4.6 Article

Characteristics of users of HIV self-testing in Kenya, outcomes, and factors associated with use: results from a population-based HIV impact assessment, 2018

Journal

BMC PUBLIC HEALTH
Volume 22, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12889-022-12928-0

Keywords

HIV testing; HIV self-testing; Population-based HIV Impact Assessment (PHIA); Kenya

Funding

  1. U.S. President's Emergency Plan for AIDS Relief (PEPFAR) through the United States Centers for Disease Control and Prevention (CDC) [U2GGH001226]
  2. United States Agency for International Development (USAID)
  3. Global Fund to Fight AIDS, TB, and Malaria

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Kenya has made progress in rolling out HIV self-testing (HIVST), but geographic differences and sociodemographic factors could influence its usage. It is necessary to scale up the use of HIVST among various subpopulations and use multiple access models to ensure equitable access to HIVST.
Background and setting About 20% of persons living with HIV aged 15-64 years did not know their HIV status in Kenya, by 2018. Kenya adopted HIV self-testing (HIVST) to help close this gap. We examined the sociodemographic characteristics and outcomes of self-reported users of HIVST as our primary outcome. Methods We used data from a 2018 population-based cross-sectional household survey in which we included self-reported sociodemographic and behavioral characteristics and HIV test results. To compare weighted proportions, we used the Rao-Scott chi-square test and Jackknife variance estimation. In addition, we used logistic regression to identify associations of sociodemographic, behavioral, and HIVST utilization. Results Of the 23,673 adults who reported having ever tested for HIV, 937 (4.1%) had ever self-tested for HIV. There were regional differences in HIVST, with Nyanza region having the highest prevalence (6.4%), p < 0.001. Factors independently associated with having ever self-tested for HIV were secondary education (adjusted odds ratio [aOR], 3.5 [95% (CI): 2.1-5.9]) compared to no primary education, being in the third (aOR, 1.7 [95% CI: 1.2-2.3]), fourth (aOR, 1.6 [95% CI: 1.1-2.2]), or fifth (aOR, 1.8 [95% CI: 1.2-2.7]) wealth quintiles compared to the poorest quintile and having one lifetime sexual partner (aOR, 1.8 [95% CI: 1.0-3.2]) or having >= 2 partners (aOR, 2.1 [95% CI: 1.2-3.7]) compared to none. Participants aged >= 50 years had lower odds of self-testing (aOR, 0.6 [95% CI: 0.4-1.0]) than those aged 15-19 years. Conclusion Kenya has made progress in rolling out HIVST. However, geographic differences and social demographic factors could influence HIVST use. Therefore, more still needs to be done to scale up the use of HIVST among various subpopulations. Using multiple access models could help ensure equity in access to HIVST. In addition, there is need to determine how HIVST use may influence behavior change towardsaccess to prevention and HIV treatment services.

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