Residential neighborhood features associated with objectively measured walking near home: Revisiting walkability using the Automatic Context Measurement Tool (ACMT). (May 2020) - Mooney, Stephen J.; Hurvitz, Philip M.; Moudon, Anne Vernez; Zhou, Chuan; Dalmat, Ronit; Saelens, Brian E.
Abstract: Many distinct characteristics of the social, natural, and built neighborhood environment have been included in walkability measures, and it is unclear which measures best describe the features of a place that support walking. We developed the Automatic Context Measurement Tool, which measures neighborhood environment characteristics from public data for any point location in the United States. We explored these characteristics in home neighborhood environments in relation to walking identified from integrated GPS, accelerometer, and travel log data from 681 residents of King Country, WA. Of 146 neighborhood characteristics, 92 (63%) were associated with walking bout counts after adjustment for individual characteristics and correction for false discovery. The strongest built environment predictor of walking bout count was housing unit count. Models using data-driven and a priori defined walkability measures exhibited similar fit statistics. Walkability measures consisting of different neighborhood characteristic measurements may capture the same underlying variation in neighborhood conditions. Highlights: We assessed neighborhood predictors of walking bouts in King County, WA. 92 of 146 neighborhood measures predicted frequency of walking bouts. Housing unit count was the strongest predictor of walking. The Automatic Context Measurement Tool promotes replicable research. ACMT code is available at https://github.com/smooney27/ACMT