Adherence to HIV Care and Associated Health Functioning among Youth Living with HIV in Sub-Saharan Africa

Abstract

Older adolescents and young adults (youth) living with HIV (YLH) in sub-Saharan Africa are at high risk for poor HIV treatment adherence and associated negative health outcomes including viral non-suppression. To describe this risk, we conducted a comprehensive review of studies involving YLH. Eligible studies compared youth adherence or adherence-related health functioning to older or younger samples, examined factors associated with adherence or health outcomes among YLH, or evaluated adherence interventions with YLH. Databases searched included MEDLINE, Web of Science, Global Health, CINAHL, Africa-Wide Information, PsycINFO, and the Cochrane Library. Of the 7,054 articles found, 156 were reviewed and 130 were eligible. Across 16 adherence-related behaviors or health outcomes such as lost to follow-up, retention in care, antiretroviral use, CD4 count, viral suppression, and mortality, 73% of studies comparing YLH to other age groups (n=106) found worse outcomes among YLH. In 22 studies, barriers and facilitators to adherence were identified, some unique to YLH (e.g., conflicting treatment expectations of providers) and some common to other age groups. Finally, of the eight adherence interventions with YLH reviewed, five showed evidence of being effective. Our findings suggest that YLH in sub-Saharan Africa face numerous obstacles to engaging in HIV treatment across a range of shifting social contexts. Accounting for this group’s transition to treatment self-management, developmentally tailored and holistic interventions should be the focus of adherence promotion efforts.

INTRODUCTION

Of the world’s 37 million individuals living with HIV, nearly 70% reside in sub-Saharan Africa (SSA)¹. Fortunately, antiretroviral therapy (ART) coverage in the region has dramatically expanded. Between 2010 and 2015, for example, the number of individuals receiving ART more than doubled in southern and eastern Africa². Consistent adherence to HIV care, however, is very difficult. Only an estimated two-thirds of patients achieve 90% ART adherence in SSA³, and within a year, 25% who start ART are not retained in care⁴. One group is particularly vulnerable to poor adherence: older adolescents and young adults (youth) living with (YLH). Compared to other age groups, this population has shown lower rates of ART adherence⁵, greater treatment attrition^6–8, and worse health outcomes⁸. To document the extent of these disparities, the current study conducted a comprehensive review of the literature.

Observation of the factors associated with these outcomes among YLH is also warranted. Research into why YLH in SSA face stark treatment challenges is scarce. Some may assume that these young people are similar in their social and cognitive development to adults. While it is true that youth in SSA continue to face adult expectations during middle to late adolescence⁹, many also now take on adult roles at later ages (i.e., in their 20s)¹⁰. Further, the classification of late adolescence and early adulthood as a developmentally distinct period in Western settings has been applied to young people in SSA as well¹⁰. The age group of 15 to 24, defined as “youth” by the United Nations, captures young people in SSA at the widely varying ages that they begin adulthood transitions. For YLH, treatment self-management is a major transition, one many are likely unprepared to make¹². It occurs while YLH also encounter the many other barriers to adherence people living with HIV in SSA of all ages experience¹³. Individual studies have supported these claims¹⁴; however, existing reviews have focused on research related to treatment adherence among SSA-based children or adolescents¹⁵ or adults, undefined by age¹⁶. Thus, experiences of YLH in this period of life have yet to be fully evaluated.

A result of the above-mentioned research gap is perhaps an absence of adherence interventions designed specifically for YLH. Moreover, unlike research conducted with studies from high-income countries¹⁷, reviews of adherence interventions in SSA have mostly examined those intended for adults^18–20, or have broadly focused on youth, inclusive of YLH and younger samples^21,22. We know from these latter reviews that YLH-tailored interventions are rare²³. Because of their unique stage of development, YLH may not benefit from an adult or child/adolescent-focused intervention. While adult interventions assume a level of autonomy that many YLH have not yet obtained, interventions for younger populations are likely to under-utilize their increased autonomy, instead focusing on caretaker or provider involvement²⁴. Alternatively, existing interventions, untailored to this age group, could prove to effectively engage youth in care, a question not posed by previous reviews.

The current study had three aims. First, we reviewed the evidence age-related adherence and health disparities that we hypothesized would exist in this population when compared to other age groups. We focused exclusively on YLH in SSA and broadly defined our adherence and health factors to include all ART adherence behaviors, medical treatment retention characteristics, and HIV-related health outcomes. Second, we examined all studies which have presented data on the factors associated with these behaviors and outcomes within YLH samples. Finally, we report on extant publications of adherence promotion interventions for YLH or interventions that have tested their impact on YLH among the broader cohort.

METHOD

Search Strategy and Selection Criteria

To provide a comprehensive review, we searched the following databases: MEDLINE, Web of Science, Global Health, CINAHL, Africa-Wide Information, PsycINFO, and the Cochrane Library. Searches were conducted using keywords and MESH terms, with the addition of the asterisk operator for alternate versions, combining four categories: population descriptors (e.g., adolescen*, young adult), HIV-related terms (e.g., antiretroviral), indicators of adherence (e.g., LTFU), and geographic regions. Retrieval of search results and removal of duplicates was managed using Endnote. An initial screen for ineligible articles based on keywords was conducted. This was followed by two reviewers (NT, AL) independently screening the remaining titles and abstracts. Inter-rater agreement was 86% on a subsample of studies (n = 50). A partial-text screen was then performed by one reviewer (NT) to briefly examine the articles for eligibility based on sample age and obvious exclusion criteria.

We included only peer-reviewed articles presenting original data from SSA. Studies were included if their YLH participants were within or between the ages of 15 to 25 (inclusive of ages 15 and 25) or if the mean sample age fell within the 15 to 25 range. The age limit of 25 was chosen rather than 24 after a preliminary review revealed that many studies used this cut-off. Adherence was defined as ART adherence or initiation or characteristics of retention (e.g., linkage to care, lost to follow-up, missed clinic visits). Studies with any HIV-related health outcome (e.g., viral suppression, mortality) were also included. Eligible studies could fall into three mutually inclusive categories: (1) studies comparing outcomes between YLH and other age groups; (2) studies examining factors associated with adherence or health functioning among YLH; and (3) studies of adherence interventions designed specifically for YLH or studies of interventions which examined age (with a youth grouping) as a moderator of intervention outcomes. Quantitative studies in the second category must have conducted a significance test. Only English language articles published prior to November 2017 were reviewed. Studies were excluded if they did not meet inclusion criteria. In addition, studies primarily focused on specific populations (e.g., pregnant women) were excluded to increase generalizability. Case studies, case series, quantitative studies with small youth samples (<10 participants), studies of HIV/TB co-infection, studies with a biomedical focus, and studies using population-based estimates as data were excluded. A full-text review of studies passing the title and abstract screen and the partial-text screen was conducted to determine study eligibility.

Data Extraction

Extracted data included study author, year, country, design, age groups, sample size of (full sample and YLH sample), adherence or health outcome, and a summary of key findings. For comparison studies, summaries included the significance of effects when statistical tests were conducted. For studies reporting factors associated with youth adherence, factor type was extracted. Additional data was also extracted from intervention studies: whether the intervention was tailored for YLH, descriptive information, and intervention outcomes.

RESULTS

Searches results are presented in a flow diagram (Figure 1). A total of 130 studies met eligibility criteria (see Appendix 1; studies cited below in parentheses): 82% were comparison studies (n = 106); 17% were studies examining factors associated with adherence (n = 22); and 6% were intervention studies (n = 8). Six studies met criteria for multiple categories. Most studies were observational with quantitative methodology (111; 85%); 11 (9%) were qualitative; eight (6%) had a pre-post intervention or randomized controlled trial design; and one study used multiple designs. Studies were published between 2002 and 2017 with most (91%) being published after 2011. At each review stage, studies were most commonly excluded due to not meeting the age inclusion criteria. Many did not group age to identify YLH (e.g., < 35 vs. ≥ 35 years), examined age as a continuous variable, or included age categories encompassing our target age range (e.g., 10 to 19) without providing a sample mean. The most common discrete age classification for eligible studies was 15–24 (43%) followed by 18–24 (12%). Other studies consisted only of older adolescents (age < 20; 16%) while only two studies were focused primarily or exclusively on young adults (age > 19; 2%). Among comparison studies that reported a sample size for the YLH sample (n = 87), the proportion of YLH represented in their total sample ranged from 2% to 86% and was generally low (mean percent of YLH = 13%). Most reports came from East Africa (70%), followed by Southern Africa (22%), West Africa (9%), and Central Africa (3%), with six from multiple regions. The countries of South Africa (20%) and Uganda (19%) had the highest representation.

Fig. 1.

Workflow of comprehensive review. Adapted from PRISMA guidelines (Moher et al., 2009).

Comparing YLH to Other Age Groups

Overall, of the 106 comparison studies, 73% found evidence for worse outcomes among YLH in comparison to other groups; 15% found evidence for better outcomes among YLH; and 17% found no evidence for age-related differences (percentages do not total 100% because five studies reported mixed findings). Age-related comparison reports of adherence behavior and health functioning were assessed over a total of 16 outcomes. Studies reported on LTFU (45%), mortality (40%), viral load (24%), ART adherence (13%), and CD4 count (12%). Less frequently were reports of ART uptake (8%), linkage to care (7%), retention (7%), missed clinic visits (5%), or other outcomes (e.g., switching to second-line ART; 8%). Four comparison studies (4%) did not conduct significance tests to determine age-related differences (1–4).

Linkage to care and ART uptake, adherence, and discontinuation.

Of the 26 studies examining these outcomes, 16 (62%) found worse outcomes among YLH compared to other age groups. Six reported on linkage to HIV care (5–10). In all but one, which found no age differences (5), YLH were less likely than adults to be linked to care. Similarly, five of seven ART uptake studies found that YLH were less likely than adults to be initiated to ART (2, 3, 10–12); the remaining two found either no age differences (13) or a higher likelihood of ART uptake among YLH compared to adults (14). Twelve studies reported on ART adherence; half found that YLH were at greater risk for poor adherence compared to younger or older samples (15–20) and the other half found no age-related differences in adherence (21–26). One study found no differences in rates of discontinuing ART based on patient age (27).

HIV-related health functioning.

Viral load, measured in different ways (e.g., virologic failure, viral suppression), was the most common indicator of HIV-related health functioning. Of the 25 studies examining viral load, 17 (68%) found evidence for worse outcomes among YLH compared to younger (28) or older samples (1, 10, 19, 29–41); the remaining eight found no age differences (22, 42–48). Evidence for other health outcomes was less consistent: eight studies reported better outcomes for youth compared to adults in terms of immunologic functioning (e.g., change in CD4 count following ART initiation) or morbidity (e.g., presence of advanced disease) (13, 34, 42, 44, 49–52); four reported no age differences in CD4 count response (22, 31, 33, 53); and three studies found that YLH had worse outcomes compared to adults in terms of CD4 count, antiviral (ARV) resistance, or having to switch to second-line ARVs (30, 54, 55).

LTFU and related outcomes.

LTFU for pre-ART or post-ART care was a common outcome; although, its measurement varied widely, and it was often measured jointly with mortality as a single outcome. Nevertheless, consistently, in 42 of 47 studies (89%) of LTFU, youth had worse outcomes than children or younger adolescents (56–59), adults (1, 15, 29, 33, 35, 43–45, 50, 53, 54, 60–80), or both younger and older age samples (34, 81–85). The remaining five studies found no differences based on age in risk for LTFU (27, 86–89). Fifteen studies of other adherence to care indicators (i.e., retention, missed clinic visits, treatment interruptions, and transferring to other clinics) had similar findings: nine found that YLH had worse outcomes than adults or younger patients (4, 38, 42, 83, 90–94); five found no age-related differences (27, 95–98); and one found that YLH were at lower risk for missed clinic visits than adults (88).

Mortality.

Risk for mortality was reported in 41 studies. No consistent pattern of results was observed. Several studies found that youth were at greater risk for LTFU and mortality as a combined outcome (nine studies) or mortality as a sole outcome (seven studies) compared to adults (1, 58, 61, 69–71, 75, 76, 79, 99, 100), younger age groups (57), or both older and younger age groups (81, 83–85). Almost an equal number (17) found no significant age-related differences in mortality risk (25, 32–34, 43, 44, 54, 60, 66, 74, 78, 80, 87–89, 101, 102). Finally, eight reported that youth were at lower risk for mortality than adults (35, 50, 67, 72, 103–106).

Factors Associated with Adherence among YLH

Table 1 summarizes the factors found to be related to adherence and health outcomes. Half of the 22 studies were qualitative, one used qualitative and quantitative methods, and the remaining studies were solely quantitative. Most focused on ART adherence (17; 73%), while others examined LTFU, retention, linkage to care, mortality, and switch to second-line ART.

Table 1.

Summary of Factors Associated with Treatment Adherence and Health Outcomes among Youth Living with HIV

Category of Risk/Protective Factor	Factors Associated with Negative Outcome	Factors Associated with Positive Outcome
Demographic	Male gender	Female gender
Psychological, cognitive, and behavioral	Psychological distress Alcohol use Feeling like a burden on others Resentment for being infected Denial/anger of lifelong ART treatment Fear of HIV disclosure (family, school, clinic, peers, partner) Desire to not feel different Non-adherence as a tactic to hurt others Changing weekly routine Conflict with day-to-day activities Conflict with leisure activities (parties, alcohol use) Spending nights away from home Belief in traditional healing Forgetfulness	Having reasons to live Recognition of health benefits Personal agency Belief that HIV-negative peers also have health problems Motivation to stay in school Use of ARV concealment strategies Prayer Attendance at religious services Reminders to take medication and go to clinic Keeping a daily routine
Treatment/disease-related	High (> 350) or very low (<100) CD4 count Advanced disease (WHO State III/IV) First treated with efavirenz (compared to nevirapine) On cotrimoxazole prophylactic therapy Burden of ARV pill amount, size, smell, and taste Burden of daily ARV use ARV side effects Not knowing own HIV status ART initiation as an older adolescent (vs. at a younger age)	High CD4 count (> 350) Advanced disease (WHO Stage IV) On ART On TB treatment (pre-ART care only) Pill ARV delivery (compared to syrup) Once daily ARV regimen (vs. more frequent ARV use) Knowledge of HIV status
HIV clinic	Peer groups at clinic not age-specific Adolescent-specific clinic hours Clinic screens for STIs Attendance at HIV clinic alone Poor provider support Rushed clinic appointments Long clinic wait times Inadequate post HIV test counseling Lack of confidentiality and privacy at clinic Conflicting expectations for self-care from HIV clinic	Peer support groups at clinic Clinic has adolescent peer educators Clinic provides condoms Urban clinic setting (vs. semi-urban) Provider support HIV testing during hospitalization VCT entry into care (vs. other points of entry) Same day treatment following HIV diagnosis
Family and peers	Non-disclosure of HIV status at home Lack of family adherence support Discrimination at home Anti-ART family beliefs Death of parent or spouse due to HIV infection Stigma felt by caregivers who pick up ARVs Lack of privacy at home or foster care Avoidance by friends and colleagues in close relationships Conflict with time spent forming peer relationships	HIV disclosure to family and peers HIV treatment-related support from family Tangible support (money, food, rides) from family Emotional support from family Living with HIV-positive family member Parents bring ARVs to boarding school Parent present during HIV diagnosis HIV-negative peer support HIV treatment-related from peers and partners
School	Non-disclosure of HIV status to school staff Discrimination at school School policy on absenteeism Lack of privacy for taking ARVs at school	Supportive school staff Being in school (vs. out of school) HIV-negative peer support at school
Economic resources	Low access to food/water to take ARV pills Costs of transportation Costs of non-ARV medication

Demographic factors.

Of the demographic factors examined, only gender emerged as a correlate of adherence or health functioning. Young men were at greater risk for nonadherence (i.e., ART adherence and LTFU/mortality) compared to young women (81, 107, 108).

Psychological, cognitive, and behavioral factors.

In six studies, behavioral health issues – depressive symptoms (109–112), posttraumatic stress (109), general mental health problems (109, 113), and/or alcohol use (107, 112) – were associated with ART nonadherence.

Cognitive factors associated with adherence were identified in 10 studies. Forgetfulness was as a barrier to ART adherence (16, 114–117). Attitudes and beliefs were barriers as well including resentment for being HIV infected (118), feeling one was a burden on others (118), and the denial of, or anger towards, needing lifelong HIV treatment (115). One study identified the desire of YLH to not want to feel different from their peers as linked to nonadherence (115). Fear of inadvertent HIV disclosure was another barrier (114, 116, 119). YLH feared disclosure to family members (115), staff and peers at school (120), peers and partners in the community (16, 115, 121), and health clinic staff (112, 119). A study also revealed how beliefs in spiritual healing can promote ART cessation (114). More positive beliefs, conversely, were related to optimal adherence (115, 120, 121), including the recognition of ART health benefits (112, 114–117, 120). Further, one study identified the positive influence of personal agency; youth who felt responsible for their own care and able to initiate care had success in seeking treatment (118).

Certain behaviors were associated with adherence as well (six studies). Reports indicated that YLH found it difficult to take ARVs due to changing weekly schedules (16), conflict with daily activities (e.g., 16, 114, 116, 121), and conflict with leisure activities (115). Other behaviors promoted adherence: use of reminder alarms, having friends or family give ART reminders, and keeping a set daily routine; 114–116, 121. One quantitative study found a positive association between prayer and attendance at religious services and ART adherence (113).

Treatment or disease-related factors.

Health factors, co-morbid treatment, ART use and delivery, and HIV status awareness were associated with adherence (12 studies). Mixed findings were reported when examining CD4 count and disease progression; one study found that YLH with high (> 350) or very low (<100) CD4 counts compared to other YLH had a greater risk for LTFU or mortality (81), while a second study observed that youth with high CD4 counts had a lower risk for LTFU (122). Similarly, YLH with an advanced disease stage (WHO Stage IV or Stage III or IV), either currently (123) or at pre-ART initiation (107), compared to youth with a less advanced stage (WHO Stage I or Stage I or II) have been found to have both better (123) and worse (107) ART adherence outcomes. Outcomes for YLH receiving treatment also for co-morbid conditions also varied. YLH on TB treatment were found to be at lower risk for LTFU/mortality than youth not on TB treatment (81). Conversely, being on cotrimoxazole prophylactic therapy was associated with worse ART adherence (123)

ART initiation, medication type, and mode of delivery also influenced adherence and treatment outcomes. One study found a link between being on ART and a lower risk for LTFU (122). A second study observed that YLH first treated with efavirenz compared to youth first treated with nevirapine had a higher rate of switching to second-line ART (124). Timing of initiation was also linked to this outcome with youth initiating ART as an older adolescent vs. as a child more likely to be switched (124). Further, youth on second-line treatment had worse ART adherence than those on first-line treatment (124). Studies cited the burden of ART medication side effects, daily uptake, and pill characteristics (e.g., taste) as barriers to adherence (112, 114, 116, 117, 120, 121, 125). Conversely, other ART factors were associated with better adherence including pill (vs. syrup) delivery and once daily (vs. more frequent) pill regimens (117, 120).

There were also reports of YLH not knowing their own HIV status. Being unaware was linked in one qualitative study to problems with ART adherence (114). In contrast, awareness was found in a second study to be a facilitator of optimal adherence (112).

Clinic factors.

Clinic characteristics were discussed in six studies. One study sampling YLH from four SSA countries found that youth attending clinics with certain services (i.e., peer educators, condom distribution) were at lower risk for a LTFU/mortality outcome than youth at clinics without these services (81). Unexpectedly, this same study found that YLH at clinics using related services (e.g.,, adolescent-specific hours) were at greater risk for LTFU/mortality than other youth (81). Other clinic factors positively affecting retention outcomes observed in our review included being from an urban (vs. semi-urban) clinic (81), entry into HIV treatment via voluntary testing (vs. perinatal care) (81), getting HIV tested during a hospitalization (120), adequate post-test counseling (120), and same day HIV treatment following diagnosis (120). In addition, YLH in qualitative studies identified several clinic barriers to adherence: long wait times (120), little privacy or confidentiality (119), and feeling rushed during appointments (125).

The social context of HIV clinic attendance was also a consideration. Studies found that while supportive clinic staff can engage youth in treatment (119, 120), unsupportive staff can have the opposite effect (119, 120). One study of YLH who were LTFU found that clinic staff had conflicting role expectations for youth: on the one hand, they expected youth patients to attend appointments with their guardians who they believed should be actively involved in their care; on the other hand, they blamed youth for missing appointments (119). Clinic peers groups were also found to promote adherence and protect against LTFU (81, 114, 120). However, one qualitative study found that a clinic without age-specific peer groups (e.g., grouping 17 year-olds with 12 year-olds) could be a barrier to retention (119). Finally, a quantitative study of an older adolescent sample found that YLH who attended their clinic appointments alone had worse ART adherence than those who attended with someone else (107).

Family and peer factors.

Eleven studies observed the complex role that families play in treatment. A major obstacle to adherence was found to be youths’ non-disclosure of their HIV status to family members (107, 119–121). A related concern was a lack of privacy at home to store and use ART (112). Studies showed that families can also be unsupportive of treatment (16, 119), voice anti-ART beliefs (120), discriminate against YLH (16, 119), and experience HIV stigma when providing youth treatment support (112). In addition, death of a parent or spouse was associated with worse ART adherence in three studies (110, 119, 123). Families were found to be facilitators of positive outcomes as well via their support to YLH (114, 116, 117, 119–121). One study found that having an HIV-positive family member promoted adherence (121).

Similarly results were indicated when examining the friends and partners of YLH. Youth who had disclosed their HIV status to peers or partners were found to receive HIV treatment support (117, 121). However, another study saw an association between being avoided by “friends and colleagues” in close relationships and problems with ART adherence (110). Findings from a final study showed how ART use and clinic attendance interfered with young people’s pursuit of new relationships, which led, consequently, to adherence problems (125).

School factors.

Results of a quantitative study with a large sample of YLH demonstrated that being in school was associated with better ART adherence (107). Nonetheless, other research identified several school-related barriers to adherence. The largest concern was privacy (16, 112, 119, 121). YLH often attended boarding schools where they had to hide their ART and feared HIV disclosure. Studies found that they also feared disclosure and disciplinary actions due to missing school for doctor’s appointments (112, 119, 120). Qualitative reports of YLH revealed that HIV disclosure could have adverse consequences while non-disclosure was often associated with adherence problems (112, 119). School staff and peers could offer treatment-related support (112, 120, 121); however, they could also be a source of HIV-related discrimination (112, 119).

Economic resources.

Free ARV medication is often available to youth in SSA. However, other costs associated with care including the costs of medication for ARV side-effects (120), transportation to attend clinic appointments or obtain ARV refills (116, 117), and food and water to take ARV medication (112, 116), were found to challenge youth adherence efforts.

Adherence Interventions

Of the eight intervention studies uncovered in our review, four examined interventions not designed specifically for youth. Two used the same sample of Ugandan participants enrolled in an RCT (5, 95). Each examined the effects of an extended counseling intervention (involving, for example, monthly home visits from a counselor) compared to standard of care counseling on either linkage to pre-ART care (5) or retention in pre-ART care (95). The studies conducted age-related subgroup analyses and each determined that the intervention had a significant effect for YLH (ages 18 to 24) on their respective outcome. A third study from Uganda examining the effect of an adherence intervention designed also conducted a subgroup analysis with YLH aged 18 to 25 years (126). This multicomponent intervention included counseling, health education, enhanced clinic monitoring of adherence, and other adherence strategies (e.g., text messaging, use of a treatment supporter). No significant impact of the intervention was found on rates of ART adherence for YLH; however, high initial rates of adherence, as well as the small sample size of YLH (<5% of the sample; n = 40), may have reduced power to detect an effect (126). The fourth study reported on the outcomes of participation in South African community-based adherence clubs (CAC), an approach led by health workers for patients with optimal adherence, vs. participation in traditional community health centers (29). The CAC approach proved to reduce risk of LTFU for all adult age groups but not for youth participants (ages 16 to 24) (29).

The four remaining interventions studies were tailored for YLH. Three had positive impact on adherence outcomes. The first, a Ugandan study, evaluated the large-scale implementation of an intervention which had several strategies to improve youth adherence to care including: formation of peer-led support groups, training of physicians and nurses at healthcare facilities to provide youth-focused care, creation of separate youth-friendly clinic spaces, and linking support group members to healthcare facilities with a voucher program (127). Researchers found significant improvements in several outcomes including ART uptake, ART adherence, and CD4 monitoring among their participants (127). A second study also evaluated the large-scale implementation of an adherence program (128). This Kenyan program intervened in two settings, healthcare facilities and boarding schools, in order to establish youth-friendly, peer-focused services in each aimed at linking newly diagnosed youth to treatment and supporting adherence to care once linked (128). The pre-post evaluation of the program revealed significant improvements in linkage to care and retention in care among its YLH sample (ages 15–21; 128). The third study, an examination of a peer support group for YLH ages 16 to 24 in South Africa, revealed that YLH attending the group compared to other YLH had higher rates of linkage to care (129). A fourth study evaluated HIV care facilities in Kenya before and after they implemented “youth and adolescent friendly services” including staff training on care for YLH, a dedicated clinic day for YLH, and peer support groups. Comparisons were made between these clinics and facilities that did not provide YLH-friendly services (130). No significant effects of the introduction of these services on rates of youth LTFU were observed (130).

CONCLUSIONS

The current study reviewed articles reporting on HIV treatment adherence and health outcomes among YLH residing in SSA. Our review revealed that YLH generally have worse adherence and health functioning than other age groups on a broad range of outcomes. We also reviewed studies reporting on barriers to youth adherence. Some barriers were unique to YLH and some were common to other age groups. Finally, we report on a small number of adherence interventions designed for or including YLH samples.

Research presented in our review highlights the vulnerability of YLH to poor adherence at all stages of HIV care. This finding was most evident when examining linkage to care, ART uptake and adherence, virologic outcomes, and LFTU. Less consistency was observed when examining other adherence-related health outcomes (e.g., immunological functioning, disease progression) and mortality, perhaps a reflection of young people’s physical resiliency despite suboptimal treatment engagement. Our finding that 89% of 47 studies found youth to be at higher risk for LTFU is alarming. Without at least some contact with healthcare providers, YLH are at risk for every other indicator of poor adherence or health functioning reported in this study. Clinic visits are the avenue to obtain ART and ART adherence counseling; checks on viral load, immunological functioning, ARV drug resistance, co-morbid conditions, and disease progression; and, in some clinics, screening and referral for behavioral health services²⁶.

The myriad of obstacles to engaging in HIV care faced by YLH may perpetuate age disparities. Factors unique to this population were identified such as managing treatment demands while away at boarding school, confronting conflicting role expectations for treatment self-management from providers, having personal agency to engage in treatment, and navigating new peer relationships. In addition, consistent with reviews of the adult literature¹⁶, male gender, mental health problems, substance use, unsupportive clinics, and inadequate family social support were all found to be adherence barriers for YLH. Youth also had barriers common to younger populations including discrimination at school and problems with guardians who they rely on for support. Finally, some risk factors for poor adherence we uncovered are likely common across all ages including HIV discrimination and low access to economic resources.

Enhancing treatment engagement among YLH is complicated by this array of adherence-related factors and will likely require multicomponent interventions similar to some we identified in our review. One underlying factor worth addressing is HIV stigma and its role in young people’s transition into novel social relationships and environments. YLH become less reliant on families and closer with friends, initiate romantic relationships for the first time, enter and/or finish educational programs, and are often moved from pediatric to adult HIV services. Our review showed that fear of unintended HIV disclosure and HIV-related discrimination was a primary barrier to adherence and permeated across all these contexts. In contrast, we found that receiving treatment-related support in each was a facilitator of adherence. Interventions should therefore help maintain and strengthen YLH’s existing relationships with supportive individuals as YLH face emerging social contexts and disclosure/discrimination fears. YLH could use this support to problem-solve their many barriers to adherence, particularly when access to other resources is low. Socially oriented mobile health interventions, which are increasingly accessible in SSA, may be one strategy to provide social support continuity among YLH.

It is notable that while YLH account for nearly 40% of new infections in SSA, they represented, on average, only 13% of a given study’s sample. Thus, many YLH are not in care and the disparities we uncovered are likely an underestimate. Studies of adults typically included a youth subgroup. However, many were excluded because they did not do separate age-group analyses. Researchers are encouraged to revisit their data with a focus on youth outcomes. In addition, the factors we found to be associated with YLH adherence or health functioning could be more representative of older adolescent YLH since only a few studies examined young adult YLH specifically. A more detailed age analysis may have revealed worse outcomes among young adults, who often deal with greater life transitions.

Study limitations should be noted. Due to the scope of the review, we were unable to thoroughly evaluate study design. Thus, given the wide range of methodologies employed, an assessment of study quality was not conducted, and articles were qualitatively assessed. The review’s scope also precluded an analysis of YLH treatment adherence by geographical region or country. Further review research is now needed to explore study methodology and regional differences of reports on youths’ experience with HIV treatment across SSA.

YLH in SSA are diverse and reside in a range of sociocultural settings. Yet, they confront similar obstacles to HIV care. The dearth of published adherence intervention studies indicates that more work is warranted to establish an evidence base and inform practice guidelines. YLH may need an intervention, guided by culturally-relevant theory, that accounts for their increasingly dynamic social contexts, while also addressing the common risk factors for non-adherence ranging from individual to economic and sociocultural domains.