title: Geographic distribution of insufficient sleep across the United States: a county-level hotspot analysis.
abstract: BACKGROUND
  Insufficient sleep is associated with cardiometabolic risk and neurocognitive impairment. Determinants of insufficient sleep include many social and environmental factors. Assessment of geographic hot/coldspots may uncover novel risk groups and/or targets for public health intervention. The aim of this study was to discern geographic patterns in the first data set to include county-level sleep data.
  
  
  METHODS
  The 2009 Behavioral Risk Factor Surveillance System was used. Insufficient sleep was assessed with a survey item and dichotomized. Data from n = 2231 counties were available. Tests for significant spatial concentrations of high/low levels of insufficient sleep (hotspots/coldspots) used the Getis-Ord G* statistic of local spatial concentration, chosen due to the nature of missing data.
  
  
  RESULTS
  Eighty-four counties were hotspots, with high levels of insufficient sleep (P< .01), and 45 were coldspots, with low insufficient sleep (P< .01). Hotspots were found in Alabama (1 county), Arkansas (1), Georgia (1), Illinois (1), Kentucky (25), Louisiana (1), Missouri (4), Ohio (7), Tennessee (12), Texas (9), Virginia (6), and West Virginia (16). Coldspots were found in Alabama (1 county), Georgia (2), Illinois (6), Iowa (6), Michigan (2), Minnesota (1), North Carolina (1), Texas (7), Virginia (12), and Wisconsin (6). Several contiguous hotspots and coldspots were evident. Notably, the 17 counties with the highest levels of insufficient sleep were found in a contiguous set at the intersection of Kentucky, Tennessee, Virginia, and West Virginia (allP< .0002).
  
  
  CONCLUSIONS
  Geographic distribution of insufficient sleep in the United States is uneven. Some areas (most notably parts of Appalachia) experience disproportionately high amounts of insufficient sleep and may be targets of intervention. Further investigation of determinants of geographic variability needs to be explored, which would enhance the utility of these data for development of public health campaigns.
authors.affiliation: Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Center for Sleep and Circadian Neurobiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Department of Psychiatry, University of Arizona, Tucson, AZ.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Grandner
authors.affiliation: Department of Electrical Systems Engineering, University of Pennsylvania, Philadelphia, PA.
authors.forename: Tony E
authors.initials: TE
authors.lastname: Smith
authors.affiliation: Department of Psychology, University of Southern California, Los Angeles, CA.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Jackson
authors.affiliation: Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
authors.forename: Tara
authors.initials: T
authors.lastname: Jackson
authors.affiliation: Department of Sociology, University of Michigan, Ann Arbor, MI; Department of Epidemiology, University of Michigan, Ann Arbor, MI.
authors.forename: Sarah
authors.initials: S
authors.lastname: Burgard
authors.affiliation: Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
authors.forename: Charles
authors.initials: C
authors.lastname: Branas