Center for Sleep and Circadian Neurobiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
J Clin Sleep Med. 2012 Feb 15;8(1):77-86. doi: 10.5664/jcsm.1668.
Social and demographic influences are important for sleep attainment. Geographic location has not been previously explored.
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.
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.
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).
社会人口因素对睡眠的获得很重要。地理位置以前尚未被探索过。
使用了 2006 年行为风险因素监测系统（BRFSS）的数据（N=157319）。参与者回答了一个关于睡眠障碍和白天疲劳的问题。36 个州/地区提供了这些项目的数据。采用年龄、性别、种族、教育、收入、就业、总体健康、医疗保健可及性和抑郁等因素对患病率估计值进行了调整。对各州和人口普查区域进行了卡方检验，并计算了州相对于其他预测因素的效果的伪 R(2)值。为了评估人口普查区域差异的潜在中介因素，对与特定协变量和协变量组相关的 p 值变化进行了分析。
调整后的睡眠障碍总体患病率在各州/地区之间存在差异（χ(2) = 412.3，p < 0.0001），男性（χ(2) = 139.5，p < 0.0001）和女性（χ(2) = 350.0，p < 0.0001）也存在差异，白天疲劳的总体患病率也存在差异（χ(2) = 245.7，p < 0.0001），男性（χ(2) = 117.5，p < 0.0001）和女性（χ(2) = 181.2，p < 0.0001）也是如此。伪 R(2)值的分析表明，尽管存在这些显著发现，但州的差异总体上是一个较弱的预测因素，仅占最佳预测因素（心理健康）效应幅度的 1.30%至 1.73%。当比较人口普查区域时，睡眠障碍存在显著差异（p = 0.002），但在调整协变量后，这些差异不再显著。调整后的日间疲劳总体分析存在差异（p<0.0001），西部报告的抱怨最少，南部报告的抱怨最多。
这些结果表明，睡眠相关投诉的报告因州而异，独立（至少部分）于影响昼夜节律的因素（例如，纬度）。
