Journal of Preventive Medicine and Public Health

Original Articles

Mental Disorders Mediate the Relationship Between Adverse Childhood Experiences and Suicidal Behavior in a High-risk Population: A Counterfactual Analysis From Jeju Island: Yeon Woo Oh, Dongkyu Lee, Young-Eun Jung, Sun Jae Jung; J Prev Med Public Health. 2025;58(5):505-515. Published online May 7, 2025; DOI: https://doi.org/10.3961/jpmph.25.120

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Abstract Summary PDF Supplementary Material: Objectives
Jeju Island, Korea, is characterized by a significantly higher prevalence of adverse childhood experiences (ACE, 32.4%), elevated rates of mental disorders (34.6 vs. 22.9%), and lifetime suicidal thoughts (20.6 vs. 10.7%) compared to national averages. We investigated the mediating role of mental disorders in the pathway from ACE to suicidal behavior in Jeju.
Methods
Data from the Jeju Special Self-Governing Province Mental Health Survey 2023 (n=703) were analyzed. Exposure was defined as experiencing at least one ACE from the 10-item Adverse Childhood Experience International Questionnaire. Depressive disorder, anxiety disorder, and alcohol use disorder were diagnosed using the Korean-Composite International Diagnostic Interview. Suicidal behavior was defined as experiencing suicidal ideation, planning, or attempts. A counterfactual mediation model was used to evaluate the natural direct effect and natural indirect effect (NIE) of mental disorders.
Results
The total effect of ACE on suicidal behavior showed a risk difference of 35.3 percntage points (%p). When considering all three mental disorders simultaneously, the NIE was 27.6%p, accounting for 78.1% of the total effect. Stratification analyses revealed stronger total effects in women and older adults, while the proportion mediated was higher in women and younger adults.
Conclusions
In this ACE-prevalent population, mental disorders collectively mediated approximately three-quarters of the pathway from ACE to suicidal behavior. These findings, derived through robust counterfactual analysis, suggest that strengthening screening and management protocols for mental disorders among adults with a history of ACE may effectively prevent suicide in populations with high ACE prevalence.; Summary

Korean summary
이 연구는 제주도 성인 인구를 대상으로 아동기 역경 경험(ACE)이 자살 행동에 미치는 영향 중 정신질환(우울, 불안, 알코올 사용장애)이 약 78%를 매개한다는 것을 확인했다. 이는 ACE가 높은 지역사회에서 정신질환 대한 체계적인 선별검사와 관리가 자살 예방에 효과적일 수 있음을 시사한다.

Key Message
This study found that mental disorders(depression, anxiety, and alcohol use disorders) mediate approximately 78% of the pathway from adverse childhood experiences (ACE) to suicidal behavior in Jeju Island's adult population. The findings suggest that systematic screening and management of mental disorders could effectively prevent suicide in communities with high ACE prevalence.

Association Between Parental BMI and Offspring’s Blood Pressure by Mediation Analysis: A Study Using Data From the Korean National Health and Nutrition Examination Survey: Hyowon Choi, Hunju Lee, Yeon-Soon Ahn; J Prev Med Public Health. 2023;56(6):533-541. Published online October 30, 2023; DOI: https://doi.org/10.3961/jpmph.23.289

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Abstract Summary PDF Supplementary Material: Objectives
This study analyzed the relationship between parental body mass index (BMI; BMI_p) and hypertension in their adolescent offspring (HTN_a), focusing on the mediating effect of adolescents’ BMI (BMI_a).
Methods
Utilizing data from the Korea National Health and Nutrition Examination Survey, including participants aged 12-18, we conducted a mediation analysis while controlling for confounding factors such as age, sex, physical activity, dietary habits, household income quartile, and parents’ alcohol and smoking habits.
Results
The study included a total of 5731 participants, of whom 3381 and 5455 participants had data on fathers’ and mothers’ BMI, respectively. For adolescent systolic blood pressure (SBP_a), the father’s BMI (BMI_f) had a significant total effect (β, 0.23; 95% confidence interval [CI], 0.12 to 0.34) and average controlled mediated effect (ACME) (β, 0.27; 95% CI, 0.23 to 0.32), but the average direct effect (ADE) was not significant. The mother’s BMI (BMI_m) had a significant total effect (β, 0.17; 95% CI, 0.09 to 0.25), ACME (β, 0.25; 95% CI, 0.22 to 0.28) and ADE (β, -0.08; 95% CI, -0.16 to 0.00). For adolescent diastolic blood pressure, both BMI_f and BMI_m had significant ACMEs (β, 0.10; 95% CI, 0.08 to 0.12 and β, 0.09; 95% CI, 0.07 to 0.12, respectively), BMI_m had a significant ADE (β, -0.09; 95% CI, -0.16 to -0.02) but BMI_f had an insignificant ADE and total effect.
Conclusions
The study found that parental BMI had a significant effect on SBP_a, mediated through BMI_a. Therefore, a high BMI in parents could be a risk factor, mediated through BMI_a, for systolic hypertension in adolescents, necessitating appropriate management.; Summary

Korean summary
본 연구를 통해 부모의 BMI가 청소년기의 BMI를 매개하여 청소년의 수축기 혈압에 영향을 미침을 확인할 수 있었습니다. 그러나 본 연구는 단면적인 데이터를 활용하였으며, 후향적 연구로 이에 대한 한계를 가지고 있으며, 이후 이에 대한 추가 연구가 필요합니다.

Key Message
This study was able to confirm that parents' BMI mediated their BMI during adolescence and affected systolic blood pressure in adolescents. However, this study utilized cross-sectional data, and has limitations on this as a retrospective study, so further studies are needed.

Special Articles

An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages: Sangmin Byeon, Woojoo Lee; J Prev Med Public Health. 2023;56(4):303-311. Published online July 31, 2023; DOI: https://doi.org/10.3961/jpmph.23.189

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17 Crossref

Abstract Summary PDF Supplementary Material

Traditional mediation analysis, which relies on linear regression models, has faced criticism due to its limited suitability for cases involving different types of variables and complex covariates, such as interactions. This can result in unclear definitions of direct and indirect effects. As an alternative, causal mediation analysis using the counterfactual framework has been introduced to provide clearer definitions of direct and indirect effects while allowing for more flexible modeling methods. However, the conceptual understanding of this approach based on the counterfactual framework remains challenging for applied researchers. To address this issue, the present article was written to highlight and illustrate the definitions of causal estimands, including controlled direct effect, natural direct effect, and natural indirect effect, based on the key concept of nested counterfactuals. Furthermore, we recommend using 2 R packages, ‘medflex’ and ‘mediation’, to perform causal mediation analysis and provide public health examples. The article also offers caveats and guidelines for accurate interpretation of the results.

Summary

Korean summary
전통적 매개분석은 여러 유형의 변수 혹은 복잡한 상호작용을 포함할 경우, 직접 및 간접효과의 정의가 불분명하다는 비판에 직면해왔다. 이에 대한 대안으로서 인과매개분석은 반사실적 개념에 기반하여 직접 및 간접효과를 명료하게 정의하며 유연한 모델링을 가능하게 한다. 다만 이 새로운 접근의 주요 개념을 응용 연구자들이 이해하는 데에는 다소 어려운 측면이 있다. 이러한 점에서 이 논문에서는 중첩된 반사실적 변수에 기반한 인과적 모수의 정의를 상술하고 인과매개분석을 위한 대표적인 R 패키지인 medflex 및 mediation을 활용하여 공공 보건 사례에 대한 분석 실례 및 유의사항을 제공하였다.

Citations

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Introduction to Mediation Analysis and Examples of Its Application to Real-world Data: Sun Jae Jung; J Prev Med Public Health. 2021;54(3):166-172. Published online May 7, 2021; DOI: https://doi.org/10.3961/jpmph.21.069

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Abstract Summary PDF

Traditional epidemiological assessments, which mainly focused on evaluating the statistical association between two major components-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 amendment 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.

Summary

Korean summary
본 리뷰에서는 전통적으로 쓰여왔던 회귀분석 기반 매개요인분석방법과 인과적 매개요인분석방법에 대하여 간략히 소개하며, 또한 예시를 들어 설명하고 있다. 매개요인 분석 전에는 필요한 가정들이 맞는 지를 확인하는 것이 중요하다. 또한 분석결과를 올바르게 해석하는 것 또한 요구된다. 이러한 방법은 그동안의 노출-결과만을 다루는 단순 역학연구을 뛰어넘어, 인구집단연구에서 매커니즘을 밝히는 도구로서 유용하게 쓰일 것이다.

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