Rural–Urban Differences in Suicide Mortality: An Observational Study in Newfoundland and Labrador, Canada: Différences de la Mortalité Par Suicide en Milieu Rural-Urbain: Une Étude Observationnelle à Terre-Neuve et Labrador, Canada
Bibliographic record
Abstract
Background:Suicide rates are higher in rural compared to urban areas. Although this pattern appears to be driven by higher rates among men, there is limited evidence about the characteristics of rural people who die by suicide in Canada. The objective of this study was to examine the demographics, manner of death, and social and clinical antecedents of people who died by suicide in rural areas compared to urban areas.Methods:We conducted an observational study of all suicide deaths that occurred among Newfoundland and Labrador residents between 1997 and 2016 using a linked data set derived from a comprehensive review of provincial medical examiner records. We used t tests and χ2 to assess associations between rural/urban status and variables related to demographics, circumstances, and manner of death, as well as social and medical history. Logistic regression was utilized to assess the independent contribution of any variable found to be significant in univariate analysis.Results:Rural people who died by suicide accounted for 54.8% of all deaths over a 20-year period. Overall, 81.6% of people who died were male. Compared to urban, rural people who died by suicide were younger, more likely to use firearms or hanging, and had a higher mean blood alcohol content at the time of death (27.69 vs. 22.95 mmol/L). Rural people were also less likely to have had a known history of a prior suicide attempt, psychiatric disorder, alcohol or substance abuse, or chronic pain.Discussion:The demographic and clinical differences between rural and urban people who died by suicide underscore the need for suicide prevention approaches that account for place-based differences. A key challenge for suicide prevention in rural communities is to ensure that interventions are developed and implemented in a manner that fits local contexts.
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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 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".