Abstract P210: The Social Distribution Of Ideal Cardiovascular Health: A Global Systematic Review
Notice bibliographique
Résumé
Introduction: Numerous studies have examined the social determinants of ideal cardiovascular health (ICVH) around the world, but no work has summarized evidence to date. This study aimed to systematically review findings on the social distribution of ICVH globally, and to compare trends in high-income countries (HICs) vs. low/middle-income countries (LMICs). Methods: In November 2019, we systematically searched PubMed, Embase, and LILACS for observational studies published after the American Heart Association (AHA) defined ICVH as a combination of health factors and behaviors in 2010. Search terms included ICVH/Life’s Simple 7 and a pre-defined set of social determinants of health (i.e., education, income/wealth, socioeconomic status (SES), employment, occupation, and race/ethnicity). Each abstract was reviewed by two independent researchers. Studies were included if associations between a composite measure of ICVH and a social determinant of health was quantified using statistical methods. We evaluated risk of bias using an adapted version of the Newcastle-Ottawa Quality Assessment Scale. Overall findings and comparisons between HICs and LMICs (defined by World Bank guidelines) were summarized narratively. Results: A total of 33 studies met inclusion criteria. Only 8 studies were from LMICs (n=4 from China), while 25 were from HICs (n=19 from the US). The most commonly assessed social determinants were education (n=18) and income/wealth (n=17). In both HICs and LMICs, few studies examined occupation or area-level measures, like rurality/urbanicity. Most studies were cross-sectional (n=27). Two thirds of studies and had a moderate (n=14, 43%) or high (n=8, 24%) risk of bias, but no systematic differences were noted by country setting. Nearly half of studies used composite ICVH measures that were of moderate or poor quality (i.e., based on only self-reported data and/or unvalidated instruments), and only 15% of studies (n=5) assessed each ICVH component using the exact criteria defined by the AHA. Despite substantial heterogeneity in how ICVH measures were derived and analyzed (e.g., as a binary, categorical, or count variable), fairly consistent associations were observed between higher levels of ICVH and higher social status (higher education, income/wealth, racial/ethnic majority status) across both HICs and LMICs. Studies of occupation (n=6, all from HICs) and area-level measures (n=4, 3 from LMICs) were less conclusive. Conclusion: Associations between higher social status and ICVH were noted in both HICs and LMICs, but most evidence was based on correlational data from cross-sectional studies in the US, primarily in relation to education and income. Important gaps in the literature include studies from LMICs, longitudinal designs to improve causal inference, and investigations of occupation, rurality/urbanicity, and race/ethnicity in non-US settings.
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 | 0,022 | 0,093 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,009 | 0,006 |
| Bibliométrie | 0,017 | 0,018 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».