Strengthening Causal Inference in Behavioral Obesity Research

加强行为肥胖研究中的因果推断

• 批准号: 9306177
• 负责人: DAVID B ALLISON
• 金额: $ 5.79万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-15 至 2017-08-09
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9306177
• 关键词: Address; Affect; Alabama; Behavior; Behavior Therapy; Behavioral; Behavioral Sciences; Body Composition; Clinical; Clinical Trials; Cluster randomized trial; Collaborations; Communities; Complex; Cookbook; Data; Disadvantaged; Discipline; Economics; Epidemiologic Methods; Epidemiology; Etiology; Experimental Designs; Exposure to; Foundations; Genetic; Government; Health Policy; Individual; Influentials; Institute of Medicine (U.S.); Instruction; Internet; Intervention; Judgment; Lead; Learning; Mathematics; Measures; Medicine; Meta-Analysis; Methodology; Methods; Natural experiment; Obesity; Outcome; Pathway interactions; Philosophy; Physiological; Plant Roots; Policies; Policy Maker; Population; Population Distributions; Positioning Attribute; Prevention; Prevention strategy; Psychology; Public Health; Quasi-experiment; Randomized; Randomized Controlled Trials; Research; Research Design; Research Personnel; Research Technics; Resources; Science; Scientist; Strategic Planning; System; Techniques; Testing; Training; United States National Institutes of Health; Universities; Variant; Work; behavioral study; course module; design; energy balance; experience; experimental study; genetic approach; next generation; novel; obesity in children; personalized approach; programs; psychologic; public health relevance; research study; role model; social; sound; statistics

DESCRIPTION (provided by applicant): The identification of 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 component contributing to variations in energy balance and body composition, the final common pathways of obesity. Social factors are key influences on behaviors, and perhaps even physiological factors, which affect energy balance. Understanding which social and behavioral factors cause variations in adiposity and which other factors (e.g., environmental) cause variations in behavioral and social factors is vital to producing, evaluating, and selecting among intervention and prevention strategies as well as to understanding obesity's root causes. Evidence for causation (or lack thereof) of hypothesized influential factors exists on a continuum from weakest to strongest. Yet, most dialogue and research in obesity does not consider the evidence continuum between ordinary association studies (observational non-intervention studies among unrelated individuals), which do not offer strong assessments of causal effects, and randomized controlled trials (RCTs), which do offer strong inferences, but cannot be done in all circumstances. In contrast to this polarized view, there are techniques that lie intermediar between ordinary association tests 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 rarely used in obesity research. Our ability to draw causal inferences in obesity research could be strengthened by increased judicious use of 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 in some cases behavioral or statistical genetics. The application of these techniques, however, does not involve routine well-known 'cookbook' approaches but requires understanding of underlying principles, so the investigator can tailor approaches to specific and varying situations. Yet, no ongoing resource exists to provide such training and role models of scientists who regularly can and do traverse these disciplines are in short supply. The proposed annual 5-day short course on methods for causal inference in obesity research features some of the world's finest scientists who will help to fill this unmet need. This course for established and up- and-coming obesity researchers will be held annually at the University of Alabama at Birmingham. The nine course modules are formatted to provide rigorous exposure to the key fundamental principles underlying a broad array of techniques and experience in applying those principles and techniques through guided discussion of real examples in obesity research. The NIH and the scientific community at large call for better assessment of causal effect in obesity research and more training on such methods. We request the opportunity to be part of the solution.

描述（由申请人提供）：因果关系的识别是干预和预防科学的基础。肥胖是一个重大问题，在认识、治疗和预防方面仍有待取得很大进展。行为是导致能量平衡和身体成分变化的重要组成部分，而能量平衡和身体成分是肥胖的最终常见途径。社会因素是对行为的关键影响，甚至可能是影响能量平衡的生理因素。了解哪些社会和行为因素导致肥胖的变化以及哪些其他因素（例如环境）导致行为和社会因素的变化对于制定、评估和选择干预和预防策略以及了解肥胖的根本原因至关重要。假设的影响因素存在因果关系（或缺乏因果关系）的证据存在于从最弱到最强的连续体中。然而，大多数关于肥胖的对话和研究并没有考虑普通关联研究（无关个体之间的观察性非干预研究）和随机对照试验（RCT）之间的证据连续体，普通关联研究不提供对因果效应的强有力的评估，而随机对照试验（RCT）确实提供了因果关系的证据。强有力的推论，但不能在所有情况下都这样做。与这种两极分化的观点相反，有一些介于普通关联测试和随机对照试验之间的技术，包括但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，特别是在经济学和遗传学学科中，但很少用于肥胖研究。通过更加明智地使用此类方法，可以增强我们在肥胖研究中得出因果推论的能力。深入理解和适当使用这些方法的完整连续体需要来自统计学、经济学、心理学、流行病学、数学、哲学以及在某些情况下行为或统计遗传学等学科的投入。然而，这些技术的应用并不涉及常规的众所周知的“食谱”方法，而是需要了解基本原理，因此研究人员可以根据具体和不同的情况定制方法。然而，目前还没有持续的资源来提供此类培训，而且经常能够并且确实跨越这些学科的科学家的榜样也很短缺。拟议的年度为期 5 天的肥胖研究因果推理方法短期课程由世界上最优秀的一些科学家参加，他们将帮助满足这一未满足的需求。该课程每年都会在阿拉巴马大学伯明翰分校为成熟和崭露头角的肥胖研究人员举办。九个课程模块的格式旨在通过对肥胖研究中真实例子的引导讨论，提供对各种技术背后的关键基本原理的严格接触，以及应用这些原理和技术的经验。美国国立卫生研究院和整个科学界呼吁更好地评估肥胖研究中的因果效应，并对此类方法进行更多培训。我们请求有机会参与解决方案。