African Journal of AIDS and HIV Research

African Journal of AIDS and HIV Research ISSN 2326-2691 Vol. 4 (4), pp. 218-227, July, 2016. © International Scholars Journals

Full Length Research Paper

Risk factors for HIV infection among voluntary counselling and testing clients in Namibia

*Richard Chamboko1 and Isak Neema2

1NOVA Information Management School, New University of Lisbon, Portugal.

2Namibia Statistics Agency P.O. Box 2133, Windhoek, Namibia.

*Corresponding author. E-mail:

Accepted 29 July, 2015


In an effort to provide useful information that can guide HIV prevention strategies, this study determined the risk factors for HIV infection in Namibia. It also estimated the disease risk attributable to selected risk factors. The study adopted a cross sectional research design with a sample of 14296 voluntary testing and counseling clients from Oshana, Khomas and Kavango regions for the period of 2009 to 2012. Logistic regression was used to determine the risk factors for HIV infection among VCT clients. Attributable risk measures were then computed for factors amenable to intervention and were used as the basis for selecting risk factors posing the greatest disease burden to the population. From a targeting perspective, sex (OR = 1.3), condom use (OR= 1.7), male circumcision status (OR = 1.5) among others continue to be significant predictors of HIV infection. Not using condoms and not being circumcised are amenable to interventions and eliminating these risk factors can avert up to 22% and 18% of the disease burden respectively. Elimination of both exposures will result in 37% reduction in disease burden. As such, these factors should be the priority for HIV prevention in Namibia. We therefore recommend that the introduction of male circumcision in the country should be done concurrently with a strong condom messaging programme to increase the use of condoms even among circumcised men whilst at the same time addressing other social and structural factors.  

Keywords: HIV, prevention, VCT clients, risk factors, logistic regression, attributable risk measures.