251 Urban-rural disparities in the rate of firearm injuries in British Columbia, Canada
Notice bibliographique
Résumé
<h3>Background</h3> Injuries and deaths attributable to firearms are an important public health problem in Canada. Previous research has demonstrated that this burden is unevenly distributed across socio-economic groups and urban-rural areas. In 2020, a considerable increase was noted in rates of firearm-related violent crime in some Canadian jurisdictions, including in southern rural British Columbia (B.C). <h3>Objective</h3> To determine the rates of firearm-related injuries (FRIs) across the urban-rural continuum in B.C. and to demonstrate the dominant intent and vulnerable groups across this spectrum. <h3>Methods</h3> De-identified data on the firearm-related deaths and hospitalizations among B.C. residents (2010–2019) were retrieved from B.C. Vital Statistics and Discharge Abstract Database (respectively), BC Ministry of Health, and obtained through the BC Injury Research and Prevention Unit (BCIRPU). Records pertaining to in-hospital deaths were removed to avoid double-counting of fatalities. Level of urbanization was determined according to the dissemination area of the place of residence and categorized according to 7-tier Community Health Service Area urban-rural designations (metropolitan, large-urban, medium-urban, small-urban, rural-hub, rural and remote). Rural and remote categories were further combined after the initial analysis, due to proximity of the corresponding rates, to facilitate comparisons. <h3>Results</h3> The annual rate of (combined fatal and non-fatal) FRIs was highest in remote-rural areas (8.00 per 100,000, 95% CI= 7.44–9.00), while large urban areas had the lowest rate (2.55, 95% CI= 2.19–2.97). The highest and lowest median age of injured individuals was observed in remote-rural and metropolitan areas, respectively (50 vs. 32 years). No significant differences were noted regarding the sex ratio of cases across the urban-rural spectrum (overall 11:1). While intentional self-harm comprised 67.3% of FRIs in remote-rural areas, the dominant intent in metropolitan areas was assault with 45.1%. This was consistent with the finding that 71.5% of injuries in remote-rural areas were fatal (vs. 41.2% in metropolitan) <h3>Conclusions</h3> The results demonstrated a significant disparity regarding the rate of FRIs across the urban-rural areas of B.C., driven by higher intentional self-harm among middle-aged men. These findings highlight the importance of specific preventive measures to decrease the burden of FRIs according to the urban-rural residence.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».