You are here:
BENCHMARK DOSES FOR CHEMICAL MIXTURES: EVALUATION OF A MIXTURE OF 18 PHAHS.
Citation:
NYIRABAHIZI, E., C. GENNINGS, W. W. PIEGORSCH, S. YEATTS, M. J. DEVITO, AND K. M. CROFTON. BENCHMARK DOSES FOR CHEMICAL MIXTURES: EVALUATION OF A MIXTURE OF 18 PHAHS. Presented at Society of Toxicology, Seattle, WA, March 16 - 20, 2008.
Impact/Purpose:
The present work developed and tested a methodology to estimate BMDs for mixtures of chemicals at fixed mixing ratios.
Description:
Benchmark doses (BMDs), defined as doses of a substance that are expected to result in a pre-specified level of "benchmark" response (BMR), have been used for quantifying the risk associated with exposure to environmental hazards. The lower confidence limit of the BMD is used as a basis for the point of departure (POD) in risk assessments, often with additional uncertainty factors included. This risk estimate, however, does not account for potential interaction of the substance with other chemicals included in human exposures. The present work developed and tested a methodology to estimate BMDs for mixtures of chemicals at fixed mixing ratios. Comparisons were made to the BMD under the assumption of additivity. Young female Long-Evans rats were dosed via gavage with 18 different polyhalogenated aromatic hydrocarbons [2 dioxins, 4 dibenzofurans, and 12 PCBs, including dioxin-like and non-dioxin-like PCBs], or a mixture with the ratio of the 18 chemicals based on environmental concentrations, for 4 consecutive days. Serum total T4 was measured via radioimmunoassay in samples collected 24 hr after the last dose. Analyses of these data (Crofton et al, EHP, 2005) suggested no departure from additivity in the low dose region of the mixture, implying a BMD for the mixture could be based on single-chemical data in an additivity model. Our objective was to evaluate this assumption. Three candidate nonlinear additivity models were considered and ranked with the AIC criteria. To calculate the BMD, the BMR was selected to be a 10% shift in T4 (expressed relative to controls). The results of a Wald-type test revealed no statistical significant difference between the BMD under additivity compared to that from the mixture data. We conclude that use of a BMD for this mixture could be based on single chemical data in an additivity model.