Brown School, Washington University in St. Louis, St. Louis, Missouri.
The Brookings Institution, Washington, DC.
Obes Rev. 2019 Nov;20 Suppl 2:161-178. doi: 10.1111/obr.12877. Epub 2019 Jul 17.
The problem of obesity has recently been reframed as part of the global syndemic-the co-occurring, interacting pandemics of obesity, undernutrition, and climate change that are driven by common underlying societal drivers. System science modeling approaches may help clarify how these shared drivers operate and the best ways to address them. The objective of this paper was to determine to what extent existing agent-based and system dynamics computational models of obesity provide insights into the shared drivers of the global syndemic. Peer-reviewed studies published until July 2018 were identified from Scopus, Web of Science, and PubMed databases. Thirty-eight studies representing 30 computational models were included. They show a growing use of system dynamics and agent-based modeling in the past decade. They most often examined mechanisms and interventions in the areas of social network-based influences on obesity, physiology and disease state mechanics, and the role of food and physical activity environments. Usefulness for identifying common drivers of the global syndemic was mixed; most models represented Western settings and focused on obesity determinants close to the person (eg, social circles, school settings, and neighborhood environments), with a relative paucity in models at mesolevel and macrolevel and in developing country contexts.
肥胖问题最近被重新定义为全球综合征的一部分 - 肥胖、营养不足和气候变化这三种大流行病同时发生且相互作用,而这些问题是由共同的社会驱动因素造成的。系统科学建模方法可以帮助阐明这些共同驱动因素的运作方式以及解决这些问题的最佳方法。本文的目的是确定肥胖的现有基于代理和系统动力学计算模型在多大程度上提供了对全球综合征共同驱动因素的深入了解。从 Scopus、Web of Science 和 PubMed 数据库中确定了截至 2018 年 7 月发表的同行评审研究。包括 38 项研究,代表 30 个计算模型。这些模型表明,在过去十年中,系统动力学和基于代理的建模的使用越来越多。它们最常用于研究社会网络对肥胖的影响、生理和疾病状态力学以及食物和体育活动环境的作用等领域的机制和干预措施。对于识别全球综合征的共同驱动因素的有用性参差不齐;大多数模型代表了西方环境,并且侧重于个人附近的肥胖决定因素(例如社交圈、学校环境和邻里环境),而在中观和宏观层面以及发展中国家环境中,模型相对较少。