Using hair and fingernails in binary logistic regression for bio-monitoring of heavy metals/metalloid in groundwater in intensively agricultural areas, Thailand

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Abstract

In this study, the hair and fingernails of the local people in an intensively cultivated agricultural area in Ubon Ratchathani province, Thailand, were used as biomarkers of exposure to arsenic (As) and heavy metals. The study area has shallow acidic groundwater that is contaminated with As and heavy metals. The local people often consume this shallow groundwater; thus, they are exposed to As and heavy metals. Hair and fingernail samples were collected to characterize the differences between shallow groundwater drinking (SGWD) and tap water drinking (TWD) residents. The concentrations of As and the heavy metals Cd, Pb and Hg were significantly higher in the hair samples from the SGWD group than those from the TWD group, especially for As (0.020–0.571 vs. 0.024–0.359 μg/g) and Cd (0.009–0.575 vs. 0.013–0.230 μg/g). Similarly, the concentrations of As and the heavy metals in the fingernail samples collected from the SGWD group were larger than those of the TWD group, especially for As (0.039–2.440 μg/g vs. 0.049–0.806 μg/g). The χ2 statistic and binary logistic regression were used to find the associated factors and assess the associated probabilities. The regression results show that the factors associated with the concentrations of As and the heavy metals in the hair samples were drinking water source, rate of water consumption, gender, bathing water source, education, smoking and underlying disease, whereas the factors associated with the concentrations of these species in the fingernail samples were drinking water source, gender, occupation, work hours per day, alcohol consumption, and the use of pesticides.

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