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Korean J Occup Environ Med. 2010 Sep;22(3):200-209. Korean. Original Article. https://doi.org/10.35371/kjoem.2010.22.3.200
Noh D , Wang JH , Choi H , Lim S , Kim K , Won CW , Jung-Choi K .
Department of Occupational and Environmental Medicine, College of Medicine, Kyung Hee University, Korea.
Department of Occupational and Environmental Medicine, Konkuk University Chungju Hospital, Korea.
Department of Family Medicine, College of Medicine, Kyung Hee University, Korea.
Department of Preventive Medicine, Ewha Women's University School of Medicine, Korea. jungchoikh@gmail.com
Abstract

OBJECTIVES: The present study was designed to determine the characteristics of shift work and the relationship between shift work and the level of self-rated health using the Korean Labor and Income Panel Study (KLIPS) data, which represents urban households in Korea. METHODS: Using the 9th wave of KLIPS, this study analyzed 2,087 male workers aged 25 to 64 years; participants missing data were excluded from analysis. To determine the impact of shift work on the level of self-rated health, logistic regression analysis was applied that controlled for socio-demographic characteristics, labor environment, and health-related behaviors. RESULTS: Shift workers comprised 13.4% of study subjects overall. The majority(69.2%) of participants were in 2-teams and in 2-shifts. Week 1 shift cycle changes were the highest, 56.3%. The risk of poor self-rated health was not significantly higher among shift workers compared to non-shift workers (OR=1.08, 95% CI=0.79~1.48). When divided by tenure, shift workers with more than 10-years experience (OR=1.79, 95% CI=0.91~3.50) tended to show greater risk than non-shift workers at marginal significance. CONCLUSIONS: In the present study, a significantly higher risk of self-rated poor health among shift workers was not observed. However, shift workers with more than 10-years experience tended to show increased health risk compared to non-shift workers. Further studies are required to determine time-series data and to consider both healthy worker effect and information bias.

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