Socioeconomic marginalization and plasma HIV-1 RNA nondetectability among individuals who use illicit drugs in a Canadian setting
Bibliographic record
Abstract
OBJECTIVE: Given that people who use illicit drugs (PWUD) often engage in prohibited income generation to support their basic needs, we sought to examine the role of these activities in shaping antiretroviral therapy (ART) adherence and plasma HIV RNA-1 viral load suppression among HIV-infected PWUD. DESIGN: Longitudinal analyses among HIV-positive, ART-exposed PWUD in the AIDS Care Cohort to evaluate Exposure to Survival Services prospective cohort study (2005-2013). METHODS: Generalized linear mixed-effects and mediation analyses examined the relationship between prohibited income generation (e.g., sex work, drug dealing, theft, street-based income) and virologic suppression (plasma viral load ≤50 copies/ml plasma) adjusting for adherence and potential confounders. RESULTS: Among 687 HIV-infected PWUD, 391 (56.9%) individuals reported prohibited income generation activity during the study period. In multivariate analyses, prohibited income generation remained independently and negatively associated with virologic suppression (adjusted odds ratio: 0.68, 95% confidence interval: 0.52-0.88) following adjustment for hypothesized confounders, including high-intensity drug use, ART adherence and homelessness. Although partially mediated by ART adherence, the relationship between prohibited income generation and virologic suppression was maintained in mediation analyses (Sobel statistic = -1.95, P = 0.05). CONCLUSION: Involvement in prohibited income generation decreases the likelihood of virologic suppression directly and indirectly through its negative association with ART adherence. These findings suggest that linkages between socioeconomic marginalization, the criminalization of illicit drug use, and insufficient employment opportunities may produce barriers to access and retention in care. Programmatic and policy interventions that decrease socioeconomic vulnerability may therefore reduce HIV-related morbidity, mortality, and onward transmission.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".