start-ver=1.4
cd-journal=joma
no-vol=
cd-vols=
no-issue=
article-no=
start-page=JE20250409
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2025
dt-pub=2025
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Effect modification and its impact on preventable and attributable fractions in the potential outcomes framework
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Background: Policy decisions should be guided by measures that capture the impact of exposures on outcomes and that explicitly account for present-day exposure distribution. Both the preventable and attributable fractions have been used for this purpose; however, exposure effects can vary across subpopulations, and when this occurs, appropriate interpretation of these measures should be facilitated by a discussion of the contributions of different subpopulations.<br>
Methods: We analyze preventable and attributable fractions in the presence of effect modification. In particular, we use potential outcomes to formally define these quantities and to clarify the weighting of different strata in the total population measures.<br>
Results: Our derivations show that stratum-specific preventable and attributable fractions are weighted in proportion to the relative frequencies of effect modifiers among individuals with the outcome of interest. We also demonstrate that these weights are valid for the related quantities, preventable and attributable proportions. Finally, we present an example that illustrates how effect modification affects interpretation of these measures.<br>
Conclusions: In sum, when effect modification is present, investigators should consider reporting these measures by the relevant population strata, and information that would allow quantification of their implicit weights in the total population estimate. Our study provides a formal justification for this approach.
en-copyright=
kn-copyright=

en-aut-name=GonçalvesBronner P.
en-aut-sei=Gonçalves
en-aut-mei=Bronner P.
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=SuzukiEtsuji
en-aut-sei=Suzuki
en-aut-mei=Etsuji
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

affil-num=1
en-affil=Faculty of Health and Medical Sciences, University of Surrey
kn-affil=

affil-num=2
en-affil=Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=preventable fraction
kn-keyword=preventable fraction
en-keyword=attributable fraction
kn-keyword=attributable fraction
en-keyword=effect modification
kn-keyword=effect modification
en-keyword=causality
kn-keyword=causality
END

start-ver=1.4
cd-journal=joma
no-vol=32
cd-vols=
no-issue=12
article-no=
start-page=567
end-page=569
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=20221205
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Association Between Fever and Antibody Titer Trends After a Third Dose of the mRNA-1273 Vaccine
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=
en-copyright=
kn-copyright=

en-aut-name=MatsumotoNaomi
en-aut-sei=Matsumoto
en-aut-mei=Naomi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=KadowakiTomoka
en-aut-sei=Kadowaki
en-aut-mei=Tomoka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

en-aut-name=MatsuoRumi
en-aut-sei=Matsuo
en-aut-mei=Rumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=

en-aut-name=SasakiAyako
en-aut-sei=Sasaki
en-aut-mei=Ayako
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=

en-aut-name=MiyajiChikara
en-aut-sei=Miyaji
en-aut-mei=Chikara
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=

en-aut-name=HiguchiChigusa
en-aut-sei=Higuchi
en-aut-mei=Chigusa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=

en-aut-name=NakayamaMasanori
en-aut-sei=Nakayama
en-aut-mei=Masanori
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=

en-aut-name=SakuradaYasue
en-aut-sei=Sakurada
en-aut-mei=Yasue
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=

en-aut-name=HagiyaHideharu
en-aut-sei=Hagiya
en-aut-mei=Hideharu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=

en-aut-name=TakaoSoshi
en-aut-sei=Takao
en-aut-mei=Soshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=

en-aut-name=OtsukaFumio
en-aut-sei=Otsuka
en-aut-mei=Fumio
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=11
ORCID=

en-aut-name=YorifujiTakashi
en-aut-sei=Yorifuji
en-aut-mei=Takashi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=12
ORCID=

affil-num=1
en-affil=Department of Epidemiology, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=

affil-num=2
en-affil=Department of Epidemiology, Okayama University Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences
kn-affil=

affil-num=3
en-affil=Department of Epidemiology, Okayama University Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences
kn-affil=

affil-num=4
en-affil=Department of Epidemiology, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=

affil-num=5
en-affil=Okayama University Health Service Center
kn-affil=

affil-num=6
en-affil=Okayama University Health Service Center
kn-affil=

affil-num=7
en-affil=Office of Innovative Medicine, Organization for Research Strategy and Development, Okayama University
kn-affil=

affil-num=8
en-affil=Department of General Medicine, Okayama University Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences
kn-affil=

affil-num=9
en-affil=Department of General Medicine, Okayama University Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences
kn-affil=

affil-num=10
en-affil=Department of Epidemiology, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=

affil-num=11
en-affil=Department of General Medicine, Okayama University Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences
kn-affil=

affil-num=12
en-affil=Department of Epidemiology, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=SARS-CoV-2
kn-keyword=SARS-CoV-2
en-keyword=mRNA-1273
kn-keyword=mRNA-1273
en-keyword=antibody
kn-keyword=antibody
en-keyword=reactogenicity
kn-keyword=reactogenicity
en-keyword=adverse reaction
kn-keyword=adverse reaction
END

start-ver=1.4
cd-journal=joma
no-vol=33
cd-vols=
no-issue=2
article-no=
start-page=110
end-page=111
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2023
dt-pub=20230205
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Adverse Reactions and Attitudes Toward the BNT162b2 COVID-19 Vaccine in Children 5 to 11 Years of Age in Japan
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=
en-copyright=
kn-copyright=

en-aut-name=MatsumotoNaomi
en-aut-sei=Matsumoto
en-aut-mei=Naomi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=ShimizuJunya
en-aut-sei=Shimizu
en-aut-mei=Junya
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

en-aut-name=YokoyamaYuji
en-aut-sei=Yokoyama
en-aut-mei=Yuji
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=

en-aut-name=TsukaharaHirokazu
en-aut-sei=Tsukahara
en-aut-mei=Hirokazu
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=

en-aut-name=YorifujiTakashi
en-aut-sei=Yorifuji
en-aut-mei=Takashi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=

affil-num=1
en-affil=Department of Epidemiology, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=

affil-num=2
en-affil=Department of Pediatrics, National Hospital Organization, Okayama Medical Center
kn-affil=

affil-num=3
en-affil=Department of Pediatrics, Okayama Aiiku Clinic
kn-affil=

affil-num=4
en-affil=Department of Pediatrics, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=

affil-num=5
en-affil=Department of Epidemiology, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
END

start-ver=1.4
cd-journal=joma
no-vol=30
cd-vols=
no-issue=1
article-no=
start-page=12
end-page=14
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2020
dt-pub=20200105
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Lessons From an Early-stage Epidemiological Study of Minamata Disease
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=
en-copyright=
kn-copyright=

en-aut-name=YorifujiTakashi
en-aut-sei=Yorifuji
en-aut-mei=Takashi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

affil-num=1
en-affil=Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=
en-keyword=environment and public health
kn-keyword=environment and public health
en-keyword=epidemiology
kn-keyword=epidemiology
en-keyword=food contamination
kn-keyword=food contamination
en-keyword=methylmercury compounds
kn-keyword=methylmercury compounds
en-keyword=Minamata disease
kn-keyword=Minamata disease
END

start-ver=1.4
cd-journal=joma
no-vol=30
cd-vols=
no-issue=4
article-no=
start-page=153
end-page=162
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2020
dt-pub=20200405
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Causal Diagrams: Pitfalls and Tips
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Graphical models are useful tools in causal inference, and causal directed acyclic graphs (DAGs) are used extensively to determine the variables for which it is sufficient to control for confounding to estimate causal effects. We discuss the following ten pitfalls and tips that are easily overlooked when using DAGs: 1) Each node on DAGs corresponds to a random variable and not its realized values; 2) The presence or absence of arrows in DAGs corresponds to the presence or absence of individual causal effect in the population; 3) "Non-manipulable" variables and their arrows should be drawn with care; 4) It is preferable to draw DAGs for the total population, rather than for the exposed or unexposed groups; 5) DAGs are primarily useful to examine the presence of confounding in distribution in the notion of confounding in expectation; 6) Although DAGs provide qualitative differences of causal structures, they cannot describe details of how to adjust for confounding; 7) DAGs can be used to illustrate the consequences of matching and the appropriate handling of matched variables in cohort and case-control studies; 8) When explicitly accounting for temporal order in DAGs, it is necessary to use separate nodes for each timing; 9) In certain cases, DAGs with signed edges can be used in drawing conclusions about the direction of bias; and 10) DAGs can be (and should be) used to describe not only confounding bias but also other forms of bias. We also discuss recent developments of graphical models and their future directions.
en-copyright=
kn-copyright=

en-aut-name=SuzukiEtsuji
en-aut-sei=Suzuki
en-aut-mei=Etsuji
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=ShinozakiTomohiro
en-aut-sei=Shinozaki
en-aut-mei=Tomohiro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

en-aut-name=YamamotoEiji
en-aut-sei=Yamamoto
en-aut-mei=Eiji
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=

affil-num=1
en-affil=Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
kn-affil=

affil-num=2
en-affil=Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science
kn-affil=

affil-num=3
en-affil=Okayama University of Science
kn-affil=
en-keyword=bias
kn-keyword=bias
en-keyword=causal inference
kn-keyword=causal inference
en-keyword=causality
kn-keyword=causality
en-keyword=confounding
kn-keyword=confounding
en-keyword=directed acyclic graphs
kn-keyword=directed acyclic graphs
END

start-ver=1.4
cd-journal=joma
no-vol=29
cd-vols=
no-issue=4
article-no=
start-page=123
end-page=124
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2018
dt-pub=20180915
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Long-term Trends in Prevalence of Neural Tube Defects in Japan
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=
en-copyright=
kn-copyright=

en-aut-name=YorifujiTakashi
en-aut-sei=Yorifuji
en-aut-mei=Takashi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

affil-num=1
en-affil=Department of Human Ecology, Graduate School of Environmental and Life Science, Okayama University
kn-affil=
en-keyword=dietary supplements
kn-keyword=dietary supplements
en-keyword= folic acid
kn-keyword= folic acid
en-keyword=fortification of the food supply
kn-keyword=fortification of the food supply
en-keyword=long-term trend
kn-keyword=long-term trend
en-keyword=neural tube defects
kn-keyword=neural tube defects
en-keyword=spina bifida
kn-keyword=spina bifida
END