504 VOLUME 113 | NUMBER 4 | April 2005 • Environmental Health Perspectives

Children’s Health | Article

Measurement of dialkyl phosphate (DAP)

compounds in urine has been used to assess

exposure to organophosphate pesticides (OPs)

in children living in rural agricultural settings

(Azaroff 1999; Curl et al. 2002; Koch et al.

2002; Loewenherz et al. 1997; Lu et al. 2000;

Shalat et al. 2003) and more recently in urban

communities (Curl et al. 2003; Lu et al.

2001). These biomarkers provide an integrated estimate of exposure received through

ingestion, inhalation, and dermal absorption

during the 24–48 hr preceding testing

(Feldman and Maibach 1974; Loewenherz

et al. 1997). Because the analytical method

used to quantify urinary DAPs is relatively

new and technically difficult (Moate et al.

1999), data on the extent of OP exposure in

various types of communities are limited.

Children have been the focus of many

exposure assessments because their activity

patterns, behavior, and diet lead to increased

risk of exposure relative to adults (Eskenazi

et al. 1999). The sensitivity of developing

organ systems, specifically the brain and central nervous system, and immature detoxification and elimination capacities further

increase children’s risk for adverse health

effects (Faustman et al. 2000). In the United

States, most children are probably exposed to

OPs to some extent. Household surveys indicate extensive residential use of these compounds (Whitemore et al. 1994), and the

potential for widespread low-level chronic

exposure exists (Adgate et al. 2001). Children

who live in agricultural communities are

regarded to be at particularly high risk for

exposure because of their proximity to fields

and orchards where these chemicals are

applied in high volume (Simcox et al. 1995).

Additionally, children whose parents work in

agriculture receive “carry-home” exposure via

transport on their parents’ work clothing and

shoes (Lu et al. 2000). Our studies in Oregon

have characterized these exposure pathways in

children of migrant farmworkers and have

demonstrated elevated levels of residues in

their residences (McCauley et al. 2001).

In this report, we describe the occurrence

of DAP compounds in urine samples collected from children of migrant farmworkers

in three separate communities that host differing agricultural industries using varying

types of OPs, and a reference group of children living in a urban area.

Materials and Methods

Study design. This study was conducted as a

partnership between Oregon Health and

Science University (OHSU) and the Oregon

Child Development Coalition (OCDC),

which is the grantee for Oregon Migrant

Head Start. A cross-sectional design was

employed to collect serial samples of urine

from preschoolers attending Head Start programs at three centers operated by OCDC in

the communities of Hood River, The Dalles,

and Cornelius. For comparison purposes, a

reference sample of preschool-age Hispanic

children who lived in an urban area, Portland,

and whose parents did not work in agriculture

was also assembled. Urine was collected from

the agricultural communities during June–

September 2001, at the beginning, mid-point,

and end of each work season. The timing of

the sampling varied in each community

depending on the time that the farmworkers

began to arrive in the community, enrolled

their children in Head Start programs, and

started work harvesting crops. In the reference

community group, samples of urine were collected during July and November 2001.

Survey sites. The communities selected

for study are geographically separate and differ in the type of agricultural industry. Hood

River primarily produces pears but also produces apples. Hood River is located along the

Address correspondence to L. McCauley, FAAN,

Nursing Education Building, 420 Guardian Dr.,

University of Pennsylvania, Philadelphia, PA 19104-

6096 USA. Telephone: (215) 898-9160. Fax: (215)

898-3056. E-mail: lmccaule@nursing.upenn.edu

We thank the children and the staff of the Migrant

Head Start centers who participated in this study.

We also acknowledge the data collection and technical contributions of R. Travers and J. Phillips of the

Oregon Child Development Coalition, and those of

G. Higgins, E. Mahoney, L. Pham, J. Richman, and

K. Wax of the Center for Research on Occupational

and Environmental Toxicology at Oregon Health

and Science University.

This work was supported by the National Institute

of Environmental Health Sciences (NIEHS) through

a Community-Based Prevention/Intervention

Research Program grant (R01 ES08707, L.M.,

Principal Investigator). Its contents are solely the

responsibility of the authors and do not necessarily

represent the official view of the NIEHS.

The authors declare they have no competing

financial interests.

Received 4 December 2003; accepted 10 January

2005.

Variation in Organophosphate Pesticide Metabolites in Urine of Children

Living in Agricultural Communities

William E. Lambert,1 Michael Lasarev,1 Juan Muniz,2 Jennifer Scherer,1 Joan Rothlein,1 Juanita Santana,3 and

Linda McCauley2

1Center for Research on Occupational and Environmental Toxicology, Oregon Health and Science University, Portland, Oregon, USA;

2School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania, USA; 3Oregon Child Development Coalition, Wilsonville,

Oregon, USA

Children of migrant farmworkers are at increased risk of exposure to organophosphate pesticides

because of “carry-home” transport processes and residential location. Although this at-risk status

is generally recognized, few available reports describe the extent of this exposure among agricultural communities. We quantified dialkyl phosphate (DAP) levels in serial samples of urine from

176 children, 2–6 years of age, in three Oregon communities hosting differing agricultural industries: pears, cherries, and fruit berries. Up to three spot samples of urine were collected from children at the beginning, mid-point, and end of their parents’ work seasons. The median levels of

dimethylthiophosphate (DMTP), the most commonly detected metabolite, was significantly

higher in urine samples from children in each of the three agricultural communities (17.5, 19.0,

and 41.0 ng/mL) relative to a reference group of children who lived in an urban community and

whose parents did not work in agriculture (6.5 ng/mL; Kruskal-Wallis, p < 0.001). After controlling for age, sex, and weight, the median level of DMTP in children in the pear community was

1.92 times higher than the level in children of the berry community [95% confidence interval

(CI), 1.14–3.23] and 1.75 times higher than the level in children of the cherry community

(95% CI, 0.95–3.23). We observed increasing levels of DMTP across the work season only within

the berry community. Levels decreased in the cherry community and remained constant in the

pear community. Substantial temporal variation within the children followed demonstrates the

need for multiple urine samples to most accurately characterize longer term and/or cumulative

exposure. The observed variability in urinary DAP levels, between communities and over time,

could be attributed to the types and amounts of organophosphate pesticides used, the timing of

applications and degradation of residues in the environment, work operations and hygiene practices, the proximity of housing to orchards and fields, or the movement of these working families.

Additional studies of variation in pesticide exposure across agricultural regions are needed.

Key words: agriculture, children, farmworkers, pesticides. Environ Health Perspect 113:504–508

(2005). doi:10.1289/ehp.6890 available via http://dx.doi.org/ [Online 10 January 2005]
Columbia Gorge, approximately 100 km east

of Portland, Oregon. The farmworkers in

this community tend to be semipermanent

residents who live in cabins, trailers, or

apartments that are located in or alongside

orchards. Azinphos-methyl [trade name

Guthion; Chemical Abstract Service (CAS)

No. 86-50-0], chlorpyrifos (CAS No. 2921-

88-2), and phosmet (trade name Imidan;

CAS No. 732-11-6) are used to control pests

such as coddling moth and are applied

May–August. Harvesting of tree fruit begins

in August and extends through October.

Urine samples were collected from the children at the Hood River Migrant Head Start

day care centers in Parkdale and Odell in

June, August, and October.

The second survey site was The Dalles,

where cherries are grown. The Dalles is located

along the Columbia Gorge, 30 km east of the

Hood River community. Cherry harvest lasts

only 1 month, usually beginning in mid-June.

The cherries are hand harvested by migrant

farmworkers, who live with their families in

camps, cars, trailers, and tents. Chlorpyrifos

can be applied to the cherry crop at prebloom

in March by air blast method from the

ground, whereas ultra-low-volume concentrate

malathion (CAS No. 121-75-5) is applied

aerially in late May and every 7–10 days

throughout harvest. Urine samples were collected at the Dalles Migrant Head Start Center

in June and July.

The third agricultural community,

Cornelius, has both rural and suburban features

and is situated in the northwest Willamette

Valley. The farmworker population consists of

settled farmworkers who work in the nursery,

vineyard, and berry industries and a highly

mobile migrant population of farmworkers

who harvest the strawberry, caneberry, and

blueberry crops during the summer months.

The migrant population of farmworkers

receive priority enrollment in Migrant Head

Start and was targeted for this study. These

families tend to live in camps composed of

wood cabins and trailers that are adjacent to

berry fields. Strawberry, caneberry, and blueberry growers apply diazinon (CAS No. 333-

41-5), azinphos methyl, chlorpyrifos, and

malathion to control pests. Urine samples

were collected at the Cornelius Migrant Head

Start Center the months of June, July, and

August.

Reference subjects were recruited through

Head Start and school-based programs in the

Portland metropolitan area. Hispanic families

were screened and invited to participate only if

the parents reported that they did not work in

agriculture, nursery, or landscaping businesses.

Typical jobs held by families in the reference

group include food service, factory work, and

child care. These families lived in apartments

in an urban setting.

Recruitment and data collection. Eligibility

for participation was restricted to preschool-age

children, 2–6 years of age, who were able to urinate while sitting on a toilet. Signed informed

consent was obtained from parents as they registered their child for the Migrant Head Start

Program. All participants except children from

the reference population had at least one parent

working in the field, orchard, or nursery while

participating in the study. Demographic information was extracted from Head Start records,

which were completed at time of registration.

The extracted information included the child’s

name, sex, age, date of birth, type of residence,

previous and current place of employment, and

crop worked by the parents. Reference subjects

were selected from summer Head Start programs at three sites in northeast and north

Portland, and Gresham (a suburban community east of Portland). When reference subjects

were recruited and informed consent from

the mother was obtained, each parent was

asked questions to confirm that their child was

between the ages of 2 and 6 years, and that neither the parents nor other adult household

members worked in agriculture. At the time the

urine sample was collected, participants were

weighed.

Human subjects review. The study protocol and procedures for informed consent were

reviewed and approved by the OHSU institutional review board (protocol 4216).

Urine collection. Urine samples were collected from each participant while the child

attended Migrant Head Start. Research assistants collected the single void urine samples

mid-morning through early afternoon using

commode inserts. The urine was transferred

into a urine specimen cup, labeled, and transferred on ice to the Center for Research on

Occupational and Environmental Technology

analytical laboratory.

Urinalysis. Urine specimens were adjusted

to pH 3.0 and stored at –20°C until extraction and analysis. Five DAPs were analyzed

by gas chromatography (GC): dimethylphosphate (DMP), diethylphosphate (DEP),

dimethylthiophosphate (DMTP), diethylthiophosphate (DETP), and dimethyldithiophosphate (DMDTP). Urine samples were

prepared for GC analysis according to a modified method of Moate et al. (1999). Aliquots

of the samples underwent azeotropic distillation with methanol and evaporation under a

nitrogen stream. Sample extracts were then

derivatized with 2,3,4,5,6-pentafluorobenzylbromide to convert phosphate acids to esters.

Extracted samples were analyzed on a gas

chromatograph (model 5890; HewlettPackard, Palo Alto, CA) equipped with a

pulsed flame photometric detector (OI

Analytical, College Station, TX). The limit of

detection (LOD) for each of the metabolites

was calculated from the instrument response

factor corresponding to a concentration having a peak area three times the baseline noise

(blank signal). The specific LODs for the five

metabolites were 4.0 ng/mL for DMP,

2.0 ng/mL for DEP, 2.2 ng/mL for DMTP,

1.6 ng/mL for DMDTP, and 1.6 ng/mL for

DETP. The average extraction efficiencies of

the five metabolites were, respectively, 87, 84,

97, 96, and 93%. Creatinine concentrations

(micrograms per deciliter) were determined

by the modified Jaffe rate method (Sigma

Diagnostics Creatinine Kit no. 555; SigmaAldrich, St. Louis, MO).

Quality control/quality assurance. Quality

control data generated for each set of urine

samples were used to provide an overall assessment of precision, accuracy and overall reliability of the method. Spike sample recoveries and

urine blank analysis were conducted for every

set of 12 samples. Urine samples known to

contain low levels of DAP were used for blanks

and for spike recoveries. Urine samples were

spiked with DAP reference standards varying

in concentration from 2 to 50 ng/mL.

LOD is defined as the lowest concentration that can be determined to be statistically

different from a blank. However, in practice,

the detection of an analyte by an instrument

is often based on the extent to which the analyte signal exceeds peak to peak noise (U.S.

Environmental Protection Agency 2000). The

LOD for each set of metabolites was calculated from the instrument response factor corresponding to a concentration having a peak

area three times the baseline noise (signal)

corresponding to the urine blank sample.

Data analysis. To obtain stable measurements of urinary metabolites, we averaged the

concentrations measured in the second and

third samples, corresponding to the mid-point

and end of the work season. The first sample,

collected at the time the child was being registered in Head Start, was not included because it

could represent exposures that had occurred

before the parents began working in agriculture

in the area. The second sample was obtained at

least 2 weeks into the work, reflecting exposures

while the parents were working in the area, and

the third sample, taken at the end of the work

season, also reflected exposures occurring while

their parents were working in the area.

We evaluated the distribution of creatinine

levels and excluded urine samples less than the

5th percentile (14 mg/dL) and greater than the

95th percentile (110 mg/dL) from the analysis

because of concerns of hydration state and

metabolic disorders (Loewenherz et al. 1997;

Lu et al. 2001). Tampering by dilution is

unlikely given the young age of the subjects

and the supervision of urine collection by our

field staff.

During the course of the survey, urine samples were collected from a total of 214 subjects.

Nineteen subjects were excluded from the

Children’s Health | Variation in urinary OP metabolites

Environmental Health Perspectives • VOLUME 113 | NUMBER 4 | April 2005 505
statistical analysis because second or third samples were not obtained. Data for an additional

19 subjects were excluded because creatinine

levels fell outside the range of 14–110 mg/dL.

Statistical analyses were performed on a data

set consisting of 176 subjects.

DMTP was the most commonly quantified DAP. The percentage of samples below

the LOD was 20.5%. DMP and DMDTP

were below the LOD in 33.0 and 58.8% of

creatinine valid samples, respectively. For

comparison, the ethyl compounds, DEP and

DETP, were below LOD in 91.2 and 68.2%

of samples, respectively. Because ethyl metabolites were detected with much less frequency,

statistical analysis was restricted to the methyl

metabolites. The infrequent detection of DEP

and DETP in our survey is consistent with the

experience of researchers at the University of

Washington (Curl et al. 2002; Fenske et al.

2000; Lu et al. 2001). In our case, inclusion of

the large proportion of unquantifiable observations would needlessly complicate analyses and

not produce informative results.

Standardization of DAP metabolites to

creatinine (nanomoles per gram creatinine) was

performed in the statistical analysis. However,

because this adjustment did not alter findings

in any substantive way, we chose to present

our findings in units unadjusted for creatinine

(nanograms per milliliter and micromoles

per liter).

We summed the molar equivalent concentrations of the methyl metabolites to

create a combined methyl DAP measure.

Nondetects were treated as zeroes in the summation of molar concentrations, and if the

total methyl DAP value was zero, then it was

assigned the value of 0.5 LOD for DMDTP

(0.5 × 0.010 μmol/L), the methyl DAP with

the lowest LOD.

Statistical methods. Demographic data were

summarized using means ± SDs. Metabolite

levels below the LOD were treated as 0.5 LOD

for the purpose of statistical analysis and were

summarized using the geometric mean, geometric SD, and percentiles. The geometric

mean is a descriptive statistic suitable only for

summarizing the data; however, it is an estimator for the population median. Hypothesis

tests or confidence intervals based on the geometric mean make inference to the population

median, and subsequent wording indicates

the median is the parameter being tested/

estimated. We used Kruskal-Wallis one-way

rank analysis of variance to test for differences

in the median concentrations of metabolites

between the communities. We used separate

Wilcoxon tests, with p-values adjusted by the

method of Benjamini and Hochberg (1995),

to determine which pairs of medians significantly differed at the 0.05 level. Within the

three agricultural communities, potential confounding of the location effect by age, sex,

and weight was controlled for using a general

linear model (GLM) applied to the logtransformed data. After back-transformation,

adjusted means from this model estimate the

population median and additive changes

become multiplicative effects (Aitkin et al.

1994; Ramsey and Schafer 2002). We used

extra-sum-of-squares F-tests (Netter et al.

1989) to test significance of multiple effects

within the GLM.

To analyze variation in metabolite levels

within subjects and communities over time,

DMTP concentrations were log-transformed,

and paired t-tests were applied to assess differences between sample collection times: time 1

versus time 2 (beginning vs. middle of work

season), time 2 versus time 3 (middle vs. end of

work season), and time 1 versus time 3 (beginning vs. end of work season). We used Pitman’s

test for correlated variances (Pitman 1939;

Snedecor and Cochran 1980) to determine

whether the amount of dispersion changed

between two points in time. All analyses were

performed using R version 1.9 (R Development

Core Team 2004).

Results

Table 1 presents the characteristics of the

samples obtained in each community. The

distribution of males and females did not vary

across the four communities. Overall, 52.3%

of the sample was female. There was indication that the weight of children differed significantly from one community to the next

(F3,210 = 6.25, p < 0.01). Children from the

pear community weighed significantly less

than did children from either the cherry or

reference community [95% confidence interval (CI), 3.6–10.4 lb less]. The mean age of

children was not compared across communities because, by design, we sampled only children between 4 and 6 years of age.

In our comparisons of urinary metabolites, we averaged the concentrations measured in the second and third samples for each

individual collected during the mid-point and

end of their parents work season. The median

concentrations of urinary DMTP and the

combined methyl DAP by weight-volume

concentrations units were significantly higher

in the agricultural communities versus the

urban reference community [Kruskal-Wallis

test: χ2 (3 df) = 27.29 and χ2 (3 df) = 25.237,

respectively; p < 0.001 for both) (Table 2)].

The median concentrations of DMTP and

combined methyl DAPs were significantly

higher in children from the pear community,

relative to those observed in either the cherry

or the strawberry communities (adjusted

p-value from Wilcoxon test = 0.008 for both).

Median values in samples from the cherry and

strawberry communities were not significantly

different (adjusted p-value from Wilcoxon

test = 0.786).

We used a GLM applied to log-transformed

data to compare urinary DMTP and the combined methyl DAP levels across the agricultural

communities. The analysis adjusted for age, sex,

Children’s Health | Lambert et al.

506 VOLUME 113 | NUMBER 4 | April 2005 • Environmental Health Perspectives

Table 1. Age, sex, and weight of children from three agricultural communities and reference urban community

in Oregon.

Community

Reference Berries Cherries Pears

Parameter (n = 65) (n = 63) (n = 38) (n = 48) Significancea

No. of samples/child

Mean ± SD 1.2 ± 0.4 2.9 ± 0.4 2.8 ± 0.5 2.6 ± 0.7 —

Min, max 1, 2 1, 3 1, 3 1, 3

Age [years (mean ± SD)] NAb 4.2 ± 1.0 4.3 ± 1.1 4.2 ± 1.0 —

Sex (% male) 51 44 50 46 χ2(3) = 0.66

p = 0.88

Weight [lb (mean ± SD)] 42.1 ± 9.6 39.2 ± 10.2 42.6 ± 11.2 35.9 ± 7.5 F3,210 = 6.25

p < 0.01

Abbreviations: max, maximum; min, minimum; NA, not applicable.

aNumber of samples per child and age were controlled by design and not tested. bDate of birth not collected.

Table 2. Comparison of child urinary DMTP (ng/mL) and combined methyla (μmol/L) DAP metabolitesb

among three agricultural communities and referent community.

Reference (n = 61) Berries (n = 52) Cherries (n = 29) Pears (n = 33)

Combined Combined Combined Combined

Summary statistics DMTP methylb DMTP methyl DMTP methyl DMTP methyl

Geometric meanc 7.25 0.12 18.81 0.25 20.24 0.26 38.54 0.40

Geometric SDd 5.33 3.80 3.43 2.54 2.51 1.93 3.07 2.34

10th percentile 1.10 0.01 4.48 0.09 5.60 0.12 7.68 0.11

25th percentile 1.10 0.06 7.97 0.12 9.40 0.15 27.00 0.27

50th percentile 6.50 0.15 17.50 0.23 19.00 0.25 41.00 0.44

75th percentile 30.00 0.30 40.50 0.46 37.00 0.39 87.00 0.77

90th percentile 61.00 0.50 99.90 0.90 63.00 0.53 126.00 1.00

a“Combined methyl” is the summed molar equivalent concentration of DMP, DMTP, and DMDTP (μmol/L). bConcentrations

are the average of the mid- and the end-of-season samples (ng/mL). cBack-transformed mean of log-transformed data (an

estimate of the median). dBack-transformed SD of log-transformed data.
and weight. Means from this analysis (derived

from β-coefficients) estimated the median

effect in the population after they had been

back-transformed. CIs for the effects were

derived from CIs for specific β-coefficients and

then back-transformed. The results indicated

that the differences in the median level of

DMTP in children of agricultural communities remained significant after controlling for

age, sex, and weight (extra-sum-of-squares

F-test, F2,108 = 8.270, p = 0.04). The median

level in the pear community was 1.92 times

higher than the level in the berry community

(95% CI, 1.14–3.23). Median levels were

1.75 times higher in the pear community than

in the cherry community (95% CI, 0.95–3.23),

but this was only a suggestive difference

(p = 0.075). The difference between the berry

community and the cherry community was

not significant when accounting for age,

sex, and weight (p = 0.719). Controlling for

age, sex, and weight reduced the statistical

significance of the community effect for the

combined methyl DAP data within the three

agricultural communities (extra-sum-of-squares

F-test, F2,108 = 2.165, p = 0.120).

Table 3 presents the geometric means and

SDs for DMTP measurements by community

and sample time. CIs for the effect were found

by first calculating a confidence interval for

the mean difference of the log-transformed

data and then back-transforming the end

points with corresponding inference made to

median levels. In the berry community, concentrations tended to increase from beginning

to end of the work season (Table 3). The

median was estimated to be 2.18 times higher

than the median at the beginning of the work

season (95% CI, 1.26–4.08 times higher).

In the cherry community, concentrations of

DMTP sharply decreased from the beginning

of the work season to the midpoint, 10 days

later. At the end of the work season, three

weeks after the initial sample, urinary DMTP

began to increase. In the pear community,

concentrations of DMTP did not change in

an appreciable way from the beginning to end

of the work season.

Discussion

Our analysis of urinary biomarkers adds to a

growing body of literature that suggests children of agricultural workers experience more

exposure to OPs than do children who live in

urban areas (Lu et al. 2000). The median level

of DMTP, the most commonly detected

metabolite, was significantly higher in the children of migrant farmworkers relative to urban

Hispanic children whose parents did not work

in agriculture. More important, however, is

our demonstration of substantial variation in

OP metabolite levels across communities hosting differing agricultural industries, and substantial variation within a community over

time. This variation was demonstrated among

communities within the same geographic

region, and within relatively short work seasons lasting weeks to months, conditions that

could be expected to foster homogeneity.

Median levels of DMTP differed significantly among communities, despite substantial

interchild variability and overlapping distributions. Although the precise reasons for the

observed differences between locations cannot

be inferred from our data, we attribute the

variation to differences in the types of pesticides used on the fruits and berries, and the

timing of application and opportunity for environmental degradation before contact with

workers at the time of harvest. For example,

OPs are applied to pears as needed to control

infestations until the time of harvest, whereas

OPs are applied very early in the development

of cherry fruit and not again, or infrequently,

with months of time for breakdown of residues

in sunlight and moisture. It is also possible that

the greater extent of contact with foliage associated with picking pears (vs. cherries) may create greater opportunity for transfer of foliar

residues to the clothing and skin of adults, who

may carry these residues to their children.

Finally, differences in type of housing and

proximity of residence to orchards and fields

may also explain the observed differences. The

pear community is located in a valley, and air

blast spraying and drift transport occurs near

the homes of migrant farmworkers, possibly

increasing the opportunity for exposure.

Proximity of housing to application areas has

been demonstrated to influence carpet residue

levels in the homes of workers in Washington

(Lu et al. 2000) and Oregon (McCauley et al.

2001). Furthermore, we have observed a larger

number of detectable OPs in carpet dust of

homes in the pear community (Hood River)

compared with homes in the berry community

(Cornelius, Washington County) (McCauley

et al. 2001).

Koch et al. (2002) reported a temporal

pattern of pesticide exposures in children living

in an agricultural community over an entire

year and the impact of agricultural spraying on

exposure. The children studied in the Koch

et al. (2002) report were enrolled via Women,

Infants, and Children clinic populations in

central Washington State. There are important

differences in the design of these two studies.

We were unable to study children over an

entire year because, by the nature of their parent’s migratory work, they move on to other

agricultural regions or return to their native

country for a portion of the year. We were

unable to assess the impact of spraying pesticides on urinary OP levels, because at the time

the parents are harvesting the crops, the active

spraying season is over. Instead, the goal of our

study was to point to differences between the

OP metabolite levels in children according to

the type of harvesting work their parents were

engaged in and to compare agricultural children to urban children.

The levels of urinary metabolites observed

in the children of our pear community are

similar to those reported for children of apple

orchard workers living in central Washington

State and extensively characterized by Fenske

and colleagues (Loewenherz et al. 1997). The

same OPs (e.g., azinphos methyl, phosmet)

are applied to both crops to control coddling

moth, using similar air blast spray systems, in

similar settings of cultivation. In fact, apples

are cultivated adjacent to pear orchards at our

study site.

For reference, we collected urine samples

from Hispanic children attending summer

Head Start programs in the Portland, Oregon,

metropolitan area. The geometric mean level of

DMTP in this control group was 7.2 ng/mL.

This level is slightly higher than the geometric

mean of 2.7 ng/mL (95% CI, 1.85–4.01)

reported for 471 children, 6–11 years of age,

sampled in the 1999–2000 National Health

and Nutrition Examination Survey [Centers for

Disease Control and Prevention (CDC) 2003].

The difference may be attributed to age and

differing hand-to-mouth behavior and floor

contact in our younger children. Our combined methyl DAP median concentration was

0.15 μmol/L, very similar to the 0.11 μmol/L

median reported for Seattle children 2–5 years

of age (Lu et al. 2001). Presumably, the urinary metabolites observed in studies of urban

Children’s Health | Variation in urinary OP metabolites

Environmental Health Perspectives • VOLUME 113 | NUMBER 4 | April 2005 507

Table 3. The amount and variation of DMTP levels from children in agricultural communities across three time points in a harvest season.

Geometric mean (geometric SD) p-Values for comparison of DMTP levelsa p-Values for comparison of variationb

Community T1 T2 T3 T1 vs. T2 T1 vs. T3 T2 vs. T3 T1 vs. T2 T1 vs. T3 T2 vs. T3

Berries (n = 50) 7.2 (5.0) 9.6 (5.5) 15.7 (4.3) 0.34 0.02 0.10 0.67 0.54 0.30

Cherries (n = 29) 43.4 (2.6) 14.0 (2.5) 18.3 (4.0) < 0.01 0.01 0.33 0.90 0.06 0.04

Pears (n = 31) 22.4 (3.4) 22.5 (5.3) 22.8 (5.4) 0.99 0.95 0.97 0.10 0.08 0.95

Abbreviations: T1, time 1; T2, time 2; T3, time 3. The amount and variation are summarized in terms of the geometric mean and geometric SD; p-values show whether the changes are

significant.

aBased on paired t-test of log-transformed data. bBased on Pitman’s test for correlated variances (performed on log-transformed data).
Children’s Health | Lambert et al.

508 VOLUME 113 | NUMBER 4 | April 2005 • Environmental Health Perspectives

children derive from dietary exposures to

residues, and exposures associated with residential and public (schools, parks) applications.

Our serial sampling design provided an

opportunity to consider temporal variation in

urinary metabolite levels. Given the short halflife of 24–48 hr for DAPs, we expected to

observe variation, specifically increased excretion of metabolites, as parents began work and

started to transfer residues to the home environment. Further, we expected increasing concentrations as body burdens increased and new

doses were superimposed on previous doses that

were being metabolized and eliminated from

the children’s bodies. We observed increasing

levels of DMTP across the work season only in

the berry community. Levels decreased at the

cherry community and remained constant in

the pear community. We attribute this pattern

to differences in the migrant farmworker labor

forces. In the berry community, migrant workers who arrived to work for the short harvest

season apparently had low body burdens and

low exposures to OPs in the period immediately before arriving. In the cherry community,

most migrant farmworker families arrived

directly from agricultural work in California

and/or from the nearby pear community, and

sufficient time had not yet passed for the OP

metabolites to wash out of their bodies. In the

pear community, the workers are settled and

maintain their migrant status and Head Start

benefits by returning to Mexico once per year

in the winter. These workers and their children

live for extended periods in the valley, in close

proximity to the orchards and associated pesticides; therefore, their body burdens may reflect

steady state, rather than new and accumulating

doses. Although the differences that we

observed could be attributed to differences in

the work patterns and total exposure to OPs, it

is possible that the different pharmacokinetics

of specific pesticides used in these communities

and their half-lives could have contributed to

the observed difference.

Our findings are subject to several limitations. First, the DAP metabolites measured in

this study represent a partial view of the total

mix of pesticide exposures received by children.

Exposures to other classes of pesticides and herbicides certainly occur, and the total exposure

to all classes of agricultural chemicals is not

quantified by our methods. Further, the sources

and routes of exposure to OP compounds cannot be identified by measurement of urine

DAPs, which provide an integrated indicator of

exposure to a variety of OP compounds via

ingestion, inhalation, and dermal exposure.

Despite these limitations, our survey is

based on homogeneous samples of children

who by virtue of their eligibility for enrollment in Migrant Head Start are of the same

preschool age, share Hispanic ethnicity and

come from the same socioeconomic class, and

have at least one parent who works in agriculture. We collected measurements on age, sex,

and weight and analyzed creatinine levels to

control for physiologic variation. Appreciating

the relatively short half-life of these metabolites, we collected serial samples from the children and used the average of two samples

collected at the middle and end of the work

season to investigate between community differences and to improve the characterization

of longer-term exposure. We did not use the

first urine sample, collected at the time of

Migrant Head Start enrollment, because of

concerns that this urine sample represented the

exposure of the child before the family’s move

to the new work location and Head Start center. Although some methyl DAPs probably

come from exposure to OP residues on foods

(Curl et al. 2003), this class of biomarker has

proven to be a valid and reliable measure of

exposure via other pathways, including handto-mouth transfer, dermal absorption, and

inhalation, and the observed pattern of variation between communities is consistent with

differing pesticide application practices by the

agricultural industries in these areas. Although

it was not practically possible to measure exposure to the full suite of chemicals to which

these children are exposed, OPs as a class are

among the most toxic chemicals in use by the

agriculture industry and, as a class, present significant health risks.

In conclusion, our findings indicate that

there is substantial variation in level of exposure to OPs among the children of migrant

farmworkers living in different communities.

This diversity in exposure experience must be

considered in exposure assessments and health

risk analyses. Failure to characterize potential

differences between communities may introduce exposure misclassification into epidemiologic studies. Further, our observation of

substantial temporal variation within a child

supports the need for multiple urine samples

to accurately characterize longer term and/or

cumulative exposure.

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CORRECTION

In the original manuscript published online,

Michael Lasarev and William E. Lambert

were listed as the first and second author,

respectively. The order has been reversed here.