Table 2.
Univariate and Multivariable Binary Logistic Regression Models for Predicting Initiation of Pre-exposure Prophylaxis (PrEP) Among Participants Offered PrEP Through the Total Test (n = 920, of Whom 172 Initiated PrEP)
| Univariate Model | Multivariable Modela | |||||
|---|---|---|---|---|---|---|
| Model | OR | (95% CI) | P Value | aOR | (95% CI) | P Value |
| Recent Grindr use | 2.006 | (1.433–2.808) | < .001 | 1.611 | (1.129–2.299) | .009 |
| Adjusted SDET score (per point) | 1.250 | (1.174–1.331) | < .001 | 1.196 | (1.116–1.282) | < .001 |
| Age (per year) | 0.960 | (.944–.976) | < .001 | 0.964 | (.948–.981) | < .001 |
| Substance use last 3 mo | 1.634 | (1.090–2.450) | .017 | NS | … | |
| Diagnosis of chlamydia or gonorrhea infection at testing encounter | 3.751 | (2.139–6.576) | < .001 | 1.996 | (1.076–3.701) | .028 |
| Hispanic ethnicity | 1.381 | (.983–1.940) | .063 | NS | … | |
Abbreviations: aOR, adjusted odds ratio; CI, confidence interval; NS, not significant; OR, odds ratio; SDET, San Diego Early Test.
aχ 2 = 6.077, P = .639, Hosmer-Lemeshow; forward Wald binary logistic regression.