Risk factors for elevated HIV incidence rates among female injection drug users in Vancouver.
Bibliographic record
Abstract
BACKGROUND: In 1997, we found a higher prevalence of HIV among female than among male injection drug users in Vancouver. Factors associated with HIV incidence among women in this setting were unknown. In the present study, we sought to compare HIV incidence rates among male and female injection drug users in Vancouver and to compare factors associated with HIV seroconversion. METHODS: This analysis was based on 939 participants recruited between May 1996 and December 2000 who were seronegative at enrolment with at least one follow-up visit completed, and who were studied prospectively until March 2001. Incidence rates were calculated using the Kaplan-Meier method. The Cox proportional hazards regression model was used to identify independent predictors of time to HIV seroconversion. RESULTS: As of March 2001, seroconversion had occurred in 110 of 939 participants (64 men, 46 women), yielding a cumulative incidence rate of HIV at 48 months of 13.4% (95% confidence interval [CI] 11.0%-15.8%). Incidence was higher among women than among men (16.6% v. 11.7%, p = 0.074). Multivariate analysis of the female participants' practices revealed injecting cocaine once or more per day compared with injecting less than once per day (adjusted relative risk [RR] 2.6, 95% CI 1.4-4.8), requiring help injecting compared with not requiring such assistance (adjusted RR 2.1, 95% CI 1.1-3.8), having unsafe sex with a regular partner compared with not having unsafe sex with a regular partner (adjusted RR 2.9, 95% CI 0.9-9.5) and having an HIV-positive sex partner compared with not having an HIV-positive sex partner (adjusted RR 2.7, 95% CI 1.0-7.7) to be independent predictors of time to HIV seroconversion. Among male participants, injecting cocaine once or more per day compared with injecting less than once per day (adjusted RR 3.3, 95% CI 1.9-5.6), self-reporting identification as an Aboriginal compared with not self-reporting identification as an Aboriginal (adjusted RR 2.5, 95% CI 1.4-4.2) and borrowing needles compared with not borrowing needles (adjusted RR 2.0, 95% CI 1.1-3.4) were independent predictors of HIV infection. INTERPRETATION: HIV incidence rates among female injection drug users in Vancouver are about 40% higher than those of male injection drug users. Different risk factors for seroconversion for women as opposed to men suggest that sex-specific prevention initiatives are urgently required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".