Mendelian randomisation (MR) studies allow a better understanding of the causal effects of modifiable exposures on health outcomes, but the published evidence is often hampered by inadequate reporting. Reporting guidelines help authors effectively communicate all critical information about what was done and what was found. STROBE-MR (strengthening the reporting of observational studies in epidemiology using mendelian randomisation) assists authors in reporting their MR research clearly and transparently. Adopting STROBE-MR should help readers, reviewers, and journal editors evaluate the quality of published MR studies. This article explains the 20 items of the STROBE-MR checklist, along with their meaning and rationale, using terms defined in a glossary. Examples of transparent reporting are used for each item to illustrate best practices. Observational epidemiology often examines the associations between exposures and health outcomes. However, such associations reported in epidemiological studies are often not reliable estimates of causal effects, and can be produced by confounding (that is, by another factor that affects both the outcome and exposure)123 or by other forms of bias. For example, alcohol consumption might be related to many potential confounding factors, including smoking, an unhealthy diet, and limited exercise. In turn, ill health could be related to a reduction or cessation of alcohol consumption, introducing potential bias due to reverse causality, when interest is in studying the effect of alcohol consumption on subsequent health.45 Several approaches have been developed with the aim of mitigating such biases.6 For example, instrumental variable methods rely on an external factor that determines the exposure of interest but is not associated with the outcome other than through its effect on the exposure.67 Over the past decade, advances in genetic technologies have enabled the identification of thousands of reproducible associations between genetic variation and relevant exposures, traits, and health …

中文翻译：

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使用孟德尔随机化（STROBE-MR）加强流行病学观察性研究的报告：解释和阐述


孟德尔随机化 (MR) 研究可以更好地了解可改变的暴露对健康结果的因果影响，但已发表的证据往往因报告不充分而受到阻碍。报告指南帮助作者有效地传达有关已完成的工作和发现的内容的所有关键信息。 STROBE-MR（使用孟德尔随机化加强流行病学观察性研究的报告）帮助作者清晰透明地报告他们的 MR 研究。采用 STROBE-MR 应该可以帮助读者、审稿人和期刊编辑评估已发表的 MR 研究的质量。本文使用术语表中定义的术语解释了 STROBE-MR 检查表的 20 项及其含义和基本原理。每个项目都使用透明报告的示例来说明最佳实践。观察流行病学经常检查暴露与健康结果之间的关联。然而，流行病学研究中报告的此类关联通常不是对因果效应的可靠估计，并且可能是由混杂因素（即影响结果和暴露的另一个因素）123或其他形式的偏见产生的。例如，饮酒可能与许多潜在的混杂因素有关，包括吸烟、不健康的饮食和有限的运动。反过来，健康不良可能与减少或停止饮酒有关，当人们有兴趣研究饮酒对随后健康的影响时，由于反向因果关系，会引入潜在的偏差。 45 已经开发了几种方法，旨在减轻这种影响。这样的偏见。6 例如，工具变量方法依赖于决定感兴趣暴露的外部因素，但除了通过其对暴露的影响之外，与结果无关。67 在过去的十年中，基因技术的进步使得人们能够识别出遗传变异与相关暴露、性状和健康之间的数千个可重复的关联……