To introduce Agent-Based Model (ABM) to physical activity (PA) research and, using data from a study of neighborhood walkability and walking behavior, to illustrate parameters for an ABM of walking behavior.
The concept, brief history, mechanism, major components, key steps, advantages, and limitations of ABM were first introduced. For illustration, 10 participants (age in years: mean = 68, SD = 8) were recruited from a walkable and a nonwalkable neighborhood. They wore AMP 331 triaxial accelerometers and GeoLogger GPA tracking devices for 21 days. Data were analyzed using conventional statistics and highresolution geographic image analysis, which focused on a) path length, b) path duration, c) number of GPS reporting points, and d) interaction between distances and time.
Average steps by subjects ranged from 1810−10,453 steps per day (mean = 6899, SD = 3823). No statistical difference in walking behavior was found between neighborhoods (Walkable = 6710 ± 2781, Nonwalkable = 7096 ± 4674). Three environment parameters (ie, sidewalk, crosswalk, and path) were identified for future ABM simulation.
ABM should provide a better understanding of PA behavior’s interaction with the environment, as illustrated using a real-life example. PA field should take advantage of ABM in future research.
Zhu, McAuley, and Chodzko-Zajko are with the Dept of Kinesiology and Community Health, University of Illinois at Urbana-Champaign. Nedovic-Budic is with the Dept of Geography, Planning, and Environmental Policy, University College Dublin, Belfield, Ireland. Olshansky is with the Dept of Urban and Regional Planning, University of Illinois at Urbana–Champaign. Marti is with ARTIS, LLC, Salt Lake City, Utah. Gao is with the Dept of Kinesiology, Boise State University, Boise, ID. Park is with the Dept of Physical Education, Springfield College, Springfield, MA.