Abstract
OBJECTIVES: To examine the interrelations among chelatable lead (by dimercaptosuccinic acid, DMSA), tibial lead, and blood lead concentrations in 802 Korean workers with occupational exposure to lead and 135 employed controls with only environmental exposure to lead. METHODS: This was a cross sectional study wherein tibial lead, DMSA chelatable lead, and blood lead were measured. Linear regression was used to identify predictors of the three lead biomarkers, evaluating the influence of age, job duration, sex, education level, alcohol and tobacco use, creatinine clearance rate, and body mass index. RESULTS: DMSA chelatable lead concentrations ranged from 4.8 to 2102.9 microg and were positively associated with age, current smoking, and creatinine clearance rate. On average, women had 64 microg less DMSA chelatable lead than men. When blood lead and its square were added to a model with age, sex, current smoking, body mass index, and creatinine clearance rate, blood lead accounted for the largest proportion of the variance and sex became of borderline significance. Tibial lead concentrations ranged from -7 to 338 microg/g bone mineral and were positively associated with age, job duration, and body mass index. Women had, on average, 9.7 microg/g less tibial lead than men. Blood lead concentrations ranged from 4.3 to 85.7 microg/dl and were positively associated with age and tibial lead, whereas current smokers had higher blood lead concentrations and women had lower blood lead concentrations. CONCLUSIONS: The data suggest that age and sex are both predictors of DMSA chelatable lead, blood lead, and tibial lead concentrations and that tibial lead stores in older subjects are less bioavailable and may contribute less to blood lead concentrations than tibial lead stores in younger subjects. Although blood lead concentrations accounted for a large proportion of the variance in DMSA chelatable lead concentrations, suggesting that measurement of both in epidemiological studies may not be necessary, the efficacy of each measure in predicting health outcomes in epidemiological studies awaits further investigation.