Geospatial analysis of short sleep duration and cognitive disability in US adults: a multi-state study using machine learning techniques.
Journal:
BioData mining
Published Date:
Jun 13, 2025
Abstract
BACKGROUND: There is evidence of increased risk of cognitive disability due to short sleep duration and adverse Social Determinants of Health (SDoH). To determine whether spatial associations (correlation between spatially distributed variables within a given geographic area) exist between neighborhoods with short sleep duration and cognitive disability across the United States (US) after adjusting for other factors. We conducted a spatial analysis using a spatial lag model at the neighborhood-level with the census tract as unit-of-analysis within each state in the US. We aggregated our results nationally using a weighted analysis to adjust for the number of census tracts per state. This study used Centers for Disease Control and Prevention (CDC) data on short sleep duration, cognitive disability and other health factors. We used 2021-2022 neighborhood-level data from the CDC and US Census Bureau adjusting for social determinants of health (SDoH) and demographics, excluding Florida due to inconsistencies in data availability. Our exposure variable was self-reported short sleep defined by the CDC ("sleep less than 7 hours per 24 hour period"). Our outcome was self-reported cognitive disability defined by the CDC ("difficulty concentrating, remembering, or making decision"). We adjusted for other factors including 'health outcomes', 'preventive practices', and the CDC's Social Vulnerability Index.
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