Research

A Section 508–conformant HTML version of this article
is available at https://doi.org/10.1289/EHP504.

Prenatal Residential Proximity to Agricultural Pesticide Use and IQ in
7-Year-Old Children
Robert B. Gunier, Asa Bradman, Kim G. Harley, Katherine Kogut, and Brenda Eskenazi
School of Public Health, University of California, Berkeley, Berkeley, California, USA

BACKGROUND: Residential proximity to agricultural pesticide use has been associated with neural tube defects and autism, but more subtle outcomes
such as cognition have not been studied.
OBJECTIVES: We evaluated the relationship between prenatal residential proximity to agricultural use of potentially neurotoxic pesticides and neurodevelopment in 7-year-old children.
METHODS: Participants included mothers and children (n = 283) living in the agricultural Salinas Valley of California enrolled in the Center for the
Health Assessment of Mothers and Children of Salinas (CHAMACOS) study. We estimated agricultural pesticide use within 1 km of maternal residences during pregnancy using a geographic information system, residential location, and California’s comprehensive agricultural Pesticide Use
Report data. We used regression models to evaluate prenatal residential proximity to agricultural use of five potentially neurotoxic pesticide groups
(organophosphates, carbamates, pyrethroids, neonicotinoids, and manganese fungicides) and five individual organophosphates (acephate, chlorpyrifos,
diazinon, malathion, and oxydemeton-methyl) and cognition in 7-year-old children. All models included prenatal urinary dialkyl phosphate metabolite
concentrations.
RESULTS: We observed a decrease of 2.2 points [95% confidence interval (CI): –3.9, –0.5] in Full-Scale IQ and 2.9 points (95% CI: –4.4, –1.3) in
Verbal Comprehension for each standard deviation increase in toxicity-weighted use of organophosphate pesticides. In separate models, we observed
similar decrements in Full-Scale IQ with each standard deviation increase of use for two organophosphates (acephate and oxydemeton-methyl) and
three neurotoxic pesticide groups (pyrethroids, neonicotinoids, and manganese fungicides).
CONCLUSIONS: This study identified potential relationships between maternal residential proximity to agricultural use of neurotoxic pesticides and
poorer neurodevelopment in children. https://doi.org/10.1289/EHP504

Introduction
In 2007, 311 million kg (684 million pounds) of pesticide active
ingredients were used in agriculture in the United States (Grube
et al. 2011). California, the state with the largest agricultural output, uses 25% of all U.S. agricultural pesticides, or 84.5 million
kg (186 million pounds) annually [California Department of
Pesticide Regulation (CDPR) 2014]. Although recent studies
have demonstrated widespread organophosphate (OP) pesticide
exposures in the general U.S. population, including pregnant
women and children [Whyatt et al. 2003; Berkowitz et al. 2003;
Lu et al. 2001; Adgate et al. 2001; Centers for Disease Control
and Prevention (CDC) 2009], exposures are often higher in agricultural populations (Lu et al. 2004; Fenske et al. 2002). Among
pregnant women in the Center for the Health Assessment of
Mothers and Children of Salinas (CHAMACOS) study, all of
whom lived in an agricultural region, and many of whom either
worked in agriculture or lived with people who did, OP urinary
metabolites or dialkylphosphate (DAP) levels were ∼40% higher
than those in a representative sample of U.S. women of childbearing age (Bradman et al. 2005). We observed adverse associations in the CHAMACOS study between prenatal maternal DAP

Address correspondence to R. Gunier, Center for Environmental Research
and Children’s Health (CERCH), School of Public Health, University of
California at Berkeley, 1995 University Ave., Suite 265, Berkeley, CA 94704.
Telephone: (510) 847-3858. E-mail: gunier@berkeley.edu.
Supplemental Material is available online (https://doi.org/10.1289/EHP504).
A.B. is a volunteer member of the Board for The Organic Center, a nonprofit
organization addressing scientific issues around organic food and agriculture.
All other authors declare they have no actual or potential competing financial
interests.
Received 8 January 2016; Revised 13 May 2016; Accepted 14 June 2016;
Published 25 May 2017.
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Environmental Health Perspectives

concentrations and children’s performance on the Bayley Scales
of Infant Development at 2 y (Eskenazi et al. 2007), measures of
attention at 5 y (Marks et al. 2010), and on the Wechsler
Intelligence Scale for Children (WISC) at 7 y (Bouchard et al.
2011a). Several studies in other populations have similarly
reported adverse associations of prenatal exposure to OP pesticides and child neurodevelopment (Engel et al. 2011; Rauh et al.
2011), but few studies have examined the effects of other potentially neurotoxic pesticides on child cognitive development.
Populations residing in agricultural areas may be exposed to a
complex mixture of neurotoxic pesticides through pesticide drift
and para-occupational exposures (Fenske et al. 2002). Some of
these pesticide classes—including OPs as well as carbamates—
share at least one mode of action, depression of acetylcholinesterase
(AChE), and there is in vitro evidence that there may be additive inhibitory effects from exposure to certain pesticide mixtures (Mwila
et al. 2013). Furthermore, although biomarkers such as DAP metabolites are an important tool for assessing exposures to pesticides,
several challenges limit the utility of pesticide biomarkers in epidemiologic analyses. For example, many pesticides have a short halflife in the body, and biomarkers reflect only very recent exposures
(on the order of hours to days) (Bradman et al. 2013). In addition, no
biomarkers are available for some pesticides, leaving only environmental concentrations or modeling to characterize exposure.
Since 1990, all agricultural pesticide applications in California
have been compiled in the uniquely comprehensive Pesticide Use
Reporting (PUR) database. In several studies, PUR data have
been shown to correlate with pesticide levels in various media.
For example, we have shown significant associations between
nearby use of specific pesticides based on the PUR data and levels in house dust (Harnly et al. 2009; Gunier et al. 2011), and
moderate to strong associations (R2 ∼ 0:28 − 0:65) between agricultural use of malathion, chlorpyrifos, and diazinon with community air samples (Harnly et al. 2005). In addition, several
epidemiologic studies conducted in California have shown that
higher nearby agricultural pesticide use is associated with various
adverse health outcomes, including OP and fungicide use with
Parkinson disease (Costello et al. 2009; Wang et al. 2011), OP
and pyrethroid use with autism (Shelton et al. 2014) and birth

057002-1

 defects (Carmichael et al. 2014), organochlorine pesticide use
with autism (Roberts et al. 2007), and the use of carbamates
(benomyl and methomyl) and the neonicotinoid imidacloprid
with neural tube defects in children (Rull et al. 2006; Yang et al.
2014). To our knowledge, there have not been any previous studies evaluating residential proximity to reported agricultural
pesticide use and more subtle neurodevelopmental outcomes
such as cognitive function in children. In the present study,
we evaluated the relationship between prenatal residential
proximity to agricultural use of a variety of neurotoxic pesticides and neurodevelopment using WISC assessed at 7 y of
age because this test provides a more specific and reliable
measure of cognition than earlier neurodevelopmental assessments conducted in our cohort and may have greater implications for school performance.

Methods
Study Population
Between October 1999 and October 2000, we enrolled 601 pregnant women as part of the CHAMACOS study. Women were eligible if they were  18 y of age, <20 wk gestational age, eligible for
California’s low-income health care program (MediCal), spoke
English or Spanish, and were planning to deliver at the county hospital. We followed the women through the delivery of 537 live-born
children. We excluded twins (n = 10) and children with medical
conditions that could affect neurodevelopmental assessment (n = 4,
one child each with Down syndrome, autism, deafness, and hydrocephalus). We included children who had a neurodevelopmental
assessment at 7 y (n = 330) and whose prenatal residential location
was known for at least 75 d per trimester during two or more trimesters of pregnancy (n = 283). We excluded two participants who did
not have prenatal measurements of DAP metabolites. Our final
study population for this analysis was 283. The mothers of children
included in our analyses were more likely (p < 0:05) than those not
included to be married (85% vs. 77%), nonsmokers during pregnancy (96% vs. 92%), and older at delivery (mean ¼ 26:9
vs: 24:9 y) than the mothers of children who were not included in
these analyses; otherwise, the two populations were similar demographically. Written informed consent was obtained from all
women, and oral assent was obtained from all children at 7 y of age;
all research was approved by the University of California,
Berkeley, Committee for the Protection of Human Subjects before
the study began.

Cognitive Assessment
We used the Wechsler Intelligence Scale for Children, fourth edition (WISC-IV) (Wechsler 2003) to assess cognitive abilities
when the children were 7 y of age. All assessments were completed by a single bilingual psychometrician, who was trained
and supervised by a pediatric neuropsychologist. Scores for four
domains were calculated based on the following subtests: Verbal
Comprehension (composed of Vocabulary and Similarities subtests),
Perceptual Reasoning (Block Design and Matrix Reasoning subtests),
Working Memory (Digit Span and Letter–Number Sequencing subtests), and Processing Speed (Coding and Symbol Search subtests).
We administered all subtests in the dominant language of the child,
which was determined through administration of the oral vocabulary
subtest of the Woodcock-Johnson/Woodcock-Muñoz Tests of
Cognitive Ability in both English and Spanish (Woodcock and
Muñoz-Sandoval 1990) at the beginning of the assessment.
Among participants included in these analyses, 68% of the children were tested in Spanish, and 32% of the children were tested
in English. The psychometrician was blinded to exposure status.
Environmental Health Perspectives

We standardized WISC-IV scores against U.S. population–based
norms for English- and Spanish-speaking children. We did not
administer Letter–Number Sequencing or Symbol Search subtests for the first 3 mo of assessments; therefore, 27 participants
lacked scores for Processing Speed and Working Memory
domains. A Full-Scale IQ was available for 255 children.

Maternal Interviews and Assessments
Bilingual interviewers conducted maternal interviews in Spanish
or English twice during pregnancy (∼13 and 26 wk gestation), after delivery, and when the children were 6 mo and 1, 2, 3.5, 5, 7,
and 9 y of age. Interviews obtained demographic information
including maternal age, education, country of birth, number of
years living in the United States, marital status, paternal education, and family income. We collected residential history information by asking participants if they had moved since the last
interview and, if so, the dates of all moves. We conducted home
visits shortly after enrollment (∼16 wk gestation) and when the
child was 6 mo of age. For both visits, the latitude and longitude
coordinates of the participant’s home were determined using a
handheld global positioning system unit. Residential mobility
during pregnancy was common in our cohort, with 53% of all
participants moving at least once during pregnancy. For the present analysis, we included women in the sample if their residential
location was known for ≥75 d per trimester for at least two trimesters of pregnancy.
Mothers were administered the Peabody Picture Vocabulary
Test (PPVT) for English speakers or the Test de Vocabulario en
Imagenes Peabody (TVIP) for Spanish speakers at the 6-mo visit
to assess verbal intelligence (Dunn and Dunn 1981). If maternal
PPVT or TVIP scores were unavailable from the 6-mo visit, we
used scores from the re-administration of the test conducted at a
9-y visit (n = 5) or assigned the mean score of the sample (n = 2).
A short version of the HOME (Home Observation for Measurement
of the Environment) inventory was completed during the 7-y visit
(Caldwell and Bradley 1984).

Geographic-Based Estimates of Agricultural Pesticide Use
We estimated agricultural pesticide use near each woman’s residence during pregnancy using California PUR data from 1999–
2001 (CDPR 2015). We selected potentially neurotoxic pesticides with agricultural use in our study area (Monterey County,
CA) during the prenatal period, including fifteen OPs and six carbamates (see Table S1), two manganese (Mn)-based fungicides
(maneb and mancozeb), eight pyrethroids (permethrin, cypermethrin, tau-fluvalinate, cyfluthrin, fenpropathrin, lambdacyhalothrin, bifenthrin, and esfenvalerate), and one neonicotinoid
(imidacloprid). The PUR data include the amount (in kilograms)
of active ingredient applied, the application date, and the location, defined as a 1-mi2 section (1:6 km × 1:6 km) defined by the
Public Land Survey System (PLSS). We edited the PUR data to
correct for likely outliers that had unusually high application rates
by replacing the amount of pesticide applied based on the median
application rate for that pesticide and crop combination (Gunier
et al. 2001). For each woman, we estimated the amount of all pesticides in each pesticide class used within a 1-km radius of the
pregnant woman’s residence using the latitude and longitude
coordinates and a geographic information system. In all cases,
the 1-km buffer around the home included more than one PLSS
section; thus, we weighted the amount of pesticide applied in
each section by the proportion of land area that was included in
the buffer. We selected a 1-km buffer distance for this analysis
because it best captures the spatial scale most strongly correlated
with measured agricultural pesticide concentrations in house-dust

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 samples (Harnly et al. 2009; Gunier et al. 2011). Detailed
descriptions of the equations and methods that we used to calculate nearby pesticide use have been published previously (Gunier
et al. 2011). We estimated pesticide use within 1 km of the maternal residence during each trimester of pregnancy for participants
with residential location information available for two or more
trimesters (n = 283) and computed the average pesticide use during pregnancy by summing the trimester-specific values and
dividing by the number of trimesters included. We also created
individual variables for nearby use of each of the five individual
OP pesticides (acephate, chlorpyrifos, diazinon, malathion, and
oxydemeton-methyl) with the highest use in our study area during the prenatal period (Table S1).

Toxicity Weighting and Neurotoxic Pesticide Index
In addition to examining the simple sum of pesticide use in each
class, we also used relative potency factors (RPFs) to generate
class-specific toxicity-weighted sums to account for differences
in the neurotoxicity of individual pesticides in OP and carbamate
classes. The RPF of a chemical is the ratio of the relevant toxicological dose of an index chemical to the relevant toxicological
dose of the chemical of interest. Currently, RPFs are available for
OP and carbamate pesticides [U.S. Environmental Protection
Agency (EPA) 2006, 2007], but not for neonicotinoids, pyrethroids, or Mn-fungicides. Thus, we were only able to create
toxicity-weighted sum variables for OPs and carbamates. We calculated the toxicity-weighted use for each OP or carbamate pesticide, expressed as kg-equivalents of chlorpyrifos, by multiplying
the kilograms of pesticide used within 1 km of the maternal residence during each trimester for each pesticide by the RPF of that
pesticide, and summing to create the toxicity-weighted use for
the fifteen OP and six carbamate pesticides. Additionally,
because these pesticides share a common mechanism of toxicity
[acetylcholinesterase (AChE) inhibition], we also generated a
toxicity-weighted sum for OPs and carbamates combined (Jensen
et al. 2009; U.S. EPA 2002). The RPFs, total kilograms and
toxicity-weighted kilograms of use in the Salinas Valley in 2000
for each OP and carbamate pesticide are provided in Table S1.
Finally, we created a rank index of neurotoxic pesticide use
that included the five pesticide classes of interest (i.e., OPs,
carbamates, neonicotinoids, pyrethroids, and Mn-fungicides) by
generating a percentile rank of the participants from lowest to
highest use for each neurotoxic pesticide class and then calculating the average percentile rank across the five classes. We also
explored principal components analysis (PCA) as a method for
combining pesticide use across the five different classes of neurotoxic pesticides.

Data Analysis
We log10-transformed continuous pregnancy average and trimesterspecific sums of pesticide use (kilograms=year þ 1) to reduce heteroscedasticity and the influence of outliers and to improve the linear fit of the model. The scores for Full-Scale IQ and for the four
subdomains were normally distributed and were modeled as continuous outcomes.
We selected model covariates a priori based on factors associated with infant neurodevelopment in previous analyses [i.e.,
child’s exact age at assessment, sex, maternal PPVT score (continuous) and maternal education (< sixth grade vs:   seventh
grade)]. We considered the following variables as additional
covariates in our models (Table 1): maternal country of birth,
maternal age at delivery, marital status at enrollment, and maternal depression [using the Center for Epidemiologic Studies
Depression Scale (CES-D)] ( 16 on CES-D) at the child’s 7-y
Environmental Health Perspectives

Table 1. CHAMACOS Study cohort characteristics (n = 283).
Cohort characteristic
Maternal country of birth
Mexico
United States and other
Maternal age at delivery (years)
18–24
25–29
30–34
35–45
Maternal education
  6th grade
≥ 7th grade
Marital status at enrollment
Married/living as married
Not married
Paternal education
  6th grade
≥ 7th grade
Family income at 7-y visit
< Poverty level
  Poverty level
Maternal depression at 7-y visit
Yes
No
Sex
Female
Male
Language of WISC-IV tests
Spanish
English

n (%)
249 (88.0)
34 (12.0)
107 (37.8)
99 (35.0)
49 (17.3)
28 (9.9)
132 (46.6)
151 (53.4)
239 (84.4)
44 (15.6)
129 (60.6)
84 (39.4)
203 (71.7)
80 (28.3)
78 (27.6)
205 (72.4)
152 (53.7)
131 (46.3)
193 (68.2)
90 (31.8)

Note: WISC-IV, Wechsler Intelligence Scale for Children, fourth edition.

visit. In addition, we considered covariates collected at each visit
including housing density (number of persons per room), HOME
score (continuous), household poverty level (< federal poverty
level vs:   federal poverty level), presence of father in the home
(yes/no), maternal work status, location of assessment (field
office or recreational vehicle), and season of assessment. We
imputed missing values (<10% missing) at a visit point using
data from the nearest available visit.
We retained covariates that were significant (p < 0:2) at any
time point in the multivariate regression models and used the
same covariates in all models. We fit separate regression models
for each pesticide class or individual pesticide; we also fit models
including multiple classes or pesticides.
We used generalized additive models (GAMs) with a threedegrees-of-freedom cubic spline function to test for nonlinearity.
None of the digression from linearity tests was significant
(p < 0:05); therefore, we expressed neurotoxic pesticide use linearly (on the log10 scale) in regression models.
We controlled for DAP metabolites of OP insecticides measured in maternal urine samples (Bradman et al. 2005) collected during prenatal interviews at 13 and 26 wk gestation (n = 283) in all
models. Prenatal DAPs and agricultural use of OPs were not highly
correlated in our cohort (q = 0:04); therefore, we believe that they
provide complementary measures of exposure to OP pesticides. We
averaged the two prenatal DAP measurements and used log10-transformed concentrations (nanomoles/liter) in our analyses. In separate sensitivity analyses, we controlled for exposure to other
neurotoxicants, which we have previously found to be related to
child IQ in our cohort (Eskenazi et al. 2013; Gaspar et al. 2015).
Specifically, we considered log10-transformed lipid-adjusted concentrations (nanograms/gram-lipid) measured in prenatal maternal
blood samples of p,p′-dichlorodiphenyltrichloroethylene (DDT), p,p′dichlorodiphenyldichloroethylene (DDE) (n = 219) (Bradman et al.
2007), and polybrominated diphenyl ether flame retardants (PBDEs)
(n = 221) (Castorina et al. 2011). We used the sum of the four major

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 Table 2. Total neurotoxic pesticide use in Monterey County in 2000 and distributions of agricultural use within 1 km of the maternal residence during pregnancy (n = 283).
Neurotoxic pesticides

Kilograms used (2000)
Monterey

p25

244,696
34,792
25,357
56,434
37,161
28,767
964,130
59,914
335,611
1,299,741
7,103
16,386
154,698

31
2
1
11
0
2
59
3
14
95
1
1
25

OPs
Acephate
Chlorpyrifos
Diazinon
Malathion
Oxydemeton-methyl
OPs toxicity weighted
Carbamates
Carbamates toxicity weighted
Carbamates and OPs toxicity weighted
Neonicotinoids
Pyrethroids
Mn-fungicides

Kilograms used within 1 km of residence during pregnancy
p50
p75
Max
GM (GSD)
93
10
9
22
2
11
331
16
66
485
3
4
62

218
29
29
50
19
24
891
49
291
1,379
6
15
139

1,615
354
331
579
422
260
8,587
618
9,222
9,774
34
79
960

75 (5)
9 (4)
8 (5)
23 (3)
5 (6)
9 (4)
175 (9)
16 (5)
66 (7)
270 (9)
4 (2)
6 (3)
54 (4)

Notes: GM, geometric mean; GSD, geometric standard deviation; Max, maximum; Mn, manganese; OPs, organophosphates; p25, 25th percentile; p50, 50th percentile; p75, 75th
percentile.

congeners (BDE-47, BDE-99, BDE-100, and BDE-153) to estimate
PBDE exposure (Eskenazi et al. 2013).
In other sensitivity analyses, we excluded outliers identified
with studentized residuals >3. To control for potential selection
bias resulting from loss to follow-up, we ran regression models
with weights determined as the inverse probability of inclusion in
our analyses at each time point (Hogan et al. 2004). We determined the probability of inclusion using multiple logistic regression models with baseline covariates as potential predictors.

Results
Most mothers were born in Mexico (88.0%), under 30 y of age at
delivery (72.8%), and married or living as married (84.4%) at the
time of enrollment (Table 1). Nearly half of the mothers (46.6%)
and most fathers (60.6%) had a sixth-grade education or less, and
most families (71.7%) were living below the poverty level at the
time of the 7-y visit. Slightly more than half of the children were
girls (53.7%), and most children completed their WISC-IV
assessment in Spanish (68.2%).
The distributions of agricultural use of neurotoxic pesticides
within 1 km of maternal residences during pregnancy are shown
in Table 2. The most heavily used pesticide class was OPs, followed by Mn-fungicides. The geometric mean (GM) and geometric standard deviation (GSD) for the cumulative use of 15 OP
pesticides within 1 km of maternal residences during pregnancy
was 75 (5) kg. For individual OP pesticides, the GM (GSD)
ranged from 5 (6) kg for malathion to 23 (3) kg for diazinon, and
the use of these five individual OP pesticides was moderately
(0.40 for malathion and diazinon) to highly (0.91 for acephate
and oxydemeton-methyl) correlated. The GM (GSD) of the other

neurotoxic pesticide groups ranged from 4 (2) kg for neonicotinoids to 54 (4) kg for Mn-fungicides. There was moderate to
high correlation (0:68 − 0:90) between the use of the five different neurotoxic pesticide groups within one kilometer of the
maternal residence during pregnancy (Table S2).

OP Pesticides
In general, IQ scores decreased across all domains with increasing use of OP pesticides within 1 km of the maternal residence
during pregnancy. Each SD increase in toxicity-weighted OP use
during pregnancy was associated with an estimated 2.2-point
[95% confidence interval (CI): –3.9, –0.5] (Table 3) decrease in
Full-Scale IQ, which was very similar to but slightly greater than
that for the nonweighted use of all OP pesticides combined (–2.1
points; 95% CI: –3.8, –0.3) (Table 4). A 1-SD increase in
toxicity-weighted OP pesticide use during pregnancy was also
associated with a 2.9-point decrease in Verbal Comprehension
scores (95% CI: –4.4, –1.3) (Table 3). The results were similar in
the unadjusted and adjusted models. For the other WISC
domains, there was a nonsignificant decrease of ∼1.4 points per
SD increase in toxicity-weighted OP pesticide use. The results
were similar whether or not we included the maternal prenatal
urinary DAP concentrations in the model. In fact, we observed
independent and similar decreases in WISC scores for both a
1-SD increase in prenatal urinary DAPs and a 1-SD increase in
toxicity-weighted OP pesticide use when both exposures were
included in the same model (Table 3).
In separate adjusted models for individual OP pesticides
(Table 4), there was a 2.3-point decrease in Full-Scale IQ for

Table 3. Unadjusted and adjusted associations between an SD increase in toxicity-weighted OP pesticide use within 1 km of maternal residence and urinary
DAPs during pregnancy included in the same model and IQ scales at 7 y of age.

Cognitive test
(WISC-IV Scale)
Working Memory
Processing Speed
Verbal Comprehension
Perceptual Reasoning
Full-Scale IQ

n
256
256
283
283
255

Unadjusted model
Toxicity-weighted
OP pesticides (kg)
b
(95% CI)
–0.9
–0.9
–3.5
–1.2
–2.1

(–2.7, 0.8)
(–2.6, 0.9)
(–5.5, –1.5)**
(–3.1, 0.7)
(–4.0, –0.3)*

Adjusteda models

b
–1.4
–1.3
–2.9
–1.4
–2.2

Toxicity-weighted
OP pesticides (kg)
(95% CI)
(–3.1, 0.4)
(–3.0, 0.5)
(–4.4, –1.3)**
(–3.3, 0.5)
(–3.9, –0.5)*

Urinary DAPs (nmol/L)
b
(95% CI)
–1.7
–1.2
–2.8
–1.7
–2.4

(–3.3, –0.1)*
(–2.8, 0.4)
(–4.3, –1.4)**
(–3.5, 0.1)
(–4.0, –0.9)**

Notes: CI, confidence interval; DAPs, dialkylphosphates; OPs, organophosphates; WISC-IV, Wechsler Intelligence Scale for Children, fourth edition.
a
Adjusted for child’s age at assessment, sex, language of assessment, maternal education, maternal intelligence, maternal country of birth, maternal depression at 7-year visit, Home
Observation for Measurement of the Environment (HOME) Score at 7-year visit and household poverty level at 7-year visit. *p < 0:05. **p < 0:01.

Environmental Health Perspectives

057002-4

 Table 4. Adjusted association between a standard deviation increase in neurotoxic pesticide use within one kilometer of residence during pregnancy and IQ
scales at 7 y of age from separate models for each exposure.

Neurotoxic pesticides
OPs
Acephate
Chlorpyrifos
Diazinon
Malathion
Oxydemeton–methyl
OPs toxicity weighted
Carbamates
Carbamates toxicity weighted
Carbamates and OPs toxicity
weighted
Neonicotinoids
Pyrethroids
Mn-fungicides
Rank index of 5 neurotoxic groups

Full-Scale IQ
(n = 255)
b
(95% CI)

Working Memory
(n = 256)
b
(95% CI)

Processing Speed
(n = 256)
b
(95% CI)

Perceptual
Reasoning (n = 283)
b
(95% CI)

Verbal
Comprehension
(n = 283)
b
(95% CI)

–2.1
–2.3
–1.4
–1.7
–0.8
–2.3
–2.2
–1.2
–1.3
–2.1

(–3.8, –0.3)
(–3.9, –0.6)**
(–3.0, 0.2)
(–3.4, 0.1)
(–2.5, 0.8)
(–4.0, –0.7)**
(–3.9, –0.5)**
(–2.8, 0.4)
(–2.9, 0.3)
(–3.7, –0.4)*

–1.3
–1.4
–1.3
–1.3
–0.8
–1.5
–1.4
–0.4
–0.6
–1.1

(–3.1, 0.4)
(–3.1, 0.3)
(–3.0, 0.3)
(–3.0, 0.5)
(–2.4, 0.9)
(–3.2, 0.2)
(–3.1, 0.4)
(–2.0, 1.2)
(–2.2, 1.1)
(–2.9, 0.6)

–1.1
–1.4
–0.3
–1
0.8
–1.5
–1.3
–0.2
–0.1
–1

(–2.9, 0.7)
(–3.1, 0.2)
(–1.9, 1.4)
(–2.8, 0.7)
(–0.9, 2.5)
(–3.2, 0.2)
(–3.0, 0.5)
(–1.8, 1.4)
(–1.7, 1.5)
(–2.7, 0.7)

–1.8
–1.8
–0.8
–1.7
–1.2
–1.5
–1.4
–1.1
–1
–1.4

(–3.7, 0.1)
(–3.6, 0.1)
(–2.6, 1.1)
(–3.6, 0.2)
(–3.0, 0.6)
(–3.4, 0.4)
(–3.3, 0.5)
(–2.9, 0.7)
(–2.8, 0.8)
(–3.3, 0.5)

–2.5
–2.7
–2.2
–1.6
–1.3
–2.8
–2.9
–2.4
–2.5
–2.9

(–4.1, –1.0)**
(–4.3, –1.2)**
(–3.7, –0.7)**
(–3.2, –0.1)*
(–2.8, 0.2)
(–4.3, –1.3)**
(–4.4, –1.3)**
(–3.9, –1.0)**
(–4.0, –1.0)**
(–4.5, –1.4)**

–1.7
–2
–2
–2

(–3.3, 0.0)*
(–3.7, –0.3)*
(–3.7, –0.2)
(–3.7, –0.4)*

–1.1
–1.5
–1.2
–1.3

(–2.8, 0.5)
(–3.2, 0.2)
(–2.9, 0.6)
(–3.0, 0.4)

–0.8
–1.1
–1.2
–1

(–2.4, 0.9)
(–2.8, 0.6)
(–2.9, 0.6)
(–2.7, 0.7)

–1.9
–2.1
–1.7
–1.9

(–3.8, –0.1)*
(–4.0, –0.2)*
(–3.6, 0.1)
(–3.8, –0.1)*

–1.9
–1.8
–2.1
–2.4

(–3.5, –0.3)*
(–3.4, –0.3)*
(–3.7, –0.6)**
(–4.0, –0.9)**

Notes: Mn, manganese. Adjusted for child's age at assessment, sex, language of assessment, maternal education, maternal intelligence, maternal country of birth, maternal depression
at 7-y visit, Home Observation for Measurement of the Environment (HOME) score at 7-y visit, household poverty level at 7-year visit and prenatal urinary dialkylphosphates.
*p < 0:05. **p < 0:01.

each SD increase in acephate (95% CI: –3.9, –0.6) or
oxydemeton-methyl (95% CI: −4.0, −0.7). Although they were
also negatively related, there was no significant relationship
between the use of chlorpyrifos, malathion, or diazinon and FullScale IQ. There was a significant negative relationship between
agricultural use of acephate, chlorpyrifos, diazinon, and
oxydemeton-methyl and Verbal Comprehension. There was no
relationship with Working Memory, Processing Speed, or
Perceptual Reasoning for any of the individual OPs evaluated.
We also included the top 5 OP pesticides in the same model
(Model 1, Table S3) and found no association (p < 0:05) with
Full-Scale IQ for any individual OP pesticide, but the strongest
relationship was with oxydemeton-methyl (–4.2 points; 95% CI:
–10.1, 1.8).

Other Pesticide Groups
We observed a nearly universal trend of lower IQ scores for all
domains with greater use of individual OP pesticides and other
potentially neurotoxic pesticide groups within 1 km of the maternal residence during pregnancy (Table 4). The combined
toxicity-weighted use of OPs and carbamates was associated with
decreased Full-Scale IQ, although the unweighted and toxicityweighted use of carbamates alone was not significantly associated
with Full-Scale IQ. In separate models with the other neurotoxic
pesticide groups, the use of neonicotinoids, pyrethroids, and Mnfungicides was each significantly associated (p < 0:05) with an
approximately 2-point decrease in Full-Scale IQ, Perceptual
Reasoning, and Verbal Comprehension (Table 4).
In a single model that included all five neurotoxic pesticide
groups, the strongest association with Full-Scale IQ was for
toxicity-weighted OP pesticide use with a 2.8-point decrease
(95% CI: –6.8, 1.3) for each SD increase (Model 2, Table S3).
The associations with IQ scales were nearly identical for the first
component from PCA, which explained ∼80% of the variance
and weighted the five neurotoxic pesticide groups equally, and
the average rank index, with a 2.0-point decrease (95% CI: –3.7,
–0.4) in Full-Scale IQ for each SD increase in estimated exposure
(Table 4).
Environmental Health Perspectives

Sensitivity Analyses
For all analyses, point estimates were similar but confidence
intervals were wider when we restricted the study population to
those mothers with residential location known for three trimesters
of pregnancy (n = 150 with Full-Scale IQ), and associations were
weaker when we included all mothers with residential location known for one trimester during pregnancy (n = 284 with
Full-Scale IQ) (data not shown). Our results were very similar
after excluding the relatively few outliers (1–3 participants per
exposure/outcome) based on studentized residuals (data not
shown). Associations between prenatal neurotoxic pesticide
use and WISC scores at 7 y of age became slightly stronger
when we used inverse probability weighting to adjust for
potential selection bias (data not shown). Including other prenatal exposures that have been related to WISC scores at 7 y
of age (DDT/DDE and PBDEs) reduced the number of participants (n = 191 for Full-Scale IQ), but the results were very
similar for toxicity-weighted OP pesticide use and the other
neurotoxic pesticide groups for all WISC scales with and
without inclusion of these other prenatal exposures in the
models.

Discussion
We observed an inverse relationship between the agricultural use
of OP pesticides within 1 km of maternal residences during pregnancy and cognitive development in children at 7 y of age. For
each standard deviation increase in agricultural use of total OPs
(237 kg) or toxicity-weighted OPs, there was a 2-point decrease
(15% of a standard deviation) in Full-Scale IQ. To put these findings in perspective, other authors have estimated that each 1point decrease in IQ decreases worker productivity by ∼2%
(Grosse et al. 2002), reducing lifetime earnings by US$18,000 in
2005 dollars (Nedellec and Rabl 2016). The results were independent of prenatal urinary DAP concentrations in the model,
and the effect estimates of nearby OP use and urinary DAPs were
of similar magnitude. These independent associations suggest
that our previous observation of a relationship between prenatal
urinary DAPs and IQ (Bouchard et al. 2011a) did not completely
account for exposure to OP pesticides during pregnancy and that
using both urinary DAPs and PUR data seems to provide a more

057002-5

 complete characterization of OP pesticide exposure. Urinary DAP
concentrations provide an estimate of exposure to some, but not all,
of the OP pesticides we evaluated using PUR data (Castorina et al.
2010) and primarily reflect dietary exposures (McKone et al. 2007;
Bradman et al. 2015). The two individual OP pesticides that had the
strongest inverse relationship with Full-Scale IQ were acephate and
oxydemeton-methyl, but agricultural use of these two pesticides was
highly correlated (r = 0:91). It is important to note that although
oxydemeton-methyl devolves to urinary DAPs, acephate does not; it
is also important to note that oxydemeton-methyl is the most toxic of
all the OPs used in the Salinas Valley (∼11 times more toxic than
acephate, based on the RPF).
Agricultural use of other potentially neurotoxic pesticide
classes was correlated with the use of OPs, and there were also significant inverse associations between Full-Scale IQ and nearby agricultural use of pyrethroid insecticides, Mn-based fungicides
(mostly maneb), and a neonicotinoid insecticide (imidacloprid).
The combined agricultural use of pesticides from five neurotoxic
pesticide classes based on an average rank index and PCA produced
similar results to those observed for toxicity-weighted OP pesticide
use alone, making it difficult to determine whether OP pesticide use
alone is driving the relationship or if the results are caused by the
combined use of neurotoxic pesticides that are highly correlated.
This is the first study to evaluate the relationship between
cognitive abilities in children and reported agricultural use of
neurotoxic pesticides near maternal residences during pregnancy.
A recent study conducted in Spain that used residential proximity
to agricultural fields as a proxy for pesticide exposure observed
an inverse relationship between postnatal, but not prenatal, hectares of crops near the residence and Full-Scale IQ, Verbal
Comprehension, and Processing Speed in children 6–11 y of age
(González-Alzaga et al. 2015). A study in California utilizing
PUR data found that any agricultural use of OPs or pyrethroids
within 1.5 km of maternal residences during the third trimester of
pregnancy compared with no agricultural use of these pesticides
was associated with an approximately doubled risk of autism
spectrum disorder (Shelton et al. 2014). Higher concentrations of
pyrethroid metabolites in children’s urine have been associated
with an increased risk of behavioral problems in school-age children (Oulhote and Bouchard 2013) and with attention deficit/
hyperactivity disorder in one study (Wagner-Schuman et al. 2015)
but not in another (Quirós-Alcalá et al. 2014). Previous studies have
observed inverse associations between children’s cognition and
levels of manganese in blood (Riojas-Rodríguez et al. 2010) and
hair (Bouchard et al. 2011b; Menezes-Filho et al. 2011). Proximity
to agricultural use of the neonicotinoid imidacloprid during pregnancy has been associated with an increased risk of neural tube
defects (Rull et al. 2006; Yang et al. 2014), but there are no previously published studies evaluating cognition in children.
The main strength of this study is the use of PUR data, which
provide the amount of active ingredients in and the locations of
all agricultural pesticide applications, and which represent a
major improvement in exposure classification compared with
using only crop locations, as in the recent Spanish study
(González-Alzaga et al. 2015). The PUR data allowed us to
examine pesticides that do not have biomarkers and to assess pesticide mixtures. We also had extensive information on potential
confounders and other chemical exposures available for the
CHAMACOS cohort. However, there are some limitations of our
study. We were able to determine proximity to agricultural pesticide use only at the maternal residence, but not at other locations
where the mother may have spent time. Although we used residential proximity to agricultural pesticide use as a proxy for pesticide exposure, previous studies have shown that PUR data are
correlated with environmental pesticide concentrations (Harnly
Environmental Health Perspectives

et al. 2009; Harnly et al. 2005), suggesting that these data provide
a meaningful indicator of pesticide exposure. We did not account
for prenatal exposure information from other potential sources of
pesticide exposure including home use, occupational take-home,
and dietary intake, but our models included prenatal urinary
DAPs, which we believe primarily reflect both dietary and residential exposures (McKone et al. 2007). In general, these limitations would likely lead to exposure misclassification and would
bias our results toward the null.
People living in agricultural communities are exposed to a complex mixture of many individual pesticide active ingredients as well
as to potentially neurotoxic adjuvants included in the formulation.
Better methods are needed for toxicity weighting across neurotoxic
pesticide classes. To improve pesticide exposure assessment based
on PUR data, exposure models should be optimized using measured
pesticide concentrations in air or house-dust samples. In future
analyses, we intend to use more complex statistical methods to
address collinearity of exposures, such as weighted quantile sum
regression (Gennings et al. 2013) and hierarchical Bayesian models
(Kalkbrenner et al. 2010; Rull et al. 2009). The results from the
present study need to be replicated in studies that include children
living in both agricultural and nonagricultural communities to
obtain more variability in exposure to pesticide mixtures.

Conclusions
We observed an inverse association between prenatal residential
proximity to agricultural use of OPs and other neurotoxic pesticides and cognition in children at 7 y of age. The results for OPs
based on PUR data remained significant when we included prenatal urinary maternal DAP concentrations in the model, and the
effect estimates of nearby OP use and urinary DAPs were of similar magnitude. The association also remained after adjustment for
prenatal exposure to other neurotoxic chemicals. Agricultural use
of individual pesticides and classes of neurotoxic pesticides were
highly correlated, making it difficult to identify the specific pesticides that were driving these associations.

Acknowledgments
This study was funded by the National Institute of Environmental
Health Sciences grants P01 ES009605 and R56ES023591 and
U.S. Environmental Protection Agency grants R82670901 and
RD83451301.

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