2020
DOI: 10.1111/obr.13096
|View full text |Cite
|
Sign up to set email alerts
|

Walkability indices and childhood obesity: A review of epidemiologic evidence

Abstract: Summary The lack of an active neighbourhood living environment can impact community health to a great extent. One such impact manifests in walkability, a measure of urban design in connecting places and facilitating physical activity. Although a low level of walkability is generally considered to be a risk factor for childhood obesity, this association has not been established in obesity research. To further examine this association, we conducted a literature search on PubMed, Web of Science and Scopus for art… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
28
0
1

Year Published

2020
2020
2023
2023

Publication Types

Select...
10

Relationship

3
7

Authors

Journals

citations
Cited by 37 publications
(29 citation statements)
references
References 51 publications
0
28
0
1
Order By: Relevance
“…Although it could be argued that the deep learning analysis of satellite imagery is simply a measurement of population density, this approach also measures several other factors that may contribute to COVID-19 infection and death rates independent of population density, such as built environment features that contribute to the development of COVID-19 risk factors and features that may put individuals at risk of contracting COVID-19. Examples of features that may put individuals at risk for developing risk factors include walkability (which contributes to obesity [48]) and road proximity (which can increase risk for heart disease [49]). Additionally certain architectural and built environment features that might put individuals at risk of COVID-19 infection, such as the configuration of pedestrian traffic in an urban area [50], can be partly quantified with this approach.…”
Section: Principal Resultsmentioning
confidence: 99%
“…Although it could be argued that the deep learning analysis of satellite imagery is simply a measurement of population density, this approach also measures several other factors that may contribute to COVID-19 infection and death rates independent of population density, such as built environment features that contribute to the development of COVID-19 risk factors and features that may put individuals at risk of contracting COVID-19. Examples of features that may put individuals at risk for developing risk factors include walkability (which contributes to obesity [48]) and road proximity (which can increase risk for heart disease [49]). Additionally certain architectural and built environment features that might put individuals at risk of COVID-19 infection, such as the configuration of pedestrian traffic in an urban area [50], can be partly quantified with this approach.…”
Section: Principal Resultsmentioning
confidence: 99%
“…Un creciente número de estudios han utilizado distintas metodologías y descriptores para evaluar la caminabilidad de un entorno. En la actualidad existen aproximaciones basadas en sistemas de información geográfica, los cuales emplean métricas basadas en áreas -como la densidad de restaurantes, minoristas de alimentos y características ambientales construidas dentro de unidades estadísticas (distritos censales y zonas postales) (Yang et al, 2021)-. De igual manera, se pueden emplear métricas basadas en redes, considerando la caminabilidad como una medida de accesibilidad a servicios cercanos (como el transporte público o centros educativos) desde ubicaciones residenciales o lugares de trabajo (D'Orso y Migliore, 2020; Yitzhaki, 1983).…”
Section: Caminabilidadunclassified
“…Moreover, the MNUACI has a higher spatial resolution than the previous DMSP/OLS-and NPP-VIIRS-based indexes by using NTL data from the Luojia 1-01 NTL satellite, designed and developed by Wuhan University in China, which has started providing nighttime imagery with a finer resolution of 130 m since 2018. The MNUACI would be useful for a wide array of urban studies, such as urban population health [25], urban spatial structure [26], and energy carbon emissions [27], where such an index has been urgently demanded.…”
Section: Introductionmentioning
confidence: 99%