Strengthening Causal Inference in Behavioral Obesity Research

项目概要/摘要 确定因果关系是干预和预防科学的基础。肥胖是一个主要问题 在认识、治疗和预防方面仍有很大进展。行为是至关重要的 这是导致能量平衡和身体成分变化的因素，也是肥胖的最终共同途径。社交， 环境和生理因素也是影响能量平衡的行为的关键影响因素。 这些假设因素的因果关系的证据存在于从最弱到最强的连续体上。然而，大多数 肥胖研究没有考虑普通关联检验（OAT）之间的证据连续性 （在无关个体中进行的观察性、非干预性研究），这些研究没有提供强有力的证据， 因果效应和随机对照试验（RCT），这些试验确实提供了强有力的证据，但不能在 所有的情况。相反，有一些技术介于OAT和RCT之间，包括但不限于 不限于准实验研究和自然实验。这种设计越来越多地被使用， 尤其是在经济学和遗传学领域，但肥胖研究人员使用的频率低于 似乎是有道理的。我们在肥胖研究中得出因果推论的能力可以通过使用这种方法来加强。 接近。深入理解和适当使用这些方法的全部连续性需要投入 来自统计学、经济学、心理学、流行病学、数学、哲学和 行为或统计遗传学。然而，应用这些技术并不涉及常规的“食谱”。 方法，但需要了解基本原则，因此研究人员可以定制方法， 具体和不同的情况。然而，除了我们每年5天的短期课程，没有资源提供这种培训， 特别是对于行为和社会科学研究者来说。我们的短期课程因果推理的方法， 肥胖研究，其中包括一些世界上最优秀的科学家，一直受到评估， 与会者对他们的研究和教学至关重要。该课程提供了严格的接触的关键 通过指导，广泛的技术和应用经验的基本原则 使用真实的例子进行讨论。该课程是动态的，因为我们改进和修改其内容和交付 基于利益相关者反馈的方法。在这次更新申请中，我们建议继续提供这种 课程，交替在印第安纳州大学和伯明翰的亚拉巴马大学之间的位置。给定 肥胖及其相关健康问题的流行，培训行为和社会科学研究人员， 更好地评估因果效应比以往任何时候都更加重要。

Project Summary/Abstract Identifying causal relations is fundamental to a science of intervention and prevention. Obesity is a major problem for which much progress in understanding, treatment, and prevention remains to be made. Behavior is a vital contributor to variations in energy balance and body composition, the final common pathways of obesity. Social, environmental and physiological factors are also key influences on behaviors which affect energy balance. Evidence for causation of these hypothesized factors exists on a continuum from weakest to strongest. Yet, most obesity research does not consider the evidence continuum between ordinary association tests (OATs) (observational, non-intervention studies among unrelated individuals), which do not offer strong evidence of causal effects, and randomized controlled trials (RCTs), which do offer strong evidence, but cannot be done in all circumstances. In contrast, there are techniques that lie intermediary between OATs and RCTs, including but not limited to quasi-experimental studies and natural experiments. Such designs are increasingly used, especially in the disciplines of economics and genetics, but are used by obesity researchers less often than seems warranted. Our ability to draw causal inferences in obesity research could be strengthened by using such approaches. In-depth understanding and appropriate use of the full continuum of these methods requires input from disciplines including statistics, economics, psychology, epidemiology, mathematics, philosophy, and behavioral or statistical genetics. Applying these techniques, however, does not involve routine ‘cookbook’ approaches but requires understanding of underlying principles, so the investigator can tailor approaches to specific and varying situations. Yet, other than our annual 5-day short course, no resource provides such training, particularly for behavioral and social science researchers. Our short course on methods for causal inference in obesity research, which features some of the world’s finest scientists, has been consistently evaluated by attendees as essential for their research and teaching. The course provides rigorous exposure to the key fundamental principles underlying a broad array of techniques and experience in application through guided discussion using real examples. The course is dynamic in that we refine and modify its content and delivery methods based on feedback from stakeholders. In this renewal application, we propose to continue to offer this course, alternating its location between Indiana University and the University of Alabama at Birmingham. Given the prevalence of obesity and its related health problems, training behavioral and social science researchers to better assess causal effects is more important than ever.