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Fan YUAN, Cai-cui DING, Wei-yan GONG, . Status and its influencing factors of sleep among occupational populations in China[J]. Chinese Journal of Public Health, 2018, 34(6): 791-794. DOI: 10.11847/zgggws1116210
Citation: Fan YUAN, Cai-cui DING, Wei-yan GONG, . Status and its influencing factors of sleep among occupational populations in China[J]. Chinese Journal of Public Health, 2018, 34(6): 791-794. DOI: 10.11847/zgggws1116210

Status and its influencing factors of sleep among occupational populations in China

  •   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.
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