Pesticide dose estimates for children of Iowa farmers and non-farmers.

Abstract

Farm children have the potential to be exposed to pesticides. Biological monitoring is often employed to assess this exposure; however, the significance of the exposure is uncertain unless doses are estimated. In the spring and summer of 2001, 118 children (66 farm, 52 non-farm) of Iowa farm and non-farm households were recruited to participate in a study investigating potential take-home pesticide exposure. Each child provided an evening and morning urine sample at two visits spaced approximately 1 month apart, with the first sample collection taken within a few days after pesticide application. Estimated doses were calculated for atrazine, metolachlor, chlorpyrifos, and glyphosate from urinary metabolite concentrations derived from the spot urine samples and compared to EPA reference doses. For all pesticides except glyphosate, the doses from farm children were higher than doses from the non-farm children. The difference was statistically significant for atrazine (p<0.0001) but only marginally significant for chlorpyrifos and metolachlor (p = 0.07 and 0.1, respectively). Among farm children, geometric mean doses were higher for children on farms where a particular pesticide was applied compared to farms where that pesticide was not applied for all pesticides except glyphosate; results were significant for atrazine (p = 0.030) and metolachlor (p = 0.042), and marginally significant for chlorpyrifos (p = 0.057). The highest estimated doses for atrazine, chlorpyrifos, metolachlor, and glyphosate were 0.085, 1.96, 3.16, and 0.34 microg/kg/day, respectively. None of the doses exceeded any of the EPA reference values for atrazine, metolachlor, and glyphosate; however, all of the doses for chlorpyrifos exceeded the EPA chronic population adjusted reference value. Doses were similar for male and female children. A trend of decreasing dose with increasing age was observed for chlorpyrifos.

Full text

Page 1

Environmental Research 105 (2007) 307–315
Pesticide dose estimates for children of Iowa farmers and non-farmers
Brian D. Curwina,?, Misty J. Heina, Wayne T. Sandersonb, Cynthia Strileyc, Dick Heederikd,
Hans Kromhoutd, Stephen J. Reynoldse, Michael C. Alavanjaf
aDivision of Surveillance, Hazard Evaluations and Field Studies, National Institute for Occupational Safety and Health, 4676 Columbia Parkway, MS R-14,
Cincinnati, OH 45226, USA
bDepartment of Occupational and Environmental Health, University of Iowa, Iowa City, IA, USA
cDivision of Applied Research and Technology, National Institute for Occupational Safety and Health, Cincinnati, OH, USA
dInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
eDepartment of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA
fDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
Received 29 November 2006; received in revised form 23 May 2007; accepted 4 June 2007
Available online 19 July 2007
Abstract
Farm children have the potential to be exposed to pesticides. Biological monitoring is often employed to assess this exposure; however,
the significance of the exposure is uncertain unless doses are estimated. In the spring and summer of 2001, 118 children (66 farm, 52 non-
farm) of Iowa farm and non-farm households were recruited to participate in a study investigating potential take-home pesticide
exposure. Each child provided an evening and morning urine sample at two visits spaced approximately 1 month apart, with the first
sample collection taken within a few days after pesticide application. Estimated doses were calculated for atrazine, metolachlor,
chlorpyrifos, and glyphosate from urinary metabolite concentrations derived from the spot urine samples and compared to EPA
reference doses. For all pesticides except glyphosate, the doses from farm children were higher than doses from the non-farm children.
The difference was statistically significant for atrazine (po0.0001) but only marginally significant for chlorpyrifos and metolachlor
(p ¼ 0.07 and 0.1, respectively). Among farm children, geometric mean doses were higher for children on farms where a particular
pesticide was applied compared to farms where that pesticide was not applied for all pesticides except glyphosate; results were significant
for atrazine (p ¼ 0.030) and metolachlor (p ¼ 0.042), and marginally significant for chlorpyrifos (p ¼ 0.057). The highest estimated doses
for atrazine, chlorpyrifos, metolachlor, and glyphosate were 0.085, 1.96, 3.16, and 0.34mg/kg/day, respectively. None of the doses
exceeded any of the EPA reference values for atrazine, metolachlor, and glyphosate; however, all of the doses for chlorpyrifos exceeded
the EPA chronic population adjusted reference value. Doses were similar for male and female children. A trend of decreasing dose with
increasing age was observed for chlorpyrifos.
r 2007 Elsevier Inc. All rights reserved.
Keywords: Pesticides; Exposure; Children; Dose; Biological monitoring; Urine; Herbicides; Insecticides
1. Introduction
Children of farmers have the potential to be exposed to
agricultural pesticides via the take-home pathway. That is,
farmers may inadvertently bring pesticides into the home
on their clothing and shoes, which can be deposited into
dust and onto surfaces or they may directly deposit
pesticides on their children if they handle their children
prior to washing. Children, especially children less than 6
years old, spend more time indoors and on the floors and
may be exposed via hand and object to mouth contact.
Black et al. (2005) observed an hourly median hand to
mouth contact frequency of 10–19 and an hourly median
object to mouth contact frequency of 6–18 for children
aged 7–53 months. Furthermore, farm children may have
the opportunity to be exposed to agricultural pesticides by
playing or working in treated fields, contact with treated
animals, contact with contaminated farm vehicles, equip-
ment or storage areas, and even through direct handling of
ARTICLE IN PRESS
www.elsevier.com/locate/envres
0013-9351/$-see front matter r 2007 Elsevier Inc. All rights reserved.
doi:10.1016/j.envres.2007.06.001
?Corresponding author. Fax: +15138414486.
E-mail address: bcurwin@cdc.gov (B.D. Curwin).

Page 2

pesticides. Parental occupation involving pesticide applica-
tion has been associated with childhood cancers (Daniels
et al., 1997; Flower et al., 2004; Zahm and Ward, 1998) and
household pesticide use has been associated with childhood
leukemia (Ma et al., 2002).
Several papers have been published investigating farm
children’s exposure to pesticides using biological monitor-
ing (Acquavella et al., 2004; Coronado et al., 2004; Curl
et al., 2002; Curwin et al., 2007; Fenske et al., 2000, 2002;
Koch et al., 2002; Loewenherz et al., 1997; Lu et al., 2000;
Thompson et al., 2003). However, only a few have
estimated pesticide dose to ascertain the potential health
significance of these exposures (Acquavella et al., 2004;
Fenske et al., 2000). Biological monitoring has the
advantage of aggregating exposures from all sources and
routes, a current requirement for pesticide health risk
assessment in the United States as mandated by the Food
Quality Protection Act of 1996 (FQPA, 1996). Biological
monitoring data are often collected in the form of urinary
metabolite concentrations. While this is useful, an estimate
of dose would be helpful in ascertaining the risk associated
with the urinary metabolite concentrations. Mage et al.
(2004) described an approach to estimating pesticide dose
from urinary metabolite concentration for adults and
suggested that a similar approach could be used for
children, provided that the appropriate equations are used
for predicting a child’s daily creatinine clearance rate.
The US Environmental Protection Agency (USEPA) sets
reference doses (RfD), which reflect dietary risk, for
pesticides during the registration process. The reference
dose is derived from animal toxicity studies and is generally
based on the most sensitive toxic endpoint (e.g. weight loss)
in the most appropriate animal model. Different routes,
such as oral and dermal, and duration of exposure are used
in the toxicity studies and a weight of evidence approach
may be taken when determining the RfD. The RfD
incorporates an uncertainty factor of 100 to account for
inter- and intra-species variability and, in response to the
FQPA, recent re-registration eligibility decisions have
incorporated an additional FQPA safety factor where
warranted. The FQPA has mandated that the EPA take
into consideration sensitive subpopulations when establish-
ing reference doses. Where toxicity data indicate a
subpopulation (e.g. children) may be more sensitive to a
pesticide, an additional safety factor up to 10 may be
incorporated into the reference dose. The additional safety
factor will depend on the endpoint of concern, the route of
exposure, and the degree of sensitivity. Such a reference
dose is called a population adjusted dose (PAD).
In 2001, a study was initiated in Iowa to investigate take-
home exposure among farm families. The results of
biological monitoring among these families have been
reported previously (Curwin et al., 2005, 2007). In this
paper, dose estimates for the children in the study have
ARTICLE IN PRESS
Table 1
EPA acute reference doses
Pesticide Acute RfDa
(mg/kg/day)
StudyToxicity endpoint
Atrazine10b
Developmental toxicity study in rat and rabbitDelayed ossification in fetuses; decreased body
weight gain in adults
Plasma cholinesterase inhibition
n/a
n/a
Chlorpyrifos
Metolachlor
Glyphosate
0.5b
n/ac
n/a
Acute blood time course study in male rats
n/a
n/a
aThe USEPA defines an acute RfD as an ‘‘estimate of a daily oral exposure for an acute duration (24h or less) to the human population (including
susceptible subgroups) that is likely to be without an appreciable risk of adverse health effects over a lifetime’’.
bDenotes a population adjusted reference dose (PAD) which incorporates an additional FQPA safety factor of 10.
cn/a, not available.
Table 2
EPA chronic reference doses
PesticideChronic RfDa
(mg/kg/day)
Study Toxicity endpoint
Atrazine 1.8b
Six-month LH surge study in ratAttenuation of preovulatory luteinizing
hormone (LH) surge
Plasma and red blood cell cholinesterase
inhibition
Chlorpyrifos0.03b
Weight of evidence from five studies: 2-year
dog, 90-day dog, 2-year rat, 90-day rat,
developmental neurotoxicity in rat
1 year toxicity study in dogs
Developmental toxicity study in rabbit
Metolachlor
Glyphosate
100
2000
Decreased body weight gain
Maternal death
aThe USEPA defines a chronic RfD as an ‘‘estimate of a daily oral exposure for a chronic duration (up to a lifetime) to the human population (including
susceptible subgroups) that is likely to be without an appreciable risk of adverse health effects over a lifetime’’.
bDenotes a population adjusted reference dose (PAD) which incorporates an additional FQPA safety factor of 10.
B.D. Curwin et al. / Environmental Research 105 (2007) 307–315
308

Page 3

been calculated from the urine concentrations in an effort
to determine the significance of the exposure levels
observed. The purpose of this paper was twofold: (1) to
calculate the dose estimates in children of farmers and non-
farmers in Iowa for four pesticides: atrazine, metolachlor,
chlorpyrifos, and glyphosate; and (2) to compare the dose
estimates to EPA reference values for each pesticide. The
acute and chronic reference doses and the studies and
endpoints used to derive them for the four pesticides
studied here can be found in Tables 1 and 2 (USEPA, 1993,
1995, 2002, 2003).
2. Methods
In the spring and summer of 2001, the children less than 16 years of age
of farmers and non-farmers residing in 10 counties in central, eastern
Iowa were recruited to participate in the study. Sixty-six farm children
(29 female and 37 male) and 52 non-farm children (20 female and 32 male)
were enrolled in the study. Participant recruitment has been described
previously (Curwin et al., 2002). In short, recruitment was conducted by
convenience sampling. To be eligible for the study, the non-farm families
had to live in a home on land that was not used for farming, and where
nobody in the household worked in agriculture or commercial pesticide
application. The non-farm families came from both rural and small town
environments. In some cases, the non-farm families lived near farms, but
as long as their land was not used for farming, they were eligible. The farm
families had to be using at least one of seven target pesticides—atrazine,
acetochlor, metolachlor, alachlor, chlorpyrifos, glyphosate, and 2,4-D.
The target pesticides were selected because of their extensive use in Iowa
agriculture and are among those most commonly used in Iowa. All of the
pesticides are corn or soybean herbicides, with the exception of
chlorpyrifos which is an insecticide used on corn. Only the results for
atrazine, metolachlor, chlorpyrifos, and glyphosate are reported due to
limitations of the analytical methods for the urine samples. The National
Institute for Occupational Safety and Health (NIOSH) Human Subject
Review Board approved this study.
Sample collection and analysis has been described previously (Curwin
et al., 2007). Briefly, the children were visited on two occasions and two
spot urine samples were collected by the participants: one in the evening
and the first void the following morning. For young children, a parent
collected the urine samples. The samples were stored in a cooler or
refrigerator until collected by research staff. Twenty-five milliliter aliquots
were stored on dry ice and shipped frozen to the NIOSH laboratory. The
total volume of each urine void was recorded. The metabolites or parent
compound of four pesticides—atrazine (atrazine mercapturate), chlorpyr-
ifos (3,5,6-trichloro2-pyridinol), metolachlor (metolachlor mercapturate),
and glyphosate (parent glyphosate)—were analyzed in the urine samples
using immunoassay techniques and reported in micrograms of pesticide
per liter of urine (mg/L). The limits of detection for atrazine mercapturate,
trichloropyridinol (TCP), metolachlor mercapturate, and glyphosate were
1.16, 3.32, 0.3, 0.9mg/L, respectively. Urinary creatinine was measured in
the urine samples using a commercially available enzyme slide technology
(Vitros 250 Chemistry System, Ortho-Clinical Diagnostics). Urine
pesticide concentrations by volume were normalized by creatinine to give
a concentration in micrograms of pesticide per gram of creatinine (mg/g).
2.1. Dose estimates
The absorbed daily dose (ADD) in micrograms of pesticide per
kilogram body weight per day (mg/kg/day) was calculated using formula
(1). The doses were calculated from spot urine samples collected on two
occasions and are assumed to represent daily dose:
ADDðmg=kg=dayÞ ¼ðCÞðCnÞðCFÞðRmwÞ
BW
,(1)
where C is the concentration of metabolite or pesticide in urine per gram
creatinine (mg/g), Cn is the calculated mass of creatinine excreted per day
(g/day), CF is a correction factor, Rmwis the ratio of parent pesticide and
pesticide metabolite molecular weights, and BW is the body weight (kg).
Since spot urine samples were collected from each subject, total daily
(24-h) excretion of creatinine (Cn) was calculated using the following
equation (adapted from Cockcroft and Gault, 1976):
?
? BSA ?
Cnðg=dayÞ ¼
CnER ? 1440 min=day
1:73
1g
1000mg,
?
ð2Þ
where Cn ER is the creatinine urinary excretion rate in mg/min per 1.73m2
body surface area and BSA is body surface area (m2).
The creatinine urinary excretion rate was calculated as a function of age
using the following equation from Shull et al. (1978)
CnER ¼ 0:035 ? ageðyearsÞ þ 0:236.
The Shull et al. formula, which averages male and female creatinine
excretion rates, was used for all children in the study, even those who had
reached puberty. After puberty, however, females with the same weight
and height as males of the same age would be expected to have diminished
creatinine excretion due to diminished muscle mass. Thus, the use of the
Shull relation implicitly makes a simplifying assumption by using an
average value for boys and girls after puberty.
BSA was calculated as a function of height and weight using the
following equation from Mosteller (1987)
?
BSA was estimated using the EPA Exposure Factors Handbook (1997) for
four farm children of unknown height.
Correction factors were used to account for incomplete excretion of the
pesticides in urine. Approximately 67% of atrazine is excreted via urine
(Timchalk et al., 1990) with atrazine mercapturate accounting for
approximately 80% of the excreted metabolites (Buchholtz et al., 1999)
resulting in a correction factor of (1/0.67)/0.8 ¼ 1.9. Approximately 50%
of metolachlor is excreted in urine (Davison et al., 1994); however,
estimates of the percentage of metolachlor mercapturate in urine were not
available. Metolachlor is structurally similar to alachlor and the
percentage of alachlor mercapturate in human urine has been shown to
range from 25% to 62% (Driskell et al., 1996). Using a conservative
estimate of 60% for the percentage of metolachlor mercapturate in urine
resulted in a correction factor of (1/0.5)/0.6 ¼ 3.3. For chlorpyrifos,
approximately 70% is excreted as TCP in urine (Nolan et al., 1984)
resulting in a correction factor of 1/0.7 ¼ 1.4. Finally, approximately 30%
of glyphosate is excreted via the urine with almost 100% excreted as
unchanged parent compound (Kennepohl and Munro, 2001) resulting in a
correction factor of (1/0.3)/1 ¼ 3.3.
The ratio of molecular weights (Rmw), calculated by dividing the
pesticide parent molecular weight by the pesticide metabolite molecular
weight, was 0.63, 0.69, 1.77, and 1.00 for atrazine, metolachlor,
chlorpyrifos, and glyphosate, respectively. This calculation assumes that
one molecule of the parent compound produces one molecule of the
metabolite. The ratio of molecular weights corrects for the differences in
mass between one molecule of the parent pesticide and one molecule of the
metabolite.
(3)
BSAðm2Þ ¼
htðcmÞ ? wtðkgÞ
3600
?0:5
. (4)
2.2. Data analysis
All statistical analyses were performed using SAS 9 Softwares(SAS
Institute Inc., Cary, NC). Data analysis methods needed to address two
primary concerns. First, since children from each household provided
evening and morning urine samples at two visits and multiple children
were sampled from each household, urinary pesticide concentrations could
not be treated as independent. A second concern was that urinary pesticide
concentrations were frequently below the analytical limit of detection
ARTICLE IN PRESS
B.D. Curwin et al. / Environmental Research 105 (2007) 307–315
309

Page 4

(LOD), particularly for atrazine, metolachlor, and glyphosate (Curwin
et al., 2007). Of the 417 urine samples obtained from children, only 20%
detected atrazine above the LOD, 61% detected metolachlor above the
LOD and 84% detected glyphosate above the LOD; however, nearly all
(n ¼ 416) samples detected chlorpyrifos above the LOD. Furthermore, the
laboratory did not censor urine samples below the LOD, rather, values
were reported as non-detect, a positive level below the LOD, or a level
greater than or equal to the LOD. Values reported below the LOD may be
within the error around a zero value and are not as reliable as values above
the LOD. Furthermore, these values are typically not reported as such,
rather they are usually reported as left-censored at the LOD. Methods are
commonly available for dealing with correlated data (i.e., mixed-effects
regression modeling) and highly censored data (i.e., maximum likelihood
estimation); however, methods are not readily available for dealing with
both of these problems at the same time.
Initially, maximum likelihood estimation via the LIFEREG procedure
in SAS was used to estimate geometric mean (GM) doses, adjusted for age
and sex, separately for farm and non-farm children. In the maximum
likelihood analysis, urinary metabolite concentrations reported as either a
non-detect or a positive level below the LOD were considered to be left-
censored at the LOD. The concentration for each urine void (identified by
child, visit, and time) was adjusted for creatinine and used to calculate an
estimated dose. Doses based on urinary metabolite concentrations
censored at the LOD were considered to be left-censored at the dose
level calculated using the LOD. The lognormal distribution was specified
as the underlying distribution. Since the LIFEREG procedure assumes
independence among the observations, standard errors were known to be
underestimated by the procedure; therefore, the LIFEREG procedure was
not used for significance testing.
Mixed-effects modeling via the MIXED procedure in SAS was used to
test whether the GM dose for farm children was significantly different
than the GM dose for non-farm children. The dependent variable was the
natural log transformed dose; fixed effects were household type, age, and
sex; and random effects were household and child nested within
household. To simplify the models, the average of the evening and
morning dose estimates was used as an estimate of dose for the visit.
In these models, urinary metabolite concentrations reported as a
positive level below the LOD were used to estimate pesticide dose (i.e.,
they were not censored at the LOD). For urinary metabolite concentra-
tions reported as a non-detect, the minimum positive concentration
divided by two was used to estimate pesticide dose. The mixed-effects
model was given by
lnðyijkÞ ¼ b0þ b1ðhousehold typeÞ þ b2ðsexÞ
þ b3ðageÞ þ giþ gjðiÞþ ?ijk,
ð5Þ
where yijkis the kth dose estimate for child j within household i, i ¼ 1–50,
j ¼ 1–ni, k ¼ 1–2, niis the number of children in household i, giis the
random effect for household, gj(i)is the random effect for child nested
within household, and eijkis the random error term. The model specified
separate covariance parameter estimates for farm and non-farm house-
holds. Results are presented as adjusted GMs by taking the antilog of the
adjusted log-transformed means. The covariance parameter estimates
from the mixed-effects models provided estimates of the between-
household, between-child, and within-child variance components. For
each child, a single dose estimate was obtained by averaging the individual
dose estimates for comparison to EPA reference doses.
In order to evaluate the accuracy of the immunoassay techniques used,
178 duplicate urine samples from 50 fathers of the children were analyzed
by enzyme-linked immunosorbent assay (ELISA) techniques (i.e., the
same immunoassay techniques used to analyze the children’s samples) and
also by high-performance liquid chromatography (HPLC)–tandem mass
spectrometry. The HPLC method has been described previously (Curwin
et al., 2005). Mixed-effects modeling was used to relate the urinary TCP
concentrations derived from HPLC to the concentrations derived from
ELISA and the observed relationship was used to correct the dose
estimates for potential bias due to ELISA method.
3. Results
Farm and non-farm households were similar with
respect to the number of children residing in the household
(median 2 children per household, range 1–4 children per
household). Approximately 60% of the children were
male. Children ranged from less than 1 year to 15 years
of age (median 7 years). The distributions of age, height,
and weight were similar for farm and non-farm children
(Table 3).
The estimated GM doses obtained using maximum
likelihood methods and mixed-effects modeling are pre-
sented in Table 4. The two methods produced similar
estimates for chlorpyrifos, which was expected since there
was little censoring for chlorpyrifos. Estimates for metola-
chlor and glyphosate, which saw considerable censoring,
were fairly close for the two methods. Estimates for
atrazine, which saw the greatest amount of censoring, were
similar for farm children, but approximately eight times
higher based on mixed-effects modeling compared to
maximum likelihood for non-farm children. Regardless of
the method used to estimate the GM, for all pesticides
except glyphosate, the GM dose for farm children was
higher than the GM dose for non-farm children. The
differencewas statistically
(po0.0001) but only marginally significant for chlorpyrifos
and metolachlor (p ¼ 0.07 and 0.10, respectively). Non-
farm children had slightly higher glyphosate doses, but the
difference was not statistically significant. When comparing
the children on farms where a particular pesticide was
applied versus farms where that pesticide was not applied,
the GM doses were higher for children where that pesticide
was applied for all pesticides except glyphosate. This result
was significant for atrazine (p ¼ 0.030) and metolachlor
(p ¼ 0.042), and marginally significant for chlorpyrifos
(p ¼ 0.057).
A trend of decreasing dose with increasing age for all
childrencombinedwas
(po0.0001); increasing age by 1 year was associated with
a ?4.0% change (95% confidence interval ?5.4% to
?2.6%) in the estimated GM chlorpyrifos dose. In a
categorical analysis, the estimated least-squares GM
significant foratrazine
observed forchlorpyrifos
ARTICLE IN PRESS
Table 3
Characteristics of the farm and non-farm children in the study
CharacteristicFarm children
(n ¼ 66)
Non-farm children
(n ¼ 52)
Male (%)
Age (years) median
(range)
Height (cm) median
(range)a
Weight (kg) median
(range)b
56
7.0 (o1–15.6)
62
7.2 (o1–15.7)
124 (61–178) 122 (79–175)
27.2 (7.3–63.5)22.7 (12.7–68.9)
aHeight information was missing for five farm children and one non-
farm child.
bWeight information was missing for one non-farm child.
B.D. Curwin et al. / Environmental Research 105 (2007) 307–315
310

Page 5

chlorpyrifos dose was significantly higher for children less
than 10 years of age (0.67mg/kg/day) when compared to
children 10 years or older (0.49mg/kg/day, po0.0001).
Trends were not observed with age for atrazine, metola-
chlor, and glyphosate. Pesticide doses were similar for male
and female children.
The highest dose estimates for farm children were 0.085,
1.96, 3.16, and 0.34mg/kg/day and the highest dose
estimates for non-farm children were 0.040, 1.36, 0.072,
and 0.33mg/kg/day for atrazine, chlorpyrifos, metolachlor,
and glyphosate, respectively (Table 4). No child had an
overall dose estimate that exceeded the EPA chronic
reference values for atrazine, metolachlor, and glyphosate;
however, every child’s overall dose estimate exceeded the
EPA population adjusted chronic reference value for
chlorpyrifos (Table 5). About 97% and 92% of the
estimated chlorpyrifos doses for farm and non-farm
children, respectively, exceeded the EPA general popula-
tion reference value of 0.3 (the reference dose not
incorporating the extra safety factor of 10 for sensitive
subpopulations) and 83% and 74% of farm and non-farm
children, respectively, exceeded the EPA population
adjusted acute reference value (Table 5).
Results of the analysis of the fathers’ urine samples
analyzed by HPLC and immunoassay were previously
reported (Curwin et al., 2005, 2007). When compared, TCP
concentrations based on the ELISA method were three–
four times higher compared to the HPLC method. The
observed relationship was given by
^CHPLC¼ ?1:05 þ 0:411 ? CELISA,
where CHPLCrepresents the concentration of chlorpyrifos
in the urine based on the HPLC method and CELISA
represents the concentration of chlorpyrifos in the urine
based on the ELISA method. This relationship was used to
correct the children’s chlorpyrifos doses based on ELISA.
The percentage of the corrected doses exceeding the EPA
reference values are provided in Table 5.
Estimates of the between-household, between-child,
and within-child variance components for the children’s
ARTICLE IN PRESS
Table 4
Geometric mean pesticide doses (mg/kg/day) for farm and non-farm children
Pesticide
household type
Number of Absorbed daily dose (mg/kg/day)
Homes Childrena
Samples% oLODb(%)Rangec
ML GMd
Mixed GMe
p-Value
Atrazine
Farm
Non-farm
25
25
65
51
235
180
74
88
0.002–0.085
0.000–0.040
0.013
0.008
0.011
0.001
o0.0001
Farm
Applied
Not applied
20
5
53
12
127
108
74
75
0.000–0.11
0.000–0.055
0.014
0.012
0.015
0.007
0.030
Chlorpyrifos
Farm
Non-farm
25
25
65
51
235
180
o10.27–1.96
0.24–1.36
0.67
0.58
0.68
0.57
0.071
0
Farm
Applied
Not applied
26 12
223
00.59–1.40
0.22–1.96
0.93
0.66
0.89
0.67
0.057
23 59
o1
Metolachlor
Farm
Non-farm
25
25
65
51
235
180
37
42
0.000–3.16
0.000–0.072
0.016
0.013
0.015
0.008
0.10
Farm
Applied
Not applied
7 17
48
40
195
10
43
0.008–6.30
0.000–3.09
0.038
0.014
0.030
0.013
0.042
18
Glyphosate
Farm
Non-farm
25
25
65
51
235
180
19
12
0.013–0.34
0.037–0.33
0.11
0.13
0.10
0.12
0.23
Farm
Applied
Not applied
17
8
40
25
98
137
16
20
0.001–0.33
0.003–0.64
0.11
0.11
0.090
0.11
0.32
aUrine samples were not provided for one farm and one non-farm child.
bPercent of samples with pesticide dose estimate censored at the limit of detection (LOD).
cFor farm and non-farm, range of overall dose (one per child averaged over both visits); for farm-applied and farm-not applied, range of dose for each
visit (one per child-visit).
dEstimated geometric mean (GM) dose based on maximum likelihood (ML) methods was adjusted for age and sex.
eEstimated GM dose and p-value for farm GM versus non-farm GM based on mixed-effect models with fixed effects of household type, age and sex, and
random effects of household and child within household.
B.D. Curwin et al. / Environmental Research 105 (2007) 307–315
311

Page 6

pesticide doses are provided in Table 6. Variance compo-
nents were computed for farm and non-farm children after
adjusting for age and sex. The within-child variance
components were generally higher than the other variance
components for both farm and non-farm children. The
between-child variance contributed relatively little to the
overall variance.
4. Discussion
The results presented here provide an indication of the
significance of pesticide exposure among farm children.
The doses were higher for farm children than non-farm
children and for children on farms where a particular
pesticide was applied than children on farms where that
pesticide was not applied for all the pesticides except
glyphosate. Glyphosate is used both agriculturally and
residentially which may explain why the doses were similar.
However, all of the dose estimates for atrazine, metola-
chlor, and glyphosate were well below the EPA chronic
reference value for these pesticides.
Of concern, however, were the dose estimates for
chlorpyrifos. All of the dose estimates for chlorpyrifos
were above the EPA population adjusted chronic reference
dose for children. The lowest estimated dose for chlorpyr-
ifos was 0.24mg/kg/day compared to the reference dose of
0.03mg/kg/day. The EPA reference dose for chlorpyrifos
wasbasedon ano-observable-adverse-effect-level
(NOAEL) of 30mg/kg/day and incorporates a safety factor
of 100 for inter- and intra-species variation and an
additional safety factor of 10 for all children and for
females between the ages of 13 and 50 years, both of which
are considered to be sensitive subpopulations. Addition-
ally, most of the estimated doses for farm and non-farm
children exceeded the general population chronic reference
dose without the additional safety factor and the popula-
tion adjusted acute reference value of 0.5mg/kg/day. None
of the dose estimates exceeded the general population acute
reference dose or the NOAEL.
It is probable that the chlorpyrifos doses were over-
estimated as a result of direct exposure to TCP, a
metabolite of chlorpyrifos; however, the calculated chlor-
pyrifos doses assume that the TCP excreted in urine came
entirely from chlorpyrifos exposure. TCP was observed in
100% of dust and wipe samples and in greater than 95% of
food and air samples in a study investigating chlorpyrifos
exposure among pre-school children (Morgan et al., 2005).
Chlorpyrifos was also found in these media, and generally
in higher amounts, except in food where TCP was found to
be 12 times higher than chlorpyrifos. Wilson et al. (2003) in
another study of pre-school children, conclude that the
estimated intake of TCP from food can account for all of
the TCP found in the children’s urine. However, the
children were not from farm environments so chlorpyrifos
ARTICLE IN PRESS
Table 5
Percent of children with estimated dose exceeding reference valuesa
Reference valueb
Atrazine Chlorpyrifos MetolachlorGlyphosate
Farm
(%)
Non-farm
(%)
Farm (%)Non-farm
(%)
Farm
(%)
Non-farm
(%)
Farm
(%)
Non-farm
(%)
NOAEL
Acute RfD
Acute PAD
Chronic RfD
Chronic PAD
0
0
0
0
0
0
0
0
0
0
0 (0)c
0 (0)
83 (3)
97 (31)
100 (100)
0 (0)
0 (0)
74 (2)
92 (14)
100 (100)
0
n/ad
n/a
0
n/a
0
n/a
n/a
0
n/a
0
n/a
n/a
0
n/a
0
n/a
n/a
0
n/a
aOverall estimated dose based on the average of the available dose estimates for each child.
bNOAEL, no observable adverse effect level; RfD, reference dose; PAD, population adjusted reference dose.
cPercents in parentheses used the corrected dose estimates.
dn/a, not available.
Table 6
Within- and between-household variance components for children’s
pesticide doses
Pesticide
household type
Estimated variance componentsa
Between-
household
Between-childWithin-child
^ s2
bh
%b
^ s2
bc
%
^ s2
wc
%
Atrazine
Farm
Non-farm
0.54
3.36
17
33
0
0
0
0
2.64
6.76
83
67
Chlorpyrifos
Farm
Non-farm
0.091
0.066
52
44
0.0015
0.017
10.081
0.069
47
4511
Metolachlor
Farm
Non-farm
1.16
1.36
39
51
0.35
0
12
0
1.45
1.33
49
49
Glyphosate
Farm
Non-farm
0.45
0.13
42
30
0
0
0
0
0.61
0.31
58
70
aVariance components ð^ s2
natural log transformed doses using a mixed-effects model with fixed
effects of household type, age and sex, and random effects of household
and child within household. The model specified separate covariance
parameter estimates for farm and non-farm households.
b% denotes the proportion of the total variance.
bh; ^ s2
bc; ^ s2
wcÞ were estimated by modeling the
B.D. Curwin et al. / Environmental Research 105 (2007) 307–315
312

Page 7

exposures were much lower than TCP exposures. Direct
TCP exposure is probably accounting for some of the TCP
in the children’s urine in this study but to what extent is
unclear.
The chlorpyrifos doses may also be overestimated due to
the ELISA analytical method used to determine TCP
concentration in urine. If a bias exists with the ELISA
method, resulting in higher urinary TCP concentrations,
than the calculated doses would also be higher. The
observed relationship between HPLC and ELISA for the
fathers’ urine samples was used to ‘‘correct’’ the ELISA
concentrations for the children’s urine samples which
resulted in estimated doses for chlorpyrifos that were
much lower. Using the adjusted concentrations, the
percentage of farm children with doses exceeding the acute
PAD, chronic, and chronic PAD reference values was 3%,
31%, and 100%, respectively. Similarly, the percent of
non-farm children with doses exceeding the acute PAD,
chronic, and chronic PAD reference doses was 2%, 14%,
and 100%, respectively. Thus, 100% of the children had
doses exceeding the chronic PAD dose based on the
corrected urinary metabolite concentrations, but the
percent of children exceeding the acute PAD and chronic
reference doses was much reduced. This potential upward
bias of the ELISA method was not explored for the other
pesticides in this paper. However, all of the estimated doses
for the other pesticides were below all of the reference
values; therefore, correcting the estimated doses downward
would not change this result.
Fenske et al. (2000) found that 56% of estimated
azinphos-methyl doses for children of agricultural workers
exceeded the EPA reference dose, while 44% of the doses
for non-agricultural children exceeded the reference dose.
Values were much lower for phosmet where less than 10%
exceeded the EPA reference dose. Additionally, single day
dose estimates were calculated for azinphos-methyl and
26% exceeded the EPA acute reference dose. None of the
estimates exceeded the empirically derived NOAEL for
these compounds. The authors concluded that the results
indicated that children in agricultural communities have
pesticide exposures of regulatory concern.
Fenske’s results appear to contrast with our results. Our
study would indicate, with the exception of chlorpyrifos,
that children in agricultural communities may not have
exposures of regulatory concern at least for atrazine,
metolachlor, and glyphosate. It should be noted that
Fenske’s doses were derived by summing two urinary
metabolites that are common to organophosphate expo-
sure in general and are not specific to azinphos-methyl and
phosmet. As a result, it is possible that they overestimated
the dose for these pesticides. Acquavella et al. (2004)
observed results similar to ours in that none of their
estimated doses for glyphosate exceeded the EPA chronic
reference dose.
An interesting result was the trend of decreasing dose
with increasing age for chlorpyrifos; in particular, doses
were higher among children under the age of 10 years.
Creatinine excretion is known to be positively associated
with age among children (Barr et al., 2005). In our study,
the amount of creatinine excreted per day was estimated
from body surface area, which in turn was estimated from
height and weight, which are both positively associated
with age among children. Since body weight increases
substantially as a child gets older, the normalized pesticide
dose per kilogram body weight for a given urinary
metabolite concentration is reduced. Therefore, the trend
observed here may be partly an artifact of how the doses
were estimated. Urinary metabolite concentrations among
the children were negatively associated with age, but the
associations were not significant (Curwin et al., 2007).
However, it seems probable that younger children would
have a higher dose for a given exposure than older children.
Black et al. (2005) observed that the time children spent
playing on the floor decreased with increasing age and that
infants had the highest frequency of mouthing behavior.
To better determine the effect of age on dose, 24-h urine
samples should be collected over several days.
There are several limitations in our pesticide dose
estimates that are common to the estimation of doses from
spot urinary metabolite concentrations. First, it was
assumed that the spot urine samples were representative
of average daily pesticide excretion and that the doses
estimate average daily doses. Depending on the timing of
the urine collection with respect to pesticide application in
the farm homes, the doses may be overestimated. Urine
samples were not collected in the fall and winter months.
Presumably, the urine concentrations would be lower
during these months and therefore the average daily dose
over a year could be lower. Second, the merits of creatinine
adjustment for spot urine samples are being debated,
especially in children (Barr et al., 2005; Boeniger et al.,
1993). Lastly, it was assumed that the amount of pesticide
metabolite excreted in urine was equivalent to an absorbed
pesticide dose. However, chlorpyrifos doses due to
chlorpyrifos exposure are probably overestimated due to
direct exposure to TCP. Further, all the doses may
underestimate exposure if the percentage of metabolite
excreted in urine used to derive the correction factors is
lower and conversely the dose would be overestimated if
the percents excreted where higher. The correction factors
were derived from the best estimate of the amount of
metabolite excreted in urine from the current literature.
5. Conclusion
Farm children generally had higher pesticide dose
estimates than non-farm children. However, with the
exception of chlorpyrifos, all the estimates were below
EPA chronic and acute reference doses. All chlorpyrifos
dose estimates for both farm and non-farm children were
above the EPA population adjusted chronic reference dose
and most were above the population adjusted acute
reference dose and are of concern. Estimation of pesticide
dose from farm children’s urine samples allows comparison
ARTICLE IN PRESS
B.D. Curwin et al. / Environmental Research 105 (2007) 307–315
313

Page 8

to EPA reference doses and therefore provides an indica-
tion of the significance of pesticide exposure. Additional
longitudinal studies which better estimate daily pesticide
doses over the course of a year are needed to truly
determine the health significance of pesticide exposures.
Disclaimer
The findings and conclusions in this paper are those of
the authors and do not necessarily represent the views of
the National Institute for Occupational Safety and Health.
References
Acquavella, J.F., Alexander, B.H., Mandel, J.S., Gustin, C., Baker, B.,
Chapman, P., 2004. Glyphosate biomonitoring for farmers and their
families: results from the farm family exposure study. Environ. Health
Perspect. 112 (3), 321–326.
Barr, D.B., Wilder, L.C., Caudill, S.P., Gonzales, A.J., Needham, L.L.,
Pirkle, J.L., 2005. Urinary creatinine concentrations in the US
population: implications for urinary biologic monitoring measure-
ments. Environ. Health Perspect. 113, 192–200.
Black, K., Shalat, S.L., Freeman, N.C.G., Jimenez, M., Donnelly, K.C.,
Calvin, J.A., 2005. Children’s mouthing and food-handling behavior in
an agricultural community on the US/Mexico border. J. Exp. Anal.
Environ. Epidemiol. 15 (3), 244–251.
Boeniger, M.F., Lowry, L.K., Rosenburg, J., 1993. Interpretation of urine
results used to assess chemical exposure with emphasis on creatinine
adjustments: a review. Am. Ind. Hyg. Assoc. J. 54, 615–627.
Buchholtz, B.A., Fultz, E., Haack, K.W., Vogel, J.S., Gilman, S.D., Gee, S.J.,
et al., 1999. HPLC accelerator MS measurement of atrazine metabolites in
human urine after dermal exposure. Anal. Chem. 71, 3519–3525.
Cockcroft, D.W., Gault, M.H., 1976. Prediction of creatinine clearance
from serum creatinine. Nephron. 16, 31–41.
Coronado, G.D., Thompson, B., Strong, L., Griffith, W.C., Islas, I., 2004.
Agricultural task and exposure to organophosphate pesticides among
farmworkers. Environ. Health Perspect. 112 (2), 142–147.
Curl, C.L., Fenske, R.A., Kissel, J.C., Shirai, J.H., Moate, T.F., Griffith, W.,
et al., 2002. Evaluation of take-home organophosphorus pesticide
exposure among agricultural workers and their children. Environ. Health
Perspect. 110 (12), A787–A792.
Curwin, B.D., Sanderson, W.T., Reynolds, S.J., Hein, M.J., Alavanja, MC.,
2002. Pesticide use and practices in an Iowa farm family pesticide exposure
study. J. Agric. Saf. Health 8 (4), 423–433.
Curwin, B.D., Hein, M.J., Sanderson, W.T., Barr, D.B., Heederik,
D., Reynolds, S.J., et al., 2005. Urinary and hand wipe pesticide levels
among farmers and non- farmers in Iowa. J. Exp. Anal. Environ.
Epidemiol. 15 (6), 500–508 (Online 20 April 2005).
Curwin, B.D., Hein, M.J., Sanderson, W.T., Striley, C., Heederik,
D., Kromhout, H., et al., 2007. Urinary pesticide concentrations
among children, mothers, and fathers living in farm and non-farm
households in Iowa. Ann. Occup. Hyg. 51 (1), 53–65 (online September
19, 2006).
Daniels, J.L., Olshan, A.F., Savitz, D.A., 1997. Pesticides and childhood
cancers. Environ. Health Perspect. 105 (10), 1068–1077.
Davison, K.L., Larsen, G.L., Feil, V.J., 1994. Comparative metabolism
and elimination of acetanilide compounds by rat. Xenobiotica 24 (10),
1003–1012.
Driskell, W.J., Hill, R.H., Sheally, D.B., Hull, R.D., Hines, C.J., 1996.
Identification of a major urinary metabolite of alachlor by LC-MS/
MS. Bull. Environ. Contam. Toxicol. 156, 853–859.
Fenske, R.A., Kissel, J.C., Lu, C., Kalman, D.A., Simcox, N.J., Allen, E.H.,
et al., 2000. Biologically based pesticide dose estimates for children
in an agricultural community. Environ. Health Perspect. 108 (6),
515–520.
Fenske, R.A., Lu, C., Barr, D., Needham, L., 2002. Children’s exposure to
chlorpyrifos and parathion in an agricultural community in central
Washington State. Environ. Health Perspect. 110 (5), 549–553.
Flower, K.B., Hoppin, J.A., Lynch, C.F., Blair, A., Knott, C., Shore, D.L.,
et al., 2004. Cancer risk and parental pesticide application in children of
Agricultural Health Study participants. Environ. Health Perspect. 112
(5), 631–635.
Food Quality Protection Act, 1996. Public Law, pp. 104–170.
Kennepohl, E., Munroe, I.C., 2001. Phenoxy herbicides (2,4-D). In:
Krieger, R. (Ed.), Handbook of Pesticide Toxicology, second ed.
Academic Press, San Diego, CA.
Koch, D., Lu, C., Fisker-Anderson, J., Jolley, L., Fenske, R.A., 2002.
Temporal association of children’s pesticide exposure and agricultural
spraying: report of a longitudinal biological monitoring study.
Environ. Health Perspect. 110 (8), 829–833.
Loewenherz, C., Fenske, R.A., Simcox, N.J., Bellamy, G., Kalman, D.,
1997. Biological monitoring of organophosphorus pesticide exposure
among children of agricultural workers in central Washington State.
Environ. Health Perspect. 105 (12), 1344–1353.
Lu, C., Fenske, R.A., Simcox, N.J., Kalman, D., 2000. Pesticide exposure
of children in an agricultural community: Evidence of household
proximity to farmland and take-home exposure pathways. Environ.
Res. 84, 290–302.
Ma, X., Buffler, P.A., Gunier, R.B., Dahl, G., Smith, M.T., Reinier, K.,
et al., 2002. Critical windows of exposure to household pesticides and
risk of childhood leukemia. Environ. Health Perspect. 110 (9),
955–960.
Mage, D.T., Allen, R.H., Gondy, G., Smith, W., Barr, D.B., Needham, L.L.,
2004. Estimating pesticide dose from urinary pesticide concentration data
by creatinine correction in the Third National Health and Nutrition
Examination Survey (NHANES-III). J. Exp. Anal. Environ. Epidemiol.
14 (6), 457–465.
Morgan, M.K., Sheldon, L.S., Croghan, C.W., Jones, P.A., Robertson, G.L.,
Chuang, J.C., et al., 2005. Exposure of preschool children to
chlorpyrifos and its degradation product 2,3,6-trichloro-2-pyridinol in
their everyday environments. J. Exp. Anal. Environ. Epidemiol. 15 (4),
297–309.
Mosteller, R.D., 1987. Simplified calculation of body surface area.
N. Engl. J. Med. 317, 1098 (letter).
Nolan, R.J., Rick, D.L., Freshour, N.L., Saunders, J.H., 1984.
Chlorpyrifos: pharmacokinetics in human volunteers. Toxicol. Appl.
Phamacol. 73 (1), 8–15.
SAS Institute Inc., 2004. SAS/STATs9.1 User’s Guide. SAS Institute
Inc., Cary, NC.
Shull, B.C., Haughey, D., Koup, J.R., Ballah, T., Li, P.K., 1978. A useful
method for predicting creatinine clearance in children. Clin. Chem. 24
(7), 1167–1169.
Thompson, B., Coronado, G.D., Grossman, J.E., Puschel, K., Solomon, C.C.,
Islas, I., et al., 2003. Pesticide take-home pathway among children of
agricultural workers: study design, methods, and baseline findings. J.
Occup. Environ. Med. 45, 42–53.
Timchalk, C., Drysga, M.D., Langvardt, P.W., Kastl, P.E., Osborne, D.W.,
1990. Determination of the effect of triphane on the pharmacokinetics
of [14C]-atrazine following oral administration to male Fischer 344 rats.
Toxicology 61, 27–40.
USEPA, 1993. Reregistration Eligibility Decision for Glyphosate EPA
738-R-93-014. Health Effects Division, Office of Pesticide Programs,
US Environmental Protection Agency, Washington, DC.
USEPA, 1995. Reregistration Eligibility Decision for Metolachlor EPA
738-R-95-006. Health Effects Division, Office of Pesticide Programs,
US Environmental Protection Agency, Washington, DC.
USEPA, 1997. Exposure Factors Handbook: Volume 1-General Factors.
EPA/600/P-95/002Fa. Office of Research and Development, National
Center for Environmental Assessment, US Environmental Protection
Agency, Washington DC.
USEPA, 2002. Interim Reregistration Eligibility Decision for Chlorpyrifos
(Case No. 0100) EPA 738-R-01-007. Health Effects Division, Office of
ARTICLE IN PRESS
B.D. Curwin et al. / Environmental Research 105 (2007) 307–315
314

Page 9

Pesticide Programs, US Environmental Protection Agency, Washing-
ton, DC.
USEPA,2003. InterimReregistration
Atrazine (Case No. 0062). Health Effects Division, Office of Pesti-
cide Programs, US Environmental Protection Agency, Washington,
DC.
EligibilityDecision for
Wilson, N.K., Chuang, J.C., Lyu, C., Menton, R., Morgan, M.K., 2003.
Aggregate exposures of nine preschool children to persistent organic
pollutants at day care and home. J. Exp. Anal. Environ. Epidemiol. 13
(3), 187–202.
Zahm, S.H., Ward, M.H., 1998. Pesticides and childhood cancer. Environ.
Health Perspect. 106 (Suppl. 3), 893–908.
ARTICLE IN PRESS
B.D. Curwin et al. / Environmental Research 105 (2007) 307–315
315