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Walkability and walking for transport: characterizing the built environment using space syntax

BACKGROUND: Neighborhood walkability has been shown to be associated with walking behavior. However, the availability of geographical data necessary to construct it remains a limitation. Building on the concept of space syntax, we propose an alternative walkability index, space syntax walkability (S...

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Autores principales: Koohsari, Mohammad Javad, Owen, Neville, Cerin, Ester, Giles-Corti, Billie, Sugiyama, Takemi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5122155/
https://www.ncbi.nlm.nih.gov/pubmed/27881173
http://dx.doi.org/10.1186/s12966-016-0448-9
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author Koohsari, Mohammad Javad
Owen, Neville
Cerin, Ester
Giles-Corti, Billie
Sugiyama, Takemi
author_facet Koohsari, Mohammad Javad
Owen, Neville
Cerin, Ester
Giles-Corti, Billie
Sugiyama, Takemi
author_sort Koohsari, Mohammad Javad
collection PubMed
description BACKGROUND: Neighborhood walkability has been shown to be associated with walking behavior. However, the availability of geographical data necessary to construct it remains a limitation. Building on the concept of space syntax, we propose an alternative walkability index, space syntax walkability (SSW). This study examined associations of the full walkability index and SSW with walking for transport (WT). METHODS: Data were collected in 2003–2004 from 2544 adults living in 154 Census Collection Districts (CCD) in Adelaide, Australia. Participants reported past week WT frequency. Full walkability (consisting of net residential density, intersection density, land use mix, and net retail area ratio) and SSW (consisting of gross population density and a space syntax measure of street integration) were calculated for each CCD using geographic information systems and space syntax software. Generalized linear models with negative binomial variance and logarithmic link functions were employed to examine the associations of each walkability index with WT frequency, adjusting for socio-demographic variables. RESULTS: Two walkability indices were closely correlated (ρ = 0.76, p < 0.01). The associations of full walkability and SSW with WT frequency were positive, with regression coefficients of 1.12 (95% CI: 1.08, 1.17) and 1.14 (95% CI: 1.10, 1.19), respectively. CONCLUSIONS: SSW employs readily-available geographic data, yet is comparable to full walkability in its association with WT. The concept and methods of space syntax provide a novel approach to further understanding how urban design influences walking behaviors.
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spelling pubmed-51221552016-11-30 Walkability and walking for transport: characterizing the built environment using space syntax Koohsari, Mohammad Javad Owen, Neville Cerin, Ester Giles-Corti, Billie Sugiyama, Takemi Int J Behav Nutr Phys Act Research BACKGROUND: Neighborhood walkability has been shown to be associated with walking behavior. However, the availability of geographical data necessary to construct it remains a limitation. Building on the concept of space syntax, we propose an alternative walkability index, space syntax walkability (SSW). This study examined associations of the full walkability index and SSW with walking for transport (WT). METHODS: Data were collected in 2003–2004 from 2544 adults living in 154 Census Collection Districts (CCD) in Adelaide, Australia. Participants reported past week WT frequency. Full walkability (consisting of net residential density, intersection density, land use mix, and net retail area ratio) and SSW (consisting of gross population density and a space syntax measure of street integration) were calculated for each CCD using geographic information systems and space syntax software. Generalized linear models with negative binomial variance and logarithmic link functions were employed to examine the associations of each walkability index with WT frequency, adjusting for socio-demographic variables. RESULTS: Two walkability indices were closely correlated (ρ = 0.76, p < 0.01). The associations of full walkability and SSW with WT frequency were positive, with regression coefficients of 1.12 (95% CI: 1.08, 1.17) and 1.14 (95% CI: 1.10, 1.19), respectively. CONCLUSIONS: SSW employs readily-available geographic data, yet is comparable to full walkability in its association with WT. The concept and methods of space syntax provide a novel approach to further understanding how urban design influences walking behaviors. BioMed Central 2016-11-24 /pmc/articles/PMC5122155/ /pubmed/27881173 http://dx.doi.org/10.1186/s12966-016-0448-9 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Koohsari, Mohammad Javad
Owen, Neville
Cerin, Ester
Giles-Corti, Billie
Sugiyama, Takemi
Walkability and walking for transport: characterizing the built environment using space syntax
title Walkability and walking for transport: characterizing the built environment using space syntax
title_full Walkability and walking for transport: characterizing the built environment using space syntax
title_fullStr Walkability and walking for transport: characterizing the built environment using space syntax
title_full_unstemmed Walkability and walking for transport: characterizing the built environment using space syntax
title_short Walkability and walking for transport: characterizing the built environment using space syntax
title_sort walkability and walking for transport: characterizing the built environment using space syntax
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5122155/
https://www.ncbi.nlm.nih.gov/pubmed/27881173
http://dx.doi.org/10.1186/s12966-016-0448-9
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