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The Built Environment Predicts Observed Physical Activity

Background: In order to improve our understanding of the relationship between the built environment and physical activity, it is important to identify associations between specific geographic characteristics and physical activity behaviors. Purpose: Examine relationships between observed physical ac...

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Autores principales: Kelly, Cheryl, Wilson, Jeffrey S., Schootman, Mario, Clennin, Morgan, Baker, Elizabeth A., Miller, Douglas K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4033002/
https://www.ncbi.nlm.nih.gov/pubmed/24904916
http://dx.doi.org/10.3389/fpubh.2014.00052
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author Kelly, Cheryl
Wilson, Jeffrey S.
Schootman, Mario
Clennin, Morgan
Baker, Elizabeth A.
Miller, Douglas K.
author_facet Kelly, Cheryl
Wilson, Jeffrey S.
Schootman, Mario
Clennin, Morgan
Baker, Elizabeth A.
Miller, Douglas K.
author_sort Kelly, Cheryl
collection PubMed
description Background: In order to improve our understanding of the relationship between the built environment and physical activity, it is important to identify associations between specific geographic characteristics and physical activity behaviors. Purpose: Examine relationships between observed physical activity behavior and measures of the built environment collected on 291 street segments in Indianapolis and St. Louis. Methods: Street segments were selected using a stratified geographic sampling design to ensure representation of neighborhoods with different land use and socioeconomic characteristics. Characteristics of the built environment on-street segments were audited using two methods: in-person field audits and audits based on interpretation of Google Street View imagery with each method blinded to results from the other. Segments were dichotomized as having a particular characteristic (e.g., sidewalk present or not) based on the two auditing methods separately. Counts of individuals engaged in different forms of physical activity on each segment were assessed using direct observation. Non-parametric statistics were used to compare counts of physically active individuals on each segment with built environment characteristic. Results: Counts of individuals engaged in physical activity were significantly higher on segments with mixed land use or all non-residential land use, and on segments with pedestrian infrastructure (e.g., crosswalks and sidewalks) and public transit. Conclusion: Several micro-level built environment characteristics were associated with physical activity. These data provide support for theories that suggest changing the built environment and related policies may encourage more physical activity.
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spelling pubmed-40330022014-06-05 The Built Environment Predicts Observed Physical Activity Kelly, Cheryl Wilson, Jeffrey S. Schootman, Mario Clennin, Morgan Baker, Elizabeth A. Miller, Douglas K. Front Public Health Public Health Background: In order to improve our understanding of the relationship between the built environment and physical activity, it is important to identify associations between specific geographic characteristics and physical activity behaviors. Purpose: Examine relationships between observed physical activity behavior and measures of the built environment collected on 291 street segments in Indianapolis and St. Louis. Methods: Street segments were selected using a stratified geographic sampling design to ensure representation of neighborhoods with different land use and socioeconomic characteristics. Characteristics of the built environment on-street segments were audited using two methods: in-person field audits and audits based on interpretation of Google Street View imagery with each method blinded to results from the other. Segments were dichotomized as having a particular characteristic (e.g., sidewalk present or not) based on the two auditing methods separately. Counts of individuals engaged in different forms of physical activity on each segment were assessed using direct observation. Non-parametric statistics were used to compare counts of physically active individuals on each segment with built environment characteristic. Results: Counts of individuals engaged in physical activity were significantly higher on segments with mixed land use or all non-residential land use, and on segments with pedestrian infrastructure (e.g., crosswalks and sidewalks) and public transit. Conclusion: Several micro-level built environment characteristics were associated with physical activity. These data provide support for theories that suggest changing the built environment and related policies may encourage more physical activity. Frontiers Media S.A. 2014-05-20 /pmc/articles/PMC4033002/ /pubmed/24904916 http://dx.doi.org/10.3389/fpubh.2014.00052 Text en Copyright © 2014 Kelly, Wilson, Schootman, Clennin, Baker and Miller. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Kelly, Cheryl
Wilson, Jeffrey S.
Schootman, Mario
Clennin, Morgan
Baker, Elizabeth A.
Miller, Douglas K.
The Built Environment Predicts Observed Physical Activity
title The Built Environment Predicts Observed Physical Activity
title_full The Built Environment Predicts Observed Physical Activity
title_fullStr The Built Environment Predicts Observed Physical Activity
title_full_unstemmed The Built Environment Predicts Observed Physical Activity
title_short The Built Environment Predicts Observed Physical Activity
title_sort built environment predicts observed physical activity
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4033002/
https://www.ncbi.nlm.nih.gov/pubmed/24904916
http://dx.doi.org/10.3389/fpubh.2014.00052
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