Human Interindividual Variability in Parameters Related to Health Risks

This paper reviews existing data on the variability in parameters relevant for health risk analyses. We cover both exposure-related parameters and parameters related to individual susceptibility to toxicity. The toxicity/susceptibility data base under construction is part of a longer term research effort to lay the groundwork for quantitative distributional analyses of non-cancer toxic risks. These data are broken down into a variety of parameter types that encompass different portions of the pathway from external exposure to the production of biological responses. The discrete steps in this pathway, as we now conceive them, are:Contact Rate (Breathing rates per body weight; fish consumption per body weight)Uptake or Absorption as a Fraction of Intake or Contact RateGeneral Systemic Availability Net of First Pass Elimination and Dilution via Distribution Volume (e.g., initial blood concentration per mg/kg of uptake)Systemic Elimination (half life or clearance)Active Site Concentration per Systemic Blood or Plasma ConcentrationPhysiological Parameter Change per Active Site Concentration (expressed as the dose required to make a given percentage change in different people, or the dose required to achieve some proportion of an individual's maximum response to the drug or toxicant)Functional Reserve Capacity–Change in Baseline Physiological Parameter Needed to Produce a Biological Response or Pass a Criterion of Abnormal FunctionComparison of the amounts of variability observed for the different parameter types suggests that appreciable variability is associated with the final step in the process–differences among people in functional reserve capacity. This has the implication that relevant information for estimating effective toxic susceptibility distributions may be gleaned by direct studies of the population distributions of key physiological parameters in people that are not exposed to the environmental and occupational toxicants that are thought to perturb those parameters. This is illustrated with some recent observations of the population distributions of Low Density Lipoprotein Cholesterol from the second and third National Health and Nutrition Examination Surveys.     

Using Average Lifetime Dose Rate for Intermittent Exposures to Carcinogens

The effect of using the average dose rate over a lifetime as a representative measure of exposure to carcinogens is investigated by comparing the true theoretical multistage intermittent-dosing lifetime low-dose excess risk to the theoretical multistage continuous-dosing lifetime risk corresponding to the average lifetime dose rate. It is concluded that low-dose risk estimates based on the average lifetime dose rate may overestimate the true risk by several orders of magnitude, but that they never underestimate the true risk by more than a factor of k/r, where k is the total number of stages in the multistage model and r is the number of stages that are dose-related.     

Comparative Risks of Cancer from Drywall Finishing Based on Stochastic Modeling of Cumulative Exposures to Respirable Dusts and Chrysotile Asbestos Fibers

Sanding joint compounds is a dusty activity and exposures are not well characterized. Until the mid 1970s, asbestos‐containing joint compounds were used by some people such that sanding could emit dust and asbestos fibers. We estimated the distribution of 8‐h TWA concentrations and cumulative exposures to respirable dusts and chrysotile asbestos fibers for four worker groups: (1) drywall specialists, (2) generalists, (3) tradespersons who are bystanders to drywall finishing, and (4) do‐it‐yourselfers (DIYers). Data collected through a survey of experienced contractors, direct field observations, and literature were used to develop prototypical exposure scenarios for each worker group. To these exposure scenarios, we applied a previously developed semi‐empirical mathematical model that predicts area as well as personal breathing zone respirable dust concentrations. An empirical factor was used to estimate chrysotile fiber concentrations from respirable dust concentrations. On a task basis, we found mean 8‐h TWA concentrations of respirable dust and chrysotile fibers are numerically highest for specialists, followed by generalists, DIYers, and bystander tradespersons; these concentrations are estimated to be in excess of the respective current but not historical Threshold Limit Values. Due to differences in frequency of activities, annual cumulative exposures are highest for specialists, followed by generalists, bystander tradespersons, and DIYers. Cumulative exposure estimates for chrysotile fibers from drywall finishing are expected to result in few, if any, mesothelioma or excess lung cancer deaths according to recently published risk assessments. Given the dustiness of drywall finishing, we recommend diligence in the use of readily available source controls.     

Modeling Long-Term Exposure of the Whole Population to Chemicals in Food

This paper discusses a statistical exposure model (STEM) that can be used to estimate the percentage of the population exceeding ingestion intake criteria (e.g., ADI or TDI). In addition, STEM may be linked to toxicokinetic models to evaluate the interindividual variability in internal doses that results from variability in consumption habits. The assumptions of STEM are investigated by analyzing dioxin and cadmium intake data for the Dutch population.     

Peak Exposures in Epidemiologic Studies and Cancer Risks: Considerations for Regulatory Risk Assessment

We review approaches for characterizing “peak” exposures in epidemiologic studies and methods for incorporating peak exposure metrics in dose–response assessments that contribute to risk assessment. The focus was on potential etiologic relations between environmental chemical exposures and cancer risks. We searched the epidemiologic literature on environmental chemicals classified as carcinogens in which cancer risks were described in relation to “peak” exposures. These articles were evaluated to identify some of the challenges associated with defining and describing cancer risks in relation to peak exposures. We found that definitions of peak exposure varied considerably across studies. Of nine chemical agents included in our review of peak exposure, six had epidemiologic data used by the U.S. Environmental Protection Agency (US EPA) in dose–response assessments to derive inhalation unit risk values. These were benzene, formaldehyde, styrene, trichloroethylene, acrylonitrile, and ethylene oxide. All derived unit risks relied on cumulative exposure for dose–response estimation and none, to our knowledge, considered peak exposure metrics. This is not surprising, given the historical linear no‐threshold default model (generally based on cumulative exposure) used in regulatory risk assessments. With newly proposed US EPA rule language, fuller consideration of alternative exposure and dose–response metrics will be supported. “Peak” exposure has not been consistently defined and rarely has been evaluated in epidemiologic studies of cancer risks. We recommend developing uniform definitions of “peak” exposure to facilitate fuller evaluation of dose response for environmental chemicals and cancer risks, especially where mechanistic understanding indicates that the dose response is unlikely linear and that short‐term high‐intensity exposures increase risk.     

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.     

Assessment of Inhalation Exposures and Potential Health Risks to the General Population that Resulted from the Collapse of the World Trade Center Towers

In the days following the collapse of the World Trade Center (WTC) towers on September 11, 2001 (9/11), the U.S. Environmental Protection Agency (EPA) initiated numerous air monitoring activities to better understand the ongoing impact of emissions from that disaster. Using these data, EPA conducted an inhalation exposure and human health risk assessment to the general population. This assessment does not address exposures and potential impacts that could have occurred to rescue workers, firefighters, and other site workers, nor does it address exposures that could have occurred in the indoor environment. Contaminants evaluated include particulate matter (PM), metals, polychlorinated biphenyls, dioxins, asbestos, volatile organic compounds, particle-bound polycyclic aromatic hydrocarbons, silica, and synthetic vitreous fibers (SVFs). This evaluation yielded three principal findings. (1) Persons exposed to extremely high levels of ambient PM and its components, SVFs, and other contaminants during the collapse of the WTC towers, and for several hours afterward, were likely to be at risk for acute and potentially chronic respiratory effects. (2) Available data suggest that contaminant concentrations within and near ground zero (GZ) remained significantly elevated above background levels for a few days after 9/11. Because only limited data on these critical few days were available, exposures and potential health impacts could not be evaluated with certainty for this time period. (3) Except for inhalation exposures that may have occurred on 9/11 and a few days afterward, the ambient air concentration data suggest that persons in the general population were unlikely to suffer short-term or long-term adverse health effects caused by inhalation exposures. While this analysis by EPA evaluated the potential for health impacts based on measured air concentrations, epidemiological studies conducted by organizations other than EPA have attempted to identify actual impacts. Such studies have identified respiratory effects in worker and general populations, and developmental effects in newborns whose mothers were near GZ on 9/11 or shortly thereafter. While researchers are not able to identify specific times and even exactly which contaminants are the cause of these effects, they have nonetheless concluded that exposure to WTC contaminants (and/or maternal stress, in the case of developmental effects) resulted in these effects, and have identified the time period including 9/11 itself and the days and few weeks afterward as a period of most concern based on high concentrations of key pollutants in the air and dust.     

Modeling Risk‐Related Knowledge in Tunneling Projects

Knowledge on failure events and their associated factors, gained from past construction projects, is regarded as potentially extremely useful in risk management. However, a number of circumstances are constraining its wider use. Such knowledge is usually scarce, seldom documented, and even unavailable when it is required. Further, there exists a lack of proven methods to integrate and analyze it in a cost‐effective way. This article addresses possible options to overcome these difficulties. Focusing on limited but critical potential failure events, the article demonstrates how knowledge on a number of important potential failure events in tunnel works can be integrated. The problem of unavailable or incomplete information was addressed by gathering judgments from a group of experts. The elicited expert knowledge consisted of failure scenarios and associated probabilistic information. This information was integrated using Bayesian belief‐networks‐based models that were first customized in order to deal with the expected divergence in judgments caused by epistemic uncertainty of risks. The work described in the article shows that the developed models that integrate risk‐related knowledge provide guidance as to the use of specific remedial measures.     

Modeling Pathology Workload and Complexity to Manage Risks and Improve Patient Quality and Safety

Anatomic pathology (AP) laboratories provide critical diagnostic information that help determine patient treatments and outcomes, but the risks of AP operations and their impact on patient safety and quality of care remain poorly recognized and undermanaged. Hospital-based laboratories face an operational and risk management challenge because clinical work of unknown quantity and complexity arrives with little advance notice, which results in fluctuations in workload that can push operations beyond planned capacity, leading to diagnostic delays and potential errors. Modeling the dynamics of workload and complexity in AP offers the opportunity to better use available information to manage risks. We developed a stock-and-flow model of a typical AP laboratory operation and identified key exogenous inputs that drive AP work. To test the model, we generated training and validations data sets by combining data from the electronic medical records and laboratory information systems over multiple years. We demonstrate the implementation of 10-day AP work forecast generated on a daily basis, and show its performance in comparison with actual work. Although the model somewhat underpredicts work as currently implemented, it provides a framework for prospective management of resources to ensure quality during workload surges. Although full implementation requires additional model development, we show that AP workload largely depends on few and accessible clinical inputs. Recognizing that level loading of work in a hospital is not practical, predictive modeling of work can empower laboratories to triage, schedule, or mobilize resources more effectively and better manage risks that reduce the quality or timeliness of diagnostic information.     

Projections of Cancer Risks Attributable to Future Exposure to Asbestos

To assess the maximum possible impact of further government regulation of asbestos exposure, projections were made of the use of asbestos in nine product categories for the years 1985-2000. A life table risk assessment model was then developed to estimate the excess cases of cancer and lost person-years of life likely to occur among those occupationally and nonoccupationally exposed to the nine asbestos product categories manufactured in 1985-2000. These estimates were made under the assumption that government regulation remains at its 1985 level. Use of asbestos in the nine product categories was predicted to decline in all cases except for friction products. The risk assessment results show that, although the cancer risks from future exposure to asbestos are significantly less than those from past exposures, in the absence of more stringent regulations, a health risk remains.     

Model Averaging Using Fractional Polynomials to Estimate a Safe Level of Exposure

Quantitative risk assessment involves the determination of a safe level of exposure. Recent techniques use the estimated dose-response curve to estimate such a safe dose level. Although such methods have attractive features, a low-dose extrapolation is highly dependent on the model choice. Fractional polynomials, basically being a set of (generalized) linear models, are a nice extension of classical polynomials, providing the necessary flexibility to estimate the dose-response curve. Typically, one selects the best-fitting model in this set of polynomials and proceeds as if no model selection were carried out. We show that model averaging using a set of fractional polynomials reduces bias and has better precision in estimating a safe level of exposure (say, the benchmark dose), as compared to an estimator from the selected best model. To estimate a lower limit of this benchmark dose, an approximation of the variance of the model-averaged estimator, as proposed by Burnham and Anderson, can be used. However, this is a conservative method, often resulting in unrealistically low safe doses. Therefore, a bootstrap-based method to more accurately estimate the variance of the model averaged parameter is proposed.     

Awareness and Perceptions of the Risks of Exposure to Indoor Radon: A Population‐Based Approach to Evaluate a Radon Awareness and Testing Campaign in England and Wales

The current study aimed to evaluate the locally directed radon roll‐out program that was conducted between 2001 and 2005 in England and Wales to increase radon awareness and testing rates. A representative sample of 1,578 residents aged 16 and older were interviewed who lived in radon‐affected areas of 15 local authorities in England and Wales that were eligible for participation in the program. The study systematically sampled across participating and nonparticipating local authorities, “actionable” and “nonactionable” radon‐affected areas, and geographic regions with different campaign histories (Wales, Southwest England, and the rest of England). As a multistage sampling strategy was used, the data were analyzed from a multilevel perspective. This study found that participants living in participating local authorities had higher levels of awareness and were more likely to have tested their home for radon than participants living in nonparticipating local authorities. Similar results were found for participants living in “actionable” areas as compared to those living in “nonactionable” radon‐affected areas. The study further found that radon awareness and testing rates were the highest in Southwest England and the lowest in Wales. This study suggests that the radon roll‐out program has been effective in raising awareness and testing rates, and that ongoing domestic radon campaigns in Southwest England may have raised radon awareness and testing in these areas, showing important reinforcement effects of multiple risk communication campaigns.     

What Are the Sources of Exposure to Eight Frequently Used Phthalic Acid Esters in Europeans?

Phthalic acid esters (phthalates) are used as plasticizers in numerous consumer products, commodities, and building materials. Consequently, phthalates are found in human residential and occupational environments in high concentrations, both in air and in dust. Phthalates are also ubiquitous food and environmental contaminants. An increasing number of studies sampling human urine reveal the ubiquitous phthalate exposure of consumers in industrialized countries. At the same time, recent toxicological studies have demonstrated the potential of the most important phthalates to disturb the human hormonal system and human sexual development and reproduction. Additionally, phthalates are suspected to trigger asthma and dermal diseases in children. To find the important sources of phthalates in Europeans, a scenario-based approach is applied here. Scenarios representing realistic exposure situations are generated to calculate the age-specific range in daily consumer exposure to eight phthalates. The scenarios demonstrate that exposure of infant and adult consumers is caused by different sources in many cases. Infant consumers experience significantly higher daily exposure to phthalates in relation to their body weight than older consumers. The use of consumer products and different indoor sources dominate the exposure to dimethyl, diethyl, benzylbutyl, diisononyl, and diisodecyl phthalates, whereas food has a major influence on the exposure to diisobutyl, dibutyl, and di-2-ethylhexyl phthalates. The scenario-based approach chosen in the present study provides a link between the knowledge on emission sources of phthalates and the concentrations of phthalate metabolites found in human urine.     

Leukemia Risk Associated with Benzene Exposure in the Pliofilm Cohort: I. Mortality Update and Exposure Distribution

The National Institute of Occupational Safety and Health (NIOSH) recently completed a vital status update adding 6 years of observation on the rubber workers known as the Pliofilm cohort. Using traditional standardized mortality ratio (SMR) analysis, we investigate the impact of the additional information gathered in the NIOSH update. We also compare the effect of using three sets of job-, plant-, and year-specific exposure estimates on the evaluation of benzene's leukemogenicity. The lack of any additional cases of multiple myeloma does not support trends toward elevated risks for this endpoint (as had been observed earlier), and there is no indication of increased incidences of solid tumors (as predicted by animal studies). Qualitatively, which exposure estimates are used does not alter the conclusions. The data added in the update did not greatly modify the estimated relative risk of leukemia associated with benzene exposure, but did confirm previous findings that occupational exposure to high concentrations had leukemogenic potential. The fact that leukemia has not been observed in any individual who started employment in Pliofilm production after 1950 suggests that the observed leukemia cases could be a response to very high levels of benzene exposure that occurred during the early years of this manufacturing process.     

Evaluation of Take‐Home Exposure and Risk Associated with the Handling of Clothing Contaminated with Chrysotile Asbestos

The potential for para‐occupational (or take‐home) exposures from contaminated clothing has been recognized for the past 60 years. To better characterize the take‐home asbestos exposure pathway, a study was performed to measure the relationship between airborne chrysotile concentrations in the workplace, the contamination of work clothing, and take‐home exposures and risks. The study included air sampling during two activities: (1) contamination of work clothing by airborne chrysotile (i.e., loading the clothing), and (2) handling and shaking out of the clothes. The clothes were contaminated at three different target airborne chrysotile concentrations (0–0.1 fibers per cubic centimeter [f/cc], 1–2 f/cc, and 2–4 f/cc; two events each for 31–43 minutes; six events total). Arithmetic mean concentrations for the three target loading levels were 0.01 f/cc, 1.65 f/cc, and 2.84 f/cc (National Institute of Occupational Health and Safety [NIOSH] 7402). Following the loading events, six matched 30‐minute clothes‐handling and shake‐out events were conducted, each including 15 minutes of active handling (15‐minute means; 0.014–0.097 f/cc) and 15 additional minutes of no handling (30‐minute means; 0.006–0.063 f/cc). Percentages of personal clothes‐handling TWAs relative to clothes‐loading TWAs were calculated for event pairs to characterize exposure potential during daily versus weekly clothes‐handling activity. Airborne concentrations for the clothes handler were 0.2–1.4% (eight‐hour TWA or daily ratio) and 0.03–0.27% (40‐hour TWA or weekly ratio) of loading TWAs. Cumulative chrysotile doses for clothes handling at airborne concentrations tested were estimated to be consistent with lifetime cumulative chrysotile doses associated with ambient air exposure (range for take‐home or ambient doses: 0.00044–0.105 f/cc year).     

Assessment of Health Risk from Exposure to Contaminated Soil

The risk to human health posed by contaminated soil in a residential area depends on the potential extent of exposure to soil and on the toxic properties of the contaminants. A detailed soil exposure analysis is presented for young children, older children, and adults living in a house surrounded by contaminated soil. From this analysis, a lifetime exposure model is derived and used to assess chronic health risks.     

A Dynamic Model to Assess Microbial Health Risks Associated with Beneficial Uses of Biosolids

There is increasing interest in the development of a microbial risk assessment methodology for regulatory and operational decision making. This document presents a methodology for assessing risks to human health from pathogen exposure using a population-based model that explicitly accounts for properties unique to an infectious disease process, specifically secondary transmission and immunity. To demonstrate the applicability of this risk-based method, numerical simulations were carried out for a case study example in which the route of exposure was direct consumption of biosolids-amended soil and the pathogen present in the soil was enterovirus. The output from the case study yielded a decision tree that differentiates between conditions in which the relative risk from biosolids exposure is high and those conditions in which the relative risk from biosolids is low. This decision tree illustrates the interaction among the important factors in quantifying risk. For the case study example, these factors include biosolids treatment processes, the pathogen shedding rate of infectious individuals, secondary transmission, and immunity. Further refinement in methods for determining biosolids exposures under field conditions would certainly increase the utility of these approaches.     

基于提前期的多阶通用件库存模型

针对单个企业内部应用通用件的环境,在假定一个多阶生产系统的基础上,对应用通用件的库存量水平及其成本进行了分析,建立了多阶通用件库存模型,提出通过对采用通用件和不采用通用件的成本差异的比较,来决策多阶生产系统中在哪一阶工序采用通用件,并求解出每一阶工序优化的基本库存水平。