Characterization of occupational, demographic and health determinants in Canadian reservists veterans and the relationship with poor self-rated health
Notice bibliographique
Résumé
BACKGROUND: Self-rated health is an useful indicator of the general health in specific populations and used to propose interventions after service in the military context. However, there is scarce literature about self- rated health (SRH) in the Canadian Veterans of the Reserve Force and its relationship with demographic, health and occupational characteristics of this specific group. The aims of this research were to determine the SRH in Canadian Reserve Force Veterans and to explore the relationship between demographic, military service and health factors by reserve class. METHODS: Data from the individuals was collected from the Life After Service (LASS) 2013 survey, including Veterans with Reserve Class C (n = 922) and Class A/B (n = 476). Bivariate and multivariate analysis using logistic regression models, were used to assess the association between the demographic characteristics, physical health, mental health, and military service characteristics and the self-rate health by both reserve classes. RESULTS: The overall prevalence of poor SRH in Reserve Class C Veterans was 13.1% (CI:11.08-15.4) and for Reserve Class A/B was 6.9% (CI:5.0-9.1). Different degrees of associations were observed during the bivariate analysis and two different models were produced for each reserve class. Veterans of Reserve Class C showed that being single was (OR = 2.76, CI: 1.47-5.16), being 50-59 years old (OR = 4.6, CI: 1.28-17.11), reporting arthritis (OR = 2.49, CI: 1.33-4.67), back problems (OR = 3.02, CI:1.76-5.16), being obese (OR = 1.96, CI: 1.13-3.38), depression (OR = 2.34, CI: 1.28-4.20), anxiety (OR = 4.11, CI: 2.00-8.42), PTSD (OR = 2.1 CI: 0.98-4.47), PTSD (OR = 20.9, CI:0.98-4.47) and being medically released (OR = 4.48, CI: 2.43-8.24) were all associated with higher odds of poor SRH. The Reserve Class A/B model showed that completing high school (OR = 4.30, CI: 1.37-13.81), reporting arthritis (6.60, CI: 2.15-20.23), diabetes (OR = 11.19, CI: 2.72-46.0), being obese (OR = 3.37, CI: 1.37-8.27), daily smoking (OR = 2.98, CI: 1.05-8.38), having anxiety (OR = 9.8, CI: 3.70-25.75) were associated with higher odds of poor SRH. CONCLUSIONS: These results suggested that the relationship of poor SRH with demographic, health and military occupation domains varied depending on the class on the Reserve Force Service. Different strengths of association showed different risk compositions for both populations. This can be used to better understand the health and well-being of Veterans of the Reserve Force.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 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 ».