0308 Insufficient Sleep Across the US: A Comparative Analysis of Place-Based Indices

Abstract Introduction The places people live, work, and socialize shape health across the lifespan. Climate change increasingly threatens population health through flooding, wildfires, and extreme weather events, all of which can contribute to injuries, displacement, chronic stress, and disruptions in healthcare delivery. Although vulnerability indices are widely used in public health and sleep research, few incorporate environmental or climate-related factors. This study compared six place-based vulnerability indices explain variation in insufficient sleep prevalence, with a specific focus on climate/environmental domains or indices. Methods Data from CDC PLACES was used to measure the relationship between insufficient sleep and Area Deprivation Index [ADI], Childhood Opportunity Index [COI], Environmental Justice Index [EJI], Social Vulnerability Index [SVI], Heat and Health Index [HHI], Climate Vulnerability Index [CVI] scores across 3,131 U.S. counties and 67,974 census tracts (populations ≥ 50). Beta regression models included each index's component domains, with geography demographics (poverty, minority status, age ≥65, uninsured) as reference. Pseudo R² compared variance explained nationally and across four Census regions. Results CVI demonstrated strongest associations with insufficient sleep (county pseudo R² = 0.568, tract = 0.537), even excluding baseline health domains (county = 0.538, tract = 0.523). ADI explained the least variance across all geographies (county = 0.179, tract = 0.234), performing particularly poorly in the West. The demographic reference model matched or outperformed most indices. Regional patterns varied substantially. Indices generally performed weakest in the West (tract and county) and the South (county only) and best in the Midwest. Conclusion Climate-related indices meaningfully explain differences in insufficient sleep beyond traditional measures (e.g., ADI). However, geographic scale and regional context influence index performance. Researchers should consider both when selecting vulnerability measures for sleep health research. Support (if any)

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Journal
SLEEP
Published
2026-05-01
DOI
https://doi.org/10.1093/sleep/zsag091.0308
Primary Topic
Climate Change and Health Impacts
Type
article
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article

0308 Insufficient Sleep Across the US: A Comparative Analysis of Place-Based Indices

Danica Slavish, Emily Feldman
SLEEP
Climate Change and Health Impacts
article

0308 Insufficient Sleep Across the US: A Comparative Analysis of Place-Based Indices

Danica Slavish, Emily Feldman
article en

Abstract

Abstract Introduction The places people live, work, and socialize shape health across the lifespan. Climate change increasingly threatens population health through flooding, wildfires, and extreme weather events, all of which can contribute to injuries, displacement, chronic stress, and disruptions in healthcare delivery. Although vulnerability indices are widely used in public health and sleep research, few incorporate environmental or climate-related factors. This study compared six place-based vulnerability indices explain variation in insufficient sleep prevalence, with a specific focus on climate/environmental domains or indices. Methods Data from CDC PLACES was used to measure the relationship between insufficient sleep and Area Deprivation Index [ADI], Childhood Opportunity Index [COI], Environmental Justice Index [EJI], Social Vulnerability Index [SVI], Heat and Health Index [HHI], Climate Vulnerability Index [CVI] scores across 3,131 U.S. counties and 67,974 census tracts (populations ≥ 50). Beta regression models included each index's component domains, with geography demographics (poverty, minority status, age ≥65, uninsured) as reference. Pseudo R² compared variance explained nationally and across four Census regions. Results CVI demonstrated strongest associations with insufficient sleep (county pseudo R² = 0.568, tract = 0.537), even excluding baseline health domains (county = 0.538, tract = 0.523). ADI explained the least variance across all geographies (county = 0.179, tract = 0.234), performing particularly poorly in the West. The demographic reference model matched or outperformed most indices. Regional patterns varied substantially. Indices generally performed weakest in the West (tract and county) and the South (county only) and best in the Midwest. Conclusion Climate-related indices meaningfully explain differences in insufficient sleep beyond traditional measures (e.g., ADI). However, geographic scale and regional context influence index performance. Researchers should consider both when selecting vulnerability measures for sleep health research. Support (if any)

SLEEPVol. 49(Supplement_1)
University of North Texas (US)
No poverty
Openalex Percentile: Top 6%
Climate Change and Health Impacts
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