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Record W4405501208 · doi:10.1016/j.lana.2024.100961

Opioid toxicity deaths in Indigenous people who experienced incarceration in Ontario, Canada 2015–2020: a whole population retrospective cohort study

2024· article· en· W4405501208 on OpenAlexafffundabout
Tenzin Butsang, Natalie Owl, Amanda Butler, Hollie Sabourin, Ruth Croxford, Lacey Gislason, Fiona G. Kouyoumdjian

Bibliographic record

VenueThe Lancet Regional Health - Americas · 2024
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsImpactNative Women's Association of CanadaSimon Fraser UniversityMcMaster UniversityPublic Health OntarioUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsIndigenousMedicinePopulationDemographyRetrospective cohort studyMortality rateCohortOpioidEnvironmental healthInternal medicine

Abstract

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Background: While Indigenous people are overrepresented in Canada's prisons and in the toxic drug supply crisis, we lack data on the harms related to opioids for Indigenous people with experiences of incarceration. We aimed to examine opioid toxicity deaths in Indigenous peoples who experienced incarceration and to compare opioid toxicity mortality rates with rates for people with no incarceration. Methods: This retrospective cohort study linked correctional data for all people who were incarcerated in provincial correctional facilities and coronial data for all people who died from opioid toxicity in Ontario, Canada between 2015 and 2020. We calculated opioid mortality rates for Indigenous people who experienced incarceration and for people who did not experience incarceration using publicly available population data and calculated age-standardized mortality rates for Indigenous and non-Indigenous people who experienced incarceration compared with people who did not experience incarceration. Findings: Of 14,885 Indigenous people who experienced incarceration, 2% (N = 242) died from opioid toxicity in custody or post-release, representing 2.9% of all opioid toxicity deaths in Ontario during this period. The crude opioid toxicity mortality rate per 100 person-years was 0.53 for Indigenous females and 0.36 for Indigenous males who experienced incarceration, compared with 0.0060 for females and 0.0132 for males who did not experience incarceration. Rates of opioid toxicity death were highest in the month post-release for Indigenous people who experienced incarceration, at 1.13 per 100 person-years. Standardized for age and compared with people with no incarceration, the mortality ratio was 81.0 (95% CI 62.1-100.0) for Indigenous females who experienced incarceration and 23.6 (95% CI 20.1-27.1) for Indigenous males who experienced incarceration. The SMRs for Indigenous and non-Indigenous females who experienced incarceration were not significantly different, at 81.0 compared with 76.4, and were significantly different for Indigenous and non-Indigenous males who experienced incarceration, at 23.6 compared with 28.5. Interpretation: This whole-population study identified a substantial and inequitable burden of opioid toxicity death for Indigenous people who experienced incarceration, similar to the burden for non-Indigenous people who experienced incarceration. The large burden is particularly concerning in the context of the overrepresentation of Indigenous people in correctional facilities. Focus is warranted to prevent substance use harms for Indigenous people, including through community- and custody-based interventions to support health. Funding: Canadian Institutes of Health Research through the Canadian Research Initiative in Substance Misuse (SMN-139150 and REN-181677).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.024
GPT teacher head0.336
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

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