The Effect of Shift Work on the Level of Self-Rated Health.
- Author:
Daehee NOH
1
;
Jong Ho WANG
;
Hyunrim CHOI
;
Sinye LIM
;
Keunwhoe KIM
;
Chang Won WON
;
Kyunghee JUNG-CHOI
Author Information
1. Department of Occupational and Environmental Medicine, College of Medicine, Kyung Hee University, Korea.
- Publication Type:Original Article
- Keywords:
Shift work;
Self-rated health
- MeSH:
Aged;
Bias (Epidemiology);
Family Characteristics;
Healthy Worker Effect;
Humans;
Korea;
Logistic Models;
Male
- From:Korean Journal of Occupational and Environmental Medicine
2010;22(3):200-209
- CountryRepublic of Korea
- Language:Korean
-
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.
