2. Please cite this article in press as: González-Alzaga, B., et al., A systematic review of neurodevelopmental effects of prenatal and postnatal
organophosphate pesticide exposure. Toxicol. Lett. (2013), http://dx.doi.org/10.1016/j.toxlet.2013.11.019
ARTICLE IN PRESS
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TOXLET-8548; No.of Pages18
2 B. González-Alzaga et al. / Toxicology Letters xxx (2013) xxx–xxx
Intensive use of these compounds is posing a significant risk to
public health because of their potential adverse effects. Exposure
to pesticides does not only affect those who use them occupation-
ally, as the general population is also exposed to low concentrations
through foodstuffs and the environment throughout their life-
time. There is scientific evidence of the carcinogenic, neurological,
reproductive, immunological and genotoxic effects associated with
exposure to non-persistent pesticides in adults (Koureas et al.,
2012). However, little information is available about the effects
in children, although researchers have observed a higher risk of
adverse reproductive effects (Eskenazi et al., 2004; Lacasaña et al.,
2006; Rauch et al., 2012) and changes in the nervous system and
in neurobehavioural development (Bouchard et al., 2010; Engel
et al., 2011; Eskenazi et al., 2007; Marks et al., 2010; Rauh et al.,
2012). This means that the neurotoxic effects of these compounds
on children’s central nervous systems could be causing a series of
subclinical neurodevelopmental disorders. This has been termed a
‘silent pandemic’ and could have major health, economic and social
impact (Grandjean and Landrigan, 2006).
Toxicological studies in animals have provided information
about the neurotoxicity mechanisms and adverse effects of non-
persistent pesticides. For example, Maurissen (2000) and Rice and
Barone (2000) observed changes in the nervous system develop-
ment and sensory, motor and cognitive cerebral function of rodents
associated with prenatal and early postnatal exposure to chlorpyri-
fos. Prenatal exposure even to low concentrations of chlorpyrifos
also affects rodents’ organogenesis (Tian et al., 2005) and leads to
behavioural changes such as hyperactivity and working and refer-
ence memory deficit.
Factors such as age, sex, nutritional status, lifestyle and genetic
variability can modify the effects of non-persistent pesticides in
children, who are particularly susceptible to these compounds. The
health risks derived from exposure to toxic agents are strongly
influenced by genetics as a result of the variability of the genes
that code for metabolising enzymes (Costa et al., 2003; Eaton
et al., 1998; Furlong, 2007). The different possible combinations
of these polymorphisms can determine favourable or unfavourable
metabolic configurations, either facilitating the breakdown of some
neurotoxic compounds, or bioactivating initially inactive com-
pounds or delaying the metabolic breakdown of active compounds
(Costa et al., 2005a,b; Guo et al., 2012). Recent studies have ana-
lysed the effect of different paraoxonase-1 (PON1) polymorphisms
on neurodevelopment in children. Certain genotypes (PON1–108TT,
PON1192QR and PON1192RR) may be associated with reduced men-
tal and motor development in children exposed to OP pesticides
(Engel et al., 2011; Eskenazi et al., 2010).
The limited number of epidemiological studies available and the
huge variability of the methodologies used to assess exposure to OP
pesticides and its effects on neurodevelopment in children make
it difficult to compare their results. The aim of this review is to
carry out a detailed analysis of the evidence gathered in the stud-
ies performed to date, taking into account some of the factors that
can modify the effects of these pesticides, such as sex and gen-
der differences, genetic variability and epigenetic factors. This will
provide a better overview of the relationship between exposure to
OP pesticides and neurodevelopment and behaviour in children.
2. Material and methods
2.1. Search strategy
A systematic review of articles in the PubMed, Scopus,
Embase and Lilacs databases was carried out using the follow-
ing key words or text word combinations: “organophosphates”
OR “organophosphorus”, “child” OR “infant”, “neurodevelopment”,
“neurobehavioral” OR “neurobehavioural” (for more details see
Supplemental Material, annex I).
2.2. Inclusion and exclusion criteria
The articles selected for the review met the following inclu-
sion criteria: (a) original articles; (b) published before or during
December 2012; (c) written in Spanish, English, French or Por-
tuguese; (d) carried out in children and adolescents up to 16 years
of age; (e) evaluating prenatal and/or postnatal exposure to OP
pesticides; (f) using general intelligence tests or specific tests to
assess changes in mental and motor development or behaviour in
children.
Case series studies were not included and literature reviews
were only used to identify other original articles which had not
been found using the search syntax used.
2.3. Data analysis
Studies that met the inclusion criteria were sorted into cat-
egories based on exposure type (prenatal or postnatal) and
compared using the following criteria: (a) study design; (b) sam-
ple size; (c) age of participants; (d) exposure assessment; (e) levels
of exposure to compounds; (f) neurodevelopment tests used; (g)
effects observed; (h) adjustment variables. Table 1 provides a sum-
mary of the neuropsychological tests used in the studies included
in this review, categorised based on age range and the areas (men-
tal, motor and behavioural development) and/or specific functions
evaluated.
The level of exposure to OP pesticides is usually measured by
determining the total dialkylphosphate (DAPs) levels in the urine.
DAPs usually include the following 6 metabolites: dimethylphos-
phate (DMP), dimethylthiophosphate (DMTP), dimethyldithio-
phosphate (DMDTP), diethylphosphate (DEP), diethylthiophos-
phate (DETP) and diethyldithiophosphate (DEDTP). In these studies,
the results are expressed in nanomoles per litre (nmol/L) once all
the figures expressed in g/L have been converted.
2.3.1. Assessment of methodological quality of the articles
The methodological quality of the studies included in the review
was assessed using the ‘Strengthening the Reporting of Observa-
tional Studies in Epidemiology (STROBE) - Statement’ checklist (von
Elm et al., 2008). This tool was designed to evaluate the clarity of the
results of observational studies, but it has been used in other sys-
tematic reviews for the same purposes because no other tools are
available (Olmos et al., 2008; Ricci-Cabello et al., 2010; Rodríguez-
Barranco et al., 2013).
The checklist is made up of 22 items in 6 sections (title, introduc-
tion, methods, results, discussion and other information). Each item
specifies the aspects that should be included in the study and can
be used to assess its quality. For this review, the 9 items included
in the methods section were used to give a score for the method-
ological quality of each study. The studies were categorized as low
quality (0–3 of the 9 items), moderate quality (4–6 items) and high
quality (7–9 items) (see Supplementary Material; annex II). The
methodological quality scores are summarised in Tables 2 and 3.
3. Results
134 articles were identified using the search strategy described
above. Twenty of those met the inclusion criteria, 7 of which
analysed prenatal exposure to OP pesticides, 8 analysed postna-
tal exposure, and 5 analysed both pre- and postnatal exposure.
Cohort studies were the most frequent design (n = 10), followed by
cross-sectional (n = 9) and case-control (n = 1) studies. The method-
ological quality of studies on prenatal exposure was high (n = 9) or
3. Please
cite
this
article
in
press
as:
González-Alzaga,
B.,
et
al.,
A
systematic
review
of
neurodevelopmental
effects
of
prenatal
and
postnatal
organophosphate
pesticide
exposure.
Toxicol.
Lett.
(2013),
http://dx.doi.org/10.1016/j.toxlet.2013.11.019
ARTICLE
IN
PRESS
G
Model
TOXLET-8548;
No.
of
Pages
18
B.
González-Alzaga
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al.
/
Toxicology
Letters
xxx
(2013)
xxx–
xxx
3
Table 1
Summary of tests applied in the reviewed studies to assess functions of mental development (MD), psychomotor development (PD) and behavior (B).
Agea
Test MD PD B Reference
Since birth VABS Communication Fine and gross motor Daily living skills, socialization,
maladaptive behavior
Ruckart et al., 2004
Newborn–2 months BNBAS Habituation, orientation, motor
performance, range of state, regulation
of state, autonomic stability and
reflexes
Engel et al., 2007; Young et al., 2005
1 month–12 years PSI Adaptability, acceptability,
demandingness, mood,
distractability/hyperactivity and
reinforces parent
Ruckart et al., 2004
2 months–6 years GDS Adaptive behavior, language, personal
and social behavior
Motor behavior (locomotion, reaching,
balance, comprehension, drawing and
hand control)
Guodong et al., 2012
3 months–5 years A&S Q Communication, problem solving and
personal-social
Gross motor and fine motor Handal et al., 2008
6 months–3 years BSID Language (receptive and expressive)
and cognitive development
Fine motor and gross motor Engel et al., 2011; Eskenazi et al., 2007;
Rauh et al., 2006
2–7 years WPPSI-III Verbal comprehension, perceptual
organization and processing speed
abilities
Engel et al., 2011
2–18 years CBCL Social withdrawal, somatic complaints,
anxiety and depression, destructive
behavior, social problems, thought
problems, attention problems,
aggressive behavior and delinquent
behaviors
Eskenazi et al., 2007; Lizardi et al.,
2008; Marks et al., 2010; Rauh et al.,
2006
3–16 years NEPSY Attention, executive functions,
language, communication, learning,
memory and social perception
Sensor-motor and Visuospatial Attention Kofman et al., 2006; Marks et al., 2010
4–5 years K-CPT ADHD Harari et al., 2010; Marks et al., 2010
>4 years BARS Attention, memory, visual memory,
learning, motivation, response speed
Coordination Sustained attention Rohlman et al., 2005
K-Bit General intelligence, verbal ability and
nonverbal reasoning
Ruckart et al., 2004
>5 years PP Visual-motor coordination, manual
dexterity and motor speed
Ruckart et al., 2004
RCPM General intelligence Harari et al., 2010
M&L Test Memory Ruckart et al., 2004
5–19 years PIC Cognitive impairment Family Dysfunction and Psychological
Discomfort. Impulsivity and
Distractibility, Reality Distortion, Social
Withdrawal, Delinquency, Somatic
Concern and Social Skill Deficits.
Ruckart et al., 2004
6–16 years WISC-III Verbal comprehension, perceptual
organization, processing speed and
freedom from distractibility
Lizardi et al., 2008
WISC-IV Verbal comprehension, perceptive
reasoning, working memory and
processing speed
Bouchard et al., 2011; Engel et al.,
2011; Horton et al., 2012; Rauh et al.,
2011
WISC-R Verbal comprehension, perceptual
organization and freedom from
distractibility
Grandjean et al., 2006; Kofman et al.,
2006; Harari et al., 2010
6–18 years DISC-IV ADHD Bouchard et al., 2010
6–8 yearsb
Santa Ana Form
Board
Motor coordination Grandjean et al., 2006; Harari et al.,
2010
4. Please cite this article in press as: González-Alzaga, B., et al., A systematic review of neurodevelopmental effects of prenatal and postnatal
organophosphate pesticide exposure. Toxicol. Lett. (2013), http://dx.doi.org/10.1016/j.toxlet.2013.11.019
ARTICLE IN PRESS
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4 B. González-Alzaga et al. / Toxicology Letters xxx (2013) xxx–xxx
Table
1
(Continued)
Age
a
Test
MD
PD
B
Reference
6–8
years
b
CTSB
Visuospatial
and
visuoconstructional
functions
Grandjean
et
al.,
2006;
Harari
et
al.,
2010
6–8
years
b
FTT
Motor
speed
and
dexterity
Harari
et
al.,
2010
7
years
b
Catsys
force
plate
Postural
stability
Grandjean
et
al.,
2006
>7
years
WCST
Cognitive
skills
ADHD
Lizardi
et
al.,
2008
>8
years
BVRT
Visual
perception
and
visual
memory
Abdel
Rasoul
et
al.,
2008
>9
years
Trail
making
A&B
Visual
perception,
sequential
skills
and
symbol
recognition
Motor
speed
Abdel
Rasoul
et
al.,
2008;
Lizardi
et
al.,
2008;
Ruckart
et
al.,
2004
>10
years
WAIS
Verbal
comprehension,
working
memory,
perceptual
organization
and
processing
speed
Abdel
Rasoul
et
al.,
2008
ADHD:
Attention
deficit
and
hyperactivity
disorder.
Tests
abbreviations:
A&S
Q:
Ages
and
Stages
Questionnaire;
BARS:
Behavioral
Assessment
and
Research
System;
BNBAS:
Brazelton
Neonatal
Behavioral
Assessment
Scale;
BSID:
Bayley
Scales
for
Infant
Development;
BVRT:
Benton
Visual
Retention
Test;
CBCL:
Child
Behavior
Checklist;
CTSB:
Copying
test
of
the
Stanford-Binet;
DISC-IV:
Diagnostic
Interview
Schedule
for
Children
IV;
FTT:
Finger
Tapping
Test;
GDS:
Gesell
Developmental
Schedules;
K-Bit:
Kaufman
Brief
Intelligence
test;
K-CPT:
Conner’
Kiddie
Continuous
Performance;
M&L
Test:
Memory
and
learning
test;
NEPSY:
A
Developmental
Neuropsychological
Assessment;
PIC:
Personality
Inventory
for
Children;
PSI:
Parenting
Stress
Index;
PP:
Purdue
Pegboard;
RCPM:
Raven’
Colored
Progressive
Matrices;
VABS:
Vineland
Adaptive
Behavior
Scales;
WAIS:
Wechsler
Adult
Intelligence
Scale;
WCST:
Wisconsin
Card
Sorting
Test;
WISC-III:
Wechsler
Intelligence
Scale
for
Children-III;
WISC-IV:
Wechsler
Intelligence
Scale
for
Children-IV;
WPPSI-III:
Wechsler
Preschool
and
Primary
Scale
of
Intelligence-III;
WISC-R:
Wechsler
Intelligence
Scale
for
Children-Revised.
a
Age
range
in
which
tests
are
usually
applied.
b
Age
range
of
children
included
in
the
study.
moderate (n = 3), while that of studies on postnatal exposure was
high (n = 7), moderate (n = 4) and low (n = 2).
3.1. Exposure assessment
Two study types were identified based on the methodol-
ogy used to assess exposure to OP pesticides. Firstly, studies
that analyse exposure based on biological samples: (a) lev-
els of parent compounds (chlorpyrifos); (b) levels of specific
metabolites of OP pesticides (3,5,6-trichloro-2-pyridinol–TCPy–as
a metabolite of chlorpyrifos; p-nitrophenol as a metabolite of
methyl-parathion); (c) levels of non-specific metabolites of OP pes-
ticides (DAPs). These compounds were detected and measured
using gas chromatography–tandem mass spectrometry (Bouchard
et al., 2010; Bouchard et al., 2011; Grandjean et al., 2006; Engel
et al., 2007; Engel et al., 2011; Eskenazi et al., 2007; Harari et al.,
2010; Marks et al., 2010; Young et al., 2005), gas chromatography
with flame photometric detection (Guodong et al., 2012; Lizardi
et al., 2008), gas chromatography-high-resolution mass spectrom-
etry (Horton et al., 2012; Rauh et al., 2006; Rauh et al., 2011)
and liquid chromatography-tandem mass spectrometry (Lu et al.,
2009). Secondly, other studies assessed exposure using question-
naires. Prenatal exposure was evaluated based on the mother’s
employment during pregnancy, especially in agricultural work
(Grandjean et al., 2006; Handal et al., 2008; Harari et al., 2010),
and postnatal exposure was assessed based on proximity to farm-
land (Rohlman et al., 2005), the children’s medical history of OP
pesticide poisoning (Kofman et al., 2006) and the agricultural work
carried out by the children (Abdel Rasoul et al., 2008).
3.2. Prenatal Exposure
The effects associated with prenatal exposure observed in the
different studies are summarised in Tables 2 and 4.
The effects in the first stages of children’s lives were analysed
in two birth cohort studies, one in a multi-ethnic population in
New York (Engel et al., 2007) and another in a Hispanic population
living in farming communities in California (CHAMACOS Project)
(Young et al., 2005). Both studies found that an increase in urinary
DAPs levels during pregnancy was associated with an increase in
the frequency of abnormal reflexes in children up to 2 months of
age, and this increase was statistically significant in the study by
Young et al. (2005). However, neither of the two studies found a link
between prenatal exposure to OP and other neonatal behaviours
such as habituation, orientation, motor, range of state, regulation
of state or autonomic stability.
In the CHAMACOS cohort, urinary DAPs concentrations during
pregnancy were inversely and significantly associated with the
child’s mental development index (MDI) at 24 months, but not
at 6 or 12 months (Eskenazi et al., 2007). Similarly, in the New
York birth cohort there was an inverse, but not significant, associa-
tion between maternal urinary DAPs concentrations and the MDI of
black and Hispanic children at 12 months (Engel et al., 2011). How-
ever, in white children the levels of these metabolites were not
significantly associated with a higher MDI. Neither of the two stud-
ies found significant associations between maternal DAPs levels
and the children’s psychomotor development index (PDI).
There is also evidence of the effects of prenatal exposure to OP
pesticides in children of school age. In the CHAMACOS cohort, an
increase in the average levels of maternal urinary DAPs during preg-
nancy was associated with a significant decrease in the Perceptual
Reasoning (PR), Working Memory (WM), Verbal Comprehension
(VC) and Processing Speed (PS) scores and full scale intelligence
quotient (FSIQ) of children aged 7 (Bouchard et al., 2011). The same
trend was observed by Engel et al. (2011) but the decrease was not
statistically significant. Furthermore, a significant link was found
5. Please
cite
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article
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as:
González-Alzaga,
B.,
et
al.,
A
systematic
review
of
neurodevelopmental
effects
of
prenatal
and
postnatal
organophosphate
pesticide
exposure.
Toxicol.
Lett.
(2013),
http://dx.doi.org/10.1016/j.toxlet.2013.11.019
ARTICLE
IN
PRESS
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Model
TOXLET-8548;
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Table 2
Studies on prenatal exposure to OP pesticides and neurodevelopmental and behavioural outcomes in children.
Prenatal exposure
Author, year Country Study
design
n Age Biological
samples/timing
Analyte assayed
Median (95%CI)
Test Findings Adjusted variables MQ
Engel et al., 2007 USA P 311 Newborns (before
hospital discharge)
Maternal urine
during pregnancy
(mean gestational
age: 31,2 weeks;
SD = ±3,7)
DAPs (nmol/L) 82
(35.2–194.7)a
BNBAS Increase of
abnormal reflexes
Examiner,
anesthesia during
delivery, PON1
enzyme tertiles,
urinary creatinine
and overdispersion.
H
Young et al., 2005 USA P 381 Up to 2 months Maternal urine
before and after
delivery (up to 1
week)
DAPs (nmol/L)
Average
pregnancy: 132
(4,17–12)a
;
Post-delivery: 222
(7–21.87)a
BNBAS Significant
increment of
abnormal reflexes
among 3 days old
infants. No
significant
differences in
Habituation,
Orientation, Motor
performance,
Range of state,
Regulation of state
and Autonomic
stability.
Age at BNBAS,
maternal age at
delivery, smoking,
vitamin use, BNBAS
interviewer, and
mean diastolic and
systolic blood
pressure.
M
Handal et al., 2008 Ecuador C-S 121 3–21 months Questionnaire Pesticides AS Q (all ages).
Tests of prehension
and Visual acuity
test (only 9–18
months)
Mother working in
the floriculture
during pregnancy ↓
scores on
communication,
motor skills and
visual acuity.
Child’s age,
mother’s education
(communication).
Anemia, stunting,
housing
construction,
pesticide use at
home during
pregnancy (for
gross motor).
Anemia,
stimulation at
home, housing
construction (for
fine motor).
M
Eskenazi et al., 2007 USA P 396 6–24 months Maternal urine
during pregnancy
(1st: 14–26 weeks;
2nd: shortly after
delivery)
DAPs (nmol/L)
114.9b
(105.7–125.0) TCPy
(g/L) = 3.54
BSID-II CBCL Significant ↓ MDI at
24 months. No
association at 6 or
12 months. No
effect on PDI at 6,
24 or 36 months.
TCPy not associated
with MDI or PDI.
Psychometrician,
location, exact age
at assessment, sex,
breast-feeding
duration, HOME
score, household
income above
poverty threshold,
parity and
maternal PPVT.
H
6. Please
cite
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González-Alzaga,
B.,
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al.,
A
systematic
review
of
neurodevelopmental
effects
of
prenatal
and
postnatal
organophosphate
pesticide
exposure.
Toxicol.
Lett.
(2013),
http://dx.doi.org/10.1016/j.toxlet.2013.11.019
ARTICLE
IN
PRESS
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Model
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xxx
Table 2 (Continued)
Prenatal exposure
Author, year Country Study
design
n Age Biological
samples/timing
Analyte assayed
Median (95%CI)
Test Findings Adjusted variables MQ
Engel et al., 2011 USA P 200 12 months Maternal urine
during pregnancy
(26–28 weeks)
DAPs (nmol/L)
81.3 (31.7–198.1)a
BSID-II ↓ MDI among Black
and Hispanic
children. ↑ MDI
among White
children.
Maternal age at
enrolment, child
sex, examiner,
maternal PON1
enzyme activity,
season of urine
collection,
laboratory batch,
HOME score,
alcohol
consumption
during pregnancy,
urinary creatinine.
H
Rauh et al., 2006 USA P 254 12–36 months Umbilical cord
blood. Maternal
blood (2 days after
delivery)
Chlorpyrifos (pg/g)
High exposure
6.17, Low
exposure ≤6.17
BSID-II CBCL High exposure
(6.17 pg/g)
significantly
associated with ↓
MDI and PDI at 36
months. No effects
on MDI and PDI
Scores at 12 and 24
months.
Race, gender,
maternal
education,
maternal IQ,
gestational age,
prenatal ETS
exposure.
H
Marks et al., 2010 USA P 331 3.5–5 años Maternal urine
(Mean gestation
age. 1st sample: 14
week, 2nd sample:
26 week)
DAPs (nmol/L)
109b
(99.4–119.6)
NEPSY-II (3.5
years) K-CPT (5
years) CBCL (3.5
and 5 years)
Significant increase
of Attention
problems and
ADHD at 5 years.
Psychometrician,
age at assessment,
sex, child care,
breast-feeding,
maternal
education,
depressive
symptoms and
PPVT.
H
Harari et al., 2010 Ecuador C-S 84 6–8 years Questionnaire Pesticides WISC-R (WM) FTT,
Santa Ana Form
Board, K-CPT, CTSB
and RCPM.
Maternal exposure
significantly
associated with
↓scores in FTT,
Santa Ana Form
Board and CTSB.
Sex, age, BMI,
number of daily
meals (only for
current exposure),
stunting,
hematrocrit, school
grade, having
repeated one
grade, maternal
educational level,
family living in a
traditional house,
drinking water
supply, paternal
education and
employment.
H
7. Please
cite
this
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González-Alzaga,
B.,
et
al.,
A
systematic
review
of
neurodevelopmental
effects
of
prenatal
and
postnatal
organophosphate
pesticide
exposure.
Toxicol.
Lett.
(2013),
http://dx.doi.org/10.1016/j.toxlet.2013.11.019
ARTICLE
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PRESS
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Model
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Toxicology
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7
Table 2 (Continued)
Prenatal exposure
Author, year Country Study
design
n Age Biological
samples/timing
Analyte assayed
Median (95%CI)
Test Findings Adjusted variables MQ
Engel et al., 2011 USA P 210 6–9 years Maternal urine
during pregnancy
(26–28 weeks)
DAPs (nmol/L)
81.3 (31.7–198.1)a
WISC-IV (7–9
years): PR
(BD/PC/MR), VC
(Sim/Voc/Com),
WM (DS/LNS), PS
(SS), FSIQ
WPPSI-III (6 years):
PR (BD/MR/PC), VC
(Inf/Voc/WR), PS
(SS/Cod), FSIQ
Slight decrement in
FSIQ, PR, PS and
WM (WISC-IV) and
in FSIQ, PR, VC and
PS (WPPSI-III)
Sex, race/ethnicity,
maternal
education,
language in the
home, maternal
PON1 enzymatic
activity, alcohol
use in pregnancy,
batch season of
urine collection,
urinary creatinine.
H
Horton et al., 2012 USA P 335 7 years Umbilical cord
blood plasma
Chlorpyrifos (ng/g)
0.36 (0.25–32.1)c
WISC-IV (WM,VC,
PR, PS, FSIQ)
Borderline
significant
interaction
between prenatal
exposure to
chlopyrifos and
child sex: ↓ WM
score among males.
Total HOME score,
Parental
nurturance and
environmental
stimulation.
M
Bouchard et al., 2011 USA P 329 7 years Maternal urine
during pregnancy
(≤20 weeks and
20 weeks)
DAPs
(nm/L) = 128
WISC-IV: PR
(BD/MR), VC
(Voc/Sim), WM
(DS/LNS), PS
(Cod/SS), FSIQ
Signficant
decrement in FSIQ,
WM, PS, VC and PR.
HOME score at 6
months and
maternal education
and intelligence.
VC and FSIQ
adjusted for
language
assessment.
Creatinine-
adjusted
urine.
H
Rauh et al., 2011 USA P 265 7 years Umbilical cord
blood plasma
Chlorpyrifos (pg/g)
3.17d
(0.09–32)c
WISC-IV (WM, VC,
PR, PS, FSIQ)
Significant
decrement in WM
and FSIQ.
Child sex,
race/ethnicity/maternal
IQ/maternal
education income,
child age at testing,
ETS and PAH.
H
Grandjean et al., 2006 Ecuador C-S 72 7 years Questionnaire Pesticides WISC-R: WM (DS).
Santa Ana
Pegborad, CTSB and
Catsys force plate
Prenatal exposure
significantly
associated with ↓
scores in CTSB.
Age, sex, trauma,
other injury and
meningitis in the
past medical
history, maternal
education and
current nutrition.
H
Study design abbreviations. C-S: Cross-sectional; P: Prospective; MQ: Methodology Quality; H: High; M: Medium. Tests and subtests abbreviations. AS Q: Ages and Stages Questionnaire; BD: Block Design; BNBAS: Brazelton
Neonatal Behavioral Assessment Scale; BSID-II: Bayley Scales for Infant Development; CBCL: Child Behavior Checklist; Cod: Coding; Com: Comprehension; CTSB: Copying test of the Stanford-Binet; DS: Digit Span; FSIQ: Full
Scale Intelligence Quotient; FTT: Finger Tapping Test; Inf: Information; K-CPT: Conner’ Kiddie Continuous Performance; LNS: Letter-Number Sequence; MR: Matrix Reasoning; NEPSY-II: A Developmental Neuropsychological
Assessment; PC: Picture Concepts; PR: Perceptual Reasoning; PS: Processing Speed; RCPM: Raven’ Colored Progressive Matrices; Sim: Similarities; SS: Symbol Search; VC: Verbal Comprehension; Voc: Vocabulary; WISC-IV:
Wechsler Intelligence Scale for Children-IV; WISC-R: Wechsler Intelligence Scale for Children-Revised; WM: Working Memory; WPPSI-III: Wechsler Preschool and Primary Scale of Intelligence-III; WR: Word Reasoning.
a
Interquartile range.
b
Geometric mean.
c
Range.
d
Mean are reported when median or 95% CI were not available.
8. Please
cite
this
article
in
press
as:
González-Alzaga,
B.,
et
al.,
A
systematic
review
of
neurodevelopmental
effects
of
prenatal
and
postnatal
organophosphate
pesticide
exposure.
Toxicol.
Lett.
(2013),
http://dx.doi.org/10.1016/j.toxlet.2013.11.019
ARTICLE
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G
Model
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Table 3
Studies on postnatal exposure to OP pesticides and neurodevelopmental and behavioural outcomes in children.
Postnatal exposure
Author, year Country Study
design
n Age Biological
samples/timing
Analyte assayed
median (95%CI)
Test Findings Adjusted variables MQ
Eskenazi et al., 2007 USA P 396 6–24 months Child urine (6,12
and 24 months)
DAPs (nmol/L) 6
months 45.5
(39.6–52.3); 12
months 59.5
(51.7–68.5); 24
months 70.9
(61.4–81.9)
BSDI, CBCL Significant ↑MDI at
24 months. No
association at 6 or
12 months. No
effects on PDI at 6,
12 or 24 months.
Psychometrician,
location, exact age at
assessment, sex,
breast-feeding
duration, HOME score,
household income
above poverty
threshold, parity and
maternal PPVT.
H
Guodong et al., 2012 China C-S 301 23–25 months Child urine DAPs (nmol/L)
DMP 20.16
(LOD-1495.9)a
;
DMTP 11.06
(LOD-228.3)a
;
DEP 11.64
(LOD-210.39)a
;
DETP 18.82
(LOD-317.8)a
;
DEDTP n.c.
(LOD-20.54)a
GDS No effects
observed.
Child sex, maternal
education level,
household income.
Creatinine-adjusted
urine.
M
Rohlman et al., 2005 USA C-S
(with
follow
up)
78 48–71 months Questionnaire OP BARS Exposed children
performed poorer
on Finger tapping
and Match to
Sample compared
to Non-exposed
children.
Age, mother’s
education.
M
Marks et al., 2010 USA P 331 3.5–5 years Child urine at 3.5
and 5 years.
DAPs (nmol/L)
3.5 years = 77.5
(65.4–91.9); 5
years = 92.6
(78.6–109)
NEPSY-II (3.5
years); K-CPT (5
years); CBCL (3.5
and 5 years)
Limited evidence of
association
between child
DAPs and attention.
Psychometrician, age at
assessment, sex, child
care, breast-feeding,
maternal education,
depressive symptoms
and PPVT.
H
Lu et al., 2009 Costa Rica C-S 35 17 + 18 4–10 years Two spot urine
samples of
children: evening
day 1 and first
morning urine day
2
TCPy (g/L); La
Amistad = 0d
(0–3.31)a
; Las
Mellizas = 0d
(0–6.71)a
BARS TCPy levels and
BARS scores not
associated.
Age, gender,
conventional or
organic group,
handedness and grade.
L
Harari et al., 2010 Ecuador C-S 84 6–8 years Child urine DAPs (levels not
available)
WISC-R: WM (DS);
FTT, Santa Ana
Form Board, K-CPT,
CTSB and RCPM.
Current exposure
associated with ↑
Reaction time
(with a borderline
statistical
significance)
Sex, age, BMI, number
of daily meals (only for
current exposure),
stunting, hematrocrit,
school grade, having
repeated one grade,
maternal educational
level, family living in a
traditional house,
drinking water supply,
paternal education and
employment.
Creatinine-adjusted
urine.
H
9. Please
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González-Alzaga,
B.,
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A
systematic
review
of
neurodevelopmental
effects
of
prenatal
and
postnatal
organophosphate
pesticide
exposure.
Toxicol.
Lett.
(2013),
http://dx.doi.org/10.1016/j.toxlet.2013.11.019
ARTICLE
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9
Table 3 (Continued)
Postnatal exposure
Author, year Country Study
design
n Age Biological
samples/timing
Analyte assayed
median (95%CI)
Test Findings Adjusted variables MQ
Kofman et al., 2006 Israel C-C
(age-
sex
match)
18 6–12 years Acute intoxication
by OP before age 3
OP WISC-R: WM (DS)
NEPSY
Significant deficit
in motor control
among children
exposed to OP.
Age M
Ruckart et al., 2004 USA P 652 6-aged
children or
younger at the
moment of the
spray with MP
Wipe samples
Urine of family
members
Methyl Parathion
(MP) in wipe
samples
Exposed:
≥150 g/cm2
(Mississippi) and
≥132.9 g/cm2
(Ohio)
p-nitrphenol (PNP)
in urine (ppb)
Exposed: PNP ≥
100 ppb for at least
one person in the
household
Non-exposed: no
one in the
household with
PNP 100 ppb
K-Bit, Purdue
Pegboard, ML
Test, Trail Making
AB, PSI, PIC, VABS.
No differences
between exposed
and non exposed
children.
Income, race, ethnicity,
mother’ use of
chemical at work, child
had lead or mercury
poisoning and mother
had one or more of
these conditionsc
H
Bouchard et al., 2011 USA P 329 7 years Child urine (6
months, 1, 2, 3.5
and 5 years)
DAPs (levels not
available)
WISC-IV: VC
(Voc/Sim), PR
(BD/MR), WM
(DS/LNS), PS
(Cod/SS), FSIQ
Significant ↑ scores
in VC and FSIQ at
12 months.
Exposure no
consistently
associated with
poorer scores in
FSIQ, WM, PS, VC
and PR at 6 months,
2, 3.5 and 5 years.
HOME score at 6
months and maternal
education and
intelligence. VC and
FSIQ adjusted for
language assessment.
Creatinine-adjusted
urine.
H
Lizardi et al., 2008 USA C-S 48 7 years Child urine DAPs (nmol/L)
Exposed Group:
118.28b
(95.7–149.5)
Non-exposed
Group = 52.68b
(38.7–67.74)
WISC-III,WCST,
Trail Making Test A
B, CBCL
No significant
association
between levels of
OP metabolites and
performance on
WISC-III.
– L
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González-Alzaga,
B.,
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A
systematic
review
of
neurodevelopmental
effects
of
prenatal
and
postnatal
organophosphate
pesticide
exposure.
Toxicol.
Lett.
(2013),
http://dx.doi.org/10.1016/j.toxlet.2013.11.019
ARTICLE
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Table 3 (Continued)
Postnatal exposure
Author, year Country Study
design
n Age Biological
samples/timing
Analyte assayed
median (95%CI)
Test Findings Adjusted variables MQ
Grandjean et al., 2006 Ecuador C-S 72 7 years Child urine DMP (nmol/kg
per day)
Prenatally
exposed = 0.2d
(max 6.94);
Non-prenatally
exposed = 0.42d
(max 6.53)
DEP (nmol/kg per
day)
Prenatally
exposed = 0.27d
(max 14.62)
Non-prenatally
exposed = 0.43d
(max 2.49)
WISC-R: WM (DS)
Santa Ana
Pegboard, CTSB and
Catsys force plate
Current exposure
significantly
associated with ↑
reaction time.
Age, sex, trauma other
injury and meningitis
in the past medical
history, maternal
education and current
nutrition.
Creatinine-adjusted
urine.
H
Bouchard et al., 2010 USA C-S 1139 8–15 years Child urine DAPs (nmol/L)
68.3 (6-10195)a
DISC-IV Significant risk of
ADHD diagnostic.
Gender, age,
race/ethnicity, PIR and
fasting duration.
H
Abdel Rasoul et al., 2008 Egypt C-S 60 9–15 years Questionnaire.
AChE levels in child
blood
Pesticides WAIS: VC (Inf/Sim),
WM (Ar), PR (BD)
BVRT, DS and Trail
Making AB
Pesticides
applicators
significantly ↓
scores on all the
measures
compared to the
control group.
Effects of age and
education (13-year-old
individual with 6 years
of education and a
body mass index (BMI)
of 21.7).
M
Study design abbreviations: C-S: Cross-sectional; P: Prospective; C-C: Case-Control. MQ: Methodology Quality; H: High; M: Medium; L: Low. Tests and subtests abbreviations. Ar: Arithmetic; BARS: Behavioral Assessment and
Research System; BSID: Bayley Scales for Infant Development; BD: Block Design; BVRT: Benton Visual Retention Test; CBCL: Child Behavior Checklist; Cod: Coding; CTSB: Copying test of the Stanford-Binet; DISC-IV: Diagnostic
Interview Schedule for Children IV; DS: Digit Span; FSIQ: Full Scale Intelligence Quotient; FTT: Finger Tapping Test; GDS: Gesell Developmental Schedules; Inf: Information; K-Bit: Kaufman Brief Intelligence test; K-CPT: Conner’
Kiddie Continuous Performance; LNS: Letter-Number Sequence; ML Test: Memory and learning test; MR: Matrix Reasoning; NEPSY-II: A Developmental Neuropsychological Assessment; PIC: Personality Inventory for Children;
PR: Perceptual Reasoning; BD: Block Design; PS: Processing Speed; PSI: Parenting Stress Index; RCPM: Raven’ Colored Progressive Matrices; Sim: Similarities; SS: Symbol Search; VABS: Vineland Adaptive Behavior Scales; VC:
Verbal Comprehension; Voc: Vocabulary; WAIS: Wechsler Adult Intelligence Scale; WCST Wisconsin Card Sorting Test; WISC-III, Wechsler Intelligence Scale for Children-III; WISC-IV: Wechsler Intelligence Scale for Children-IV;
WISC-R: Wechsler Intelligence Scale for Children-Revised; WM: Working Memory.
a
Range.
b
Mean.
c
Diabetes or epilepsy/seizures before pregnancy, hospitalized or confined to bed during pregnancy, fever, X rays, or vaginal bleeding during pregnancy.
d
Median were reported when geometric mean or 95% CI were not available.
11. Please cite this article in press as: González-Alzaga, B., et al., A systematic review of neurodevelopmental effects of prenatal and postnatal
organophosphate pesticide exposure. Toxicol. Lett. (2013), http://dx.doi.org/10.1016/j.toxlet.2013.11.019
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Table 4
Summary of effects of prenatal exposure to OP pesticides on mental development, psychomotor development, attention deficit hiperactivity disorder (ADHD) and pervasive
development disorder (PDD).
Compounds Age Findings Reference
Mental development Psychomotor development Attention problems ADHD PDD
DMP
↑ DMP Newborns ↓*
Engel et al., 2007
2 months ↓*
Young et al., 2005
6 months ↓ ↓ Eskenazi et al., 2007
12 months ↓black/hispanic ↑white ↓black/hispanic ↑white Engel et al., 2011
↓ ↓ Eskenazi et al., 2007
24 months ↓ ↑ Engel et al., 2011
↓*
↓*
↑ ↑ ↑*
Eskenazi et al., 2007
3.5 years ↑*
↑*
Marks et al., 2010
5 years ↑*
↑*
Marks et al., 2010
6–9 years ↓ Engel et al., 2011
7 years ↓*
Bouchard et al., 2011
DEP
↑ DEP Newborns ↓ Engel et al., 2007
2 months ↓*
Young et al., 2005
6 months ↓ ↑ Eskenazi et al., 2007
12 months ↓black/hispanic ↑white ↓black/hispanic ↑white Engel et al., 2011
↓ ↑ Eskenazi et al., 2007
24 months ↓ ↑ Engel et al., 2011
↓ ↓ ↑ ↑ ↑ Eskenazi et al., 2007
3.5 years – ↓ Marks et al., 2010
5 years ↑ ↑ Marks et al., 2010
6–9 years ↓ Engel et al., 2011
7 years ↓*
Bouchard et al., 2011
DAPs
↑ DAPs Newborns ↓*
Engel et al., 2007
2 months ↓*
Young et al., 2005
6 months ↓ ↓ Eskenazi et al., 2007
12 months ↓black/hispanic ↑white ↓black/hispanic ↑white Engel et al., 2011
↓ ↓ Eskenazi et al., 2007
24 months ↓ ↑ Engel et al., 2011
↓*
↓ ↑ ↑ ↑*
Eskenazi et al., 2007
3.5 years ↑ ↑ Marks et al., 2010
5 years ↑*
↑*
Marks et al., 2010
6–9 years ↓ Engel et al., 2011
7 years ↓*
Bouchard et al., 2011
Chlorpyrifos
↑ Chlorpyrifos 12 months ↓ ↓*
Rauh et al., 2006
24 months ↓ ↑ Rauh et al., 2006
36 months ↓*
↓*
↑*
↑*
↑*
Rauh et al., 2006
7 years ↓*
Horton et al., 2012
7 years ↓*
Rauh et al., 2011
↑ TCPy 6 months ↑ ↓ Eskenazi et al., 2007
12 months ↓ ↓ Eskenazi et al., 2007
24 months ↓ ↓ – – – Eskenazi et al., 2007
Pesticides (questionnaire) 3–21 months ↓ ↓ Handal et al., 2008
6–8 years ↓*
↓*
Harari et al., 2010
7 years ↓*
– Grandjean et al., 2006
(–) no effect observed; blank cells indicate effects that were not measured.
*
p 0.1.
between occupational exposure to OP pesticides during pregnancy
in farming communities in Ecuador and a decrease in the visual-
spatial function of children aged 6 -8 years (Grandjean et al., 2006;
Harari et al., 2010), and in their visual memory and motor coordi-
nation and speed (Harari et al., 2010).
The evidence of a link between prenatal exposure to OP pesti-
cides and behavioural disorders is limited because few studies have
been carried out. These effects were assessed in the CHAMACOS
cohort when the children were 2, 3.5 and 5 years of age (Eskenazi
et al., 2007; Marks et al., 2010). Average urinary DAPs levels during
pregnancy were associated with a significantly higher risk of perva-
sive developmental disorder (PDD) at 2 years of age, but not with
other attention problems or attention deficit hyperactivity disor-
der (ADHD) (Eskenazi et al., 2007). However, an increased risk of
ADHD was observed at 3.5 years, and a significantly higher risk was
observed at the 5-year point (Marks et al., 2010).
With regard to the effects of exposure to chlorpyrifos on neu-
rodevelopment and behaviour in children, those with 6.17 pg/g
of chlorpyrifos in umbilical cord blood had significantly lower MDI
and PDT scores at 36 months (Rauh et al., 2006). This trend was also
observed at the 7-year point, and it has been estimated that for each
standard deviation increase in chlorpyrifos exposure (4.61 pg/g
in cord blood), full-scale intelligence quotient (IQ) declined by
1.4% and working memory declined by 2.8% (Horton et al., 2012;
Rauh et al., 2011). However, Eskenazi et al. (2007) found no link
between maternal urinary levels of TCPy, the specific metabo-
lite of chlorpyrifos, and children’s MDI or PDI scores at 6 and 24
months.
12. Please cite this article in press as: González-Alzaga, B., et al., A systematic review of neurodevelopmental effects of prenatal and postnatal
organophosphate pesticide exposure. Toxicol. Lett. (2013), http://dx.doi.org/10.1016/j.toxlet.2013.11.019
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12 B. González-Alzaga et al. / Toxicology Letters xxx (2013) xxx–xxx
3.3. Postnatal Exposure
Thirteen studies analysed the association between postnatal
exposure to OP pesticides and neurodevelopmental and/or neu-
robehavioural effects in children. Overall, no clear trend was
observed during the first few years of life. The results of the different
studies are summarised in Tables 3 and 5.
An increase in urinary DAPs levels in children aged 6-8 was asso-
ciated with a significantly higher reaction time in the studies by
Grandjean et al. (2006) and Harari et al. (2010).
Other studies assessed postnatal exposure to OP pesticides indi-
rectly based on children’s agricultural work (Abdel Rasoul et al.,
2008), the proximity of their homes to farmland, their parents
working in farming (Rohlman et al., 2005) and the children’s his-
tory of OP poisoning (Kofman et al., 2006). These studies found
significant decreases in the children’s verbal comprehension (VC),
working memory (WM) and perceptual reasoning (PR) scores
(Abdel Rasoul et al., 2008), and changes in their response times and
latency (Rohlman et al., 2005) and motor control (Kofman et al.,
2006).
However, other studies found no association between postnatal
exposure to OP pesticides and effects on children’s motor or cogni-
tive function (Bouchard et al., 2011; Guodong et al., 2012; Lizardi
et al., 2008; Lu et al., 2009; Ruckart et al., 2004). Some studies even
reached the opposite conclusion, as a significant link was found
between an increase in urinary DAPs levels and increased MDI in
children aged 12-24 months (Eskenazi et al., 2007).
In terms of behavioural effects, high levels of urinary DAPs
have been linked with a significant increase in attention problems
(Harari et al., 2010) and ADHD (Lizardi et al., 2008; Bouchard et al.,
2010) in children aged 6-15, and PDD in children aged 2 (Eskenazi
et al., 2007).
4. Discussion
4.1. Effects potentially associated with prenatal and postnatal
exposure to OPs
The results of the aforementioned studies suggest that prena-
tal exposure to OP pesticides may affect neurodevelopment and
behaviour in infancy and childhood as well as children’s cognitive
and motor function.
The average maternal urinary DAPs in the studies reviewed
ranged from 81.3 nmol/L (Engel et al., 2007) to 132 nmol/L (Young
et al., 2005). These levels are slightly higher than those found
in the pregnant women who took part in the National Health
and Nutrition Survey 1999–2000 (NHANES), where they ranged
from 70.5 nmol/L to 72.0 nmol/L (Bradman et al., 2005). However,
25% of pregnant women in the NHANES study had DAPs levels of
246.2 nm/L (percentile 75), higher than those found in the stud-
ies where neurodevelopmental and/or behavioural changes were
observed (Bouchard et al., 2011; Engel et al., 2011; Marks et al.,
2010). It is therefore essential to assess exposure to OP pesticides
not just in populations with a higher probability of exposure, but
also in the general population, in order to identify subgroups in
young children with higher risk of developing neurodevelopmental
changes.
All of the studies that determined the urinary DAPs levels of
pregnant women collected two urine samples over the course of
the pregnancy, except Engel et al. (2007, 2011), who collected only
one sample in the third trimester. The collection of several urine
samples enable to assess if prenatal exposure to OP pesticides has
been more or less constant throughout the pregnancy or if there
have been periods of higher or lower exposure. This information is
very important because there are critical windows associated with
a higher vulnerability, as occurs during organogenesis or the devel-
opment of the central nervous system (Rice and Barone, 2000). The
knowledge of the time-point of exposure to OP pesticides during
pregnancy is more informative to predict potential impacts on the
child’s motor and cognitive function.
Although there is some evidence of these effects in newborns,
the most consistent evidence has been found in children aged 24
months and over (Eskenazi et al., 2007; Marks et al., 2010; Rauh
et al., 2006). This delay between the time of exposure and the
appearance of the effect is one of the least-understood aspects in
this area. According to Rice and Barone (2000), exposure to a neuro-
toxic compound during a critical window of development may only
manifest later in time because exposure occurs at a time when cas-
cading development processes are taking place. These processes
begin during gestation and continue during the first stages of
infancy, and this could explain why these effects on cognitive func-
tion are observed at this point and not at an earlier age. It is also
difficult to detect these changes until they are quite advanced, and
some neuropsychological tests are not very sensitive. This could
account for by the delay between exposure and effect.
It is difficult to draw conclusions about the possible effects
of postnatal exposure to OP pesticides on neurodevelopment and
behaviour in children, because in some studies the level of signif-
icance of the association decreased when postnatal exposure was
analysed instead of prenatal exposure (Marks et al., 2010), or the
results for postnatal exposure were not consistent with those for
prenatal exposure (Eskenazi et al., 2007).
These differences between the effects associated with pre- and
postnatal exposure could be linked to neuroplasticity. Some animal
studies suggest that the nervous system can be adapted to expo-
sure to environmental toxins and compensate for their effects on
the organism (Rice and Barone, 2000; Selemon, 2013). This neuro-
plasticity has also been studied in children and adolescents where
a continuous development of the structures responsible for motor
function and oral communication has been observed in subjects
aged 4–17 (Paus et al., 1999). However, further studies are needed
to evaluate the effects of pre- and postnatal exposure to OP pesti-
cides using a common methodology to obtain more evidence and
evaluate the consistency of findings.
4.2. Variability in the methodologies used to evaluate exposure to
OP pesticides and effects on neurodevelopment
The wide variety of different techniques used to evaluate expo-
sure to OP pesticides and its effects on neurodevelopment and
behaviour is a major limitation when the available results are to
be compared.
The possibility of carrying out a meta-analysis of the studies
included in this systematic review was considered, distinguish-
ing between prenatal and postnatal exposure, in order to estimate
the overall effects of exposure to OP pesticides on neurodevelop-
ment and/or behaviour in children. However, this was not possible
because of the large variability in: (a) methods used to evaluate
exposure to OP pesticides (biomarkers vs. questionnaires, use of
different biomarkers); (b) windows of exposure; (c) neuropsychol-
ogical tests used to assess children’s mental and motor functions;
(d) age of the children; and (e) statistical methods used to evaluate
links between exposure to OP pesticides and neurodevelopment in
children.
Study design is another of the aspects that must be considered
when comparing the results of different studies. Cross-sectional
studies provide information about levels of exposure to a particular
compound, while prospective studies provide information about
exposure at different time-points (e.g., during pregnancy and in
the first few years of life in the case of birth cohorts). This makes it
13. Please cite this article in press as: González-Alzaga, B., et al., A systematic review of neurodevelopmental effects of prenatal and postnatal
organophosphate pesticide exposure. Toxicol. Lett. (2013), http://dx.doi.org/10.1016/j.toxlet.2013.11.019
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Table 5
Summary of effects of postnatal exposure to OP pesticides on mental development, psychomotor development, attention deficit hiperactivity disorder (ADHD) and pervasive
development disorder (PDD).
Compounds Age Findings Reference
Mental development Psychomotor development Attention problems ADHD PDD
DMP
↑ DMP 6 months ↓ ↑ Eskenazi et al., 2007
12 months ↑ ↑ Eskenazi et al., 2007
24 months ↑*
↑ ↑ ↑ ↑*
Eskenazi et al., 2007
23–25 months ↑ ↓ Guodong et al., 2012
3.5 years ↑ ↑ Marks et al., 2010
5 years ↓ – Marks et al., 2010
7 years ↓*
↓*
Grandjean et al., 2006
8–15 years ↑*
Bouchard et al., 2010
DEP
↑ DEP 6 months ↑ ↑ Eskenazi et al., 2007
12 months ↑*
↑ Eskenazi et al., 2007
24 months ↑ ↑ ↑ ↑ ↑*
Eskenazi et al., 2007
23–25 months ↓ ↑ Guodong et al., 2012
3.5 years ↑*
↑ Marks et al., 2010
5 years – ↑ Marks et al., 2010
7 years ↓*
↓*
Grandjean et al., 2006
8–15 years ↑ Bouchard et al., 2010
DAPs
↑ DAPs 6 months ↓ ↑ Eskenazi et al., 2007
12 months ↑*
↑ Eskenazi et al., 2007
24 months ↑*
↑ ↑ ↑ ↑*
Eskenazi et al., 2007
23–25 months ↑ ↑ Guodong et al., 2012
3.5 years ↑ ↑ Marks et al., 2010
5 years – – Marks et al., 2010
6–8 years ↓ ↓ ↑*
Harari et al., 2010
↑ Bouchard et al., 2011
7 years – ↑*
Lizardi et al., 2008
8–15 years ↑*
Bouchard et al., 2010
↑ Methyl Parathion 6 years ↑ ↑ ↑ Ruckart et al., 2004
↑ TCPy 4–10 years – – Lu et al., 2009
OP Pesticides (questionnaire) 48–71 months ↓*
↓*
Rohlman et al., 2005
6–12 years – ↓*
Kofman et al., 2006
9–15 years ↓*
↓*
Abdel Rasoul et al., 2008
(–) no effect observed; blank cells indicate effects that were not measured.
*
p 0.1.
possible to determine if exposure to these toxins over a particular
period of time has been constant or sporadic.
Most of the studies (77%) that analysed prenatal exposure to
OP pesticides used a longitudinal design (Bouchard et al., 2011;
Engel et al., 2007; Engel et al., 2011; Eskenazi et al., 2007; Horton
et al., 2012; Marks et al., 2010; Rauh et al., 2006; Rauh et al.,
2011; Young et al., 2005). However, studies evaluating postnatal
exposure mainly used the cross-sectional approach (61.5%) (Abdel
Rasoul et al., 2008; Bouchard et al., 2010; Grandjean et al., 2006;
Guodong et al., 2012; Harari et al., 2010; Lizardi et al., 2008; Lu et al.,
2009; Rohlman et al., 2005), followed by the longitudinal approach
(30.7%) (Bouchard et al., 2011; Eskenazi et al., 2007; Marks et al.,
2010; Ruckart et al., 2004) or a case-control design (7.8%) (Kofman
et al., 2006).
Prospective studies provide better information about pre- and
postnatal exposure to OP pesticides and the effects observed in
each window of exposure. They can therefore be used to identify
critical stages in the development of a child’s nervous system and
provide more evidence of how these effects develop in each stage.
The availability of several measurements of exposure also provides
information about intraindividual variability in terms of exposure
to OP pesticides, as a single measurement of these non-persistent
pesticides is not a good indicator of an individual’s usual exposure.
Griffith et al. (2011) measured children’s urinary DAPs levels over
a period of 21 months and found that the individual DAPs levels
varied by 3–7 folds depending on the metabolite analysed, and
day-to-day variability was much greater than the between-child
variability. Inter- and intraindividual variability is a major limi-
tation of cross-sectional studies, as reported Sudakin and Stone
(2011).
The use of biomonitoring techniques to evaluate exposure to
environmental pollutants is becoming more common. In fact, 9 of
the 12 studies that evaluated prenatal exposure to OP pesticides
and 10 of the 13 studies that evaluated postnatal exposure deter-
mined the levels of the biomarkers as a measure of exposure to
these compounds in the urine or blood.
Most of the studies that analysed prenatal exposure by mea-
suring specific or non-specific (DAPs) biomarkers for OP observed
significant or near significant effects on neurodevelopment and
behaviour in children (Bouchard et al., 2011; Engel et al., 2007;
Eskenazi et al., 2007; Horton et al., 2012; Marks et al., 2010; Rauh
et al., 2006; Rauh et al., 2011; Young et al., 2005). The same
occurred in studies that estimated exposure by using question-
naires (Grandjean et al., 2006; Harari et al., 2010). However, the
percentage of studies on postnatal exposure where evidence of
the effects was observed was lower when biomonitoring tech-
niques were used (3 out of 10) as compared to the utilisation of
a questionnaire (3 out of 3). Since questionnaires may examine the
accumulated exposure, to a compound, this would explain why the
effects observed in these studies were greater (Abdel Rasoul et al.,
2008; Kofman et al., 2006; Rohlman et al., 2005).
Biomonitoring techniques can be used to accurately evaluate
current exposure to non-persistent pesticides by measuring the
amount of the parent compound or one of its metabolites in urine
14. Please cite this article in press as: González-Alzaga, B., et al., A systematic review of neurodevelopmental effects of prenatal and postnatal
organophosphate pesticide exposure. Toxicol. Lett. (2013), http://dx.doi.org/10.1016/j.toxlet.2013.11.019
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or blood samples, or to analyse accumulated exposure using hair
or meconium samples. Biomarkers of exposure to OP pesticides
in the mother or child’s urine and, to a lesser extent, in umbili-
cal cord blood samples were more often measured in the studies
included in this review. Because of their chemical structure, OP
pesticides are quickly metabolised and eliminated 24–72 h after
exposure (Fourth National Report on Human Exposure to Environ-
mental Chemicals, 2009; Maroni et al., 2000; WHO, 1996). This
means that analysing their presence in urine (OP metabolites) or
blood samples (original compounds) provides information about
recent exposure instead of accumulated exposure, and this makes
it difficult to estimate representative exposure. In the case of prena-
tal exposure, meconium samples could provide information about
the levels of exposure of the foetus from the second trimester until
birth (Bearer et al., 1999; Ostrea, 1999). Some studies that mea-
sured DAPs levels in meconium samples highlighted the usefulness
of this biological matrix for the evaluation of prenatal exposure to
OP pesticides (Tsatsakis et al., 2009; Whyatt and Barr, 2001). Recent
studies have also discussed the importance of hair as an indica-
tor of chronic exposure to these compounds (Tsatsakis et al., 2008,
2010). Measuring DAPs levels in hair could provide information
about exposure over a longer period (months), representative of
the child’s accumulated exposure (medium/long-term exposure)
during the postnatal period (Tsatsakis et al., 2008).
Analyses of prenatal and/or postnatal exposure to OP pesti-
cides have generally been carried out based on urinary DAPs levels.
However, because DAPs are non-specific metabolites it is not pos-
sible to determine the exact compound to which the subjects have
been exposed to, as these metabolites are common to several OPs
and a single OP can produce several types of DAPs (Barr et al.,
2004). Moreover, the population may be directly exposed to these
metabolites present in foodstuffs and in the atmosphere (Sudakin
and Stone, 2011) as a result of the spontaneous breakdown of the
original pesticides. There is evidence that this type of exposure con-
tributes to total urinary DAPs levels in children (Curl et al., 2002,
2003), as diet is one of the major sources of exposure to OP pesti-
cides amongst this population group (Aprea et al., 2000; Lu et al.,
2008). Despite these limitations, DAPs levels are used frequently
in epidemiological studies as occurred in almost all of the studies
included in this review. Only 5 of the 20 studies measured the con-
centrations of parent compounds such as chlorpyrifos (Horton et al.,
2012; Rauh et al., 2011; Rauh et al., 2006) or a specific metabolite
such as 3,5,6-trichloro-2-pyridinol (TCPy) (Eskenazi et al., 2007)
or p-nitrophenol (PNP) (Ruckart et al., 2004), which represent the
leaving groups of chlorpyrifos and parathion or methyl-parathion,
respectively.
Distinguishing between residential and dietary exposure is a key
part of the process of characterising children’s exposure to OP pesti-
cides. However, the epidemiological studies analysing exposure to
these compounds provide little information about the role of diet
(Jurewicz and Hanke, 2008). Only 3 of the 20 studies included in
this review assessed the influence of diet on levels of exposure and
the effects studied (Grandjean et al., 2006; Guodong et al., 2012;
Harari et al., 2010).
There is scant research on the contribution of the diet to the chil-
dren’ total exposure to OP pesticides. Several studies have assessed
the contribution of the diet to the total exposure to OP pesticides
in children. Children on organic diet showed lower urinary DAPs
levels than those on conventional diet and the full substitution of a
conventional diet by an organic diet was associated with a decrease
in urinary DAPs levels (Curl et al., 2003; Lu et al., 2006). Therefore,
dietary information should be considered in future studies to clar-
ify the contribution of different food items to children’ exposure
as compared to other sources of exposure. This would represent an
important step-forward in the search and in the implementation of
feasible measures to reduce children’ exposure to these chemicals.
Social factors such as socioeconomic level, family environment,
parents’ mental health and intelligence quotient are directly linked
with a child’s upbringing, influencing aspects such as diet, exposure
to environmental toxins, the child’s level of stimulation and devel-
opment, amongst others (Forns et al., 2012). More recent studies
have started to incorporate these variables into their designs to
assess their effect on exposure to environmental pollutants and
children’s level of development and behaviour. Almost all of the
studies included in this review included one or several social indi-
cators as confounding variables to adjust their statistical models.
The most frequent variables were those related to the family’s eco-
nomic status (family income, poverty income ratio), race/ethnicity,
paternal education (level of education of the mother and/or father,
years at school, occupation), the mother’s intelligence and mental
health, and the child’s living conditions (HOME score, living in a
traditional house). Because of the limited number of studies (n = 4)
that did not include any of these confounding variables and the vari-
ability of the designs used (age of the study population, exposure
biomarkers studied, neurodevelopment tests used), it was not pos-
sible to assess the differences between the results of those studies
and the ones that did include those confounding variables.
With regard to the tests used to assess children’s neurobe-
havioural development, many of the studies used the different
Wechsler intelligence scales (WISC III, WISC-IV, WPPSI-III, WISC-R,
WAIS) and the Bayley scale (BSID-II), depending on the age range of
the participants and the date on which the population was recruited
in the studies reviewed. Both scales provide more thorough infor-
mation on children’ neurodevelopment than those tests assessing
only specific functions, such as visual memory, dexterity, motor
speed and coordination, among others. All tests can be used to
assess children’ neurodevelopment and provide valuable informa-
tion. However, the selection of a particular test responds to the aim
of the investigation and takes into account the age range of the par-
ticipants and the date when the study was performed. For a better
comparability of the results of epidemiological studies it is impor-
tant to harmonize the neurodevelopmental tests available (White
et al., 2009). Table 1 shows detailed information on the tests used
in the reviewed studies is shown.
The evaluation of effects on neurodevelopment using IQ tests is
gradually being complemented by other indexes measuring differ-
ent areas such as memory, verbal comprehension, processing speed
and perceptual reasoning, amongst others (Flanagan and Kaufman,
2004). Using specific tests would be better than simply using gen-
eral intelligence tests, as previous studies suggest that exposure to
environmental toxins could cause specific types of damage to the
central nervous system which would not be detected based on the
child’s IQ alone (White et al., 2009; Forns et al., 2012; Grandjean
et al., 2006).
Some of the studies included in this review also evaluated
behavioural disorders and attention problems in children (Eskenazi
et al., 2007; Marks et al., 2010). The Child Behavior Checklist (CBCL)
for parents was the most frequently used method of identifying this
type of disorder along with other tests and questionnaires (Table 1).
There is a specific CBCL questionnaire for each age range that allow
the identification of behavioural changes in children, such as hyper-
activity, violent behaviour, anxiety and depression, amongst others
(Achenbach and Rescorla, 2000).
4.3. Limitations associated with the study design
An accurate estimation of the number of participants accord-
ing to the research purposes is crucial since a small sample size
could underestimate the magnitude of the associations. Since the
sample size is determined by the levels of OP exposure, the lack of
information on exposure may hamper the estimation of the sample
size in the study population. Moreover, a reduced sample size may
15. Please cite this article in press as: González-Alzaga, B., et al., A systematic review of neurodevelopmental effects of prenatal and postnatal
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also prevent from observing neurodevelopmental or behavioural
effects associated with pre- or postnatal exposure to OP pesticides
(Guodong et al., 2012). Other studies, despite admitting having a
limited sample size, observed significant or near-significant effects
(Engel et al., 2011; Grandjean et al., 2006; Handal et al., 2008;
Harari et al., 2010; Rauh et al., 2006; Rohlman et al., 2005). Loss
of recruited children during the follow-up could introduce a selec-
tion bias that might affect the results of the study. The reviewed
studies highlighted the limitations associated with the sample size
as regards exposure assessment to OP pesticides (Bouchard et al.,
2011; Eskenazi et al., 2007; Marks et al., 2010; Rauh et al., 2011),
very likely because of the low persistence of these compounds and
the use of non-specific biomarkers, such as DAPs.
In addition to sample size limitations, the influence of statistical
analysis is also remarkable. Most of the studies reviewed were lon-
gitudinal in design, however cross-sectional analyses were made.
This could limit the advantages of cohort studies since they did not
evaluate longitudinally the changes in children’ performance over
time. Likewise, to our best knowledge no study has evaluated the
potential reversibility of effects associated either with decreased
exposure or with social, educational and/or biological factors.
4.4. Differences linked to sex/gender
Few studies have analysed the link between sex and gender
and exposure to environmental pollutants and its effects on health,
especially in children. Sex differences are due to biological factors
and affect the metabolism and exposure to xenobiotics, as well as
susceptibility and health throughout lifetime (Clougherty, 2010).
Gender, on the other hand, is a social construct, influenced by cul-
tural norms, roles and behaviour due to the relationships between
men and women and between boys and girls (Clougherty, 2010).
There are also differences in the foods that girls and boys eat and
the activities they take part in (games, sport) (Molinero et al., 2010).
Social environment during pregnancy and childhood also have a
significant influence on exposure to environmental pollutants and
neurodevelopment (Jedrychowski et al., 2009), so these factors
should be included in epidemiological studies.
A study carried out by van Wendel et al. (2011, personal
communication, unpublished) in a banana farming community in
Costa Rica found a link between postnatal exposure to chlorpyrifos
and a reduction in short-term memory in children aged 6–9, and the
effect was greater in males than in females. The reasons for these
differences between sexes are not clearly identifiable, although
they may not only be due to biological factors (hormonal differ-
ences, differences in pesticide metabolism or in the repair processes
of the damage caused by OP pesticides in cholinergic pathways)
(Arbuckle, 2006; Slotkin et al., 2008), but also to social factors, such
as different lifestyles, behaviour and occupations. It is also impos-
sible to rule out the possibility that differences between sexes vary
by age, so sex could play a greater or lesser role in children than in
adults or vice versa.
Overall, the studies reviewed have included sex as a confound-
ing variable when adjusting multivariate models, either because
they found a link in the univariate analysis or because of assumed
differences between the sexes in terms of nervous system devel-
opment or exposure to OP pesticides. Very few studies conducted
stratified analysis by sex (Bouchard et al., 2011; Horton et al., 2012;
Marks et al., 2010; Rohlman et al., 2005) to disaggregate biological
and social differences between boys and girls.
Some studies on prenatal exposure to OP pesticides found a
decrease in working memory (Horton et al., 2011) or an increase
in attention problems and ADHD (Marks et al., 2010) in boys but
not in girls. One study on postnatal exposure to OP pesticides also
found a significant decrease in response time in boys but not in
girls (Rohlman et al., 2005). However, another study that stratified
the analysis by sex did not find any difference in the association
between urinary DAPs and effects on neurodevelopment between
boys and girls (Bouchard et al., 2011).
None of these articles carried out an analysis of gender differ-
ences to separate social differences from biological characteristics,
which would have allowed the identification of differences in expo-
sure patterns in children linked to the different way in which they
interact with the environment. Beamer et al. (2008) observed major
differences between the behaviour of boys and girls aged 6–27
months in a farming community in California, where the boys came
into contact with the ground and toys more frequently, while the
girls came into more frequent contact with clothes, towels, toys
and other objects. These differences in activities could lead to dif-
ferences in their exposure to certain environmental toxins.
Future studies should examine the role that sex and gender
play in exposure to environmental contaminants and its effects on
health in children. This would help to identify effect modification
factors, as well as pathways and sources of exposure, making it
possible to design more effective interventions.
4.5. Toxicity mechanisms of organophosphate pesticides and
neurodevelopment
The association between neurodevelopmental disorders and OP
pesticide exposure could be linked to its inhibiting effect on the
enzyme acetylcholinesterase (AChE), which plays an important role
in the nervous system function. When AChE is inhibited by OP,
the excess acetylcholine that accumulates in the synaptic terminals
overstimulates the nicotinic and muscarinic receptors (Ecobichon,
2001). This toxic action could interfere the human neurological
development process from the early stages of development (Rice
and Barone, 2000).
However, recent studies have identified toxicity mechanisms
other than AChE inhibition that could be involved in neurodevel-
opmental disorders (Androutsopoulos et al., 2013). Recent in vitro
studies have found a decrease in the number of neurites associ-
ated with diazoxon (active metabolite of diazinon), DNA synthesis
inhibition and alterations in the differentiation of C6 glioma cells
associated with chlorpyrifos oxon (Flaskos, 2012). These effects
occur at low OP concentrations which do not inhibit AChE so that
cholinergic transmission is unaffected (Pope et al., 2005). Chlor-
pyrifos oxon is capable of phosphorylating (and therefore activate)
transcription factors involved in brain development (e.g. cAMP
response element-binding protein, CREB) at much lower concen-
trations (nanomolar) than those required to inhibit AChE, thus
affecting key processes in neural development and the develop-
ment of cognitive functions (Schuh et al., 2002).
4.6. Genetic susceptibility
Genetic variability plays an important role in determining the
individual susceptibility to environmental pollutants. This means
that genetic variations in the enzymes involved in the detoxifi-
cation of these chemicals could make an individual more or less
susceptible to their toxic effects (Costa et al., 2003).
An individual’s capacity to hydrolyse OP pesticides can also be
affected by their plasma PON1 levels, and is 3–4 folds lower in chil-
dren than in adults (Cole et al., 2012; Furlong et al., 2006; Huen
et al., 2009) making them more susceptible to the effects of these
compounds (Padilla et al., 2000). Other factors such as diet, alcohol
consumption or drug use, as well as psychological or physiological
factors, can also affect PON1 activity (Costa et al., 2005a,b).
Although some enzymes have been considered as biomarkers
of genetic susceptibility related to OP pesticide metabolism (Costa
et al., 2005a,b), only PON1 genetic polymorphisms have been eval-
uated so far in epidemiological studies (Furlong, 2007).
16. Please cite this article in press as: González-Alzaga, B., et al., A systematic review of neurodevelopmental effects of prenatal and postnatal
organophosphate pesticide exposure. Toxicol. Lett. (2013), http://dx.doi.org/10.1016/j.toxlet.2013.11.019
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Eskenazi et al. (2010) evaluated the interaction effects between
prenatal exposure to OP pesticides and PON1192 and PON1-108
polymorphisms on neurodevelopment and behaviour in children.
There was a significant association between maternal urinary DAPs
and a lower mental development index in 2-year-olds carrying
the PON1-108T allele, as well as a lower psychomotor develop-
ment index, although in the latter case the differences were not
statistically significant. This gene-environment interaction did not
occur with the PON1192 polymorphism. The PON1192 and PON1-108
polymorphisms had no significant effect on pervasive development
disorder (PDD) in the same age group.
Engel et al. (2011) observed that increased maternal urinary
DAPs were associated with a significant decrease in the MDI of
children aged 12–24 months whose mothers carried the PON1192R
allele. In 6 to 9-year-olds, the children of mothers with the
PON1192QQ genotype scored considerably lower on the Wech-
sler perceptual reasoning scale than the children of mothers with
the PON1192R allele, although the difference was not statistically
significant. However, the other polymorphisms studied (PON155,
PON1-108) were not found to have an effect on neurodevelopment.
4.7. Epigenetics and neurodevelopment
A number of illnesses and functional changes in organ systems
have been linked with epigenetic mechanisms, including cogni-
tive dysfunction and developmental neuropsychological disorders
(Martínez-Frías, 2010; Martino et al., 2009; Weinhold, 2006). Epi-
genetics is the study of heritable changes in gene expression or
phenotype occurring without changes in DNA sequence (Martínez-
Frías, 2010; Perera and Herbstman, 2011; Rodríguez-Milord et al.,
1990). Epigenetic mechanisms that regulate gene expression, such
as DNA methylation, take place in a carbon cycle where one methyl
group, from S-adenosylmethionine, is covalently added to the car-
bon 5 of the DNA cytosine ring (CpG dinucleotide). This process is
highly dependent on the folate levels (Bird, 2002; Costello and Plass,
2001; Lee et al., 2009; Martínez-Frías, 2010). There is evidence
that the process also involves chromatin remodelling and vari-
ous complex histone modifications including acetylation for gene
expression, and phosphorylation for gene activation and repression
(mainly through different families of methyltransferases, acetyl-
transferases and deacetylases) (Cheung and Lau, 2005; Shahbazian
and Grunstein, 2007; Varga-Weisz and Becker, 2006). Less is known
about other mechanisms such as protein modifications (e.g. ubi-
quitination, sumoylation). Other epigenetic processes involve small
non-coding RNAs, known as microRNAs (miRNAs), which are the
main regulators of gene function and expression during prena-
tal development and during germ line formation in both sexes
(Filipowicz et al., 2008; Hayashi et al., 2008; Martínez-Frías, 2010;
Tam et al., 2008).
Some authors have discussed how exposure to environmental
factors, including xenobiotics, can lead to epigenetic alterations
(Perera and Herbstman, 2011; Venerosi et al., 2012). There is
a growing amount of evidence that exposure to environmen-
tal chemicals during early development may lead to epigenetic
changes that could determine susceptibility to diseases in later life
or may be transmitted from one generation to another (Weinhold,
2006).
The effect of three OP pesticides (fonofos, parathion and ter-
bufos) on human DNA was recently studied ‘in vitro’. The three
pesticides caused methylation changes in the promoter regions of
the same 712 genes, as well as exhibited their own OP-specific
methylation alterations (Zhang et al., 2012b). Epigenetic mecha-
nisms may also contribute to OP-induced carcinogenesis (Zhang
et al., 2012a,b) and possibly to other complex disorders. How-
ever, few animal studies have examined other potential epigenetic
implications of OP pesticides in neurodevelopmental disorders
(Martínez-Frías, 2010; Persico and Bourgeron, 2006; Venerosi et al.,
2012). New, innovative and multidisciplinary studies on gene-gene
and gene-environment interactions and gene susceptibility are
essential to prevent effects associated with epigenetic mechanisms.
5. Conclusions
The studies included in this review used a wide variety of dif-
ferent designs and methods to evaluate the effects of OP pesticide
exposure on neurodevelopment and behaviour in children, and this
makes it difficult to compare their results. The studies reviewed
suggest that exposure during pregnancy may have a negative effect
on the child’s mental and motor development and behaviour during
the first stages of childhood. The effects associated with postnatal
exposure are less consistent, although may also affect the child’s
cognitive and motor function, as well as increase the risk of atten-
tion problems. In order to draw conclusions, further studies need
to be carried out evaluating exposure to OP pesticides at differ-
ent stages of pregnancy and monitoring the possible effects on
neurodevelopment after birth. Studies analysing both pre- and
postnatal exposure (current and accumulated) to these compounds
are also required. It is therefore important to identify the most
suitable methods for evaluating exposure to OP pesticides and its
effects on neurodevelopment and behaviour in children so that a
standardised method can be established. This would make it eas-
ier to compare results and estimate the overall effects of exposure
to these compounds in children. It is also important to incorporate
differences associated with gender and sex into epidemiological
designs, as well as information about the children’s diet, fam-
ily environment and lifestyle. This is key to identifying the main
determining factors of exposure to OP pesticides and its possible
health effects in children. By using existing evidence as well as
future research that will broaden knowledge of the mechanisms
involved in OP pesticide metabolism, and studying the role that
an individual’s genetic characteristics play when exposed to these
compounds, it will be possible to design measures to reduce levels
of exposure and its possible health effects in children.
Conflict of interest
The authors declare that there are no conflicts of interest.
Acknowledgements
This study was partially supported by grants from the Council
of Innovation of the Andalusian Government (reference number
P08-CTS-04313, FEDER funds), the Institute of Health Carlos III
(reference numbers PI10/01101 and FIS-FEDER 11/02038) and the
European Union (EU FP7-ENV-2011 DENAMIC 2cod 28957).
The content of this article is part of the PhD thesis of Beat-
riz Gonzalez-Alzaga which was conducted at the University of
Granada under the doctoral programme “Clinical Medicine and
Public Health”.
Appendix A. Supplementary data
Supplementary data associated with this article can be found,
in the online version, at http://dx.doi.org/10.1016/j.toxlet.2013.
11.019.
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