UCLA

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.