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O23.1 Sexual Risk Trajectories Among MSM in the United States: Implications For PrEP Delivery
  1. H A Pines1,
  2. P M Gorbach1,
  3. R E Weiss2,
  4. S Shoptaw3,
  5. D G Ostrow4,5,
  6. R D Stall6,
  7. M Plankey7
  1. 1Department of Epidemiology, University of California, Los Angeles Fielding School of Public Health, Los Angeles, CA, United States
  2. 2Department of Biostatistics, University of California, Los Angeles Fielding School of Public Health, Los Angeles, CA, United States
  3. 3Department of Family Medicine, Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
  4. 4David Ostrow & Associates, LLC, Chicago, IL, United States
  5. 5The Chicago MACS, Northwestern University, Evanston, IL, United States
  6. 6Department of Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
  7. 7Department of Medicine, Georgetown University Medical Center, Washington, DC, United States


Background CDC guidelines state that men who have sex with men (MSM) at ongoing high risk of HIV infection should be targeted for pre-exposure prophylaxis (PrEP). Longitudinal data can inform the implementation of these guidelines.

Methods HIV-seronegative MSM enrolled in the Multicenter AIDS Cohort Study at 4 U.S. sites completed ACASIs at semi-annual visits. Behaviors since the last visit from 10/1/2003–9/30/2011 were used to assign participants sexual risk behaviour (SRB) scores ranking their risk level at each visit: (0) no insertive and/or receptive anal intercourse (IAI/RAI), (1) no unprotected IAI and/or RAI (UIAI/URAI), (2) only UIAI, (3) URAI with 1 HIV-negative partner, (4) condom-seropositioning, (5) condom-serosorting, and (6) no seroadaptive behaviours. Group-based trajectory modelling was used to examine SRB scores (< 4 vs. ≥ 4) and identify groups with distinct patterns of sexual risk.

Results The sample (N = 430) was 38.4% White, 42.3% Black, 14.9% Hispanic and had a median age of 39.1 years (IQR = 31.3–44.3). Three trajectory groups were identified: no risk (N = 286; 66.5%), low risk (N = 89; 20.7%), and high risk (N = 55; 12.8%). Compared to the no risk group, high risk group membership was negatively associated with older age (adjusted odds ratio [AOR] for 5-year age difference = 0.68, 95% CI: 0.56–0.84) and positively associated with being White (AOR = 2.12, 95% CI: 0.97–4.62), earning an income ≥$20,000 (AOR = 4.96, 95% CI: 2.10–11.71), depression (CESD≥ 16) (AOR = 2.06, 95% CI: 0.98–4.31), and stimulant use (AOR = 2.37, 95% CI: 1.18–4.78) at the index visit. Adjusted group membership probabilities for a 30 year-old, White male reporting an income ≥$20,000, depression, and stimulant use at the index visit were 0.15 (no risk), 0.39 (low risk), and 0.46 (high risk).

Conclusion Findings suggest MSM following high risk trajectories could be identified by the socio-demographic and behavioural factors described above, thus enabling PrEP programmes to target those at ongoing high risk of HIV infection.

  • Longitudinal
  • men who have sex with men
  • sexual risk behavior

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