Socioeconomic and clinical factors explaining the risk of unstructured antiretroviral therapy interruptions among Kenyan adult patients

Bibliographic Data

ID19439342
AuthorsEdwin Mûnene (0000-0002-9831-4184, corresponding author), Björn Ekman (0000-0001-7630-7904, Lund University)
Year2016
Volume28
Issue9
Pages1110-1118
Publication date2016-09-01
Open AccessNo
TypeARTICLE
VenueAIDS Care (JOURNAL)
Journal identifiersISSN: 0954-0121 • E-ISSN: 1360-0451
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/09540121.2016.1140890
PMID26846424
OpenAlexW2289907679
LanguageEN
Citations received1
References cited27

A cross-sectional study was conducted to assess the extent of unstructured HIV treatment interruptions (TIs) and investigate the effects of socioeconomic, socio-demographic, HIV treatment-related and clinical factors on the magnitude and rate of the same among adult patients at a Kenyan regional referral center. Four hundred and twenty-one adult patients actively receiving antiretroviral therapy at Nyeri County Referral Hospital since 2003 were randomly selected to complete a health survey questionnaire. Electronic records were used to obtain their HIV treatment utilization history. The marginal effects of selected determinants on prevalence and rate of TI were assessed by fitting multiple Poisson log-linear regression models. In total, 392 patients participated in the study. HIV TI was prevalent with 64.5% having had at least one TI of 3 months or more during treatment. The risk of TI was significantly higher in those longer on treatment (prevalence ratio = 1.2, 95% confidence interval [CI] 1.12-1.28). Greater risk of TI was also associated with lower income (prevalence rate ratio [PRR] = 0.9, 95% CI 0.83-1.00), low medication adherence (PRR = 0.3, 95% CI 0.13-0.72), inconsistent treatment engagement (PRR = 0.4, 95% CI 0.19-0.75) and, contrarily, fewer adverse drug reactions (PRR = 0.9, 95% CI 0.90-0.97). Unstructured HIV TIs appear to be fairly common at the study site. The results suggest that efforts to minimize HIV TI could benefit from treatment-continuity monitoring strategies that target the high-risk sub-samples identified

Adverse effect · Antiretroviral therapy · Confidence interval · Environmental health · Family medicine · Kenya · Poisson regression · Population · Rate ratio · Referral · Socioeconomic status · Viral load · Demography · HIV Research and Treatment · HIV/AIDS drug development and treatment · HIV/AIDS Research and Interventions · Medicine · Internal Medicine · Pediatrics

Tools

Open DOISci-Hub