INTRODUCTION
Throughout sub-Saharan Africa, adolescent girls and young women (AGYW) are at increased risk for acquisition of HIV infection because of a combination of biological, behavioral, and structural factors.1,2 It is therefore critical to engage AGYW in HIV prevention efforts, including testing, pre-exposure prophylaxis (PrEP), comprehensive sexual education, and condom provision.
In South Africa, engagement in HIV prevention remains low among many groups. Men are particularly disengaged from HIV testing, which elevates the risk of transmission of unknown HIV infection to their female partners.3,4 Home-based HIV self-testing presents an opportunity to engage individuals that are difficult to reach by traditional, clinic-based testing services.4–6 Secondary distribution of self-test kits by uninfected female sex workers and women receiving antenatal and postpartum care to their male partners has shown promise as a strategy to engage men in HIV testing in Kenya.5 Empowering AGYW to distribute HIV self-test kits to their sexual partners can lead to detection of previously undetected infections in young men, resulting in AGYW learning their partners' status and gaining more accurate understandings of their own risk. AGYW can then determine whether and how to access prevention methods such as PrEP. Although PrEP has great potential as an HIV prevention option for AGYW, adherence among AGYW in both research and implementation contexts has been challenging, reducing its impact.7–9 Understanding AGYW's interest in and uptake of PrEP is a critical first step for targeting PrEP communications strategies to AGYW at greatest risk of HIV acquisition.
HIV prevention interventions for AGYW often approach them as independent individuals, ignoring the context of their relationships.10–12 To gain insight into the factors that determine successful uptake of secondary distribution of self-testing kits to partners and AGYW's uptake of PrEP, it is important to understand the role played by both AGYW and male sexual partners in these processes. Relationships with male partners influence AGYW's risk of HIV both directly, through exposing them to HIV, and indirectly, through positioning them in wider sexual networks and fostering sexual risk behavior, and through influencing decisions made by AGYW.11–13
A recent qualitative study from South Africa showed that distinct types of sexual partnerships can differentially influence AGYW's decisions around engagement in the HIV prevention cascade.14 The study identified 4 primary relationship typologies with defined patterns of risk, which resulted in successful or unsuccessful engagement in the HIV prevention cascade. These included (1) relationship turnover and male partners with multiple partnerships, (2) intimate partner violence and male partner temperament, (3) AGYW with multiple partners, and (4) stable relationships with male partner openness.14 Studies with AGYW and their male sexual partners in Uganda and Mozambique have further demonstrated that AGYW's relationships are diverse, driven by social and cultural norms, and often fluid (changing from casual to stable), influencing AGYW's perceptions of their risk.15,16 These findings highlight the importance of understanding partner and relationship typologies to more effectively inform targeted HIV prevention interventions.
The objective of this study was to identify underlying constructs of AGYW's sexual relationship types and assess the association between relationship type and engagement in HIV prevention interventions. Specifically, we aimed to identify the main types of heterosexual relationships that exist among AGYW in South Africa and assess how relationship types influence successful partner testing (secondary distribution of HIV self-test kits to partners, partner uptake of HIV self-testing, and disclosure of results) and AGYW PrEP uptake.
METHODS
Study Setting and Sample
This study analyzed data from the Determined, Resilient, Empowered, AIDS-Free, Mentored, and Safe (DREAMS) Innovation Challenge project at Witkoppen Clinic in Johannesburg, South Africa. AGYW were recruited between May 2018 and February 2019 after AGYW HIV testing at a participating clinic, mobile site, or event in the community. Recruitment predominantly occurred alongside the DREAMS community testing team targeting AGYW but was coupled with recruitment among AGYW attending the local primary health centers for HIV testing, antenatal care, family planning, or other services. AGYW were eligible for participation if they were aged 16–24 years, had tested HIV-negative, were in a heterosexual relationship for 3 or more months, were sexually active, had at least one partner of unknown HIV status, and did not report violence or fear of violence in their relationship. Each prospective participant received study information from a team member in her preferred language (English, Zulu, or Sotho).
Ethics approval for the study was obtained from the Human Research Ethics Committee at the University of Witwatersrand in Johannesburg, South Africa. Oversight was seconded by the Johns Hopkins Bloomberg School of Public Health Institutional Review Board to the South African Committee. Written informed consent or assent (if <18 years) were obtained from each participant; for AGYW younger than 18 years, parental consent was obtained.
Procedures
Participating AGYW (n = 2200) completed baseline questionnaires about their demographic and socioeconomic characteristics, perceived HIV risk, sexual behavior, and partnerships.
After completing the baseline questionnaire, AGYW watched a video explaining how to give an HIV self-test to their partners and received further counseling from study staff. Each AGYW received one self-test kit per sexual partner. The kit contained an oral HIV self-test (OraQuick), an instructional pamphlet with information about the self-testing process and post-test counseling, a universal serial bus flash drive with a video for male partners that included motivational messages for HIV testing and use of condoms and lubricants as well as instructions on how to perform the self-test. Additional kits were offered if AGYW had multiple partners and if they were interested in retesting together with partners. PrEP was offered to all nonpregnant, nonlactating AGYW.
We followed up with AGYW through phone calls or face-to-face clinic meetings for those not reached by phone but attending the clinic at 1-week and 2-week postintervention, and then monthly for 3 months to determine the outcome of the self-test kit delivery. At each follow-up contact, we asked AGYW about their perceived HIV risk and their participation in the prevention cascade inquiring about their discussion of self-testing with their partner(s), distribution of self-test kits to their partner(s), actual self-testing of their male partner(s), disclosure of the test result by their male partner(s), their partners' linkage to care, AGYW PrEP uptake, and PrEP adherence.
Measures
Four sociodemographic variables were included in our models. First, age was measured continuously. Second, the educational level was measured categorically (no schooling or primary, secondary, or postsecondary schooling). Third, self-reported alcohol use was measured categorically (never drink, drink with friends but never get drunk, sometimes get drunk, or drink a lot). Fourth, access to income was measured categorically (no personal income, part-time job, or full-time job).
Latent classes were identified through the following variables: perceived HIV risk (highest tercile vs. lowest 2 terciles), multiple AGYW partnerships (2 or more male sexual partners in the last 6 months), short-term partnerships (<3 months in duration), age-disparate partnerships (male partner ≥5 years older), cohabitation with partner, consistent condom use with partner in past 30 days, male partner suspected to have one or more other sex partners, low overall sexual relationship power (summary score at or below 25th percentile on the Sexual Relationship Power Scale17), awareness of male partner's HIV status, talking about HIV with partner, and receipt of financial support from partner. All characteristics were dichotomized as present/absent. Details on their measurement and coding are provided in Table 1, Supplemental Digital Content, https://links.lww.com/QAI/B573.
Three key outcome variables were used in our final models. First, HIV self-test cascade completion was measured as follows: at follow-up, we asked AGYW the following: (1) “did you give the HIV self-test to [partner]?” (2) “did [partner] test?” and (3) “did [partner] share his result?” If AGYW responded “yes” to all 3 questions, we assigned a variable indicating they had completed the cascade. If AGYW responded “no” to any of these 3 questions, they were classified as not having completed the cascade. Second, PrEP interest was measured among AGYW who were eligible for PrEP (ie, not pregnant or breastfeeding) based on preliminary interest (yes/no) in receiving more information about PrEP for a current or future PrEP referral; this was documented as part of intervention implementation. Third, PrEP uptake was assessed among PrEP-eligible AGYW and was defined as receiving a prescription and a 1-month supply of pills by the study nurse (other clinics or community services in the area did not provide PrEP) at baseline or within the 3-month follow-up period as part of implementation.
Statistical Analysis
We used descriptive statistics to summarize the demographic and relationship characteristics of AGYW and used latent class analysis (LCA) to determine and classify sexual relationships based on 11 characteristics reported by AGYW at baseline (see Table 1, Supplemental Digital Content, https://links.lww.com/QAI/B573). Selection of the 11 characteristics was informed by the literature on relational factors influencing AGYW's HIV risk and by qualitative findings from a subsample in our study.14
We considered models with 2–6 classes and compared the Akaike Information Criterion, Bayesian Information Criterion, Vuong-Lo-Mendell-Rubin, bootstrapped likelihood ratio test, and entropy to assess model fit and select the most parsimonious model. Model fit statistics are available in Table 2, Supplemental Digital Content, https://links.lww.com/QAI/B573. Along with fit statistics, we examined the probabilities of latent class membership and conditional probabilities to select the best fitting and most interpretable model.
After the final model was selected, we used the Bolck, Croon, and Hagenaars (BCH) 3-step mixture modeling procedure18 to estimate differences in engagement in HIV prevention interventions between classes without changing the class structure. Mixture modeling is a latent variable modeling approach which is suitable for analyses involving both latent (unobserved) and observed variables. In our mixture models, class membership was treated as latent, while covariates and outcomes were observed. The BCH procedure outperforms other 3-step approaches by avoiding shifts in latent classes and using weights to account for measurement error of latent classes.
We ran 3 BCH models to estimate the impact of class membership on each outcome separately. We used Wald tests to assess differences in the outcome by class and calculated risk ratios to summarize the relative magnitude of these differences. All models were adjusted for age and education. For the model assessing HIV self-test cascade completion, we generated stabilized inverse probability of observation weights to account for differential follow-up of outcome ascertainment.19 Weights were conditional on age, education, country of origin, income, relationship status, cohabitation with a partner, condom use, presence of an older partner, and receiving financial support from a partner. Data on PrEP outcome were complete, so these analyses were unweighted.
Analyses were performed in Stata Version 1520 and Mplus Version 8.21
RESULTS
AGYW Demographic and Relationship Characteristics
A total of 2200 AGYW participated. The median age was 22 years (interquartile range 20–23, Table 1), the majority (78%) had completed some or all of secondary school, just over a quarter (27%) reported some source of personal income, half (52%) reported living with their family, and 40% reported living with their partner or his family.
TABLE 1. -
Demographic Characteristics of Adolescent Girls and Young Women Engaged in the HIV Prevention Intervention in Johannesburg at Baseline (n = 2200)
| AGYW Demographic Characteristics |
N (%), Median (IQR) |
| Age |
22 (20–23) |
| Country of origin |
|
| South Africa |
1475 (67.0%) |
| Zimbabwe |
579 (26.3%) |
| Others |
146 (6.6%) |
| Currently in school |
|
| No |
1661 (75.5%) |
| Yes |
539 (24.5%) |
| Educational level |
|
| Primary school or less |
67 (3.0%) |
| Some secondary school |
846 (38.5%) |
| Completed secondary school |
875 (39.8%) |
| Tertiary education |
412 (18.7%) |
| Living situation |
|
| Living together with family |
1145 (52.0%) |
| Living with partner or his family |
889 (40.4%) |
| Living alone |
137 (6.2%) |
| Living with friends |
29 (1.3%) |
| Monthly household income (ZAR) |
4000 (2500–6000) |
| Personal steady income |
|
| None |
1604 (72.9%) |
| Part-time job |
220 (10.0%) |
| Full-time job |
303 (13.8%) |
| Income not from a job |
73 (3.3%) |
| Relationship status |
|
| Casual |
348 (15.8%) |
| Steady, not living together |
964 (43.8%) |
| Steady, living together |
727 (33.0%) |
| Married |
161 (7.3%) |
| History of pregnancy |
|
| No |
718 (32.6%) |
| Yes |
1482 (67.4%) |
| History of previous HIV testing |
|
| No |
97 (4.4%) |
| Yes |
2103 (95.6%) |
| Ever experienced physical violence |
|
| No |
2109 (95.9%) |
| Yes |
91 (4.1%) |
| Ever experienced sexual violence |
|
| No |
2162 (98.3%) |
| Yes |
38 (1.7%) |
IQR, interquartile range.
The majority of AGYW (75%) felt they had a low risk of acquiring HIV in the next 6 months. Most (89%) reported only 1 partner in the last 6 months, nearly all (98%) had been sexually active in the past 30 days, 20% reported consistent condom use with their partners in the last 30 days, and just over half (56%) reported having more say than their partners about condom use (Table 2). The median sexual relationship power score was 55 (interquartile range: 52–57), with possible scores ranging from 23 to 76.
TABLE 2. -
Baseline Relationship Characteristics of 2200 Adolescent Girls and Young Women Engaged in the HIV Prevention Intervention in Johannesburg
| AGYW-Reported Partner Characteristics |
N (%), Median (IQR) |
| Perceived HIV risk |
|
| Low (0–33) |
1641 (74.6%) |
| Medium (34–66) |
409 (18.6%) |
| High (67–100) |
150 (6.8%) |
| No. of sexual partners in past 6 mo |
|
| 0 |
10 (0.5%) |
| 1 |
1958 (89.0%) |
| 2 |
155 (7.0%) |
| 3 or more |
77 (3.5%) |
| Partner's suspected number of other female sexual partners |
|
| 0 |
1799 (81.8%) |
| 1 or more |
401 (18.2%) |
| Who has more say about condom use? |
|
| AGYW |
1226 (55.7%) |
| Male partner |
974 (44.3%) |
| Sexual relationship power score* |
55 (52–57) |
| Sex in the past 30 d |
|
| No |
49 (2.2%) |
| Yes |
2151 (97.8%) |
| Condom use in the past 30 d |
|
| Always |
425 (19.8%) |
| Often |
280 (13.0%) |
| Rarely |
586 (27.2%) |
| Never |
860 (40.0%) |
| Primary partner HIV status† |
|
| HIV Positive |
1 (0%) |
| HIV Negative |
1008 (45.8%) |
| Unknown |
1191 (54.2%) |
*Score generated from the 23-item Sexual Relationship Power Scale, with a total possible score ranging from 23 (low power) to 76 (high power) and sample range of 36–75.
†Some AGYW had multiple partners, at least one of which was of unknown HIV status to meet eligibility criteria.
IQR, interquartile range.
LCA: Classes of Sexual Relationships
LCA identified 3 types of relationships (Table 3). Class 1 consisted of stable, longer-duration relationships with older partners and low AGYW perception of risk. These relationships were characterized by stability, AGYW empowerment (higher AGYW relationship power score), higher probability of cohabitation, provision of financial support by the partner, and discussing HIV with the partner. Class 2 relationships were shorter relationships with peer partners, characterized by AGYW relationship empowerment, moderate discussion of HIV with partners, and the highest probability of consistent condom use across the 3 classes. Class 3 relationships were shorter in duration with risky partners and were characterized by less consistent condom use, greater suspicion that the partner had other partners, higher perceived HIV risk, and lower sexual relationship power. For example, the conditional probability of having high perceived HIV risk was 34% in class 3, compared with 4% in class 2, and the probability of having high sexual relationship power was 34% in class 3, compared with 85% in class 2.
Based on posterior classification probabilities, the prevalence of the 3 relationship types were 47% for class 1 (stable, empowered relationships with older less risky partners), 43% for class 2 (shorter, empowered relationships with peer partners), and 10% for class 33 (shorter relationships with risky partners).
TABLE 3. -
Classes of Relationship Type, Prevalence of Class Membership, and Conditional Probabilities of Class Indicators Identified Through Latent Class Analysis Among 2200 Adolescent Girls and Young Women in Johannesburg,
South Africa.
*
|
Class 1: Stable, Empowered Relationship With Older Partners |
Class 2: Shorter, Empowered Relationship With Peer Partners |
Class 3: Shorter, Less Empowered Relationship With Risky Partners |
| Prevalence of class membership |
47% |
43% |
10% |
| High perceived HIV risk |
0.04 |
0.04 |
0.34
|
| ≥2 sexual partners in last 6 months |
0.05 |
0.13 |
0.31
|
| Relationship duration <3 mo |
0.22 |
0.39 |
0.44
|
| Cohabit with partner |
0.80
|
0.01 |
0.25 |
| Always used condom with partner in past 30 days |
0.08 |
0.35
|
0.07 |
| Partner suspected to have one or more other partners |
0.09 |
0.17 |
0.66
|
| Previously discussed partner HIV status |
0.50
|
0.46 |
0.26 |
| Receive financial support from partner |
0.97
|
0.73 |
0.71 |
| Partner ≥5 years older |
0.61
|
0.34 |
0.49
|
| High sexual relationship power |
0.71 |
0.85
|
0.34
|
| Talk about HIV with partner |
0.63
|
0.34 |
0.36 |
*Bold values indicate key characteristics used to define relationship types, based on having a low or high conditional probability of the characteristic compared with other classes.
AGYW's demographic, family, and relationship characteristics varied by most likely the relationship type (Table 4). Most AGYW most likely in classes 2 or 3 were from South Africa (83% and 70%, respectively), whereas those in class 1 were more diverse in their countries of origin (P < 0.01). Around half (51.8%) of AGYW most likely in class 1 had completed some secondary school or less, and only 8.9% had received tertiary education, whereas 27.7% and 18.1% of AGYW most likely in classes 2 and 3, respectively, had received tertiary education (P < 0.01). Although reported history of transactional sex was low in the sample overall, 9.4% of AGYW most likely in class 3 reported ever engaging in transactional sex, compared with 2.4% and 2.5% of AGYW most likely in classes 1 and 2, respectively (P < 0.01). There was also variation in living situation, reported relationship status, and history of pregnancy between classes (P < 0.01).
TABLE 4. -
Characteristics of AGYW (N = 2200), by Most Likely the Relationship Type as Determined Through LCA.
*
|
Class 1: Stable Empowered Relationship With Older Less Risky Partners (N = 973) |
Class 2: Shorter Empowered Relationship With Peer Partners (N = 1067) |
Class 3: Shorter, Less Empowered Relationship With Risky Partners (N = 160) |
P† |
| Age |
22 (21–24) |
21 (19–23) |
22 (19.5–24) |
<0.01 |
| Country of origin |
|
|
|
|
| South Africa |
478 (49.1%) |
892 (83.0%) |
112 (70.0%) |
<0.01 |
| Zimbabwe |
377 (38.8%) |
161 (15.0%) |
42 (26.3%) |
|
| Others |
118 (12.1%) |
22 (2.0%) |
6 (3.7%) |
|
| Educational level |
|
|
|
|
| Primary school or less |
46 (4.7%) |
15 (1.4%) |
6 (3.8%) |
<0.01 |
| Somesecondary school |
458 (47.1%) |
329 (30.1%) |
59 (36.9%) |
|
| Completed secondary school |
382 (39.3% |
427 (40.0%) |
66 (41.3%) |
|
| Tertiary education |
87 (8.9%) |
296 (27.7%) |
29 (18.1%) |
|
| Living situation |
|
|
|
|
| Living together with family |
103 (10.6%) |
938 (87.9%) |
104 (65.0%) |
<0.01 |
| Living with partner or his family |
854 (87.8%) |
0 (0.0%) |
33 (21.9%) |
|
| Living alone |
12 (1.2%) |
107 (10.0%) |
18 (11.3%) |
|
| Living with friends |
4 (0.4%) |
22 (2.1%) |
3 (1.9%) |
|
| Monthly household income (ZAR) |
4000(2800–6000) |
4000(2500–6000) |
3600 (2000–5100) |
0.34 |
| Personal steady income |
|
|
|
|
| No |
725 (74.5%) |
772 (72.4%) |
107 (66.9%) |
0.14 |
| Yes, from part-time job |
92 (9.5%) |
113 (10.6%) |
15 (9.4%) |
|
| Yes, from full-time job |
131 (13.5%) |
144 (13.5%) |
28 (17.5%) |
|
| Other income not from a job |
25 (2.6%) |
38 (3.6%) |
10 (6.3%) |
|
| Relationship status |
|
|
|
|
| Casual |
28 (2.9%) |
270 (25.3%) |
50 (31.3%) |
<0.01 |
| Steady, not living together |
144 (14.8%) |
742 (69.5%) |
78 (48.8%) |
|
| Steady, living together |
645 (66.3%) |
53 (4.9%) |
29 (18.1%) |
|
| Married |
156 (16.0%) |
2 (0.2%) |
3 (1.9%) |
|
| History of pregnancy |
|
|
|
|
| No |
158 (16.2%) |
507 (47.5%) |
53 (33.1%) |
<0.01 |
| Yes |
815 (83.8%) |
560 (52.5%) |
107 (66.9%) |
|
| History of previous HIV testing |
|
|
|
|
| No |
35 (3.6%) |
55 (5.2%) |
7 (4.4%) |
0.23 |
| Yes |
938 (96.4%) |
1012 (94.9%) |
153 (95.6%) |
|
| History of transactional sex |
|
|
|
|
| No |
950 (97.6%) |
1040 (97.5%) |
145 (90.6%) |
<0.01 |
| Yes |
23 (2.4%) |
27 (2.5%) |
15 (9.4%) |
|
| Ever experienced physical violence |
|
|
|
|
| No |
939 (96.5%) |
1023 (95.9%) |
147 (91.9%) |
0.02 |
| Yes |
34 (3.5%) |
44 (4.1%) |
13 (8.1%) |
|
| Ever experienced sexual violence |
|
|
|
|
| No |
958 (98.5%) |
1048 (98.2%) |
156 (97.5%) |
0.68 |
| Yes |
15 (1.5%) |
19 (1.8%) |
4 (2.5%) |
|
*A most likely relationship type was assigned to AGYW based on their posterior probabilities of class membership.
†P values are based on χ2 test for categorical variables and analysis of variance for continuous variables.
Relationship Type and HIV Prevention Outcomes
Outcome data were available for 1673 (76%) of the 2200 participating AGWY. Overall, most (79.6%) of these AGYW reported completing all steps of the partner HIV self-testing cascade. Relationship class membership was significantly associated with HIV self-test cascade completion (Table 5). The likelihood of HIV self-test cascade completion was lower in class 2 and 3 relationships compared with class 1 relationships. Compared with AGYW in class 1 partnerships, AGYW in class 2 partnerships were 10% less likely [adjusted risk ratio (aRR) 0.90, 95% confidence interval (CI): 0.85 to 0.95], and AGYW in class 3 relationships were 16% less likely to have completed the partner testing cascade including seeing his test result in the weighted model. There was no difference in HIV self-test cascade completion between AGYW in class 2 vs. class 3 relationships (results not shown).
TABLE 5. -
aRR and 95% CIs for the Association Between Relationship Type and HIV Prevention Outcomes (Completion of HIV Prevention Cascade, PrEP Interest, and PrEP Uptake) Among AGYW.
*
| Outcome: Partner Self-Testing Cascade Completion† |
| Relationship Type |
Completed Cascade Crude, N (%)‡ |
aRR (95% CI)†§ |
| Class 1: Stable empowered relationship with older less risky partners |
613 (63.0%) |
REF |
| Class 2: Shorter empowered relationship with peer partners |
632 (59.2%) |
0.89 (0.85 to 0.95) |
| Class 3: Shorter, less empowered relationship with risky partners |
87 (54.4%) |
0.84 (0.73 to 0.94) |
| Outcome: PrEP Interest‖ |
| Relationship Type |
PrEP Interest Crude, N (%) |
aRR (95% CI) |
| Class 1: Stable empowered relationship with older less risky partners |
248 (31.1%) |
REF |
| Class 2: Shorter empowered relationship with peer partners |
368 (38.7%) |
1.26 (1.13 to 1.39) |
| Class 3: Shorter, less empowered relationship with risky partners |
87 (64.9%) |
2.10 (1.95 to 2.24) |
| Outcome: PrEP Uptake‖ |
| Relationship Type |
PrEP Uptake Crude, N (%) |
P¶ |
| Class 1: Stable empowered relationship with older less risky partners |
8 (1.0%) |
<0.001 |
| Class 2: Shorter empowered relationship with peer partners |
36 (3.8%) |
|
| Class 3: Shorter, less empowered relationship with risky partners |
15 (11.2%) |
|
*Models were adjusted for the following to estimate aRR: age and educational level.
†Estimates for the outcome of partner self-testing cascade completion were weighted using stabilized inverse probability of observation weights as outcome ascertainment was not available for all AGYW.
‡To calculate Ns and percentages, a most likely relationship type was assigned to AGYW are based on posterior probabilities of class membership. However, these class assignments were not fixed, and aRRs calculated through mixture modeling–treated class membership as a latent variable.
§Among AGWY for whom outcome data were available (N = 1673). Complete data were available for 716 AGYW most likely in class 1, 840 most likely in class 2, and 117 most likely in class 3.
‖Among AGYW who were eligible for PrEP (N = 1882). Of the AGYW eligible for PrEP, 793 were most likely in class 1, 964 were most likely in class 2, and 125 were most likely in class 3.
¶PrEP uptake models did not converge; aRRs are not presented, but rather a P value from a χ2 test of the crude association between most likely relationship type and PrEP uptake.
Overall, 37.4% of eligible AGYW expressed interest in PrEP. Relationship class membership was significantly associated with PrEP interest and PrEP uptake. PrEP interest was highest among AGYW in class 3 relationships (64.9%) (Table 5). Compared with AGYW in class 1, AGYW in class 2 were 26% more likely to express an interest in PrEP (aRR 1.26, 95% CI: 1.13 to 1.39), and AGYW in class 3 were more than twice as likely to likely to express an interest in PrEP in the BCH-weighted analysis. PrEP interest also significantly differed when comparing AGYW in class 2 vs. class 3 partnerships (aRR 0.60; 95% CI: 0.46 to 0.74). Although PrEP uptake was low overall (3.1%), it was highest among AGYW most likely to be in class 3 relationships (11.2%; P < 0.001).
DISCUSSION
In this study, we identified 3 distinct relationship types characterized by relationship power and HIV risk. We observed significant associations between the type of relationships in AGYW in urban South Africa and outcomes of distribution of HIV self-tests to male partners and AGYW PrEP interest and uptake, 2 vital HIV prevention efforts. Our findings highlight the important role of sexual partnerships in HIV prevention for AGYW and supports the development of targeted communication strategies to optimize the effectiveness of HIV prevention in this critically vulnerable population.
AGYW in class 1, the most frequent relationship type among these urban South African AGYW, were empowered, had had stronger partner communication and stable relationships with older (>5 years age difference) partners, and low suspicion of the male partner having other partners, but were less educated and reported relying on their partners financially. AGYW in class 1 type relationships were the most likely AGYW to report completion of the partner HIV self-testing cascade. This is in contrast to previous research that found that older male partners may be less likely to discuss HIV with younger partners.22,23 Our finding challenges notions that older male partners are inherently “risky” for AGYW and suggests that AGYW in relationships with older partners may not necessarily be disempowered but may be more likely to discuss HIV and engage in HIV preventive behavior with these partners. Others have further explored the social and economic benefits associated with age-disparate relationships.24–26 Although such benefits were not directly explored in our study, it is likely that for many AGYW in this community who struggle to meet their needs, older partners may offer access to food, clothing, and shelter along with other commodities that, although less economically valuable, increase AGYW's social standing. AGYW may also pursue these relationships with the goal of gaining financial independence and social mobility. However, because class 1 relationships were also characterized by cohabitation and longer duration of the relationship, they may reflect that more committed, stable partnerships are protective for AGYW. At the same time, because AGYW's perceptions of their own risk may not always be accurate, it is important to consider whether AGYW in class 1 partnerships may remain vulnerable to unknown risks. Despite the positive features, we identified in these relationships, the risk of HIV acquisition for AGYW with older partners has been well established in the literature.27–29 For these AGYW, interventions may include financial empowerment, promotion of male engagement in HIV and sexual and reproductive health, and interventions which help AGYW accurately assess their own HIV risk.
Although AGYW in shorter relationships with peer partners (class 2) generally reported empowerment within their relationships, the frequency with which these AGYW reported discussing HIV with partners was low, and AGYW knowledge of their partner's HIV status was less than 50%. Interventions that encourage positive engagement with peer male partners at a younger age and early on within relationships may promote more sustained engagement in HIV preventive behavior and more effectively protect AGYW as they age.30
AGYW in shorter relationships with risky partners (class 3) were most likely to view themselves at high risk of HIV acquisition, to have experienced some form of violence, and to have poor partner communication and low sexual relationship power. Despite perceiving themselves at high risk, they were least likely to report completion of the partner HIV self-testing cascade. One possible explanation for this is that these AGYW tend to engage in transactional relationships with older partners who may belong to higher-risk sexual networks, causing AGYW to perceive their own risk as higher yet remain disempowered to negotiate HIV testing, condom use, or other preventive behaviors.31–33 For these AGYW, empowerment interventions as well as enhanced promotion of PrEP and other prevention services may be needed, but attention must also be paid to the potential for violence, multiple partnerships, nascent relationships, and economic vulnerabilities of these AGYW.
Regarding relationship types, our quantitative results were similar to the 4 relationship types identified in Holmes et al's14 qualitative study on a subsample of our study population. The qualitative study identified a relationship type characterized by male partner openness and relationship stability; this aligns closely with our LCA-identified class 1. The qualitative study found that AGYW in these relationships had committed relationships and were willing to engage in the HIV self-testing intervention and PrEP.14 This aligns with our finding that AGYW in class 1 relationships were most likely to complete the self-testing cascade. Holmes et al also identified a group of AGYW with multiple partners who successfully engaged in the HIV self-testing cascade, which aligns with our class of empowered AGYW in short-term peer partnerships (class 2). This finding challenges notions of all AGYW as a disempowered, sexually vulnerable group and suggests that some AGYW who are not ready for a monogamous relationship may choose to pursue multiple shorter partnerships, yet remain aware of their HIV risk and are empowered to take preventive action.
In contrast to the findings of the qualitative study, we did not observe differences between AGYW who had multiple partners themselves and AGYW who suspected their partners to have multiple other partners. In our LCA, these characteristics were most probable in a single class (class 3). Another important difference between our findings and those from the qualitative study was a fourth qualitatively identified relationship type, characterized by fear of violence. This type was not identified by our LCA, potentially because of underreporting of violence in the quantitative survey. We, however, did observe differences across classes in experiences of violence, supporting the potential salience of violence, although we were not directly able to include it in our measurement model. The triangulation of our quantitative results with qualitative findings from a subsample of our study gives strong support for our conclusions.14
Others have also used LCA to identify types of relationships among AGYW. In rural South Africa, 1 study identified 5 types of relationships, including 1 with older partners and 4 with peer partners further differentiated by in-of-school vs. out-of-school, presence of monogamy, partner anonymity, and cohabitation.13 Because LCA is a data-driven approach, these differences are not surprising and likely reflect differences in age and urban vs. rural in study samples. We could not identify any other studies that investigated the association between AGYW relationship typologies and the outcome of engagement in HIV prevention interventions.
There are some limitations to this study. First, LCA relied on AGYW's self-reported partner characteristics and self-testing outcomes, so misclassification, recall, and social desirability bias may have been present. Second, because LCA is a data-driven approach, our findings are specific to AGYW in our sample and may not be generalizable to other populations. Furthermore, our sample was limited to AGYW reporting being in a nonviolent relationship for at least 3 months, thus other relationship types may have been missed. We also did not assess emotional violence in relationships. Third, although we were successful in recruiting a small number of younger AGYW, the requirement for parental consent may have limited our ability to reach this group. Fourth, sparse data precluded use of the 3-step procedure for PrEP uptake, so we were unable to present BCH-weighted aRRs for this outcome. Finally, although we were able to adjust for possible confounders of the association between relationship type and HIV cascade completion and applied inverse probability weighting to account for incomplete outcome ascertainment, there remains potential for unmeasured confounding and bias.
Our findings highlight several additional areas for research. First, greater understanding of the heterogeneity of risk across AGYW's older partners is warranted. Our findings suggest that, although some older partnerships may be risky for AGYW, others may be more stable and potentially protective in nature. Better understanding the HIV burden among AGYW's various older male partners is important for better estimating AGYW's risk and targeting interventions. It is also important to understand how relationship durations may drive HIV risk. We found, for example, that AGYW with longer-term relationships were most likely to complete the partner self-testing cascade which might reduce risk, although these relationships were also characterized by factors (ie, older partners and financial support) that may subsequently increase risk. It is possible that relationship duration moderates the impact of age-disparate or transactional sex partnerships and HIV risk. Third, additional research is needed on the specific role of empowerment in HIV risk. We found that AGYW with high risk perception and low sexual relationship power (class 3) were least likely to complete the partner self-testing cascade but most likely to express interest in PrEP and take it up. Better understanding the mechanisms through which sexual and other forms of empowerment influence HIV preventive behavior and subsequent risk is important to inform and appropriately target interventions. Finally, the association between relationship type and PrEP use should be examined with greater depth. We found that PrEP interest and uptake varied across relationship types in our sample, with AGYW at potentially greater risk being more likely to express interest in and take up PrEP. In addition, longitudinal research should examine how AGYW with various sexual relationship characteristics not only take PrEP but use it long term, including patterns of PrEP continuation and cycling on and off PrEP.
CONCLUSIONS
AGYW in South Africa remain a priority population for HIV intervention. Relationship power, communication, multiple partnerships, and relationship duration demonstrate complex dynamics impacting AGYW's sexual relationships. Together, these are associated with AGYW's condom use, engagement in transactional sex, and experiences of physical violence. Our findings reinforce evidence that heterogeneity of risk is more complex than age disparateness and that appropriately characterizing AGYW's sexual partnerships has important implications for targeting communication to improve the effectiveness of HIV prevention interventions. Communication strategies should consider moving beyond a focus on age-disparate or short-term relationships and take more nuanced approaches to addressing risk heterogeneity in reducing AGYW's sexual HIV risk.
ACKNOWLEDGMENTS
The authors thank Joel Gittelsohn and Andrew Thorne-Lyman for their feedback on earlier versions of this article. The authors are also grateful to the young women and men participating in this study, as well as the data collection team at Witkoppen Health and Welfare Centre.
REFERENCES
1. UNAIDS. Global AIDS Update 2019—Communities at the Centre. Geneva, Switzerland: United Nations Joint Programme on HIV/AIDS (UNAIDS); 2019.
2. UNAIDS. Women and HIV: A Spotlight on Adolescent Girls and Young Women. Geneva, Switzerland: United Nations Joint Programme on HIV/AIDS (UNAIDS); 2019.
3. UNAIDS. Addressing a Blind Spot in the Response to HIV—Reaching Out to Men and Boys. Geneva, Switzerland: United Nations Joint Programme on HIV/AIDS (UNAIDS); 2017.
4. Orne-Gliemann J, Balestre E, Tchendjou P, et al. Increasing HIV testing among male partners. AIDS. 2013;27:1167–1177.
5. Thirumurthy H, Masters SH, Mavedzenge SN, et al. Promoting male partner testing and safer sexual decision-making through secondary distribution of HIV self-tests by HIV-uninfected female sex workers and women receiving antenatal and postpartum care in Kenya: a cohort study. Lancet HIV. 2016;3:e266–e274.
6. Hlongwa M, Mashamba-Thompson T, Makhunga S, et al. Mapping evidence of intervention strategies to improving men's uptake to HIV testing services in sub-Saharan Africa: a systematic scoping review. BMC Infect Dis. 2019;19:496.
7. Cowan FM, Delany-Moretlwe S, Sanders EJ, et al. PrEP implementation research in Africa: what is new? J Int AIDS Soc. 2016;19(suppl 6):21101.
8. Hodges-Mameletzis I, Fonner VA, Dalal S, et al. Pre-exposure prophylaxis for HIV prevention in women: current status and future directions. Drugs. 2019;79:1263–1276.
9. Vuyokazi L, Ramballi Greener L, Makamu T, et al. How Do We Roll Out PrEP for Adolescent Girls and Young Women (AGYW)? Healthcare Providers Perspectives on Challenges and Facilitators to PrEP Provision to AGYW in
South Africa. 20th Conference on AIDS and STIs in Africa 2019, 2–7 December 2019; Kigali, Rwanda; 2019.
10. Mojola SA, Wamoyi J. Contextual drivers of HIV risk among young African women. J Int AIDS Soc. 2019;22(suppl 4):e25302.
11. Hargreaves JR, Morison LA, Kim JC, et al. Characteristics of sexual partnerships, not just of individuals, are associated with condom use and recent HIV infection in rural
South Africa. AIDS Care. 2009;21:1058–1070.
12. Gorbach PM, Holmes KK. Transmission of STIs/HIV at the partnership level: beyond individual-level analyses. J Urban Health. 2003;80(4 suppl 3):iii15–iii25.
13. Nguyen N, Powers KA, Miller WC, et al. Sexual partner types and incident HIV infection among rural South African adolescent girls and young women enrolled in HPTN 068: a latent class Analysis. J Acquir Immune Defic Syndr. 2019;82:24–33.
14. Holmes L, Kaufman M, Casella A, et al. Characterizing the relationship environments of South African adolescent girls and young women and the implications for engagement across the HIV prevention cascade. J Int AIDS Soc. 2019;23(suppl 3):e25521.
15. Chapman J, do Nascimento N, Mandal M. Role of male sex partners in HIV risk of adolescent girls and young women in Mozambique. Glob Health Sci Pract. 2019;7:435–446.
16. Gottert A, Pulerwitz J, Siu G, et al. Male partners of young women in Uganda: understanding their relationships and use of HIV testing. PLoS One. 2018;13:e0200920.
17. Pulerwitz J, Gortmaker SL, DeJong W. Measuring sexual relationship power in HIV/STD research. Sex Roles. 2000;42:637–660.
18. Asparouhov T, Muthén B. Auxiliary variables in mixture modeling: using the BCH method in Mplus to estimate a distal outcome model and an arbitrary secondary model. Mplus Web Notes. 2014;21:1–22.
19. Howe CJ, Cole SR, Lau B, et al. Selection bias due to loss to follow up in cohort studies. Epidemiology. 2016;27:91–97.
20. Stata Statistical Software: Release 15 [computer program]. College Station, TX: StataCorp LLC; 2017.
21. Mplus [computer program]. Los Angeles, CA: Muthén & Muthén; 2017.
22. Reynolds Z, Gottert A, Luben E, et al. Who are the male partners of adolescent girls and young women in Swaziland? Analysis of survey data from community venues across 19 DREAMS districts. PLoS One. 2018;13:e0203208.
23. Doyle AM, Floyd S, Baisley K, et al. Who are the male sexual partners of adolescent girls and young women? Comparative analysis of population data in three settings prior to DREAMS roll-out. PLoS One. 2018;13:e0198783.
24. Mavhu W, Rowley E, Thior I, et al. Sexual behavior experiences and characteristics of male-female partnerships among HIV positive adolescent girls and young women: qualitative findings from Zimbabwe. PLoS One. 2018;13:e0194732.
25. Wamoyi J, Buller AM, Nyato D, et al. “Eat and you will be eaten”: a qualitative study exploring costs and benefits of age-disparate sexual relationships in Tanzania and Uganda: implications for girls' sexual and reproductive health interventions. Reprod Health. 2018;15:207.
26. Wamoyi J, Heise L, Meiksin R, et al. Is transactional sex exploitative? A social norms perspective, with implications for interventions with adolescent girls and young women in Tanzania. PLoS One. 2019;14:e0214366.
27. Stoner MCD, Nguyen N, Kilburn K, et al. Age-disparate partnerships and incident HIV infection in adolescent girls and young women in rural
South Africa. AIDS. 2019;33:83–91.
28. Maughan-Brown B, Venkataramani A, Kharsany ABM, et al. Recently formed age-disparate partnerships are associated with elevated HIV-incidence among young women in
South Africa. AIDS. 2020;34:149–154.
29. Topazian HM, Stoner MCD, Edwards JK, et al. Variations in HIV risk by young women's age and partner age disparity in rural
South Africa (HPTN 068). J Acquir Immune Defic Syndr. 2020;83:350–356.
30. Groves AK, Gebrekristos LT, McNaughton Reyes L, et al. Describing relationship characteristics and postpartum HIV risk among adolescent, young adult, and adult women in
South Africa. J Adolesc Health. 2020;67:123–126.
31. Ranganathan M, Kilburn K, Stoner MCD, et al. The mediating role of partner selection in the association between transactional sex and HIV incidence among young women. J Acquir Immune Defic Syndr. 2020;83:103–110.
32. Ranganathan M, Heise L, Pettifor A, et al. Transactional sex among young women in rural
South Africa: prevalence, mediators and association with HIV infection. J Int AIDS Soc. 2016;19:20749.
33. Ranganathan M, MacPhail C, Pettifor A, et al. Young women's perceptions of transactional sex and sexual agency: a qualitative study in the context of rural
South Africa. BMC Public Health. 2017;17:666.