| Summary: | Walk Score® is a proprietary walkability metric that ranks locations by proximity to destinations, with emerging health promotion applications for increasing walking as physical activity. Currently, field validations of Walk Score® have only occurred in metropolitan regions of the United States; moreover, many studies employ an earlier Walk Score® version utilizing straight line distance. To address this gap, we conducted a field validation of the newest, network-based metric for three municipal types along a rural-urban continuum in Alberta, Canada. In 2015, using street-level systematic observations collected in Bonnyville, Medicine Hat, and North Central Edmonton in 2008 (part of the Community Health and the Built Environment (CHBE) project), we reverse engineered 2181 scores with the network Walk Score® algorithm. We computed means, 95% confidence intervals, and t-tests (α = 0.05) for both sets of scores. Applying the Clifford-Richardson adjustment for spatial autocorrelation, we calculated Spearman's Rank Correlation Coefficients (rho, rs) and adjusted p-values to measure the strength of association between the derived scores and original network scores provided by Walk Score®. Spearman's rho for scores were very high for Bonnyville (rs = 0.950, adjusted p < 0.001), and high for Medicine Hat (rs = 0.790, adjusted p < 0.001) and North Central Edmonton (rs = 0.763, adjusted p < 0.001). High to very high correlations between derived scores and Walk Scores® field validated this metric across small, medium, and large population centres in Alberta, Canada. However, we suggest caution in interpreting Walk Score® for planning and evaluating health promotion interventions, since the strength of association between destinations and walking may vary across different municipal types. Keywords: Chronic disease, Geographic mapping, Health promotion, Validation studies, Walking
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