Complex systems modeling for obesity research.

TLDR

The obesity epidemic has rapidly become a major public health challenge worldwide, demanding urgent, well‑crafted policy interventions despite its complex, multi‑scale, and diverse nature. This article demonstrates that obesity’s breadth of scale, actor diversity, and multiple mechanisms make it a complex adaptive system, and that complexity science can guide research and policy. It reviews modeling techniques—such as agent‑based, network, and system‑dynamics models—that capture obesity’s rich, complex dynamics and support policy design. The authors conclude that treating obesity as a complex adaptive system enables the application of complexity‑science methods to better understand the epidemic and develop more effective interventions.

Abstract

The obesity epidemic has grown rapidly into a major public health challenge, in the United States and worldwide. The scope and scale of the obesity epidemic motivate an urgent need for well-crafted policy interventions to prevent further spread and (potentially) to reverse the epidemic. Yet several attributes of the epidemic make it an especially challenging problem both to study and to combat. This article shows that these attributes--the great breadth in levels of scale involved, the substantial diversity of relevant actors, and the multiplicity of mechanisms implicated--are characteristic of a complex adaptive system. It argues that the obesity epidemic is driven by such a system and that lessons and techniques from the field of complexity science can help inform both scientific study of obesity and effective policies to combat obesity. The article gives an overview of modeling techniques especially well suited to study the rich and complex dynamics of obesity and to inform policy design.