Hazardous alcohol use associated with increased sexual risk behaviours among people who inject drugs
Bibliographic record
Abstract
Background—Alcohol is associated with a multitude of severe health consequences. While risk behaviours related to illicit drug use are commonly studied among people who inject drugs (PWID), the role of alcohol use has received substantially less attention in this population. We explored whether drug and sexual risk behaviours as well as experiences of violence were associated with hazardous alcohol use in a cohort of PWID. Methods—Analyses were conducted using observational data from a prospective cohort of community-recruited HIV-negative PWID in Vancouver, Canada. We used the US National Institute on Alcohol Abuse and Alcoholism definition of hazardous alcohol use (i.e., > 14 drinks/week or > 4 drinks on one occasion for men, and > 7 drinks/week or > 3 drinks on one occasion for women.) We used multivariable generalized estimating equations to identify factors associated with hazardous alcohol use. Results—Between 2006 and 2012, 1114 HIV-negative individuals were recruited, and 186 (16.7%) reported hazardous alcohol use in the previous six months at baseline. In multivariable GEE analyses, having multiple sex partners (Adjusted Odds Ratio [AOR] = 1.25), history of sexually transmitted infection (AOR = 1.50), experiencing violence (AOR = 1.36) and incarceration (AOR = 1.29) were each independently associated with hazardous alcohol use. Caucasian ethnicity (AOR = 0.56), ≥ daily heroin injection (AOR = 0.81) and engagement in addiction treatment (AOR = 0.84) were negatively associated with hazardous alcohol use (all p <0.05). Conclusions—A considerable proportion of PWID reported hazardous alcohol use, which was independently associated with reporting sexual, but not drug-related, HIV risk behaviours and experiencing recent violence. Findings suggest a need to integrate regular screening and evidence-based alcohol interventions into treatment efforts for PWID.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".