Evidence map›Paper›PMID 40216835›Full record

ArticleScientific reports2025

CHARLS insights into the impact of dual interactions of chronic diseases on depression in middle-aged and elderly individuals.

Dian-Yin Liang, Xue Chen, Ke-Hua Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Dian-Yin Liang *Department of Public Health, School of Medicine, Guangxi University of Science and Technology, Liuzhou, 545005, China.ORCID https://orcid.org/0000-0003-1354-2581
Xue Chen *Department of Basic Medical Experiment Teaching Center, Yulin Campus of Guangxi Medical University, Yulin, 537000, China.
Ke-Hua LiDepartment of Physiology and Pathophysiology, Yulin Campus of Guangxi Medical University, Yulin, 537000, China. 875885661@qq.com.ORCID https://orcid.org/0009-0002-5416-0213

Funding

Youth Science Foundation of Guangxi Medical University GXMUYSF202332
6 · The paper itself

Abstract

Depression and chronic diseases are closely linked, but the combined impact of multiple chronic diseases on depression is not well understood due to limited research on their interaction. This study aimed to examine how the interaction of chronic diseases influences depression in middle-aged and elderly individuals, and to identify high-risk factors for depression related to these disease interactions. In this study, depression among middle-aged and elderly individuals was designated as the dependent variable. The dataset from the 2015 China Health and Retirement Longitudinal Study (CHARLS) underwent both univariate and multivariate analyses. Subsequently, a dual interaction analysis was performed to examine the significant impact of the number of chronic diseases on depression, complemented by an attribution analysis. Among the 8163 participants, depression was more common in females, unmarried individuals, rural residents, and non-retired (P < 0.05, 0.01 or 0.001). Higher education correlate with lower depression rates. Participants with chronic diseases show higher depression rates than those without (P < 0.05, 0.01, or 0.001). The depression group exhibited lower episodic memory, cognitive ability, and sleep duration (P < 0.05, 0.01, or 0.001). Various factors significantly contribute to depression in middle-aged and elderly individuals (P < 0.05, 0.01 or 0.001). Finally, the majority of chronic diseases have a significant contribution to the occurrence of depression in middle-aged and elderly individuals after dual interaction. Chronic diseases significantly influence depression in middle-aged and elderly individuals, with their dual interaction having a complex effect. While most chronic disease indicators aren't useful for diagnosing depression, memory and cognitive function indicators can help. These should be considered alongside other chronic disease indicators when diagnosing depression.

Indexed as

DepressionAgedChinaChronic DiseaseFemaleHumansLongitudinal StudiesMaleMiddle AgedRisk FactorsChronic diseasesCross-sectional surveyDepressionDual interactionMiddle-aged and elderly individuals

Identifiers

PMID40216835
PMCPMC11992256

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.