Implementation and reporting of causal mediation analysis in 2015: a systematic review in epidemiological studies. (December 2016)

• Record Type: Journal Article
• Authors: Liu, Shao-Hsien; Ulbricht, Christine; Chrysanthopoulou, Stavroula; Lapane, Kate
• Is Part Of: BMC research notes. Volume 9:Number 1(2016)
• Page Start: 1
• Page End: 21
• Publication Date: 2016-12
• Subjects: Causal mediation analysis -- Systematic review -- Causal inference -- Causality; Medicine -- Periodicals; Biology -- Periodicals; 610.5
• DOI: 10.1186/s13104-016-2163-7
• Languages: English
• ISSNs: 1756-0500

Abstract

Abstract Background Causal mediation analysis is often used to understand the impact of variables along the causal pathway of an occurrence relation. How well studies apply and report the elements of causal mediation analysis remains unknown. Methods We systematically reviewed epidemiological studies published in 2015 that employed causal mediation analysis to estimate direct and indirect effects of observed associations between an exposure on an outcome. We identified potential epidemiological studies through conducting a citation search within Web of Science and a keyword search within PubMed. Two reviewers independently screened studies for eligibility. For eligible studies, one reviewer performed data extraction, and a senior epidemiologist confirmed the extracted information. Empirical application and methodological details of the technique were extracted and summarized. Results Thirteen studies were eligible for data extraction. While the majority of studies reported and identified the effects of measures, most studies lacked sufficient details on the extent to which identifiability assumptions were satisfied. Although most studies addressed issues of unmeasured confounders either from empirical approaches or sensitivity analyses, the majority did not examine the potential bias arising from the measurement error of the mediator. Some studies allowed for exposure-mediator interaction and only a few presented results from models both with and without interactions. Power calculations were scarce. Conclusions Reporting of causal mediation analysis is varied and suboptimal. Given that the application of causal mediation analysis will likely continue to increase, developing standards of reporting of causal mediation analysis in epidemiological research would be prudent.