Inter- and intra-individual variation in urinary biomarker concentrations over a 6-day sampling period. Part 1: Metals

Abstract The aim of the current HBM-study is to further the understanding of the impact of inter- and intra-individual variability in HBM surveys as it may have implications for the design and interpretation of the study outcomes. As spot samples only provide a snapshot in time of the concentrations of chemicals in an individual, it remains unclear to what extent intra-individual variability plays a role in the overall variability of population-wide HBM surveys. The current paper describes the results of an intensive biomonitoring study, in which all individual urine samples of 8 individuals were collected over a 6-day sampling period (a total of 352 unique samples). By analyzing different metals (As, Cd, Mn, Ni) in each individual sample, inter- and intra-individual variability for these four metals could be determined, and the relationships between exposure, internal dose, and sampling protocol assessed. Although the range of biomarker values for different metals was well within the normal range reported in large-scale population surveys, large intra-individual differences over a 6-day period could also be observed. Typically, measured biomarker values span at least an order of magnitude within an individual, and more if specific exposure episodes could be identified. Fish consumption for example caused a twenty- to thirty-fold increase in urinary As-levels over a period of 2–6 h. Intra-class correlation coefficients (ICC) were typically low for uncorrected biomarker values (between 0.104 and 0.460 for the 4 metals), but improved when corrected for creatinine or specific gravity (SG). The results show that even though urine is a preferred matrix for HBM studies, there are certain methodological issues that need to be taken into account in the interpretation of urinary biomarker data, related to the intrinsic variability of the urination process itself, the relationship between exposure events and biomarker quantification, and the timing of sampling. When setting up HBM-projects, this expected relationship between individual exposure episode and urinary biomarker concentration needs to be taken into account.