Public Health Research & Systems/ Network Science: Childhood Obesity

描述（由申请人提供）：申请的资金将支持一系列科学会议，以促进新墨西哥州预防研究中心（PRC）的公共卫生研究科学家和桑迪亚国家实验室（SNL）的系统建模科学家之间最近建立的独特的跨学科和跨机构合作。我们建议的工作重点是儿童健康，重点是儿童肥胖症。我们正在制定一项研究议程，将基于社区的公共卫生调查与基于系统的概念和计算建模相结合。我们认为，这两种方法的综合将建立一个更复杂的框架，为加强社区一级的预防和促进更健康的社区提供深刻见解。肥胖是一种全国性流行病，在过去几十年中，儿童超重和肥胖的流行率惊人地增加。1 -7然而，迄今为止，肥胖在许多层面上给预防科学提出了难题。部分挑战在于问题的复杂性，既包括影响人群中个人肥胖症发展的因素，也包括影响预防工作成功的因素。8 -14这种复杂性很难概念化，因为它包括同时存在于多个影响层面的各种因素（个人、家庭、社区、国家、民族），以及这些因素汇合在一起形成的相互联系和关系及其影响范围。越来越多的人认识到这种因素和背景的多样性需要新的方法和观点，这鼓励了在肥胖预防研究中采用系统导向的概念框架的支持。15 -22计算建模的最新进展使得有可能适应越来越大的复杂性，这与跨学科系统导向研究的发展相一致。现在，人们对应用网络科学来理解与肥胖等大规模公共卫生问题相关的复杂和交叉的社会生态因素存在相当大的兴趣。19 -21，23考虑到这一点，拟议的会议将使我们的研究中心能够利用我们独特的多学科合作伙伴关系，并努力将系统和网络科学整合到中国以社区为基础的公共卫生方法中。我们的工作将最终在合作PRC/SNL R21或R 01研究资助申请的发展。这些会议将为我们提供定期举办团队研讨会和定期密集的战略概念化研讨会的机会，这些研讨会将磨练我们对计算建模和肥胖预防框架的理解，建立我们的团队进行跨学科研究的能力，并使我们能够概念化如何将基于社区的方法与基于系统的计算建模所提供的进步相结合。我们将邀请相关领域的知名专家通过工作坊、演讲和工作讨论与我们分享他们的知识和经验。我们的目标是确定最佳建模方法，并与社区合作创建原型概念模型，这将是R21或R 01应用程序以及未来更深入工作的基础。我们还将组建一个对这种方法感兴趣的研究人员联盟。我们目前正在考虑建立一个潜在合作者网络，其中可能包括来自全国学术机构其他预防研究中心的研究人员。 公共卫生相关性：申请的资金将支持一系列科学会议，以进一步发展新墨西哥州预防研究中心（PRC）的公共卫生研究科学家和桑迪亚国家实验室（SNL）的系统建模科学家之间最近建立的独特的跨学科和机构间合作。我们建议的工作重点是儿童健康，重点是儿童肥胖症。我们正在制定一项研究议程，将基于社区的调查与基于系统的概念和计算建模相结合。

DESCRIPTION (provided by applicant): The requested funding will support a series of scientific meetings to foster a unique, inter- disciplinary and inter-institutional collaboration that has recently been established between public health research scientists at the University of New Mexico Prevention Research Center (PRC) and systems modeling scientists at Sandia National Laboratories (SNL). The focus of our proposed work is on child health with an emphasis on childhood obesity. We are developing a research agenda to integrate community-based public health investigation with systems-based conceptual and computational modeling. We believe that the synthesis of these two approaches will create a more sophisticated framework that will provide insights to strengthen community-level prevention and promote healthier communities. Obesity is a national epidemic with the prevalence of overweight and obesity among children increasing alarmingly over the last several decades.1-7 To date however, obesity has presented a conundrum to prevention science on a number of levels. Part of the challenge has been the complex nature of the problem, both in terms of the factors that influence the development of obesity among individuals in a population, but also in terms of those that influence the success of prevention efforts.8-14 This complexity is difficult to conceptualize, as it includes a variety of factors that exist simultaneously at multiple levels of influence (individual, family, community, state, national), together with the interconnections and relationships formed by the confluence of these factors and their spheres of influence. Increasing acknowledgement that this multiplicity of factors and contexts requires new approaches and perspectives has encouraged support for employing systems-oriented conceptual frameworks in obesity prevention research.15-22 Recent advances in computational modeling make it possible to accommodate increasingly-greater complexity which dovetails with the development of systems-oriented research across disciplines. Considerable interest now exists for applying network science to understanding complex and intersecting socio-ecological factors involved in large-scale public health issues like obesity.19-21, 23 With this in mind, the proposed meetings will allow our workgroup to capitalize on our unique multi-disciplinary partnership and work to integrate systems and network science into the community-based public health approach of the PRC. Our work will culminate in the development of a collaborative PRC/SNL R21 or R01 research grant application. These meetings will provide us with the opportunity to hold regular Team Workshops and periodic intensive Strategic Conceptualization Workshops that will hone our understanding of computational modeling and obesity-prevention frameworks, build the capacity of our workgroup to conduct research that bridges disciplines, and allow us to conceptualize how to integrate community-based approaches with the advances offered by systems-based computational modeling. We will invite prominent experts from relevant fields to share their knowledge and experience with us through workshops, presentations and working discussions. Our goal will be to identify the best modeling approaches and to work with a community to create a prototype Conceptual Model that will be the basis for the R21 or R01 application and for more in-depth future work. We will also form a consortium of researchers interested in this approach. We currently have in mind a network of potential collaborators that could include researchers from other Prevention Research Centers at academic institutions across the country. PUBLIC HEALTH RELEVANCE: The requested funding will support a series of scientific meetings to further develop a unique, inter-disciplinary and inter-institutional collaboration that has recently been established between public health research scientists at the University of New Mexico Prevention Research Center (PRC) and systems modeling scientists at Sandia National Laboratories (SNL). The focus of our proposed work is on child health with an emphasis on childhood obesity. We are developing a research agenda to integrate community-based investigation with systems-based conceptual and computational modeling.