142 VOLUME 112 | NUMBER 2 | February 2004 • Environmental Health Perspectives

Research | Article

Farmworkers in various aspects of U.S. agriculture are routinely exposed to pesticides as

part of their occupation. Many of these workers perform job tasks that have high risk for

direct exposure to pesticides, such as mixing,

loading, or applying pesticide formulations.

The U.S. Environmental Protection Agency’s

Worker Protection Standards (U.S. EPA

1992) mandates that personal protective

equipment and training be provided to these

workers. Workers with direct pesticide contact are required to carry a pesticide handlers’

permit or a pesticide license and, therefore,

are required to receive training in the proper

use and storage of pesticides and in protective

measures to minimize exposure. The patterns

of pesticide exposure and the effectiveness of

protective measures among this group have

been the topics of previous research (Alavanja

et al. 1999a, 1999b; Arbuckle et al. 2002;

Dosemeci et al. 2002; Garry et al. 2002a,

2002b; Gladen et al. 1998; Hoppin et al.

2002; Karr et al. 1992; Loewenherz et al.

1997; O’Fallon and Dearry 2001) and policy

recommendations (cholinesterase monitoring) in recent years (Wilson et al. 1997).

The pattern of exposure is less understood

among workers who perform tasks that do not

require the use of personal protective equipment or safety training, such as harvesting

crops, pruning vines and trees, loading or

packing plants fruits and vegetables, or thinning orchards. Some of these workers may

have substantial physical contact with fruits,

leaves, twigs, and branches that may contain

pesticide residues. Because many fieldworkers

work on several crops, they may be exposed to

several different types of pesticides throughout

a given growing season. A limited number of

previous investigations have examined workplace protective practices of this group (such

as the frequency of use of gloves, long-sleeve

shirts, and long pants) (Jackson 2002;

Vela-Acosta et al. 2002); only a limited number have assessed pesticide exposure among

this group (Fenske et al. 1999; McCurdy et al.

1994; Simcox et al. 1999).

Even less is known about the patterns of

exposure of children living in households with

farmworkers. A limited number of previous

investigations have suggested that the children

of farmworkers may experience adverse effects

of pesticide exposure. Two studies that examined cancer end points among children of

farmworkers reported elevated incidence of

leukemia (Daniels et al. 1997) and cancers of

the brain (Daniels et al. 1997) and kidney

(Fear et al. 1998). A related study found miscarriage and fetal loss to be more common

among spouses of pesticide applicators than

among spouses of nonagricultural workers.

Moreover, miscarriage and fetal loss were

more commonly experienced during the spray

season (Garry et al. 2002a, 2002b).

It is widely believed that pesticide residues

in the home environment are exposed to little

sunlight or water and thus break down at a

slower pace than pesticides in fields and

orchards. Children may be uniquely susceptible to this exposure because they spend greater

amounts of time on carpets and floors (where

pesticides accumulate), they often wear minimal clothing during the summer spray season

(increasing their likelihood of dermal exposure), and they engage in hand-to-mouth

behavior (increasing their likelihood of ingesting pesticides) (Mills and Zahm 2001). With

less developed immune systems than adults,

children may be less able to clear pesticides

from their bodies, thus prolonging the effects

of exposure (Mills and Zahm 2001).

Using a quasi-population-based sampling

technique and a large sample of farmworkers

from several agricultural communities in eastern Washington State, we sought to examine

the association between specific agricultural

tasks and levels of pesticide exposure among

adult workers and children living in the same

household. We used adult and child urinary

pesticide metabolite concentrations and dust

residues from vehicles and cars of the same set

of households as markers of exposure. In this

report, we use the term farmworker generally

to mean any agricultural worker, including

seasonal workers and growers.

Methods

Setting. This study is part of a larger study that

sought to develop and test a culturally appropriate intervention to break the take-home

pathway of pesticide exposure. The setting,

study design, study participants, and survey

procedures have been described previously

Address correspondence to G.D. Coronado, P.O. Box

19024, 1100 Fairview Avenue N, MP-702, Seattle,

WA 98109 USA. Telephone: (206) 667-4216. Fax:

(206) 667-5977. E-mail: gcoronad@fhcrc.org

We acknowledge the contribution of members of

our community advisory board in designing and carrying out the project. We thank C. Curl, R. Fenske, and

J. Kissel for processing the urine and dust samples for

this study. 

The research described in this article has been

funded in part by the by the U.S. Environmental

Protection Agency (grant R826886) and the National

Institutes of Health (grant P01 ES09601), but it has

not been subjected to either agency’s required peer

and policy review. The article does not necessarily

reflect the views of either agency, and no official

endorsement should be inferred.

The authors declare they have no competing financial

interests.

Received 25 April 2003; accepted 22 October 2003.

Agricultural Task and Exposure to Organophosphate Pesticides 

Among Farmworkers

Gloria D. Coronado,1 Beti Thompson,1 Larkin Strong,1 William C. Griffith,2 and Ilda Islas1

1Cancer Prevention Research Program, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA; 2Department of

Environmental Health, School of Public Health and Community Medicine, University of Washington, Seattle, Washington, USA

Little is known about pesticide exposure among farmworkers, and even less is known about the

exposure associated with performing specific farm tasks. Using a random sample of 213 farmworkers in 24 communities and labor camps in eastern Washington State, we examined the association between occupational task and organophosphate (OP) pesticide residues in dust and OP

metabolite concentrations in urine samples of adult farmworkers and their children. The data are

from a larger study that sought to test a culturally appropriate intervention to break the takehome pathway of pesticide exposure. Commonly reported farm tasks were harvesting or picking

(79.2%), thinning (64.2%), loading plants or produce (42.2%), planting or transplanting

(37.6%), and pruning (37.2%). Mixing, loading, or applying pesticide formulations was reported

by 20% of our sample. Workers who thinned were more likely than those who did not to have

detectable levels of azinphos-methyl in their house dust (92.1% vs. 72.7%; p = 0.001) and vehicle

dust (92.6% vs. 76.5%; p = 0.002). Thinning was associated with higher urinary pesticide

metabolite concentrations in children (91.9% detectable vs. 81.3%; p = 0.02) but not in adults.

Contrary to expectation, workers who reported mixing, loading, or applying pesticide formulations had lower detectable levels of pesticide residues in their house or vehicle dust, compared with

those who did not perform these job tasks, though the differences were not significant. Future

research should evaluate workplace protective practices of fieldworkers and the adequacy of reentry

intervals for pesticides used during thinning. Key words: applicators, farmworker, field worker, job

task, occupational exposure, pesticide. Environ Health Perspect 112:142–147 (2004).

doi:10.1289/ehp.6412 available via http://dx.doi.org/ [Online 22 October 2003]
(Thompson et al. 2003). Briefly, the study took

place in the Yakima Valley of Washington

State, a region that includes many small agricultural communities. An estimated 50,000 people

in the region work in agriculture; the primary

crops are apples, pears, peaches, cherries, grapes,

and hops. Approximately 50% of the area’s

population is Hispanic.

Agriculture in the valley. The agricultural

products grown in this area require that farmworkers perform a variety of farm tasks.

Workers in apple and pear orchards remove

small buds from the limbs of trees (known as

thinning) so that the remaining buds provide

larger fruit. Pruning is commonly performed

on grape vines and orchard trees.

For most crops cultivated in the Yakima

Valley, such as apples, pears, and cherries,

harvesting is done by hand. Pesticide application is generally carried out by air blast

sprayers, which are attached to tractors. In

recent years, some growers in the valley have

begun to use alternative methods of pest control, such as pheromone disruption systems,

although the use of such methods remains

limited. The main agricultural pest in the

Yakima Valley is the coddling moth. The

amount of pesticides used in a given year

depends on the infiltration of the coddling

moth, which itself is determined by soil and

air temperatures, wind, and humidity.

Organophosphate pesticide use in

Washington State. One of the most commonly used pesticides in the Yakima Valley is

azinphos-methyl, a broad spectrum insecticide registered for use in the control of many

insect pests on a wide variety of fruit, vegetable, nut, and field crops as well as on ornamentals, tobacco, and forest and shade trees.

In the Yakima Valley, it is generally used to

control the coddling moth. Azinphos-methyl

works as both a contact insecticide and a

stomach poison; it is one of the most toxic

organophosphate insecticides and is classified

at level I toxicity (Extension Toxicology

Network 1996). It is reported to be highly

toxic through inhalation, dermal absorption,

ingestion, and eye contact (Extension

Toxicology Network 2001). The current reentry interval for azinphos-methyl applied to

apple crops is 14 days (although thinning may

be performed 7 days after application if

< 1.0 lb/acre has been applied in a calendar

year) (Bayer Corporation Crop Protection

2003). Data from the Washington Agricultural

Statistics survey show that, in the year 2001,

> 241,000 lb of azinphos-methyl were applied

to Washington State apple orchards and

> 22,000 lb were applied to pear orchards

[U.S. Department of Agriculture (USDA)

2002]. Other organophosphate (OP) pesticides such as malathion, methyl-parathion,

phosmet, and parathion are also used on

crops grown in the Yakima Valley.

A previous study conducted in the Yakima

Valley emphasized the populations’ concern

with pesticide exposure, especially among children. Funding for the Child Environmental

Health Center at the University of

Washington (Faustman et al. 2000) made it

possible to address the pesticide concerns. An

advisory board, which included community,

health department, and agricultural department representatives, farmworkers, and grower

advocates, was formed before baseline data collection (Thompson et al. 2001). The board

met monthly, hired a local project coordinator,

and guided the entire project. The community

advisory board and staff from the Fred

Hutchinson Cancer Research Center (subcontractor for the Community Intervention

Project) formed a strong partnership, where the

board had input on all aspects of the project.

All study procedures were reviewed and

approved by the Fred Hutchinson Cancer

Research Center (Institutional Review Board

#5105). 

Study procedures. An initial cross-sectional

sample of farmworkers was identified as part

of a larger community study in the same valley

(Thompson et al. 2002). Additional households were included from local labor camps

and from areas of previously identified communities that were known to have a high concentration of farmworkers. A total of 571

households were surveyed as part of the project. Of these households, 218 had age-eligible

children (2–6 years of age); this group is the

sample used for this study.

Questionnaire. An in-person interview was

conducted with the farmworkers using a 73-

item questionnaire that included nine sections.

Before implementation, the questionnaire was

translated into Spanish, piloted among farmworkers, and reviewed by members of the

community advisory board. 

Questions about job tasks asked workers if

they had performed the following tasks in the

last 3 months: harvesting or picking, pruning,

and loading plants, fruits, or vegetables; packing

plants, fruits, or vegetables; sorting or grading

plants, fruits, or vegetables; planting or transplanting; weeding; thinning; irrigating; mixing

or loading farm chemicals; and spraying or

applying farm chemicals. An additional question asked workers whether they had performed

any other job task. Questions about workplace

spraying of pesticides asked if pesticides had

been sprayed at the respondent’s work in the

past 3 months. Those who responded affirmatively were asked when the most recent spraying

occurred: today, yesterday, 2–3 days ago,

4 days–1 week ago, 1–2 weeks ago, 2–4 weeks

ago, or > 4 weeks ago.

Survey procedures. Among eligible households (those with a farmworker and an ageeligible child), an adult respondent was

identified. Where more than one adult

farmworker or age-eligible child lived in the

household, we used birth date to select a single

adult respondent and a study child. The

selected farmworker was interviewed by a study

staff member. All interviewers were bilingual

(Spanish–English), bicultural, and from the

local area, and they had been trained and certified in data collection (Thompson et al. 2003).

In farmworker households with children

between the ages of 2 and 6 years, families

were invited to participate in the specimen

collection aspect of the study. For these families, we collected urine samples from the adult

farmworker and study child, as well as dust

samples from selected areas of the home

(where the child was thought to play) and

from the vehicle used to commute to and

from work. Our analysis is limited to families

that participated in the specimen collection

aspect of the study.

Specimen collection. The urine and dust

collection procedures have been described

previously (Curl et al. 2002). Briefly, for each

household, two or three urine samples were

collected from an adult farmworker and from

the age-eligible child. Each collection was separated by a minimum of 3 days, and most

samples were collected within a 2-week

period. All samples from each individual were

combined, and the composite samples were

separated into three equal volumes and stored

at –10°C.

Dust samples were collected from homes

and commuter vehicles using the Nilfisk vacuum cleaner (Nilfisk -Advance Inc., Plymouth,

MN). The selection of area to be vacuumed

was determined by asking the parent or adult

participant where the child played most frequently. The size of the area vacuumed

depended on the floor type, and ranged from

a 1 m2 area for plush carpets to a 4 m2 area

for hard or smooth floors. Foot wells from

both the front and back of cars (and only the

front of trucks) were vacuumed. Mats were

not removed before vacuuming. All dust samples were stored at –10°C in the field office

laboratory.

Specimen analysis. Urine samples were analyzed for the presence of five dialkylphosphate

(DAP) compounds produced by the metabolism of most OP pesticides: dimethylphosphate

(DMP), dimethylthiophosphate (DMTP),

dimethyldithiophosphate (DMDTP), diethylphosphate (DEP), and diethylthiophosphate

(DETP). Dust samples were analyzed for the

presence of four dimethyl OP pesticides (azinphos-methyl, malathion, methyl parathion, and

phosmet), and two diethyl OP pesticides

(chlorpyrifos and diazinon) (Curl et al. 2002).

Statistical analysis. We calculated the frequency of demographic characteristics among

our subsample of farmworkers with age-eligible

children. We also calculated the frequency that

these farmworkers performed specific job tasks.

Article | Job task and pesticide exposure

Environmental Health Perspectives • VOLUME 112 | NUMBER 2 | February 2004 143
For each individual, the values for the

urinary metabolites were combined to generate values for two broad categories:

dimethyl (i.e., DMP, DMTP, DMDTP)

and diethyl (i.e., DEP and DETP). For the

purposes of this analysis we limited our

investigation to dimethyl compounds

because they are more commonly used in

the Yakima Valley. For each job task, we

chose to report workers’ values for the individual metabolites, because metabolic pathways for a given pesticide may be different

from that of another. Where the value of a

given individual metabolite was below the

limit of quantitation, we treated it as nondetectable. We limited our analysis of house

and vehicle dust samples to azinphos-methyl

because it is most commonly used in the valley and it was found in the greatest number

of households and vehicles.

We used chi-square tests to compare the

observed and expected percentage of detectable

samples among workers who did and did not

perform a given job task. A difference in proportions was determined to be significant if the

associated p values were < 0.05. Although our

analysis compares percentages of detectable urinary metabolite or pesticide concentrations for

workers who may have performed several job

tasks, we consider our analysis exploratory;

thus, we chose not to report Bonferroniadjusted p-values.

Because timing of spray activity may be

associated with both job tasks and exposure

levels, we used chi-square tests to examine the

association between recent pesticide spraying

(within 3 days) and selected job tasks.

Associated p-values are reported as measures

of significance.

Results

Initially, a total of 218 households had an

age-eligible child and agreed to enroll in the

specimen collection aspect of the study.

Seven children declined to provide urine

samples at the time of collection; thus, we

collected urine samples from one adult and

one child in 211 households. Dust samples

were collected in 210 homes and 205 commuter vehicles. For 54 homes and 15 vehicles, insufficient masses of dust were collected

for analysis. Thus, we conducted residue

analysis on 156 house-dust samples and 190

vehicle-dust samples. Samples were collected

June–October 1999.

Nearly two-thirds of our study respondents

were younger than 35 years of age (Table 1).

The majority had completed ≤ 8 years of

schooling; only 5% had graduated from high

school or earned an advanced degree. Annual

household income was generally low, with

nearly 90% of families earning < $25,000. In

general, the farmworkers in this study were

married (88.2%) and were born in Mexico

(92.4%). Nearly half had worked in agriculture for < 10 years. Slightly less than twothirds were male, and the vast majority

(92.9%) completed the interview in Spanish.

Approximately three-fourths of our sample

had harvested or picked agricultural products

in the 3 months prior to being interviewed; a

substantially lower proportion had pruned

trees or vines; loaded, packed, or sorted plants,

fruits or vegetables; or planted or transplanted

seeds, plants, or trees (Table 2). Half of our

sample reported having weeded fields or

orchards, and about two-thirds had thinned

plants or trees. Approximately one-fourth of

Article | Coronado et al.

144 VOLUME 112 | NUMBER 2 | February 2004 • Environmental Health Perspectives

Table 1. Demographic characteristics of selected

adult farmworkers having a child between 2 and 6

years of age in the household (n = 211).

Characteristic No. (%)

Age (years)

18–24 24 (13.3)

25–34 90 (49.7)

35–49 57 (31.5)

≥ 50 10 (5.5)

Education

< 4th grade 63 (29.9)

5th–8th grade 85 (40.3)

8th–12th grade 52 (24.6)

High school graduate or higher 11 (5.2)

Annual household income

< 10,000 44 (21.2)

10,000 to < 15,000 58 (27.9)

15,000 to < 25,000 85 (40.9)

≥ 25,000 21 (10.1)

Marital status

Married or living as married 186 (88.2)

Separated or divorced 5 (2.4)

Never married 19 (9.0)

Other 1 (0.5)

Birthplace

United States 13 (6.2)

Mexico 195 (92.4)

Other 3 (1.4)

No. of years working in agriculture

< 10 102 (48.3)

10 to < 20 63 (29.9)

≥ 20 46 (21.8)

Sex

Male 136 (64.5)

Language for interview

Spanish 196 (92.9)

Table 2. Percentage of farmworkers who performed

selected job tasks (n = 211).a

Job task No (%)

Harvesting or picking 159 (72.0)

Pruning 77 (36.5)

Loading plants, fruits, or vegetables 90 (42.7)

Packing plants, fruits, or vegetables 45 (21.3)

Sorting plants, fruits, or vegetables 59 (28.0)

Planting or transplanting 79 (37.4)

Weeding 106 (50.2)

Thinning 136 (64.5)

Irrigating 56 (26.5)

Mixing or loading pesticides 45 (21.3)

Spraying pesticides 46 (21.8)

aEach respondent was asked about each task.

Table 3. Percent detectable dimethyl urinary metabolites among adult farmworkers, by job task (n = 211).

DMP DMTP DMDTP

Job task Percent p-Value Percent p-Value Percent p-Value

Harvesting or picking

Yes 23.5 93.3 56.4

No 12.3 0.07 91.2 0.61 49.1 0.35

Pruning

Yes 23.4 94.8 58.4

No 18.6 0.41 91.5 0.37 51.9 0.37

Loading plants, fruits, or vegetables

Yes 25.8 92.1 57.3

No 16.2 0.09 93.2 0.78 52.1 0.46

Packing plants, fruits, or vegetables

Yes 31.8 90.9 54.6

No 17.3 0.03 93.2 0.60 54.3 0.98

Sorting plants, fruits, or vegetables

Yes 23.7 89.8 54.2

No 19.1 0.45 93.9 0.31 54.4 0.98

Planting or transplanting

Yes 27.3 94.8 49.4

No 16.3 0.06 91.5 0.37 57.4 0.26

Weeding

Yes 24.0 94.2 55.8

No 16.7 0.19 91.2 0.40 52.9 0.68

Thinning

Yes 23.3 94.0 56.4

No 15.1 0.16 90.4 0.35 50.7 0.43

Irrigating

Yes 23.6 89.1 63.6

No 19.2 0.49 94.0 0.23 51.0 0.11

Mixing or loading pesticides

Yes 18.2 90.9 54.6

No 21.0 0.68 93.2 0.60 54.3 0.98

Spraying pesticides

Yes 15.6 95.6 46.7

No 21.7 0.36 91.9 0.41 56.5 0.24
our sample had irrigated fields or orchards.

Slightly more than 20% of workers had mixed,

loaded, or applied pesticide formulations.

When we examined individual metabolites,

we observed differences in the proportion of

workers who had and had not performed a

given job task (Table 3). The proportion of

detectable levels of DMP showed a slight trend

for greater proportions among workers who

performed fieldwork (harvesting or picking,

pruning, loading, packing, or sorting plants,

fruits, or vegetables; weeding, thinning, or irrigating) compared to workers who mixed,

loaded, or applied pesticides; the differences

were significant for workers who packed plants,

fruits, or vegetables and close to significant (p =

0.06) for workers who planted or transplanted.

Notably, workers who mixed, loaded, or

applied pesticides had slightly lower (18.2%),

although nonsignificant, proportions of

detectable DMP compared to those who did

not perform these tasks (21.0%).

Children living in the same household as

adult farmworkers who had performed thinning in the previous 3 months had higher

percentages of detectable levels of composite

dimethyl metabolite concentration in their

urine than those not living with such adult

farmworkers (Table 4). This observation

appears to be attributable to the higher percentages of DMTP found in these children.

By contrast, we found that children of workers who mixed, loaded, or applied pesticide

formulations had a slightly lower, although

nonsignificant, percentage of detectable levels

of dimethyl metabolites. When we examined

differences in the proportion of detectable

levels of DMP and DMDTP in samples from

children, we found no significant differences

on the basis of whether or not the childrens’

parents performed any of the job tasks.

Our analysis of vehicle and house dust

showed varying percentages of detectable samples by job task (Table 5). A similar share of

workers who did and did not harvest or pick

fruits or vegetables had detectable levels of azinphos-methyl in their house and vehicle dust.

This pattern was observed for workers who

reported loading, packing, or sorting plants,

fruits, or vegetables; planting or transplanting;

and irrigating. Workers who thinned orchards

were found to have a greater likelihood of having detectable levels of azinphos-methyl in their

homes and vehicles used for commuting than

those who did not. Workers who pruned vines

or branches or weeded were found to have a

significantly greater proportion of detectable

azinphos-methyl residues in their vehicle dust,

but not in their house dust, than those who did

not. We found that a similar share of workers

who mixed, loaded, or applied pesticide formulations had detectable levels of azinphos-methyl

in their homes and vehicles compared to workers who had not performed these tasks.

When we examined the association

between recent pesticide spraying and selected

job tasks, we found that workers who mixed,

loaded, and applied pesticides were more likely

than other workers to report recent spray activity (Table 6). No other job task was found to

be significantly associated with recent spray

activity.

Discussion

In this study, we found that workers who

thinned crops appeared to have greater levels of

azinphos-methyl residues in their homes and

vehicles than workers who did not thin crops;

this probably contributed to the levels of pesticides to which children in the households were

exposed. The results of this study appear to

support our hypothesis that pesticides brought

home on workers’ bodies, clothing, and shoes

accumulate in the home environment, thus

potentially exposing children and other family

members. Curl et al. (2002) suggested that this

leads to children’s exposure; using the same

data, these authors demonstrated a strong correlation between urinary dimethyl concentrations of adult farmworkers and children living

in the same household.The urinary dimethyl

concentration is the sum of DMP, DMTP,

and DMDTP metabolite concentrations

expressed as micromoles per liter of urine. The

take-home pathway was further demonstrated

by analysis showing a significant correlation

between pesticide concentrations in house dust

and respective vehicle dust (Curl et al. 2002).

Because there is considerable scientific interest

in the manner in which workers are exposed to

pesticides, these findings are potentially important in informing policy and programs that

aim to train farmworkers in pesticide safety.

The presence of a take-home pathway of

pesticide exposure has also been demonstrated

in Oregon by McCauley et al. (2001), who

showed a direct correlation between the number of agricultural workers living in a household and the concentration of azinphos-methyl

found in dust collection from the home. This

finding is consistent with a limited number of

studies that show elevated risk of illness

among children of farmworkers. In a review

of 31 studies, Daniels et al. (1997) showed

greater risk for developing leukemia and brain

cancer among children of farmworkers who

experienced frequent occupational exposure

to pesticides, compared with children of

exterminators. Daniels et al. also reported

kidney cancer, Ewing’s (bone) sarcoma, and

germ cell tumors to be associated with occupational pesticide exposure. That parents’

occupational exposure is linked to the subsequent development of cancer in offspring is

Article | Job task and pesticide exposure

Environmental Health Perspectives • VOLUME 112 | NUMBER 2 | February 2004 145

Table 4. Percent detectable dimethyl urinary metabolites among children 2–6 years of age by farmworker’s job task (n = 211).

DMP DMTP DMDTP

Job task Percent p-Value Percent p-Value Percent p-Value

Harvesting or picking

Yes 21.7 88.8 44.7

No 13.6 0.18 86.4 0.63 44.1 0.93

Pruning

Yes 18.2 89.6 46.8

No 20.2 0.73 87.3 0.62 43.3 0.63

Loading plants, fruits, or vegetables

Yes 16.7 87.8 41.1

No 21.5 0.38 88.4 0.89 47.1 0.39

Packing plants, fruits, or vegetables

Yes 24.4 84.4 55.6

No 18.1 0.34 89.2 0.39 41.6 0.09

Sorting plants, fruits, or vegetables

Yes 17.0 89.9 44.3

No 20.4 0.57 88.2 0.99 41.5 0.15

Planting or transplanting

Yes 15.2 89.9 44.3

No 22.0 0.23 87.1 0.55 44.7 0.96

Weeding

Yes 17.9 87.7 50.0

No 21.0 0.58 88.6 0.85 39.1 0.11

Thinning

Yes 22.8 91.9 44.1

No 13.3 0.10 81.3 0.02 45.3 0.87

Irrigating

Yes 16.1 87.5 42.9

No 20.7 0.46 88.4 0.86 45.2 0.77

Mixing or loading pesticides

Yes 17.8 86.7 35.6

No 19.9 0.75 88.6 0.73 47.0 0.17

Spraying pesticides

Yes 13.0 84.8 39.1

No 21.2 0.22 89.1 0.42 46.1 0.40
also supported by Fear et al. (1998), who used

167,703 childhood death records in England

and Wales to show elevated incidence of kidney cancer among children of men with

potential occupational exposure to pesticides.

Our data show that a significantly greater

proportion of children in households in which

the adult farmworker had performed thinning

had detectable concentrations of dimethyl

metabolites compared with those in which the

adult farmworker had not thinned crops.

However, we found no significant differences

in urinary metabolite concentrations of adult

thinners compared with those who had not

thinned. This finding may be explained by the

longer half-life of pesticides in the home environment, the greater opportunity for children

to be exposed in this environment, or the lessened ability of children’s bodies to metabolize

pesticides.

In the Yakima Valley, thinners may be at

high risk for exposure to pesticides because

they are the first to enter recently sprayed

fields. The region receives scant precipitation,

and orchards are generally irrigated using

sprinklers that direct water upward. Thus, pesticide residues can remain on the foliage for

long periods, thereby enhancing opportunities

for exposure among workers who thin crops or

otherwise have direct contact with the foliage.

Because the half-life of some pesticides is

≥ 2 weeks, it is likely that some farmworkers

enter pesticide-treated fields within the time

that pesticides are present in substantial

amounts (Stewart et al. 2001). De Cock et al.

(1998a, 1998b) reported that exposure intensity for orchard thinning is about twice that of

orchard harvesting or pruning. This may be

due to the workers’ substantial physical contact with tree foliage or to the high dermal

absorption of pesticides such as azinphosmethyl (Simcox et al. 1999). Moreover, the

duration of exposure may be greater for field

workers than for pesticide handlers (Fenske

and Birnbaum 1997); although our analyses

demonstrate that the recency of spray activity

did not account for the relatively high pesticide levels among thinners. In contrast, compared to pesticide handlers, field workers may

be disproportionately affected by a lack of

available work-site laundering facilities, showers, and handwashing facilities, thus prolonging their exposures to pesticides and other

farm chemicals (Ward et al. 2001).

Contrary to our expectation, we found that

workers who reported having mixed, loaded, or

applied pesticide formulations had slightly

lower proportions of detectable residues in

their house dust and vehicle dust than nonhandlers, although these differences were not

significant. This finding is particularly notable

in light of our analyses showing pesticide handlers to be more likely than nonhandlers to

report recent workplace spraying of pesticides.

Pesticide handlers have the greatest risk for

direct exposure to pesticides at times when the

pesticides are most highly toxic. Provisions of

the Worker Protection Standards (U.S. EPA

1992) aim to limit this exposure by requiring

the use of personal protective equipment and

pesticide safety training; however, personal

protective equipment is not required for workers who do not handle pesticides. Thus, our

findings suggest that personal protective equipment confers a relative benefit to those who

work directly with pesticides.

For pesticide mixers, loaders, and applicators, training in pesticide safety may reinforce

the importance of protective practices, and this

attitude may carry over to the home environment, motivating safe practices. Analysis conducted by Thompson et al. (2003) on these

data showed that, compared with nonhandlers,

workers who mixed, loaded, or applied pesticides were significantly more likely to wash

their hands after work, wash their clothing

after wearing one time, and remove their work

clothes before hugging their children.

Moreover, training may foster a greater sense

of control over one’s environment, a factor that

several researchers have found to be directly

associated with the likelihood of engaging in

home protective practices (Arcury et al. 2001;

Austin et al. 2001; Quandt et al. 2001).

Article | Coronado et al.

146 VOLUME 112 | NUMBER 2 | February 2004 • Environmental Health Perspectives

Table 5. Percent detectable azinphos-methyl residues in vehicle and house dust.

Vehicle (n = 190) House (n = 150)

Job task Percent p-Value Percent p-Value

Harvesting or picking

Yes 88.2 87.3

No 84.0 0.44 85.0 0.72

Pruning

Yes 95.5 89.8

No 82.4 0.01 85.2 0.43

Loading plants, fruits, or vegetables

Yes 81.5 87.5

No 91.4 0.05 86.1 0.80

Packing plants, fruits, or vegetables

Yes 84.6 87.5

No 87.8 0.60 86.4 0.88

Sorting plants, fruits, or vegetables

Yes 87.0 93.0

No 87.1 0.99 84.1 0.15

Planting or transplanting

Yes 84.5 86.0

No 88.7 0.41 87.1 0.84

Weeding

Yes 81.9 85.7

No 92.4 0.03 87.7 0.73

Thinning

Yes 93.3 92.8

No 76.1 0.001 75.5 0.003

Irrigating

Yes 87.2 86.5

No 87.1 0.97 86.7 0.97

Mixing or loading pesticides

Yes 87.2 84.9

No 87.1 0.99 87.2 0.73

Spraying pesticides

Yes 87.5 83.9

No 87.0 0.93 87.4 0.61

Masses of dust from 15 vehicles and 54 homes were insufficient for analysis.

Table 6. Association between job task and recent pesticide spray activity (within the past 3 days).

No. Pesticides were sprayed ≤ 3 days

Job task performing task No. (%) p-Value

Harvesting or picking 113 19 (16.8) 0.16

Pruning 59 11 (18.6) 0.81

Loading plants, fruits, or vegetables 75 13 (17.3) 0.49

Packing plants, fruits, or vegetables 32 5 (15.6) 0.52

Sorting plants, fruits, or vegetables 42 6 (14.3) 0.31

Planting or transplanting 65 16 (24.6) 0.19

Weeding 87 16 (18.4) 0.67

Thinning 106 19 (17.9) 0.44

Irrigating 48 14 (29.2) 0.05

Mixing or loading pesticides 44 17 (38.6) < 0.001

Spraying pesticides 43 17 (39.5) < 0.001

p-Values are based on chi-square tests comparing job task (yes, no) and recent pesticide exposure (≤ 3 days or ≥ 4 days).
Article | Job task and pesticide exposure

Environmental Health Perspectives • VOLUME 112 | NUMBER 2 | February 2004 147

Also, reentry intervals, which is the major

form of protection for fieldworkers, may inadequately protect workers from pesticide exposure. For azinphos-methyl, workers are

allowed to return to the fields 14 days after the

pesticide has been sprayed. The reentry intervals and provisions for personal protective

equipment use of fieldworkers are established

for the workers themselves. Consideration for

potential exposure to children is not a basis for

the standard, although this exposure appears

to affect them.

Farmworkers as a group are difficult populations to assess, both in term of identifying

them and adequately assessing their exposure

levels (Kamel et al. 2001; Zahm and Blair

2001). The previous studies we cited (Fenske

et al. 1999; Karr et al. 1992; Loewenherz et al.

1997; McCurdy et al. 1994; Simcox et al.

1999) have generally been convenience samples or samples obtained from a small selection

of farms (where workplace norms may confer

greater protection), or the samples may have

been limited to certain farm tasks (such as

mixing, loading, or applying pesticides) and it

is not possible to determine whether the samples represent the larger population of workers

within the same region. The strength of this

study is the large study sample and the recruitment of both fieldworkers and pesticide mixers, loaders, and applicators.

One potential disadvantage of our study is

that our samples were collected relatively late

in the season. Nevertheless, we found differential patterns of exposure in the home environment, which lends support to the theory

that pesticide levels persist in this setting. We

also found that all pesticide mixers, loaders,

and applicators in our study had detectable

levels of dimethyl compounds in their urine,

which suggests recent exposure.

Our findings suggest that farmworkers who

thin crops are more likely than those who do

not perform this task to have detectable concentrations of azinphos-methyl in their homes,

where the children appear to be affected. Future

investigations should examine the association

between fieldworkers’ use of protective clothing, such as gloves, hats, and other equipment,

and levels of personal exposure to pesticides

and concentrations of pesticides in the home

environment.

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