| Title: | Daytime Napping, Incident Atrial Fibrillation, and Dynamic Transitions With Dementia |
| Journal: | JACC Advances |
| Published: | 1 Aug 2024 |
| DOI: | https://doi.org/10.1016/j.jacadv.2024.101108 |
Publication 12725
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Abstract
Background Associations between napping and incident atrial fibrillation (AF) remain unknown, and few studies have accounted for dynamic transitions between AF and dementia. Objectives The purpose of this study was to evaluate associations between napping with incident AF and the dynamic transitions of AF and dementia, as well as the mediation pathway of left ventricular (LV) size and function. Methods A total of 476,588 participants from UK Biobank were included. Napping frequency and other sleep behaviors were evaluated. Incident AF, dementia, and mortality were ascertained via linkage to external registry databases. LV size and function indices were obtained from cardiovascular magnetic resonance imaging phenotypes. A multistate survival analysis was conducted to examine daytime napping in relation to dynamic transitions. Weighed AF genetic risk score was calculated. Results Frequent daytime napping, compared to never/rarely napping, was associated with a 1.17-fold AF risk (HR: 1.17; 95% CI: 1.12-1.22), which persisted after controlling for other sleep behaviors. Genetic predisposition significantly modified associations between napping and AF (P for interaction <0.001), with stronger associations observed in those of low and moderate genetic risk. LV ejection fraction significantly mediated 26.2% (95% CI: 4.2%-74.1%) of associations between napping and AF. Frequent napping was also associated with a 1.27-fold risk of transition from AF to comorbidity of AF and dementia. Conclusions Our findings highlight the potential importance of screening for napping in view of the association with incident AF and dementia. Routine evaluations of the LV ejection fraction could be warranted to timely identify early indications of AF onset among habitual nappers.</p>
4 Authors
- Chenglong Li
- Daijun He
- Chao Yang
- Luxia Zhang
1 Application
| Application ID | Title |
|---|---|
| 90018 | Environment, genotype, AI-derived phenotype, and the risk of cardiovascular diseases, metabolic diseases, and chronic kidney disease |
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