Distance from Home to Study Clinic and Risk of Follow-Up Interruption in a Cohort of HIV-1-Discordant Couples in Nairobi, Kenya

Background: Longitudinal studies of HIV-1-infected individuals or those at risk of infection are subject to missed study visits that may have negative consequences on the care of participants and can jeopardize study validity due to bias and loss of statistical power. Distance between participant residence and study clinic, as well as other socioeconomic and demographic factors, may contribute to interruptions in patient follow-up. Methods: HIV-1-serodiscordant couples were enrolled between May 2007 and October 2009 and followed for two years in Nairobi, Kenya. At baseline, demographic and home location information was collected and linear distance from each participant’s home to the study clinic was determined. Participants were asked to return to the study clinic for quarterly visits, with follow-up interruptions (FUI) defined as missing two consecutive visits. Cox proportional hazards regression was used to assess crude and adjusted associations between FUI and home-to-clinic distance, and other baseline characteristics. Results: Of 469 enrolled couples, 64% had a female HIV-1-infected partner. Overall incidence of FUI was 13.4 per 100 person-years (PY), with lower incidence of FUI in HIV-1-infected (10.8 per 100 PY) versus -uninfected individuals (16.1 per 100 PY) (hazard ratio [HR] = 0.66; 95% confidence interval [CI]: 0.50, 0.88). Among HIV-1-infected participants, those living between 5 and 10 kilometers (km) from the study clinic had a two-fold increased rate of FUI compared to those living <5 km away (HR = 2.17; 95% CI: 1.09, 4.34). Other factors associated with FUI included paying higher rent (HR = 1.67; 95% CI: 1.05, 2.65), having at least primary school education (HR = 1.96; 95% CI: 1.02, 3.70), and increased HIV-1 viral load (HR = 1.23 per log10 increase; 95% CI: 1.01, 1.51). Conclusions: Home-to-clinic distance, indicators of socioeconomic status, and markers of disease progression may affect compliance with study follow-up schedules. Retention strategies should focus on participants at greatest risk of FUI to ensure study validity

Validity and Reliability of a Self-Reported Measure of Antihypertensive Medication Adherence in Uganda

Background: The Morisky Medication Adherence scale (MMAS-8) is a widely used self-reported measure of adherence to antihypertensive medications that has not been validated in hypertensive patients in sub-Saharan Africa. Methods: We carried out a cross-sectional study to examine psychometric properties of a translated MMAS-8 (MMAS-U) in a tertiary care hypertension clinic in Uganda. We administered the MMAS-U to consecutively selected hypertensive adults and used principal factor analysis and Cronbach’s alpha to determine its validity and internal consistency respectively. Then we randomly selected one-sixth of participants for a 2-week test-retest telephone interview. Lastly, we used ordinal logistic regression modeling to explore factors associated with levels of medication adherence. Results: Of the 329 participants, 228 (69%) were females, median age of 55 years [Interquartile range (IQR) (46–66)], and median duration of hypertension of 4 years [IQR (2–8)]. The adherence levels were low (MMAS-U score ≤ 5) in 85%, moderate (MMAS-U score 6–7) in 12% and high (MMAS-U score ≥8) in 3%. The factor analysis of construct validity was good (overall Kaiser’s measure of sampling adequacy for residuals of 0.72) and identified unidimensionality of MMAS-U. The internal consistency of MMAS-U was moderate (Cronbach α = 0.65), and test-retest reliability was low (weighted kappa = 0.36; 95% CI -0.01, 0.73). Age of 40 years or greater was associated with low medication adherence (p = 0.02) whereas a family member buying medication for participants (p = 0.02) and purchasing medication from a private clinic (p = 0.02) were associated with high adherence. Conclusion: The Ugandan version of the MMAS-8 (MMAS-U) is a valid and reliable measure of adherence to antihypertensive medication among Ugandan outpatients receiving care at a public tertiary facility. Though the limited supply of medication affected adherence, this easy to use tool can be adapted to assess medication adherence among adults with hypertension in Uganda

Clinical characteristics according to medication adherence scores.

<p>Clinical characteristics according to medication adherence scores.</p

Exploratory Factor Analysis of the Ugandan Morisky medication adherence scale in hypertensive patients.

<p>Exploratory Factor Analysis of the Ugandan Morisky medication adherence scale in hypertensive patients.</p

Multivariate ordinal logistic model of factors associated with low adherence to antihypertensive medication.

<p>Multivariate ordinal logistic model of factors associated with low adherence to antihypertensive medication.</p

Baseline characteristics of hypertensive patients.

<p>Baseline characteristics of hypertensive patients.</p