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The Wisconsin Assessment of the Social and Built Environment (WASABE): a multi-dimensional objective audit instrument for examining neighborhood effects on health.

Malecki KC, Engelman CD, Peppard PE, Nieto FJ, Grabow ML, Bernardinello M, Bailey E, Bersch AJ, Walsh MC, Lo JY, Martinez-Donate A - BMC Public Health (2014)

Bottom Line: Growing evidence suggests that mixed methods approaches to measuring neighborhood effects on health are needed.Sidewalk density in neighborhoods surrounding households of participants living at less than 100% of the poverty level was 67% (95% confidence interval, 55-80%) compared to 34% (25-44%) for those living at greater than 400% of the poverty level.Findings illustrate the complex milieu of built environment features found in participants neighborhoods and have relevance for future research, policy, and community engagement purposes.

View Article: PubMed Central - PubMed

Affiliation: Department of Population Health Sciences, University of Wisconsin-Madison School of Medicine and Public Health, 610 N, Walnut Street, Madison WI 53726, USA. kmalecki@wisc.edu.

ABSTRACT

Background: Growing evidence suggests that mixed methods approaches to measuring neighborhood effects on health are needed. The Wisconsin Assessment of the Social and Built Environment (WASABE) is an objective audit tool designed as an addition to a statewide household-based health examination survey, the Survey of the Health of Wisconsin (SHOW), to objectively measure participant's neighborhoods.

Methods: This paper describes the development and implementation of the WASABE and examines the instrument's ability to capture a range of social and built environment features in urban and rural communities. A systematic literature review and formative research were used to create the tool. Inter-rater reliability parameters across items were calculated. Prevalence and density of features were estimated for strata formed according to several sociodemographic and urbanicity factors.

Results: The tool is highly reliable with over 81% of 115 derived items having percent agreement above 95%. It captured variance in neighborhood features in for a diverse sample of SHOW participants. Sidewalk density in neighborhoods surrounding households of participants living at less than 100% of the poverty level was 67% (95% confidence interval, 55-80%) compared to 34% (25-44%) for those living at greater than 400% of the poverty level. Walking and biking trails were present in 29% (19-39%) of participant buffer in urban areas compared to only 7% (2-12%) in rural communities. Significant environmental differences were also observed for white versus non-white, high versus low income, and college graduates versus individuals with lower level of education.

Conclusions: The WASABE has strong inter-rater reliability and validity properties. It builds on previous work to provide a rigorous and standardized method for systematically gathering objective built and social environmental data in a number of geographic settings. Findings illustrate the complex milieu of built environment features found in participants neighborhoods and have relevance for future research, policy, and community engagement purposes.

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Example of a 400-meter non-Euclidian street-network buffer for measuring neighborhood environment around select- participant household.
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Fig1: Example of a 400-meter non-Euclidian street-network buffer for measuring neighborhood environment around select- participant household.

Mentions: In order to define “neighborhood” environments, ArcGIS Network Analyst (ESRI, Redwood, CA) was used to define a 400-meter (about a quarter of a mile) non-Euclidian street network buffer around each selected household. This distance (equivalent of a 5–10 minute walk) was chosen because previous studies on “walkability” have found it to be the upper limit of the distance individuals are generally willing to walk to procure a service [28, 48, 54]. The resulting street network polygon includes a representation of the routes pedestrians and cyclists normally rely on for travel around each household (see Figure 1) [48, 54]. Within polygons, units of analyses were defined as street segments and intersections. The distance between two intersections, or from one intersection to the edge of the polygon boundary, was termed a segment. Segment lengths were set at a maximum of 400 meters (common in more rural areas) and minimum of 6 meters. Intersections were defined as a point from which an observer, pedestrian, or driver has to choose between two or more different directions to continue walking and/or driving (excluding driveways).Figure 1


The Wisconsin Assessment of the Social and Built Environment (WASABE): a multi-dimensional objective audit instrument for examining neighborhood effects on health.

Malecki KC, Engelman CD, Peppard PE, Nieto FJ, Grabow ML, Bernardinello M, Bailey E, Bersch AJ, Walsh MC, Lo JY, Martinez-Donate A - BMC Public Health (2014)

Example of a 400-meter non-Euclidian street-network buffer for measuring neighborhood environment around select- participant household.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4289353&req=5

Fig1: Example of a 400-meter non-Euclidian street-network buffer for measuring neighborhood environment around select- participant household.
Mentions: In order to define “neighborhood” environments, ArcGIS Network Analyst (ESRI, Redwood, CA) was used to define a 400-meter (about a quarter of a mile) non-Euclidian street network buffer around each selected household. This distance (equivalent of a 5–10 minute walk) was chosen because previous studies on “walkability” have found it to be the upper limit of the distance individuals are generally willing to walk to procure a service [28, 48, 54]. The resulting street network polygon includes a representation of the routes pedestrians and cyclists normally rely on for travel around each household (see Figure 1) [48, 54]. Within polygons, units of analyses were defined as street segments and intersections. The distance between two intersections, or from one intersection to the edge of the polygon boundary, was termed a segment. Segment lengths were set at a maximum of 400 meters (common in more rural areas) and minimum of 6 meters. Intersections were defined as a point from which an observer, pedestrian, or driver has to choose between two or more different directions to continue walking and/or driving (excluding driveways).Figure 1

Bottom Line: Growing evidence suggests that mixed methods approaches to measuring neighborhood effects on health are needed.Sidewalk density in neighborhoods surrounding households of participants living at less than 100% of the poverty level was 67% (95% confidence interval, 55-80%) compared to 34% (25-44%) for those living at greater than 400% of the poverty level.Findings illustrate the complex milieu of built environment features found in participants neighborhoods and have relevance for future research, policy, and community engagement purposes.

View Article: PubMed Central - PubMed

Affiliation: Department of Population Health Sciences, University of Wisconsin-Madison School of Medicine and Public Health, 610 N, Walnut Street, Madison WI 53726, USA. kmalecki@wisc.edu.

ABSTRACT

Background: Growing evidence suggests that mixed methods approaches to measuring neighborhood effects on health are needed. The Wisconsin Assessment of the Social and Built Environment (WASABE) is an objective audit tool designed as an addition to a statewide household-based health examination survey, the Survey of the Health of Wisconsin (SHOW), to objectively measure participant's neighborhoods.

Methods: This paper describes the development and implementation of the WASABE and examines the instrument's ability to capture a range of social and built environment features in urban and rural communities. A systematic literature review and formative research were used to create the tool. Inter-rater reliability parameters across items were calculated. Prevalence and density of features were estimated for strata formed according to several sociodemographic and urbanicity factors.

Results: The tool is highly reliable with over 81% of 115 derived items having percent agreement above 95%. It captured variance in neighborhood features in for a diverse sample of SHOW participants. Sidewalk density in neighborhoods surrounding households of participants living at less than 100% of the poverty level was 67% (95% confidence interval, 55-80%) compared to 34% (25-44%) for those living at greater than 400% of the poverty level. Walking and biking trails were present in 29% (19-39%) of participant buffer in urban areas compared to only 7% (2-12%) in rural communities. Significant environmental differences were also observed for white versus non-white, high versus low income, and college graduates versus individuals with lower level of education.

Conclusions: The WASABE has strong inter-rater reliability and validity properties. It builds on previous work to provide a rigorous and standardized method for systematically gathering objective built and social environmental data in a number of geographic settings. Findings illustrate the complex milieu of built environment features found in participants neighborhoods and have relevance for future research, policy, and community engagement purposes.

Show MeSH