Factors Associated with PrEP Refusal Among Transgender Women in Northeastern Brazil

  • Fabiane SoaresEmail author
  • Sarah MacCarthy
  • Laio Magno
  • Luís Augusto Vasconcelos da Silva
  • Leila Amorim
  • Amy Nunn
  • Catherine E. Oldenburg
  • Inês Dourado
  • The PopTrans Group
Original Paper


Brazil has recently integrated HIV Pre-exposure Prophylaxis (PrEP) into its public health system and offered to key populations such as transgender women (TGW). This study investigates factors associated with PrEP refusal among TGW living in one of the largest and poorest cities of Brazil. We recruited 127 TGW using Respondent Driven Sampling (RDS) in Salvador, Brazil. Latent class analysis (LCA) was used to define acceptability of PrEP. Two latent classes were identified: “high acceptability of PrEP” (91.3%) and “PrEP refusal” (8.7%). PrEP was less acceptable among white TGW and among those age 25 or older, with income above minimum wage (≥ US$252.87), and reporting unprotected receptive anal intercourse with (URAI) causal partners. The findings highlight how nuanced strategies that takes into consideration unique characteristics are needed to effectively address the acceptability of PrEP.


HIV Pre-exposure prophylaxis (PrEP) Prevention Transgender people Refusal  


Brasil ha integrado recientemente la Profilaxis de Preexposición (PrEP) ao VIH en su sistema de salud pública y se ofrece a las poblaciones claves como las mujeres transgénero (TGW). Este estudio investiga los factores asociados al rechazo de la PrEP entre las TGW que viven en una de las ciudades más grandes y más pobres de Brasil. Reclutamos 127 TGW utilizando Respondent Driven Sampling (RDS) en Salvador, Brasil. El análisis de clase latente (LCA) se usó para definir la aceptabilidad de PrEP. Se identificaron dos clases latentes: “alta aceptabilidad de PrEP” (91.3%) y “recusa da PrEP” (8.7%). La PrEP fue menos aceptable entre las TGW de piel blanca, de 25 años o más, con ingresos de > $ 252.87 dólares y con relaciones anales receptivas no protegidas con parejas casuales (RARNP). La PrEP fue muy aceptable en esta muestra de las TGW en el nordeste de Brasil. Sin embargo, las TGW con mayor riesgo de infección por VIH, que generalmente tienen RARNP, estaban menos dispuestas a usar PrEP.

Palabras clave

VIH Profilaxis de Preexposición (PrEP) Prevención Personas transgénero  Rechazo 



The authors would like to express their gratitude to the participants of the study, to the local team that carried out the fieldwork in Salvador and all the collaborating NGO: Association of Transvestites in Salvador (Associação de Travestis de Salvador: ATRAS); Conceição Macedo Beneficent Institute (Instituto Beneficente Conceição Macedo: IBCM). Additionally, we appreciate the CAPES support for the Master´s fellowship granted to FS. The funding financial support for this study was provided by Brazilian Ministry of Health, through its Secretariat for Health Surveillance and its Department of Prevention, Surveillance and Control of Sexually Transmitted Infections, HIV/AIDS and Viral Hepatitis through a grant number: 225,943/2014. No funding bodies had any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


  1. 1.
    Brazil, Ministry of Health. The Brazilian response to HIV and AIDS—Global AIDS Response Progress Reporting (GARPR). Brasília; 2015.
  2. 2.
    Baral SD, Poteat T, Strömdahl S, Wirtz AL, Guadamuz TE, Beyrer C. Worldwide burden of HIV in transgender women: a systematic review and meta-analysis. Lancet Infect Dis. 2013;13(3):214–22.Google Scholar
  3. 3.
    Grinsztejn B, Jalil EM, Monteiro L, et al. Unveiling of HIV dynamics among transgender women: a respondent-driven sampling study in Rio de Janeiro, Brazil. Lancet HIV. 2017;4(4):e169–76.Google Scholar
  4. 4.
    World Health Organization. Transgender people and Hiv. 2015.
  5. 5.
    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(27):2587–99.Google Scholar
  6. 6.
    Anderson PL, Glidden DV, Liu A, et al. Emtricitabine-tenofovir concentrations and pre-exposure prophylaxis efficacy in men who have sex with men. Sci Transl Med. 2012;4(151):151ra125.Google Scholar
  7. 7.
    Montgomery MC, Oldenburg CE, Nunn AS, et al. Adherence to pre-exposure prophylaxis for HIV prevention in a clinical setting. PLoS ONE. 2016;11(6):e0157742.Google Scholar
  8. 8.
    Parker S, Chan PA, Oldenburg CE, et al. Patient experiences of men who have sex with men using pre-exposure prophylaxis to prevent HIV infection. AIDS Patient Care STDS. 2015;29(12):639–42.Google Scholar
  9. 9.
    Chan PA, Glynn TR, Oldenburg CE, et al. Implementation of preexposure prophylaxis for human immunodeficiency virus prevention among men who have sex with men at a new england sexually transmitted diseases clinic. Sex Transm Dis. 2016;43(11):717–23.Google Scholar
  10. 10.
    Sevelius JM, Deutsch MB, Grant R. The future of PrEP among transgender women: the critical role of gender affirmation in research and clinical practices. J Int AIDS Soc. 2016;19(Suppl 6):21105.Google Scholar
  11. 11.
    Deutsch MB, Glidden DV, Sevelius J, et al. HIV pre-exposure prophylaxis in transgender women: a subgroup analysis of the iPrEx trial. Lancet HIV. 2015;2(12):e512–9.Google Scholar
  12. 12.
    Paim J, Travassos C, Almeida C, Bahia L, Macinko J. Health in Brazil 1. The Brazilian health system: history, advances, and challenges. Lancet. 2011;377(377):1778–97.Google Scholar
  13. 13.
    Nunn AS, Massard E, Fonseca D, Bastos FI, Gruskin S, Nunn A. AIDS treatment in Brazil: impacts and challenges. Heal Aff (Millwood). 2009;28(4):1103–13.Google Scholar
  14. 14.
    Hoagland B, De Boni RB, Moreira RI, et al. Awareness and willingness to use pre-exposure prophylaxis (PrEP) among men who have sex with men and transgender women in Brazil. AIDS Behav. 2017;21(5):1278–87.Google Scholar
  15. 15.
    Brasil, Ministry of Health. Profilaxia Pré-Exposição (PrEP) de Risco à Infecção pelo HIV. 2017;47.
  16. 16.
    Luz PM, Benzaken A, de Alencar TM, Pimenta C, Veloso VG, Grinsztejn B. PrEP adopted by the brazilian national health system: what is the size of the demand? Medicine (Baltimore). 2018;97(Suppl 1):S75–7.Google Scholar
  17. 17.
    Mensch BS, van der Straten A, Katzen LL. Acceptability in microbicide and PrEP trials: current status and a reconceptualization. Curr Opin HIV AIDS. 2012;7(6):534–41.Google Scholar
  18. 18.
    Dolezal C, Frasca T, Giguere R, et al. Awareness of post-exposure prophylaxis (PEP) and pre-exposure prophylaxis (PrEP) is low but interest is high among men engaging in condomless anal sex with men in Boston, Pittsburgh, and San Juan. AIDS Educ Prev. 2015;27(4):289–97.Google Scholar
  19. 19.
    Mimiaga MJ, Case P, Johnson CV, Safren SA, Mayer KH. Preexposure antiretroviral prophylaxis attitudes in high-risk Boston area men who report having sex with men: limited knowledge and experience but potential for increased utilization after education. J Acquir Immune Defic Syndr. 2009;50(1):77–83.Google Scholar
  20. 20.
    Frankis JS, Young I, Lorimer K, Davis M, Flowers P. Towards preparedness for PrEP: PrEP awareness and acceptability among MSM at high risk of HIV transmission who use sociosexual media in four Celtic nations: Scotland, Wales, Northern Ireland and The Republic of Ireland: an online survey. Sex Transm Infect. 2016;92(4):6.Google Scholar
  21. 21.
    Oldenburg CE, Le B, Toan T, et al. HIV pre-exposure prophylaxis indication and readiness among HIV-uninfected transgender women in Ho Chi Minh City, Vietnam. AIDS Behav. 2016;20(Suppl 3):365–70.Google Scholar
  22. 22.
    Dourado I, Silva LAV, Magno L, et al. Building bridges: interdisciplinarity in practice. PopTrans Study: a study with transvestites and transsexual women in Salvador, Bahia State, Brazil. Cad Saude Publica. 2016;32(9):3. Scholar
  23. 23.
    Barbosa Júnior A, Pascom ARP, Szwarcwald CL, Kendall C, McFarland W. Transfer of sampling methods for studies on most-at-risk populations (MARPs) in Brazil. Cad Saude Publica. 2011;27(suppl 1):s36–44.Google Scholar
  24. 24.
    Heckathorn DD. Respondent-driven sampling: a new approach to the study of hidden populations. Soc Probl. 1997;44(2):174–99.Google Scholar
  25. 25.
    Johnston LG, Sabin K. Sampling hard-to-reach populations with respondent driven sampling. Methodol Innov Online. 2010;5(2):38–48.Google Scholar
  26. 26.
    MacCarthy S, Reisner S, Hoffmann M, et al. Mind the gap: implementation challenges break the link between HIV/AIDS research and practice. Cad Saúde Pública. 2016;32(10):e00047715.Google Scholar
  27. 27.
    Kerr LRFS, Mota RS, Kendall C, et al. HIV among MSM in a large middle-income country. Wolters Kluwer Health AIDS. 2013;27:427–35.Google Scholar
  28. 28.
    Baptista CJ, Dourado I, Brignol S, de Matos Andrade T, Bastos FI. Factors associated with syphilis seroreactivity among polydrug users in Northeast Brazil: a cross-sectional study using Respondent Driven Sampling. Int J Drug Policy. 2017;1(39):37–42.Google Scholar
  29. 29.
    Chan PA, Rose J, Maher J, et al. A latent class analysis of risk factors for acquiring HIV among men who have sex with men: implications for implementing pre-exposure prophylaxis programs. AIDS Patient Care STDS. 2015;29(11):597–605.Google Scholar
  30. 30.
    Nunn A, Brinkley-Rubinstein L, Rose J, et al. Latent class analysis of acceptability and willingness to pay for self-HIV testing in a United States urban neighbourhood with high rates of HIV infection. J Int AIDS Soc. 2017;20(1):21290.Google Scholar
  31. 31.
    Collins LM, Lanza ST. Latent class and latent transition analysis: with applications in the social behavioral, and health sciences. 1st ed. Los Angeles: Wiley; 2010. p. 285.Google Scholar
  32. 32.
    Celeux G, Soromenho G. An entropy criterion for assessing the number of clusters in a mixture model. J Classif. 1996;13(2):195–212.Google Scholar
  33. 33.
    Burnham KP, Anderson DR. Model selection and multimodel inference: a practical information-theoretic approach. New York: Springer; 2002. p. 488.Google Scholar
  34. 34.
    Henson JM, Reise SP, Kim KH. Detecting mixtures from structural model differences using latent variable mixture modeling: a comparison of relative model fit statistics. Struct Equ Model. 2007;14(2):202–26.Google Scholar
  35. 35.
    Salganik MJ, Heckathorn DD. Sampling and estimation in hidden populations using respondent-driven sampling. Sociol Methodol. 2004;34:193–239.Google Scholar
  36. 36.
    Muthén LK, Muthén BO. Mplus statistical analysis With latent variables user’s guide. 6th ed. Los Angeles: Muthén & Muthén; 2010. p. 758.Google Scholar
  37. 37.
    Tukey JW. Exploratory data analysis. Menlo Park: Addison-Wesley Pub. Co; 1977. p. 688.Google Scholar
  38. 38.
    Volz E, Heckathorn DD. Probability based estimation theory for respondent driven sampling. J Off Stat. 2008;24(1):79–97.Google Scholar
  39. 39.
    Hosmer DW, Lemeshow S. Applied logistic regression. 2nd ed. New York: Wiley; 2000. p. 376.Google Scholar
  40. 40.
    Garnett M, Hirsch-Moverman Y, Franks J, Hayes-Larson E, El-Sadr WM, Mannheimer S. Limited awareness of pre-exposure prophylaxis among black men who have sex with men and transgender women in New York city. AIDS Care. 2018;30(1):9–17.Google Scholar
  41. 41.
    Draper BL, Oo ZM, Thein ZW, et al. Willingness to use HIV pre-exposure prophylaxis among gay men, other men who have sex with men and transgender women in Myanmar. J Int AIDS Soc. 2017;20(1):21885.Google Scholar
  42. 42.
    Goedel WC, Perry Halkitis BN, Richard Greene BE, Duncan DT. Correlates of awareness of and willingness to use pre-exposure prophylaxis (PrEP) in gay, bisexual, and other men who have sex with men who use geosocial-networking smartphone applications in New York City. AIDS Behav. 2016;20:1435–42.Google Scholar
  43. 43.
    Lebouché B, Engler K, Machouf N, Lessard D, Thomas R. Predictors of interest in taking pre-exposure prophylaxis among men who have sex with men who used a rapid HIV-testing site in Montreal (Actuel sur Rue). HIV Med. 2016;17(2):152–8.Google Scholar
  44. 44.
    Galea JT, Kinsler JJ, Salazar X, et al. Acceptability of pre-exposure prophylaxis as an HIV prevention strategy: barriers and facilitators to pre-exposure prophylaxis uptake among at-risk Peruvian populations. Int J STD AIDS. 2011;22(5):256–62.Google Scholar
  45. 45.
    Wei S, Zou Y, Xu Y, et al. Acceptability and influencing factors of pre-exposure prophylaxis among men who have sex with men in Guangxi. Zhonghua Liu Xing Bing Xue Za Zhi. 2011;32(8):786–8.Google Scholar
  46. 46.
    Biello KB, Hosek S, Drucker MT, et al. Preferences for injectable PrEP among young U.S. cisgender men and transgender women and men who have sex with men. Arch Sex Behav. 2017;47(7):2101–7.Google Scholar
  47. 47.
    Meyers K, Rodriguez K, Moeller RW, Gratch I, Markowitz M, Halkitis PN. High interest in a long-acting injectable formulation of pre-exposure prophylaxis for HIV in young men who have sex with men in NYC: a P18 Cohort substudy. PLoS ONE. 2014;9(12):e114700.Google Scholar
  48. 48.
    Golub SA, Gamarel KE, Rendina HJ, Surace A, Lelutiu-Weinberger CL. From efficacy to effectiveness: facilitators and barriers to PrEP acceptability and motivations for adherence among MSM and transgender women in New York City. AIDS Patient Care STDS. 2013;27(4):248–54.Google Scholar
  49. 49.
    Van Minh H, Giang LM, Cashin C, Hinh ND. Health system research in Vietnam: generating policy-relevant knowledge. Glob Public Health. 2015;10(1):S1–4.Google Scholar
  50. 50.
    Beyrer C, Crago A-L, Bekker L-G, Butler J, Shannon K, Kerrigan D, et al. An action agenda for HIV and sex work. Lancet. 2015;385(9964):287–301.Google Scholar
  51. 51.
    Boyce S, Barrington C, Bolaños H, Galindo Arandi C, Paz-Bailey G. Facilitating access to sexual health services for men who have sex with men and male-to-female transgender persons in Guatemala City. Cult Health Sex. 2012;14(3):313–27.Google Scholar
  52. 52.
    Sanchez NF, Sanchez JP, Danoff A. Health care utilization, barriers to care, and hormone usage among male-to-female transgender persons in New York City. Am J Public Health. 2009;99(4):713–9.Google Scholar
  53. 53.
    Young I, Flowers P, Mcdaid LM. Barriers to uptake and use of pre-exposure prophylaxis (PrEP) among communities most affected by HIV in the UK: findings from a qualitative study in Scotland. BMJ Open. 2014;4(11):8.Google Scholar
  54. 54.
    Yi S, Tuot S, Mwai GW, et al. Awareness and willingness to use HIV pre-exposure prophylaxis among men who have sex with men in low- and middle-income countries: a systematic review and meta-analysis. J Int AIDS Soc. 2017;20(1):21580.Google Scholar
  55. 55.
    Doniec K, Dall’Alba R, King L. Austerity threatens universal health coverage in Brazil. Lancet. 2016;388(10047):867–8.Google Scholar
  56. 56.
    Doniec K, Dall’Alba R, King L. Brazil’s health catastrophe in the making. Lancet. 2018;392(10149):731–2.Google Scholar
  57. 57.
    Malta M. Human rights and political crisis in Brazil: public health impacts and challenges. Glob Public Health. 2018;13(11):1577–84.Google Scholar
  58. 58.
    Lopes M, Faiola A. What the first days of Bolsonaro’s presidency say about the direction he will take Brazil—The Washington Post. The Washington Post. 2019. Accessed 20 Jan 2019.
  59. 59.
    Londoño E, Darlington S. Jair Bolsonaro Wins Brazil’s Presidency, in a Shift to the Far Right. The New York Times. 2018. Acessed 3 Jan 2019.
  60. 60.
    Londoño E, Darlington S. Far-Right Candidate Jair Bolsonaro Widens Lead in Brazil’s Presidential Race. The New York Times. 2018. Accessed 3 Jan 2019.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Fabiane Soares
    • 1
    Email author
  • Sarah MacCarthy
    • 2
  • Laio Magno
    • 1
    • 3
  • Luís Augusto Vasconcelos da Silva
    • 1
    • 4
  • Leila Amorim
    • 1
    • 5
  • Amy Nunn
    • 6
  • Catherine E. Oldenburg
    • 7
  • Inês Dourado
    • 1
  • The PopTrans Group
    • 1
  1. 1.Institute of Collective HealthFederal University of Bahia (Universidade Federal da Bahia/Instituto de Saúde Coletiva)SalvadorBrazil
  2. 2.Rand CorpSanta MonicaUSA
  3. 3.Department of Life ScienceState University of Bahia (Universidade do Estado da Bahia/Departamento de Ciências da Vida)SalvadorBrazil
  4. 4.Institute of Humanities, Arts and Sciences Professor Milton SantosFederal University of Bahia (Universidade Federal da Bahia/Instituto de Humanidades, Artes e Ciências Professor Milton Santos)SalvadorBrazil
  5. 5.Institute of Mathematics and StatisticsFederal University of Bahia (Universidade Federal da Bahia/Instituto de Matemática e Estatística)SalvadorBrazil
  6. 6.School of Public HealthBrown UniversityProvidenceUSA
  7. 7.Francis I. Proctor Foundation and Department of OphthalmologyUniversity of CaliforniaSan FranciscoUSA

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