Examining associations between work-related injuries and all-cause healthcare use among middle-aged and older workers in Canada using CLSA data
Notice bibliographique
Résumé
INTRODUCTION: Prior studies examining the relationship between work- related injuries and healthcare use among middle-aged and older workers were mainly cross-sectional and reported inconsistent results. OBJECTIVE: The objective of this study was to examine the associations between work-related injuries and 10 types of healthcare service use for any cause among middle-aged and older Canadian workers using longitudinal data. METHODS: Our study involved longitudinal analysis of baseline and 18-month follow-up Maintaining Contact Questionnaire data from the Canadian Longitudinal Survey on Aging (CLSA) for a national sample of Canadian males and females aged 45-85 years who worked or were recently retired (N = 24,748). RESULTS: Among CLSA participants who worked or were recently retired, 361 per 10,000 reported a work-related injury within the year prior to the survey. Work-related injuries decreased with increasing age. Work-related injury was associated with emergency department visits, overnight hospitalization, visits to dentists, and visits to physiotherapists, occupational therapists, or chiropractors at follow-up in bivariate analyses. Compared to those with no work-related injuries, Canadians with work-related injuries had used, on average, a significantly higher number of health services within the last 12 months prior their survey. When controlling for the contribution of various socio-demographic, work-related, and health-related characteristics, work-related injuries remained a significant predictor of emergency department visits and visits to physiotherapists, occupational therapists, or chiropractors. CONCLUSIONS: The relationship between work-related injuries, emergency department visits, and visits to physiotherapists, occupational therapists, or chiropractors in middle-aged and older workers in Canada suggests that workplace injuries can be associated with ongoing health problems. PRACTICAL APPLICATIONS: Healthcare services used by injured employees must be considered priorities for employment insurance coverage, if not already covered. Future research should more fully examine whether pre-existing health conditions predict both work-related injury and subsequent health problems. Injury-specific healthcare use following work-related injuries in middle-aged and older workers, as well as economic costs, should also be examined.
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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 | 0,017 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,006 |
| 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 ».