Assessing the built environment through photographs and its association with obesity in 21 countries: the PURE Study
Notice bibliographique
Résumé
BACKGROUND: The built environment can influence human health, but the available evidence is modest and almost entirely from urban communities in high-income countries. Here we aimed to analyse built environment characteristics and their associations with obesity in urban and rural communities in 21 countries at different development levels participating in the Prospective Urban and Rural Epidemiology (PURE) Study. METHODS: ) were assessed using multilevel regression models, adjusting for individual, household, and community confounding factors. Attenuation in the associations due to walking was examined. FINDINGS: Analyses include 143 338 participants from 530 communities. The mean integrated built environment score was higher in high-income countries (13·3, SD 2·8) compared with other regions (10·1, 2·5) and urban communities (11·2, 3·0). More than 60% of high-income country communities had pedestrian safety features (eg, crosswalks, sidewalks, and traffic signals). Urban communities outside high-income countries had higher rates of sidewalks (176 [84%] of 209) than rural communities (59 [28%] of 209). 15 (5%) of 290 urban communities had bike lanes. Litter and graffiti were present in 372 (70%) of 530 communities, and poorly maintained buildings were present in 103 (19%) of 530. The integrated built environment score was significantly associated with reduced obesity overall (relative risk [RR] 0·58, 95% CI 0·35-0·93; p=0·025) for high compared with low scores and for increasing trend (0·85, 0·78-0·91; p<0·0001). The trends were statistically significant in urban (0·85, 0·77-0·93; p=0·0007) and rural (0·87, 0·78-0·97; p=0·015) communities. Some built environment features were associated with a lower prevalence of obesity: community beautification RR 0·75 (95% CI 0·61-0·92; p=0·0066); bike lanes RR 0·58 (0·45-0·73; p<0·0001); pedestrian safety RR 0·75 (0·62-0·90; p=0·0018); and traffic signals RR 0·68 (0·52-0·89; p=0·0055). Community disorder was associated with a higher prevalence of obesity (RR 1·48, 95% CI 1·17-1·86; p=0·0010). INTERPRETATION: Community built environment features recorded in photographs, including bike lanes, pedestrian safety measures, beautification, traffic density, and disorder, were related to obesity after adjusting for confounders, and stronger associations were found in urban than rural communities. The method presents a novel way of assessing the built environment's potential effect on health. FUNDING: Population Health Research Institute, Hamilton Health Sciences Research Institute, Heart and Stroke Foundation of Ontario, Canadian Institutes of Health Research's Strategy for Patient Oriented Research, Ontario Support Unit, Ontario Ministry of Health and Long-Term Care, AstraZeneca, Sanofi-Aventis, Boehringer Ingelheim, Servier, and GlaxoSmithKline.
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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».