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Assessing the Associations Between Light Rail Transit (LRT) and Physical Activity: A Systematic Review

2021· other· en· W6989427676 sur OpenAlexaboutno aff

Notice bibliographique

RevueOSF Preprints (OSF Preprints) · 2021
Typeother
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPublic transportPublic healthPhysical activityTransit (satellite)Light rail transitPopulationInvestment (military)Health impact assessmentBuilt environment
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

In response to growing environmental and population health concerns, many cities worldwide are increasing their investment in public transit systems. Indeed, public transit has many benefits to both individuals and communities: it is an affordable travel mode (especially when compared to car use), and can reduce congestion, improve air quality, and encourage physical activity [1]. For this review, we will focus on one health impact of public transit: physical activity. \nThe relationship between the built environment and physical activity has been systematically reviewed [2, 3], and three papers have specifically reviewed the impact of public transit on physical activity [1, 4, 5]. One systematically reviewed the impacts of building, extending, or improving local public transit options on physical activity and found that public transit investments are associated with approximately 30 minutes of additional walking (or other light to moderate physical activity) per week. No significant relationship between new transit and moderate to vigorous physical activity was found [4]. Another non-exhaustive review of the evidence on transit’s impacts on self-reported physical activity, objectively measured physical activity, health outcomes, as well as the health care costs associated with transit [1]. Finally, an older systematic review examined the extent of association between the use of public transport and time spent in physical activity (walking/cycling to transport stops/stations) among adults [5]. Further, a meta-analysis on rapid transit has been conducted, and found that while transport-related physical activity increased after transit interventions, overall physical activity decreased [6].\nThe three existing reviews focus on all types of public transit. One form of public transit that has become increasingly popular in recent years is Light Rail Transit (LRT), which tends to have lower capital costs and increased reliability compared with other public transit systems. The meta-analysis did focus on rapid transit, but because it only included studies with natural experiment designs, only five studies were eligible, three of which focused on LRTs. Therefore, we to will conduct a systematic review of the literature to identify studies examining the relationship between Light Rail Transit and physical activity. The primary objective of this review is to assess the evidence of the associations between LRTs and physical activity. Secondary objectives include comparing the evidence across (1) exposure measurements (e.g., living near an LRT vs. occasional use vs. frequent use), (2) outcome measurements (e.g., self-reported vs. device measured vs. direct observation of physical activity), (3) population density of the city under study, (4) population age (e.g., youth, adults, older adults), and (4) the geography of the stations under study, as well as considering the theoretical frameworks used in this work (e.g., socio-ecological), and whether this body of work considers equity (e.g., whether the physical outcomes are distributed equally by sex/gender, SES indicators, age, residential location, etc.). We will derive policy and research recommendations based off the results of the review. We limit our focus to LRTs in Canada, the United States, Australia, and New Zealand, as the urban areas of these countries tend to share similar built environment characteristics. In doing so, we expand the scope of others [6] by including all studies focused on physical activity and light rail, regardless of the methodology, and deviate from other reviews [1, 4, 5] by conducting a review of the evidence on the impacts of one specific, and increasingly popular, mode of public transit: LRTs. \n

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,010
score de la tête « metaresearch » (Gemma)0,008
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,365
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0100,008
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0030,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0020,002
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,1800,545

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.

Tête enseignante Opus0,033
Tête enseignante GPT0,323
Écart entre enseignants0,290 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeRevue systématique
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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