Competing definitions of contextual environments

<p>Abstract</p> <p>Background</p> <p>The growing interest in the effects of contextual environments on health outcomes has focused attention on the strengths and weaknesses of alternate contextual unit definitions for use in multilevel analysis. The present research exa...

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Main Authors: Jerrett Michael, Milam Joel E, Wilson John P, Tatalovich Zaria, McConnell Rob
Format: Article
Language:English
Published: BMC 2006-12-01
Series:International Journal of Health Geographics
Online Access:http://www.ij-healthgeographics.com/content/5/1/55
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spelling doaj-0602fcca818a48c4b09c95465af1f93a2020-11-24T22:22:23ZengBMCInternational Journal of Health Geographics1476-072X2006-12-01515510.1186/1476-072X-5-55Competing definitions of contextual environmentsJerrett MichaelMilam Joel EWilson John PTatalovich ZariaMcConnell Rob<p>Abstract</p> <p>Background</p> <p>The growing interest in the effects of contextual environments on health outcomes has focused attention on the strengths and weaknesses of alternate contextual unit definitions for use in multilevel analysis. The present research examined three methods to define contextual units for a sample of children already enrolled in a respiratory health study. The Inclusive Equal Weights Method (M1) and Inclusive Sample Weighted Method (M2) defined communities using the boundaries of the census blocks that incorporated the residences of the CHS participants, except that the former estimated socio-demographic variables by averaging the census block data within each community, while the latter used weighted proportion of CHS participants per block. The Minimum Bounding Rectangle Method (M3) generated minimum bounding rectangles that included 95% of the CHS participants and produced estimates of census variables using the weighted proportion of each block within these rectangles. GIS was used to map the locations of study participants, define the boundaries of the communities where study participants reside, and compute estimates of socio-demographic variables. The sensitivity of census variable estimates to the choice of community boundaries and weights was assessed using standard tests of significance.</p> <p>Results</p> <p>The estimates of contextual variables vary significantly depending on the choice of neighborhood boundaries and weights. The choice of boundaries therefore shapes the community profile and the relationships between its components (variables).</p> <p>Conclusion</p> <p>Multilevel analysis concerned with the effects of contextual environments on health requires careful consideration of what constitutes a contextual unit for a given study sample, because the alternate definitions may have differential impact on the results. The three alternative methods used in this research all carry some subjectivity, which is embedded in the decision as to what constitutes the boundaries of the communities. The Minimum Bounding Rectangle was preferred because it focused attention on the most frequently used spaces and it controlled potential aggregation problems. There is a need to further examine the validity of different methods proposed here. Given that no method is likely to capture the full complexity of human-environment interactions, we would need baseline data describing people's daily activity patterns along with expert knowledge of the area to evaluate our neighborhood units.</p> http://www.ij-healthgeographics.com/content/5/1/55
collection DOAJ
language English
format Article
sources DOAJ
author Jerrett Michael
Milam Joel E
Wilson John P
Tatalovich Zaria
McConnell Rob
spellingShingle Jerrett Michael
Milam Joel E
Wilson John P
Tatalovich Zaria
McConnell Rob
Competing definitions of contextual environments
International Journal of Health Geographics
author_facet Jerrett Michael
Milam Joel E
Wilson John P
Tatalovich Zaria
McConnell Rob
author_sort Jerrett Michael
title Competing definitions of contextual environments
title_short Competing definitions of contextual environments
title_full Competing definitions of contextual environments
title_fullStr Competing definitions of contextual environments
title_full_unstemmed Competing definitions of contextual environments
title_sort competing definitions of contextual environments
publisher BMC
series International Journal of Health Geographics
issn 1476-072X
publishDate 2006-12-01
description <p>Abstract</p> <p>Background</p> <p>The growing interest in the effects of contextual environments on health outcomes has focused attention on the strengths and weaknesses of alternate contextual unit definitions for use in multilevel analysis. The present research examined three methods to define contextual units for a sample of children already enrolled in a respiratory health study. The Inclusive Equal Weights Method (M1) and Inclusive Sample Weighted Method (M2) defined communities using the boundaries of the census blocks that incorporated the residences of the CHS participants, except that the former estimated socio-demographic variables by averaging the census block data within each community, while the latter used weighted proportion of CHS participants per block. The Minimum Bounding Rectangle Method (M3) generated minimum bounding rectangles that included 95% of the CHS participants and produced estimates of census variables using the weighted proportion of each block within these rectangles. GIS was used to map the locations of study participants, define the boundaries of the communities where study participants reside, and compute estimates of socio-demographic variables. The sensitivity of census variable estimates to the choice of community boundaries and weights was assessed using standard tests of significance.</p> <p>Results</p> <p>The estimates of contextual variables vary significantly depending on the choice of neighborhood boundaries and weights. The choice of boundaries therefore shapes the community profile and the relationships between its components (variables).</p> <p>Conclusion</p> <p>Multilevel analysis concerned with the effects of contextual environments on health requires careful consideration of what constitutes a contextual unit for a given study sample, because the alternate definitions may have differential impact on the results. The three alternative methods used in this research all carry some subjectivity, which is embedded in the decision as to what constitutes the boundaries of the communities. The Minimum Bounding Rectangle was preferred because it focused attention on the most frequently used spaces and it controlled potential aggregation problems. There is a need to further examine the validity of different methods proposed here. Given that no method is likely to capture the full complexity of human-environment interactions, we would need baseline data describing people's daily activity patterns along with expert knowledge of the area to evaluate our neighborhood units.</p>
url http://www.ij-healthgeographics.com/content/5/1/55
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