How to use human biomonitoring in chemical risk assessment: Methodological aspects, recommendations, and lessons learned from HBM4EU.

One of the aims of the European Human Biomonitoring Initiative, HBM4EU, was to provide examples of and good practices for the effective use of human biomonitoring (HBM) data in human health risk assessment (RA). The need for such information is pressing, as previous research has indicated that regulatory risk assessors generally lack knowledge and experience of the use of HBM data in RA. By recognising this gap in expertise, as well as the added value of incorporating HBM data into RA, this paper aims to support the integration of HBM into regulatory RA. Based on the work of the HBM4EU, we provide examples of different approaches to including HBM in RA and in estimations of the environmental burden of disease (EBoD), the benefits and pitfalls involved, information on the important methodological aspects to consider, and recommendations on how to overcome obstacles. The examples are derived from RAs or EBoD estimations made under the HBM4EU for the following HBM4EU priority substances: acrylamide, o-toluidine of the aniline family, aprotic solvents, arsenic, bisphenols, cadmium, diisocyanates, flame retardants, hexavalent chromium [Cr(VI)], lead, mercury, mixture of per-/poly-fluorinated compounds, mixture of pesticides, mixture of phthalates, mycotoxins, polycyclic aromatic hydrocarbons (PAHs), and the UV-filter benzophenone-3. Although the RA and EBoD work presented here is not intended to have direct regulatory implications, the results can be useful for raising awareness of possibly needed policy actions, as newly generated HBM data from HBM4EU on the current exposure of the EU population has been used in many RAs and EBoD estimations.

Polycyclic aromatic hydrocarbons (PAHs) in men and lactating women in Slovenia: Results of the first national human biomonitoring.

In the first national human biomonitoring study in the Slovenian population of adults (18-49 years), including men (n = 297) and lactating primiparous women (n = 304), exposure to polycyclic aromatic hydrocarbons (PAHs) was evaluated. Nine urinary metabolites of four parent PAHs were determined. These included 1-hydroxypyrene (1-OHPYR), 2-hydroxynaphthalene (2-OHNAP), 2-hydroxyphenanthrene (2-OHPHE), 3-hydroxyphenanthrene (3-OHPHE), 4-hydroxyphenanthrene (4-OHPHE), a combination of 2-hydroxyfluorene and 3-hydroxyfluorene (2/3-OHFLU) and a combination of 1-hydroxyphenanthrene and 9-hydroxyphenanthrene (1/9-OHPHE). For comparison, the analysed phenanthrene metabolites were reported as a sum (ΣOHPHE = 1/9-OHPHE + 2-OHPHE + 3-OHPHE + 4-OHPHE) and all the analysed PAH metabolites were reported as a sum (ΣOHPAH = 1-OHPYR + 2/3-OHFLU + 2-OHNAP + ΣOHPHE). All metabolites or their combinations were determined in more than 91% of the samples, except 4-OHPHE, which was determined in only 5% of the samples. The highest concentration was found for 2-OHNAP. This was followed by 2/3-OHFLU and the phenanthrene metabolites, while the lowest concentration was determined for 1-OHPYR. Among the phenanthrene metabolites, the highest concentration was determined for 2-OHPHE, followed by 1/9-OHPHE and then by 3-OHPHE. Values in units of volume and values adjusted for specific gravity were significantly higher in men than in lactating primiparous women for all metabolites, whereas values in units adjusted for creatinine were generally higher in lactating primiparous women than in men. The difference between the two study groups, men and lactating primiparous women, was no longer significant in statistical models adjusted for specific gravity, suggesting that smoking, wood-burning exposure, and/or education largely explained the difference in PAH exposure in both study groups. For most metabolites, predictors of exposure were less significant in lactating primiparous women than in men. Also, site-specific patterns of exposure were observed, with additional predictors identified in certain areas, namely, proximity to roads and release of particulate matter (PM10) from industry. The time of year in which sampling took place appeared to be an important determinant in urban areas and in the case of participants who used wood for heating. Specific dietary factors could not be identified, as the study questionnaire did not include information on PAH-related diet. Despite the low number of paired partners (women and men living in the same household, n = 84), significant positive correlations for all metabolites were observed. This indicated that 31%-56% of variability in exposure could be explained by shared exposure to sources within the households (such as diet and wood-burning-related determinants).

Efficacy of hair analysis for monitoring exposure to uranium: a mini-review.

In spite of the ease with which samples may be collected and the stability of the samples after collection, the use of hair mineral analysis for monitoring environmental exposures and evaluating heavy metal poisonings has remained controversial since its initial applications for these purposes in the early 1950s. Among the major arguments against using hair mineral analysis in general were the absence of biokinetic models and/or metabolic data that adequately described the incorporation of trace elements into the hair, the absence of correlations between the concentrations of trace elements in the hair and their concentrations in other tissues, the inability to distinguish between trace elements that were deposited in the hair endogenously and those that were deposited on the hair exogenously, the absence of reliable reference ranges for interpreting the results of hair mineral analysis and a lack of standard procedures for the collecting, preparing and analyzing the hair samples. The developments of the past two decades addressing these objections are reviewed here, and arguments supporting the use of hair analysis for monitoring environmental and/or occupational exposures to uranium are made on the basis of the information presented in this review.