Kang, Bumjoon; Moudon, Anne V.; Hurvitz, Philip M.; Saelens, Brian E. (2017). Differences in Behavior, Time, Location, and Built Environment between Objectively Measured Utilitarian and Recreational Walking. Transportation Research: Part D, 57, 185 – 194.
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Abstract
Objectives: Utilitarian and recreational walking both contribute to physical activity. Yet walking for these two purposes may be different behaviors. We sought to provide operational definitions of utilitarian and recreational walking and to objectively measure their behavioral, spatial, and temporal differences in order to inform transportation and public health policies and interventions. Methods: Data were collected 2008-2009 from 651 Seattle-King County residents, wearing an accelerometer and a GPS unit, and filling-in a travel diary for 7 days. Walking activity bouts were classified as utilitarian or recreational based on whether walking had a destination or not. Differences between the two walking purposes were analyzed, adjusting for the nested structure of walking activity within participants. Results: Of the 4905 observed walking bouts, 87.4% were utilitarian and 12.6% recreational walking. Utilitarian walking bouts were 45% shorter in duration (-12.1 min) and 9% faster in speed (+0.3 km/h) than recreational walking bouts. Recreational walking occurred more frequently in the home neighborhood and was not associated with recreational land uses. Utilitarian walking occurred in areas having higher residential, employment, and street density, lower residential property value, higher area percentage of mixed-use neighborhood destinations, lower percentage of parks/trails, and lower average topographic slope than recreational walking. Conclusion: Utilitarian and recreational walking are substantially different in terms of frequency, speed, duration, location, and related built environment. Policies that promote walking should adopt type-specific strategies. The high occurrence of recreational walking near home highlights the importance of the home neighborhood for this activity.
Keywords
Walking; Utilitarianism; Recreation; Behavioral Assessment; Built Environment; Physical Activity Measurement; Accelerometer; Active Transportation; Gps; Home And Non-home Based Walking; Pedestrian; Physical-activity; Us Adults; Accelerometer Data; Trip Purpose; Urban Form; Travel; Neighborhood; Distance; System
Kang, Mingyu; Moudon, Anne Vernez; Kim, Haena; Boyle, Linda Ng. (2019). Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS. International Journal Of Environmental Research And Public Health, 16(19).
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Abstract
Intersection and non-intersection locations are commonly used as spatial units of analysis for modeling pedestrian crashes. While both location types have been previously studied, comparing results is difficult given the different data and methods used to identify crash-risk locations. In this study, a systematic and replicable protocol was developed in GIS (Geographic Information System) to create a consistent spatial unit of analysis for use in pedestrian crash modelling. Four publicly accessible datasets were used to identify unique intersection and non-intersection locations: Roadway intersection points, roadway lanes, legal speed limits, and pedestrian crash records. Two algorithms were developed and tested using five search radii (ranging from 20 to 100 m) to assess the protocol reliability. The algorithms, which were designed to identify crash-risk locations at intersection and non-intersection areas detected 87.2% of the pedestrian crash locations (r: 20 m). Agreement rates between algorithm results and the crash data were 94.1% for intersection and 98.0% for non-intersection locations, respectively. The buffer size of 20 m generally showed the highest performance in the analyses. The present protocol offered an efficient and reliable method to create spatial analysis units for pedestrian crash modeling. It provided researchers a cost-effective method to identify unique intersection and non-intersection locations. Additional search radii should be tested in future studies to refine the capture of crash-risk locations.
Keywords
Traffic Crash; Walking; Collisions; Accidents; Models; Pedestrian Safety; Spatial Autocorrelation; Algorithm
Duncan, Glen E.; Hurvitz, Philip M.; Moudon, Anne Vernez; Avery, Ally R.; Tsang, Siny. (2021). Measurement of Neighborhood-Based Physical Activity Bouts. Health & Place, 70.
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Abstract
This study examined how buffer type (shape), size, and the allocation of activity bouts inside buffers that delineate the neighborhood spatially produce different estimates of neighborhood-based physical activity. A sample of 375 adults wore a global positioning system (GPS) data logger and accelerometer over 2 weeks under free-living conditions. Analytically, the amount of neighborhood physical activity measured objectively varies substantially, not only due to buffer shape and size, but by how GPS-based activity bouts are identified with respect to containment within neighborhood buffers. To move the neighborhood-effects literature forward, it is critical to delineate the spatial extent of the neighborhood, given how different ways of measuring GPS-based activity containment will result in different levels of physical activity across different buffer types and sizes.
Keywords
Built Environment; Walking; Home; Accelerometry; Geographic Information Systems; Gps; Neighborhood; Physical Activity
The Urban Form Lab (UFL) research aims to affect policy and to support approaches to the design and planning of more livable environments. The UFL specializes in geospatial analyses of the built environment using multiple micro-scale data in Geographic Information Systems (GIS). Current research includes the development of novel GIS routines for performing spatial inventories and analyses of the built environment, and of spatially explicit sampling techniques. Projects address such topics as land monitoring, neighborhood and street design, active transportation, non-motorized transportation safety, physical activity, and access to food environments.
Research at the UFL has been supported by the U.S. and Washington State Departments of Transportation, the Centers for Disease Control and Prevention, the Robert Wood Johnson Foundation, the National Institutes of Health, and local agencies.
The Urban Form Lab is directed by Anne Vernez Moudon, Dr es Sc, a leading researcher and educator in quantifying the properties of the built environment as related to health and transportation behaviors. Philip M. Hurvitz, PhD, a veteran of geographic information science and data processing, leads data management and GIS work.
The Urban@UW initiative brings together labs that study urban issues from across the University of Washington. Urban@UW works with scholars, policymakers, and community stakeholders in order to strengthen the connection between research and solutions to urban issues through cross-disciplinary and cross-sector collaborative research. Key functions of Urban@UW include amplifying public awareness of ongoing projects, connecting researchers with outside constituencies, providing staff and administrative support services, and providing pilot funding and fundraising assistance. Multiple BE labs are involved, including the Northwest…
The University of Washington Data Collaborative (UWDC) is now offering services to researchers across campus, including BE researchers Gregg Colburn at the Runstad Department of Real Estate and the Urban Form Lab. Housed at the Center for Studies in Demography & Ecology, UWDC provides infrastructure to access restricted data in a secure and sophisticated computing environment. Data sets available to researchers cover health records, polling data, business and consumer data, and real estate data. Researchers interested in accessing these data…