Health Promotion and Disease Prevention Research Centers: Special Interest Project(s)

健康促进和疾病预防研究中心：特殊兴趣项目

• 批准号: 8845320
• 负责人: PHILIP J LEAF
• 金额: $ 60.75万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2019-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8845320
• 关键词: Health; Promotion; Disease; Prevention; Research

 DESCRIPTION (provided by applicant): High rates of obesity and obesity-related chronic disease persist among low-income children and adults in Baltimore City. The causes of this epidemic are multifactorial, and require multi-level and multi-component policies and programs. However, developing, testing, and evaluating interventions for obesity control can cost considerable time, effort, and resources. Computational simulation models offer an effective manner of determining the impact and unintended consequences of policies and interventions before implementation in the real world. Our team has expertise and experience in developing computational simulation models to guide policy makers and other stakeholders and in combining these with data collection and intervention studies, including a basic agent-based model (ABM) to represent children in the low income Baltimore City food environment. The overall objective of this proposal is to conduct mixed methods formative research to further develop the agent-based model of the low income Baltimore food environment, which will then be used to engage and work with policy makers, funders and other key stakeholders. The following specific aims will be addressed: 1. To conduct formative research to collect additional data on the food behaviors and environment. 2. To iteratively revise our existing ABM with this collected data and then utilize the progressively revised models to test the impact of and refine policies/program strategies for these venues. 3. To develop a process and the associated ABM tool that can be used to guide data collection, study development and implementation of obesity prevention programs and policies. 4. To offer our approach and a transferable ABM to the Nutrition and Obesity Policy Research and Evaluation Network (NOPREN) and others. The proposed work will have 5 phases: 1) Mixed methods formative research; 2) Revision of the Baltimore Low Income Food Environment Model (BLIFE) model/begin modifications for transferability; 3) Iterative data collection, model revision, interaction of researcher-practitionr teams; 4) Documentation of process and development of user-friendly version of the BLIFE model; and 5) Finalization of transferable version; support to other NOPREN Centers. The proposed work is highly innovative. The use of computational modeling to address obesity control has many gaps, including lack of attention to evaluating specific policies; little work usig geospatially specific information; limited efforts to model food source and food choice decisions of individual agents built on real data; and lack of transferability. BLIFE model will be the first geospatially specific computational model to include detailed data on most components of a city's low income food and physical activity environments, and will incorporate data from real adults and children. It will be the first use of agent-based modeling to support local policymakers as they formulate policies and programs to improve the urban food environment and reduce obesity risk in low income populations, and it will lead to the development of an ABM tool that can be disseminated to researchers and policy makers in other urban settings. We are submitting this application to become a NOPREN Collaborating Center (SIP 14-027). The aims and objective of our proposed Collaborating Center are directly in line with the HP 2020 goals related to obesity reduction, reductions in sugar and fat consumption, and increases in whole grain, and fruit and vegetable consumption. Our Center will contribute to the National Prevention Strategy by identifying policies and programs to improve access to healthy foods and beverages, and supports a CDC Winnable Battle with the same aim.

 描述（由申请人提供）：巴尔的摩市低收入儿童和成人的肥胖率和与肥胖相关的慢性病的发病率很高。这种流行病的原因是多因素的，需要多层次、多组成部分的政策和计划。然而，开发、测试和评估肥胖控制干预措施可能需要花费大量时间、精力和资源，计算模拟模型提供了一种有效的方法，可以在现实世界中实施之前确定政策和干预措施的影响和意外后果。开发方面的专业知识和经验指导政策制定者和其他利益相关者的计算模拟模型，以及在巴尔的摩将这些模型与数据收集和干预研究相结合，包括代表低收入城市食品环境中的儿童的基本代理模型（ABM）。进行混合方法形成性研究，进一步开发基于主体的低收入巴尔的摩食品环境模型，然后将其用于与政策制定者、资助者和其他主要利益相关者接触和合作，将解决以下具体目标：1。进行形成性研究以收集有关食物行为的额外数据。 2. 利用收集到的数据迭代修改我们现有的 ABM，然后利用逐步修改的模型来测试这些场所的影响并完善政策/计划策略。 3. 开发一个流程和相关的 ABM 工具。用于指导肥胖预防计划和政策的数据收集、研究开发和实施 4. 向营养和肥胖政策研究与评估网络 (NOPREN) 和其他机构提供我们的方法和可转移的 ABM 拟议的工作将有 5。阶段： 1) 混合方法形成性研究； 2) 修订巴尔的摩低收入食品环境模型 (BLIFE) 模型/开始修改可转移性； 3) 迭代数据收集、模型修订、研究人员与实践者团队的互动； BLIFE 模型的用户友好版本的流程和开发；以及 5) 完成对其他 NOPREN 中心的可移植版本的支持；使用计算模型来解决肥胖控制问题。存在许多差距，包括缺乏对具体政策评估的关注；使用地理空间特定信息的工作有限；基于真实数据的个体食物来源和食物选择决策的建模工作有限；以及缺乏可转移性。 地理空间特定的计算模型，包括城市低收入食品和体育活动环境大部分组成部分的详细数据，并将纳入来自真实成人和儿童的数据，这将是基于代理的模型首次用于支持当地决策者。 随着他们制定政策和计划来改善城市食品环境并降低低收入人群的肥胖风险，这将导致开发出可以传播给其他城市环境的研究人员和政策制定者的 ABM 工具。申请成为 NOPREN 合作中心 (SIP 14-027) 我们提议的合作中心的宗旨和目标与减少肥胖、减少糖和脂肪消耗以及增加相关的 HP 2020 目标直接一致。我们的中心将通过确定改善健康食品和饮料获取的政策和计划，为国家预防战略做出贡献，并支持疾病预防控制中心为实现同一目标而开展的“胜利之战”。