Investigating the association between income inequality in youth and deaths of despair in Canada: a population-based cohort study from 2006 to 2019
Bibliographic record
Abstract
BACKGROUND: Deaths due to suicide, drug overdose and alcohol-related liver disease, collectively known as 'deaths of despair', have been markedly increasing since the early 2000s and are especially prominent in young Canadians. Income inequality has been linked to this rise in deaths of despair; however, this association has not yet been examined in a Canadian context, nor at the individual level or in youth. The study objective was to examine the association between income inequality in youth and deaths of despair among youth over time. METHODS: We conducted a population-based longitudinal study of Canadians aged 20 years or younger using data from the Canadian Census Health and Environment Cohorts. Baseline data from the 2006 Canadian Census were linked to the Canadian Vital Statistics Database up to 2019. We employed multilevel survival analysis models to quantify the association between income inequality in youth and time-to deaths of despair. RESULTS: The study sample included 1.5 million Canadians, representing 7.7 million Canadians between the ages of 0 and 19 at baseline. Results from the weighted, adjusted multilevel survival models demonstrated that income inequality was associated with an increased hazard of deaths of despair (adjusted HR (AHR) 1.35; 95% CI 1.04 to 1.75), drug overdose (AHR 2.38; 95% CI 1.63 to 3.48) and all-cause deaths (AHR 1.10; 95% CI 1.04 to 1.18). Income inequality was not significantly associated with suicide deaths (AHR 1.23, 95% CI 0.93 to 1.63). CONCLUSION: The results show that higher levels of income inequality in youth are associated with an increased hazard of all-cause death, deaths of despair and drug overdose in young Canadians. This study is the first to reveal the association between income inequality and deaths of despair in youth and does so using a population-based longitudinal cohort involving multilevel data. The results of this study can inform policies related to income inequality and deaths of despair in Canada.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".