Lead and cadmium are harmful heavy metals that are used for a variety of occupational purposes. Considering their potentially hazardous effects on health, studies on the association between exposure to these two heavy metals and health disorders have been actively conducted. This study aimed to determine the association between blood lead and cadmium levels and blood pressure in workers exposed to lead and cadmium in a smelter.
Nine hundred and sixty-three male workers who worked in a smelter, and underwent medical examinations at the Ulsan University Hospital between January 1 and December 31, 2014, were selected as participants. Among them, 310 subjects whose data on height, weight, blood pressure, fasting blood glucose, lipid profile, and blood lead and cadmium levels were available and who answered the questionnaire were selected as the final participants. We investigated the drinking habit, smoking status, exercise adequacy, and family history of hypertension of these workers using formal questionnaires. A statistical analysis was conducted using Student’s
The association between blood lead and cadmium levels and blood pressure was analyzed through statistical adjustment of the risk factors of hypertension. Results showed an association between blood cadmium level and blood pressure elevation. However, blood lead level was found to be not correlated with blood pressure elevation.
This study shows the association between blood cadmium level and systolic blood pressure (SBP) and diastolic blood pressure (DBP) elevation.
IRB No. 2017–03-037. Retrospectively Registered 30 March 2017.
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Populations neighboring industrial complexes are at an increased health risk, due to constant exposure to various potentially hazardous compounds released during industrial production activity. Although there are many previous studies that focus on occupational exposure to heavy metals, studies that focused on environmental exposure to lead and cadmium are relatively rare. The purpose of this study is to evaluate the extent of the environmental exposure of heavy metals in residents of industrial area.
Four areas in close proximity to the Ulsan petrochemical industrial complex and the Onsan national industrial complex were selected to be included in the exposure group, and an area remotely located from these industrial complexes was selected as the non-exposure group. Among the residents of our study areas, a total of 1573 subjects aged 20 years and older were selected and all study subjects completed a written questionnaire. Blood and urine samples were obtained from about one third of the subjects (465 subjects) who provided informed consent for biological sample collection. Total 429 subjects (320 subjects from exposure area, 109 subjects from non-exposure area) were included in final analysis.
The geometric mean blood lead level among the subjects in the exposed group was 2.449 μg/dL, which was significantly higher than the non-exposure group’s level of 2.172 μg/dL. Similarly, the geometric mean urine cadmium levels between the two groups differed significantly, at 1.077 μg/g Cr. for the exposed group, and 0.709 μg/g Cr. for the non-exposure group.
In a multiple linear regression analysis to determine the relationship between blood lead level and related factors, the results showed that blood lead level had a significant positive correlation with age, the male, exposure area, and non-drinkers. In the same way, urine cadmium level was positively correlated with age, the female, exposure area, and smokers.
This study found that blood lead levels and urine cadmium levels were significantly higher among the residents of industrial areas than among the non-exposure area residents, which is thought to be due to the difference in environmental exposure of lead and cadmium. Furthermore, it was clear that at a low level of exposure, differences in blood lead or urine cadmium levels based on age, gender, and smoking status were greater than the differences based on area of residence. Therefore, when evaluating heavy metal levels in the body at a low level of exposure, age, gender, and smoking status must be adjusted, as they are significant confounding factors.
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