Agneta Falk Filipsson

Phthalate diesters and their metabolites in human breast milk, blood or serum, and urine as biomarkers of exposure in vulnerable populations

Background Phthalates may pose a risk for perinatal developmental effects. An important question relates to the choice of suitable biological matrices for assessing exposure during this period. Objectives This study was designed to measure the concentrations of phthalate diesters or their metabolites in breast milk, blood or serum, and urine and to evaluate their suitability for assessing perinatal exposure to phthalates. Methods In 2001, 2–3 weeks after delivery, 42 Swedish primipara provided breast milk, blood, and urine samples at home. Special care was taken to minimize contamination with phthalates (e.g., use of a special breast milk pump, heat treatment of glassware and needles, addition of phosphoric acid). Results Phthalate diesters and metabolites in milk and blood or serum, if detected, were present at concentrations close to the limit of detection. By contrast, most phthalate metabolites were detectable in urine at concentrations comparable to those from the general population in the United States and in Germany. No correlations existed between urine concentrations and those found in milk or blood/serum for single phthalate metabolites. Our data are at odds with a previous study documenting frequent detection and comparatively high concentrations of phthalate metabolites in Finnish and Danish mothers’ milk. Conclusions Concentrations of phthalate metabolites in urine are more informative than those in milk or serum. Furthermore, collection of milk or blood may be associated with discomfort and potential technical problems such as contamination (unless oxidative metabolites are measured). Although urine is a suitable matrix for health-related phthalate monitoring, urinary concentrations in nursing mothers cannot be used to estimate exposure to phthalates through milk ingestion by breast-fed infants.

The Benchmark Dose Method—Review of Available Models, and Recommendations for Application in Health Risk Assessment

The benchmark dose method has been proposed as an alternative to the no-observed-adverse-effect level (NOAEL) approach for assessing noncancer risks associated with hazardous compounds. The benchmark dose method is a more powerful statistical tool than the traditional NOAEL approach and represents a step in the right direction for a more accurate risk assessment. The benchmark dose method involves fitting a mathematical model to all the dose-response data within a study, and thus more biological information is incorporated in the resulting estimates of guidance values (e.g., acceptable daily intakes, ADIs). Although there is an increasing interest in the benchmark dose approach, it has not yet found its way into the regulatory toxicology in Europe, while in the United States the U.S. Environmental Protection Agency (EPA) already uses the benchmark dose in health risk assessment. Several software packages are today available for benchmark dose calculations. The availability of software to facilitate the analysis can make modeling appear simple, but often the interpretation of the results is not trivial, and it is recommended that benchmark dose modeling be performed in collaboration with a toxicologist and someone familiar with this type of statistical analysis. The procedure does not replace expert judgments of toxicologists and others addressing the hazard characterization issues in risk assessment. The aim of this article is to make risk assessors familiar with the concept, to show how the method can be used, and to describe some possibilities, limitations, and extensions of the benchmark dose approach. In this article the benchmark dose approach is presented in detail and compared to the traditional NOAEL approach. Statistical methods essential for the benchmark dose method are presented in Appendix A, and different mathematical models used in the U.S. EPAs BMD software, the Crump software, and the Kalliomaa software are described in the text and in Appendix B. For replacement of NOAEL in health risk assessment it is considered important that consensus is reached on the crucial parts of the benchmark dose method, that is, selection of risk types and the determination of a response level corresponding to the BMD, especially for continuous data. It is suggested that the BMD method is used as a first choice and that in cases where it is not possible to fit a model to the data the traditional NOAEL approach should be used instead. The possibilities to make benchmark dose calculations on continuous data need to be further investigated. In addition, it is of importance to study whether it would be appropriate to increase the number of dose levels by decreasing the number of animals in each dose group.

Benchmark Dose for Cadmium-Induced Renal Effects in Humans

Objectives Our goal in this study was to explore the use of a hybrid approach to calculate benchmark doses (BMDs) and their 95% lower confidence bounds (BMDLs) for renal effects of cadmium in a population with low environmental exposure. Methods Morning urine and blood samples were collected from 820 Swedish women 53–64 years of age. We measured urinary cadmium (U-Cd) and tubular effect markers [N-acetyl- β-D-glucosaminidase (NAG) and human complex-forming protein (protein HC)] in 790 women and estimated glomerular filtration rate (GFR; based on serum cystatin C) in 700 women. Age, body mass index, use of nonsteroidal anti-inflammatory drugs, and blood lead levels were used as covariates for estimated GFR. BMDs/BMDLs corresponding to an additional risk (benchmark response) of 5 or 10% were calculated (the background risk at zero exposure was set to 5%). The results were compared with the estimated critical concentrations obtained by applying logistic models used in previous studies on the present data. Results For both NAG and protein HC, the BMDs (BMDLs) of U-Cd were 0.5–1.1 (0.4–0.8) μg/L (adjusted for specific gravity of 1.015 g/mL) and 0.6–1.1 (0.5–0.8) μg/g creatinine. For estimated GFR, the BMDs (BMDLs) were 0.8–1.3 (0.5–0.9) μg/L adjusted for specific gravity and 1.1–1.8 (0.7–1.2) μg/g creatinine. Conclusion The obtained benchmark doses of U-Cd were lower than the critical concentrations previously reported. The critical dose level for glomerular effects was only slightly higher than that for tubular effects. We suggest that the hybrid approach is more appropriate for estimation of the critical U-Cd concentration, because the choice of cutoff values in logistic models largely influenced the obtained critical U-Cd.

Benchmark Calculations in Risk Assessment Using Continuous Dose‐Response Information: The Influence of Variance and the Determination of a Cut‐Off Value

A benchmark dose (BMD) is the dose of a chemical that corresponds to a predetermined increase in the response (the benchmark response, BMR) of a health effect. In this article, a method (the hybrid approach) for benchmark calculations from continuous dose-response information is investigated. In the formulation of the methodology, a cut-off value for an adverse health effect has to be determined. It is shown that the influence of variance on the hybrid model depends on the choice of determination of the cut-off point. If the cut-off value is determined as corresponding to a specified tail proportion of the control distribution, P(0), the BMD becomes biased upward when the variance is biased upward. On the contrary, if the cut-off value is directly determined to some level of the continuous response variable, the BMD becomes biased upward when the variance is biased downward. A simulation study was also performed in which the accuracy and precision of the BMD was compared for the two ways of determining the cut-off value. In general, considering BMRs of 1, 5, and 10% (additional risk) the precision of the BMD became higher when the cut-off value was estimated by specifying P(0), relative to the case with a direct determination. Use of the square-root of the maximum-likelihood estimator of the variance in BMD estimation may provide a bias that is reflected by the cut-off formulation (downward bias if specifying P(0), and upward bias if specifying the cut-off, c, directly). This feature may be reduced if an unbiased estimator of the standard deviation is used in the calculations.

Comparison of available benchmark dose softwares and models using trichloroethylene as a model substance

By using trichloroethylene as a model substance the U.S. EPA benchmark dose software was compared to the software by Crump and the software by Kalliomaa. Dose-response and dose-effect data on the liver, kidneys, central nervous system (CNS), and tumours were selected for the evaluation. Based on the present study the U.S. EPA software is preferable to the other softwares for dichotomous data. A wider range in benchmark doses was often observed for dichotomous data when the numbers of dose levels were limited. The log-logistic model in most cases gave the best fit when ranking the dichotomous models. In addition, the log-logistic model often implied a more conservative benchmark dose. For continuous data it was more difficult to find a model describing the data. The softwares by Kalliomaa and by the U.S. EPA offered the best opportunities for benchmark dose modelling of continuous data. Flexible models, like the Hill- and the Mult model, are needed for S-shaped continuous data but these models demand more dose levels in order to describe the data. Since the number of dose levels are important for model selection study design is important and should be further evaluated.