Predictors of HIV testing among youth aged 15–24 years in The Gambia

Abstract

Background Worldwide, an estimated 38.0 million people lived with the human immunodeficiency virus in 2019, and 3.4 million young people aged 15~24 years were living with HIV. Sub-Saharan Africa carries a significant HIV burden with West and Central Africa most affected with HIV. Among the young people living with HIV in West and Central Africa, an estimated 810,000 were aged 15~24 years. This study aimed to assess predictors that influence the uptake of HIV testing among youth aged 15~24 years in The Gambia. Methods The 2013 Gambia Demographic and Health Survey data for youth aged 15~24 years was used. The Andersen behavioral model of health service use guided this study. A cross-sectional study design was used on 6194 subjects, among which 4730 were female. The analysis employed Chi-squared tests and hierarchical logistic regression. Results Less than one-quarter of the youth 1404 (22.6%) had ever been tested for HIV. Young people aged 20~24 years (adjusted odds ratio (aOR): 1.98), who were females (aOR: 1.13), married youth (aOR: 3.89), with a primary (aOR: 1.23), secondary or higher education (aOR: 1.46), and who were from the Jola/Karoninka ethnic group (aOR: 1.81), had higher odds of having been tested for HIV. Those with adequate HIV knowledge and those who were sexually active and had aged at first sex ≥15 years (aOR: 3.99) and those <15 years (aOR: 3.96) were more likely to have been tested for HIV compared to those who never had sex. Conclusion This study underscores the low level of model testing on HIV testing among youth (15~24 years) in The Gambia. Using Anderson’s Model of Health Service Utilization, the predisposing factors (socio-demographic and HIV knowledge) and the need-for-care factors (sexual risk behaviors) predict healthcare utilization services (HIV testing) in our study; however, only socio-demographic model explained most of the variance in HIV testing. The low effect of model testing could be related to the limited number of major variables selected for HIV knowledge and sexual risk behavior models. Thus, consideration for more variables is required for future studies.

Prevalence and predictors of HIV testing among young men in Papua New Guinea: a cross-sectional analysis of a nationally representative sample

“…Our study found a significantly lower prevalence of HIV testing among young men than in studies conducted in Nigeria [40] and the Gambia [41]; however, these findings contributed to a better understanding of the current HIV prevention challenges among young men in PNG.…”

“…Our study found a significantly lower prevalence of HIV testing among young men than in studies conducted in Nigeria [40] and the Gambia [41]; however, these findings contributed to a better understanding of the current HIV prevention challenges among young men in PNG. The low rates of HIV testing found in this study show only a minimal decrease in the HIV testing uptake in this age group when compared to the country’s recent data [39].…”

Self-reported adherence to HIV/AIDS management and associated factors among gender-groups at a referral treatment centre in Port Harcourt, Nigeria

“…18,[34][35][36][37][38][39] Conversely, a systematic review carried out in sub-Saharan Africa in addition to other crosssectional studies conducted in the Gambia and South Africa reported higher odds of self-reported optimal adherence among the female respondents compared to their male counterparts. 29,31,40 However, there was no observed statistically significant gender difference between self-reported adherence and socio-demographic variables in studies conducted in Togo, Cameroun, Malawi and the United States of America. 27,33,39,41 Furthermore, variables such as; level of education, religion and HIV/AIDS support services were statistically significantly associated with self-reporting optimal adherence only among the male group.…”

Association between self-reported medication adherence and virologic outcome among human immuno-deficiency virus positive adults accessing care at a tertiary treatment centre in Rivers State, Nigeria

“…32,[35][36][37][38] Although, two other studies carried out in Nigeria and Cameroun showed no statistically significant association between the variables of interest in between male and female gender. 39,40 This implies that gender may play a vital role in self-reporting of medication adherence.…”