Exploring the emergence and evolution of population patterns of leisure-time physical activity through agent-based modelling.

Diez Roux, Ana V 
Martins, André CR 
Yang, Yong 
Florindo, Alex A 

Thumbnail Image
Change log

INTRODUCTION: Most interventions aiming to promote leisure-time physical activity (LTPA) at population level showed small or null effects. Approaching the problem from a systems science perspective may shed light on the reasons for these results. We developed an agent-based model to explore how the interactions between psychological attributes and built and social environments may lead to the emergence and evolution of LTPA patterns among adults. METHODS: The modeling process consisted of four stages: (1) conceptual model development, (2) formulation of the agent-based model, (3) parametrization and calibration, and (4) consistency and sensitivity analyses. The model represents a stylized community containing two types of agents: persons and LTPA sites. Persons interact with each other (proximal network and perceived community) and with the built environment (LTPA sites) over time. Decision-making is based on the person's intention to practice LTPA, conditioned to the perceived environment. Each iteration is equivalent to one week and we assessed a period of 10 years. RESULTS: The model was able to reproduce population temporal trends of intention and LTPA reported in the literature. Sensitivity analyses indicated that population patterns and trends of intention and LTPA were highly influenced by the relationship between a person's behavior in the preceding week and his current intention, the person's access to built and social environment, and the density of LTPA sites. CONCLUSIONS: The proposed agent-based model is suitable to explore the emergence and evolution of LTPA patterns among adults, considering the dynamic interaction between individuals' psychological attributes and the built and social environments in which they live. The model is available at https://doi.org/10.17605/OSF.IO/J2KAS .

Publication Date
Online Publication Date
Acceptance Date
Agent-based modeling, Complex systems, Computer simulation, Physical activity, Theoretical models, Attitude, Environment Design, Exercise, Health Behavior, Health Promotion, Humans, Intention, Leisure Activities, Social Environment, Systems Analysis
Journal Title
Int J Behav Nutr Phys Act
Journal ISSN
Volume Title
Springer Science and Business Media LLC
Medical Research Council (MR/K023187/1)
Economic and Social Research Council (ES/G007462/1)
LG was supported by a scholarship from the Brazilian Coordination for the Improvement of Higher Education Personnel (grant 1406604). LG has worked under the auspices of the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence which is funded by the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the National Institute for Health Research, and the Wellcome Trust (grant MR/K023187/1). ADR is supported by the Wellcome Trust (grant 205177/Z/16/Z). AAF receives a fellowship from the Brazilian National Council for Scientific and Technological Development (CNPq) (grant 306635/2016-0).