Evidence map›Paper›PMID 41015581›Full record

SynthesisSocial psychiatry and psychiatric epidemiology2026

Social relationships and risk of cardio-cerebrovascular diseases: a meta-analysis of longitudinal cohort studies.

Zhengkun Liu, Yue Li, Zihan Mei, Ji Li, Xiangyu Yan, Chunxia Cao

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Social psychiatry and psychiatric epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Zhengkun Liu *School of Disaster and Emergency Medicine, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China.
Yue Li *School of Disaster and Emergency Medicine, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China.
Zihan MeiSchool of Disaster and Emergency Medicine, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China.
Ji LiSchool of Disaster and Emergency Medicine, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China.
Xiangyu YanSchool of Disaster and Emergency Medicine, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China. yanxiangyu@tju.edu.cn.
Chunxia CaoSchool of Disaster and Emergency Medicine, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China. caochunxia@tju.edu.cn.

Funding

The National Key R&D Program of China 2023YFF1204104
6 · The paper itself

Abstract

purposeIncreasing evidence supports the existence of an association between social relationships and cardio-cerebrovascular diseases (CCVDs). However, the magnitude of the association between various social relationship factors and CCVDs remains uncertain.

methodsFour databases were systematically searched to investigate the associations between social relationship factors and CCVDs in the general population. The retrieved longitudinal cohort studies were independently subjected to eligibility screening, data extraction, and quality assessment using the modified Newcastle-Ottawa scale by two reviewers. Relative risk (RR) with 95% confidence interval (CI) were pooled using random effects models. We conducted a synthesis across social relationship factors to estimate overall effects for the structural and functional aspects.

resultsThirty cohort studies were included. The meta-analysis revealed that social support (RR: 1.28, 95% CI: 1.11-1.47), social isolation (RR: 1.14, 95% CI: 1.07-1.22), loneliness (RR: 1.21, 95% CI: 1.07-1.37), social integration (RR: 1.16, 95% CI: 1.05-1.27) and social network (RR: 1.49, 95% CI: 1.02-2.18) were significantly associated with CCVDs. Compared with structural aspects of social relationships, functional aspects were associated with a slightly greater CCVD risk (RR: 1.23, 95% CI: 1.13-1.35 vs. RR: 1.14, 95% CI: 1.09-1.20).

conclusionsOur findings confirm that adequate social support, high social integration, and large social networks are associated with a lower CCVD risk, whereas high social isolation and loneliness are associated with a higher risk. Furthermore, functional aspects of social relationships are associated with a slightly greater CCVD risk than structural aspects. This analysis provides evidence that enhancing social relationships may help prevent CCVD.

Indexed as

Cardiovascular DiseasesCerebrovascular DisordersInterpersonal RelationsSocial IsolationSocial SupportHumansLonelinessLongitudinal StudiesRisk FactorsSocial IntegrationCardio-cerebrovascular diseasesLonelinessSocial integration.Social isolationSocial relationshipsSocial support

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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.