The systems approach has a nearly 50-year history since its development by Forrester at the Massachusetts Institute of Technology (Forrester, 1991). Increasingly, obesity scholars are looking to other disciplines, from biology to psychology to computer sciences and engineering, that use this approach. In the health arena, the approach has been used to elucidate seemingly intractable problems, including cardiovascular disease (Homer et al., 2004), diabetes (Milstein et al., 2007), mental health (Smith et al., 2004), public health emergencies (Hoard et al., 2005), and tobacco control (National Cancer Institute, 2007).
The complex issue of obesity lends itself to a systems approach quite well. Like tobacco control, which employed diverse and multilevel strategies (Abrams et al., 2003, 2010), progress in the obesity field will require a paradigm shift toward an interdisciplinary knowledge base that integrates systems theory with concepts and practice from community development, social ecology, social networks, and public health (Best et al., 2003).
This chapter explains how systems thinking expands upon the multilevel, multisector strategies already proposed or in use to prevent obesity. It provides a primer on the concepts of such thinking and examines how the systems approach can be applied to identify the determinants, strategies, and actions that must be considered to address the obesity crisis. The chapter provides several practical examples of how systems thinking can be used in both small and large ways to expand the boundaries of current models and advance effective change in public health. The chapter also links the systems approach and its application to the L.E.A.D. framework (Figure 4-1), describing how it enhances the ability to generate, use, and learn from evidence and explaining how specific content pertaining to each step of the framework will differ according to the system on which one is focusing. Box 4-1 defines the key systems concepts pertinent to the discussion.
As explained in Chapter 2, multilevel, multisector strategies, often based on ecological models (e.g., Figure 1-5 in Chapter 1),1 have gained widespread acceptance for understanding the determinants of obesity and for framing prevention and control activities (Glass and McAtee, 2006). While these models acknowledge the multiple levels of a system and show their interrelationships, however, they may not always be complex enough to capture the dynamic interactions and the short- and long-term feedback loops among the many influences on the energy balance (Foresight, 2007; Sterman, 2006). Systems investigation can complement other methods by capturing this complexity, translating it into actions that can have an impact on the obesity problem and making it possible to predict unintended consequences and time-delayed effects (Mabry et al., 2008).