Publications by authors named "Richard C Hertzberg"

The interaction-based hazard index (HI), a mixtures approach to characterizing toxicologic interactions, is demonstrated and evaluated by statistically analyzing data on four regulated trihalomethanes (THMs). These THMs were the subject of a multipurpose toxicology study specifically designed to evaluate the HI formula. This HI evaluation uses single, binary and quaternary mixture THM data.

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In this study, proportional response addition (Prop-RA), a model for predicting response from chemical mixture exposure, is demonstrated and evaluated by statistically analyzing data on all possible binary combinations of the four regulated trihalomethanes (THMs). These THMs were the subject of a multipurpose toxicology study specifically designed to evaluate Prop-RA. The experimental design used a set of doses common to all components and mixtures, providing hepatotoxicity data on the four single THMs and the binary combinations.

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Benchmark dose (BMD) modeling is now the state of the science for determining the point of departure for risk assessment. Key advantages include the fact that the modeling takes account of all of the data for a particular effect from a particular experiment, increased consistency, and better accounting for statistical uncertainties. Despite these strong advantages, disagreements remain as to several specific aspects of the modeling, including differences in the recommendations of the US Environmental Protection Agency (US EPA) and the European Food Safety Authority (EFSA).

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In assessing environmental health risks, the risk characterization step synthesizes information gathered in evaluating exposures to stressors together with dose-response relationships, characteristics of the exposed population, and external environmental conditions. This article summarizes key steps of a cumulative risk assessment (CRA) followed by a discussion of considerations for characterizing cumulative risks. Cumulative risk characterizations differ considerably from single chemical- or single source-based risk characterization.

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The historical approach to assessing health risks of environmental chemicals has been to evaluate them one at a time. In fact, we are exposed every day to a wide variety of chemicals and are increasingly aware of potential health implications. Although considerable progress has been made in the science underlying risk assessments for real-world exposures, implementation has lagged because many practitioners are unaware of methods and tools available to support these analyses.

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Mixture risk assessment is often hampered by the lack of dose-response information on the mixture being assessed, forcing reliance on component formulas such as dose addition. We present a four-step approach for evaluating chemical mixture data for consistency with dose addition for use in supporting a component based mixture risk assessment. Following the concepts in the U.

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Statistical design and environmental relevance are important aspects of studies of chemical mixtures, such as pesticides. We used a dose-additivity model to test experimentally the default assumptions of dose additivity for two mixtures of seven N-methylcarbamates (carbaryl, carbofuran, formetanate, methomyl, methiocarb, oxamyl, and propoxur). The best-fitting models were selected for the single-chemical dose-response data and used to develop a combined prediction model, which was then compared with the experimental mixture data.

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Previously, we reported that acute treatment with propoxur or carbaryl decreased the duration of the photic after discharge (PhAD) of flash evoked potentials (FEPs). In the current studies, we compared the effects of acute or repeated exposure to a mixture of carbaryl and propoxur (1:1.45 ratio; propoxur:carbaryl) on the duration of the PhAD and brain ChE activity in Long Evans rats.

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The role of nonchemical stressors in modulating the human health risk associated with chemical exposures is an area of increasing attention. On 9 March 2011, a workshop titled "Approaches for Incorporating Nonchemical Stressors into Cumulative Risk Assessment" took place during the 50th Anniversary Annual Society of Toxicology Meeting in Washington D.C.

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Reactions between chemicals used to disinfect drinking water and compounds present in source waters produce chemical mixtures containing hundreds of disinfection byproducts (DBPs). Although the results have been somewhat inconsistent, some epidemiological studies suggest associations may exist between DBP exposures and adverse developmental outcomes. The potencies of individual DBPs in rodent and rabbit developmental bioassays suggest that no individual DBP can account for the relative risk estimates reported in the positive epidemiologic studies, leading to the hypothesis that these outcomes could result from the toxicity of DBP mixtures.

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Humans are exposed daily to multiple chemicals, including incidental exposures to complex chemical mixtures released into the environment and to combinations of chemicals that already co-exist in the environment because of previous releases from various sources. Exposures to chemical mixtures can occur through multiple pathways and across multiple routes. In this paper, we propose an iterative approach for assessing exposures to environmental chemical mixtures; it is similar to single-chemical approaches.

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Project-level research strategies at the U.S. Environmental Protection Agency regarding chemical mixtures are impacted by administrative priorities, public interests, expert opinions, scientific advances, regulatory needs, and legislative actions, influencing the setting of priorities and goals.

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Chemical disinfection of water is of direct public health benefit as it results in decreased water-borne illness. The chemicals used to disinfect water react with naturally occurring organic matter, bromide, and iodide in the source water, resulting in the formation of disinfection by-products (DBPs). Despite the identification of several hundred DBPs, more than 50% of the mass of total organic halide formed during chlorination remains unidentified.

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Risk assessment formulas are often distinguished from dose-response models by being rough but necessary. The evaluation of these rough formulas is described here, using the example of mixture risk assessment. Two conditions make the dose-response part of mixture risk assessment difficult, lack of data on mixture dose-response relationships, and the need to address risk from combinations of chemicals because of public demands and statutory requirements.

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A substantial effort has been spent over the past few decades to label toxicologic interaction outcomes as synergistic, antagonistic, or additive. Although useful in influencing the emotions of the public and the press, these labels have contributed fairly little to our understanding of joint toxic action. Part of the difficulty is that their underlying toxicological concepts are only defined for two chemical mixtures, while most environmental and occupational exposures are to mixtures of many more chemicals.

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