AIDS and Behavior

, Volume 17, Issue 7, pp 2376–2386 | Cite as

Partnership Concurrency and Coital Frequency

  • Lauren Gaydosh
  • Georges Reniers
  • Stéphane Helleringer
Original Paper

Abstract

National HIV prevalence estimates across sub-Saharan Africa range from less than 1 percent to over 25 percent. Recent research proposes several explanations for the observed variation, including prevalence of male circumcision, levels of condom use, presence of other sexually transmitted infections, and practice of multiple concurrent partnerships. However, the importance of partnership concurrency for HIV transmission may depend on how it affects coital frequency with each partner. The coital dilution hypothesis suggests that coital frequency within a partnership declines with the addition of concurrent partners. Using sexual behavior data from rural Malawi and urban Kenya, we investigate the relationship between partnership concurrency and coital frequency, and find partial support for the coital dilution hypothesis. We conclude the paper with a discussion of our findings in light of the current literature on concurrency.

Keywords

Concurrency Coital frequency HIV/AIDS Malawi Kenya 

Supplementary material

10461_2013_525_MOESM1_ESM.docx (22 kb)
Supplementary material 1 (DOCX 22 kb)

References

  1. 1.
    Bongaarts J, Buettner T, Heilig G, Pelletier F. Has the HIV epidemic peaked? Popul Dev Rev. 2008;34(2):199–224.CrossRefGoogle Scholar
  2. 2.
    Cameron DW, D’Costa LJ, Maitha GM, Cheang M, Piot P, Simonsen JN, Ronald AR, Gakinya MN, Ndinya-Achola JO, Brunham RC. Female to male transmission of human immunodeficiency virus type 1: risk factors for seroconversion in men. Lancet. 1989;334(8660):403–7.CrossRefGoogle Scholar
  3. 3.
    Bongaarts J, Reining P, Way P, Conant F. The relationship between male circumcision and HIV infection in African populations. AIDS. 1989;3(6):373–7.PubMedCrossRefGoogle Scholar
  4. 4.
    Moses S, Bradley JE, Jagelkerke NJD, Ronald AR, Ndinya-Achla JO, Plummer FA. Geographical patterns of male circumcision practices in Africa: association with HIV seroprevalence. Int J Epidemiol. 1990;19:693–7.PubMedCrossRefGoogle Scholar
  5. 5.
    Chin J. The AIDS Pandemic: the collision of epidemiology with political correctness. Oxford: Radcliffe Publishing; 2007.Google Scholar
  6. 6.
    United Nations. Levels and trends of contraceptive use as Assessed in 2002. Population Division, Department of Economic and Social Affairs. New York: United Nations (ST/ESA/SER.A/239); 2006.Google Scholar
  7. 7.
    Morris M, Kretzschmar M. Concurrent partnerships and the spread of HIV. AIDS. 1997;11(5):641–8.PubMedCrossRefGoogle Scholar
  8. 8.
    Halperin DT, Epstein H. Concurrent sexual partnerships help to explain Africa’s high HIV prevalence: implications for prevention. Lancet. 2004;364(9428):4–6.PubMedCrossRefGoogle Scholar
  9. 9.
    Mah TL, Halperin DT. Concurrent sexual partnerships and the HIV epidemics in Africa: evidence to move forward. AIDS Behav. 2010;14(1):11–6.PubMedCrossRefGoogle Scholar
  10. 10.
    Moody J. The importance of relationship timing for diffusion. Soc Forces. 2002;81(1):25–56.CrossRefGoogle Scholar
  11. 11.
    Boily MC, Alary M, Baggaley RF. Neglected issues and hypotheses regarding the impact of sexual concurrency on HIV and sexually transmitted infections. AIDS Behav. 2012;16(2):304–11.Google Scholar
  12. 12.
    Wawer M, Gray RH, Sewankambo NK, Serwadda D, Li X, Laeyendecker O, Kiwanuka N, Kigozi G, Kiddugavu M, Lutalo T, Nalugoda F, Wabwire-Mangen F, Meehan MP, Quinn TC. Rates of HIV-1 transmission per coital act, by stage of HIV-1 infection, in Rakai, Uganda. J Infect Dis. 2005;191(9):1403–9.PubMedCrossRefGoogle Scholar
  13. 13.
    Eaton J, Hallett T, Garnett GP. Concurrent sexual partnerships and primary HIV infection: a critical interaction. AIDS Behav. 2010;15(4):687–92.CrossRefGoogle Scholar
  14. 14.
    Goodreau SM, Cassels S, Kasprzyk D, Montano DE, Greek A, Morris M. Concurrent partnerships, acute infection, and HIV epidemic dynamics among young adults in Zimbabwe. AIDS Behav. 2012;16(2):312–22.Google Scholar
  15. 15.
    Reniers G, Watkins S. Polygyny and the spread of HIV in sub-Saharan Africa: a case of benign concurrency. AIDS. 2010;24(2):299–307.PubMedCrossRefGoogle Scholar
  16. 16.
    Sawers L, Isaac AG, Stillwaggon E. HIV and concurrent sexual partnerships: modeling the role of coital dilution. J Int AIDS Soc. 2011;14:44.PubMedCrossRefGoogle Scholar
  17. 17.
    Reniers G, Tfaily R. Polygyny, partnership concurrency and the spread of HIV in sub-Saharan Africa. Demography. 2012;49(3):1075–101. doi:10.1007/s13524-012-0114-z.PubMedCrossRefGoogle Scholar
  18. 18.
    Xu H, Luke N, Zulu E. Concurrent sexual partnerships among youth in urban Kenya: prevalence and partnership effects. Pop Stud. 2010;64(3):247–61.CrossRefGoogle Scholar
  19. 19.
    Kaler A. My girlfriends could fill a Yanu–Yanu bus: Rural Malawian men’s claims about their own serostatus. Demogr Res. 2003; Special Collection 1(Article 11):349–72.Google Scholar
  20. 20.
    Nnko S, Boerma JT, Urassa M, Mwaluko G, Zaba B. Secretive females or swaggering males? an assessment of the quality of sexual partnership reporting in rural Tanzania. Soc Sci Med. 2004;59(2):299–310.PubMedCrossRefGoogle Scholar
  21. 21.
    Curtis SL, Sutherland EG. Measuring sexual behavior in the era of HIV/AIDS: the experience of Demographic and Health Surveys and similar enquiries. Sex Transm Infect. 2004; 80(Supplement 2):ii1–ii7.Google Scholar
  22. 22.
    Helleringer S, Kohler H-P, Kalilani-Phiri L, Mkandawire J, Armbruster B. The reliability of sexual partnership histories: implications for the measurement of partnership concurrency during surveys. AIDS. 2011;25(4):503–11.PubMedCrossRefGoogle Scholar
  23. 23.
    Cleland J, Boerma JT, Caraël M, Weir SS. Monitoring sexual behavior in general populations: a synthesis of lessons of the past decade. Sex Transm Infect. 2004; 80(Supplement 2): ii1–ii7.Google Scholar
  24. 24.
    Clark S, Kabiru C, Zulu E. Do men and women report their sexual partnerships differently? evidence from Kisumu, Kenya. Int Perspect Sex Reprod Health. 2011;37(4):181–90.PubMedCrossRefGoogle Scholar
  25. 25.
    Luke N, Clark S, Zulu E. The relationship history calendar: improving the scope and quality of data on youth sexual behavior. Demography. 2011;48:1151–76.PubMedCrossRefGoogle Scholar
  26. 26.
    Helleringer S, Kohler H-P. Sexual network structure and the spread of HIV in Africa: evidence from Likoma Island, Malawi. AIDS. 2007;21(17):2323–32.PubMedCrossRefGoogle Scholar
  27. 27.
    Helleringer S, Kohler H-P, Chimbiri A, Chatonda P, Mkandawire J. The Likoma network study: context, data collection and initial results. Demogr Res. 2009;21:427–68.PubMedCrossRefGoogle Scholar
  28. 28.
    Helleringer S, Kohler H-P, Kalilani-Phiri L. The association of HIV serodiscordance and partnership concurrency in Likoma Island, Malawi. AIDS. 2009;23(10):1285–7.PubMedCrossRefGoogle Scholar
  29. 29.
    UNAIDS. 2010 Report on the Global AIDS Epidemic. Geneva, UNAIDS; 2010.Google Scholar
  30. 30.
    Clark AL, Wallin P. The accuracy of husbands’ and wives’ reports of the frequency of marital coitus. Pop Stud. 1964;18(2):165–73.Google Scholar
  31. 31.
    Glynn JR, Dube A, Kayuni N, Floyd S, Molesworth A, Parrott F, French N, Crampin AC. Measuring concurrency: an empirical study of different methods in a large population-based survey and evaluation of the UNAIDS guidelines. AIDS. 2012;26(8):977–85.PubMedCrossRefGoogle Scholar
  32. 32.
    Eaton J. HIV: consensus indicators are needed for concurrency. Lancet. 2010;375:621–2.CrossRefGoogle Scholar
  33. 33.
    Morris M, Epstein H, Wawer M. Timing is everything: international variations in historical sexual partnership concurrency and HIV prevalence. PLoS One. 2010;5(11):e14092.PubMedCrossRefGoogle Scholar
  34. 34.
    Sawers L. Measuring and modeling concurrency. J Int AIDS Soc. 2013;16(1):17431.PubMedGoogle Scholar
  35. 35.
    Eaton J, McGrath N, Newell M-L. Unpacking the recommended indicator for concurrent sexual partnerships. AIDS. 2012;26(8):1037–9.PubMedCrossRefGoogle Scholar
  36. 36.
    Epstein H. The invisible cure. New York: Farrar, Straus and Giroux; 2007.Google Scholar
  37. 37.
    Hudson CP. Concurrent partnerships could cause AIDS epidemics. Int J STD AIDS. 1993;4(5):249–53.PubMedGoogle Scholar
  38. 38.
    Watts CH, May RM. The influence of concurrent partnerships on the dynamics of HIV/AIDS. Math Biosci. 1992;108(1):89–104.PubMedCrossRefGoogle Scholar
  39. 39.
    Lurie MN, Rosenthal S. Concurrent partnerships as the driver of the HIV epidemic in sub-Saharan Africa? The evidence is limited. AIDS Behav. 2010;14(1):17–24.PubMedCrossRefGoogle Scholar
  40. 40.
    Sawers L, Stillwaggon E. Concurrent sexual partnerships do not explain the HIV epidemics in Africa: a systematic review of the evidence. J Int AIDS Soc. 2010;13(1):34.PubMedCrossRefGoogle Scholar
  41. 41.
    Kretzschmar M, Caraël M. Is concurrency driving HIV transmission in sub-Saharan African sexual networks? the significance of sexual partnership typology. AIDS Behav. 2012;. doi:10.1007/s10461-012-0254-6.PubMedGoogle Scholar
  42. 42.
    Blower SM, Boe C. Sex acts, sex partners, and sex budgets: implications for risk factor analysis and estimation of HIV transmission probabilities. J AIDS. 1993;6(12):1347–52.Google Scholar
  43. 43.
    Epstein H, Swidler A, Gray R, Reniers G, Parker W, Parkhurst J, Short R, Halperin D. Measuring concurrent partnerships. Lancet. 2010; 375(9729):1869; author reply 1870.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Lauren Gaydosh
    • 1
  • Georges Reniers
    • 2
  • Stéphane Helleringer
    • 3
  1. 1.Office of Population Research and Department of SociologyPrinceton UniversityPrincetonUSA
  2. 2.Department of Population HealthLondon School of Hygiene and Tropical MedicineLondonUK
  3. 3.Heilbrunn Department of Population and Family HealthMailman School of Public Health, Columbia UniversityNew YorkUSA

Personalised recommendations