TY - JOUR
T1 - Geographic distribution of insufficient sleep across the United States
T2 - A county-level hotspot analysis
AU - Grandner, Michael A.
AU - Smith, Tony E.
AU - Jackson, Nicholas
AU - Jackson, Tara
AU - Burgard, Sarah
AU - Branas, Charles
N1 - Publisher Copyright:
© 2015 National Sleep Foundation.
PY - 2015/9/1
Y1 - 2015/9/1
N2 - Introduction: 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 (all P < .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.
AB - Introduction: 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 (all P < .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.
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U2 - 10.1016/j.sleh.2015.06.003
DO - 10.1016/j.sleh.2015.06.003
M3 - Article
AN - SCOPUS:84940895499
SN - 2352-7218
VL - 1
SP - 158
EP - 165
JO - Sleep Health
JF - Sleep Health
IS - 3
ER -