Do school-based physical activity interventions increase or reduce inequalities in health?
Notice bibliographique
Résumé
Little is known about the effectiveness of school-based health promotion on physical activity inequalities among children from low-income areas. This study compared the two-year change in physical activity among 10-11 year-old children attending schools with and without health promotion programs by activity level, body weight status, and socioeconomic backgrounds to assess whether health promotion programs reduce or exacerbate health inequalities. This was a quasi-experimental trial of a Comprehensive School Health (CSH) program implemented in schools located in socioeconomically disadvantaged neighbourhoods in Edmonton, Alberta, Canada. In the spring of 2009 and 2011, pedometer (7 full days) and demographic data were collected from cross-sectional samples of grade five children from 10 intervention and 20 comparison schools. Socioeconomic status was determined from parent self-report. Low-active, active, and high-active children were defined according to step-count tertiles. Multilevel linear regression methods adjusted for potential confounders were used to assess the relative inequity in physical activity and were compared between groups and over-time. In 2009, a greater proportion of students in the intervention schools were overweight (38% vs. 31% p = 0.03) and were less active (10,827 vs. 12,265 steps/day p < 0.001). Two years later, the relative difference in step-counts between intervention and comparison schools reduced from -15.5% to 0% among low-active students, from -13.4% to 0% among active students, and from -15.1% to -2.7% among high-active students. The relative difference between intervention and comparison schools reduced from -11.1% to -1.6% among normal weight students, from -16.8% to -1.4% among overweight students, and was balanced across socioeconomic subgroups. These findings demonstrate that CSH programs implemented in socioeconomically disadvantaged neighbourhoods reduced inequalities in physical activity. Investments in school-based health promotion are a viable, promising, and important approach to improve physical activity and prevent childhood obesity, and may also reduce inequalities in health.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».