Dynamic Transgenerational Fate of Polychlorinated Biphenyls and Dioxins/Furans in Lactating Cows and Their Offspring.

We report on two farms in Switzerland heavily contaminated by polychlorinated biphenyls (PCBs) and dioxins (PCDD/Fs), occurring in the first case from diffuse sources and in the second case from PCB-containing wall paint. Extensive measurements of PCBs and PCDD/Fs on site (soil, forage, and paint) and in cattle (blood, fat, and milk) allowed validation of our novel dynamic toxicokinetic model, which includes the transfer of contaminants from the mother cows to their suckling calf and the uptake of soil by grazing cattle. We show that for calves, the mother milk is the main uptake route of contaminants. For both cows and calves, ingestion of contaminated soil, although often overlooked, is an appreciable uptake path. The remediation of the contaminated stable lead to a 2-3 fold reduction of the PCB levels in animals within one year. The transfer of animals to an uncontaminated mountain site during summer proved to be an effective decontamination procedure with up to 50% reduction of the levels within three months. Our study calls for a rapid removal of PCB-containing materials in animal husbandry farms and shows that the diffuse contamination of soils will remain a source for PCBs and PCDD/Fs in our food chain for decades to come.

Long-term time trends in human intake of POPs in the Czech Republic indicate a need for continuous monitoring.

Polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) from the group of persistent organic pollutants are detected in human tissues years or even decades after their ban. Exposure to PCBs and OCPs can pose risks to human health. In the present study, we calculated the daily intakes of PCBs and OCPs in the Czech population and investigated the long-term trends of human exposure to POPs. Data on POP concentrations from a 16-year period of breast-milk monitoring were used. A toxicokinetic model with consideration of compound-specific elimination half-lives was used to calculate the mothers' daily intake of PCBs and OCPs representing the intake of POPs by all exposure routes. The calculated intakes were compared with dietary intakes calculated by the Czech National Institute of Public Health. The comparison shows good agreement of both intake estimates with decreasing intake trends of POPs in the Czech population in the time period studied. However, several fluctuations with peaks of higher levels were observed in both datasets which are not typical for the period after the ban of use and production of POPs. The available evidence suggests that the increases in chemical concentrations might be caused by food contamination. The calculated intakes of compounds with longer elimination half-lives, such as higher-chlorinated PCBs, were higher in older mothers. This "memory effect" was already observed in other studies and indicates higher exposure in earlier life periods of the mother. Our results suggest that exposure to POPs is still relevant for the Czech population in the period after the ban of the use and production of POPs (post-ban period), especially via food ingestion, though the intake trends are decreasing. Possible food contamination by POPs in the post-ban period requires further assessment.

Recommendations for Evaluating Temporal Trends of Persistent Organic Pollutants in Breast Milk.

BACKGROUND: Biomonitoring data of persistent organic pollutants (POPs) in breast milk are increasingly collected and available for quantitative analysis of levels and time trends. A common approach is to apply log-linear regression to calculate doubling and halving times of the POP concentrations based on the temporal trend observed in breast milk. However, there are different, sometimes conflicting interpretations of these doubling and halving times. OBJECTIVES: We provide a mechanistic understanding of doubling and halving times where possible. Five recommendations are proposed for dealing with POP concentration trends in breast milk during three distinct periods (pre-ban, transition, post-ban period). DISCUSSION: Using temporal trends of BDE-47 and PCB-153 in breast milk data, we show which information can be gained from the time-trend data. To this end, we analyzed time trends of hypothetical POPs for different periods with time-variant exposure and different intrinsic elimination half-lives, using a dynamic population-based pharmacokinetic model. Different pieces of information can be extracted from time-trend data from different periods. The analysis of trends of short-lived POPs is rather straightforward and facilitates extraction of the intrinsic elimination half-lives from the breast milk data. However, trends of slowly eliminated POPs only provide indications for the exposure time trend. CONCLUSIONS: Time-trend data of rapidly eliminated POPs provide information on exposure time trends and elimination half-lives. Temporal trends of slowly eliminated POPs are more complicated to interpret, and the extraction of exposure time trends and elimination half-lives require data sets covering several decades. CITATION: Gyalpo T, Scheringer M, Hungerbühler K. 2016. Recommendations for evaluating temporal trends of persistent organic pollutants in breast milk. Environ Health Perspect 124:881-885; http://dx.doi.org/10.1289/ehp.1510219.

Insights into PBDE Uptake, Body Burden, and Elimination Gained from Australian Age-Concentration Trends Observed Shortly after Peak Exposure.

BACKGROUND: Population pharmacokinetic models combined with multiple sets of age-concentration biomonitoring data facilitate back-calculation of chemical uptake rates from biomonitoring data. OBJECTIVES: We back-calculated uptake rates of PBDEs for the Australian population from multiple biomonitoring surveys (top-down) and compared them with uptake rates calculated from dietary intake estimates of PBDEs and PBDE concentrations in dust (bottom-up). METHODS: Using three sets of PBDE elimination half-lives, we applied a population pharmacokinetic model to the PBDE biomonitoring data measured between 2002-2003 and 2010-2011 to derive the top-down uptake rates of four key PBDE congeners and six age groups. For the bottom-up approach, we used PBDE concentrations measured around 2005. RESULTS: Top-down uptake rates of Σ4BDE (the sum of BDEs 47, 99, 100, and 153) varied from 7.9 to 19 ng/kg/day for toddlers and from 1.2 to 3.0 ng/kg/day for adults; in most cases, they were--for all age groups--higher than the bottom-up uptake rates. The discrepancy was largest for toddlers with factors up to 7-15 depending on the congener. Despite different elimination half-lives of the four congeners, the age-concentration trends showed no increase in concentration with age and were similar for all congeners. CONCLUSIONS: In the bottom-up approach, PBDE uptake is underestimated; currently known pathways are not sufficient to explain measured PBDE concentrations, especially in young children. Although PBDE exposure of toddlers has declined in the past years, pre- and postnatal exposure to PBDEs has remained almost constant because the mothers' PBDE body burden has not yet decreased substantially.

Estimation of human body concentrations of DDT from indoor residual spraying for malaria control.

Inhabitants of dwellings treated with DDT for indoor residual spraying show high DDT levels in blood and breast milk. This is of concern since mothers transfer lipid-soluble contaminants such as DDT via breastfeeding to their children. Focusing on DDT use in South Africa, we employ a pharmacokinetic model to estimate DDT levels in human lipid tissue over the lifetime of an individual to determine the amount of DDT transferred to children during breastfeeding, and to identify the dominant DDT uptake routes. In particular, the effects of breastfeeding duration, parity, and mother's age on DDT concentrations of mother and infant are investigated. Model results show that primiparous mothers have greater DDT concentrations than multiparous mothers, which causes higher DDT exposure of first-born children. DDT in the body mainly originates from diet. Generally, our modeled DDT levels reproduce levels found in South African biomonitoring data within a factor of 3.