TY - JOUR
T1 - State and regional prevalence of sleep disturbance and daytime fatigue
AU - Grandner, Michael A.
AU - Jackson, Nicholas J.
AU - Pigeon, Wilfred R.
AU - Gooneratne, Nalaka S.
AU - Patel, Nirav P.
PY - 2012
Y1 - 2012
N2 - 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-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 signifi cant 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).
AB - 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-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 signifi cant 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).
KW - Epidemiology
KW - Fatigue
KW - Geographic factors
KW - Health services
KW - Sleep
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U2 - 10.5664/jcsm.1668
DO - 10.5664/jcsm.1668
M3 - Article
C2 - 22334813
AN - SCOPUS:84857560283
SN - 1550-9389
VL - 8
SP - 77
EP - 86
JO - Journal of Clinical Sleep Medicine
JF - Journal of Clinical Sleep Medicine
IS - 1
ER -