Evidence map›Paper›PMID 40873497›Full record

ArticleNature and science of sleep2025

Sleep Duration and Cardiometabolic-Kidney-Metabolic Syndrome: The Role of Depressive Symptoms in a Longitudinal Study.

Yilin Pan, Jingru Bi, Long Feng, Xiaoyun Li

Abstract read
In one paragraph

Article in Nature and science of sleep, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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.

Yilin Pan *Department of Critical Care Medicine, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.ORCID 0000-0002-8143-1544
Jingru Bi *School of Medicine, Nankai University, Tianjin, People's Republic of China.
Long FengDepartment of Critical Care Medicine, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Xiaoyun LiDepartment of Pharmacy, Chun'an County Hospital of Traditional Chinese Medicine, Hangzhou, Zhejiang, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sleep disturbances are increasingly recognized as modifiable risk factors for metabolic and cardiovascular diseases. However, the relationship between sleep duration patterns and Cardiometabolic-Kidney-Metabolic (CKM) syndrome remains underexplored, particularly regarding the mediating role of mental health factors. This study investigates the longitudinal association between sleep duration and CKM risk, examining whether depressive symptoms mediate this relationship. Methods: We analyzed data from 6462 participants (aged ≥45 years) from the China Health and Retirement Longitudinal Study. Sleep duration was self-reported and categorized as short (<7 hours), optimal (7-9 hours), or long (>9 hours), with 2-year sleep trajectories also defined. CKM syndrome was classified per American Heart Association guidelines, and depressive symptoms were assessed via the 10-item Center for Epidemiologic Studies Depression Scale. Associations were examined using multivariable logistic regression, restricted cubic splines, and causal mediation analysis. Results: Baseline short sleep duration was independently associated with increased CKM risk (adjusted OR = 1.148; 95% CI: 1.014-1.299). Persistently abnormal sleep over two years further elevated this risk (OR = 1.259; 95% CI: 1.077-1.471). We observed a significant non-linear dose-response relationship between sleep duration and CKM risk (P = 0.031). Causal mediation analysis showed that depressive symptoms partially mediated this association (ACME = -0.002; P < 0.001). Subgroup analyses revealed stronger associations among women, individuals with lower education, and urban residents. Conclusion: Both short and persistently abnormal sleep independently increase CKM syndrome risk, with depressive symptoms acting as a key mediator. These findings highlight the importance of integrated interventions targeting sleep optimization and mental health management, particularly for high-risk demographic subgroups. Sleep assessment should be incorporated into CKM risk stratification and prevention strategies.

Indexed as

cardiometabolic-kidney-metabolic syndromedepressive symptomslongitudinal studymediation analysissleep duration

Identifiers

PMID40873497
PMCPMC12379983

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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.