Sex differences in suicide mortality in Newfoundland and Labrador: An observational study with medical examiner data from 1997 to 2016
Bibliographic record
Abstract
Background: Globally, the suicide rate is two times higher for males than for females. Previous studies in Newfoundland and Labrador did not examine age-specific rates by sex. The objectives of this study were to determine suicide rates by sex and age group and to compare the demographic and clinical characteristics of males and females who died by suicide. Data and methods: This observational study analyzed a routinely collected dataset based on all medical examiner-determined suicide deaths among people aged 10 years and older in Newfoundland and Labrador, Canada, between 1997 and 2016. Age-standardized and age-specific suicide rates and rate ratios were calculated based on the number of deaths during the period, and descriptive statistics were used to compare demographic and clinical characteristics between males and females. Results: The age-standardized suicide rate was 4.6 times higher among males than females and was higher for males in most age groups. Rates were highest in the young adult age groups for males (20 to 24 years) and females (35 to 39 years). Males who died by suicide were more likely to be from a rural community and to have died by firearm; females were more likely to die by self-poisoning and to have had a mental illness or substance use history. Interpretation: The results are broadly consistent with previous research, though this is the first study to report age-specific suicide rates among females across the life course in Newfoundland and Labrador. The results underscore the need to design public health and clinical interventions that account for sex differences in suicide risks.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".