Perceived neighborhood environmental attributes associated with adults’ transport-related walking and cycling: Findings from the USA, Australia and Belgium
Notice bibliographique
Résumé
BACKGROUND: Active transportation has the potential to contribute considerably to overall physical activity levels in adults and is likely to be influenced by neighborhood-related built environment characteristics. Previous studies that examined the associations between built environment attributes and active transportation, focused mainly on transport-related walking and were conducted within single countries, limiting environmental variability. We investigated the direction and shape of relationships of perceived neighborhood attributes with transport-related cycling and walking in three countries; and examined whether these associations differed by country and gender. METHODS: Data from the USA (Baltimore and Seattle), Australia (Adelaide) and Belgium (Ghent) were pooled. In total, 6,014 adults (20-65 years, 55.7% women) were recruited in high-/low-walkable and high-/low-income neighborhoods. All participants completed the Neighborhood Environmental Walkability Scale and the International Physical Activity Questionnaire. Generalized additive mixed models were used to estimate the strength and shape of the associations. RESULTS: Proximity to destinations, good walking and cycling facilities, perceiving difficulties in parking near local shopping areas, and perceived aesthetics were included in a 'cyclability' index. This index was linearly positively related to transport-related cycling and no gender- or country-differences were observed. The 'walkability' index consisted of perceived residential density, land use mix access, proximity of destinations and aesthetics. A non-linear positive relationship with transport-related walking was found. This association was stronger in women than in men, and country-specific associations were identified: the strongest association was observed in Seattle, the weakest in Adelaide. In Ghent, the association weakened at higher levels of walkability. CONCLUSIONS: For cycling, consistent correlates were found in the three countries, but associations were less straightforward for transport-related walking. Moreover, the identified neighborhood environmental correlates were different for walking compared to cycling. In order to further clarify the shape of these associations and reach more specific international guidelines for developing walkable and bikeable neighborhoods, future studies should include even more countries to maximize environmental variability.
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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 | 0,001 |
| 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 ».