Abstract P468: Geographic and Socioeconomic Inequalities in Poor Cardiovascular Health in Canada
Notice bibliographique
Résumé
Background: Poor cardiovascular health (CVH), characterized by clinical risk and unhealthy lifestyle habits, is a leading cause of death and disease worldwide. Despite advances in healthcare and policy, there remains an inequitable burden of poor CVH among Canadian sub-populations based on socioeconomic status and geographic region. Using recently published data and a national toolkit, this study aimed to quantify inequalities in poor CVH across the Canadian population. Methods: We conducted a cross-sectional study on Canadian adults, ≥20 years, from the nationally representative Canadian Community Health Survey 2017. Using the American Heart Association’s CVH Index, CVH was defined for each individual as a summed score of 7 components, where 1 point was awarded for achieving ideal health in each component. A total score of 0-2 points indicated poor overall CVH. The Canadian Institute for Health Information (CIHI) Measuring Health Inequalities Toolkit, a standardized methodological approach to analyzing health inequalities in population-based data using pre-defined stratifications and second-level interactions, was used to quantify inequalities in poor CVH based on Toolkit-defined stratifications in sex, income, urban/rural status, and region of residence. The regional distribution of CVH was mapped using ArcGIS software. Results: Approximately 7% of Canadians had poor CVH, representing 2 million Canadians. Poor dietary habits were noted in 99.0% of the population, with poor body mass index and poor physical activity noted in 58.1% and 42.3%, respectively. The eastern provinces of Newfoundland and Labrador and New Brunswick had the greatest proportion of health regions with poor CVH. An examination of the largest CVH inequalities across provinces revealed that females in the lowest income tercile residing in Prince Edward Island were 8-times more likely to experience poor CVH than females in the highest income tercile (RR 8.43, 95%CI 7.09-10.04). Additionally, females in New Brunswick residing in rural regions were almost 3-times more likely to experience poor CVH than females residing in urban regions (RR 3.07, 95%CI 1.07-4.87). In most provinces, income and urban/rural inequalities among males were observed but were of smaller magnitude than the inequalities among females. Conclusion: The greatest inequalities in poor CVH were experienced by females in the lowest income groups. Urban/rural inequalities in CVH were complex and varied by geographic region. The CIHI toolkit is a robust and systematic approach to understanding health inequalities that will enable comparison between studies and health/disease states, and thus facilitate comparative policy evaluation and population health priority setting.
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 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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,007 |
| Études des sciences et des technologies | 0,006 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».