• Journal of agricultural medicine and community health
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• v.47 no.3
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• pp.181-188
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• 2022

Objectives: The prevalence of diabetes mellitus was approximately 16% in populations of over age 30 years, and deaths from diabetes mellitus became the sixth most prevalent cause of death by disease. To assess the relationship between HbA1c and heavy metal level in blood and urine, targeted residents were evaluated in a vast steel industrial complex. Methods: We selected 414 subjects for analysis after applying the following exclusion criterion: 18 persons with diabetes mellitus. They took part in a questionnaire survey and underwent blood and urinary assessments. HbA1c and lead (Pb) level were measured in blood and, cadmium (Cd), inorganic arsenic (iAs) and mercury (Hg) were evaluated in urine. Two subgroups were divided by HbA1c 6.5%. Each subgroup was divided by 10th, 20th, 30th, 40th, 50th, 60th, 70th, 80th and 90th percentile levels of biological exposure index of the heavy metals for logistic regression. Results: Odd ratios have a tendency to increase as they go from the 90th to the 10th percentile of cadmium. However, lead, arsenic and mercury did not have significant relationships with HbA1c. In correction of age, region, gender and smoking history, a higher distribution in the subgroup with cadmium above 0.8318 ㎍/g creatinine (30th percentile) was demonstrated in the subgroup with HbA1c levels above the 6.5%, with an odds ratio of 5.26 (95% C.I. ; 1.44~19.17). Conclusion: This study found a significant correlation between urinary levels of cadmium and HbA1c in correction of several factors. It is meaningful that this outcome may be used as a basis for a study to establish the acceptable limit of urinary cadmium in Korea.

• Journal of Preventive Medicine and Public Health
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• v.42 no.2
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• pp.89-95
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• 2009

Objectives : To assess the protective effects of wearing protective devices among the residents and volunteers who participated in the cleanup of the Hebei Spirit oil spill. Methods : A total of 288 residents and 724 volunteers were surveyed about symptoms, whether they were wearing protective devices and potential confounding variables. The questionnaires were administered from the second to the sixth week following the accident. Spot urine samples were collected and analyzed for metabolites of 4 volatile organic compounds(VOCs), 2 polycyclic aromatic hydrocarbons(PAHs), and 6 heavy metals. The association between the wearing of protective devices and various symptoms was assessed using a multiple logistic regression adjusted for confounding variables. A multiple generalized linear regression model adjusted for the covariates was used to test for a difference in least-square mean concentration of urinary biomarkers between residents who wore protective devices and those who did not. Results : Thirty nine to 98% of the residents and 62-98% of volunteers wore protective devices. Levels of fatigue and fever were higher among residents not wearing masks than among those who did wear masks(odds ratio 4.5; 95% confidence interval 1.23-19.86). Urinary mercury levels were found to be significantly higher among residents not wearing work clothes or boots(p<0.05). Conclusions : Because the survey was not performed during the initial high-exposure period, no significant difference was found in metabolite levels between people who wore protective devices and those who did not, except for mercury, whose biological half-life is more than 6 weeks.