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3 Applications of Exposure Science INTRODUCTION Exposure science plays a fundamental role in the development and appli- cation of epidemiology, toxicology, and risk assessment. It provides critical in- formation for protecting human and ecosystem health. Exposure science also has the ability to play an effective role in other fields, including environmental regu- lation, urban and ecosystem planning, and disaster management; in many cases these are untapped opportunities. Exposure science links human and ecologic behavior to environmental processes in such a way that the information gener- ated can be used to mitigate or prevent future adverse exposures. This chapter discusses current and future opportunities for and challenges to applying expo- sure science to those fields and frames some of the needs for further develop- ment of exposure science. Text boxes are intended to illustrate specific examples of the role of exposure science. EPIDEMIOLOGY Exposure assessment is a major component of environmental epidemiol- ogy; it is equal in importance to outcome assessment. Historically, the main fo- cus of many environmental epidemiology studies has been on single chemical, biologic, and physical stressors (for example, individual pesticides, air pollut- ants, ionizing radiation, or water contaminants). But human populations are ex- posed to a multitude of potentially hazardous stressors simultaneously, often with highly correlated patterns of spatial and temporal variation, and are affected by human activities and behaviors, so it is difficult to pinpoint the specific stressor associated with a particular outcome. New high-throughput genomic and biomonitoring technologies (discussed in Chapter 5) are providing for a greater number of potential biomarkers that can be used to assess multiple expo- sures simultaneously. In addition to chemical, biologic, or physical stressors, epidemiologists may be concerned with psychosocial stressors that influence 50
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Applications of Exposure Science 51 disease risks directly or modify a person's susceptibility to the effects of other agents (Shankardass et al. 2009). The direct effects of psychosocial risk factors on health outcomes are beyond the scope of this report, but their role as modifi- ers of exposures is within the committee's charge. Figure 3-1 provides a general schema for thinking about the components of exposure assessment in environ- mental epidemiology. Each of the components shown in solid boxes represent areas where exposure science can contribute, providing data on determinants of people's exposures (the intensity of the spatio-temporal exposure fields they are moving through and their personal time/activity patterns in that field) and direct measurements of individuals' external exposures or internal doses, along with relevant modifying factors. The hypothesized (but not directly observable) his- tory of doses to the relevant target organs are then used by epidemiologists to relate to the health outcomes. Psychosocial factors Biomarkers of exposure Exposure Personal spatio/temporal external field (stressor) exposure monitoring Personal exposure Internal Health (stressor/receptor dose outcomes interaction) Personal time/activity factors (receptor) Metabolic genes, Susceptibility genes age, gender, other and other risk factors modifying factors (for example, age, comorbidity conditions) FIGURE 3-1 General schema of exposure assessment in environmental epidemiology. Items in gray, related to health outcomes and their determinants other than environmental exposures, are included to place exposure assessment in context but are outside the charge of this committee. Boxes represent measurable quantities, and ovals denote hypo- thetical intermediate variables that can be assessed only indirectly. Solid arrows denote direct effects, and dashed arrows indicate modifying effects. For example, the oval marked "personal exposure" represents the entire history of an individual's true biologi- cally-relevant exposure, which is not directly observable. The boxes labeled "personal external exposure monitoring" and "biomarkers of exposure" represent the data that are potentially observable.
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52 Exposure Science in the 21st Century: A Vision and A Strategy Traditional exposure assessment for epidemiology combines the use of measurements and models to characterize the spatio-temporal field of environ- mental concentrations of a stressor with individual data on interactions of recep- tors (people) with their environment (for example, derived from questionnaires on time≠activity patterns) to estimate personal exposures. In some studies, direct measurements of personal exposures (for example, film-badge measurements of occupational radiation exposures) and novel methods of tracking individual ac- tivities (for example, Global Positioning System (GPS) monitoring of locations and accelerometers for physical activity rates and videotaping of activities) have been used, either on an entire study population or on some sample for calibration or validation of model predictions. The emerging field of molecular epidemiol- ogy, based on the use of biomarkers of exposure (as well as of susceptibility or early signs of disease), offers potentially transformative advances in exposure science, particularly if combined with novel genomic, transcriptomic, me- tabolomic, and other "≠omic" technologies and bioinformatic tools for organiz- ing and integrating the massive, often disparate, data sets (see Chapter 5). Box 3-1 illustrates some of the complexities of exposure assessment for the National Children's Study, with longitudinal measurements of a broad array of environ- mental and personal (external and internal) exposures and health outcomes. Historically, comprehensive measurement of environmental exposures has not been possible, requiring statistical models to interpolate among relatively sparse measurements. The models can be purely statistical, such as geostatistical models for air pollution, or can be based on mathematical models for tracking agents from sources through intake by receptors (see NCRP 2010a for a discus- sion of the general principles of environmental dose reconstruction for radiation exposures and NCRP 2008, 2010b for recommended approaches to uncertainty analysis for external and internal exposures respectively). Box 3-2 provides an example of environmental pathway analysis applied to evaluate radionuclide exposures from the Hanford nuclear plant in Hanford, WA, and illustrates the value of involving the affected communities in all stages of the planning of an epidemiology project. As novel sensing technologies, such as satellite imaging, become more widely available and more accurate, the need for models will remain, but the focus will shift from interpolation to exploitation of massive datasets. A key function of models is not just to provide point estimates of individual exposures but to quantify the uncertainty in exposure estimates, to understand measure- ment error in health analyses. Environmental exposures typically occur over extended periods of time at varying intensities, requiring a shift in thinking from simple exposure-response to exposure-time-response relationships (Thomas 1988). These can be quite complex, involving modifying effects of age-at-exposure (for example, at par- ticularly sensitive developmental stages), time-since-exposure, duration-of- exposure, or other time-related factors. In addition, for most conditions, little is known about whether short intense exposures have larger or smaller effects than
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Applications of Exposure Science 53 BOX 3-1 Case Study of Exposure Assessment for the National Children's Study The National Children's Study (NCS) is a nationwide cohort study of pregnancy outcomes and child development through the age of 21 years. The study aims to investigate the separate and combined effects of environmental exposures on pregnancy outcomes, child health and development, and ori- gins of adult disease. Environmental exposures in the NCS are broadly de- fined to include chemical, biologic, physical, psychosocial, and genomic fac- tors. The study also aims to examine determinants of child, maternal, and developmental health disparities, such as prenatal exposures, geography, social status, race, ethnicity, neighborhood characteristics, and quality of so- cial networks, and the impact of various disparities on health outcomes. The current study has about 100 study locations, but the number, size, and selec- tion process for these study locations may evolve (Hirschfeld et al. 2011). A complex exposure assessment is planned, entailing a combination of techniques--questionnaires on diet and product use; environmental sampling of house dusts; and collection, storage, and assays of biologic specimens (for example, blood, urine, saliva, hair, breast milk, and adipose tissue) (Barr et al. 2005; Needham et al. 2005). Depending on the particular agent, exposure assessments will be conducted at various life stages, for example, in utero, postnatal, and peripubertal (Bradman and Whyatt 2005; Wang et al. 2005; Landrigan et al. 2006). In addition, data from national and state agencies are being used to profile areas within a county and locations of the study partici- pants (Lioy et al. 2009; Downs et al. 2010); a test case is being conducted in Queens County, NY (Lioy et al. 2009). Sophisticated modeling will be needed to combine the various data sources. Given the size, scope, and complexity of the NCS, there have been chal- lenges to identify exposure assessment approaches and methods that are feasible, acceptable, and limited in both cost and participant burden. Valida- tion sub-studies have been investigated (Strauss et al. 2010), extant data will be relied on, and choices will have to be made about which chemicals to measure in stored environmental or biologic samples (÷zkaynak et al. 2005; Gilliland et al. 2005; NRC/IOM 2008). The development of the exposure assessment component of the NCS study highlights the challenges for exposure science to meet the demands for exposure information across time scales for large populations. In 2010, EPA, NIEHS, and the NCS organized a workshop to engage scientists from the exposure, epidemiology, and health effects disciplines with the goal of identifying the most promising and practical exposure metrics to use in a study the size and scope of the NCS (Tulve et al. 2010). For the most part, the workshop participants agreed that questionnaires and diaries provide inadequate and unreliable exposure information; that more effective exposure metrics are needed that will provide better information on exposures and their inter- and intra-individual variabilities, and that high quality samples should be collected (in particular in the perinatal period) and archived for future analyses as new analytic methods are developed.
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54 Exposure Science in the 21st Century: A Vision and A Strategy BOX 3-2 Case Study of the Hanford Environmental Dose-Reconstruction Project As part of the Manhattan Project and continuing into the 1960s, all the plutonium for the U.S. nuclear-weapons program was produced at the Han- ford Nuclear Reservation in the southeastern part of Washington State. Dur- ing the early years, considerable quantities of radionuclides were released into the environment, notably iodine-131, which tends to accumulate in the thyroid gland of exposed people and can lead to thyroid cancers and other thyroid abnormalities. To address concerns of the downwind population, two projects were launched by the Centers for Disease Control and Prevention: the Hanford Environmental Dose Reconstruction (HEDR) Project and the Hanford Thyroid Disease Study (HTDS). The latter was an epidemiologic co- hort study that made use of dose estimates produced by the HEDR Project. The HEDR Project is an important illustration of how exposure science in- forms epidemiologic research. The HEDR Project began by reviewing over 38,000 pages of environ- mental-monitoring documents. Technical panels of experts in nuclear engi- neering, radiation dosimetry, environmental transport, meteorology, hydrol- ogy, statistics, and other fields developed an environmental-pathway model. The model reconstructed the releases from the plant and modeled their transport through air, soil, and water contamination; uptake by vegetation; intake by dairy cows and goats; milk production and distribution and ingestion by individual study participants and their mothers while pregnant; and ulti- mately dose delivery to the thyroid gland. Some parts of the complex model were informed by measurements, others by expert judgment; each step en- tailed careful consideration of the relevant uncertainties. The entire model was incarnated in a Monte Carlo computer program that yielded multiple re- alizations of possible doses to each individual, with variability among the re- alizations reflecting the uncertainties in the final dose assignments (Shipler et al. 1996). Although much concern had been expressed about contamination of the Columbia River, the analysis found the contribution to human expo- sures by that pathway to be negligible. The distribution of final dose estimates used by the HTDS had a range that was shown to provide adequate power to test for dose≠response relationships with various thyroid outcomes (Kopecky et al. 2004). The null results for all types of thyroid abnormalities provided evidence that most cases in the region were unlikely to be due to radioactive releases from the Hanford plant (Kopecky et al. 2005), although this interpre- tation remains somewhat controversial (Hoffman et al. 2007). A major lesson yielded by the HEDR Project and HTDS was the impor- tance of community involvement, particularly in light of a concurrent class action lawsuit and suspicions that the U.S. Department of Energy (the owner and operator of the site) was influencing the study. Public, state, and Ameri- can Indian representation in the independent Technical Steering Panel (TSP) that oversaw the project was viewed as essential from the beginning (Shipler 1995). The TSP adopted a commendable policy of openness in all aspects of (Continued)
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Applications of Exposure Science 55 BOX 3-2 Continued the project, including definition of scope, budget, and priorities. The investiga- tors commented that the open approach required more time and energy but concluded that "if these issues and concerns are addressed early and if scop- ing of the project with an advisory panel is completed before major work is initiated, cost-effective planning and management can be achieved and `sci- ence in a fishbowl' can be successful" (Shipler 1995, p. 108). long low-intensity exposures or other patterns of temporal variation. While such issues are amenable to epidemiologic analysis, this is possible only if detailed histories of exposure are available, requiring exposure scientists to develop novel ways of reconstructing the entire history of past exposures or for monitor- ing time-varying exposures prospectively for extended periods. The "exposome" concept (see Chapter 1) may provide a framework for representing a person's lifetime of exposure to all potentially hazardous or bene- ficial agents. Although the concept is generally interpreted as relating to the to- tality of biologically-relevant exposures of either external or endogenous ori- gins, the current enthusiasm is driven largely by the rapid advances of various ≠omics technologies (reviewed in Chapter 5) that permit agnostic assessment of a broad swath of internal biomarkers of exposure. For example, two recent pub- lications illustrate its potential utility with "Environment-Wide Association Studies (EWAS)," agnostic scans for associations using a panel of a few hun- dred metabolite measurements (Box 3-3). These illustrations are analogous-- albeit on a smaller scale--to genome-wide association studies that test the asso- ciation of a disease or trait with hundreds of thousands to millions of genetic variants, but provide a "proof of concept" for an approach that could in principle be extended to a much broader range of exposures, monitored longitudinally. Novel approaches are needed to mine such data (Thomas 2010), together with internal and external markers of exposure to improve assessment of exposure- response relationships and, more importantly, to find ways to intervene before an adverse outcome is observed in an individual or population. That is a long- term goal that will require new approaches for conducting research, including capitalizing on future advances in individualized medicine and understanding the effects of changes in lifestyle and human behaviors. Exposure assessment is usually constrained by cost or other feasibility considerations. It is seldom possible to measure everything that one would like to measure over the lifetime of an entire epidemiologic cohort. Hence, various sub-study designs are needed to devise a cost-efficient method of exposure as- sessment. That typically entails statistical modeling to combine the substudy data with the main-study data (Breslow et al. 2009). The study-design challenge involves trying to optimize the various tradeoffs--for example, between num bers of subjects and locations and breadth and duration of measurements--to yield the most precise estimates of the exposure≠response relationship of inter-
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56 Exposure Science in the 21st Century: A Vision and A Strategy est. Key to the optimization challenge is the measurement-error distribution ex- pected with alternative designs and the use of statistical methods for adjusting for measurement errors (Carroll et al. 2006). Another type of hybrid design en- tails combining individual and group measurements. For example, one might correlate disease rates in large populations with estimates of the joint distribu- tion of exposure, confounders, and modifiers obtained from sample surveys within each population (Sheppard et al. 1996). Box 3-4 illustrates the value of improved exposure estimates for epidemiologic studies. The availability of various population-wide outcome databases--such as databases of mortality, hospitalization, and cancer incidence--is unfortunately not matched by population-wide exposure databases. The availability of a na- tional dose registry for radiation workers in Canada, however, has made it pos- sible to use record-linkage techniques to conduct large-scale studies of dose≠ response relationships for cancer (Zablotska et al. 2004). Establishing such reg- istries and extending them to include medical-radiation doses, perhaps in the form of an electronic personal dose history, would be a boon for the field of radiation epidemiology. Ultimately, it would be desirable to have some life- course exposure registry for the entire population, or a periodic census of a large sample of the population that would inquire about a broad spectrum of environ- mental exposures for research purposes. BOX 3-3 Environment-Wide Association Study (EWAS) Patel et al. (2010) conducted an agnostic scan for associations of many measurements of internal exposures with type 2 diabetes; this was similar in spirit to Genome-Wide Association Studies (GWAS) that test the association of a disease or trait with hundreds of thousands to millions of genetic variants. Rather than using traditional methods of characterizing external exposures, the investigators used the "exposome" concept to assess potentially biologi- cally effective exposures with a panel of 266 metabolite measurements ob- tained from the National Health and Nutrition Examination Survey of 503≠ 3,318 people. They found statistically significant associations (after adjusting for multiple comparisons) with heptachlor epoxide (a pesticide derived me- tabolite), vitamin tocopherol, and some PCBs and found protective effects of carotenes. A similar EWAS (Patel and Butte 2010) looked at associations with gene expression levels. Because it was not a longitudinal study, there is the potential for "reverse causation" bias, a tendency for disease or its treat- ment to affect biologic measurements rather than for the exposure to be a cause of the disease. Cohort studies would avoid that difficulty by relating biomarker measurements in unaffected people to their later onset of new dis- ease. The Patel et al. study should be considered as a "proof of concept" for an approach that shows great promise for application of far more extensive panels of biomarkers from the various biobanks being assembled or already in existence that have stored biologic specimens from hundreds of thousands or millions of subjects with followup for disease incidence.
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Applications of Exposure Science 57 BOX 3-4 Value of Improved Exposure Estimates for Epidemiologic Studies Reducing exposure error is critical for epidemiologic investigations. Pre- vious air-pollution health-effects studies have underlined the importance of capturing spatial variability, particularly in urban areas (Logue et al. 2010; Bell et al. 2011). Accurate assessment of human exposures to atmospheric pollu- tion requires knowledge of the spatial distribution of pollutants over cities on scales of 1-100 m (Chow et al. 2002). The improved resolution is expected not only to reduce exposure-assessment error but generally to result in larger health-effects estimates. For example, Jerrett et al. (2005) applied kriging techniques to study the association between within-city PM2.5 exposure gradi- ents and mortality and found a substantially larger effect than previously re- ported with the city-average exposures (Liu et al. 2009, p. 886). The Women's Health Initiative found a larger pollution effect on mortality when within-city exposure estimates were used (Miller et al. 2007). Nevertheless, although it is generally true that reductions in exposure measurement error can lead to improvements in health-effect estimates, it is not always true, and it depends on the specifics of the measurement error and the true exposure distributions (Szpiro et al. 2011). (See discussion in Chapter 5.) The goal of a truly population-based exposure registry may be less feasi- ble in the United States than in countries that have national health systems and population registries, at least in the foreseeable future. However, health- maintenance organizations (HMOs) may provide unique opportunities to build large-scale databases that, when combined with biomarkers of exposure assayed from routinely collected biospecimens and systematically collected exposure information (from clinic visits or questionnaires), could form the basis of long- term cohort studies. Outcome data reflecting clinic visits, hospitalizations, diag- noses, medication prescriptions, and mortality would be routinely available through followup data collection. Although not strictly random, the coverage of the larger HMOs is extensive enough to represent a broad spectrum of the popu- lation. Exposure science could also take advantage of data obtained on individu- als and populations through market-based and product-use research to improve questions on exposures in epidemiologic studies. TOXICOLOGY Toxicology, whether focused on mechanisms or hazards, has historically been conducted outside the context of actual human exposures. Two major haz- ard evaluation programs, the U.S. Environmental Protection Agency (EPA) ToxCast and the National Institute of Environmental Health Sciences National Toxicology Program select chemicals and other materials (such as nanomateri- als) for evaluation and use exposure as one qualitative selection criterion (Dix et al. 2007). But exposure context is for more than selection of chemicals for test-
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58 Exposure Science in the 21st Century: A Vision and A Strategy ing. The biology of systems perturbed by exposures to stressors is highly sensi- tive to the magnitude of exposure (Slikker et al. 2004; Andersen et al. 2010). Mechanistic studies and hazard assessments conducted at concentrations that far exceed actual human exposures may produce results that are misleading because the observed effects are not likely to occur at lower doses or because low-dose effects may be masked by more overt toxicity at high doses. The availability of more exposure data could guide dose concentrations in toxicity studies. The interdependence of toxicology and exposure science is recognized in these two communities, but exposure science is typically underemphasized as a principle in toxicology. The committee responsible for Toxicity Testing in the 21st Century: A Vision and A Strategy (NRC 2007) recognized the need for bet- ter integration and use of exposure science in toxicity assessment and called for its greater use in each step of the vision. The report spurred the rapid develop- ment of toxicity testing, in particular in in vitro, high-throughput methods, but its use of exposure science has seen little growth over the same period. That is unfortunate in light of the fundamental interdependence of the two fields, in- cluding the importance of exposure information in the design and interpretation of toxicity testing (Cohen Hubal et al. 2010; 2011). In place of current practice, the present committee envisions a shift toward a toxicologic assessment program that has an interface with exposure science and is influenced by and responsive to human and environmental exposure data. Such a program would strengthen the current toxicology-driven paradigm by focusing on the four activities de- scribed below. Select and set priorities among chemicals for toxicity testing. As EPA implements the recommendations of the 2007 National Research Council report, exposure science will become even more important for priority-setting (Cohen Hubal et al. 2010). As described in Chapter 2, that report envisioned a process for screening chemicals in commerce for hazard potential with rapid toxicity- pathway screens informed by and with priorities set through screening-level exposure assessments. The EPA ToxCast program is one example of such an implementation effort. In addition, efforts to reform the Toxic Substances Con- trol Act (TSCA) will probably rely on priority-setting strategies that consider both exposure and toxicity potential. For those reasons, the present committee's vision of enhancing the publicly available information on chemicals in com- merce, improving screening for chemicals in the environment and in people (via biomonitoring and microsensor networks), and improving exposure modeling will form a solid foundation for priority-setting in relation to toxicity-pathway screening studies. Provide internal and external exposure information to inform selection of relevant concentrations of stressors for high-throughput toxicity testing. Ex- posure science needs to develop strategies to provide the information required to enable testing of stressors in animals. However, statistical-power considerations may make it infeasible or inadvisable to use only environmentally relevant doses in whole-animal studies. Newer in vitro toxicity-pathway studies can be con-
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Applications of Exposure Science 59 ducted at a wide range of doses, and these studies can be informed by exposure- related information, especially as it relates to internal dose. Reaching that goal will require a shift in exposure science toward collection of internal measures of exposure, as discussed in Chapter 5. Provide quantitative pharmacokinetic data (on absorption, distribution, metabolism, and excretion) derived from human-exposure studies. Targeted ex- posure studies need to include collection of exposure information to allow infer- ence about human pharmacokinetic measures, such as the time course of expo- sure, for some high-priority chemicals. Exposure-characterization protocols should include measurements of external and internal markers of exposure to assess bioavailability, especially when exposures are predominantly via a single route. Greater use of longitudinal internal exposure studies that include periods of high and low or no exposures (such as those in occupational environments during and after work) could provide concentration time-course data similar to repeated-dose pharmacokinetic studies. For example, absorption rates, half- lives, and other pharmacokinetic measures and their variability within and be- tween individuals could be derived from those data and would provide a wealth of critical human pharmacokinetic data for setting exposure concentrations for toxicity testing and for use in risk assessment (Teeguarden et al. 2011). Link exposure data with in vivo data on perturbations of toxicity pathways in human or wildlife populations to identify exposure-response rela- tionships directly. The conventional hazard-assessment paradigm uses cell- culture systems or animal models to identify hazards. In the future, the present committee expects collection of higher-resolution and larger quantities of expo- sure data in a broader swath of the population to allow epidemiologists to iden- tify potential hazards in human populations or ecosystems. The characterization of the hazards could then be explored by using more focused, efficient toxi- cologic studies at relevant exposure concentrations and durations or measure- ments of perturbations of toxicity pathways (that is, as seen in genetic or other biomarkers of effect) in exposed human or wildlife populations. Although these studies might be expected initially to focus on individual stressors, they would evolve with advances in exposure technologies to identify and characterize combinations of stressors. There are also opportunities for epidemiology and toxicology to be more closely tied to the process of exposure assessment. For example, cell lines de- rived from epidemiologic study subjects could be exposed in culture to mixtures derived from samples from the specific environments to which the subjects were exposed, to identify measures of biologic activity of these complex mixtures. The measures of biologic activity would then represent more relevant, more specific measures of response for use as variables in subsequent epidemiologic studies. Exposure of experimental animal models to environmental mixtures associated with specific epidemiologic studies would provide additional infor- mation on exposure-response relationships, the time-course of development of disease, and the role of genetics as modifiers of exposure and response. In vivo
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60 Exposure Science in the 21st Century: A Vision and A Strategy challenge studies in humans or experimental animal models can also provide much information on intermediate biologic responses to agents (for example, diesel-exhaust particles or second-hand smoke) and on genetic modifiers of these responses to exposures (Gilliland et al. 2004). That information could in- form exposure≠response or gene≠environment interaction analyses of epidemi- ologic data. Finally, epidemiology and toxicology would benefit from a more sophisticated approach to modeling that takes advantage of the source-to-effect continuum and reduces uncertainties in study design and misinterpretation of results for use in mitigation and prevention (Georgopoulos et al. 2009). ENVIRONMENTAL REGULATION Risk Assessment Exposure assessment is one of the core components of regulatory quantita- tive risk assessment; therefore, the quality of exposure information and the state of exposure science are paramount in the quality and utility of risk assessment. The National Research Council and EPA have previously described the major steps in risk assessment, including hazard identification, dose≠response assess- ment, exposure assessment, and risk characterization (NRC 1983, 1994, 2009). Although exposure assessment is often described as perhaps the most challeng- ing component of risk assessment, prior National Research Council reports on risk assessment have made limited recommendations for improving the quality of exposure data or the utility of exposure assessment for quantitative risk as- sessment. Although those steps are important, a strategy for improving the qual- ity and quantity of exposure data is needed to reduce uncertainties stemming from the exposure-assessment component of risk assessment. A recent EPA Science Advisory Board panel provided nearly 100 recom- mendations for improving guidance in ecologic risk assessment (EPA SAB 2007; Dale et al. 2008) and suggested that further consideration was needed for assessing simultaneous exposure to multiple stressors, assessing spatial and temporal variation in exposures, and addressing uncertainties in exposure mod- els. Exposure assessment poses numerous challenges for risk assessment. Ex- posures change, so a risk assessment that uses data that are available today may no longer be valid months or years from now; this is especially true for chemi- cals newly entering the market, for which use and exposure patterns have not yet fully emerged. Important exposure pathways may be missed, and this can lead to underestimation of overall exposure or neglect of highly exposed populations. Risk assessments and exposure assessments tend to focus on one chemical at a time and potentially miss interactive effects that could influence both exposure and risk. Data needed for exposure assessment, such as data on chemical sales and product ingredients, may be proprietary and not publicly available because of trade-secrecy protections.
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Applications of Exposure Science 79 and the community is essential. Ideally, it would be conducted routinely on first- responder personnel, in advance of a disaster, to measure toxicants associated with their jobs and thus provide a baseline measure. However, biomonitoring cannot take the place of environmental sensors for real-time measurement of hazardous agents. REFERENCES Alberti, M., J. M. Marzluff, E. Shulenberger, G. Bradley, C. Ryan, and C. Zumbrunnen. 2003. Integrating humans into ecology: Opportunities and challenges for study- ing urban ecosystems. Bioscience 53(12):1169-1179. Allan, B.F., H.P. Dutra, L.S. Goessling, K. Barnett, J.M. Chase, R.J. Marquis, G. Pang, G.A. Storch, R.E. Thach, and J.L. Orrock. 2010. Invasive honeysuckle eradica- tion reduces tick-borne disease risk by altering host dynamics. Proc. Natl. Acad. Sci. USA 107(43):18523-18527. Almanza, E., M. Jerrett, G. Dunton, E. Seto, and M. Pentz. 2011. Green Spaces in Healthy Places: Objective Data Demonstrates an Association between Green- ness and Momentary Measures of Physical Activity in Children. Presentation at Active Living Research (ALR) Conference, February 22-24 2011, San Diego, CA [online]. Available: http://www.activelivingresearch.org/files/2011_GPS_ Almanza.pdf [accessed Dec. 15, 2011]. Andersen, M.E., H.J. Clewell, III, E. Bermudez, D.E. Dodd, G.A. Wilson, J.L. Campbell, and R.S. Thomas. 2010. Formaldehyde: Integrating dosimetry, cytotoxicity, and genomics to understand dose-dependent transitions for an endogenous compound. Toxicol. Sci. 118(2):716-731. Anderson, D.M., P.M. Glibert, and J.M. Burkholder. 2002. Harmful algal blooms and eutrophication: Nutrient sources, composition, and consequences. Estuaries 25(4b):704-726. Barr, D.B., R.Y. Wang, and L.L. Needham. 2005. Biologic monitoring of exposure to environmental chemicals throughout the life stages: Requirements and issues for consideration for the National Children's Study. Environ. Health Perspect. 13(8):1083-1091. Bell, M.L., K. Ebisu, and R.D. Peng. 2011. Community-level spatial heterogeneity of chemical constituent levels of fine particulates and implications for epidemiological research. J. Expo. Sci. Environ. Epidemiol. 21(4):372-384. Benson, P. 1989. Caline4 - A Dispersion Model for Predicting Air Pollution Concentra- tion Near Roadways. Report No. FHWA/CA/TL-84/15. California Department of Transportation, Sacramento, CA [online]. Available: http://www.weblakes. com/products/calroads/resources/docs/CALINE4.pdf [accessed May 9, 2012]. Bhatia, R. 2007. Protecting health using an environmental impact assessment: A case study of San Francisco land use decision-making. Am. J. Public Health 97(3):406-413. Bhatia, R., and T. Rivard. 2008. Assessment and Mitigation of Air Pollutant Health Ef- fects from Intra-urban Roadways: Guidance for Land Use Planning and Envi- ronmental Review. San Francisco, CA: San Francisco Department of Public Health [online]. Available: http://www.sfphes.org/publications/Mitigating_Roa dway_AQLU_Conflicts.pdf [accessed Dec. 14, 2011].
OCR for page 80
80 Exposure Science in the 21st Century: A Vision and A Strategy Bhatia, R., and E. Seto. 2011. Quantitative estimation in health impact assessment: Op- portunities and challenges. Environ. Impact Assess. Rev. 31(3):301-309. Bhatia, R., and A. Wernham. 2008. Integrating human health into environmental impact assessment: An unrealized opportunity for environmental health and justice. Environ. Health Perspect. 116(8):991-1000. Bongers, S., N.A.H. Janssen, B. Reiss, L. Grievink, E. Lebret, and H. Kromhout. 2008. Challenges of exposure assessment for health studies in the aftermath of chemical incidents and disasters. J. Expo. Sci. Environ. Epidemiol. 18(4):341- 359. Bowling, A.M., C.R. Hammerschmidt, and J.T. Oris. 2011. Necrophagy by a benthic omnivore influences biomagnification of methylmercury in fish. Aquat. Toxi- col. 102(3-4):134-141. Bradley, C.A., and S. Altizer. 2006. Urbanization and the ecology of wildlife diseases. Trends Ecol. Evol. 22(2):95-102. Bradman, A., and R.M. Whyatt. 2005. Characterizing exposures to nonpersistent pesticides during pregnancy and early childhood in the National Children's Study: A review of monitoring and measurement methodologies. Environ. Health Perspect. 113(8):1092-1099. Brecken-Folse, J.A., F.L. Mayer, L.E. Pedigo, and L.L. Marking. 1994. Acute toxicity of 4-nitrophenol, 2,4-dinitrophenol, terbufos and trichlorfon to grass shrimp (Pa- laemonetes Spp) and sheepshead minnows (Cyprinodon variegatus) as affected by salinity and temperature. Environ. Toxicol. Chem. 13(1):67-77. Breslow, N.E., T. Lumley, C.M. Ballantyne, L.E. Chambless, and M. Kulich. 2009. Us- ing the whole cohort in the analysis of case-cohort data. Am. J. Epidemiol. 169(11):1398-1405. Brown, P., J.G. Brody, R. Morello-Frosch, J. Tovar, A.R. Zota, and R.A. Rudel. 2012. Measuring the success of community science: The Northern California House- hold Exposure Study. Environ. Health Perspect. 120(3):326-331. Brussard, P.F, M.J. Reed, and T.C. Richard. 1998. Ecosystem management: What is it really? Landscape Urban Plan. 40:9-20. Carroll, R.J., D. Ruppert, L.A. Stefanski, and C. Crainiceanu. 2006. Measurement Error in Nonlinear Models: A Modern Perspective, 2nd Ed. Boca Raton, FL: Chap- man & Hall/CRC. CDC (Centers for Disease Control and Prevention). 2011. Fourth National Report on Hu- man Exposure to Environmental Chemicals. U.S. Department of Health and Hu- man Services, Centers for Disease Control and Prevention, Atlanta, GA [online]. Available: http://www.cdc.gov/exposurereport/ [accessed Dec. 12, 2011]. CDPH (California Department of Public Health). 2010a. Public Drinking Water System [online]. Available: http://www.cdph.ca.gov/certlic/drinkingwater/Pages/default. aspx [accessed Jan. 3, 2012]. CDPH (California Department of Public Health). 2010b. Implementation of the California Environmental Contaminant Biomonitoring Program. Report to the California Legislature. California Department of Public Health in Collaboration with Cali- fornia Environmental Protection Agency's Office of Health Hazard Assessment and Department of Toxic Substances Control, January 2010 [online]. Available: http://oehha.ca.gov/multimedia/biomon/pdf/CECBPLegReport.pdf [accessed Dec. 6, 2011]. Chandra, S., H. Segale, and S. Adler. 2009. Lake Tahoe Species Introduction Timeline. Tahoe Environmental Research Center [online]. Available: http://terc.ucdavis.
OCR for page 81
Applications of Exposure Science 81 edu/education_outreach/educationprograms/TIC_InvasiveSpeciesTimeline.pdf [ac- cessed 17 May, 2012]. Cherkasov, A.S., P.K. Biswas, D.M. Ridings, A.H. Ringwood, and I.M. Sokolova. 2006. Effects of acclimation temperature and cadmium exposure on cellular energy budgets in the marine mollusk Crassostrea virginica: Linking cellular and mi- tochondrial responses. J. Exp. Biol. 209(7):1274-1284. Cherkasov, A.S., S. Grewal, and I.M. Sokolova. 2007. Combined effects of temperature and cadmium exposure on haemocyte apoptosis and cadmium accumulation in the eastern oyster Crassostrea virginica (Gmelin). J. Therm. Biol. 32(3):162- 170. Chow, J.C., J.P. Engelbrecht, N.C. Freeman, J.H. Hashim, M. Jantunen, J.P. Michaud, S. Saenz de Tejada, J.G. Watson, F. Wei, W.E. Wilson, M. Yasuno, and T. Zhu. 2002. Chapter one: Exposure measurements. Chemosphere 49(9):873-901. Cloern, J.E. 2001. Our evolving conceptual model of the coastal eutrophication problem. Mar. Ecol. Prog. Ser. 210:223-253. Cohen Hubal, E.A., A.M. Richard, I. Shah, J. Gallagher, R. Kavlock, J. Blancato, and S.W. Edwards. 2010. Exposure science and the U.S. EPA National Center for Computational Toxicology. J. Expo. Sci. Environ. Epidemiol. 20(3):231-236. Cohen Hubal, E.A., D.B. Barr, H.M. Koch, and T. Bahadori. 2011. The promise of expo- sure science. J. Expo. Sci. Environ. Epidemiol. 21(2):121-122. Dahmann, N., J. Wolch, P. Joassart-Marcelli, K. Reynolds, and M. Jerrett. 2009. The active city? Disparities in provision of urban public recreation resources. Health Place 16(3):431-445. Dale, V., G.R. Biddinger, M.C. Newman, J.T. Oris, G.W. Suter, T. Thompson, T.M. Armitage, J.L. Meyer, R.M. Allen-King, G.A. Burton, P.M. Chapman, L.L. Conquest, I.J. Fernandez, W.G. Landis, L.L. Master, W.J. Mitsch, T.C. Muel- ler, C.F. Rabeni, A.D. Rodewald, J.G. Sanders, and I.L. van Heerden. 2008. Enhancing the ecological risk assessment process. Integr. Environ. Assess. Manag. 4(3):306-313. Dean Runyan Associates. 2009. The Economic Significance of Travel the North Lake Tahoe Area: 2003-2008 Detailed Visitor Impact Estimates. Prepared for North Lake Tahoe Resort Association, Tahoe City, CA, by Dean Runyan Associates, Portland, OR [online]. Available: http://www.deanrunyan.com/doc_library/Fin alReportCA.pdf [accessed May 21, 2012]. de Hartog, J.J., H. Boogaard, H. Nijland, and G. Hoek. 2010. Do the health benefits of cycling outweigh the risks? Environ. Health Perspect. 118(8):1109-1116. de Nazelle, A., M.J. Nieuwenhuijsen, J.M. Anto, M. Brauer, D. Briggs, C. Braun- Fahrlander, N. Cavill, A.R. Cooper, H. Desqueyroux, S. Fruin, G. Hoek, L.I. Panis, N. Janssen, M. Jerrett, M. Joffe, Z. Jovanovic Andersen, E. van Kempen, S. Kingham, N. Kubesch;, K.M. Leyden, J.D. Marshall, J. Matamala, G. Mel- lios, M. Mendez, H. Nassif, D. Oglivie, R. Peiro, K. Perez, A. Rabl, M. Raget- tli, D. Rodriguez, D. Rojas, P. Ruiz, J.F. Sallis, J. Terwoert, J.F. Toussaint, J. Tuomisto, M. Zuurbier, and E. Lebret. 2011. Improving health through policies that promote active travel: A review of evidence to support integrated health impact assessment. Environ. Int. 37(4):766-777. Dix, D.J., K.A. Houck, M.T. Martin, A.M. Richard, R.W. Setzer, and R.J. Kavlock. 2007. The ToxCast program for prioritizing toxicity testing of environmental chemi- cals. Toxicol. Sci. 95(1):5-12. Dobson, A., and J. Foufopoulos. 2001. Emerging infectious pathogens of wildlife. Philos. Trans. R. Soc. London B 356(1411):1001-1012.
OCR for page 82
82 Exposure Science in the 21st Century: A Vision and A Strategy Dominici, F., J.I. Levy, and T.A. Louis. 2005. Methodological challenges and contribu- tions in disaster epidemiology. Epidemiol. Rev. 27(1):9-12. Downs, T.J., Y. Ogneva-Himmelberger, O. Aupont , Y. Wang, A. Raj, P. Zimmerman, R. Goble, O. Taylor, L. Churchill, C. Lemay, T. McLaughlin, and M. Felice. 2010. Vulnerability-based spatial sampling stratification for the National Children's Study, Worcester County, Massachusetts: Capturing health-relevant environ- mental and sociodemographic variability. Environ. Health Perspect. 118(9):1318-1325. Drevnick, P.E., A. Shinneman, C. Lamborg, D.R. Engstrom, M. Bothner, and J.T. Oris. 2010. Mercury flux to sediments of Lake Tahoe, California-Nevada. Water Air Soil Pollut. 210 (1-4):399-407. Dwyer, J.F., E.G. McPherson, H.W. Schroeder, and A. Rowntree. 1992. Assessing the benefits and costs of the urban forest. J. Arborculture 18(5):227-234. Edelman, P., J. Osterloh, J. Pirkle, S.P. Caudill, J. Grainger, R. Jones, B. Blount, A. Cala- fat, W. Turner, D. Feldman, S. Baron, B. Bernard, D.B. Lushniak, K. Kelly, and D. Prezant. 2003. Biomonitoring of chemical exposure among New York City firefighters responding to the World Trade Center fire and collapse. Envi- ron. Health Perspect. 111(16):1906-1911. Eiswerth, M.E., S.G. Donaldson, and W.S. Johnson. 2000. Potential environmental im- pacts and economic damages of Eurasian watermilfoil (Myriophyllum spica- tum) in western Nevada and northeastern California. Weed Technol. 14(3):511- 518. EPA (U.S. Environmental Protection Agency). 1992. Guidelines for Exposure Assess- ment. EPA600Z-92/001. Risk Assessment Forum, U.S. Environmental Protec- tion Agency, Washington, DC. EPA (U.S. Environmental Protection Agency). 2000. Guidance for Assessing Chemical Contaminant Data for Use in Fish Advisories. Volume 2: Risk Assessment and Fish Consumption Limits -Third Edition. EPA 823-B-00-008. Office of Science and Technology, Office of Water, U.S. Environmental Protection Agency, Washington, DC [online]. Available: http://water.epa.gov/scitech/swguidance/ fishshellfish/techguidance/risk/upload/2009_04_23_fish_advice_volume2_v2cov er.pdf [accessed May 9, 2012]. EPA (U.S. Environmental Protection Agency). 2002. Exposure and Human Health Evaluation of Airborne Pollution from the World Trade Center Disaster. Exter- nal Review Draft. EPA/600/P-2/002A. National Center for Environmental As- sessment, Office of Research and Development, U.S. Environmental Protection Agency, Washington, DC [online]. Available: http://nycosh.org/uploads/listit/ id21/WTC_FINAL5.pdf [accessed Jan. 4, 2012]. EPA (U.S. Environmental Protection Agency). 2003. EPA's Response to the World Trade Center Collapse: Challenges, Successes, and Areas for Improvement. Report No. 2003-P-00012. Office of Inspector General, U.S. Environmental Protection Agency, Washington, DC. August 21, 2003 [online]. Available: http://www.epa.gov/oig/reports/2003/WTC_report_20030821.pdf [accessed Dec. 12, 2011]. EPASAB (U.S. Environmental Protection Agency Science Advisory Board). 2007. Ad- vice to EPA on Advancing the Science and Application of Ecological Risk As- sessment in Environmental Decision Making. EPA-SAB-08-002. Science Ad- visory Board, U.S. Environmental Protection Agency, Washington, DC [online]. Available: http://yosemite.epa.gov/sab/sabproduct.nsf/7140DC0E56E B148A8525737900043063/$File/sab-08-002.pdf [accessed Dec. 14, 2011].
OCR for page 83
Applications of Exposure Science 83 Faeth, S.H., P.S. Warren, E. Shochat, and W.A. Marussich. 2005. Trophic dynamics in urban communities. Bioscience 55(5):399-407. Filser, J., H. Koehler, A. Ruf, J. Rombke, A. Prinzing, and M. Schaefer. 2008. Ecological theory meets soil ecotoxicology: Challenge and chance. Basic Appl. Ecol. 9(4):346-355. Fitzpatrick, K., and M. LaGory. 2011. Unhealthy Cities: Poverty, Race, and Place in America, 2nd Ed. New York: Routledge. GAO (U.S. Government Accountability Office). 2007. World Trade Center: EPA's Most Recent Test and Clean Program Raises Concerns That Need to Be Addressed to Better Prepare for Indoor Contamination Following Disasters. GAO 07-1091. Washington, DC: U.S. Government Accountability Office. September 2007 [online]. Available: http://www.gao.gov/new.items/d071091.pdf [accessed Dec. 12, 2011]. GAO (General Accountability Office). 2009. Chemical Regulation: Options for Enhanc- ing the Effectiveness of the Toxic Substances Control Act. GAO-09-428T. Washington, DC: U.S. Government Accountability Office [online]. Available: http://www.gao.gov/new.items/d09428t.pdf [accessed May 9, 2011]. GarcŪa-Berthou, E. 2002. Ontogenetic diet shifts and interrupted piscivory in introduced largemouth bass (Micropterus salmoides). Int. Rev. Hydrobiol. 87(4):353-363. Gehrt, S.D. 2010. The urban ecosystem. Pp. 3-11 in Urban Carnivores: Ecology, Conflict, and Conservation, S.D. Gehrt, S.P.D. Riley, and B.L. Cypher, eds. Baltimore, MD: The Johns Hopkins University Press. Georgopoulos, P.G., A.F. Sasso, S.S. Isukapalli, P.J. Lioy, D.A. Vallero, M. Okino, and L. Reiter. 2009. Reconstructing population exposures to environmental chemi- cals from biomarkers: Challenges and opportunities. J. Expo. Sci. Environ. Epidemiol. 19(2):149-171. Gevertz, A.K., A.J. Tucker, A.M. Bowling, C.E. Williamson, and J.T. Oris. 2012. Differ- ential tolerance of native and non-native fish exposed to ultraviolet radiation and fluoranthene in Lake Tahoe (CA/NV). Environ. Toxicol. Chem. 31(5): 1129-1135. Gilliland, F.D., Y.F. Li, A. Saxon, and D. Diaz-Sanchez. 2004. Effect of glutathione-S- transferase M1 and P1 genotypes on xenobiotic enhancement of allergic re- sponses: Randomised, placebo-controlled crossover study. Lancet 363(9403): 119-125. Gilliland, F., E. Avol, P. Kinney, M. Jerrett, T. Dvonch, F. Lurmann, T. Buckley, P. Breysse, G. Keeler, T. de Villiers, and R. McConnell. 2005. Air pollution expo- sure assessment for epidemiologic studies of pregnant women and children: Lessons learned from the Centers for Children's Environmental Health and Disease Prevention Research. Environ. Health Perspect. 113(10):1447-1454. Goldman, C.R. 2000. Four decades of change in two subalpine lakes. Verh. Internat. Verein. Limnol. 27(Pt. 1):7-26. Greenland, S., and J.M. Robins. 2000. Epidemiology, justice, and the probability of cau- sation. Jurimetrics 40:321-340. Grumbine, R.E. 1994. What is ecosystem management? Conserv. Biol. 8(1):27-38. Gupta, P.K., B.S. Khangarot, and V.S. Durve. 1981. The temperature-dependence of the acute toxicity of copper to a fresh-water pond snail, Viviparus bengalensis L. Hydrobiologia 83(3):461-464. Hammerschmidt, C., and W. Fitzgerald. 2006. Bioaccumulation and trophic transfer of methylmercury in the Long Island Sound. Arch. Environ. Contam. Toxicol. 51(3):416-424.
OCR for page 84
84 Exposure Science in the 21st Century: A Vision and A Strategy Hankey, S., J.D. Marshall, and M. Brauer. 2012. Health impacts of the built environment: Within-urban variability in physical inactivity, air pollution, and ischemic heart disease mortality. Environ. Health Perspect. 120(2):247-253. HEI (Health Effects Institute). 2010. Traffic-Related Air Pollution: A Critical Review of the Literature on Emissions, Exposure, and Health Effects. Special Report 17. Boston, MA: Health Effects Institute [online]. Available: http://pubs.health effects.org/view.php?id=334 [accessed Dec. 12, 2011]. Hirschfeld, S., D. Songco, B.S. Kramer, and A.E. Guttmacher. 2011. National Children's Study: Update in 2010. Mt Sinai J. Med. 78(1):119-125. Hoffman, F.O., A.J. Ruttenber, A.I. Apostoaei, R.J. Carroll, and S. Greenland. 2007. The Hanford Thyroid Disease Study: An alternative view of the findings. Health Phys. 92(2):99-111. IOM (Institute of Medicine). 2000. Protecting Those Who Serve: Strategies to Protect the Health of Deployed U.S. Forces. Washington, DC: National Academy Press. IOM (Institute of Medicine). 2008. Improving the Presumptive Disability Decision- Making Process for Veterans, J.M. Samet, and C.C. Bodurow, eds. Washing- ton, DC: National Academies Press. Jassby, A.D., J.E. Reuter, and C.R. Goldman. 1996. Determining long-term water quality in the presence of climate variability: Lake Tahoe (USA). Can. J. Fish. Sci. 60(12):1452-1461. Jerrett, M., R.T. Burnett, R. Ma, C.A. Pope, D. Krewski, K.B. Newbold, G. Thurston, Y. Shi, N. Finkelstein, E.E. Calle, and M.J. Thun. 2005. Spatial analysis of air pol- lution and mortality in Los Angeles. Epidemiology 16(6):727-736. Jerrett, M., J. Su, J. Apte, and B. Beckerman. 2011. Estimates of population exposure to traffic-related air pollution in Beijing, China and New Delhi, India: Extending exposure analyses report in HEI Special Report 17, Traffic-Related Air Pollu- tion: Critical Review of the Literature on Emissions, Exposure, and Health Ef- fects, November 5, 2010. Boston, MA: Health Effects Institute [online]. Avail- able: http://www.healtheffects.org/International/Jerrett_Asia_Traffic_Exposure. pdf [accessed Dec. 10, 2011]. Kamerath, M., S. Chandra, and B.C. Allen. 2008. Distribution and impacts of war water invasive fish in Lake Tahoe, USA. Aquat. Invasions 3(1):35-41. Kearney, A.R., G.A. Bradley, C.H. Petrich, R. Kaplan, S. Kaplan, and D. Simpson- Colbank. 2008. Public perception as support for scenic quality regulation in a nationally treasured landscape. Landscape Urban Plan. 87(2):117-128. Kemp, W.M., W.R. Boynton, J.E. Adolf, D.F. Boesch, W.C. Boicourt, G. Brush, J.C. Cornwell, T.R. Fisher, P.M. Glibert, J.D. Hagy, L.W. Harding, E.D. Houde, D.G. Kimmel, W.D. Miller, R.I.E. Newell, M.R. Roman, E.M. Smith, and J.C. Stevenson. 2005. Eutrophication of Chesapeake Bay: Historical trends and eco- logical interactions. Mar. Ecol. Prog. Ser. 303:1-29. Khan, M.A., S.A. Ahmed, B. Catalin, A. Khodadoust, O. Ajayi, and M. Vaughn. 2006. Effect of temperature on heavy metal toxicity to juvenile crayfish, Orconectes immunis (Hagen). Environ. Toxicol. 21(5):513-520. Kopecky, K.J., S. Davis, T.E. Hamilton, M.S. Saporito, and L.E. Onstad. 2004. Estimation of thyroid radiation doses for the Hanford thyroid disease study: Results and implications for statistical power of the epidemiological analyses. Health Phys. 87(1):15-32. Kopecky, K.J., L. Onstad, T.E. Hamilton, and S. Davis. 2005. Thyroid ultrasound abnormalities in persons exposed during childhood to 131I from the Hanford nuclear site. Thyroid 15(6):604-613.
OCR for page 85
Applications of Exposure Science 85 KŁnzli, N., R. McConnell, D. Bates, T. Bastain, A. Hricko, F. Lurmann, E. Avol, F. Gilliland, and J. Peters. 2003. Breathless in Los Angeles: The exhausting search for clean air. Am. J. Public Health 93(9):1494-1499. Lahr, J., and L. Kooistra. 2010. Environmental risk mapping of pollutants: State of the art and communication aspects. Sci. Total Environ. 408(18):3899-3907. Landrigan, P.J., L. Trasande, L.E. Thorpe, C. Gwynn, P.J. Lioy, M.E. D'Alton, H.S. Lip- kind, J. Swanson, P.D. Wadhwa, E.B. Clark, V.A. Rauh, F.P. Perera, and E. Susser. 2006. The National Children's Study: A 21-year prospective study of 100,000 American children. Pediatrics 118(5):2173-2186. Lioy, P.J. 2010a. Dust: The Inside Story of its Role in the Septemer 11th Aftermath. Lanham, MD: Rowman & Littlefield Publishers. Lioy, P.J. 2010b. Exposure science: A view of the past and milestones for the future. Environ Health Perspect. 118(8):1081-1090. Lioy, P.J., and M. Gochfeld. 2002. Lessons learned on environmental, occupational, and residential exposures from the attack on the World Trade Center. Am. J. Ind. Med. 42(6):560-565. Lioy, P.J., S.S. Isukapalli, L. Trasande, L. Thorpe, M. Dellarco, C. Weisel, P.G. Georgopoulos, C. Yung, M. Brown, S. Alimokhtari, and P.J. Landrigan. 2009. Using national and local extant data to characterize environmental exposures in the National Children's Study: Queens County, New York. Environ Health Perspect. 117(10):1494-1504. Liu, Y., C.J. Paciorek, and P. Koutrakis. 2009. Estimating regional spatial and temporal variability of PM(2.5) concentrations using satellite data, meteorology, and land use information. Environ. Health Perspect. 117(6):886-892. Logue, J.M., M.J. Small, D. Stern, J. Maranche, and A.L. Robinson. 2010. Spatial variation in ambient air toxics concentrations and health risks between industrial-influenced, urban, and rural sites. J. Air Waste Manag. Assoc. 60(3): 271-286. Lorber, M., H. Gibb, L. Grant, J. Pinto, J. Pleil, and D. Cleverly. 2007. Assessment of inhalation exposures and potential health risks to the general population that resulted from the collapse of the World Trade Center towers. Risk Anal. 27(5):1203-1221. Maas, J., R.A. Verheij, P.P. Groenewegen, S. de Vries, and P. Spreeuwenberg. 2006. Green space, urbanity, and health: How strong is the relation? J. Epidemiol. Community Health 60(7):587-592. Maller, C., M. Townsend, A. Pryor, P. Brown, and L. St Leger. 2006. Healthy nature healthy people: 'Contact with nature' as an upstream health promotion interven- tion for populations. Health Promot. Int. 21(1):45-54. Marentette, J.R., K.L. Gooderham, M.E. McMaster, T. Ng, J.L. Parrott, J.Y. Wilson, C.M. Wood, and M. Balshine. 2010. Signatures of contamination in invasive round gobies (Neogobius melanostomus): A double strike for ecosystem health? Ecotoxicol. Environ. Saf. 73(7):1755-1764. Marshall, J.D., R.D. Wilson, K.L. Meyer, S.K. Rajangam, N.C. McDonald, and E.J. Wil- son. 2010. Vehicle emissions during children's school commuting: Impacts of education policy. Environ. Sci. Technol. 44(5):1537-1543. McPherson, E.G., D. Nowak, G. Heisler, S. Grimmond, C. Souch, R. Grant, and R. Rowntree. 1997. Quantifying urban forest structure, function, and value: The Chicago Urban Forest Climate Project. Urban Ecosystems 1(1):49-61.
OCR for page 86
86 Exposure Science in the 21st Century: A Vision and A Strategy Meironyte, D., K. Noren, and A. Bergman. 1999. Analysis of polybrominated diphenyl ethers in Swedish human milk. A time-related trend study, 1972-1997. J. Toxi- col. Environ. Health 58(6):329-341. Melia, S., G. Parkhurst, and H. Barton. 2011. The paradox of intensification. Transport. Policy 18(1):46-52. Miller, K.A., D.S. Siscovick, L. Sheppard, K. Shepherd, J.H. Sullivan, G.L. Anderson, and J.D. Kaufman. 2007. Long-term exposure to air pollution and incidence of cardiovascular events in women. N. Engl. J. Med. 356(5):447-458. Minckley, W.L., and J.E. Craddock. 1961. Active predation of crayfish on fishes. Prog. Fish Cult. 23(3):120-123. Mitchell, R., and F. Popham. 2008. Effect of exposure to natural environment on health inequalities: An observational population study. Lancet 372(9650):1655-1660. Momot, W.T., H. Gowing, and P.D. Jones. 1978. The dynamics of crayfish and their role in ecosystems. Am. Midl. Nat. 99(1):10-35. NCRP (National Council on Radiation Protection and Measurements). 2008. Uncertain- ties in the Measurement and Dosimetry of External Radiation. Report No. 158. Bethesda, MD: National Council on Radiation Protection and Measurements. NCRP (National Council on Radiation Protection and Measurements). 2010a. Radiation Dose Reconstruction: Principles and Practices. Report No. 163. Bethesda, MD: National Council on Radiation Protection and Measurements. NCRP (National Council on Radiation Protection and Measurements). 2010b. Uncertain- ties in Internal Radiation Dose Assessment. Report No. 164. Bethesda, MD: National Council on Radiation Protection and Measurements. Needham, L.L., H. Ozkaynak, R.M. Whyatt, D.B. Barr, R.Y. Wang, L. Naeher, G. Ak- land, T. Bahadori, A. Bradman, R. Fortmann, L.J. Liu, M. Morandi, M.K. O'Rourke, K. Thomas, J. Quackenboss, P.B. Ryan, and V. Zartarian. 2005. Exposure assessment in the National Children's Study: Introduction. Environ. Health Perspect. 113(8):1076-1082. NIH (National Institutes of Health). 1985. Report of the National Institutes of Health Ad Hoc Working Group to Develop Radioepidemiologic Tables. NIH Publication No. 85-2748. U.S. Department of Health and Human Services, Public Health Service, National Institutes of Health, Washington, DC [online]. Available: http://www.cdc.gov/niosh/ocas/pdfs/42cfr81/71.pdf [accessed Dec. 13, 2011]. NIOSH (National Institute for Occupational Safety and Health). 2011. Interactive Ra- dioEpidemiological Program. NIOSH-IREP v.5.6 [online]. Available: https:// www.niosh-irep.com/irep_niosh/ [accessed Oct. 20, 2011]. NRC (National Research Council). 1983. Risk Assessment in the Federal Government: Managing the Process. Washington, DC: National Academy Press. NRC (National Research Council). 1984. Assigned Share for Radiation as a Cause of Cancer: Review of Radioepidemiological Tables Assigning Probabilities of Causation: Final Report. Washington, DC: National Academy Press. NRC (National Research Council). 1994. Science and Judgment in Risk Assessment. Washington, DC: National Academy Press. NRC (National Research Council). 1999. Strategies to Protect the Health of Deployed U.S. Forces: Force Protection and Decontamination. Washington, DC: National Academy Press. NRC (National Research Council). 2000a. Strategies to Protect the Health of Deployed U.S. Forces: Analytical Framework for Assessing Risks. Washington, DC: Na- tional Academy Press.
OCR for page 87
Applications of Exposure Science 87 NRC (National Research Council). 2000b. Strategies to Protect the Health of Deployed U.S. Forces: Detecting, Characterizing and Documenting Exposures. Washing- ton, DC: National Academy Press. NRC (National Research Council). 2007. Toxicity Testing in the 21st Century: A Vision and A Strategy. Washington, DC: National Academies Press. NRC (National Research Council). 2009. Science and Decisions: Advancing Risk As- sessment. Washington, DC: National Academies Press. NRC (National Research Council). 2011. Improving Health in the United States: The Role of Health Impact Assessment. Washington, DC: National Academies Press. NRC/IOM (National Research Council and Institute of Medicine). 2008. The National Children's Study Research Plan: A Review. Washington, DC: National Academies Press. O'Fallon, L.R., and A. Dearry. 2002. Community-based participatory research as a tool to advance environmental health sciences. Environ. Health Perspect. 110(suppl. 2):155-159. Oris, J.T., S. Guttman, A.J. Bailer, J. Reuter, and G. Miller. 2004. Multi-Level Indicators of Ecosystem Integrity in Alpine Lakes of the Sierra Nevada (EPA No. R827643). U.S. EPA Final Project Report, Ecological Indicators Program, 99- NCERQA-E1[online]. Available: http://zoology.muohio.edu/oris/tahoe/SierraFi nalReport.htm [accessed May 21, 2012]. Osterauer, R., and H. Koehler. 2008. Temperature-dependent effects of the pesticides thiacloprid and diazinon on the embryonic development of zebrafish (Danio re- rio). Aquat. Toxicol. 86(4):485-494. ÷zkaynak, H., R.M. Whyatt, L.L. Needham, G. Akland, and J. Quackenboss. 2005. Exposure assessment implications for the design and implementation of the National Children's Study. Environ. Health Perspect. 113(8):1108-1115. Paerl, H.W. 1997. Coastal eutrophication and harmful algal blooms: Importance of at- mospheric deposition and groundwater as ''new'' nitrogen and other nutrient sources. Limnol. Oceanogr. 42(5):1154-1165. Patel, C.J., and A.J. Butte. 2010. Predicting environmental chemical factors associated with disease-related gene expression data. BMC Med Genomics. 3:17. Patel, C.J., J. Bhattacharya, and A.J. Butte. 2010. An environment-wide association study (EWAS) on Type 2 Diabetes Mellitus. PLoS ONE 5(5):e10746. Pickett, S.T.A., M.L. Cadenasso, J.M. Grove, C.H. Nilon, R.V. Pouyat, W.C. Zipperer, and R. Constanza. 2001. Urban ecological systems: Linking terrestrial ecologi- cal, physical, and socioeconomic components of metropolitan areas. Annu. Rev. Ecol. Syst. 32:127-157. PLOTS (Public Laboratory for Open Source Technology). 2012. About PLOTS [online]. Available: http://publiclaboratory.org/about [accessed March 29, 2012]. Rodes, C.E., E.D. Pellizzari, M.J. Dellarco, M.D. Erickson, D.A. Vallero, D.B. Reissman, P.J. Lioy, M. Lippmann, T.A. Burke, and B.D. Goldstein. 2008. ISEA2007 panel: Integration of better exposure characterizations into disaster preparedness for responders and the public. J. Expo. Sci. Environ. Epidemiol. 18(6):541-550. Rose, K.C., C.E. Williamson, S.G. Schladow, M. Winder, and J.T. Oris. 2009. Patterns of spatial and temporal variability of UV transparency in Lake Tahoe, California- Nevada. J. Geophys. Res. Biogeosci. 114:G00D03. Schecter, A., M. Pavuk, O. Pšpke, J.J. Ryan, L. Birnbaum, and R. Rosen. 2003. Polybrominated diphenyl ethers (PBDEs) in U.S. mother's milk. Environ. Health Perspect. 111(14):1723-1729.
OCR for page 88
88 Exposure Science in the 21st Century: A Vision and A Strategy Shankardass, K., R. McConnell, M. Jerrett, J. Milam, J. Richardson, and K. Berhane. 2009. Parental stress increases the effect of traffic-related air pollution on childhood asthma incidence. Proc. Natl. Acad. Sci. USA 106(30):12406-12411. Sheppard, L., R.L. Prentice, and M.A. Rossing. 1996. Design considerations for estimation of exposure effects on disease risk, using aggregate data studies. Stat. Med. 15(17-18):1849-1858. Shipler, D.B. 1995. Science in a fishbowl: Public involvement in the Hanford Environmental Dose Reconstruction Project. Fedl. Fac. Environ. J. 6(3):97-108. Shipler, D.B., B.A. Napier, W.T. Farris, and M.D. Freshley. 1996. Hanford Environmental Dose Reconstruction Project--an overview. Health Phys. 71(4):532-544. Slikker, W., Jr., M.E. Andersen, M.S. Bogdanffy, J.S. Bus, S.D. Cohen, R.B. Conolly, R.M. David, N.G. Doerrer, D.C. Dorman, D.W. Gaylor, D. Hattis, J.M. Rogers, R. Woodrow Setzer, J.A. Swenberg, and K. Wallace. 2004. Dose-dependent transitions in mechanisms of toxicity. Toxicol. Appl. Pharmacol. 201(3):203- 225. Strauss, W.J., L. Ryan, M. Morara, N. Iroz-Elardo, M. Davis, M. Cupp, M.G. Nishioka, J. Quackenboss, W. Galke, H. Ozkaynak, and P. Scheidt. 2010. Improving cost- effectiveness of epidemiological studies via designed missingness strategies. Stat Med. 29(13):1377-1387. Su, J.G., M. Jerrett, A. deNazelle, and J. Wolch. 2011. Does exposure to air pollution in urban park shave socioeconomic, racial or ethnic gradients? Environ. Res. 11(3):319-328. Swift, T.J., J. Perez-Losada, S.G. Schladow, J.E. Reuter, A.D. Jassby, and C.R. Goldman. 2006. A mechanistic clarity model of lake waters: Linking suspended matter characteristics to clarity. Aquat. Sci. 68:1-15. Szaro, R.C., W.T. Sexton, and C.R. Malone. 1998. The emergence of ecosystem man- agement as a tool for meeting people's needs and sustaining ecosystems. Land- scape Urban Plan. 40(1-3):1-7. Szpiro, A.A., C.J. Paciorek, and L. Sheppard. 2011. Does more accurate exposure prediction necessarily improve health effect estimates? Epidemiology 22(5):680-685. Teeguarden, J.G., A.M. Calafat, X. Ye, D.R. Doerge, M.I. Churchwell, R. Gunawan, and M.K. Graham. 2011. Twenty-four hour human urine and serum profiles of bisphenol A during high-dietary exposure. Toxicol. Sci. 123(1):48-57. Thomas, D.C. 1988. Models for exposure-time-response relationships with applications to cancer epidemiology. Annu. Rev. Publ. Health 9:451-482. Thomas, D. 2010. Gene-environment-wide association studies: Emerging approaches. Nat. Rev. Genet. 11(4):259-272. Tucker, A.J., C.E. Williamson, K.C. Rose, J.T. Oris, S. Connelly, M.H. Olson, and D.L. Mitchell. 2010. Ultraviolet radiation affects invasibility of lake ecosystems by warmwater fish. Ecology 91(3): 882-890. Tucker, A.J., C.E. Williamson, and J.T. Oris. in press. Development and application of a UV attainment threshold for the prevention of warmwater aquatic invasive spe- cies. Biol. Invasions in press. Tulve, N.S., L.S. Sheldon, and R.C. Fortmann. 2010. Workshop on Optimizing Exposure Metrics for the National Children's Study: Summary of Workgroup Discus- sions and Recommendations. EPA/600/R-10/064. Office of Research and De- velopment, U.S. Environmental Protection Agency, Research Triangle Park, NC. June 2010 [online]. Available: http://oaspub.epa.gov/eims/eimscomm.get file?p_download_id=497487 [accessed Jan. 2, 2012].
OCR for page 89
Applications of Exposure Science 89 Wang, R. Y., L.L. Needham, and D.B. Barr. 2005. Effects of environmental agents on the attainment of puberty: Considerations when assessing exposure to environmental chemicals in the National Children's Study. Environ. Health Perspect. 113(8):1100-1107. Wiener, J.G., D.P. Krabbenhoft, G.H. Heinz, and A.M. Scheuhammer. 2002. Ecotoxicol- ogy of mercury. Pp. 409-463 in Handbook of Ecotoxicology, 2nd Ed., D.J. Hoffman, B.A. Rattner, G.A. Burton, and J. Cairns, eds. Boca Raton: Lewis. Wier, M., J. Weintraub, E. Humphreys, E. Seto, and R. Bhatia. 2009a. An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning. Accid. Anal. Prev. 41(1):137-145. Wier, M., C. Sciammas, E. Seto, R. Bhatia, and T. Rivard. 2009b. Health, traffic, and environmental justice: Collaborative research and community action in San Francisco, California. Am. J. Public Health 99(suppl. 3):S499-S504. Wolch, J., M. Jerrett, K. Reynolds, R. McConnell, R. Chang, N. Dahmann, K. Brady, F. Gilliland, J.G. Su, and K. Berhane. 2011. Childhood obesity and proximity to urban parks and recreational resources: A longitudinal cohort study. Health Place 17(1):207-214. Zablotska, L.B., J.P. Ashmore, and G.R. Howe. 2004. Analysis of mortality among Ca- nadian nuclear power industry workers after chronic low-dose exposure to ion- izing radiation. Radiat. Res. 161(6):633-641.