Agent-Based Modeling of Physical Activity Behavior and Environmental Correlations: An Introduction and Illustration

Authored by Zorica Nedovic-Budic, Robert B. Olshansky, Yong Gao, Youngsik Park, Edward McAuley, Wojciech Chodzko-Zajko

Date Published: 2013-03

Sponsors: Robert Wood Johnson Foundation

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

Purpose: 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. Method: 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 high-resolution 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. Results: 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. Conclusion: 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.

Tags

environment GPS mapping statistical modeling