Young women in sub-Saharan Africa remain at the epicenter of the HIV epidemic, with persistent high HIV incidence.1,2 In South Africa, incidence rates for young black African women are among the highest of any population globally.3 A better understanding of factors that influence young women's HIV-infection risk is critical for the success of efforts to reduce the burden of disease among this vulnerable population. Conflicting evidence has generated uncertainty about the role that age-disparate partnerships (ie, those in which the male partner is 5 or more years older) play in young women's HIV risk, and consequently, the value of HIV-prevention interventions aimed specifically at reducing risk within such partnerships.4–12
Two compounding factors give plausibility to the hypothesis that age-disparate partnerships increase HIV risk for young women. First, HIV prevalence among men increases steeply with age until approximately 40 years old.3 Unless young women are able to select older HIV-negative partners, age-disparate male partners are more likely to be HIV positive than younger partners and therefore pose greater HIV-infection risk. Second, several studies have documented a range of riskier sexual behaviors within age-disparate partnerships, including condomless sex,13–15 transactional sex,16 and concurrent sexual partnering.17
Conversely, differences by age in the uptake of HIV testing and antiretroviral therapy (ART) among men could theoretically mitigate HIV-infection risk within age-disparate partnerships. HIV testing is positively associated with age,18–21 and older HIV-positive men are more likely to have been diagnosed than their younger counterparts. Moreover, older men are also more likely to link to HIV care and treatment after diagnosis.22–24 Consequently, although age-disparate partners of young women are more likely to be HIV positive, a greater percentage could be on ART and virally supressed. As viral suppression reduces the onward transmission of HIV,25,26 age-disparate partners may, therefore, not pose additional HIV-infection risk for young women if the proportion of men who are HIV positive with a suppressed HIV viral load is similar within age-similar and age-disparate partnerships.
The potential for ART to mitigate risk from age-disparate partnerships will likely vary across time and location as ART uptake, retention, and adherence among men and age differentials in ART coverage change. Contextual factors relating to ART coverage may, for example, partially explain why age-disparate partnerships among young women in the Africa Center for Population Health cohort in rural KwaZulu-Natal were not found to increase HIV risk.10 Men in the study region are part of an ongoing demographic surveillance system that includes regular HIV testing and referral to care.27 Potential geographic and temporal effects on the relationship between age-disparate partnerships and young women's HIV risk highlight the importance of regular monitoring in different contexts.
In this study, we assess the association between age-disparate partnerships and HIV status among 15- to 24-year-old women in a high burden region of South Africa. Second, we explore the biological plausibility of the hypothesis that age-disparate partnerships increase risk for young women by examining HIV status and viral load among men who partner with 15- to 24-year-old women. Specifically, this analysis examines whether the proportion of young women's partners with a viral load ≥1000 copies per milliliter (ie, a marker of individuals who pose an HIV-infection risk) differs between age-disparate and age-similar partnerships.
This study used data from the baseline survey conducted within the HIV Incidence Provincial Surveillance System (HIPSS) from June 2014 to June 2015.28 This cross-sectional household-based survey was conducted in 2 subdistricts [Vulindlela (rural) and Greater Edendale (urban)] of the uMgungundlovu district in KwaZulu-Natal, South Africa. Households were randomly selected using two-stage random sampling methods. First enumeration areas, the primary sampling unit, were selected, and then households were drawn systematically in selected enumeration areas using a serpentine pattern from a random starting location. One individual per household, within the age range 15–49 years, was randomly selected from a roster of eligible household members. The sample comprised 9812 individuals. Venous blood samples were collected for HIV-antibody and viral load tests from all participants. A face-to-face questionnaire was administered to collect data on inter alia, demographics, socioeconomic status, and health-related information. Details on participants' first and 3 most recent sexual partners, including an estimated start date of each relationship, were recorded. Participants were also asked the date of their most recent HIV test and the test result.
The study was approved by the Biomedical Research Ethics Committee, University of KwaZulu-Natal (BF269/13), the Centers for Disease Control and Prevention (CDC) of the United States of America, and by the KwaZulu-Natal Provincial Department of Health in South Africa (HRKM 08/14). Eligible participants provided informed written consent before study enrollment. All study procedures followed were in accordance with the ethical standards of the Helsinki Declaration of 1975, as revised in 2000.
HIV testing was performed using fourth-generation HIV enzyme immunoassays to test for HIV antibodies and antigens using enzyme Biomerieux Vironostika Uniform II Antigen/Antibody Microelisa system (BioMérieux, Marcy I'Etoile, France) and HIV 1/2 Combi Roche Elecys (Roche Diagnostics, Penzberg, Germany). Positive tests were confirmed with a western blot (Biorad assay; Bio-Rad Laboratories, Redmond, WA, USA). Viral load among HIV-positive participants was measured using Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 v2.0 assay (CAP/CTM HIV-1 v2.0). All serology and viral load tests were performed by an accredited laboratory (through the South African National Accreditation System) according to the manufacturers' manuals and were validated in the laboratories that were conducting the testing. Two binary dependent variables were created using laboratory data. The first identified individuals who tested HIV positive, with the reference category representing all HIV-negative individuals. The second variable identified individuals who tested HIV positive and had a viral load ≥1000 copies per milliliter, with the reference category representing HIV-negative individuals, and HIV-positive individuals who had a viral load <1000 copies per milliliter. A viral load of ≥1000 copies per milliliter was chosen as an indicator of individuals who pose an HIV-infection risk as male-to-female HIV transmission is rare below this level.29,30
All sexually active respondents were asked the age of their first and 3 most recent sexual partners. Based on the UNAIDS definition,31 and consistent with the literature,4,7,9,10,32 age-disparate partnerships were identified as those in which the male partner was 5 or more years older. Partnerships in which women were >2 years older than their partner were rare (eg, only 0.6% (n = 9) of the most recent partnerships reported by 15- to 24-year-old women) and were coded as age-similar partnerships because these partnerships are not assumed to carry additional risk for young women.
For the analyses of HIV risk among 15- to 24-year-old women, 3 separate binary measures of age-disparate partnering were created. The first variable was created to identify women who reported age-disparity in their most recent partnership. As partnership age disparities in previous partnerships may have influenced HIV risk, we expanded the definition of the first measure with a second variable that identified women who reported an age disparity in any of their 3 most recent partnerships. Furthermore, a third age-disparate measure was created by included all available partnership data to identify woman who reported an age disparity in their first-ever partnership or any of their 3 most recent partnerships. There is the potential for selection bias in analyses based on the third measure as a result of 414 (26%) participants missing data regarding first-ever partnerships, participants' age at first sex, or the partner's age.
For each measure of age-disparate partnering, we excluded data among HIV-positive women on partnerships (n = 142) in which the start date of the partnership occurred after the reported date of an HIV-positive test. These partnerships were unrelated to HIV infection. The age-disparate measures for these analyses were therefore based on data from all partnerships before a self-reported HIV-positive diagnosis.
All analyses were weighted to take into account the complex multilevel study design of the survey and to adjust for nonresponse. We adjusted standard errors for clustering at the enumeration area level to account for all potential within-cluster error correlation.33 All analyses were conducted using Stata 14 (Stata Corporation LP, College Station, TX, USA).
HIV Status Among Young Women
Analyses of the association between age-disparate partnerships and HIV risk among young women were based on data collected from 15- to 24-year-old women who provided information on at least one sexual partner. Differences in the prevalence of HIV by partnership type (age similar vs. age disparate) were assessed in bivariate analysis using 2-sample equality of proportions tests. Multiple logistic regression models [odds ratios (OR) presented] were used to assess the association between HIV status and age-disparate partnerships among 15- to 24-year-old women. Separate models were created using the 3 age-disparate measures as the key independent variable of interest. All models controlled for factors that could be correlated with both the dependent variable and the formation or dissolution of age-disparate partnerships (past and present). We did not control for factors that theoretically may be influenced by age-disparate partnerships, such as condom use, but are unlikely to be a factor explaining the existence of these partnerships. Control variables in all models included age of the woman (years); education (grade 12 completed or not); having always lived in the area; a household asset index (count of assets from 0 to 14); monthly household income; number of lifetime sexual partners; HIV-testing history (no, yes); and number of useful sources of HIV information exposed to during the previous 12 months (0–16).
HIV Prevalence and Viral Load Among Men in Partnerships With Young Women
To assess whether older male partners of young women represent a higher infection risk, our second analysis used data on all ongoing partnerships (ie, participants reported that the sexual relationship had not ended) men reported with a woman 15–24 years old. Given the HIPSS data are representative of the total sampled population, our assumption is that these partnerships represent all partnerships involving 15- to 24-year-old women in the study region. The men in these partnerships would therefore be a good proxy for the partners of all 15- to 24-year-old women in the area. In other words, each of the partnerships reported by men represents one 15- to 24-year-old women. Accordingly, using these partnerships as individual data for 15- to 24-year-old women, the laboratory data on the men in each partnership provide HIV data on each male partner of 15- to 24-year-old women.
Two-sample equality of proportions tests were used to compare the percentage of HIV-positive male partners, and HIV-positive male partners with a viral load ≥1000 copies per milliliter, in age-disparate and age-similar partnerships. Multiple logistic regression models were used to assess the association between partnership type and both HIV status and viral load of male partners, after controlling for the age of the female partner (in years from 15 to 24).
As intergenerational partnerships (ie, those with an age gap between partners of 10 or more years) have been a specific target of HIV-prevention campaigns in South Africa,34 we repeated our analysis among men to compare HIV prevalence and viral load among age-similar male partners to 2 categories of age-disparate partners: (1) men 5–9 years older, and (2) men 10 or more years older.
Sample of 15- to 24-Year-Old Women
A total of 1459 women aged 15–24 years old provided data on at least one sexual partnership meeting the inclusion criteria for our analyses (Table 1). The majority (69%) were 20–24 years old. Thirty-two percent reported that their most recent partnership involved a partner 5 or more years older than them (ie, age disparate). Forty-two percent reported at least one age-disparate partner either in any of their 3 most recent partnerships or in their first-ever partnership. HIV prevalence was 29% (95% CI: 26% to 3%) among these women.
Sample of Men in Partnerships With 15- to 24-Year-Old Women
A total of 1079 men reported ongoing partnerships with a woman 15–24 years old (Table 1). Most men (63%) were under 25 years old and few were older than 34 (3.7%). HIV prevalence was 15% (95% CI: 12% to 18%) among men in the study population. These men reported 1229 ongoing partnerships with a woman 15–24 years old, with 104 men reporting more than one ongoing relationship. Among these partnerships, 26% where characterized as age disparate by study definitions. The male partner was 5–9 years older in 19% of partnerships and 10 or more years older in 7% of all partnerships.
HIV Status Among Young Women
For all age-disparate measures, bivariate and multiple logistic regression analyses (Table 2) showed that women who reported age-disparate partnerships were significantly more likely to have HIV than women who only reported age-similar partnerships. Bivariate analysis (Table 2, columns 1 and 2) indicated that HIV prevalence was 12 percentage points higher among women who reported an age disparity in any of their 3 most recent partnerships (37% vs. 25%; OR: 1.75, 95% CI: 1.35 to 2.28, P < 0.01) compared with women who did not report an age disparity with any partner. Results were substantively similar after controlling for potential confounders, such as number of lifetime sexual partners reported (Table 2, column 3). According to data on the 3 most recent partnerships, the odds of a woman having HIV (aOR: 1.58, 95% CI: 1.20 to 2.09, P < 0.01) were greater in age-disparate partnerships.
HIV Prevalence and Viral Load Among Men in Partnerships With Young Women
Among the 1229 ongoing partnerships men reported with a woman 15–24 years old, unadjusted logistic regression analyses showed that age-disparate male partners were significantly more likely to be HIV positive (27% vs. 11%; OR: 2.97, 95% CI: 1.87 to 4.73, P < 0.01) than age-similar male partners. Compared with age-similar partners, age-disparate male partners were also significantly more likely to be HIV positive with a viral load ≥1000 (17% vs. 9%; OR: 2.11, 95% CI: 1.35 to 3.30, P < 0.01). Similar results were found in the multiple logistic regression analyses (Table 3, models 1 and 3). Age-disparate male partners of young women were more likely to be HIV positive with a viral load ≥1000 copies per milliliter (aOR: 2.05, 95% CI: 1.30 to 3.24, P < 0.01) compared with age-similar partners (Table 3, model 3).
Models 2 and 4 (Table 3) display the associations between the outcome measures and 2 categories of age-disparate male partners: men 5–9 years older and men 10+ years older. Compared with male partners in the age-similar partnerships, men 5–9 years older (aOR: 2.29, 95% CI: 1.37 to 3.82, P < 0.01) and men 10 or more years older (aOR: 5.39, 95% CI: 2.54 to 11.44, P < 0.01) than their female partners were more likely to be HIV positive (model 2). Compared with age-similar male partners, male partners in both categories of age-disparate partnerships were more likely to be HIV positive with a viral load ≥1000 copies per milliliter (model 4): men 5–9 years older (aOR: 2.01, 95% CI: 1.18 to 3.43, P = 0.010); men 10+ years older (aOR:2.17, 95% CI: 1.01 to 4.66, P = 0.048).
The similar size of the ORs in Model 4 for men 5–9 years older and men 10+ years older than their partner indicates that HIV risk within these different partnerships may be similar after taking ART into account. The reduction in the size of the odds ratio for men 10+ years older than their partners from models 2 to 4 (from 5.39 to 2.17) is consistent with additional study findings (see Table S2, Supplemental Digital Content 2, http://links.lww.com/QAI/B127) of a positive relationship between age among HIV-positive men and reporting being on ART (aOR: 1.13, P < 0.01). Moreover, among the HIV-positive men in our sample, only 22% of those who reported a partner 5–9 years younger than themselves had a viral load <1000 copies per milliliter compared with 50% of men who reported a partnership with a 10+ year age difference. These data indicate that older HIV-positive men were more likely to be on ART and virally suppressed.
With persistent high HIV incidence among young women in sub-Saharan Africa, there is a growing need to understand the factors that increase HIV risk among this population. In this article, we provide evidence on the role age-disparate partnerships play in HIV-infection risk among 15- to 24-year-old women in a high-prevalence setting in South Africa. Consonant with other studies in Southern Africa,9,10,16 a substantial proportion of women in this study had age-disparate partners. Based on all the measures of age-disparate partnering we used, evidence indicates an elevated HIV risk among women in age-disparate partnerships.
Moreover, results indicate biological plausibility for a positive association between age-disparate partnerships and HIV-infection risk among young women. Older male partners of young women were not only more likely to be HIV positive, but also more likely to be HIV positive and have a viral load ≥1000 copies per milliliter—a marker of partners who pose an HIV-infection risk—compared with age-similar partners. These findings, in conjunction with several studies showing that age-disparate partnerships involve more risky sexual behavior,13,14,16,35,36 point to an increased HIV-infection risk for young women in age-disparate partnerships.
However, results provide evidence that current patterns of ART uptake among men in this population could mitigate HIV-infection risk for young (15–24 years old) women in age-disparate partnerships involving men 10 or more years older than their female partners (defined as intergenerational partnerships). Consistent with other studies,23 our data indicated that older HIV-positive men in our sample were more likely to be on ART than younger HIV-positive men. Consequently, although intergenerational male partners of young women had the highest HIV prevalence, findings suggest that young women with intergenerational male partners had a similar likelihood of having an infectious HIV-positive partner (ie, a partner with a detectable viral load) than young women with partners 5–9 years older than them. These findings suggest that, although age-disparate partnerships in general may increase young women's HIV risk, ART could mitigate the additional biological risk posed by intergenerational partnerships. In other words, in terms of the biological risk of HIV infection, the distinction between different types of age-disparate partnerships could be less relevant.
These findings indicate how variation by age among men in the uptake of an intervention that reduces the probability of onward transmission of HIV could affect the dynamics between age-disparate partnering and HIV risk for young women. It is also theoretically possible that variation in age in the uptake of interventions that reduce the likelihood of HIV infection for men, such as voluntary medical male circumcision, will change the relative risk that age-disparate partnerships and intergenerational partnerships pose for young women. In contexts with a larger proportion of young men circumcised compared with older men, for example, the HIV risk associated with age-disparate partners may be large for young women. The potential for the relationship between age-disparate partnering and HIV risk for young women, and women of other ages, to vary according to differential uptake of HIV services by age among men indicates the importance of further research in different contexts. Given the potential for geographic and temporal variation, the external validity of findings on the relationship between age-disparate partnerships and HIV-infection risk should be considered carefully.
These results should be interpreted in the context of the study limitations. Although the use of biomedical data reduces the potential for social desirability bias on the key dependent variables, it is possible that social desirability bias, recall bias, and incorrect knowledge might have resulted in miss-reporting of partnerships,37 and partner age.38 There is also the potential for selection bias in the analysis of HIV status among women, which includes data on first-ever partnerships in the measure of age-disparate partnering. This is due to a large amount of missing data on first-ever partnerships, participants' age at first sex, or the partner's age. In addition, we do not have data on the timing of HIV infection among women and, therefore, do not know in which partnership HIV infections occurred. There is the potential that some women who had age-disparate partners also engaged in high-risk sex with age-similar partners, and the HIV risk was associated with the age-similar rather than the age-disparate partner.
In analyses using partnership data reported by men on ongoing partnerships with 15- to 24-year-old women, we also do not have data on the timing of HIV infection among HIV-positive men. Accordingly, we do not know which men acquired HIV from the young women reported in the partnerships. There is potential for bias in our analyses if the proportion of men who acquired HIV from the partnerships reported in our data differed between men in age-similar and age-disparate partnerships. If for example, a greater percentage of men in the age-disparate partnerships compared with those in the age-similar partnerships acquired HIV within the reported partnership, which is possible as condomless sex is often more common in age-disparate partnerships, then our findings provide an overestimation of young women's risk of HIV exposure from age-disparate partnerships. In addition, our analyses of male partners are based on the assumption that the partnerships reported by men in our sample represent all partnerships involving 15- to 24-year-old women in the study region. However, data on partnerships between 15- to 24-year-old women in the study region and men outside the study region are missing, and some partnerships reported by men are likely to be with young women from other regions. There is the potential for bias if the relationship between HIV prevalence and age among male partners from other regions differs from that among the male partners living in the study region.
Overall, our results help to reduce the uncertainty in the literature by providing evidence to support the argument that age-disparate partnerships could elevate young women's HIV risk. Our results are consistent with a phylogenetic transmission network analysis conducted using a subsample of participants from the HIPSS study that identified a cycle of HIV transmission driven by high rates of new HIV infections in adolescent girls and young women from men who were on average 8 years older.39 The corollary of our findings, especially in high HIV-prevalence settings, is that interventions to reduce HIV-infection risks associated with age-disparate partnerships may help to prevent new infections among young women and break this cycle of transmission. Our results highlight the importance of early diagnosis and treatment of HIV-positive men in age-disparate partnerships with young women as an integral component of the treat-all strategy for HIV prevention.40
The authors thank all the participants of the HIV Incidence Provincial Surveillance System (HIPSS), as well as HIPSS coinvestigators and members of the HIPSS study team from the following organizations: Epicentre, CAPRISA, HEARD, NICD, and CDC. The authors thank the HIPSS collaborating partners: The National Department of Health, Provincial KwaZulu-Natal Department of Health, uMgungundlovu Health District, the uMgungundlovu District AIDS Council, local municipal and traditional leaders, and community members for all their support throughout the HIPPS study. The authors are extremely grateful to Kassahun Ayalew, Karidia Diallo, and Mary Glenshaw for valuable feedback on previous versions of this article.
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