Research | Article

Methods for evaluating risks from exposure to

toxic substances for noncancer health end

points (such as birth defects, respiratory

effects, and hepatotoxicity) are based on the

theory that there is a threshold below which

there is negligible risk of adverse health effects

from environmental exposures. At the U.S.

Environmental Protection Agency (U.S. EPA),

this negligible risk is quantified through the

use of reference doses (RfDs) and reference

concentrations (RfCs). The RfD or RfC is

defined as an estimate of daily or continuous

exposure to the human population (including

sensitive subgroups) that is likely to be without

an appreciable risk of deleterious effects during

a lifetime (U.S. EPA 1999a). The value of the

RfD or RfC is derived by determining a point

of departure divided by uncertainty factors

(UFs), which are used to account for uncertainties in the available studies, such as limitations in the database, variability within

humans, and differences in species response

(i.e., animal-to-human extrapolation).

The point of departure in environmental

health risk assessment is meant to represent the

lowest dose within the range of experimental

data. In past practices, the point of departure

was exclusively based on a no-observedadverse-effect level (NOAEL) or a lowestobserved-adverse-affect level (LOAEL), derived

from animal or epidemiologic studies. The

NOAEL is the highest dose for which there are

no observed statistically or biologically significant increases in the frequency or severity of

adverse effects between the exposed population

and its control. Similarly, the LOAEL is the

lowest dose at which there are statistically or

biologically significant increases in the frequency or severity of adverse effects between

the exposed population and its appropriate

control group. The NOAEL/LOAEL structure, however, does not provide sufficient

information to quantify the equivalent risk levels from exposure at the RfD/RfC because

there is no estimated risk at the NOAEL or

LOAEL itself. Several authors have criticized

the use of the NOAEL because of its sensitivity

to sample size, the high sampling variability

from experiment to experiment, and the

inability to use all of the available dose–

response data (Barnes et al. 1995; Crump

1984; Gaylor et al. 1998; Leisenring and Ryan

1992; U.S. EPA 2000a). Leisenring and Ryan

(1992) have shown that average risk levels

associated with the NOAEL may be substantial. The true risk of exposure at the NOAEL

can vary from zero to > 20%, depending on

the end point, spacing of doses, and numbers

of animals used (Leisenring and Ryan 1992).

In many cases, an adverse effect may not be

detected in a critical effect study because of

insufficient statistical power.

Although the NOAEL/LOAEL structure

does not provide sufficient information to

quantify risk levels from exposure (Gaylor

and Kodell 2000), the resulting RfDs and

RfCs are assumed to be equivalent to negligible or de minimis risks. As a point of comparison, the U.S. EPA has defined 1 in 1,000,000

excess cancer risk as a de minimis risk level for

cancer (Caldwell et al. 1998; Clean Air Act

Amendments 1990; Fiori and Meyerhoff

2002; U.S. EPA 1991), although regulatory

actions are sometimes limited to instances

where risk exceeds 1 in 100,000.

Over the past several years, the U.S. EPA

has been in the process of developing the

benchmark dose (BMD), which is derived

from modeling the exposure–response data, as

an alternative to the NOAEL/LOAEL as the

point of departure for noncancer risk assessments. The BMD is the dose that corresponds

to a specified level of increased response [the

benchmark response (BMR)] compared with

background. This dose is calculated by fitting

a mathematical model to the dose–response

data, which can be continuous or quantal.

The BMD method has several advantages over

the NOAEL/LOAEL method, including making better use of dose–response information

and reflecting sample size more appropriately

(Barnes et al. 1995; Crump 1995). In singlechemical hazard assessments, the BMD

allows for consideration of the dose–response

over the entire exposure range, and furthermore, when a dose derived from benchmark

modeling is used as the point of departure,

actual risk levels can be calculated as an alternative to the hazard index (which is typically

based on comparisons of human exposures

with an RfD or RfC).

Assessment of Potential Risk Levels Associated with U.S. Environmental

Protection Agency Reference Values

Rosemary Castorina1,2 and Tracey J. Woodruff 2

1Center for Children’s Environmental Health Research, School of Public Health, University of California, Berkeley, California, USA; 2U.S. Environmental Protection Agency, Washington, DC, USA

Address correspondence to T.J. Woodruff, Public

Health and Environmental Policy Team, National

Center for Environmental Economics, U.S. EPA, 75

Hawthorne St., MC SPE-1, San Francisco, CA 94105

USA. Telephone: (415) 947-4277. Fax: (415) 947-

3519. E-mail: Woodruff.Tracey@epamail.epa.gov

We thank D. Axelrad, V.J. Cogliano, J. Gift, J.

Jinot, and T. McKone for their expert technical

assistance and advice. 

This work was supported in part by grants from the

U.S. EPA and the National Institute of Environmental

Health Sciences (R826709 and ES09605). The views

expressed in this article are those of the authors and do

not necessarily reflect those of the U.S. EPA.

The authors declare they have no conflict of interest.

Received 2 January 2003; accepted 12 May 2003.

The U.S. Environmental Protection Agency (U.S. EPA) generally uses reference doses (RfDs) or

reference concentrations (RfCs) to assess risks from exposure to toxic substances for noncancer

health end points. RfDs and RfCs are supposed to represent lifetime inhalation or ingestion exposure with minimal appreciable risk, but they do not include information about the estimated risk

from exposures equal to the RfD/RfC. We used results from benchmark dose modeling

approaches recently adopted for use in developing RfDs/RfCs to estimate the risk levels associated

with exposures at the RfD/RfC. We searched the U.S. EPA Integrated Risk Information System

(IRIS) database and identified 11 chemicals with oral RfDs and 12 chemicals with inhalation RfCs

that used benchmark dose modeling. For assessments with sufficient model information, we found

that 16 of 21 (76%) of the dose–response models were linear or supralinear. We estimated the risk

from exposures at the established RfDs and RfCs for these chemicals using a linear dose–response

curve to characterize risk below the observed data. Risk estimates ranged from 1 in 10,000 to 5 in

1,000 for exposures at the RfDs, and from 1 in 10,000 to 3 in 1,000 for exposures at the RfCs.

Risk estimates for exposures at the RfD/RfC values derived from sublinear dose–response curves

ranged from 3 in 1,000,000,000 to 8 in 10,000. Twenty-four percent of reference values corresponded to estimated risk levels greater than 1 in 1,000; 10 of 14 assessments had points of departure greater than the no-observed-adverse-effect levels. For policy development regarding

management of cancer risks, the U.S. EPA often uses 1 in 1,000,000 as a de minimis risk level.

Although noncancer outcomes may in some instances be reversible and considered less severe than

cancer, our findings call into question the assumption that established RfD and RfC values represent negligibly small risk levels. Key words: benchmark dose, noncancer, risk assessment. Environ

Health Perspect 111:1318–1325 (2003). doi:10.1289/ehp.6185 available via http://dx.doi.org/

[Online 12 May 2003]

1318 VOLUME 111 | NUMBER 10 | August 2003 • Environmental Health Perspectives
In 2000, the U.S. EPA published a draft

guidance document on the application of the

BMD approach in determining the point of

departure for all types of health effects data

(U.S. EPA 2000a). Although a BMR of 10%

has most often been used by the U.S. EPA in

its assessments, it is anticipated that 5% or 1%

would be a more appropriate response level for

some end points and designs. Furthermore, in

these draft guidelines, a lower statistical confidence limit on the BMD (BMDL) is specifically proposed as a replacement for the

NOAEL/LOAEL in setting the point of departure, which is used to determine acceptable levels of human exposure to environmental

toxicants. A lower confidence limit is placed on

the BMD to obtain a dose (BMDL) that

assures with high confidence (e.g., 95%) that

the BMR is not exceeded (U.S. EPA 2000a).

In addition to ensuring an added measure of

protection, this process rewards better experimental design and procedures that provide

more precise estimates of the BMD.

Most new and revised RfDs and RfCs in

the U.S. EPA Integrated Risk Information

System (IRIS) assessments are based on BMD

modeling. Certain health end points, however, are not amenable to modeling, and the

NOAEL/LOAEL approach will continue to

be used in some cases (U.S. EPA 2000a). For

this article, we have reviewed and synthesized

currently available risk assessment information on the chemicals for which U.S. EPA reference values are based on BMD modeling.

We estimate the equivalent risk levels

expected from hypothetical human exposures

at established RfD and RfC values using the

BMD dose–response information to investigate whether these levels represent negligible

risks, and to underscore some of the potential

strengths of using benchmark modeling in

environmental health risk assessment.

Methods

We searched the U.S. EPA IRIS database (U.S.

EPA 2000b) to identify the chemicals for

which current regulatory reference values relied

on BMD modeling. We identified 11 chemicals with RfDs based on oral BMD values, and

12 chemicals with RfCs based on benchmark

concentration (BMC) values. The BMD and

Environmental Health Perspectives • VOLUME 111 | NUMBER 10 | August 2003 1319

Table 1. Risk assessment information for chemicals with oral RfDs derived from benchmark modeling.a

NOAEL LOAEL BMD10 BMDL10 BMD05 BMDL05 RfD

Chemical (mg/kg/day) (mg/kg/day) (mg/kg/day) (mg/kg/day) (mg/kg/day) (mg/kg/day) BMD/BMDL UF (mg/kg/day)

Quantal end point

Beryllium and compounds (U.S. EPA 1998a) 0.1 — 1.4 0.46b — — 3.0 300 0.002

Chloroformc (U.S. EPA 2001b) — 15 (12.9ADJ) 1.7 (1.5ADJ) 1.2 (1.0ADJ)

b — — 1.4 100 0.01

1,1-Dichloroethylene (U.S. EPA 2002a) 9 14 6.6 4.6b — — 1.4 100 0.05

1,3-Dichloropropene (U.S. EPA 2000c) 2.5 — 5.1 3.4b — — 1.5 100 0.03

Hexachlorocyclopentadiene (U.S. EPA 2001d) — 10 (7ADJ) 11 6b — — 1.8 1,000 0.006

Continuous end point

Benzened (U.S. EPA 2003) — 1.2 2.2 1.2b — — 1.8 300 0.004

EGBEe (U.S. EPA 1999b) — 59 — — 7.7HED 5.1HEDb 1.5 10 0.5

Methylmercury (U.S. EPA 2001a) — — — — 1.4–2.6E–03 0.9–1.5E–03b 1.6 10 0.0001

Naphthalenef (U.S. EPA 1998i) 100 (71ADJ)

b 200 (143ADJ) 171(122ADJ) 130 (93ADJ) — — — 1.3 3,000 0.02

Phenolg (U.S. EPA 2002c) 60 — 157 93b — — 1.7 300 0.3

Tributyltin oxide (U.S. EPA 1997a) 0.025 — 0.05 0.034b — — 1.5 100 0.0003

Abbreviations: ADJ, adjusted for duration of exposure; BMD10, BMD that equals a BMR of 10%; BMDL10, lower confidence limit on the BMD10; BMD05, BMD that equals a BMR of 5%;

BMDL05, lower confidence limit on BMD05; Cmax, peak blood concentration; EGBE, ethylene glycol monobutyl ether; HED, human dose of an agent that is believed to induce the same

magnitude of toxic effect as the experimental animal species concentration or dose (this adjustment may incorporate toxicokinetic information on the particular agent, if available, or

use a default procedure, such as assuming that daily oral doses experienced for a lifetime are proportional to body weight raised to the 0.75 power). aThe reported number of significant figures is not standardized in IRIS. bPoint of departure. cRfD derived from the LOAEL (1,000-fold UF) = 0.01 mg/kg/day; BMD-based RfD (100-fold UF) = 0.01

mg/kg/day. dOral BMDL[ADJ] was derived from the BMCL[ADJ] (8.2 mg/m3

) by route-to-route extrapolation with the assumptions that inhalation absorption was 50% and oral absorption was

100% in the dose range near the BMC; BMDL (adjusted for continuous exposure) = (8.2 mg/m3 × 20 m3

/day × 0.5)/70 kg = 1.2 mg/kg/day; former RfD derived from the LOAEL (1,000-fold UF) =

0.001. eHED was calculated as follows: using Cmax for 2-butoxyacetic acid as the dose metric, the BMDL05 was determined to be 64 μM; physiologically based pharmacokinetic modeling was

used to “back-calculate” a human equivalent dose of 5.1 mg/kg/day, assuming that rats and humans receive their entire dose of EGBE from drinking water over a 12-hr period each day. f

RfDs were based on the NOAEL and BMD10 values adjusted for duration (e.g., BMD × 5/7 days); the RfD in IRIS is derived from the NOAEL (3,000-fold UF) = 0.02 mg/kg/day; prospective RfD

derived from BMD (3,000-fold UF) = 0.03 mg/kg/day. gBMD was based on a benchmark response of a 1-standard-deviation change from the control mean. 

Table 2. End points and UFs for chemicals with oral RfDs derived from benchmark modeling.

Composite UFa

Chemical Reference End point: quantal or continuous UF Interspecies Intraspecies Subchronic Database ELE

Beryllium and compounds U.S. EPA 1998a Quantal (small intestinal lesions) 300 10 10 — 3 —

Chloroform U.S. EPA 2001b Quantal (fatty cyst formation in liver and elevated 100 10 10 — — —

serum glutamate-pyruvate transaminase)

1,1-Dichloroethylene U.S. EPA 2002a Quantal [liver toxicity (fatty change)] 100 10 10 — — —

1,3-Dichloropropene U.S. EPA 2000c Quantal (chronic irritation of stomach) 100 10 10 — — —

Hexachlorocyclopentadiene U.S. EPA 2001d Quantal (chronic irritation of stomach) 1,000 10 10 3b 3b —

Benzene U.S. EPA 2003 Continuous (decreased lymphocyte count) 300 — 10 3 3 3

EGBE U.S. EPA 1999b Continuous (changes in mean corpuscular 10 — 10 — — —

volume)

Methylmercury U.S. EPA 2001a Continuous (developmental neuropsychologic 10 — 10 — — —

impairment)

Naphthalene U.S. EPA 1998i Continuous (decreased mean terminal body 3,000 10 10 10 3 —

weight in males)

Phenol U.S. EPA 2002c Continuous (decreased maternal body 300 10 10 — 3 —

weight gain)

Tributyltin oxide U.S. EPA 1997a Continuous (immunosuppression; 100 10 10 — — —

decrease in IgE titer)

Abbreviations: EGBE, ethylene glycol monobutyl ether; ELE, effect level extrapolation factor. 

aInterspecies extrapolation, intraspecies differences (human variability), subchronic-to-chronic extrapolation, database deficiencies, and ELE. bUFs assigned a value of 101/2 were

rounded to 3.

Article | Reference values and risk
BMC values and other risk assessment information for these chemicals are presented in

Tables 1–4 (U.S. EPA 1995a, 1995b, 1995c,

1995d, 1997a, 1998a, 1998c, 1998e, 1998g,

1999b, 2000c, 2001a, 2001b, 2001d, 2002a,

2002c, 2002e, 2003). We have included risk

assessment information for naphthalene, a

chemical with an IRIS assessment containing

an established RfD based on a NOAEL (RfD

= 0.02 mg/kg/day) as well as a prospective

RfD based on BMD modeling (RfD = 0.03

mg/kg/day) (U.S. EPA 1998i).

We determined whether the principal study

identified for each chemical’s IRIS assessment

was derived from quantal (dichotomous) or

continuous critical effect data (Tables 2 and 4).

For compounds with BMD or BMC values

based on quantal data, the BMR is expressed in

terms of a percent increase in risk of adverse

outcome compared with background. For compounds with BMD or BMC values based on

continuous data, the BMR may be expressed as

a percent change in mean response compared

with control (e.g., immunosuppression with

tributyltin oxide) or in terms of a 1 standard

deviation change from the control mean

response (e.g., decreased lymphocyte count

with benzene). The BMR is a response level

used to define a BMD, which is used as the

point of departure, from which an RfD or RfC

can be developed. The BMR is typically set at

the lower end of the range of responses (e.g.,

10% or 5% change) that can be detected experimentally. This can help to avoid uncertainties

associated with low-dose extrapolation using

models that may not reflect biologic realities

(Crump 1995).

Using the benchmark modeling information described above from the IRIS assessments

of 19 chemicals, we estimated the equivalent

risk levels expected from hypothetical human

exposures at the established RfDs and RfCs.

We also evaluated whether each of the models

used for BMD calculations was linear, sublinear, or supralinear in the observed dose range

(Table 5) [National Research Council (NRC)

2000; U.S. EPA 1995a, 1995b, 1995c, 1995d,

1997b, 1998b, 1998c, 1998d, 1998f, 1998h,

1320 VOLUME 111 | NUMBER 10 | August 2003 • Environmental Health Perspectives

Table 3. Risk assessment information for chemicals with RfCs derived from benchmark modeling.a

BMC/

Chemical NOAEL LOAEL BMC10 BMCL10 BMCL10[ADJ] BMCL10[HEC] BMC05 BMCL05 BMCL UF RfC

Quantal end point

Antimony trioxideb (U.S. EPA 1995b) 0.51 (0.42HEC) — 1.43 0.87 0.16 0.074c — — 1.6 300 0.0002

1,3-Butadiene (U.S. EPA 2002e) — 2.5 2.25 1.98c — — — — 1.1 1,000 0.002

1,1-Dichloroethylene (U.S. EPA 2002a) 99.2 (17.7HEC) 297.8 (53.2HEC) 59.95 38.9 — 6.9c — — 1.5 30 0.2

1,3-Dichloropropene (U.S. EPA 2000c) 3.7ADJ 14.9ADJ 5.91ADJ — 3.66 0.72c — — 1.6 30 0.02

Methyl methacrylate (U.S. EPA 1998e) 102.4 (18.2ADJ) — 178.7 143 25.6 7.2c — 104.6 1.2 10 0.7

Methylene diphenyl diisocyanate 0.2 (0.036ADJ) 1.0 (0.18ADJ) 0.22ADJ — 0.14 0.06c — — 1.6 100 0.0006

(U.S. EPA 1998g)

Phosphoric acid (U.S. EPA 1995d) 50 (2.7ADJ) 180 150 100 5.4 3.4c 112 64 1.5 300 0.01

1,1,1,2-Tetrafluoroethane (U.S. EPA 1995a) 7,450HEC 37,250HEC — 46,000 8,200 8,200c — —— 100 80

Continuous end point

Benzened (U.S. EPA 2003) — 8.7ADJ 43.77 23 8.2c — — — 1.9 300 0.03

Carbon disulfidee (U.S. EPA 1995c) 15.9 (5.7ADJ) 39.2 (14.0ADJ) — 55.1 19.7c — — —— 30 0.7

Chromium VI (particulates) (U.S. EPA — 0.05 0.036 0.016 0.034c — — — 2.3 300 0.0001

1998c)

EGBE (U.S. EPA 1999b) — 150HEC — —— — 530HEC 380HECc 1.4 30 13

Abbreviations: ADJ, dose that has been adjusted for duration of exposure; BMC10, BMC that equals a BMR of 10%; BMCL10, lower confidence limit on the BMC10; BMC05, BMC that equals

a BMR of 5%; BMCL05, lower confidence limit on BMC05; HEC, human equivalent concentration [the human concentration (for inhalation exposure) of an agent that is believed to induce the

same magnitude of toxic effect as the experimental animal species concentration or dose; this adjustment may incorporate toxicokinetic information on the particular agent, if available, or

use a default procedure, such as assuming that daily oral doses experienced for a lifetime are proportional to body weight raised to the 0.75 power]; MVh, human ambient default minute

volume; MVho, human occupational default minute volume; RDDR, regional deposited dose ratio (the ratio of the regional deposited dose calculated for a give exposure in the animal

species of interest to the regional deposited dose of the same exposure in a human; this ratio is used to adjust the exposure effect level for interspecies dosimetric differences to derive a

human equivalent concentration for particles). 

aThe reported number of significant figures is not standardized in IRIS. bPoint of departure is the BMCL10[HEC] (BMCL10[HEC] = BMC10[ADJ] × RDDR = 0.074 mg/m3

. cPoint of departure. dBMC was

based on a benchmark response of a 1-standard-deviation change from the control mean; the BMCL is the statistical lower bound estimate on the dose corresponding to a 1-standarddeviation change from control. eBMC is based on an 8-hr time-weighted average occupational exposure; its point of departure is BMCL10[HEC] = 55.1 mg/m3 × (MVho/MVh × 5/7 days) =

19.7 mg/m3

. MVho = 10 m3/day; MVh = 20 m3/day.

Table 4. End points and UFs for chemicals with RfCs derived from benchmark modeling.

Composite UFa

Chemical Reference End point: quantal or continuous UF Interspecies Intraspecies Subchronic Database ELE

Antimony trioxide U.S. EPA 1995b Quantal (pulmonary toxicity, chronic 300 3 10 3 3 —

interstitial inflammation)

1,3-Butadiene U.S. EPA 2002e Quantal (ovarian atrophy) 1,000 3 10 — 3 10

1,1-Dichloroethylene U.S. EPA 2002a Quantal [liver toxicity (fatty change)] 30 3 10 — — —

1,3-Dichloropropene U.S. EPA 2000c Quantal (hyperplasia of nasal epithelium) 30 3 10 — — —

Methyl methacrylate U.S. EPA 1998e Quantal (degeneration/atrophy of 10 3 3 — — —

olfactory epithelium)

Methylene diphenyl diisocyanate U.S. EPA 1998g Quantal (hyperplasia of the olfactory epithelium) 100 3 10 — 3 —

Phosphoric acid U.S. EPA 1995d Quantal (bronchiolar fibrosis) 300 3 10 10 — —

1,1,1,2-Tetrafluoroethane U.S. EPA 1995a Quantal (Leydig cell hyperplasia) 100 3 10 — 3 —

Benzene U.S. EPA 2003 Continuous (decreased lymphocyte count) 300 — 10 3 3 3

Carbon disulfide U.S. EPA 1995c Continuous (peripheral nervous system 30 — 3 — 10 —

dysfunction)

Chromium VI (particulates) U.S. EPA 1998c Continuous (lactate dehydrogenase 300 3 10 10 — —

in bronchioalveolar lavage fluid)

EGBE U.S. EPA 1999b Continuous (changes in red blood cell count) 30 — 10 — — 3

Abbreviations: EGBE, ethylene glycol monobutyl ether; ELE, effect level extrapolation factor.

aInterspecies extrapolation, intraspecies differences (human variability), subchronic-to-chronic extrapolation, database deficiencies, and ELE.

Article | Castorina and Woodruff
1998j, 1999c, 2000d, 2001c, 2001e, 2002b,

2002d]). To estimate the risk level of the

derived RfDs and RfCs, which have a linear or

supralinear dose–response curve at the

BMD/BMC, we assumed that the dose–

response curves for these compounds are linear

at doses below the BMD or BMC (Figure 1).

For two assessments, sufficient information

was not available to determine the shape of the

dose–response curve (carbon disulfide and

1,1,1,2-tetrafluoroethane), and we assumed

linearity [this assumption did not overly bias

our results because linearity or supralinearity

was the shape of the dose–response curve in

approximately three-quarters (16 of 21) of

cases in which the shape of the dose–response

curve was discernable]. This assumption of linearity at the relevant part of the dose–response

curve is necessary to extrapolate equivalent risk

levels from U.S. EPA reference values derived

from BMD modeling, and it is consistent with

methods proposed in the U.S. EPA draft cancer risk assessment guidelines (U.S. EPA

1999d). Such risk-level extrapolation is not

possible using the NOAEL/LOAEL approach.

Methods for risk-level estimation varied

between reference values based on quantal end

points and those based on continuous end

points. For BMD/BMC values derived from

quantal critical effect data, we estimated risk

from exposure at concentrations equal to established RfD and RfC values by extrapolating

linearly from the point represented by the

BMR at the BMDL/BMCL to the established

RfD and RfC values (Figure 1). We divided

the risk at the BMR by the composite UF for

those BMD models that were linear or supralinear. For example, to estimate risk from

exposure to chloroform’s RfC, we divided the

estimated risk level at the point of departure (1

in 10 for BMR = 10%) by the composite UF

of 100, to arrive at a risk of 1 in 1,000. For

BMD/BMC values derived from continuous

critical effect data (normally distributed), a

change in response of 1 standard deviation

from control is considered roughly equivalent

to a 10% increase in risk of adverse response

from exposure (e.g., benzene’s BMR = change

of 1 standard deviation in lymphocyte count

compared with control mean) (U.S. EPA

2000a, 2003). Therefore, when data quality

and distribution allowed, we treated the dose

that resulted in a 1-standard-deviation change

from control as equivalent to BMD10/BMC10

(BMD that equals a BMR of 10%/BMC that

equals a BMR of 10%) values derived from

quantal data. For assessments based on sublinear dose–response curves, we estimated risk of

exposure at the RfD/RfC dose levels by extrapolating the BMD model response function to

the RfD/RfC (i.e., using the BMD model, we

estimated risk by putting the exposure equal to

the RfD/RfC in the model).

For all chemicals in our assessment group

with adequate data, we calculated the ratio of

the central estimate (BMD or BMC) to the

lower statistical confidence limit on the

benchmark dose (BMDL) or concentration

(BMCL) (Tables 1 and 3). This ratio (e.g.,

BMD/BMDL) provides a metric to compare

the relative impact on estimated risk levels

resulting from the selection of the BMD/BMC

versus the BMDL/BMCL as the point of

departure. Finally, among the studies that

identified NOAELs, we compared the modeled BMDL and BMCL values with the

empirical NOAELs as a means to investigate

how using BMDL/BMCL values versus

NOAELs compares with previous RfD/RfC

methods based on the NOAEL approach.

Environmental Health Perspectives • VOLUME 111 | NUMBER 10 | August 2003 1321

BMRa

Risk at RfD

RfD BMDL

or

POD

BMD

Dose (mg/kg/day)

Risk level

Composite

UF

Central

estimate ×

× ×

×

×

Lower confidence

limit on BMD

Figure 1. Linear extrapolation of risk from exposure

at the RfD when the RfD is derived from benchmark

modeling of quantal dose–response data. Assuming

the relationship between risk of adverse outcome

and dose is linear at low doses, we estimated risk

from exposure at concentrations equal to established RfD and RfC values by extrapolating from the

point represented by the BMR at the BMDL or

BMCL to established RfD and RfC values. POD,

point of departure. 

aFor quantal data, the BMR represents a percentage

increase in risk compared with controls.

Table 5. Fitted BMD models and dose–response curve characterizations for 23 RfD/RfC assessments.

Shape of 

Chemical Reference value End point Fitted modelsa dose–response curve

Antimony trioxide (U.S. EPA 1995b) RfC Quantal Linear and Weibullb Linear

EGBE (U.S. EPA 1999b, 1999c; NTP 1993, 1998) RfC Continuous Power model (k = 0.95) Linear

Methylene diphenyl diisocyanate (U.S. EPA 1998g, 1998h) RfC Quantal Polynomial regression (βi = 0)c Linear

Methylmercury (U.S. EPA 2001a; NRC 2000) RfD Continuous Power model (k = 1)d Linear

Phenol (U.S. EPA 2002c, 2002d) RfD Continuous Polynomial (β2 ≅ 0)e Linear

Phosphoric acid (U.S. EPA 1995d) RfC Quantal Linear and Weibullb Linear

Tributyltin oxide (U.S. EPA 1997a, 1997b) RfD Continuous Polynomial mean response (βi = 0)c Linear

Benzene (U.S. EPA 2003) RfD Continuous Log-linear Supralinear

Benzene RfC Continuous Log-linear Supralinear

Beryllium (U.S. EPA 1998a, 1998b) RfD Quantal Exponential polynomial Supralinear

1,3-Butadiene (U.S. EPA 2002e) RfC Quantal Weibull Supralinear

Chloroform (U.S. EPA 2001b, 2001c) RfD Quantal Quantal-linear Supralinear

1,1-Dichloroethylene (U.S. EPA 2002a, 2002b) RfD Quantal Gamma Supralinear

1,1-Dichloroethylene RfC Quantal Quantal-linear Supralinearf

EGBE (U.S. EPA 1999b, 1999c; NTP 1993, 1998) RfD Continuous Power model (k = 0.66) Supralinear

Naphthalene (U.S. EPA 1998i, 1998j) RfD Continuous Polynomial and power Supralinearg

Chromium VI (particulates) (U.S. EPA 1998c, 1998d) RfC Continuous Polynomial mean response Sublinear

1,3-Dichloropropene (U.S. EPA 2000c, 2000d) RfD Quantal Gamma Sublinear

1,3-Dichloropropene RfC Quantal Gamma Sublinear

Hexachlorocyclopentadiene (U.S. EPA 2001d, 2001e) RfD Quantal Log-logistic Sublinear

Methyl methacrylate (U.S. EPA 1998e, 1998f) RfC Quantal Polynomial mean response Sublinear

Carbon disulfide (U.S. EPA 1995c) RfC Continuous Weibull and polynomial NAh

1,1,1,2-Tetrafluoroethane (U.S. EPA 1995a) RfC Quantal Weibull and polynomial (multistage) NAh

Abbreviations: EGBE, ethylene glycol monobutyl ether; NA, not available. aModels were defined for an observed range of experimental data. bBMCs were obtained using both Weibull and linear models; the models gave similar goodness of fit to the data and

BMC estimates. cLinear dose–response curve because assessment is based on a polynomial model with βi = 0 for i > 1. dModel restricted to not allow supralinear forms. eEssentially linear

dose–response curve because squared coefficient term of second-degree polynomial model is insignificantly small (β2 ≅ 0). f

Shape of dose–response curve determined supralinear based

on visual inspection; because slope parameter is small, curve approaches linear at low doses. gShape of dose–response curve determined supralinear based on visual inspection; BMD

model response function was not available. hShape of dose–response curve information was not available; assumed linear or supralinear.

Article | Reference values and risk
Results

We found that 13 out of 23 (57%) of the

BMD and BMC values were derived from

quantal versus continuous data. A 10% additional risk or 10% change from control mean

response was selected as the BMR for 17 of the

23 assessments, and a 5% BMR was selected

for 3 of the remaining 6 assessments (Tables 6

and 7) [National Toxicology Program (NTP)

1993; U.S. EPA 1995a, 1995b, 1995c, 1995d,

1997a, 1998a, 1998c, 1998e, 1998g, 1998i,

1999b, 2000c, 2001a, 2001b, 2001d, 2002a,

2002e]. The BMR values for benzene’s BMC

and BMD and for phenol’s BMD were based

on a 1-standard-deviation change in acute lymphocyte count and maternal body weight,

respectively, compared with the control mean

(U.S. EPA 2002c, 2003).

Of the 21 BMD and BMC values for

which sufficient dose–response information

was available, we found that 16 (76%) were

derived from dose–response data fitted to linear or supralinear models in the observed dose

range (Table 5) (NRC 2000; NTP 1993,

1998; U.S. EPA 1995b, 1995d, 1997b,

1998b, 1998c, 1998d, 1998f, 1998h, 1998j,

1999c, 2000c, 2001c, 2001e, 2002b, 2002d,

2002e, 2003). Seven assessments were based

on linear models (two linear models; three

polynomial models with βi ≅ 0 for i > 1; two

power models with k ≅ 1), nine were based on

supralinear models, and five were based on

sublinear models. Sufficient information was

not available to determine the shape of the fitted model for two assessments, carbon disulfide and 1,1,1,2-tetrafluoroethane (i.e., the

response function and model parameters were

not provided) (U.S. EPA 1995a, 1995c).

We calculated 17 RfD and RfC equivalent

risk levels (for 14 compounds) assuming linear

dose–response curves. These risk estimates

ranged from 1 in 10,000 to 5 in 1,000 for the

oral route of exposure for compounds with

RfDs based on BMD values, and from 1 in

10,000 to 3 in 1,000 for inhalation for compounds with RfCs based on BMC values

(Tables 6 and 7). Figures 2 and 3 present the

RfD and RfC equivalent risk estimates on a

1322 VOLUME 111 | NUMBER 10 | August 2003 • Environmental Health Perspectives

Table 6. Estimated risk levels from exposure at the RfD.

Point of departure RfD

Chemical (mg/kg/day) BMR UF (mg/kg/day) Risk estimate End point: quantal or continuous

Beryllium and compounds (U.S. EPA 1998a) 0.46 10% 300 0.002 1 in 10,000 Quantal (small intestinal lesions)

Chloroform (U.S. EPA 2001b) 1.2 10% 100 0.01 1 in 1,000 Quantal (fatty cyst formation in liver and elevated 

serum glutamate-pyruvate transaminase)

1,1-Dichloroethylene (U.S. EPA 2002a) 4.6 10% 100 0.05 1 in 1,000 Quantal [liver toxicity (fatty change)]

1,3-Dichloropropene (U.S. EPA 2000c) 3.4 10% 100 0.03 1 in 100,000a Quantal (chronic irritation of stomach)

Hexachlorocyclopentadiene (U.S. EPA 2001d) 6.0 10% 1,000 0.006 3 in 109a Quantal (chronic irritation of stomach)

Benzeneb (U.S. EPA 2003) 1.2 1 SD 300 0.004 3 in 10,000 Continuous (decreased lymphocyte count)

EGBE (U.S. EPA 1999b; NTP 1993) 5.1 5% 10 0.5 2 in 1,000 Continuous (changes in mean corpuscular volume)

Methylmercuryc (U.S. EPA 2001a) 0.0009 5% 10 0.0001 5 in 1,000 Continuous (developmental neuropsychological 

impairment)

Naphthalened (U.S. EPA 1998i) 93 10% 3,000 0.03 — Continuous (decreased mean terminal body weight)

Phenol (U.S. EPA 2002c) 93 1 SD 300 0.3 3 in 10,000 Continuous (decreased maternal body weight gain)

Tributyltin oxide (U.S. EPA 1997a) 0.03 10% 100 0.0003 1 in 10,000 Continuous (immunosuppression—decrease in

IgE titer)

EGBE, ethylene glycol monobutyl ether.

aBecause IRIS assessment is based on sublinear dose–response curve, linearity was not assumed for low dose extrapolation, and risk estimate was derived from the BMD model

response function. bBMR is expressed in terms of the standard deviation (in the absence of a clear definition for an adverse effect for this continuous end point, a default BMR of 1-standard-deviation change from the control mean was selected). This default definition of a BMR for continuous end points corresponds to an excess risk of approximately 10% for the proportion of individuals below the second percentile (or above the 98th percentile) of the control distribution for normally distributed effects. Benzene’s oral BMDL[ADJ] was derived from

the BMCL[ADJ] (8.2 mg/m3

) by route-to-route extrapolation with the assumptions that inhalation absorption was 50% and oral absorption was 100% in the dose range near the BMC. cBMR

represents a 5% increased risk of neuropsychologic impairment compared to background. dInsufficient data available to estimate risk level (i.e., the response function, underlying distribution of the end point, or mean response and standard deviation of the treatment group and controls were not provided). Naphthalene’s RfD in IRIS derived from the NOAEL (3,000-fold

uncertainty factor) = 0.02 mg/kg/day; Tthe prospective RfD derived from the BMD (3,000-fold uncertainty factor) = 0.03 mg/kg/day.

Table 7. Estimated risk levels from exposure at the RfC.

Point of departure RfC

Chemical (mg/m3) BMR UF (mg/m3) Risk estimate End point: quantal or continuous

Antimony trioxide (U.S. EPA 1995b) 0.074 10% 300 0.0002 3 in 10,000 Quantal (pulmonary toxicity, chronic interstitial

inflammation)

1,3-Butadiene (U.S. EPA 2002e) 1.98 10% 1,000 0.002 1 in 10,000 Quantal (ovarian atrophy)

1,1-Dichloroethylene (U.S. EPA 2002a) 6.9 10% 30 0.2 3 in 1,000 Quantal [liver toxicity (fatty change)]

1,3-Dichloropropene (U.S. EPA 2002c) 0.72 10% 30 0.02 3 in 106a Quantal (hyperplasia of nasal epithelium)

Methyl methacrylate (U.S. EPA 1998e) 7.2 10% 10 0.7 8 in 10,000a Quantal (degeneration/atropy of olfactory 

epithelium)

Methylene diphenyl diisocyanate (U.S. EPA 1998g) 0.06 10% 100 0.0006 1 in 1,000 Quantal (hyperplasia of the olfactory epithelium)

Phosphoric acid (U.S. EPA 1995d) 3.4 10% 300 0.01 3 in 10,000 Quantal (bronchiolar fibrosis)

1,1,1,2-Tetrafluoroethane (U.S. EPA 1995a) 8,200 10% 100 80 1 in 1,000 Quantal (Leydig cell hyperplasia)

Benzeneb (U.S. EPA 2003) 8.2 1 SD 300 0.03 3 in 10,000 Continuous (decreased lymphocyte count)

Carbon disulfidec (U.S. EPA 1995c) 19.7 10% 30 0.7 3 in 1,000 Continuous (peripheral nervous system 

dysfunction)

Chromium VI (particulates)d (U.S. EPA 1998c) 0.034 10% 300 0.0001 — Continuous (lactate dehydrogenase in 

bronchioalveolar lavage fluid)

EGBE (U.S. EPA 1999b; NTP 1993) 380 5% 30 13 2 in 1,000 Continuous (changes in red blood cell count)

EGBE, ethylene glycol monobutyl ether.

aBecause IRIS assessment is based on sublinear dose–response curve, linearity was not assumed for low dose extrapolation, and risk estimate was derived from the BMC model

response function. bBMC was based on a BMR of 1-standard-deviation change from the control mean (in the absence of a clear definition for an adverse effect for this continuous end

point, a default BMR of 1-standard-deviation change from the control mean was selected). This default definition of a BMR for continuous end points corresponds to an excess risk of

approximately 10% for the proportion of individuals below the second percentile (or above the 98th percentile) of the control distribution for normally distributed effects. cA 10% relative

change was selected as an appropriate BMR for the nerve conduction velocity measurements because this level is about equal to a difference of 1 standard deviation from the control,

and because a change of about 10% would likely raise concern in a clinical setting. dInsufficient data available to estimate risk level (i.e., the response function, underlying distribution

of the end point, or mean response and standard deviation of the treatment group and controls were not provided).

Article | Castorina and Woodruff
logarithmic scale for these chemicals with linear or supralinear dose–response curves at the

BMD/BMC. For four RfD and RfC equivalent risk levels (for 3 compounds), we used the

sublinear dose–response model to calculate

risk at the RfD or RfC. These risk estimates

ranged from 3 in 1,000,000,000 to 1 in

100,000 from the oral route of exposure for

compounds with RfDs based on BMD values,

and from 3 in 1,000,000 to 8 in 10,000 from

inhalation for compounds with RfCs based on

BMC values (Tables 6 and 7).

Five of 21 reference values (24%) reviewed

for this assessment corresponded to estimated

risk levels greater than 1 in 1,000. Insufficient

information was available to estimate risk

from exposure at two reference values that

were based on continuous response data,

chromium VI particulates and naphthalene

(i.e., the response function, underlying distribution of the end point, or mean response and

standard deviation of the treatment group and

controls were not provided). Figure 4 presents

the distribution of estimated risk levels from

human exposures at established RfD and RfC

values for compounds with a linear or supralinear dose–response curve at the BMD. Risk

estimates for four assessments derived from

sublinear dose–response curves are presented

in Tables 6 and 7.

Among the chemicals for which the RfD

was based on a BMD, the BMD/BMDL ratio

ranged from 1.3 to 3.0. Among the chemicals

for which the RfC was based on a BMC, the

BMC/BMCL ratio ranged from 1.1 to 2.3

(Tables 1 and 3). Thus, using the central estimate of the BMD or BMC (maximum likelihood estimate) instead of the lower statistical

confidence limit (BMDL or BMCL) as the

point of departure would result in a 1- to

3-fold difference in the estimated risk levels

(Figures 2 and 3).

The effect level extrapolation factor (ELE)

is an UF analogous to the LOAEL-toNOAEL extrapolation factor. ELEs were

applied in the assessments of three compounds, 1,3-butadiene (RfC), benzene (RfC

and RfD), and ethylene glycol monobutyl

ether (RfC) (Tables 2 and 4) (U.S. EPA

1999b, 2002e, 2003). Thus, no ELE factor

was assigned for 16 of 17 assessments that

were based on a BMR of 10%.

When we compared the points of departure (i.e., BMDL/BMCL values) with the

NOAELs, we found that the points of departure were higher than the NOAELs in 10 of

the 14 studies with identified NOAELs

(Figure 5). The BMDL values were up to 4.6

times higher than the empirical NOAELs

(range, 0.5–4.6), and the BMCL values were

up to 3.9 times higher than the empirical

NOAELs (range, 0.2–3.9) (Tables 1 and 3).

Environmental Health Perspectives • VOLUME 111 | NUMBER 10 | August 2003 1323

1/10

1/100

1/1,000

1/10,000

1/100,000 Risk level (log scale)

Beryllium Chloroform DichloroethyleneTributyltin

oxide

Benzene Phenol EGBE Methyl mercury

Quantal data Continuous data

Chemical

Risk level based on BMDL

Risk level based on BMD

1/10

1/100

1/1,000

1/10,000

1/100,000 Risk level (log scale)

Butadiene Antimony trioxidePhosphoric acidMethylene

diphenyl

diisocyante

TetrafluoroethaneaCarbon

disulfidea

Quantal data Continuous data

Chemical

Risk level based on BMCL

Risk level based on BMC

DichloroethyleneBenzene EGBE

Figure 2. Estimated risk levels from exposure at the RfD based on the BMD and the BMDL derived from linear

or supralinear dose–response curves. EGBE, ethylene glycol monobutyl ether. 

Figure 3. Estimated risk levels from exposure at the RfC based on the BMC and the BMCL derived from linear

or supralinear dose–response curves. EGBE, ethylene glycol monobutyl ether. 

aBMC central estimate not provided by the U.S. EPA.

Figure 4. Distribution of estimated risk levels from

human exposures at established RfD and RfC values for reference doses derived from linear or

supralinear dose–response curves. 

aRisk estimates for assessments based on sublinear

dose–response curves are not included.

Figure 5. Ratio of the points of departure (PODs) to

empirically derived NOAELs. PODs based on benchmark modeling. 

6

5

4

3

2

1

No. of chemical assessments

0 1/10,000

Estimated risk levela

3/10,000 1/1,000 2–3/1,000 5/1,000

6

5

4

3

2

1

0

No. of chemicals

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

POD < NOAEL POD > NOAEL

Article | Reference values and risk
1324 VOLUME 111 | NUMBER 10 | August 2003 • Environmental Health Perspectives

Discussion

To determine whether U.S. EPA reference values represent negligibly small risk levels, we

reviewed and synthesized currently available

risk assessment information on chemicals for

which established RfD and RfC values are

based on BMD modeling. For RfDs and RfCs

derived from linear or supralinear dose–

response curves, our risk estimates ranged

from 1 in 10,000 to 5 in 1,000 for the oral

route of exposure, and from 1 in 10,000 to 3

in 1,000 for inhalation. Risk estimates for

RfDs and RfCs derived from sublinear

dose–response curves ranged from 3 in

1,000,000,000 to 8 in 10,000. Twenty-four

percent of reference values reviewed for this

assessment corresponded to estimated risk levels greater than 1 in 1,000. The estimated risk

of exposure to 1,1-dichloroethylene at its RfC,

for example, corresponded to a 3-in-1,000 risk

of adverse effect [liver toxicity (fatty change)].

The BMD methodology is the first step in

the development of continuous risk functions

that can be used to estimate risks at different

exposures rather than using an RfD/RfC

approach, which has limited use in the decision-making process. For example, BMD and

BMC values that are based on the same level

of adverse response (e.g., BMR = 10%) can be

used to rank the potential hazard of exposure

to multiple toxicants. Further application of

BMD models, such as has been done here,

can be used for estimating adverse noncancer

health outcomes from different exposures for

other risk-ranking exercises, regulatory policy

development, and cost/benefit analyses.

The U.S. EPA used a variety of fitted

models to calculate the BMD/BMC values

found in IRIS (e.g., K power, linear, quantallinear, exponential polynomial, and Weibull).

To compare RfD and RfC equivalent risk levels, we assumed that the dose–response curves

for the chemicals in our assessment group are

linear at doses below the point of departure.

This assumption could have resulted in both

underestimates and overestimates of risk. In

the case of a supralinear dose–response curve

at low doses, for example, this assumption

may have resulted in an underestimate of risk.

Among the chemicals we reviewed, 9 of the

21 assessments with sufficient information to

determine the shape of the dose–response

curve were based on supralinear functions. In

the case of a sublinear dose–response, this

assumption may have resulted in a marked

overestimate of risk. For the 5 assessments

based on sublinear dose–response curves,

therefore, we did not assume linearity for low

dose extrapolation and risk estimation.

We believe that the assumption of linearity in the relevant part of the dose–response

curve is justified and useful to compare risk

levels among this group of compounds.

Seventy-six percent of BMD and BMC values

considered in this assessment were derived

from dose–response data fitted to linear or

supralinear models. Furthermore, the range of

extrapolation for the RfD/RfC calculations

was not large among this group, with most

based on points of departure extrapolated to 2

orders of magnitude or less (7 were extrapolated to 1 order of magnitude, 13 were extrapolated to 2 orders of magnitude, and 3 were

extrapolated to 3 orders of magnitude). The

average and median composite UFs among

the compounds in our assessment are 340 and

100, respectively. This implies that even if the

dose–response curve for a particular compound is not strictly linear at much lower

doses, we could expect the potential impact on

the risk estimate to be relatively small.

Current U.S. EPA methodology for reference value derivation assumes that the established RfDs/RfCs represent negligibly small

risk levels. For assessments that have linear

dose–response curves, the extrapolation from

the point of departure is typically 2 orders of

magnitude or less. Therefore, for the RfD/RfC

values to represent risk levels that are below

regulatory concern, the dose–response curve

would have to drop off sharply after the point

of departure. This assumption seems unlikely,

especially given our finding that a large number

of the assessments we reviewed (9 of 21) were

based on supralinear dose–response functions.

Although this supralinearity may carry significant implications for risk assessment, more

research is needed to determine whether these

dose–response relationships remain supralinear

at very low doses. On the other hand, assessments based on dose–response curves that are

not monotonic may have sublinear or stepwise

relationships below the observed data.

Using the BMDL or BMCL as the point of

departure in the risk assessment of noncarcinogenic compounds rather than the BMD or

BMC central estimate is generally characterized

as a conservative assumption (in the health-protective sense). We found that using the central

estimate of the BMD (maximum likelihood

estimate) instead of the lower bound estimate as

the point of departure results in a 1- to 3-fold

difference in the risk estimates. According to

the U.S. EPA draft BMD guidelines (U.S.

EPA 2000a), a lower confidence limit is placed

on the BMD to obtain a dose (BMDL) that

assures with high confidence (e.g., 95%) that

the BMR is not exceeded. This process of

using the BMDL rewards better experimental

design and procedures that provide more precise estimates of the BMD, resulting in

tighter confidence intervals and thus BMDLs

that are closer to the central estimate. Our

results suggest that the current practice of

using the statistical lower bound estimate versus the maximum likelihood estimate as the

point of departure is reasonable and does not

substantially bias the risk estimate.

For carcinogens, the U.S. EPA typically

develops a linear estimate of the slope of the

dose–response curve, under the assumption

that the curve is linear at low doses. This

allows for quantification of risk at any given

level of exposure. The U.S. EPA has defined

1 in 1,000,000 excess cancer risk as a de minimis risk level for cancer (Caldwell et al. 1998;

Clean Air Act Amendments 1990; Fiori and

Meyerhoff 2002; U.S. EPA 1991), although

regulatory actions are sometimes limited to

instances where risk exceeds 1 in 100,000.

Among compounds in IRIS with RfDs and

RfCs based on BMD modeling, however, we

found risk estimates as great as 5 in 1,000.

Although noncancer outcomes may in some

instances be reversible and considered less

severe, this finding calls into question the

assumption that noncancer RfD and RfC values represent “acceptable levels” of exposure.

In addition, some of the noncancer health end

points considered in this assessment are severe

and irreversible events, for example, ovarian

atrophy (1,3-butadiene) and developmental

neuropsychologic impairment (methylmercury), highlighting the need for a renewed discussion within the public health community

about what should be considered an “acceptable level” of risk from exposure to toxicants

with noncancer health end points.

Most of the BMDLs and BMCLs used as

points of departure in IRIS are based on 10%

BMRs, many with values higher than the

empirically derived NOAELs. This research

should help inform discussions about whether

this level of BMR is adequately protective of

the public health, and whether human exposures at concentrations equal to the resulting

reference values do in fact represent negligibly

small risk levels.

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Article | Reference values and risk