge of HIVST. Better HIVST knowledge was observed amongst employed women than unemployed.…”

“…Women's educational level, household wealth, and residential and employment status were selected as the socio-economic factors in this study. Previous studies 12,17,18,19 also used these factors whilst investigating for socioeconomic factors. Women's education was categorised as no formal education, primary, secondary and higher.…”

“…The strengths and limitations of this study are similar to those reported in a previous study, which used DHS data. 12 For example, this study used nationally representative data, which is suitable for making plausible comparisons. However, data from a cross-sectional study were analysed, and therefore only association and not causality can be determined.…”

“…11 Several studies have shown that socio-economic factors drive the transmission of HIV amongst adolescent girls and young women. 10,12 Despite the high incidence of HIV in South Africa, particularly amongst women, and the socio-economic inequalities experienced by women, there is little understanding of the actual socio-economic contributors influencing their HIVST knowledge. The objective of this study was to examine the association between socioe-conomic factors and HIVST knowledge amongst South African women.…”

Socioeconomic inequalities in the 90–90–90 target, among people living with HIV in 12 sub-Saharan African countries — Implications for achieving the 95–95–95 target — Analysis of population-based surveys

“…One explanation for this disparity is that PLHIV may face different barriers depending on their socioeconomic background. 21 , 22 Poor women living with HIV in Ethiopian cities, for example, reported selling antiretroviral drugs to cover ART-related cost. 22 In contrast, PLHIV from wealthy backgrounds may have faced barriers to accessing HIV testing and treatment, such as stigma and discrimination, lack of private clinics, and concerns about potential loss of social status and community standing if community members learned about their HIV positive status.…”