Antiretroviral Therapy Adherence, Virologic and Immunologic Outcomes in Adolescents Compared With Adults in Southern Africa : JAIDS Journal of Acquired Immune Deficiency Syndromes

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Epidemiology and Social Science

Antiretroviral Therapy Adherence, Virologic and Immunologic Outcomes in Adolescents Compared With Adults in Southern Africa

Nachega, Jean B MD, PhD*†; Hislop, Michael MSc; Nguyen, Hoang MD, MPH*; Dowdy, David W MD, PhD§; Chaisson, Richard E MD*§‖; Regensberg, Leon MBChB, MRCP; Cotton, Mark MBChB, PhD; Maartens, Gary MBChB, FCP

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JAIDS Journal of Acquired Immune Deficiency Syndromes 51(1):p 65-71, May 2009. | DOI: 10.1097/QAI.0b013e318199072e
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The goal of combination antiretroviral therapy (ART) is to achieve the sustained suppression of HIV replication. Although large studies of efficacy of ART in HIV-infected adults1-4 and children5,6 have been conducted, relatively few data have been collected describing the virologic outcomes of ART in adolescents. According to the World Health Organization, the number of adolescents on ART continues to increase reflecting successful treatment of perinatally infected children, infections during early adolescence, and expanding worldwide access to ART.7 Because of the unique behavioral characteristics of adolescents, they may have worse adherence to ART,8,9 which would increase their risk of both morbidity and drug resistance. As a result, measurement of adherence and virologic outcomes in this population is important.

The level of ART adherence required to achieve optimal virologic response remains controversial. Although adherence rates of greater than 95% were traditionally considered to be mandatory for adequate response to nonboosted protease inhibitor (PI)-based ART regimens,10 recent findings have shown that nonnucleoside reverse transcriptase inhibitor (NNRTI)-based ART often leads to viral suppression at moderate levels of adherence (70%-90%). However, individuals with such “moderate” adherence levels are likely to have improved outcomes with higher adherence.11,12 Mills et al13 have shown that, on average, 77% of African adults on ART had high levels of ART adherence (>80%) compared with 55% of North American patients. However, this meta-analysis did not include adolescent populations from Africa. In fact, the existing data on ART adherence and outcomes in adolescents come almost exclusively from the developed world.

Belzer et al9 conducted a pilot survey of 31 youths (aged 13-24 years) from a multidisciplinary adolescent HIV clinic and reported that 61% of the subjects self-reported >90% compliance with their medications in the previous 90 days. “Too many pills” was the most common reason youths reported missing medication (46%), especially for the previous 90 days. The first large-scale disease progression study in the United States of HIV-positive adolescents infected through sexual behavior or injection drug use, called REACH (Reaching for Excellence in Adolescent Care and Health), found that only 41% of adolescents (aged 12-19 years) on ART reported >95% adherence and that factors associated with poor adherence included depression, pill burden, advanced HIV status, alcohol use, and dropping out of school.14 In this same cohort, Murphy et al15 reported that only 28.3% of adolescents reported taking all of their prescribed antiretroviral medications in the previous month, and factor analysis revealed barriers to adherence to be medication-related adverse effects (both physical and psychological) and complications in day-to-day routines. In another US study, the Pediatric AIDS Clinical Trial Group 381, the cohort included 120 adolescents (aged 11-22 years) infected via high-risk behaviors and treated with at least 2 nucleoside reverse transcriptase inhibitors plus either a PI or an efavirenz-containing highly active antiretroviral therapy regimen. Of these 120 subjects, 44 (37%) stayed on study treatment for the 3 years of observation. Twenty-nine subjects (24%) reached and maintained undetectable viral loads. Poorer adherence was the main predictor of virologic failure.16

In these studies, however, data from adolescents were not directly compared with data from adults, and it is also uncertain whether the data from these adolescents could be generalized to sub-Saharan Africa, currently home to 70% of all people living with AIDS.7 Therefore, we compared adherence and virologic outcomes in adolescents (not perinatally infected) and in adults enrolled in Aid for AIDS, a large private sector HIV management program in southern Africa.


Data Source

We evaluated records from HIV-1-infected adults and adolescents enrolled in Aid for AIDS, a private sector, employer-subsidized disease management program that operates in 9 countries of southern Africa and that has been described in detail elsewhere.17 Patients become eligible for ART with either a documented CD4+ T-cell count <350 cells per microliter on 2 occasions or a medical confirmation of an AIDS-defining illness. Aid for AIDS does not manage clinics but reimburses patients' private medical practitioners. Authorization for ART reimbursement is subject both to the receipt of a physician prescription and to approval by Aid for AIDS clinical staff, after prespecified clinical guidelines.18 ART is dispensed monthly at a pharmacy of the patient's choice. For reimbursement, patients submit a claim containing the date ART was dispensed, the specific medication regimen followed, and the quantity supplied. Reimbursement requires no patient co-payment.

Adherence in our analysis is estimated by pharmacy refills (the total number of months in which ART medications were claimed divided by the total number of months during which ART was authorized). Of note, adherence based on pharmacy data has been validated with medication electronic monitor system caps19 and therapeutic drug levels20,21 and can reliably predict virologic success,22-24 drug resistance,25 and survival.17,26,27

This study used data from patients who had initiated ART between January 1999 and August 2006. ART is defined as taking a minimum of 2 nucleoside reverse transcriptase inhibitors plus either one NNRTI or a boosted PI. To be included in the study, patients had to meet the following criteria: (1) no known prior exposure to ART, (2) age ≥11 years old at ART initiation, (3) at least 6 months of follow-up data available, (4) have a baseline (pre-ART) HIV viral load >400 copies per milliliter, and (5) at least 1 known viral load measurement after ART initiation. There were no differences in baseline characteristics for patients who did not have at least 6 months of follow-up data compared with patients meeting our eligibility criteria. Follow-up continued from initiation of ART until (a) some change in ART regimen, (b) loss to follow-up, (c) death, or (d) study end in February 2007 (6 months after the last eligibility date). Patients who left their medical insurance fund or whose medical insurance fund changed to a different disease management program were censored as “lost to follow-up” at the date of departure.

Our primary analyses compared adolescents (defined as aged 11-19 years, inclusive) with adults (aged ≥20 years) based on age at ART initiation. The primary outcomes were virologic suppression (HIV viral load ≤400 copies/mL) and viral rebound, defined as virologic failure (viral load >400 copies/mL) after achieving virologic suppression. The cutoff value of 400 copies per milliliter was selected because some of the laboratories measuring HIV viral load used assays with a limit of detection of 400 copies per milliliter. Adherence rates were classified as ≤50%, 51%-67%, 68%-84%, 85%-99%, and 100% of possible pharmacy refills. Other covariates in the analysis included sex, race, CD4+ T-cell count and viral load at program enrollment, year of ART initiation, and number of viral load measurements. In a secondary analysis, we divided the study population into 3 age group strata: adolescent (11-19 years), young adult (20-29 years), and older adult (30 years or older).

Statistical Analysis

Two analytic methods to compare virologic suppression in adolescents vs. adults were used. In the first method, 4 prespecified time points for viral load assessment were used, 6, 12, 18, and 24 months after ART initiation. Assessments performed within 3 months of each specified time point were deemed valid for that time point. In addition, the following data were also recorded at each prespecified time point: (a) pharmacy refill adherence to that point and (b) last available post-ART viral load measurement. We then used virologic suppression at each time point as the dependent variable in a loglinear model, with adolescent status as an independent variable. Both univariate and multivariate models (including all covariates listed above) were analyzed. The imputation by chained equations technique was used in <4% of adults and <10% of adolescents; in this technique, a missing value in a variable is replaced by its predicted value, as determined by multiple regression with the rest of the full model predictors.28 The Pearson χ2 goodness-of-fit statistic was used to assess model fit. The second analysis employed a Cox proportional hazards model to evaluate the association between adolescent status and time from virologic suppression to virologic rebound. The assumption of proportional hazards was assessed by the model-based test for the time by log (t) interaction.

All P values reported are 2-tailed, with a value of <0.05 considered statistically significant. Fisher exact test and the Wilcoxon rank-sum test were used in 2-way comparisons of binary and continuous variables, respectively. Statistical analyses were performed using STATA Release 8.2 (Stata Corporation, College Station, TX).

Ethical Approvals

This study was approved by the University of Cape Town Research Ethics Committee and by the Aid for AIDS Clinical Advisory Board, Cape Town, South Africa.


Seven thousand seven hundred seventy-six eligible patients (97% on NNRTI-based ART vs. <3% on PI-based ART) were included, of whom, 154 were adolescents (11-19 years) per our definition, 1380 were young adults (20-29 years), and 6242 were adults (30 years and older) for a total adult (20.1-76.7 years) sample size of 7622. Characteristics of the study cohort are shown in Table 1. Adolescents were more likely than adults to be female (72.7% vs. 62.3%, P = 0.01) and to initiate ART in 2003 or later (50.1% vs. 40.3%, P = 0.02). The adolescents were less likely to get NNRTI-based ART (92% vs. 97.2%; P < 0.001) and more likely to have shorter follow-up duration [median 27 months; interquartile range (IQR) of 18.1-43.7 vs. 36.9 (IQR: 23.6-54.5), P < 0.001].

Demographic and Clinical Characteristics of Study Population (Adolescent: 10-19 Years of Age; Young Adult: 20-30 Years of Age; and Adult: 30 years or older)

In a subset of patients with adherence data available through 6, 12, and 24 months of follow-up, adolescents had consistently and significantly lower adherence than adults. Adolescents claimed medication for a median of 4 of 6 (IQR 3-5), 8 of 12 (IQR 5-10), and 15 of 24 (IQR 8-19) months, vs. 5 of 6 (IQR 3-6), 10 of 12 (IQR 6-12), and 19 of 24 (IQR 12-23) months for adults (P ≤ 0.001 at all time points). Similarly, the percentage of adolescents achieving 100% adherence was 20.7% at 6 months, 14.3% at 12 months, and 6.6% at 24 months compared with 40.5%, 27.9%, and 20.6% for adults (P < 0.01 at all time points, Table 1). For patients started on the NNRTI-based regimen, the proportion of adolescents with 100% adherence at 6, 12, and 24 months was 23.9%, 14.9%, and 7.6%, compared with 99.4%, 28.8%, and 21.5% for adults (P < 0.01 at all time points).

The proportion of adolescents achieving viral suppression was lower than that of adults, although the differences were significant only at 12, 18, and 24 months after ART initiation (Table 1). Patients achieving 100% 12-month adherence were significantly more likely to exhibit virologic suppression at 12 months, whether adolescent (91% of perfect adherers suppressed at 12 months vs. 45% of others, P = 0.007) or adult (86% vs. 59%, P < 0.001). The association between adolescent status and lower rates of virologic suppression persisted despite adjustment for potential confounders, although adjustment for adherence did weaken the measured association (Table 2).

Relative Risks for Virologic Suppression in Adolescents Compared With Adults

In the subset of patients who achieved initial virologic suppression (n = 5504 adults and 93 adolescents, of which 3805 adults and 62 adolescents had at least 1 viral load measurement after initial suppression), the proportion of adolescents with viral rebound was greater than for adults (31.3% vs. 16.6%, P = 0.02 at 6 months; 42.4% vs. 20.2% at 12 months, P = 0.004; 38.9% vs. 21.5% at 18 months, P = 0.09; and 37.5% vs. 24.2%, P = 0.24 at 24 months) (Table 1). This association between adolescent status and higher rate of viral rebound was sustained in both unadjusted and adjusted models (Table 3). Furthermore, adolescents were less likely than adults to experience immunologic recovery on ART as evidenced by their median CD4+ T-cell count (IQR)(cells/μL): 295 (135-482) vs. 246 (142-377), P = 0.26 at 6 months; 281 (154-538) vs. 276 (159-412) at 12 months, P = 0.96; 263 (157-439) vs. 308 (177-464) at 18 months, P = 0.72; and 172 (44-451) vs. 339 (187-496), P = 0.02 at 24 months) (Table 1).

Relative risks for Viral Rebound in Adolescents Compared With Adults

In Cox proportional hazards analysis in the subset of patients who achieved initial virologic suppression, adolescents compared with adults had a significantly shorter time to viral rebound when unadjusted [hazard ratio (HR) 2.10 (1.43-3.080; P < 0.001] and adjusted for both baseline characteristics and adherence [HR 2.18 (1.41-3.38); P < 0.001] (Fig. 1). In our secondary analyses, we found that young adults have virologic outcomes that are intermediate between those of adolescents and adults ≥30 years (Table 1 and Fig. 2). In the Cox proportional hazards analysis, adolescents compared with adults aged 20-29 years had a significantly shorter time to viral rebound when unadjusted [HR 1.82 (1.22-2.73); P = 0.003] and adjusted for both baseline characteristics and adherence [HR 1.79 (1.12-2.86); P = 0.02]. In addition, younger adults compared with adults ≥30 years had also a significantly shorter time to viral rebound when unadjusted [HR 1.18 (1.02-1.36); P = 0.02] and adjusted for both baseline characteristics and adherence [HR 1.20 (1.03-1.39); P = 0.02] (Fig. 2).

Time to rebound, adolescents vs. adults. The P value for log-rank test <0.001.
Time to rebound, comparing adolescents (11-19 years old) to young adults (20-29 years old) and to adults (≥30 years old).


Our results suggest that HIV-infected adolescents and young adults on ART in southern Africa have poorer adherence rates and poorer virologic outcomes than their adult counterparts. In this study, adolescents were approximately 50% less likely than adults to maintain perfect adherence at all time points and 70%-75% less likely to be virologically suppressed (≤400 copies/mL) at 1 and 2 years after ART initiation. At 6 months, rates of virologic suppression among adolescents and adults were similar; thus, lower rates of long-term suppression among adolescents were largely explained by more rapid viral rebound. Interestingly, we found that young adults (aged 19-20 years) have virologic outcomes that are intermediate between those of adolescents and adults ≥30 years (Fig. 2). Furthermore, adolescents were less likely than young adults, adults >30 years, and all adults to experience long-term immunologic recovery; despite having nearly identical initial CD4+ T-cell counts, adolescents experienced very small increases in CD4+ T-cell counts after 2 years, from a median of 144 cells per microliter to 172 cells per microliter vs. increases in young adults, adults >30 years, and all adults from a median of 175 cells per microliter to 348 cells per microliter (P = 0.01), 140 cells per microliter to 337 cells per microliter (P = 0.03), and 146 cells per microliter to 339 cells per microliter (P = 0.02), respectively (Table 1). Our data are in agreement with studies from the developed world. Flynn et al16 also reported that adolescents infected with HIV via high-risk behaviors have less than optimal responses to highly active antiretroviral therapy, with only 24% achieving and maintaining undetectable viral loads over 3 years.13 Also in this study, CD4+ T-cell count measurements improved from entry to the end of follow-up only in the subjects with sustained undetectable viral loads.

We also found in the present study that HIV-infected adolescents were more likely than adults to be female (72.7% vs. 62.3%, P = 0.01), a finding consistent with previous epidemiological studies in South Africa which found higher HIV seroprevalence in adolescent females that was explained by greater high-risk sexual behavior, earlier sexual debut, greater likelihood of older sexual partners, and additional sociological issues such as gender-power imbalance.29,30

Low medication adherence in adolescents, the very population most likely to benefit from optimal adherence (ie, those who would have the longest life expectancy on successful ART), underscores the urgent need to identify risk factors that contribute to poor adherence in HIV-infected adolescents in sub-Saharan Africa. Such knowledge would help guide the design of targeted interventions to achieve or maintain high adherence rates in this population. Given the limited availability of second-line and salvage ART regimens in this region, preserving long-term success of first-line ART is critical, particularly in adolescents who would be expected to live longer than HIV-infected adults by virtue of their younger age, if both groups are able to achieve equivalent treatment success.

Barriers to risk factors for nonadherence to HIV medication in adults from sub-Saharan Africa have been reported and include nondisclosure to a loved one or fear of being stigmatized,31,32 substance abuse (mostly alcohol),31 cost33-35 in countries where ART is not free of charge, and the complexity of the drug regimen.31 Although some of these factors may be specific to this setting, others overlap with factors identified in adolescents with HIV infection or other chronic diseases from industrialized countries. Indeed, as mentioned earlier, factors associated with poor adherence in the REACH cohort included depression, pill burden, advanced HIV status, alcohol use, dropping out of school, side effects, and complications of day-to-day routine.8,9,14,15 Furthermore, medication noncompliance for other chronic conditions seemed to be associated with a restriction of independence in daily life, lack of harmony in family relations, and low self-esteem in teenage epileptics36 and forgetfulness, busy schedules, and nonavailability of medication in adolescents with cancer.37 In a qualitative study in Uganda, Bikaako-Kajural et al38 found that structural factors including poverty and stigma were barriers to both ART and cotrimoxazole adherence, even in children who had complete disclosure and a supportive relationship with their parents. If these factors are shared by adolescents, then interventions to encourage voluntary testing and disclosure of HIV status, or to reduce the cost and complexity of ART, might also improve adherence rates in this age group. Further research on barriers to ART adherence in adolescents is critically needed.

Our study has certain limitations. First, although our study population is among the largest cohorts on ART under observation in sub-Saharan Africa, our sample size for this analysis was limited by the small proportion of these patients who were adolescents. Adolescents are underrepresented in the Aid for AIDS database because many HIV-infected adolescents may be newly infected and therefore not at a sufficiently advanced disease stage to qualify for ART (CD4+ T-cell count <350 cells/μL). Furthermore, infected adolescents who are eligible to begin ART are less likely to be previously employed and therefore less likely to qualify for private health insurance-unless they are children of a qualifying adult-because only adolescent dependents of adult employees in medical insurance schemes participating in the Aid for AIDS program are eligible. Finally, our dataset was not originally designed as a comprehensive research tool and so is limited in certain data elements and is not structured to capture the reasons for nonadherence. As a result of these limitations, further studies on ART adherence in African adolescents are needed to determine whether the results from this study are fully generalizable (eg, to the public sector) and to describe relationships that could not be measured with the limited data in the current database. Ultimately, studies of interventions to improve adherence in this vulnerable population will be essential to maximize the number of HIV-infected infants who successfully survive into adulthood.

In conclusion, compared with adults, adolescents in southern Africa are less adherent to ART, have lower rates of virologic suppression at all time points after ART initiation, and experience more rapid viral rebound. Studies to determine barriers to adherence in adolescents and to develop interventions to address them are sorely needed in this setting.


Drs. J.B.N., R.E.C., and G.M. acknowledge research support from the National Institute of Allergy and Infectious Diseases, United States National Institutes of Health, AI 5535901 and AI 016137. We are grateful to Joanna Downer, PhD, and Roderick Graham, MA, for critical reading of this article. Author contributions-Conception and design: J.B.N., G.M., and M.C.; interpretation of the data: J.B.N., M.H., L.R., H.N., M.C., G.M., D.W.D., and R.E.C.; drafting of the article: J.B.N., D.W.D., and G.M.; critical revision of the article for important intellectual content: J.B.N., D.W.D., R.E.C., M.C., and G.M.; final approval of the article: J.B.N., M.H., D.W.D., H.N., R.E.C., L.R., G.M., and M.C.; provision of study materials or patients: M.H. and L.R.; statistical expertise: J.B.N., D.W.D., and H.N.; Administrative, technical, or logistic support: R.E.C. and L.R.


1. Markowitz M, Conant M, Hurley A, et al. A preliminary evaluation of nelfinavir mesylate, an inhibitor of human immunodeficiency virus (HIV)-1 protease, to treat HIV infection. J Infect Dis. 1998;177:1533-1540.
2. Markowitz M, Saag M, Powderly WG, et al. A preliminary study of ritonavir, an inhibitor of HIV-1 protease, to treat HIV-1 infection. N Engl J Med. 1995;333:1534-1539.
3. Hirsch M, Steigbigel R, Staszewski S, et al. A randomized, controlled trial of indinavir, zidovudine, and lamivudine in adults with advanced human immunodeficiency virus type 1 infection and prior antiretroviral therapy. J Infect Dis. 1999;180:659-665.
4. Staszewski S, Morales-Ramirez J, Tashima KT, et al, for the Study 006 Team. Efavirenz plus zidovudine and lamivudine, efavirenz plus indinavir, and indinavir plus zidovudine and lamivudine in the treatment of HIV-1 infection in adults. N Engl J Med. 1999;341:1865-1873.
5. Starr SE, Fletcher CV, Spector SA, et al, for the Pediatric AIDS Clinical Trials Group 382 Team. Combination therapy with efavirenz, nelfinavir, and nucleoside reverse-transcriptase inhibitors in children infected with human immunodeficiency virus type 1. N Engl J Med. 1999;341:1874-1881.
6. Krogstad P, Lee S, Johnson G, et al. Nucleoside-analogue reverse-transcriptase inhibitors plus nevirapine, nelfinavir, or ritonavir for pretreated children infected with human immunodeficiency virus type 1. Clin Infect Dis. 2002;34:991-1001.
7. World Health Organization. Towards Universal Access: Scaling Up Priority HIV/AIDS Interventions in the Health Sector. Progress Report April 2007. Geneva, Switzerland: WHO Press; 2007.
8. Murphy DA, Wilson CM, Durako SJ, et al. Antiretroviral medication adherence among the REACH HIV-infected adolescent cohort in the USA. AIDS Care. 2001;13:27-40.
9. Belzer ME, Fuchs DN, Luftman GS, et al. Antiretroviral adherence issues among HIV-positive adolescents and young adults. J Adolesc Health. 1999;25:316-319.
10. Paterson DL, Swindells S, Mohr J, et al. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med. 2000;133:21-30.
11. Bangsberg DR. Less than 95% adherence to nonnucleoside reverse-transcriptase inhibitor therapy can lead to viral suppression. Clin Infect Dis. 2006;43:939-941.
12. Nachega JB, Hislop M, Dowdy D, et al. Adherence to non-nucleoside reverse transcriptase-based HIV therapy and virologic outcomes. Ann Intern Med. 2007;146:564-573.
13. Mills EJ, Nachega JB, Buchan I, et al. Adherence to antiretroviral therapy in sub-Saharan Africa and North America: a meta-analysis. JAMA. 2006;296:679-690.
14. Murphy DA, Belzer M, Durako SJ, et al, and Adolescent Medicine HIV/AIDS Research Network. Longitudinal antiretroviral adherence among adolescents infected with human immunodeficiency virus. Arch Pediatr Adolesc Med. 2005;159:764-770.
15. Murphy DA, Sarr M, Durako SJ, et al, for the Adolescent Medicine HIV/AIDS Research Network. Barriers to HAART adherence among human immunodeficiency virus-infected adolescents. Arch Pediatr Adolesc Med. 2003;157:249-255.
16. Flynn PM, Rudy BJ, Lindsey JC, et al, and PACTG 381 Study Team. Long-term observation of adolescents initiating HAART therapy: three-year follow-up. AIDS Res Hum Retroviruses. 2007;23:1208-1214.
17. Nachega JB, Hislop M, Dowdy DW, et al. Adherence to highly active antiretroviral therapy assessed by pharmacy claims predicts survival in HIV-infected South African adults. J Acquir Immune Defic Syndr. 2006;43:78-84.
18. Aid for AIDS. AfA clinical guidelines. Available at: Accessed October 29, 2006.
19. Choo PW, Rand CS, Inui TS, et al. Validation of patient reports, automated pharmacy records, and pill counts with electronic monitoring of adherence to antihypertensive therapy. Med Care. 1999;37:846-857.
20. Steiner JF, Koepsell TD, Fihn SD, et al. A general method of compliance assessment using centralized pharmacy records: description and validation. Med Care. 1988;26:814-823.
21. Steiner JF, Prochazka AV. The assessment of refill compliance using pharmacy records: methods, validity, and applications. J Clin Epidemiol. 1997;50:105-116.
22. Low-Beer S, Yip B, O'Shaughnessy MV, et al. Adherence to triple therapy and viral load response. J Acquir Immune Defic Syndr. 2000;23:360-361.
23. Gross R, Yip B, Lo Re V III, et al. A simple, dynamic measure of antiretroviral therapy adherence predicts failure to maintain HIV-1 suppression. J Infect Dis. 2006;194:1108-1114.
24. Grossberg R, Zhang YW, Gross R. A time-to-prescription-refill measure of antiretroviral adherence predicted changes in viral load in HIV. J Clin Epidemiol. 2004;57:1107-1110.
25. Harrigan PR, Hogg RS, Dong WW, et al. Predictors of HIV drug-resistance mutations in a large antiretroviral-naive cohort initiating triple antiretroviral therapy. J Infect Dis. 2005;191:339-347.
26. Hogg RS, Heath K, Bangsberg DR, et al. Intermittent use of triple-combination therapy is predictive of mortality at baseline and after 1 year of follow-up. AIDS. 2002;16:1051-1058.
27. Wood E, Hogg RS, Yip B, et al. Impact of baseline viral load and adherence on survival of HIV-infected adults with baseline CD4 cell counts ≥ 200 cells/μL. AIDS. 2006;20:1117-1123.
28. Royston P. Imputation by chained equations. Available at: = st0067_3. Accessed July 4, 2008.
29. Connolly C, Colvin M, Shishana O, et al. Epidemiology of HIV in South Africa-results of a national, community-based survey. S Afr Med J. 2004;94:776-781.
30. Singh JA, Karim SS, Karim QA, et al. Enrolling adolescents in research on HIV and other sensitive issues: lessons from South Africa. PLoS Med. 2006;3:e180.
31. Mills EJ, Nachega JB, Bangsberg DR, et al. Adherence to HAART: a systematic review of developed and developing nation patient-reported barriers and facilitators. PLoS Med. 2006;3:e438.
32. Nachega JB, Stein DM, Lehman DA, et al. Adherence to antiretroviral therapy in HIV-infected adults in Soweto, South Africa. AIDS Res Hum Retroviruses. 2004;20:1053-1056.
33. Weiser S, Wolfe W, Bangsberg D, et al. Barriers to antiretroviral adherence for patients living with HIV infection and AIDS in Botswana. J Acquir Immune Defic Syndr. 2003;34:281-288.
34. Crane JT, Kawuma A, Oyugi JH, et al. The price of adherence: qualitative findings from HIV positive individuals purchasing fixed-dose combination generic HIV antiretroviral therapy in Kampala, Uganda. AIDS Behav. 2006;10:437-442.
35. Laniece I, Ciss M, Desclaux A, et al. Adherence to HAART and its principal determinants in a cohort of Senegalese adults. AIDS. 2003;17(Suppl 3):103-108.
36. Friedman IM, Litt IF. Adolescents' compliance with therapeutic regimens: psychological and social aspects and intervention. J Adolesc Health Care. 1987;8:52-67.
37. Tebbi CK, Cummings KM, Zevon MA, et al. Compliance of pediatric and adolescent cancer patients. Cancer. 1986;58:1179-1184.
38. Bikaako-Kajura W, Luyirika E, Purcell DW, et al. Disclosure of HIV status and adherence to daily drug regimens among HIV-infected children in Uganda. AIDS Behav. 2006;10(Suppl 4):85-93.

adults; adherence; adolescents; antiretroviral therapy; HIV; sub-Saharan Africa

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