The impact of natural experiments on child obesity: A systems science approach

自然实验对儿童肥胖的影响：系统科学方法

基本信息

批准号：
8915236
负责人：
MICHAEL Lee PRELIP
金额：
$ 46.79万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-16 至 2016-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8915236
关键词：
5 year old Address Advocate Algorithms American Behavior California Characteristics Child Communities Complex Country County Data Data Analyses Databases Developed Countries Development Diet Dose Eating Effectiveness Environment Environmental Policy Epidemic Epidemiology Evaluation Research Feedback Food Policy Foundations Goals Habits Health Health education Height Individual Infant Intervention Interview Journals Learning Los Angeles Low income Measurement Methodology Methods Modeling Natural experiment Neighborhoods Nonprofit Organizations Nursery Schools Obesity Outcome Participant Pattern Physical activity Policies Population Population Intervention Prevalence Protocols documentation Public Health Public Health Practice Public Policy Research Research Methodology Research Personnel Resources Science Social Policies System Target Populations Time United States Vulnerable Populations Weight Woman Work World Health Organization administrative database aged base causal model community intervention early childhood evidence base experience improved indexing informant member multilevel analysis novel nutrition obesity in children obesity risk older women programs tobacco control

项目摘要

DESCRIPTION (provided by applicant): The long-term goal is to reduce the prevalence of child obesity, which has been declared one of the major public health challenges of the 21st century by the World Health Organization. The immediate purpose of the proposed study is to evaluate the impact of obesity-related interventions and policies on early childhood obesity risk in communities throughout Los Angeles County, a socio-demographically diverse region with a population of 10 million. An interdisciplinary team from UCLA and UC Berkeley will form partnerships with the Los Angeles County Department of Public Health (LACDPH), Public Health Foundation Enterprises WIC (PHFE WIC) [the largest local agency Supplemental Nutrition Assistance Program for Women, Infants and Children (WIC) in the country], and California Food Policy Advocates (CFPA) to develop new evaluation research methodology using systems science approaches, for this purpose. The proposed study will challenge and shift current paradigms in evaluation research methodology by (1) using outcome data (obesity status in preschool-aged children) from a large administrative database; (2) developing a methodology for retrospectively quantifying the impact of community efforts to address obesity or obesity-related behaviors (diet and physical activity), and (3) pioneering the combined use of causal inference methods and systems science approaches for the analysis. The administrative database providing the outcome data has been maintained by PHFE WIC since 2003; it contains height and weight data gathered from about ~ 200,000 two to five year old WIC participants each year. These data have recently been evaluated for validity and shown to correlate highly with measurements taken by a research team from UCLA. The methodology for quantifying the impact of obesity-related community interventions and policies on early childhood obesity will use existing data gathered by LACDPH as well as information from interviews with key informants identified with the help of LACDPH and CFPA (two organizations highly knowledgeable about community efforts to address child obesity in LA County), to develop an index; development of this index will borrow from the experiences of research groups that have conducted similar work in the field of tobacco control. The application of causal inference methods, which perhaps represent the fastest growing methodological advances in epidemiology, in combination with systems science approaches to analyze the data will shift current paradigms in evaluation research methodology, allowing for the assessment of the effects of unplanned mixtures of possibly time-varying interventions.

描述（由申请人提供）：长期目标是减少儿童肥胖的患病率，世界卫生组织已将其宣布为21世纪主要的公共卫生挑战之一。拟议研究的直接目的是评估与肥胖相关的干预措施和政策对整个洛杉矶县社区早期儿童肥胖风险的影响，洛杉矶县是一个社会人口多样化的地区，拥有 1000 万人口。来自加州大学洛杉矶分校和加州大学伯克利分校的跨学科团队将与洛杉矶县公共卫生部 (LACDPH)、公共卫生基金会企业 WIC (PHFE WIC) [当地最大的机构妇女、婴儿和儿童补充营养援助计划 (WIC) ）和加州食品政策倡导者组织（CFPA）为此目的使用系统科学方法开发新的评估研究方法。拟议的研究将通过以下方式挑战和改变当前的评估研究方法范式：（1）使用来自大型管理数据库的结果数据（学龄前儿童的肥胖状况）； (2) 开发一种方法来回顾性量化社区努力解决肥胖或肥胖相关行为（饮食和身体活动）的影响，以及 (3) 开创性地结合使用因果推理方法和系统科学方法进行分析。自 2003 年以来，提供结果数据的管理数据库一直由 PHFE WIC 维护；它包含每年从约 200,000 名 2 至 5 岁 WIC 参与者收集的身高和体重数据。这些数据最近经过了有效性评估，并显示与加州大学洛杉矶分校研究小组的测量结果高度相关。量化与肥胖相关的社区干预措施和政策对儿童早期肥胖的影响的方法将使用 LACDPH 收集的现有数据以及在 LACDPH 和 CFPA（两个对社区工作非常了解的组织）帮助下确定的关键知情人的访谈信息。解决洛杉矶县的儿童肥胖问题），制定一个指数；该指数的制定将借鉴在烟草控制领域开展类似工作的研究小组的经验。因果推理方法的应用可能代表了流行病学中增长最快的方法论进步，与系统科学方法相结合来分析数据将改变当前评估研究方法的范式，从而可以评估可能的时间意外混合的影响- 不同的干预措施。