Agent-Based Model of Individual-level Food Choice and Physical Activity Behavior

基于主体的个人食物选择和身体活动行为模型

• 批准号: 7936809
• 负责人: May C Wang
• 金额: $ 45.24万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-25 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7936809
• 关键词: Accounting; Address; Affect; Algorithms; American; Applied Research; Area; Behavior; Behavioral; Child; Childhood; Communities; Complex; Country; Crime; Data; Demographic Factors; Developing Countries; Development; Diet; Discipline; Eating; Eating Behavior; Environment; Environmental Policy; Environmental Risk Factor; Epidemic; Family; Food; Geographic Information Systems; Growth; Health; Individual; Investigation; Knowledge; Life Style; Methodology; Methods; Modeling; National Heart, Lung, and Blood Institute; Neighborhoods; Obesity; Outcome; Physical activity; Physical environment; Policies; Prevention; Prevention program; Process; Recovery; Research; Research Methodology; Research Support; Risk Factors; Running; Simulate; Social Behavior; Social Impacts; Spatial Distribution; Statistical Methods; Supercomputing; Technology; Testing; United States; Woman; Work; base; behavior influence; cohort; cost; environmental change; epidemiologic data; girls; improved; innovation; interest; meetings; nutrition; obesity prevention; parallel processing; programs; prospective; scientific computing; simulation; social

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (01) Behavior, Behavioral Change, and Prevention and specific Challenge Topic, 01-GM-101: Individual-based model of social behavior. Obesity, which has reached crisis proportions in the United States, is clearly a multi-factorial problem, and describing causal mechanisms and developing effective programs and policies has been challenging. Our primary aim is to borrow intensive scientific computing modeling methods used in other disciplines to develop a robust and well-characterized model of individual-level behavior related to nutrition and physical activity, as influenced by social and physical environmental factors. In particular, we propose to develop an agent-based model that quantifies social-demographic and built-environmental mechanisms by which behavioral choices are made in young women, and calibrate it to existing data from the Berkeley center of the ten-year prospective NHLBI Growth and Health Study (NGHS) of obesity development in Black and White girls. Once calibrated, the model, which will simulate complex and dynamic individual-based behaviors within changing environments, will be used to evaluate the impact of environmental policies aiming to promote healthy behaviors. Development of such a model will address the need for model-based assessments of health impacts associated with environmental changes. The modeling work will be innovative, leveraging recent advancements in computing technology, including algorithms that run on inexpensive multi-core graphics processing units (GPUs). Further, this study will meet the intent of the American Recovery and Reinvestment Act by stimulating interest in the use of new research methods and computing technology. Our specific aims are: 1. To develop an individual-level agent-based model of food choice and physical activity for young women. The model will be based on knowledge about childhood eating behaviors and family environment, and a geographic information system, thereby accounting for the influences of social factors that operate at the individual, family, and community-level, as well as the spatial distribution of physical environmental features that could influence behavior, such as green space and the food environment. The model will be calibrated and validated to existing data from the NGHS. 2. To explore hypothetical scenarios using the calibrated/validated model based on changes to social and physical environments. Our model will simulate various scenarios (e.g., rezoning, introducing more food stores, etc.) to determine the potential effect on our cohort. Based on these findings we will determine the sensitivity of various policy changes for improving eating and physical activity behaviors. 3. To make use of new advancements in low-cost commercial GPU technology to support the use of such technology for massive simulation studies that previously required expensive supercomputing technology. This research concerns the challenge of obesity, and our current inability to quantify the impact of environmental changes on food choice and physical activity behaviors. Quantifying the impact of environmental changes on food and physical activity behaviors will provide much needed information to guide the development of effective obesity prevention programs and policies. Our research will use advances in computing technology to develop and test an innovative model that will quantify the impact of social and built environments on the development of food choice and physical activity behaviors in young women. The successful completion of this project will allow this innovative methodology to be applied to other socio-demographic groups, advancing our knowledge of effective approaches for dealing with the obesity epidemic.

描述（由申请人提供）：此申请涉及广泛的挑战领域（01）行为，行为改变和预防以及特定的挑战主题，01- gm -101：基于个人的社会行为模型。肥胖在美国已经达到了危机的程度，显然是一个多因素问题，描述因果机制和制定有效的计划和政策一直具有挑战性。我们的主要目标是借鉴其他学科中使用的密集科学计算建模方法，开发一个与营养和身体活动相关的、受社会和物理环境因素影响的、健壮的、特征良好的个人层面行为模型。特别是，我们建议开发一个基于主体的模型，量化年轻女性做出行为选择的社会人口和建筑环境机制，并将其校准为来自伯克利中心的黑人和白人女孩肥胖发展的十年前瞻性NHLBI生长与健康研究（NGHS）的现有数据。一旦校准，该模型将在不断变化的环境中模拟复杂和动态的基于个人的行为，将用于评估旨在促进健康行为的环境政策的影响。开发这样一个模型将满足对与环境变化有关的健康影响进行基于模型评估的需要。建模工作将是创新的，利用最新的计算技术，包括在廉价的多核图形处理单元（gpu）上运行的算法。此外，这项研究将通过激发对使用新研究方法和计算技术的兴趣来满足美国复苏和再投资法案的意图。我们的具体目标是：1。为年轻女性建立基于个体的食物选择和身体活动模型。该模型将基于关于儿童饮食行为和家庭环境的知识，以及地理信息系统，从而考虑在个人、家庭和社区层面上运作的社会因素的影响，以及可能影响行为的物理环境特征的空间分布，如绿地和食物环境。该模型将根据NGHS的现有数据进行校准和验证。2. 利用基于社会和自然环境变化的校准/验证模型探索假设情景。我们的模型将模拟各种场景（例如，重新规划，引入更多的食品商店等），以确定对我们的队列的潜在影响。基于这些发现，我们将确定改善饮食和体育活动行为的各种政策变化的敏感性。3. 利用低成本商用GPU技术的新进展，支持使用这种技术进行大规模模拟研究，而这些研究以前需要昂贵的超级计算技术。这项研究涉及肥胖的挑战，以及我们目前无法量化环境变化对食物选择和体育活动行为的影响。量化环境变化对食物和身体活动行为的影响将为指导制定有效的肥胖预防计划和政策提供急需的信息。我们的研究将利用先进的计算技术来开发和测试一种创新模型，该模型将量化社会和建筑环境对年轻女性食物选择和体育活动行为发展的影响。这一项目的成功完成将使这一创新方法能够应用于其他社会人口群体，从而提高我们对处理肥胖流行病的有效方法的认识。