Suicide and Self-Harm in Recent Immigrants in Ontario, Canada: A Population-Based Study
Bibliographic record
Abstract
Objective:To estimate the rates of suicide and self-harm among recent immigrants and to determine which immigrant-specific risk factors are associated with these outcomes.Methods:Population-based cohort study using linked health administrative data sets (2003 to 2017) in Ontario, Canada which included adults ≥18 years, living in Ontario (N = 9,055,079). The main exposure was immigrant status (long-term resident vs. recent immigrant). Immigrant-specific exposures included visa class and country of origin. Outcome measures were death by suicide or emergency department visit for self-harm. Cox proportional hazards estimated adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs).Results:We included 590,289 recent immigrants and 8,464,790 long-term residents. Suicide rates were lower among immigrants (n = 130 suicides, 3.3/100,000) than long-term residents (n = 6,354 suicides, 11.8/100,000) with aHR 0.3, 95% CI, 0.2 to 0.3. Male–female ratios in suicide rates were attenuated in immigrants. Refugees had 2.1 (95% CI, 1.3 to 3.6; rate 6.1/100,000) and 2.8 (95% CI, 2.5 to 3.2) times the likelihood of suicide and self-harm, respectively, compared with nonrefugee immigrants. Self-harm rate was lower among immigrants (n = 2,256 events, 4.4/10,000) than long-term residents (n = 68,039 events, 9.7/10,000 person-years; aHR 0.3; 95% CI, 0.3 to 0.3). Unlike long-term residents, where low income was associated with high suicide rates, income was not associated with suicide among immigrants and there was an attenuated income gradient for self-harm. Country of origin-specific analyses showed wide ranges in suicide rates (1.4 to 9.9/100,000) and self-harm (1.8 to 14.9/10,000).Conclusion:Recent immigrants have lower rates of suicide and self-harm and different sociodemographic predictors compared with long-term residents. Analysis of contextual factors including immigrant class, origin, and destination should be considered for all immigrant suicide risk assessment.
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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 | 0.003 |
| Science and technology studies | 0.002 | 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".