中国居民的睡眠时间分析

  目的  了解我国职业人群睡眠状况及其影响因素，为促进职业人群健康提供依据。  方法  在“2010 — 2012年中国居民营养与健康状况调查”的资料中选取31 694名职业人群为研究对象进行睡眠状况及其影响因素分析。  结果  我国职业人群平均每天睡眠时间为（7.6 ± 1.0）h，大城市职业人群平均睡眠时间最低（7.5±1.0）h，男性（7.6 ± 1.0）h低于女性（7.7 ± 0.9）h，睡眠时间随着年龄增加逐渐减少。我国职业人群每天睡眠不足的比例为11.6 %，睡眠过多的比例为11.5 %；多因素logistic回归分析结果显示，居住在普通农村、中小城市和大城市、男性、年龄越大是睡眠不足的危险因素，文化水平越高、有配偶、中等经济收入是睡眠不足的保护因素；居住在普通农村、中小城市、大城市、年龄越大、文化程度越高、经济收入越高是睡眠过多的保护因素。  结论  我国职业人群睡眠不足与睡眠过多并存，睡眠时间分布存在地区、性别、年龄、文化程度、婚姻状况、经济状况及职业的差异，应对重点人群进行采取干预措施。

U-shaped relationships between sleep duration and metabolic syndrome and metabolic syndrome components in males: a prospective cohort study

  Objective  To explore the status and influencing factors of sleep among occupational populations in China and to provide evidences for promoting the health of occupational populations.  Methods  The data were derived from China National Nutrition and Health Survey, 2010 – 2012. A total of 31 694 employees were involved and their sleep status was analyzed.  Results  The average sleep time was 7.6 ± 1.0 hours per day among the participants. The average sleep time of the male participants was shorter than that of the female participants (7.6 ± 1.0 hours vs. 7.7 ± 0.9 hours) and the participants living in large cities had the shortest sleep time (7.5 ± 1.0 hours) compared to those living in other regions. The average sleep time decreased with the increment of age among the participants. The results of multivariate logistic regression showed that living in common rural area, living in medium- or small-sized city, living in large city, and at elder age were risk factors of insufficient sleep; the protective factors against insufficient sleep were with higher education, married, and with medium income; while, living in common rural area, living in medium- or small-sized city, living in large city, at elder age, with higher education, and with higher income were protective factors against excessive sleep.   Conclusion  Both insufficient and excessive sleep exist in Chinese occupational populations; the sleep time of occupational populations differs by residential region, gender, age, education, marital status, economic condition, and occupation type. The results suggest that interventions on sleep status should be implemented among the populations at higher risk of abnormal sleep.