Causes and Interventions for Childhood Obesity:Innovative Systems Analysis

儿童肥胖的原因和干预措施：创新系统分析

• 批准号: 8041225
• 负责人: YOUFA WANG
• 金额: $ 40.45万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-29 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8041225
• 关键词: Causes; Interventions; Childhood; Obesity; Innovative

DESCRIPTION (provided by applicant): Causes and Interventions for Childhood Obesity: Innovative Systems Analysis Obesity has become a public health crisis in the United States. Obesity is believed as the result of a complex interplay between biological, behavioral, cultural, social, environmental and economic dynamics operating at multiple levels. Studying such complex dynamics is a challenge using traditional analytical approaches. Our proposed project aimed to meet several urgent needs in the field, including both empirical results and methodological issues. Our project will address several of the objectives specified in several recent NIH RFA and PAR including PAR-08-224 "Using Systems Science Methodologies to Protect and Improve Population Health (R21)." Our central hypothesis is that the determinants of individuals' energy balance related behaviors (EBRB) and body weight outcomes involve complex, dynamic processes including various feedback loops across multi-level factors. We have four specific aims (analysis in Aim 1 prepares for Aims 2-3; and system models developed in Aims 2-3 will be used in Aim 4): Aim 1: Using innovative, integrated conceptual framework and multilevel statistical analysis approaches, to examine the influences and interactions between individual, family and environmental factors on childhood obesity. Aim 2: Using agent-based models (ABM) to test simple rules (e.g., how children may interact with their social and built environments) that help explain individuals' EBRB and obesity risk and the changes in population level rates of these outcomes. Aim 3: To determine the key contextual drivers of the childhood obesity epidemic at the population level (i.e., time trends), using a novel combination of systems analysis methods and nationally representative data sets linked with contextual measures. This will help develop and calibrate systems dynamics models (SDM) that can replicate the time-course of the obesity epidemic and help project future obesity trends and impact of intervention options. Aim 4: To identify and characterize promising intervention/policy strategies based our results of aims 1-3 and those in the literature, taking into account non- linearities, feedback loops and recursive causal relations; and to project/simulate impacts of these strategies on obesity rates using SDM and ABM models developed and calibrated in Aims 2-3. We will conduct sensitivity analyses based on various specifications of models. Our systematic analysis will be conducted using a set of innovative, sophisticated methods including multilevel models (MLM) and systems analysis models for analyses of empirical and simulation data. Data from national surveys including cohort studies linked with contextual measures from other data sources will be used. Our multidisciplinary team has extensive related experiences. Our methodological products will benefit future studies, and our empirical findings will help clarify several controversies surrounding the causes of childhood obesity epidemic and help guide future interventions. PUBLIC HEALTH RELEVANCE: Using integrated conceptual framework, innovative statistical analysis approaches including systems analysis models, national survey data sets and contextual measures we will study the influences and interactions between individual and environmental factors on childhood obesity, the key drivers of the US childhood obesity epidemic. We will also project the impacts of several childhood obesity intervention strategies.

描述（由申请人提供）：儿童肥胖的原因和干预措施：创新系统分析肥胖已成为美国的公共卫生危机。肥胖被认为是生物、行为、文化、社会、环境和经济动力学在多个层面上复杂相互作用的结果。使用传统的分析方法来研究这种复杂的动态是一个挑战。我们提出的项目旨在满足该领域的几个迫切需要，包括经验结果和方法问题。我们的项目将解决最近几个NIH RFA和PAR中规定的几个目标，包括PAR-08-224“使用系统科学方法保护和改善人口健康”（R21）。“我们的中心假设是，个人能量平衡相关行为（EBRB）和体重结果的决定因素涉及复杂的动态过程，包括跨多层次因素的各种反馈回路。我们有四个具体目标（目标1的分析为目标2-3做准备;目标2-3中开发的系统模型将用于目标4）：目标1：采用创新的、综合的概念框架和多层次的统计分析方法，研究个人、家庭和环境因素对儿童肥胖的影响和相互作用。目标2：使用基于代理的模型（ABM）来测试简单规则（例如，儿童如何与他们的社会和建筑环境互动），这有助于解释个人的EBRB和肥胖风险以及这些结果的人口水平比率的变化。目标3：确定儿童肥胖流行病在人群水平上的关键背景驱动因素（即，时间趋势），使用系统分析方法和与背景措施相联系的国家代表性数据集的新组合。这将有助于开发和校准系统动力学模型（SDM），这些模型可以复制肥胖流行的时间过程，并有助于预测未来的肥胖趋势和干预方案的影响。目标4：根据我们的目标1-3的结果和文献中的结果，确定和描述有希望的干预/政策战略，同时考虑到非线性、反馈回路和递归因果关系;并使用目标2-3中开发和校准的SDM和ABM模型，预测/模拟这些战略对肥胖率的影响。我们将根据模型的各种规格进行敏感性分析。我们的系统分析将使用一套创新的，复杂的方法，包括多层次模型（MLM）和系统分析模型进行实证和模拟数据的分析。将使用来自国家调查的数据，包括与其他数据来源的背景措施相联系的队列研究。我们的多学科团队拥有丰富的相关经验。我们的方法学产品将有利于未来的研究，我们的实证研究结果将有助于澄清围绕儿童肥胖流行原因的几个争议，并有助于指导未来的干预措施。 公共卫生相关性：使用综合的概念框架，创新的统计分析方法，包括系统分析模型，全国调查数据集和背景措施，我们将研究儿童肥胖，美国儿童肥胖流行的关键驱动因素，个人和环境因素之间的影响和相互作用。我们还将预测几种儿童肥胖干预策略的影响。