There has been an explosion of interest in how features of the social and built environments of communities affect the physical activity of residents. Because of the relevance of walking as a component of physical activity, and the possibility of increasing population-levels of physical activity by increasing walking in daily life, the study of the environmental determinants of walking has received special attention. Studies have documented associations of walking with environmental features such as land use mix and proximity of destinations, street connectivity and presence of sidewalks, aesthetic and design features of the environment, and safety and violence levels. However, important questions remain regarding the policy implications of this work. A major challenge is the need to account for the multiple dynamic relations between individuals (e.g. the behavior of one individual affecting those of others around him or her), between individuals and their environments (e.g. the environment changing in response to the behaviors of individuals and vice versa), and between environments (e.g. street connectivity affecting levels of safety). Accounting for these dynamic relationships is fundamental to understanding how environmental factors operate and to identifying plausible effects of various policies. Systems science methodologies (including agent-based models or ABMs) have received increasing attention as a way to better capture the complex set of dynamic relationships inherent in population health problems, but few applications to specific research problems exist. The overall goal of this proposal is to develop a generic agent-based model (ABM) of people's walking behavior within a hypothetical city. This model will be used to enhance scientific understanding of the ways in which environmental factors affect population-levels of walking and socioeconomic inequalities in walking.
The Specific Aims are: (1) To build a generic agent-based model to simulate people's walking behavior within a hypothetical city;(2) To use the proposed model to specifically investigate how mixed land use and safety could contribute to population- levels of walking and to socioeconomic inequalities in walking;and (3) To explore the feasibility (including data availability and new data needs) of making the model reflect a real city. This proposal will apply novel systems methodologies to a policy resistant population health problem and will generate one of the first exemplars of applications of this approach in population health. It will develop a generic model useful for understanding dynamics that operate across cities and will lay the ground work for further development of more realistic models specific to real cities. The systems approach we propose has great potential for improving our understanding of the environmental determinants of walking which will be crucial to identifying relevant policies and anticipating their effects in future research. The development of these models represents a paradigm change in the way evidence is used to select and support interventions and policies to prevent major chronic conditions, including cardiovascular disease and cancer.

Public Health Relevance

This project will develop a generic spatial agent-based model of the determinants of population-levels of walking behavior in a city. The model can be used to better understand the dynamic ways in which environmental features affect walking and identify the plausible impacts of different types of interventions. This basic model will lay the groundwork for the development of more realistic models specific to a given city. The use of these modeling approaches could have major implications for the types of evidence that are used to make policy decisions and for the ways in which the possible impact of public health interventions and policies is assessed.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21HL106467-01A1
Application #
8192385
Study Section
Special Emphasis Panel (ZRG1-HDM-Q (50))
Program Officer
Pratt, Charlotte
Project Start
2011-08-18
Project End
2013-07-31
Budget Start
2011-08-18
Budget End
2012-07-31
Support Year
1
Fiscal Year
2011
Total Cost
$194,375
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Yang, Yong (2016) A dynamic framework on travel mode choice focusing on utilitarian walking based on the integration of current knowledge. J Transp Health 3:336-345
Yang, Yong; Auchincloss, Amy H; Rodriguez, Daniel A et al. (2015) Modeling spatial segregation and travel cost influences on utilitarian walking: Towards policy intervention. Comput Environ Urban Syst 51:59-69
Yang, Yong (2015) Interactions between psychological and environmental characteristics and their impacts on walking. J Transp Health 2:195-198
Yang, Yong; Diez-Roux, Ana; Evenson, Kelly R et al. (2014) Examining the impact of the walking school bus with an agent-based model. Am J Public Health 104:1196-203
Yang, Yong; Diez-Roux, Ana V (2013) Using an agent-based model to simulate children's active travel to school. Int J Behav Nutr Phys Act 10:67
Yang, Yong; Diez-Roux, Ana V (2012) Walking distance by trip purpose and population subgroups. Am J Prev Med 43:11-9
Yang, Yong; Diez Roux, Ana V; Auchincloss, Amy H et al. (2012) Exploring walking differences by socioeconomic status using a spatial agent-based model. Health Place 18:96-9
Yang, Yong; Atkinson, Peter M; Ettema, Dick (2011) Analysis of CDC social control measures using an agent-based simulation of an influenza epidemic in a city. BMC Infect Dis 11:199
Yang, Yong; Diez Roux, Ana V; Bingham, C Raymond (2011) Variability and seasonality of active transportation in USA: evidence from the 2001 NHTS. Int J Behav Nutr Phys Act 8:96
Yang, Yong; Diez Roux, Ana V; Auchincloss, Amy H et al. (2011) A spatial agent-based model for the simulation of adults' daily walking within a city. Am J Prev Med 40:353-61