OBJECTIVE: The purpose of this paper is to analyze the effects of precarious employment status on the level of self-rated health, based on various criteria, by participants in the Korean Labor and Income Panel Survey. METHODS: Data were obtained from 3,268 subjects(2,057 men and 1,211 women), who participated in the 2005-2006 Korean Labor and Income Panel Survey. Group A was classified as Non-precarious employment by both the Ministry of Labor (MoLab) and the Korea Labor and Society Institute (KLSI). The group B was classified as Non-precarious employment by the MoLab and as precarious employment by the KLSI. The group C is classified as Non-precarious employment by both MoLab and KLSI. Outcome variables were self-rated health and a panel logistic regression analysis was performed on the data. RESULTS: The level of self-rated health was worse among group B males (OR: 1.45, C.I:1.00~2.11) and group C males (OR: 1.69, C.I:1.35~2.10) compared to group A males. A substantial difference(57.8%) in the level of self-rated health between groups A and B was attributed to the sociodemographic characteristics of the populations. The difference in self-rated health between groups A and C was explained by work environments(15.7%), as well as by sociodemographic characteristics(26.1%). For female workers, the level of self-rated health in group B and C was worse than in group A, but this finding was not statistically significant. CONCLUSIONS: These findings suggested that the policy to improve the working environment, as well as a more comprehensive effort to reduce the disparity, is needed for the precarious employment worker.
Employment ; Female ; Health Status ; Humans ; Korea ; Logistic Models ; Longitudinal Studies ; Male

OBJECTIVE: This study evaluated the cost for occupational health and safety in manufacturing factories in Korea according to the factory's size and the industrial classification. METHODS: The costs to prevent occupational injuries and promote the general health of the workers were calculated by using the data of The Occupational Safety and Health Survey in Korea in the year of 2005 and the data of the Industrial Accident Compensation Insurance (IACI) premiums at the same factories for the year of 2004. RESULTS: The mean cost per one worker was as follows: 990,000 won for the factory with 5~49 workers, 869,000 won for the factory with 50~299 workers and 1,773,000 won for the factory with more than 300 workers. In the factories with 5~49 workers and 50~299 workers, the premium for the IACI was the largest portion of the cost (62.8% and 52.8%, respectively) and the cost for gear to protect workers from dangerous machineries was the next biggest portion of the cost (20.1% and 19.1%, respectively). The largest portion of the cost in the factories with more than 300 workers was the premium for the IACI (37.5%). CONCLUSIONS: The investment costs to prevent occupational injuries and to promote the general health of the workers were very diverse according to the size of the factories and the industrial classification. To reduce the occupational injuries and to promote the general health of the workers, systematic and continuous approaches to evaluate the investment costs for the occupational health and safety are required.
Accidents, Occupational ; Compensation and Redress ; Health Surveys ; Insurance ; Investments ; Korea ; Occupational Health ; Occupational Injuries ; Occupations

OBJECTIVE: This study evaluated the cost for occupational health and safety in manufacturing factories in Korea according to the factory's size and the industrial classification. METHODS: The costs to prevent occupational injuries and promote the general health of the workers were calculated by using the data of The Occupational Safety and Health Survey in Korea in the year of 2005 and the data of the Industrial Accident Compensation Insurance (IACI) premiums at the same factories for the year of 2004. RESULTS: The mean cost per one worker was as follows: 990,000 won for the factory with 5~49 workers, 869,000 won for the factory with 50~299 workers and 1,773,000 won for the factory with more than 300 workers. In the factories with 5~49 workers and 50~299 workers, the premium for the IACI was the largest portion of the cost (62.8% and 52.8%, respectively) and the cost for gear to protect workers from dangerous machineries was the next biggest portion of the cost (20.1% and 19.1%, respectively). The largest portion of the cost in the factories with more than 300 workers was the premium for the IACI (37.5%). CONCLUSIONS: The investment costs to prevent occupational injuries and to promote the general health of the workers were very diverse according to the size of the factories and the industrial classification. To reduce the occupational injuries and to promote the general health of the workers, systematic and continuous approaches to evaluate the investment costs for the occupational health and safety are required.
Accidents, Occupational ; Compensation and Redress ; Health Surveys ; Insurance ; Investments ; Korea ; Occupational Health ; Occupational Injuries ; Occupations

OBJECTIVES: We evaluated the effect of the aircraft noise on the behavior and affect status of the local elementary school students. METHODS: The daytime noise levels of the exposed and control areas were compared and the self answered questionnaires from 272 students and their parents of the exposed area and 91 of the control area were collected. The questionnaires are regarding the noise sensitivity and the psychosocial status of the students, noise sensitivity of the parents and the parents' behavioral evaluation for their children. RESULTS: The mean noise level of the exposed area (67.6 dB(A)) showed higher level than the control area (57.1 dB(A), 58.2 dB(A), 60.2 dB(A)) and it was statistically significant. The mean score for noise sensitivity and the mean score for brief mental exam. in the exposed students were lower than the mean scores in the control group but they were not statistically significant (p=0.056 & 0.165). The mean score for behavioral evaluation of students by their parents in the exposed area(15.5) was higher than the mean score in the control group(13.2) and it was statistically significant(p=0.043). The mean score for noise sensitivity in the exposed parent(27.5) was higher than the mean score in the control group(24.1) and it was statistically significant(p=0.045). CONCLUSIONS: This study revealed that the noise sensitivity of the parents affected the behavioral evaluation of the students than noise-exposure itself. The further study is needed to evaluate relationship between aircraft noise and it's effect on children's health.
Aircraft ; Child ; Humans ; Noise ; Parents ; Surveys and Questionnaires

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.
Aged ; Bias (Epidemiology) ; Family Characteristics ; Healthy Worker Effect ; Humans ; Korea ; Logistic Models ; Male