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.     

Evaluating the Risk of Liver Cancer in Humans Exposed to Trichloroethylene Using Physiological Models

Trichloroethylene (TCE) is a widespread environmental pollutant. TCE is classified as a rodent carcinogen by the U.S. Environmental Protection Agency (EPA). Using the rodent cancer bioassay findings and estimates of metabolized dose, the EPA has estimated lifetime exposure cancer risks for humans that ingest TCE in drinking water or inhale TCE. In this study, a physiologically based pharmacokinetic (PB-PK) model for mice was used to simulate selected gavage and inhalation bioassays with TCE. Plausible dose-metrics thought to be linked with the mechanism of action for TCE carcinogenesis were selected. These dose-metrics, adjusted to reflect an average amount per day for a lifetime, were metabolism of TCE (AMET, mg/kg/day) and systemic concentration of TCA (AUCTCA, mg/L/day). These dose-metrics were then used in a linearized multistage model to estimate AMET and AUCTCA values that correspond to liver cancer risks of 1 in 1 million in mice. A human PB-PK model for TCE was then used to predict TCE concentrations in drinking water and air that would provide AMET and AUCTCA values equal to the predicted mice AMET and AUCTCA values that correspond to liver cancer risks of 1 in 1 million. For the dose-metrics, AMET and AUCTCA, the TCE concentrations in air were 10.0 and 0.1 ppb TCE (continuous exposure), respectively, and in water, 7 and 4 μg TCE/L, respectively.     

Estimation of Dietary Exposure to Chemicals: A Case Study Illustrating Methods of Distributional Analyses for Food Consumption Data

There are a number of sources of variability in food consumption patterns and residue levels of a particular chemical (e.g., pesticide, food additive) in commodities that lead to an expected high level of variability in dietary exposures across a population. This paper focuses on examples of consumption pattern survey data for specific commodities, namely that for wine and grape juice, and demonstrates how such data might be analyzed in preparation for performing stochastic analyses of dietary exposure. Data from the NIAAA/NHIS wine consumption survey were subset for gender and age group and, with matched body weight data from the survey database, were used to define empirically-based percentile estimates for wine intake (μl wine/kg body weight) for the strata of interest. The data for these two subpopulations were analyzed to estimate 14-day consumption distributional statistics and distributions for only those days on which wine was consumed. Data subsets for all wine-consuming adults and wine-consuming females ages 18 through 45, were determined to fit a lognormal distribution ( R ²= 0.99 for both datasets). Market share data were incorporated into estimation of chronic exposures to hypothetical chemical residues in imported table wine. As a separate example, treatment of grape juice consumption data for females, ages 18–40, as a simple lognormal distribution resulted in a significant underestimation of intake, and thus exposure, because the actual distribution is a mixture (i.e., multiple subpopulations of grape juice consumers exist in the parent distribution). Thus, deriving dietary intake statistics from food consumption survey data requires careful analysis of the underlying empirical distributions.     

An Exposure Assessment of Methyl Mercury via Fish Consumption for the Japanese Population

The objective of this article was to propose an exposure assessment model to describe the relationship between fish consumption and body methyl mercury (MeHg) levels in the Japanese population. Individual MeHg intake was estimated by the summation of species-specific fish consumption multiplied by species-specific fish MeHg levels. The distribution of fish consumed by individuals and the MeHg level in each fish species were assigned based on published data from Japanese government institutions. The probability of MeHg intake for a population was accomplished through a Monte Carlo simulation by the random sampling of fish consumption and species-specific MeHg levels. Internal body MeHg levels in blood and hair were estimated using a one-compartment model. Overall, the mean value of MeHg intake for the Japanese population was estimated to be 6.76 μg/day or 0.14 μg/kg body weight per day (bw/day), while the mean value for the hair mercury level was 2.02 μg/g. Compared with the survey data that tabulated hair mercury levels in a cross-section of the Japanese population, the simulation results matched the hair mercury survey data very well for women, but somewhat underestimated for men and all of the population. This exposure assessment model is a useful attempt at further risk assessment with respect to a risk-benefit analysis.     

Risk Perception and Human Health Risk in Rural Communities Consuming Unregulated Well Water in Saskatchewan,Canada

Rural communities dependent on unregulated drinking water are potentially at increased health risk from exposure to contaminants. Perception of drinking water safety influences water consumption, exposure, and health risk. A community‐based participatory approach and probabilistic Bayesian methods were applied to integrate risk perception in a holistic human health risk assessment. Tap water arsenic concentrations and risk perception data were collected from two Saskatchewan communities. Drinking water health standards were exceeded in 67% (51/76) of households in Rural Municipality #184 (RM184) and 56% (25/45) in Beardy's and Okemasis First Nation (BOFN). There was no association between the presence of a health exceedance and risk perception. Households in RM184 or with an annual income >$50,000 were most likely to have in‐house water treatment. The probability of consuming tap water perceived as safe (92%) or not safe (0%) suggested that households in RM184 were unlikely to drink water perceived as not safe. The probability of drinking tap water perceived as safe (77%) or as not safe (11%) suggested households in BOFN contradicted their perception and consumed water perceived as unsafe. Integration of risk perception lowered the adult incremental lifetime cancer risk by 3% to 1.3 × 10^?5 (95% CI 8.4 × 10^?8 to 9.0 × 10^?5) for RM184 and by 8.9 × 10^?6 (95% CI 2.2 × 10^?7 to 5.9 × 10^?5) for BOFN. Probability of exposure to arsenic concentrations >1:100,000, negligible cancer risk, was 23% for RM184 and 22% for BOFN.     

Treating and Drinking Well Water in the Presence of Health Risks from Arsenic Contamination: Results from a U.S. Hot Spot

The Safe Drinking Water Act of 1974 regulates water quality in public drinking water supply systems but does not pertain to private domestic wells, often found in rural areas throughout the country. The recent decision to tighten the drinking water standard for arsenic from 50 parts per billion (ppb) to 10 ppb may therefore affect some households in rural communities, but may not directly reduce health risks for those on private wells. The article reports results from a survey conducted in a U.S. arsenic hot spot, the rural area of Churchill County, Nevada. This area has elevated levels of arsenic in groundwater. We find that a significant proportion of households on private wells are consuming drinking water with arsenic levels that pose a health risk. The decision to treat tap water for those on private wells in this area is modeled, and the predicted probability of treatment is used to help explain drinking water consumption. This probability represents behaviors relating to the household's perception of risk.     

A Monte Carlo Risk Assessment Model for Acrylamide Formation in French Fries

The objective of this study is to estimate the likely human exposure to the group 2a carcinogen, acrylamide, from French fries by Irish consumers by developing a quantitative risk assessment model using Monte Carlo simulation techniques. Various stages in the French-fry-making process were modeled from initial potato harvest, storage, and processing procedures. The model was developed in Microsoft Excel with the @Risk add-on package. The model was run for 10,000 iterations using Latin hypercube sampling. The simulated mean acrylamide level in French fries was calculated to be 317 μg/kg. It was found that females are exposed to smaller levels of acrylamide than males (mean exposure of 0.20 μg/kg bw/day and 0.27 μg/kg bw/day, respectively). Although the carcinogenic potency of acrylamide is not well known, the simulated probability of exceeding the average chronic human dietary intake of 1 μg/kg bw/day (as suggested by WHO) was 0.054 and 0.029 for males and females, respectively. A sensitivity analysis highlighted the importance of the selection of appropriate cultivars with known low reducing sugar levels for French fry production. Strict control of cooking conditions (correlation coefficient of 0.42 and 0.35 for frying time and temperature, respectively) and blanching procedures (correlation coefficient −0.25) were also found to be important in ensuring minimal acrylamide formation.     

Cancer Dose-Response Modeling of Epidemiological Data on Worker Exposures to Aldrin and Dieldrin

The paper applies classical statistical principles to yield new tools for risk assessment and makes new use of epidemiological data for human risk assessment. An extensive clinical and epidemiological study of workers engaged in the manufacturing and formulation of aldrin and dieldrin provides occupational hygiene and biological monitoring data on individual exposures over the years of employment and provides unusually accurate measures of individual lifetime average daily doses. In the cancer dose-response modeling, each worker is treated as a separate experimental unit with his own unique dose. Maximum likelihood estimates of added cancer risk are calculated for multistage, multistage-Weibull, and proportional hazards models. Distributional characterizations of added cancer risk are based on bootstrap and relative likelihood techniques. The cancer mortality data on these male workers suggest that low-dose exposures to aldrin and dieldrin do not significantly increase human cancer risk and may even decrease the human hazard rate for all types of cancer combined at low doses (e.g., 1 g/kg/day). The apparent hormetic effect in the best fitting dose-response models for this data set is statistically significant. The decrease in cancer risk at low doses of aldrin and dieldrin is in sharp contrast to the U.S. Environmental Protection Agency's upper bound on cancer potency based on mouse liver tumors. The EPA's upper bound implies that lifetime average daily doses of 0.0000625 and 0.00625 g/kg body weight/day would correspond to increased cancer risks of 0.000001 and 0.0001, respectively. However, the best estimate from the Pernis epidemiological data is that there is no increase in cancer risk in these workers at these doses or even at doses as large as 2 g/kg/day.     

Bounding Analysis of Drinking Water Health Risks from a Spill of Hydraulic Fracturing Flowback Water

A bounding risk assessment is presented that evaluates possible human health risk from a hypothetical scenario involving a 10,000‐gallon release of flowback water from horizontal fracturing of Marcellus Shale. The water is assumed to be spilled on the ground, infiltrates into groundwater that is a source of drinking water, and an adult and child located downgradient drink the groundwater. Key uncertainties in estimating risk are given explicit quantitative treatment using Monte Carlo analysis. Chemicals that contribute significantly to estimated health risks are identified, as are key uncertainties and variables to which risk estimates are sensitive. The results show that hypothetical exposure via drinking water impacted by chemicals in Marcellus Shale flowback water, assumed to be spilled onto the ground surface, results in predicted bounds between 10⁻¹⁰ and 10⁻⁶ (for both adult and child receptors) for excess lifetime cancer risk. Cumulative hazard indices (HI_CUMULATIVE) resulting from these hypothetical exposures have predicted bounds (5th to 95th percentile) between 0.02 and 35 for assumed adult receptors and 0.1 and 146 for assumed child receptors. Predicted health risks are dominated by noncancer endpoints related to ingestion of barium and lithium in impacted groundwater. Hazard indices above unity are largely related to exposure to lithium. Salinity taste thresholds are likely to be exceeded before drinking water exposures result in adverse health effects. The findings provide focus for policy discussions concerning flowback water risk management. They also indicate ways to improve the ability to estimate health risks from drinking water impacted by a flowback water spill (i.e., reducing uncertainty).     

Risk Characterization of Methyl tertiary Butyl Ether (MTBE) in Tap Water

Methyl tertiary butyl ether (MTBE) can enter surface water and groundwater through wet atmospheric deposition or as a result of fuel leaks and spills. About 30% of the U.S. population lives in areas where MTBE is in regular use. Ninety-five percent of this population is unlikely to be exposed to MTBE in tap water at concentrations exceeding 2 ppb, and most will be exposed to concentrations that are much lower and may be zero. About 5% of this population may be exposed to higher levels of MTBE in tap water, resulting from fuel tank leaks and spills into surface or groundwater used for potable water supplies. This paper describes the concentration ranges found and anticipated in surface and groundwater, and estimates the distribution of doses experienced by humans using water containing MTBE to drink, prepare food, and shower/bathe. The toxic properties (including potency) of MTBE when ingested, inhaled, and in contact with the skin are summarized. Using a range of human toxic potency values derived from animal studies, margins of exposure (MOE) associated with alternative chronic exposure scenarios are estimated to range from 1700 to 140,000. Maximum concentrations of MTBE in tap water anticipated not to cause adverse health effects are determined to range from 700 to 14,000 ppb. The results of this analysis demonstrate that no health risks are likely to be associated with chronic and subchronic human exposures to MTBE in tap water. Although some individuals may be exposed to very high concentrations of MTBE in tap water immediately following a localized spill, these exposures are likely to be brief in duration due to large-scale dilution and rapid volatilization of MTBE, the institution of emergency response and remediation measures to minimize human exposures, and the low taste and odor thresholds of MTBE which ensure that its presence in tap water is readily detected at concentrations well below the threshold for human injury.     

Dietary and Inhalation Intake of Lead and Estimation of Blood Lead Levels in Adults and Children in Kanpur, India

This research was initiated to study lead levels in various food items in the city of Kanpur, India, to assess the dietary intake of lead and to estimate blood lead (PbB) levels, a biomarker of lead toxicity. For this purpose, sampling of food products, laboratory analysis, and computational exercises were undertaken. Specifically, six food groups (leafy vegetables, nonleafy vegetables, fruits, pulses, cereals, and milk), drinking water, and lead air concentration were considered for estimating lead intake. Results indicated highest lead content in leafy vegetables followed by pulses. Fruits showed low lead content and drinking water lead levels were always within tolerable limits. It was estimated that average daily lead intake through diet was about 114 microg/day for adults and 50 microg/day in children; tolerable limit is 250 microg/day for adults and 90 microg/day for children. The estimated lead intakes were translated into the resultant PbB concentrations for children and adults using a physiologically-based pharmacokinetic (PBPK) model. Monte Carlo simulation of PbB level variations for adults showed that probability of exceeding the tolerable limit of PbB (i.e.,10 microg/dL) was 0.062 for the pre-unleaded and 0.000328 for the post-unleaded gasoline period. The probability of exceeding tolerable limits in PbB level was reduced by a factor of 189 in the post-unleaded scenario. The study also suggested that in spite of the introduction of unleaded gasoline, children continue to be at a high risk (probability of exceeding 10 microg/dL = 0.39) because of a high intake of lead per unit body weight.     

The Risk of MTBE Relative to Other VOCs in Public Drinking Water in California

Ongoing publicity about methyl tertiary butyl ether (MTBE) suggests that this chemical is of greater concern than other contaminants commonly found in drinking water. The purpose of this article is to evaluate the available MTBE data in context with other volatile organic compounds (VOCs) that are detected in public drinking water sources in California. We find that of the 28 VOCs with a primary maximum contaminant level (MCL) in California, 21 were found in 50 or more drinking water sources from 1985 to 2002. Over the last 10 years, the most frequently detected VOCs were chloroform, tetrachloroethylene (PCE), and trichloroethylene (TCE), which were found in about 9-15% of all sampled drinking water sources. These same chemicals were found to have the highest mean detected concentrations over the last 5 years, ranging from 13 to 15 microg/L. Many VOCs were also found to routinely exceed state and federal drinking water standards, including benzene and carbon tetrachloride. By comparison, MTBE was found in approximately 1% of sampled drinking water sources for most years, and of those drinking water sources found to contain MTBE from 1998 to 2002, over 90% had detected concentrations below California's primary MCL of 13 microg/L. Relative to the other VOCs evaluated, MTBE has the lowest estimated California cancer potency value, and was found to pose one of the least cancer risks from household exposures to contaminated drinking water. These findings suggest that MTBE poses an insignificant threat to public drinking water supplies and public health in California, particularly when compared to other common drinking water contaminants.     

Development of a Screening Approach to Interpret Human Biomonitoring Data on Volatile Organic Compounds: Reverse Dosimetry on Biomonitoring Data for Trichloroethylene

A screening approach is developed for volatile organic compounds (VOCs) to estimate exposures that correspond to levels measured in fluids and/or tissues in human biomonitoring studies. The approach makes use of a generic physiologically-based pharmacokinetic (PBPK) model coupled with exposure pattern characterization, Monte Carlo analysis, and quantitative structure property relationships (QSPRs). QSPRs are used for VOCs with minimal data to develop chemical-specific parameters needed for the PBPK model. The PBPK model is capable of simulating VOC kinetics following multiple routes of exposure, such as oral exposure via water ingestion and inhalation exposure during shower events. Using published human biomonitoring data of trichloroethylene (TCE), the generic model is evaluated to determine how well it estimates TCE concentrations in blood based on the known drinking water concentrations. In addition, Monte Carlo analysis is conducted to characterize the impact of the following factors: (1) uncertainties in the QSPR-estimated chemical-specific parameters; (2) variability in physiological parameters; and (3) variability in exposure patterns. The results indicate that uncertainty in chemical-specific parameters makes only a minor contribution to the overall variability and uncertainty in the predicted TCE concentrations in blood. The model is used in a reverse dosimetry approach to derive estimates of TCE concentrations in drinking water based on given measurements of TCE in blood, for comparison to the U.S. EPA's Maximum Contaminant Level in drinking water. This example demonstrates how a reverse dosimetry approach can be used to facilitate interpretation of human biomonitoring data in a health risk context by deriving external exposures that are consistent with a biomonitoring data set, thereby permitting comparison with health-based exposure guidelines.     

Estimated Rate of Fatal Automobile Accidents Attributable to Acute Solvent Exposure at Low Inhaled Concentrations

Acute solvent exposures may contribute to automobile accidents because they increase reaction time and decrease attention, in addition to impairing other behaviors. These effects resemble those of ethanol consumption, both with respect to behavioral effects and neurological mechanisms. These observations, along with the extensive data on the relationship between ethanol consumption and fatal automobile accidents, suggested a way to estimate the probability of fatal automobile accidents from solvent inhalation. The problem can be approached using the logic of the algebraic transitive postulate of equality: if A=B and B=C, then A=C. We first calculated a function describing the internal doses of solvent vapors that cause the same magnitude of behavioral impairment as ingestion of ethanol (A=B). Next, we fit a function to data from the literature describing the probability of fatal car crashes for a given internal dose of ethanol (B=C). Finally, we used these two functions to generate a third function to estimate the probability of a fatal car crash for any internal dose of organic solvent vapor (A=C). This latter function showed quantitatively (1) that the likelihood of a fatal car crash is increased by acute exposure to organic solvent vapors at concentrations less than 1.0 ppm, and (2) that this likelihood is similar in magnitude to the probability of developing leukemia from exposure to benzene. This approach could also be applied to other potentially adverse consequences of acute exposure to solvents (e.g., nonfatal car crashes, property damage, and workplace accidents), if appropriate data were available.     

Evaluation of the Uncertainty in an Oral Reference Dose for Methylmercury Due to Interindividual Variability in Pharmacokinetics

An analysis of the uncertainty in guidelines for the ingestion of methylmercury (MeHg) due to human pharmacokinetic variability was conducted using a physiologically based pharmacokinetic (PBPK) model that describes MeHg kinetics in the pregnant human and fetus. Two alternative derivations of an ingestion guideline for MeHg were considered: the U.S. Environmental Protection Agency reference dose (RfD) of 0.1 g/kg/day derived from studies of an Iraqi grain poisoning episode, and the Agency for Toxic Substances and Disease Registry chronic oral minimal risk level (MRL) of 0.5 g/kg/day based on studies of a fish-eating population in the Seychelles Islands. Calculation of an ingestion guideline for MeHg from either of these epidemiological studies requires calculation of a dose conversion factor (DCF) relating a hair mercury concentration to a chronic MeHg ingestion rate. To evaluate the uncertainty in this DCF across the population of U.S. women of child-bearing age, Monte Carlo analyses were performed in which distributions for each of the parameters in the PBPK model were randomly sampled 1000 times. The 1st and 5th percentiles of the resulting distribution of DCFs were a factor of 1.8 and 1.5 below the median, respectively. This estimate of variability is consistent with, but somewhat less than, previous analyses performed with empirical, one-compartment pharmacokinetic models. The use of a consistent factor in both guidelines of 1.5 for pharmacokinetic variability in the DCF, and keeping all other aspects of the derivations unchanged, would result in an RfD of 0.2 g/kg/day and an MRL of 0.3 g/kg/day.     

Quantitative Links Between Arsenic Exposure and Influenza A (H1N1) Infection‐Associated Lung Function Exacerbations Risk

The objective of this study was to link arsenic exposure and influenza A (H1N1) infection‐induced respiratory effects to assess the impact of arsenic‐contaminated drinking water on exacerbation risk of A (H1N1)‐associated lung function. The homogeneous Poisson process was used to approximate the related processes between arsenic exposure and influenza‐associated lung function exacerbation risk. We found that (i) estimated arsenic‐induced forced expiratory volume in 1 second (FEV₁) reducing rates ranged from 0.116 to 0.179 mL/μg for age 15–85 years, (ii) estimated arsenic‐induced A (H1N1) viral load increasing rate was 0.5 mL/μg, (iii) estimated A (H1N1) virus‐induced FEV₁ reducing rate was 0.10 mL/logTCID50, and (iv) the relationship between arsenic exposure and A (H1N1)‐associated respiratory symptoms scores (RSS) can be described by a Hill model. Here we showed that maximum RSS at day 2 postinfection for Taiwan, West Bengal (India), and the United States were estimated to be in the severe range of 0.83, 0.89, and 0.81, respectively, indicating that chronic arsenic exposure and A (H1N1) infection together are most likely to pose potential exacerbations risk of lung function, although a 50% probability of lung function exacerbations risk induced by arsenic and influenza infection was within the mild and moderate ranges of RSS at day 1 and 2 postinfection. We concluded that avoidance of drinking arsenic‐containing water could significantly reduce influenza respiratory illness and that need will become increasingly urgent as the novel H1N1 pandemic influenza virus infects people worldwide.     

Cancer Risk Estimation for Mixtures of Coal Tars

Two-year chronic bioassays were conducted by using B6C3F1 female mice fed several concentrations of two different mixtures of coal tars from manufactured gas waste sites or benzo(a)pyrene (BaP). The purpose of the study was to obtain estimates of cancer potency of coal tar mixtures, by using conventional regulatory methods, for use in manufactured gas waste site remediation. A secondary purpose was to investigate the validity of using the concentration of a single potent carcinogen, in this case benzo(a)pyrene, to estimate the relative risk for a coal tar mixture. The study has shown that BaP dominates the cancer risk when its concentration is greater than 6,300 ppm in the coal tar mixture. In this case the most sensitive tissue site is the forestomach. Using low-dose linear extrapolation, the lifetime cancer risk for humans is estimated to be: Risk < 1.03 × 10⁻⁴ (ppm coal tar in total diet) + 240 × 10⁻⁴ (ppm BaP in total diet), based on forestomach tumors. If the BaP concentration in the coal tar mixture is less than 6,300 ppm, the more likely case, then lung tumors provide the largest estimated upper limit of risk, Risk < 2.55 × 10⁻⁴ (ppm coal tar in total diet), with no contribution of BaP to lung tumors. The upper limit of the cancer potency (slope factor) for lifetime oral exposure to benzo(a)pyrene is 1.2 × 10⁻³ per μg per kg body weight per day from this Good Laboratory Practice (GLP) study compared with the current value of 7.3 × 10⁻³ per μg per kg body weight per day listed in the U.S. EPA Integrated Risk Information System.     

Drinking Water as a Proportion of Total Human Exposure to Volatile N‐Nitrosamines

Some volatile N‐nitrosamines, primarily N‐nitrosodimethylamine (NDMA), are recognized as products of drinking water treatment at ng/L levels and as known carcinogens. The U.S. EPA has identified the N‐nitrosamines as contaminants being considered for regulation as a group under the Safe Drinking Water Act. Nitrosamines are common dietary components, and a major database (over 18,000 drinking water samples) has recently been created under the Unregulated Contaminant Monitoring Rule. A Monte Carlo modeling analysis in 2007 found that drinking water contributed less than 2.8% of ingested NDMA and less than 0.02% of total NDMA exposure when estimated endogenous formation was considered. Our analysis, based upon human blood concentrations, indicates that endogenous NDMA production is larger than expected. The blood‐based estimates are within the range that would be calculated from estimates based on daily urinary NDMA excretion and an estimate based on methylated guanine in DNA of lymphocytes from human volunteers. Our analysis of ingested NDMA from food and water based on Monte Carlo modeling with more complete data input shows that drinking water contributes a mean proportion of the lifetime average daily NDMA dose ranging from between 0.0002% and 0.001% for surface water systems using free chlorine or between 0.001% and 0.01% for surface water systems using chloramines. The proportions of average daily dose are higher for infants (zero to six months) than other age cohorts, with the highest mean up to 0.09% (upper 95th percentile of 0.3%).     

Predictive Bayesian Microbial Dose-Response Assessment Based on Suggested Self-Organization in Primary Illness Response: Cryptosporidium parvum

The probability of illness caused by very low doses of pathogens cannot generally be tested due to the numbers of subjects that would be needed, though such assessments of illness dose response are needed to evaluate drinking water standards. A predictive Bayesian dose-response assessment method was proposed previously to assess the unconditional probability of illness from available information and avoid the inconsistencies of confidence-based approaches. However, the method uses knowledge of the conditional dose-response form, and this form is not well established for the illness endpoint. A conditional parametric dose-response function for gastroenteric illness is proposed here based on simple numerical models of self-organized host-pathogen systems and probabilistic arguments. In the models, illnesses terminate when the host evolves by processes of natural selection to a self-organized critical value of wellness. A generalized beta-Poisson illness dose-response form emerges for the population as a whole. Use of this form is demonstrated in a predictive Bayesian dose-response assessment for cryptosporidiosis. Results suggest that a maximum allowable dose of 5.0 x 10(-7) oocysts/exposure (e.g., 2.5 x 10(-7) oocysts/L water) would correspond with the original goals of the U.S. Environmental Protection Agency Surface Water Treatment Rule, considering only primary illnesses resulting from Poisson-distributed pathogen counts. This estimate should be revised to account for non-Poisson distributions of Cryptosporidium parvum in drinking water and total response, considering secondary illness propagation in the population.     

Use of Markov Chain Monte Carlo Analysis with a Physiologically-Based Pharmacokinetic Model of Methylmercury to Estimate Exposures in U.S. Women of Childbearing Age

A Bayesian approach, implemented using Markov Chain Monte Carlo (MCMC) analysis, was applied with a physiologically‐based pharmacokinetic (PBPK) model of methylmercury (MeHg) to evaluate the variability of MeHg exposure in women of childbearing age in the U.S. population. The analysis made use of the newly available National Health and Nutrition Survey (NHANES) blood and hair mercury concentration data for women of age 16–49 years (sample size, 1,582). Bayesian analysis was performed to estimate the population variability in MeHg exposure (daily ingestion rate) implied by the variation in blood and hair concentrations of mercury in the NHANES database. The measured variability in the NHANES blood and hair data represents the result of a process that includes interindividual variation in exposure to MeHg and interindividual variation in the pharmacokinetics (distribution, clearance) of MeHg. The PBPK model includes a number of pharmacokinetic parameters (e.g., tissue volumes, partition coefficients, rate constants for metabolism and elimination) that can vary from individual to individual within the subpopulation of interest. Using MCMC analysis, it was possible to combine prior distributions of the PBPK model parameters with the NHANES blood and hair data, as well as with kinetic data from controlled human exposures to MeHg, to derive posterior distributions that refine the estimates of both the population exposure distribution and the pharmacokinetic parameters. In general, based on the populations surveyed by NHANES, the results of the MCMC analysis indicate that a small fraction, less than 1%, of the U.S. population of women of childbearing age may have mercury exposures greater than the EPA RfD for MeHg of 0.1 μg/kgg/day, and that there are few, if any, exposures greater than the ATSDR MRL of 0.3 μgg/kgg/day. The analysis also indicates that typical exposures may be greater than previously estimated from food consumption surveys, but that the variability in exposure within the population of U.S. women of childbearing age may be less than previously assumed.