ArticleClinical and experimental nephrology2025
Association of sleep parameters with kidney function: analysis of baseline data from 9216 adults in the Fasa Adult Cohort Study (FACS).
Article in Clinical and experimental nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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Who cites it
2 citing papers in PubMed.
- Cross-sectional and longitudinal associations between fatty liver index and kidney function using updated MASLD and CKD-EPI 2021 definitions: a population-based study with region-specific cutoffs.European journal of medical research · 2025Article
- Inappropriate GFR equations misrepresent CKD epidemiology and risk interpretation in scientific reports.BMC nephrology · 2025Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe evidence on the impact of sleep parameters on kidney function and chronic kidney disease (CKD) risk is inconsistent and warrants further research across diverse populations. Our study investigates the relationship between sleep and kidney function in both healthy individuals and those with CKD.
methodsThis cross-sectional study analyzed data from 9216 adults aged 35-70. Various sleep parameters were assessed and calculated using the Pittsburgh Sleep Quality Questionnaire. Kidney function was assessed by estimated glomerular filtration rate (eGFR), with CKD characterized as eGFR < 60 mL/min/1.73 m
resultsIn general, sleep duration (β: 0.18, 95% CI0.06, 0.30, p value < 0.001) and sleep efficiency (β: 0.03, 95% CI 0.01, 0.05, p value = 0.02) were positively correlated with GFR, while sleep latency (β: - 0.01, 95%CI - 0.02, 0.00, p value < 0.001) and daily naps (β: - 1.33, 95%CI - 1.76, - 0.90, p value < 0.001) were negatively correlated with GFR. Similarly, for those without CKD, sleep duration (β: 0.23, 95%CI 0.1, 0.36, p value < 0.001) and sleep efficiency (β: 0.04, 95%CI 0.01, 0.06, p value = 0.002) positively and sleep latency (β: - 0.01, 95%CI - 0.02, 0.00, p value = 0.002) and daily naps (β: - 1.02, 95%CI - 1.65, - 0.74, p value < 0.001) negatively were correlated with GFR. These associations were not significant in individuals with CKD.
conclusionEnhancing sleep duration, decreasing sleep latency, improving sleep efficiency, and minimizing daytime napping could potentially boost kidney function. The linear relationships suggest that even slight changes in sleep could affect GFR in non-CKD individuals. Although our statistically significant effect sizes show a small clinical impact, their consistent association warrants further exploration over longer periods with longitudinal studies, to assess if improving sleep can prevent declining renal function, potentially delaying the onset of renal issues in non-CKD populations.
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