Journal of Urban Health

, Volume 90, Issue 3, pp 464–481

HIV Sexual Risk Behavior among Black Men Who Meet Other Men on the Internet for Sex

  • Jaclyn M. White
  • Matthew J. Mimiaga
  • Sari L. Reisner
  • Kenneth H. Mayer


Using the Internet to meet sexual partners is associated with increased HIV risk behavior, including substance use, sex with multiple or anonymous partners, and unprotected anal sex (UAS), among diverse samples of MSM, yet little is known about Internet use and HIV risk among Black MSM specifically. In 2008, a sample of 197 Black MSM completed an interviewer-administered assessment and voluntary HIV counseling and testing. One fifth of the sample (20 %) reported meeting a sexual partner via the Internet in the past 12 months. Men who met sexual partners over the Internet had significantly more male sex partners (M = 13.44, SD = 20.01) than men who did not meet partners in this manner (M = 4.11, SD = 4.14, p < 0.001) and reported significantly higher rates of UAS (p < 0.05). Adjusting for sociodemographic and other HIV-related covariates, factors significantly associated with the increased odds of engaging in at least one episode of UAS with a male partner in the past 12 months included: meeting sexual partners on the Internet, identifying as gay, and lower knowledge about HIV transmission. These findings highlight the unique HIV risk behaviors among Black MSM meeting sexual partners via the Internet and warrant tailoring of prevention activities to address the specific behaviors and social influences that may contribute to increased HIV spread among this population.


MSM Internet African American/Black HIV Sexual risk 


  1. 1.
    CDC. HIV and AIDS among gay and bisexual men. 2010;
  2. 2.
    CDC. HIV surveillance in men who have sex with men (MSM). 2011;
  3. 3.
    CDC. HIV in the United States. 2011;
  4. 4.
    CDC. HIV Surveillance in Men Who Have Sex with Men (MSM). Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2010.Google Scholar
  5. 5.
  6. 6.
    Liau A, Millett G, Marks G. Meta-analytic examination of online sex-seeking and sexual risk behavior among men who have sex with men. Sex Transm Dis. 2006;33(9):576-584.PubMedCrossRefGoogle Scholar
  7. 7.
    Benotsch EG, Kalichman S, Cage M. Men who have met sex partners via the Internet: prevalence, predictors, and implications for HIV prevention. Arch Sex Behav. 2002;31(2):177-183.PubMedCrossRefGoogle Scholar
  8. 8.
    Garofalo R, Herrick A, Mustanski BS, Donenberg GR. Tip of the iceberg: young men who have sex with men, the Internet, and HIV risk. Am J Public Health. 2007;97(6):1113-1117.PubMedCrossRefGoogle Scholar
  9. 9.
    Horvath KJ, Rosser BRS, Remafedi G. Sexual risk taking among young Internet-using men who have sex with men. Am J Public Health. 2008;98(6):1059-1067.PubMedCrossRefGoogle Scholar
  10. 10.
    McFarlane M, Bull SS, Rietmeijer CA. The Internet as a newly emerging risk environment for sexually transmitted diseases. JAMA. 2000;284(4):443-446.PubMedCrossRefGoogle Scholar
  11. 11.
    Rosser SB, Oakes J, Horvath K, Konstan J, Danilenko G, Peterson J. HIV sexual risk behavior by men who use the Internet to seek sex with men: results of the Men’s INTernet Sex Study-II (MINTS-II). AIDS Behav. 2009;13(3):488-498.PubMedCrossRefGoogle Scholar
  12. 12.
    Mettey A, Crosby R, DiClemente RJ, Holtgrave DR. Associations between internet sex seeking and STI associated risk behaviours among men who have sex with men. Sex Transm Infect. 2003;79(6):466-468.PubMedCrossRefGoogle Scholar
  13. 13.
    Klausner JD, Wolf W, Fischer-Ponce L, Zolt I, Katz MH. Tracing a syphilis outbreak through cyberspace. JAMA. 2000;284(4):447-449.PubMedCrossRefGoogle Scholar
  14. 14.
    Tashima KT, Alt EN, Harwell JI, Fiebich-Perez DK, Flanigan TP. Internet sex-seeking leads to acute HIV infection: a report of two cases. Int J STD AIDS. 2003;14(4):285-286.PubMedCrossRefGoogle Scholar
  15. 15.
    Klein H. HIV risk practices sought by men who have sex with other men, and who use internet websites to identify potential sexual partners. Sex Health. 2008;5(3):243-250.PubMedCrossRefGoogle Scholar
  16. 16.
    Mayer KH, Mimiaga MJ, VanDerwarker R, Goldhammer H, Bradford JB. Fenway Community Health’s model of integrated community-based LGBT care, education, and research. In: Meyer IH, Northridge ME, eds. The Health of Sexual Minorities. New York: Springer Science & Business Media, LLC; 2007:693-715.CrossRefGoogle Scholar
  17. 17.
    Heckathorn DD. Respondent-driven sampling: a new approach to the study of hidden populations. Soc Probl. 1997;44:174-199.CrossRefGoogle Scholar
  18. 18.
    Mimiaga M, Reisner S, Tetu A, et al. Psychosocial and Behavioral Predictors of Partner Notification After HIV and STI Exposure and Infection Among MSM. AIDS Behav. 2009;13(4):738-745.Google Scholar
  19. 19.
    Mimiaga MJ, Goldhammer H, Belanoff C, Tetu AM, Mayer KH. Men who have sex with men: perceptions about sexual risk, HIV and sexually transmitted disease testing, and provider communication. Sex Transm Dis. 2007;34:113-119.PubMedCrossRefGoogle Scholar
  20. 20.
    Heckathorn DD. Respondent-driven sampling II: deriving valid population estimates from chain-referral samples of hidden populations. Soc Probl. 2002;49:11-34.CrossRefGoogle Scholar
  21. 21.
    Sanchez T, Finlayson T, Drake A, et al. Human immunodeficiency virus (HIV) risk, prevention, and testing behaviors—United States, National HIV Behavioral Surveillance System: men who have sex with men, November 2003–April 2005, vol. 55. Atlanta, GA, ETATS-UNIS: US Department of Health, Education, and Welfare, Public Health Service, Center for Disease Control; 2006.Google Scholar
  22. 22.
    Catania JA, Coates TJ, Kegeles S. A test of the AIDS Risk Reduction Model: psychosocial correlates of condom use in the AMEN Cohort Survey. Health Psychol. 1994;13(6):548-555.PubMedCrossRefGoogle Scholar
  23. 23.
    Carey MP, Schroder KE. Development and psychometric evaluation of the brief HIV Knowledge Questionnaire. AIDS Educ Prev. 2002;14(2):172-182.PubMedCrossRefGoogle Scholar
  24. 24.
    Ewing JA. Detecting alcoholism. The CAGE questionnaire. JAMA. 1984;252:1905-1907.PubMedCrossRefGoogle Scholar
  25. 25.
    Knowlton R, McCusker J, Stoddard A, Zapka J, Mayer KH. The use of the CAGE questionnaire in a cohort of homosexually active men. J Stud Alcohol. 1994;55:692-694.PubMedGoogle Scholar
  26. 26.
    Mayfield D, McLeod G, Hall P. The CAGE questionnaire: validation of a new alcoholism screening instrument. Am J Psychiatry. 1974;131:1121-1123.PubMedGoogle Scholar
  27. 27.
    Buchsbaum DG, Buchanan RG, Centor RM, Schnoll SH, Lawton MJ. Screening for alcohol abuse using CAGE scores and likelihood ratios. Ann Intern Med. 1991;115:774-777.PubMedCrossRefGoogle Scholar
  28. 28.
    SAS® version 9.2 [computer program]. Cary, NC: SAS Institute Inc.; 2003.Google Scholar
  29. 29.
    Rhodes SD, Hergenrather KC, Yee LJ, Ramsey B. Comparing MSM in the Southeastern United States who participated in an HIV prevention chat room-based outreach intervention and those who did not: how different are the baseline HIV-risk profiles? Health Educ Res. 2008;23(1):180-190.PubMedCrossRefGoogle Scholar
  30. 30.
    Heckman TG, Kelly JA, Bogart LM, Kalichman SC, Rompa DJ. HIV risk differences between African-American and white men who have sex with men: National Medical Association; 1999.Google Scholar
  31. 31.
    Peterson JL, Coates TJ, Catania JA, Middleton L, Hilliard B, Hearst N. High-risk sexual behavior and condom use among gay and bisexual African-American men. Am J Public Health. 1992;82(11):1490-1494.PubMedCrossRefGoogle Scholar
  32. 32.
    Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol. 1981;17(6):368-376.PubMedCrossRefGoogle Scholar
  33. 33.
    Felsenstein J. Maximum likelihood and minimum-steps methods for estimating evolutionary trees from data on discrete characters. Syst Zool. 1973;22(3):240-249.CrossRefGoogle Scholar
  34. 34.
    Anderton J, Valdiserri R. Combating syphilis and HIV among users of Internet chatrooms. J Health Commun. 2005;10:665-671.PubMedCrossRefGoogle Scholar
  35. 35.
    Kim AA, Kent C, McFarland W, Klausner JD. Cruising on the Internet highway. JAIDS. 2001;28(1):89-93.PubMedGoogle Scholar
  36. 36.
    McKirnan D, Houston E, Tolou-Shams M. Is the Web the culprit? Cognitive escape and Internet sexual risk among gay and bisexual men. AIDS Behav. 2007;11(1):151-160.PubMedCrossRefGoogle Scholar
  37. 37.
    Crosby R, Holtgrave DR, Stall R, Peterson JL, Shouse L. Differences in HIV risk behaviors among Black and White men who have sex with men. Sex Transm Dis. 2007;34(10):744–748.Google Scholar
  38. 38.
    Bolding G, Davis M, Hart G, Sherr L, Elford J. Gay men who look for sex on the Internet: is there more HIV/STI risk with online partners? AIDS. 2005;19(9):961-968.PubMedCrossRefGoogle Scholar
  39. 39.
    Rietmeijer CA, Bull SS, McFarlane M, Patnaik JL, Douglas JM. Risks and benefits of the Internet for populations at risk for sexually transmitted infections (STIs): results of an STI clinic survey. Sex Transm Dis. 2003;30(1):15-19.PubMedCrossRefGoogle Scholar
  40. 40.
    Ostrow DG, Whitaker RED, Frasier K, et al. Racial differences in social support and mental health in men with HIV infection: a pilot study. AIDS Care. 1991;3(1):55-62.PubMedCrossRefGoogle Scholar
  41. 41.
    Magnus M, Kuo I, Phillips G, et al. Elevated HIV prevalence despite lower rates of sexual risk behaviors among Black men in the District of Columbia who have sex with men. AIDS Patient Care STDS. 2010;24(10):615-622.PubMedCrossRefGoogle Scholar
  42. 42.
    Millett G, Malebranche D, Mason B, Spikes P. Focusing “down low”: bisexual Black men, HIV risk and heterosexual transmission: National Medical Association; 2005.Google Scholar
  43. 43.
    Miller M, Serner M, Wagner M. Sexual diversity among Black men who have sex with men in an inner-city community. J Urban Health. 2005;82:i26-i34.PubMedCrossRefGoogle Scholar
  44. 44.
    Wheeler D. Exploring HIV, prevention needs for nongay-identified Black and African American men who have sex with men: a qualitative exploration, vol. 33. Hagerstown: Lippincott Williams; 2006.Google Scholar
  45. 45.
    Raymond H, McFarland W. Racial mixing and HIV risk among men who have sex with men. AIDS Behav. 2009;13(4):630-637.PubMedCrossRefGoogle Scholar
  46. 46.
    Paul JP, Ayala G, Choi K-H. Internet sex ads for MSM and partner selection criteria: the potency of race/ethnicity online. J Sex Res. 2010;47(6):528-538.PubMedCrossRefGoogle Scholar
  47. 47.
    Peterson JL, Jones KT. HIV prevention for Black men who have sex with men in the United States. Am J Public Health. 2009;99(6):976-980.PubMedCrossRefGoogle Scholar
  48. 48.
    Stokes J, Peterson J. Homophobia, self-esteem, and risk for HIV among African American men who have sex with men. AIDS Educ Prev. 1998;10:278-292.PubMedGoogle Scholar
  49. 49.
    Malebranche DJ. Black men who have sex with men and the HIV epidemic: next steps for public health. Am J Public Health. 2003;93(6):862-865.PubMedCrossRefGoogle Scholar
  50. 50.
  51. 51.
    Berg R. Barebacking among MSM Internet users. AIDS Behav. 2008;12(5):822-833.PubMedCrossRefGoogle Scholar
  52. 52.
    The Boston Foundation. US Bureau of Labor Statistics: in-home access to computers and the Internet. 2001; Accessed April 19, 2011.
  53. 53.
    Schwartz S, Meyer IH. Mental health disparities research: the impact of within and between group analyses on tests of social stress hypotheses. Soc Sci Med. 2010;70(8):1111-1118.PubMedCrossRefGoogle Scholar

Copyright information

© The New York Academy of Medicine 2012

Authors and Affiliations

  • Jaclyn M. White
    • 1
  • Matthew J. Mimiaga
    • 1
    • 2
    • 3
  • Sari L. Reisner
    • 1
    • 4
  • Kenneth H. Mayer
    • 1
    • 5
  1. 1.The Fenway Institute, Fenway HealthBostonUSA
  2. 2.Department of PsychiatryHarvard Medical School/Massachusetts General HospitalBostonUSA
  3. 3.Department of EpidemiologyHarvard School of Public HealthBostonUSA
  4. 4.Department of Society, Human Development and HealthHarvard School of Public HealthBostonUSA
  5. 5.Harvard Medical School/Beth Israel Deaconess Medical CenterBostonUSA

Personalised recommendations