Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 121
Risk Assessment of M ixtures of
Systemic Toxicants in Drinking
Water
Even if the resources now devoted to studies of chemical interactions could
be multiplied by 1,000 or more, those studies would provide only a small
portion of the information required to determine precisely the toxicity of
complex mixtures prevailing in the environment. It would still fall to toxi-
cologists and other scientists to integrate the separate pieces of information
into a form useful for risk assessment. With the goal of providing adequate
but not excessively conservative exposure standards for health protection,
this chapter presents various approaches to using incomplete empirical in-
formation and scientific judgment to assess the health risks associated with
exposure to mixtures in drinking water.
The dominant concern with mixtures, as noted earlier, is unexpected am-
plification of toxicity arising from combinations of mixture components. The
extent of the problem increases with the complexity of the mixture. For
example, in a combination of 10 toxicants there are ('°), or 45, possible 2-
factor interactions; (~3), or 120, possible 3-factor interactions; (I''), or 210,
possible 4-factor interactions; ('I), or 252, possible 5-factor interactions;
(a), or 210, possible 6-factor interactions; (a), or 120, possible 7-factor
interactions; ('°), or 45, possible 8-factor interactions; (a), or 10, possible
9-factor interactions; and 1 possible 10-factor interaction. The total number
of interactions that must be considered in a study of combinations of 10
substances is:
'The notation ('I) refers to the number of two-substance combinations possible from a group of
10 substances; the general notation, (m), can be rewritten as m!lc!(m - c)!, where ! is the symbol
forfactorial.m!equalsm(m - l)(m-2)...(2)(1)i.e., 10! = (10)(9)(8)(7)...(2)(1).
121
OCR for page 122
122 DRINKING WATER AND HEALTH
~0
(',"y = 2"'- ll = 1~013.
=2
(1)
It is difficult to imagine a procedure developed from consideration of the
effects of 10 separate agents that adequately accounts for each of the 1,013
possible interactions.
To model interaction requires precise definition of the term "interaction."
As described in the 1988 publication by the Committee on Methods for the
In Vivo Toxicity Testing of Complex Mixtures (NRC, 1988, p. 1001:
Int~r~rtinn char Hill rPfP~rPA to tic clPvi~tinn from
Alla Lo V__~lJ 4~ V ~ A- I---- . . . additive behavior expected
on the basis of dose-response curves obtained with individual agents. [But] to a
biostatistician, the definition includes information on the underlying dose-response
model and on units of measure. For ordinary linear models, "interaction" refers to
a departure from response additivity. Different measures of response can lead to
different conclusions concerning departure from additivity. For nonlinear models,
such as log-logistic, log-linear, log-probit, and multistage models, . . . there is
additivity for the logarithm of response. Thus, when the word "interaction" is used,
one must make certain of the units in which toxicity or dose is expressed, as well
as the assumptions about the nature of joint action that was predicted by the model
used.
THE PROBLEM OF SYNERGISM
Of greatest concern is the possibility that exposure to mixtures could result
in a much more severe toxic response than that expected on the basis of the
potencies of the individual components. "Synergism" is here defined as a
response greater than additivity.
The mixture problem for drinking water is mainly a problem of relatively
low concentrations of individual agents on which human observational data
are lacking. Demonstrations of synergism come largely from the laboratory
and are usually based on high doses. A limited review of the literature
uncovered no cases in which the potency of a particular agent at high doses
had been multiplied by more than 100 by combination with another agent.
Furthermore, in the extensive literature on drug interactions, novel effects
are rarely observed. Instead, if binary combinations act synergistically, they
tend to do so through an increase in the effects of one of the agents. Assume,
then, that 100 represents the maximal enhancement of toxicity due to the
addition of a second agent. That is also the number by which no-observed-
adverse-effect levels (NOAELs) or their advocated replacement, bench-
mark doses are divided to yield acceptable daily intakes (ADIs), or "reference
doses" (the EPA term), although the uncertainty factor of 100 is usually
designed to protect against uncertainties other than those arising from inter-
actions. The number 100 has been said to incorporate a species variation of
OCR for page 123
Risk Assessment of Mixtures of Systemic Toxicants 123
10 and a range of individual human susceptibility of 10, though formal
documentation of this view is lacking.
THE CONCEPT OF COMMONALITY
One concept that might be useful in combining numerical estimates of
toxicity of different substances is that of commonality, formulated by Weiss
(1986) in relation to food additives. (Food additives are regulated on the
basis of individual ADIs, no explicit account being taken of the possibility
that their basic actions might not be mutually independent.) Commonality
reflects the extent to which several agents are likely to act on the same target
organ and elicit the same toxic response. For instance, several organophos-
phorus and carbamate chemicals have the commonality of inhibiting acetyl-
cholinesterase. Compounds of the heavy metals mercury and cadmium disrupt
renal cellular function and produce renal necrosis.
"Commonality" does not now translate readily into any simple arithmetic
manipulations, but Figure 3-1 is an attempt to illustrate the concept. The
ADI, or acceptable level (AL), is transformed on the Taxis into total toxic
burden or exposure. The x-axis corresponds to the number of chemicals in
the mixture to which there is exposure. The y-axis (commonality) represents
the overlap in biologic effects of various chemicals. It represents the degree
to which the individual constituents of a mixture contribute to a particular
process. It recognizes that most agents have broad biologic actions, so their
toxic contribution depends on the choice of a specific end point. Fewer agents
or a lower commonality would lead to a lower total burden. A higher com-
monality, assuming a fixed intake as a proportion of the ADI for each agent,
would raise the total burden. A commonality factor of less than l implies
less than full identity of action.
MODIFYING THE HAZARD INDEX
EPA (1986b) has published guidelines for assessing the health risks as-
sociated with chemical mixtures. If data on the toxicity of a specific mixture
as a whole are unavailable, the risks may be estimated on the basis of what
is known about the individual constituents. A hazard index (HI) associated
with a mixture of k toxicants may be defined as:
Ek
,2 ALi (2)
where Ei is the exposure level of the ith toxicant in the mixture and ALi is
the maximum acceptable concentration of the ith toxicant.
When the HI exceeds 1, it evokes the same concerns about the mixture
OCR for page 124
124 DRINKING WATER AND HEALTH
/~CR=~_ ~
FIGURE 3-1 Three-dimensional idealized representation illustrating increasing toxic burden with
the addition of several agents. Lower commonality would reduce total burden; higher commonality
would increase it. This illustration applies to only one system or organ at a time. Total burden would
be measured in percent of ADI.
as those evoked when any individual AL is exceeded, which is, in fact, a
special case, with k = 1. This computation of the hazard index is based on
the assumption of adding toxically equivalent doses i.e., the absence of
interactions among the components of the mixture. However, such dose-
additive models as are implied by the hazard index might not provide the
most biologically plausible approach to describing the effects of a complex
mixture of toxicants if the compounds do not have the same mode of toxic
action. EPA (1986b) has suggested that separate hazard indexes should be
developed for separate end points of concern. It further notes that "dose
addition for dissimilar effects does not have strong scientific support, and,
OCR for page 125
Risk Assessment of Mixtures of Systemic Toxicants 125
if done, should be justified." In addition, EPA recognizes that the biologic
meaning of the index given above is unknown and that much additional
research is required before its utility as a predictor of toxic severity can be
validated.
Other Risk-Oriented Approaches
Identification of risk associated with the consumption of chemical mixtures
in drinking water will come from many sources: laboratory data, such as
those obtained from bioassay-directed fractionation; epidemiologic data, such
as those based on similar exposures; and models based on knowledge of the
toxicity of individual constituents. When models are the primary source, the
assumptions described above and the already available empirical data point
to an empirical policy: adoption of the additivity assumption for low-response
exposures.
Three strategies for protection against the risks associated with exposure
to drinking water contaminants might be defined in this argument. The choice
of strategy is a policy issue based on public concern; the data are clearly
inadequate to dictate a firm choice.
1. Least adequate. Each agent's ADI is determined independently; hence,
regulations would consider each agent individually. This alternative is un-
satisfactory, because of the low likelihood that each agent can truly act in
biologic isolation of every other agent. Furthermore, individually acceptable
risks might lose their acceptability when there are 50 or 100 of them.
2. Usually adequate. A water quality or hazard index similar to the EPA
index would be defined under some assumptions of additivity. Given that
ADIs already incorporate uncertainty factors, usually of 100, and given that
only one study (Murphy et al., 1959) has reported a 100-fold increase in
toxicity through a binary combination (of organophosphates), the simple
dose-additive model should be satisfactory under most circumstances. For
materials that are assumed to have thresholds for response, special concern
must be given to the biologic mechanisms leading to a toxic response. If the
mechanisms of toxicity of two or more toxicants are the same, combining
below-threshold doses (i.e., doses with zero response) could lead to an above-
threshold dose and produce a nonzero response. This concept is inherent in
the consideration of toxic equivalents and the idea of relative potency, which
implies that one material is (in effect) a dilution of the other material. For
these reasons, dose-additivity must be considered for materials that affect
the same toxic end point.
3. Most adequate. Although most attempts to examine the joint actions
of binary combinations find that toxic responses are well described by simple
additivity (e.g., S myth et al., 1969) or that additivity is violated to only a
OCR for page 126
126 DRINKING WATER AND HEALTH
small degree, maximal protection might require an additional margin of safety
beyond that provided by the additivity model. Because of the 100-fold in-
crease observed by Murphy et al. (1959), adjustments of an index based on
additivity by an equivalent factor should provide a rather robust safety margin.
Such a margin, however, would be excessive in most cases. That is, just as
it seems unreasonable to expect totally independent actions of the agents
identified in a drinking water source, it seems equally unreasonable to expect
complete overlap in toxic targets, so even the additivity alternative already
embodies this additional but unrecognized safety factor. Later in this chapter,
it is suggested that an uncertainty factor can be considered to compensate
for any synergism.
In addition to the EPA hazard index, there are other precedents for com-
bining the toxic manifestations of individual components of a mixture. Threshold
limit values (TLVs), which are workplace standards, are combined for si-
multaneous exposure to more than one agent of the same class of compounds
(ACGIH, 1983; NRC, 19801. For example, the joint action of several volatile
organic solvents, which induce central nervous system impairment, is esti-
mated by adding the individual ratios of exposure concentration to TLV. For
some combinations, such as n-hexane and methylethyl ketone, the assump-
tion of additivity might underestimate toxicity, even though both compounds
are organic solvents. The additive model might seem reasonable only for
conditions in which the mode of action of the constituents is well understood
and greater than additive effects can therefore be excluded on the basis of
mechanistic processes. It might be adapted, however, for situations in which
drinking water standards, such as MCLs, are based on ADIs derived from
chronic studies devoid of mechanistic information.
One way to apply the additive model to extract an overall assessment of
drinking water quality is to use the dose-additive procedure adopted by the
State of New York to regulate aldicarb and carbofuran. The prescribed limits
are 7 and 15 ~g/liter, respectively. The actual concentrations at any site are
used in the following expression:
(actual aldicarb) (actual carbofuran) T.
15
(3)
If T ' l, no action is taken. If T > 1, filters are installed, and the cost is
charged to the manufacturer whose product is calculated to give the higher
ratio. The procedure is based on the assumption that both agents act on
identical systems and are totally interchangeable.
A corresponding expression can be based on many more than two agents,
as for workplace TLVs. If dose additivity is assumed, as in the case in New
York, then the sum of the ratios identified for the hazardous constituents can
OCR for page 127
Risk Assessment of Mixtures of Systemic Toxicants 127
be required to be no more than 1.0, on the basis of the sum of quotients
determined as described above in Equation 3.
The hazard index defined by Equation 2 can be modified to take into
account the sensitivity of each toxic end point. As noted earlier, applying
the uncertainty factor incorporated in ALs or ADIs is intended to provide a
safe (nontoxic) exposure of the most sensitive persons for the toxic mani-
festation or end point that occurs at the lowest dose if a given material has
several manifestations of toxicity. The operating assumption is that an ex-
posure that is safe for the most sensitive end point will be safe for any other
toxic manifestation. If sensitivity is defined by the no-observed-adverse-effect
level (NOAEL) the most sensitive end point being defined as the one with
the lowest NOAEL- then the relative sensitivities of various end points can
be estimated by comparing NOAELs or ratios of NOAELs. That is, sensitivity
is taken to be the inverse of the NOAEL, and relative sensitivity is defined
as the ratio of the NOAEL for the most sensitive end point to the NOAEL
for a specific subsidiary end point. If this relative sensitivity, or ratio of
NOAELs, is used as a weighting factor, called Wij (which will always be
less than or equal to 1), then the equation for HI can be modified to read:
j ,2 AL`,
(4)
where i is the toxic material and j is some specific end point. This procedure
assumes that the AL for each substance is not known for each end point of
concern; if it were, 1/ALij could be substituted for Wij/ALij in the above
equation. The HIj would then be computed by summing HIj across all ma-
terials i. If any of the HIj values exceeded 1, the sum also must exceed 1,
and the actions indicated above for the unmodified HIj would be taken. This
method is sensitive to fractionation by the number of toxicity categories used;
thus, it might be most reasonable to sum across all toxic end points:
HI= 2, HIj,
i=]
(5)
where I is the number of toxic end points considered.
Modifying HI by using the weighting factor Wij takes into account the
possibly different toxic spectra of different materials, avoids the lumping
together of unrelated toxicities, and still incorporates all reported toxicities
into a unified measure.
Grouping Agents with Common Toxicities
With a small number of agents, it might be possible to invoke expert
opinion to separate components of toxic mixtures into clusters and to assign
OCR for page 128
128 DRINKING WATER AND HEALTH
an average commonality to each cluster. Or, as an upper limit in the dose-
additive model, a commonality of 1.0 could be assumed within each cluster;
this would lead to dose additivity. The concept could also be extended by
estimating commonalities between clusters defined as chemical classes. For
example, clusters as diverse as the heavy metals, organic solvents, and
insecticides might all have a given end point, such as peripheral nerve dam-
age. Clustering could be on the basis of mechanistic, toxic, or structural
properties. Structural classification, in fact, is the first step by which EPA
assesses potential hazards associated with new chemicals, so the process is
not unfamiliar for estimating commonalities within a group. With larger
numbers or a lack of sufficient data to describe a toxicity profile, such a
procedure might prove unwieldy; but commonalities among clusters could
still be considered after commonality within a cluster is established. The
concept of commonality clearly could be helpful, but more work is needed
to develop its application.
Incorporating an Uncertainty Factor for Synergism
The issue of toxic interactions synergistic or antagonistic is central in
the development of a risk assessment strategy for chemical mixtures in drink-
ing water. Even though the concentrations of contaminants in most sources
of drinking water for the general public are likely to be very low, there is
insufficient evidence about the toxicity of chemical mixtures after long-term,
low-dose exposure to support a definite conclusion that toxic interactions are
absent under these conditions. For instance, a combination of chemicals,
even at low concentrations, could conceivably act to modify the immune
system, thereby compromising natural defense systems. Evidence supporting
the existence or absence of such a response process is clearly not available
for all relevant mixtures. The argument for the consideration of greater than
response additive effects is strengthened by the possibility that water sources
in heavily polluted areas (e.g., hazardous-waste sites or point-source acci-
dental spills) contain much higher concentrations of contaminants. Thus, at
least a small fraction of the population is sometimes exposed to relatively
high (parts per million) concentrations of mixtures of chemicals in drinking
water. These types of concerns could lead to approaches that are more pro-
tective than those given above.
It is important to address the issue of toxic interactions in the risk assess-
ment of chemical mixtures, but flexibility must be provided to avoid inap-
propriate regulation. Therefore, the additive approach represented by Equation
5 might be modified by incorporating an additional uncertainty factor (UF),
which could be applied to the hazard index defined above to yield:
HI = (UF) ~ HI
j=,
(6)
OCR for page 129
Risk Assessment of Mixtures of Systemic Toxicants 129
The UF could vary from 1 to 100, depending on the amount of information
available and the concentrations of the contaminants. If a great deal of
toxicologic information is available on the individual contaminants, if toxic
interactions are not likely (on the basis of the knowledge available), or if
the concentrations of the contaminants are "low," the UF might be set at l
(thus assuming simple additivity). If less is known about the toxicity of
individual components and the concentrations of the contaminants are higher,
the UF might be set at 10. The greater the uncertainty involved (because of
the lack of information) and the higher the concentrations of the contaminants,
the higher the UF would be set.
Other Considerations
In keeping with the NRC report on complex mixtures (1988, p. 8), we
have here defined "low" dose for carcinogens as one associated with a true
relative risk of less than or equal to 1.01. Such a small relative risk is likely
to be unmeasurable, and the "low" dose considered would be one estimated
to produce a relative risk of 1.01 or less. The present subcommittee first
considered tying the previous report's definition of "low" dose to detection
limits, but decided not to do so, because this concept is related more to the
physicochemical properties of an agent than to its biologic or toxic properties.
Moreover, detection limits are likely to change as measurement technology
improves. Further investigation into the magnitude of synergism as a function
of dose might yield guidance here. Such investigation would involve the
analysis of empirical data, alternative dose-response models, and additional
laboratory experiments.
"Amount of information available" remains unavoidably ambiguous. Ob-
viously, if perfect information were available about the existence and nature
of any synergism, it could be included in a risk assessment. In the absence
of complete knowledge, information about synergism among similar agents
or about the mechanisms of toxicity of agents would be helpful.
In considering uncertainty factors, we recognize that a different type of
uncertainty factor is already incorporated into the estimation of ADIs and
ALs. Traditionally, this safety margin (usually a factor of 100) was provided
to allow for possible interspecies and interindividual variations. Potential
synergistic effects were not used in this development of safety margins. From
a different perspective, however, the incorporation of a UF is not intended
to trigger regulatory action every time contaminants are detected in drinking
water sources. The hazard index in the new approach must be assessed in
actual situations.
The above approaches apply to mixtures of systemic toxicants. For car-
cinogens, models that assume no threshold for response are recommended?
OCR for page 130
130 DRINKING WATER AND HEALTH
and indeed they are used; hence, the constructs associated with ALs or ADIs
do not apply. Mixtures of carcinogens are considered in Chapter 7.
For noncancer end points, dose-response models are not widely available
(or accepted), because most toxicity evaluations have described effects in
terms of single numerical values, such as the EDso or NOAEL. That is
reasonable when a single compound is under consideration, but it is not
necessarily realistic for a combination. When it is known that the compounds
interact to produce dose-additive effects, it might be useful to use the hazard
index.
RESPONSE-SURFACE MODELING
Just as knowledge of the concentration-response curve is necessary to
characterize the toxicity of a single agent, knowledge of the concentration-
response surface is required to characterize the toxicity of a combination.
Response-surface methods are mathematical and statistical techniques that
have been developed to aid in the solution of particular types of problems
in scientific and engineering processes (Box and Draper, 1987; Carter et al.,
1983; Cornell? 1981; Khuri and Cornell, 1987; Myers, 19761. The report
ASAIEPA Conferences on the Interpretation of Environmental Data. 1. Cur-
rent Assessment of the Combined Toxicant Effects (EPA' 1986a) referred
briefly to the potential applicability of response-surface methods for describ-
ing the effects of combinations of toxicants The methods include experi-
mental design, statistical inference? and mathematical techniques that, when
combined, enable an experimenter to explore empirically the process of
interest.
One important aspect of this approach is experimental design. It can be
used to guide the generation of data suitable for estimating the parameters
of a statistical model of the dose response relationship (NRC 19881. Ex-
perimental designs have been developed to estimate the effects of each com-
ponent of a mixture and the effects of interactions on the basis of a small
number of experimental points. Such designs could be useful for indicating
the presence or absence of low-order interactions, once an appropriate model
has been determined. One design that permits the estimation of the inter-
actions of interest and requires only a small number of experimental test
groups is the 2-factorial experiment. Each of k factors is present at two
levels, and each level of each factor is combined with each level of every
other factor. Such a protocol requires 2t observations. The data from such
experiments allow the estimation of the effect of each of k toxicants and
each of the interactions of 2,3, . . . ? k toxicants (factors). If some interactions
are of less interest, more compact experimental designs (fractional factorial
designs), which require fewer groups of exposed subjects, are available
(NRC, 19881.
OCR for page 131
Risk Assessment of Mixtures of Systemic Toxicants 131
The response-surface approach has been used to evaluate combinations of
toxic substances (Kinne, 1972; Schnute and McKinnell, 1984; Voyer and
Heltshe, 1984; Voyer et al., 19821. Its use seems appropriate in this setting
and should be encouraged. The availability of computer graphics has per-
mitted plotting of observed and fitted data as either the surface or contours
of constant response. Such plots are often informative in assessing interac-
tions among components. However, their use is limited to combinations of
only a few toxicants. There is some expectation that graphic procedures can
be developed to display the associated surfaces in higher dimensions; these
efforts should be encouraged and supported.
CONCLUSIONS
Given the current availability of information about the presence and mag-
nitude of synergism among contaminants in drinking water, no single risk-
assessment approach can be justified scientifically for systemic toxicants.
The possibility of synergism cannot be ignored, so approaches that consider
only individual toxic agents are likely to be inadequate. Approaches based
on additivity of response or additivity of doses that produce a given response
are likely to be useful in many situations. In risk assessments of mixtures,
these approaches should be limited to groups of agents that have similar
mechanisms of action and act at the same biologic site.
Nevertheless, the possibility remains that some unexpected and important
synergism (or antagonism) exists and that either additive model could seri-
ously underestimate risk. Societal and policy concerns about the existence
of such interactions could lead to the introduction of further uncertainty
factors in risk assessment. Uncertainty factors should not be uniform, but
should increase with increasing exposure and decrease with increasing knowl-
edge about the agents in mixtures.
REFERENCES
ACGIH (American Conference of Governmental and Industrial Hygienists). 1983. TLVs:
Threshold Limit Values for Chemical Substances and Physical Agents in the Work Envi-
ronment, with Intended Changes for 1983-1984. Cincinnati Ohio: American Conference
of Governmental and Industrial Hygienists.
Box, G. E. P., and N. R. Draper. 1987. Empirical Model-Buildin~ and Response Surface.
New York: John Wiley & Sons. 669 pp.
Carter, W. H., G. L. Wampler, and D. M. Stablein. 1983. Regression Analysis of Survival
Data in Cancer Chemotherapy. New York: Marcel Dekker. 209 pp.
Cornell, J. A. 1981. Experiments with Mixtures: Designs' Models, and the Analysis of Mixture
Data. New York: John Wiley & Sons. 305 pp.
EPA (U.S. Environmental Protection Agency). 1986a. ASA/EPA Conferences on the Inter
OCR for page 132
132 DRlNKlNG WATER AND HEALTH
pretation of Environmental Data. 1. Current Assessment of the Combined Toxicant Effects,
May 5-6, 1986.
EPA (U.S. Environmental Protection Agency). 1986b. Guidelines for the health risk assessment
of chemical mixtures. Fed. Regist. 51(185):34014-34025.
Khuri, A. I., and J. A. Cornell. 1987. Response Surfaces: Designs and Analyses. New York:
Marcel Dekker. 405 pp.
Kinne, O., ed. 1972. Environmental factors. Part 3 in Marine Ecology. A Comprehensive
Integrated Treatise on Life in Oceans and Coastal Waters, Vol. 1. New York: Wiley In-
terscience.
Murphy, S. D., R. L. Anderson, and K. P. du Bois. 1959. Potentiation of the toxicity of
malathion by triorthotolyl phosphate. Proc. Soc. Exp. Biol. Med. 100:483-487.
Myers, R. H. 1976. Response Surface Methodology. 246 pp. [Distributed by R. H. Myers.
Department of Statistics, Virginia Polytechnic Institute and State University, Blacksburg.
Virginia. ]
NRC (National Research Council). 1980. Principles of Toxicological Interaction Associated
with Multichemical Exposures. Washington, D.C.: National Academy Press. 213 pp.
NRC (National Research Council). 1988. Complex Mixtures: Methods for In Vivo Toxicity
Testing. Washington, D.C.: National Academy Press. 227 pp.
Schnute, J., and S. McKinnell. 1984. A biologically meaningful approach to response surface
analysis. Can. J. Fish. Aquat. Sci. 41:936-953.
Smyth. H. F., C. S. Well, J. S. West. and C. P. Carpenter. 1969. An exploration of joint
toxic action: I. Twenty-seven industrial chemicals intubated in rats in all possible pairs.
Toxicol. Appl. Pharmacol. 14:340-347.
Voyer, R. A. ~ and J. F. Heltshe. 1984. Factor interactions and aquatic toxicity testing. Water
Res . 18:441 -447.
Voyer, R. A., J. A. Cardin. J. F. Heltshe, and G. L. Hoffman. 1982. Viability of embryos
of the winter flounder Pseudopleuronectes americanus exposed to mixtures of cadmium and
silver in combination with selected fixed sabinities. Aquat. Toxicol. 2:223-233.
Weiss, B. 1986. Emerging challenges to behavioral toxicology. Pp. 1-2 in Neurobehavioral
Toxicology. Z. Annau, ed. Baltimore: Johns Hopkins University Press.
Representative terms from entire chapter:
hazard index
