Evidence map›Paper›PMID 34689754›Full record

ArticleBMC medical research methodology2021

Mediation analysis methods used in observational research: a scoping review and recommendations.

Judith J M Rijnhart, Sophia J Lamp, Matthew J Valente, David P MacKinnon, Jos W R Twisk, Martijn W Heymans

Abstract readScoping Review
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical research methodology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 173 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
173citing papers in PubMed, 4 pooled it
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

173 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Associations Between the Built Environment and Adult Obesity and the Mediating Role of Physical Activity: A Systematic Review.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2025
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113 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Judith J M RijnhartDepartment of Epidemiology and Data Science, Amsterdam UMC, Location VU University Medical Center, Amsterdam Public Health Research Institute, PO Box 7057, 1007, MB, Amsterdam, The Netherlands. j.rijnhart@amsterdamumc.nl.
Sophia J LampDepartment of Psychology, Arizona State University, Tempe, AZ, USA.
Matthew J ValenteDepartment of Psychology, Center for Children and Families, Florida International University, Miami, FL, USA.
David P MacKinnonDepartment of Psychology, Arizona State University, Tempe, AZ, USA.
Jos W R TwiskDepartment of Epidemiology and Data Science, Amsterdam UMC, Location VU University Medical Center, Amsterdam Public Health Research Institute, PO Box 7057, 1007, MB, Amsterdam, The Netherlands.
Martijn W HeymansDepartment of Epidemiology and Data Science, Amsterdam UMC, Location VU University Medical Center, Amsterdam Public Health Research Institute, PO Box 7057, 1007, MB, Amsterdam, The Netherlands.

Funding

Estimating Mediation Effects in Prevention StudiesR37DA009757 · NIDA · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI MACKINNON, DAVID P · 2015 to 2024
$3.5M
NIDA NIH HHS R37 DA009757
6 · The paper itself

Abstract

backgroundMediation analysis methodology underwent many advancements throughout the years, with the most recent and important advancement being the development of causal mediation analysis based on the counterfactual framework. However, a previous review showed that for experimental studies the uptake of causal mediation analysis remains low. The aim of this paper is to review the methodological characteristics of mediation analyses performed in observational epidemiologic studies published between 2015 and 2019 and to provide recommendations for the application of mediation analysis in future studies.

methodsWe searched the MEDLINE and EMBASE databases for observational epidemiologic studies published between 2015 and 2019 in which mediation analysis was applied as one of the primary analysis methods. Information was extracted on the characteristics of the mediation model and the applied mediation analysis method.

resultsWe included 174 studies, most of which applied traditional mediation analysis methods (n = 123, 70.7%). Causal mediation analysis was not often used to analyze more complicated mediation models, such as multiple mediator models. Most studies adjusted their analyses for measured confounders, but did not perform sensitivity analyses for unmeasured confounders and did not assess the presence of an exposure-mediator interaction.

conclusionsTo ensure a causal interpretation of the effect estimates in the mediation model, we recommend that researchers use causal mediation analysis and assess the plausibility of the causal assumptions. The uptake of causal mediation analysis can be enhanced through tutorial papers that demonstrate the application of causal mediation analysis, and through the development of software packages that facilitate the causal mediation analysis of relatively complicated mediation models.

Indexed as

Mediation AnalysisResearch DesignCausalityEpidemiologic StudiesHumansModels, StatisticalObservational Studies as TopicCounterfactualsDirect effectIndirect effectMediation analysisObservational dataPotential outcomes

Identifiers

PMID34689754
PMCPMC8543973

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.