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工作和家庭特征作为社会经济决定因素与长期病假的关系:日本公务员研究。

Work and family characteristics as socioeconomic determinants in long sickness absence: the Japanese civil servants study.

机构信息

Department of Epidemiology and Health Policy, School of Medicine, University of Toyama, Japan.

出版信息

Ind Health. 2022 Apr 1;60(2):164-175. doi: 10.2486/indhealth.2020-0234. Epub 2021 Oct 15.

Abstract

Long sickness absence is more common among low socioeconomic status (SES) groups than high SES groups. This study aimed to evaluate whether work and family characteristics contribute to SES and sex differences in long sickness absence (7 days or more). The participants were 3080 civil servants working for a local Japanese government. In both sexes, low-grade employees were likely to take long sickness absence, with a statistically significant association for men (age-adjusted OR of lowest-grade employees for long sickness absence: 2.30 (95% Confidence Interval (CI): 1.32-4.02)). After adjusting for all variables, SES differences in long sickness absence in men decreased to OR 1.98 (CI 1.10-3.55) but remained significant; in men, being without a spouse was significantly associated with long sickness absence. Employees working long hours had lower OR for long sickness absence after adjusting for all variables in both sexes. Conversely, poor sleep quality and longstanding illness significantly increased OR for long sickness absence. In conclusion, SES differences in sickness absence were explained partly by work and family characteristics, longstanding illness, and poor sleep quality; however, other factors that were not evaluated in this study may also be associated with SES differences.

摘要

长期病假在社会经济地位(SES)较低的人群中比 SES 较高的人群更为常见。本研究旨在评估工作和家庭特征是否会导致 SES 和性别差异导致长期病假(7 天或以上)。参与者为为当地日本政府工作的 3080 名公务员。在男性和女性中,低级别员工更有可能请长期病假,这与统计学显著相关(男性最低级别员工长期病假的调整后 OR:2.30(95%置信区间(CI):1.32-4.02))。在调整所有变量后,男性的 SES 差异导致长期病假的差异减少到 OR 1.98(CI 1.10-3.55),但仍有统计学意义;在男性中,没有配偶与长期病假显著相关。在调整了所有变量后,男性和女性中工作时间长的员工长期病假的 OR 较低。相反,睡眠质量差和长期患病显著增加了长期病假的 OR。总之,病假中的 SES 差异部分可以通过工作和家庭特征、长期患病和睡眠质量差来解释;然而,本研究未评估的其他因素也可能与 SES 差异相关。

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