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The Use of Kernel Density Estimation to Examine Associations between Neighborhood Destination Intensity and Walking and Physical Activity

BACKGROUND: Local destinations have previously been shown to be associated with higher levels of both physical activity and walking, but little is known about how the distribution of destinations is related to activity. Kernel density estimation is a spatial analysis technique that accounts for the...

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Autores principales: King, Tania L., Thornton, Lukar E., Bentley, Rebecca J., Kavanagh, Anne M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4565552/
https://www.ncbi.nlm.nih.gov/pubmed/26355848
http://dx.doi.org/10.1371/journal.pone.0137402
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author King, Tania L.
Thornton, Lukar E.
Bentley, Rebecca J.
Kavanagh, Anne M.
author_facet King, Tania L.
Thornton, Lukar E.
Bentley, Rebecca J.
Kavanagh, Anne M.
author_sort King, Tania L.
collection PubMed
description BACKGROUND: Local destinations have previously been shown to be associated with higher levels of both physical activity and walking, but little is known about how the distribution of destinations is related to activity. Kernel density estimation is a spatial analysis technique that accounts for the location of features relative to each other. Using kernel density estimation, this study sought to investigate whether individuals who live near destinations (shops and service facilities) that are more intensely distributed rather than dispersed: 1) have higher odds of being sufficiently active; 2) engage in more frequent walking for transport and recreation. METHODS: The sample consisted of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Destinations within these areas were geocoded and kernel density estimates of destination intensity were created using kernels of 400m (meters), 800m and 1200m. Using multilevel logistic regression, the association between destination intensity (classified in quintiles Q1(least)—Q5(most)) and likelihood of: 1) being sufficiently active (compared to insufficiently active); 2) walking≥4/week (at least 4 times per week, compared to walking less), was estimated in models that were adjusted for potential confounders. RESULTS: For all kernel distances, there was a significantly greater likelihood of walking≥4/week, among respondents living in areas of greatest destinations intensity compared to areas with least destination intensity: 400m (Q4 OR 1.41 95%CI 1.02–1.96; Q5 OR 1.49 95%CI 1.06–2.09), 800m (Q4 OR 1.55, 95%CI 1.09–2.21; Q5, OR 1.71, 95%CI 1.18–2.48) and 1200m (Q4, OR 1.7, 95%CI 1.18–2.45; Q5, OR 1.86 95%CI 1.28–2.71). There was also evidence of associations between destination intensity and sufficient physical activity, however these associations were markedly attenuated when walking was included in the models. CONCLUSIONS: This study, conducted within urban Melbourne, found that those who lived in areas of greater destination intensity walked more frequently, and showed higher odds of being sufficiently physically active–an effect that was largely explained by levels of walking. The results suggest that increasing the intensity of destinations in areas where they are more dispersed; and or planning neighborhoods with greater destination intensity, may increase residents’ likelihood of being sufficiently active for health.
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spelling pubmed-45655522015-09-18 The Use of Kernel Density Estimation to Examine Associations between Neighborhood Destination Intensity and Walking and Physical Activity King, Tania L. Thornton, Lukar E. Bentley, Rebecca J. Kavanagh, Anne M. PLoS One Research Article BACKGROUND: Local destinations have previously been shown to be associated with higher levels of both physical activity and walking, but little is known about how the distribution of destinations is related to activity. Kernel density estimation is a spatial analysis technique that accounts for the location of features relative to each other. Using kernel density estimation, this study sought to investigate whether individuals who live near destinations (shops and service facilities) that are more intensely distributed rather than dispersed: 1) have higher odds of being sufficiently active; 2) engage in more frequent walking for transport and recreation. METHODS: The sample consisted of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Destinations within these areas were geocoded and kernel density estimates of destination intensity were created using kernels of 400m (meters), 800m and 1200m. Using multilevel logistic regression, the association between destination intensity (classified in quintiles Q1(least)—Q5(most)) and likelihood of: 1) being sufficiently active (compared to insufficiently active); 2) walking≥4/week (at least 4 times per week, compared to walking less), was estimated in models that were adjusted for potential confounders. RESULTS: For all kernel distances, there was a significantly greater likelihood of walking≥4/week, among respondents living in areas of greatest destinations intensity compared to areas with least destination intensity: 400m (Q4 OR 1.41 95%CI 1.02–1.96; Q5 OR 1.49 95%CI 1.06–2.09), 800m (Q4 OR 1.55, 95%CI 1.09–2.21; Q5, OR 1.71, 95%CI 1.18–2.48) and 1200m (Q4, OR 1.7, 95%CI 1.18–2.45; Q5, OR 1.86 95%CI 1.28–2.71). There was also evidence of associations between destination intensity and sufficient physical activity, however these associations were markedly attenuated when walking was included in the models. CONCLUSIONS: This study, conducted within urban Melbourne, found that those who lived in areas of greater destination intensity walked more frequently, and showed higher odds of being sufficiently physically active–an effect that was largely explained by levels of walking. The results suggest that increasing the intensity of destinations in areas where they are more dispersed; and or planning neighborhoods with greater destination intensity, may increase residents’ likelihood of being sufficiently active for health. Public Library of Science 2015-09-10 /pmc/articles/PMC4565552/ /pubmed/26355848 http://dx.doi.org/10.1371/journal.pone.0137402 Text en © 2015 King et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
King, Tania L.
Thornton, Lukar E.
Bentley, Rebecca J.
Kavanagh, Anne M.
The Use of Kernel Density Estimation to Examine Associations between Neighborhood Destination Intensity and Walking and Physical Activity
title The Use of Kernel Density Estimation to Examine Associations between Neighborhood Destination Intensity and Walking and Physical Activity
title_full The Use of Kernel Density Estimation to Examine Associations between Neighborhood Destination Intensity and Walking and Physical Activity
title_fullStr The Use of Kernel Density Estimation to Examine Associations between Neighborhood Destination Intensity and Walking and Physical Activity
title_full_unstemmed The Use of Kernel Density Estimation to Examine Associations between Neighborhood Destination Intensity and Walking and Physical Activity
title_short The Use of Kernel Density Estimation to Examine Associations between Neighborhood Destination Intensity and Walking and Physical Activity
title_sort use of kernel density estimation to examine associations between neighborhood destination intensity and walking and physical activity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4565552/
https://www.ncbi.nlm.nih.gov/pubmed/26355848
http://dx.doi.org/10.1371/journal.pone.0137402
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