背景:当研究人员调整从暴露到结果的因果途径的解释变量时,就会发生过度调整偏差,这导致对暴露的因果效应的估计有偏差。本元研究综述旨在研究先前对健康领域社会经济不平等的系统评价和荟萃分析如何管理过度调整偏差。
方法:我们搜索了Medline和Embase,直到2021年4月16日,对任何人群中个体水平的社会经济地位与健康结果之间的关联进行系统评价和荟萃分析。制定了一套标准,以检查纳入审查(评级为是/否/有些/不清楚)所采用的过度调整偏见的方法学方法。
结果:84篇评论符合资格(47篇系统评论,37元分析)。关于过度调整的方法,而在84条评论中,有73%的人被评为“是”,因为他们清楚地定义了风险敞口和结果,对于<55%的评论,所有其他方法都被评为是;例如,5%明确定义的混杂因素和中介,2%构建了因果图,35%报告了纳入研究的调整变量。而只有2%的人在偏见风险评估中包括过度调整,54%包括混杂因素。在37项荟萃分析中,16%的人进行了与过度调整相关的敏感性分析。
结论:我们的研究结果表明,过度调整偏差在健康社会经济不平等的系统评价和荟萃分析中没有得到足够的考虑。这是一个关键问题,因为过度调整偏差可能导致对健康不平等的估计有偏差,需要准确的估计来为公共卫生干预提供信息。有必要强调审查指南中的过度调整偏差。
BACKGROUND: Overadjustment bias occurs when researchers adjust for an explanatory variable on the causal pathway from exposure to outcome, which leads to biased estimates of the causal effect of the exposure. This meta-research review aimed to examine how previous systematic reviews and meta-analyses of socio-economic inequalities in health have managed overadjustment bias.
METHODS: We searched Medline and Embase until 16 April 2021 for systematic reviews and meta-analyses of observational studies on associations between individual-level socio-economic position and health outcomes in any population. A set of criteria were developed to examine methodological approaches to overadjustment bias adopted by included reviews (rated Yes/No/Somewhat/Unclear).
RESULTS: Eighty-four reviews were eligible (47 systematic reviews, 37 meta-analyses). Regarding approaches to overadjustment, whereas 73% of the 84 reviews were rated as Yes for clearly defining exposures and outcomes, all other approaches were rated as Yes for <55% of reviews; for instance, 5% clearly defined confounders and mediators, 2% constructed causal diagrams and 35% reported adjusted variables for included studies. Whereas only 2% included overadjustment in risk of bias assessment, 54% included confounding. Of the 37 meta-analyses, 16% conducted sensitivity analyses related to overadjustment.
CONCLUSIONS: Our findings suggest that overadjustment bias has received insufficient consideration in systematic reviews and meta-analyses of socio-economic inequalities in health. This is a critical issue given that overadjustment bias is likely to result in biased estimates of health inequalities and accurate estimates are needed to inform public health interventions. There is a need to highlight overadjustment bias in review guidelines.