Gary L Diamond

URINARY CADMIUM ELIMINATION AS A BIOMARKER OF EXPOSURE FOR EVALUATING A CADMIUM DIETARY EXPOSURE - BIOKINETICS MODEL

The Cadmium Dietary Exposure Model (CDEM) utilizes national survey data on food cadmium concentrations and food consumption patterns to estimate dietary intakes in the U.S. population. The CDEM has been linked to a modification of the cadmium biokinetic model of Kjellström and Nordberg (KNM) to derive predictions of kidney and urinary cadmium that reflect U.S. dietary cadmium intake and related variability. Variability in dietary cadmium intake was propagated through the KNM using a Monte Carlo approach. The model predicts a mean peak kidney cadmium burden of approximately 3.5 mg and a 5th-95th percentile range of 2.2-5.1 mg in males. The corresponding peak renal cortex cadmium concentration in males is 15 µg/g wet cortex (10-22, 5th-95th percentile). Predicted kidney cadmium levels in females were higher than males: 5.1 (3.3-7.6) mg total kidney, 29 (19-43) µg/g wet cortex. Predicted urinary cadmium in males and females agreed with empirical estimates based on the NHANES III, with females predicted and observed to excrete approximately twice the amount of cadmium in urine than males. An explanation for the higher urinary cadmium excretion in females is proposed that is consistent with the NHANES III data as well as experimental studies in humans and animals. Females may absorb a larger fraction of ingested dietary cadmium than males, and this difference may be the result of lower iron body stores in females compared to males. This would suggest that females may be at greater risk of developing cadmium toxicity than males. The predicted 5th-95th percentile values for peak kidney cadmium burden are approximately 60% of the peak kidney burden (8-11 mg) predicted for a chronic intake at the U.S. Environmental Protection Agency (EPA) chronic reference dose of 1 µg/kg-d.

Pharmacokinetics/pharmacodynamics (PK/PD) modeling of risks of kidney toxicity from exposure to cadmium: estimates of dietary risks in the U.S. population.

An analysis of epidemiological studies of associations between exposure to cadmium and kidney toxicity was conducted. Dose-response functions relating low-molecular-weight (LMW) proteinuria to various indices of cadmium dose (dietary cadmium intake, urinary cadmium excretion, or tissue cadmium burden) were obtained from 15 studies of diverse exposures (occupational, general environmental, environmental contamination). Estimates of the dose corresponding to probabilities of LMW proteinuria of 0.1, 0.15, or 0.2 were transformed from the reported dose units into corresponding estimates of target organ dose (μg Cd/g renal cortex, RC) by simulation using a pharmacokinetics (PK) model. The median RC associated with a 0.1 probability(RC10M) of LMW proteinuria was predicted to be 153 μg Cd/g cortex (95% confidence interval [Cl]: 84–263). The lower confidence limit on the RC10M (RC10L 84 μg/g cortex) was predicted to be attained with a constant chronic intake of 1 μg/kg/d in females or 2.2 μg/kg/d in males. The RC10L was 2.5–5 times higher than the median RCs predicted to result from dietary cadmium intake in U.S. nonsmokers (μg Cd/g cortex: 33, females; 17, males)and 1.6–3 times higher than the corresponding 95th percentile RCs (53, females; 27, males). Additional exposure from smoking cigarettes (approximately 20 cigsrettes/d, 3 μg Cd inhaled/d) was predicted to increase the median RC (μg/g cortex) by approximately 45–70% (48, females; 29, males); however, predicted 95th percentile RCs for smokers (66, females; 38, males) were lower than the RC1OL. These results indicate that, for most of the U.S. population, dietary-derived risks are likely to be negligible, in the absence of exposures from other sources.

Gastrointestinal Absorption of Metals

Estimating gastrointestinal absorption remains a significant challenge in the risk assessment of metals. This presentation reviews our current understanding of the gastrointestinal absorption of lead (Pb) to illustrate physiological mechanisms involved in metal absorption, new approaches that are being applied to the problem of estimating metal absorption in humans, and issues related to integrating this information into risk assessment. Absorption of metals can be highly variable in human populations because it is influenced by a variety of factors that include the chemical form of the metal, environmental matrix in which the ingested metal is contained, gastrointestinal tract contents, diet, nutritional status, age, and, in some cases, genotype. Thus, in risk assessment models, gastrointestinal absorption is best described as a variable whose distribution is determined in part by the above multiple influences. Although we cannot expect to evaluate empirically each of the above factors in human populations, we can expect to achieve a sufficiently detailed understanding of absorption mechanisms to develop conceptual and, eventually, quantitative models of absorption that account for some aspects of individual variability. A conceptual model is presented of the physiological processes involved in the transfer of ingested metals from the lumen of the gastrointestinal tract to the blood circulation. Components of the model include delivery to the site(s) of absorption; distribution among intracellular and extracellular ligands and transcellular and paracellular pathways of transfer across the gastrointestinal tract epithelium. The gastrointestinal absorption of Pb is discussed in the context of this model.

Lead Intervention and Pediatric Blood Lead Levels at Hazardous Waste Sites

Lead intervention at Superfund sites typically seeks to reduce pediatric blood lead levels by disrupting the surface-to-hand-to-mouth pathway. This article presents the results of a survey of the publicly available literature on the effectiveness of lead intervention on pediatric blood lead levels at hazardous waste sites. The survey includes six hazardous waste sites located in Canada, Australia, and the United States at which intervention activities were conducted and pediatric blood lead levels were sampled both pre- and postintervention. Evaluation of the effectiveness of intervention on pediatric blood lead levels is often complicated due to con-founding variables and statistical limitations. Nevertheless, the outcomes of the intervention studies reviewed in this report suggest that various approaches to the intervention of the dust ingestion pathway, alone or in combination, contributed to declines in blood lead levels in children living in areas heavily contaminated with lead.

Application of geostatistics to risk assessment

Geostatistics offers two fundamental contributions to environmental contaminant exposure assessment: (1) a group of methods to quantitatively describe the spatial distribution of a pollutant and (2) the ability to improve estimates of the exposure point concentration by exploiting the geospatial information present in the data. The second contribution is particularly valuable when exposure estimates must be derived from small data sets, which is often the case in environmental risk assessment. This article addresses two topics related to the use of geostatistics in human and ecological risk assessments performed at hazardous waste sites: (1) the importance of assessing model assumptions when using geostatistics and (2) the use of geostatistics to improve estimates of the exposure point concentration (EPC) in the limited data scenario. The latter topic is approached here by comparing design-based estimators that are familiar to environmental risk assessors (e.g., Lands method) with geostatistics, a model-based estimator. In this report, we summarize the basics of spatial weighting of sample data, kriging, and geostatistical simulation. We then explore the two topics identified above in a case study, using soil lead concentration data from a Superfund site (a skeet and trap range). We also describe several areas where research is needed to advance the use of geostatistics in environmental risk assessment.

Monte Carlo modeling of childhood lead exposure: Development of a probabilistic methodology for use with the Usepa Ieubk model for lead in children

Abstract An integrated stochastic exposure (ISE) model using microexposure techniques was developed to characterize short‐term variability and uncertainty in residential childhood lead exposure at the census tract level. The ISE model was linked to the biokinetic module of the United States Environmental Protection Agency (USEPA) IEUBK Model for Lead in Children (v. .99D) to predict the distribution of blood lead concentrations (PbB). We demonstrate an application of the ISE model using probability distributions to characterize variability and uncertainty in age‐specific physiology and activity patterns, demographics and housing conditions, concentrations of lead in multiple environmental media, and media‐specific uptake rates. Output from the ISE/IEUBK model was compared with output from the IEUBK Model using central tendency point estimates for exposure variables and an assumed geometric standard deviation (GSD). Results of sensitivity analyses suggest that key exposure variables include percent lead in...

Application of a Probabilistic Risk Assessment Methodology to a Lead Smelter Site

Exposure of children to lead in the environment was assessed at the Murray Smelter Superfund site using both a deterministic risk assessment approach, the Integrated Exposure Uptake Biokinetic (IEUBK) model, and a probabilistic approach, the Integrated Stochastic Exposure (ISE) model. When site-specific data on lead in environmental media were input as point estimates into the IEUBK model, unacceptable risks were predicted for children living within five of eight study zones. The predicted soil cleanup goal was 550 ppm. Concentration and exposure data were then input into the ISE model as probability distribution functions and a one-dimensional Monte Carlo analysis (ID MCA) was run to predict the expected distribution of exposures and blood lead values. Uncertainty surrounding these predictions was examined in a two-dimensional Monte Carlo analysis (2-D MCA). The ISE model predicted risks that were in the same rank order as those predicted by the IEUBK model, although the probability estimates of exceedin...

Issues Related to Time Averaging of Exposure in Modeling Risks Associated with Intermittent Exposures to Lead

Typical exposures to lead often involve a mix of long-term exposures to relatively constant exposure levels (e.g., residential yard soil and indoor dust) and highly intermittent exposures at other locations (e.g., seasonal recreational visits to a park). These types of exposures can be expected to result in blood lead concentrations that vary on a temporal scale with the intermittent exposure pattern. Prediction of short-term (or seasonal) blood lead concentrations arising from highly variable intermittent exposures requires a model that can reliably simulate lead exposures and biokinetics on a temporal scale that matches that of the exposure events of interest. If exposure model averaging times (EMATs) of the model exceed the shortest exposure duration that characterizes the intermittent exposure, uncertainties will be introduced into risk estimates because the exposure concentration used as input to the model must be time averaged to account for the intermittent nature of the exposure. We have used simulation as a means of determining the potential magnitude of these uncertainties. Simulations using models having various EMATs have allowed exploration of the strengths and weaknesses of various approaches to time averaging of exposures and impact on risk estimates associated with intermittent exposures to lead in soil. The International Commission of Radiological Protection (ICRP) model of lead pharmacokinetics in humans simulates lead intakes that can vary in intensity over time spans as small as one day, allowing for the simulation of intermittent exposures to lead as a series of discrete daily exposure events. The ICRP model was used to compare the outcomes (blood lead concentration) of various time-averaging adjustments for approximating the time-averaged intake of lead associated with various intermittent exposure patterns. Results of these analyses suggest that standard approaches to time averaging (e.g., U.S. EPA) that estimate the long-term daily exposure concentration can, in some cases, result in substantial underprediction of short-term variations in blood lead concentrations when used in models that operate with EMATs exceeding the shortest exposure duration that characterizes the intermittent exposure. Alternative time-averaging approaches recommended for use in lead risk assessment more reliably predict short-term periodic (e.g., seasonal) elevations in blood lead concentration that might result from intermittent exposures. In general, risk estimates will be improved by simulation on shorter time scales that more closely approximate the actual temporal dynamics of the exposure.

Application of PBPK model for 2,4-D to estimates of risk in backpack applicators

A PBPK model for 2,4-D was developed that involves flow-limited pH trapping modified to consider tissue binding, binding to plasma, and high-dose inhibition of urinary excretion. The PBPK model provides reasonable estimates of the kinetics of 2,4-D in rats as well as in humans, providing a common metric for expressing risk. The risk characterization for 2,4-D based on the PBPK model is consistent with that based on standard risk assessment methods, except that the apparent variability in the risk characterization is reduced. The model demonstrates that non-linear pharmacokinetics and inhibition of urinary excretion would not be expected in occupational exposures. This case study suggests that preliminary PBPK models could be developed for numerous pesticides based on commonly available data. If properly validated with well-designed worker exposure studies, such models may be useful in more complete assessments of risks to workers as well as members of the general public.

Assessing Lead Risks at Non-Residential Hazardous Waste Sites

ABSTRACT In 1996, the U.S. Environmental Protection Agency (USEPA) developed the Adult Lead Methodology (ALM) to provide an interim approach to assessing risks from non-residential exposures to lead. Because such exposures often involve occupational activities of adults, the ALM was directed at assessing soil-related lead risks to adults. Consistent with other approaches used in Superfund risk assessment, the ALM was designed to predict quasi-steady state blood lead concentrations (PbB) that might result from soil exposure. These predictions are converted to a risk estimate, expressed as the probability of exceeding a PbB level of concern. To examine the assumptions and variables in the ALM that have become available since 1996, a comparison was made of the attributes of seven alternative research models for which adequate documentation is available to understand and implement each approach. Several of these models have been used in regulatory decision-making; however, the USEPA has officially embraced none for general use. This analysis suggests that the ALM can continue to serve as a reasonable tool for assessing risks associated with non-residential exposures to soil. Under certain circumstances other models may be more applicable (i.e., for assessing acute or intensive exposures); however, the ALM is recommended for the majority of risk assessment applications.