Systems Science to Guide Whole-of-Community Childhood Obesity Interventions

描述（由申请人提供）： 肥胖抵抗简单的治疗，特别是在今天的环境，促进不健康的饮食，久坐不动的行为，和不良的睡眠习惯。幼儿期是一个发育可塑期，在此期间，正确的环境和发育影响可能会为生活带来健康的体重轨迹。预防幼儿肥胖不能通过单一学科的工作来实现，而是需要一个广泛的系统视角来框定问题，确定关键的影响杠杆点，并采取有效的行动。整个社区代表多个部门、层次和关键杠杆点汇聚的地点。这个美国-澳大利亚合作项目的总体目标是通过解决“什么有效，对谁有效，在什么情况下有效”来推进干预科学。“为了实现这一目标，我们将使用一种新颖的迭代方法，将计算系统科学建模与来自两个已完成和两个新的全社区干预计划的经验信息相结合。我们将通过与这些干预措施的数据进行重复和双向交互来开发，测试和改进我们的基于计算代理的模型。通过这些努力，我们的目标不仅是设计和完善我们自己的幼儿肥胖预防工作，而且还创建了一个灵活的基于代理的模型，具有广泛的适用性，以帮助未来的努力。从我们初步的系统映射工作和文献中的动态假设开始，我们将应用并测试一个初始模型，该模型使用已经从成功改变行为和BMI的2项已完成干预措施中收集的数据：1。塑造萨默维尔（马萨诸塞州），对学龄儿童进行全社区、多环境和政策干预; 2.）Romp & Chomp，这是澳大利亚维多利亚州一个城市的学龄前儿童社区肥胖预防示范项目。接下来，我们将使用从萨默维尔和澳大利亚的参与性小组模型构建练习中获得的细粒度数据迭代改进模型，并处理来自维多利亚的儿童肥胖干预试验的新全州准实验性试验的数据。然后，我们将应用改进的模型和从第一组中生成的见解 设计、计划和实施一项新的试点干预措施“塑造5岁以下儿童”的研究，这是一个重新设计的塑造萨默维尔的版本，针对0-5岁服务不足的儿童及其主要照顾者。在拟议的项目结束时，我们将测试和校准最终模型的结果数据，从多年的试验在维多利亚和萨默维尔试点。为了实现这些目标，我们组建了一个跨学科的研究团队，在肥胖预防，计算系统建模，基于社区的研究和实施科学方面拥有广泛的专业知识。该项目的影响在于有可能为新的可持续战略提供信息，以减轻美国和国外儿童肥胖的负担及其后果。

DESCRIPTION (provided by applicant): Obesity resists simple treatments, especially in today's environment which promotes unhealthful eating, sedentary behaviors, and poor sleep habits. Early childhood is a developmentally plastic period during which the right environmental and developmental influences may entrain healthful weight trajectories for life. Preventing obesity in early childhood cannot be achieved by working in single disciplines, but rather warrants a broad systems perspective to frame the problem, identify critical leverage points of influence, and take effective action. Whole communities represent loci in which multiple sectors, levels, and key leverage points converge. The overall goal of this US-Australian collaborative project is to advance intervention science by addressing "what works, for whom and under what circumstances?" To achieve this goal, we will use a novel, iterative, approach that combines computational systems science modeling with empirical information from two completed and two new whole-of-community intervention programs. We will develop, test, and refine our computational agent-based model through repeated and bi-directional interaction with data from these interventions. Through these efforts we aim not only to design and refine our own obesity prevention efforts in young children, but also to create a flexible agent-based model with wide applicability to aid future efforts. Beginning with dynamic hypotheses from our preliminary systems mapping work and the literature, we will apply and test an initial model using already collected data from 2 completed interventions that successfully changed behavior and BMI: 1.) Shape Up Somerville (Mass.), a community-wide, multi-environmental and policy intervention among school-age children; and 2.) Romp & Chomp, a whole-of-community obesity prevention demonstration project for preschoolers in one city in the state of Victoria, Australia. Next, we will iteratively refine the model using fine grained data drawn from participatory group model building exercises in both Somerville and Australia, and process data from a new state-wide quasi-experimental trial of childhood obesity intervention trial in Victoria. We will then apply the improved model and insights generated from this first set of studies to design, plan and conduct a new pilot intervention, "Shape Up Under-5," a re- designed version of Shape Up Somerville targeting underserved children age 0-5 years and their primary caregivers. At the end of the proposed project, we will test and calibrate the final model with outcome data from the multi-year trial in Victoria and the Somerville pilot. To achieve these aims we have assembled a trans-disciplinary research team with extensive expertise in obesity prevention, computational systems modeling, community-based research, and implementation science. The impact of this project lies in the potential to inform new and sustainable strategies to reduce the burden of childhood obesity and its consequences in the US and abroad.