Evidence map›Paper›PMID 41629986›Full record

ArticleBMC psychology2026

Evaluating potential effect of adverse childhood experiences on depressive symptoms in Chinese middle-aged and older adults: a simulation-based network analysis.

Yingjun Guan, Jiapeng Zhang, Hairong Gu, Lixia Yu

Abstract read
In one paragraph

Article in BMC psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yingjun GuanDepartment of Nursing, Medical College, Jiaying University, Meizhou, Guangdong Province, China.
Jiapeng ZhangDepartment of Nursing, Medical College, Jiaying University, Meizhou, Guangdong Province, China.
Hairong GuDepartment of Nursing, Medical College, Jiaying University, Meizhou, Guangdong Province, China.
Lixia YuDepartment of Nursing, Medical College, Jiaying University, Meizhou, Guangdong Province, China. meizhouylx@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost studies examining the association between adverse childhood experiences (ACEs) and depressive symptoms using traditional regression analyses fail to capture how specific types of ACEs relate to certain depressive symptoms, thereby impeding deeper insight into their associations. A simulation-based network analysis provides a novel approach to explore these complex interrelationships.

objectivesThis study aims to explore the complex relationship between ACEs and depressive symptoms, and to identify the types of ACEs that most strongly influence depressive symptoms among middle-aged and older.

methodsWe conducted a secondary analysis of data from the China Health and Retirement Longitudinal Study. Depressive symptoms were assessed using 10-item Center for Epidemiologic Studies Depression Scale. 8 ACEs indicators were obtained through self-reported questionnaires. The Ising model was used to estimate the network structure and analyze the bridge indices of each node. The NodeIdentifyR algorithm was applied to simulate the effects of hypothetically decreasing or increasing the activation of individual ACE nodes on the summed scores of the depressive symptom network. An age-stratified analysis (45–60 vs. ≥60 years) was further conducted to test the robustness of the results.

resultsThe final analysis included 13,771 participants aged ≥ 45 years. The Ising model indicated that household mental illness (HMI) showed the highest bridge centrality. Under hypothetical scenarios of increased node activation, HMI was associated with the largest increase in overall depressive symptom network activation, suggesting a critical risk factor for symptom worsening. In contrast, under hypothetical scenarios of reduced node activation, parental death (PD) showed the greatest reduction in projected depressive symptom sum scores, indicating that PD could have a propelling effect on depressive symptom levels. An age-stratified analysis reached consistent results. DISCUSSION: Our findings indicate that HMI and PD represent critical markers for early detection of depression risk in middle-aged and older adults.

Indexed as

Adverse Childhood ExperiencesDepressionAgedChinaEast Asian PeopleFemaleHumansLongitudinal StudiesMaleMiddle AgedAdverse childhood experiencesDepressive symptomsNetwork analysisNIRA

Identifiers

PMID41629986
PMCPMC12952141

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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.