Lee M. Johnston is with the Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada. Carrie L. Matteson and Diane T. Finegood are with the Chronic Disease Systems Modeling Laboratory, Department of Biomedical Physiology and Kinesiology, Simon Fraser University.
Am J Public Health. 2014 Jul;104(7):1270-8. doi: 10.2105/AJPH.2014.301884. Epub 2014 May 15.
We demonstrate the use of a systems-based framework to assess solutions to complex health problems such as obesity.
We coded 12 documents published between 2004 and 2013 aimed at influencing obesity planning for complex systems design (9 reports from US and Canadian governmental or health authorities, 1 Cochrane review, and 2 Institute of Medicine reports). We sorted data using the intervention-level framework (ILF), a novel solutions-oriented approach to complex problems. An in-depth comparison of 3 documents provides further insight into complexity and systems design in obesity policy.
The majority of strategies focused mainly on changing the determinants of energy imbalance (food intake and physical activity). ILF analysis brings to the surface actions aimed at higher levels of system function and points to a need for more innovative policy design.
Although many policymakers acknowledge obesity as a complex problem, many strategies stem from the paradigm of individual choice and are limited in scope. The ILF provides a template to encourage natural systems thinking and more strategic policy design grounded in complexity science.
我们展示了一种基于系统的框架,用于评估肥胖等复杂健康问题的解决方案。
我们对 2004 年至 2013 年间发表的 12 篇旨在影响复杂系统设计肥胖规划的文件进行了编码(9 篇来自美国和加拿大政府或卫生当局的报告、1 篇 Cochrane 综述和 2 篇美国医学研究所报告)。我们使用干预水平框架(ILF)对数据进行了分类,这是一种针对复杂问题的新颖的解决方案导向方法。对 3 份文件的深入比较进一步深入了解了肥胖政策中的复杂性和系统设计。
大多数策略主要集中在改变能量失衡的决定因素(食物摄入和体力活动)上。ILF 分析揭示了旨在提高系统功能水平的行动,并指出需要更具创新性的政策设计。
尽管许多政策制定者承认肥胖是一个复杂的问题,但许多策略源于个人选择的范式,范围有限。ILF 提供了一个模板,鼓励基于自然系统思维和更具战略性的基于复杂性科学的政策设计。