Brief report
Walk Score™ As a Global Estimate of Neighborhood Walkability

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Background

Walk Score recently has been demonstrated as a valid and reliable tool for estimating access to nearby facilities, a critical component of the physical activity environment. It has not yet been determined whether Walk Score relates to other critical components of the physical activity environment, including street connectivity, access to public transit, residential density, and crime.

Purpose

The aim of this study was to explore the relationship between Walk Score and objective/subjective measures of the physical activity environment.

Methods

Walk Scores were calculated for residential addresses of 296 participants of two RCTs (2006–2009). Street connectivity, residential density, access to public transit provisions, and crime were objectively measured (GIS) and cross-referenced with Walk Scores and participant's perceptions of the environment (e.g., perceived crime, access to physical activity facilities, perceived neighborhood walkability). Pairwise Pearson correlations were calculated in March 2010 to compare Walk Score to subjective/objective measures of neighborhood walkability.

Results

Significant positive correlations were identified between Walk Score and several objective (e.g., street connectivity, residential density and access to public transit provisions) and subjective (e.g., summed score of the physical activity environment) measures of the physical activity environment. However, positive correlations also were observed between Walk Score and crime.

Conclusions

Collectively, these findings support Walk Score as a free, easy-to-use, and quick proxy of neighborhood density and access to nearby amenities. However, positive associations between Walk Score and reported crime highlight a limitation of Walk Score and warrant caution of its use.

Introduction

Increasing physical activity is one of the largest public health concerns of the 21st century.1 Growing research suggests that physical activity may be influenced by the built (e.g., access to amenities,2 residential density,3, 4 land-use diversity,4, 5 street connectivity,5 access to public transit) and social (e.g., safety6) environment. Further, evidence3, 5 suggests physical activity levels are higher among residents of supportive physical activity–friendly environments.

To further explore the impact of the environment on physical activity, it is necessary to equip researchers with adequate measurement tools. Current measures rely primarily on costly and time-intensive observational measures,7 self-report measures suffering from limited construct validity,8 and objective measures including GIS analyses that require specific expertise and can be difficult to access.

Recently, Walk Score™ (www.walkscore.com), a publicly available website, was found9 to be valid and reliable for estimating access to nearby walkable amenities.

Walk Score uses data provided by the Google™ AJAX Search application program interface (API)10 along with a geography-based algorithm to identify nearby areas and calculate a score of “walkability.” The Walk Score algorithm calculates a score of walkability based on distance to 13 categories of amenities (e.g., grocery stores, coffee shops, restaurants, bars, movie theaters, schools, parks, libraries, bookstores, fitness centers, drugstores, hardware stores, clothing/music stores). Each category is weighted equally and points are summed and normalized to yield a score of 0–100.

Although valid and reliable for measuring access to amenities, it is unknown whether Walk Score relates to other critical components of the physical activity environment. Likewise, it is unknown how Walk Score relates to individual perceptions of the physical activity environment. Therefore, the aims of the present study are to examine the relationship between Walk Score and multiple objective and subjective measures of the physical activity environment among a sample of 296 sedentary adults.

Section snippets

Methods

A convenience sample of 296 participants of one of two RCTs conducted in Rhode Island between September 2006 and July 2009 were included.11 Participants authorized the use of their residential addresses for spatial analyses, and research protocols were approved by each study's IRB (i.e., Brown University and The Miriam Hospital).

GIS data were analyzed using ESRI's ArcGIS suite, version 9.3. Prior to analysis, addresses were geocoded and an address locator was created based on the 2005 Rhode

Results

The M±SD Walk Score of the 296 addresses was 50.9±24.9, and scores were widespread ranging from 0 to 94. Strong and significant correlations were observed between Walk Score and all objective measures of the physical activity environment assessed, including intersection density (0.81, p<0.001); street density (0.74, p<0.001); average block length (–0.32, p<0.001); residential density (0.76, p<0.001); and access to public transit (0.52, p<0.001). However, positive correlations also were observed

Discussion

The present findings indicate Walk Score significantly correlates with multiple objective measures of the physical activity environment, including measures of street connectivity, residential density, and access to public transit. These findings support Walk Score as a quick, free, and easy-to-use proxy of neighborhood density and access to nearby destinations. Walk Score quickly calculates walkability scores addressing the time-sensitive limitations of previous measures of the physical

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