OBJECTIVE: To investigate the musculoskeletal symptoms of migrant workers. We focused on the relationship between job stress and musculoskeletal symptoms. METHOD A questionnaire was administered to 502 migrant workers who visited NGO migrant worker centers located in Gyung-gi province. A structured, self-reported questionnaire was administered to participants in order to capture the following information: sociodemographics, health factors including past medical history, work related characteristics, job stress, and musculoskeletal symptoms. The job stress questionnaires were used according to KOSS-26 and musculoskeletal symptoms were measured using KOSHA Code H-30-2003. We used multiple logistic regression analysis to assess the relationship between risk factors which included job stress, and musculoskeletal symptoms. RESULTS The prevalence rate of musculoskeletal symptoms in survey subjects was 35.1%. Other than job stress factors, past medical history was the only factor that had a statistical relationship to musculoskeletal symptoms (P<0.01). In the domains of job stress, physical environment (OR 1.62, 95% CI: 1.03~2.54), job demand (OR 2.43, 95% CI: 1.46~4.03), job insecurity (OR 1.59, 95% CI: 1.03~2.47), occupational climate (OR 2.30, 95% CI: 1.27~4.19) were most likely experience musculoskeletal symptoms. CONCLUSION The job stress factor appeared to correlate more with musculoskeletal symptoms than with sociodemographics or other factors. Hence, in order to prevent migrant worker's musculoskeletal symptoms, we believe that intervention in job stress (physical environment, job demand, job insecurity, occupational climate) is necessary.
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OBJECTIVES To investigate the mental health status of migrant workers. We focused on the relationship between depressive symptoms and job stress.
METHEOD: A questionnaire was administered to 488 migrant workers who visited NGO migrant worker centers located in Kyung-gi province. A structured, self-reported questionnaire was used to assess each responder's sociodemographics, work related characteristics, health behaviors, past medical history, job stress and depression symptoms. The job stress questionnaire was used according to KOSS-26 and depression symptoms were measured using CES-D, which was translated into Korean. We used multiple logistic regression analysis to assess the relationship between risk factors included job stress and depression symptoms. RESULTS The prevalence of depression symptoms in survey subjects was 25.2%, but the prevalence of non-Chinese nationalities and illegal workers were 32.1% and 32.8%, respectively. Adjusting for confounding factors, job stress (OR 2.55, 95% CI=1.30-4.99) had a statistical meaningful relationship with depression symptoms. Among job stress domains, physical environment (OR 2.97, 95% CI=1.59-5.53), job demand (OR 2.33, 95% CI=1.26-4.32) and occupational climate(OR 3.10, CI=1.49-6.48) were most likely to experience depression symptoms. CONCLUSIONS The prevalence of depressive symptoms among the study subjects was similar to the prevalence among the general population in Korea, but higher than that among the Korean workers. In particular, the prevalence among non-Chinese and illegal workers was higher. However, the job stress factor appeared to have a more direct correlation with depressive symptoms than the sociodemographic factors of nationality or residential status. Hence, in order to prevent depressive symptoms of the migrant workers, we believe that intervention on job stress is necessary.
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OBJECTIVES To investigate the general health status and severity of exposure to hazardous agents - with a focus on heavy metals - of migrant workers utilizing the 2005 Special Health Examination data. METHODS With data from the 2005 Special Health Examination, we examined the biologic exposure indices and several major clinical exam items of 25,086 migrant workers in the whole country in comparison with those of 19,616 native Korean workers in Kyunggi-do province. Of these we chose homogeneous samples from the same 3 health service centers in Kyunggi-do. (native workers:19,616, migrant workers:1,886) to be more precise. RESULTS The results from the samples of the 3 centers were as follows. Blood lead (natives: 6.09 microgram/dl migrants: 8.37 microgram/L) and cadmium (natives: 0.29 microgram/dl, migrants: 0.36 microgram/L) were higher in the migrant workers than in the native Korean workers, whereas the biologic exposure indices of organic solvents were higher in the native workers. As for major clinical exam items, the liver battery was worse in the natives with incidence of abnormal AST/ALT level (natives: 8.1/6.8% migrants: 5.7/5.4%, p-value<0.01 for AST). Anemia was more prevalent in the migrant workers (natives: 9.0% migrants: 11.0%, p-value<0.05). CONCLUSIONS Migrant workers in Korea are more frequently or more severely exposed to a hazardous working environment containing heavy metals. However, we were not able to explain the results for the exposure indices or organic solvents, and such an explanation will require further study in the future.
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The number of foreign workers, which has increased since 1989, can be classified into industrial trainees and illegal migratory workers. As of January 1995, the official number of foreign workers reached 49,805 according to the Ministry of Labor. But the real number is estimated to be around 100,000 and industrial trainees are 22,583 among them. The stress induced by the culture shock, 3D (dirty, difficult and dangerous) working conditions, and illegal status of the foreign workers is greater than that of regular Korean workers. By using a psychological well-being index (PWI) measuring stress on 144 foreign workers, it was revealed that 68 people experienced "high risk stress", 76 "latent stress", and the average score was 62.8. The overall stress level was very high. Considering the distribution of high risk stress group and latent stress group by socio-demographic factors, the percentage of high risk stress group was higher among workers whose contract periods are less than 2 years than among workers whose contract periods are longer than 2 years. And the percentage of high risk stress group was higher when the number of workers at factory becoming larger, and also higher among workers who can not communicate well than among workers communicate well. After having a multiple stepwise regression analysis to find the socio-demographic factors which influence the PWI score, we found that the PWI score goes higher when the contract period is becoming shorter and the work hours is becoming longer, and these two factors are able to explain the score to the level 16.3%.
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