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Journal of
Preventive Medicine
& Public Health
166
Copyright © 2021 The Korean Society for Preventive Medicine
J Prev Med Public Health 2021;54:166-172 • https://doi.org/10.3961/jpmph.21.069
Introduction to Mediation Analysis and Examples of Its
Application to Real-world Data
Sun Jae Jung
1,2
1
Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea;
2
Department of Public Health, Yonsei University Graduate
School, Seoul, Korea
Special Article
Traditional epidemiological assessments, which mainly focused on evaluating the statistical association between two major compo-
nents—the exposure and outcome—have recently evolved to ascertain the in-between process, which can explain the underlying
causal pathway. Mediation analysis has emerged as a compelling method to disentangle the complex nature of these pathways. The
statistical method of mediation analysis has evolved from simple regression analysis to causal mediation analysis, and each amend-
ment refined the underlying mathematical theory and required assumptions. This short guide will introduce the basic statistical
framework and assumptions of both traditional and modern mediation analyses, providing examples conducted with real-world data.
Key words: Mediation analysis, Epidemiology, Humans, Logic, Probability
Received:
February 9, 2021
Accepted:
April 29, 2021
Corresponding author:
Sun Jae Jung
Department of Preventive Medicine, Yonsei University College of
Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
E-mail:
sunjaejung@yuhs.ac
This is an Open Access article distributed under the terms of the Creative Commons
Attribution Non-Commercial License (https://creativecommons.org/licenses/by-
nc/4.0/) which permits unrestricted non-commercial use, distribution, and repro-
duction in any medium, provided the original work is properly cited.
INTRODUCTION
In the early days, traditional analytic epidemiological meth-
ods mainly focused on the statistical association between two
major variables: the exposure (E) and the outcome (Y). How-
ever, methods have evolved to explore the “black box” be-
tween the E and the Y by investigating the mechanism under-
lying the association and various pathways. In the same con-
text, the mechanism has also been visualized as being near the
center of “Chinese boxes,” or a set of nested boxes. The “black
box” is presumed to contain factors, both above and below the
level of the individual—the factors above the individual may
contain items such as interpersonal dynamics and socioeco-
pISSN 1975-8375 eISSN 2233-4521
nomic status, including items related to ethnicity and politics,
whereas the factors below the individual level comprise genes,
proteins, cells, and organ systems [1].
Mediation analysis was developed to assess this “black box,”
and psychologists and social scientists have utilized this frame-
work particularly frequently. Mediation analysis can explore
and evaluate biological or social mechanisms, thereby eluci-
dating unknown biological pathways and/or aiding in policy-
making [2]. However, because of advances in methodologies,
including biostatistics, epidemiological research designs, and
causal inference, traditional mediation analysis has evolved
and been applied in various elds. In particular, the concept of
mediation analysis has been especially appealing in social sci-
ences and psychology. There are several overviews of these
topics [3-6], and this study is a guide to the full literature.
TRADITIONAL REGRESSION-BASED
MEDIATION ANALYSIS
Mediation was initially hypothesized as a variable in the
middle of a causal chain. Previously, most of the epidemiologi-