1. Factors associated with concurrent sexual partnerships among men who have sex with men (MSM)
Kyle T. Bernstein, Katherine Ahrens, Susan S. Philip, Jeffrey D. Klausner
STD Prevention and Control Services San Francisco Department of Public Health

2. Concurrency Having two or more sex partners that overlap in time
Mathematical models suggest concurrency may be an important factors in creating and maintaining epidemic STD transmission within sexual networks

3. Concurrency as an individual risk factor
Nearly all empiric studies in heterosexual populations
Some report increased risk for STDs, while others show no increased risk
Few studies conducted among MSM

4. Objectives To examine the relationship between concurrency and STDs
Is concurrency associated with an STD diagnosis?
Are other demographic/behavioral risk factors associated with concurrency?

5. Methods
Between June - August, 2007, MSM seeking services at SF City Clinic were asked to complete a survey:
How many men did you have anal sex with in the last 6 months?
If more than one:
Have you had anal sex with the same person more than once in the past 6 months?
If ‘Yes,’
Have you had anal sex with anyone else between those fucks (for example, did you have sex with “Joe” and then “Sam” and then “Joe” again)?

6. Methods Survey data linked to clinic records Demographics Condom Use
Number of Sex Partners
HIV Serosorting
Any unprotected sex partners by their HIV status (3 mo)
Patient HIV status
HIV Status
Drug Use
STD Diagnosis (GC, CT, Syphilis)
At visit
6 months prior to visit
Obtained from clinic record, not self-report

7. Statistical Analysis Univariate Multivariate χ2 and Wilcoxon Rank Sum
Logistic regression
Adjusted Odds Ratios, 95% Confidence Limits

8. Participants Prevalence of concurrency = 183/468=39.1%
468 MSM completed survey
<2 sex partners (n=156)
2+ sex partners (N=312)
Concurrent Partnerships (n=183)
No Concurrent Partnerships (n=129)
Prevalence of concurrency = 183/468=39.1%

9. Univariate Results CP n=183 No CP n=129 P-value Median Age, years 3534
0.791
White Race
67.8%
51.9%
0.034
Gay
89.1%
81.4%
0.055
Median # Male Sex Part*
4.5
3.0
0.014
HIV-infected
31.2%
18.6%
0.013
Serosorting
39.3%
24.8%
0.007
* In the past 3 months

10. Univariate Results P-value CP n=183 No CP n=129 Drug Use (3 months)
Alcohol
12.0%
2.3%
0.002
Meth
30.1%
35.7%
0.297
Popper
6.0%
1.6%
0.052
STDs (current or past 6 months) CT
14.8%
11.6%
0.426 GC
14.2%
16.6%
0.614
PS syphilis
3.8%
0.237

11. Multivariate Results OR 95% CI White Race (vs. non-white) 1.80
Alcohol Use
5.35
Number of Male Sex Partners
1.36
Serosorting
2.38
Current or prior STDs and HIV status were not associated with concurrency

12. Mantra: Concurrency is bad….
but for whom
Network
Individual

13. Limitations One measure of concurrency Cross-sectional data
STD clinic population in SF
May be of limited generalizibility

14. Summary
Among a clinic-based population of MSM, concurrency was associated with being White, using alcohol, practicing serosorting, and having a larger number of sex partners
Concurrency was not associated with GC, CT, syphilis, or HIV infection

15. Conclusions Concurrency may be important at the network level
Increases “speed” at which an STD moves through a network
Concurrency may have less of an impact on individual risk

16. Acknowledgments SF DPH CA DPH Robert Kohn, Ken Katz
Deborah Williams, Tochia Brewster, Serlina Cheung, Wendy Ho, Amalia Jarquin
CA DPH
Dan Wohlfeiler, Julia Marcus

17. Additional Slides

18. What is the role of concurrency in individual STD risk?
Concurrent Partnerships
STD
More Sex Partners