Linear regression models of methyl mercury exposure during prenatal and early postnatal life among riverside people along the Upper Madeira river, Amazon

This research is focused on prenatal and early postnatal mercury (Hg) exposure among the riverside people along the Upper Madeira river in the Amazon. Linear regression models were developed to predict the hair Hg concentration in infants. The independent variables included in the model of Group 1 (87 pairs of mothers and their infants) were the average maternal hair Hg concentration and maternal age. Group 2 (31 pairs) included maternal segmental hair Hg concentrations. For the segmental hair Hg analysis over time, it was assumed that hair grows at a rate of 11 cm per month. Thus, information on the timing of the dates of pregnancy and breast feeding from the birth history was used to cut the hair strands into segments, making them correspond to the mother's reproductive stage of life (31 pairs of mothers and their infants). Breast milk Hg concentration results were included with segmental and average maternal hair Hg concentration values (22 and 44 pairs of mothers and their infants, respectively). The models including the breast milk Hg concentration indicated that 61 and 55% of the variability of the infant hair Hg concentrations were due to the independent variables: segmental maternal hair Hg with breast milk Hg and average maternal hair Hg with breast milk Hg, respectively. The regression coefficients mere in the range of 0.19 to 0.90, and P values mere in the range of 0.0001 to 0.1490. Further recommendations include fish advisories to prevent critical Hg exposures during reproductive life and investigation of neurobehavioral performance of this study population. (C) 2000 Academic Press.