HIV antiretroviral medications have been shown to reduce the transmission of the virus when used for prophylaxis by HIV-negative individuals.1–3 Based on these studies, the US Food and Drug Administration approved the use of tenofovir (TDF)/emtricitabine; an antiretroviral drug for pre-exposure prophylaxis (PrEP) by HIV-negative individuals with a high risk of acquiring sexually transmitted HIV.4 PrEP is now one of the few available HIV prevention strategies in a field where vaccines and a cure have long been elusive.
Adherence to prescribed antiretroviral medication is known to be vital to successful viral suppression and better clinical outcomes in HIV treatment settings.5 Additionally, adherence has been identified to be a key component of effective PrEP.6 Poor adherence to assigned medication is likely the primary reason for the null findings in the FEM-PREP and VOICE studies, which assessed the efficacy of oral and topical TDF for HIV PrEP among heterosexual African women.7
Because PrEP is a new tool in HIV prevention, there are limited data on the associations of adherence to this medication. However, we recently reported that several factors including age, heavy alcohol use, being in a polygamous marriage, and sexual behavior might affect adherence to HIV PrEP.8 For the purposes of this study, polygamy status was defined at baseline and referred to 1 of 2 situations: (1) an HIV-negative man with more than 1 wife, one of whom was HIV-positive or (2) an HIV-negative woman whose HIV-infected husband had more than 1 wife. Marriage was be defined by law, religious, or local custom. We assessed quarterly sexual behavior through interviewer-administered questionnaires, and quarterly adherence was assessed using the medication event monitoring system (MEMS; Aardex, Union City, CA). We found that HIV-negative participants who reported sex with only people other than their primary sexual partners were twice as likely to have low rates of adherence as compared with those who only reported sex with their primary partners (aOR = 2.3, 95% CI: 1.3 to 3.8). In a second study using short message surveys for assessing sexual behavior,9 participants who did not have sex on a particular day were almost twice as likely to miss a dose of PrEP medication on that same day (aOR = 1.87, 95% CI: 1.35 to 2.60).
To better understand the relationship between sexual behavior and adherence to PrEP, in this study, we assessed the associations of sexual behavior with monthly adherence rates, which may better assess short-term effects of sexual behavior and with patterns of adherence to PrEP. Patterns may be more informative than summary measures of adherence (eg, median values) because lengthy gaps may expose an individual to more risk for HIV acquisition compared with occasional missed doses.10 We also explore the effect of condom use on adherence within all strata of sexual behavior. We further evaluated the influence of polygamy within strata of sexual behavior to explore more closely the role of polygamy on adherence to PrEP.
Study Setting and Population
We analyzed data from the Partners Ancillary Adherence Study, a substudy of the Partners PrEP Study.1 The Partners PrEP Study was a multisite, phase 3, randomized, double-blind, placebo-controlled clinical trial that assessed the efficacy and safety of TDF and emtricitabine/TDF (FTC/TDF) for PrEP against HIV acquisition. This clinical trial enrolled 4758 heterosexual serodiscordant couples at 4 sites in Kenya and 5 sites in Uganda. Heterosexual couples were defined as “sexual partners of the opposite gender who were married, had been living together, or otherwise considered each other a primary partner.” The adherence study took place at 3 of the Ugandan sites, including Kampala (an urban setting), Kabwohe, and Tororo (rural settings; Fig. 1). We have previously described details of this study,8 but briefly we enrolled 1147 HIV-negative individuals in long-term serodiscordant relationships. All PrEP study participants at these sites were eligible for participation as long as they consented for study procedures and had at least 6 or more months of follow-up in the parent clinical trial. Enrollment was offered on a rolling basis, and all participants provided written informed consent. In addition to monthly follow-up visits at the clinics, we conducted unannounced home visits for pill counts monthly for the first 6 months and then quarterly thereafter. We also used the MEMS to monitor the date and time of pill bottle openings. Finally, participants with <80% monthly adherence to PrEP were started on multisession adherence intervention.11 Data for this analysis were censored at July 10, 2011, the date of unbinding of the placebo arm.
The study was approved by the institutional review boards of participating study sites and those of Massachusetts General Hospital/Partners Healthcare and of the University of Washington.
Assessment of Sexual Behavior
Sexual behavior was assessed through interviewer-administered questionnaires completed at monthly clinic visits. Face-to-face interviews have not been validated in a PrEP setting but have been shown to consistently assess sexual behavior.12 At each visit, study participants met with counselors and discussed several issues relating to HIV discordancy including sexual behavior in the past month. The interviewers queried the number of sexual acts, condom use, and sexual acts with anyone besides the primary partner. Whenever “sex” or “sexual intercourse” was stated in a question, it included vaginal and anal sex, but not oral sex. Interviews were conducted in either English or in a local language of a participant's preference and participants were given the option of being interviewed by a counselor of their choice.
We categorized monthly sexual behavior as follows: participants who abstained, those who had sex with only their primary partners, those who had sex with only other partners (but not with their primary partner), and those who had sex with both the primary and other partner(s). Each of the above categories was dichotomized into either 100% condom use or <100% condom use. The “other partner” category included participants who in the previous month did not have sex with their primary partner but reported sex with someone else. We were unable to stratify this category by polygamy status at baseline due to small numbers. The number of participants was sufficient, however, to make this stratification for the category reporting sex with both the primary and other partner(s).
Assessment of Adherence
Monthly adherence to PrEP medication was assessed using the MEMS. This system uses an electronic microchip in the cap of a pill bottle to record dates and times the pill bottle was opened and closed. The underlying assumption is that every opening and closure of the pill bottle translates to a swallowed dose of the study drug. Recorded adherence data were then downloaded during monthly clinic visits. Although MEMS is a proxy measure and is subject to misclassification, it allows for assessment of adherence patterns by documenting daily pill taking behavior13 and has been shown to have a high positive predictive value of treatment outcomes.14
We assessed execution of adherence as a dichotomous variable, with 80% or greater adherence defined as “high adherence” and <80% adherence defined as “low adherence.” The level of adherence required for effective PrEP is not known. However, we recently found 100% PrEP efficacy if participants' adherence rates are maintained at 80% and above.8 We also assessed patterns of adherence (ie, the number of periods of at least 48 hours, 72 hours, and 1 week during with the pill bottle was unopened). We looked at a range of patterns because there are limited data on how much TDF must be present in blood and tissue to offer protection against HIV. Data are also limited on how gaps in adherence before and after achievement of stable states affect this protection. Using the heuristic that drugs remain in the body for about 4 half-lives,15 it is likely that TDF (half life ∼17 hours) is undetectable after a gap of 68 hours or approximately 3 days.
Assessments of Other Covariates
We collected baseline data on the study participant's age, gender, social–economic status, and level of education, all of which have been shown to be associated with adherence in HIV treatment settings.16 We assessed partnership characteristics including how long the couple had been living together, the number of children they had, whether one of them was in a polygamous marriage, and how long they had known that they were HIV discordant. Social–economic status was assessed using the Filmer–Pritchett Index, which uses household items to estimate wealth.17 For this study, the wealth index for a couple's home reflected the presence of a concrete floor, running water, electricity, a television, and a house with 2 or more rooms of residence.
Time-varying characteristics assessed included heavy alcohol use, depression, number of study drug's side effects, the participant's perceived risk of HIV acquisition, and CD4 cell counts of the HIV-infected partner. Depression was assessed using the Hopkins Symptom Checklist, a functional impairment assessment instrument that can be used to approximate a Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) depression diagnosis, which has been validated in similar populations.18 Heavy alcohol use was assessed using the Rapid Alcohol Problems Screen that has been shown to have good sensitivity and specificity in identifying detrimental drinking patterns and has cross-nation validity.19
We performed bivariate analyses between each possible covariate and adherence using generalized estimating equations. Monthly adherence execution was modeled using a binomial distribution, whereas adherence patterns were modeled with a Poisson distribution. For model selection, the initial multivariate model included all variables with a P value ≤0.20 from the bivariate analyses. Starting with variables with the highest P values, we assessed the scale of maximum likelihood, 1 at a time and dropped those with P values ≥0.10 from the final multivariate model. We used a similar method to assess possible interaction effects between sexual behaviors with age, gender, study site, and social–economic status, all chosen apriori and used a P value of <0.10 as a cutoff for statistical significance. Data were analyzed using SAS version 9.3 (SAS Institute Inc, Cary, NC).
A total of 1751 HIV-negative participants enrolled in the parent clinical trial at the 3 sites. Of these, 1182 were offered participation in the adherence study and 1147 (97%) were enrolled. Reasons for not being offered participation included having less than 6 months remaining for follow-up while on study drug, logistical reasons that would make study procedures difficult to conduct, and stopping of the parent clinical trial before participation could be offered. Thirty-five participants did not meet the criteria for enrollment resulting in a final analysis data set of 1093 participants (Table 1). Of these, 53.4% were male, 51.2% were aged between 18 and 34 years, the median number of years living with the HIV-positive partner was 8.5 years, and 24.2% were in polygamous marriages. The mean follow-up duration was 11 months.
Overall Adherence and Sexual Behavior
A total of 402 (36.7%) participants had at least 1 month with <80% adherence; this translated into 13.3% of the observed months of low adherence. Levels of adherence are presented by category of sexual activity and condom use in Table 2. Participants who reported sex with other partners only (ie, no sex with their primary sexual partner) and also reported <100% condom use (N = 92) were more than twice as likely to be low adherers as compared with those who had sex only with their primary partners with 100% condom use (aOR = 2.48, 95% CI: 1.70 to 3.62). The number of other sexual partners had no effect on odds for low adherence (OR = 0.98, 95% CI: 0.68 to 1.40). Using the same reference group, those who abstained from sex in the previous month (N = 465) had 30% increased odds of low adherence (aOR = 1.30, 95% CI: 1.05 to 1.62). Participants who reported sex with both their primary and other partners (not including polygamous marriages) with <100% condom use (N = 60) were almost twice as likely to be low adherers (aOR = 1.76, 95% CI: 1.01 to 3.08). However, those with similar sexual behavior in the past month but in polygamous marriages did not have significantly higher odds of low adherence (aOR = 1.10, 95% CI: 0.49 to 2.53).
Participants who reported sex with only their primary partners were more likely to have 100% condom use as compared with those who had sex with both their primary partners and other partner(s) and with those who had sex with only other partners (79%, 33% and 36%, respectively). Those with low or moderate concern of contracting HIV had 41% lower odds of low adherence as compared with those who had no concern of HIV acquisition. Men were 34% more likely to be low adherers than women. We did not find any significant interaction effects of sexual behavior with age (P = 0.91), social–economic status (P = 0.23), or study site (P = 0.17) on the likelihood of having <80% monthly adherence to PrEP.
Patterns of Adherence
Prevalence of gaps in adherence by sexual behavior is presented in Table 3. A total of 598 (54.7%) of the participants had at least 1 gap of 72 consecutive hours of nonadherence, and 254 (23.2%) of these also had at least one 1-week gap of nonadherence. Of the participants who reported <100% use of condoms in a previous month (N = 546), 38.8% had at least one 72-hour gap in adherence in that month and 17% had a 1-week gap in adherence in that month.
Participants who reported sex with other partners only and <100% condom use had 50% higher odds of having at least one 72-hour gap in adherence as compared with those who had sex with only their primary partners with 100% condom use (aOR = 1.50, 95% CI: 1.19 to 1.91), whereas those who abstained from sex in the previous month had 17% elevated odds (aOR = 1.17, 95% CI: 1.01 to 1.35; Table 4). Adherence gaps of 72 hours were not associated with reporting sex with both primary and other partners in the previous month, regardless of polygamy status. We found similar results when assessing odds of having 48-hour gaps in adherence (data not shown). Men were more likely to have had a 1-week gap as compared with women (aOR = 1.54, 95% CI: 1.04 to 2.27).
In this prospective observational study within a randomized clinical trial, HIV-negative participants who reported sex with people other than their primary partner and those who abstained from sexual activity in the previous month were more likely to be low adherers. We found similar, although somewhat weaker, associations between sexual activity and gaps in adherence. Our findings also indicate that <100% condom use was more common in participants who reported sex with only other partners and that participants in polygamous marriages did not have increased odds of being low adherers.
These findings extend results from our previous study.8 This study, however, observed somewhat weaker associations among participants who had abstained in the past month, which suggests that the association of abstinence with adherence may be stronger if this sexual behavior is sustained over a longer period (in this case, quarterly versus monthly). We also found that participants who had sex with only other partners had the highest odds of low adherence and having gaps of nonadherence. We are however unable to distinguish whether this other partner was a new sexual partner or a partner in a polygamous marriage. Nonetheless, these findings indicate that participants who had sex with only other partners are more likely to be low adherers. A similar pattern has been observed in some HIV treatment settings, where patients with risky sexual behaviors are also more likely to be poor adherers to therapy.20,21 Also, the highest odds of low adherence were observed in participants who had sex with only other partners and in the same month also had less than 100% condom use. Additional research is needed on the dynamics influencing condom use with primary partners (HIV-infected) and with other partners. However, 1 possible explanation for both lower adherence and <100% condom use is low perceived risk of acquiring HIV from the other partner.
To our knowledge, no study has explicitly assessed the role of polygamy on adherence. Several studies have however found that polygamy offers a protective effect against HIV acquisition.22,23 Our previous findings showed that participants in polygamous marriage had a 60% reduced odds for low adherence as compared with those from monogamous marriages.8 We did not find a protective effect in this study but did find no increased risk among polygamous partners. We hypothesize that HIV-negative partners in discordant and polygamous marriages receive extra social support to adhere to PrEP so as to prevent transmission of HIV within the polygamous marriage. This concept is consistent with our recent findings that spousal support plays a key role in PrEP adherence.24 The lack of a protective effect in our study could be multifactorial. First, we had small numbers of people in these stratifications. Secondly, the 1-month exposure period might not be long enough to assess the protective effect that was observed in quarterly assessment of sexual behavior on adherence.
This is the first study to assess the effect of sexual behavior on patterns of adherence. Although previous studies have shown that participants in Partners PrEP Study had high rates of adherence,8 we found that many participants had gaps of not taking their medication. Such intermittent dosing is likely to increase the risk of acquiring HIV because every subsequent day of nonadherence results in a lower concentration of active drug. This increased risk is consistent with findings from the FEM-PrEP study that showed high rates of inconsistent use of the study drug that could have contributed to the lack of a protective effect in the active study arms.25 Some of the observed gaps, however, could have been due to pocket doses (ie, removal of multiple tablets with 1 opening for later use), a well-established limitation of electronic adherence measurement, and may not reveal true gaps in adherence. The correlation of adherence gaps with other potentially risky sexual behaviors, like sex with other partners, suggests that many are real. Additionally, we do not know if these gaps in adherence were covered by other forms of HIV prevention (eg, condoms). This highlights the need for a better understanding of the use of combination prevention strategies. Additionally, among participants who reported abstinence in the previous month, some extended gaps could have been intentional because of no perceived risk of HIV transmission in that period. Such practices may be logical; however, the correlation of specific dosing patterns with achievement and maintenance of drug levels sufficient for providing effective protection against HIV infection are unknown. Such an understanding will be crucial in advising individuals on how to start and stop PrEP (ie, periodic dosing) with the confidence that it will be effective. These findings can be used in designing HIV prevention programs with a PrEP component. For example, PrEP might not be the recommended HIV prevention method for people who know that they will not be having sex for certain periods. Also, individuals with outside partners may benefit from additional counseling on risk perception and strategies for including PrEP when they are with these other partners.
Our study's strengths include the use of a prospective study design to assess the effects of short-term sexual behaviors on low adherence. Our large sample size enabled us to assess the effects of many aspects of sexual behavior. One study limitation was that few participants reported sexual activity with both their primary and other partners. We therefore had limited statistical power to assess associations between sexual behavior and adherence within some strata of sexual behavior. Also, we did not have data on relationship discord, a risk factor that has been suggested to be critical to adherence to PrEP medication26 and were therefore unable to evaluate possible confounding by this factor. Also, data on sexual behavior were collected using self-report, which is subject to social desirability bias, which may result in to less reporting of some risky sexual behaviors. Finally, we could not distinguish if other partners were actually within polygamous marriages.
In conclusion, our findings identify groups of people in HIV-serodiscordant relationships who may require additional adherence support during PrEP implementation programs, namely, those with multiple partners but are not in polygamous marriages. In addition, PrEP eligible persons who are likely to abstain from sex may need prevention methods that are more suitable to intermittent need. Also, we found that although overall adherence rates were high, many participants missed taking their study pills for relatively long periods of time, potentially creating risk for HIV acquisition. Additional research is needed on the use and efficacy of intermittent and periodic PrEP from trials and demonstration projects. We also found that polygamy might be a factor influencing better adherence due to the desire to prevent HIV transmission within a polygamous marriage. However, more work is needed to ascertain this effect using a study with more people who report this behavior and 1 that distinguishes whether the “other partner” is part of the polygamous marriage.
The authors would like to thank the study participants and the study teams in Kabwohe, Kampala, and Tororo.
Partners Ancillary Adherence Study Team.
Massachusetts General Hospital and Harvard University (Boston, MA): David Bangsberg, Jessica Haberer, Stephen Safren, Christina Psaros, Norma Ware, Monique Wyatt; University of Washington (Seattle, WA): Connie Celum, Jared M. Baeten, Deborah Donnell; Johns Hopkins University (Baltimore, MD): Craig Hendrix; Kabwohe Clinical Research Center (Kabwohe, Uganda): Elioda Tumwesigye, Stephen Asiimwe; Makerere University (Kampala, Uganda): Elly Katabira, Allan Rolland, Edith Nakku-Joloba; Centers for Disease Control and Prevention-Uganda and The AIDS Support Organization (Tororo, Uganda): James Campbell, Aloysious Kakia. Study drug was donated by Gilead Sciences (CA).
1. Baeten JM, Donnell D, Ndase P, et al.. Antiretroviral prophylaxis for HIV prevention in heterosexual men and women. N Engl J Med. 2012;367:399–410.
2. Abdool Karim Q, Abdool Karim SS, Frohlich JA, et al.. Effectiveness and safety of tenofovir gel, an antiretroviral microbicide, for the prevention of HIV infection in women. Science. 2010;329:1168–1174.
3. Grant RM, Lama JR, Anderson PL, et al.. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. N Engl J Med. 2010;363:2587–2599.
4. Holmes D. FDA paves the way for pre-exposure HIV prophylaxis. Lancet. 2012;380:325.
5. Paterson DL, Swindells S, Mohr J, et al.. Adherence
to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med. 2000;133:21–30.
6. Kashuba AD, Patterson KB, Dumond JB, et al.. Pre-exposure prophylaxis
for HIV prevention: how to predict success. Lancet. 2012;379:2409–2411.
7. Amico KR, Mansoor LE, Corneli A, et al.. Adherence
support approaches in biomedical HIV prevention trials: experiences, insights and future directions from four multisite prevention trials. AIDS Behav. 2013;17:2143–2155.
8. Haberer JE, Baeten JM, Campbell J, et al.. Adherence
to antiretroviral prophylaxis for HIV prevention: a substudy cohort within a clinical trial of serodiscordant couples in East Africa. PLoS Med. 2013;10:e1001511.
9. Curran K, Mugo NR, Kurth A, et al.. Daily short message service surveys to measure sexual behavior
and pre-exposure prophylaxis
use among Kenyan men and women. AIDS Behav. 2013;17:2977–2985.
10. van der Straten A, Van Damme L, Haberer JE, et al.. Unraveling the divergent results of pre-exposure prophylaxis
trials for HIV prevention. AIDS. 2012;26:F13–F19.
11. Psaros C, Haberer JE, Katabira E, et al.. An intervention to support HIV preexposure prophylaxis adherence
in HIV-serodiscordant couples in Uganda. J Acquir Immune Defic Syndr. 2014;66:522–529.
12. Mensch BS, Hewett PC, Gregory R, et al.. Sexual behavior
and STI/HIV status among adolescents in rural Malawi: an evaluation of the effect of interview mode on reporting. Stud Fam Plann. 2008;39:321–334.
13. Knafl GJ, Bova CA, Fennie KP, et al.. An analysis of electronically monitored adherence
to antiretroviral medications. AIDS Behav. 2010;14:755–768.
14. Farley J, Hines S, Musk A, et al.. Assessment of adherence
to antiviral therapy in HIV-infected children using the medication event monitoring system, pharmacy refill, provider assessment, caregiver self-report, and appointment keeping. J Acquir Immune Defic Syndr. 2003;33:211–218.
15. Anderson PL, Kiser JJ, Gardner EM, et al.. Pharmacological considerations for tenofovir and emtricitabine to prevent HIV infection. J Antimicrob Chemother. 2011;66:240–250.
16. Reda AA, Biadgilign S. Determinants of adherence
to antiretroviral therapy among HIV-infected patients in Africa. AIDS Res Treat. 2012;2012:574656.
17. Filmer D, Pritchett LH. Estimating wealth effects without expenditure data–or tears: an application to educational enrollments in states of India. Demography. 2001;38:115–132.
18. Bolton P, Wilk CM, Ndogoni L. Assessment of depression prevalence in rural Uganda using symptom and function criteria. Soc Psychiatry Psychiatr Epidemiol. 2004;39:442–447.
19. Cherpitel CJ, Ye Y, Bond J, et al.. Cross-national performance of the RAPS4/RAPS4-QF for tolerance and heavy drinking: data from 13 countries. J Stud Alcohol. 2005;66:428–432.
20. Kalichman SC, Rompa D. HIV treatment adherence
and unprotected sex practices in people receiving antiretroviral therapy. Sex Transm Infect. 2003;79:59–61.
21. Ndziessi G, Boyer S, Kouanfack C, et al.. Adherence
as a predictor of sexual behaviors in people living with HIV/AIDS during the first year of antiretroviral therapy in rural Cameroon: data from Stratall ANRS 12110/ESTHER trial. PLoS One. 2012;7:e36118.
22. Kuate S, Mikolajczyk RT, Forgwei GW, et al.. Time trends and regional differences in the prevalence of HIV infection among women attending antenatal clinics in 2 provinces in Cameroon. J Acquir Immune Defic Syndr. 2009;52:258–264.
23. Mitsunaga TM, Powell AM, Heard NJ, et al.. Extramarital sex among Nigerian men: polygyny and other risk factors. J Acquir Immune Defic Syndr. 2005;39:478–488.
24. Ware NC, Pisarski EE, Haberer JE, et al.. Lay social resources for support of adherence
to antiretroviral prophylaxis for HIV prevention among serodiscordant couples in sub-Saharan Africa: a qualitative study. AIDS Behav. 2014.
25. Corneli AL, Deese J, Wang M, et al.. FEM-PrEP: adherence
patterns and factors associated with adherence
to a daily oral study product for pre-exposure prophylaxis
. J Acquir Immune Defic Syndr. 2014;66:324–331.
26. Ware NC, Wyatt MA, Haberer JE, et al.. What's love got to do with it? Explaining adherence
to oral antiretroviral pre-exposure prophylaxis
for HIV-serodiscordant couples. J Acquir Immune Defic Syndr. 2012;59:463–468.