A Multi-scale Paradigm to Design Policy Options for Obesity Prevention: Exploring the Integration of Individual-Based Modeling and System Dynamics.
Year: 2011
Type: article
Abstract: Complex adaptive systems-of-systems are inherently multi-scale across several dimensions, including temporal, geographical, and organizational. We present a multi-model paradigm integrating a community-scale individual-based model (IBM) to investigate the immediate effects of interventions with a population-scale system dynamics (SD) model to analyze longterm results of those interventions. The IBM incorporates actors embedded in a social network to simulate the spread of opinions relating to nutrition and physical activity (N&PA) behaviors such as dieting and exercise, and the effects of these opinions on individual actions and consequential body weights. The IBM network structure is composed of a mixture of scale-free and uniformly random connections to represent a social network of relationships and interactions within a community: opinions regarding obesogenic behaviors propagate among individuals on the network, or are influenced by media sources via advertising, public health campaigns, and counter-marketing. We analyze and compare effects of possible policy interventions, and illustrate a policy cocktail that addresses multiple aspects of the obesity problem, resulting in amplification of desirable results and a strong uncertainty reduction. The outputs of the IBM, seen as changes in obesogenic behaviors, are used by the SD model to calculate the resulting changes in mortality and morbidity over ensuing decades.
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2345763983