Finegood Diane T, Karanfil Ozge, Matteson Carrie L
School of Kinesiology, Simon Fraser University, Canada.
Healthc Pap. 2008;9(1):36-41; discussion 62-67. doi: 10.12927/hcpap.2008.20184.
Public policy aimed at reducing obesity is just one of many avenues that must be pursued to address the still-growing obesity pandemic. The complexity of the problem is illustrated in ecological frameworks and system maps of the determinants. These conceptual maps illustrate the complexity by acknowledging the influence of many different factors such as social norms and values; sectors of influence such as the food and beverage industries, media and transportation; behavioural settings including home and family, school and community; and individual factors such as genetics, psychosocial and other personal elements. But to solve such a complex problem, we need to move from an analysis of the determinants or causes of the problem to a solution orientation; the frameworks used to describe the problem may not be the right ones for building the "best" solutions. Solution-oriented frameworks, like those presented by Hobbs and Seeman, have been based on parameters such as the sector of influence (e.g., public policy) but would benefit from the consideration of complexity and the leverage points for intervention in complex systems, which are a function of parameters such as the structure of relationships and the presence or absence of feedback loops.
旨在减少肥胖的公共政策只是应对仍在不断蔓延的肥胖流行问题所需采取的众多途径之一。问题的复杂性在决定因素的生态框架和系统图中得到了体现。这些概念图通过承认许多不同因素的影响来展示复杂性，这些因素包括社会规范和价值观；影响领域，如食品和饮料行业、媒体和交通；行为环境，包括家庭、学校和社区；以及个体因素，如基因、心理社会因素和其他个人因素。但是，要解决这样一个复杂的问题，我们需要从对问题的决定因素或原因的分析转向以解决方案为导向；用于描述问题的框架可能并不适合构建“最佳”解决方案。以解决方案为导向的框架，如霍布斯和西曼提出的那些框架，是基于影响领域（如公共政策）等参数构建的，但如果能考虑到复杂性以及复杂系统中干预的杠杆点，将会更有益处，而这些杠杆点是由诸如关系结构和反馈回路的存在与否等参数决定的。
