• Journal of agricultural medicine and community health
• /
• v.47 no.3
• /
• pp.181-188
• /
• 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 Environmental Health Sciences
• /
• v.48 no.6
• /
• pp.306-314
• /
• 2022

Background: Due to the rapid aging of the South Korean population, neurological diseases such as dementia are increasing. Many studies have reported that the incidence of dementia is associated with environmental factors along with age. Objectives: This study analyzed the association between cognitive function and ten heavy metals in the body: arsenic, aluminum, chromium, manganese, cobalt, nickel, iron, copper, zinc, and lead. Methods: From 2018 to 2019, a total of 120 participants who suffered from cognitive impairment were recruited for this study. Blood and urine samples were collected and analyzed for heavy metal concentrations using an inductively coupled plasma mass spectrometer. Demographic information was obtained through face-to-face questionnaires completed by a trained investigator. Cognitive function was evaluated with the Korean version of the Mini-Mental State Examination and the Korean version of the Boston Name Waiting Test. The associations between cognitive function scores and heavy metal concentrations were analyzed using multiple logistic regression analysis. Results: The average age of the 120 participants was 72.7 years, and 69.2% were female. The mean of the MMSE-K and K-BNT scores were 22.9 and 37.9, respectively. The geometric mean of aluminum (Al) was 8.42 ㎍/L. MMSE-K was associated with iron (Fe), but the significance was removed in the logistic regression based on 24 points. K-BNT was significantly associated with aluminum and the odds ratio for K-BNT above 38 decreased by 45% as the aluminum concentration increased. Conclusions: The association between aluminum and the K-BNT score indicated that aluminum is associated with language-related cognitive decline. Based on this result, further study will be conducted by considering co-exposure effects of heavy metals including aluminum.