Public Health Unit Funding and Emergency Department Visits due to Self-Harm, Alcohol, and Drug Poisoning Before and During COVID-19 in Ontario, Canada
Notice bibliographique
Résumé
Background: Self-harm, alcohol use, and drug poisoning harms (SAD) are major public health concerns in Canada. Since the early 2000s, SAD deaths, hospitalizations, and ED visits have increased over time, and it was predicted that the COVID-19 pandemic may have exacerbated these conditions in Canada. Current research suggest that increased government public health funding towards mental health and substance use programs was associated with decreased rates of SAD hospitalization and emergency department (ED) visits. However, this research consists of mainly ecological or simulated studies, with a lack of observational cohort data that examines whether public health funding is associated with individual risks of these health outcomes. Objectives: The study objectives were to: 1) estimate the association between local public health unit (PHU) funding per capita with SAD ED visits among individuals aged 15+ years living in Ontario, Canada between April 1st 2018-March 31st 2020 (before COVID-19) and April 1st 2020-March 31st 2022 (during COVID-19), and 2) to test for effect modification and determine whether the observed associations were heterogeneous across age, gender, ethnicity, rurality, and socio-economic status. Method: This was a cohort study using data from the Canadian Census Health and Environmental Cohorts (CanCHEC) which includes individuals from the 2016 Census linked to National Ambulatory Care Reporting System (NACRS) for follow up on ED visits. Individuals in this study were linked to Ontario Public Health Information Database (OPHID) using the location of the PHU in which they resided at the start of baseline in order to determine their exposure to PHU funding at the start of follow-up. Socioeconomic characteristics of this cohort were obtained from census respondents of CanCHEC 2016. Multilevel mixed effects survival models were conducted. Survey weights were applied to generalize the findings. Results: There were 34 PHUs in 2018 and 33 PHUs in 2020 for analysis. The unweighted baseline samples (rounded to the nearest 5) included 2,435,300 individuals in 2018 and 2,417,640 individuals in 2020 aged 15 and over. A small proportion, <1% of the sample, had a SAD ED visit. A $10 increase of total public health funding per capita was associated with a decrease hazards of self-harm ED visits (adjusted hazard ratio (aHR): 0.96; 95% CI: 0.92-0.99) before COVID-19 and alcohol-attributable ED visits (aHR: 0.93; 95% CI: 0.88-0.98) during COVID-19. An increase of Substance Use and Injury Prevention (SUIP) funding per capita by $2 was associated with decreased hazards of alcohol ED visits (aHR: 0.93; 95% CI: 0.85-1.01) before COVID-19 and decreased hazards of self-harm ED visits (aHR: 0.95; 95% CI: 0.92-0.98) during COVID-19. Cross-level interactions indicated that increased PHU funding per capita was associated with: decreased self-harm and drug poisoning ED visits among youth aged 15-24, decreased alcohol ED visits among males and middle adults aged 45-64, and decreased SAD ED visits among those with moderate income and residing in mixed, rural, and northern PHU regions. Conclusion: Increased PHU funding was associated with decreased self-harm and alcohol attributable ED visits. Increased PHU funding was mainly associated with groups at highest risk of SAD ED visits, such as young females and middle adult males living in northern or rural PHUs, with exception to those with low income. Although PHU funding may be an important tool to enhance mental health and substance services in Ontario, further research is needed to apply health equity to low-income groups.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».