Urinary pesticide concentrations among children, mothers and fathers living in farm and non-farm households in iowa.

Abstract

In the spring and summer of 2001, 47 fathers, 48 mothers and 117 children of Iowa farm and non-farm households were recruited to participate in a study investigating take-home pesticide exposure. On two occasions approximately 1 month apart, urine samples from each participant and dust samples from various rooms were collected from each household and were analyzed for atrazine, metolachlor, glyphosate and chlorpyrifos or their metabolites. The adjusted geometric mean (GM) level of the urine metabolite of atrazine was significantly higher in fathers, mothers and children from farm households compared with those from non-farm households (P < or = 0.0001). Urine metabolites of chlorpyrifos were significantly higher in farm fathers (P = 0.02) and marginally higher in farm mothers (P = 0.05) when compared with non-farm fathers and mothers, but metolachlor and glyphosate levels were similar between the two groups. GM levels of the urinary metabolites for chlorpyrifos, metolachlor and glyphosate were not significantly different between farm children and non-farm children. Farm children had significantly higher urinary atrazine and chlorpyrifos levels (P = 0.03 and P = 0.03 respectively) when these pesticides were applied by their fathers prior to sample collection than those of farm children where these pesticides were not recently applied. Urinary metabolite concentration was positively associated with pesticide dust concentration in the homes for all pesticides except atrazine in farm mothers; however, the associations were generally not significant. There were generally good correlations for urinary metabolite levels among members of the same family.

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Urinary Pesticide Concentrations among
Children, Mothers, and Fathers living in Farm
and Non-Farm Households in Iowa

Brian Curwin, Misty Hein, Wayne Sanderson, Cynthia Striley, Dick Heederik, Hans
Kromhout, Stephen Reynolds, Michael Alavanja

Annals of Occupational Hygiene (in press)

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Abstract
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
In the spring and summer of 2001, 47 fathers, 48 mothers and 117 children of Iowa farm
and non-farm households were recruited to participate in a study investigating take-
home pesticide exposure. On two occasions approximately one month apart, urine
samples from each participant and dust samples from various rooms were collected
from each household and were analyzed for atrazine, metolachlor, glyphosate and
chlorpyrifos or their metabolites. The adjusted geometric mean (GM) level of the urine
metabolite of atrazine was significantly higher in fathers, mothers and children from
farm households compared to those from non-farm households (p = <0.0001). Urine
metabolites of chlorpyrifos were significantly higher in farm fathers (p = 0.02) and
marginally higher in farm mothers (p = 0.05) when compared to non-farm fathers and
mothers, but metolachlor and glyphosate levels were similar between the two groups.
GM levels of the urinary metabolites for chlorpyrifos, metolachlor and glyphosate were
not significantly different between farm children and non-farm children. Farm children
had significantly higher urinary atrazine and chlorpyrifos levels (p = 0.03 and p = 0.03
respectively) when these pesticides were applied by their fathers prior to sample
collection than those of farm children where these pesticides were not recently applied.
Urinary metabolite concentration was positively associated with pesticide dust
concentration in the homes for all pesticides except atrazine in farm mothers, however
the associations were generally not significant. There were generally good correlations
for urinary metabolite levels among members of the same family.

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Introduction
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
Children and spouses of farmers are potentially exposed to pesticides indirectly by take-
home contamination; pesticides can be tracked into farm homes on the clothing and
shoes of farmers. Farmers are the biggest users of pesticides applying approximately
540 million kilograms in 1999 in the United States; herbicides accounted for the largest
proportion of this amount with approximately 240 million kilograms applied (USEPA
2002a). Concern for pesticide exposure among the children of farmers and farm
workers was raised by the National Institute for Occupational Safety and Health
(NIOSH) with the Report to Congress on Workers’ Home Contamination Study
Conducted Under the Workers’ Family Protection Act (29 U.S.C. 671a) (NIOSH 1995).
The Natural Resources Defense Council (NRDC) considers pesticides to be one of the
top five environmental threats to children’s health and considers farm children to be the
most highly pesticide-exposed subgroup in the United States. (NRDC 1998).

Although the literature is inconclusive, pesticide exposure is thought to be associated
with a variety of health effects including cancer, reproductive disorders, neurotoxicity,
and endocrine disruption (Alavanja et al. 2004; Dich et al. 1997; Kirkhorn and Schenker
2002; Maroni and Fait 1993; Richter and Chlamtac 2002; Zahm et al. 1997). More
specifically, phenoxy herbicides (e.g. 2,4-D) have been associated with a number of
cancers including soft tissue sarcomas, non-Hodgkin’s lymphoma (NHL), stomach,
colon and prostate; triazine herbicides (e.g. atrazine) have been associated with ovarian
cancer; and organophosphate insecticides (e.g. chlorpyrifos) have been associated with
delayed neuropathy, chromosome aberrations, central nervous system alterations and
NHL (Maroni and Fait 1993). Further, parental occupation involving pesticide

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B.D. Curwin

application has been associated with childhood cancers (Daniels et al. 1997; Flower et
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
al. 2004; Zahm and Ward 1998) and household pesticide use has been associated with
childhood leukemia (Ma et al. 2002).

Differences in children’s physiology, behavior patterns and hygiene may result in
significantly greater exposures to environmental contaminants than adults (Bearer 1995;
Health Council of the Netherlands 2004; National Academy of Sciences 1993). Small
children spend much of their time on the floor or ground and are very likely to come
into contact with pesticide residues on carpets or uncovered floors when playing inside,
and yard dirt when playing outside (Renwick 1998). These factors can result in
different sources and levels of pesticide exposure for children than adults in the same
scenario (Garry 2004). Children may also be more susceptible than adults to the toxic
effects of pesticides, due to the sensitivity of developing organ systems. Older children,
through their increased mobility and ability to assist with farm work, may have
opportunities for direct contact with pesticide products. Although the public health
importance of preventing injury to farm families has been well-recognized, the hazards
of exposure to pesticides and other chemicals to families in the farm environment have
received relatively little attention.

A study was initiated to investigate agricultural pesticide contamination inside farm
homes and family exposure to agricultural pesticides (Curwin et al. 2002, 2005a,
2005b). The goal of this study was to evaluate pesticide exposure among farm families
and compare their exposure to non-farm controls. The objectives presented in this paper
were twofold: 1) to measure urinary pesticide levels among farm and non-farm families

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B.D. Curwin

in Iowa and 2) to ascertain what factors may influence these levels.
Take-home pesticide exposure among farm families: Urinary pesticide concentrations

Methods
In Iowa in the spring and summer of 2001, farm and non-farm households were
recruited to participate in the study. Participant recruitment has been described in more
detail previously (Curwin et al. 2002). In short, recruitment was conducted by
convenience sampling. To be eligible for the study, households had to have at least one
child under the age of 16 years. Non-farm households had to be on land that was not
used for farming, and nobody in the household could be working in agriculture or
commercial pesticide application. Farm households 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. All of the pesticides are corn or soybean herbicides, with the
exception of chlorpyrifos which is an insecticide used on corn. Twenty-five farm
households (24 fathers, 24 mothers and 66 children (29 female and 37 male)) and 25
non-farm households (23 fathers, 24 mothers, and 51 children (19 female and 32 male))
were enrolled in the study. Only the results for atrazine, metolachlor, chlorpyrifos and
glyphosate are reported to due to limitations of analytical methods for the other
pesticides in urine (e.g. cross reactivity with other chemicals, poor analytical methods).
NIOSH Human Subject Review Board approved this study.

Sample Collection
During May – August, 2001, each household was visited on two occasions. The first
visit was shortly after a pesticide application event (within 1-5 days) and the second

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visit was approximately 4 weeks later (average 4 weeks, range 3-5 weeks). Two spot
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
urine samples were collected from the participants at each visit, one in the evening on
the day of the visit and one the following morning. Urine samples were collected in 500
mL Nalgene® bottles and participants were asked to store the urine in their refrigerator
or in a provided cooler with ice packs. Samples were collected the day after the visit
and 25 mL aliquots were removed, stored on dry ice and shipped to the laboratory. The
total volume of each urine void was recorded. Dust sample collection and analysis has
been described previously (Curwin et al. 2005a). Briefly, dust samples were collected
at each visit from various rooms in the homes using the HVS3 vacuum sampler
(Cascade Stamp Sampling Systems (CS3) Inc., Sandpoint, ID) according to the
American Society for Testing Material (ASTM) Standard Practice for Collection of
Dust from Carpeted Floors for Chemicals (ASTM 2000).

A questionnaire was administered to all participants at the first visit and re-administered
at the second visit. Questions were asked about crops grown, use of personal protective
equipment (PPE), crop size, pesticides used, dates and hours of application, who applied
the pesticide, and the number of acres applied. This information was gathered from the
start of the 2001 growing season until the second visit, and generally reflected the early
2001 growing season among the participants. Information on children’s age, weight,
height and sex was also collected.

Sample Analysis
The metabolites of 4 pesticides – atrazine (atrazine mercapturate), chlorpyrifos (3,5,6-
trichloro-2-pyridinol (TCP)), metolachlor (metolachlor mercapturate), and glyphosate

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(parent glyphosate) – were analyzed in urine samples using immunoassay techniques.
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
The analytical limits of detection (LOD) varied by analyte and were 1.16, 3.32, 0.3, and
0.9 µg/L for atrazine mercapturate, TCP, metolachlor mercapturate, and glyphosate
respectively. Urinary creatinine was measured using a commercially-available enzyme
slide technology (Vitros 250 Chemistry System, Ortho-Clinical Diagnostics, Raritan,
NJ).

Immunoassay for Atrazine (A00071) RaPID Assay® enzyme-linked immunosorbent
assay (ELISA) kit (Strategic Diagnostics, Newtown, PA) was used to determine the
metabolite atrazine mercapturate according to the manufacturer’s instructions with the
following exception: calibration standards (0.0, 0.1, 0.5, 1.0, 2.0, and 5.0 ppb) were
prepared by fortifying pooled urine from anonymous volunteers diluted 1:10 with
UriSub (CST Technologies Inc., Great Neck, NY) with synthesized atrazine
mercapturate. All participant urine samples were diluted 1:10 with UriSub.

A previously published immunoassay for TCP (A00208) RaPID Assay® ELISA
(Strategic Diagnostics, Newtown, PA) was used to determine the urinary metabolite of
chlorpyrifos (MacKenzie et al. 2000) according to the manufacturer’s instructions with
the following exception: calibration standards (0.0, 0.0156, 0.3125, 0.625, 1.25, 2.5, 5.0,
and 10.0 ppb) were prepared by fortifying UriSub with 3,5,6 trichloro-2-pyridinol. All
participant urine samples were diluted 1:10 with UriSub. In addition, each sample was
treated with 20 µL of β-glucuronidase (Roche Diagnostics, Part# 1-585-665,
Mannheim, Germany) for 30 minutes at room temperature prior to analysis in order to
cleave 3,5,6 trichloro-2-pyridinol from its glucuronide conjugate form.

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Glyphosate and metolachlor mercapturate were measured simultaneously in urine using
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
a newly developed fluorescence covalent microbead immunoassay (FCMIA) (Biagini et
al. 2004). Pesticide-protein conjugates for each of the pesticides were coupled to
separate addressable sets of microbeads. The conjugate coupled microbeads were then
used in a competitive assay for the pesticides. The pesticide in solution competed with
the bead-bound conjugate for fluorescently labeled anti-pesticide antibodies. Thus
increasing concentrations of a given pesticide in urine resulted in decreasing
fluorescence signals from the microbead for that pesticide. The coupling of different
pesticide conjugates to separate addressable sets of microbeads allows simultaneous
measurement of the two pesticides. Calibration standards (0.0, 0.1, 0.3, 1.0, 3.0, 10.0,
30.0, 100, and 300 ppb) were prepared. Pooled urine diluted 1:10 in a mixture of assay
buffer (Abraxis LLC, Hatboro, PA) and UriSub (1:3) were fortified with glyphosate and
metolachlor mercapturate. Two hundred and fifty microlitres of the fortified mixture
were treated with 20 µL of derivitizing agent (Abraxis LLC, Hatboro, PA) for 10
minutes at room temperature. Fifty microliters of the derivitized mixture were analyzed
by FMCIA. All participant urine samples were diluted 1:10 in a mixture of assay buffer
and UriSub (1:3). Two hundred and fifty microliters of the mixture were treated with
derivitizing agent for 10 minutes and 50 µL of the derivitized sample analyzed by
FMCIA. There was no measurable cross reactivity between the pesticides allowing
simultaneous measurement.

Data Analysis
Statistical analyses were performed using SAS 9 Software® (SAS Institute Inc., Cary,
NC). Methods needed to address two concerns: First, since participants from each

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household provided evening and morning urine samples at two visits and multiple
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
children were sampled from each household, concentrations could not be treated as
independent. A second concern was that concentrations were frequently below the
analytical LOD, particularly for atrazine, metolachlor and glyphosate (Table 1). The
laboratory did not censor values below the LOD, rather, they were reported as non-
detect, a level below the LOD, or a level greater than or equal to the LOD. Methods are
commonly available for dealing with correlated data (e.g., mixed-effects regression
modeling) and highly censored data (e.g., maximum likelihood estimation); however,
methods are not readily available for simultaneously dealing with these problems.

Initially, maximum likelihood estimation, shown to work well even in the presence of
high censoring rates (Helsel 2005), was used to estimate geometric means separately for
farm and non-farm family members via the LIFEREG procedure in SAS. In this
analysis, urinary concentrations reported below the LOD were considered to be left-
censored at the LOD and the lognormal distribution was specified as the underlying
distribution. The procedure does not work well when there are fewer than 50 detected
values; consequently, estimates should be considered less reliable for atrazine, which
had the fewest number of samples detected above the LOD. Since standard errors were
known to be underestimated by the procedure by the LIFEREG procedure, which
assumes independence, the LIFEREG procedure was not used for significance testing.

Mixed-effects modeling via the MIXED procedure in SAS was used to test for
associations between the concentrations and covariates, estimate variance components,

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and estimate correlation coefficients between visit 1 and visit 2 for each family member
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
and among the family members within each visit.

Table 1: Number and percent of urine levels reported as non-detect (ND), positive but
below the limit of detection (LOD), or greater than or equal to the LOD
Number of Pesticide
Subject type
Homes Subjects Samples
Atrazine
Father

Farm
24
24
92
Mother
Farm 24 24 94
Child Non-farm
Farm 25 65 235
Chlorpyrifos
Father

Farm
24
24
92
Mother
Farm 24 24 94
Child Non-farm
Farm 25 65 235
Metolachlor
Father

Farm
24
24
92
Mother
Farm 24 24 94
Child Non-farm
Farm 25 65 235
Glyphosate
Father

Farm
24
24
92
Mother
Farm 24 24 94
Child Non-farm
Farm 25 65 235
a The laboratory did not censor values detected below the LOD. These values may be
within the error around a zero value and are not reliably quantifiable.
b P-value for comparing the proportion of samples detected above the LOD for farm
subjects versus non-farm subjects obtained using the GENMOD procedure in SAS with
a REPEATED effect of household ID to account for the correlated nature of the data.
c Tests were not conducted due to the high proportion of samples detecting
chlorpyrifos.

Urine level
< LOD a

(44%)
(51%)
43
59 (63%)
101
157(67%)

(6%)
(0%)
5
0 (0%)
0
1 (<1%)

(25%)
(30%)
28
40 (43%)
53
64(27%)

(28%)
(23%)
28
24 (26%)
20
37(16%)
Household
ND

(38%)
(4%)
(39%)
(7%)
(32%)
(8%)

(0%)
(0%)
(0%)
(0%)
(0%)
(0%)

(26%)
(9%)
(24%)
(14%)
(12%)
(10%)

(6%)
(2%)
(5%)
(7%)
(1%)
(3%)
≥ LOD

16
41
(45%)
14
28 (30%)
22
60 (26%)

84
92
(100%)
88
94 (100%)
182
234 (100%)

44
56
(61%)
43
41 (44%)
107
147 (63%)

59
69
(75%)
60
63 (67%)
160
191 (81%)

P-value b

Non-farm

23

23

89 34
4
39
47

(18%)

0.0153
Non-farm 24 24 93 36
7
(46%) (15%) 0.0601
25 51 182 59
18
(55%)(12%) 0.0355

Non-farm

23

23

89 0
0
0
0
0
0
5
0

(94%)

--- c
Non-farm 24 24 93 (5%) (95%) ---
25 51 182 (0%) (100%) ---

Non-farm

23

23

89 23
8
22
28

(49%)

0.34
Non-farm 24 24 93 22
13
22
24
(30%)(46%) 0.82
25 51 182 (29%)(59%) 0.65

Non-farm

23

23

89 5
2
5
7
2
7
25
21

(66%)

0.34
Non-farm 24 24 93 (30%)(65%) 0.79
25 51 182 (11%)(88%) 0.29
In the mixed-effects models, concentrations reported as positive but below the LOD
were used as-is and concentrations reported as non-detect were replaced with one-half

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of the minimum reported positive level . Urinary concentrations were skewed to the
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
right; therefore, concentrations were natural log transformed prior to analysis. A
majority of the participants provided both an evening and a morning void; however,
there were instances where only a single void (evening or morning) was provided at a
particular visit (7 out of 94 father-visits, 3 out of 95 mother-visits and 19 out of 218
child-visits). To simplify the covariance structures, evening and morning voids, which
were not significantly different, were averaged to give a single result for each visit.

All mixed-effects models assumed that the households were independent. Data models
utilized a compound symmetric covariance structure. For children, data models utilized
a compound symmetric covariance structure for children from the same household
within a particular visit. That is, parameters were estimated for the variance of the
levels and the covariance between levels obtained at the same visit but from different
children. Parameters were also estimated for the covariance between levels obtained
from the same child at different visits and from different children at different visits.
Covariance parameters for farm and non-farm subjects were allowed to vary. The
model with the lowest Akaike’s Information Criterion (AIC) was deemed to best fit the
data. Estimates of the variance and covariance parameters were used to estimate inter-
and intra-individual variability (Kromhout and Heederik 2005). In turn, these estimates
were used to estimate the attenuation ratio expected when assessing associations with
exposure based on two repeated observations (Liu et al. 1998).

The pesticide concentration in urine (µg/L), log transformed but unadjusted for
creatinine, was the dependent variable for all models; creatinine adjustment was

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B.D. Curwin

accomplished by including the creatinine level (mg/dL) as an independent variable in
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
the model (Barr et al. 2005). In the mixed-effects models, since the dependent variable
was the mean of the evening and morning pesticide concentrations, adjustment for
creatinine was accomplished by including the mean of the evening and morning
creatinine levels as an independent variable in the model. When modeling pesticide
levels in urine from children, the age and sex of the child were considered potential
confounders. Covariates of interest included household type (farm, non-farm), pesticide
application prior to the visit and the concentration of pesticide in dust. Dust sample
results have been previously reported (Curwin et al. 2005a). In order to have sufficient
amounts of collected dust for analysis, dust samples from some households were tested
for atrazine, chlorpyrifos and metolachlor (20 farm and 19 non-farm) while dust
samples from the remaining households were tested for glyphosate (5 farm and 6 non-
farm). Consequently, in analyses involving pesticide levels in dust, the sample size was
reduced accordingly. A summary measure of the amount of pesticide in household dust
was obtained by averaging the natural log transformed dust concentrations over all of
the rooms tested. Farm size, amount of pesticide applied, number of acres applied and
the number of days since the pesticide was last applied were considered in models of
pesticide levels in urine from farm subjects. When modeling pesticide levels in urine
from farm children, additional covariates included indicator variables for playing in
crop fields, participation in farm chores, contact with treated fields and handling or
applying pesticides. Results are presented as adjusted geometric means for comparative
purposes. The significance level was set at 5%.



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B.D. Curwin

Results
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
The number of children per household and their age distributions were similar for farm
and non-farm households. Among farm children, 12% (8 out of 66) reported playing in
crop fields, 47% (31 out of 66) reported completing farm chores, 8% (5 out of 66)
reported working in treated fields and 8% (5 out of 66) reported handling or applying
pesticides. None of the 52 non-farm children in the study reported working in treated
fields or handling or applying pesticides, but one non-farm child and two non-farm
children reported playing in crop fields and completing farm chores, respectively.

Urine samples
A majority of the urine voids detected the metabolites of chlorpyrifos, metolachlor and
glyphosate above the LOD (Table 1). For atrazine, only approximately 23% of the
voids were detected above the LOD; however, when values below the LOD reported by
the laboratory were considered, nearly 80% of the voids had an analytical level.
Creatinine concentrations ranged from18.7-418 mg/dL (median 95 mg/dL) and a
majority of the concentrations were in the 30 – 300 mg/dL range (733 of 785, or 93%).
Urinary pesticide results based on a high performance liquid chromatography (HPLC)
method of analysis have already been reported for fathers (Curwin et al. 2005b). Here
we present analyses for fathers, mothers and children based on an immunoassay method
of analysis.

Estimated urinary metabolite geometric means (GM) based on the maximum likelihood
estimation method and adjusted for urinary creatinine are presented in Table 2 for
fathers, mothers and children stratified by household type. Estimated GM levels based

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on the mixed-effects model and adjusted for urinary creatinine are also provided in
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
Table 2. Estimates for chlorpyrifos are similar for the two methods which was expected
since nearly all samples detected chlorpyrifos above the LOD. For the remaining
pesticides, both estimates require cautious interpretation due to high levels of censoring,
particularly for atrazine. Based on the mixed-effects models, adjusted GM levels of the
metabolite of atrazine were significantly higher in fathers, mothers and children from
farm households compared to non-farm households (p < 0.0001). Metabolites of
chlorpyrifos were higher in farm fathers (p = 0.018) and marginally higher in farm
mothers (p = 0.052) when compared to non-farm fathers and mothers, but metolachlor
and glyphosate levels were similar between the two groups. GM levels of the
metabolites of chlorpyrifos and metolachlor were not significantly different between
farm and non-farm children. The GM glyphosate level for non-farm children was
marginally significantly higher than the GM level for farm children.

Application status
At the farm households, each pesticide was either not applied prior to the visit, or if it
had been applied, it may have been applied by either a custom applicator or the farm
father. Estimated geometric means (GM) based on the mixed-effects model and
adjusted for urinary creatinine are presented in Table 3 for urinary levels of the
metabolites of atrazine, chlorpyrifos, metolachlor and glyphosate for farm fathers,
mothers and children stratified by application status. In most cases no application had
taken place; however, when the pesticide had been applied, it was more often than not
applied by the father.


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B.D. Curwin



Table 2: Urinary pesticide metabolite concentration, by household type
Pesticide
Subject type (µg/L)
Take-home pesticide exposure among farm families: Urinary pesticide concentrations
ML estimate b
GM (µg/L)

0.46
0.84
0.42
0.75
0.46
0.71

12
17
11
14
16
16

0.32
0.46
0.28
0.24
0.40
0.45

1.4
1.9
1.2
1.5
2.7
2.0
Mixed-effect model estimate c
GM (µg/L)
95% CI

0.067
1.1
0.60 – 2.0
0.031
0.65 0.41 – 1.0
0.054
0.60 0.38 – 0.93

13
17
15 – 20
11
14 12 – 17
15
17 15 – 19

0.17
0.41
0.17 – 0.98
0.17
0.21 0.11 – 0.41
0.24
0.39 0.24 – 0.65

1.5
1.6
1.1 – 2.4
1.2
1.1 0.71 – 1.8
2.5
1.9 1.3 – 2.5
Household Range a
p-value d

<0.0001
Atrazine
Father

Mother

Child

Non-farm
Farm
Non-farm
Farm
Non-farm
Farm

Non-farm
Farm
Non-farm
Farm
Non-farm
Farm

Non-farm
Farm
Non-farm
Farm
Non-farm
Farm

Non-farm
Farm
Non-farm
Farm
Non-farm
Farm

0.00062 – 3.8
0.046 – 68
0.0013 – 2.8
0.024 – 4.9
0.0028 – 2.2
0.037 – 3.6

3.8 – 47
6.5 – 58
1.8 – 35
5.6 – 52
5.4 – 54
6.1 – 87

0.012 – 1.4
0.0075 – 170
0.0075 – 2.6
0.010 – 9.7
0.010 – 4.2
0.0075 – 64

0.13 – 5.4
0.020 – 18
0.062 – 5.0
0.10 – 11
0.10 – 9.4
0.022 – 18

0.021 – 0.21
0.010 – 0.096 <0.0001
0.020 – 0.15 <0.0001
Chlorpyrifos
Father

Mother

Child

11 – 15

0.018
9.6 – 14 0.052
13 – 18 0.27
Metolachlor
Father

Mother

Child

0.095 – 0.30

0.087
0.090 – 0.34 0.68
0.14 – 0.40 0.17
Glyphosate
Father

Mother

Child

1.2 – 2.0

0.74
0.91 – 1.6 0.73
2.1 – 3.1 0.082
a Range excludes values reported as non-detect.
b Geometric mean (GM) estimated using maximum likelihood methods via the
LIFEREG procedure in SAS. Values below the limit of detection were left censored at
the limit of detection and the lognormal distribution was specified as a model option.
Estimates for fathers and mothers were adjusted for urinary creatinine. Estimates for
children were adjusted for age, sex and urinary creatinine.
c Geometric mean (GM) estimated using mixed-effects modeling via the MIXED
procedure in SAS. Values below the laboratory limit of detection were used if reported
and non-detects were replaced with one-half the minimum reported level. Values were
natural log transformed prior to modeling. Estimates for fathers and mothers were
adjusted for urinary creatinine. Estimates for children were adjusted for age, sex and
urinary creatinine.
d P-value was for farm geometric mean versus non-farm geometric mean based on the
mixed-effects model.


109