Evidence map›Paper›PMID 40760830›Full record

ArticleBrain and behavior2025

Association Between Trajectories of Depressive Symptoms and Cardiovascular Disease in Elderly Chinese Adults: Findings From the China Health and Retirement Longitudinal Study (CHARLS).

Danhua Wang, Qiannan Chen, Apei Jiang, Xianzhen Peng

Abstract read
In one paragraph

Article in Brain and behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

4 authors.

Danhua Wang *Department of Public Health and Preventive Medicine, Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.ORCID https://orcid.org/0000-0002-2402-8775
Qiannan Chen *Department of Public Health and Preventive Medicine, Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Apei JiangDepartment of Public Health and Preventive Medicine, Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Xianzhen PengDepartment of Public Health and Preventive Medicine, Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.

Funding

2023 Soft Science Research Project of Lianyungang Association for Science and TechnologResearch Program of Kangda College of Nanjing Medical University
6 · The paper itself

Abstract

backgroundAlthough the association between depressive symptoms and cardiovascular disease (CVD) has been widely investigated, most existing studies have relied on single-timepoint assessments of depression. Examining longitudinal trajectories of depressive symptoms may provide deeper insights into the dynamic and complex relationship between depression and CVD risk.

methodsBased on data from the China Health and Retirement Longitudinal Study (CHARLS), this study analyzed the relationship between depressive symptom trajectories and CVD risk through logistic regression modeling and latent category growth modeling (LCGM) and explored causality using two-sample Mendelian randomisation (MR).

resultsThe study found four depressive symptom trajectories among Chinese older adults: low-level symptoms, symptom relief, symptom worsening, and high-level symptoms. Compared with the low-level symptom group, the symptom relief, symptom worsening, and high-level symptom groups had a significantly increased risk of CVD, with ORs of 1.51, 1.60, and 2.87, respectively (all P values < 0.05). MR analyses also showed a significant association between depressive symptoms and CVD risk.

conclusionsThe study indicates that longitudinal assessment of depressive symptom trajectories provides a more robust prediction of CVD risk compared to single-timepoint assessments.

Indexed as

Cardiovascular DiseasesDepressionAgedAged, 80 and overChinaEast Asian PeopleFemaleHumansLongitudinal StudiesMaleMendelian Randomization AnalysisMiddle AgedRetirementRisk Factorscardiovascular diseasedepressive symptom trajectoriesmendelian randomizationolder adults

Identifiers

PMID40760830
PMCPMC12321971

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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.