1. Variation in concurrent sexual partnerships and sexually transmitted diseases among African men in Cape Town, South Africa Brendan Maughan-Brown Southern Africa Labour and Development Research Unit (SALDRU) University of Cape Town

2. Introduction  Inconsistent findings wrt concurrency and STDs  1 Factor: dichotomous measures (yes/no) of concurrency typically used  Different forms of concurrency have different degrees of associated risk for disease transmission  Conflate high & low risk behaviours  This paper examines: Variation in individual concurrency Variation in partner concurrency Relationship between partner concurrency and STD status

3. Data  Cape Area Panel Study Longitudinal study in Cape Town Young adults: 14-22 (2002), 20-30 (2009) African male sample: 930 (2002), 582 (2009) Estimation sample: 439 (data for all variables)  Wave 3 (2005) and 5 (2009) Wave 3 & 5: sexual partner history tables Wave 5: self-administered questions about concurrency

4. Data – concurrency measures Sexual partner history tables (2005 & 2009)  Individual concurrency “Did you have any other sexual partners during the time that you and [partner] were having a sexual relationship?”  Partner concurrency As far as you know, did [partner] have any other sexual partners during the time that you and he/she were having a sexual relationship?

5. Data – partnership variables  Partnership type Main partner vs Non-main partner Main partner: relationship with concurrency, > 5 months and coital frequency >10  Condom use Consistent vs inconsistent Consistent: relationship with concurrency, condoms always used with partner

6. Data – concurrency measures Self-administered questions (2009)  Individual concurrency Have you ever been in a sexual relationship with someone and had sex with somebody else? This includes main partners, side-partners, roll-ons and one night stands. What is the largest number of sexual partners you have had at the same time for a week or more? What is the longest period of time during which you have had more than one sexual partner?

7. Research Strategy  Sample characteristics  Reported concurrency  Relationship between partner concurrency and STD Probit marginal effects regression STD status: Self-report  “Have you ever had a sexually transmitted disease (STD) that is not HIV?” Individual concurrency added as control. Proxy for unobserved factors.

8. Results - Sample

9. Results – Individual concurrency (partner tables)

10. Results – Individual concurrency (Self-administered questions)

11. Results – Partner concurrency (partner tables)

12. ResultsResults: Concurrency & STDs (Probit mfx)

13. Summary of Core Findings  Majority reported individual concurrency, almost half reported perceived partner concurrency  Significant variation between concurrent partnerships wrt partnership type, condom-use, number of partners concurrently and partnership duration  These variations associated with different STD risk

14. Limitations  Self-reported STD data  Timing of STDs & concurrency unknown  Perceptions of partner concurrency will involve measurement error  Characteristics of partnerships of the second/third concurrent partner unmeasured: risk differentials unknown  Specific population: unknown whether results apply more broadly

15. Implications  Need to expand the concept of risk from a focus on the individual to one on partnerships in order to better understand sexual behaviour and disease transmission  Future research on concurrency should include more nuanced analysis using measures of partnership type, condom use, number of partners involved in concurrent partnerships and duration of concurrent partnerships

16. Thank you brendan.maughanbrown@gmail.com Thanks to Mark Lurie, Timothy Mah, Nicola Branson, Atheendar Venkataramani for comments. The Cape Area Panel Study is a joint project of the universities of Cape Town and Michigan. Funding for this study was provided by the US National Institute for Child Health and Human Development, the Andrew W. Mellon Foundation, the National Institute on Aging, the Health Economics & HIV/AIDS Research Division (HEARD) at the University of KwaZulu-Natal and the European Union. Further information is available from www.caps.uct.ac.za.