Browsing by Subject "Adolescent girls"

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    Determinants of HIV infection among adolescent girls and young women aged 15–24 years in South Africa: a 2012 population-based national household survey
    (BioMed Central, 2018-01-26) Mabaso, Musawenkosi; Sokhela, Zinhle; Mohlabane, Neo; Chibi, Buyisile; Zuma, Khangelani; Simbayi, Leickness
    Abstract Background South Africa is making tremendous progress in the fight against HIV, however, adolescent girls and young women aged 15–24 years (AGYW) remain at higher risk of new HIV infections. This paper investigates socio-demographic and behavioural determinants of HIV infection among AGYW in South Africa. Methods A secondary data analysis was undertaken based on the 2012 population-based nationally representative multi-stage stratified cluster random household sample. Multivariate stepwise backward and forward regression modelling was used to determine factors independently associated with HIV prevalence. Results Out of 3092 interviewed and tested AGYW 11.4% were HIV positive. Overall HIV prevalence was significantly higher among young women (17.4%) compared to adolescent girls (5.6%). In the AGYW model increased risk of HIV infection was associated with being young women aged 20–24 years (OR = 2.30, p = 0.006), and condom use at last sex (OR = 1.91, p = 0.010), and decreased likelihood was associated with other race groups (OR = 0.06, p < 0.001), sexual partner within 5 years of age (OR = 0.53, p = 0.012), tertiary level education (OR = 0.11, p = 0.002), low risk alcohol use (OR = 0.19, p = 0.022) and having one sexual partner (OR = 0.43, p = 0.028). In the adolescent girls model decreased risk of HIV infection was associated with other race groups (OR = 0.01, p < 0.001), being married (OR = 0.07), p = 0.016], and living in less poor household (OR = 0.08, p = 0.002). In the young women’s models increased risk of HIV infection was associated with condom use at last sex (OR = 2.09, p = 0.013), and decreased likelihood was associated with other race groups (OR = 0.17, p < 0.001), one sexual partner (OR = 0.6, p = 0.014), low risk alcohol use (OR = 0.17, p < 0.001), having a sexual partner within 5 years of age (OR = 0.29, p = 0.022), and having tertiary education (OR = 0.29, p = 0.022). Conclusion These findings support the need to design combination prevention interventions which simultaneously address socio-economic drivers of the HIV epidemic, promote education, equity and access to schooling, and target age-disparate partnerships, inconsistent condom use and risky alcohol consumption.
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    Open Access
    Determinants of HIV infection among adolescent girls and young women aged 15–24 years in South Africa: a 2012 population-based national household survey
    (2018) Mabaso, Musawenkosi; Sokhela, Zinhle; Mohlabane, Neo; Chibi, Buyisile; Zuma, Khangelani; Simbayi, Leickness
    BACKGROUND: South Africa is making tremendous progress in the fight against HIV, however, adolescent girls and young women aged 15-24 years (AGYW) remain at higher risk of new HIV infections. This paper investigates socio-demographic and behavioural determinants of HIV infection among AGYW in South Africa. METHODS: A secondary data analysis was undertaken based on the 2012 population-based nationally representative multi-stage stratified cluster random household sample. Multivariate stepwise backward and forward regression modelling was used to determine factors independently associated with HIV prevalence. RESULTS: Out of 3092 interviewed and tested AGYW 11.4% were HIV positive. Overall HIV prevalence was significantly higher among young women (17.4%) compared to adolescent girls (5.6%). In the AGYW model increased risk of HIV infection was associated with being young women aged 20-24 years (OR = 2.30, p = 0.006), and condom use at last sex (OR = 1.91, p = 0.010), and decreased likelihood was associated with other race groups (OR = 0.06, p < 0.001), sexual partner within 5 years of age (OR = 0.53, p = 0.012), tertiary level education (OR = 0.11, p = 0.002), low risk alcohol use (OR = 0.19, p = 0.022) and having one sexual partner (OR = 0.43, p = 0.028). In the adolescent girls model decreased risk of HIV infection was associated with other race groups (OR = 0.01, p < 0.001), being married (OR = 0.07), p = 0.016], and living in less poor household (OR = 0.08, p = 0.002). In the young women's models increased risk of HIV infection was associated with condom use at last sex (OR = 2.09, p = 0.013), and decreased likelihood was associated with other race groups (OR = 0.17, p < 0.001), one sexual partner (OR = 0.6, p = 0.014), low risk alcohol use (OR = 0.17, p < 0.001), having a sexual partner within 5 years of age (OR = 0.29, p = 0.022), and having tertiary education (OR = 0.29, p = 0.022). CONCLUSION: These findings support the need to design combination prevention interventions which simultaneously address socio-economic drivers of the HIV epidemic, promote education, equity and access to schooling, and target age-disparate partnerships, inconsistent condom use and risky alcohol consumption.
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    Safe spaces for beneficiaries of a combination HIV prevention intervention for adolescent girls and young women in South Africa: access, feasibility, and acceptability
    (BioMed Central, 2022-05-21) Mathews, Catherine; Duby, Zoe; Bunce, Brittany; van Blydenstein, Nathanael; Bergh, Kate; Ambrose, Anthony; Mpungu, Fiona; Jonas, Kim
    Background Safe Spaces are a feature of combination HIV prevention interventions for adolescent girls and young women (AGYW) in South Africa. We investigated whether AGYW at risk for adverse sexual and reproductive health (SRH) outcomes accessed Safe Spaces that were part of an intervention, as well as their feasibility and acceptability. Methods In December 2020 to February 2021, as part of a process evaluation of a combination HIV prevention intervention, we randomly sampled 2160 AGYW intervention beneficiaries aged 15–24 years from 6 of the 12 intervention districts. We invited them to participate in a phone survey, with questions about their vulnerability to adverse SRH outcomes, and participation in intervention components including Safe Spaces. We examined factors associated with use of Safe Spaces using bivariate analyses and Pearson’s chi squared tests. We also conducted in-depth interviews with 50 AGYW beneficiaries, 27 intervention implementers, 4 health workers, 7 social workers, and 12 community stakeholders, to explore perceptions and experiences of the intervention. Thematic analysis of the qualitative data was performed. Results At least 30 Safe Spaces were established across 6 districts. Five hundred fifteen of two thousand one hundred sixty sampled AGYW participated in the survey of whom 22.6% visited a Safe Space, accessing HIV testing (52.2%), mobile health services (21.2%) and counselling for distress (24.8%) while there. Beneficiaries of lower socioeconomic status (SES) were less likely to have visited a Safe Space, compared with those of higher SES (13.6% versus 25.3%; p < 0.01). Implementers described political, structural and financial challenges in identifying and setting up Safe Spaces that were safe, accessible and adequately-resourced, and challenges with AGYW not utilising them as expected. AGYW shared positive views of Safe Spaces, describing benefits such as access to computers and the internet, support with homework and job and education applications, and a space in which to connect with peers. Conclusion AGYW are attracted to Safe Spaces by educational and employment promoting interventions and recreational activities, and many will take up the offer of SRH services while there. The poorest AGYW are more likely to be excluded, therefore, an understanding of the obstacles to, and enablers of their inclusion should inform Safe Space intervention design.