Research and practice methodA Spatial Agent-Based Model for the Simulation of Adults' Daily Walking Within a City
Introduction
Environmental effects on walking have received increasing attention as a strategy to increase population levels of physical activity.1, 2, 3 Built environment characteristics found to be associated with walking include density of residents, land use mix, features of street design, and aesthetics.1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 Greater safety, less violence, and greater social support for walking have also been found to be positively associated with walking.16, 17, 18, 19
The majority of existing research has applied statistical models to observational data to estimate the associations of environmental characteristics with walking after controls for confounding variables. A limitation of this approach is the inability to completely account for the selection of people into neighborhoods.20, 21 Another important limitation is that statistical models are unable to fully capture the dynamic set of relationships (including feedback loops and dynamic interactions among individuals, among environments, and between individuals and environments) through which environmental and personal attributes interact to shape walking behavior. Because population levels of walking emerge from the functioning of a system with various interacting components, the identification of the possible effects of a given policy or intervention requires understanding of the functioning of the system as a whole.
Agent-based models (ABMs) have received increasing attention as tools to investigate how dynamic processes shape the distribution of health outcomes, including the ways in which physical and social environments contribute to health-related behaviors.22, 23 An ABM is a computational model that can be used to simulate the actions and interactions of agents as well as the dynamic interactions between agents and their environments in order to gain understanding of the functioning of the system.24, 25 These models can be used to investigate the impact of policy alternatives in the presence of nonlinear relationships and feedbacks. ABMs have been used to investigate the transmission of infectious diseases, the determinants of drinking and drug use, and the effects of healthy food availability on diet.22, 26, 27, 28 Although ABMs have been used to study pedestrian movement29, 30, 31, 32 and there have been calls for greater use in the study of environmental effects on walking,33, 34 applications in public health are still scarce.
An exploratory spatial ABM was developed to simulate people's walking behavior within a hypothetic city. The model was calibrated against existing population data. The model was then used to investigate how the spatial patterning of built and social environments (specifically land use and safety as illustrative examples) contributes to social inequalities in walking in the context of residential segregation by SES.
Section snippets
Model Development
The model was developed in Java and Repast. It is a time-discrete model with each time step being 1 day. For parsimony, the model includes adults on working days only (no weekends), seasonal variations and weather are ignored, a public transportation network is not included, and each individual is assumed to have a car.
The model represents a city of 64 km2, comparable in size to the city of Ann Arbor MI. It is an 800×800 grid space, where each cell of size 10 m×10 m can be occupied by a
Model Assessment and Results
Table 2 shows similarities between NHTS data and model predictions for the specific distributional characteristics used in the calibration. As expected from the calibration and the assumption in the model, for both NHTS data and the calibrated model, 35%–40% of people do not walk, most people (>60%) walk no more than three times a week, and only 10%–20% walk more than seven times a week. The distribution of the distances of walking trips is highly skewed for both NHTS and model predictions:
Discussion
By incorporating feedback mechanisms that allowed individuals to alter their walking behaviors in response to their social networks, their own previous experiences, and the prevalence of walking they encountered, this relatively simple model was able to generate patterns of walking behaviors that have been observed in empirical studies. The model allowed for feedbacks over time from both built and social environment features. In addition, walking for one purpose had effects on walking for other
References (47)
- et al.
Understanding environmental influences on walking: review and research agenda
Am J Prev Med
(2004) - et al.
How the built environment affects physical activity views from urban planning
Am J Prev Med
(2002) - et al.
A hierarchy of sociodemographic and environmental correlates of walking and obesity
Prev Med
(2008) - et al.
Environmental factors associated with adults' participation in physical activity: a review
Am J Prev Med
(2002) - et al.
The relative influence of individual, social and physical environment determinants of physical activity
Soc Sci Med
(2002) - et al.
Social epidemiology and complex system dynamic modelling as applied to health behaviour and drug use research
Int J Drug Policy
(2009) - et al.
Extent and correlates of walking in the U.S.
Transp Res Pt D Transp Environ
(2007) - et al.
Prevalence of transportation and leisure walking among U.S. adults
Prev Med
(2008) Angels in the details: comment on “The relationship between destination proximity, destination mix and physical activity behaviors.”
Prev Med
(2008)- et al.
The relationship between destination proximity, destination mix and physical activity behaviors
Prev Med
(2008)
Dog ownership, health and physical activity: a critical review of the literature
Health Place
Environmental correlates of walking and cycling: findings from the transportation, urban design, and planning literatures
Ann Behav Med
Environmental and policy approaches for promoting physical activity in the U.S.: a research agenda
J Phys Act Health
TRB Special Report 282: does the built environment influence physical activity? Examining the Evidence
Health and community design: the impact of the built environment on physical activity
Association of the built environment with physical activity and obesity in older persons
Am J Public Health
Environmental and policy determinants of physical activity in the U.S.
Am J Public Health
The Effectiveness of urban design and and use and transport policies and practices to increase physical activity: a systematic review
J Phys Act Health
Physical activity and environment research in the health field: implications for urban and transportation planning practice and research
J Plann Literature
Environmental correlates of walking and cycling: findings from the transportation, urban design, and planning literatures
Ann Behav Med
Built environment correlates of walking: a review
Med Sci Sports Exerc
Relative influences of individual, social environmental, and physical environmental correlates of walking
Am J Public Health
Cited by (99)
A survey on agents applications in healthcare: Opportunities, challenges and trends
2023, Computer Methods and Programs in BiomedicineNeighbourhoods and oral health: Agent-based modelling of tooth decay
2021, Health and PlaceImpact of built environment on walking in the case of Tehran, Iran
2021, Journal of Transport and HealthThe application of modeling and simulation to public health: Assessing the quality of Agent-Based Models for obesity
2021, Simulation Modelling Practice and Theory