摘要：Obesity is associated with a prolonged imbalance between energy intake and expenditure, both of which are regulated by multiple feedback processes within and across individuals. These processes constitute 3 hierarchical control systems—homeostatic, hedonic, and cognitive—with extensive interaction among them. Understanding complex eating behavior requires consideration of all 3 systems and their interactions. Existing models of these processes are widely scattered, with relatively few attempts to integrate across mechanisms. We briefly review available empirical evidence and dynamic models, discussing challenges and potential for better integration. We conclude that developing richer models of dynamic interplay among systems should be a priority in the future study of obesity and that systems science modeling offers the potential to aid in this goal. The worldwide obesity epidemic is characterized by a gradual increase in mean body weight of the population over a time scale of decades. 1 At its most basic level, development of obesity occurs when intake of calories exceeds the calories expended to maintain life and perform physical work. 2 This statement should not be confused with an explanation of obesity because it is merely a reiteration of the first law of thermodynamics, also known as the principle of energy balance. Nevertheless, the energy balance framework provides a useful way to evaluate the relative contribution of the multiple interacting components of energy intake and expenditure and their contribution to body weight change. 3 Energy intake and expenditure, the core components of energy balance, are regulated by a series of feedback processes within and across individuals, and influenced by environmental, economic, and social drivers. Increased mechanization and the transition from energetically expensive to more sedentary occupations have certainly resulted in decreased individual energy needs and may have contributed to obesity epidemic. 4 However, many of these occupational changes began to take place long before the onset of the obesity epidemic and the per capita food availability correspondingly decreased in the early part of the 20th century. 1 These observations, along with little direct evidence of decreased physical activity from the late 1970s, suggest that increased food intake is likely to be the primary driver of obesity. 1,5–7 We therefore focus our discussion on the feedback mechanisms regulating food intake. Great progress has been achieved in the past decade delineating the molecular mechanisms and the powerful homeostatic physiology that helps regulate food intake. 8 These homeostatic feedback control circuits—sufficient for body weight regulation over the course of most of human history—are likely still functioning perfectly normally, but have been recently overwhelmed by a changing food environment that frequently activates 2 other major processes—hedonic feedback and cognitive feedback. Actual food intake in humans is governed by the interaction and joint function of these 3 hierarchical control systems “below the skin,” 9,10 any of which may be affected by environmental, economic, and social contextual factors “above the skin.” The determinants of obesity are widely recognized to be complex, including important factors across multiple levels of scale. 11,12 In this article, we argue that quantitative frameworks integrating the neurobiological feedback mechanisms through which many of these factors are processed is likely to yield important new insights for understanding obesity and assessing alternative interventions and policies. Although the concept of energy balance lies at the heart of most quantitative models of weight change, the existing work on modeling the feedback processes governing food intake and energy expenditure is widely scattered and there are relatively few attempts to integrate across mechanisms. We will briefly review available empirical evidence and dynamic models for each of these systems (including research conducted as part of the National Collaborative on Childhood Obesity Research Envision network), and will discuss the challenges and potential for computational modeling and “systems science” to facilitate better integration across multiple feedback systems.
