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Environmental Health Perspectives Supplements Volume 110, Number 1, February 2002
Assessing Exposure in Epidemiologic Studies to Disinfection By-Products in Drinking Water: Report from an International Workshop
Tye E. Arbuckle,1 Steve E. Hrudey,2 Stuart W. Krasner,3 Jay R. Nuckols,4 Susan D. Richardson,5 Philip Singer,6 Pauline Mendola,7 Linda Dodds,8 Clifford Weisel,9 David L. Ashley,10 Kenneth L. Froese,2 Rex A. Pegram,7 Irvin R. Schultz,11 John Reif,4 Annette M. Bachand,4 Frank M. Benoit,12 Michele Lynberg,13 Charles Poole,14 and Kirsten Waller15
1Bureau of Reproductive and Child Health, Health Canada, Ottawa, Ontario, Canada; 2Department of Public Health Sciences, University of Alberta, Edmonton, Alberta, Canada; 3Metropolitan Water District of Southern California, La Verne, California, USA; 4Department of Environmental Health, Colorado State University, Fort Collins, Colorado, USA; 5National Exposure Research Laboratory, U.S. Environmental Protection Agency, Athens, Georgia, USA; 6Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina, USA; 7National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA; 8Departments of Obstetrics, and Gynecology and Pediatrics, Dalhousie University, Halifax, Nova Scotia, Canada; 9Environmental and Occupational Health Sciences Institute, Department of Obstetrics and Gynecology and Department of Pediatrics, University of Medicine and Dentistry of New Jersey, Piscataway, New Jersey, USA; 10Air Toxicants Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA; 11Battelle Pacific Northwest National Laboratory, Richland, Washington, USA; 12Environmental Health Sciences Bureau, Health Canada, Ottawa, Ontario, Canada; 13Division of Environmental Hazards and Health Effects, Centers for Disease Control and Prevention, Atlanta, Georgia, USA; 14Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA; 15Sequoia Foundation, Frederick, Maryland, USA
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Abstract
The inability to accurately assess exposure has been one of the major shortcomings of epidemiologic studies of disinfection by-products (DBPs) in drinking water. A number of contributing factors include a) limited information on the identity, occurrence, toxicity, and pharmacokinetics of the many DBPs that can be formed from chlorine, chloramine, ozone, and chlorine dioxide disinfection; b) the complex chemical interrelationships between DBPs and other parameters within a municipal water distribution system; and c) difficulties obtaining accurate and reliable information on personal activity and water consumption patterns. In May 2000, an international workshop was held to bring together various disciplines to develop better approaches for measuring DBP exposure for epidemiologic studies. The workshop reached consensus about the clear need to involve relevant disciplines (e.g., chemists, engineers, toxicologists, biostatisticians and epidemiologists) as partners in developing epidemiologic studies of DBPs in drinking water. The workshop concluded that greater collaboration of epidemiologists with water utilities and regulators should be encouraged in order to make regulatory monitoring data more useful for epidemiologic studies. Similarly, exposure classification categories in epidemiologic studies should be chosen to make results useful for regulatory or policy decision making. Key words: disinfection by-products, epidemiologic methods, exposure assessment, haloacetic acids, trihalomethanes. Environ Health Perspect 110(suppl 1):53-60 (2002).
http://ehpnet1.niehs.nih.gov/docs/2002/suppl-1/53-60arbuckle/abstract.html
Address correspondence to T. Arbuckle, Bureau of Reproductive and Child Health, A.L. 0701D, Health Canada, Tunney's Pasture, Ottawa, Ontario K1A 0L2 Canada. Telephone: (613) 941-1287. Fax: (613) 941-9927. E-mail: tye_arbuckle@hc-sc.gc.ca
The workshop described in this article was sponsored by Health Canada and by the U.S. Environmental Protection Agency through contract OD-5366-NAFX to Health Canada. The workshop has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency or of Health Canada and no official endorsement should be inferred. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. The authors acknowledge the valuable contribution of the participants at the workshop to the discussion and recommendations.
Received 24 April 2001; accepted 8 August 2001.
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The disinfection of potable waters has been a major public health initiative of the past century, drastically reducing waterborne diseases. However, epidemiologic studies found associations between elevated levels of disinfection by-products (DBPs) and increased risks of bladder, rectal, and/or colon cancers (
1-6) and adverse pregnancy outcomes (
7-10). A major criticism of these studies is the inadequate characterization of exposure (
11). Many different indices are used to assign exposure, including surface water versus groundwater source; chloraminated versus chlorinated source; total or individual trihalomethanes (THMs); and haloacetic acid (HAA) concentrations. Generally, average DBP levels measured at the treatment plant or within the distribution system are assigned to all residents served by that treatment plant, which can result in DBP exposure misclassification.
To address DBP exposure assessment issues in epidemiologic studies, scientists from various disciplines (e.g., chemists, engineers, toxicologists, biostatisticians, epidemiologists) participated in a workshop in Ottawa, Canada, on 7-10 May 2000. The goals of the workshop were to develop better approaches in exposure assessment, provide insight on how to better interpret previously conducted studies, and promote more understanding among the disciplines of the need for more effective exposure assessment tools for epidemiologic studies.
The workshop was divided into four sessions with presentations and panel discussions. In this report, we review key elements of the problems discussed at each session of the workshop and summarize the major findings and recommendations. The Appendix lists the members of the panel.
The first session was concerned with drinking water sampling (timing, frequency, parameters to measure), factors affecting DBP formation, chemical analysis, and modeling of DBPs within the distribution system. Historical data on the occurrence of DBPs have been collected mostly in response to regulatory requirements. Consequently, the sampling strategies have not been designed to determine exposure for studies of adverse health effects. For example, in the United States, DBP concentrations are required to be reported only four times per year (quarterly basis) at four locations in the distribution system (three at average detention time and one at maximum detention time), with compliance based on a running annual average of these 16 samples. Smaller utilities may sample even less frequently.
DBP concentrations in a water distribution system can differ significantly from concentrations at the point of entry from the water treatment plant. Concentrations can increase or decrease because of biologic and chemical reactions within the distribution system and because of system hydraulics. For example, in a chlorinated system, THMs can increase in concentration with increasing distance from the plant, whereas some HAAs (e.g., dichloroacetic acid) are biodegraded at the end of a distribution system (locations with maximum retention time), where there is little or no chlorine residual. Other DBPs (e.g., chloral hydrate, haloacetonitriles, haloketones) may degrade in a distribution system maintained at an alkaline pH (e.g., ~pH 8-9) because of base-catalyzed hydrolysis. In fact, the hydrolysis by-products of some of these DBPs are other DBPs (e.g., chloral hydrate or 1,1,1-trichloropropanone are hydrolyzed to chloroform, one of the THMs). Hence, an individual's exposure from tap water may vary spatially (e.g., workplace vs. home) and temporally (depending on variations in water quality and/or treatment from season to season, day to day, and throughout the day) (12).
Current water utility sampling protocols for monitoring DBPs within the distribution system are generally inadequate for classifying an individual's exposure in reproductive/developmental epidemiologic studies. A grab sample represents only the DBP concentrations at that location and time. Fetal organ development occurs very early in gestation and over a relatively short time interval. During this period of organogenesis, the fetus is particularly sensitive to environmental exposures (13). Fetal growth mostly occurs during the last trimester of gestation. Therefore, the exposure during the time period (window) relevant to a specific outcome must be accurately characterized. Even quarterly sampling may not be suitable for reproductive studies because the samples may be taken as much as 5 months apart, and hence peak occurrences could be missed. Although the critical exposure window, if any, for DBPs remains unknown, the workshop recommended at least monthly sampling of several representative locations within the distribution system for exposure assessment in human reproductive/developmental studies. When data are not available for the time window of interest, one approach for reproductive studies has been to estimate DBP levels by sampling one year later (9). However, this may be problematic if there have been significant year-to-year variations in hydrology, climate, water quality, DBP precursor levels, treatment practices, and/or distribution-system hydraulics. The extent of the temporal differences will be system specific. A comparison of routinely collected parameters, such as total organic carbon (TOC), bromide, chlorine dose, chlorine residual, temperature, pH, and hydraulic parameters, from the two time periods could be used to assess the validity of reliance on the subsequent sampling period.
Quarterly monitoring was considered adequate for long-term chronic health effect studies (such as cancer). However, because of the long latency periods (decades) for cancer, historical exposure data are required. For cancer studies, the challenge is in predicting historical DBP exposure, especially if the etiologically relevant time period is prior to the implementation of current DBP monitoring programs and there have been significant changes in treatment practices (e.g., to meet current DBP regulations). Moreover, measures of DBP precursors (TOC, bromide) have been collected only in recent years. Historical DBP predictions may need to depend on collecting other water quality parameters (e.g., color, chloride) to estimate historical DBP precursor loadings.
Overall, a utility-specific (intrasystem) monitoring plan is needed to account for the degree of spatial and temporal variation in planning an epidemiologic study (14). Perhaps even more important, a determination must be made as to how much intrasystem variation in DBP concentrations is tolerable in the context of an epidemiologic study. Accurate assessment of DBP levels in an individual's water supply is important in calculating exposure because these levels are the basis for actual exposure due to water-use activities and consumption patterns (7,15,16). However, the degree of accuracy necessary for such studies has yet to be determined.
The recommended ideal set of parameters to adequately characterize DBP exposure is shown in Table 1. However, in most studies, it will be difficult or impossible to obtain data for all the parameters listed in this table. Therefore, researchers will need to prioritize which parameters to obtain to significantly improve exposure assessment for their study. The estimated costs for the suite of four THMs and nine HAAs is $400 (U.S.) per sample. The suggested level of precision for concentration of individual DBPs at the tap should be within 10-20%. Strict protocols must be followed to preserve the integrity of the sample and ensure that the DBP levels at the time of the analysis accurately reflect the levels at the time of sample collection. This is achieved by quenching the disinfectant residual and adjusting the pH of the sample. Analyses of polar DBPs, like the HAAs, have required expensive, complex, and time-consuming (about 20 samples/24 hr) preparative analytical procedures. Some promising new techniques such as electrospray ionization-mass spectrometry (ESI-MS) alone (17) or in combination with high-field asymmetric waveform ion mobility spectrometry (ESI-FAIMS-MS) (18,19) offer prospects for substantial improvements for polar DBPs like that seen with HAAs. ESI-MS and ESI-FAIMS-MS can reduce the time required for analysis to less than 5 min/sample.
The focus of most of the data collection and research has been on the THMs and, to a lesser extent, on the HAAs. However, hundreds of other DBPs have been identified (20,21) in treated drinking water. Very little data exist on the occurrence or toxicity of these DBPs; however, new efforts are addressing certain priority DBPs (21-23). The workshop participants recommended specific DBPs to consider in future studies based on toxicologic considerations (Table 2).
Water quality simulation models can be used to estimate DBP levels at specific residences in a water distribution system. Most of the predictive equations for THM and HAA formation are empirical in nature, derived from multiple linear regression analysis of laboratory chlorination experiments conducted under controlled experimental conditions (24,25). Although these equations are typically based on experiments conducted on a wide range of waters, they yield a central tendency prediction that may not characterize variability in exposure at specific sites. In some cases, a central tendency model can be modified to improve the predictive capacity for site-specific uses. In other cases, a new model needs to be developed. However, linkage of predictive equations for DBP formation to epidemiologic studies is not a trivial endeavor. Important considerations are how well the models predict DBP concentrations at a set of predetermined node points such as those used in hydraulic performance models, and how well those node points represent hydraulic and water-quality conditions at individual residences. Evaluation of the predictive equations for THMs and HAAs in a simulated pipe environment has shown that the rate of THM formation from point-of-entry kinetic tests performed in clean bottles can be significantly different than the rate in an actual pipe system (26). This effect was not as pronounced for HAAs. A first-order DBP saturation growth model applied to a water distribution system by linking it with a hydraulic model found the results disappointing for predicting both THMs and HAAs (27).
The panel identified a number of research needs for sampling, analysis, and modeling of DBPs (Table 3). Evidence is mounting that knowledge about exposure to specific DBPs within a given class (e.g., brominated vs. total THMs) is likely to be as important or more important than total DBP class exposure levels. Improved techniques and standardization of methods are needed for water sample collection and measuring residence time in the system (e.g., "water age"). Effective collaboration is required among analytical chemists, water quality specialists, and epidemiologists to develop monitoring programs that will achieve the exposure assessment objectives.
The discussion in this session focused on features of epidemiologic study design and questionnaire content (and other surrogate measures of exposure) that affect the quality of DBP exposure assessment. Water utility personnel and other professionals (e.g., chemists, engineers, and toxicologists) should be involved as collaborators early in the design of epidemiologic studies. Strategies for measuring DBP exposure will differ among studies of cancer and reproductive outcomes. Cancer studies present unique challenges by requiring estimates of exposure data from the distant past usually without relevant exposure measurements. Most of the discussion at the workshop was related to exposure assessment for reproductive studies, which focus on relatively recent exposures. Table 4 is a summary of the panel's recommendations on minimum exposure information to collect for reproductive outcome studies.
One promising study design is for the investigator to select study sites that maximize contrasts in potential DBP exposure among populations while minimizing variability of DBP exposures within sites. Sites that are consistently in the low or high tails of the distribution for the DBPs of interest, and that have low temporal and spatial variation within their distribution systems, offer the best prospects, provided the population base is sufficiently large for the health outcomes under study. Within a site chosen for its DBP level, variations in exposure will occur, particularly if individuals do not live and work in the same area or use filters or bottled water. When comparing different geographical areas with differing DBPs, however, investigators must understand that underlying differences among the sites could bias results (e.g., access to prenatal screening or abortion clinics [in studies of reproductive outcomes], other environmental exposures, lifestyle factors, and risk-taking behaviors).
When analyzing the data, investigators should select exposure categories that, when possible, are relevant to regulatory and policy decisions. For example, researchers could use cut-points for assigning exposure categories that include current and proposed maximum contaminant levels.
The current state of knowledge is sufficiently limited that some studies are still needed to generate viable hypotheses about DBPs (hazard identification), whereas other studies are needed to test hypotheses (e.g., whether brominated DBPs are a greater health risk than chlorinated DBPs). In exploratory types of studies, researchers should avoid restricting data collection to only one exposure window of interest. Deferring this restriction to the analysis phase of the study will allow greater flexibility in exploring several hypotheses regarding the critical exposure period for the health outcomes under study.
Ecologic study designs (where information on the exposure and disease is an overall index available for a group of people rather than for the individual) may be attractive for interesting natural experiments such as before-and-after studies evaluating changes in treatment practices over time in the same geographical area. For the ecologic design, problems with selection bias, recall errors, and missing data on individual exposure or outcome may be less important. Of course, analytic study designs will ultimately be needed to test hypotheses that have been generated by effective ecologic study designs.
The panel identified a number of areas needing further research (Table 5), such as developing, testing, standardizing, and validating questions on water consumption and use patterns. The common view held by members of the panel is that our estimates of recent DBP personal exposure are likely in error by well over a factor of 2 (i.e., quantitative estimates of individual DBP exposure from all routes likely range from 0.5 to 2 times the true value for any individual). Further research is needed to determine how much exposure misclassification is tolerable and what level of accuracy is needed to achieve that tolerable level. Finely characterizing answers to questions on activity patterns may provide more detailed information, but the value of incremental detail needs to be judged according to its ability to reduce errors in exposure misclassification. Resources may be better spent increasing the number of tap water samples collected. Future epidemiologic research needs to reflect the inevitable diversity of DBP exposures and emerging insights from toxicology studies about DBP exposure routes, metabolic pathways, and toxicity mechanisms.
Biomarkers have been classified into biomarkers of exposure, biomarkers of effect, and biomarkers of susceptibility. The primary concern of this session was biomarkers of exposure, but some insights about the utility for exposure assessment of biomarkers of effect and of susceptibility also emerged.
Optimally, DBP biomarkers should be sensitive and specific to the exposure of interest, readily accessible, inexpensive to measure, and technically feasible to measure; have an elimination half-life appropriate to the exposure window of interest; be indicative of exposure duration, intensity, and pattern; and be consistently and quantitatively related to exposure.
Biomarkers of exposure can be used to refine exposure assessment (i.e., establish that exposure has occurred with some measure of the extent of exposure), reconstruct exposure from all routes, evaluate effectiveness of interventions (e.g., changes in treatment practices or regulations), identify important data gaps for questionnaires, and identify susceptible populations. Some work has been done in developing biomarkers for THMs in blood (28-30) and exhaled breath (31-33) and HAAs in urine (33-35). The studies on HAAs in urine (33-35) involved a cross-sectional sampling design that precluded evaluation of intraindividual variability and limited the assessment of interindividual variability. Recent research from a longitudinal exposure trial to evaluate trichloroacetic acid (the most promising HAA biomarker) indicated that both of these sources of variability are important (36). DBP biomarker research has developed sufficiently to discriminate population average exposure differences, but more research is needed to interpret individual differences in biomarker levels and to validate what the measured biomarker levels actually represent in terms of DBP exposure. In particular, the contribution to biomarker levels of sources other than drinking water must be better understood. Knowledge of DBP toxicokinetics, which continues to be developed for HAAs and THMs (37,38), and human physiologically based toxicokinetic models, which will soon be available for bromodichloromethane (39), should prove valuable in using biomarker data to ascertain DBP exposure.
The practicality of using biomarkers in epidemiologic studies should be considered. Standard methods for a biomarker such as trichloroacetic acid in urine are very labor intensive and susceptible to analyte loss. Estimated costs for a study population of 2,000 couples, with two urine samples per person and associated residential and workplace tap water samples, would be more than $1.5 million over a 2-year period. New methods may substantially reduce the cost and time required to measure biomarkers [e.g., solid-phase microextraction followed by fast gas chromatography with either electron capture detection or mass spectometry can substantially reduce sample volume requirements and analysis time for biological samples (40)]. The emerging technology of ESI-MS and ESI-FAIMS-MS shows early promise for rapid analyses of HAAs (18,19), which may eventually make such biomarkers more feasible, although considerable method development and validation are required.
Collecting and analyzing biomarkers at very low concentrations require rigorous protocols. Commercial vacutainer rubber stoppers contain volatile compounds (e.g., bromoform), which can severely interfere with accurate measurements of THMs in blood (41). These compounds must be removed by heating the stoppers under vacuum prior to use. Current detection limits for THMs in blood are below 1 pg/mL (42), which is sufficient to provide quantitative levels of THMs in the blood of most users of chlorine- or chloramine-treated water. Blood samples can be stored under refrigeration for up to 10 weeks before analysis. Less progress has been made in measuring HAAs in blood. Currently, HAAs have a considerably higher detection limit in blood (at least 1,000 times greater) and improved detection methods are needed.
Preliminary measurements on a series of large, differentially exposed populations indicate that blood levels are responsive to concentrations and species of THMs found in household water (30). Measurements of blood levels after exposure through specific routes indicate that internal dose levels of THMs increase to a much greater extent from inhalation or dermal exposure compared with dose levels from ingestion (30,43). However, because the putative etiologic agent(s) in disinfected drinking water has not yet been identified, we cannot discount the role of the ingestion route or any metabolites of the parent compounds in causing any observed health effect.
The research needs in DBP biomarker development are detailed in Table 6. Possible biomarkers of susceptibility include DBP-metabolizing enzymes that are polymorphically expressed in people. For example, glutathione S-transferase theta, can catalyze the activation of brominated THMs to mutagenic intermediates (44,45).
Because currently unknown biomarkers of effect or of genetic susceptibility may be discovered in the future, investigators in human studies should explore the possibility of collecting and storing appropriate tissue samples (e.g., blood, exfoliated bladder epithelial cells, buccal epithelial cells) for future biomarker research. The challenges in obtaining ethics approval and informed consent in human studies to allow for subsequent genetic analysis were discussed but not resolved.
This session focused on the impact and interpretation of exposure misclassification, methods and approaches to model personal exposure to specific DBPs, and uncertainty analysis of the parameters of these models.
A "closest-site" method has been proposed and developed as a way to possibly reduce exposure misclassification created by using utilitywide average exposure assessment methods. However, reliance on the proximity of a subject's residence to the closest utility sampling site can produce exposure misclassification. The magnitude of the error will depend on how the distribution system is configured. For example, nearby or even adjacent residences may be served by different segments of a distribution system, which could result in substantially different DBP levels. Errors may also occur if study subjects reside in undersampled areas of the distribution system.
Misclassification of exposure can also occur because of difficulty in recalling and reporting drinking water activities and consumption. Number preferences by subjects in response to questions about time spent in an activity or volume consumed may also contribute to misclassification errors (e.g., rounding estimates to common increments, such as 5 or 10 vs. 7 min of showering time). Whether such errors matter in the context of actual dose needs to be assessed. In a preliminary study of the effect of showering on predicted dose of chloroform, two factors had a significant impact--time in the shower and amount of time spent in the bathroom after the shower (46).
Assumptions about drinking water source also need to be verified, as illustrated by a convenience sample of 114 women that found 26% used bottled or filtered water, 50% worked outside the home, and 80% of those working outside the home used the workplace water supply as one of their drinking water sources (47).
Some evaluation of the nature and direction of the exposure measurement error (misclassification) is required, including whether the error is similar in all study groups. For dichotomous exposure variables, methods are available to estimate the impact of misclassification errors that use sensitivity (probability that someone who is truly exposed will be classified as exposed) and specificity (probability that someone who is truly unexposed will be classified as unexposed) (48).
When nondifferential misclassification is assumed, the same values of sensitivity and specificity apply to both cases and noncases. This assumption may be less reasonable in case-control studies if, for example, cases are more likely to recall exposures (correctly or incorrectly) than are controls. When the exposure variable has more than two categories, nondifferential misclassification can lead to bias away from the null value. For example, in a case-control study, if 20% of the observations in each exposure category were incorrectly classified into the lowest exposure category and all observations in the lowest category were classified correctly, depending on the sample size within each category and disease status, the expected odds ratios could be approximately one half of what they would have been if no misclassification had occurred (49).
Misclassification measures such as sensitivity and specificity should be treated as probabilities. This will create a recognition and quantification of the fact that, if the expected bias (i.e., the bias on average) from misclassification is in one direction (e.g., toward the null), there is always a nonzero probability that the misclassification in a given study will cause that study's results to be distorted in the opposite direction (e.g., away from the null). This probability can be appreciable in some circumstances. In addition, measures of random variability (e.g., estimated standard errors) of estimated misclassification probabilities from exposure assessment validation studies need to be propagated throughout any correction, adjustment, or sensitivity analyses of exposure misclassification bias in which those estimates are employed.
The detailed personal DBP exposure models are driven by human activities. Information on what activities are undertaken, when, and for how long must be collected. Any exposure model developed must account for all relevant exposure pathways and routes of uptake. The research needs in this area are listed in Table 7.
An accurate characterization of DBP exposure (from all sources and routes) for all individuals in the study population is required for valid risk assessment of the potentially associated adverse health effects. The complexity of issues requires an interdisciplinary approach.
Current information on DBP exposures is largely determined by monitoring results that are driven by regulatory requirements. Meanwhile, regulators look to epidemiologic evidence to justify regulatory levels. Despite this obvious interconnection, the workshop panel found that regulatory monitoring for DBPs was of limited value for improving individual classification of exposure to DBPs, particularly for acute health effects investigations such as reproductive studies. The value of performing new epidemiologic studies using inadequate DBP exposure data sources is questionable.
The workshop panel concluded that greater collaboration with water utilities and regulators should be encouraged for future epidemiologic studies. Likewise, exposure scales, categories, and contrasts analyzed in future epidemiologic studies should be chosen to make study results useful for regulatory or policy decision makers. For example, if municipal water authorities are faced with the choice between different methods for disinfecting water from a given source, with little or no option to change the water source itself, they will need epidemiologic evidence that compares different disinfection methods applied to similar source waters. In these circumstances, studies comparing different source waters (e.g., surface water vs. groundwater) are of limited value for making informed choices among disinfection alternatives.
Overall, improving the quality of individual DBP exposure assessments will improve the quality of evidence that can be generated through epidemiologic studies. Achieving these improvements will require an interdisciplinary approach to the problem.
Organizing Committee Chair
Tye E. Arbuckle, Health Canada
Workshop Chair
Steve E. Hrudey, University of Alberta
Tap Water Sampling, Analysis, and Distribution Modeling
Robert C. Andrews, University of Toronto
Frank M. Benoit, Health Canada
Nicole Graziano, University of Colorado
Stuart W. Krasner, Glendora, CA
Michele Lynberg, Centers for Disease Control and Prevention
Jay R. Nuckols, Colorado State University
Susan D. Richardson, U.S. Environmental Protection Agency
Phillip C. Singer, University of North Carolina at Chapel Hill
Surrogate Measures of Exposure
Linda Dodds, Dalhousie University
Will King, Queen's University
John Reif, Colorado State University
Kirsten Waller, Sequoia Foundation
Biomarkers of Exposure
David L. Ashley, Centers for Disease Control and Prevention
Kenneth L. Froese, University of Alberta
Pauline Mendola, U.S. Environmental Protection Agency
Rex A. Pegram, U.S. Environmental Protection Agency
Irvin R. Schultz, Battelle
Clifford Weisel, University of Medicine and Dentistry of New Jersey
Exposure Modeling and Uncertainty Analysis
Annette M. Bachand, Colorado State University
Amit Roy, University of Medicine and Dentistry of New Jersey
Charles Poole, University of North Carolina at Chapel Hill
Charles Wilkes, Wilkes Technologies
References and Notes
1. King WD, Marrett LD. Case-control study of bladder cancer and chlorination by-products in treated water (Ontario, Canada). Cancer Causes Control 7:596-604 (1996).
2. Koivusalo M, Pukkala E, Vartiainen T, Jaakkola JJK, Hakulinen T. Drinking water chlorination and cancer--a historical cohort study in Finland. Cancer Causes Control 8:192-200 (1997).
3. Doyle TJ, Zheng W, Cerhan JR, Hong C-P, Sellers TA, Kushi LH, Folsom AR. The association of drinking water source and chlorination by-products with cancer incidence among postmenopausal women in Iowa: a prospective cohort study. Am J Public Health 87:1168-1176 (1997).
4. Cantor KP, Lynch CF, Hildesheim ME, Dosemeci M, Lubin J, Alavanja M, Craun G. Drinking water source and chlorination by-products--risk of bladder cancer. Epidemiology 9:21-28 (1998).
5. Yang C-Y, Chiu H-F, Cheng M-F, Tsai S-S. Chlorination of drinking water and cancer mortality in Taiwan. Environ Res 78:1-6 (1998).
6. King WD, Marrett LD, Woolcott CG. Case-control study of colon and rectal cancers and chlorination by-products in treated water. Cancer Epidemiol Biomarkers Prev 9:813-818 (2000).
7. Waller K, Swan SH, DeLorenze G, Hopkins B. Trihalomethanes in drinking water and spontaneous abortion. Epidemiology 9:134-140 (1998).
8. Dodds L, King W, Woolcott C, Pole J. Trihalomethanes in public water supplies and adverse birth outcomes. Epidemiology 10:233-237 (1999).
9. Klotz JB, Pyrch LA. Neural tube defects and drinking water disinfection by-products. Epidemiology 10:383-390 (1999).
10. King WD, Dodds L, Allen AC. Relation between stillbirth and specific chlorination by-products in public water supplies. Environ Health Perspect 108:883-886 (2000).
11. Reif JS, Hatch MC, Bracken M, Holmes L, Schwetz BA, Singer PC. Reproductive and developmental effects of disinfection by-products in drinking water. Environ Health Perspect 104:1056-1061 (1996).
12. Singer PC. Variability and assessment of disinfection by-product concentrations in water distribution systems. In: Microbial Pathogens and Disinfection By-Products in Drinking Water: Health Effects and Management of Risks (Craun GF, Hauchman FS, Robinson DE, eds). Washington, DC:International Life Sciences Institute 2001;211-223.
13. Selevan SG, Kimmel CA, Mendola P. Identifying critical windows of exposure for children's health. Environ Health Perspect 108(suppl 3):451-455 (2000).
14. Raucher RS, Nuckols JR, Krapfl H, Weigel SW. Identifying Geographic Regions for Potential Future Epidemiology Research on Disinfection By-Products. Denver, CO:American Water Works Research Foundation, 2000.
15. Lynberg ML, Nuckols JR, Langlois P, Ashley D, Singer P, Mendola P, Wilkes C, Krapfl H, Miles E, Speight V, et al. Assessing exposure to disinfection by-products in women of reproductive age living in Corpus Christi, Texas, and Cobb County, Georgia: descriptive results and methods. Environ Health Perspect 109:597-604 (2001).
16. Nuckols JR, Rossman LA, Singer PS, Speight V, Krapfl H, Miles A, Small L. Development of Exposure Assessment Methods for THM and HAA in Water Distribution Systems. Report 341. Denver, CO:American Water Works Research Foundation, 2001.
17. Magnuson ML, Kelty CA. Microextraction of nine haloacetic acids in drinking water at microgram per liter levels with electrospray-mass spectrometry of stable association complexes. Anal Chem 72:2308-2312 (2000).
18. Ells B, Barnett DA, Froese K, Purves RW, Hrudey S, Guevremont R. Detection of chlorinated and brominated byproducts of drinking water disinfection using electrospray ionization-high-field asymmetric waveform ion mobility spectrometry-mass spectrometry. Anal Chem 71:4747-4752 (1999).
19. Ells, B, Barnett, D. Guevremont, R, Purves, R. Detection of the nine chlorinated and brominated haloacetic acids at part-per-trillion levels in drinking water using ESI-FAIMS-MS. Anal Chem 72:4555-4559 (2000).
20. Richardson, SD. Drinking water disinfection by-products. In: The Encyclopedia of Environmental Analysis and Remediation, Vol 3. New York:John Wiley & Sons, 1998;1398-1421.
21. Richardson SD, Thurston AD Jr, Caughran TV, Chen PH, Collette TW, Schenck KM, Lykins BW Jr, Rav-Acha C, Glezer V. Identification of new drinking water disinfection by-products from ozone, chloride dioxide, chloramine, and chlorine. Water Air Soil Pollut 123:95-102 (2000).
22. Gonzalez AC, Krasner SW, Weinberg H, Richardson SD. Determination of newly identified disinfection by-products in drinking water. In: Proceedings of Water Quality Technology Conference, 5-9 November 2000, Salt Lake City, Utah. Denver, CO:American Water Works Association, 2000.
23. Onstad GD, Weinberg HS, Richardson SD. Evolution of analytical methods for halogenated furanones in drinking water. In: Proceedings of the Water Quality Technology Conference, 5-9 November 2000, Salt Lake City, Utah. Denver, CO:American Water Works Association, 2000.
24. Amy G, Siddiqui M, Ozekin K, Zhu HW, Wang C. Empirically Based Models for Predicting Chlorination and Ozonation By-Products: Trihalomethanes, Haloacetic Acids, Chloral Hydrate, and Bromate. EPA-815-R-98-005. Cincinnati, OH:U.S. Environmental Protection Agency, 1998.
25. Cowman GA, Singer PC. Effect of bromide ion on haloacetic acid speciation resulting from chlorination and chloramination of aquatic humic substances. Environ Sci Technol 30:1-16 (1996).
26. Rossman LA, Brown RA, Singer PC, Nuckols JR. DBP formation kinetics in a simulated distribution system. Water Res 35:3485-3489 (2001).
27. Speight VL, Nuckols JR, Rossman L, Miles A, Singer P. DBP exposure assessment using distribution system modeling. In: Proceedings of the Water Quality Technology Conference, 5-9 November 2000, Salt Lake City, Utah. Denver, CO:American Water Works Association, 2000.
28. Aggazzotti G, Fantuzzi G, Righi E, Predieri G. Blood and breath analyses as biological indicators of exposure to trihalomethanes in indoor swimming pools. Sci Total Environ 217:155-163 (1998).
29. Backer LC, Ashley DL, Bonin MA, Cardinali FL, Kieszak SM, Wooten JV. Household exposures to drinking water disinfection by-products: whole blood trihalomethanes. J Expos Anal Environ Epidemiol 10:321-326 (2000).
30. Miles AM, Singer PC, Ashley D, Lynberg M, Mendola P, Nuckols J. Comparison of trihalomethanes measured in tap water with levels measured in blood samples. In: Proceedings of the Water Quality Technology Conference, 5-9 November 2000, Salt Lake City, Utah. Denver, CO:American Water Works Association, 2000.
31. Levesque B, Ayotte P, LeBlanc A, Dewailly E, Prud'Homme D, Lavoie R, Allaire S, Levallois P. Evaluation of dermal and respiratory chloroform exposure in humans. Environ Health Perspect 102:1082-1087 (1994).
32. Lindstrom AB, Pleil JD, Berkoff DC. Alveolar breath sampling and analysis to assess trihalomethane exposures during competitive swimming training. Environ Health Perspect 105:636-642 (1997).
33. Weisel CP, Kim H, Haltmeier P, Klotz JB. Exposure estimates to disinfection by-products of chlorinated drinking water. Environ Health Perspect 107:103-110 (1999).
34. Kim H, Weisel CP. Dermal absorption of dichloro- and trichloroacetic acids from chlorinated water. J Expos Anal Environ Epidemiol 8:555-575 (1998).
35. Kim H, Haltmeier P, Klotz JB, Weisel CP. Evaluation of biomarkers of environmental exposures: urinary haloacetic acids associated with ingestion of chlorinated drinking water. Environ Res 80:187-195 (1999).
36. Froese KL, Sinclair M, Hrudey SE. Trichloroacetic acid as a biomarker of exposure for DBPs in drinking water. In: Microbial/Disinfection By-products Health Effects Symposium, 24-26 March 2001, Chicago, Illinois. Denver, CO:American Water Works Association, 2001.
37. International Programme on Chemical Safety. Environmental Health Criteria 216. Disinfectants and Disinfectant By-products. Geneva:World Health Organization, 2000.
38. Schultz IR, Merdink AL, Gonzalez-Leon A, Bull RJ. Comparative toxicokinetics of chlorinated and brominated haloacetates in F344 rats. Toxicol Appl Pharmacol 158:103-114 (1999).
39. Lilly PD, Andersen ME, Ross TM, Pegram RA. A physiologically based pharmacokinetic description of the oral uptake, tissue dosimetry and rates of metabolism of bromodichloromethane in the male rat. Toxicol Appl Pharmacol 150:205-217 (1998).
40. Wu F, Gabryelski W, Ongley M. Froese KL. Fast gas chromatography methods for small volume analysis of haloacetic acids. In: Microbial/Disinfection By-products Health Effects Symposium, 24-26 March 2001, Chicago, Illinois. Denver, CO:American Water Works Association, 2001.
41. Cardinali FL, McCraw JM, Ashley DL, Bonin M, Wooten J. Treatment of vacutainers for use in the analysis of volatile organic compounds in human blood at low parts-per-trillion level. J Chromatogr Sci 33:557-560 (1995).
42. Ashley DL, Bonin MA, Cardinali FL, McCraw JM, Holler JL, Needham LL, Patterson DG Jr. Determining volatile organic compounds in human blood from a large sample population by using purge and trap gas chromatography/mass spectrometry. Anal Chem 64:1021-1029 (1992).
43. Weisel CP, Jo WK. Ingestion, inhalation and dermal exposures to chloroform and trichloroethene from tap water. Environ Health Perspect 104:48-51 (1996).
44. Pegram RA, Andersen ME, Warren SH, Ross TM, Claxton LD. Glutathione S-transferase-mediated mutagenicity of trihalomethanes in Salmonella typhimurium: contrasting results with bromodichloromethane and chloroform. Toxicol Appl Pharmacol 144:183-188 (1997).
45. DeMartini DM, Shelton ML, Warren SH, Ross TM, Shim JY, Richard AM, Pegram RA. Glutathione S-transferase-mediated induction of GC to AT transitions by halomethanes in Salmonella. Environ Mol Mutagen 30:440-447 (1997).
46. Wilkes C, Nuckols JR. Comparing exposure classification by three alternative methods: measured blood levels, questionnaire results, and model predictions. Presented at the International Society of Exposure Analysis, 24-27 October 2000, Monterey, California.
47. Zender R, Bachand AM, Reif JS. Exposure to tap water during pregnancy. J Expos Anal Environ Epidemiol 11:224-230 (2001).
48. Greenland S. Basic methods for sensitivity analysis and external adjustment. In: Modern Epidemiology, 2nd ed (Rothman KJ, Greenland S, eds). Philadelphia:Lippincott-Raven, 1998;343-357.
49. Reif JS, Bachand A, Andersen M. Reproductive and Developmental Effects of Disinfection By-products, Final Report. Ottawa, ON:Bureau of Reproductive and Child Health, Health Canada, 2000.
Last Updated: January 26, 2002
