Self-harm hospitalizations and neighbourhood level material and social deprivation in Canada: an ecological study
Bibliographic record
Abstract
BACKGROUND: Socio-economic status is associated with self-harm at the individual and area level. In Canada, there is limited evidence on the relationship between area-level markers of socio-economic status and self-harm. The objective of this study was to assess the impact of small area-level material and social deprivation on rates of hospitalization due to self-harm. METHODS: Administrative data on hospitalizations from two databases in Canada (Discharge Abstract Database and Ontario Mental Health Reporting System) for the period April 1, 2015 to March 31, 2022, were analyzed. Rates of self-harm hospitalization and percentage of repeated admissions were estimated across quintiles of material and social deprivation. Rate ratios were computed to evaluate disparities. The rates were stratified by sex and age group; the percentage of repeated admissions were stratified by sex. RESULTS: In total, the study included 109,398 hospitalizations due to self-harm. Populations in more deprived areas had higher rates of self-harm hospitalizations than those in less deprived areas. The rate ratios for people who lived in the most deprived areas over the least deprived areas were 1.48 (95% CI: 1.38-1.58) and 1.71 (95% CI: 1.60-1.82) for material and social deprivation, separately. The largest disparity was among people aged 25-44 years for material and 45-64 years for social deprivation. Percentages of repeated self-harm hospitalizations were significantly higher in more deprived areas compared to less deprived areas for social deprivation, and among males but not females for material deprivation. CONCLUSIONS: Both material and social deprivation were associated with self-harm hospitalization and repeated admissions; the disparity varied by subgroup and the deprivation components. This study demonstrated a need to consider interventions at the neighbourhood level and address both community and population-level conditions of social and material need.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".