Chronic disease and where you live: Built and natural environment relationships with physical activity, obesity, and diabetes
Notice bibliographique
Résumé
BACKGROUND: Diabetes is among the most prevalent non-communicable diseases causing significant morbidity and mortality globally. The aetiology and disease development of diabetes are influenced by genetic, lifestyle, and environmental factors. Due to an increasing number of cases each year, it is imperative to improve the understanding of modifiable environmental risk and protective factors. In this study we aimed to analyse associations between built and natural environment features and diabetes prevalence; and two major risk factors: physical activity and obesity and their mediation effects. METHODS: We analysed relationships between walkability and park availability with physical activity, obesity, and diabetes, using self-reported data from a large cross-sectional survey in British Columbia, Canada (n = 22,418). We validated results with an independent cohort (n = 11,972) in a subset of the analyses. The outcome measures included walking, moderate to vigorous physical activity (MVPA), body mass index (BMI), and diabetes. Built and natural environment features within a 1 km road network buffer around residential postal code centroids were assessed using validated indicators of walkability and park availability. We used general linear multivariable models (GLM) to examine the direct relationship between environmental features, physical activity, obesity, and diabetes respectively. Path models were developed to analyse mediation effects of physical activity and obesity on the association between environmental indicators and diabetes. The relative contribution of direct versus indirect effects was assessed. All models were adjusted for age, gender, income. ethnicity, years lived in neighbourhood and regional accessibility. RESULTS: Walkable neighbourhoods and areas with greater park availability were associated with lower rates of diabetes. There was a direct association of walkability and park availability on physical activity (highest vs. lowest quintile OR = 1.15; 95% CI: 1.00, 1.33 and OR = 1.28, 95% CI: 1.13, 1.45 respectively), obesity (highest vs. lowest quintile OR = 0.58, 95% CI: 0.49, 0.70 and OR = 0.57, 95% CI: 0.48, 0.68 respectively) and diabetes (highest vs. lowest quintile OR = 0.62, 95% CI: 0.45, 0.85, and OR = 0.63, 95% CI: 0.47, 0.84 respectively). Results were similar in the independent cohort. The associations between diabetes and walkability and park availability respectively were partly mediated by obesity (41% of total association for walkability and 53% of total association for park availability). The mediating effect of physical activity was negligible. CONCLUSION: Results support investments in walkability through active transportation and transit infrastructure. Changes in zoning and subdivision regulations governing land use actions are required to enable compact mixed-use environments with access to parks and high quality transit service. Future studies including cost-benefit analyses of health-related economic impacts of such investments can contribute to evidence-based decisions for healthier cities.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».