Environmental Protection
Agency
urnce 01 nesearcn ana
Development
Washington DC 20460
EPA/600/P-00/001Ag
June 2000
External Review Draft
v>EPA
Review
Draft
(Do Not
Exposure and Human C'te or
Health Reassessment of Quote)
2,3,7,8-Tetrachlorodibenzo-
p-Dioxin (TCDD) and
Related Compounds
Part III: Integrated Summary and
Risk Characterization for 2,3,7,8-
Tetrachlorodibenzo-p-Dioxin
(TCDD) and Related Compounds
Notice
This document is a preliminary draft. It has not been formally
released by EPA and should not at this stage be construed to
represent Agency policy. It is being circulated for comment on its
technical accuracy and policy implications.
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DRAFT EPA/600/P-00/001Ag
DO NOT CITE OR QUOTE June 2000
External Review Draft
www. epa. gov/ncea
Exposure and Human Health Reassessment
of 2,3,7,8-Tetrachlorodibenzo-/?-Dioxin (TCDD)
and Related Compounds
Part III: Integrated Summary and Risk Characterization for
2,3,7,8-TetrachIorodibenzo-/7-Dioxin (TCDD) and Related Compounds
NOTICE
THIS DOCUMENT IS A PRELIMINARY DRAFT. It has not been formally released by the
U.S. Environmental Protection Agency and should not at this stage be construed to represent
Agency policy. It is being circulated for comment on its technical accuracy and policy
implications.
National Center for Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
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DISCLAIMER
This document is a draft for review purposes only and does not constitute U.S.
Environmental Protection Agency policy. Mention of trade names or commercial products does
not constitute endorsement or recommendation for use.
n
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TABLE OF CONTENTS - OVERVIEW
Exposure and Human Health Reassessment
of 2,3,7,8-TetrachIorodibenzo-p-Dioxin (TCDD)
and Related Compounds
PART I: ESTIMATING EXPOSURE TO DIOXIN-LIKE COMPOUNDS
Volume 1: Executive Summary
Volume 2: Sources of Dioxin-Like Compounds in the United States
Chapters 1 through 12
Volume 3: Properties, Environmental Levels, and Background Exposures
Chapters 1 through 6
Volume 4: Site-Specific Assessment Procedures
Chapters 1 through 8
Addendum: Revisions since March are included as an addendum to Part I.
PART ILHEALTH ASSESSMENT FOR 2,3,7,8-TETRACHLORODIBENZO-/?-DIOXIN
(TCDD) AND RELATED COMPOUNDS
Chapter 1. Disposition and Pharmacokinetics
Chapter 2. Mechanism(s) of Actions
Chapter 3. Acute, Subchronic, and Chronic Toxicity
Chapter 4. Immunotoxicity
Chapter 5. Developmental and Reproductive Toxicity
Chapter 6. Carcinogenicity of TCDD in Animals
Chapter 7. Epidemiology/Human Data
Chapter 8. Dose-Response Modeling for 2,3,7,8-TCDD
Chapter 9. Toxicity Equivalence Factors (TEF) for Dioxin and Related Compounds
Part III: INTEGRATED SUMMARY AND RISK CHARACTERIZATION FOR
2,3,7,8-TETRACHLORODIBENZO-p-DIOXIN (TCDD) AND RELATED
COMPOUNDS
in
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CONTENTS
1. INTRODUCTION 1
1.1. DEFINITION OF DIOXIN-LIKE COMPOUNDS '..'.'.'.'.'.'.'. 3
1.2. TOXICITY EQUIVALENCE FACTORS 4
1.3. UNDERSTANDING EXPOSURE/DOSE RELATIONSHIPS FOR DIOXIN-
LIKE COMPOUNDS 7
2. EFFECTS SUMMARY 10
2.1. BIOCHEMICAL RESPONSES 11
2.2. ADVERSE EFFECTS IN HUMANS AND ANIMALS 14
2.2.1. Cancer 14
2.2.1.1. Epidemiologic Studies 14
2.2.1.2. Animal Carcinogenicity 17
2.2.1.3. Other Data Related to Carcinogenesis • 19
2.2.1.4. Cancer Hazard Characterization 20
2.2.2. Reproductive and Developmental Effects 21
2.2.2.1. Human 22
2.2.2.2. Experimental Animal 24
2.2.2.3. Other Data Related to Developmental and Reproductive
Effects 27
2.2.2.4. Developmental and Reproductive Effects Hazard
Characterization 29
2.2.3. Immunotoxicity 31
2.2.3.1. Epidemiologic Finding 31
2.2.3.2. Animal Findings 31
2.2.3.3. Other Data Related to Immunologic Effects 32
2.2.3.4. Immunologic Effects Hazard Characterization 33
2.2.4. Chloracne 34
2.2.5. Diabetes 36
2.2.6. Other Effects 37
2.2.6.1. Elevated GOT 37
2.2.6.2. Thyroid Function 38
2.2.6.3. Cardiovascular Disease 39
2.2.6.4. Oxidative Stress 40
3. MECHANISMS AND MODE OF DIOXIN ACTION 40
3.1. MODE VERSUS MECHANISM OF ACTION 41
3.2. GENERALIZED MODEL FOR DIOXIN ACTION 42
3.2.1. The Receptor Concept 42
3.2.2. A Framework to Evaluate Mode of Action 44
3.2.3. Mechanistic Information, Mode of Action, and Risk Assessment 45
IV
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4. EXPOSURE CHARACTERIZATION 48
4.1. SOURCES 49
4.1.1. Inventory of Releases 50
4.1.2. General Source Observations 52
4.2. ENVIRONMENTAL FATE 54
4.3. ENVIRONMENTAL MEDIA AND FOOD CONCENTRATIONS 56
4.4. BACKGROUND EXPOSURES 57
4.4.1. Tissue Levels 57
4.4.2. Intake Estimates 58
4.4.3. Variability in Intake Levels 59
4.5. POTENTIALLY HIGHLY EXPOSED POPULATIONS OR
DEVELOPMENTAL STAGES 60
4.6. ENVIRONMENTAL TRENDS 62
5. DOSE-RESPONSE CHARACTERIZATION 63
5.1. DOSE METRIC(s) 66
5.1.1. Calculations of Effective Dose (ED) 69
5.2. EMPIRICAL MODELING OF INDIVIDUAL DATA SETS 70
5.2.1. Cancer 71
5.2.1.1. Estimates of Slope Factors and Risk at Current Background
Body Burdens Based on Human Data 76
5.2.1.2. Estimates of Slope Factors and Risk at Current Background
Body Burdens Based on Animal Data 77
5.2.1.3. Estimates of Slope Factors and Risk at Current Background
Body Burdens Based on a Mechanistic Model 78
5.2.2. Noncancer Endpoints 79
5.3. MODE-OF-ACTION BASED DOSE-RESPONSE MODELING 80
5.4. SUMMARY DOSE-RESPONSE CHARACTERIZATION 81
6. RISK CHARACTERIZATION 82
REFERENCES FOR RISK CHARACTERIZATION 131
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LIST OF TABLES
Table 1-1. The TEF scheme for I-TEQDFa 107
Table 1-2. The TEF scheme for TEQDFP-WHO94a 108
Table 1-3. The TEF scheme for TEQDFP-WHO9ga 109
Table 2-1. Effects of TCDD and related compounds in different animal species 110
Table 3-1. Early molecular events in response to dioxin Ill
Table 4-1. Confidence rating scheme 112
Table 4-2. Quantitative inventory of environmental releases of TEQDF-WHO98 in the United
States 113
Table 4-3. Preliminary indication of the potential magnitude of TEQDF-WHO98 releases from
"unquantified" (i.e., Category D) sources in reference year 1995 115
Table 4-4. Unquantified sources 116
Table 4-5. Estimates of the range of typical background levels of dioxin-like compounds in
various environmental media 117
Table 4-6. Estimates of levels of dioxin-like compounds in food 118
Table 4-7. Background serum levels in the United States 1995-1997 119
Table 4-8. Adult contact rates and background intakes of dioxin-like compounds 120
Table 4-9. Variability in average daily TEQ intake as a function of age 121
Table 5-1. Serum dioxin levels in the background population and epidemiological cohorts
(back-calculated) 122
Table 5-2. Doses yielding 1% excess risk (95% lower confidence bound) based upon 2-year
animal carcinogenicity studies using simple multistage (Portier et. al, 1984)
models 124
LIST OF FIGURES
Figure 1-1. Chemical structure of 2,3,7,8-TCDD and related compounds 125
Figure 2-1. Cellular mechanism for AhR action 126
Figure 2-2. Some of the genes whose expression is altered by exposure to TCDD 127
Figure 4-1. Estimated CDD/CDF I-TEQ emissions to air from combustion sources in the
United States, 1995 128
Figure 4-2. Comparison of estimates of annual I-TEQ emissions to air (grams I-TEQ/yr) for
reference years 1987 and 1995 129
Figure 5-1. Dioxin body burden levels in background populations and epidemiological
cohorts (back-calculated) 130
VI
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AUTHORS AND CONTRIBUTORS
William H. Farland
Director
National Center for Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Linda S. Birnbaum
Director
Environmental Toxicology Division
National Health and Environmental Effects Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina
Michael J. DeVito
National Health and Environmental Effects Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina
John L. Schaum
National Center for Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Bruce D. Rodan
Senior Health Scientist
National Center for Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Dwain L. Winters
Director
Dioxin Policy Project
Office of Pollution Prevention and Toxics
Office of Prevention, Pesticides, and Toxic Substances
U.S. Environmental Protection Agency
Washington, DC
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1. INTRODUCTION
1 This document presents an integrated summary of available information related to exposure
2 to and possible health effects of dioxin and related compounds. It also presents a short risk
3 characterization, which is a concise statement of dioxin science and the public health
4 implications of both general population exposures from environmental "background"'and
5 incremental exposures associated with proximity to sources of dioxin and related compounds.
6 Even though it summarizes key findings developed in the exposure and health assessment
7 portions (Parts I and II, respectively) of the Agency's dioxin reassessment, it is meant to be
8 detailed enough to stand on its own for the average reader. Readers are encouraged to refer to the
9 more detailed documents for further information on the topics covered here and to see complete
10 literature citations. These documents are:
11
12 Estimating Exposure to Dioxin-like Compounds: This document, hereafter referred to as Part I,
13 the Exposure Document, is divided into four volumes: (1) Executive Summary; (2) Sources of
14 Dioxin in the United States; (3) Properties, Environmental Levels, and Background Exposures;
15 and (4) Site-Specific Assessment Procedures.
16
17 Health Assessment Document for 2,3,7,8-TCDD and Related Compounds: This document,
18 hereafter referred to as Part II, the Health Document, contains two volumes with nine chapters
19 covering pharmacokinetics, mechanisms of action, epidemiology, animal cancer and various non-
20 cancer effects, toxiciry equivalence factors (TEFs), and dose-response.
21
22 Parts of this integrative summary and risk characterization go beyond individual chapter
23 findings to reach general conclusions about the potential impacts of dioxin-like compounds on
24 human health. This document specifically identifies issues concerning the risks that may be
25 occurring in the general population at or near population background exposure levels. It
26 articulates the strengths and weaknesses of the available evidence for possible sources, exposures
27 and health effects, and presents assumptions made and inferences used in reaching conclusions
28 regarding these data. The final risk characterization provides a synopsis of dioxin science and its
'The term "background" exposure has been used throughout this reassessment to describe
exposure of the general population, who are not exposed to readily identifiable point sources of
dioxin-like compounds. Most (>95%) of this exposure results from minute amounts of dioxin-
like compounds being present in dietary fat.
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1 implications for characterizing hazard and risk for use by risk assessors and managers inside and
2 outside EPA and by the general public.
3
4 This document (Part III) is organized as follows:
5
6 1. Introduction - This section describes the purpose/organization of, and the process for
7 developing, the report; defines dioxin-like compounds in the context of the EPA re-
8 assessment; and explains the Toxicity Equivalency (TEQ) concept.
9 2. Effects Summary - This section summarizes the key findings of the Health Document
10 and provides links to relevant aspects of exposure, mechanisms, and dose-response.
11 3. Mechanisms and Mode of Dioxin Action - This section discusses the key findings on
12 effects in terms of mode of action. It uses the "Mode-of-Action Framework" recently
13 described by the WHO/IPCS Harmonization of Approaches to Risk Assessment Project and
14 contained in the Agency's draft Guidelines for Carcinogen Risk Assessment as the basis for
15 the discussions.
16 4. Exposure Summary - This section summarizes the key findings of the Exposure
17 Document and links them to the effects, mechanisms, and dose-response characterization.
18 5. Dose Response Summary - This section summarizes approaches to dose response that
19 are found in the Health Document and provides links to relevant aspects of exposure and
20 effects.
21 6. Risk Characterization - This section presents conclusions based on an integration of
22 the exposure, effects, mechanisms and dose response information. It also highlights key
23 assumptions and uncertainties.
24
25 The process for developing this risk characterization and companion documents has been
26 open and participatory. Each of the documents has been developed in collaboration with
27 scientists from inside and outside the Federal Government. Each document has undergone
28 extensive internal and external review, including review by EPA's Science Advisory Board
29 (SAB). In September 1994, drafts of each document, including an earlier version of this risk
30 characterization, were made available for public review and comment. This included a 150-day
31 comment period and 11 public meetings around the country to receive oral and written
32 comments. These comments, along with those of the SAB, have been considered in the drafting
33 of this final document. The Dose-Response Chapter of the Health Effects Document underwent
34 peer review in 1997; an earlier version of this Integrated Summary and Risk Characterization
35 underwent development and review in 1997 and 1998, and comments have been incorporated. In
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1 addition, as requested by the SAB, a chapter on Toxicity Equivalence has been developed and
2 will undergo review in parallel with this document. When complete, and following final SAB
3 review, the comprehensive set of background documents and this integrative summary and risk
4 characterization will be published as final reports and replace the previous dioxin assessments as
5 the scientific basis for EPA decision-making.
6
7 1.1. DEFINITION OF DIOXIN-LIKE COMPOUNDS
8 As defined in Part I, this assessment addresses specific compounds in the following
9 chemical classes: polychlorinated dibenzodioxins (PCDDs or CDDs), polychlorinated
10 dibenzofurans (PCDFs or CDFs), polybrominated dibenzodioxins (PBDDs or BDDs),
11 polybrominated dibenzofurans (PBDFs or BDFs), and polychlorinated biphenyls (PCBs), and
12 describes this subset of chemicals as "dioxin-like." Dioxin-like refers to the fact that these
13 compounds have similar chemical structure, similar physical-chemical properties, and invoke a
14 common battery of toxic responses. Because of their hydrophobic nature and resistance towards
15 metabolism, these chemicals persist and bioaccumulate in fatty tissues of animals and humans.
16 The CDDs include 75 individual compounds; CDFs include 135 different compounds. These
17 individual compounds are referred to technically as congeners. Likewise, the BDDs include 75
18 different congeners and the BDFs include an additional 135 congeners. Only 7 of the 75
19 congeners of CDDs, or of BDDs, are thought to have dioxin-like toxicity; these are ones with
20 chlorine/bromine substitutions in, at a minimum, the 2, 3, 7, and 8 positions. Only 10 of the 135
21 possible congeners of CDFs or of BDFs are thought to have dioxin-like toxicity; these also are
22 ones with substitutions in the 2, 3, 7, and 8 positions. This suggests that 17 individual
23 CDDs/CDFs, and an additional 17 BDDs/ BDFs, exhibit dioxin-like toxicity. The database on
24 many of the brominated compounds regarding dioxin-like activity has been less extensively
25 evaluated, and these compounds have not been explicitly considered in this assessment.
26 There are 209 PCB congeners. Only 12 of the 209 congeners are thought to have dioxin-
27 like toxicity; these are PCBs with 4 or more lateral chlorines with 1 or no substitution in the
28 ortho position. These compounds are sometimes referred to as coplanar, meaning that they can
29 assume a flat configuration with rings in the same plane. Similarly configured polybrominated
30 biphenyls (PBBs) are likely to have similar properties. However, the database on these
31 compounds with regard to dioxin-like activity has been less extensively evaluated, and these
32 compounds have not been explicitly considered in this assessment. Mixed chlorinated and
33 brominated congeners of dioxins, furans, and biphenyls also exist, increasing the number of
34 compounds potentially considered dioxin-like within the definitions of this assessment. The
35 physical/chemical properties of each congener vary according to the degree and position of
36 chlorine and/or bromine substitution. Very little is known about occurrence and toxicity of the
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1 mixed (chlorinated and brominated) dioxin, furan, and biphenyl congeners. Again, these
2 compounds have not been explicitly considered in this assessment. Generally speaking, this
3 assessment focuses on the 17 CDDs/CDFs and a few of the coplanar PCBs that are frequently
4 encountered in source characterization or environmental samples. While recognizing that other
5 "dioxin-like" compounds exist in the chemical classes discussed above (e.g., brominated or
6 chlorinated/brominated congeners) or in other chemical classes (e.g., halogenated naphthalenes
7 or benzenes, azo- or azoxybenzenes), the evaluation of less than two dozen chlorinated congeners
8 is generally considered sufficient to characterize environmental "dioxin."
9 The chlorinated dibenzodioxins and dibenzofurans are tricyclic aromatic compounds with
10 similar physical and chemical properties. Certain of the PCBs (the so-called coplanar or mono-
11 ortho coplanar congeners) are also structurally and conformationally similar. The most widely
12 studied of this general class of compounds is 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). This
13 compound, often called simply "dioxin," represents the reference compound for this class of
14 compounds. The structure of TCDD and several related compounds is shown in Figure 1-1.
15 Although sometimes confusing, the term "dioxin" is often also used to refer to the complex
16 mixtures of TCDD and related compounds emitted from sources, or found in the environment or
17 in biological samples. It can also be used to refer to the total TCDD "equivalents" found in a
18 sample. This concept of toxicity equivalence is discussed extensively in Part II, Chapter 9, and is
19 summarized below.
20
21 1.2. TOXICITY EQUIVALENCE FACTORS
22 CDDs, CDFs, and PCBs are commonly found as complex mixtures when detected in
23 environmental media and biological tissues, or when measured as environmental releases from
24 specific sources. Humans are likely to be exposed to variable distributions of CDDs, CDFs, and
25 dioxin-like PCB congeners that vary by source and pathway of exposures. This complicates the
26 human health risk assessment that may be associated with exposures to variable mixtures of
27 dioxin-like compounds. In order to address this problem, the concept of toxicity equivalence has
28 been considered and discussed by the scientific community, and toxic equivalency factors (TEFs)
29 have been developed and introduced to facilitate risk assessment of exposure to these chemical
30 mixtures.
31 On the most basic level, TEFs compare the potential toxicity of each dioxin-like compound
32 comprising the mixture to the well-studied and understood toxicity of TCDD, the most toxic
33 member of the group. The background and historical perspective regarding this procedure is
34 described in detail in Part II, Chapter 9, and in Agency documents (U.S. EPA 1987,1989,
35 1991 a). This procedure involves assigning individual TEFs to the 2,3,7,8 substituted CDD/CDF
36 congeners and "dioxin-like" PCBs. To accomplish this, scientists have reviewed the
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1 toxicological databases along with considerations of chemical structure, persistence, and
2 resistance to metabolism, and have agreed to ascribe specific, "order of magnitude" TEFs for
3 each dioxin-like congener relative to TCDD, which is assigned a TEF of 1.0. The other
4 congeners have TEF values ranging from 1.0 to 0.00001. Thus, these TEFs are the result of
5 scientific judgment of a panel of experts using all of the available data and are selected to
6 account for uncertainties in the available data and to avoid underestimating risk. In this sense,
7 they can be described as "public health conservative" values. To apply this TEF concept, the
8 TEF of each congener present in a mixture is multiplied by the respective mass concentration and
9 the products are summed to represent the 2,3,7,8-TCDD Toxic Equivalence (TEQ) of the
10 mixture, as determined by Equation 1 -1.
, 2 TEQ = X ,_„ (Congener, x TEF,) + (congener! x TEF} )+ (congenern x TEFn \ (]. 1)
13 The TEF values for PCDDs and PCDFs were originally adopted by international convention
14 (U.S. EPA, 1989a). Subsequent to the development of the first international TEFs for CDD/Fs,
15 these values were further reviewed and/or revised and TEFs were also developed for PCBs
16 (Ahlborg et al., 1994; van den Berg et al, 1998). A problem arises in that past and present
17 quantitative exposure and risk assessments may not have clearly identified which of three TEF
18 schemes was used to estimate the TEQ. This reassessment introduces a new uniform TEQ
19 nomenclature that clearly distinguishes between the different TEF schemes and identifies the
20 congener groups included in specific TEQ calculations. The nomenclature uses the following
21 abbreviations to designate which TEF scheme was used in the TEQ calculation:
22
23 1. I-TEQ refers to the International TEF scheme adopted by EPA in 1989 (U.S. EPA, 1989a).
24 See Table 1-1.
25 2. TEQ-WHO94 refers to the 1994 World Health Organization (WHO) extension of the I-TEF
26 scheme to include 13 dioxin-like PCBs (Ahlborg et al., 1994). See Table 1-2.
27 3. TEQ-WHO9g refers to the 1998 WHO update to the previously established TEFs for
28 dioxins, furans, and dioxin-like PCBs (van den Berg et al., 1998). See Table 1-3.
29
30 The nomenclature also uses subscripts to indicate which family of compounds is included
31 in any specific TEQ calculation. Under this convention, the subscript D is used to designate
32 dioxins, the subscript F to designate furans and the subscript P to designate PCBs. As an
33 example, "TEQDF-WHO98" would be used to describe a mixture for which only dioxin and furan
34 congeners were determined and where the TEQ was calculated using the WHO9g scheme. If
35 PCBs had also been determined, the nomenclature would be "TEQDFP-WHO9g." Note that the
36 designations TEQDF-WHO94 and I-TEQDF are interchangeable, as the TEFs for dioxins and furans
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1 are the same in each scheme. Note also that in the current draft of this document, I-TEQ
2 sometimes appears without the D and F subscripts. This indicates that the TEQ calculation
3 includes both dioxins and furans.
4 This reassessment recommends that the WHO98 TEF scheme be used to assign toxicity
5 equivalence to complex environmental mixtures for assessment and regulatory purposes. Later
6 sections of this document describe the mode(s) of action by which dioxin-like chemicals mediate
7 biochemical and toxicological actions. These data provide the scientific basis for the TEF/TEQ
8 methodology. In its 20-year history, the approach has evolved, and decision criteria supporting
9 the scientific judgment and expert opinion used in assigning TEFs has become more transparent.
10 Numerous states, countries, and several international organizations have evaluated and adopted
11 this approach to evaluating complex mixtures of dioxin and related compounds (Part II, Chapter
12 9). It has become the accepted methodology, although the need for research to explore
13 alternative approaches is widely endorsed. Clearly, basing risk on TCDD alone or assuming all
14 chemicals are equally potent to TCDD is inappropriate on the basis of available data. Although
15 uncertainties in the use of the TEF methodology have been identified and are described later in
16 this document and in detail in Part II, Chapter 9, one must examine the use of this method in the
17 broader context of the need to evaluate the potential public health impact of complex mixtures of
18 persistent, bioaccumulative chemicals. It can be generally concluded that the use of TEF
19 methodology for evaluating complex mixtures of dioxin-like compounds decreases the overall
20 uncertainties in the risk assessment process as compared to alternative approaches. Use of the
21 latest consensus values for TEFs assures that the most recent scientific information informs this
22 "useful, interim approach" (U.S. EPA, 1989a; Kutz et al., 1990) to dealing with complex
23 environmental mixtures of dioxin-like compounds. As stated by the U.S. EPA Science Advisory
24 Board (U.S. EPA, 1995), "The use of the TEFs as a basis for developing an overall index of
25 public health risk is clearly justifiable, but its practical application depends on the reliability of
26 the TEFs and the availability of representative and reliable exposure data." EPA will continue to
27 work with the international scientific community to update these TEF values to assure that the
28 most up-to-date and reliable data are used in their derivation and to evaluate their use on a
29 periodic basis. One of the limitations of the use of the TEF methodology in risk assessment of
30 complex environmental mixtures is that the risk from non-dioxin-like chemicals is not evaluated
31 in concert with that of dioxin-like chemicals. Future approaches to the assessment of
32 environmental mixtures should focus on the development of methods that will allow risks to be
33 predicted when multiple mechanisms are present from a variety of contaminants.
34
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1 1.3. UNDERSTANDING EXPOSURE/DOSE RELATIONSHIPS FOR DIOXIN-LIKE
2 COMPOUNDS
3 Dose can be expressed as a variety of metrics (e.g., daily intake, serum concentrations,
4 steady-state body burdens, or area under the plasma concentration versus time curve [AUC]).
5 Ideally, the best dose metric is that which is directly and clearly related to the toxicity of concern
6 by a well-defined mechanism. In the mechanism-based cancer modeling for TCDD which will
7 be discussed later, for instance, instantaneous values of a dose-metric, CYP1A2 or EOF receptor
8 concentrations are used as surrogates for mutational rates and growth rates within a two-stage
9 cancer model. The utility of a particular metric will also depend upon the intended application
10 and the ability to accurately determine this dose metric. For example, if concentration of
11 activated Ah receptors in a target tissue was determined to be the most appropriate dose metric
12 for a particular response in laboratory animals, its utility would be questionable since we
13 presently have no means to determine these values in humans.
14 In this reassessment of the health effects of dioxins, dose is used to understand the
15 animal-to-human extrapolations, comparing human exposure as well as comparing the sensitivity
16 of different toxic responses. Previous assessments of TCDD have used daily dose as the dose
17 metric and applied either an allometric scaling factor or an uncertainty factor for species
18 extrapolation. The present assessment uses steady-state body burdens as the dose metric of
19 choice. One reason for the change in dose metrics is that recent data demonstrate that the use of
20 either allometric scaling or uncertainty factors underestimates the species differences in the
21 pharmacokinetic behavior of TCDD and related chemicals. This is due to persistence and
22 accumulation of dioxins in biological systems and to the large (approximately 100-fold)
23 difference in half-lives between humans and rodents.
24 When extrapolating across species, steady-state body burden appears to be the most
25 appropriate dose metric. The choice of body burden as the dose metric is based on scientific and
26 pragmatic approaches. As stated earlier, the best dose metric is that which is directly and clearly
27 related to the toxicity of concern. For dioxins, there is evidence in experimental animals that
28 tissue concentrations of dioxins is an appropriate dose metric for the developmental,
29 immunological, and biochemical effects of dioxins (Hurst et al., 2000; Van Birgelen et al., 1996;
30 Walker et al., 1998). Comparing target tissue concentrations of dioxins between animals and
31 humans is impractical. In humans, the tissues for which we have estimates of the concentration
32 are limited to those that may not be the target tissue of concern, such as serum, blood, or adipose
33 tissue. However, tissue concentrations are directly related to body burdens of dioxins. Therefore,
J4 steady-state body burdens can be used as surrogates for tissue concentrations.
J5
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1 Body burdens have been estimated through two different methods. Serum, blood, or
2 adipose tissue concentrations of dioxins are reported as pg/g lipid. Evidence supports the
3 assumption that TCDD and related chemicals are approximately evenly distributed throughout
4 the body lipid. Using the tissue lipid concentrations and the assumption that TCDD is equally
5 distributed based on lipid content, body burdens are calculated by multiplying the tissue
6 concentration by the percent body fat composition. One potential problem for estimating body
7 burdens is the hepatic sequestration of dioxins. In rodents, dioxins accumulate in hepatic tissue
8 to a greater extent than predicted by lipid content. This sequestration is due to CYP1A2, which
9 binds dioxins. There is also evidence in humans that dioxins are sequestered in hepatic tissue.
10 Estimating body burdens on serum, blood, or adipose tissue concentrations may underpredict true
11 body burdens of these chemicals. This underprediction should be relatively small. As liver is
12 approximately 5% of body weight, even a 10-fold sequestration in hepatic tissue compared to
13 adipose tissue would result in a 50% difference in the body burden estimated using serum, blood,
14 or adipose tissue concentrations. In addition, the sequestration is dose-dependent, and at human
15 background exposures, hepatic sequestration should not be significant.
16 A second method for determining body burdens is based on estimates of the daily intake
17 and half-life of dioxins. Limitations on estimating body burden through this method are
18 dependent upon the accuracy of the estimates for intake and half-life. Historically, intakes of
19 dioxins have varied and there is some uncertainty about past exposures. In addition, little is
20 known about the half-life of dioxins at different life stages, although there is a relationship
21 between fat composition and elimination of dioxins. Finally, depending on the exposure
22 scenario, using the half-life of TCDD for the TEQ concentrations may result in some
23 inaccuracies. While the chemicals that contribute most to the total TEQ, such as the
24 pentachlorodioxins and dibenzofurans and PCS 126, have similar half-lives to TCDD, other
25 contributors to the total TEQ have significantly different half-lives. This document uses
26 pharmacokinetic modeling in a number of places where it is assumed that the 7-year half-life for
27 TCDD can be applied to the TEQDFP of a mixture of dioxins, furans, and PCBs. The validity of
28 this assumption was tested in the following way. First, congener-specific half-lives and intake
29 rates were identified for each of the dioxin and furan congeners with nonzero TEFs. These half-
30 lives and intakes were input into a one-compartment, steady-state pharmacokinetic model to get
31 congener-specific tissue concentrations. The congener-specific tissue levels were summed to get
32 an overall TEQDF tissue value. Second, the pharmacokinetic model was run using the 7-year
33 half-life and total TEQDF intake to get a TEQDF tissue concentration. Both of these modeling
34 approaches yielded very similar TEQDF tissue levels. Although this exercise did not include
35 PCBs (because of lack of half-life estimates), and the congener-specific half-lives for many of the
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1 dioxins and furans have limited empirical support, it provides some assurance that this is a
2 reasonable approach (see full discussion in Part I, Volume 3, Chapter 4).
3 Body burdens also have an advantage as a dose metric when comparing occupational or
4 accidental exposures to background human exposures. In the epidemiological studies, the
5 external exposure and the rate of this exposure are uncertain. The only accurate information we
6 have is on serum, blood, or adipose tissue concentrations. Because of the long biological half-
7 life of TCDD, these tissue concentrations of dioxins are better markers of past exposures than
8 they are of present exposures. Hence, body burdens allow for estimations of exposure in these
9 occupational and accidentally exposed cohorts. In addition, this dose metric allows us to
10 compare these exposures with those of background human exposures.
11 The use of body burden, for many effects within species and, particularly, for cross-
12 species scaling, appears to provide a better dose metric than daily dose. There is sufficient
13 scientific evidence to support the use of body burden as a reasonable approximation of tissue
14 concentrations. Future efforts to better understand the dose-response relationships for the effects
15 of dioxin-like chemicals should provide insight into determining better dose metrics for this class
16 of chemicals.
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2. EFFECTS SUMMARY
1 Since the identification of TCDD as a chloracnegen in 1957, more than 5,000
2 publications have discussed its biological and toxicological properties. A large number of the
3 effects of dioxin and related compounds have been discussed in detail throughout the chapters in
4 Part II of this assessment. They illustrate the wide range of effects produced by this class of
5 compounds. The majority of effects have been identified in experimental animals; some have
6 also been identified in exposed human populations.
7 Cohort and case-control studies have been used to investigate hypothesized increases in
8 malignancies among the various 2,3,7,8-TCDD-exposed populations (Fingerhut et al., 1991a,b;
9 Steenland et al., 1999; Manz et al., 1991; Eriksson et al., 1990). Cross-sectional studies have
10 been conducted to evaluate the prevalence or extent of disease in living 2,3,7,8-TCDD-exposed
11 groups (Suskind and Hertzberg, 1984; Moses et al., 1984; Lathrop et al., 1984, 1987; Roegner et
12 al., 1991; Grubbs et al. 1995; Sweeney et al., 1989; Centers for Disease Control Vietnam
13 Experience Study, 1988; Webb et al., 1989; Ott and Zober, 1994). The limitations of the cross-
14 sectional study design for evaluating hazard and risk is discussed in Part II, Chapter 7b. Many of
15 the earliest studies were unable to define exposure-outcome relationships owing to a variety of
16 shortcomings, including small sample size, poor participation, short latency periods, selection of
17 inappropriate controls, and the inability to quantify exposure to 2,3,7,8-TCDD or to identify
18 confounding exposures. In more recent analyses of cohorts (NIOSH, Hamburg) and cross-
19 sectional studies of U.S. chemical workers (Sweeney et al., 1989), U.S. Air Force Ranch Hand
20 personnel (Roegner et al., 1991; Grubbs et al., 1995), and Missouri residents (Webb et al., 1989),
21 serum or adipose tissue levels of 2,3,7,8-TCDD were measured to evaluate 2,3,7,8-TCDD-
22 associated effects in exposed populations. The ability to measure tissue or serum levels of
23 2,3,7,8-TCDD for all or a large sample of the subjects confirmed exposure to 2,3,7,8-TCDD and
24 permitted the investigators to test hypothesized dose-response relationships.
25 A large number of effects of exposure to TCDD and related compounds have been
26 documented in the scientific literature. Although many effects have been demonstrated in
27 multiple species (see Table 2-1), other effects may be specific to the species in which they are
28 measured and may have limited relevance to the human situation. Although this is an important
29 consideration for characterizing potential hazard, all observed effects may be indicative of the
30 fundamental level at that dioxin produces its biological impact and illustrate the multiple
31 sequelae that are possible when primary impacts are at the level of signal transduction and gene
32 transcription. Even though not all observed effects may be characterized as "adverse" effects
33 (i.e., some may be adaptive and of neutral consequence), they represent a continuum of response
34 expected from the fundamental changes in biology caused by exposure to dioxin-like
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1 compounds. As discussed in the following sections, the dose associated with this plethora of
2 effects is best compared across species using a common measurement unit of body burden of
3 TCDD and other dioxin-like compounds, as opposed to the level or rate of exposure/intake.
4 The effects discussed in the following sections are focused on development of an
5 understanding of dioxin hazard and risk. This discussion is by its nature selective of findings
6 that inform the risk assessment process. Readers are referred to the more comprehensive
7 chapters for further discussion of the epidemiologic and toxicologic database.
8
9 2.1. BIOCHEMICAL RESPONSES (Cross reference: Part II, Chapters 2,3, and 8)
10 As described later in Section 3, mechanistic studies can reveal the biochemical pathways
11 and types of biological events that contribute to adverse effects from exposure to dioxin-like
12 compounds. For example, much evidence indicates that TCDD acts via an intracellular protein
13 (the aryl hydrocarbon receptor, AhR), which is a ligand-dependent transcription factor that
14 functions in partnership with a second protein (known as the Ah receptor nuclear translocator,
15 Arnt). Therefore, from a mechanistic standpoint, TCDD's adverse effects appear likely to reflect
16 alterations in gene expression that occur at an inappropriate time and/or for an inappropriate
17 length of time. Mechanistic studies also indicate that several other proteins contribute to TCDD's
18 gene regulatory effects and that the response to TCDD probably involves a relatively complex
19 interplay between multiple genetic and environmental factors. This model is illustrated in Figure
20 2-1 (from Part II, Chapter 2).
21 Comparative data from animal and human cells and tissues suggest a strong qualitative
22 similarity across species in response to dioxin-like chemicals. This further supports the
23 applicability to humans of the generalized model of early events in response to dioxin exposure.
24 These biochemical and biological responses are sometimes considered adaptive and are often not
25 considered adverse in and of themselves. However, many of these biochemical changes are
26 potentially on a continuum of dose-response relationships, which leads to adverse responses. At
27 this time, caution must be used when describing these events as adaptive.
28 If, as we can infer from the evidence, TCDD and other dioxin-like compounds operate
29 through these mechanisms, there are constraints on the possible models that can plausibly
30 account for dioxin's biological effects and also on the assumptions used during the risk
31 assessment process. Mechanistic knowledge of dioxin action may also be useful in other ways.
32 For example, a further understanding of the ligand specificity and structure of the Ah receptor
33 will likely assist in the identification of other chemicals to which humans are exposed that may
34 either add to, synergize, or antagonize the toxicity of TCDD and other dioxin-like compounds.
35 Knowledge of genetic polymorphisms that influence TCDD responsiveness may also allow the
36 identification of individuals at particular risk from exposure to dioxin. In addition, knowledge of
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1 the biochemical pathways that are altered by dioxin-like compounds may help in the
2 development of drugs that can prevent dioxin's adverse effects.
3 As described in Part II, Chapter 2, biochemical and genetic analyses of the mechanisms
4 by which dioxin modulates particular genes have revealed the outline of a novel regulatory
5 system whereby a chemical signal can alter cellular regulatory processes. Future studies of
6 dioxin action have the potential to provide additional insights into mechanisms of mammalian
7 gene regulation that are of relatively broad interest. Additional perspectives on dioxin action can
8 be found in several recent reviews (Birnbaum, 1994a,b; Schecter, 1994; Hankinson, 1995;
9 Schmidt and Bradfield, 1996; Rowlands and Gustafsson, 1997; Gasiewicz, 1997; Harm, 1998;
10 Denison et al., 1998; Wilson and Safe, 1998).
11 The ability of TCDD and other dioxin-like compounds to modulate a number of
12 biochemical parameters in a species-, tissue-, and temporal-specific manner is well recognized.
13 Despite the ever-expanding list of these responses over the past 20 years and the elegant work on
14 the molecular mechanisms mediating some of these, there still exists a considerable gap between
15 our knowledge of these changes and the degree to which they are related to the more complex
16 biological and toxic endpoints elicited by these chemicals. A framework for considering these
17 responses in a mode-of action context is discussed later in this document.
18 TCDD-elicited activation of the Ah receptor has been clearly shown to mediate altered
19 transcription of a number of genes, including several oncogenes and those encoding growth
20 factors, receptors, hormones, and drug-metabolizing enzymes. Figure 2-2 provides an
21 illustrative list of gene products shown to be mediated by TCDD. Although this list is not meant
22 to be exhaustive, it demonstrates the range of potential dioxin impacts.
23 As discussed in Volume 2, Chapter 2, it is possible that the TCDD-elicited alteration of
24 activity of these genes may occur through a variety of mechanisms, including signal transduction
25 processes. These alterations in gene activity may be secondary to other biochemical events that
26 may be directly regulated transcriptionally by the AhR. Some of the changes may also occur by
27 post-transcriptional processes such as mRNA stabilization and altered phosphorylation (Gaido et
28 al., 1992; Matsumura, 1994). Thus, the molecular mechanisms by which many, if not most, of
29 the biochemical processes discussed herein are altered by TCDD treatment remain to be
30 determined. Nevertheless, it is presumed, based on the cumulative evidence available, that all of
31 these processes are mediated by the binding of TCDD to the AhR. Although the evidence for the
32 involvement of the AhR in all of these processes has not always been ascertained,
33 structure-activity relationships, genetic data, and reports from the use of biological models like
34 "knockout" mice that are lacking the Ah receptor (AhR"A) are consistent with the involvement of
35 the AhR as the initial step leading to many of these biochemical alterations. In fact, for every
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1 biochemical response that has been well studied, the data are consistent with the particular
2 response being dependent on the AhR.
3 The dioxin-elicited induction of certain drug-metabolizing enzymes such as C YP1A1,
4 CYP1A2, and CYP1B1 is clearly one of the most sensitive responses observed in a variety of
5 different animal species including humans, occurring at body burdens as low as 1-10 ng
6 TCDD/kg in animals (see Part II, Chapter 8). These and other enzymes are responsible for the
7 metabolism of a variety of exogenous and endogenous compounds. Several lines of
8 experimental evidence suggest that these enzymes may be responsible for either enhancing or
9 protecting against (depending on the compounds and experimental system used) toxic effects of a
10 variety of agents, including known carcinogens as well as endogenous substrates such as
11 hormones. Several reports (Kadlubar et al., 1992; Esteller et al., 1997; Ambrosone et al., 1995;
12 Kawajiri et al., 1993) provide evidence that human polymorphisms in CYPIA1 and CYPIA2 that
13 result in higher levels of enzyme are associated with increased susceptibility to colorectal,
14 endometrial, breast, and lung tumors. Also, exposure of AhR-deficient ("knockout") mice to
15 benzo[a]pyene (BaP) results in no tumor response, suggesting a key role for the AhR, and
16 perhaps, CYPIA1 and CYPIA2, in BaP carcinogenesis (Dertinger et al., 1998; Shimizu et al.,
17 2000). Modulation of these enzymes by dioxin may play a role in chemical carcinogenesis.
18 However, the exact relationship between the induction of these enzymes and any toxic endpoint
19 observed following dioxin exposure has not been clearly established.
20 As with certain of the cytochrome P450 isozymes, there does not yet exist a precise
21 understanding of the relationships between the alteration of specific biochemical processes and
22 particular toxic responses observed in either experimental animals or humans exposed to the
23 dioxins. This is due predominantly to our incomplete understanding of the complex and
24 coordinate molecular, biochemical, and cellular interactions that regulate tissue processes during
25 development and under normal homeostatic conditions. Nevertheless, a further understanding of
26 these processes and how TCDD may interfere with them remains an important goal that would
27 greatly assist in the risk characterization process. In particular, knowledge of the causal
28 association of these responses coupled with dose-response relationships may lead to a better
29 understanding of sensitivity to various exposure levels of the dioxin-like compounds.
30 In contrast to what is known about the P450 isozymes, there exists some evidence from
31 experimental animal data to indicate that the alteration of certain other biochemical events might
32 have a more direct relationship to sensitive toxic responses observed following TCDD exposure.
33 Some of these may be relevant to responses observed in humans, and further work in these areas
34 is likely to lead to data that would assist in the risk characterization process. For example,
35 changes in epidermal growth factor (EOF) receptor have been observed in tissues from
36 dioxin-exposed animals and humans (see Part II, Chapters 3 and 6 ). EOF and its receptor
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1 possess diverse functions relevant to cell transformation and tumorigenesis, and changes in these
2 functions may be related to a number of dioxin-induced responses including neoplastic lesions,
3 chloracne, and a variety of reproductive and developmental effects . Likewise, the known ability
4 of TCDD to directly or indirectly alter the levels and/or activity of other growth factors and
5 hormones, such as estrogen, thyroid hormone, testosterone, gonadotropin-releasing hormone and
6 their respective receptors, as well as enzymes involved in the control of the cell cycle (Safe,
7 1995), may affect growth patterns in cells/tissues, leading to adverse consequences. In fact, most
8 of the effects that the dioxins produce at the cellular and tissue levels are due not to cell/tissue
9 death but to altered growth patterns (Bimbaum, 1994b). Many of these may occur at critical
10 times in development and/or maturation and thus may be irreversible.
11 From this brief discussion and that detailed in Part II, Chapters 2 and 8, it seems clear that
12 much work needs to be done to clarify the exact sequence and interrelations of those biochemical
13 events altered by TCDD and how and at what point they might lead to irreversible biological
14 consequences. Nevertheless, it is important to recognize that many of the biochemical and
15 biological changes observed are consistent with the notion that TCDD is a powerful growth
16 dysregulator. This notion may play a considerable role in the risk characterization process by
17 providing a focus on those processess, such as development, reproduction, and carcinogenesis,
18 that are highly dependent on coordinate growth regulation. Further understanding of these
19 biochemical events in humans may provide useful biomarkers of exposure and responsiveness.
20 The use of these potential biomarkers may subsequently improve our understanding of the
21 variation of responsiveness within an exposed population.
22
23 2.2. ADVERSE EFFECTS IN HUMANS AND ANIMALS
24 2.2.1. Cancer (Cross Reference: Volume 2, Chapters 6,7, and 8)
25 2.2.1.1. Epidemiologic Studies
26 Since the last formal U.S. EPA review of the human database relating to the
27 carcinogenicity of TCDD and related compounds in 1988, a number of new follow-up mortality
28 studies have been completed. This body of information is described in Part II, Chapter 7, of this
29 assessment and has recently been published as part of an I ARC Monograph (1997) and the
30 ATSDR ToxProfile (ATSDR, 1999). Among the most important of these are the studies of 5,172
31 U.S. chemical manufacturing workers by Fingerhut et al. (1991a) and Steenland et al. (1999)
32 from NIOSH and an independent study by Aylward et al. (1996); a study of 2,479 German
33 workers involved in the production of phenoxy herbicides and chlorophenols by Becher et al.
34 (1996, 1998) and by others in separate publications (Manz et al., 1991; Nagel et al., 1994;
35 Flesch-Janys et al., 1995, 1998); a study of more than 2,000 Dutch workers in two plants
36 involved in the synthesis and formulation of phenoxy herbicides and chlorophenols (Bueno de
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1 Mesquita et al., 1993) and subsequent follow-up and expansion by Hooiveld et al., 1998); a
2 smaller study of 247 workers involved in a chemical accident cleanup by Zober et al. (1990) and
3 subsequent follow-up (Ott and Zober, 1996b); and an international study of more than 18,000
4 workers exposed to phenoxy herbicides and chlorophenols by Saracci et al. (1991), with
5 subsequent follow-up and expansion by Kogevinas et al. (1997). Although uncertainty remains
6 in interpreting these studies because not all potential confounders have been ruled out and
7 coincident exposures to other carcinogens are likely, all provide support for an association
8 between exposure to dioxin and related compounds and increased cancer mortality. One of the
9 strengths of these studies is that each has some exposure information that permits an assessment
10 of dose response. Some of these data have, in fact, served as the basis for fitting the risk models
11 in Chapter 8. In addition, limited results have been presented on the non-occupational Seveso
12 cohort (Bertazzi et al., 1993, 1997) and on women exposed to chlorophenoxy herbicides,
13 chlorophenols, and dioxins (Kogevinas et al., 1993). Although these two studies have
14 methodologic shortcomings that are described in Chapter 7, they provide findings, particularly
15 for exposure to women, that warrant additional follow-up.
16 Increased risk for all cancers combined was a consistent finding in the occupational
17 cohort studies. Although the increase was generally low (20%-50%), it was highest in
18 subcohorts with presumed heaviest exposure. Positive dose-response trends in the German
19 studies and increased risk in the longer duration U.S. subcohort and the most heavily exposed
20 Dutch workers support this view.
21 One of the earliest reported associations between exposure to dioxin-like compounds in
22 dioxin-contaminated phenoxy herbicides and increased cancer risk involved an increase in soft
23 tissue sarcomas (Hardell and Sandstrom, 1979; Eriksson et al., 1981; Hardell and Eriksson, 1988;
24 Eriksson et al., 1990). In this and other recent evaluations of the epidemiologic database, many
25 of the earlier epidemiological studies that suggested an association with soft tissue sarcoma are
26 criticized for a variety of reasons. Arguments regarding selection bias, differential exposure
27 misclassification, confounding, and chance in each individual study have been presented in the
28 scientific literature, which increases uncertainty around this association. Nonetheless, the
29 incidence of soft tissue sarcoma is elevated in several of the most recent studies (Bertazzi et al.,
30 1993; 1997, 1999; Fingerhut et al., 1991a; Hertzman et al., 1997; Kogevinas et al., 1997; Lampi
31 et al., 1992; Lynge, 1998; Pesatori et al., 1999; Saracci et al., 1999; Vinels et al., 1986),
32 supporting the findings from previous studies. The fact that similar results were obtained in
33 independent studies of differing design and evaluating populations exposed to dioxin-like
34 compounds under varying conditions, along with the rarity of this tumor type, weighs in favor of
35 a consistent and real association.
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1 In addition to soft tissue sarcoma, other cancer sites have been associated with exposure
2 to dioxin. Excess respiratory cancer was noted by Fingerhut et al. (1991a), Zober et al. (1994),
3 and Manz et al. (1991). These results are also supported by significantly increased mortality
4 from lung and liver cancers subsequent to the Japanese rice oil poisoning accident where
5 exposure to high levels of PCDFs and PCBs occurred (Kuratsune et al., 1988; Kuratsune, 1989).
6 Again, while smoking as a confounder cannot be totally eliminated as a potential explanation of
7 the occupational studies results, analyses (Fingerhut, 1991b; Ott and Zober, 1996b) conducted to
8 date suggest that smoking is not likely to explain the entire increase in lung cancer and may even
9 suggest synergism between occupational exposure to dioxin and smoking. These analyses have
10 not been deemed entirely satisfactory by some reviewers of the literature. The question of
11 confounding exposures, such as asbestos and other chemicals, in addition to smoking, has not
12 been entirely ruled out and must be considered as potentially adding to the observed increases.
13 Although increases of cancer at other sites (e.g., non-Hodgkin's lymphoma, stomach cancer)
14 have been reported (see Part II, Chapter la), the data for an association with exposure to
15 dioxin-like chemicals are less compelling.
16 As mentioned above, both past and more recent human studies have focused on males.
17 Although males comprise all the case-control studies and the bulk of the cohort study analyses,
18 animal and mechanism studies suggest that males and females might respond differently to
19 TCDD. There are now, however, some limited data suggesting carcinogenic responses
20 associated with dioxin exposure in females. The only reported female cohort with good TCDD
21 exposure surrogate information was that of Manz et al. (1991), which had a borderline
22 statistically significant increase in breast cancer. Although Saracci et al. (1991) did report
23 reduced female breast and genital organ cancer mortality, this was based on few observed deaths
24 and on chlorophenoxy herbicide, rather than TCDD, exposures. In the later update and
25 expansion of this cohort Kogevinas et al. (1997) provided evidence of a reversal of this deficit
26 and produced a borderline significant excess risk of breast cancer in females. Bertazzi et al.
27 (1993,1997,1998) reported nonsignificant deficits of breast cancer and endometrial cancer in
28 women living in geographical areas around Seveso contaminated by dioxin. Although
29 Kogevinas et al. (1993) saw an increase in cancer incidence among female workers most likely
30 exposed to TCDD, no increase in breast cancer was observed in his small cohort. In sum, TCDD
31 cancer experience for women may differ from that of men, but currently there are few data.
32 Because both laboratory animal data and mechanistic inferences suggest that males and females
33 may respond differently to the carcinogenic effects of dioxin-like chemicals, further data will be
34 needed to address this question of differential response between sexes, especially to hormonally
35 mediated tumors. No epidemiological data are available to address the question of the potential
36 impact of exposure to dioxin-like compounds on childhood cancers. However, recent studies of
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1 Brown et al. (1998) demonstrate that prenatal exposure of rats enhances their sensitivity as adults
2 to chemical carcinogenesis.
3 As discussed above and based on the analysis of the cancer epidemiology data as
4 presented in Part II, Chapters 7 and 8, TCDD and, by inference, other dioxin-like compounds are
5 described as potentially multisite carcinogens in more highly exposed human populations that
6 have been studied, consisting primarily of adult males. Although uncertainty remains, the cancer
7 findings in the epidemiologic literature are generally consistent with results from studies of
8 laboratory animals where dioxin-like compounds have clearly been identified as multisite
9 carcinogens. In addition, the findings of increased risk at multiple sites appear to be plausible
10 given what is known about mechanisms of dioxin action, and the fundamental level at which it
11 appears to act in target tissues. While several studies exhibit a positive trend in dose-response
12 and have been the subject of empirical risk modeling (Becher et al., 1998), the epidemiologic
13 data alone provide little insight into the shape of the dose-response curve below the range of
14 observation in these occupationally exposed populations. This issue will be further discussed in
15 Section 5.2.1. The contribution of cancer epidemiology to overall cancer hazard and risk
16 characterization is discussed in Section 6.
17
18 2.2.1.2. Animal Carcinogenicity (Cross reference, Part II: Chapters 6 and 8)
19 An extensive database on the carcinogenicity of dioxin and related compounds in
20 laboratory studies exists and is described in detail in Chapter 6. There is adequate evidence that
21 2,3,7,8-TCDD is a carcinogen in laboratory animals based on long-term bioassays conducted in
22 both sexes of rats and mice (U.S. EPA, 1985; Huff et al., 1991; Zeise et al., 1990; IARC, 1997).
23 All studies have produced positive results, leading to conclusions that TCDD is a multistage
24 carcinogen increasing the incidence of tumors at sites distant from the site of treatment and at
25 doses well below the maximum tolerated dose. Since this issue was last reviewed by the Agency
26 in 1988, TCDD has been shown to be a carcinogen in hamsters (Rao et al., 1988), which are
27 relatively resistant to the lethal effects of TCDD. Other preliminary data have also shown TCDD
28 to be a liver carcinogen in the small fish Medaka (Johnson et al., 1992). Few attempts have been
29 made to demonstrate the carcinogenicity of other dioxin-like compounds. Other than a mixture
30 of two isomers of hexachlorodibenzodioxin (HCDDs), which produced liver tumors in both
31 sexes of rats and mice (NTP, 1980) when given by the gavage route, but not by the dermal route
32 in Swiss mice (NTP, 1982a,b) and a recent report (Rozman et al., 2000) attributing lung cancer in
33 female rats to gavage exposures of l,2,3,4,6,7,8-heptachlorodibenzo-p-dioxi(HpCDD), neither
34 the more highly chlorinated PCDDs/ PCDFs nor the co-planar PCBs have been studied in
35 long-term animal cancer bioassays. However, it is generally recognized that these compounds
36 bioaccumulate and exhibit toxicities similar to TCDD and are, therefore, also likely to be
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1 carcinogens (U.S. EPA, 1989b). The National Toxicology Program is currently testing the
2 relative carcinogenic potency of four dioxin-like congeners (PeCDF, PeCDD, and PCS 118 and
3 PCB 126), both alone and in combination. Because no chronic animal bioassays are available on
4 these compounds, these data, when they are available, should add significantly to our certainty
5 regarding the carcinogenicity of these dioxin-like congeners.
6 In addition to the demonstration of TCDD as an animal carcinogen in long-term cancer
7 bioassays, a number of dioxin-like PCDDs and PCDFs, as well as several PCBs, have been
8 demonstrated to be tumor promoters in two-stage (initiation-promotion) protocols in rodent liver,
9 lung, and skin. These studies are described in some detail in Part II, Chapter 6. In that Chapter,
10 TCDD is characterized as a nongenotoxic carcinogen because it is negative in most assays for
11 DNA damaging potential, as a potent "promoter," and as a weak initiator or noninitiator in two-
12 stage initiation-promotion (I-P) models for liver and for skin.
13 The liver response is characterized by increases in altered hepatocellular foci (AHF),
14 which are considered to be preneoplastic lesions because increases in AHFs are associated with
15 liver cancer in rodents. The results of the multiple I-P studies enumerated in Figure 6-8 in Part
16 II, Chapter 6, have been interpreted as showing that induction of AHFs by TCDD is dose-
17 dependent (Maronpot et al., 1993; Teegarden et al., 1999), are exposure-duration dependent
18 (Dragan et al., 1992; Teegarden et al., 1999; Walker et al., 2000), and are partially reversible
19 after cessation of treatment (Dragan et al., 1992; Tritscher et al., 1995; Walker et al., 2000).
20 Other studies indicate that other dioxin-like compounds have the ability to induce AHFs. These
21 studies show that the compounds demonstrate a rank-order of potency for AHF induction that is
22 similar to that for CYP1A1 (Flodstrom and Ahlborg, 1992; Waern et al., 1991; Schrenk et al.,
23 1994). Non-ortho substituted, dioxin-like PCBs also induce the development of AHFs according
24 to their potency to induce CYP1A1 (Hemming et al., 1995; van der Plas et al., 1999). It is
25 interesting to note that liver I-P studies carried out in ovariectomized rats demonstrate the
26 influence that the intact hormonal system has on AHF development. AHF are significantly
27 reduced in the livers of ovariectomized female rats (Graham et al., 1988; Lucier et al., 1991).
28 I-P studies on skin have demonstrated that TCDD is a potent tumor promoter in mouse
29 skin as well as rat liver. Early studies demonstrated that TCDD is at least two orders of
30 magnitude more potent than the "classic" promoter tetradecanoyl phorbol acetate (TPA) (Poland
31 et al., 1982); that TCDD skin tumor promotion is AhR dependent (Poland and Knutsen, 1982);
32 that TCDD had weak or no initiating activity in the skin system (DiGiovanni et al., 1977); and
33 that TCDD's induction of drug-metabolizing enzymes is associated with both metabolic
34 activation and deactivation as described by Lucier et al. (1979). More recent studies show that
35 the skin tumor promoting potencies of several dioxin-like compounds reflect relative AhR
36 binding and pharmacokinetic parameters (Hebert et al., 1990).
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1 Although few I-P studies have demonstrated lung tumors in rats or mice, the study of
2 Clark et al. (1991) is particularly significant because of its use of ovariectomized animals. In
3 contrast to liver tumor promotion, lung tumors were seen only in initiated (diethylnitrosamine
4 [DEN]), TCDD-treated rats. No tumors were seen in DEN only, TCDD only, control, or
5 DEN/TCDD intact rats. Liver tumors are ovary dependent, but ovaries appear to protect against
6 TCDD-mediated tumor promotion in rat lung. Perhaps use of transgenic animal models will
7 allow further understanding of the complex interaction of factors associated with carcinogenesis
8 in rodents as well, presumably in humans. Several such systems are being evaluated (Eastin et
9 al., 1998; van Birgelen et al., 1999; Dunson et al., 2000).
10 Several potential mechanisms for TCDD carcinogenicity are discussed in Part II, Chapter
11 6. These include oxidative stress, indirect DNA damage, endocrine disruption/growth
12 dysregulation/altered signal transduction, and cell replication/apoptosis leading to tumor
13 promotion. All of these are biologically plausible as contributors to the carcinogenic process and
14 none are mutually exclusive. Several biologically based models that encompass many of these
15 activities are described in Part II, Chapter 8. Further work will be needed to elucidate a detailed
16 mechanistic model for any particular carcinogenic response in animals or in humans. Despite
17 this lack of a defined mechanism at the molecular level, there is a consensus that TCDD and
18 related compounds are receptor-mediated carcinogens in that (1) interaction with the AhR is a
19 necessary early event; (2) TCDD modifies a number of receptor and hormone systems involved
20 in cell growth and differentiation, such as the epidermal growth factor receptor and estrogen
21 receptor; and (3) sex hormones exert a profound influence on the carcinogenic action of TCDD.
22
23 2.2.1.3. Other Data Related to Carcinogenesis
24 Despite the relatively large number of bioassays on TCDD, the study of Kociba et al.
25 (1978) and those of the NTP (1982a), because of their multiple dose groups and wide dose range,
26 continue to be the focus of dose-response modeling efforts and of additional review. Goodman
27 and Sauer (1992) reported a re-evaluation of the female rat liver tumors in the Kociba study using
28 the latest pathology criteria for such lesions. The review confirmed only approximately one-third
29 of the tumors of the previous review (Squire, 1980). Although this finding did not change the
30 determination of carcinogenic hazard, as TCDD induced tumors in multiple sites in this study, it
31 did have an effect on evaluation of dose-response and on estimates of risk at low doses. These
32 issues will be discussed in a later section of this document.
33 One of the more intriguing findings in the Kociba bioassay was reduced tumor incidences
34 of the pituitary, uterus, mammary gland, pancreas, and adrenals in exposed female rats as
35 compared to controls (Kociba et al, 1978). While these findings, coupled with evaluation of
36 epidemiologic data, have led some authors to conclude that dioxin possesses "anticarcinogenic"
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1 activity (Kayajanian, 1997; Kayajanian, 1999), it should be noted that, in experimental studies,
2 with the exception of mammary gland tumors, the decreased incidence of tumors is associated
3 with significant weight loss in these rats. Examination of the data from the National Toxicology
4 Program also demonstrates a significant decrease in these tumor types when there is a
5 concomitant weight loss in the rodents, regardless of the chemical administered (Haseman and
6 Johnson, 1996). As discussed later in Section 3.2.3, under certain circumstances exposure to
7 TCDD may elicit beneficial effects. For example, TCDD protects against the subsequent
8 carcinogenic effects of PAHs in mouse skin, possibly reflecting induction of detoxifying
9 enzymes (Cohen et al., 1979; DiGiovanni et al., 1980). In other situations, TCDD-induced
10 changes in estrogen metabolism may alter the growth of hormone-dependent tumor cells,
11 producing a potential anticarcinogenic effect (Spink et al., 1990; Gierthy et al., 1993). Because
12 the mechanism of the decreases in the tumors is unknown, extrapolation of these effects to
13 humans is premature. In considering overall risk, one must take into account factors such as the
14 range of doses to target organs and hormonal state to obtain a complete picture of hazard and
15 risk. Although exposure to dioxins may influence cancer response directly or indirectly,
16 positively or negatively, it is unlikely that such data will be available to argue that dioxin
17 exposure provides a net benefit to human health.
18
19 2.2.1.4. Cancer Hazard Characterization
20 TCDD, CDDs, CDFs, and dioxin-like PCBs are a class of well-studied compounds whose
21 human cancer potential is supported by a large database including limited epidemiological
22 support, unequivocal animal carcinogenesis, and biologic plausibility based on mode-of-action
23 data. In 1985, EPA classified TCDD and related compounds as "probable" human carcinogens
24 based on the available data. During the intervening years, the database relating to the
25 carcinogenicity of dioxin and related compounds has grown and strengthened considerably. In
26 addition, EPA guidance for carcinogen risk assessment has evolved (U.S. EPA, 1996). Under
27 EPA's current approach, TCDD is best characterized as a "human carcinogen." This means that,
28 based on the weight of all of the evidence (human, animal, mode of action), TCDD meets the
29 stringent criteria that allows EPA and the scientific community to accept a causal relationship
30 between TCDD exposure and cancer hazard. The guidance suggests that "human carcinogen" is
31 an appropriate descriptor of carcinogenic potential when there is an absence of conclusive
32 epidemiologic evidence to clearly establish a cause-and-effect relationship between human
33 exposure and cancer, but there is compelling carcinogenicity data in animals and mechanistic
34 information in animals and humans demonstrating similar modes of carcinogenic action. The
35 "human carcinogen" descriptor is suggested for TCDD because all of the following conditions
36 are met:
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1 • Occupational epidemiologic studies show an association between TCDD exposure
2 and increases in cancer at all sites, in lung cancer, and perhaps at other sites, but the
3 data are insufficient on their own to demonstrate a causal association
4 • There is extensive carcinogenicity in both sexes of multiple species of animals at
5 multiple sites.
6 • There is general agreement that the mode of TCDD' s carcinogenicity is AhR
7 dependent and proceeds through modification of the action of a number of receptor
8 and hormone systems involved in cell growth and differentiation, such as the
9 epidermal growth factor receptor and estrogen receptor.
10 • Equivalent body burdens in animals and in human populations expressing an
11 association between exposure to TCDD and cancer, and the determination of active
12 AhR and dioxin-responsive elements in the general human population. There is no
13 reason to believe that these events would not occur in the occupational cohorts
14 studied.
15 Other dioxin-like compounds are characterized as "likely" human carcinogens primarily
16 because of the lack of epidemiological evidence associated with their carcinogenicity, although
17 the inference based on toxicity equivalence is strong that they would behave in humans as TCDD
18 does. Other factors, such as the lack of congener-specific chronic bioassays, also support this
19 characterization. For each congener, the degree of certainty is dependent on the available
20 congener-specific data and its consistency with the generalized mode of action that underpins
21 toxicity equivalence for TCDD and related compounds. Based on this logic, all complex
22 environmental mixtures of TCDD and dioxin-like compounds would be characterized as "likely"
23 carcinogens, but the degree of certainty of the cancer hazard would be dependent on the major
24 constituents of the mixture. For instance, the hazard potential, although still considered "likely,"
25 would be characterized differently for a mixture whose TEQ was dominated by OCDD as
26 compared to one dominated by other PCDDs.
27
28 2.2.2. Reproductive and Developmental Effects
29 Several sections of this reassessment (Part II, Chapter 5, and Chapter 7b) have focused on
30 the variety of effects that dioxin and dioxin-like agents can have on human reproductive health
31 and development. Emphasis in each of these chapters has been on the discussion of the more
32 recent reports of the impact of dioxin-like compounds on reproduction and development. These
33 have been put into context with previous reviews of the literature applicable in risk assessment
34 (Hatch, 1984; Sweeney, 1994; Kimmel, 1988) to develop a profile of the potential for dioxin and
35 dioxin-like agents to cause reproductive or developmental toxicity, based on the available
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1 literature. An earlier version of the literature review and discussion contained in Part II, Chapter
2 5, has been previously published (Peterson et al., 1993).
3 The origin of concerns regarding a potential link between exposure to chlorinated dioxins
4 and adverse developmental events can be traced to early animal studies reporting increased
5 incidence of developmental abnormalities in rats and mice exposed early in gestation to 2,4,5-
6 trichlorophenol (2,4,5-T) (Courtney and Moore, 1971). 2,4,5-T is a herbicide that contains
7 dioxin and related compounds as impurities. Its use was banned in the late 1970s, but exposure
8 to human populations continued as a result of past production, use, and disposal.
9
10 2.2.2.1. Human
11 The literature base with regard to potential human effects is detailed in Part II, Chapter
12 7b. In general, there is little epidemiological evidence that makes a direct association between
13 exposure to TCDD or other dioxin-like compounds and effects on human reproduction or
14 development. One effect that may illustrate this relationship is the altered sex ratio (increased
15 females) seen in the 6 years after the Seveso, Italy, accident (Mocarelli et al., 1996, 2000).
16 Particularly intriguing in this latest evaluation is the observation that exposure before and during
17 puberty is linked to this sex ratio effect. Other sites have been examined for the effect of TCDD
18 exposure on sex ratio with mixed results, but with smaller numbers of offspring. Continued
19 evaluation of the Seveso population may provide other indications of impacts on reproduction
20 and development but, for now, such data are very limited and further research is needed.
21 Positive human data on developmental effects of dioxin-like compounds are limited to a few
22 studies of populations exposed to a complex mixture of potentially toxic compounds (e.g.,
23 developmental studies from the Netherlands and effects of ingestion of contaminated rice oil in
24 Japan (Yusho) and Taiwan (Yu-Cheng). In the latter studies, however, all four manifestations of
25 developmental toxicity (reduced viability, structural alterations, growth retardation, and
26 functional alterations) have been observed to some degree, following exposure to dioxin-like
27 compounds as well as other agents. Data from the Dutch cohort of children exposed to PCBs and
28 dioxin-like compounds (Huisman et al., 1995a,b; Koopman-Esseboom et al., 1994a-c; 1995a,b;
29 1996; Pluim et al., 1992, 1993, 1994; Weisglas-Kuperus et al., 1995; Patandin et al., 1998,
30 1999) suggest impacts of background levels of dioxin and related compounds on neurobehavioral
31 outcomes, thyroid function, and liver enzymes (AST and ALT). Although these effects cannot be
32 attributed solely to dioxin and related compounds, several associations suggest that these are, in
33 fact, likely to be Ah-mediated effects. Similarly, it is highly likely that the developmental effects
34 in human infants exposed to a complex mixture of PCBs, PCDFs, and poly chlorinated
35 quaterphenyls (PCQs) in the Yusho and Yu-Cheng poisoning episodes may have been caused by
36 the combined exposure to those PCB and PCDF congeners that are Ah-receptor agonists (Lii and
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1 Wong, 1984; Kuratsune, 1989; Rogan, 1989). However, it is not possible to determine the
2 relative contributions of individual chemicals to the observed effects.
3 The incidents at Yusho and Yu-Cheng resulted in increased perinatal mortality and low
4 birthweight in infants born to women who had been exposed. Rocker bottom heal was observed
5 in Yusho infants, and functional abnormalities have been reported in Yu-Cheng children. Not all
6 the effects that were seen are attributable only to dioxin-like compounds. The similarity of
7 effects observed in human infants prenatally exposed to this complex mixture with those reported
8 in adult monkeys exposed only to TCDD suggests that at least some of the effects in the Yusho
9 and Yu-Cheng children are due to the TCDD-like congeners in the contaminated rice oil ingested
10 by the mothers of these children. The similar responses include a clustering of effects in organs
11 derived from the ectodermal germ layer, referred to as ectodermal dysplasia, including effects on
12 the skin, nails, and Meibomian glands; and developmental and psychomotor delay during
13 developmental and cognitive tests (Chen et al., 1992). Some investigators believe that, because
14 all of these effects in the Yusho and Yu-Cheng cohorts do not correlate with TEQ, some of the
15 effects are exclusively due to nondioxin-like PCBs or a combination of all the congeners. It is
16 still not clear to what extent there is an association between overt maternal toxicity and
17 embryo/fetal toxicity in humans.
18 Of particular interest is the common developmental origin (ectodermal layer) of many of
19 the organs and tissues that are affected in the human. An ectodermal dysplasia syndrome has
20 been clearly associated with the Yusho and Yu-Cheng episodes, involving hyperpigmentation,
21 deformation of the fingernails and toenails, conjunctivitis, gingival hyperplasia, and
22 abnormalities of the teeth. An investigation of dioxin exposure and tooth development was done
23 in Finnish children as a result of studies of dental effects in dioxin-exposed rats, mice, and
24 nonhuman primates (Chapter 5), and in PCB-exposed children (Rogan et al., 1988). The Finnish
25 investigators examined enamel hypomineralization of permanent first molars in 6-7 year old
26 children (Alaluusua et al., 1996, 1999). The length of time that infants breast fed was not
27 significantly associated with either mineralization changes or with TEQ levels in the breast milk.
28 However, when the levels and length of breast feeding were combined in an overall score, a
29 statistically significant association was observed (r = 0.3, p = 0.003, regression analysis). These
30 data are discussed further in Part II, Chapter 7b. The developmental effects that can be
31 associated with the nervous system are also consistent with this pattern of impacts on tissues of
32 ectodermal origin, as the nervous system is of ectodermal origin. These data are limited but are
33 discussed in Part II, Chapter 7b.
34 Other investigations into noncancer effects of human exposure to dioxin have provided
35 human data on TCDD-induced changes in circulating reproductive hormones. This was one of
36 the effects judged as having a positive relationship with exposure to TCDD in Part II, Chapter
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1 7b. Levels of reproductive hormones have been measured with respect to exposure to 2,3,7,8-
2 TCDD in three cross-sectional medical studies. Testosterone, LH, and FSH were measured in
3 TCP and 2,4,5-T production workers (Egeland et al., 1994), in Army Vietnam veterans (Centers
4 for Disease Control Vietnam Experience Study, 1988), and in Air Force personnel, known as
5 "Ranch Hands," who handled and/or sprayed Agent Orange during the Vietnam War (Roegner et
6 al., 1991; Grubbs et al., 1995). The risk of abnormally low testosterone was two to four times
7 higher in exposed workers with serum 2,3,7,8-TCDD levels above 20 pg/g than in unexposed
8 referents (Egeland et al., 1994). In both the 1987 and 1992 examinations, mean testosterone
9 concentrations were slightly, but not significantly, higher in Ranch Hands (Roegner et al., 1991;
10 Grubbs et al., 1995). FSH and LH concentrations were no different between the exposed and
11 comparison groups. No significant associations were found between Vietnam experience and
12 altered reproductive hormone levels (Centers for Disease Control Vietnam Experience Study,
13 1988). Only the NIOSH study found an association between serum 2,3,7,8-TCDD level and
14 increases in serum LH.
15 The findings of the NIOSH and Ranch Hand studies are plausible given the
16 pharmacological and toxicological properties of 2,3,7,8-TCDD in animal models, which are
17 discussed in Part II, Chapters 5 and 7. One plausible mechanism responsible for the effects of
18 dioxins may involve their ability to influence hormone receptors. The AhR, to which 2,3,7,8-
19 TCDD binds, and the hormone receptors are signaling pathways that regulate homoeostatic
20 processes. These signaling pathways are integrated at the cellular level and there is considerable
21 "cross-talk" between these pathways. For example, studies suggest that 2,3,7,8-TCDD
22 modulates the concentrations of numerous hormones and/or their receptors, including estrogen
23 (Romkes and Safe, 1988; Romkes et al., 1987), progesterone (Romkes et al., 1987),
24 glucocorticoid (Ryan et al., 1989), and thyroid hormones (Gorski and Rozman, 1987).
25 In summary, the results from both the NIOSH and Ranch Hand studies are limited by the
26 cross-sectional nature of the data and the type of clinical assessments conducted. However, the
27 available data provide evidence that small alterations in human male reproductive hormone
28 levels are associated with serum 2,3,7,8-TCDD.
29
30 2.2.2.2. Experimental Animal
31 The extensive experimental animal database with respect to reproductive and
32 developmental toxicity of dioxin and dioxin-related agents has been discussed in Part II, Chapter
33 5. Dioxin exposure has been observed to result in both male and female reproductive effects, as
34 well as effects on development. These latter effects are among the most responsive health
35 endpoints to dioxin exposure (see Part II, Chapter 8). In general, the prenatal and developing
36 postnatal animal is more sensitive to the effects of dioxin than is the adult. In several instances
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1 (e.g., fetotoxicity in hamsters, rats, mice, and guinea pigs), the large species differences seen in
2 acute toxicity are greatly reduced when developing animals are evaluated. Most of the data
3 reviewed are from studies of six genera of laboratory animals. Although much of the data comes
4 from animals exposed only to TCDD, more recent studies of animals exposed to mixtures of
5 PCDD/PCDF isomers provide results that are consistent with the studies of TCDD alone.
6
7 2.2.2.2.1. Developmental toxicity. Dioxin exposure results in a wide variety of developmental
8 effects; these are observed in three different vertebrate classes and in several species within each
9 class. All four of the manifestations of developmental toxicity have been observed following
10 exposure to dioxin, including reduced viability, structural alterations, growth retardation, and
11 functional alterations. As summarized previously (Peterson et al., 1993), increased prenatal
12 mortality (rat and monkey), functional alterations in learning and sexual behavior (rat and
13 monkey), and changes in the development of the reproductive system (rat, hamster) occur at the
14 lowest exposure levels tested (see also Part II, Chapter 8).
15 Dioxin exposure results in reduced prenatal or postnatal viability in virtually every
16 species in which it has been tested. Previously, increased prenatal mortality appeared to be
17 observed only at exposures that also resulted in maternal toxicity. However, the studies of Olson
18 and McGarrigle (1990) in the hamster and Schantz et al. (1989) in the monkey were suggestive
19 that this was not the case in all species. Although the data from these two studies were limited,
20 prenatal death was observed in cases where no maternal toxicity was evident. In the rat,
21 Peterson's laboratory (Bjerke et al., 1994a,b; Roman et al., 1995) reported increased prenatal
22 death following a single exposure to TCDD during gestation that did not cause maternal toxicity,
23 and Gray et al. (1995a) observed a decrease in postnatal survival under a similar exposure
24 regimen. While identifying the presence or absence of maternal toxicity may be instructive as to
25 the specific origin of the reduced prenatal viability, it does not alter the fact that pre- and
26 postnatal deaths were observed. In either case, the Agency considers these effects as being
27 indicators of developmental toxicity in response to the exposure (U.S. EPA, 1991b).
28 Some of the most striking findings regarding dioxin exposure relate to the effects on the
29 developing reproductive system in laboratory animals. Only a single, low-level exposure to
30 TCDD during gestation is required to initiate these developmental alterations. Mably et al.
31 (1992a-c) originally reported that a single exposure of the Holtzman maternal rat to as low as
32 0.064 |ig/kg could alter normal sexual development in the male offspring. A dose of 0.064 ng/kg
33 in these studies results in a body maximal burden in the maternal animal of 64 ng/kg during
34 critical windows in development. More recently, these findings of altered normal sexual
35 development have been further defined (Bjerke et al., 1994a,b; Gray et al., 1995a; Roman et al.,
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1 1995), as well as extended to females and another strain and species (hamster) (Gray et al.,
2 1995b). In general, the findings of these later studies have produced qualitatively similar results
3 that define a significant effect of dioxin on the developing reproductive system.
4 In the developing male rat, TCDD exposure during the prenatal and lactational periods
5 results in delay of the onset of puberty as measured by age at preputial separation. There is a
6 reduction in testis weight, sperm parameters, and sex accessory gland weights. In the mature
7 male exposed during the prenatal and lactational periods, there is an alteration of normal sexual
8 behavior and reproductive function. Males exposed to TCDD during gestation are
9 demasculinized. Feminization of male sexual behavior and a reduction in the number of
10 implants in females mated with exposed males have also been reported, although these effects
11 have not been consistently found. These effects do not appear to be related to reductions in
12 circulating androgens, which were shown in the most recent studies to be normal. Most of these
13 effects occur in a dose-related fashion, some occurring at 0.05 ng/kg and 0.064 ng/kg, the lowest
14 TCDD doses tested (Mably et al., 1992c; Gray et al., 1997a).
15 In the developing female rat, Gray and Ostby (1995) have demonstrated altered sexual
16 differentiation in both the Long Evans and Holtzman strains. The effects observed depended on
17 the timing of exposure. Exposure during early organogenesis altered the cyclicity, reduced
18 ovarian weight, and shortened the reproductive lifespan. Exposure later in organogenesis
19 resulted in slightly lowered ovarian weight, structural alterations of the genitalia, and a slight
20 delay in puberty. However, cyclicity and fertility were not affected with the later exposure. The
21 most sensitive dose-dependent effects of TCDD in the female rat were structural alterations of
22 the genitalia that occurred at 0.20 ng TCDD/kg administered to the dam (Gray et al., 1997b).
23 As described above, studies demonstrating adverse health effects from prenatal exposures
24 often involved a single dose administered at a discrete time during pregnancy. The production of
25 prenatal effects at a given dose appears to require exposure during critical times in fetal
26 development. This concept is well supported by a recent report (Hurst et al., 2000) which
27 demonstrated the same incidence of adverse effects in rat pups born to dams with a single
28 exposure of 0.2 ng TCDD/kgBW on gestation day 15 (GD 15) versus 1.0 ng TCDD/kgBW on
29 gestation day 8 (GD 8). Both of these experimental paradigms result in the same fetal tissue
30 concentrations and body burdens during the critical window of sensitivity. For example,
31 exposure to 0.2 ng TCDD/kgBW on GD 15 results in 13.2 pg TCDD/g fetal tissue on GD 16;
32 exposure to 1.0 jig TCDD/kgBW on gestation GD 8 resulted in 15.3 pg TCDD/g fetus on GD 16.
33 This study demonstrates the appropriateness of the use of body burden to describe the effects of
34 TCDD when comparing different exposure regimens. The uncertainties introduced when trying
35 to compare studies with steady-state body burdens with single-dose studies may make it difficult
36 to determine a lowest effective dose. Application of pharmacokinetics models, described earlier
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1 in Parts I and II, to estimate body burdens at the critical time of development is expected to be a
2 sound method for relating chronic background exposures to the results obtained from single-dose
3 studies.
4 Structural malformations, particularly cleft palate and hydronephrosis, occur in mice
5 administered doses of TCDD. The findings, while not representative of the most sensitive
6 developmental endpoints, indicate that exposure during the critical period of organogenesis can
7 affect the processes involved in normal tissue formation. The TCDD-sensitive events appear to
8 require the AhR. Mouse strains that produce AhRs with relatively high affinity for TCDD
9 respond to lower doses than do strains with relatively low-affinity receptors. Moreover,
10 congeners with a greater affinity for the AhR are more developmentally toxic than those with a
11 lower affinity. This is consistent with the rank ordering of toxic potency based on affinity for the
12 receptor as discussed in Part II, Chapter 9.
13
14 2.2.2.2.2. Adult female reproductive toxicity. The primary effects of TCDD on female
15 reproduction appear to be decreased fertility, inability to maintain pregnancy for the full
16 gestational period and, in the rat, decreased litter size. In some studies of rats and of primates,
17 signs of ovarian dysfunction such as anovulation and suppression of the estrous cycle have been
18 reported (Kociba et al., 1976; Barsotti et al., 1979; Allen et al., 1979; Li et al., 1995a,b).
19
20 2.2.2.2.3. Adult male reproductive toxicity. TCDD and related compounds decrease testis and
21 accessory sex organ weights, cause abnormal testicular morphology, decrease spermatogenesis,
22 and reduce fertility when given to adult animals in doses sufficient to reduce feed intake and/or
23 body weight. In the testes of these different species, TCDD effects on spermatogenesis are
24 characterized by loss of germ cells, the appearance of degenerating spermatocytes and mature
25 spermatozoa within the lumens of seminiferous tubules, and a reduction in the number of tubules
26 containing mature spermatozoa (Allen and Lalich, 1962; Allen and Carstens, 1967; McConnell et
27 al., 1978; Chahoud et al., 1989). This suppression of spermatogenesis is not a highly sensitive
28 effect when TCDD is administered to postweanling animals, as an exposure of 1 ng/kg/day over
29 a period of weeks appears to be required to produce these effects.
30
31 2.2.2.3. Other Data Related to Developmental and Reproductive Effects
32 2.2.2.3.1. Endometriosis. The association of dioxin with endometriosis was first reported in a
33 study of Rhesus monkeys that had been exposed for 4 years to dioxin in their feed and then held
34 for an additional 10 years (Rier et al., 1993). There was a dose-related increase in both the
35 incidence and severity of endometriosis in the exposed monkeys as compared to controls.
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1 Follow-up on this group of monkeys revealed a clear association with total TEQ. A study in
2 which Rhesus monkeys were exposed to PCBs for up to 6 years failed to show any enhanced
3 incidence of endometriosis (Arnold et al., 1996). However, many of these monkeys were no
4 longer cycling, and the time may not have been adequate to develop the response. In the TCDD
5 monkey study, it took 7 years before the first endometriosis was noted (Rier et al., 1993). A
6 recent study in Cynomolgus monkeys has shown promotion of surgically induced endometriosis
7 by TCDD within 1 year after surgery (Yang et al., in press). Studies using rodent models for
8 surgically induced endometriosis have also shown the ability of TCDD to promote lesions in a
9 dose-related manner (Cummings et al., 1996,1999; Johnson et al., 1997; Bruner-Tran et al.,
10 1999). This response takes at least 2 months to be detected (Cummings et al., 1996, 1999;
11 Johnson et al., 1997). Another study in mice which failed to detect dioxin promotion of
12 surgically induced endometriosis only held the mice for only 1 month, not long enough to detect
13 a response (Yang et al., 1997). Prenatal exposure to mice also enhanced the sensitivity of the
14 offspring to the promotion of surgically induced endometriosis by TCDD. The effects of TCDD
15 in the murine model of endometriosis appear to be AhR-mediated, as demonstrated in a study in
16 which AhR ligands were able to promote the lesions, while non-Ah ligands, including a non-
17 dioxin-like PCB, had no effect on surgically induced endometriosis. Dioxin has also been shown
18 to result in endometriosis in human endometrial tissue implanted in nude mice (Bruner-Tran et
19 al., 1999).
20 Data on the relationship of dioxins to endometriosis in people is intriguing, but
21 preliminary. Studies in the early 1990s suggested that women with higher levels of persistent
22 organochlorines were at increased risk for endometriosis (Gerhard and Runnebaum, 1992). This
23 was followed by the observation that Belgian women, who have the highest levels of dioxins in
24 their background population, had higher incidences of endometriosis than reported from other
25 populations (Koninckx et al., 1994). A study from Israel then demonstrated that there was a
26 correlation between detectable TCDD in women with surgically confirmed endometriosis, in
27 comparison to those with no endometriosis (Mayani et al., 1997). Recent studies from Belgium
28 have indicated that women with higher body burdens, based on serum TEQ determinations, are at
29 greater risk for endometriosis (Pauwels et al., 1999). No association was seen with total PCBs in
30 this study. A small study in the United States, which did not involve surgically confirmed
31 endometriosis, saw no association between TCDD and endometriosis (Boyd et al., 1995).
32 Likewise, a study in Canada saw no association between total PCBs and endometriosis (Lebel et
33 al.. 1998). The negative association with total PCBs is not surprising because the rodent studies
34 have indicated that this response is AhR-mediated (Johnson et al., 1997). Preliminary results
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1 from Seveso suggest a higher incidence of endometriosis in the women from the two highly
2 exposed zones (A and B) as compared to the background incidence in Italy (Eskanzi et al., 1998).
3 The animal results lend biological plausibility to the epidemiology findings.
4 Endometriosis is not only an endocrine disorder, but is also associated with immune system
5 alterations (Rier et al., 1995). Dioxins are known to be potent modulators of the animal immune
6 system, as well as affecting estrogen homeostasis. Further studies are clearly needed to provide
7 additional support to this association of endometriosis and dioxins, as well as to demonstrate
8 causality.
9
10 2.2.2.3.2. Androgenic deficiency. The effects of TCDD on the male reproductive system when
11 exposure occurs in adulthood are believed to be due in part to an androgenic deficiency. This
12 deficiency is characterized in adult rats by decreased plasma testosterone and DHT
13 concentrations, unaltered plasma LH concentrations, and unchanged plasma clearance of
14 androgens and LH (Moore et al., 1985, 1989; Mebus et al., 1987; Moore and Peterson, 1988;
15 Bookstaff et al., 1990a). The cause of the androgenic deficiency was believed to be due to
16 decreased testicular responsiveness to LH and increased pituitary responsiveness to feedback
17 inhibition by androgens and estrogens (Moore et al., 1989, 1991; Bookstaff et al., 1990a,b; .
18 Kleeman et al., 1990). The single dose used in some of those earlier studies (15
19 ugTCDD/kgBW) is now known to affect Leydig cells (Johnson et al., 1994).
20
21 2.2.2 A. Developmental and Reproductive Effects Hazard Characterization
22 There is limited direct evidence addressing the issues of how or at what levels humans
23 will begin to respond to dioxin-like compounds with adverse impacts on development or
>4 reproductive function. The series of published Dutch studies suggest that pre- and early postnatal
!5 exposures to PCBs and other dioxin-like compounds may impact developmental milestones at
!6 levels at or near current average human background exposures. Although it is unclear whether
!7 these measured responses indicate a clearly adverse impact, if humans respond to TCDD
:8 similarly to animals in laboratory studies, there are indications that exposures at relatively low
9 levels might cause developmental effects and at higher exposure levels might cause reproductive
0 effects. There is especially good evidence for effects on the fetus from prenatal exposure. The
1 Yusho and Yu-Cheng poisoning incidents are clear demonstrations that dioxin-like compounds
2 can produce a variety of mild to severe developmental effects in humans that resemble the effects
3 of exposure to dioxins and dioxin-like compounds in animals. Humans do not appear to be
4- particularly sensitive or insensitive to effects of dioxin exposure in comparison to other animals.
5 Therefore it is reasonable to assume that human responsiveness would lie across the middle
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1 ranges of observed responses. This still does not address the issues surrounding the potentially
2 different responses humans (or animals) might have to the more complex and variable
3 environmental mixtures of dioxin-like compounds.
4 TCDD and related compounds have reproductive and developmental toxicity potential in
5 a broad range of wildlife, domestic, and laboratory animals. Many of the effects have been
6 shown to be TCDD dose-related. The effects on perinatal viability and male reproductive
7 development are among the most sensitive effects reported, occurring at a single prenatal
8 exposure range of as little as 0.05-0.075 fig/kg, resulting in calculated fetal tissue concentrations
9 of 3-4 ng/kg. In these studies, effects were often observed at the lowest exposure level tested,
10 thus a no-observed adverse effect level (NOAEL) has not been established for several of these
11 endpoints. In general, the structure-activity results are consistent with an AhR-mediated
12 mechanism for the developmental effects that are observed in the low dose range. The structure-
13 activity relationship in laboratory mammals appears to be similar to that for AhR binding. This
14 is especially the case with cleft palate in the mouse.
15 It is assumed that the responses observed in animal studies are indicative of the potential
16 for reproductive and developmental toxicity in humans. This is an established assumption in the
17 risk assessment process for developmental toxicity (U.S. EPA, 1991b). It is supported by the
18 number of animal species and strains in which effects have been observed. The limited human
19 data are consistent with an effect following exposure to TCDD or TCDD-like agents. In
20 addition, the phylogenetic conservation of the structure and function of the AhR also increases
21 our confidence that these effects may occur in humans.
22 Although there is evidence in experimental animals that exposure to dioxin-like
23 chemicals during development produces neurobehavioral effects, the situation in humans is more
24 complex. Studies in humans demonstrate associations between dioxin exposure and alterations
25 in neurological development. These same studies often show similar associations between
26 exposure to non-dioxin-like PCBs and these same effects. On the basis of the human studies, it
27 is possible that the alterations in neurological development are due to an interaction between the
28 dioxins and the non-dioxin-like PCBs. At present there are limited data that define the roles of
29 the dioxins versus the non-dioxin-like PCBs in these effects on neurological development.
30 In general, the structure-activity results on dioxin-like compounds are consistent with an
31 AhR-mediated mechanism for many of the developmental effects that are observed. The
32 structure-activity relationship in laboratory mammals appears to be similar to that for AhR
33 binding. This is especially the case with cleft palate in the mouse. However, a direct
34 relationship with Ah binding is less clear for other effects, including those involving the nervous
35 system.
36
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1 2.2.3. Immunotoxicity
2 2.2.3.1. Epidemiologic Finding
3 The available epidemiologic studies on immunologic function in humans relative to
4 exposure to 2,3,7,8-TCDD
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1 certain infectious agents, which likely result from TCDD-induced suppression of immunological
2 functions.
3 The primary antibody response to the T cell-dependent antigen, sheep red blood cells
4 (SRBCs), is the most sensitive immunological response that is consistently suppressed in mice
5 exposed to TCDD and related compounds. The degree of immunosuppression is related to the
6 potency of the dioxin-like congeners. There is remarkable agreement among several different
7 laboratories for the potency of a single acute dose of TCDD (i.e., suppression at a dose as low as
8 0.1 ng TCDD/kg with an average 50% immunosupressive dose [ID50J value of approximately 0.7
9 //g TCDD/kg) to suppress this response in Ah-responsive mice. Results of studies that have
10 compared the effects of acute exposure to individual PCDDs, PCDFs, and PCB congeners, which
11 differ in their binding affinity for the AhR, on this response have provided critical evidence that
12 certain dioxin-like congeners are also immunosuppressive. The degree of immunosuppression
13 has been found to be related to potency of the dioxin-like congeners. Antibody responses to
14 T cell-independent antigens, such as trinitrophenyl-lipopolysaccharide (TNP-LPS) and the
15 cytotoxic T lymphocyte (CTL) response, are also suppressed by a single acute exposure to
16 TCDD, albeit at higher doses than those that suppress the SRBC response. Although a thorough
17 and systematic evaluation of the immunotoxicity of TCDD-like congeners in different species
18 and for different immunological endpoints has not been performed, it can be inferred from the
19 available data that dioxin-like congeners are immunosuppressive.
20 Perinatal exposure of experimental animals to TCDD results in suppression of primarily
21 T cell immune functions, with evidence of suppression persisting into adulthood. In mice, the
22 effects on T cell functions appear to be related to the fact that perinatal TCDD exposure alters
23 thymic precursor stem cells in the fetal liver and bone marrow, and thymocyte differentiation in
24 the thymus. These studies suggest that perinatal development is a critical and sensitive period for
25 TCDD-induced immunotoxicity. Efforts should be made to determine the consequences of
26 perinatal exposure to TCDD and related compounds and mixtures on immune system integrity.
27
28 2.2.3.3. Other Data Related to Immunologic Effects
29 In addition to the TCDD-like congener results, studies using strains of mice that differ in
30 the expression of the AhR have provided critical evidence to support a role for Ah-mediated
31 immune suppression following exposure to dioxin-like compounds. Recent in vitro work also
32 supports a role for Ah-mediated immune suppression. Other in vivo and in vitro data, however,
33 suggest that non-Ah-mediated mechanisms may also play some role in immunotoxicity induced
34 by dioxin-like compounds. However, more definitive evidence remains to be developed to
35 support this latter view.
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1 Although the immunosuppressive potency of individual dioxin-like compounds in mice is
2 related to their structural similarity to TCDD, this pattern of suppression is observed only
3 following exposure to an individual congener. The immunotoxicity of TCDD and related
4 congeners can be modified by co-exposure to other congeners in simple binary or more complex
5 mixtures resulting in additive or antagonistic interactions. There is a need for the generation of
6 dose-response data of acute, subchronic, and chronic exposure to the individual congeners in a
7 mixture and for the mixture itself in order to fully evaluate potential synergistic, additive, or
8 antagonistic effects of environmentally relevant mixtures.
9 Animal host resistance models that mimic human disease have been used to assess the
10 effects of TCDD on altered host susceptibility. TCDD exposure increases susceptibility to
11 challenge with bacteria, viruses, parasites, and tumors. Mortality is increased in TCDD-exposed
12 mice challenged with certain bacteria. Increased parasitemia occurs in TCDD-exposed mice and
13 rats challenged with parasitic infections. Low doses of TCDD also alter resistance to virus
14 infections in rodents. Increased susceptibility to infectious agents is an important benchmark of
15 immunosuppression; however, the role that TCDD plays in altering immune-mediated
16 mechanisms important in murine resistance to infectious agents remains to be elucidated. Also,
17 because little is known about the effects that dioxin-like congeners have on host resistance, more
18 research is recommended in this area.
19 Studies in nonhuman primates exposed acutely, subchronically, or chronically to
20 halogenated aromatic hydrocarbons (HAH) have revealed variable alterations in lymphocyte
21 subpopulations, primarily T lymphocyte subsets. In three separate studies in which monkeys
22 were exposed subchronically or chronically to PCBs, the antibody response to SRBC was
23 consistently found to be suppressed. These results in nonhuman primates are important because
24 they corroborate the extensive database of HAH-induced suppression of the antibody response to
25 SRBC in mice and thereby provide credible evidence for immunosuppression by HAHs across
26 species. In addition, these data indicate that the primary antibody response to this T cell-
27 dependent antigen is the most consistent and sensitive indicator of HAH-induced
28 immunosuppression.
29 The available database derived from well-controlled animal studies on TCDD
30 immunotoxicity can be used for the establishment of NOELS. As the antibody response to
31 SRBCs has been shown to be dose-dependently suppressed by TCDD and related dioxin-like
32 compounds, this database is best suited for the development of dose-response modeling.
33
34 2.2.3.4. Immunologic Effects Hazard Characterization
35 Accidental or occupational exposure of humans to TCDD and/or related compounds
36 variably affects a number of immunological parameters. Unfortunately, the evaluation of
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1 immune system integrity in humans exposed to dioxin-like compounds has provided data that is
2 inconsistent across studies. However, the broad range of "normal" responses in humans due to
3 the large amount of variability inherent in such a heterogenous population, the limited number
4 and sensitivity of tests performed, and poor exposure characterization of the cohorts in these
5 studies compromise any conclusions about the ability of a given study to detect immune
6 alterations. Consequently, there are insufficient clinical data from these studies to fully assess
7 human sensitivity to TCDD exposure. Nevertheless, based on the results of the extensive animal
8 work, the database is sufficient to indicate that immune effects could occur in the human
9 population from exposure to TCDD and related compounds at some dose level. At present, it is
10 EPA's scientific judgment that TCDD and related compounds should be regarded as nonspecific
11 immunosuppressants and immunotoxicants until better data to inform this judgment are
12 available.
13 It is interesting that a common thread in several human studies is the observed reduction
14 in CD4+ T helper cells, albeit generally within the "normal" range, in cohorts exposed to dioxin-
15 like compounds. Even though these reductions may not translate into clinical effects, it is
16 important to note that these cells play an important role in regulating immune responses and that
17 their reduction in clinical diseases is associated with immunosuppression. Another important
18 consideration is that a primary antibody response following immunization was not evaluated in
19 any of the human studies. Because this immune parameter has been revealed to be the most
20 sensitive in animal studies, it is recommended that TCDD and related compounds be judged
21 immunosupressive and that this parameter be included in future studies of human populations
22 exposed to TCDD and related compounds. It is also recommended that research focused on
23 delineating the mechanism(s) underlying dioxin-induced immunotoxicity and
24 immunosuppression continue.
25
26 2.2.4. Chloracne
27 Chloracne and associated dermatologic changes are widely recognized responses to
28 TCDD and other dioxin-like compounds in humans. Along with the reproductive hormones
29 discussed above and gamma glutamyl transferase (GOT) levels, which are discussed below,
30 chloracne is one of the noncancer effects that has a strong positive association with exposure to
31 TCDD in humans (see Part II. Chapter 7b). Chloracne is a severe acnelike condition that
32 develops within months of first exposure to high levels of dioxin and related compounds. For
33 many individuals, the condition disappears after discontinuation of exposure, despite initial
34 serum levels of dioxin in the thousands of parts per trillion; for others, it may remain for many
35 years. The duration of persistent chloracne is on the order of 25 years, although cases of
36 chloracne persisting over 40 years have been noted (see Chapter 7, Epidemiology).
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1 In general, chloracne has been observed in most incidents where substantial dioxin
2 exposure has occurred, particularly among trichlorophenol (TCP) production workers and Seveso
3 residents (see Part II, Chapter 7b). The amount of exposure necessary for development of
4 chloracne has not been resolved, but studies suggest that high exposure (both high acute and
5 long-term exposure) to 2,3,7,8-TCDD increases the likelihood of chloracne, as evidenced by
6 chloracne in TCP production workers and Seveso residents who have documented high serum
7 2,3,7,8-TCDD levels (Beck et al., 1989; Fingerhut et al., 1991a; Mocarelli et al., 1991;
8 Neuberger et al., 1991) or in individuals who have a work history with long duration of exposure
9 to 2,3,7,8-TCDD-contaminated chemicals (Bond et al., 1989). In earlier studies, chloracne was
10 considered to be a "hallmark of dioxin intoxication" (Suskind, 1985). However, only in two
11 studies were risk estimates calculated for chloracne. Both were studies of different cohorts of
12 TCP production workers (Suskind and Hertzberg, 1984; Bond et al., 1989); one group was
13 employed in a West Virginia plant, the other in a plant in Michigan. Of the 203 West Virginia
14 workers, 52.7% (p<0.001) were found to have clinical evidence of chloracne, and 86.3% reported
15 a history of chloracne (p<0.001) (Suskind and Hertzberg, 1984). None of the unexposed workers
16 had clinical evidence or reported a history of chloracne. Among the Michigan workers, the
17 relative risk for cases of chloracne was highest for individuals with the longest duration of
18 exposure (>60 months; RR = 3.5, 95% CI = 2.3-5.1), those with the highest cumulative dose of
1.9 TCDD (based on duration of assignment across and within 2,3,7,8-TCDD-contaminated areas in
20 the plant) (RR = 8.0, 95% CI = 4.2-15.3), and those with the highest intensity of 2,3,7,8-TCDD
21 exposure (RR = 71.5, 95% CI = 32.1-159.2) (Bond etal., 1989).
22 Studies in multiple animal species have been effective in describing the relationship
23 between 2,3,7,8-TCDD and chloracne, particularly in rhesus monkeys (McNulty, 1977; Allen et
24 al., 1977; McConnell et al., 1978). Subsequent to exposure to 2,3,7,8-TCDD, monkeys
25 developed chloracne and swelling of the meibomian glands, modified sebaceous glands in the
26 eyelid. The histologic changes in the meibomian glands are physiologically similar to those
27 observed in human chloracne (Dunagin, 1984).
28 In summary, the evidence provided by the various studies convincingly supports what is
29 already presumed, that chloracne is a common sequel of high levels of exposure to 2,3,7,8-
30 TCDD and related compounds. More information is needed to determine the level and frequency
31 of exposure to dioxin-like compounds needed to cause chloracne, and whether personal
32 susceptibility plays a role in the etiology. Finally, it is important to recall that the absence of
33 chloracne does not imply lack of exposure (Mocarelli et al., 1991).
34
35
36
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1 2.2.5. Diabetes
2 Diabetes mellitus is a heterogeneous disorder that is a consequence of alterations in the
3 number or function of pancreatic beta cells responsible for insulin secretion and carbohydrate
4 metabolism. Diabetes and fasting serum glucose levels were evaluated in more recent cross-
5 sectional medical studies because of the apparently high prevalence of diabetes and abnormal
6 glucose tolerance tests in one case report of 55 TCP workers (Pazderova-Vejlupkova et al.,
7 1981). Recent epidemiology studies, as well as early case reports, have indicated a weak
8 association between serum concentrations of dioxin and diabetes. This association was first
9 noted in the early 1990s when a decrease in glucose tolerance was seen in the NIOSH cohort.
10 This was followed by a report of an increase in diabetes in the Ranch Hand cohort (Michalek et
11 al., 1999; Longnecker and Michalek, 2000). Several reports from other occupational cohorts
12 (Steenland et al., 1999; Vena et al., 1998), as well as the Sevesd population (Pesatori et al., 1998)
13 then followed. There was not a significant increase in diabetes in the NIOSH mortality study,
14 although 6 of the 10 most highly exposed workers did have diabetes (Calvert et al., 1999).
15 However, it is well understood that mortality studies are limited in their ability to assess risk
16 from diabetes mellitus. The recent paper by Longnecker and Michalek (2000) found a pattern
17 suggesting that low levels of dioxin may influence the prevalence of diabetes. However, these
18 results did not show an exposure-response relationship. Because it is the only study of its type to
19 have been published, additional population-based studies are warranted to validate its findings.
20 The most recent update of the Ranch Hand study shows a 47% excess of diabetes in the most
21 heavily exposed group of veterans (Michalek et al., 1999).
22 Most of the data suggest that the diabetes is Type II, or adult-onset, diabetes, rather than
23 insulin dependent, or Type I. Aging and obesity are the key risk factors for Type II diabetes.
24 However, dioxins may shift the distribution of sensitivity, putting people at risk at younger ages
25 or with less weight. Dioxin alters lipid metabolism in multiple species, including humans
26 (Sweeney et al., 1997; Pohjanvirta and Tuomisto, 1994). Dioxin also alters glucose uptake into
27 both human and animal cells in culture (Enan and Matsumura, 1994; Olsen et al., 1994).
28 Mechanistic studies have demonstrated that dioxin affects glucose transport (Enan and
29 Matsumura, 1994), a property under the control of the hypoxia response pathway (Ouiddir et al.,
30 1999). A key regulatory protein in this pathway is the partner of the AhR, Arnt (also known as
31 HIF1 -beta) (Gu et al., 2000; Taylor and Zhulin, 1999). Activation of the AhR by dioxin may
32 compete with other pathways, such as the HIF pathway, for Arnt (Gradin, et al., 1992). Dioxin
33 has also been shown to downregulate the insulin growth factor receptor (Liu et al., 1992). These
34 three issues — altered lipid metabolism, altered glucose transport, and alterations in the insulin
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1 signaling pathway — all provide biological plausibility to the association of dioxins with
2 diabetes.
3 A causal relationship between diabetes and dioxin has not been established, although the
4 toxicologic data are suggestive of a plausible mechanism. Many questions are yet to be
5 answered. Does diabetes alter the pharmacokinetics of dioxin? Diabetes is known to alter the
6 metabolism of several drugs in humans (Matzke et al., 2000) and may also alter dioxin
7 metabolism and kinetics. As adult-onset diabetes is also associated with overweight, and body
8 composition has been shown to modify the apparent half-life of dioxin, could the rate of
9 elimination of dioxins be lowered in people with diabetes, causing them to have higher body
10 burdens? This may be relevant to the background population, but is hardly likely to be an
11 explanation in highly exposed populations. Key research needs are twofold. The first is to
12 develop an animal model in which to study the association between dioxins and diabetes and
13 glucose perturbation. Several rodent models for Type II diabetes exist and may be utilized. The
14 second is to conduct population-based incidence studies that take into account dioxin levels as
15 well as the many known factors associated with diabetes. Although diabetes may cause the
16 underlying pathology leading to death, it is often not attributed as the cause of death, and thus
17 limits the utility of mortality studies.
18
19 2.2.6. Other Effects
20 2.2.6.1. Elevated GGT
21 As mentioned above, there appears to be a consistent pattern of increased GGT levels
22 among individuals exposed to 2,3,7,8-TCDD-contaminated chemicals. Elevated levels of serum
23 GGT have been observed within a year after exposure in Seveso children (Caramaschi et al.,
24 1981; Mocarelli et al., 1986) and 10 or more years after cessation of exposure among TCP and
25 2,4,5-T production workers (May, 1982; Martin, 1984; Moses et al., 1984; Calvert et al., 1992)
26 and among Ranch Hands (Roegner et al., 1991; Grubbs et al., 1995). All of these groups had a
27 high likelihood of substantial exposure to 2,3,7,8-TCDD. In addition, for those studies that
28 evaluated dose-response relationships with 2,3,7,8-TCDD levels, the effect was observed only at
29 the highest levels or categories of 2,3,7,8-TCDD and, in the NIOSH study, only in workers who
30 reported drinking high levels of alcohol. In contrast, although background levels of serum
31 2,3,7,8-TCDD suggested minimal exposure to Army Vietnam veterans, GGT was increased, at
32 borderline significance, among Vietnam veterans compared to non-Vietnam veterans (Centers for
33 Disease Control Vietnam Experience Study, 1988). In addition, despite the increases observed in
34 some occupational cohorts, other studies of TCP production workers from West Virginia or
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1 Missouri residents measured but did not report elevations in GOT levels (Suskind and Hertzberg,
2 1984; Webb etal., 1989).
3 In clinical practice, GOT is often measured because it is elevated in almost all
4 hepatobiliary diseases and is used as a marker for alcoholic intake (Guzelian, 1985). In
5 individuals with hepatobiliary disease, elevations in GGT are usually accompanied by increases
6 in other hepatic enzymes, e.g., AST and ALT, and metabolites, e.g., uro- and coproporphyrins.
7 Significant increases in hepatic enzymes other than GGT and metabolic products were not
8 observed in individuals whose GGT levels were elevated 10 or more years after exposure ended,
9 suggesting that the effect may be GGT-specific. These data suggest that in the absence of
10 increases in other hepatic enzymes, elevations in GGT are associated with exposure to 2,3,7,8-
11 TCDD, particularly among individuals who were exposed to high 2,3,7,8-TCDD levels.
12 The animal data with respect to 2,3,7,8-TCDD-related effects on GGT are sparse.
13 Statistically significant changes in hepatic enzyme levels, particularly AST, ALT, and ALK, have
14 been observed after exposure to 2,3,7,8-TCDD in rats and hamsters (Gasiewicz et al., 1980;
15 Kociba et al., 1978; Olson et al., 1980). Only one study evaluated GGT levels (Kociba et al.,
16 1978). Moderate but statistically nonsignificant increases were noted in rats fed 0.10 ng/kg
17 2,3,7,8-TCDD daily for 2 years, and no increases were observed in control animals.
18 In summary, GGT is the only hepatic enzyme examined that was found in a number of
19 studies to be chronically elevated in adults exposed to high levels of 2,3,7,8-TCDD. The
20 consistency of the findings in a number of studies suggests that the elevation may reflect a true
21 effect of exposure, but its clinical significance is unclear. Long-term pathological consequences
22 of elevated GGT have not been illustrated by excess mortality from liver disorders or cancer, or
23 in excess morbidity in the available cross-sectional studies.
24 It must be recognized that the absence of an effect in a cross-sectional study, for example,
25 liver enzymes, does not obviate the possibility that the enzyme levels may have increased
26 concurrent to the exposure but declined after cessation. The apparently transient elevations in
27 ALT levels among the Seveso children suggest that hepatic enzyme levels other than GGT may
28 react in this manner to 2,3,7,8-TCDD exposure.
29
30 2.2.6.2. Thyroid Function
31 Many effects of 2,3,7,8-TCDD exposure in animals resemble signs of thyroid dysfunction
32 or significant alterations of thyroid-related hormones. In the few human studies that examined
33 the relationship between 2,3,7,8-TCDD exposure and hormone concentrations in adults, the
34 results are mostly equivocal (Centers for Disease Control Vietnam Experience Study, 1988;
35 Roegner et al., 1991; Grubbs et al., 1995; Suskind and Hertzberg, 1984). However,
36 concentrations of thyroid binding globulin (TBG) appear to be positively correlated with current
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1 levels of 2,3,7,8-TCDD in the BASF accident cohort (Ott et al., 1994). Little additional
2 information on thyroid hormone levels has been reported for production workers and none for
3 Seveso residents, two groups with documented high serum 2,3,7,8-TCDD levels.
4 Thyroid hormones play important roles in the developing nervous system in all vertebrate
5 species, including humans. In fact, thyroid hormones are so important in development that in the
6 United States all infants are tested for hypothyroidism shortly after birth. Several studies of
7 nursing infants suggest that ingestion of breast milk with a higher dioxin TEQ may alter thyroid
8 function (Pluim et al., 1993; Koopman-Esseboom et al., 1994c; Nagayama et al., 1997).
9 These findings suggest a possible shift in the distribution of thyroid hormones, particularly T4,
10 and point out the need for collection of longitudinal data to assess the potential for long-term
11 effects associated with developmental exposures. The exact processes accounting for these
12 observations in humans are unknown, but when put in perspective of animal responses, the
13 following might apply: dioxin increases the metabolism and excretion of thyroid hormone,
14 mainly T4, in the liver. Reduced T4 levels stimulate the pituitary to secrete more TSH, which
15 enhances thyroid hormone production. Early in the disruption process, the body can
16 overcompensate for the loss of T4, which may result in a small excess of circulating T4 to the
17 increased TSH. In animals given higher doses of dioxin, the body is unable to maintain
18 homeostasis, and TSH levels remain elevated and T4 levels decrease.
19
20 2.2.6.3. Cardiovascular Disease
21 Elevated cardiovascular disease has been noted in several of the occupational cohorts
22 (Steenland et al., 1999; Sweeney et al., 1997; Flesch-Janys et al., 1995) and in Seveso (Pesatori
23 et al., 1998), as well as in the rice oil poisonings. This appears to be associated with ischemic
24 heart disease and in some cases with hypertension. In fact, recent data from the Ranch Hand
25 study indicates that dioxin may be a possible risk factor for the development of essential
26 hypertension (Grubbs, et al., 1995). Elevated blood lipids have also been seen in several cohorts.
27 The association of dioxins with heart disease in people has biological plausibility given the data
28 in animals. First is the key role of hypoxia in heart disease, and the potential for involvement of
29 the activated AhR in blocking an hypoxic response (Gradin et al., 1996; Gu et al., 2000). Dioxin
30 has been shown to perturb lipid metabolism in multiple laboratory species (Pohjanvirta and
31 Tuomisto, 1994). The heart, in fact the entire vascular system, is a clear target for the adverse
32 effects of dioxin in fish and birds (Hornung et al., 1999; Cheung et al., 1981). In mammals,
33 dioxin has been shown to disturb heart rhythms at high doses in guinea pigs (Gupta et al., 1973;
34 Pohjanvirta and Tuomisto, 1994).
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1 2.2.6.4. Oxidative Stress
2 Several investigators have hypothesized that the some of the adverse effects of dioxin and
3 related compounds may be associated with oxidative stress. Induction of CYPIA isoforms has
4 been shown to be associated with oxidative DNA damage (Park et al., 1996). Altered
5 metabolism of endogenous molecules such as estradiol can lead to the formation of quinones and
6 redox cycling. This has been hypothesized to play a role in the enhanced sensitivity of female
7 rats to dioxin-induced liver tumors (Tritscher et al., 1996). Lipid peroxidation, enhanced DNA
8 single-strand breaks, and decreased membrane fluidity have been shown in liver as well as in
9 extrahepatic tissues following exposure to high doses of TCDD (Stohs, 1990). A dose- and time-
10 dependent increase in superoxide anion is caused in peritoneal macrophages by exposure to
11 TCDD (Alsharif et al., 1994). A recent report that low-dose (0.15 ng TCDD/kg/day) chronic
12 exposure can lead to oxidative changes in several tissues in mice (Slezak et al., 2000) suggests
13 that this mechanism or mode of toxicity deserves further attention.
14
15
3. MECHANISMS AND MODE OF DIOXIN ACTION
1 Mechanistic studies can reveal the biochemical pathways and types of biological and
2 molecular events that contribute to dioxin's adverse effects. For example, much evidence
3 indicates that TCDD acts via an intracellular protein (the aryl hydrocarbon receptor, AhR), which
4 functions as a ligand-dependent transcription factor in partnership with a second protein (known
5 as the AhR nuclear translocator, Arnt). Therefore, from a mechanistic standpoint, TCDD's
6 adverse effects appear likely to reflect alterations in gene expression that occur at an
7 inappropriate time and/or for an inappropriately long time. Mechanistic studies also indicate that
8 several other proteins contribute to TCDD's gene regulatory effects and that the response to
9 TCDD probably involves a relatively complex interplay between multiple genetic and
10 environmental factors. If TCDD operates through such a mechanism, as all evidence indicates,
11 then there are certain constraints on the possible models that can plausibly account for TCDD's
12 biological effects and, therefore, on the assumptions used during the risk assessment process
13 (e.g., Poland, 1996; Limbird and Taylor, 1998).
14 Mechanistic knowledge of dioxin action may also be useful in other ways. For example,
15 a further understanding of the ligand specificity and structure of the AhR will likely assist in the
16 identification of other chemicals to which humans are exposed that may add to, synergize, or
17 block the toxicity of TCDD. Knowledge of genetic polymorphisms that influence TCDD
18 responsiveness may also allow the identification of individuals at greater risk from exposure to
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1 dioxin. In addition, knowledge of the biochemical pathways that are altered by TCDD may help
2 identify novel targets for the development of drugs that can antagonize dioxin's adverse effects.
3 As described below, biochemical and genetic analyses of the mechanisms by which
4 dioxin may modulate particular genes have revealed the outline of a novel regulatory system
5 whereby a chemical signal can alter cellular regulatory processes. Future studies of dioxin action
6 have the potential to provide additional insights into mechanisms of mammalian gene regulation
7 that are of a broader interest. Additional perspectives on dioxin action can be found in several
8 recent reviews (Birnbaum, 1994a,b; Schecter, 1994; Hankinson, 1995; Schmidt and Bradfield,
9 1996; Gasiewicz, 1997; Rowlands and Gustafsson, 1997; Denison et al, 1998; Hahn, 1998;
10 Wilson and Safe, 1998).
11 Knowledge of the mode(s) of action by which the broad class of chemicals known as
12 dioxins act may facilitate the risk assessment process by imposing bounds on the models used to
13 describe possible responses of humans resulting from exposure to mixtures of these chemicals.
14 The relatively extensive database on TCDD, as well as the more limited database on related
15 compounds, has been reviewed with emphasis on the role of the specific cellular receptor for
16 TCDD and related compounds, the AhR, in the mode(s) of action. This discussion will focus on
17 summarizing the elements of the mode(s) of dioxin action that are relevant for understanding and
18 characterizing dioxin risk for humans. These elements include:
19 • Similarities between humans and other animals with regard to receptor structure and
20 function;
21 • The relationship between receptor binding and toxic effects; and
22 • The extent to which the purported mechanism(s) or mode(s) of action might contribute to
23 the diversity of biological responses seen in animals and, to some extent, in humans.
24
25 In addition, this section will identify important and relevant knowledge gaps and
26 uncertainties in the understanding of the mechanism(s) of dioxin action, and will indicate how
27 these may affect the approach to risk characterization.
28
29 3.1. MODE VERSUS MECHANISM OF ACTION
30 In the context of revising its Cancer Risk Assessment Guidelines, the EPA has proposed
31 giving greater emphasis to use of all of the data in hazard characterization, dose-response
32 characterization, exposure characterization, and risk characterization (U.S. EPA, 1996). One aid
33 to the use of more information in risk assessment has been the definition of mode versus
34 mechanism of action. Mechanism of action is defined as the detailed molecular description of a
35 key event in the induction of cancer or other health endpoints. Mode of action refers to the
36 description of key events and processes, starting with interaction of an agent with the cell,
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1 through functional and anatomical changes, resulting in cancer or other health endpoints.
2 Despite a desire to construct detailed biologically based toxicokinetic and toxicodynamic models
3 to reduce uncertainty in characterizing risk, few examples have emerged. Use of a mode-of-
4 action approach recognizes that, although all of the details may not have been worked out,
5 prevailing scientific thought supports moving forward using a hypothesized mode of action
6 supported by data. This approach is consistent with advice offered by the National Research
7 Council in its report entitled, Science and Judgment in Risk Assessment (NAS/NRC, 1994).
8 Mode-of-action discussions help to provide answers to the questions: How does the chemical
9 produce its effect? Are there mechanistic data to support this hypothesis? Have other modes of
10 action been considered and rejected? In order to demonstrate that a particular mode of action is
11 operative, it is generally necessary to outline the hypothesized sequence of events leading to
12 effects, identify key events that can be measured, outline the information that is available to
13 support the hypothesis, and discuss those data that are inconsistent with the hypothesis or support
14 an alternative hypothesis. Following this, the information is weighed to determine if there is a
15 causal relationship between key precursor events associated with the mode of action and cancer
16 or other toxicological endpoint.
17 3.2. GENERALIZED MODEL FOR DIOXIN ACTION
18 Dioxin and related compounds are generally recognized to be receptor-mediated
19 toxicants. The generalized model has evolved over the years to appear as illustrated in Table 3-1
20 and Figure 2-1.
21
22 3.2.1. The Receptor Concept
23 One of the fundamental concepts that influences our approach to risk assessment of
24 dioxin and related compounds is the receptor concept. The idea that a drug, hormone,
25 neurotransmitter, or other chemical produces a physiological response by interacting with a
26 specific cellular target molecule, i.e., a "receptor," evolved from several observations. First,
27 many chemicals elicit responses that are restricted to specific tissues. This observation implies
28 that the responsive tissue (e.g., the adrenal cortex) contains a "receptive" component whose
29 presence is required for the physiologic effect (e.g., cortisol secretion). Second, many chemicals
30 are quite potent. For example, picomolar to nanomolar concentrations of numerous hormones
31 and growth factors elicit biological effects. This observation suggests that the target cell contains
32 a site(s) to which the particular chemical binds with high affinity. Third, stereoisomers of some
33 chemicals (e.g., catecholamines, opioids) differ by orders of magnitude in their ability to produce
34 the same biological response. This observation indicates that the molecular shape of the
35 chemical strongly influences its biological activity. This, in turn, implies that the binding site on
36 or in the target cell also has a specific, three-dimensional configuration. Together, these types of
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1 observations support the prediction that the biological responses to some chemicals involve
2 stereospecific, high-affinity binding of the chemicals to specific receptor sites located on or in the
3 target cell. Many of these characteristics were noted for TCDD and related compounds.
4 The availability of compounds of high specific radioactivity has permitted quantitative
5 analyses of their binding to cellular components in vitro. To qualify as a potential "receptor," a
6 binding site for a given chemical must satisfy several criteria: (1) the binding site must be
7 saturable, i.e., the number of binding sites per cell should be limited; (2) the binding should be
8 reversible; (3) the binding affinity measured in vitro should be consistent with the potency of the
9 chemical observed in vivo; (4) if the biological response exhibits stereospecificity, so should the
10 in vitro binding; (5) for a series of structurally related chemicals, the rank order for binding
11 affinity should correlate with the rank order for biological potency; and (6) tissues that respond to
12 the chemical should contain binding sites with the appropriate properties.
13 The binding of a chemical ("ligand") to its specific receptor is assumed to obey the law of
14 mass action; that is, it is a bimolecular, reversible interaction. The concentration of the liganded,
15 or occupied, receptor [RL] is a function of both the ligand concentration [L] and the receptor
16 concentration [R] as shown in Equation 3-1:
17 k,
18 v (3-1)
19 [L] + [R] ^— [RL]
20 k2
21 Inherent in this relationship is the fact that the fractional occupancy (i.e., [RL]/[RJ) is a
22 function of ligand concentration [L] and the apparent equilibrium dissociation constant KD, which
23 is a measure of the binding affinity of the ligand for the receptor, that is, [RLJ/fRJ = [L]/(KD+
24 [L]), where KD = [L] [RJ/[LR] = k2/k,. Therefore, the relationship between receptor occupancy
25 and ligand concentration is hyperbolic. At low ligand concentrations (where [L]«KD), a small
26 increase in [LJ produces an approximately linear increase in fractional receptor occupancy. At
27 high ligand concentration (where [L]»KD), the fractional occupancy of the receptor is already
28 very close to 1, that is, almost all receptor sites are occupied. Therefore, a small increase in [L]
29 is likely to produce only a slight increase in receptor occupancy. These issues are discussed in
30 regard to TCDD binding to the AhR and dose-response in Part II, Chapter 8.
31 Ligand binding constitutes only one aspect of the receptor concept. By definition, a
32 receptor mediates a response, and the functional consequences of the ligand-receptor binding
33 represent an essential aspect of the receptor concept. Receptor theory attempts to quantitatively
34 relate ligand binding to biological responses. The classical "occupancy" model of Clark (1933)
35 postulated that (1) the magnitude of the biological response is directly proportional to the fraction
36 of receptors occupied and (2) the response is maximal when all receptors are occupied.
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1 However, analyses of numerous receptor-mediated effects indicate that the relationship between
2 receptor occupancy and biological effect is not as straightforward as Clark envisioned. In certain
3 cases, no response occurs even when there is some receptor occupancy. This suggests that there
4 may be a threshold phenomenon that reflects the biological "inertia" of the response (Ariens et
5 al., 1960). In other cases, a maximal response occurs well before all receptors are occupied, a
6 phenomenon that reflects receptor "reserve" (Stephenson, 1956). Therefore, one cannot simply
7 assume that the relationship between fractional receptor occupancy and biological response is
8 linear. Furthermore, for a ligand (such as TCDD) that elicits multiple receptor-mediated effects,
9 one cannot assume that the binding-response relationship for a simple effect (such as enzyme
10 induction) will necessarily be identical to that for a different and more complex effect (such as
11 cancer). The cascades of events leading to different complex responses (e.g., altered immune
12 response to pathogens or development of cancer) are likely to be different, and other rate-limiting
13 events likely influence the final biological outcome resulting in different dose-response curves.
14 Thus, even though ligand binding to the same receptor is the initial event leading to a spectrum
15 of biological responses, ligand-binding data may not always mimic the dose-effect relationship
16 observed for particular responses.
17 Another level of complexity is added when one considers different chemical ligands that
18 bind to the same receptor. Relative potencies are determined by two properties of the ligand:
19 affinity for the receptor and capacity to confer a particular response in the receptor (e.g., a
20 particular conformational change), also called efficacy (Stephenson, 1956). Ligands with
21 different affinities and the same degree of efficacy would be expected to produce parallel dose-
22 response curves with the same maximal response within a particular model system. However,
23 ligands of the same affinity with different efficacies may result in dose-response curves that are
24 not parallel or that differ in maximal response. Many of these issues may apply to dioxin-
25 receptor interactions. To the extent that they do occur, they may present complications to use of
26 the toxicity equivalence approach, particularly for extrapolation purposes. As described
27 previously, this argues strongly for the use of all available information in setting TEFs and
28 highlights the important role that scientific judgment plays in the face of incomplete mechanistic
29 understanding to address uncertainty.
30
31 3.2.2. A Framework to Evaluate Mode of Action
32 EPA in its revised proposed cancer guidelines (U.S. EPA, 1999) recommends the use of a
33 structured approach to evaluating mode of action. This approach is similar to and builds upon an
34 approach developed within the World Health Organization's (WHO) International Programme on
35 Chemical Safety's Harmonization Project (WHO, 2000). Fundamentally, the approach uses a
36 modification of the "Hill Criteria" (Hill, 1965), which have been used in the field of
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1 epidemiology for many years to examine causality between associations of exposures and effects.
2 The framework calls for a summary description of the postulated mode of action, followed by the
3 identification of key events that are thought to be part of the mode of action. These key events
4 are then evaluated as to strength, consistency, and specificity of association with the endpoint
5 under discussion. Dose-response relationships between the precursor key events are evaluated
6 and temporal relationships are examined to be sure that "precursor" events actually precede the
7 induction of the endpoint. Finally, biological plausibility and coherence of the data with the
8 biology are examined and discussed. All of these "criteria" are evaluated and conclusions are
9 drawn with regard to postulated mode of action.
10 In the case of dioxin and related compounds, elements of such an approach are found for
11 a number of effects including cancer in Part II. Application of the framework to dioxin and
12 related compounds would now stop short of evaluating the association between the chemical or
13 complex mixture and clearly adverse effects. Instead, the approach would apply to early events,
14 e.g., receptor binding and intermediate events such as enzyme induction or endocrine impacts.
15 Additional data will be required to extend the framework to most effects, but several have data
16 that would support a framework analysis. Several of these are discussed below.
17
18 3.2.3. Mechanistic Information, Mode of Action, and Risk Assessment
19 A substantial body of evidence from investigations using experimental animals indicates
20 that the AhR mediates the biological effects of TCDD. The key role of the AhR in the effects of
21 dioxin and related compounds is substantiated by four lines of research: (1) structure/activity
22 relationships; (2) responsive versus nonresponsive mouse strains; (3) mutant cell lines; and (4)
23 the development of transgenic mice in which the gene for the AhR has been "knocked out"
24 Birnbaum, 1994; Fernandez-Salguero et al., 1996; Lahvis and Bradfield, 1998). Dioxin appears
25 not to cause effects in the AhR knockout mouse (Fernandez-Salguero et al., 1996; Lahvis and
26 Bradfield, 1998). It is clear that the AhR is necessary, but not sufficient, for essentially all of the
27 well-studied responses to dioxin. The AhR functions as a ligand-activated transcription factor,
28 controlling the expression of specific genes via interaction with defined nucleotide sequences in
29 the promoter regions. In order to control transcription, the TCDD-AhR complex interacts with
30 another protein, Arnt, to bind to the dioxin response element. This complex is also bound by
31 other nuclear coactivators, and/or corepressors, to bind to the transcriptional complex and initiate
32 transcription (Gu et al., 2000). However, Arnt has many other partners that control hypoxia
33 response, neuronal differentiation, morphological branching, etc. (Gu et al., 2000). It is possible
34 that there are other mechanisms of how dioxin initiates its toxic effects, apart from its direct
35 transcriptional activation of drug metabolizing genes. It may be that the adverse effects of dioxin
36 may result from competition of the ligand-activated AhR with other Arnt partners (Gradin et al.,
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1 1996). The AhR, Arat, and Arnt partners are all members of the PAS family of basic helix-loop-
2 helix proteins that function as nuclear regulatory proteins (Gu et al., 2000). The PAS proteins are
3 highly conserved, with homologous proteins being present in prokaryotes. They play key roles in
4 circadian rhythms and development. The embryolethality of Amt knockout mice, as well as the
5 reduced fertility and viability of the AhR knockout mice (Abbott et al., 1999), point to a key role
6 of these proteins in normal physiology.
7 Another potential mechanism by which TCDD can cause effects involves the
8 protein/protein interactions of the AhR. When not bound to a ligand, the AhR exists in a
9 multimeric protein complex, involving two molecules of heat shock protein 90 as well as other
10 proteins, including AIP/XAP2/ara9, ara3, ara6, src, rel, and Rb (Carver et al., 1998; Enan and
11 Matsumura, 1996; Puga et al., 2000a). AIP/XAP2/ara9 is a 37 kd protein that is related to known
12 immunophilins and involved in control of signal transduction processes. C-src has been shown
13 to be associated with the AhR in several tissues and is a tyrosine kinase (Enan and Matsumura,
14 1996). Dioxin has been known to cause a rapid increase in phosphorylation upon exposure.
15 Recent studies have shown that rel, which is a key component of the NF-kappaB complex that
16 controls apoptosis, binds to the AhR complex (Tian et al., 1999; Puga et al., 2000b). Similarly,
17 several investigators have demonstrated an association between the AhR and the retinoblastoma
18 protein; this has been shown to affect cell cycling (Puga et al., 2000a).
19 Thus, the AhR may act as a negative regulator of key regulator molecules involved in
20 phosphorylation, cell cycling, and apoptosis in its unliganded state. Upon binding of TCDD,
21 these other proteins are now able to exert their effects. In addition, dioxin may act by competing
22 for Arnt<, thus blocking key roles of other PAS regulatory proteins. Both of these mechanisms
23 for the effects of dioxin are in addition to the direct role of the ligand-bound form of the receptor
24 in control of transcription via the well-studied mechanism of binding to a dioxin-response
25 element in DNA.
26 Although studies using human tissues are much less extensive, it appears reasonable to
27 assume that dioxin's mode of action to produce effects in humans includes receptor-mediated key
28 events. Studies using human organs and cells in culture are consistent with this hypothesis. A
29 receptor-based mode of action would predict that, except in cases where the concentration of
30 TCDD is already high (i.e., [TCDD]~KD), incremental exposure to TCDD will lead to some
31 increase in the fraction of AhRs occupied. However, it cannot be assumed that an increase in
32 receptor occupancy will necessarily elicit a proportional increase in all biological response(s)
33 because numerous molecular events (e.g., cofactors, other transcription factors, genes)
34 contributing to the biological endpoint are integrated into the overall response. That is, the final
35 biological response should be considered as an integration of a series of dose-response curves
36 with each curve dependent on the molecular dosimetry for each particular step. Dose-response
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1 relationships that will be specific for each endpoint must be considered when using mathematical
2 models to estimate the risk associated with exposure to TCDD. It remains a challenge to develop
3 models that incorporate all the complexities associated with each biological response.
4 Furthermore, the parameters for each mathematical model may only apply to a single biological
5 response within a given tissue and species.
6 Given TCDD's widespread distribution, its persistence, and its accumulation within the
7 food chain, it is likely that most humans are exposed to some level of dioxin; thus, the population
8 at potential risk is large and genetically heterogeneous. By analogy with the findings in inbred
9 mice, polymorphisms in the AhR probably exist in humans. Therefore, a concentration of TCDD
10 that elicits a particular response in one individual may not do so in another. For example, studies
11 of humans exposed to dioxin following an industrial accident at Seveso, Italy, fail to reveal a
12 simple and direct relationship between blood TCDD levels and development of chloracne
13 (Mocarelli et al., 1991). These differences in responsiveness to TCDD may reflect genetic
14 variation either in the AhR or in some other component of the dioxin-responsive pathway.
15 Therefore, analyses of human polymorphisms in the AhR and Arnt genes have the potential to
16 identify genotypes associated with higher (or lower) sensitivities to dioxin-related effects. Such
17 molecular genetic information may be useful in the future for accurately predicting the health
18 risks dioxin poses to humans.
19 Complex responses (such as cancer) probably involve multiple events and multiple genes.
20 For example, a homozygous recessive mutation at the hr (hairless) locus is required for TCDD's
21 action as a tumor promoter in mouse skin (Poland et al., 1982). Thus, the hr locus influences the
22 susceptibility of a particular tissue (in this case, skin) to a specific effect of dioxin (tumor
23 promotion). An analogous relationship may exist for the effects of TCDD in other tissues. For
24 example, TCDD may produce porphyria cutanea tarda only in individuals with inherited
25 uroporphyrinogen decarboxylase deficiency (Doss et al., 1984). Such findings suggest that, for
26 some adverse effects of TCDD, the population at risk may be limited to individuals with a
27 particular genetic predisposition.
28 Other factors can influence an organism's susceptibility to TCDD. For example, female
29 rats are more prone to TCDD-induced liver neoplasms than are males; this phenomenon is
30 related to the hormonal status of the animals (Lucier et al., 1991). In addition, hydrocortisone
31 and TCDD synergize in producing cleft palate in mice. Retinoic acid and TCDD produce a
32 similar synergistic teratogenic effect (Couture et al., 1990). These findings indicate that, in some
33 cases, TCDD acts in combination with hormones or other chemicals to produce adverse effects.
34 Such phenomena might also occur in humans. If so, the difficulty in assessing risk is increased,
35 given the diversity among humans in hormonal status, lifestyle (e.g., smoking, diet), and
36 chemical exposure.
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1 Dioxin's action as a tumor promoter and developmental toxicant presumably reflects its
2 ability to alter cell proliferation and differentiation processes. There are several plausible
3 mechanisms by which this could occur. First, TCDD might activate a gene (or genes) that is
4 directly involved in tissue proliferation. Second, TCDD-induced changes in hormone
5 metabolism may lead to tissue proliferation (or lack thereof) and altered differentiation secondary
6 to altered secretion of a trophic hormone. Third, TCDD-induced changes in the expression of
7 growth factor or hormone receptors may alter the sensitivity of a tissue to proliferative stimuli.
8 Fourth, TCDD-induced toxicity may lead to cell death, followed by regenerative proliferation.
9 These mechanisms likely differ among tissues and periods of development, and might be
10 modulated by different genetic and environmental factors. As such, this complexity increases the
11 difficulty associated with assessing the human health risks from dioxin exposure.
12 Under certain circumstances, exposure to TCDD may elicit beneficial effects. For
13 example, TCDD protects against the subsequent carcinogenic effects of PAHs in mouse skin,
14 possibly reflecting induction of detoxifying enzymes (Cohen et al., 1979; DiGiovanni et al.,
15 1980). In other situations, TCDD-induced changes in estrogen metabolism may alter the growth
16 of hormone-dependent tumor cells, producing a potential anticarcinogenic effect (Spink et al.,
17 1990; Gierthy et al., 1993). However, several recent studies in mice indicate that the AhR has an
18 important role in the genetic damage and carcinogenesis caused by components in tobacco smoke
1.9 such as benzo[a]pyrene through its ability to regulate CYP1A1 gene induction (Dertinger et al.,
20 1998; Shimizu et al., 2000). TCDD's biological effects likely reflect a complicated interplay
21 between genetic and environmental factors. These issues complicate the risk assessment process
22 for dioxin.
23
24
4. EXPOSURE CHARACTERIZATION
1 This section summarizes key findings developed in the exposure portion of the Agency's
2 dioxin reassessment. The findings are developed in the companion document entitled "Part I:
3 Estimating Exposure to Dioxin-Like Compounds." This document is divided into four volumes:
4 (1) Executive Summary; (2) Sources of dioxin in the United States; (3) Properties,
5 Environmental Levels, and Background Exposures; and (4) Site-Specific Assessment Procedures.
6 Readers are encouraged to examine the more detailed companion document for further
7 information on the topics covered here and to see complete literature citations. The
8 characterization discussion provides cross references to help readers find the relevant portions of
9 the companion document.
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1 This discussion is organized as follows: (1) Sources; (2) Fate; (3) Environmental Media
2 and Food Concentrations; (4) Background Exposures; (5) Potentially Highly Exposed
3 Populations; and (6) Trends. The key findings are presented in italics.
4
5 4.1. SOURCES (Cross reference: Part I, Volume 2: Sources of Dioxin-Like Compounds
6 in the U.S.)
7 The CDD/CDFs have never been intentionally produced other than on a laboratory scale
8 basis for use in scientific analysis. Rather, they are generated as unintended by-products in trace
9 quantities in various combustion, industrial and biological processes. PCBs on the other hand,
10 were commercially produced in large quantities, but are no longer commercially produced in the
11 United States. EPA has classified sources of dioxin-like compounds into five broad categories:
12
13 1. Combustion Sources. CDD/CDFs are formed in most combustion systems. These
14 can include waste incineration (such as municipal solid waste, sewage sludge, medical
15 waste, and hazardous wastes), burning of various fuels (such as coal, wood, and
16 petroleum products), other high temperature sources (such as cement kilns), and
17 poorly or uncontrolled combustion sources (such as forest fires, building fires, and
18 open burning of wastes). Some evidence exists that very small amounts of dioxin-like
19 PCBs are produced during combustion, but they appear to be a small fraction of the
20 total TEQs emitted.
21 2. Metals Smelting, Refining, and Processing Sources. CDD/CDFs can be formed
22 during various types of primary and secondary metals operations including iron ore
23 sintering, steel production, and scrap metal recovery.
24 3. Chemical Manufacturing. CDD/CDFs can be formed as by-products from the
25 manufacture of chlorine-bleached wood pulp, chlorinated phenols (e.g.,
26 pentachlorophenol, or PCP), PCBs, phenoxy herbicides (e.g., 2,4,5-T), and
27 chlorinated aliphatic compounds (e.g., ethylene bichloride).
28 4. Biological and Photochemical Processes. Recent studies suggest that CDD/CDFs
29 can be formed under certain environmental conditions (e.g., composting) from the
30 action of microorganisms on chlorinated phenolic compounds. Similarly, CDD/CDFs
31 have been reported to be formed during photolysis of highly chlorinated phenols.
32 5. Reservoir Sources. Reservoirs are materials or places that contain previously formed
33 CDD/CDFs or dioxin-like PCBs and have the potential for redistribution and
34 circulation of these compounds into the environment. Potential reservoirs include
35 soils, sediments, biota, water, and some anthropogenic materials. Reservoirs become
36 sources when they have releases to the circulating environment.
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1 Development of release estimates is difficult because only a few facilities in most
2 industrial sectors have been tested for CDD/CDF emissions. Thus an extrapolation is needed to
3 estimate national emissions. The extrapolation method involves deriving an estimate of
4 emissions per unit of activity at the tested facilities and multiplying this by the total activity level
5 in the untested facilities. In order to convey the level of uncertainty in both the measure of
6 activity and the emission factor, EPA developed a qualitative confidence rating scheme. The
7 confidence rating scheme, presented in Table 4-1, uses qualitative criteria to assign a high,
8 medium, or low confidence rating to the emission factor and activity level for those source
9 categories for which emission estimates can be reliably quantified. The overall "confidence
10 rating" assigned to a quantified emission estimate was determined by the confidence ratings
11 assigned to the corresponding "activity level" and "emission factor." If the lowest rating
12 assigned to either the activity level or emission factor terms is "high," then the category rating
13 assigned to the emission estimate is high (also referred to as "A"). If the lowest rating assigned
14 to either the activity level or emission factor terms is "medium," then the category rating
15 assigned to the emission estimate is medium (also referred to as "B"). If the lowest rating
16 assigned to either the activity level or emission factor terms is "low," then the category rating
17 assigned to the emission estimate is low (also referred to as "C"). For many source categories,
18 either the emission factor information or activity level information were inadequate to support
19 development of reliable quantitative release estimates for one or more media. For some of these
20 source categories, sufficient information was available to make preliminary estimates of
21 emissions of CDD/CDFs or dioxin-like PCBs; however, the confidence in the activity level
22 estimates or emission factor estimates was so low that the estimates cannot be included in the
23 sum of quantified emissions from sources with confidence ratings of A, B, or C. These estimates
24 were given an overall confidence class rating of D. For other sources, some information exists
25 suggesting that they may release dioxin-like compounds; however, the available data were judged
26 to be insufficient for developing any quantitative emission estimate. These estimates were given
27 an overall confidence class rating of E.
28
29 4.1.1. Inventory of Releases
30 This dioxin reassessment has produced an inventory of source releases for the United
31 States (Table 4-2). The inventory was developed by considering all sources identified in the
32 published literature and numerous individual emissions test reports. U.S. data were always given
33 first priority for developing emission estimates. Data from other countries were used for making
34 estimates in only a few source categories where foreign technologies were judged similar to those
35 found in the United States and the U.S. data were inadequate. The inventory is limited to sources
36 whose releases can be reliably quantified (i.e., those with confidence ratings of A, B, or C as
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1 defined above). Also, it is limited to sources with releases that are created essentially
2 simultaneously with formation. This means that the reservoir sources are not included. As
3 discussed below, this document does provide preliminary estimates of releases from these
4 excluded sources (i.e., reservoirs and Class D sources) but they are presented separately from the
5 Inventory.
6 The inventory presents the environmental releases in terms of two reference years: 1987
7 and 1995. 1987 was selected primarily because little empirical data existed for making source-
8 specific emission estimates. 1995 represents the latest year that could reasonably be addressed
9 within the timetable for producing the rest of this document. EPA expects to conduct periodic
10 revisions to the inventory in the future to track changes in environmental releases over time.
11 Figure 4-1 displays the emission estimates to air for sources included in the Inventory and
12 shows how the emission factors and activity levels were combined to generate emission
13 estimates. Figure 4-2 compares the annual mean TEQDF-WHO98 emission estimates to air for the
14 two reference years (i.e., 1987 and 1995).
15 The following conclusions are made for sources of dioxin-like compounds included in the
16 Inventory:
17
18 • EPA's best estimates of releases ofCDD/CDFs to air, water, and land from
19 reasonably quantifiable sources were approximately 2,800 gram (g) TEQDF-WHO98 in
20 1995 and 13,500 g TEQDrWHO98 in 1987.
21 • The decrease in estimated releases ofCDD/CDFs between 1987 and 1995
22 (approximately 80%) was due primarily to reductions in air emissions from municipal
23 and medical waste incinerators, and further reductions are anticipated. For both
24 categories, these emission reductions have occurred from a combination of improved
25 combustion and emission controls and from the closing of a number of facilities.
26 Regulations recently promulgated or under development should result in additional
'.7 reductions in emissions from major combustion sources. Recent data, although not
18 included in the 1995 inventory, support this trend.
>9 • The environmental releases ofCDD/CDFs in the United States occur from a wide
50 variety of sources, but are dominated by releases to the air from combustion sources.
J1 The current (1995) inventory indicates emissions from combustion sources are more
!2 than an order of magnitude greater than emissions from the sum of emissions from all
!3 other categories.
!4 . Insufficient data are available to comprehensively estimate point source releases of
!5 dioxin-like compounds to water. Sound estimates of releases to water are only
i6 available for chlorine-bleached pulp and paper mills and manufacture of ethylene
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1 dichloride/vinyl chloride monomer. Other releases to water bodies that cannot be
2 quantified on the basis of existing data include effluents from POTWs and most
3 industrial/commercial sources.
4 • Based on the available information, the inventory includes only a limited set of
5 activities that result in direct environmental releases to land. The only releases to
6 land quantified in the inventory are land application of sewage sludge, and pulp and
7 paper mill wastewater sludges. Not included in the Inventory's definition of an
8 environmental release is the disposal of sludges and ash into approved landfills.
9 • The inventory is likely to underestimate total releases. A number of investigators
10 have suggested that national inventories may underestimate emissions due to the
11 possibility of unknown sources. These possibilities have been supported with mass
12 balance analyses suggesting that deposition exceeds emissions. The uncertainty,
13 however, in both the emissions and deposition estimates for the United States prevent
14 the use of this approach for reliably evaluating the issue. As explained below, this
15 document has instead evaluated this issue by making preliminary estimates of poorly
16 characterized sources and listing other sources that have been reported to emit dioxin-
17 like compounds but cannot be characterized on even a preliminary basis.
18
19 4.1.2. General Source Observations
20 The preliminary release estimates for contemporary formation sources and reservoir
21 sources are presented in Table 4-3. Table 4-4 lists all the sources that have been reported to
22 release dioxin-like compounds but cannot be characterized on even a preliminary basis.
23 For any given time period, releases from both contemporary formation sources and
24 reservoir sources determine the overall amount of the dioxin-like compounds that are being
25 released to the open and circulating environment. Because existing information is incomplete
26 with regard to quantifying contributions from contemporary and reservoir sources, it is not
27 currently possible to estimate the total magnitude of release for dioxin-like compounds into the
28 U.S. environment from all sources. For example, in terms of 1995 releases from reasonably
29 quantifiable sources, this document estimates releases of 2,800 g TEQDF-WHO98 for
30 contemporary formation sources and 2,900 g TEQDF-WHO98 for reservoir sources. In addition,
31 there remains a number of unquantifiable and poorly quantified sources. No quantitative release
32 estimates can be made for agricultural burning or for most dioxin/furan reservoirs or for any
33 dioxin-like PCB reservoirs. The preliminary estimate of 1995 poorly characterized contemporary
34 formation sources is 1,900 g TEQDF-WHO9g.
35 Additional observations and conclusions about all sources of dioxin-like compounds are
36 summarized below:
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1 • The contribution ofdioxin-like compounds to waterways from nonpoint source
2 reservoirs is likely to be greater than the contributions from point sources. Current
3 data are only sufficient to support preliminary estimates of nonpoint source
4 contributions of dioxin-like compounds to water (i.e., urban storm water runoff and
5 rural soil erosion). These estimates suggest that, on a nationwide basis, total nonpoint
6 releases are significantly larger than point source releases.
7 • Current emissions ofCDD/CDFs to the U.S. environment result principally from
8 anthropogenic activities. Evidence that supports this finding includes matches in
9 time of rise of environmental levels with time when general industrial activity began
10 rising rapidly (see trend discussion in Section 4.6), lack of any identified large natural
11 sources, and observations of higher CDD/CDF body burdens in industrialized vs. less
12 industrialized countries (see discussion on human tissue levels in Section 4.4).
13 • Although chlorine is an essential component for the formation ofCDD/CDFs in
14 combustion systems, the empirical evidence indicates that for commercial scale
15 incinerators, chlorine levels in feed are not the dominant controlling factor for rates
16 ofCDD/F stack emissions. Important factors that can affect the rate of dioxin
17 formation include the overall combustion efficiency, postcombustion flue gas
18 temperatures and residence times, and the availability of surface catalytic sites to
19 support dioxin synthesis. Data from bench, pilot, and commercial-scale combustors
20 indicate that dioxin formation can occur by a number of mechanisms. Some of these
21 data, primarily from laboratory and pilot-scale combustors, have shown direct
22 correlation between chlorine content in fuels and rates of dioxin formation. Other
23 data, primarily from commercial-scale combustors, show little relation with
24 availability of chlorine and rates of dioxin formation. The conclusion that chlorine in
25 feed is not a strong determinant of dioxin emissions applies to the overall population
26 of commercial-scale combustors. For any individual commercial scale combustor,
27 circumstances may exist in which changes in chlorine content of feed could affect
28 dioxin emissions. For uncontrolled combustion, such as open burning of household
29 waste, chlorine content of wastes may play a more significant role in affecting levels
30 of dioxin emissions than observed in commercial-scale combustors.
31 • No significant release of newly formed dioxin-like PCBs is occurring in the United
32 States. Unlike CDD/CDFs, PCBs were intentionally manufactured in the United
33 States in large quantities from 1929 until production was banned in 1977. Although it
34 has been demonstrated that small quantities of coplanar PCBs can be produced during
35 waste combustion, no strong evidence exists that the dioxin-like PCBs make a
36 significant contribution to TEQ releases during combustion. The occurrences of
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1 dioxin-like PCBs in the U.S. environment most likely reflects past releases associated
2 with PCB production, use, and disposal. Further support of this finding is based on
3 observations of reductions since 1980s in PCBs in Great Lakes sediment and other
4 areas.
5 • It is unlikely that the emission rates of CDD/CDFs from known sources correlate
6 proportionally with general population exposures. Although the Emissions Inventory
7 shows the relative contribution of various sources to total emissions, it cannot be
8 assumed that these sources make the same relative contributions to human exposure.
9 It is quite possible that the major sources of dioxin in food (see discussion in Section
10 2.6 indicating that the diet is the dominant exposure pathway for humans) may not be
11 those sources that represent the largest fractions of current total emissions in the
12 United States. The geographic locations of sources relative to the areas from which
13 much of the beef, pork, milk, and fish come is important to consider. That is, much
14 of the agricultural areas that produce dietary animal fats are not located near or
15 directly downwind of the major sources of dioxin and related compounds.
16 • The contribution of reservoir sources to human exposure may be significant. Several
17 factors support this finding. First, human exposure to the dioxin-like PCBs is thought
18 to be derived almost completely from reservoir sources. Because one-third of general
19 population TEQ exposure is due to PCBs, at least one-third of the overall risk from
20 dioxin-like compounds conies from reservoir sources. Second, CDD/CDF releases
21 from soil via soil erosion and runoff to waterways appear to be greater than releases to
22 water from the primary sources included in the Inventory. CDD/CDFs in waterways
23 can bioaccumulate in fish, leading to human exposure via consumption offish. This
24 suggests that a significant portion of the CDD/CDF TEQ exposure could be due to
25 releases from the soil reservoir. Finally, soil reservoirs could have vapor and
26 particulate releases that deposit on plants and enter the terrestrial food chain. The
27 magnitude of this contribution, however, is unknown.
28
29 4.2. ENVIRONMENTAL FATE (Cross reference: Part I, Volume 3, Chapter 2)
30 Dioxin-like compounds are widely distributed in the environment as a result of a number
31 of physical and biological processes. The dioxin-like compounds are essentially insoluble in
32 water, generally classified as semivolatile, and tend to bioaccumulate in animals. Some evidence
33 has shown that these compounds can degrade in the environment, but in general they are
34 considered very persistent and relatively immobile in soils and sediments. These compounds are
35 transported through the atmosphere as vapors or attached to airborne particulates and can be
36 deposited on soils, plants, or other surfaces (by wet or dry deposition). The dioxin-like
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1 compounds enter water bodies primarily via direct deposition from the atmosphere, or by surface
2 runoff and erosion. From soils, these compounds can reenter the atmosphere either as
3 resuspended soil particles or as vapors. In water, they can be resuspended into the water column
4 from sediments, volatilized out of the surface waters into the atmosphere or become buried in
5 deeper sediments. Immobile sediments appear to serve as permanent sinks for the dioxin-like
6 compounds. Though not always considered an environmental compartment, these compounds
7 are also found in anthropogenic materials (such as PCP) and have the potential to be released
8 from these materials into the broader environment.
9 Atmospheric transport and deposition of the dioxin-like compounds are a primary
10 means of dispersal of these compounds throughout the environment. The dioxin-like compounds
11 can be measured in wet and dry deposition in most locations including remote areas. Numerous
12 studies have shown that they are commonly found in soils throughout the world. Industrialized
13 countries tend to show similar elevated concentrations in soil, and detectable levels have been
14 found in nonindustrialized countries. The only satisfactory explanation available for this
15 distribution is air transport and deposition. Finally, by analogy these compounds would be
16 expected to behave similarly to other compounds with similar properties, and this mechanism of
17 global distribution is becoming widely accepted for a variety of persistent organic compounds.
18 The two primary pathways for the dioxin-like compounds to enter the ecological food
19 chains and human diet are air-to-plant-to-animal and water/sediment-to-fish. Vegetation
20 receives these compounds via atmospheric deposition in the vapor and particle phases. The
21 compounds are retained on plant surfaces and bioaccumulated in the fatty tissues of animals that
22 feed on these plants. Vapor phase transfers onto vegetation have been experimentally shown to
23 dominate the air-to-plant pathway for the dioxin-like compounds, particularly for the lower
24 chlorinated congeners. In the aquatic food chain, dioxins enter water systems via direct
25 discharge or deposition and runoff from watersheds. Fish accumulate these compounds through
26 their direct contact with water, suspended particles, bottom sediments, and through their
27 consumption of aquatic organisms. Although these two pathways are thought to normally
28 dominate contribution to the commercial food supply, others can also be important. Elevated
29 dioxin levels in cattle resulting from animal contact with PCP-treated wood have been
30 documented by the U.S. Department of Agriculture. Animal feed contamination episodes have
31 led to elevations of dioxins in poultry in the United States, milk in Germany, and meat/dairy
32 products in Belgium.
33
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1 4.3. ENVIRONMENTAL MEDIA AND FOOD CONCENTRATIONS (Cross reference:
2 Part I, Volume 3, Chapter 3)
3 Estimates of the range of typical background levels of dioxin-like compounds in various
4 environmental media are presented in Table 4-5. Estimates for background levels of dioxin-like
5 compounds in environmental media are based on a variety of studies conducted at different
6 locations in North America. Of the studies available for this compilation, only those conducted
7 in locations representing "background" were selected. The amount and representativeness of the
8 data vary, but in general these data were derived from studies that were not designed to estimate
9 national background means. The environmental media concentrations were similar to studies in
10 Western Europe. These data are the best available for comparing with site-specific values.
11 Because of the limited number of locations examined, it is not known if these estimates
12 adequately capture the full national variability. As new data are collected, these ranges are likely
13 to be expanded and refined. The limited data on dioxin-like PCBs in environmental media are
14 summarized in this document (Part I, Volume 3, Chapter 4).
15 Estimates for levels of dioxin-like compounds in food are based on data from a variety of
16 studies conducted in North America. Beef, pork, and poultry were derived from statistically
17 based national surveys. Milk estimates were derived from a survey of a nationwide milk
18 sampling network. Dairy estimates were derived from milk fat concentrations, coupled with
19 appropriate assumptions for the amount of milk fat in dairy products. Egg samples were grab
20 samples from retail stores. Fish data were collected from a combination of field and retail
21 outlets, and all concentrations were expressed on the basis of fresh weight in edible tissue. As
22 with environmental media, food levels found in the United States are similar to levels found in
23 Europe.
24
25 The current data on levels of dioxin-like compounds in fish and eggs are limited
26 compared with other meats and dairy products. EPA hopes to receive additional data sets over
27 the next few months that can be incorporated into this report before it becomes final. Issues
28 specific to fish and eggs are discussed below:
29 • Fish. The data set used for deriving dioxin-like compound levels in
30 freshwater/estuarine fish are somewhat dated because the sample collections and
31 chemical analysis occurred in the late 1980s. Additionally, freshwater fish used in
32 this study were all caught in the wild and may not be representative of the commercial
33 species commonly consumed. For example, no farm-raised fish were sampled, and
34 they represent almost all of the commercial freshwater fish consumed. Very few
35 studies were found describing levels of dioxin-like compounds in marine fish. The
36 currently used marine fish data for dioxin-like compounds do not represent some of
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1 the most highly consumed species in the United States (e.g., tuna, cod, salmon, etc.).
2 EPA will continue to seek new data, but new surveys are likely to be needed to
3 improve our understanding of dioxin levels in fish.
4 • Eggs. EPA is currently reviewing some unpublished egg data and, if found
5 acceptable, will incorporate them into this report before it becomes final. Based on a
6 preliminary analysis, it does not appear that these new data will significantly change
7 the current background TEQ estimate for eggs, but they should provide additional
8 support and strengthen the confidence in the estimate. Given the low egg
9 consumption rate, total TEQ intakes also will not be significantly affected.
10
11 4.4. BACKGROUND EXPOSURES (Cross reference: Part I, Volume 3, Chapter 4)
12 4.4.1. Tissue Levels
13 The average CDD/CDF/PCB tissue level for the general adult U.S. population appears to
14 be declining, and the best estimate of current (late 1990s) levels is 25 ppt (TEQDFP-WHO9K, lipid
15 basis).
16 The tissue samples collected in North America in the late 1980s and early 1990s showed
17 an average TEQDFP-WHO9g level of about 55 pg/g lipid. This finding is supported by a number of
18 studies which measured dioxin levels in adipose, blood, and human milk, all conducted in North
19 America. The number of people in most of these studies, however, is relatively small and the
20 participants were not statistically selected in ways that assure their representativeness of the
21 general U.S. adult population. One study, the 1987 National Human Adipose Tissue Survey
22 (NHATS), involved over 800 individuals and provided broad geographic coverage, but did not
23 address coplanar PCBs. Similar tissue levels of these compounds have been measured in Europe
24 and Japan during similar time periods.
25 Because dioxin levels in the environment have been declining since the 1970s (see trends
26 discussion), it is reasonable to expect that levels in food, human intake, and ultimately human
27 tissue have also declined over this period. The changes in tissue levels are likely to lag the
28 decline seen in environmental levels, and the changes in tissue levels cannot be assumed to occur
29 proportionally with declines in environmental levels. CDC (2000) summarized levels of CDDs,
30 CDFs, and PCBs in human blood collected during the time period 1995 to 1997. The individuals
31 sampled were all U.S. residents with no known exposures to dioxin other than normal
32 background. The blood was collected from 316 individuals in six different locations with an age
33 range of 20 to 70 years. All TEQ calculations were made assuming nondetects were equal to half
34 the detection limit. While these samples were not collected in a manner that can be considered
35 statistically representative of the national population and lack wide geographic coverage, they are
36 judged to provide a better indication of current tissue levels in the United States than the earlier
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1 data. PCBs 105, 118, and 156 are missing from the blood data for the comparison populations
2 reported by CDC (2000). These congeners account for 62% of the total PCB TEQ estimated in
3 the early 1990s. Assuming that the missing congeners from the CDC study data contribute the
4 same proportion to the total PCB TEQ as in earlier data, they would increase our estimate of
5 current body burdens by another 3.3 pg TEQ/g lipid for a total PCB TEQ of 5.3 pg/g lipid and a
6 total DFP TEQ of 25.4 pg/g lipid (see Table 4-7).
7 This finding regarding current tissue levels is further supported by the observation that
8 this mean tissue level is consistent with our best estimate of current intake, i.e., 1 pg/kg-d in
9 TEQDFP-WHO98. Using this intake in a one-compartment, steady-state pharmacokinetic model
10 yields a tissue level estimate of about 16 pg TEQDFP WHO98/g lipid (assumes TEQDFP has an
11 effective half-life of 7 yr, 80% of ingested dioxin is absorbed into the body, and lipid volume is
12 19 L). Because intake rates appear to have declined in recent years and steady-state is not likely
13 to have been achieved, it is reasonable to observe higher measured tissue levels than predicted by
14 the model.
15 Characterizing national background levels of dioxins in tissues is uncertain because the
16 current data cannot be considered statistically representative of the general population. It is also
17 complicated by the fact that tissue levels are a function of both age and birth year. Because
18 intake levels have varied over time, the accumulation of dioxins in a person who turned 50 years
19 old in 1990 is different than in a person who turned 50 in 2000. Future studies should help
20 address these uncertainties. The National Health and Nutrition Examination Survey (NHANES)
21 began a new national survey in 1999 that will measure blood levels of CDDs, CDFs, and PCBs
22 126, 77, 169, and 81 in about 1,700 people per year (see http:www.cdc.gov/nchs/nhanes.htm).
23 The survey is conducted at 15 different locations per year and is designed to select individuals
24 statistically representative of the civilian United States population in terms of age, race, and
25 ethnicity. These new data should provide a much better basis for estimating national background
26 tissue levels and evaluating trends than the currently available data.
27
28 4.4.2. Intake Estimates
29 Adult daily intakes ofCDD/CDFs and dioxin-like PCBs are estimated to average 45 and
30 25 pg TEQDFr WHO9f/day, respectively, for a total intake of 70 pg/day TEQDFP- WHO98. Daily
31 intake is estimated by combining exposure media concentrations (food, soil, air) with contact
32 rates (ingestion, inhalation). Table 4-8 summarizes the intake rates derived by this method.
33 The intake estimate is supported by an extensive database on food consumption rates and
34 estimates of dioxin-like compounds in food (as discussed above). Pharmacokinetic (PK)
35 modeling provides further support for the intake estimates. Applying a simple steady-state PK
36 model to an adult average CDD/CDF adipose tissue level of 18.8 ppt TEQDF-WHO9g (on a lipid
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1 basis) yields a daily intake of 110 pg TEQDF-WHO9g/day. Insufficient half-life data are available
2 for making a similar intake estimate for the dioxin-like PCBs. This PK-modeled CDD/CDF
3 intake estimate is about 2.5 times higher than the direct intake estimate of 45 pg TEQDF-
4 WHO98/day. This difference is to be expected with this application of a simple steady-state PK
5 model to current average adipose tissue concentrations. Current adult tissue levels reflect intakes
6 from past exposure levels that are thought to be higher than current levels (see Trends, Section
7 2.6). Because the direction and magnitude of the difference in intake estimates between the two
8 approaches are understood, the PK-derived value is judged supportive of the pathway-derived
9 estimate. It should be recognized, however, that the pathway-derived value will underestimate
10 exposure if it has failed to capture all significant exposure pathways.
11
12 4.4.3. Variability in Intake Levels
13 CDD/CDF and dioxin-like PCB intakes for .the general population may extend to levels at
14 least three times higher than the mean. Variability in general population exposure is primarily
15 the result of the differences in dietary choices that individuals make. These are differences in
16 both quantity and types of food consumed. A diet that is disproportionately high in animal fats
17 will result in an increased background exposure over the mean. Data on variability of fat
18 consumption indicate that the 95th percentile is about twice the mean and the 99th percentile is
19 approximately three times the mean. Additionally, a diet that substitutes meat sources that are
20 low in dioxin (i.e., beef, pork, or poultry) with sources that are high in dioxin (i.e., freshwater
21 fish) could result in exposures elevated over three times the mean. This scenario may not
22 represent a significant change in total animal fat consumption, even though it results in an
23 increased dioxin exposure.
24 Intakes ofCDD/CDFs and dioxin-like PCBs are over three times higher for a young child
25 as compared to that of an adult, on a body weight basis. Using age-specific food consumption
26 rate and average food concentrations, as was done above for adult intake estimates, Table 4-9
27 describes the variability in average intake values as a function of age.
28 Only four of the 17 toxic CDD/CDF congeners and one of the 11 toxic PCBs account for
29 most of the toxicity in human tissue concentrations: 2,3,7,8-TCDD, 1,2,3,7,8-PCDD,
30 1,2,3,6,7,8-HxCDD, 2,3,4,7,8-PCDF, and PCB 126. This finding is derived directly from the
31 data described earlier on human tissue levels and is supported by intake estimations indicating
32 that these congeners are also the primary contributors to dietary dose. These five compounds
33 make up more than one-half of the total TEQ tissue level. The variability in intake levels is also
34 supported by the blood data from CDC (2000), which showed that the 95th percentile of blood
35 level estimates, presumably resulting primarily from dietary intake, was almost twice the mean
36 level.
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1 4.5. POTENTIALLY HIGHLY EXPOSED POPULATIONS OR DEVELOPMENTAL
2 STAGES (Cross reference: Part I, Volume 3, Chapter 6)
3 As discussed earlier, background exposures to dioxin-like compounds may extend to
4 levels at least three times higher than the mean. This upper range is assumed to result from the
5 normal variability of diet and human behaviors. Exposures from local elevated sources or
6 exposures resulting from unique diets would be in addition to this background variability. Such
7 elevated exposures may occur in small segments of the population such as individuals living near
8 discrete local sources, or subsistence or recreational fishers. Nursing infants represent a special
9 case: for a limited portion of their lives, these individuals may have elevated exposures on a body
10 weight basis when compared with nonnursing infants and adults.
11 Dioxin contamination incidents involving the commercial food supply have occurred in
12 the United States and other countries. For example, in the United States, contaminated ball clay
13 was used as an anticaking agent in soybean meal and resulted in elevated dioxin levels in some
14 poultry and catfish. This incident, which occurred in 1998, involved less than 5% of the national
15 poultry production and has since been eliminated. Elevated dioxin levels have also been
16 observed in a few beef and dairy animals where the contamination was associated with contact
17 with PCP-treated wood. Evidence of this kind of elevated exposure was not detected in the
18 national beef survey. Consequently its occurrence is likely to be low, but it has not been
19 determined. These incidents may have led to small increases in dioxin exposure to the general
20 population. However, it is unlikely that such incidents have led to disproportionate exposures to
21 populations living near where these incidents have occurred, because in the United States, meat
22 and dairy products are highly distributed on a national scale. If contamination events were to
23 occur in foods that are predominantly distributed on a local or regional scale, then such events
24 could lead to highly exposed local populations.
25 Elevated exposures associated with the workplace or industrial accidents have also been
26 documented. United States workers in certain segments of the chemical industry had elevated
27 levels of TCDD exposure, with some tissue measurements in the thousands of ppt TCDD. There
28 is no clear evidence that elevated exposures are currently occurring among United States
29 workers. Documented examples of past exposures for other groups include certain Air Force
30 personnel exposed to Agent Orange during the Vietnam War and people exposed as a result of
31 industrial accidents in Europe and Asia.
32 Consumption of breast milk by nursing infants leads to higher levels of exposure and
33 higher body burdens ofdioxins during early years of life as compared with nonnursing infants.
34 Two studies have compared dioxins in infants who have been breast-fed versus those who have
35 been formula-fed, and both have shown elevations in the concentrations ofdioxins in infants
36 being breast-fed. One study obtained blood samples from two infants (1 breast-fed and 1
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1 formula-fed) at 11 and 25 months and the other obtained adipose tissue from 17 infants (9 breast-
2 fed and 8 formula-fed) who had died from Sudden Infant Death Syndrome. Both studies showed
3 formula-fed infants having lipid-based concentrations <5 ppt TEQDF-WH09g, while breast-fed
4 infants had average lipid-based concentrations >20 ppt TEQDF-WHO98 (maximum of 35 ppt
5 TEQDF-WHO98). The dose to the infant varies as a function of infant body weight, the
6 concentration of dioxins in the mother's milk, and the trend of dioxins in the mother's milk to
7 decline over time. Using current data on this information and PK modeling, a 12-month nursing
8 scenario was modeled and results include:
9
10 • Doses at birth could exceed 200 pg TEQDFP-WHO98/kg/day, which would drop to
11 about 20 pg TEQDFP-WH09g/kg/day after 12 months. The average dose over a year
12 was calculated to be 77 pg TEQDFP-WHO98/kg/day. These results assumed an initial
13 concentration in the mother's milk of 25 ppt TEQDFP-WHO98, which declined to about
14 6 ppt TEQDFP-WHO98 after 1 year, and an initial infant total body weight of 3.3 kg,
15 which rose to over 9 kg after 1 year.
16 • On a mass basis, this hypothetical exposure to dioxins in breast milk over the course
17 of a year is estimated to represent about 10% of the total lifetime dose of an
18 individual to dioxins.
19 • Infant lipid concentrations were found to peak at about 42 ppt TEQDFP-WHO9g,
20 compared with lipid concentrations of less than 10 ppt for the formula-fed infants.
21 The dioxin concentrations in these two hypothetical children merged at about 10 years
22 of age, at a lipid concentration of about 13 ppt TEQDFP-WHO98.
23 While the average annual infant dose of 77 pg TEQDFP-WHO9g/kg/day exceeds the
24 currently estimated adult dose of 1 pg TEQDFP-WHO98/kg/day, the effect on infant body burdens
25 is expected to be less dramatic — i.e., infant body burdens will not exceed adult body burdens
26 by 77 times. This is due to the rapidly expanding infant body weight and lipid volume, the
27 decrease in concentration of dioxins in the mother's milk over time, as well as the possibly faster
28 elimination in infants. As noted above by both monitoring and modeling, dioxin concentrations
29 in the lipids of breast-fed infants appear to be in the range of <20 to >40 ppt TEQDFP-WHO98,
30 which compares to the 25 ppt TEQDFP-WHO9g identified as the representative current background
31 lipid concentrations in adults.
32 Consumption of unusually high amounts offish, meat, or dairy products containing
33 elevated levels of dioxins and dioxin-like PCBs can lead to elevated exposures in comparison
34 with the general population. Most people eat some fish from multiple sources, both fresh and
35 salt water. The estimated dioxin concentrations in these fish and the typical rates of consumption
36 are included in the mean background calculation of exposure. People who consume large
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1 quantities offish at estimated contamination levels may have elevated exposures. These kinds of
2 exposures are addressed within the estimates of variability of background and are not considered
3 to result in highly exposed populations. If high-end consumers obtain their fish from areas where
4 the concentration of dioxin-like chemicals in the fish is elevated, they may constitute a highly
5 exposed subpopulation. Although this scenario seems reasonable, no supporting data could be
6 found for such a highly exposed subpopulation in the United States. One study measuring
7 dioxin-like compounds in the blood of sport fishers in the Great Lakes area showed elevations
8 over mean background, but within the range of normal variability. Elevated CDD/CDF levels in
9 human blood have been measured in Baltic fishermen. Similarly elevated levels of coplanar
10 PCBs have been measured in the blood of fishers on the north shore of the Gulf of the St.
11 Lawrence River who consume large amounts of seafood.
12 Similarly, high exposures to dioxin-like chemicals as a result of consuming meat and
13 dairy products would only occur in situations where individuals consume large quantities of these
14 foods and the level of these compounds is elevated. Most people eat meat and dairy products
15 from multiple sources and, even if large quantities are consumed, they are not likely to have
16 unusually high exposures. Individuals who raise their own livestock for basic subsistence have
17 the potential for higher exposures if local levels of dioxin-like compounds are high. One study in
18 the United States showed elevated levels in chicken eggs near a contaminated soil site. European
19 studies at several sites have shown elevated CDD/CDF levels in milk and other animal products
20 near combustion sources.
21
22 4.6. ENVIRONMENTAL TRENDS (Cross reference: Part I, Volume 3, Chapter 6)
23 Concentrations ofCDD/CDFs and PCBs in the United States environment were
24 , consistently low before the 1930s. Then concentrations rose steadily until about 1970. At this
25 time, the trend reversed and the concentrations have declined to the present.
26 The most compelling supportive evidence of this trend for the CDD/CDFs and PCBs
27 comes from dated sediment core studies. Sediment concentrations in these studies are generally
28 assumed to be an indicator of the rate of atmospheric deposition. CDD/CDF and PCB
29 concentrations in sediments began to increase around the 1930s and continued to increase until
30 about 1970. Decreases began in 1970 and have continued to the time of the most recent sediment
31 samples (about 1990). Sediment data from 20 United States lakes and rivers from seven separate
32 research efforts consistently support this trend. Additionally, sediment studies in lakes located in
33 several European countries have shown similar trends.
34 It is reasonable to assume that sediment core trends should be driven by a similar trend in
35 emissions to the environment. The period of increase generally matches the time when a variety
36 of industrial activities began rising and the period of decline appears to correspond with growth
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1 in pollution abatement. Many of these abatement efforts should have resulted in decreases in
2 dioxin emissions, i.e., elimination of most open-burning, particulate controls on combustors,
3 phase out of leaded gas, and bans on PCBs, 2,4,5-T, hexachlorophene, and restrictions on the use
4 of PCP. Also, the national source inventory of this assessment documented a significant decline
5 in emissions from the late 1980s to the mid-1990s. Further evidence of a decline in CDD/CDF
6 levels in recent years is emerging from data, primarily from Europe, showing declines in foods
7 and human tissues.
8 In addition to the congener-specific PCB data discussed earlier, a wealth of data on total
9 PCBs, Aroclors, and other commercial PCB mixtures exist that also supports these trends. It is
10 reasonable to assume that the trends for dioxin-like PCBs are similar to those for PCBs as a class
11 because the predominant source of dioxin-like PCBs is their occurrence in Aroclor mixtures.
12 PCBs were intentionally manufactured in large quantities from 1929 until production was banned
13 in the United States in 1977. United States production peaked in 1970, with a volume of 39,000
14 metric tons. Further support is derived from data showing declining levels of total PCBs in Great
15 Lakes sediments and biota during the 1970s and 1980s. These studies indicate, however, that
16 during the 1990s the decline was slowing and may have been leveling off.
17 Past human exposures to dioxins were most likely higher than current estimates. This is
18 supported by a study that applied a non-steady-state PK model to data on background United
19 States tissue levels of 2,3,7,8-TCDD from the 1970s and 1980s. Various possible intake
20 histories (pg/kg-day over time) were tested to see which best-fit the data. An assumption of a
21 constant dose over time resulted in a poor fit to the data. The "best-fit" (statistically derived) to
22 the data was found when the dose, like the sediment core trends, rose through the 1960s into the
23 1970s and declined to current levels. Some additional support for this finding comes from a
24 limited study of preserved meat samples from several decades in the 20th century. One sample
25 from before 1910 showed very low concentrations of dioxins and coplanar PCBs. Thirteen other
26 samples, from the 1940s until the early 1980s consistently showed elevated levels of all dioxin-
27 like compounds as compared with food surveys conducted during the 1990s.
28
29
5. DOSE-RESPONSE CHARACTERIZATION
1 Previous sections of this integrated summary have focused on characterizing the hazards
2 of and exposure to dioxin-like compounds. In order to bring these issues together and provide an
3 adequate characterization of risk, the relationships of exposure to dose and, ultimately, to
4 response must be evaluated. Key questions to be asked include: (1) What can be said about the
5 shape of the dose-response function in the observable range and what does this imply about
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1 dose-response in the range of environmental exposures? (2) What is a reasonable limit (critical
2 dose or point of departure) at the lower end of the observable range and what risk is associated
3 with this exposure? In addition, one can address the issue of extrapolation beyond the range of
4 the data in light of the answers to the above questions. Although extrapolation of risks beyond
5 the range of observation in animals and/or humans is an inherently uncertain enterprise, it is
6 recognized as an essential component of the risk assessment process (NAS/NRC, 1983). The
7 level of uncertainty is dependent on the nature (amount and scope) of the available data and on
8 the validity of the models that have been used to characterize dose-response. These form the
9 bases for scientific inference regarding individual or population risk beyond the range of current
10 observation ((NAS/NRC, 1983,1994)
11 In Part II, Chapter 8, the body of literature concerning dose-response relationships of
12 TCDD is presented. This chapter addresses the important concept of selecting an appropriate
13 metric for cross-species scaling of dose and presents the results of empirical modeling for many
14 of the available data sets on TCDD exposures in humans and in animals. Although not all
15 human observations or animal experiments are amenable to dose-response modeling, more than
16 200 data sets were evaluated for shape, leading to an effective dose (ED) value expressed as a
17 percent response being presented for the endpoint being evaluated (e.g., ED01 equals an effective
18 dose for a 1% response). The analysis of dose-response relationships for TCDD, considered
19 within the context of toxicity equivalence, mechanism of action, and background human
20 exposures, helps to elucidate the common ground and the boundaries of the science and science
21 policy components inherent in this risk characterization for the broader family of dioxin-like
22 compounds. For instance, the dose-response relationships provide a basis to infer a point of
23 departure for extrapolation for cancer and noncancer risk for a complex mixture of dioxin-like
24 congeners given the assumption of toxicity equivalence as discussed in Part II, Chapter 9.
25 Similarly, these relationships provide insight into the shape of the dose-response at the point of
26 departure, which can help inform choices for extrapolation models for both TCDD and total
27 TEQ.
28 In evaluating the dose-response relationships for TCDD as a basis for assessing this
29 family of compounds, both empirical dose-response modeling approaches and mode-of-action-
30 based approaches have been developed and applied (see Part II, Chapter 8; Portier et al., 1996).
31 Empirical models have advantages and disadvantages relative to more ambitious
32 mechanism-based models. Empirical models provide a simple mathematical model that
33 adequately describes the pattern of response for a particular data set; they can also provide the
34 means for hypothesis testing and interpolation between data points. In addition, they can provide
35 qualitative insights into underlying mechanisms. However, the major disadvantage of empirical
36 models is their inability to quantitatively link data sets in a mechanistically meaningful manner.
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1 On the other hand, mechanism-based modeling can be a powerful tool for understanding and
2 combining information on complex biological systems. Use of a truly mechanism-based
3 approach can, in theory, enable more reliable and scientifically sound extrapolations to lower
4 doses and between species. However, any scientific uncertainty about the mechanisms that the
5 models describe is inevitably reflected in uncertainty about the predictions of the models.
6 Physiologically based pharmacokinetic (PBPK) models have been validated in the
7 observable response range for numerous compounds in both animals and humans. The
8 development of PBPK models for disposition of TCDD in animals has proceeded through
9 multiple levels of refinement, with newer models showing increasing levels of complexity by
10 incorporating data for disposition of TCDD, its molecular actions with the AhR and other
11 proteins, as well as numerous physiological parameters (Part II, Chapter 1). These have provided
12 insights into key determinants of TCDD disposition in treated animals. The most complete
13 PBPK models give similar predictions about TCDD tissue dose metrics. The PBPK models have
14 been extended to generate predictions for early biochemical consequences of tissue dosimetry of
15 TCDD, such as induction of CYP1A1. Nevertheless, extension of these models to more complex
16 responses is more uncertain at this time. Differences in interpretation of the mechanism of action
17 lead to varying estimates of dose-dependent behavior for similar responses. The shape of the
8 dose-response curves governing extrapolation to low doses are determined by these hypotheses
9 and assumptions.
!0 At this time, the knowledge of the mechanism of action of dioxin, receptor theory, and
11 the available dose-response data do not firmly establish a scientific basis for replacing a linear
!2 procedure for estimating cancer potency. Consideration of this same information indicates that
:3 the use of different procedures to estimate the risk of exposure for cancer and noncancer
4 endpoints may not be appropriate. Both the cancer and noncancer effects of dioxin appear to
5 result from qualitatively similar modes of action. Initial steps in the process of toxicity are the
6 same and many early events appear to be shared. Thus, the inherent potential for low dose
7 significance of either type of effect (cancer or noncancer) should be considered equal and
8 evaluated accordingly. In the observable range around 1% excess response, the quantitative
9 differences are relatively small. Below this response, the different mechanisms can diverge
0 rapidly. The use of predicted biochemical responses as dose metrics for toxic responses is
1 considered a potentially useful application of these models. However, greater understanding of
2 the linkages between these biochemical effects and toxic responses is needed to reduce the
3 potentially large uncertainty associated with these predictions.
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1 5.1. DOSE METRIC(s)
2 One of the most difficult issues in risk assessment is the determination of the dose metric
3 to use for animal-to-human extrapolations. To provide significant insight into differences in
4 sensitivity among species, an appropriate animal-to-human extrapolation of tissue dose is
5 required. The most appropriate dose metric should reflect both the magnitude and frequency of
6 exposure, and should be clearly related to the toxic endpoint of concern by a well-defined
7 mechanism. This is, however, often difficult because human exposures with observable
8 responses may be very different from highly controlled exposures in animal experiments. In
9 addition, comparable exposures may be followed by very different pharmacokinetics (absorption,
10 distribution, metabolism and/or elimination) in animals and humans. Finally, the sequelae of
11 exposure in the form of a variety of responses related to age, organ, and species sensitivity
12 complicate the choice of a common dose metric. Despite these complexities, relatively simple
13 default approaches, including body surface or body weight scaling of daily exposures, have often
14 been recommended (U.S. EPA, 1992, 1996).
15 Given the data available on dioxin and related compounds, dose can be expressed in a
16 multitude of metrics (DeVito et al., 1995) such as daily intake (ng/kg/d), current body burden
17 (ng/kg), average body burden over a given period of time, plasma concentration, etc. Examples
18 of other dose metrics of relevance for TCDD and related compounds can be found in the
19 literature including concentration of occupied AhR (Jusko, 1995), induced CYP1A2 (Andersen
20 et al., 1997; Kohn et al., 1993) and reduced epidermal growth factor receptor (EGFR) (Portier
21 and Kohn, 1996). Considering the variety of endpoints seen with TCDD and expected with other
22 dioxin-like chemicals in different species, it is unlikely that a single dose metric will be adequate
23 for interspecies extrapolation for all of these endpoints. The issue of an appropriate dose metric
24 for developmental effects considering the potential for a narrow time window of sensitivity, for
25 instance, has been discussed in a number of places in this document. Furthermore, the use of
26 different dose metrics with respect to the same endpoint may lead to widely diverse conclusions.
27 This latter point is discussed in more detail in Part II, Chapter 8. Nevertheless, it is possible to
28 express dose in a form that allows for comparison of responses for selected endpoints and
29 species. This can be done by choosing a given exposure and comparing responses (e.g., URL) or
30 choosing a particular response level and comparing the associated exposures (e.g., ED).
31 As discussed above, dose can be expressed in a number of ways. For TCDD and other
32 dioxin-like compounds, attention has focused on the consideration of dose expressed as daily
33 intake (ng/kg/day), body burden (ng/kg), or AUC (DeVito et al, 1995; Aylward et al, 1996). The
34 concept of physiological time (lifetime of an animal) complicates the extrapolation, as the
35 appropriate scaling factor is uncertain for toxic endpoints. Because body burden incorporates
36 differences between species in TCDD half-life (these differences are large between rodent
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1 species and humans [Table 8.2], this dose metric appears to be the most practical for this class of
2 compounds (DeVito et al, 1995). Average lifetime body burden is best suited for steady-state
3 conditions, with difficulties arising when this dose metric is applied to evaluation of acute
4 exposures, such as those occurring in the 1976 accidental exposure of some people living in
5 Seveso, Italy (Bertazzi and di Domenico, 1994). In cases such as this, increased body burden
6 associated with the acute exposure event is expected to decline (half-life for TCDD is
7 approximately 7 years) until it begins to approach a steady-state level associated with the much
8 smaller daily background intake. However, this issue of acute exposure is not a major factor in
9 the current analyses. In general, daily excursions in human exposure are relatively small and
10 have minor impact on average body burden. Instead, PBPK models suggest that human body
11 burdens increase over time and begin to approach steady-state after approximately 25 years with
12 typical background doses. Occupational exposures represent the middle ground where daily
13 excursions during the working years can significantly exceed daily background intakes for a
14 number of years, resulting in elevated body burdens. This is illustrated in Table 5-1. Estimation
15 of the range and mean or median of "attained" body burden in accidentally or occupationally
16 exposed cohorts is presented and compared with body burdens based on background exposures.
17 These data are presented graphically in Figure 5-1.
18 Table 5-1 and Figure 5-1 summarize literature on levels of dioxin TEQs in the
19 background human population and in commonly cited epidemiological cohorts. Table 5-1
20 collates data on tissue lipid levels (ppt lipid adjusted) in populations, principally from serum,
21 tabulating either current levels for the background population or back calculated levels for the
22 exposed cohorts. Figure 5-1 graphs the estimated range and central tendency of the total TEQDFP
23 body burden (ng/kg whole body), combining the range of measured 2,3,7,8-TCDD values with
24 the estimate of the background non-2,3,7,8-TCDD TEQ level from the U.S. population in the late
25 1980s/early 1990s. TEQ levels are calculated for PCDD, PCDF, and PCBs, based on
26 TEQDFP-WHO98 values, and assume a constant 25% body fat ratio when converting from serum
27 lipid ppt to ng/kg body burden. Total TEQ values for the Hamburg cohort women were
28 calculated by the authors, and for this cohort the TCDD graph includes non-TCDD TEQ. Seveso
29 values reported by Needham et al. (1999) are based on stored serum samples from subjects
30 undergoing medical examinations contemporaneous with the exposure, and were not back-
31 calculated.
32 For the background U.S. populations (CDC; USA ~1990s), the bars represent the range of
33 total TEQ measured in the population. The lower shaded portion represents the variability from
34 non-2,3,7,8-TCDD derived TEQs, the upper shaded portion the variability in the 2,3,7,8-TCDD.
35 Note, that the respective bar sizes do not represent the total non-2,3,7,8-TCDD TEQ or
36 2,3,7,8-TCDD contributions, because a portion of each of these contributions is contained within
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1 the region between the x-axis and bottom of the bar, namely the minimum estimated body
2 burden. For each of the back-calculated epidemiological cohort exposures, the bar was estimated
3 based on the combination of two distributions: the 2,3,7,8-TCDD levels measured in the
4 respective cohort plus the estimated range of background non-2,3,7,8-TCDD derived TEQs from
5 the U.S. population. The lower estimate is the combination of the lower 2,3,7,8-TCDD and
6 lower non-2,3,7,8-TCDD TEQ contributions; the shading junction represents the variability in
7 background U.S. population non-2,3,7,8-TCDD levels that have been added to this bar; the
8 mean/median/geometric mean indicators represent the addition of the measured 2,3,7,8-TCDD
9 central estimate with the mean background US population non-2,3,7,8-TCDD TEQ level
10 (-47.6 ppt lipid, 11.9 ng/kg body burden at 25% body fat); and the upper limit is the combination
11 of the upper 2,3,7,8-TCDD and upper non-2,3,7,8-TCDD TEQs.
12 As discussed earlier, using background of total body burden (TEQDFP-WHO98) as a point
13 of comparison, these often- termed "highly exposed" populations have maximum body burdens
14 that are relatively close to general population backgrounds at the time. When compared to
15 background body burdens of the late 1980s, many of the median values and some of the mean
16 values fall within a range of one order of magnitude (factor of 10) and all fall within a range of
17 two orders of magnitude (factor of 100). General population backgrounds at the time are likely
18 to have been higher. As these are attained body burdens, measured at the time of the Seveso
19 accident or back-calculated to the time of last known elevated exposure, being compared to
20 backgound, average lifetime body burdens in these cohorts will be even closer to lifetime average
21 background levels. This will be important if, as demonstrated for some chronic effects in
22 animals and as assumed when relying on average body burden as a dose metric, cancer and other
23 noncancer effects are a consequence of average tissue levels over a lifetime. Body burdens begin
24 to decline slowly soon after elevated exposure ceases. Some data in humans and animals suggest
25 that elimination half-lives for dioxin and related compounds may be dose dependent, with high
26 doses being eliminated more rapidly than lower doses. Nonetheless, the use of an approximately
27 7-year half-life of elimination presents a reasonable approach for evaluating both back-calculated
28 and average lifetime levels, because for most cohorts the exposure is primarily to TCDD.
29 The ability to detect effects in epidemiologic study is dependent on a sufficient difference
30 between control and exposed populations. The relatively small difference (<10-100 fold)
31 between exposed and controls in these studies makes exposure characterization in the studies a
32 particularly serious issue. This point also strengthens the importance of measured blood or tissue
33 levels in the epidemiologic analyses, despite the uncertainties associated with calculations
34 extending the distribution of measured values to the entire cohort and assumptions involved in
35 back-calculations.
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1 Characterization of the risk of exposure of humans today remains focused on the levels
2 of exposure that occur in the general population, with particular attention given to special
3 populations (see Part I). For evaluation of multiple endpoints and considering the large
4 differences in half-lives for TCDD across multiple species, it is generally best to use body burden
5 rather than daily intake as the dose metric for comparison unless data to the contrary are
6 presented. Further discussion of this point, which provides the rationale for this science-based
7 policy choice, is presented in Part II, Chapters 1 and 8.
8
9 5.1.1. Calculations of Effective Dose (ED)
10 Comparisons across multiple endpoints, multiple species, and multiple experimental
11 protocols are too complicated to be made on the basis of the full dose-response curve. As
12 discussed above, comparisons of this sort can be made by either choosing a given exposure and
13 comparing the responses, or choosing a particular response level and comparing the associated
14 exposures. In the analyses contained in Chapter 8 and elsewhere in the reassessment, comparison
15 of responses is made using estimated exposures associated with a given level of excess response
16 or risk. To avoid large extrapolations, this common level of excess risk was chosen such that for
17 most studies, the estimated exposure is in or near the range of the exposures seen in the studies
18 being compared, with extra weight given to the human data. A common metric for comparison is
19 the effective dose or ED, which is the exposure dose resulting in an excess response over
20 background in the studied population. EPA has suggested this approach in calculating
21 benchmark doses (BMD) (Allen et al, 1994) and in its proposed approaches to quantifying
22 cancer risk (U.S. EPA, 1996). Although effective dose evaluation at the 10% response level
23 (ED10 or lower bound on ED10 [LED10]) is somewhat the norm, given the power of most chronic
24 toxicology studies to detect an effect, this level is actually higher than those typically observed in
25 the exposed groups in studies of TCDD impacts on humans. To illustrate, lung cancer mortality
26 has a background lifetime risk of approximately 4% (smokers and nonsmokers combined), so
27 that even a relative risk of 2.0 (2 times the background lifetime risk) represents approximately a
28 4% increased lifetime risk. Based upon this observation and recognizing that many of the
29 TCDD-induced endpoints studied in the laboratory include 1% effect levels in the experimental
30 range, Chapter 8 presents effective doses of 1% or ED01. The use of ED values below 10% is
31 consistent with the Agency's guidance on the use of mode of action in assessing risk, as
32 described in the evaluation framework discussed in Section 3.3, in that the observed range for
33 many "key events" extends down to or near the 1% response level. Determining the dose at
34 which key events for dioxin toxicity begin to be seen in a heterogeneous human population
35 provides important information for decisions regarding risk and safety.
36
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1 5.2. EMPIRICAL MODELING OF INDIVIDUAL DATA SETS
2 As described in Chapter 8, empirical models have advantages and disadvantages relative
3 to more ambitious mechanism-based models. Empirical models provide a simple mathematical
4 model that adequately describes the pattern of response for a particular data set and can also
5 provide the means for hypothesis testing and interpolation between data points. In addition, they
6 can provide qualitative insights into underlying mechanisms. However, the major disadvantage
7 is their inability to quantitatively link data sets in a mechanistically meaningful manner. Data
8 available for several biochemical and toxicological effects of TCDD. and on the mechanism of
9 action of this chemical, indicate that there is good qualitative concordance between responses in
10 laboratory animals and humans (see Table 1). For example, human data on exposure and cancer
11 response appear to be qualitatively consistent with animal-based risk estimates derived from
12 carcinogenicity bioassays (see Part II, Chapter 8). These and other data presented throughout this
13 reassessment would suggest that animal models are generally an appropriate basis for estimating
14 human responses. Nevertheless, there are clearly differences in exposures and responses between
15 animals and humans, and recognition of these is essential when using animal data to estimate
16 human risk. The level of confidence in any prediction of human risk depends on the degree to
17 which the prediction is based on an accurate description of these interspecies extrapolation
18 factors. See Chapter 8 for a further discussion of this point.
19 Almost all data are consistent with the hypothesis that the binding of TCDD to the AhR is
20 the first step in a series of biochemical, cellular, and tissue changes that ultimately lead to toxic
21 responses observed in both experimental animals and humans (see Part II, Chapter 2). As such,
22 an analysis of dose-response data and models should use, whenever possible, information on the
23 quantitative relationships among ligand (i.e., TCDD) concentration, receptor occupancy, and
24 biological response. However, it is clear that multiple dose-response relationships are possible
25 when considering ligand-receptor mediated events. For example, dose-response relationships for
26 relatively simple responses, such as enzyme induction, may not accurately predict dose-response
27 relationships for complex responses such as developmental effects and cancer. Cell- or
28 tissue-specific factors may determine the quantitative relationship between receptor occupancy
29 and the ultimate response. Indeed, for TCDD there are much experimental data from studies
30 using animal and human tissues to indicate that this is the case. This serves as a note of caution,
31 as empirical data on TCDD are interpreted in the broader context of complex exposures to
32 mixtures of dioxin-like compounds as well as to non-dioxin-like toxicants.
33 As for other chemical mechanisms where high biological potency is directed through the
34 specific and high-affinity interaction between chemical and critical cellular target, the
35 supposition of a response threshold for receptor-mediated effects is a subject for scientific
36 debate. The basis of this controversy has been ret jntly summarized (Sewall and Lucier, 1995).
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1 Based on classic receptor theory, the occupancy assumption states that the magnitude of
2 biological response is proportional to the occupancy of receptors by drug molecules. The
3 "typical" dose-response curve for such a receptor-mediated response is sigmoidal when plotted
4 on a semilog graph or hyperbolic if plotted on a arithmetic plot. Implicit in this relationship is
5 low-dose linearity (0-10% fractional response) through the origin. Although the law of mass
6 action predicts that a single molecule of ligand can interact with a receptor, thereby inducing a
7 response, it is also stated that there must be some dose that is so low that receptor occupancy is
8 trivial and therefore no perceptible response is obtainable.
9 Therefore, the same receptor occupancy assumption of the classic receptor theory is
10 interpreted by different parties as support for and against the existence of a threshold. It has been
11 stated that the occupancy assumption cannot be accepted or rejected on experimental or
12 theoretical grounds (Goldstein et al., 1974). To determine the relevance of receptor interaction
13 for TCDD-mediated responses, one must consider (1) alternatives as well as limitations of the
14 occupancy theory; (2) molecular factors contributing to measured endpoints; (3) limitations of
15 experimental methods; (4) contribution of measured effect to a relevant biological/toxic
16 endpoint; and (5) background exposure.
17 Throughout this reasssessment, each of these considerations has been explored within the
18 current context of the understanding of the mechanism of a action of TCDD, of the
19 methods for analysis of dose-response for cancer and noncancer endpoints, and of the available
20 data sets of TCDD dose and effect for several rodent species, as well as humans that were
21 occupationally exposed to TCDD at levels exceeding the exposure of the general population.
22
23 5.2.1. Cancer
24 As described in Section 2.2.1.4, TCDD has been classified as a human carcinogen, and is
25 a carcinogen in all species and strains of laboratory animals tested. The epidemiological
26 database for TCDD, described in detail in Part II, Chapter 7a, suggests that exposure may be
27 associated with increases in all cancers combined, in respiratory rumors and, perhaps, in soft-
28 tissue sarcoma. Although there are sufficient data in animal cancer studies to model dose-
29 response for a number of tumor sites, as with many chemicals, it is generally difficult to find
30 human data with sufficient information to model dose-response relationships. For TCDD, there
31 exist three studies of human occupational exposure with enough information to perform a
32 quantitative dose-response analysis. These are the NIOSH study (Fingerhut et al., 199la), the
33 Hamburg cohort study (Manz et al., 1991), and the BASF cohort study (Zober et al., 1990). In
34 Part II, Chapter 8, simple empirical models were applied to these studies for which
35 exposure-response data for TCDD are available in human populations.
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1 Modeling cancer in humans uses slightly different approaches from those used in
2 modeling animal studies. The modeling approach used in the analysis of the human
3 epidemiology data for all cancers combined and lung cancer involves applying estimated human
4 body burden to cancer response and estimating parameters in a linear risk model for each data
5 set. A linear risk model was used because the number of exposure groups available for analyses
6 was too small to support more complicated models. Because of this, evaluating the shape of the
7 dose-response data for the human studies was not done. Access to the raw data may make it
8 possible to use more complicated mathematical forms that allow for the evaluation of shape. In
9 the one case in which this has been done, the dose-response shape suggested a response that was
10 less than linear (dose raised to a power <1) (Becher et al., 1998). For these studies, there are
11 several assumptions and uncertainties involved in modeling the data, including extrapolation of
12 dosage, both in back-calculation and in elimination kinetics, and the type of extrapolation model
13 employed.
14 As described in Part II, Chapter 8, the data used in the analyses are from Aylward et al.
15 (1996) for the NIOSH study, Flesch-Janys et al. (1998) for the Hamburg cohort, and Ott and
16 Zober (1996a,b) for the BASF cohort. The limited information available from these studies is in
17 the form of standard mortality ratios (SMRs) and/or risk ratios by exposure subgroups with some
18 estimate of cumulative subgroup exposures. Exposure subgroups were defined either by number
19 of years of exposure to dioxin-yielding processes or by extrapolated TCDD levels. No study
20 sampled TCDD blood serum levels for more than a fraction of its cohort, and these samples were
21 generally taken decades after last known exposure. In each study, serum fat or body fat levels of
22 TCDD were back calculated using a first-order model. The assumed half-life of TCDD used in
23 the model varied from study to study. Aylward et al. used the average TCDD levels of those
24 sampled in an exposure subgroup to represent the entire subgroup. Flesch-Janys et al. and Ott
25 and Zober performed additional calculations, using regression procedures with data on time spent
26 at various occupational tasks, to estimate TCDD levels for all members of their respective
27 cohorts. They then divided the cohorts into exposure groups based on the estimated TCDD
28 levels. The information presented in the literature cited above was used to calculate estimated
29 average TCDD dose levels in Chapter 8.
30 To provide ED01 estimates for comparison in Chapter 8, Poisson regression (Breslow and
31 Day, 1987) was used to fit a linear model to the data described above. Analysis of animal cancer
32 data suggests a mixture of linear and nonlinear responses with linear shape parameters
33 predominating; complex responses to TCDD, both cancer and noncancer, are more often than not
34 nonlinear. Besides the issue of use of a linear model, several other important uncertainties
35 discussed in Chapter 8 are the representativeness and precision of the dose estimates that were
36 used, the choice of half-life and whether it is dose dependent, and potential interactions between
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1 TCDD and smoking or other toxicants. Nevertheless, with these qualifications, it is possible to
2 apply simple empirical models to studies in which exposure data for TCDD are available in
3 human populations.
4 The analysis of these three epidemiological studies of occupationally exposed individuals
5 suggest an effect of TCDD on all cancers, and on lung cancers in the adult human male. The
6 EDOIs based upon average excess body burden of TCDD ranged from 6 ng TCDD/kg to 161 ng
7 TCDD/kg in humans. The lower bounds on these doses (based on a modeled 95% C.I.) range
8 from 3.5 ng TCDD/kg to 77 ng TCDD/kg. For the effect of TCDD on lung cancers, the only
9 tumor site increased in both rodents and humans, the human ED01s ranged from 24 ng/kg to 161
10 ng/kg. The lower bounds on these doses (based on a modeled 95% C.I.) range from 10.5 ng
11 TCDD/kg to 77 ng TCDD/kg. These estimates of ED01s are compared to animal estimates later
12 in this discussion.
13 Both empirical and mechanistic models were used to examine cancer dose-response in
14 animals. Portier et al. (1984) used a simple multistage model of carcinogenesis with up to two
15 mutation stages affected by exposure to model the five tumor types observed to be increased in
16 the 2-year feed study of Kociba et al. (Sprague-Dawley rats, 1978) and the eight tumor types
17 observed to be increased in the 2-year gavage cancer study conducted by the National Toxicology
18 Program (Osborne-Mendel rats and B6C3F, mice, 1982a). The findings from this analysis,
19 which examined cancer dose-response within the range of observation are presented in their
20 Table 8.3.2., which is reproduced with slight modifications as Table 5-2. All but one of the
21 estimated ED01s are above the lowest dose used in the experiment (approximately 1 ng
22 TCDD/kg/day in both studies) and are thus interpolations rather than extrapolations. The
23 exception, liver cancer in female rats from the Kociba study, is very near the lowest dose used in
24 this study and is only a small extrapolation (from 1 ng TCDD/kg/day to 0.77 ng TCDD/kg/day).
25 Steady-state body burden calculations were also used to derive doses for comparison across
26 species. Absorption was assumed to be 50% for the Kociba et al. study (feed experiment) and
27 100% for the NTP study (gavage experiment). Also presented in Table 5-2 are the shapes of the
28 dose-response curves as determined by Portier et al. (1984).
29 The predominant shape of the dose-response curve in the experimental region is linear;
30 this does not imply that a nonlinear model such as the quadratic or cubic would not fit these data.
31 In fact, it is unlikely that in any one case, a linear model or a quadratic model could be rejected
32 statistically for these cases. These studies had only three experimental dose groups, hence these
33 shape calculations are not based upon sufficient doses to guarantee a consistent estimate; they
34 should be viewed with caution. The ED0! steady-state body burdens range from a low value of
35 14 ng/kg based upon the linear model associated with liver tumors in female rats to as high as
36 1,190 ng/kg based upon a cubic model associated with thyroid follicular cell adenomas in female
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1 rats. Lower bounds on the steady-state body burdens in the animals range from 10 ng TCDD/kg
2 to 224 ng/kg. The corresponding estimates of daily intake level at the ED01 obtained from an
3 empirical linear model range from 0.8 to 43 ng TCDD/kg body weight/day depending on the
4 tumor site, species, and sex of the animals investigated. Lower confidence bounds on the
5 estimates of daily intake level at the ED01 in the animals range from 0.6 to 14 ng TCDD/kg body
6 weight/day. In addition, using a mechanistic approach to modeling, Portier and Kohn (1996)
7 combined the biochemical response model of Kohn et al. (1993) with a single initiated phenotype
8 two-stage model of carcinogenesis to estimate liver tumor incidence in female Sprague-Dawley
9 rats from the 2-year cancer bioassay of Kociba et al. (1978). By way of comparison, the ED0,
10 estimate obtained from this linear mechanistic model was 0.15 ng TCDD/kg body weight/day
11 based on intake, which is equivalent to 2.7 ng TCDD/kg steady-state body burden. No lower
12 bound on this modeled estimate of steady-state body burden was provided.
13 As discussed in Part II, Chapter 8, different dose metrics can lead to widely diverse
14 conclusions. For example, as described in Chapter 8, the ED0, intake for the animal tumor sites
15 presented above ranges from less than 1 to tens of ng/kg/day, and the lowest dose with an
16 increased tumorigenic response (thyroid tumors) in a rat is 1.4 ng/kg/day (NTP, 1982a). The
17 daily intake of TCDD in humans is estimated to be 0.14 to 0.4 pg TCDD/kg/day. This implies
18 that humans are exposed to doses 3,500 to 10,000 times lower than the lowest tumorigenic daily
19 dose in rat thyroid. However, 1.4 ng/kg/d in the rat leads to a steady-state body burden of
20 approximately 25 ng/kg, assuming a half-life of TCDD of 23 days and absorption from feed of
21 50%2. If the body burden of TCDD in humans is approximately 5 ng TCDD/kg lipid or 1.25
22 ng/kg body weight (assuming about 25% of body weight is lipid), humans are exposed to about
23 20 times less TCDD than the minimal carcinogenic dose for the rat. If total TEQ is considered
24 the difference is even less, approaching only a factor of 2 difference. The difference between
25 these two estimates is entirely due to the approximately 100-fold difference in the half-life
26 between humans and rats. At least for this comparison, if cancer is a function of average levels
27 in the body, the most appropriate metric for comparison is the average or steady-state body-
28 burden, since the large differences in animal to human half-life are accounted for. Comparisons
29 of human and animal ED01s from Part II, Chapter 8, for cancer response on a body-burden basis
30 show approximately equal potential for the carcinogenic effects of TCDD. In humans, restricting
31 the analysis to log-linear models in Part II, Chapter 8, resulted in cancer ED01s ranging from 6
32 ng/kg to 161 ng/kg. This was similar to the empirical modeling estimates from the animal
• Steady-state body burden (ng/kg) = (daily dose (ng/kg/day) * (half-life)/Ln(2)) (f), where f is the fraction
absorbed from the exposure route (unitless) and half-life is the half-life in days.
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1 studies, which ranged from 14 ng/kg to 1,190 ng/kg (most estimates were in the range from 14
2 to 500 ng/kg). The lower bounds on the human body-burdens at the ED01s (based on a modeled
3 95% C.I.) range from 3.5 ng TCDD/kg to 77 ng TCDD/kg. Lower bounds on the steady-state
4 body burdens in the animals range from 10 ng TCDD/kg to 224 ng/kg. The estimate for the
5 single mechanism-based model presented earlier (2.7 ng/kg) was approximately 2 times lower
6 than the lower end of the range of human ED01 estimates and less than the lower bound on the
7 LED01. The same value was approximately 5 times lower than the lower end of the range of
8 animal ED01 estimates and less than 4 times less than the LED0).
9 Using human and animal cancer ED01s, their lower bound estimates, and the value of
10 2.7 ng TCDD/kg from the single mechanism-based model, slope factors and comparable risk
11 estimates for a human background body burden of approximately 5 ng TEQ/kg (20 ng TEQ/kg
12 lipid) can be calculated using the following equations:
13 Slope factor (per pg TEQ/kgBW/day) = risk at ED01 / intake (pg TEQ/kgBW/day)
14 associated with human equivalent steady-state body burden at ED01 where:
15 Risk at ED01 = 0.01; and
16 Intake (pgTEQ/kgBW/day) = [body burden at ED., fag TEO/kg)*half-life Cdavs)] * f (5-1)
17 Ln(2)
18 half-life = 2,593 days in humans and 25 days in rats (see Table 8.1 in Part II, Chapter 8)
19 f = fraction of dose absorbed; assumed to be 50% for absorption from food (Kociba et al., 1976)
20 and 100% for other routes.
21
22 Upper bound on excess risk at human background body burden = (human (5-2)
23 background body burden (ng/kg))(risk at ED01)/lower bound on human equivalent
24 steady-state body burden (ng/kg) at EDO 1, where:
25
26 Risk at ED01 = 0.01
27
28 Use of these approaches reflects methodologies being developed within the context of the
29 revised draft Cancer Risk Assessment Guidelines. Slopes are estimated by a simple proportional
30 method at the "point of departure" (LED01) at the low end of the range of experimental
31 observation. As discussed below, these methods can be compared to previous approaches using
32 the linearized multistage (LMS) procedure to determine if the chosen approach has significantly
33 changed the estimation of slope. The estimates of ED01/LED01 represent the human-equivalent
34 body burden for 1% excess cancer risk based on exposure to TCDD and are assumed for
35 purposes of this analysis to be equal for TCDD equivalents (total TEQ). This assumption is
36 based on the toxicity equivalence concept discussed throughout this report and in detail in Part II,
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1 Chapter 9. All cancer slope factors can be compared to the Agency's previous slope factor of
2 1.6x 10'4perpgTCDD/kgBW/day(orl.6x 105permgTCDD/kgBW/day) (U.S. EPA, 1985).
3
4 5.2.1.1. Estimates of Slope Factors and Risk at Current Background Body Burdens Based on
5 Human Data
6 Estimates of upper bound slope factors (per pg TCDD/kgB W/day) calculated from the
7 human ED01s presented in Table 8.3.1 range from 5.3 * 10'3, if the LED01 for all cancer deaths in
8 the Hamburg cohort is used, to 2.4 x 10'4 if the ED0] for lung cancer deaths in the smaller BASF
9 cohort is used. All of the other slope factors for all cancer deaths or lung cancer deaths in the
10 three cohorts would fall within this range. LED01s for all cancer deaths span approximately an
11 order of magnitude and would generate slope factors in the range of 5 x 10~3 to 5 x 10"4. Slightly
12 smaller slope factors are generated when LED0,s for lung cancer are used. The largest slope
13 factors based on LED01s come from the Hamburg cohort (5.3 x 10"3 and 1.8 x 10"3 respectively
14 for all cancer deaths and lung cancer deaths.) These estimates compare well with the estimates
15 of risk associated with TCDD exposure in the Hamburg cohort published by Becher et al. (1998).
16 The risk estimates of Becher et al. derived from data on TCDD exposure to male workers with a
17 10-year latency and taking greater caution over other factors affecting risk including choice of
18 model, latency, job category, dose metric, and concurrent exposures. These estimates range from
19 1.3 x 10'3 to 5.6 x 10~3 per pg TCDD/kgB W/day. In this analysis all excess cancers are
20 attributed to TCDD exposure, despite significant levels of other dioxin-like compounds in blood
21 measurements of this cohort (see Table 5-1). Although risk estimates using TCDD alone in this
22 cohort might suggest an overestimate of risk, no evidence for this emerged from the analysis and,
23 assuming that TCDD will still dominate total TEQ in this population, differences in slope factor
24 estimates are likely to be less than a factor of 2 and may not be discemable. Taking into account
25 different sources of variation, Becher et al. (1998) suggest a range of 10"3 to 10"2 for additional
26 lifetime cancer risk for a daily intake of 1 pg TCDD/kg BW/day. By inference, that range could
27 also apply to total TEQ intake. As described in Section 4.4.2, current estimates of intake in the
28 United States are estimated to be approximately 1 pg TEQ/kg BW/day. Using Equation 5-2, the
29 upper bound range of risks estimated from current human body burdens of 5 ng TEQ/kgBW
30 (which equates to a serum level of 20 pg/g lipid [see Table 4.7]) based on all cancer deaths in the
31 three cohorts ranged from 1.4 x 10"2 to 1.3 x 10"3; based on lung cancer deaths, the upper bound
32 on the estimates of excess risk extended to 6 x 10'4. The range of these estimates provides
33 further support for the perspective on risk provided by Becher et al. (1998). Uncertainties
34 associated with these estimates from human studies are discussed in Part II, Chapter 8, and in
35 Becher etal. (1998).
36
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1 5.2.1.2. Estimates of Slope Factors and Risk at Current Background Body Burdens Based on
2 Animal Data
3 Upper bound slope factors (per pg TCDD/kgBW/day) for human cancer risk calculated
4 from lower bounds in ED0,s (LEDs01) for the animal cancers presented in Table 5-2 range from
5 1.9 x 10'3 to 8.4 x 10'5. This spans a range from being 12 times greater than the previous upper
6 bound estimate on cancer slope (1.6 x 1Q-4 [U.S. EPA, 1985]) to 2 times less. The largest slope
7 factor is derived from the same study as the 1985 estimate; that is, the slope factor derived from
8 the female liver cancer in the Kociba et al. (1978) study continues to give the largest slope factor.
9 In attempting these comparisons, two issues became apparent. First, the body burden and the
10 intake at the ED0, from Portier et al. (1984) does not result in the same slope factor as U.S. EPA
11 (1985). Despite the use of the same study results, a slope factor of 1.8 x Q"5 per pg
12 TCDD/kgBW/day results using the LMS approach. This is a factor of approximately 10 lower
13 than the EPA (1985) estimate of the slope. The differences are attributable to the aims of the
14 respective calculations at the time. Portier et al. (1984) calculated "virtually safe doses"
15 assuming that rodent and human doses scaled on a mg/kg basis, and he used the original tumor
16 counts from the study. EPA (1985), on the other hand, used (BW)2/3 to arrive at a human
17 equivalent dose and used the pathology results from a reread of the original Kociba study (U.S.
18 EPA, 1980). In addition, tumor counts were adjusted for early mortality in the study. The factor
19 to adjust for (BW)3/4-scaling in the rat is 5.8. The correction for early mortality can be accounted
20 for with a factor of 1.6 (this is the ratio of the intake values at the ED01 with and without the
21 early mortality correction). If the Portier et al. slope factor (1.8 x 10~5 per pg TCDD/kgBW/day)
22 is multiplied by these two factors, a slope of 1.7 x 10~4per pg TCDD/kgBW/day is calculated.
23 This is equivalent to the U.S. EPA (1985) estimate of 1.6 x 10'4per pg TCDD/kgBW/day.
24 Reconciling these issues is important to ensure appropriate comparisons of slope factor
25 estimates.
26 More important is the calculation of slope factor estimates using current methods of
27 analysis that recognize the importance of the dose metric and the differences in half-life of
28 dioxins in the bodies of laboratory animals and humans (see Part II, Chapter 8, for detailed
29 discussion). The major difference between the approaches used to calculate risks in the mid-
30 . 1980s (Portier et al., 1984; U.S. EPA, 1985) and the current approach is the use of body burden
31 as the dose metric for animal-to-human dose equivalence. All things being equal, the use of body
32 burden accounts for the approximately 100-fold difference between half-lives of TCDD in
33 humans and rats (2,593 days versus 25 days [see Part II, Table 8.1]). Use of Equation 5-1 results
34 in an estimated body burden at the LED01 of 6.1 ng TEQ/kg to be derived from the EPA (1985)
35 Kociba tumor counts. This compares favorably with the Portier estimate of 10 ng TEQ/kg found
36 in Table 5-2. The difference is entirely accounted for by the early deaths adjustment by EPA
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1 (1985). Use of these body burdens at the LEDOI results in slope factor estimates of 1.9 * 10"3 per
2 pg TCDD/kgBW/day and 3.1 * 1O'3 per pg TCDD/kgBW/day for the Chapter 8 and the newly
3 derived body burden, respectively. Again, the difference is due solely to the adjustment for early
4 mortality and EPA believes this provides a better estimate of upper bound lifetime risk than does
5 the unadjusted. EPA's new slope factor (3.1 x 10'3per pgTCDD/kgBW/day) is 19 times greater
6 than the slope factor from 1985.
7 A second issue with the modeling of the Kociba data relates to the appropriate tumor
8 counts to use. As mentioned in Section 2, Goodman and Sauer (1992) reported a second
9 re-evaluation of the female rat liver tumors in the Kociba study using the latest pathology criteria
10 for such lesions. Results of this review are discussed in more detail in Part II, Chapter 6. The
11 review confirmed only approximately one-third of the tumors of the previous review (U.S. EPA,
12 1980). Although this finding did not change the determination of carcinogenic hazard because
13 TCDD induced tumors in multiple sites in this study, it does have an effect on evaluation of
14 dose-response and on estimates of risk. Because neither the original EPA (1985) slope factor
15 estimate nor that of Portier et al. (1984) reflect this reread, it is important to factor these results
16 into the estimate of the ED01 and slope factor. Using the LMS procedure used by EPA in 1985
17 and the tumor counts as reported in Part II, Chapter 6, Table 6.2, the revised slope factor is
18 reduced by approximately 3.6-fold to yield a slope factor of 4.4 x 10"5 per pg TCDD/kgB W/day.
19 However, because the original estimates used a (BW)3/4 scaling, this must be adjusted to use body
20 burden and obtain an appropriate result. When dose is adjusted and Equation 5-1 is used, an
21 LED01 of 22.2 ng TEQ/kg and a slope factor of 8.3 x l O'4 per pg TCDD/kgB W/day are derived.
22 This represents EPA's most current upper bound estimate of human cancer risk based on animal
23 data. It is 5.2 times larger than the slope factor calculated in U.S. EPA (1985). This number
24 reflects the increase in slope factor based on use of the body burden dose metric (19 times
25 greater) and the use of the Goodman and Sauer (1992) pathology (3.6 times less).
26
27 5.2.1.3. Estimates of Slope Factors and Risk at Current Background Body Burdens Based on
28 a Mechanistic Model
29 As discussed above, Portier and Kohn (1996) combined the biochemical response model
30 of Kohn et al. (1993) with a single initiated-phenotype two-stage model of carcinogenesis to
31 estimate liver tumor incidence in female Sprague-Dawley rats from the Kociba et al. (1978)
32 bioassay. The model is described in more detail in Part II, Chapter 8. This model adequately fit
33 the tumor data, although it overestimated the the observed tumor response at the lowest dose in
34 the Kociba study. The shape of the dose-response curve was approximately linear and the
35 estimated ED01 value for this model was 1.3 ng/kg/day. The corresponding body burden giving a
36 1% increased effect was 2.7 ng/kg. The model authors believe that the use of CYP1A2 as a dose
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1 metric for the first mutation rate is consistent with its role as the major TCDD-inducible estradiol
2 hydrolase in liver and with its hypothesized role in the production of estrogen metabolites leading
3 to increased oxidative DNA damage and increased mutation (Yager and Liehr, 1996; Hayes et
4 al., 1996; Barman et al., 1986; Roy et al., 1992). Although no lower bound estimate of the ED01
5 is calculated, a maximum likelihood estimate of the slope factor can be calculated. It is
6 7.1 x 10° per pg TCDD/kgBW/day. This estimate represents an example of the type of modeling,
7 based on key events in a mode of action for carcinogenesis, which is consistent with future
8 directions in dose-response modeling described in EPA's revised proposed cancer risk
9 assessment guidelines (U.S. EPA, 1999). Although a number of uncertainties remain regarding
10 structure and parameters of the model, the slope estimate is consistent with those derived from
11 humans and animals. More details on this model can be found in Part II, Chapter 8.
12
13 5.2.2. Noncancer Endpoints
14 At this point, sufficient data are not available to model noncancer endpoints in humans.
15 Many studies are available to estimate ED0] values for noncancer endpoints in animals. However,
16 there are a number of difficulties and uncertainties that should be considered when comparing the
17 same or different endpoints across species. Some of these include differences in sensitivity of
18 endpoints, times of exposure, exposure routes, species and strains, use of multiple or single
19 doses, and variability between studies even for the same response. The estimated ED01s may be
20 influenced by experimental design, suggesting that caution should be used in comparing values
21 from different designs. In addition, caution should be used when comparing studies that
22 extrapolate ED01s outside the experimental range. Furthermore, it may be difficult to compare
23 values across endpoints. For example, the human health risk for a 1% change of body weight
24 may not be equivalent to a 1% change in enzyme activity. Finally, background exposures are not
25 often considered in these calculations simply because they were not known. Nevertheless, given
26 these considerations, several general trends were observed and discussed in Part II, Chapter 8.
27 The lowest ED0]s tended to be for biochemical effects, followed by hepatic responses, immune
28 responses, and responses in tissue weight. An analysis of shape parameters implies that many
29 dose-response curves are consistent with linearity over the range of doses tested. This analysis
30 does not imply that the curves would be linear outside this range of doses, but it does inform the
31 choices for extrapolation. This is particularly true when body burdens or exposures at the lower
32 end of the observed range are close to body burdens or exposures of interest for humans, which is
33 the case with dioxin-like chemicals.
34 Overall, shape parameter data suggest that biochemical responses to TCDD are more
35 likely to be linear within the experimental dose range, while the more complex responses are
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1 more likely to assume a nonlinear shape. However, a large number (> 40%) of the more complex
2 responses have shape parameters that are more consistent with linearity than nonlinearity.
3 The tissue weight changes seen for animals (using only data sets with good or moderate
4 empirical fits to the model) yielded a median ED01 at average body burdens of 510 ng/kg in the
5 multidose studies (range; 11 to 28000 ng/kg) and a median ED01 of 160 ng/kg (range 0.0001 to
6 9,700 ng/kg) in the single dose studies. Toxicity endpoints from the single dose studies resulted
7 in a median value at average body burdens of 4,300 ng/kg (range 1.3 to 1,000,000 ng/kg). For
8 tissue weight changes, 43% of the dose-response curves exhibited linear response. In contrast, the
9 toxicity endpoints from the single-dose studies exhibited predominantly nonlinear responses
10 (80%). All multidose studies demonstrated a greater degree of linear response (41%) than did
11 single-dose studies (37%), especially for tissue weight changes and toxicity endpoints (50%
12 linear for multidose versus 34% for single dose). In general, it is not possible to dissociate the
13 differences between cancer and noncancer dose-response as being due to differences in endpoint
14 response or simply to differences in the length of dosing and exposure. Also, a greater
15 percentage of the noncancer ED01s were extrapolations below the lower range of the data (42%)
16 than was the case for the cancer endpoints (8% in animals and no extrapolations in humans).
17
18 5.3. MODE-OF-ACTION BASED DOSE-RESPONSE MODELING
19 As described in Chapter 8, mechanism-based modeling can be a powerful tool for
20 understanding and combining information on complex biological systems. Use of a truly
21 mechanism-based approach can, in theory, enable reliable and scientifically sound extrapolations
22 to lower doses and between species. However, any scientific uncertainty about the mechanisms
23 that the models describe is inevitably reflected in uncertainty about the predictions of the models.
24 The assumptions and uncertainties involved in the mechanistic modeling described in Chapter 8
25 are discussed at length in that chapter and in cited publications.
26 The development and continued refinement of PBPK models of the tissue dosimetry of
27 dioxin have provided important information concerning the relationships between administered
28 does and dose to tissue compartments (section 8.2). Aspects of these models have been validated
29 in the observable response range for multiple tissue compartments, species, and class of
30 chemical. These models will continue to provide important new information for future revisions
31 of this health assessment document. Such information will likely include improved estimates of
32 tissue dose for liver and other organs where toxicity has been observed, improved estimates of
33 tissue dose(s) in humans, and improved estimates of tissue dose for dioxin related compounds.
34 As a part of this reassessment, the development of biologically based dose-response
35 (pharmacodynamic) models for dioxin and related compounds has lead to considerable and
36 valuable insights regarding both mechanisms of dioxin action and dose-response relationships for
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1 dioxin effects. These efforts, described in some detail in Chapter 8, have provided additional
2 perspectives on traditional methods such as the linearized multistage procedure for estimating
3 cancer potency or the uncertainty factor approach for estimating levels below which noncancer
4 effects are unlikely to occur. These methods have also provided a biologically based rationale
5 for what had been primarily statistical approaches. The development of models like those in
6 Chapter 8 allows for an iterative process of data development, hypotheses testing and model
7 development.
8
9 5.4. SUMMARY DOSE-RESPONSE CHARACTERIZATION
10 All humans tested contain detectable body burdens of TCDD and other dioxin-like
11 compounds that are likely to act through the same mode of action. It is possible that any
12 additional exposure above current background body burdens will be additive to ongoing
13 responses. The magnitude of the additional response will be a function of the toxicity
14 equivalence of the incremental exposure. This observation, the relatively small margin of
15 exposure for "key events," and the high percentage of observed linear responses suggest that a
16 proportional model should be used when extrapolating beyond the range of the experimental
17 data. Short of extrapolating to estimate risk in the face of uncertainties described above, a simple
18 margin-of-exposure approach may be useful to decision-makers when discussing risk
19 management goals. However, this decision would have to be based upon a policy choice because
20 this analysis does not strongly support either choice.
21 Because human data for cancer dose-response analysis were available and because of a
22 strong desire to stay within the range of responses estimated by these data, the risk chosen for
23 determining a point of departure was the 1% excess risk. Doses and exposures associated with
24 this risk (the ED0]s) were estimated from the available data using both mechanistic and empirical
25 models. Comparisons were made on the basis of body burdens to account for differences in
26 half-life across the numerous species studied.
27 In humans, restricting the analysis to log-linear models resulted in cancer ED0,s ranging
28 from 6 ng/kg to 161 ng/kg. This was similar to the estimates, from empirical modeling, from the
29 animal studies which ranged from 14 ng/kg to 1,190 ng/kg (most estimates were in the range
30 from 14 to 500 ng/kg), and 2.7 ng/kg for the single mechanism-based model. Lower bounds on
31 these ED01 estimates were used to calculate upper bound slope factors and risk estimates for
32 average background body burdens. These estimates are presented above. Upper bound slope
33 factors allow the calculation of the probability of cancer risk for the highly vulnerable in the
34 population (estimated to be the top 5% or greater). Even though there may be individuals in the
35 population who might experience a higher cancer risk on the basis of genetic factors or other
36 determinants of cancer risk not accounted for in epidemiologic data or animal studies, the vast
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1 majority of the population is expected to have less risk per unit of exposure and some may have
2 zero risk. Based on these slope factor estimates (per pg TEQ/kgBW/day), average current
3 background body burdens (5 ng/kgBW) that result from average intakes of approximately 3
4 pgTEQ/kgBW/day are in the range of 10~3 to 10~2. A very small percentage of the population
5 (< 1 %) may experience risks that are 2-3 times higher than this if they are among both the most
6 vulnerable and the most highly exposed (among the top 5%) based on dietary intake of dioxin
7 and related compounds. This range of upper bound risk for the general population has increased
8 an order of magnitude from the risk described at background exposure levels based on EPA's
9 draft of this reassessment (10-4-10-3) (U.S. EPA, 1994).
10 Estimates for noncancer endpoints showed much greater variability, ranging over 10
11 orders of magnitude. In general, the noncancer endpoints displayed lower ED0]s for short-term
12 exposures versus longer term exposures, and for simple biochemical endpoints versus more
13 complex endpoints such as tissue weight changes or toxicity. In addition, the noncancer
14 endpoints generally displayed higher estimated ED01s than the cancer endpoints, with most
15 estimates ranging from 100 ng/kg to 100,000 ng/kg. The mechanism-based models for
16 noncancer endpoints gave a lower range of ED01s (0.17 to 105 ng/kg). Although most of these
17 estimates were based upon a single model the estimate from the hepatic zonal induction model
18 gave an ED0, for CYP1A2 induction of 51 ng/kg and hence was within the same range.
19 These estimates, although highly variable, suggest that any choice of body burden, as a
20 point of departure, above 100 ng/kg would likely yield >1% excess risk for some endpoint in
21 humans. Also, choosing of a point of departure below 1 ng/kg would likely be an extrapolation
22 below the range of these data and would likely represent a risk of <1%. Any choice in the middle
23 range of 1 ng/kg to 100 ng/kg would be supported by the analyses, although the data provide the
24 greatest support in the range of 10 ng/kg to 50 ng/kg.
25
26
6. RISK CHARACTERIZATION
1 Characterizing risks from dioxin and related compounds requires the integration of
2 complex data sets and the use of science-based inferences regarding hazard, mode of action, dose
3 response, and exposure. It also requires consideration of incremental exposures in the context of
4 an existing background exposure that is, for the most part, independent of local sources and
5 dominated by exposure through the food supply. Finally, this characterization must consider risks
6 to special populations and developmental stages (subsistence fishers, children, etc.) as well as the
7 general population. It is important that this characterization convey the current understanding of
8 the scientific community regarding these issues, highlight uncertainties in this understanding, and
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1 specify where assumptions or inferences have been used in the absence of data. Although
2 characterization of risk is inherently a scientific exercise, by its nature it must go beyond
3 empirical observations and draw conclusions in untested areas. In some cases, these conclusions
4 are, in fact, untestable given the current capabilities in analytical chemistry, toxicology, and
5 epidemiology. This situation should not detract from our confidence in a well structured and
6 documented characterization of risk, but should serve to confirm the importance of considering
7 risk assessment as an iterative process that benefits from evolving methods and data collection.
8
9 Dioxin and related compounds can produce a wide variety of effects in animals and might
10 produce many of the same effects in humans.
11 There is adequate evidence based on all available information discussed in Parts I and II
12 of this reassessment, as well as that discussed in this Integrated Summary, to support the
13 inference that humans are likely to respond with a broad spectrum of effects from exposure to
14 dioxin and related compounds. These effects will likely range from biochemical changes at or
15 near background levels of exposure to adverse effects with increasing severity as body burdens
16 increase above background levels. Enzyme induction, changes in hormone levels, and indicators
17 of altered cellular function seen in humans and laboratory animals represent effects of unknown
18 clinical significance but that may be early indicators of toxic response. Induction of
19 activating/metabolizing enzymes at or near background levels, for instance, may be adaptive, and
20 in some cases, beneficial, or may be considered adverse. Induction may lead to more rapid
21 metabolism and elimination of potentially toxic compounds, or may lead to increases in reactive
22 intermediates and may potentiate toxic effects. Demonstration of examples of both of these
23 situations is available in the published literature and events of this type formed the basis for a
24 biologically based model discussed in Section 5. Subtle effects, such as the impacts on
25 neurobehavioral outcomes, thyroid function, and liver enzymes (AST and ALT) seen in the
26 Dutch children exposed to background levels of dioxin and related compounds, or changes in
27 circulating reproductive hormones in men exposed to TCDD, illustrate the types of responses
28 that support the finding of arguably adverse effects at or near background body burdens. Clearly
29 adverse effects including, perhaps, cancer may not be detectable until exposures contribute to
30 body burdens that exceed background by one or two orders of magnitude (10 or 100 times). The
31 mechanistic relationships of biochemical and cellular changes seen at or near background body
32 burden levels to production of adverse effects detectible at higher levels remains uncertain, but
33 data are accumulating to suggest mode of action hypotheses for further testing.
34 It is well known that individual species vary in their sensitivity to any particular dioxin
35 effect. However, the evidence available to date indicates that humans most likely fall in the
36 middle of the range of sensitivity for individual effects among animals rather than at either
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1 extreme. In other words, evaluation of the available data suggests that humans, in general, are
2 neither extremely sensitive nor insensitive to the individual effects of dioxin-like compounds.
3 Human data provide direct or indirect support for evaluation of likely effect levels for several of
4 the endpoints discussed in the reassessment, although the influence of variability among humans
5 remains difficult to assess. Discussions have highlighted certain prominent, biologically
6 significant effects of TCDD and related compounds. In TCDD-exposed men, subtle changes in
7 biochemistry and physiology such as enzyme induction, altered levels of circulating reproductive
8 hormones, or reduced glucose tolerance and, perhaps, diabetes, have been detected in a limited
9 number of epidemiologic studies. These findings, coupled with knowledge derived from animal
10 experiments, suggest the potential for adverse impacts on human metabolism, and developmental
11 and/or reproductive biology, and, perhaps, other effects in the range of current human exposures.
12 These biochemical, cellular, and organ-level endpoints have been shown to be affected by
13 TCDD, but specific data on these endpoints do not generally exist for other congeners. Despite
14 this lack of congener-specific data, there is reason to infer that these effects may occur for all
15 dioxin-like compounds, based on the concept of toxicity equivalence.
16 In this volume, dioxin and related compounds are characterized as carcinogenic,
17 developmental, reproductive, immunological, and endocrinological hazards. The deduction that
18 humans are likely to respond with noncancer effects from exposure to dioxin-like compounds is
19 based on the fundamental level at that these compounds impact cellular regulation and the broad
20 range of species that have proven to respond with adverse effects. For example, because
21 developmental toxicity following exposure to TCDD-like congeners occurs in fish, birds, and
22 mammals, it is likely to occur at some level in humans. It is not currently possible to state
23 exactly how or at what levels individuals will respond with specific adverse impacts on
24 development or reproductive function, but analysis of the Dutch cohort data and laboratory
25 animal studies suggests that some effects may occur at or near background levels. Fortunately,
26 there have been few human cohorts identified with TCDD exposures high enough to raise body
27 burdens significantly over background levels (see Table 5-1 and Figure 5-1 in Section 5), and
28 when these cohorts have been examined, relatively few clinically significant effects were
29 detected. The lack of exposure gradients and adequate human information and the focus of most
30 currently available epidemiologic studies on occupationally TCDD-exposed adult males makes
31 evaluation of the inference that noncancer effects associated with exposure to dioxin-like
32 compounds may be occurring, difficult. It is important to note, however, that when exposures to
33 very high levels of dioxin-like compounds have been studied, such as in the Yusho and Yu-
34 Cheng cohorts, a spectrum of adverse effects have been detected in men, women, and children.
35 Some have argued that to deduce that a spectrum of noncancer effects will occur in humans in
36 the absence of better human data overstates the science; most scientists involved in the
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1 reassessment as authors and reviewers have indicated that such inference is reasonable given the
2 weight-of-the-evidence from available data. As presented, this logical conclusion represents a
3 testable hypothesis which may be evaluated by further data collection. EPA, its Federal
4 colleagues, and others in the general scientific community are continuing to fill critical data gaps
5 that will reduce our uncertainty regarding both hazard and risk characterization for dioxin and
6 related compounds.
7
8 Dioxin and related compounds are structurally related and elicit their effects through a
9 common mode of action.
10 The scientific community has identified and described a series of common biological
11 steps that are necessary for most, if not all, of the observed effects of dioxin and related
12 compounds in vertebrates including humans. Binding of dioxin-like compounds to a cellular
13 protein called the AhR represents the first step in a series of events attributable to exposure to
14 dioxin-like compounds including biochemical, cellular, and tissue-level changes in normal
15 biological processes. Binding to the AhR appears to be necessary for all well-studied effects of
16 dioxin but is not sufficient, in and of itself, to elicit these responses. There remains some
17 uncertainty as to whether every dioxin response is AhR-mediated. Sensitive biological tools such
18 as aryl hydrocarbon receptor deficient (AhR~;~) mice indicate a small residual of effects to
19 exposure to TCDD that does not allow us to rule out receptor-independent alternative pathways.
20 The well-documented effects elicited by exposure of animals and, in some cases, humans, to
21 2,3,7,8-TCDD are shared by other chemicals with similar structure and AhR binding
22 characteristics. In the past 5 years, significant data has accumulated that support the concept of
23 toxicity equivalence, that is at the heart of risk assessment for the complex mixtures of dioxin
24 and related compounds encountered in the environment. These data have been analyzed and
25 summarized in Part II, Chapter 9. This chapter has been added to EPA's dioxin reassessment to
26 address questions raised by the Agency's Science Advisory Board (SAB) in 1995. The SAB
27 suggested that, because the TEQ approach was a critical component of risk assessment for dioxin
28 and related compounds, the Agency should be explicit in its description of the history and
29 application of the process and go beyond reliance on the Agency's published reference
30 documents on the subject (U.S. EPA, 1987, 1989).
31
32 EPA and the international scientific community have adopted toxicty equivalence of dioxin
33 and related compounds as prudent science policy.
34 Dioxin and related compounds always exist in nature as complex mixtures. As discussed
35 in the Exposure Document, these complex mixtures can be characterized through analytic
36 methods to determine concentrations of individual congeners. Dioxin and related compounds
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1 can be quantified and biological activity of the mixture can be estimated using relative potency
2 values and an assumption of dose additivity. Such an approach has evolved over time to form
3 the basis for the use of TEQ in risk assessment for this group of compounds. Although such an
4 approach is dependent on critical assumptions and scientific judgement, it has been characterized
5 as a "useful, interim" way to deal with the complex mixture problem and has been accepted by
6 numerous countries and several international organizations. Alternative approaches, including
7 the assumption that all congeners carry the toxicity equivalence of 2,3,7,8-TCDD, or that all
8 congeners other than 2,3,7,8-TCDD can be ignored, have been generally rejected as inadequate
9 for risk assessment purposes.
10 Significant additional literature is now available on the subject of toxicity equivalence of
11 dioxin and related compounds, and Chapter 9 provides the reader with a summary that is up to
12 date through 1999. A recent international evaluation of all of the available data (van den Berg et
13 al., 1998) has reaffirmed the TEQ approach and has provided the scientific community with the
14 latest values for TEFs for PCDDs, PCDFs, and dioxin-like PCBs. Consequently, we can infer
15 with greater confidence that humans will respond to the cumulative exposure of AhR-mediated
16 chemicals. The position taken in this reassessment is that these 1998 TEFs should be adopted for
17 use by the Agency. Future research will be needed to address remaining uncertainties inherent in
18 the current approach. The WHO has suggested that the TEQ scheme be reevaluated on a
19 periodic basis and that TEFs and their application to risk assessment be reanalyzed to account for
20 emerging scientific information.
21
22 Complex mixtures of dioxin and related compounds are highly potent, "likely"
23 carcinogens.
24 With regard to carcinogenicity, a weight-of-the-evidence evaluation suggests that
25 mixtures of dioxin and related compounds (CDDs, CDFs, and dioxin-like PCBs) are strong
26 cancer promoters and weak direct or indirect initiators and likely to present a cancer hazard to
27 humans. Because dioxin and related compounds always occur in the environment and in humans
28 as complex mixtures of individual congeners, it is appropriate that the characterization apply to
29 the mixture. According to the Agency's revised draft Cancer Guidelines, the descriptor likely is
30 appropriate when the available tumor effects and other key data are adequate to demonstrate
31 carcinogenic potential to humans. Adequate data are recognized to span a wide range. The data
32 for complex mixtures of dioxin and related compounds represents a case that, according to the
33 draft Guidelines, would approach the strong-evidence end of the adequate-data spectrum.
34 Epidemiologic observations of an association between exposure and cancer responses (TCDD);
35 unequivocal positive responses in both sexes, multiple species, and different routes in lifetime
36 bioassays or initiation-promotion protocols or other shorter-term in vivo systems such as
37 transgenic models (TCDD plus numerous PCDDs, PCDFs, dioxin-like PCBs); and mechanistic
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1 or mode-of action data that are assumed to be relevant to human carcinogenicity (PCDDs,
2 PCDFs, dioxin-like PCBs) all support the description of complex mixtures of dioxin and related
3 compounds as likely human carcinogens.
4 Even though the database from cancer epidemiologic studies remains controversial, it is
5 the view of this reassessment that this body of evidence is supported by the laboratory data
6 indicating that TCDD probably increases cancer mortality of several types. Although not all
7 confounders were ruled out in any one study, positive associations between surrogates of dioxin
8 exposure, either length of occupational exposure or proximity to a known source combined with
9 some information based on measured blood levels, and cancer have been reported. These data
10 suggest a role for dioxin exposure to contribute to a carcinogenic response but do not confirm a
11 causal relationship between exposure to dioxin and increased cancer incidence. Available human
12 studies alone cannot demonstrate whether a cause-and-effect relationship between dioxin
13 exposure and increased incidence of cancer exists. Therefore, evaluation of cancer hazard in
14 humans must include an evaluation of all of the available animal and in vitro data as well as the
15 data from exposed human populations.
16 As discussed earlier in Section 2.2.1.4, under EPA's current approach, individual
17 congeners can also be characterized as to their carcinogenic hazard. TCDD is best characterized
18 as "carcinogenic to humans." This means that, based on the weight of all of the evidence
19 (human, animal, mode of action), TCDD meets the criteria that allows U.S. EPA and the
20 scientific community to accept a causal relationship between TCDD exposure and cancer hazard.
21 The guidance suggests that "carcinogenic to humans" is an appropriate descriptor of human
22 carcinogenic potential when there is an absence of conclusive epidemiologic evidence to clearly
23 establish a cause-and-effect relationship between human exposure and cancer, but there is
24 compelling carcinogenicity in animals and mechanistic information in animals and humans
25 demonstrating similar modes of carcinogenic action. The "carcinogenic to humans" descriptor is
26 suggested for TCDD because all of the following conditions are met:
27 • There is evidence from occupational epidemiologic studies for an association between
28 TCDD exposure and increases in cancer at all sites, in lung cancer and, perhaps, at other
29 sites, but the data are insufficient on their own to demonstrate a causal association.
30 • There is extensive carcinogenicity in both sexes of multiple species at multiple sites.
31 • There is general agreement that the mode of TCDD' s carcinogenicity is AhR dependent
32 and proceeds through modification of the action of a number of receptor and hormone
33 systems involved in cell growth and differentiation, such as the epidermal growth factor
34 receptor and estrogen receptor.
35 • Key events such as equivalent body burdens in animals and in human populations
36 expressing an association between exposure to TCDD and cancer, and the determination
37 of active AhR and dioxin responsive elements in the general human population. There is
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1 no reason to believe that these events would not occur in the occupational cohorts
2 studied.
3 Other individual dioxin-like compounds are characterized as "likely" human carcinogens
4 primarily because of the lack of epidemiological evidence associated with their carcinogenicity,
5 although the inference based on toxiciry equivalence is strong that they would behave in humans
6 as TCDD does. Other factors, such as the lack of congener-specific chronic bioassays, also
7 support this characterization. For each congener, the degree of certainty is dependent on the
8 available congener-specific data and their consistency with the generalized mode of action that
9 underpins toxiciry equivalence for TCDD and related compounds. On the basis of this logic,
10 complex environmental mixtures of TCDD and dioxin-like compounds should be characterized
11 as "likely" carcinogens, with the degree of certainty of the characterization being dependent on
12 the constituents of the mixture, when known. For instance, the hazard potential, although
13 "likely," would be characterized differently for a mixture whose TEQ was dominated by OCDD
14 as compared with one which was dominated by pentaCDF.
15 Although uncertainties remain regarding quantitative estimates of upper bound cancer
16 risk from dioxin and related compounds, efforts of this reassessment to bring more data into the
17 evaluation of cancer potency have resulted in evaluation of the slope of the dose-response curve
18 at the low end of the observed range (using the LED01) using a simple proportional (linear) model
19 and a calculation of both upper bound risk and margin of exposure (MOE) based on human
20 equivalent background exposures and associated body burdens. Evaluation of shape parameters
21 (used to estimate degree of linearity or nonlinearity of dose-response within the range of
22 observation) for biochemical effects indicates that many of these biochemical effects can be
23 hypothesized to be to key events in a generalized dioxin mode-of action model. These analyses
24 do not argue for significant departures from linearity below a calculated ED0, for endpoints
25 potentially related to cancer response, for at least one to two orders of magnitude lower exposure.
26 Risk estimates for intakes associated with background body burdens or incremental
27 exposures based on this slope factor represent a plausible upper bound on risk based on the
28 evaluation of animal and human data. The slope factors based on the most sensitive cancer
29 responses, both animal and human, calculated in Section 5 fall in a range of 5 x 10~3 to 5 * 10~4
30 per pg TEQ/kgBW/day. The ranges of estimates of upper bound cancer potency calculated from
31 the human and animal data analyzed in Part II, Chapter 8, overlap. The range above is bounded
32 on the upper end by the estimate of slope from the Hamburg cohort epidemiology study and on
33 the lower end by the estimate from the reanalyzed Kociba study. Consequently, the Agency,
34 although fully recognizing this range and the public health conservative nature of the slope
35 factors that make up the range, suggests the use of 5 x 10"3 per pg TEQ/kgBW/day as an
36 estimator of upper bound cancer risk for both background intakes and incremental intakes above
3 7 background. Slope factors allow the calculation of the probability of cancer risk for the highly
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1 vulnerable in the population (estimated to be the top 5% or greater). Although there may be
2 individuals in the population who might experience a higher cancer risk on the basis of genetic
3 factors or other determinants of cancer risk not accounted for in epidemiologic data or animal
4 studies, the vast majority of the population is expected to have less risk per unit of exposure and
5 some may have zero risk. Based on these slope factor estimates (per pg TEQ/kgBW/day),
6 average current background body burdens (5 ng/kgBW) resulting from average intakes of
7 approximately 3 pgTEQ/kgBW/day are in the range of 10'3 to 10"2. A very small percentage of
8 the population (< 1%) may experience risk that are 2-3 times higher than this if they are among
9 both the most vulnerable and the most highly exposed (among the top 5%) based on dietary
10 intake of dioxin and related compounds. This range of upper bound risk for the general
11 population has increased an order of magnitude from the risk described at background exposure
12 levels based on EPA's draft of this reassessment (10-4-10-3) (U.S. EPA, 1994).
13 Despite the use of the epidemiology data to describe an upper bound on cancer risk, the
14 Peer Panel that met in September 1993 to review an earlier draft of the cancer epidemiology
15 chapter suggested that the epidemiology data alone were still not adequate to implicate dioxin
16 and related compounds as "known" human carcinogens, but that the results from the human
17 studies were largely consistent with observations from laboratory studies of dioxin-induced
18 cancer and, therefore, should not be dismissed or ignored. Other scientists, including those who
19 attended the Peer Panel meeting, felt either more or less strongly about the weight of the
20 evidence from cancer epidemiology studies, representing the range of opinion that still exists on
21 the interpretation of these studies. Similar opinions were expressed in the comments documented
22 in the SAB's report in 1995 (U.S. EPA,1995). More recently, the International Agency for
23 Research on Cancer (1997), in its reevaluation of the cancer hazard of dioxin and related
24 compounds, found that whereas the epidemiologic database for 2,3,7,8-TCDD was still
25 "limited," the overall weight of the evidence was sufficient to characterize 2,3,7,8-TCDD as a
26 Category 1 "known" human carcinogen. Other related members of the class of dioxin-like
27 compounds were considered to have "inadequate" epidemiologic data to factor into hazard
28 categorization. A similar classification has been proposed within the context of the Department
29 of Health and Human Services' Report on Carcinogens (NTP, 2000). They too base their
30 characterization on the broad base of human, animal, and mode-of-action information in humans
31 and animals that supports this conclusion. Therefore, given that 2,3,7,8-TCDD is contained in
32 complex mixtures of dioxin and related compounds, and that the TEQ approach has been adopted
33 as a reasonable approach to assessing risks of these complex mixtures, it is also reasonable to
34 apply estimates of upper bound cancer potency derived from epidemiology studies where 2,3,7,8-
35 TCDD was associated with excess cancer risk to complex mixtures of dioxin and related
36 compounds.
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1 The current evidence suggests that both receptor binding and most early biochemical
2 events such as enzyme induction are likely to demonstrate low-dose linearity. The mechanistic
3 relationship of these early events to the complex process of carcinogenesis remains to be
4 established. If these findings imply low-dose linearity in biologically based cancer models under
5 development, then the probability of cancer risk will be linearly related to exposure to TCDD at
6 low doses. Until the mechanistic relationship between early cellular responses and the
7 parameters in biologically based cancer models is better understood, the shape of the dose-
8 response curve for cancer in the below the range of observation can only be inferred with
9 uncertainty. Associations between exposure to dioxin and certain types of cancer have been
10 noted in occupational cohorts with average body burdens of TCDD approximately 1- 3 orders of
11 magnitude (10-1,000 times) higher than average TCDD body burdens in the general population.
12 The average body burden in these occupational cohorts level is within 1-2 orders of magnitude
13 (10-100 times) of average background body burdens in the general population in terms of TEQ
14 (see Table 5-1 and Figure 5-1). Thus, there is no need for large-scale low-dose extrapolations in
15 order to evaluate background intakes and body burdens, and little if any data to suggest large
16 departures from linearity in this somewhat narrow window between the lower end of the range of
17 observation and the range of general-population background exposures. Nonetheless, the
18 relationship of apparent increases in cancer mortality in these worker populations to calculations
19 of general population risk remains a source of uncertainty.
20 TCDD has been clearly shown to increase malignant tumor incidence in laboratory
21 animals. In addition, a number of studies analyzed in this reassessment demonstrate other
22 biological effects of dioxin related to the process of carcinogenesis. Initial attempts to construct
23 a biologically based model for certain dioxin effects as described in this reassessment will need
24 to be continued and expanded to accommodate more of the available biology and to apply to a
25 broader range of potential health effects associated with exposure to dioxin-like compounds.
26
27 Use a "margin-of-exposure approach" to evaluate risk for noncancer and cancer endpoints.
28 The likelihood that noncancer effects may be occurring in the human population at
29 environmental exposure levels is often evaluated using a MOE approach. The Agency has used
30 this approach for a number of years in its assessment of the safety of pesticides. This concept has
31 also been incorporated into the revised Cancer Risk Assessment guidelines. A MOE is
32 calculated by dividing a "point of departure" for extrapolation purposes at the low end of the
33 range of observation in human or animal studies (the human-equivalent animal LOAEL,
34 NOAEL, BMD, or effective dose [EDxx]) by the human exposure or body burden level of
35 interest. Generally speaking, when considering either background exposures or incremental
36 exposures plus background, MOEs in range of 100-1,000 are considered adequate to rule out the
37 likelihood of significant effects occurring in humans based on sensitive animal responses or
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1 results from epidemiologic studies. The adequacy of the MOE to be protective of health must
2 take into account the nature of the effect at the "point of departure," the slope of the dose-
3 response curve, the adequacy of the overall database, interindividual variability in the human
4 population, and other factors. Considering MOEs based on incremental exposures alone divided
5 by the human exposure of interest, is not considered to give an accurate portrayal of the
6 implications of that exposure unless background exposures are insignificant.
7 One of the difficulties in assessing the potential health risk of dioxins is that background
8 exposures not be insignificant when based on total TEQ. The average levels of background
9 intake and associated body burdens of dioxin-like compounds in terms of TEQs in the general
10 population would be well within a factor of 100 of human-equivalent exposure levels associated
11 with NOELS, LOAELs, BMDs, or EDOI values in laboratory animals exposed to TCDD or
12 TCDD equivalents. In many cases, the MOE compared to background using these endpoints is a
13 factor of 10 or less (see Tables 2-2 and 2-3). These estimates, although variable, suggest that
14 any choice of body burden, as a point of departure, above 100 ng/kg would likely yield >1%
15 excess risk for some endpoint in humans (see Section II, Chapter 8). Also, choosing of a point of
16 departure below 1 ng/kg would likely be an extrapolation below the range of these data and
17 would likely represent a risk of < 1 %. Any choice for a point of departure in the middle range of
18 1 ng/kg to 100 ng/kg would be supported by the analyses, although the data provide the greatest
19 support for a point of departure in the range of 10 ng/kg to 50 ng/kg.
20 Because of the relatively high background compared to effect levels, the Agency is not
21 recommending the derivation of an RfD for dioxin and related compounds. Although RfDs are
22 often useful because they represent a health risk goal below which there is likely to be no
23 appreciable risk of noncancer effects over a lifetime of exposure, their primary use is to evaluate
24 increments of exposure from specific sources when background exposures are low and
25 insignificant. Any RfD that the Agency would recommend under the traditional approach for
26 setting an RfD is likely to be 2-3 orders of magnitude (100-1,000) below current background
27 intakes and body burdens. Because exceeding the RfD is not a statement of risk, discussion of an
28 RfD for an incremental exposure when the RfD has already been exceeded by average
29 background exposures is meaningless.
30 When evaluating incremental exposures associated with specific sources, knowing the
31 increment relative to background may help to understand the impact of the incremental exposure.
32 For instance, it would be misleading to suggest that an incremental exposure of
33 0.001 pg TEQ/kg/day was below the RfD if "background" exposures were already at or above
34 that level. On the other hand, as part of the total, the increment represents less than a 0.1%
35 increase over average "background," and we estimate that individuals within the 50%-95% range
36 of exposure within the population may be 2-3 times (200%-300%) higher. This has led us to
37 suggest that perhaps the best information for a decision-maker to have is: (1) a characterization
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1 of average "background" exposures; (2) a characterization of the percent increase over
2 background of individuals or subpopulations of interest; and (3) a policy statement about when
3 increases over average "background" become significant for the decision. This is not easy
4 because one could argue that, given high "background," any addition, if it is widespread, is too
5 much. On the other hand, someone else could argue that a 10% increase in incremental exposure
6 for a small population around a specific point source would be well within the general population
7 exposures and would not constitute a disproportionate exposure or risk. In this case, the strategy
8 might be to bring average "background" exposures down and to focus on large incremental
9 exposures or highly susceptible populations. This would be a strategy that would parallel the
10 Agency's lead strategy. Other parallel issues between dioxin-like compounds and lead are under
11 discussion within the Agency.
12 ATSDR (1999) set a minimal risk level (MRL), which is defined similarly to the EPA's
13 RfD, for dioxin and related compounds of 1.0 pg TEQ/kgBW/day. Some of the data regarding
14 lower bounds on the ED01s from various noncancer effects call that MRL into question. WHO
15 (2000) has set a tolerable daily intake of 1-4 pg TEQ/kgBW/day and has indicated that, although
16 current exposures in that range are "tolerable" (a risk management decision rather than a risk
17 assessment), efforts should be made to ultimately reduce intake levels. Findings in this
18 reassessment appear to be supportive of that recommendation.
19
20 Children's risk from exposure to dioxin and related compounds may be increased, but
21 more data are needed to fully address this issue.
22 The issue of children's risk from exposure to dioxin-like compounds has been addressed
23 in a number of sections throughout this reassessment. Data suggest a sensitivity of response in
24 both humans and animals during the developmental period, both prenatally and postnatally.
25 However, data are limited. Because evaluation of the impacts of early exposures on both
26 children's health and health later in life is important to a complete characterization of risk,
27 collection of additional data in this area should be a high priority to reduce uncertainties in future
28 risk assessments.
29 Data from the Dutch cohort of children exposed to PCBs and dioxin-like compounds
30 suggest impacts of exposure to background levels of dioxin and related compounds prenatally
31 and, perhaps, postnatally on neurobehavioral outcomes, thyroid function, and liver enzymes
32 (AST and ALT). Although these effects cannot be attributed solely to dioxin and related
33 compounds, several associations suggest that these are, in fact, likely to be Ah-mediated effects.
34 An investigation of background dioxin exposure and tooth development was done in Finnish
35 children as a result of studies of dental effects in dioxin-exposed rats, mice, and nonhuman
36 primates, and in PCB-exposed children. The Finnish investigators examined enamel
37 hypomineralization of permanent first molars in 6-7 year old children. The length of time that
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1 infants breast fed was not significantly associated with either mineralization changes or with
2 TEQ levels in the breast milk. However, when the levels and length of breast feeding were
3 combined in an overall score, a statistically significant association was observed (r = 0.3, p =
4 0.003, regression analysis).
5 In addition, effects have been seen where significantly elevated exposure occurred. The
6 incidents at Yusho and Yu-Cheng resulted in increased perinatal mortality and low birthweight in
7 infants born to women who had been exposed. Rocker bottom heal was observed in Yusho
8 infants, and functional abnormalities have been reported in Yu-Cheng children. The similarity of
9 effects observed in human infants prenatally exposed to the complex mixture in Yusho and
10 Yu-Cheng with those reported in adult monkeys exposed only to TCDD suggests that at least
11 some of the effects on children are due to the TCDD-like congeners in the contaminated rice oil
12 ingested by the mothers of these children. The similar responses include a clustering of effects in
13 organs derived from the ectodermal germ layer, referred to as ectodermal dysplasia, including
14 effects on the skin, nails, and Meibomian glands; and developmental and psychomotor delay
15 during developmental and cognitive tests. Some investigators believe that because all of these
16 effects in the Yusho and Yu-Cheng cohorts do not correlate with TEQ, some of the effects are
17 exclusively due to nondioxin-like PCBs or a combination of all the congeners. In addition, on
18 the basis of these data, it is still not clear to what extent there is an association between overt
19 maternal toxicity and embryo/fetal toxicity in humans. Further studies in the offspring as well as
20 follow-up to the Seveso incident may shed further light on this issue. In addition to chloracne
21 and acute responses to TCDD exposure seen in Seveso children, elevated levels of serum GOT
22 have been observed within a year after exposure in some of the more highly exposed Seveso
23 children. Long-term pathologic consequences of elevated GOT have not been illustrated by
24 excess mortality from liver disorders or cancer or in excess morbidity, but further follow-up is
25 needed. It must be recognized that the absence of an effect thus far does not obviate the
26 possibility that the enzyme levels may have increased concurrent to the exposure but declined
27 after cessation. The apparently transient elevations in ALT levels among the Seveso children
28 suggest that hepatic enzyme levels other than GGT may react in this manner to 2,3,7,8-TCDD
29 exposure.
30 Impacts on thyroid hormones provide an example of an effect of elevated postnatal
31 exposure to dioxin and related compounds. Several studies of nursing infants suggest that
32 ingestion of breast milk with a higher dioxin TEQ may alter thyroid function. Thyroid hormones
33 play important roles in the developing nervous system of all vertebrate species, including
34 humans. In fact, thyroid hormones are considered so important in development that in the United
35 States all infants are tested for hypothyroidism shortly after birth. Results from the studies
36 mentioned above suggest a possible shift in the population distribution of thyroid hormone
37 levels, particularly T4, and point out the need for collection of longitudinal data to assess the
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1 potential for long-term effects associated with developmental exposures. The exact processes
2 accounting for these observations in humans are unknown, but when put in perspective of animal
3 responses, the following might apply: dioxin increases the metabolism and excretion of thyroid
4 hormone, mainly T4, in the liver. Reduced T4 levels stimulate the pituitary to secrete more TSH,
5 which enhances thyroid hormone production. Early in the disruption process, the body can
6 overcompensate for the loss of T4, which may result in a small excess of circulating T4 in
7 response to the increased TSH. In animals, given higher doses of dioxin, the body is unable to
8 maintain homeostasis, and TSH levels remain elevated and T4 levels decrease.
9 A. large number of studies in animals have addressed the question of effects of dioxin-like
10 chemicals after in utero or lactational exposure. These have included both single-congener
11 studies and exposures to complex mixtures. However, the vast majority of the data are derived
12 from studies of 2,3,7,8-TCDD, or single congeners (e.g., PCB 77) or commercial mixtures of
13 PCBs. Exposure patterns have included single doses to the dams as well as dosing on multiple
14 days during gestation beginning as early as the first day of gestation. These studies are discussed
15 in detail in Part II, Chapter 5. The observed toxic effects include developmental toxicity,
16 neurobehavioral and neurochemical alterations, endocrine effects, and developmental
17 immunotoxicity. For instance, results of this body of work suggest that 2,3,7,8-TCDD clearly
18 has the potential to produce alterations in male reproductive function (rats and hamsters) and
19 male sexual behavior (rats) after prenatal exposure. In addition, impacts on neuromotor and
20 cognitive behavior as well as development of the immune system have been indicated in a
21 number of studies.
22 No epidemiological data and limited animal data are available to address the question of
23 the potential impact of exposure to dioxin-like compounds on childhood cancers or on cancers of
24 later life. Given the relative impact of nursing on body burdens (see the discussion of breast milk
25 exposures and body burdens below), direct impacts of increased early postnatal exposure on the
26 carcinogenic process are expected to be small. This conclusion is based on the reasonable
27 assumptions that cancer risk is a function of average lifetime body burden or that, because dioxin
28 is a potent cancer promoter rather than a direct initiator of the cancer process, exposures later in
29 life might be more important than those received earlier. However, recent studies of Brown et al.
30 (1998) suggest that prenatal exposure of rats to dioxin and related compounds may indirectly
31 enhance their sensitivity as adults to chemical carcinogenesis from other chemical carcinogens.
32 Further work is needed to evaluate this issue.
33 In addition to potential vulnerability during development, fetuses, infants, and children
34 are exposed to dioxins through several routes. The fetus is exposed in utero to levels of dioxin
35 and related compounds that reflect the body burden of the mother. It is important to recognize
36 that it is not the individual meals a pregnant woman eats during pregnancy that might affect
37 development, but the consequence of her exposure history over her life, which has the greatest
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1 impact on her body burden. Again, good nutrition, including a diet with appropriate levels of fat,
2 has consequences on dietary intake and consequent body burdens of dioxin and related
3 compounds. Nursing infants represent special cases who, for a limited portion of their lives, may
4 have elevated exposures on a body-weight basis when compared with non-nursing infants and
5 adults (see discussion). In addition to breast milk exposures, intakes of CDD/CDFs and dioxin-
6 like PCBs are more than three times higher for a young child than those of an adult, on a body-
7 weight basis. Table 4-9 in Section 4 of this document describes the variability in average intake
8 values as a function of age using age-specific food consumption rates and average food
9 concentrations, as was done for adult intake estimates. However, as with for the nursing infants,
10 the differences in body burden between children and adults are expected to be much less than the
11 differences in daily intake. Assuming that body burden is the relevant dose metric for most if not
12 all effects, there is some assurance that these increased intake levels will have limited additional
13 impact on risk as compared with overall lifetime exposure.
14
15 Background exposures to dioxin and related compounds need to be considered when
16 evaluating both hazard and risk.
17 The term "background" exposure has been used throughout this reassessment to describe
18 exposure of the general population, who are not exposed to readily identifiable point sources of
19 dioxin-like compounds. Adult daily intakes of CDD/CDFs and dioxin-like PCBs are estimated
20 to average 45 and 25 pg TEQDFP-WHO98/day, respectively, for a total intake of 70 pg/day
21 TEQDFP-WHO9g. Daily intake is estimated by combining exposure media concentrations (food,
22 soil, air) with contact rates (ingestion, inhalation). Table 4-8 summarizes the intake rates derived
23 by this method. The intake estimate is supported by an extensive database on food consumption
24 rates and food data. PK modeling provides further support for the intake estimates. Current
25 adult tissue levels reflect intakes from past exposure levels, which are thought to be higher than
26 current levels (see Trends, Section 2.6).
27 CDD/CDF and dioxin-like PCB intakes for the general population may extend to levels at
28 least three times higher than the mean. Variability in general-population exposure is primarily a
29 result of differences in dietary choices that individuals make. These are differences in both
30 quantity and types of food consumed. A diet that is disproportionately high in animal fats will
31 result in an increased background exposure over the mean. Data on variability of fat
32 consumption indicate that the 95th percentile is about twice the mean and the 99th percentile is
33 approximately three times the mean. Additionally, a diet that substitutes meat sources that are
34 low in dioxin (i.e., beef, pork, or poultry) with sources that are high in dioxin (i.e., freshwater
35 fish) could result in exposures elevated more than three times the mean. This scenario may not
36 represent a significant change in total animal fat consumption, even though it results in an
37 increased dioxin exposure. Intakes of CDD/Fs and dioxin-like PCBs are over three times higher
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1 for a young child as compared to that of an adult, on a body weight basis. Using age-specific
2 food consumption rate and average food concentrations, as was done above for adult intake
3 estimates, Table 4-9 describes the variability in average intake values as a function of age.
4 The average CDD/CDF tissue level for the general adult United States population appears
5 to be declining; the best estimate of current (late 1990s) levels is 25 ppt (TEQDFP-WHO9g, lipid
6 basis). The tissue samples collected in North America in the late 1980s and early 1990s showed
7 an average TEQDFP-WHO9g level of about 55 pg/g lipid. This finding is supported by a number of
8 studies, all conducted in North America, that measured dioxin levels in adipose tissue, blood, and
9 human milk. The number of people in most of these studies, however, is relatively small and the
10 participants were not statistically selected in ways that assured their representativeness of the
11 general United States adult population. One study, the 1987 National Human Adipose Tissue
12 Survey (NHATS), involved more than 800 individuals and provided broad geographic coverage,
13 but did not address coplanar PCBs. Similar tissue levels of these compounds have been
14 measured in Europe and Japan during similar time periods.
15 Because dioxin levels in the environment have been declining since the 1970s (see trends
16 discussion), it is reasonable to expect that levels in food, human intake, and ultimately human
17 tissue have also declined over this period. The changes in tissue levels are likely to lag the
18 decline seen in environmental levels, and the changes in tissue levels cannot be assumed to occur
19 proportionally with declines in environmental levels. CDC (2000) summarized levels of CDDs,
20 CDFs, and PCBs in human blood collected during the time period 1995 to 1997. The individuals
21 sampled were all U.S. residents with no known exposures to dioxin other than normal
22 background. The blood was collected in seven different locations from 400 individuals with an
23 age range of 20 to 70 years. All TEQ calculations were made assuming nondetects were equal to
24 half the detection limit. Although these samples were not collected in a manner that can be
25 considered statistically representative of the national population and lack wide geographic
26 coverage, they are judged to provide a better indication of current tissue levels in the United
27 States than the earlier data (see Table 4-7). PCBs 105, 118, and 156 are missing from the blood
28 data for the comparison populations reported in the Calcasieu study (CDC, 2000). These
29 congeners account for 62% of the total PCB TEQ estimated in the early 1990s. Assuming that
30 the missing congeners from the Calcasieu study data contribute the same proportion to the total
31 PCB TEQ as in earlier data, they would increase our estimate of current body burdens by another
32 3.7 pg TEQ/g lipid for a total PCB TEQ of 5.9 pg/g lipid and a total DFP TEQ of 25 pg/g lipid.
33 Past background exposure of about 3 pg TEQ/ kgBW/day leads to body burdens in the
34 human population that currently average approximately 5 ng/kg (20-30 pg TEQ/g lipid) when all
35 dioxins, furans and PCBs are included; body burdens have been higher in the past. DeVito et al.
36 (1995) estimated that body burdens averaged 9-13 ng/kg based on intake values of 4-6 pg
37 TEQ/kg/day and blood levels of 40-60 pgTEQ/g lipid using data from the late 1980s. If the
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1 general population were exposed to dioxins and related compounds at the current level of intake
2 (approximately 1 pg TEQ/kg/day) for a lifetime, average steady-state body burdens would be <2
3 ng/kg and blood levels would be 7-8 pg TEQ/g lipid. These estimates are based on the
4 assumption of 50% absorption of dioxin-like compounds from the diet. Using the same
5 assumption used for intake values, high-end estimates of body burden of individuals in the
6 general population (approximately the top 5%) may be more than twice as high as these average
7 estimates. This calculation is based on data for dietary fat consumption and the assumption that
8 body burdens of dioxin and related compounds in the general population are associated with fat
9 consumption. The top 1 % is likely to be three times higher based on its intake of fat.
10 Characterizing national background levels of dioxins in tissues is uncertain because the
11 current data cannot be considered statistically representative of the general population. The task
12 is also complicated by the fact that tissue levels are a function of both age and birth year.
13 Because intake levels have varied over time, the accumulation of dioxins in a person who turned
14 50 in 1990 is different from that in a person who turned 50 in 2000. Future studies should help
15 address these uncertainties. The National Health and Nutrition Examination Survey (NHANES)
16 began a new national survey in 1999 that will measure dioxin blood levels in about 1,700 people
17 per year (see http:www.cdc.gov/nchs/nhanes.htm). The survey is conducted at 15 different
18 locations per year and is designed to select individuals statistically representative of the civilian
19 U.S. population in terms of age, race, and ethnicity. These new data should provide a much
20 better basis than the currently available data for estimating national background tissue levels and
21 evaluating trends.
22 As described above, current intake levels from food sources are estimated in this
23 reassessment to be approximately 1 pg TEQ/KgBW/day. Certain segments of the population
24 may be exposed to additional increments of exposure by being in proximity to point sources or
25 because of dietary practices. These will be described below.
26
27 Evaluation of exposure of "special" populations and developmental stages is critical to risk
28 characterization.
29 As discussed above, background exposures to dioxin-like compounds may extend to
30 levels at least three times higher than the mean. This upper range is assumed to result from the
31 normal variability of diet and human behaviors. Exposures from local elevated sources or unique
32 diets would be in addition to this background variability. Such elevated exposures may occur in
33 small segments of the population, such as individuals living near discrete local sources, or
34 subsistence or recreational fishers. Nursing infants represent a special case where, for a limited
35 portion of their lives, these individuals may have elevated exposures on a body-weight basis
36 when compared to non-nursing infants and adults. This exposure will be discussed in a separate
37 section.
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1 Dioxin contamination incidents involving the commercial food supply have occurred in
2 the United States and other countries. For example, in the United States, contaminated ball clay
3 was used as an anticaking agent in soybean meal and resulted in elevated dioxin levels in some
4 poultry and catfish. This incident involved less than 5% of national poultry production and has
5 since been eliminated. Elevated dioxin levels have also been observed in a few beef and dairy
6 animals where the contamination was associated with contact with pentachlorophenol-treated
7 wood. This kind of elevated exposure was not detected in the national beef survey.
8 Consequently, its occurrence is likely to be low, but it has not been determined. These incidents
9 may have led to small increases in dioxin exposure to the general population. However, it is
10 unlikely that such incidents have led to disproportionate exposures to populations living near
11 where these incidents have occurred, because in the United States meat and dairy products are
12 highly distributed on a national scale. If contamination events were to occur in foods that are
13 predominantly distributed on a local or regional scale, then such events could lead to highly
14 exposed local populations.
15 Elevated exposures associated with the workplace or industrial accidents have also been
16 documented. United States workers in certain segments of the chemical industry had elevated
17 levels of TCDD exposure, with some tissue measurements in the thousands of ppt TCDD. There
18 is no clear evidence that elevated exposures are currently occurring among United States
19 workers. Documented examples of past exposures for other groups include certain Air Force
20 personnel exposed to Agent Orange during the Vietnam War and people exposed as a result of
21 industrial accidents in Europe and Asia.
22 Consumption of unusually high amounts of fish, meat, or dairy products containing
23 elevated levels of dioxins and dioxin-like PCBs can lead to elevated exposures in comparison to
24 the general population. Most people eat some fish from multiple sources, both fresh and salt
25 water. The typical dioxin concentrations in these fish and the typical rates of consumption are
26 included in the mean background calculation of exposure. People who consume large quantities
27 of fish at typical contamination levels may have elevated exposures because the concentration of
28 dioxin-like compounds in fish is generally higher than in other animal food products. These
29 kinds of exposures are addressed within the estimates of variability of background and are not
30 considered to result in highly exposed populations. If high-end consumers obtain their fish from
31 areas where the concentration of dioxin-like chemicals is elevated, they may constitute a highly
32 exposed subpopulation. Although this scenario seems reasonable, no supporting data could be
33 found for such a highly exposed subpopulation in the United States. One study measuring
34 dioxin-like compounds in blood of sports fishers in the Great Lakes area showed elevations over
35 mean background, but within the range of normal variability. Elevated CDD/CDF levels in
36 human blood have been measured in Baltic fishermen. Similarly, elevated levels of coplanar
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1 PCBs have been measured in the blood of fishers on the north shore of the Gulf of the St.
2 Lawrence River who consume large amounts of seafood.
3 High exposures to dioxin-like chemicals as a result of consuming meat and dairy products
4 would occur only in situations where individuals consume large quantities of these foods and the
5 level of these compounds is elevated. Most people eat meat and dairy products from multiple
6 sources and, even if large quantities are consumed, they are not likely to have unusually high
7 exposures. Individuals who raise their own livestock for basic subsistence have the potential for
8 higher exposures if local levels of dioxin-like compounds are high. One study in the United
9 States showed elevated levels in chicken eggs near a contaminated soil site. European studies at
10 several sites have shown elevated CDD/CDF levels in milk and other animal products near
11 combustion sources.
12 In summary, in addition to general population exposure, some individuals or groups of
13 individuals may also be exposed to dioxin-like compounds from discrete sources or pathways
14 locally within their environment. Examples of these "special" exposures include contamination
15 incidents, occupational exposures, direct or indirect exposure to local populations from discrete
16 sources, or exposures to subsistence or recreational fishers.
17
18 Breast-feeding infants have higher intakes of dioxin and related compounds for a short but
19 developmentally important part of their lives. However, the benefits of breast feeding are
20 widely recognized to outweigh the risks.
21 Two studies have compared dioxins in infants who have been breast-fed versus those who
22 have been formula-fed, and both have shown elevations in the concentrations of dioxins in
23 infants being breast-fed. Formula-fed infants had lipid-based concentrations < 5 ppt TEQDF-
24 WHO98 whereas breast-fed infants had average lipid-based concentrations above 20 ppt TEQDF-
25 WHO9g (maximum of 35 ppt TEQDF-WHO98). The dose to the infant varies as a function of
26 infant body weight, the concentration of dioxins in the mother's milk, and the trend of dioxins in
27 the mother's milk to decline over time. Doses at birth could exceed 200 pg TEQDFP-
28 WHO9g/kg/day, which would drop to about 20 pg TEQDFP-WHO9g/kg/day after 12 months. The
29 average dose over a year was calculated to be 77 pg TEQDFP-WHO9g/kg/day. Although this
30 average annual infant dose of 77 pg TEQDFP-WHO98/kg/day exceeds the currently estimated adult
31 dose of 1 pg TEQDFP-WHO9g/kg/day, the effect on infant body burdens is expected to be less
32 dramatic, i.e., infant body burdens will not exceed adult body burdens by 77 times. This is due to
33 the rapidly expanding infant body weight and lipid volume, the decrease in concentration of
34 dioxins in the mother's milk over time, and possibly more rapid elimination in infants. A
35 pharmacokinetic exercise comparing a 12-month nursing scenario with formula feeding showed
36 infant lipid concentrations to exceed 40 ppt TEQDFP-WHO98, compared with lipid concentrations
37 less than 10 ppt for the formula-fed infants. The dioxin concentrations in these two hypothetical
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1 children merged at about 10 years of age, at a lipid concentration of about 13 ppt TEQDFP-
2 WHO98.
3 The American Academy of Pediatrics (1997) has made a compelling argument for the
4 diverse advantages of breast-feeding and the use of human milk for infant feeding to infants,
5 mother, families and society. These include health, nutritional, immunologic, developmental,
6 psychological, social, economic, and environmental benefits. Breast milk is the point of
7 comparison for all infant food, and the breast-fed infant is the reference for evaluation of all'
8 alternative feeding methods. In addition, increasing the rates of breast-feeding initiation is a
9 national health objective and one of the goals of the United States Government's Healthy People
10 2010. The World Health Organization (1988) maintained that the evidence did not support an
11 alteration of WHO recommendations that promote and support breast-feeding. A more recent
12 consultation in 1998 (WHO, 2000) reiterated these conclusions. Although it is important that the
13 recommendations of these groups continue to be reevaluated in light of emerging scientific
14 information, the Agency does not believe that finding contained in this report provides a
15 scientific basis for initiating such a reevaluation. This conclusion is based on the fact that
16 stronger data have been presented that body burden, not intake, is the best dose metric; that many
17 of the noncancer effects, particularly those seen in children, are more strongly associated with
18 prenatal exposure and the mother's body burden rather than postnatal exposures and breast milk
19 levels; and that dioxin-like compounds are strong promoters of carcinogenicity, a mode of action
20 that depends on late-stage impacts rather than early-stage impacts on the carcinogenic process.
21
22 Many dioxin sources have been identified and emissions to the environment are being
23 reduced.
24 Current emissions of CDDs/CDFs/PCBs to the United States environment result
25 principally from anthropogenic activities. Evidence that supports this finding includes matches
26 in time of rise of environmental levels with rise in general industrial activity (see trend discussion
27 in Section 4.6), lack of any identified large natural sources and observations of higher
28 CDD/CDF/PCB body burdens in industrialized versus less industrialized countries (see
29 discussion on human tissue levels in Section 4.4).
30 The principal identified sources of environmental release may be grouped into five major
31 types: (1) combustion and incineration sources; (2) chemical manufacturing/processing sources;
32 (3) industrial/municipal processes; (4) biological and photochemical processes; and (5) reservoir
33 sources. Development of release estimates is difficult because only a few facilities in most
34 industrial sectors have been tested for CDD/CDF emissions. Thus an extrapolation is needed to
35 estimate national emissions. The extrapolation method involves deriving an estimate of
36 emissions per unit of activity at the tested facilities and multiplying this by the total activity level
37 in the untested facilities. In order to convey the level of uncertainty in both the measure of
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1 activity and the emission factor, U.S. EPA developed a qualitative confidence rating scheme.
2 The confidence rating scheme, presented in Section 4, Table 4-1, uses qualitative criteria to
3 assign a high, medium, or low confidence rating to the emission factor and activity level for those
4 source categories for which emission estimates can be reliably quantified. The dioxin
5 reassessment has produced an inventory of source releases for the United States (Table 4-2). The
6 inventory was developed by considering all sources identified in the published literature and
7 numerous individual emissions test reports. The inventory is limited to sources whose releases
8 can be reliably quantified (i.e., those with confidence ratings of A, B, or C as defined above).
9 Also, it is limited to sources with releases that are created essentially simultaneously with
10 formation. This means that the reservoir sources are not included. The inventory presents the
11 environmental releases in terms of two reference years: 1987 and 1995. EPA's best estimates of
12 releases of CDD/CDFs to air, water, and land from reasonably quantifiable sources were
13 approximately 2,800 gram (g) (1.3 pounds) TEQDF-WHO9g in 1995 versus 13,500 g (6 pounds)
14 TEQDF-WHO9g in 1987. The decrease in estimated releases of CDD/CDFs between 1987 and
15 1995 (approximately 80%) was due primarily to reductions in air emissions from municipal and
16 medical waste incinerators.
17 The environmental releases of CDD/CDFs in the United States occur from a wide variety
18 of sources, but are dominated by releases to the air from combustion sources. Insufficient data
19 are available to comprehensively estimate point-source releases of dioxin-like compounds to
20 water. Sound estimates of releases to water are available only for chlorine-bleached pulp and
21 paper mills and manufacture of ethylene dichloride/vinyl chloride monomer. The contribution of
22 dioxin-like compounds to waterways from nonpoint source reservoirs is likely to be greater than
23 the contributions from point sources. Current data are only sufficient to support preliminary
24 estimates of nonpoint source contributions of dioxin-like compounds to water (i.e., urban storm
25 water runoff and rural soil erosion). These estimates suggest that, on a nationwide basis, total
26 nonpoint releases are significantly larger than point source releases. Other releases to water
27 bodies that cannot be quantified on the basis of existing data include effluents from POTWs and
28 most industrial/commercial sources.
29 Based on the available information, the inventory includes only a limited set of activities
30 that result in direct environmental releases to land. The only releases to land quantified in the
31 inventory are land application of sewage sludge and pulp and paper mill wastewater sludges. Not
32 included in the inventory's definition of an environmental release is the disposal of sludges and
33 ash into approved landfills. While this inventory is the most comprehensive and well-
34 documented in the world, it is likely to underestimate total releases. The magnitude of the
35 underestimate is unknown but it is unlikely that noncombustion sources today, other than
36 reservoir sources, play a dominant role in human exposure. In terms of 1995 releases from
37 reasonably quantifiable sources, this document estimates releases of 2,800 g WHO98TEQDF for
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1 contemporary formation sources and 2,900 g WHO98TEQDF for reservoir sources. In addition,
2 there remain a number of unquantifiable and poorly quantified sources that are described in
3 Section 4.
4 As described above, combustion appears to be the most significant process of formation
5 of CDDs/CDDFs today. Important factors that can affect the rate of dioxin formation include the
6 overall combustion efficiency, post-combustion flue gas temperatures and residence times, and
7 the availability of surface catalytic sites to support dioxin synthesis. Although chlorine is an
8 essential component for the formation of CDD/CDFs in combustion systems, the empirical
9 evidence indicates that for commercial-scale incinerators, chlorine levels in feed are not the
10 dominant controlling factor for rates of CDD/CDF stack emissions. The conclusion that chlorine
11 in feed is not a strong determinant of dioxin emissions applies to the overall population of
12 commercial scale combustors. For any individual commercial-scale combustor, circumstances
13 may exist in which changes in chlorine content of feed could affect dioxin emissions. For
14 uncontrolled combustion, such as open burning of household waste, chlorine content of wastes
15 may play a more significant role in affecting levels of dioxin emissions than observed in
16 commercial-scale combustors.
17 No significant release of newly formed dioxin-like PCBs is occurring in the United
18 States. Unlike CDD/CDFs, PCBs were intentionally manufactured in the United States in large
19 quantities from 1929 until production was banned in 1977. Although it has been demonstrated
20 that small quantities of coplanar PCBs can be produced during waste combustion, no strong
21 evidence exists that the dioxin-like PCBs make a significant contribution to TEQ releases during
22 combustion. The occurrences of dioxin-like PCBs in the U.S. environment most likely reflects
23 past releases associated with PCB production, use, and disposal. Further support of this finding
24 is based on observations of reductions since 1980s in PCBs in Great Lakes sediment and other
25 areas.
26 It is unlikely that the emission rates of CDD/CDFs from known sources correlate
27 proportionally with general population exposures. Although the emissions inventory shows the
28 relative contribution of various sources to total emissions, it cannot be assumed that these
29 sources make the same relative contributions to human exposure. It is quite possible that the
30 major sources of dioxin in food (see discussion in Section 2.6 indicating that the diet is the
31 dominant exposure pathway for humans) may not be those sources that represent the largest
32 fractions of total emissions in the United States. The geographic locations of sources relative to
33 the areas from which much of the beef, pork, milk, and fish come is important to consider. That
34 is, much of the agricultural areas that produce dietary animal fats are not located near or directly
35 downwind of the major sources of dioxin and related compounds.
36 The contribution of reservoir sources to human exposure may be significant. Several
37 factors support this finding. First, human exposure to the dioxin-like PCBs is thought to be
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1 derived almost completely from reservoir sources. Because one-third of general population TEQ
2 exposure is due to PCBs, at least one-third of the overall risk from dioxin-like compounds comes
3 from reservoir sources. Second, CDD/CDF releases from soil via soil erosion and runoff to
4 waterways appear to be greater than releases to water from the primary sources included in the
5 inventory. CDD/CDFs in waterways can bioaccumulate in fish-leading to human exposure via
6 consumption of fish, which makes up about one-third of the total general population CDD/CDF
7 TEQ exposure. This suggests that a significant portion of the CDD/CDF TEQ exposure could be
8 due to releases from the soil reservoir. Finally, soil reservoirs could have vapor and particulate
9 releases that deposit on plants and enter the terrestrial food chain. The magnitude of this
10 contribution, however, is unknown.
11 This assessment adopts the hypothesis that the primary mechanism by which dioxin-like
12 compounds enter the terrestrial food chain is via atmospheric deposition. Dioxin and related
13 compounds enter the atmosphere directly through air emissions or indirectly, for example,
14 through volatilization from land or water or from resuspension of particles. Once introduced into
15 the environment, dioxin-like compounds are widely distributed in the environment as a result of
16 a number of physical and biological processes. The dioxin-like compounds are essentially
17 insoluble in water, generally classified as semivolatile, and tend to bioaccumulate in animals.
18 Some evidence has shown that these compounds can degrade in the environment, but in general
19 they are considered very persistent and relatively immobile in soils and sediments. These
20 compounds are transported through the atmosphere, as vapors or attached to airborne particulates
21 and can be deposited on soils, plants, or other surfaces (by wet or dry deposition). The dioxin-
22 like compounds enter water bodies primarily via direct deposition from the atmosphere, or by
23 surface runoff and erosion. From soils, these compounds can reenter the atmosphere either as
24 resuspended soil particles or as vapors. In water, they can be resuspended into the water column
25 from sediments, volatilized out of the surface waters into the atmosphere, or become buried in
26 deeper sediments. Immobile sediments appear to serve as permanent sinks for the dioxin-like
27 compounds. Though not always considered an environmental compartment, these compounds
28 are also found in anthropogenic materials (such as pentachlorophenol) and have the potential to
29 be released from these materials into the broader environment.
30 The two primary pathways for the dioxin-like compounds to enter the ecological food
31 chains and human diet are air-to-plant-to-animal and water/sediment-to-fish. Vegetation receives
32 these compounds via atmospheric deposition in the vapor and particle phases. The compounds
33 are retained on plant surfaces and bioaccumulated in the fatty tissues of animals that feed on
34 these plants. Vapor-phase transfers onto vegetation have been experimentally shown to dominate
35 the air-to-plant pathway for the dioxin-like compounds, particularly for the lower chlorinated
36 congeners. In the aquatic food chain, dioxins enter water systems via direct discharge or
37 deposition and runoff from watersheds. Fish accumulate these compounds through direct contact
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1 with water, suspended particles, and bottom sediments and through the consumption of aquatic
2 organisms. Although these two pathways are thought to normally dominate contribution to the
3 commercial food supply, others can also be important. Elevated dioxin levels in cattle resulting
4 from animal contact with pentacholorophenol-treated wood have been documented by the
5 USD A. Animal feed contamination episodes have led to elevations of dioxins in poultry in the
6 United States, milk in Germany, and meat/dairy products in Belgium.
7 Deposition can occur directly onto soil or onto plant surfaces. At present, it is unclear
8 whether atmospheric deposition represents primarily current contributions of dioxin and related
9 compounds from all media reaching the atmosphere or whether it is past emissions of dioxin and
10 related compounds which persist and recycle in the environment. Understanding the relationship
11 between these two scenarios will be particularly important in understanding the relative
12 contributions of individual point sources of these compounds to the food chain and assessing the
13 effectiveness of control strategies focused on either current or past emissions of dioxins in
14 attempting to reduce the levels in food.
15 As discussed in Section 4.3, estimates for background levels of dioxin-like compounds in
16 environmental media are based on a variety of studies conducted at different locations in North
17 America. Of the studies available for this compilation, only those conducted in locations
18 representing "background" were selected. The amount and representativeness of the data varies,
19 but in general these data lack the statistical basis to establish true national means. The
20 environmental media concentrations were consistent among the various studies and were
21 consistent with similar studies in Western Europe. These data are the best available for
22 comparing site-specific values to national background levels. Because of the limited number of
23 locations examined, however, it is not known if these ranges adequately capture the full national
24 variability; if significant regional variability exists, making national means of limited utility; or if
25 elevated levels above this range could still be the result of background contamination processes.
26 As new data are collected, these ranges are likely to be expanded and refined. The limited data
27 on dioxin-like PCBs in environmental media are summarized in the document (Part I, Volume 3,
28 Chapter 4), but were not judged adequate for estimating background levels.
29 Concentrations of CDDs/CDFs and PCBs in the United States environment were
30 consistently low prior to the 1930s. Then concentrations rose steadily until about 1970. At this
31 time, the trend reversed and concentrations have declined to the present. The most compelling
32 supportive evidence of this trend for CDD/CDFs and PCBs comes from dated sediment core
33 studies. Sediment concentrations in these studies are generally assumed to be an indicator of the
34 rate of atmospheric deposition. CDD/CDF and PCB concentrations in sediments began to
35 increase around the 1930s and continued to increase until about 1970. Decreases began in 1970
36 and have continued to the time of the most recent sediment samples (about 1990). Sediment data
37 from 20 United States lakes and rivers from seven separate research efforts consistently support
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1 this trend. Additionally, sediment studies in lakes located in several European countries have
2 shown similar trends.
3 It is reasonable to assume that sediment core trends should be driven by a similar trend in
4 emissions to the environment. The period of increase generally matches the time when a variety
5 of industrial activities began rising, and the period of decline appears to correspond with growth
6 in pollution abatement. Many of these abatement efforts should have resulted in decreases in
7 dioxin emissions, i.e., elimination of most open burning, particulate controls on combustors,
8 phaseout of leaded gas, and bans on PCBs, 2,4,5-T, hexachlorophene, and restrictions on use of
9 pentachlorophenol. Also, the national source inventory of this assessment documented a
10 significant decline in emissions from the late 1980s to the mid-1990s. Further evidence of a
11 decline in CDD/CDF levels in recent years is emerging from data, primarily from Europe,
12 showing declines in foods and human tissues.
13 In addition to the congener-specific PCB data discussed earlier, a wealth of data on total
14 PCBs and Aroclor mixtures exist that also supports these trends. It is reasonable to assume that
15 the trends for dioxin-like PCBs are similar to those for PCBs as a class because the predominant
16 source of dioxin-like PCBs is the general production of PCBs in Aroclor mixtures. PCBs were
17 intentionally manufactured in large quantities from 1929 until production was banned in the
18 United States in 1977. United States production peaked in 1970, with a volume of 39,000 metric
19 tons. Further support is derived from data showing declining levels of total PCBs in Great Lakes
20 sediments and biota during the 1970s and 1980s. These studies indicate, however, that during
21 the 1990s the decline slowed and may be leveling off.
22 Because dioxin-like chemicals are persistent and accumulate in biological tissues,
23 particularly in animals, the major route of human exposure is through ingestion of foods
24 containing minute quantities (part per trillion or ppt levels) of dioxin-like compounds. This
25 results in widespread low-level exposure of the general population to dioxin-like compounds.
26 The issue of general population background exposure was discussed earlier.
27
28 Risk Characterization Summary Statement
29 Based on all of the data reviewed in this reassessment and scientific inference, a picture
30 emerges of TCDD and related compounds as potent toxicants in animals with the potential to
31 produce a spectrum of effects. Some of these effects may be occurring in humans at general
32 population background levels and may be resulting in adverse impacts on human health. The
33 potency and fundamental level at which these compounds act on biological systems is analogous
34 to several well-studied hormones. Dioxin and related compounds have the ability to alter the
35 pattern of growth and differentiation of a number of cellular targets by initiating a series of
36 biochemical and biological events, resulting in the potential for a spectrum of cancer and
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1 noncancer responses in animals and humans. Despite this potential, there is currently no clear
2 indication of increased disease in the general population attributable to dioxin-like compounds.
3 The lack of a clear indication of disease in the general population should not be considered
4 strong evidence for no effect of exposure to dioxin-like compounds. Rather, lack of a clear
5 indication of disease may be a result of the inability of current data and scientific tools to directly
6 detect effects at these levels of human exposure. Several factors suggest a need to further
7 evaluate the impact of these chemicals on humans at or near current background levels. These
8 are the weight of the evidence on exposure and effects, an apparently low margin of exposure for
9 noncancer effects, potential for significant risks to some portion of the general population, and
10 additivity to background processes related to carcinogenicity in the case of incremental exposures
11 above background.
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Table 1-1. The TEF scheme for I-TEQ
DF
Dioxin (D) congener
2,3,7,8-TCDD
1,2,3,7,8-PeCDD
1,2,3,4,7,8-HxCDD
1,2,3,6,7,8-HxCDD
1,2,3,7,8,9-HxCDD
1,2,3,4,6,7,8-HpCDD
1,2,3,4,6,7,8,9-OCDD
TEF
1.0
0.5
0.1
0.1
0.1
0.01
0.001
Furan (F) congener
2,3,7,8-TCDF
1,2,3,7,8-PeCDF
2,3,4,7,8-PeCDF
1,2,3,4,7,8-HxCDF
1,2,3,6,7,8-HxCDF
1,2,3,7,8,9-HxCDF
2,3,4,6,7,8-HxCDF
1,2,3,4,6,7,8-HpCDF
1,2,3,4,7,8,9-HpCDF
1,2,3,4,6,7,8,9-OCDF
TEF
0.1
0.05
0.5
0.1
0.1
0.1
0.1
0.01
0.01
0.001
aNote that the scheme does not include dioxin-like PCBs. The nomenclature for this scheme is I-TEQDF, where T
represents "International," TEQ represents the 2,3,7,8-TCDD toxic equivalence of the mixture, and the subscript DF
indicates that only dioxins (Ds) and furans (Fs) are included in the TEF scheme.
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Table 1-2. The TEF scheme for TEQDFP-WHO
94
Dioxin (D) congener
2,3,7,8-TCDD
1,2,3,7,8-PeCDD
1,2,3,4,7,8-HxCDD
1,2,3,6,7,8-HxCDD
1,2,3,7,8,9-HxCDD
1,2,3,4,6,7,8-HpCDD
1,2,3,4,6,7,8,9-OCDD
TEF
1.0
0.5
0.1
0.1
0.1
0.01
0.001
Furan (F) congener
2,3,7,8-TCDF
1,2,3,7,8-PeCDF
2,3,4,7,8-PeCDF
1,2,3,4,7,8-HxCDF
1,2,3,6,7,8-HxCDF
1,2,3,7,8,9-HxCDF
2,3,4,6,7,8-HxCDF
1,2,3,4,6,7,8-HpCDF
1,2,3,4,7,8,9-HpCDF
1,2,3,4,,6,7,8,9-OCDF
TEF
0.1
0.05
0.5
0.1
0.1
0.1
0.1
0.01
0.01
0.001
Dioxin-like
PCB (P)
PCB-77
PCB-126
PCB- 169
PCB- 105
PCB-118
PCB-123
PCB- 156
PCB-157
PCB- 167
PCB-114
PCB- 170
PCB- 180
PCB- 189
TEF
0.0005
0.1
0.01
0.0001
0.0001
0.0001
0.0005
0.0005
0.00001
0.0005
0.0001
0.00001
0.0001
"The nomenclature for this TEF scheme is TEQDFP-WHO94, where TEQ represents the 2,3,7,8-TCDD toxic equivalence
of the mixture, and the subscript DFP indicates that dioxins (Ds), furans (Fs), and dioxin-like PCBs (P) are included in
the TEF scheme. The subscript 94 following WHO displays the year changes were made to the TEF scheme.
6/8/00
108
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Table 1-3. The TEF scheme for TEQDFP-WHO,
98
Dioxin (D) congener
2,3,7,8-TCDD
1,2,3,7,8-PeCDD
1,2,3,4,7,8-HxCDD
1,2,3,6,7,8-HxCDD
1,2,3,7,8,9-HxCDD
1,2,3,4,6,7,8-HpCDD
1,2,3,4,6,7,8,9-OCDD
TEF
1.0
1.0
0.1
0.1
0.1
0.01
0.0001
Furan (F) congener
2,3,7,8-TCDF
1,2,3,7,8-PeCDF
2,3,4,7,8-PeCDF
1,2,3,4,7,8-HxCDF
1,2,3,6,7,8-HxCDF
1,2,3,7,8,9-HxCDF
2,3,4,6,7,8-HxCDF
1,2,3,4,6,7,8-HpCDF
1,2,3,4,7,8,9-HpCDF
1,2,3,4,6,7,8,9-
OCDF
TEF
0.1
0.05
0.5
0.1
0.1
0.1
0.1
0.01
0.01
0.0001
Dioxin-
like PCB
(P)
PCB-77
PCB-81
PCB-126
PCB- 169
PCB- 105
PCB-118
PCB- 123
PCB-156
PCB-157
PCB- 167
PCB- 114
PCB- 189
TEF
0.0001
0.0001
0.1
0.01
0.0001
0.0001
0.0001
0.0005
0.0005
0.00001
0.0005
0.0001
"The nomenclature for this TEF scheme is TEQDFP-WHO98, where TEQ represents the 2,3,7,8-TCDD toxic
equivalence of the mixture, and the subscript DFP indicates that dioxins (Ds), furans (Fs), and dioxin-like PCBs (P)
are included in the TEF scheme. The subscript 98 following WHO displays the year changes were made to the TEF
scheme. Note that the changes to the TEFs since 1994 are as follows:
•For 1,2,3,7,8-PeCDD, the new WHO TEF is 1 and the I-TEF is 0.5;
•For OCDD, the new WHO TEF is 0.0001 and the I-TEF is 0.001;
•For OCDF, the new WHO TEF is 0.0001 and the I-TEF is 0.001;
•For PCB 77, the new TEF is 0.0001;
•The addition of PCB 81 (i.e., 3,4,4',5-TCB); and
•For the two di-ortho substituted HpCBs in the 1994 TEF scheme (i.e., PCBs 170 and 180), no TEFs have
been assigned in the new WHO TEF scheme.
6/8/00
109
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oo
o
o
Table 2-1. Effects of TCDD and related compounds in different animal species
Effect
Presence of AhR
Binding of TCDD:
AhR Complex to
the DRI- (enhancer)
Enzyme induction
Acute lethality
Wasting syndrome
Teratogenesis/fetal
toxicity, mortality
Endocrine effects
Immunotoxicity
Carcinogenicity
Neurotoxicity
Chloracnegenic
effects
Porphyria
Ilepatotoxicity
Edema
Testicular atrophy
Bone marrow
hypoplasia
Human
+
+
+
0
+/-
+/-
+/-
+/-
+
+
+
+
Monkey
+
+
+
+
+
+
+
+
+
0
+
+
+
+
Guinea
Pig
0
+
+
+
+
+
+
0
+/-
0
+
+
Rat
+
+
+
+
+
+
+
+
+
+
-t-
-t-
0
+
Mouse
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+/-
Hamster
+
+
+
+
+
-f
+
+
0
+/-
+
Cow
+
+
+
+
+
+
+
Rabbit
+
+
+
+
+
+
+
+
Chicken
+
+
+
+
+
+
+
+
+
+
+
Fish
+
+
+
+
+
+
+
+
+
+
+
+
Avian
wildlife
+
+
+
+
+
+
+
Marine
mammals
+
+
+
+
+
+
+
+
Mink
+
+
+
+
+
+
+
O
O
2
O
H
O
H-t
H
m
+ = observed.
+/- = observed to limited extent, or +/- results.
0 = not observed.
Blank cells = no data.
o
G
O
H
-------
Table 3-1. Early molecular events in response to dioxin
Diffusion into the cell
Binding to the AhR protein
Dissociation from hsp90
Active translocation from cytoplasm to nucleus
Association with Arnt protein
Conversion of liganded receptor to the DNA-binding form
Binding of liganded receptor heteromer to enhancer DNA
Enhancer activation
Altered DNA configuration
Histone modification
Recruitment of additional proteins
Nucleosome disruption
Increased accessibility of transcriptional promoter
Binding of transcription factors to promoter
Enhanced mRNA and protein synthesis
These events are discussed in detail in Part II, Chapter 2.
6/8/00 111 DRAFT—DO NOT CITE OR QUOTE
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Table 4-1. Confidence rating scheme
Confidence
category
Confidence
rating
Activity level estimate
Emission factor estimate
Categories/media for which emissions can be reasonably quantified
A
B
C
High
Medium
Low
Derived from comprehensive
survey
Based on estimates of average
plant activity level and number of
plants or limited survey
Based on data judged possibly
nonrepresentati ve .
Derived from comprehensive survey
Derived from testing at a limited but
reasonable number of facilities
believed to be representative of
source category
Derived from testing at only a few,
possibly nonrepresentative facilities
or from similar source categories
Categories/media for which emissions cannot be reasonably quantified
D
E
Preliminary
Estimate
Not Quantified
Based on extremely limited data,
judged to be clearly
nonrepresentative.
No data.
Based on extremely limited data,
judged to be clearly
nonrepresentative.
1) Argument based on theory but no
data
2) Data indicating dioxin formation,
but not in a form that allows
developing an emission factor
6/8/00
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Table 4-2. Quantitative inventory of environmental releases of TEQDF-WHO9g in the United States
Emission source category
Releases (g TEC
Waste Incineration
Municipal waste incineration
Hazardous waste incineration
Boilers/industrial furnaces
Medical waste/pathological incineration
Crematoria
Sewage sludge incineration
Tire combustion
Pulp and paper mill sludge incinerators'
Power/Energy Generation
Vehicle fuel combustion - leaded1"
- unleaded
- diesel
Wood combustion - residential
- industrial
Coal combustion - utility
Oil combustion - industrial/utility
Other High Temperature Sources
Cement kilns (hazardous waste burning)
Lightweight aggregate kilns burning hazardous waste
Cement kilns (nonhazardous waste burning)
Petroleum refining catalyst regeneration
Cigarette combustion
Carbon reactivation furnaces
Kraft recovery boilers
Minimally Controlled or Uncontrolled Combustion
Forest, brush, and straw firesd
Metallurgical Processes
Ferrous metal smelting/refining
- Sintering plants
Nonferrous metal smelting/refining
- Primary copper
- Secondary aluminum
- Secondary copper
- Secondary lead
Drum and barrel reclamation
Chemical Manufac./Processing Sources
Ethylene dichloride/vinyl chloride
Total quantified releases to air'
Confidence rating*
Reference vear 1995
A
t^mto,/
B
C
Confidence rating"
Reference vear 1987
A
1250
5.8
14.8
27.6
60.1
2.3
28
<0.5€
1.72
11.2
0.39
488
9.1
0.11
2
5.9
35.5
62.8
10.7
156.1
3.3
17.8
2.21
0.8
0.08
208
29.1
271
0.08
2705
B
8877
5
6.1
26.4
50.8
2
<0.5e
1.29
C
0.78
2590
5 S
0.11
37.5
3.6
27.8
89.6
17.8
117.8
2.4
13.7
2.24
1
0.06
170
32.7
16.3
983
0.08
13081
6/8/00
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Table 4-2. Quantitative inventory of environmental releases of TEQDF-WHO98 in
the United States (continued)
Emission source category
Confidence rating"
Reference year 1995
A
B
C
Confidence rating"
Reference year 1987
A
B
C
Releases (g TEQ/yr) to water
Chemical Manuf./Processing Sources
Bleached chemical wood pulp and paper mills
Ethylene dichloride/vinyl chloride
Total quantified releases to water1
19.5
0.43
19.93
356
356
Releases (g TEQ/yr) to land
Chemical Manuf./Processing Sources
Bleached chemical wood pulp and paper mill
sludge
Ethlyene dichloride/vinyl chloride
Municipal wastewater treatment sludge
Commercially marketed sewage sludge
2,4-Dichlorophenoxy acetic acid
Total quantified releases to land0
Overall quantified releases to the open and
circulating environment
1.4
76.6
2.6
28.9
0.73
110.23
2835
14.1
76.6
2.6
33.4
126.7
13564
Confidence Rating A = Characterization of the Source Category judged to be Adequate for Quantitative Estimation with High Confidence in the Emission Factor and
High Confidence in Activity Level.
Confidence Rating B = Characterization of the Source Category judged to be Adequate for Quantitative Estimation with Medium Confidence in the Emission Factor and at
least Medium Confidence in Activity Level
Confidence Rating C = Characterization of the Source Category judged to be Adequate for Quantitative Estimation with Low Confidence in either the Emission Factor and/or the
Activity Level.
"A confidence rating reflects EPA *s judgment as to the adequacy of information pertaining to the emission factor and activity level
'Leaded fuel production and the manufacture of motor vehicle engines requiring leaded fuel for highway use have been prohibited in the United States, (see Section 4.1 for details.)
'TOTAL reflects only the total of the estimates made in this report.
dlt is not known what fraction, if any, of the estimated emissions from forest fires represents a "reservoir" source. The estimated emissions may be solely the result of combustion.
'Congener-specific emissions data were not available; the I-TEQDF emission estimate was used as a surrogate for the TEQDF-WHO,S emission estimate.
'Included within estimate for Wood Combustion - Industrial.
6/8/00
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Table 4-3. Preliminary indication of the potential magnitude of TEQDF-WHO98 releases from
"unqualified" (i.e., Category D) sources in reference year 1995
Emission source category
/. Contemporary Formation Sources
Biogas Combustion
Oil Combustion-Residential
Coal Combustion - Commercial/Industrial
Coal Combustion - Residential
Asphalt Mixing Plants
Combustion of Landfill Gas
Landfill Fires
Accidental Fires (Structural)
Accidental Fires (Vehicles)
Backyard Barrel Burning
Coke Production
Electric Arc Ferrous Furnaces
Ferrous Foundries
Municipal Wastewater
//. Reservoir Sources
Urban Runoff
Rural Soil Erosion
Release medium
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Water
Water
Water
Preliminary release estimate
(g WHOM-TEQDF/yr)
0.22s
6.0"
39.6"
32.0"
• T
6.6
1,050"
>20"
28.3"
804
6.9"
44.3"
17.5"
12
190"
2,700"
•Congener-specific emissions data were not available; the I-TEQDF emission factor was used as a surrogate for the TEQDF-WHO,S emissions estimate.
6/8/00
115 DRAFT—DO NOT CITE OR QUOTE
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Table 4-4. Unqualified sources
Category
Combustion sources
Metal smelting and refining
Chemical manufacturing
Biological and photochemical processes
Reservoir sources
Unqualified sources
Uncontrolled combustion of PCBs
Agricultural burning
Primary aluminum
Primary magnesium
Primary nickel
Mono- to tetrachlorophenols
Pentachlorophenol
Chlorobenzenes
Chlorobiphenyls (leaks/spills)
Dioxazine dyes and pigments
2,4-Dichlorophenoxy acetic acid
Tall oil-based liquid soaps
Composting
Air
Sediments
Water
Biota
PCP-treated wood
6/8/00
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Table 4-5. Estimates of the range of typical background levels of dioxin-Iike compounds in various
environmental media
Media
Rural soils
Urban soils
Sediments
Rural air
Urban air
TEQnF-WHO98 concentrations
l-6pg/g(ppt)
7-20 pg/g
l-60pg/g
0.002-0.02 pg/m3
0.02-0.2 pg/m3
6/8/00
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Table 4-6. Estimates of levels of dioxin-like compounds in food
Food type
Beef
Pork
Eggs
Chicken
Milk
Dairy products
Marine fish
Freshwater fish
Marine shellfish
Vegetable fats
Water
CDD/CDFs
(pgTEQDF-WH098/g
fresh weight)
0.2
0.22
0.032
0.11
0.031
0.12
0.36
1.2
0.79
0.056
0.00056 (pg/L)
PCBs
(pgTEQP-WH098/g
fresh weight)
0.094
0.09
0.1
0.044
0.016
0.058
0.25
1.2
0.042
0.037
NA
Total
(pgTEQDFP-WH098/g
fresh weight)
0.29
0.31
0.13
0.15
0.047
0.18
0.61
2.4
0.83
0.093
NA
NA = not available.
6/8/00
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Table 4-7. Background serum levels in the United States 1995 -1997
Median
Mean
95th Percentile
TEQDFPWH098(pg/glipid)
18.7
22.1*
38.8
2,3,7,8-TCDD (pg/g lipid)
1.9
2.1
4.2
* After adjusting to account for missing PCBs, the mean is 25.4 pg/g lipid.
Source: CDC, 2000.
6/8/00
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Table 4-8. Adult contact rates and background intakes of dioxin-like compounds
Exposure route
Soil ingestion
Freshwater fish
Marine fish
Marine shellfish
Inhalation
Milk
Dairy
Eggs
Beef
Pork
Poultry
Vegetable fat
Water
Contact rate
50 mg/d
6g/d
12.5 g/d
1.6g/d
13.3mVd
175 g/d
55- g/d
0.24 g/kg-d
0.67 g/kg-d
0.22 g/kg-d
0.49 g/kg-d
17 g/d
1.4L/d
Dioxins and furans
Concentration
TEQDF-WHO,8
12 pg/g
1.2pg/g
0.36 pg/g
0.79 pg/g
0.12pg/m3
0.031 pg/g
0.1 2 pg/g
0.032 pg/g
0.20 pg/g
0.22 pg/g
0.11 pg/g
0.056 pg/g
0.0005 pg/L
Total
Intake
(pg TEQDF-
WHO«,/ke-d)
0.0085
0.13
0.064
0.018
0.023
0.078
0.094
0.0077
0.13
0.048
0.054
0.014
0.000011
0.65
(45 pg/d)
Dioxin-like PCBS
Concentration
TEQp-WHO,,
NA
1-2 pg/g
0.25 pg/g
0.042 pg/g
NA
0.0 16 pg/g
0.058 pg/g
0.10 pg/g
0.094 pg/g
0.009 pg/g
0.044 pg/g
0.037 pg/g
NA
Intake
(Pg TEQP-
WHO«./ke-d)
NA
0.11
0.045
0.0096
NA
0.040
0.046
0.024
0.063
0.0020
0.022
0.0090
NA
0.35
(25 pg/d)
Total
intake
(pg TEQDFP-
WHO0, /kg-d)
0.0085
0.24
0.11
0.028
0.023
0.12
0.14
0.032
0.19
0.05
0.076
0.023
0.000011
1.0
(70 pg/d)
6/8/00
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Table 4-9. Variability in average daily TEQ intake as a function of age
Age range
l-5yr
6-1 lyr
12-19 yr
Adult
Intake, mass basis
pgTEQnFP-WHOq))/d
54
58
63
70
Intake, body weight basis
PR TEQnFP-WHO,8/kg-d
3.6
1.9
1.1
1
6/8/00
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ON
oo
O
O
Table 5-1. Scrum dioxin levels in the background population and epidemiological cohorts (back-calculated)
Cohort
CDC comparison
population, USA 1995 -
97; CDC 2000
Background, Dioxin
Assessment, USA -1990s
No.
316
pooled
results
Total TEQ
ppt lipid
Lower
2a
30
Central
Tend.
25.4 meanb
52.8 mean
55 median
Upper
50"
70
2,3,7,8-TCDD
ppt lipid
Central Tendency
2. 1 mean
1.9 median
(95% UCL = 4.2)
5.2 mean
SD~1.32C
PCBs
Mean
TEQ
5.3 (est.)b
18.8 mean
20 median
Non-2,3,7,8-TCDD
TEQ ppt lipid
Central Tendency
23.3 mean
47.6 mean
Comment
TEQDFP-WHO9g; serum;
missing PCBs 105, 118,
156 estimated
TEQDFP-WHO,8; serum,
adipose, breast milkd
Back-Calculated
Ranch Hand, low;
Ketchumetal. 1999
Ranch Hand, high;
Ketchumetal. 1999
Hamburg cohort women;
Flesch-Janys et al. 1999
N1OSH, Fingerhut et al.
1991b,NTIS
BASF, severe chloracne;
Ottetal. 1993
BASF, moderate
chloracne; Ott et al. 1993
BASF, no chloracne;
Ottetal. 1993
Seveso Zone A;
Landietal. 1998
Seveso Zone A, medical;
Needhametal. 1999
276
283
652.3,7,8
64TEQ
253
56
59
139
7
296
19.3e
811.2 meanc
172.8s median
6789. T
52.3 median
(range 27 - 94)
195.7 median
(range 94 - 3,290)
506.8 mean
125.8 median
(range 2.4 - 6397.4)
2,000 mean
(rangef 2 -32,000)
1008 geom. mean
(range8 20- 13360)
420.8 geom. mean
(range8 2.72 -49 15)
38.4 geom. mean
(range8 2.72 -2981)
230 geom. mean
325.9 median
(range 4 1.2 -399.7)
381 -4 89 median
(range 1.5 -56,000)
304.4 meane
serum
serum
I-TEQs, dioxin and
furan TEQ only; serum
serum
serum
serum
serum
serum
Samples taken 1976, not
back-calculated; serum;
using 1/2 DL
K)
s-/
5
H
O
O
z;
o
H
O
O
&
O
w
-------
o
o
Table 5-1. Serum dioxin levels in the background population and epidemiological cohorts (back-calculated) (continued)
Seveso Zone B;
Landietal. 1998
Seveso Zone B, medical;
Needham et al. 1999
Seveso Zone R, medical;
Needham etal. 1999
Seveso NonABR;
Landietal. 1998
Dutch Accident;
Hooiveld et al. 1996
Dutch Main Production;
Hooiveld et al. 1996
51
80
48
52
14
5
47.5 geom. mean
52.5 median
(range 5.3 - 273)
87- 147 median
(range 1.8 -725)
15 -89 median
(range I - 545)
4.9 geom. mean
5.5 median
(range 1.0- 18.1)
1841.8 arith. mean
1433.8 geom. mean
(range 301 -3683)
608.2 arith. mean
285.9 geom. mean
(range 17-1160)
serum
Samples taken 1 976, not
back-calculated; serum;
using Vz DL
Samples taken 1976; not
back-calculated; serum;
using '/2 DL
serum
serum
serum
to
OJ
a Estimated from ATSDR 1999 Calcasieu comparison population graph.
b CDC data scaled upward to adjust for missing data on PCB congeners 105, 1
c SD approximated from unweighted estimate.
d Weighted average levels for the subset of serum lipid TEQs were 4.54 ng/kg
congeners).
ePCDD and PCDF derived TEQ only, using I-TEFs.
f Lower interval on current level.
8 Range estimated from exponential log distribution graph.
18 and 156, by matching to PCB congener ratios measured in the early 1990s.
for 2,3,7,8-TCDD, and 55.4 ng/kg for total TEQ (PCB contribution not adjusted for missing
U
O
2
o
H
O
§
o
c:
o
H
tn
-------
Table 5-2. Doses yielding 1% excess risk (95% lower confidence bound) based upon 2-year
animal carcinogenicity studies using simple multistage (Portier et. al, 1984) models3
Tumor
Liver cancer in female rats (Kociba)
Squamous cell carcinoma of the tongue in male
rats (Kociba)
Squamous cell carcinoma of the nasal turbinates
or hard palate in male rats (Kociba)
Squamous cell carcinoma of the lung in female
rats (Kociba)
Squamous cell carcinoma of the nasal turbinates
or hard palate in female rats (Kociba)
Thyroid follicular cell adenoma in male rats
(NTP)
Thyroid follicular cell adenoma in female rats
(NTP)
Liver adenomas and carcinomas in female rats
(NTP)
Liver adenomas and carcinomas in male mice
(NTP)
Liver adenomas and carcinomas in female mice
(NTP)
Thyroid follicular cell adenomas and carcinomas
in female mice (NTP)
Subcutaneous tissue sarcomas in female mice
(NTP)
Leukemias and lymphomas in female mice
(NTP)
Shape
Linear
Linear
Cubic
Cubic
Linear
Linear
Cubic
Quadratic
Linear
Linear
Linear
Lin-Cubic
Linear
ED
Animal intake for
1 % excess risk
in ng/kg/day
(95% lower
confidence
bound)
0.77 (0.57)
14.1 (5.9)
41.4(1.2)
40.4 (2.7)
5.0 (2.0)
4.0(2.1)
33.0(3.1)
13.0(1.7)
1.3(0.86)
15.1 (7.8)
30.1 (14.0)
43.2(14.1)
10.0 (5.4)
01
Steady-state body
burden
in ng/kg at ED01
(95% lower
confidence bound)
14(10)
254(106)
746 (22)
730 (48)
90 (36)
144 (76)
1,190(112)
469(61)
20.6(13.6)
239(124)
478 (222)
686 (224)
159(86)
' Reprinted with slight modifications from Chapter 8, Table 8.3.2.
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Cl
2,3,7,8-Tetrachlorodibenzo-p-dioxin
Cl
1,2,3,7,8-Pentachlorodibenzo-p-dioxin
Cl
3,3',4,4',5,5'-Hexachlorobiphenyl
Cl
2,3,7,8-Tetrachlorodibenzofuran
Cl
2,3,4,7,8-Pentachlorodibenzofuran
ci
3,3',4,4',5-Pentachlorobiphenyl
Figure 1-1. Chemical structure of 2,3,7,8-TCDD and related compounds.
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125 DRAFT—DO NOT CITE OR QUOTE
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phosphorylation/
dephospht »ry lation
Differentiation
and
Proliferation
Altered gene expression
Changes in protein levels
(e.g., CYPIA1.IL-1B,...)
mRNA
Figure 2-1. Cellular mechanism for AhR action.
TCDD, 2,3,7,8-tetrachlorodibenzo-p-dioxin; AhR, aryl hydrocarbon receptor; AIP, associated
immunophilin-like protein; hsp90, 90 kilodalton heat shock protein; p, sites of
phosphorylization; Arnt, AhR nuclear translocator protein; RB, retinoblastoma protein; NF-kB,
nuclear transcription factor; HIF, hypoxia inducible factor; DRE, dioxin-responsive element;
BTFs, basal transcription factors; TATA, DNA recognition sequence.
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CYP1A1
CYP1A2
CYP1B1
Glutathione S-Transferase Ya
Aldehyde-3-Dehydrogenase
NAD(P)H:Quinone Oxidoreductase
TGF-a
TGF-P
Plasminogen Activator Inhibitor-2
Interleukin-lp
c-fos
jun
Figure 2-2. Some of the genes whose expression is altered by exposure to TCDD.
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Best Estimate of
Emission Source
(tested/total units)
Municipal Solid Waste Inctrveratton (39/13O)
Medical Wane I nc In »fan on (2O/2.4OO)
Secondary Cooper Smelling (2/3)
Forest Fires (NA)
Cement Kilns Burning H02 Wasie (1OY34)
Residential Wood Burning (7/25.OOO.OOO)
Utility / Industrial Coal Combustion (11/7)
On-Road Diesel Fuel Combustion (MA)
Secondary Aluminum Smelling (6/76)
Industrial Wood Burning I9/?)
Iron Ore Sinter Plants (2/1 1)
Cement Kilns Not Burning Haz Waste (15/178)
Sewage Sludge Incineration (13/257}
Manufacture of EDC/VC (?/?)
UUmy i Industrial Oil Combustion (^-2/7)
Crematoria (16/1.555)
Hazardous Waste Incineration (17/162)
On-Road Leaded Gas Fuel Combustion (?/?]
Emission Factor
(ng/kg or ng/L)
Total Annual "Activity"
(thousand metric tons/yr or
million L/yr)
o a o o <• -
>• o o o ,;
,-00°
- o
o o o
O 0 O
0 O
The figures include sources with annual TEQ emission estimates greater than 5 g TEQDF-WH09B/yr
In one or both of Reference Year 1995 and Reference Year 1987. Derivations of emission factors
and annual "activity" estimates (e.g., kg of waste incinerated) are presented in the following
chapters of this report. The difference in bar shading indicates the degree of confidence in
the estimate. The set of numbers following the source categories indicates the number of
facilities/sites for which emission test data are available versus the number of facilities/sites
in the category. A question mark (?) indicates that the precise number of facilities/sites could
not be estimated.
Annual TEQ Emission
(g TEQDF-WH098/yr)
Legend
Low Confidence
Medium Confidence
High Confidence
Figure 4-1. Estimated CDD/CDF I-TEQ emissions to air from combustion sources in the
United States, 1995.
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DRAFT—DO NOT CITE OR QUOTE
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Municipal Solid Waste Incineration
Medical Waste Incineration
Secondary Copper Smelting
Forest Fires
Cement Kilns Burning Haz Waste
Residential Wood Burning
Utility/Industrial Coal Combustion
On-Road Diesel Fuel Combustion
Secondary Aluminum Smelting
Industrial Wood Burning
Iron Ore Sinter Plants
Cement Kilns Not Burning Haz Waste
Sewage Sludge Incineration
Manufacture of EDC/VC
Utility/Industrial Oil Combustion
Crematoria
Hazardous Waste Incineration
On-Road Unleaded Gas Fuel Combustion
On-Road Leaded Gas Fuel Combustion
10
100
1000
10000
1995 D1987
Figure 4-2. Comparison of estimates of annual I-TEQ emissions to air (grams I-TEQ/yr)
for reference years 1987 and 1995.
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DRAFT—DO NOT CITE OR QUOTE
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10000
14000
1000
JU
"f 100
1
1
, —
Mulian'
Vledia
n
Mean
•«
Mean
\
I
g-Mea
J
2
1
?-Mean
i
»-Mea
|
g>
I 10
o
o
o
(N
U
o
0
!
on
Bti
03
O
I
U
on
03
o
on
15
u
g
E
03
o
>
1
<
o
w
on
"ca
•5
u
E
<
o
VI
on
£
_o
'
•o
§
0
c
a
K
f
IE
I
T3
n
u
^
Q£
**r
cd
QJ
£?
3
E
I
on
O
— ^
u
o
IX
on
<
03
c
(LI
T3
-a
o
E
u.
on
<
03
u. •«
5 =
ffl Q
-a
o
£
j=
Q
; 2378-TCDD g Est. Background Non-TCDD TEQs
Figure 5-1. Dioxin body burden levels in background populations and epidemiological
cohorts (back-calculated).
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