title: Modeling social norms and social influence in obesity.
abstract: The worldwide increase in obesity has led to changes in what is considered "normal" or desirable weight, especially among populations at higher risk. We show that social norms are key to understanding the obesity epidemic, and that social influence mechanisms provide a necessary linkage between individual obesity-related behaviors and population-level characteristics. Because influence mechanisms cannot be directly observed, we show how three complex systems tools may be used to gain insights into observed epidemiologic patterns: social network analysis, agent-based modeling, and systems dynamics modeling. However, simulation and mathematical modeling approaches raise questions regarding acceptance of findings, especially among policy makers. Nevertheless, we point to modeling successes in obesity and other fields, including the NIH-funded National Collaborative on Childhood Obesity Research (NCCOR) Envison project.
authors.affiliation: Department of Public Health Sciences, Loyola University Chicago, Maywood, IL 60153, USA.
authors.forename: David A
authors.initials: DA
authors.lastname: Shoham
authors.affiliation: Center on Social Dynamics and Policy, The Brookings Institution, Washington, DC 20036, USA.
authors.forename: Ross
authors.initials: R
authors.lastname: Hammond
authors.affiliation: Department of Industrial and Systems Engineering, Virginia Tech-Northern Virginia Center, Falls Church, VA 22043, USA.
authors.forename: Hazhir
authors.initials: H
authors.lastname: Rahmandad
authors.affiliation: Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY 14214, USA.
authors.forename: Youfa
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Social System Design Lab, George Warren Brown School of Social Work, Washington University in St. Louis, St. Louis, MO 63130, USA.
authors.forename: Peter
authors.initials: P
authors.lastname: Hovmand
keywords: Social influence; agent-based modeling; health policy; norms; obesity; social epidemiology; social network analysis; system dynamics modeling