Zeraatkar Dena, Cheung Kevin, Milio Kirolos, Zworth Max, Gupta Arnav, Bhasin Arrti, Bartoszko Jessica J, Kiflen Michel, Morassut Rita E, Noor Salmi T, Lawson Daeria O, Johnston Bradley C, Bangdiwala Shrikant I, de Souza Russell J
Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.
Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
Curr Dev Nutr. 2019 Sep 17;3(10):nzz104. doi: 10.1093/cdn/nzz104. eCollection 2019 Oct.
Observational studies provide important information about the effects of exposures that cannot be easily studied in clinical trials, such as nutritional exposures, but are subject to confounding. Investigators adjust for confounders by entering them as covariates in analytic models.
The aim of this study was to evaluate the reporting and credibility of methods for selection of covariates in nutritional epidemiology studies.
We sampled 150 nutritional epidemiology studies published in 2007/2008 and 2017/2018 from the top 5 high-impact nutrition and medical journals and extracted information on methods for selection of covariates.
Most studies did not report selecting covariates a priori (94.0%) or criteria for selection of covariates (63.3%). There was general inconsistency in choice of covariates, even among studies investigating similar questions. One-third of studies did not acknowledge potential for residual confounding in their discussion.
Studies often do not report methods for selection of covariates, follow available guidance for selection of covariates, nor discuss potential for residual confounding.
观察性研究提供了有关暴露因素影响的重要信息，这些暴露因素在临床试验中不易研究，如营养暴露，但容易受到混杂因素的影响。研究人员通过将混杂因素作为协变量纳入分析模型来对其进行调整。
本研究旨在评估营养流行病学研究中协变量选择方法的报告情况和可信度。
我们从排名前五的高影响力营养与医学期刊中抽取了2007/2008年和2017/2018年发表的150项营养流行病学研究，并提取了协变量选择方法的相关信息。
大多数研究未报告预先选择协变量的情况（94.0%）或协变量选择标准（63.3%）。即使在研究相似问题的研究中，协变量的选择也普遍不一致。三分之一的研究在讨论中未承认存在残余混杂的可能性。
研究通常不报告协变量选择方法，不遵循现有的协变量选择指南，也不讨论残余混杂的可能性。
