HIV testing uptake and prevalenceamongadolescents and adults in a large home-based HIV testing program in western Kenya

Juddy Wachira, Samson Ndege, Julius Koech, Rachel Vreeman, Paul Ayuo, Paula Braitstein

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

Objective: To describe HIV testing uptake and prevalence among adolescents and adults in a home-based HIV counseling and testing program in western Kenya. Methods: Since 2007, the Academic Model Providing Access to Healthcare program has implemented home-based HIV counseling and testing on a large scale. All individuals aged ≥13 years were eligible for testing. Data from 5 of 8 catchments were included in this analysis. We used descriptive statistics and multivariate logistic regression to examine testing uptake and HIV prevalence among adolescents (13-18 years), younger adults (19-24 years), and older adults (≥25 years). Results: There were 154,463 individuals eligible for analyses as follows: 22% adolescents, 19% younger adults, and 59% older adults. Overall mean age was 32.8 years and 56% were female. HIV testing was high (96%) across the following 3 groups: 99% in adolescents, 98% in younger adults, and 94% in older adults (P < 0.001). HIV prevalence was higher (11.0%) among older adults compared with younger adults (4.8%) and adolescents (0.8%) (P < 0.001). Those who had ever previously tested for HIV were less likely to accept HIV testing (adjusted odds ratio: 0.06, 95% confidence interval: 0.05 to 0.07) but more likely to newly test HIV positive (adjusted odds ratio: 1.30, 95% confidence interval: 1.21 to 1.40). Age group differences were evident in the sociodemographic and socioeconomic factors associated with testing uptake and HIV prevalence, particularly, gender, relationship status, and HIV testing history. Conclusions: Sociodemographic and socioeconomic factors were independently associated with HIV testing and prevalence among the age groups. Community-based treatment and prevention strategies will need to consider these factors.

Original languageEnglish
JournalJournal of Acquired Immune Deficiency Syndromes
Volume65
Issue number2
DOIs
StatePublished - 2014

Fingerprint

Kenya
HIV
Young Adult
Counseling
Age Groups
Odds Ratio
Confidence Intervals
Logistic Models
History

Keywords

  • Adolescents
  • Adults
  • Africa
  • HIV
  • Home-based HIV testing
  • Prevalence

ASJC Scopus subject areas

  • Infectious Diseases
  • Pharmacology (medical)

Cite this

HIV testing uptake and prevalenceamongadolescents and adults in a large home-based HIV testing program in western Kenya. / Wachira, Juddy; Ndege, Samson; Koech, Julius; Vreeman, Rachel; Ayuo, Paul; Braitstein, Paula.

In: Journal of Acquired Immune Deficiency Syndromes, Vol. 65, No. 2, 2014.

Research output: Contribution to journalArticle

Wachira, Juddy ; Ndege, Samson ; Koech, Julius ; Vreeman, Rachel ; Ayuo, Paul ; Braitstein, Paula. / HIV testing uptake and prevalenceamongadolescents and adults in a large home-based HIV testing program in western Kenya. In: Journal of Acquired Immune Deficiency Syndromes. 2014 ; Vol. 65, No. 2.
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AU - Ndege, Samson

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AU - Ayuo, Paul

AU - Braitstein, Paula

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N2 - Objective: To describe HIV testing uptake and prevalence among adolescents and adults in a home-based HIV counseling and testing program in western Kenya. Methods: Since 2007, the Academic Model Providing Access to Healthcare program has implemented home-based HIV counseling and testing on a large scale. All individuals aged ≥13 years were eligible for testing. Data from 5 of 8 catchments were included in this analysis. We used descriptive statistics and multivariate logistic regression to examine testing uptake and HIV prevalence among adolescents (13-18 years), younger adults (19-24 years), and older adults (≥25 years). Results: There were 154,463 individuals eligible for analyses as follows: 22% adolescents, 19% younger adults, and 59% older adults. Overall mean age was 32.8 years and 56% were female. HIV testing was high (96%) across the following 3 groups: 99% in adolescents, 98% in younger adults, and 94% in older adults (P < 0.001). HIV prevalence was higher (11.0%) among older adults compared with younger adults (4.8%) and adolescents (0.8%) (P < 0.001). Those who had ever previously tested for HIV were less likely to accept HIV testing (adjusted odds ratio: 0.06, 95% confidence interval: 0.05 to 0.07) but more likely to newly test HIV positive (adjusted odds ratio: 1.30, 95% confidence interval: 1.21 to 1.40). Age group differences were evident in the sociodemographic and socioeconomic factors associated with testing uptake and HIV prevalence, particularly, gender, relationship status, and HIV testing history. Conclusions: Sociodemographic and socioeconomic factors were independently associated with HIV testing and prevalence among the age groups. Community-based treatment and prevention strategies will need to consider these factors.

AB - Objective: To describe HIV testing uptake and prevalence among adolescents and adults in a home-based HIV counseling and testing program in western Kenya. Methods: Since 2007, the Academic Model Providing Access to Healthcare program has implemented home-based HIV counseling and testing on a large scale. All individuals aged ≥13 years were eligible for testing. Data from 5 of 8 catchments were included in this analysis. We used descriptive statistics and multivariate logistic regression to examine testing uptake and HIV prevalence among adolescents (13-18 years), younger adults (19-24 years), and older adults (≥25 years). Results: There were 154,463 individuals eligible for analyses as follows: 22% adolescents, 19% younger adults, and 59% older adults. Overall mean age was 32.8 years and 56% were female. HIV testing was high (96%) across the following 3 groups: 99% in adolescents, 98% in younger adults, and 94% in older adults (P < 0.001). HIV prevalence was higher (11.0%) among older adults compared with younger adults (4.8%) and adolescents (0.8%) (P < 0.001). Those who had ever previously tested for HIV were less likely to accept HIV testing (adjusted odds ratio: 0.06, 95% confidence interval: 0.05 to 0.07) but more likely to newly test HIV positive (adjusted odds ratio: 1.30, 95% confidence interval: 1.21 to 1.40). Age group differences were evident in the sociodemographic and socioeconomic factors associated with testing uptake and HIV prevalence, particularly, gender, relationship status, and HIV testing history. Conclusions: Sociodemographic and socioeconomic factors were independently associated with HIV testing and prevalence among the age groups. Community-based treatment and prevention strategies will need to consider these factors.

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