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

Highlights: • The heavy metals (HMs) in hairs and nails of people in agricultural areas were measured. • HMs in hairs and nails from GW drinking group were significantly higher than the other. • High drinking rate for long term of GW even low concentration of HMs had adverse health effects to human. • The associated factors and probabilities were found by χ² statistic and binary logistic regression. • Not only HMs in groundwater, but this study found other associated factors affecting to human. 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.