UMMS Affiliation

Department of Quantitative Health Sciences; Clinical and Population Health Research Program, Graduate School of Biomedical Sciences

Publication Date

7-20-2016

Document Type

Article

Disciplines

Clinical Epidemiology | Epidemiology | Health Services Research

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.

Rights and Permissions

Citation: BMC Res Notes. 2016 Jul 20;9(1):354. doi: 10.1186/s13104-016-2163-7. Link to article on publisher's site

Copyright © The Author(s) 2016. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

DOI of Published Version

10.1186/s13104-016-2163-7

Comments

Shao-Hsien Liu is a student in the Clinical and Population Health Research Program of the Graduate School of Biomedical Sciences at UMass Medical School.

Related Resources

Link to Article in PubMed

Keywords

Causal inference, Causal mediation analysis, Causality, Systematic review

Journal/Book/Conference Title

BMC research notes

PubMed ID

27439301

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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