Environmental Surveillance at Los Alamos: An Independent Reassessment of Historical Data

Since 1971, a series of annual Environmental Surveillance ... reports have served as the official public record of Los Alamos National Laboratory's (LANL) environmental performance. In northern New Mexico, where past LANL emissions are a public health concern, there is public skepticism over the accuracy of information contained in these reports. To test the hypothesis that LANL Environmental Surveillance ... reports systematically understate past emissions, we compared the data on releases in LANL's own internal Occurrence Reports Collection (ORC) to the data reported to the public in the Environmental Surveillance ... reports. A data set of 89 environmental occurrences recorded in the ORC in the time period from 1971 through 1980 was assembled. We did not find a systematic pattern of quantitative underreporting of source terms. However, 17 of the 89 (19%) environmental occurrences recorded in the ORC were not reported to the public in the Environmental Surveillance ... reports. The observed discrepancies are discussed in terms of their relevance to public health concerns. Methodological caveats dictate restraint in applying these findings beyond the scope of the relative comparison performed here. Possible social origins for the rejected hypothesis are discussed. Areas for further consideration by the Centers for Disease Control's dose reconstruction study of LANL are identified.     

Application of a Biologically-Based RFD Estimation Method to Tetrachlorodibenzo-P-Dioxin (TCDD) Mediated Immune Suppression and Enzyme Induction

The current methods for a reference dose (RfD) determination can be enhanced through the use of biologically-based dose-response analysis. Methods developed here utilizes information from tetrachlorodibenzo- p -dioxin (TCDD) to focus on noncancer endpoints, specifically TCDD mediated immune system alterations and enzyme induction. Dose-response analysis, using the Sigmoid-Emax (EMAX) function, is applied to multiple studies to determine consistency of response. Through the use of multiple studies and statistical comparison of parameter estimates, it was demonstrated that the slope estimates across studies were very consistent. This adds confidence to the subsequent effect dose estimates. This study also compares traditional methods of risk assessment such as the NOAEL/safety factor to a modified benchmark dose approach which is introduced here. Confidence in the estimation of an effect dose (ED₁₀) was improved through the use of multiple datasets. This is key to adding confidence to the benchmark dose estimates. In addition, the Sigmoid-Emax function when applied to dose-response data using nonlinear regression analysis provides a significantly improved fit to data increasing confidence in parameter estimates which subsequently improve effect dose estimates.     

Re-evaluation of the Reference Dose for Methylmercury and Assessment of Current Exposure Levels

Methylmercury (Me-Hg) is widely distributed through freshwater and saltwater food chains and human consumption of fish and shellfish has lead to widespread exposure. Both the U.S. EPA Reference Dose (0.3 μg/kg/day) and the FAO/WHO Permissible Tolerable Weekly Intake (3.3 μg/kg/week) are currently based on the prevention of paraesthesia in adult and older children. However, Me-Hg exposure in utero is known to result in a range of developmental neurologic effects including clinical CNS symptoms and delayed onset of walking. Based on a critical review of developmental toxicity data from human and animal studies, it is concluded that current guidelines for the prevention of paraesthesia are not adequate to address developmental effects. A dose of 0.07 μ/kg/day is suggested as the best estimate of a potential reference dose for developmental effects. Data on nationwide fish consumption rates and Me-Hg levels in fish/seafood weighted by proportion of the catch intended for human consumption are analyzed in a Monte Carlo simulation to derive a probability distribution of background Me-Hg exposure. While various uncertainties in the toxicologic and exposure data limit the precision with which health risk can be estimated, this analysis suggests that at current levels of Me-Hg exposure, a significant fraction of women of childbearing age have exposures above this suggested reference dose.     

Interspecies Conversion of Kinetically Equivalent Doses1

A framework is presented within which to organize consideration of appropriate measures of delivered dose and selection of an appropriate procedure for interspecies conversion of kinetically equivalent doses. Systematic species dependencies of simple kinetic relationships between administered and delivered dose are developed. Interspecies scaling of kinetic parameters, including firstorder rate constants and maximum rates of capacity-limited processes, is discussed, and the effects of conventional scaling procedures on initial and steady-state concentrations and on areas under the blood concentration curve are shown. Particular attention is given to production of reactive metabolites. It is shown that interspecies dose or dose rate conversion on the basis of the 3/4 power of body weight is consistently either realistic or conservative when the conversion is carried out from smaller to larger species, except when first-order elimination and capacity-limited production of an active metabolite coexist. In this case, the 3/4 power of body weight conversion procedure may be either overpredictive or underpredictive, depending on the relative dependence of the efficiency of metabolite production and elimination on species body weight. Interspecies dose conversion on a direct mg/kg body weight basis is consistently much less conservative than the 3/4 power of body weight procedure, resulting when scaling from smaller to larger species in underestimation of delivered dose or of steady-state concentration of both parent and metabolite for all of the kinetic relationships considered. Applicability and limitations of these procedures are also discussed.     

Estimation of the Benchmark Dose for Right-Censored Lifetime Data

In this paper, we consider estimating the benchmark dose in a dose–response study with right-censored lifetime data, where the benchmark dose is the dose corresponding to a specific benchmark response, which is related to the probability that the lifetime of a subject receiving the dose is too short. Under the Cox or Weibull extension proportional hazards model, simultaneous lower confidence limits on the benchmark dose are developed. We further conduct a Monte Carlo study to investigate the performance of the proposed lower confidence limits. Finally, a real dataset is illustrated to demonstrate the application of the proposed procedures.     

Dose‐Response Model of Rocky Mountain Spotted Fever (RMSF) for Human

Rickettsia rickettsii is the causative agent of Rocky Mountain spotted fever (RMSF) and is the prototype bacterium in the spotted fever group of rickettsiae, which is found in North, Central, and South America. The bacterium is gram negative and an obligate intracellular pathogen. The disease is transmitted to humans and vertebrate host through tick bites; however, some cases of aerosol transmission also have been reported. The disease can be difficult to diagnose in the early stages, and without prompt and appropriate treatment, it can be fatal. This article develops dose‐response models of different routes of exposure for RMSF in primates and humans. The beta‐Poisson model provided the best fit to the dose‐response data of aerosol‐exposed rhesus monkeys, and intradermally inoculated humans (morbidity as end point of response). The average 50% infectious dose among (ID₅₀) exposed human population, N₅₀, is 23 organisms with 95% confidence limits of 1 to 89 organisms. Similarly, ID₁₀ and ID₂₀ are 2.2 and 5.0, respectively. Moreover, the data of aerosol‐exposed rhesus monkeys and intradermally inoculated humans could be pooled. This indicates that the dose‐response models fitted to different data sets are not significantly different and can be described by the same relationship.     

Locally optimal designs for binary dose‐response models

In this article, we consider the problem of seeking locally optimal designs for nonlinear dose‐response models with binary outcomes. Applying the theory of Tchebycheff Systems and other algebraic tools, we show that the locally D‐, A‐, and c‐optimal designs for three binary dose‐response models are minimally supported in finite, closed design intervals. The methods to obtain such designs are presented along with examples. The efficiencies of these designs are also discussed. The Canadian Journal of Statistics 46: 336–354; 2018 © 2018 Statistical Society of Canada     

Percentiles of the Product of Uncertainty Factors for Establishing Probabilistic Reference Doses

Exposure guidelines for potentially toxic substances are often based on a reference dose (RfD) that is determined by dividing a no-observed-adverse-effect-level (NOAEL), lowest-observed-adverse-effect-level (LOAEL), or benchmark dose (BD) corresponding to a low level of risk, by a product of uncertainty factors. The uncertainty factors for animal to human extrapolation, variable sensitivities among humans, extrapolation from measured subchronic effects to unknown results for chronic exposures, and extrapolation from a LOAEL to a NOAEL can be thought of as random variables that vary from chemical to chemical. Selected databases are examined that provide distributions across chemicals of inter- and intraspecies effects, ratios of LOAELs to NOAELs, and differences in acute and chronic effects, to illustrate the determination of percentiles for uncertainty factors. The distributions of uncertainty factors tend to be approximately lognormally distributed. The logarithm of the product of independent uncertainty factors is approximately distributed as the sum of normally distributed variables, making it possible to estimate percentiles for the product. Hence, the size of the products of uncertainty factors can be selected to provide adequate safety for a large percentage (e.g., approximately 95%) of RfDs. For the databases used to describe the distributions of uncertainty factors, using values of 10 appear to be reasonable and conservative. For the databases examined the following simple "Rule of 3s" is suggested that exceeds the estimated 95th percentile of the product of uncertainty factors: If only a single uncertainty factor is required use 33, for any two uncertainty factors use 3 x 33 approximately 100, for any three uncertainty factors use a combined factor of 3 x 100 = 300, and if all four uncertainty factors are needed use a total factor of 3 x 300 = 900. If near the 99th percentile is desired use another factor of 3. An additional factor may be needed for inadequate data or a modifying factor for other uncertainties (e.g., different routes of exposure) not covered above.     

Assessing human health response in life cycle assessment using ED10s and DALYs: part 1--Cancer effects.

Life cycle assessment (LCA) is a framework for comparing products according to their total estimated environmental impact, summed over all chemical emissions and activities associated with a product at all stages in its life cycle (from raw material acquisition, manufacturing, use, to final disposal). For each chemical involved, the exposure associated with the mass released into the environment, integrated over time and space, is multiplied by a toxicological measure to estimate the likelihood of effects and their potential consequences. In this article, we explore the use of quantitative methods drawn from conventional single-chemical regulatory risk assessments to create a procedure for the estimation of the cancer effect measure in the impact phase of LCA. The approach is based on the maximum likelihood estimate of the effect dose inducing a 10% response over background, ED10, and default linear low-dose extrapolation using the slope betaED10 (0.1/ED10). The calculated effects may correspond to residual risks below current regulatory compliance requirements that occur over multiple generations and at multiple locations; but at the very least they represent a "using up" of some portion of the human population's ability to accommodate emissions. Preliminary comparisons are performed with existing measures, such as the U.S. Environmental Protection Agency's (U.S. EPA's) slope factor measure q1*. By analyzing bioassay data for 44 chemicals drawn from the EPA's Integrated Risk Information System (IRIS) database, we explore estimating ED10 from more readily available information such as the median tumor dose rate TD50 and the median single lethal dose LD50. Based on the TD50, we then estimate the ED10 for more than 600 chemicals. Differences in potential consequences, or severity, are addressed by combining betaED10 with the measure disability adjusted life years per affected person, DALYp. Most of the variation among chemicals for cancer effects is found to be due to differences in the slope factors (betaED10) ranging from 10(-4) up to 10(4) (risk of cancer/mg/kg-day).     

Tissue Dosimetry for Reactive Metabolites

In recent pharmacokinetically based risk assessments for methylene chloride, Andersen et al. argued that total reactive metabolite (TRM) divided liver weight was the proper measure of dose to target tissue, while the EPA argued that TRM divided by body weight to the two-thirds power was more appropriate. We demonstrate that the proper tissue metric for a reactive metabolite is dependent upon the mode of deactivation: metabolic or spontaneous. It is argued that the most appropriate measure of tissue dosimetry is: (1) TRM divided by the three-fourths power of body weight if the reactive metabolite is metabolically deactivated; or (2) TRM divided by body weight if the reactive metabolite is spontaneously deactivated.