Geographic variations in sleep duration: a multilevel analysis from the Boston Area Community Health (BACH) Survey.
Geographic variations in sleep duration: a multilevel analysis from the Boston Area Community Health (BACH) Survey.
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DOI：
10.1136/jech-2013-203256
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发表时间：
2015-01
影响因子：
6.3
通讯作者：
Araujo AB
中科院分区：
文献类型：
--
作者：
Fang SC;Subramanian SV;Piccolo R;Yang M;Yaggi HK;Bliwise DL;Araujo AB
睡眠在健康中发挥着重要作用，并因社会决定因素而异。然而，人们对睡眠的地理差异以及个人水平和社区水平因素的作用知之甚少。我们采用多层次建模方法量化波士顿地区社区健康调查3591名参与者自我报告的睡眠时间（极短睡眠时间<5小时；短睡眠时间5 - 6.9小时；标准睡眠时间7-8.9小时；长睡眠时间≥9小时）的邻里差异。我们确定地理差异是否在控制个人水平的人口统计学、社会经济地位（SES）和生活方式因素的情况下持续存在。然后，我们确定了邻居SES （nSES）在地理变化中的作用。其他模型考虑了个人健康因素。邻里之间的差异在睡眠持续时间的总变化中占很大一部分。在人口统计学、社会经济地位和生活方式因素的控制下，邻里差异仍然存在。在极短睡眠、短睡眠和长睡眠中，这些特征占邻域间差异的一部分（6-20%），而nSES占其余邻域间差异的大部分。低和中等nSES与极短和短睡眠相关（例如，极短睡眠OR=2.08；低和高nSES的95% CI为1.38至3.14），但与长睡眠无关。进一步纳入健康因素并没有显著增加邻里间差异的数量，也没有改变相关关系。在美国东北部不同的城市环境中，睡眠时间因社区而异。个人层面的人口统计、社会经济地位和生活方式因素解释了一些地理差异，而国家社会经济地位解释了大量差异。在未来的研究中，应该检查与nSES相关的机制，以帮助理解和减少睡眠的地理差异。
Sleep plays an important role in health and varies by social determinants. Little is known, however, about geographic variations in sleep and the role of individual-level and neighbourhood-level factors. We used a multilevel modelling approach to quantify neighbourhood variation in self-reported sleep duration (very short <5 h; short 5–6.9 h; normative 7–8.9 h; long ≥9 h) among 3591 participants of the Boston Area Community Health Survey. We determined whether geographic variations persisted with control for individual-level demographic, socioeconomic status (SES) and lifestyle factors. We then determined the role of neighbourhood SES (nSES) in geographic variations. Additional models considered individual health factors. Between neighbourhood differences accounted for a substantial portion of total variability in sleep duration. Neighbourhood variation persisted with control for demographics, SES and lifestyle factors. These characteristics accounted for a portion (6–20%) of between-neighbourhood variance in very short, short and long sleep, while nSES accounted for the majority of the remaining between-neighbourhood variances. Low and medium nSES were associated with very short and short sleep (eg, very short sleep OR=2.08; 95% CI 1.38 to 3.14 for low vs high nSES), but not long sleep. Further inclusion of health factors did not appreciably increase the amount of between-neighbourhood variance explained nor did it alter associations. Sleep duration varied by neighbourhood in a diverse urban setting in the northeastern USA. Individual-level demographics, SES and lifestyle factors explained some geographic variability, while nSES explained a substantial amount. Mechanisms associated with nSES should be examined in future studies to help understand and reduce geographic variations in sleep.
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影响因子：
5
作者：
COHEN, S;KAMARCK, T;MERMELSTEIN, R
通讯作者：
MERMELSTEIN, R
影响因子：
4.8
作者：
Grandner, Michael A.;Patel, Nirav P.;Gehrman, Philip R.;Xie, Dawei;Sha, Daohang;Weaver, Terri;Gooneratne, Nalaka
通讯作者：
Gooneratne, Nalaka
影响因子：
5.6
作者：
Hoevenaar-Blom, Marieke P.;Spijkerman, Annemieke M. W.;Verschuren, W. M. Monique
通讯作者：
Verschuren, W. M. Monique
影响因子：
5.6
作者：
Lee, Eun;Cho, Hyong Jin;Irwin, Michael R.
通讯作者：
Irwin, Michael R.
影响因子：
--
作者：
Knutson, Kristen L.;Ryden, Armand M.;Van Cauter, Eve
通讯作者：
Van Cauter, Eve