Spatial variations in the associations of mental distress with sleep insufficiency in the United States: a county-level spatial analysis

Int J Environ Health Res. 2024 Feb;34(2):911-922. doi: 10.1080/09603123.2023.2185211. Epub 2023 Mar 2.

Abstract

In this research, we conducted hierarchical multiple regression and complex sample general linear model (CSGLM) to expand knowledge on factors contributing to mental distress, particularly from a geographic perspective. Based on the Getis-Ord G* hot-spot analysis, geographic distribution of both FMD and insufficient sleep showed several contiguous hotspots in southeast regions. Moreover, in the hierarchical regression, even after accounting for potential covariates and multicollinearity, a significant association between FMD and insufficient sleep was found, explaining that mental distress increases with increasing insufficient sleep (R2 = 0.835). In the CSGLM, a R2 value of 0.782 indicated that the CSGLM procedure provided concrete evidence that FMD was significantly related to sleep insufficiency even after taking complex sample designs and weighting adjustments in the BRFSS into account. This geographic association between FMD and insufficient sleep based on cross-county study has not been reported before in the literature. These findings suggest a need for further investigation on geographic disparity on mental distress and insufficient sleep and have novel implications in our understanding of the etiology of mental distress.

Keywords: Insufficient sleep, frequent mental distress (FMD); complex sample general linear model (CSGLM); hot spot analysis.

MeSH terms

  • Behavioral Risk Factor Surveillance System
  • Humans
  • Linear Models
  • Sleep Deprivation* / complications
  • Spatial Analysis
  • United States / epidemiology