Mobility in Aging: Travel Behavior and Implications for Physical Activity
Notice bibliographique
Résumé
Rapid demographic aging in countries around the world has prompted an interest in understanding the mobility patterns of seniors. While much research has been conducted in terms of motorized modes, the promotion of healthy aging argues for new research to investigate the multi-modal travel behavior of seniors including active travel. It is generally agreed that walking is a convenient, safe, and adequate activity for all ages and particularly for seniors, because it places the right amount of stress on their joints. It also is an inexpensive mode of transportation under a wide range of circumstances and can help achieve physical activity guidelines without imposing additional time demands. The objectives of this dissertation are fourfold. The first two objectives investigate the factors that influence use, length, frequency of two motorized (transit and car) and one active mode of transportation (walking) of seniors. The third objective is to introduce a concept of Compliance Potential Mapping (CPM) that produces maps to show spatial variation in percentage of physical activity requirements seniors obtain from their regular walking for transport. Finally, the dissertation implements a street segment sampling approach and investigates the attributes of walkable environments from the perspective of seniors. A joint discrete-continuous modeling framework was used to model mode use and trip length simultaneously and, on the other hand, a trivariate ordered probit model was used for estimating the multi-modal trip generation of seniors. CPM concept used simple map algebra operations on maps of spatial variations in trip length and frequency in order to produce potential maps of physical activity compliance. Lastly, the street sampling approach used multinomial spatial scan statistic to detect cluster of street segments where walkability audits can be conducted. Data were drawn from Montreal’s Household Travel Survey of 2008. A broad array of covariates related to personal, mobility tools (possession of driver’s licence and automobile), neighborhood, and accessibility variables were considered in the models of mode use, trip length, and trip frequency for the Montreal Island. The results of the analyses reveal a significant degree of geographical variability in the travel behavior of seniors in the Island. In particular, estimates for seniors with different socio- demographic profiles show substantial intra-urban variability in walking behavior, and the role of neighborhood design attributes and accessibility in influencing the mobility of seniors. Demonstration of CPM indicates that seniors in the central parts of Montreal Island obtain higher percentage of physical activity guidelines from walking, but with variations according to gender, income, possession of driver’s licence and vehicle. The results of the walkability analysis suggest that, other factors being equal, walking is more prevalent in street segments with marked cross–walks, horizontal and vertical mixtures in land uses, and low traffic volume. Other factors being equal, walking was less prevalent in segments with unmarked cross–walks, single residential and/or vacant land use, and high traffic volume.
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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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».