Geospatial analysis of short sleep duration and cognitive disability in US adults: a multi-state study using machine learning techniques

Our study highlights the importance of short sleep duration as a significant predictor of cognitive disability across the US after adjusting for other confounders. The association between short sleep and cognitive disability was especially strong in the Western region of the US providing a deeper understanding of how geographic context and local factors can shape health outcomes.

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Publication Details

Journal
BioData Mining
Published
2025-06-13
DOI
https://doi.org/10.1186/s13040-025-00456-7
Primary Topic
Sleep and Work-Related Fatigue
Type
article
Field-Weighted Citation Impact
0.00
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article

Geospatial analysis of short sleep duration and cognitive disability in US adults: a multi-state study using machine learning techniques

Alex Bui, Constance H. Fung, Mary Regina Boland, Tue Te
BioData Mining
Sleep and Work-Related Fatigue
article

Geospatial analysis of short sleep duration and cognitive disability in US adults: a multi-state study using machine learning techniques

Alex Bui, Constance H. Fung, Mary Regina Boland, Tue Te
article en

Abstract

Our study highlights the importance of short sleep duration as a significant predictor of cognitive disability across the US after adjusting for other confounders. The association between short sleep and cognitive disability was especially strong in the Western region of the US providing a deeper understanding of how geographic context and local factors can shape health outcomes.

BioData MiningVol. 18(1)
University of California, Los Angeles (US), Saint Vincent College (US), Los Angeles Medical Center (US), VA Greater Los Angeles Healthcare System (US)
Openalex Percentile: Top 86%
Sleep and Work-Related Fatigue
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Geospatial analysis of short sleep duration and cognitive disability in US adults: a multi-state study using machine learning techniques — Alex Bui, Constance H. Fung, et al. · BioData Mining (2025) | TGRS Research Map | TGRS