Citation

Blok DJ, van Lenthe FJ, de Vlas SJ. Int. J. Behav. Nutr. Phys. Act. 2018; 15(1): e107.

Affiliation

Department of Public Health, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.

Copyright

(Copyright © 2018, Holtzbrinck Springer Nature Publishing Group - BMC)

DOI

10.1186/s12966-018-0740-y

PMID

30382862

Abstract

BACKGROUND: Income inequalities in sports participation are shaped by a system in which individuals and the environment interact. We developed an agent-based model (ABM) that could represent this system and used it to provide a proof-of-concept of its potential to explore the impact of individual and environmental interventions on reducing inequalities in sports participation.

METHODS: Our ABM simulates sports participation of individuals in the Dutch city of Eindhoven. In the model, sports participation is determined by an individual's tendency to start sports (at a fitness center, sports club or self-organized), which is influenced by attributes of individuals (i.e. age, sex, income), sports facilities (i.e. price, accessibility) and the social environment (i.e. social cohesion, social influence). Sports facilities can adapt to changes in the demand by closures or startups, which in turn influence the tendency of individuals to participate in sport. We explored the impact of five interventions scenarios.

RESULTS: Explorative results show that providing health education, increasing the availability of sports facilities, lowering prices of facilities and improving safety levels can increase sports participation and modestly reduce absolute income inequalities in sports participation. The largest gain can be attained through health education, if the effect and reach is sufficiently large. Environmental interventions alone have a modest impact. Marked effects are only achieved after five to 10 years.

CONCLUSIONS: ABMs have much potential to test the population-level effects of various interventions in the context of a system. Our study highlights the challenges of ABM development and reveals gaps in empirical data. With further refinements, our model could aid in understanding and finding optimal pathways to reduce income inequalities in sports participation.

Language: en

Keywords

Agent-based modeling; Income inequality; Intervention; Sports participation; Systems thinking