Relationship between socioeconomic status and Human Immunodeficiency Virus infection amongst adults in selected villages of Capricorn District, Limpopo Province

Abstract

Background Globally, the Human Immunodeficiency Virus continues to pose a serious threat to public health. particularly in South Africa, where socioeconomic factors are linked to the prevalence of infection. This study investigates the relationship between socioeconomic status and HIV infection rates in the selected villages of Capricorn District in Limpopo Province. Methodology This study employed a retrospective cohort approach using secondary data from HIV testing results and socioeconomic assessments of adults in the in the selected villages of Capricorn District in Limpopo Province. The SPSS version 28.0 was used to analyse the data. 1. The findings and sociodemographic traits pertaining to HIV prevalence are clearly displayed using tables, pie charts, and bar graphs. This study further utilised a multivariate binary regression model to investigate the relationship between HIV infection and various socio-economic factors, including age group, gender, marital status, education level, employment status, financial status, household assets, and SES. The analysis incorporated p-values and odds ratios to evaluate the significance of the relationships between socio-economic variables and HIV status, enhancing the understanding of factors influencing HIV infection within the study population. Results The study revealed an overall HIV prevalence of 3.8% in the selected villages of Capricorn District in Limpopo Province falling under DIMAMO catchment area, with higher rates among older individuals, particularly females. The results indicated that higher educational attainment correlates with lower HIV positivity rates, while older adults (ages 45-59) and individuals from economically vulnerable households are at greater risk. Notably, a significant gender disparity was identified, with women comprising 80% of the positive cases. While the data suggested a protective effect of higher education levels against HIV infection, the associations between socio economic status factors and HIV status were not statistically significant. Economic stability and employment did not demonstrate a clear relationship with HIV prevalence. However, statistical analyses did not reveal significant associations between socio- vi economic status variables (education, financial status, or employment and HIV infection). Conclusion This study highlights the complex interplay between socio-economic status and HIV infection, suggesting that while certain socioeconomic factors may influence risk, they do not uniformly predict infection rates. Targeted interventions are necessary to address age-specific vulnerabilities and broader socioeconomic challenges to enhance HIV prevention efforts in high-risk populations.