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)
Feldman et al. (2026) studied this question.