Scientific Investigations
State and Regional Prevalence of Sleep Disturbance and Daytime Fatigue
http://dx.doi.org/10.5664/jcsm.1668
Michael A. Grandner, Ph.D.1; Nicholas J. Jackson, M.P.H.1; Wilfred R. Pigeon, Ph.D., C.B.S.M.2,3; Nalaka S. Gooneratne, M.D., M.Sc.4; Nirav P. Patel, M.D., M.P.H.5
1Center for Sleep and Circadian Neurobiology, University of Pennsylvania, Philadelphia, PA; Division of Sleep Medicine, University of Pennsylvania, Philadelphia, PA; 2Sleep & Neurophysiology Research Laboratory, University of Rochester Medical Center, Rochester, NY; 3Center of Excellence for Suicide Prevention, Canandiagua VA Medical Center & Center for Integrated Healthcare, Syracuse VA Medical Center, Syracuse, NY; 4Center for Sleep and Respiratory Neurobiology, University of Pennsylvania, Philadelphia, PA; Division of Geriatric Medicine, University of Pennsylvania, Philadelphia, PA; 5Respiratory Specialists and Reading Hospital and Medical Center, Reading, PA
Study Objectives:
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-R2 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 (χ2 = 412.3, p < 0.0001), as well as separately for men (χ2 = 139.5, p < 0.0001) and women (χ2 = 350.0, p < 0.0001), as did rates of Daytime Fatigue overall (χ2 = 245.7, p < 0.0001), and separately for men (χ2 = 117.5, p < 0.0001) and women (χ2 = 181.2, p < 0.0001). Analysis of pseudo-R2 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).
Citation:
Grandner MA; Jackson NJ; Pigeon WR; Gooneratne NS; Patel NP. State and regional prevalence of sleep disturbance and daytime fatigue. J Clin Sleep Med 2012;8(1):77-86.
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