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首页> 外文期刊>Journal of physical activity & health >Approaches to Improve Causal Inference in Physical Activity Epidemiology
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Approaches to Improve Causal Inference in Physical Activity Epidemiology

机译：改善身体活性流行病学因果算推理的方法

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Background: It is not always clear whether physical activity is causally related to health outcomes, or whether the associations are induced through confounding or other biases. Randomized controlled trials of physical activity are not feasible when outcomes of interest are rare or develop over many years. Thus, we need methods to improve causal inference in observational physical activity studies. Methods: We outline a range of approaches that can improve causal inference in observational physical activity research, and also discuss the impact of measurement error on results and methods to minimize this. Results: Key concepts and methods described include directed acyclic graphs, quantitative bias analysis, Mendelian randomization, and potential outcomes approaches which include propensity scores, g methods, and causal mediation. Conclusions: We provide a brief overview of some contemporary epidemiological methods that are beginning to be used in physical activity research. Adoption of these methods will help build a stronger body of evidence for the health benefits of physical activity.
机译：背景：并不总是明确身体活动是否与健康结果有关，或者是否通过混淆或其他偏差引起联想。当感兴趣的结果罕见或多年来，当感兴趣的结果是罕见的或发展时，体育活动的随机对照试验是不可行的。因此，我们需要方法来改善观察身体活动研究中的因果化。方法：我们概述了一系列方法，可以改善观察物理活动研究中的因果推断，并讨论测量误差对最小化的结果和方法的影响。结果：所描述的关键概念和方法包括指导的非循环图，定量偏差分析，孟德尔随机化以及包括倾向分数，G方法和因果调解的潜在结果方法。结论：我们简要概述了一些现代流行病学方法，这些方法开始用于体育活动研究。采用这些方法将有助于为身体活动的健康益处建立更强的证据。

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