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嘈杂且个体差异大,但可行:人类轮班工作研究。

Noisy and individual, but doable: shift-work research in humans.

机构信息

Centre for Chronobiology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, United Kingdom.

University of São Paulo, School of Public Health, São Paulo, Brazil.

出版信息

Prog Brain Res. 2012;199:399-411. doi: 10.1016/B978-0-444-59427-3.00022-8.

DOI:10.1016/B978-0-444-59427-3.00022-8
PMID:22877677
Abstract

Working around the clock is common for many occupations, as diverse as nurses, truck drivers, physicians, steel workers, and pilots. Each shift-work profession is individual in more aspects than just work hours and individual work scenarios, each posing a different impact on the health of workers. Related health problems in shift workers, therefore, are also diverse and encompass sleep problems, metabolic and cardiovascular system disturbances, as well as cancer. Little is known about how all these individual factors influence a shift worker's health status, partly because many shift-work studies show inconsistent results. In addition, these individual factors create many methodological difficulties for researchers who investigate such work scenarios. This chapter presents examples from our laboratory and field studies of shift workers, which emphasize the importance of taking individual circumstances into account. Both study approaches, laboratory and field based, are needed to fully account for the difficulties that shift-work studies pose on both workers and researchers. Finally, understanding the mechanisms that underpin interindividual differences in response to shift work will advance our understanding of how to design better and healthier shift-work schedules in the future.

摘要

对于许多职业来说,昼夜不停地工作是很常见的,比如护士、卡车司机、医生、钢铁工人和飞行员。每个轮班工作的职业在工作时间和个人工作场景方面都有不同之处,对工人的健康产生不同的影响。因此,轮班工人的相关健康问题也多种多样,包括睡眠问题、代谢和心血管系统紊乱以及癌症。人们对所有这些个体因素如何影响轮班工人的健康状况知之甚少,部分原因是许多轮班工作研究的结果不一致。此外,这些个体因素给研究这些工作场景的研究人员带来了许多方法上的困难。本章介绍了我们实验室和现场研究轮班工人的一些例子,这些例子强调了考虑个体情况的重要性。实验室和现场研究都需要充分考虑轮班工作给工人和研究人员带来的困难。最后,了解导致轮班工作反应个体差异的机制将有助于我们理解如何在未来设计更好、更健康的轮班工作时间表。

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