Obesity has grown into a major global epidemic. Rates in the US have doubled since the 1980s, with more than two-thirds of adults now overweight (including more than one third who are obese). These trends are paralleled by rapid growth in childhood obesity, suggesting adult rates may continue to climb for some time even if we take action soon. This epidemic has significant implications for public health, substantially increasing morbidity and mortality for most of the major diseases affecting our citizens. For example, it is estimated that one in three children born today will be diabetic in their lifetime. Health care costs are also affected--costs related to obesity already account for fully 21% of all US medical expenditures, and the overall economic impact of the US obesity epidemic may top $215 billion annually. Unfortunately, obesity is a complex problem involving multiple inter-related contributing factors spanning a wide range of levels of scale (from the social, built, natural and economic environments to behavior, physiology, and epigenetics) and crossing the entire lifecourse. This complexity poses a challenge for traditional methods of study, and for the design of effective interventions. Many scholars now suspect that disappointing results from most obesity prevention interventions to date flow from insufficient attention to this complexity. Three recent Institute of Medicine consensus reports concluded that new approaches were needed, and specifically recommended a “systems approach” and modeling tools drawn from complexity science. This talk will review the data and trends on obesity in US (and globally), and discuss promising approaches for prevention science and policy. It will draw on the presenter’s own research as well as his participation in several Institute of Medicine/National Academy of Sciences studies and in the National Institutes of Health Envision project.