Abstract MP50: Regional Income and Relative Individual Income, but Not Income Inequality, is Associated With Cardiovascular Health
Notice bibliographique
Résumé
Background: Result from many studies support that the associations between income, income inequality, and mortality, including CVD mortality, are very complex. Given the urgent need for greater CVD prevention in populations, it is essential to understand how income inequality and income, both in individuals and the regions in which they live, can affect cardiovascular health (CVH). Objective: To examine the associations between regional income and income inequality and individual relative income and individual CVH. Setting: This study was carried out in a nationally representative sample of Canadian adults aged 20 years and older residing in 113 health regions (HR) across Canada. Data and Methods: This study is a cross-sectional design using data from the Canadian Community Health Survey (CCHS) 2015-2016 database. The CCHS is a nationwide, nationally representative survey that collects information on the health status, health care utilization, and health determinants of the Canadian population. The study outcome was individual CVH, defined using the AHA CVH Index (CVHI) and determined using self-reported responses in CCHS. Regional income inequality was measured as the Gini coefficient of the HR. Regional income was measured as the median household income in the HR. Individual income was measured as relative, not absolute, income representing the individual’s household income compared to those in the HR. Multilevel models were used to examine the associations between regional income and income inequality and individual relative income and individual CVH, controlling for individual age, sex, race and education. Analyses were conducted using SAS 9.4 software. Results: The majority of the population were males (51%), aged 40-60 (37%), with tertiary education (64%) and of the White race (79%). Overall, mean CVH for individuals was 4.5. The national average Gini coefficient across HRs was 0.4. The average individual fell within the 6 th decile for relative household income. Living in a HR with greater income inequality was not associated with lower individual CVH (β= -0.04 p-value=0.91), though living in an HR with higher median household income was associated with better individual CVH (β= 0.32 p=0.004). Finally, having higher relative household income was associated with better individual CVH (β= 0.05 p<0.0001), regardless of the median income of the region of residence. Conclusion: While the inequality of income within a HR did not significantly affect CVH, higher regional income and relative individual income was associated with better CVH. Results of this study contribute to the growing body of evidence attempting to disentangle the true associations between income, income inequality, and CVH.
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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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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 ».