Skip to main content

Advertisement

SpringerLink
Log in

Relationship Dynamics are Associated with Self-Reported Adherence but not an Objective Adherence Measure in Malawi

  • Original Paper
  • Published:
AIDS and Behavior Aims and scope Submit manuscript

Abstract

Couple relationships can be leveraged to improve adherence to antiretroviral therapy (ART), but few studies have identified relationship factors to target in interventions in sub-Saharan Africa. We conducted a cross-sectional study with 211 couples in southern Malawi with at least one partner on ART to test for associations between ART adherence and relationship dynamics (intimacy, trust, relationship satisfaction, unity, commitment, and partner support). We measured ART adherence through subjective measures (patient and partner reports) and an objective measure (ART drug levels in hair) and hypothesized that more positive relationship dynamics (e.g., higher intimacy) would be associated with better adherence. Multi-level logistic and linear regression models were used to evaluate study hypotheses, controlling for the clustering of individuals within couples. High levels of adherence were found by all three measures. Unity, satisfaction, and partner support were associated with higher patient and partner reports of adherence, and additional relationship dynamics (intimacy, trust) were associated with higher partner reported adherence. No associations were found between relationship dynamics and drug levels in hair, although drug levels were high overall. Future studies should perform longitudinal assessments of relationship dynamics and objective metrics of adherence, and examine these associations in populations with lower adherence levels such as young women or individuals starting ART.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Availability of Data and Material

De-identified data is available upon request.

Code Availability

Data analysis code is available upon request.

References

  1. UNAIDS. Global. HIV & AIDS Statistics — 2021 Fact Sheet. Geneva: UNAIDS, 2021.

    Google Scholar 

  2. UNAIDS. 90-90-90: AN AMBITIOUS TREATMENT TARGET TO HELP END THE AIDS EPIDEMIC. Geneva, Switzerland: 2017.

  3. Cornell M, Majola M, Johnson LF, Dubula-Majola V. HIV services in sub-Saharan Africa: the greatest gap is men. The Lancet. 2021;397(10290):2130–2.

    Article  Google Scholar 

  4. UNAIDS. UNAIDS Country Report on Malawi. https://www.unaids.org/en/regionscountries/countries/malawi. Geneva, Switzerland: UNAIDS, 2021.

  5. Bórquez A, Cori A, Pufall EL, et al. The incidence patterns model to estimate the distribution of new HIV infections in Sub-Saharan Africa: development and validation of a mathematical model. PLoS Med. 2016;13(9):e1002121.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Darbes L, Dladla S, Mogale T. Motivations for participating in couples-based voluntary counseling and testing in Soweto, South Africa. Poster presented at the XVIth International AIDS Conference. Toronto, Canada: International AIDS Society; 2006.

  7. Conroy AA. The Influence of Relationship Power Dynamics on HIV Testing in Rural Malawi. J Sex Res. 2014;52(3):347–59.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Conroy AA. ‘It means there is doubt in the house’: Perceptions and experiences of HIV testing in rural Malawi. Cult Health Sexuality. 2014;16(4):397–411.

    Article  Google Scholar 

  9. van Rooyen H, McGrath N, Knight L, et al.The association between cohabitation and HIV testing behaviours in heterosexual couples at baseline in KwaZulu-Natal, South Africa International AIDS Society conference; Melbourne, Australia2014.

  10. Ware NC, Idoko J, Kaaya S, et al. Explaining Adherence Success in Sub-Saharan Africa: An Ethnographic Study. PLoS Med. 2009;6(1):e1000011.

    Article  PubMed Central  Google Scholar 

  11. Lewis MA, McBride CM, Pollak KI, et al. Understanding health behavior change among couples: An interdependence and communal coping approach. Soc Sci Med. 2006;62:1369–80.

    Article  PubMed  Google Scholar 

  12. Rusbult C, Arriaga X. Interdependence theory. In: Duck S, editor. Handbook of personal relationships. 2nd ed. London: Wiley; 1997.

    Google Scholar 

  13. World Health Organization. Retention in HIV programmes: Defining the challenges and identifying solutions. Meeting report 13–15 September 2011, Geneva. 2012.

  14. Conroy AA, Leddy AM, Darbes LA, et al. Bidirectional violence is associated with poor engagement in HIV care and treatment in Malawian couples. Journal of interpersonal violence. 2021:Advance online publication.

  15. Conroy AA, McKenna SA, Comfort ML, et al. Marital infidelity, food insecurity, and couple instability: A web of challenges for dyadic coordination around antiretroviral therapy. Soc Sci Med. 2018;214:110–7.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Leddy AM, Weiss E, Yam E, Pulerwitz J. Gender-based violence and engagement in biomedical HIV prevention, care and treatment: a scoping review. BMC Public Health. 2019;19(1):897.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Conroy A, Leddy A, Johnson M, et al. ‘I told her this is your life’: relationship dynamics, partner support and adherence to antiretroviral therapy among South African couples. Cult Health Sex. 2017;19(11):1239–53.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Conroy AA, McKenna SA, Leddy A, et al. “If She is Drunk, I Don’t Want Her to Take it”: Partner Beliefs and Influence on Use of Alcohol and Antiretroviral Therapy in South African Couples. AIDS Behav. 2017;21(7):1885–91.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Conroy AA, McKenna SA, Ruark A. Couple interdependence impacts alcohol use and adherence to antiretroviral therapy in Malawi. AIDS Behav. 2019;23(1):201–10.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Knowlton AR, Bohnert A, Wissow L, Chander G, Arnsten JA. Main partner factors associated with worse adherence to HAART among women in Baltimore, Maryland: a preliminary study. AIDS Care. 2011;23(9):1102–10.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Johnson MO, Dilworth SE, Taylor JM, et al. Primary relationships, HIV treatment adherence, and virologic control. AIDS Behav. 2012;16(6):1511–21.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Robbins RN, Mellins CA, Leu C-S, et al. Enhancing Lay Counselor Capacity to Improve Patient Outcomes with Multimedia Technology. AIDS Behavior: In Press; 2015.

    Book  Google Scholar 

  23. Darbes LA, van Rooyen H, Hosegood V, et al. Uthando Lwethu (‘our love’): a protocol for a couples-based intervention to increase testing for HIV: a randomized controlled trial in rural KwaZulu-Natal, South Africa. Trials. 2014;15(1):64.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Darbes LA, McGrath NM, Hosegood V, et al. Results of a couples-based randomized controlled trial aimed to increase testing for HIV. JAIDS J Acquir Immune Defic Syndr. 2019;80(4):404–13.

    Article  PubMed  Google Scholar 

  25. Wechsberg WM, El-Bassel N, Carney T, et al. Adapting an evidence-based HIV behavioral intervention for South African couples. Substance abuse treatment, prevention, and policy. 2015;10(1):6.

  26. Wechsberg WM, Zule WA, El-Bassel N, et al. The male factor: Outcomes from a cluster randomized field experiment with a couples-based HIV prevention intervention in a South African township. Drug Alcohol Depend. 2016;161:307–15.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Wilson IB, Carter AE, Berg KM. Improving the self-report of HIV antiretroviral medication adherence: is the glass half full or half empty? Curr HIV/AIDS Rep. 2009;6(4):177.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Gandhi M, Ameli N, Bacchetti P, et al. Protease inhibitor levels in hair strongly predict virologic response to treatment. AIDS. 2009;23(4):471–8.

    Article  CAS  PubMed  Google Scholar 

  29. Gandhi M, Ameli N, Bacchetti P, et al Atazanavir concentration in hair is the strongest predictor of outcomes on antiretroviral therapy. Clin Infect Dis. 2011;52(10):1267-75.

  30. Koss CA, Natureeba P, Mwesigwa J, et al. Hair concentrations of antiretrovirals predict viral suppression in HIV-infected pregnant and breastfeeding Ugandan women. AIDS. 2015;29(7):825.

    Article  CAS  PubMed  Google Scholar 

  31. Baxi SM, Greenblatt RM, Bacchetti P, et al. Nevirapine concentration in hair samples is a strong predictor of virologic suppression in a prospective cohort of HIV-infected patients. PLoS ONE. 2015;10(6):e0129100.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Pintye J, Bacchetti P, Teeraananchai S, et al Brief report: lopinavir hair concentrations are the strongest predictor of viremia in HIV-infected Asian children and adolescents on second-line antiretroviral therapy. Journal of acquired immune deficiency syndromes. 2017;76(4):367.

  33. Prasitsuebsai W, Kerr SJ, Truong KH, et al. Using lopinavir concentrations in hair samples to assess treatment outcomes on second-line regimens among Asian children. AIDS Res Hum Retroviruses. 2015;31(10):1009–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Tabb ZJ, Mmbaga BT, Gandhi M,. AIDS (London. et al. Antiretroviral drug concentrations in hair are associated with virologic outcomes among young people living with HIV in Tanzania. England). 2018;32(9):1115.

    CAS  Google Scholar 

  35. Hickey MD, Salmen CR, Tessler RA, et al Antiretroviral concentrations in small hair samples as a feasible marker of adherence in rural Kenya. JAIDS. 2014;[epub ahead of print].

  36. Tuthill EL, Neilands TB, Johnson MO, et al. A Dyadic Investigation of Relationship Dynamics and Depressive Symptoms in HIV-Affected Couples in Malawi. AIDS Behav. 2019;23(12):3435–43.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Huang Y, Gandhi M, Greenblatt RM, et al. Sensitive analysis of anti-HIV drugs, efavirenz, lopinavir and ritonavir, in human hair by liquid chromatography coupled with tandem mass spectrometry. Rapid Communications in Mass Spectrometry: An International Journal Devoted to the Rapid Dissemination of Up‐to‐the‐Minute. Res Mass Spectrom. 2008;22(21):3401–9.

    CAS  Google Scholar 

  38. Huang Y, Yang Q, Yoon K, et al. Microanalysis of the antiretroviral nevirapine in human hair from HIV-infected patients by liquid chromatography-tandem mass spectrometry. Anal Bioanal Chem. 2011;401(6):1923–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. DiFrancesco R, Taylor CR, Rosenkranz SL, et al. Adding value to antiretroviral proficiency testing. Bioanalysis. 2014;6(20):2721–32.

    Article  CAS  PubMed  Google Scholar 

  40. Sternberg RJ. Construct validation of a triangular love scale. Eur J Soc Psychol. 1997;27(3):313–35.

    Article  Google Scholar 

  41. Ruark A, Chase R, Hembling J, et al. Measuring couple relationship quality in a rural African population: Validation of a Couple Functionality Assessment Tool in Malawi. PLoS ONE. 2017;12(11):e0188561.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Larzelere RE, Huston TL. The Dyadic Trust Scale: Toward Understanding Interpersonal Trust in Close Relationships. J Marriage Fam. 1980;42(3):595–604.

    Article  Google Scholar 

  43. Funk JL, Rogge RD. Testing the Ruler With Item Response Theory: Increasing Precision of Measurement for Relationship Satisfaction With the Couples Satisfaction Index. J Fam Psychol. 2007;21(4):572–83.

    Article  PubMed  Google Scholar 

  44. Cutrona CE, Russell DW. The provisions of social relationships and adaptation to stress. Adv personal relationships. 1987;1(1):37–67.

    Google Scholar 

  45. Darbes L, Lewis MA. HIV-specific social support predicts less sexual risk behavior in gay male couples. Health Psychol. 2006;24(6):617–22.

    Article  Google Scholar 

  46. Johnson MO, Dilworth SE, Neilands TB. Partner Reports of Patients’ HIV Treatment Adherence. JAIDS. 2011;56(4):e117-e8.

    Google Scholar 

  47. Thirumurthy H, Siripong N, Vreeman RC, et al. Differences between self-reported and electronically monitored adherence among patients receiving antiretroviral therapy in a resource-limited setting. AIDS. 2012;26(18):2399.

    Article  CAS  PubMed  Google Scholar 

  48. Filmer D, Pritchett LH. Estimating wealth effects without expenditure data–or tears: An application to educational enrollments in states of India. Demography. 2001;38(1):115–32.

    CAS  PubMed  Google Scholar 

  49. Agresti A, Finlay B. Statistical Methods for the Social Sciences. 4th ed. Upper Saddle River: Pearson Prentice Hall; 2009.

    Google Scholar 

  50. Liu AY, Yang Q, Huang Y, et al. Strong relationship between oral dose and tenofovir hair levels in a randomized trial: hair as a potential adherence measure for pre-exposure prophylaxis (PrEP). PLoS ONE. 2014;9(1):e83736.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Hatcher AM, Smout EM, Turan JM, Christofides N, Stocki H. Intimate partner violence and engagement in HIV care and treatment among women: A systematic review and meta-analysis. AIDS. 2015;29(16):2183–94.

    Article  PubMed  Google Scholar 

  52. Johnson MO, Dilworth SE, Taylor JM, et al. Primary relationships, HIV treatment adherence, and virologic control. AIDS Behav. 2012;16(6):1511–21.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Burton J, Darbes LA, Operario D. Couples-focused behavioral interventions for prevention of HIV: Systematic review of the state of evidence. AIDS Behav. 2010;14:1–10.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Crepaz N, Tungol-Ashmon MV, Vosburgh HW, Baack BN, Mullins MM. Are couple-based interventions more effective than interventions delivered to individuals in promoting HIV protective behaviors? A meta-analysis. AIDS Care. 2015;27(11):1361–6.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Remien RH, Stirratt MJ, Dolezal C, et al. Couple-focused support to improve HIV medication adherence: a randomized controlled trial. AIDS. 2005;19:807–14.

    Article  PubMed  Google Scholar 

  56. Bazzi AR, Fergus KB, Stephenson R, et al. A Dyadic Behavioral Intervention to Optimize Same Sex Male Couples’ Engagement Across the HIV Care Continuum: Development of and Protocol for an Innovative Couples-based Approach (Partner Steps). JMIR research protocols. 2016;5(3):e168.

  57. Chawana T, Nhachi C, Nathoo K, et al. Higher Tenofovir Concentrations in Hair Are Associated with Decreases in Viral Load and Not Self-Reported Adherence in HIV-Infected Adolescents with Second-Line Virological Treatment Failure. AIDS Res Hum Retroviruses. 2021;37(3).

  58. Saberi P, Chakravarty D, Ming K, et al. Moving antiretroviral adherence assessments to the modern era: correlations among three novel measures of adherence. AIDS Behav. 2020;24(1):284–90.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Wang M, Miller JD, Collins SM, et al. Social support mitigates negative impact of food insecurity on antiretroviral adherence among postpartum women in western Kenya. AIDS Behav. 2020:1–10.

  60. Mudhune V, Gvetadze R, Girde S, et al. Correlation of adherence by pill count, self-report, MEMS and plasma drug levels to treatment response among women receiving ARV therapy for PMTCT in Kenya. AIDS Behav. 2018;22(3):918–28.

    Article  PubMed  Google Scholar 

  61. Ekstrand ML, Shet A, Chandy S, et al. Suboptimal adherence associated with virological failure and resistance mutations to first-line highly active antiretroviral therapy (HAART) in Bangalore, India. Int health. 2011;3(1):27–34.

    Article  PubMed  Google Scholar 

  62. Simoni JM, Kurth AE, Pearson CR, et al. Self-report measures of antiretroviral therapy adherence: a review with recommendations for HIV research and clinical management. AIDS Behav. 2006;10(3):227–45.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Kiser JJ, Fletcher CV, Flynn PM, et al. Pharmacokinetics of antiretroviral regimens containing tenofovir disoproxil fumarate and atazanavir-ritonavir in adolescents and young adults with human immunodeficiency virus infection. Antimicrob Agents Chemother. 2008;52(2):631–7.

    Article  CAS  PubMed  Google Scholar 

  64. Anderson PL, Kiser JJ, Gardner EM, et al. Pharmacological considerations for tenofovir and emtricitabine to prevent HIV infection. J Antimicrob Chemother. 2011;66(2):240–50.

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

This research was funded by the National Institute of Mental Health (NIMH) under grant number K01MH107331 awarded to AC.

Author information

Authors and Affiliations

  1. Division of Prevention Sciences, Department of Medicine, Center for AIDS Prevention Studies, University of California San Francisco, San Francisco, CA, USA

    Amy A. Conroy Ph.D., M.P.H. & Torsten B. Neilands

  2. Stacey McKenna, LLC, Fort Collins, CO, USA

    Stacey McKenna

  3. Department of Applied Health Sciences, Wheaton College, Wheaton, IL, USA

    Allison Ruark

  4. Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA

    Matthew Spinelli & Monica Gandhi

  5. Center for AIDS Prevention Studies, University of California San Francisco, 550 16th Street, 3rd Floor, San Francisco, CA, USA

    Amy A. Conroy Ph.D., M.P.H.

Authors
  1. Amy A. Conroy Ph.D., M.P.H.
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stacey McKenna
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Allison Ruark
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Torsten B. Neilands
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Matthew Spinelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Monica Gandhi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AC designed the study, collected the data, assisted with the analysis, and drafted the manuscript. SM conceptualized the study and drafted the manuscript. AR conceptualized the study and drafted the manuscript. TN conceptualized the study and advised on data collection and analysis plans. MS assisted with the analysis and interpretation of results. MG supported data collection of hair samples, drug level analysis, and interpretation of results. All authors edited and approved the manuscript.

Corresponding author

Correspondence to Amy A. Conroy Ph.D., M.P.H..

Ethics declarations

Conflict of Interest

There are no conflicts of interest to report for any study authors.

Ethics Approval

This research was approved by the Human Research Protection Program at UCSF and the National Health Sciences Research Committee in Malawi.

Consent to Participate

All participants provided written consent to participate.

Consent for Publication

Not applicable.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Conroy, A.A., McKenna, S., Ruark, A. et al. Relationship Dynamics are Associated with Self-Reported Adherence but not an Objective Adherence Measure in Malawi. AIDS Behav 26, 3551–3562 (2022). https://doi.org/10.1007/s10461-022-03636-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10461-022-03636-2

Keywords

Search

Navigation