title: State and regional prevalence of sleep disturbance and daytime fatigue.
abstract: OBJECTIVE
  Social and demographic influences are important for sleep attainment. Geographic location has not been previously explored.
  
  
  METHODS
  Data from the 2006 Behavioral Risk Factor Surveillance System (BRFSS) were used (N = 157,319). Participants answered a question on Sleep Disturbance and Daytime Fatigue. Thirty-six states/regions provided data on these items. Prevalence estimates were adjusted for age, sex, ethnoracial group, education, income, employment, general health, healthcare access, and depression. Chi-squared tests were conducted across states and census regions, and pseudo-R(2) values were computed for the effect of state, relative to other predictors. To evaluate potential mediators of census region differences, an analysis of p value change associated with specific covariates and covariate groups was undertaken.
  
  
  RESULTS
  Adjusted prevalence rates of Sleep Disturbance differed across states/regions overall (χ(2) = 412.3, p < 0.0001), as well as separately for men (χ(2) = 139.5, p < 0.0001) and women (χ(2) = 350.0, p < 0.0001), as did rates of Daytime Fatigue overall (χ(2) = 245.7, p < 0.0001), and separately for men (χ(2) = 117.5, p < 0.0001) and women (χ(2) = 181.2, p < 0.0001). Analysis of pseudo-R(2) values revealed that despite these significant findings, state differences were an overall weak predictor, representing 1.30% to 1.73% of the magnitude of the effect of the best predictor (mental health). When Census regions were compared, significant differences were found for Sleep Disturbance (p = 0.002), but after adjustment for covariates, these were no longer significant. Differences existed for Daytime Fatigue in adjusted analyses overall (p < 0.0001), with the West reporting the fewest complaints and the South reporting the most.
  
  
  CONCLUSIONS
  These results demonstrate that reports of sleep related complaints vary across states, independent (at least partially) of factors that influence circadian rhythms (e.g., latitude).
authors.affiliation: Center for Sleep and Circadian Neurobiology, University of Pennsylvania, Philadelphia, PA 19104, USA. grandner@upenn.edu
authors.forename: Michael A
authors.initials: MA
authors.lastname: Grandner
authors.forename: Nicholas J
authors.initials: NJ
authors.lastname: Jackson
authors.forename: Wilfred R
authors.initials: WR
authors.lastname: Pigeon
authors.forename: Nalaka S
authors.initials: NS
authors.lastname: Gooneratne
authors.forename: Nirav P
authors.initials: NP
authors.lastname: Patel
mesh_terms: D040343:Behavioral Risk Factor Surveillance System; D016009:Chi-Square Distribution; D005221:Fatigue / Q000453:epidemiology*; D005260:Female; D005843:Geography; D006801:Humans; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D012737:Sex Factors; D012893:Sleep Wake Disorders / Q000453:epidemiology*; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology