The Cedar Project: mortality among young Indigenous people who use drugs in British Columbia
Bibliographic record
Abstract
BACKGROUND: Young Indigenous people, particularly those involved in the child welfare system, those entrenched in substance use and those living with HIV or hepatitis C, are dying prematurely. We report mortality rates among young Indigenous people who use drugs in British Columbia and explore predictors of mortality over time. METHODS: We analyzed data collected every 6 months between 2003 and 2014 by the Cedar Project, a prospective cohort study involving young Indigenous people who use illicit drugs in Vancouver and Prince George, BC. We calculated age-standardized mortality ratios using Indigenous and Canadian reference populations. We identified predictors of mortality using time-dependent Cox proportional hazard regression. RESULTS: Among 610 participants, 40 died between 2003 and 2014, yielding a mortality rate of 670 per 100 000 person-years. Young Indigenous people who used drugs were 12.9 (95% confidence interval [CI] 9.2–17.5) times more likely to die than all Canadians the same age and were 7.8 (95% CI 5.6–10.6) times more likely to die than Indigenous people with Status in BC. Young women and those using drugs by injection were most affected. The leading causes of death were overdose (n = 15 [38%]), illness (n = 11 [28%]) and suicide (n = 5 [12%]). Predictors of mortality included having hepatitis C at baseline (adjusted hazard ratio [HR] 2.76, 95% CI 1.47–5.16), previous attempted suicide (adjusted HR 1.88, 95% CI 1.01–3.50) and recent overdose (adjusted HR 2.85, 95% CI 1.00–8.09). INTERPRETATION: Young Indigenous people using drugs in BC are dying at an alarming rate, particularly young women and those using injection drugs. These deaths likely reflect complex intersections of historical and present-day injustices, substance use and barriers to care.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".