powers of TEFs for dioxins and dioxin-like PCBs (Walker et al. 2005; NTP 2006), ternary mixtures of TCDD, PeCDF and PCB 126 were administered at dose levels representing the four TEF-equivalent doses used for TCDD alone in previous NTP studies. While the dioxin mixtures produced a range of cellular proliferative and carcinogenic responses comparable to that seen with TCDD alone, the dose–response relationships were not identical. Therefore, while this NTP study provided some support for the TEF concept, it did show that the numerical values for TEFs may not be applicable across the full range of toxicological outcomes (Gray et al. 2006). On the other hand, Smialowicz et al. (2008) were able to validate the US EPA dioxin-like TEFs to predict immunotoxic endpoints, based on their CYP inductive effects. A more comprehensive review of the methodologies and databases used to establish dioxin TEFs has been published by Haws et al. (2006). 12.4 This approach is the one most commonly used in health risk assessments. The contribution of an individual mixture component is calculated as a ratio of predicted exposure compared with a health-based benchmark (ADI, TDI). This derived ratio is termed a hazard quotient (HQ). To derive an overall estimate of risk across all components of the mixture, the individual HQs are summed to derive a hazard index (HI) (Herzberg & Teuschler 2002). Ej = exposure level of chemical j RfDj = RfD of chemical j HQj = HQ for chemical j (dimensionless) RfD is US terminology equivalent to the ADI or TDI While this pragmatic approach may be a useful screening tool, is used quite extensively in HRA practice and is generally accepted, or even required, by Australian regulatory authorities, it is based on a potentially flawed premise. As noted above, additive risk estimates imply a common MoA, or at least a common toxicological outcome. Where the toxicity of individual components does not satisfy such an assumption, the contributions to risk are theoretically independent.
powers of TEFs for dioxins and dioxin-like PCBs (Walker et al. 2005; NTP 2006), ternary mixtures of TCDD, PeCDF and PCB 126 were administered at dose levels representing the four TEF-equivalent doses used for TCDD alone in previous NTP studies. While the dioxin mixtures produced a range of cellular proliferative and carcinogenic responses comparable to that seen with TCDD alone, the dose–response relationships were not identical. Therefore, while this NTP study provided some support for the TEF concept, it did show that the numerical values for TEFs may not be applicable across the full range of toxicological outcomes (Gray et al. 2006). On the other hand, Smialowicz et al. (2008) were able to validate the US EPA dioxin-like TEFs to predict immunotoxic endpoints, based on their CYP inductive effects. A more comprehensive review of the methodologies and databases used to establish dioxin TEFs has been published by Haws et al. (2006). 12.4 This approach is the one most commonly used in health risk assessments. The contribution of an individual mixture component is calculated as a ratio of predicted exposure compared with a health-based benchmark (ADI, TDI). This derived ratio is termed a hazard quotient (HQ). To derive an overall estimate of risk across all components of the mixture, the individual HQs are summed to derive a hazard index (HI) (Herzberg & Teuschler 2002). Ej = exposure level of chemical j RfDj = RfD of chemical j HQj = HQ for chemical j (dimensionless) RfD is US terminology equivalent to the ADI or TDI While this pragmatic approach may be a useful screening tool, is used quite extensively in HRA practice and is generally accepted, or even required, by Australian regulatory authorities, it is based on a potentially flawed premise. As noted above, additive risk estimates imply a common MoA, or at least a common toxicological outcome. Where the toxicity of individual components does not satisfy such an assumption, the contributions to risk are theoretically independent.
w.Environmental-Health-Risk-Assessment.docx