Examining the Association between Income Inequality and Physical Activity among Canadian Youth during the COVID-19 Pandemic
Notice bibliographique
Résumé
Background Physical inactivity among Canadian adolescents has become an increasing concern in recent years. This trend has been further exacerbated by periods of societal disruption, such as the COVID-19 pandemic. However, the influence of broader contextual factors—particularly income inequality—on adolescent health behaviors during such crises remains unclear. The pandemic provides a unique opportunity to examine how socioeconomic disparities may have contributed to reduced physical activity levels among youth. Objectives The influence of contextual factors on adolescent health outcomes during times of crisis remains poorly understood. This study examines changes in physical activity levels among a sample of Canadian adolescents following the onset of the COVID-19 pandemic and investigates whether income inequality at the census division (CD) level contributed to physical activity changes, with a focus on gender-specific patterns. Methods Longitudinal data from 8,812 students aged 12 to 18 within 35 CDs were obtained from three waves (2020-21, 2021-22, 2022-23) of the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary behaviour (COMPASS) study. CD-level income inequality was measured using Gini coefficients. Gender stratified multilevel models were used to analyze physical activity changes across survey waves and to quantify the association between income inequality and physical activity over the study period. Results Among the full sample, CD-level income inequality at the baseline was significantly associated with higher physical activity levels in both follow-up waves (2021-22: β = 0.042; 95% CI: 0.012, 0.072; 2022-23: β = 0.039; 95% CI: 0.009, 0.069). However, in the gender stratified analyses, income inequality was not significantly associated with physical activity in any survey wave for both males and females. Significant trends in physical activity levels among females (β = 0.057; 95% CI: 0.032, 0.081; β = 0.062; 95% CI: 0.038, 0.086) were observed across the two follow-up waves but not among males (β = 0.039; 95% CI: -0.004, 0.082; β = 0.034; 95% CI: -0.003, 0.082). Conclusion Physical activity levels increased among only females throughout the two follow-up waves. The association between income inequality and physical activity were significant in the full sample of adolescents. These unexpected findings emphasize the need for further research into how the mechanisms of income inequality and health related behaviours may have been affected by the COVID-19 pandemic.
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».