| Title: | Multi-dimensional sleep patterns predict complications and mortality in chronic kidney disease patients: a prospective study from the UK Biobank |
| Journal: | Frontiers in Public Health |
| Published: | 18 Aug 2026 |
| DOI: | https://doi.org/10.3389/fpubh.2026.1889689 |
| URL: | https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2026.1889689/pdf |
Publication 20972
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Abstract
The complex interplay of multiple sleep factors may affect the risk of complications and mortality in the chronic kidney disease (CKD) population. However, few studies have examined multi-dimensional sleep health in CKD populations. Our cohort study included 15,809 participants with laboratory-observed kidney dysfunction or a CKD diagnosis during 2006-2010 from the UK Biobank. Incidence of adverse outcomes was identified via the International Classification of Diseases, 10th Edition (ICD-10) till 2022. The multi-dimensional sleep health was evaluated through an a priori sleep health score (SHS) and sleep health cluster categorized by latent class analysis. The relationships between multi-dimensional sleep health, each sleep factor, and outcomes in CKD were estimated through Cox proportional hazards models. A total of 2,416 deaths, 2,343 anemia, 4,087 CVD, 940 cognitive impairment, and 314 hyperparathyroidism occurred during the follow-up. After adjusting for potential confounders, higher SHS was significantly associated with decreased risks of anemia, CVD, and hyperparathyroidism (all p < 0.05). Severe insomnia with short or long sleep duration and severe disturbed sleep with multiple dysfunctions were significantly associated with 19-54% higher risks of anemia, CVD and hyperparathyroidism. Each sleep factor indicated great heterogeneity in association with adverse outcomes in the CKD population, while gender and kidney function interact with some of these exposures. Poor multi-dimensional sleep health, either estimated by SHS or characterized by sleep clusters, was associated with poor prognosis in the CKD population. The specific sleep profiles in the CKD population contribute to pinpointing high-risk subgroups and providing targeted interventions.</p>
7 Authors
- Kaixin Lei
- Jiameng Li
- Lifan Xu
- Yi Teng
- Chenxi Lu
- Chunxia Qiao
- Wen Guo
1 Application
| Application ID | Title |
|---|---|
| 717009 | Prevention and Prognostic Outcomes of Cardiorenal-Metabolic Syndrome |
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