UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

WASHINGTON, DC 20460 

OFFICE OF CHEMICAL SAFETY AND 

POLLUTION PREVENTION 

MEMORANDUM 

DATE: September 15, 2015 

SUBJECT: Summary Reviews from _2015 Epidemiological Literature Review for 

Organophosphates. 

PC Code: See below 

Decision Number: 

DP Barcode: D429120 

Registration Numbers: NA 

Petition Number: Regulatory Action: 

Risk Assessment Type: NA 

TXR Number: 0057253 

MRID Numbers: NA 

Case Number: 

CAS Number: See below 

40 CFR: 

FROM: 

THRU: 

TO: 

Khin Swe Oo, MD, DABT, Toxicologist ~ £<0 t!.lt. 

Toxicology and Epidemiology Branch 

Health Effects Division (7509P) 

Elizabeth Holman, Physical Scientist ~ )J..t 

Risk Assessment Branch II (RAB2) 

Health Effects Division (HED), 7f_g 509P _ 

Anna Lowit, Senior Scientist ti} .) /1 _ 

Immediate Office ( VI 

Health Effects Division (HED), 7509P 

Dana Vogel 

Division Director 

Health Effects Division (HED), 7509P 

As part of the 2015 epidemiological literature review of the organophosphates, more detailed 

summary reviews were completed for each study included in the review. The attached document 

provides these more detailed summary reviews for each study. For the synthesis of these studies 

and an analysis of the overall results, please see the "Literature Review on Neurodevelopment 

Effects & FQPA Safety Factor Determination for the Organophosphate Pesticides" (D331251, A. 

Lowit et al, 09115/2015). This document was also reviewed by Dr. Danelle Lobdell from 

USEPA's Office of Research and Development. 

Page 1of171 
Page 2 of 171

Chemical PC Code CAS No. 

Dicrotophos 035201 141-66-2

Fosthiazate 129022 98886-44-3

Coumaphos 036501 56-72-4

Terbufos 105001 13071-79-9

Profenofos 111401 41198-08-7

Bensulide 009801 741-58-2

Diazinon 057801 333-41-5

Ethoprop 041101 13194-48-4

Dimethoate 035001 60-51-5

Malathion 057701 121-75-5

Phosmet 059201 732-11-6

Chlorethoxyfos 129006 54593-83-8

Acephate/

Methamidiphos

103301/ 

101201

30560-19-1/ 

10265-92-6

Pirimiphos-methyl 108102 29232-93-7

TCVP 083701 961-11-5

Tribufos 074801 78-48-8

Phorate 057201 298-02-2

Phostebupirim 129086 96182-53-5

DDVP 084001 62-73-7

Naled 034401 300-76-5

Trichlorfon 057901 52-68-6

Fenamiphos 100601 22224-92-6

AZM 058001 86-50-0

Methidathion 100301 950-37-8

Propetamphos 113601 31218-83-4

ODM 058702 301-12-2

Disulfoton 032501 298-04-4

Methyl parathion 053501 298-00-0

Temephos 059001 3383-96-8

Chlorpyrifos-methyl 059102 5598-13-0

 
Page 3 of 171

Table of Contents

Study Page

HIGH QUALITY STUDIES

Study 1. Barr et al. (2010).................................................................................... A-1

Study 2. Bouchard et al. (2010)............................................................................ A-5

Study 3. Fortenberry et al. (2014, 2014a) ............................................................ A-10

Study 4. Quirós-Alcalá et al. (2011) .................................................................... A-16

Study 5. Rauch et al. (2012)................................................................................. A-21

Study 6. Wolff et al. (2007), Furlong et al. (2014) .............................................. A-25

MODERATE QUALITY STUDIES

Study 7. Anderson et al. (2015)............................................................................ A-35

Study 8. Guodong et al. (2012) ............................................................................ A-40

Study 9. Handal et al. (2007, 2007B, 2008)......................................................... A-45

Study 10. Llop et al. (2013).................................................................................... A-55

Study 11. Oulhote et al. (2013) .............................................................................. A-58

Study 12. Petit et al. (2010).................................................................................... A-62

Study 13. Ruckart et al. (2004) .............................................................................. A-67

Study 14. Suarez-Lopez et al. (2012, 2013a, 2013)............................................... A-73

Study 15. Wang et al. (2012).................................................................................. A-84

Study 16. Zhang et al. (2014)................................................................................. A-88

Study 17. Shelton et al. (2014)............................................................................... A-147

LOW QUALITY STUDIES

Study 18. Acosta-Maldonado et al. (2009) ............................................................ A-92

Study 19. Dabrowski et al. (2003).......................................................................... A-95

Study 20. Grandjean et al. (2006), Harari et al. (2010).......................................... A-99

Study 21. Kofman et al. (2006).............................................................................. A-108

Study 22. Koutroulakis et al. (2014) ...................................................................... A-112

Study 23. Lizardi et al. (2008)................................................................................ A-115

Study 24. Lu et al. (2012)....................................................................................... A-120

Study 25. Moreno-Banda et al. (2009)................................................................... A-125

Study 26. Nevison (2014)....................................................................................... A-129

Study 27. Rohlman et al. (2005) ............................................................................ A-133

Study 28. Samarawickrema et al. (2008) ............................................................... A-137

Study 29. Savitz et al. (1997)................................................................................. A-141

Study 30. Wickerham et al. (2012) ........................................................................ A-152
Page 4 of 171

Study 1. Barr et al. (2010)

Barr DB, Ananth CV, Yan X, Lashley S, Smulian JC, Ledoux TA, Hore P, Robson MG. 

Pesticide concentrations in maternal and umbilical cord sera and their relation to birth 

outcomes in a population of pregnant women and newborns in New Jersey. Sci Total 

Environ. 2010;408:790–795. 

Study Summary

Researchers published a study which evaluated the relationship between prenatal exposures to 

pesticides by measuring maternal and cord serum biomarkers in a New Jersey cohort of pregnant 

women and the birth outcomes of their neonates.

The authors conducted a cross-sectional study of pesticide exposures in maternal and fetal 

compartments of mothers and their newborns. This study was conducted within a cohort of 150 

mothers and their newborns at Saint Peter's University Hospital in New Brunswick, New Jersey 

from July 2003 to May 2004. They enrolled a convenience sample based on availability of 

research personnel. Subjects eligible for recruitment included women with singleton pregnancies 

and non-anomalous fetus scheduled for an elective cesarean birth at term (≥37 weeks) and 

hemoglobin level was ≥8 mg/dl. Women were excluded if there was evidence for labor or 

rupture of membranes at the time of operative delivery and if they were taking medications that 

could potentially interfere with metabolism of environmental chemicals. Subjects were identified 

prior to admission from a scheduling list and the potential subjects' physicians were asked for 

permission to offer participation. Each potentially eligible subject was approached to verify 

eligibility and to obtain informed consent.

Maternal blood samples (10 ml) were collected prior to placement of intravenous and bladder 

catheters in the pre-operative holding area or from extra specimens available from pre-operative 

maternal blood testing stored in undisturbed Vacutainer tubes. After the cesarean delivery of the 

newborn, the umbilical cord was clamped, and 30–60 ml of cord blood was aspirated directly 

from the umbilical vein after cleaning the cord. All umbilical vein samples were obtained within 

15min of delivery. An investigator was present at each delivery to assure correct sampling 

procedures were followed. Finally, maternal pregnancy characteristics and neonatal outcome 

data were also recorded from the medical record prior to hospital discharge. The authors assessed 
Page 5 of 171

confounders such as reported pest control use and frequency of use with a maternal age, 

gravidity, race, maternal pre-pregnancy BMI, infant sex, and gestational age.

Serum samples were analyzed for OP insecticides, i.e., chlorpyrifos and diazinon, and other 

pesticides including herbicides, repellents, and fungicides using gas chromatography–high 

resolution mass spectrometry. 

The authors conducted statistical analysis consisted of assessments of distributional properties of 

each metabolite, including means, medians, distribution percentiles, ranges, and correlation 

analyses among analytes from the various matrices. In all analyses, concentration values below 

the LOD were assigned a concentration equal to LOD/√2. They performed 3 sets of analyses. In 

the first, they examined the (Pearson) correlation in each pesticide compound between maternal 

and cord sera. In the second set of analyses, they compared differences in the mean pesticide 

exposure between the maternal and cord sera, and applied the t-test. Finally, they examined the 

association between pesticide exposures and birth outcomes (birth weight, head circumference, 

abdominal circumference and birth length). For this latter analysis, they created indicators for

pesticide compounds as exposures ≥75th or <75th percentile, as well as exposures ≥90th or 

<90th percentile. These percentiles were derived from the total cohort, but specific to exposures 

in the maternal and umbilical cord sera. Since results for pesticide exposures ≥90th percentile 

were similar to those for exposures ≥75th percentiles, they presented results only for the latter 

analyses in the paper. 

The authors carried out a multivariable regression analysis to minimize biases due to 

confounding. This was accomplished by fitting general linear regression models to estimate 

changes in birth weight and birth lengths in relation to pesticide exposures, and adjusted for 

confounders. The confounders that were adjusted in the models included maternal age, 

primigravida, maternal pre-pregnancy body-mass index (BMI), infant sex, and gestational age. 

BMI was defined as weight (in kg) to squared height (in m). The authors also tested whether or 

not the continuous covariates (maternal age, BMI and gestational age) had a non-linear 

relationship with the outcomes (infant anthropometrics) by including quadratic terms for these 

continuous variables in the models. Since none of the variables demonstrated non-linear 

relationship with the outcome, these variables were included as single linear terms in the models.

The authors observed an inverse relation to both birth weight and birth length for chlorpyrifos in 

both maternal and cord serum, but when controlling for confounding variables, the associations 

were not present. Diazinon was not detected in samples thus not included in any models.
Page 6 of 171

Study Review

This study tested whether exposures to organophosphate pesticides, chlorpyrifos and diazinon, 

have an association with birth outcomes such as head circumference, abdominal circumference, 

and birth length in a population of mothers and their newborn infants in New Jersey. The 

population in this cross-sectional study varied in age, race, and ethnicity. Given that the study 

population was a convenience sample, the possibility for selection bias exists. The authors could 

not present evidence to the extent of this bias as no information exists on the potential 

participants who were not enrolled. 

The ascertainment and analysis of serum pesticide markers was appropriate. Quantification was 

conducted with consultation from the CDC pesticide laboratory. Measurement of the parent 

compounds chlorpyrifos and diazinon are likely more accurate and objective indicators of 

organophosphate pesticide exposure, relative to other ascertainment methods such as metabolites 

in urine as many metabolites. Although they are sensitive indicators of exposure, it is difficult to 

infer chlorpyrifos effects specifically from the metabolite levels, as they also indicate exposure to 

other organophosphates and the TCPY a chlorpyrifos specific metabolite has also been found in 

the environment. The study population likely sustained many other potentially relevant 

exposures to multiple chemicals and other pesticides which may affect neurodevelopment. Birth 

outcomes were assessed via medical record abstraction. 

The statistical models used are appropriate. For exposure measures that were less than the 

laboratory analytic limit of detection, the measures were substituted by dividing the LOD/√2. 

Imputation may have been a better method than substitution. It appears that the investigators 

tried to keep the models parsimonious by only including terms which changed the outcome 

measure and were statistically significant. Additionally, the authors tested whether the same 

relationships held for the different infant growth measures. Residual confounding by unmeasured 

or poorly measured confounders is possible in this study. The authors did evaluate a large 

number of potential confounders, but not all were evaluated notably, diet during pregnancy and 

exposure to other chemicals that may restrict infant growth (e.g., lead or cadmium).

This study has many strengths, including the measurement of chlorpyrifos and measurement of 

several factors related to infant growth, head circumference, abdominal circumference, and 

infant length. The authors were able to adjust for or consider many factors related to infant size, 

maternal age, primigravida, maternal pre-pregnancy body-mass index (BMI), infant sex, and 

gestational age. However, the authors noted their findings were inconsistent with findings from 
Page 7 of 171

other studies, namely the Northern Manhattan cohort (Perera 2003). The socioeconomic 

differences between the New Jersey and Northern Manhattan cohorts are not described in the 

article other than to point out that the latter was an African American and Dominican population.

This study has several limitations, including that exposures measured at birth do not necessarily 

precede the outcome measured. However, these chemicals are typically short-lived in the blood, 

thus the fact that they were measured is suggestive of a higher magnitude of exposure than was 

detected, a steady state exposure, or hospital exposures. The authors reported evidence of a 

potential hospital exposure this cohort (Yan et al., 2009), but they had little reason to believe that 

chlorpyrifos exposures would come from a hospital setting. Finally, many of the concentrations 

were near the limits of detection of the analytical method. Analytical variability can negatively 

impact outcome findings, obscuring real associations, and effectively leading to the null 

association observed in this study for chlorpyrifos and birth outcomes.

References cited

Perera FP, Rauh V, Tsai WY, Kinney P, Camann D, Barr D, et al. Effects of transplacental 

exposure to environmental pollutants on birth outcomes in a multiethnic population. 

Environ Health Perspect 2003;111:201–5.

Yan X, Lashley S, Smulian JC, Ananth CV, Barr DB, Ledoux TA, Robson MG, Ledoux TA. 

Pesticide concentrations in matrices collected in the perinatal period in a population of 

pregnant women and newborns in New Jersey. Human and Ecological Risk Assessment 

2009;15:948–67.
Page 8 of 171

Study 2. Bouchard et al. (2010)

Bouchard MF, Bellinger DC, Wright RO, Weisskopf MG. Attention Deficit/Hyperactivity 

Disorder and Urinary Metabolites of Organophosphate Pesticides in U.S. Children 8–15 

Years. Pediatrics 2010;125(6):e1270-e1277. doi:10.1542/peds.2009-3058.

Study Summary

Researchers published an analysis of data collected from the National Health and Nutrition 

Examination Survey which investigated the relationship between exposures to organophosphate 

pesticides (OPs) and diagnosis of ADHD. The National Health and Nutrition Examination 

Survey (NHANES) is a population-based, health survey of non-institutionalized US residents 

conducted by the National Center for Health Statistics of the Centers for Disease Control and 

Prevention (CDC 2010). 

This 2010 study by Bouchard et al. was conducted to examine the association between urinary 

concentrations of dialkyl phosphate metabolites of organophosphates and attentiondeficit/hyperactivity disorder (ADHD) in children 8 to 15 years of age.

The National Health and Nutrition Examination Survey (NHANES) is a population-based health 

survey of non-institutionalized U.S. residents conducted by the National Center for Health 

Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). NHANES uses a 

complex, multistage probability sampling design, with oversampling of certain subgroups. 

Participants completed household surveys, which included questions about demographics and 

health history, and blood and urine samples were collected during a physical examinations at 

mobile centers (CDC 2010). The authors used data from 2000–2004, years for which ADHD was 

assessed in children 8–15 years; a diagnosis was available for 3,998 children. Urinary DAP 

metabolites were measured on a random subsample of the NHANES participants. From 2000 to 

2002, the sampling rate was 1/2 for ages 6–11 years and 1/3 for ages 12–15 years. From 2003 to 

2004, the sampling rate was 1/3 across all ages. Measurements of urinary DAPs were available 

for 1,481 children among those with an ADHD diagnosis. NHANES was approved by the NCHS 

institutional review board, and all participants provided written informed consent (CDC 2010).

During the physical examination, “spot” urine specimens were collected from participants, 

aliquoted, and stored cold (2–4°C) or frozen until they were shipped on dry ice to the CDC for 
Page 9 of 171

analysis. Six urinary DAP metabolites, resulting from the degradation of at least 28 different 

OPs, were measured in urine to provide an indicator of the body burden of common OPs (NRC, 

1993). The urinary DAP metabolites measured are 3 dimethyl alkylphosphate (DMAP) 

molecules (dimethylphosphate, dimethylthiophosphate, dimethyldithiophosphate) and 3 diethyl 

alkylphosphate (DEAP) molecules (diethylphosphate, diethylthiophosphate, 

diethyldithiophosphate). DMAP metabolites are derived from O, O-dimethyl–substituted OP 

pesticides such as malathion; DEAP metabolites result from the degradation of O, O-diethyl–

substituted OPs such as chlorpyrifos. Concentrations below the detection limit were imputed a 

value corresponding to the value of the detection limit divided by √2. 

Attention-Deficit/Hyperactivity Disorder (ADHD) was assessed using the Diagnostic Interview 

Schedule for Children (DISC-IV), a structured diagnostic interview designed for use in 

epidemiologic studies (American Psychiatric Association, 1994). The interview was conducted 

by telephone by trained interviewers with the mother or another caretaker, two to three weeks 

after the physical examination. The interview was conducted by bilingual interviewers in English 

or Spanish. The DISC-IV has evidence of substantial validity, reliability for both its English and 

Spanish versions, and successful use via telephone in the DSM-IV field trials. Use of DISC-IV 

data is restricted for confidentiality, thus, data was accessed through the NCHS Research Data 

Center.

The DISC-IV scoring algorithms determine ADHD diagnostic status for the past year, as well as 

ADHD subtype: i) predominately inattentive subtype, ii) predominately hyperactive-impulsive 

subtype, or iii) combined subtype. Diagnosis is based on the presence, during the prior 12 

months, of symptoms related to inattention, hyperactivity and impulsivity, with significant 

impairment in two or more settings (e.g., at school and home). The DSM-IV criterion that 

symptoms must not occur in conjunction with another neuropsychiatric disorder is not assessed 

by the DISC-IV. The DSM-IV criterion that symptoms must have been present before 7 years of 

age was not used because the hypothesis was that urinary DAP concentrations are associated 

with increased odds of concurrent ADHD.

Many potential confounders were ascertained for modeling - race/ethnicity (non-Hispanic white, 

black, Mexican American, or other/multiracial), PIR (the ratio of self-reported family income to 

the family’s appropriate poverty threshold value, on the basis of Census data, recoded into 4 

categories), BMI (in quartiles), blood lead concentrations (logarithmically transformed), 

maternal age at birth, maternal smoking during pregnancy (yes or, no), and time since last 
Page 10 of 171

consuming food or drink, recorded at the time of blood and urine sampling (recorded on a scale 

of 1 [0–2 hours] to 7 [21–24 hours]).

The authors divided DAP metabolite concentrations by the respective molecular weights then 

summed to yield DEAP, DMAP, and total DAP concentrations. Because the distributions of total 

DAP, DMAP, and DEAP concentrations were skewed, logarithmic transformations (base 10) 

were applied. Because they suspected DMAP and DEAP metabolites might have different 

relationships to the outcomes (Eskenazi 2007), they were examined separately. Correlates of 

urinary DAP metabolite concentrations were examined with a general linear model. Risk was 

estimated using logistic regression analyses to estimate odds ratios (ORs) and 95% confidence 

intervals (CIs) for ADHD (any subtype) and ADHD subtypes, per 10-fold increases in total 

DAP, DMAP, and DEAP metabolite concentrations (in nanomoles per liter), the authors present 

results crude analyses and adjusted analyses. To check for potential biases due to low detection 

frequency of the DAP metabolites, the authors conducted further analyses on the metabolite with 

the highest detection frequency, namely, dimethyl thiophosphate. Cases were categorized as 

below the limit of detection or lower or higher than the median of detectable concentrations 

adjusted for creatinine levels.

The authors explored potential confounding effects for all the confounders ascertained, but only 

sex, age, race/ethnicity, PIR, fasting time, and logarithmically transformed urinary creatinine 

concentrations (as recommended by Barr et al., 2005 to adjust for urine dilution) were included 

in the models.

The authors observed evidence of an association between exposures to organophosphate 

pesticides as measured by urinary DAP metabolites and increased odds of ADHD in a 

representative sample of US children age 8-15. This finding was seen for total DAPs, total 

DMAPs, and dimethyl thiophosphate metabolites, but a null result was observed for DEAPs. 

There was a 55% to 72% increase in the odds of ADHD for a 10-fold increase in DMAP 

concentration, depending on the criteria used for case identification. This association was not 

explained by gender, age, PIR, race/ethnicity, fasting duration, or creatinine concentration.

Study Review

This study tested whether in exposures to organophosphate pesticides have an association with 

ADHD in a representative sample of US children age 8-15. The study population was 
Page 11 of 171

appropriate to the hypothesis, given that the representativeness of the sample allows for an 

estimation of risk among children with “average” exposure levels to OPs. The population in this 

cross-sectional study varied in age, race, ethnicity and geographic area. Given that the NHANES 

biomonitoring is conducted in a 1/3—1/2 subsample of the entire NHANES population, the 

possibility for further selection bias exists. However, the authors present evidence that it is 

negligible as the demographic characteristics are similar between the population included and not 

included in the subsample. 

The ascertainment and analysis of urinary organophosphate pesticide markers was appropriate. 

Quantification was conducted at the CDC, using published methods. DAP metabolites are likely 

more accurate and objective indicators of organophosphate pesticide exposure, relative to other 

ascertainment methods such as self-report. Although they are sensitive indicators of exposure, it 

is difficult to infer chlorpyrifos effects specifically from the metabolite levels, as they also 

indicate exposure to other organophosphates. The study population likely sustained many other 

potentially relevant exposures to multiple chemicals and other pesticides which may affect 

neurodevelopment. 

The ADHD test, (DSM-IV, is very widely used, and was appropriately administered by a trained 

interviewer and scored using modified standards appropriate to the hypothesis being tested. (The 

authors choose not to use the DSM-IV criterion that symptoms must have been present before 7 

years of age, because their hypothesis was that urinary DAP concentrations would be associated 

with increased odds of concurrent ADHD).

The statistical models used are appropriate and well powered. For exposure measures that were 

less than the laboratory analytic limit of detection, the measures were substituted by dividing the 

LOD/√2. Imputation may have been a better method than substitution. It appears that the 

investigators tried to keep the models parsimonious by only including terms which changed the 

outcome measure and were statistically significant. Additionally, the authors conducted a 

sensitivity analysis and tested whether the same relationships held for the different ADHD 

subtypes. Residual confounding by unmeasured or poorly measured confounders is possible in 

this study. The authors did evaluate a large number of potential confounders, but not all possible 

were evaluated, e.g., family history of ADHD.

This study has many strengths, including the representative sample, the measurement of urinary 

DAP, and measuring ADHD and its subtypes using the DSM-IV. The authors were able to adjust 
Page 12 of 171

for or consider many factors related to cognitive function, such as socioeconomic indicators. The 

statistical associations observed are plausible, several biological mechanisms might underlie an 

association between organophosphate pesticides and ADHD, as noted by authors (Sultatos 1994, 

Coccini 2009). Additionally, the authors noted that their findings were consistent with findings 

from other studies in more highly exposed populations. The many advantages of this study, the

plausibility of the findings, and that similar associations have been seen in other studies, support 

the hypothesis that exposure to OPs increases risk of ADHD. Because of the cross-sectional 

design, the authors cannot rule out the possibility that children with ADHD engage in behaviors 

that expose them to higher levels of organophosphates.

References cited

American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSMIV. 4. Washington, DC: American Psychiatric Association; 1994.

Barr DB, Wilder LC, Caudill SP, Gonzalez AJ, Needham LL, Pirkle JL. 2005. Urinary creatinine 

concentrations in the U.S. population: implications for urinary biologic monitoring 

measurements. Environ Health Perspect 113:192–200.

Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey: 

questionnaires, data sets, and related documentation. Available at: 

www.cdc.gov/nchs/nhanes/about_nhanes.htm.Accessed April 6, 2010.

Coccini T, Crevani A, Rossi G, et al. Reduced platelet monoamine oxidase type B activity and 

lymphocyte muscarinic receptor binding in unmedicated children with attention deficit 

hyperactivity disorder. Biomarkers. 2009;14(7):513–522.

Eskenazi B, Marks AR, Bradman A, et al. Organophosphate pesticide exposure and 

neurodevelopment in young Mexican-American children. Environ Health Perspect. 

2007;115(5):792–798.

Sultatos LG. Mammalian toxicology of organophosphorus pesticides. J Toxicol Environ Health. 

1994;43(3):271–289.

US National Research Council, Committee on Pesticides in the Diets of Infants and Children. 

Pesticides in the Diets of Infants and Children. Washington, DC: National Academy 

Press; 1993.
Page 13 of 171

Study 3. Fortenberry et al. (2014, 2014a)

• 2014. Urinary 3,5,6-trichloro-2-pyridinol (TCPY) in pregnant women from Mexico 

City: Distribution, temporal variability, and relationship with child attention and 

hyperactivity. GZ Fortenberry, JD Meeker, BN Sánchez, DB Barr, P Panuwet, D 

Bellinger, L Schnaas, M Solano-González, AS Ettingera, M Hernandez-Avila, H Hu, 

MM Tellez-Rojoj. International Journal of Hygiene and Environmental Health 217 

(2014): 405– 412.

• 2014a. Paraoxonase I polymorphisms and attention/hyperactivity in school-age children 

from Mexico City, Mexico. GZ Fortenberry, JD Meeker, BN Sánchez, DB Barr, K 

Peterson, D Bellinger, L Schnaas, M Solano-González, AS Ettinger, M HernandezAvila, H Hu, MM Tellez-Rojoj. Environmental Research 132:342–349.

Study Summary

Fortenberry et al. looked at mother-child pairs from a prospective birth cohort study called the 

Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) to evaluate the 

relationship between pesticide exposure and Attention Deficit Hyperactivity Disorder (ADHD) 

in school age Mexican children from Mexico City, Mexico. The aim of the first report 

(Fortenberry et al., 2014) were to define the distribution of TCPY concentrations among a 

population of pregnant women in Mexico, to assess between- and within-individual variability of 

urinary TCPY levels over the course of pregnancy, and to explore the relationship between third 

trimester maternal urinary TCPY concentrations and child neurodevelopment, particularly 

attention and hyperactivity, using subscales from psychometric assessments in children 6-

11years of age. The second report (Fortenberry et al., 2014a) examined whether maternal and/or 

child PON1 genotypes (PON1R192Q and PON1L55M) were associated with Attention Deficit 

Hyperactivity Disorder-Like Phenotypes (ADHD-LP). 

Participants of the ELEMENT study came from three different cohorts; 1994–1997 (cohort1), 

1997–2000 (cohort 2), and 2001–2005 (cohort 3). All three ELEMENT cohorts enrolled 

homogenous, low-to-moderate income, pregnant women from the National Institute of 

Perinatology, Hospital General Dr. Manuel Gea Gonzalez, or clinics affiliated with the Mexican 

Social Security Institute. Mother-child pairs from the three cohorts (N = 827) were re-invited 

between 2007 and 2011 to examine childhood and adolescent neurodevelopmental 
Page 14 of 171

characteristics. Exclusion characteristics for all ELEMENT cohorts included: plans to leave the 

area within the next 5 years; daily consumption of alcoholic beverages; addiction to illegal drugs; 

continuous use of prescription drugs; diagnosis of multiple pregnancy, preeclampsia, renal or 

heart disease, gestational diabetes; a history of infertility, diabetes, or psychosis; diagnosis of 

high risk pregnancy; or suffering from seizures requiring medical treatment.

In the overall ELEMENT study, participants provided second morning void urine samples at 

each trimester of pregnancy. For the first study (2014), third trimester urine samples from 

mother-child pairs that had completed psychometric assessments for children (N = 187) from 

cohorts 2 and 3 were utilized. In a subset of women randomly selected from the 187 motherchild pairs (N = 21), urinary TCPY in samples collected during all three trimesters of pregnancy 

was measured. TCPY concentrations in maternal urine samples were measured by enzyme 

hydrolysis. Metabolites were quantified using isotope dilution calibration. The LOD was 0.10 

ng/ml for TCPY.

For the second report (2014a), blood samples from mother–child pairs who were re-invited for 

additional studies (N = 591) were analyzed for coding PON1 polymorphisms (Q192R and 

L55M). For PON1Q192R, there were N = 531 mothers and N = 532 children with genotype 

information. For PON1L55M, 458 mothers and 478 children had genotype information. The PON1 

genotypes were determined using the Sequenom Mas- sARRAY iPLEX Platform. The three 

psychometric assessments used to evaluate behavioral characteristics of children 6–13 years of 

age were same as what was used for the first study.

Three psychometric assessments were used to evaluate behavioral characteristics of children 6–

11 years of age: Conners’ Parental Rating Scales-Revised (CPRS-R) - tool for parents used to 

determine a child’s behavior for children and adolescents 3–17years; Behavior Assessment 

System for Children-Parental Rating Scales (BASC-PRS) – tool to assess attention problems and 

hyperactivity in children 6-11 years of age; and Conners’ Continuous Performance Test (CPT) -

14-minute computer test that measures sustained attention and impulsivity and compares the 

participant’s answers to a reference group and results in a confidence index of a clinical profile. 

Scores from these psycho-metric instruments assess ADHD-related symptoms and are not 

designed as diagnostic tools, but rather for screening. The instructions and prompts were 

translated into Spanish by a researcher who also trained and supervised the personnel who 

administered the assessments. Standardization and quality control checks were conducted by 

reviews of videotaped evaluations.
Page 15 of 171

Fortenberry et al. (2014)

Multivariable regression models were created using variables found to be associated with 

ADHD-related behaviors and/or TCPY in bivariate analyses (p < 0.05). Variables were also 

considered from a priori suspicion of being potential confounders of the association between 

prenatal CPF/chlorpyrifos-methyl exposure and psychometric outcome. Covariates included: 

maternal IQ, maternal education, income, maternal urine specific gravity, breast feeding, 

maternal blood lead one month after delivery, season of sample collection, child’s age at testing, 

child’s sex, birth length, and head circumference at birth. Birth length and head circumference at 

birth were determined by a nurse at the time of delivery and were used as continuous variables. 

Maternal IQ was calculated on the basis of a mother’s scores on the Information, 

Comprehension, Similarities, and Block Designs scales of the Spanish Wechsler Adult 

Intelligence Scale.

TCPY was detected in over 90% of urine samples in the present study. Geometric mean TCPY 

concentration among ELEMENT women was significantly higher than pregnant women in 

NHANES (p-value = 0.03).Among the subset of women with repeated measures, there were no 

significant differences in geometric mean TCPY concentrations between trimesters. However, 

there was significant within-woman variability across trimesters. 

Based on the multivariable regression analysis, no statistically significant associations were 

observed in models that considered all children combined and models stratified by sex. However, 

a suggestive trend for increasing Hit RT Block Change in relation to increasing TCPY tertiles (pvalue = 0.09) was found. In models stratified by sex, this relationship appeared to be stronger 

among boys than girls. In the sex-stratified analysis, a suggestive trend for increased ADHD 

Index in relation to TCPY tertiles (p-value = 0.06) was also found. In this model, the highest 

TCPY tertile was associated with an ADHD index score that was 5.55 points higher than 

children in the lowest tertile (p-value = 0.06). Among girls, there was a suggestive increase 

inattention problems score in relation to exposure, but only for the middle TCPY tertile (p = 

0.08).

So the authors conclude that there is no statistically significant associations between tertiles of 

maternal third trimester urinary TCPY and measures of attention and hyperactivity in children. 

However, there was suggestive evidence for increases in the ADHD index in relation to TCPY 

tertiles among boys. This suggests that fetal exposure to increased quantities of chlorpyrifos, 
Page 16 of 171

chlorpyrifos-methyl, or TCPY during the last trimester of pregnancy may influence the display 

of ADHD characteristics in childhood.

Fortenberry et al. (2014a)

Multivariable regression models were created using variables found to be associated with 

ADHD-LP, and/or PON1 genotypes in bivariate analyses (p<0.05). Variables were also 

considered from a priori suspicion of being potential con-founders of the association between 

prenatal exposure to OP pesticide exposure and psychometric outcome. In PON1 main effects 

models, covariates included continuous maternal IQ, education, socioeconomic status and blood 

lead one month after delivery, breast feeding (yes/no), child's sex, continuous age at testing, birth 

length and head circumference at birth.

The distribution of genotype frequencies for PON1Q192R and PON1L55M were similar for both 

populations. For mothers, allelic frequencies for PON1Q192R were 41% for A and 59% for G 

while children's allelic frequencies 40% and 60%, correspondingly. For PON1L55M, mothers 

and children both had allelic frequencies of 88% and 12%, for A and T, respectively.

Results from the PON1 main effects multivariable regression analyses showed a 2.32-point 

higher score (95% CI (0.26, 4.38)) in DSM IV Hyperactivity/Impulsivity for children with 

mothers having PON155MM in comparison to PON155LM+LL. No other significant 

associations were found in models fitted separately by either mother or child genotype 

information. In models further stratified by child sex, no statistically significant associations 

were observed with PON1 genotypes in either boys or girls. However, in boys, there were 

suggestive associations of 2.00, 2.61 and 2.22 point higher scores, respectively, for ADHD Index 

(p = 0.09), DSM IV Hyperactivity/Impulsivity (p = 0.06), and DSM IV Total (p = 0.07) in 

relation to mothers' PON155MM. Also, in males who had mothers with PON1192QQ, there was 

a borderline significant association of 2.81-point higher score (p=0.05) for DSM IV 

Hyperactivity/Impulsivity.

The authors concluded that there is a significant relation between ADHD-LP and mother’s PON1 

genotype. Because maternal PON1 polymorphisms were associated with child ADHD-LP, this 

may be a viable biomarker of susceptibility for ADHD-LP.
Page 17 of 171

Study Review

This was a well conducted study with notable strengths and few weaknesses. The study 

population was homogenous with participants from diverse socio-economical background from 

Mexico City. The fact that this study looked into TCPY concentrations among a population of 

pregnant women to assess between – and within-individual variability of urinary TCPY levels 

over the course of pregnancy makes this study unique. The analytic methods, analytic approach, 

and statistical analysis were appropriate. The author’s approach to evaluating and adjusting for 

covariates were prudent.

The authors employed a reasonable set of inclusion/exclusion criteria that likely resulted in 

recruitment of an inner-city study population that was ethnically diverse. The investigators 

prospectively collected maternal and child information (potential confounders and effect 

modifiers). 

Selection bias is unlikely to have occurred in the study. 

Fortenberry et al (2014)

The urine sampling and quantification of TCPY in maternal urine samples appears to have been 

conducted appropriately. This method is more objective, sensitive, and likely also more accurate 

and reliable. The psychometric instruments used to assess the behavioral characteristics of 

children seem to be appropriate. Measures were taken to ensure that the tests were administered 

correctly. However, it should be noted that these instruments have their own strengths and 

weaknesses and are screening, not diagnostic tools.

The analytic methods, analytic approach, and statistical analysis were appropriate. A relatively 

modest sample size may have reduced the statistical significance of the study. The author’s 

approach to evaluating and adjusting for covariates were prudent. The investigators prospectively 

collected maternal and child information (potential confounders and effect modifiers. On the 

whole, the investigators handling of confounding was reasonable. It was interesting that TCPY 

was detected in over 90% of the samples and the geometric means of TCPY concentrations were 

significantly higher than that of the pregnant women in NHANES. This shows that the women in 

Mexico are exposed to pesticide during pregnancy. History of maternal and paternal exposure to 

pesticides was not collected in the study. Also, the use of a single urinary measure to estimate 
Page 18 of 171

exposure may not have provided the true level of exposure. In addition, potential for differential 

exposure misclassification is also possible because mothers were likely aware of the 

neurobehavioral status of their children, and it is plausible that this knowledge of outcome status 

may have impacted the psychometric assessments to assess behavioral characteristics of children.

Statistical analysis showed that there is no significant association between tertiles of maternal 

TCPY concentrations and ADHD-related outcomes in children. The authors rightly conclude 

their paper by stating that considering the continued widespread agricultural and possible 

residential use of chlorpyrifos and chlorpyrifos-methyl in Mexico and the educational 

implications of cognitive and behavior deficits, these relationships deserve further study.

Fortenberry (2014a)

This was a well conducted prospective birth cohort study with notable strengths and few 

weaknesses. The objective of this study was to investigate the relationship between maternal 

and/or child PON1 genotypes (PON1R192Q and PON1L55M) and ADHD-LP in children aged 

6-13 years of age in Mexico City, Mexico. The review comments above also apply to this report. 

The fact that maternal and child PON1 genotype was taken into consideration make this study 

unique. 

The analysis of maternal and child blood for PON1 genotype appears to have been conducted 

appropriately. This method is more objective, sensitive, and likely also more accurate and 

reliable. The psychometric instruments used to assess the behavioral characteristics of children 

seem to be appropriate. However, it should be noted that these instruments have their own 

strengths and weaknesses and are screening, not diagnostic tools.

The analytic methods, analytic approach, and statistical analysis were appropriate. A large 

sample size may have increased the statistical significance of the study. The author’s approach to 

evaluating and adjusting for covariates were prudent. The investigators prospectively collected 

maternal and child information (potential confounders and effect modifiers). On the whole, the 

investigators handling of confounding was reasonable. However, potential for differential 

exposure misclassification is also possible because mothers were likely aware of the 

neurobehavioral status of their children, and it is plausible that this knowledge of outcome status 

may have impacted the psychometric assessments to assess behavioral characteristics of children.
Page 19 of 171

Statistical analysis showed that there is an association between maternal PON1 genotype and 

parent reported ADHD-LP in children. These findings have important implications as potential 

susceptibility factors for ADHD-LP in children, and add to the growing body of evidence that 

maternal PON1 polymorphisms may affect child neurodevelopment. The authors rightly 

conclude their paper by stating that this study provides platform for further analysis.
Page 20 of 171

Study 4. Quirós-Alcalá et al. (2011)

Maternal prenatal and child organophosphate pesticide exposures and children’s 

autonomic function. Lesliam Quirós-Alcalá, Abbey D. Alkon, W. Thomas Boyce, Suzanne 

Lippert, Nicole V. Davis, Asa Bradman, Dana Boyd Barr, Brenda Eskenazi. 

NeuroToxicology 32:646–655, 2011.

Study Summary

The Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) 

longitudinal birth cohort study was conceived to evaluate the health effects of pesticides on 

maternal and child health in a population living in the agricultural community of Salinas Valley, 

California. In this report, Quirós-Alcalá et al. leverage data from the CHAMACOS cohort to 

evaluate whether urinary biomarkers of prenatal and childhood organophosphate (OP) pesticide 

exposure are associated with autonomic nervous system dysregulation at ages 6 months, 1 year, 

3.5 years, and 5 years. 

The original study population consisted of pregnant mothers recruited in 1999-2000 who were in 

the first half of their pregnancy (<20 weeks), qualified for government assistance, were receiving 

prenatal care at a specific set of community clinics, and who planned to deliver at the Salinas 

County hospital. Of the 601 women originally enrolled, 531 were followed to delivery of their 

child. A subset of participating infants with an even identification number were eligible to 

participate in the autonomic nervous system reactivity protocols at 6 months, 1 year, and 3.5 

years of age. The autonomic nervous system reactivity protocol was offered to all children at the 

5-year follow-up. After excluding children with missing or otherwise insufficient pesticide 

metabolite or outcome data, twins, and those taking medications that may affect autonomic 

nervous system responses, the study sample consisted of 149 children who provided data at the 

6-month follow-up, 149 at 1 year, 97 at 3.5 years and 274 at 5 years. 

Participating mothers were interviewed at approximately weeks 14 and 26 of their pregnancy, at 

delivery, and again at the time of each child assessment to obtain demographic and potential 

covariate information. Information was also abstracted from the child’s birth records and 

pediatric medical records.
Page 21 of 171

The investigators assessed both prenatal OP pesticide exposure and OP pesticide exposure at the 

time of the outcome assessment. To estimate prenatal exposures, dialkylphosphate (DAP) 

metabolite concentrations, including three diethylphosphates (DEP, DETP, DEDTP) and three 

dimethylphosphates (DMP, DMTP, DMDTP) were quantified in maternal spot urine samples 

collected at the time of the prenatal interviews (i.e. at 14 and 27 weeks gestation, on average). 

Childhood OP pesticide exposures were estimated by measuring the same set of DAP 

metabolites in spot urine samples collected from the children at ages 6 months, and at age 

1,2,3.5, and 5 years of age. All urine samples were processed for shipping by study staff and 

shipped to the Centers for Disease Control and Prevention for quantification of DAP 

concentrations. Individual DAP metabolite concentrations below the lower level of detection 

(LOD) were imputed as LOD/√2. DAP, DEP, and DMP concentrations were summed then 

averaged over the two prenatal sampling periods.

Assessments of autonomic nervous system dysregulation under resting and challenge conditions 

were conducted using a standardized protocol, administered by trained, bilingual research staff. 

The resting condition at 6 months and 1 year was listening to lullabies and at 3.5 and 5 years, 

listening to a story. The challenge conditions at 6 months and 1 year were watching a jack-inthe-box being wound up and jumping out of the box (social/startle), listening to a recording of a 

baby crying (emotion), and feeling a vibrator on the leg (physical). At 3.5 and 5 years, the 

challenge conditions included asking the participants to answer questions (social), watch a scary 

video (emotion), taste concentrated lemon juice (physical), and repeat a series of numbers 

(cognitive). An electrocardiograph was used to obtain continuous measures of the participants’ 

sympathetic and parasympathetic autonomic responses (respiratory sinus arrhythmia, preejection period, and heart rate) during the resting and challenge conditions. 

Covariates were selected if they were potentially related to the outcome measures (age of the 

child at the time of the outcome assessment; location of the assessment, investigator conducting 

the outcome assessments) or if they were significantly associated with OP pesticide exposure and 

outcome (α= 0.1) (breastfeeding duration). The child’s sex was also included as a covariate in all 

models, and interactions between sex and OP pesticide exposure were examined. The 

investigators also considered prenatal maternal smoking status, prenatal maternal alcohol use, 

income, maternal education, birth weight and gestational age though these were not included in 

final models because they were not significantly associated with outcomes or OP pesticide 

exposure at any age. Six separate linear regression models were constructed for the three 

autonomic nervous system outcomes (during resting and challenge conditions) at each time point 
Page 22 of 171

(6 months, and 1, 3.5, and 5 years of age). Log-transformed prenatal and current (crosssectionally sampled) child DAP concentrations and their interaction were included in each 

model, along with covariates. Cumulative prenatal and child OP pesticide exposure was also 

estimated using an area-under-the-concentration–time-curve methodology. (Kaplan et al., 1997) 

Models were constructed using unadjusted urinary DAP metabolite concentrations and repeated 

using creatinine-adjusted DAP metabolite concentrations, and (also with creatinine level entered 

as a covariate in the multivariate models. Mixed-effects models of the longitudinal relationship 

between DAP concentrations and autonomic nervous system responses were also constructed, 

but results of these models were reported to be similar to the cross-sectional modeling results and 

were not presented in the report. 

Statistically significant relationships were not observed between reactivity patterns and prenatal 

or child DAP concentrations. Child total dimethylphosphates and total DAP concentrations were 

significantly negatively associated with resting respiratory sinus arrhythmia at 6 months and 

maternal prenatal dimethylphosphates and child total diethylphosphate concentrations were 

significantly positively associated with resting pre-ejection period at age 1 year. However, no 

associations with resting autonomic system parameters were observed in 3.5 year old or 5 year 

old children, nor with reactivity (i.e. autonomic nervous system response to challenge 

conditions) at any age. Cumulative maternal total diethylphosphates were associated with lower 

average heart rate, but only at the 5-years follow-up. No statistically significant differences in 

autonomic nervous system parameters were observed for 5-year-olds who had consistently high 

total DAP levels, relative to those who had consistently low DAP concentrations. Statistically 

significant interactions between prenatal and child DAP concentrations, nor did associations 

between the OP pesticide biomarkers and autonomic nervous system profiles vary by sex of the 

child. 

Although some evidence of autonomic nervous system dysregulation under resting condition in 

early childhood (≤1 year of age) was reported in this study, associations between non-specific 

biomarkers of maternal prenatal OP pesticide exposure and child OP pesticide exposure, and 

children’s autonomic nervous system regulation during resting and challenging conditions up to 

age 5 years were not consistently observed.
Page 23 of 171

Study Review

This was a well-conducted prospective study of prenatal and postnatal OP pesticide exposure 

effects on autonomic nervous system regulation among children up to age 5 years of age 

participating in the CHAMACOS birth cohort study. The discussion of the biologic plausibility 

underpinning the study hypothesis was robust. The analytic methods, exposure assessment, 

outcome assessment, and analytic approach were appropriate. Strengths of the study include the 

reasonable large sample size, the prospective design, the measurement of prenatal maternal 

urinary DAP concentrations at two time points, and the repeated measurements of child DAP 

urinary DAP concentrations and objective measurements of autonomic nervous system profiles 

at four time points in the first 5 years of life. 

The CHAMACOS study population was selected from a low income, agricultural community. 

The participants in this study are a subset of the original study sample, but the selection of this 

subsample was likely unbiased. The exclusion criteria (i.e. missing exposure or outcome data, 

use of medications that may affect autonomic nervous system responses, and twins) were 

reasonable and unlikely to have adversely affected the generalizability of the study results. The 

reasons for having missing DAP biomarker or outcome data were not discussed in detail, but the 

missing data is a possible source of selection bias. Only 27 children had urinary DAP 

concentrations available for all four time periods, which limited the investigator’s ability to 

evaluate cumulative exposure-response associations. 

The collection of urine samples and quantification of maternal prenatal and postnatal child 

urinary DAP concentrations appears to have been well conducted, and errors in these 

measurements, to the extent they exist, are almost certainly non-differential with respect to 

autonomic nervous system outcomes. The repeated sampling of DAP biomarker concentrations 

during pregnancy and during early childhood is a strength of this study. The use of non-specific 

biomarkers of OP pesticide exposure, as were assessed in this study, are likely more objective, 

sensitive, and likely also more accurate and reliable indicators of OP pesticide exposure, relative 

to exposure assessment methodologies that rely on self-report. That said, urinary DAP metabolite 

levels may reflect exposure not only to OP parent compounds, but also to the potentially 

nontoxic pre-formed metabolites in the environment. 

The investigators collected participant information via questionnaire, and also collected birth and 

pediatric medical records, allowing for a comprehensive assessment of potential confounders and 
Page 24 of 171

potential effect modifiers. Strong residual confounding by unmeasured or poorly measured 

confounders is unlikely in this study. 

The statistical analysis was appropriate. The authors presented results only from their crosssectional statistical models, though they also constructed longitudinal models and noted that the 

estimated associations from these more complex models were generally similar to those of the 

simpler models. Though it is likely that the study was not statistically powered to evaluate effect 

modification, several interactions were assessed in this study. Perhaps owing to the limited 

power, no statistically significant effect modification was observed. The authors constructed 

many models, but did not adjust their statistical results for multiple comparisons. 

The methods used to model resting and challenge conditions appear to have been reasonable and 

were age-appropriate. The assessments of autonomic nervous system function (respiratory sinus 

arrhythmia and preejection period) appear to have been similarly appropriate, valid, and wellconducted. 

While several associations were observed, no consistent associations between biomarkers of 

prenatal and child OP pesticide exposure and autonomic nervous system function were observed. 

The findings of this well-conducted study were largely null and thus generally not consistent 

with the hypothesis that prenatal and child OP pesticide exposures are associated with autonomic 

nervous system dysregulation. Though the authors adequately convey the biological plausibility 

and potential mechanism underlying the study hypothesis, this is the first reported study of OP 

pesticide exposure and indicators of autonomic nervous system function. As such, replication of 

the study in other study samples is needed before a well-supported conclusion can be reached 

regarding the potential association between OP pesticide exposure and autonomic nervous 

system function. In addition, there is not a body of literature to compare these ANS outcome 

results against, making it difficult to put them into context. Furthermore, this study did not focus 

on neurodevelopmental outcomes, which is the focus of the OP epidemiological literature 

review. Consequently, this Quirós-Alcalá et al. 2011 study was not evaluated further in the 

synthesis of the OP epidemiological literature review (add citation). 

References cited

Kaplan B, Meier-Kriesche H, Napoli K, Kahan B. A limited sampling strategy for estimating 

sirolimus area-under-the-concentration curve. Clin Chem 1997;43(3):539–40.
Page 25 of 171

Study 5. Rauch et al. (2012)

Associations of Prenatal Exposure to Organophosphate Pesticide Metabolites with 

Gestational Age and Birth Weight. Stephen A. Rauch, Joe M. Braun, Dana Boyd Barr, 

Antonia M. Calafat, Jane Khoury, M. Angela Montesano, Kimberly Yolton, and Bruce P. 

Lanphear. Environmental Health Perspectives. 120:1055–1060 (2012).

Study Summary 

To assess the relationship of exposure to pesticides during pregnancy and its association with 

gestational age and birth weight, Rauch and colleagues (EHP 2012) used the data collected from 

mothers and newborns enrolled in the Health Outcomes and Measures of the Environment 

(HOME) study, an ongoing prospective birth cohort study. They also examined whether these 

associations differed according to maternal race and infant PON1 genotypes status.

The study population was drawn primarily from Cincinnati, OH and consisted largely of women 

attending seven prenatal clinics in the Cincinnati metropolitan area between March 2003 and 

January 2006. Eligibility criteria to be enrolled in the study included being at least 18 years of 

age, living in a home built before 1978, and ≤ 19 weeks of gestation, being HIV negative, living 

within five surrounding counties; and not receiving thyroid or seizure medications, or 

chemotherapy or radiation treatments. Of 1,263 eligible women, 468 were enrolled in the study. 

Sixty-seven women dropped out of the study before delivery. The remaining 401 women gave 

birth to 389 live singleton babies, as well as 9 sets of twins and 3 still-born infants. Of those 

delivering singletons, 344 women provided urine at both 16 and 26 weeks gestation and they 

made up the primary study sample. In addition, 38 mothers were excluded in the final model; one 

mother because of a missing creatinine value, 22 because of missing covariate values, and 15 in 

the “other race” category. Thus, the final sample size was 306. 

Pesticide exposure was assessed by measuring the concentrations of six urinary nonspecific 

dialkyl phosphate (DAP) metabolites in two maternal spot urine samples collected at 16 and 26 

weeks of gestation using a modification of the analytical method of Bravo et al. (2004) that 

employs gas chromatography-tandem mass spectrometry with isotope dilution calibration. DNA 

was extracted from frozen archived blood for PON genotyping using the TaqMan assays. 

Genotype data was available for 312 of 344 (90.7%) of infants, with 300 (87.2%) having 

identifiable single nucleotide polymorphisms (SNPs) at both PON1 sites. Birth weight was 
Page 26 of 171

abstracted from medical records and gestational age was calculated from the mother’s selfreported date of last menstrual period. When this information was not available, the results of an 

ultrasound (n = 7) was used or a Ballard examination performed just after delivery (n = 3) to 

determine gestational age. Demographic factors (maternal age, education, race/ethnicity, parity, 

income, marital status) were obtained from subject interviews.

Multivariable linear regression was performed to examine associations between the sum of six 

DAP concentrations (ΣDAP) with gestational age and birth weight. In addition, difference in 

associations according to infant PON1_192 and PON1–108 genotypes and mother’s race were 

also examined. To examine gene–environment interactions between PON1 genotype and OP 

pesticides, several PON-stratified analyses were conducted, stratifying by PON1192 or PON1–

108. Because race appeared to be an effect modifier and PON1 genotype can vary across racial 

groups, authors also ran the PON1-stratified analyses separately for black and white mothers 

whenever possible given sample sizes. 

A 10-fold increase in ΣDAP concentrations was associated with a 0.5-week decrease in 

gestational age (95% CI: –0.8, –0.1) and 151 grams decrease in birth weight (95% CI: –287, –

16). In race-stratified models, ΣDAP concentrations were associated with shortened gestation in 

white newborns (–0.7 weeks; CI: –1.1, –0.3), but not in black newborns (–0.1 weeks; 95% CI: –

0.9, 0.6). Associations with ΣDEAP and ΣDMAP concentrations were weaker, but ΣDMAP 

concentrations were associated with a 0.4-week decrease in gestational length (95% CI: –0.7, 

0.0). Birth weight was also inversely associated with ΣDAP concentrations and ΣDMAP 

concentrations (–124 g, 95% CI: –245, –2), but not ΣDEAP concentrations. PON1 genotype was 

also associated with maternal race/ethnicity in the study sample. Infants born to white mothers 

were more likely to have PON1192QQ (51.4% vs. 12.7%) and PON1108CT genotypes (45.7% 

vs. 20.0%) than infants born to black mothers. Infants with black mothers were more likely to 

have PON1192RR (44.3% vs. 10.4%) and PON1–108CC (76.3% vs. 29.8%) genotypes (all chisquare p-values < 0.001). 

In summary, prenatal OP insecticide exposure was associated with shorter gestation and lower 

birth weight in this cohort. The magnitude of these associations differed according to maternal 

race and infant PON1 genotype status. In infants born to white mothers (mostly PON1192QQ), 

OP pesticide exposure was associated with shortened gestation and in infants born to black 

mothers (mostly PON1108CT), OP pesticide exposure was associated with lower birth weight.
Page 27 of 171

Study Review

This was a well conducted study with notable strengths and few weaknesses. Study population 

included racially and demographically mixed birth cohort. The fact that two urine samples were 

collected for exposure assessment and the infants PON1 genotype was taken into consideration 

to assess the magnitude of exposure between OP insecticide and birth outcomes, make this study 

unique. The analytic methods, analytic approach, and statistical analysis were appropriate. The 

author’s approach to evaluating and adjusting for covariates were prudent. 

Biomarkers of pesticide (DAPs, DEAPs, and DMAPs) were assessed in two maternal urine 

sample provided during 16 and 26 weeks gestation. So, this study was able to account for some 

of the temporal variation in urinary DAP concentrations by combining the concentrations of two 

samples taken months apart. However, because of the short elimination half-life, episodic nature 

of exposures to OP pesticides, and individual variation in metabolism, , it is unclear the extent to 

which the biomarker assessment necessarily provided a good “level” of exposure. A urine 

sample was also collected within 24 hours of delivery but the data was not used to avoid 

confounding due to metabolic changes that occur around the time of delivery. 

Birth weight was likely to have been accurately measured, since it was abstracted from medical 

records. However, gestational age may have recall errors as that was obtained from the mother’s 

self-reported date of last menstrual period. When this information was not available, the results 

of an ultrasound (n = 7) was used or a Ballard examination performed just after delivery (n = 3) 

to determine gestational age.

According to the study, decrements in birth weight and gestational age associated with ΣDAP 

concentrations were greatest among infants with PON1192QR and PON–108CT genotypes. The 

study did not measure serum levels of PON and other OP-detoxifying enzymes, or maternal 

PON1 genotype, which may be more relevant during gestation and fetal development. Also, OP 

insecticide was associated with shorter gestation in white newborns but not in black newborns 

and the reason of this association is not clear.

The authors were also able to collect data on, and adjust for, important covariates, including 

income, education, maternal depressive symptoms, maternal IQ, insurance status, area of 

residence, prenatal care, PON1 genotype, and gestational exposure to alcohol, lead, and tobacco. 

Covariates used in the analyses were selected, according to the authors, from variables known to 

be associated with gestational age and birth weight. 
Page 28 of 171

The authors also conducted sensitivity analyses. They found that mother’s medical conditions 

were associated with birth outcomes and DAP urinary concentrations. Mothers with medical 

conditions had shorter gestations and lower birth weight newborns than the rest of the study 

population. 

Since this study evaluated the association between exposure to OP pesticides during pregnancy 

and gestational age and birth weight by maternal race, this study may be used in other studies in 

which race of a population is taken into consideration. 

Authors concluded that maternal exposure to OP insecticide is inversely associated with 

gestation age and birth weight and the magnitude of these associations differed according to 

maternal race and infant PON1 genotype status. 

References cited

Supplemental Material, Table 1 and Figures 1 and 2, http://dx.doi.org/10.1289/ehp.1104615
Page 29 of 171

Study 6. Wolff et al. (2007), Furlong et al. (2014)

• 2007. Prenatal Pesticide and PCB Exposures and Birth Outcomes. MS Wolff, S Engel, 

G Berkowitz, S Teitelbaum, J Siskind, DB Barr, J Wetmur. Pediatric Research 

61(2):243-250.

• 2014. Prenatal exposure to organophosphate pesticides and reciprocal social behavior 

in childhood. Melissa A. Furlong, Stephanie M. Engel, Dana Boyd Barr, Mary S. Wolff. 

Environment International 70:125-131.

Study Summary

In these reports on the Mt. Sinai Environmental Health Study, a multi-ethnic prospective birth 

cohort study in New York City, USA, Furlong et al. evaluate the relationship between prenatal 

organophosphate (OP) pesticide exposure and impaired social behavior during infancy among 

participant mothers and their children (Engel et al. 2007), while Wolff et al. evaluate biomarkers 

of maternal exposure to DDE, PCB, and OP metabolites in the third trimester of pregnancy 

among 404 mothers in a multiethnic cohort in New York City and their effects on fetal growth.

Primiparous women with singleton pregnancies who delivered at the Mount Sinai Hospital 

between May, 1998 and July, 2001 were recruited at either an East Harlem clinic serving a 

predominantly minority population or at either of two private practices on the Upper East Side of 

Manhattan. Of 479 mother–infant pairs recruited, 75 were excluded, resulting in a final sample 

of 404 mother–infant pairs for whom birth data were available. 

Maternal blood and urine samples were collected between 25 and 40 weeks of gestation (during 

the third trimester of pregnancy). Cord blood samples were obtained at the time of birth. 

Maternal blood plasma was used to analyze DDE and PCB levels in a random subset of women 

(n 194). Maternal urine samples collected before January 2001 (n 386) were analyzed by the 

Centers for Disease Control and Prevention (CDC) for six dialkylphosphate metabolites (DAPs) 

and malathion dicarboxylic acid (MDA) by GC-tandem MS. Metabolite levels below the lower 

LOD were assigned a value equal to the LOD/√2. Molar concentrations of diethylphosphate 

metabolites (DEP) and dimethylphosphate metabolites (DMP) were then summed to obtain total 

DEP and total dimethylphosphates, respectively. DEP and DMP totals were then together 

summed to obtain total dialkylphosphates (DAP).
Page 30 of 171

Lead levels (PbB) were measured in cord blood (n 102) or maternal whole blood (n 192) if a 

cord blood sample was not available. 

To ascertain data on social and demographic characteristics, medical history, and lifestyle 

factors, a questionnaire was administered to the expectant mothers at the time of the urine 

specimen collection. Birth outcomes were obtained from a perinatal medical database. 

Wolff et al (2007)

The authors modeled pesticide exposure and birth outcomes using linear models; covariates 

included environmental biomarker values, maternal race/ethnicity (white versus nonwhite), 

infant sex, and, except for those analyses predicting gestational age, gestational age. Models with 

total DAPs included PON1 phenotype as tertiles or PON192 genotype (RR, RQ, QQ), or BuChE. 

OC models were adjusted for maternal age. Additional covariates were identified using bivariate 

analyses for biomarkers (Spearman correlation for continuous and χ2 or Mantel-Haenszel (M-H) 

for categorical variables with p < 0.15), including those reported previously for OCs (Wolff et al. 

2005). Race, education, and marital status were highly correlated, and therefore only race was 

included in birth outcome models (Berkowitz 2004). Continuous biomarker values were logtransformed, and 0.5 was added to total DAPs to remove zero values. Potential covariates were 

added to the base model for each birth outcome, and backward stepwise elimination was used to 

remove covariates that altered biomarker betas by <15%. Final alkylphosphate models did not 

have entered any variables besides the base covariates. The authors evaluated the effect of PON1 

activity by comparing the least squares means for PON1 by examining the interactions between 

APs and PON1 or PON192 genotype for those models where a main effect at p< 0.1 had been 

seen for urinary APs, PON1, or PON192.

The authors observed maternal total DAPs exhibited weak, non-significant inverse associations 

with three birth outcomes: total DEP with birth weight, total DEP with Ponderal index, and total 

DAP with head circumference (adjusted; Table 3). MDA was not associated with any birth 

outcomes (p <0.15).

Furlong et al (2014)

This study was conducted on a subset of the initial cohort children (n= 136) who returned for the 

7–9 year follow-up visit. The investigators used regression analysis of non-missing values to 
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impute six (of 136) metabolite levels lost due to “analytic interference” (Engel et al. 2007).

Overall, approximately 97%, 89%, and 90% of the cohort had detectable levels of DAP, DEP 

and DMP metabolites, respectively. 

Impaired reciprocal social behavior in childhood was measured by the Social Responsiveness 

Scale (SRS). The SRS is a caregiver survey of social behaviors originally designed to quantify 

impairments in reciprocal social behaviors in evaluating Autism Spectrum Disorders 

(Constantino and Gruber, 2005), but was used by the investigators of this study as a general 

indicator of impaired social responsiveness common to a wider set of with neuropsychiatric 

conditions, including as ADHD, language problems, maladaptive behavior, social anxiety, and 

mood disorders. Each of the 65-items rates the frequency of a specific behavior on a Likert scale, 

with higher scores indicating greater impairment. 

Levels of DAP, DEP, and DMP (nm/L) were examined continuously (after Log10-

transformation) and using creatinine-corrected tertiles (nm/g). Multivariate linear regression was 

used to analyze relationships between the Log10-transformed OP metabolite exposure 

biomarkers (independent variables) and continuous SRS total scores (the dependent variable). 

The investigators initially identified potential confounders (maternal age, maternal education, 

race/ethnicity, marital status, child sex, smoking during pregnancy, breastfeeding, housing type, 

child age at the time of testing, and urine creatinine) after constructing and evaluating a directed 

acyclic graph (DAG) to identify confounding pathways (Rothman et al. 2008). They then used 

backward elimination and a change-in-estimate criteria of 20% to construct a parsimonious 

model. The authors also assess modification of the association between SRS score and DAP 

levels (independently) by child sex and race/ethnicity. 

Linearity of the exposure–response curve was evaluated by estimating associations between SRS 

score and tertiles of creatinine-adjusted DAP levels as well as by constructing restricted cubic 

splines of the dose–response function in exploratory analyses, although results of the smoothed 

association curves were not presented by the authors. 

In their primary analyses, Furlong et al. did not observe statistically significant associations 

between prenatal maternal total DAPs, DEP, or DMP and total SRS scores. Among all 

participants who returned for the 7-9 year visit (n=139), poorer social responsiveness as 

measured by the SRS was not associated with a 10-fold increase in any of the OP metabolites 
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metrics (DAP: β = 0.3, 95% CI: -2.3, 2.9); DEP: β = 1.8, 95% CI: -0.7, 4.3; DMP: β = -0.2, 95% 

CI: -2.4, 2.0) in multivariate models.

Although overall, no statistically significant associations were observed between non-specific 

prenatal OP metabolite (DAP, DMP, DEP) levels and impaired social responsiveness in early 

childhood in this population of urban, inner-city cohort, the investigators did observe some 

evidence of modification of the association between prenatal OP pesticide exposure and impaired 

social responsiveness in early childhood by race/ethnicity and child sex, with an association 

observed (only) among black participants and boys. Among black participants, a 10-fold increase 

in DEP was associated with poorer social responsiveness (β = 5.1; 95% CI: 0.8, 9.4). There was 

no association among whites or Hispanics, or for DAP or DMP biomarker levels. A negative 

association between DEP and SRS score was observed among boys (β = 3.5; 95% CI: 0.2, 6.8), 

with no notable association observed among girls. The study did not have sufficient sample size 

(and corresponding statistical power) to analyze the interaction between OP pesticide and the 

joint effect of race/ethnicity and child gender. 

Furlong et al. report an association between one (of three) biomarkers of prenatal OP pesticide 

exposure (DEP) and poorer scores on the Social Responsiveness Scale, indicating impairment of 

social responsiveness among blacks and possibly among boys in an urban, inner-city cohort. It is 

unclear whether the association observed among blacks is due to differences in OP pesticide 

exposures or susceptibility factors associated with race/ethnicity. These results provide relatively 

weak evidence of a relationship between prenatal OP pesticide use and subsequent social 

impairment at age 7-9 years of age.

Study Review

These were well-conducted prospective cohort analyses of prenatal OP pesticide exposure and 

subsequent birth outcomes or social functioning at age 7-9 years of age in an urban setting in the 

US. The analytic methods, questionnaire, and analytic approach were appropriate. The statistical 

analysis was well specified and appropriate. 

Wolff et al (2007)

This study tested whether exposures to organophosphate pesticides, as measured by 

diakylphosphate metabolites have an association with birth outcomes such as head 
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circumference, birth weight, birth length, ponderal index, and gestational age in a population of 

mothers and their newborn infants in New York City. This study presents very similar 

information with respect to pesticide exposure and birth outcomes as the previous report from 

this cohort (Berkowitz et al. 2004) and doesn’t really add much to the literature on OP pesticide 

exposure and neurodevelopment. The strengths and limitations of this work are largely the same 

as the previous study.

Although the study was largely null, with respect to a relationship between the birth outcomes 

and the pesticide metabolites, the stratification by PON1 status provided some plausible 

information on individual susceptibility to pesticide exposure. As with any study, there are 

notable strengths and several weaknesses. Of note, no limitations were enumerated in the 

discussion of the study by the authors.

The prospective nature of the study provides assurance the OP pesticide exposure precluded the 

outcome measurement. Biomarkers of pesticide were assessed in a single maternal urine sample 

provided during the third trimester. The authors do not discuss the impact of policies aimed at 

reducing use of chlorpyrifos on the prevalence and magnitude of pesticide exposures among the 

study population; it is likely that use of chlorpyrifos exposure was decreasing over the time 

period of the study, as noted in other similar studies. The authors do not deliberate on the degree 

to which the biomarkers assessed represent usual exposure to pesticides versus recent, acute 

exposure(s), nor do they discuss the relative importance of assessment of exposure during the 

third trimester vis-à-vis fetal growth and development. The critical window of exposure for 

pesticide effects is not fully characterized, but is likely occur either early (e.g., for effects on 

brain mass and volume) or late in gestation (e.g., for effects on birth weight and length). If 

sources and patterns of exposure remain static, a single measurement would be a good indicator 

of pesticide exposure during pregnancy, even if the pesticides have short half-lives in vivo. If, 

however, sources and exposure patterns change over short time-spans, perhaps on the order of 

days to weeks, the biomarker assessment would not necessarily provide a good indicator of the 

relevant exposure. The authors classified biomarker levels according to the assays’ levels of 

detection (above versus below). Falsely negative exposure characterization would occur if 

mothers were exposed only early in pregnancy, and the pesticides were fully metabolized prior to 

the third trimester. Incorrect classification of participants as exposed, when in fact they were not 

exposed, was unlikely to have occurred using the biomarkers. Like other sources of measurement 

error in this study, errors in the biomarker indicators of exposure in this study are likely to have 

resulted in a non-differential misclassification, with respect to fetal growth and development. 
Page 34 of 171

The health outcomes in this study, head circumference, birth weight, birth length, ponderal 

index, and gestational age were likely to have been accurately measured in this study, as 

Berkowitz et al. 2004 states they were obtained through direct linkage with the computerized 

medical record. Any errors in outcome measurement would have occurred in the clinic, and are 

likely to be small and certainly non-differential with respect to pesticide exposure. 

To some extent, the recruitment process resulted in a population that was likely homogeneous 

with respect to confounders of the in utero pesticide exposure-fetal growth relationship 

(compared to the general population), and the potential for confounding was thus limited by 

design. The authors were also able to collect data on, and adjust for, important covariates, 

including race/ethnicity, infant sex, and gestational age. The authors also controlled for birth 

weight or birth length in their assessment of head circumference and pesticide exposure. 

Covariates used in the analyses were selected, according to the authors, from variables known to 

be associated with either pesticide exposure or fetal growth. The authors did not include data on 

other environmental contaminants in their multivariate models, e.g., metals, organochlorine 

pesticides, polychlorinated biphenyls. To the extent that such contaminants are determinants of 

fetal growth and development and correlated with (but not caused by) pesticide exposure, they 

may confound the associations of interest in the study. If these co-exposures are positively 

associated with both pesticide exposure and diminished fetal development, they would bias the 

true association upward (towards larger mean differences associated with exposure). This is 

unlikely to have occurred in this largely null study, especially given that the effects of these 

compounds were largely null as well.

The authors chose to keep parsimonious models and only include factors that altered biomarker 

betas by <15% in the final models. This is preferable to using a statistical test as a means to 

select covariates from a larger set of potential confounders. 

Bias due to confounding by unmeasured determinants of fetal growth and development is 

possible in this observational study. Most worrisome is the potential for confounding by factors 

related to socioeconomic condition of those assessed and co-contaminants to which the study 

participants may have been exposed. Neither of these potential confounders is addressed in detail 

in the article. 
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Bias due to differential errors in the selection of study participants is unlikely to have occurred in 

this prospective study with no loss to follow-up. Appropriate exclusion criteria were applied, 

including mothers with no prenatal medical visit prior to 26 weeks of gestation, mothers with 

serious chronic diseases (e.g., diabetes, hypertension, thyroid disease), mothers who developed a 

serious pregnancy complication that could affect fetal growth and development, and mothers 

who consumed more than two alcoholic beverages per day or who used illicit drugs, mothers 

with multiple births, and infants born with a congenital malformation or severe prematurity. 

The generalizability of the study may be limited as consequence of the particulars of the study 

population assessed and the numerous exclusion criteria applied. Making valid inference using 

these results requires an assumption that the pesticide exposure-fetal development association is 

the same in this population as the population to which the results are being generalized. This 

study population consisted of primiparous women, recruited early on in their pregnancies from 

the prenatal clinic and two private practices at Mount Sinai Hospital in New York from March 

1998 to March 2002, consisted predominantly of young Hispanic women with low education. 

Sixty-eight percent were less than 25 years old. Just under half were Hispanic (49.8%), although 

substantial numbers of White (21.0%) and African-American (27.7%) women also participated. 

Just under half (46.8%) classified themselves as being either single, divorced, widowed, or 

separated, and just over half (50.1%) had no more than a high school education. The exclusion 

criteria applied to potential study participants further focused the population assessed, relative to 

the general population of pregnant women. In the likely situation that the prevalence of 

important modifiers of the exposure-fetal development association in this focused study 

population is different from that in other populations of concern, generalizability will be limited. 

Important modifiers to consider may include time spent in the home, patterns of food preparation 

and consumption, health consciousness, the baseline health status of the mother (and father), and 

a host of socioeconomic determinants. The investigators finding of deferring effects by PON1 

activity is illustrative of limits on the generalizability of the study; populations who have high 

levels of paraoxonase activity vary by genetotypic and phenotypic determinants. The potential 

limitation vis-à-vis generalizability is offset by a strength; the study has increased statistical 

efficiency, relative to one set in a general population, as the infants are likely at relatively higher 

risk of sustaining cognitive and behavioral deficits. Furthermore, the population assessed in this 

study is of particular public health interest due to its high baseline risk of developmental 

challenges. 
Page 36 of 171

An adverse effect of OP pesticides on infant growth and gestational age is biologically plausible, 

as is modification of the pesticide-fetal growth association. OP pesticides are a potential 

neurotoxins detoxified by PON1. The finding that maternal PON1 activity modifies the 

association between markers of pesticide exposure and fetal growth and development is 

intriguing. 

The net effects of confounding, selection bias, and information bias, are unlikely to have 

qualitatively changed the results of this well conducted, prospective cohort study. Non-specific 

biomarkers of exposure, as were assessed in this study, are likely more objective, sensitive, and 

likely also more accurate and reliable indicators of pesticide exposure, relative to exposure 

assessment methodologies that rely on self-report. Almost certainly, such biases would not have 

resulted in the observation of a falsely positive association between pesticide exposure and fetal 

growth. More likely to have occurred is an attenuation of the true (unobserved) associations, 

toward (observed) associations that are relatively smaller, or null. Indeed, the findings of this 

study are either null, or associations of small magnitude. 

Furlong et al. (2014)

Inferences from the results of the investigation are constrained by limitations of the study design, 

including substantial loss to follow-up, the exposure assessment (levels of DAP, non-specific 

biomarkers of OP pesticide exposure in a single prenatal urine sample), the assessment of social 

impairment (the SRS), and the methods used to select, and subsequently adjust for, confounders.

The authors employed a reasonable set of inclusion/exclusion criteria that likely resulted in 

recruitment of an inner-city study population that was ethnically diverse. The investigators 

prospectively collected maternal and child information (potential confounders and effect 

modifiers). 

Selection bias due to substantial loss to follow-up is likely to have occurred in the study. In this 

report, analyses were conducted among 136 mother-child pairs, representing only a third of the 

404 sets constituting the original cohort. This limited the study’s statistical power (efficiency) 

and more concerning, leaves open the possibility of selection bias resulting from loss to followup. The authors noted that the loss to follow-up appeared only to be associated with marital 

status. However, it is not possible to evaluate the extent to which determinants of selection (out 
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of the study) also affected the children’s social impairment. One can, therefore, only speculate as 

to the magnitude and direction of bias induced by the loss to follow-up.

The use of non-specific biomarkers of prenatal OP pesticide exposure, as were assessed in this 

study, are likely more objective, sensitive, and likely also more accurate and reliable indicators 

of pesticide exposure, relative to exposure assessment methodologies that rely on self-report. 

However, to the extent that in utero OP pesticide exposure is the true exposure of interest, the 

assessment of non-specific organophosphate pesticide metabolites in a single maternal sample of 

urine is a primary potential source of exposure measurement error. Levels of non-specific OP 

metabolites in a single urine sample, as was conducted in this study, reflect very recent exposure, 

i.e., in the 24 to 48 hour period prior to the collection of the urine sample, and may or may not 

represent individual’s typical OP pesticide exposure. Moreover, urinary DAP metabolite levels 

may reflect exposure not only to OP parent compounds, but also to potentially nontoxic preformed metabolites in the environment. The use of a single urine sample to estimate maternal OP 

pesticide exposure is likely to have resulted in an attenuation of associations, relative to those 

that would have been observed had the investigators used a time-integrated marker of OP 

pesticide exposure. 

On the whole, the investigators handling of confounding resulted was reasonable. Aspects of the 

investigator’s approach to evaluating and adjusting for confounding were prudent, though other 

aspects of their approach, while conventional, have limitations. In particular, their use of DAG’s, 

avoiding adjustment for hypothesized intermediates in the causal pathway between OP pesticide 

and social impairment as well as and “colliders,” their prospective ascertainment of covariate 

information from questionnaires and medical records, and their intention to construct a 

parsimonious model given the limited sample size are all positive aspects of their methods. 

However, the use of a backward elimination strategy and covariate inclusion/exclusion based on 

a change-in-estimate criteria lack strong theoretical underpinnings. Although notionally less than 

ideal, these later methods were unlikely to have had a major negative impact on the study. 

Notable, there were large differences between beta coefficients estimated from unadjusted, 

relative to the covariate-adjusted models. This is evidence of strong (net) confounding for which 

the authors appropriately adjusted. 

The investigators evaluated a priori hypotheses regarding effect modification of the association 

between OP pesticide and social impairment by race/ethnicity and sex of the child. However, the 
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small sample size limited the statistical power of the tests of these hypotheses, and precluded the 

joint interaction between OP, race/ethnicity, and sex. 

The instrument used to assess neurodevelopment in this study is commonly used, widely 

accepted, and has been validated. The authors noted that the SRS has good test–retest temporal 

stability, parent–parent and parent–teacher interrater agreement, and discriminate and concurrent 

validity (Constantino and Gruber, 2005).

References cited

Berkowitz GS, Wetmur JG, Birman-Deych E, Obel J, Lapinski RH, Godbold JH, Holzman IR, 

Wolff MS 2004 In utero pesticide exposure, maternal paraoxonase activity, and head 

circumference. Environ Health Perspect 112:388–391.

Constantino JN, Gruber CP. Social Responsiveness Scale. Western Psychological Sciences; 2005 

[Los Angeles, CA].

Engel SM, Berkowitz GS, Barr DB, Teitelbaum SL, Siskind J, Meisel SJ, et al. Prenatal 

organophosphate metabolite and organochlorine levels and performance on the Brazelton 

Neonatal Behavioral Assessment Scale in a multiethnic pregnancy cohort. Am J 

Epidemiol 2007;165:1397–404.

Rothman KG, Greenland S, Lash T. Modern epidemiology. Philadelphia, PA: Lippincott 

Williams & Wilkins; 2008.

Wolff MS, Deych E, Ojo F, Berkowitz GS 2005 Predictors of organochlorines in New York City 

pregnant women, 1998–2001. Environ Res 97:170–177.
Page 39 of 171

Study 7. Anderson et al. (2015)

Occupational pesticide exposure in early pregnancy associated with sex-specific 

neurobehavioral deficits in the children at school age. Helle R. Andersen, Fróði Debes, 

Christine Wohlfahrt-Veje, Katsuyuki Murata, Philippe Grandjean. Neurotoxicology and 

Teratology 47:1-9, 2015.

Study Summary

Anderson et al. reported on results of a study evaluating maternal occupational pesticide 

exposure during early pregnancy and impaired neurodevelopment in children at school age in a 

birth Cohort. 

This prospective birth cohort study, set in Denmark between 1996 and 2000, recruited women 

working in greenhouse horticultural occupations at the beginning of their pregnancy in order to 

study the potential health effects of prenatal pesticide exposure. Specifically, the investigators 

evaluated performance on a battery of neurobehavioral tests among children age 6 to 11 years of 

age, comparing children of women considered pesticide exposed during early pregnancy, to 

those from mothers who were defined as not having pesticide exposure during early pregnancy. 

At the start of the study, pregnant women working in greenhouses were recruited for 

participation and evaluated by one of two toxicologists at Odense University Hospital in 

Denmark with expertise in greenhouse working conditions in order to categorize them with 

respect to pesticide exposure. A detailed occupational history was collected via interview to 

elucidate the working conditions in the previous three months, to include job function, personal 

handling of pesticides, types of pesticides handled, frequency of pesticide application, protocols 

for reentering greenhouses where pesticides had been recently applied, and use of personal 

protective equipment. These interviews were conducted prior to any examinations of the 

women’s children. The women were defined as having occupational pesticide exposure if 

pesticides were applied in their work area more than once per month and the women handled 

pesticide-treated plants within one week after treatment and/or the women were directly involved 

in applying pesticides (only 6% of women applied pesticides). Women who met none of the 

above criteria were categorized as occupationally unexposed to pesticides cases. The women 

deemed pesticide-exposed, either went on paid leave or were transferred to work functions with 
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less or no pesticide exposure shortly after enrollment in the study. The occupational pesticide 

exposure was thus confined to the early weeks of the first trimester of pregnancy. 

Initially, 168 children categorized as having had prenatal pesticide exposure and 35 children 

categorized as not having had prenatal occupational pesticide exposure were enrolled in the 

study. Of this original cohort of children, 133 accepted an invitation to participate in this followup study at age 6-11 years old, 112 of whom had prenatal pesticide exposure, and 21 of whom 

were prenatally unexposed. An additional 44 unexposed children were recruited from among 

friends, relatives, and neighbors of the participating families to supplement the unexposed group.

A questionnaire was completed prior to the neurobehavioral examination to solicit information 

on medical history, education, occupation, lifestyle, and diet. Additional information on medical 

history, lifestyle, and behaviors to include diet, smoking, alcohol use, and medication use was 

collected at base-line, or prior to the neurobehavioral assessment for the new families enrolled in 

the study to supplement the number of unexposed children.

A standardized clinical exam was conducted on all children, to include the following neurologic 

functions: social response, spontaneous motility, involuntary movements, Romberg’s sign, 

walking on a straight line, standing on one leg, hopping, reflexes, patellar reflexes, finger 

opposition test, diadochokinesis, finger-to-nose coordination, hearing and vision. Heart rate 

variability and brainstem auditory evoked potential latencies were assessed to evaluate 

neurophysiological status. Neuropsychological tests included manual motor speed (finger 

tapping test), simple reaction time, attention (Conners' Continuous Performance Test II), shortterm memory (Wechsler Intelligence Scale for Children-Revised Digit Span Test), language 

function and long-term memory (Woodcock–Johnson III Tests of Cognitive Abilities, Verbal 

Comprehension test), and visuospatial performance and memory functions (Raven's Colored 

Progressive Matrices).

The authors selected potential covariates from a list of determinants for each clinical, 

neurological, neuropsychological, neurocognitive, and neurobehavioral outcome considered a 

priori. These included age at examination, gender, maternal ethnicity, maternal smoking and 

maternal alcohol consumption, and social class. The statistical analysis consisted of multivariate 

linear regression models of the numerous neurobehavioral outcomes, followed by construction of 

a structural equation model to analyze the interaction between child sex and prenatal pesticide 

exposure on general intellectual ability parameterized as a latent variable.
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After evaluating a large number of potential associations between prenatal pesticide exposure 

and neurobehavioral outcomes, Anderson et al. observed largely null associations between 

maternal occupational pesticide exposure early in pregnancy and their child neurodevelopment 

as assessed at age 6-11 years of age. A few associations were observed that were consistent with 

a hypothesis that maternal occupational pesticide exposure early in pregnancy effects their 

children's neurodevelopment, as assessed at age 6-11 years of age. Specifically, prenatal 

pesticide exposure was significantly associated with prolonged brainstem auditory evoked 

potential latencies and, among girls, also with impaired neuropsychological function. Indicators 

of language development and motor speed functions were also inversely associated with 

maternal pesticide exposure during pregnancy among girls only.

Study Review

The interpretation of the results of this prospective birth cohort study of prenatal maternal 

occupational pesticide exposure and neurobehavioral deficits conducted among Danish women 

working in greenhouses and their children is constrained by substantial loss to follow up of the 

original cohort. The potential for selection bias, and, to a lesser extent, residual confounding, 

further limit the study. Some degree of both differential and non-differential errors in recall of 

exposures and outcomes is probable. Assessment of the interview-based proxy indicator of 

pesticide exposure was well conducted, though no measurements of pesticide levels or 

biomarkers were made. Similarly, the assessment of neurobehavioral outcomes was 

comprehensive. 

Selection of participants was reasonable; however, the sample size of this study was likely not 

sufficient (consisting of too few study participants), given the investigators' objective to evaluate 

a large number of associations between prenatal pesticide exposure and subsequent 

neurobehavioral outcomes, especially considering their decision to evaluate effect modification 

by child gender. The small sample size was, in part, due to the loss of more than 30% of the 

original study sample, this occurrence reduced statistical power and potentially induced selection 

bias. Mothers who had greater exposure, or greater concern regarding their occupational 

pesticide exposure and subsequent effects on their child's health may have been more likely to 

continue their participation in the study. The author's decision to address the attrition by 

augmenting the original non-exposed group with additional children not sourced from the 

original cohort in order to increase the statistical power of the comparisons between exposed and 
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non-exposed with respect to neurobehavioral status is also a potential source of selection bias. 

For example, the authors noted that the families of the newly recruited non-exposed children 

were more likely to belong to lower social classes, compared to children from the original birth 

cohort. The investigators appropriately conducted sensitivity analyses of the neuropsychological 

outcomes that were limited to children from the original birth cohort, observing association 

estimates similar to those in their primary analysis.

The pesticide exposure assessment was well conducted, though exposure classification was made 

based on occupational history rather than actual measurements of pesticide levels or biomarkers 

of exposure. Very few (~6%) of the mothers actually applied pesticides as part of their job 

duties, and it is possible that actual exposure was very low, especially considering that personal 

protective equipment was available and was reported to have been used (by an unspecified 

proportion of the mothers). The specific pesticides classes or formulations to which the women 

were exposed during early pregnancy were not elucidated. The authors noted that, “the exposure 

situation was complex,” with use of specific pesticides varying with time and location, between 

and within companies, and according to production requirements and the type of pests being 

controlled. The authors noted that approximately 200 different pesticide formulations, with 124 

different active pesticide ingredients, were used in the greenhouses. Organophosphates (e.g., 

dichlorvos, dimethoate, and chlorpyrifos), were used frequently in the working areas.

The transfer of women classified as having been occupationally exposed to pesticides to duties 

with less or no pesticide exposure, or to paid leave, after enrollment in the study has several 

implications. Though not stated explicitly in the report, the transfers were likely conducted for 

ethical considerations. Primarily, this restricted the evaluation of occupational pesticide 

exposures to those that occurred during early pregnancy (in contrast to many other investigations 

included in this review, which focused on exposures occurring during late pregnancy (e.g., 

during the third trimester). The influence of these transfers on other behaviors - particularly those 

that influence fetal development - is unknown. It is plausible that the women’s awareness of their 

occupational exposure and the change in job duties motivates them to make healthy choices 

which positively influence fetal development. Such an influence could potentially explain the 

lack of associations between occupational pesticide exposure and subsequent 

neurodevelopmental status. 

The selection and consideration of covariates for inclusion in multivariate regression models was 

appropriate. The acquisition of covariate information by questionnaire may have resulted in 
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residual confounding due to recall errors, particularly for mothers of the children enrolled to 

augment the non-exposed group, who were asked to recall exposures during their pregnancy 

(e.g., smoking behaviors and alcohol use) which occurred 7-11 years prior to completion of the 

survey. The author's classification of social class into broad categories, a design decision made in 

light of the relatively small sample size, leaves open the possibility of residual confounding by 

socioeconomic status.

Neuropsychological tests were given and scored by the same neuropsychologist. The same 

pediatrician performed all clinical examinations. The same examiner conducted all BAEP 

latency and heart rate variability calculations. The neuropsychological tests used in the study 

chosen for their validity, and demonstrated sensitivity to neurotoxicity of environmental 

pollutants, in addition to their brevity.

The authors evaluated numerous hypotheses (>20) regarding the association between prenatal 

pesticide exposure and neurobehavioral deficits without adjusting for multiple comparisons. 

Under a null hypothesis of no effect of pesticide exposure on these outcomes, one can expect to 

observe a 5% error rate, i.e. 'false positives' due to chance, and one cannot discount chance as a 

determinant of the observed associations in this study. Similarly, one cannot discount the 

possibility that the findings of apparent effect modification by gender were also due to chance. 

The finding of associations only among girls is unique to this investigation. That said, the 

investigator's use of a structural equation model avoided specification of an even larger number 

of statistical models.

The authors' conclusion that their findings suggest an adverse effect of prenatal occupational 

pesticide exposure on their children's neurodevelopment overstates the study findings which 

were 1) largely null, and 2) largely observed only among girls who represented less than half of 

the study population. 

Furthermore, given that a proxy exposure assessments was used in this study, the pesticides used 

may have included not only OPs, but also pyrethroids, fungicides, and growth regulators. Given 

the uncertainty about whether OP exposure actually occurred in this studies and whether 

observed outcomes are associated with OP exposure or with other pesticides, this study was

excluded from further analysis in the final synthesis of the OP epidemiological literature review 

(add citation). 
Page 44 of 171

Study 8. Guodong et al. (2012)

Organophosphate Pesticide Exposure and Neurodevelopment in Young Shanghai Children. 

Ding Guodong, Wang Pei, Tian Ying, Zhang Jun, Gao Yu, Wang Xiaojin, Shi Rong, Wang 

Guoquan, and Shen Xiaoming. Environmental Science and Technology 46:2911-2917, 2012.

Study Summary

In this report, Guodong et al. evaluate the relationship between organophosphate (OP) pesticide 

exposures and neurodevelopment in two-year old healthy children living in Shanghai, China 

using a cross-sectional study design with a single assessment of urinary OP metabolites and a 

single assessment of neurodevelopment in conjunction with a questionnaire to ascertain 

demographic and additional exposure information from the children’s mothers.

Study participants were recruited during a nine-month period in 2008. The investigators invited 

healthy children visiting the child healthcare departments of two community hospitals for routine 

physical examinations. Children were considered eligible for inclusion in the study if they were 

between 23 and 25 months of age, were capable of completing the neurocognitive assessment, 

and had no history of any of the following: intrauterine distress, pathologic jaundice, intrauterine 

infection, intracranial infection, or congenital disease. The parents of 301 of 310 children 

identified as having met these inclusion criteria provided consent, allowing their children to 

participate in the study.

Urine samples were collected from each participant at intervals throughout the day of their study 

assessment. Collected samples were stored at 2−4 °C, or frozen until shipment (on dry ice) to the 

CDC in Shanghai China, where they were stored at −70 °C until analysis. Participants’ urine 

samples were analyzed for five non-specific diakyl phosphate (DAP) metabolites (the dimethyl 

metabolites dimethylphosphate (DMP) and dimethylthiophosphate (DMTP), and the diethyl 

metabolites diethylphosphate (DEP), diethylthiophosphate (DETP), and diethyldithiophosphate 

(DEDTP)) using gas chromatography with flame photometric detection (GC-FPD). The limit of 

detection (LOD) was calculated for each of the five DAP metabolites from the instrument 

response factor corresponding to a concentration having a peak area three times that of blank 

measurement. The LOD was 1.0 μg/L for all analytes except for DMP which had a LOD of 2.0 

μg/L. All metabolite levels below the LOD were assigned a value equal to the LOD/√2. The 

urinary DAP metabolite concentrations were creatinine-adjusted. The creatinine-adjusted 
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geometric means (GMs) for the five urinary DAP metabolites were 11.27 μg/g for DMP; 6.99 

μg/g for DMTP; 7.96 μg/g for DEP; 14.19 μg/g for DETP; and 4.55 μg/g for DEDTP. These are 

high relative to those commonly observed in studies conducted in developed countries: Urinary 

concentrations (μg/L) of the nonspecific OP metabolites were also converted to summed molar 

concentrations (nmol/L) of the total DAPs, the two dimethyl metabolites, and the three diethyl 

metabolites were to provide summary measures of OP pesticide exposure. 

A questionnaire was administered to the mother of each child by a trained interviewer in order to 

garner demographic and socioeconomic information as well as exposure characteristics, 

environmental exposures, child characteristics and maternal characteristics. The children’s 

medical records were also used to derive anthropomorphic characteristics. 

Neurodevelopment was assessed using the Gesell Developmental Schedules (GDS). The 

participating children were administered a revised version of the GDS for 0-3 year-old children, 

adapted for use in the Chinese population and conducted by a pediatrician trained and certified in 

the administration of the GDS (Beijing Mental Development Cooperative Group, 1985). The 

items in the GDS capture four domains of neurodevelopmental functioning: motor behavior, 

adaptive behavior, language behavior, and social behavior. Each child was assigned a 

developmental quotient (DQ) in each of the four domains.

The creatinine-adjusted DAP metabolites were summed and Log10-transformed prior to being 

entered into multivariate linear regression models predicting each of the four domain-specific 

GDS DQ. All models were adjusted for covariates associated with neurodevelopment in the 

literature and significantly associated with 2 or more GDS DQ in this population: child sex, 

maternal education level, and household income. The authors did not assess modification of the 

association between GDS and DAP levels by other factors. 

The investigators did not observe any statistically significant associations between the children’s 

urinary DAP metabolite levels and neurodevelopment as measured by the four domain-specific 

GDS DQ quotients. Regression coefficients (β) and corresponding 95% confidence intervals 

(95% CI) and p-values for log10-tranformed total non-specific DAP metabolites were as follows, 

for each of the GDS functional areas. Total dialkyl phosphates: Motor Area: 0.30 (95% CI: 

−1.40, 1.99), p=0.73; Adaptive Area: 1.71 (95% CI: −1.15, 4.57), p=0.24; Language Area: 2.79 

(95% CI: −1.01, 6.60), p=0.15; Social Area: −0.66 (95% CI: −2.12, 0.79), p=0.37. Results for 
Page 46 of 171

log10-transformed molar concentrations of dimethyl phosphates were as follows, for each of the 

GDS functional areas: 

Motor Area: −1.25 (95% CI: −2.98, 0.47), p=0.1; Adaptive Area: 2.53 (95% CI: −0.05, 5.10), 

p=0.06; Language Area: 2.83 (95% CI: −0.60, 6.26), p= 0.11; Social Area: −0.48 (95% CI: 

−1.93, 0.97), p= 0.51. Regression coefficients for log10-transformed molar concentrations of 

diethyl phosphates were as follows, for each of the four GDS functional areas: Motor Area: 0.32 

(95% CI: −1.37, 2.01), p= 0.71; Adaptive Area: −0.41 (95% CI: −3.22, 2.39), p= 0.77; Language 

Area: −0.29 (95% CI: −4.02, 3.P244), p= 0.88; Social Area: −0.93 (95% CI: −2.40, 0.54), p= 

0.22. No other associations between DAP levels and GDS DQ were presented in the paper. 

Study Review

This was a well-conducted study of OP pesticide effects on neurodevelopment conducted in a 

population of healthy, young (2-year old) Chinese children. The analytic methods, questionnaire, 

and analytic approach were appropriate. The statistical analysis was not specified in great detail, 

but appears to be appropriate. That said, inferences to be garnered from the results of the 

investigation are constrained by limitations of the study design (cross sectional), the exposure 

assessment (levels of DAP, non-specific biomarkers of OP pesticide exposure in multiple urine 

samples collected on a single day), and the assessment of neurodevelopment (the GDS). 

The authors employed a reasonable set of inclusion/exclusion criteria that likely resulted in 

recruitment of a study population that was relatively homogeneous and characterized by normal 

neurodevelopment, on the whole; greater than 97% of the population was considered normal in 

three of the four GDS neurodevelopmental domains, with 93.7% scoring in the normal range in 

the language area. The relative homogeneity of the population may have limited statistical 

power, but it also limited confounding by design. The investigators collected participant 

information corresponding to an almost exhaustive list of potential confounders (summarized in 

table 1 of the paper), and found only three factors (the child’s sex, maternal education level and 

household income) that were significantly associated with two or more of the GDS DQ, even at a 

relaxed alpha level of 0.10. Strong residual confounding by unmeasured or poorly measured 

confounders is unlikely in this study. The investigators did not discuss observed relationships 

between the potential confounding factors and the children’s DAP biomarker levels. 

Selection bias is unlikely to have occurred in the study. 
Page 47 of 171

A limitation of the cross-sectional design is the reliance on the untestable assumption that (even 

valid) biomarkers of OP pesticide exposure measured in urine sampled at the time of the 

neurodevelopmental assessment are indicative of ‘usual’ OP pesticide exposure, or, more to the 

point, accurately reflect OP pesticide exposure at the critical time-window(s) for exertion of 

deleterious effects on neurodevelopment. 

The use of non-specific biomarkers of OP pesticide exposure, as were assessed in this study, are 

likely more objective, sensitive, and likely also more accurate and reliable indicators of pesticide 

exposure, relative to exposure assessment methodologies that rely on self-report. However, to the 

extent that OP pesticide exposure during early childhood is the true exposure of interest, the 

assessment of non-specific organophosphate pesticide metabolites in a single sample of urine is a 

primary potential source of exposure measurement error. Although considered by the authors to 

be the current standard for characterizing exposure to multiple OP pesticides that originate from 

different sources, the authors concede that urinary DAP metabolite levels may reflect exposure 

not only to OP parent compounds, but also to the potentially nontoxic pre-formed metabolites in 

the environment. The geometric mean DAP concentrations observed in this investigation are 

higher than those observed in the US (CDCP, 2009; Barr et al. 2004), a German reference 

sample (Becker et al., 2006), and a study of child biomarker levels conducted in Italy (Aprea et 

al., 2000). This difference between DAP biomarker levels observed in children living in 

Shanghai could be due to higher levels of OP pesticide exposure, compared to those of Western 

populations, though the difference noted could also be due to differences in laboratory methods; 

the lower limit of detection in this study was higher than those used by Barr et al., and similar to 

those of the German and Italian studies. The authors concluded that their relatively high LODs 

did not influence the essential findings of their study, though it is possible that the high end of 

the OP pesticide exposure distribution is higher than that of the US exposure distribution and the 

investigators’ laboratory methods could not resolve the low end of the exposure distribution, 

resulting in a higher overall observed average concentration, than that which would have been 

estimated using DAP quantification methods similar to those employed in the US.

The collection of multiple maternal urine samples throughout the day makes for a more robust 

estimate of OP pesticide biomarker levels on the day of the sample collection, but, nevertheless, 

the use of a single day’s urine samples to estimate the participant’s ‘usual’ OP pesticide exposure 

is likely to have resulted in an attenuation of associations, relative to those that would have been 

observed had the investigators used a time-integrated marker of OP pesticide exposure. 
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The investigators did not report having assessed effect modification by any factors. 

The instrument used to assess neurodevelopment in this study (i.e., the GDS for 0-3 year olds, 

adapted to the Chinese population) is commonly used, widely accepted, and has been validated 

in the Chinese population. 

The authors rightly conclude their paper by stating that a large, longitudinal study with repeated 

measurement of urinary biomarkers of OP pesticide exposure is needed to further examine the 

relationship between OP pesticide exposure and child neurodevelopment in this Chinese 

population. The findings of this well-conducted cross-sectional study of children living in 

Shanghai are not consistent with the hypothesis that OP pesticide exposure adversely affects 

child neurodevelopment at two years of age. 

References cited

Barr, D. B.; Bravo, R.; Weerasekera, G.; Caltabiano, L. M.; Whitehead, R. D. Jr.; Olsson, A. O.; 

Caudill, S. P.; Schober, S. E.; Pirkle, J. L.; Sampson, E. J.; Jackson, R. J.; Needham, L. L. 

Concentrations of dialkyl phosphate metabolites of organophosphorus pesticides in the 

U.S. population. Environ. Health Perspect. 2004, 112,186−200.

Becker, K.; Seiwert, M.; Angerer, J.; Kolossa-Gehring, M.; Hoppe, H. W.; Ball, M.; Schulz, C.; 

Centers for Disease Control and Prevention. Fourth National Report on Human Exposure 

to Environmental Chemicals, December 2009. http://www.cdc.gov/exposurereport/ 

(accessed June 06, 2015)

Thumulla, J.; Seifert, B. GerES IV pilot study: assessment of the exposure of German children to 

organophosphorus and pyrethroid pesticides. Int. J. Hyg. Environ. Health 2006, 209, 

221−233.

Aprea, C.; Strambi, M.; Novelli, M. T.; Lunghini, L.; Bozzi, N. Biologic monitoring of exposure 

to organophosphorus pesticides in 195 Italian children. Environ. Health Perspect. 2000, 

108, 521−525.
Page 49 of 171

Study 9. Handal et al. (2007, 2007B, 2008)

• 2007 - Effect of Community of Residence on Neurobehavioral Development in Infants 

and Young Children in a Flower-Growing Region of Ecuador. Environmental Health 

Perspectives. 2007; 115(1):128-133.

• 2007B - Neurobehavioral Development in Children With Potential Exposure to 

Pesticides. Epidemiology. 2007; 18(3):312-320.

• 2008 - Occupational Exposure to Pesticides During Pregnancy and Neurobehavioral 

Development of Infants and Toddlers. Epidemiology. 2008. 19(6):851-859.

Study Summary

Handal et al. examined neurobehavioral development in children from the EcoSalud project, 

launched in 2001 in the Cayambe-Tabacundo region, Ecuador in two communities: 1) lower 

altitude communities dominated largely by cut-flower production, with high potential for 

exposure to organophosphate (OP) and carbamate pesticides, and 2) a higher altitude community 

with low potential for exposure to pesticides. The first report (Handal et al., 2007) compared 

neurobehavioral development in infants and young children 3 to 61 months of age living in two 

communities. The second report (Handel et al., 2007b) considered household and community 

risk factors for pesticide exposure and their potential effects on neurobehavioral development of 

young children aged 24 to 61 months. The third report in the series (Handal et al., 2008) looked 

at potential effects of maternal occupation in the cut-flower industry during pregnancy on 

neurobehavioral development in children 3 to 23 months of age.

In 2003-2004, a census of the three communities was taken to construct the sampling frame. All 

mothers living at least one year in the community with and one or more children, age 3-61 

months were eligible. In total, 219 mothers (91.3% of those eligible) and 283 children 

participated in the study. Mothers were interviewed to obtain information on socioeconomic 

status, maternal occupational history, maternal and child health characteristics, and child’s 

socialization and exposure profiles. Examinations were conducted by trained testers.

• Children’s height, weight, and head circumference were measured. 
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• The child’s hemoglobin was measured from single finger-stick blood samples 

(HemoCue hemoglobin blood testing kit).

• Neurobehavioral development was assessed using the Ages and stages Questionnaire 

(ASQ), a widely-used developmental screening test, composed of 19 age-specific 

questionnaires that cover 5 broad developmental dimensions: communication, fine 

and gross motor skills, problem solving, and personal-social skills. Each domain is 

scored from 0 – 60 points, with 60 being a perfect score. A continuous score is 

calculated for each age-specific questionnaire, with scores summarized for each 

developmental domain.

• Visual Motor Integration (VMI) Test (ages 48-61 mos) - Beery-Buktenica, 4th Ed.

• Reach-and-grasp, bi-manual coordination) abilities, videoed (ages 9-18 mos), 1 

trained tester

• Visual acuity skills (ages 9-18 mos): UC Berkeley Preferential Looking Test Cards 

(WHO visual impairment classifications), 1 trained tester

Instruments were pre-tested to ensure clarity and comprehension and researchers performed 

pilot-tests to ensure high percent agreement between testers.

2007 analysis of community of residence on neurobehavioral development (ages 3-61 

months)

The associations between community of residence and delayed development (via ASQ) were 

evaluated using multiple linear regression, adjusting for child health status and other 

characteristics of the home environment. Anthropometric measures included child and mother 

height and weight; child’s birth weight from child’s vaccine record card, or mother report; 

chronic malnutrition (stunting) from child’s height- for-age z-score (2 standard deviations below 

the median); presence of anemia (via hemoglobin), after taking into account the child’s age and 

the altitude of the community of residence; stimulation by two variables - attendance at child 

care center and type and frequency of stimulating activities mother engaged in at home with each 

child in the preceding 3 days (6 questions adapted from UNICEF multi-country survey); home 

environment - relationship with husbands, or their families in the case of single mothers; 

maternal/paternal education, mother’s ethnicity and predominant language preference, marital 

status, age; monthly household income; housing construction characteristics (roof composition, 

floor composition, wall composition, type of water used in home, bathroom type, and access to 

electricity were summarized into a housing scale); social position (job of principal economic 

provider of family). To handle correlations due to sibling pairs, one sibling was randomly 
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removed from each pair. Pairwise t-tests and chi-square were used to assess the mean difference 

in ASQ score between community comparison groups. The magnitude of the effect of 

community residence on ASQ scores was analyzed using Cohen's d. 

Younger children (3–23 months of age) who resided in high-exposure communities scored lower 

in all 5 domains, but significantly lower on gross motor (8.8 points, p = 0.002), fine motor (5.0 

points, p = 0.06), and socio-individual (5.8 points, p-value = 0.02) skills, compared with children 

in the low-exposure community. In children 24–61 months of age residing in high-exposure 

communities, developmental delays were present in 2 of 5 domains, significantly lower scores on 

gross motor skills compared with children of similar ages residing in the low-exposure 

community (3.8 points, p = 0.06). 

In younger children (3–23 months of age), the effect of high-exposure community on gross 

motor skill development was greater for stunted children compared with non-stunted children (17 

points lower, p = < 0.001). Children who attended child care in high-exposure communities 

scored significantly better in their fine motor skills.

This preliminary study suggests poorer neurobehavioral development in infants and children 

residing in high-exposure communities, especially in the development of gross motor skills, even 

after controlling for major determinants of delayed development such as low stimulation at 

home, presence of anemia, and stunting. Findings also suggest that there may be a double burden 

of pesticide exposure and poor nutrition (i.e., stunting) on the neurobehavioral development in 

infants and young children, but that child care and increased stimulation at home may attenuate 

these effects.

2007B analysis of neurodevelopment in children with exposure to pesticides (age 24-61 

months)

Distribution of key risk factors (distance home to flower farm, maternal employment, father's 

current work status, pesticide use on domestic crops, pesticide use within home, use of 

potentially-contaminated plastics/wood from flower farm, child play activities) was assessed via 

cross-tabulation for collinearity, and chi-square tests for differences across risk factor categories. 

ANOVA and t-tests were used to assess differences in mean developmental scores among risk 

factors. Multiple linear regression models for each domain were constructed to assess effects of 

household environmental exposures and development, after controlling for key confounders. Due 
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to limited sample size, only variables found to be associated with each ASQ domain and the 

exposure variable of interest were included in each model. 

Mother’s current employment in the flower industry was associated with better scores among 

their children for all 5 ASQ domains. Specifically, current employment in flowers was more 

strongly associated with better communication (beta 4.13, SE 2.23) and problem-solving (beta 

5.03, SE 2.20) skills. Employment in the flower industry during pregnancy, however, showed a 

positive association only with the problem-solving skills domain (beta 3.57, SE 2.11). 

Pesticide use on domestic crops was also associated with better gross motor (beta 4.86, SE 2.18) 

and personal-social (beta 4.12, SE 2.46) scores, while conversely, pesticide use within the home 

was associated with lower communication scores (beta -4.51, SE -2.15, effect size: d=0.2). More 

hours spent outdoors (5+ hrs/d) was associated with lower gross (beta -2.52, SE -1.94) and fine 

motor (beta -2.12, SE -2.41) and problem solving (beta -3.28, SE -2.16) skills. Occasional or 

frequent playing in irrigation water was associated with poorer fine motor (beta -4.92, SE -2.22) 

and problem solving (beta -4.39, SE -2.03) scores. On average, a child who played with 

irrigation water scored approximately 5 points lower on fine motor skills (8.2% decrease; 95% 

CI 9.3 to 0.5; effect size, d=0.4), 4.4 points lower on problem solving skills (7.3% decrease; 8.4 

to 0.4; effect size, d=0.3), and 5.5 points less on the VMI test (3.4% decrease; 12.0 to 1.1; effect 

size, d=0.2) compared with children who rarely or never played with irrigation water.

Current maternal employment in the flower industry was associated with better developmental 

scores. Longer hours playing outdoors were associated with lower gross and fine motor and 

problem solving skills. Children who played with irrigation water scored lower on fine motor 

skills (8% decrease; 95% CI -9.31 to -0.53), problem-solving skills (7% decrease; -8.40 to -0.39), 

and VMI test scores (3% decrease; -12.00 to -1.08).

Current employment in the flower industry, longer hours spent outdoors playing, and contact 

with irrigation water were all associated with lower VMI scores; however, estimates are 

imprecise, as the VMI was administered only to a subset of the study, thus reducing the sample 

size.

Certain environmental risk factors for exposure to pesticides may affect child development, with 

contact with irrigation water of particular concern. However, the relationships between these risk 

factors and social characteristics are complex, as corporate agriculture may increase risk through 
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pesticide exposure and environmental contamination, while indirectly promoting healthy 

development by providing health care, relatively higher salaries, and daycare options.

2008 analysis of occupational exposure to pesticides during pregnancy and 

neurodevelopment of infants and toddlers (age 3-23 months)

For this third report, multiple linear regression models were constructed for three domains to 

assess effects on neurobehavioral development in 3-23 year old children of maternal 

occupational exposures during pregnancy, after controlling for potential confounders. Maternal 

exposure variables for problem-solving and personal-social skills were excluded as none was 

associated. Logistic regression models were constructed for the associations with prehension 

tests (pellet test, box test); generalized estimation equations (GEE) were used to account for 

dependence between tests. Proxy exposure measures included maternal employment during 

pregnancy, total months worked during pregnancy, total hours worked per week during 

pregnancy, primary job responsibility, child plays outdoors, and pesticides used on domestic 

crops and inside the home. 

On average, children whose mothers worked in the flower industry during pregnancy scored 8% 

lower on communication skills (-4.6 points, 95% CI -9.6 to 0.3) and 13% lower on the fine motor 

skills (- 8.0 points; -13 to -3) compared with children whose mothers did not work, after 

adjusting for key confounders. Inclusion of low birth weight in the regression models did not 

change the estimates of the effect of maternal work in the flower industry during pregnancy on 

neurobehavioral development (data was not shown).

Researchers observed similar results for use of pesticides in the workplace, including lower fine 

motor score (13% decrease in score, 95% CI -21% to -5%), lower communication (6% decrease 

in score, 95% CI -15% to 2%), and poorer visual acuity (OR 3.9; 0.94 –16) scores among 

children whose mothers reported pesticide use in the workplace during pregnancy compared with 

those whose mothers did not. Paid work, which included many flower workers and some nonflower workers, also yielded similar results, with lower fine motor scores (12% decrease in 

score, 95% CI -20% to -4%) and poorer visual acuity (OR 3.3; 0.80 –13 ) among those who 

worked outside the home during pregnancy compared with those who did not work outside the 

home.

Greater total weekly hours worked during pregnancy (>45 h/wk) and pesticide use at home 

during pregnancy were associated with better gross motor scores. All measures of exposure 
Page 54 of 171

except for pesticide use at home during pregnancy were negatively associated with fine motor 

scores.

For the large- pellet test, higher frequencies of poorer grasp scores (<3) were found for work in 

the flower industry during pregnancy, use of pesticides in the work place during pregnancy, more 

hours worked per week during pregnancy, and working 6 months or more of the pregnancy. For 

a greater number of children with poor visual acuity, maternal work in the flower industry during 

pregnancy was reported. The odds of succeeding in grasping the large pellet upon first contact 

were approximately half for those children whose mother worked in the flower industry during 

pregnancy compared with those whose mothers did not work (95% CI = 0.22– 0.93). The odds of 

poor visual acuity in infants whose mothers worked in the flower industry during their pregnancy 

were 4.7 times higher compared with those children whose mothers did not work in the flower 

industry during pregnancy (95% CI = 1.1–20). However, estimates are imprecise due to the 

limited size of the infant subsample.

This study, one of few conducted in a developing country setting, provides preliminary evidence 

of the potentially harmful effects of maternal occupation in the cut-flower industry during 

pregnancy (with its potential for in utero exposure to organophosphate and carbamate pesticides) 

on neurobehavioral development. Maternal occupation in the cut-flower industry during 

pregnancy may be associated with delayed neurobehavioral development of children aged 3–23 

months, particularly with fine motor skills and visual acuity. Possible hazards associated with 

working in the flower industry during pregnancy include pesticide exposure, exhaustion, and job 

stress.

Study Review

This was a well-conducted study, in three reports, of proxy pesticide (OP and carbamates) 

exposure on infants and young children 3 to 61 months of age living in two communities in 

Ecuador. The study population was based on a census sampling frame, and so selection bias is 

unlikely to have occurred. The exposed and unexposed groups had somewhat different education 

level, child care and stimulation in the home, etc., which could impact neurodevelopment 

performance. The researchers looked at correlated and uncorrelated (due to sibling pairs) 

estimates – and found similar results.
Page 55 of 171

The analytic methods, questionnaire, and analytic approach were appropriate in all three reports. 

Inferences to be garnered from the results are constrained by limitations of the cross-sectional 

study design (cannot assess temporality between exposure and outcome due to cross-sectional 

design), the exposure assessment (proxy measures), and the assessment of neurodevelopment 

outcomes (screening measures). None of the exposure measures in this study allow 

differentiation of the contribution of specific pesticides or pesticide groups (OP or carbamate) on 

results.

Unlike formal psychometric assessments such as the Bayley Scales of Infant Development, the 

Ages and Stages Questionnaire (ASQ) is a first-level comprehensive screening instrument. Some 

sections depend on mother's recall, e.g. social interactions, and it is not validated for Andean 

populations. 

While the use of a parent-report screening test has been shown to be an effective and valid way 

in which to assess a child’s developmental progress (Glascoe 2000), general screening tools such 

as the ASQ may not capture subtle delays that may be present. For most sections of the ASQ and 

especially for the fine and gross motor sections, children were directly tested by having them 

attempt various tasks such as crawling or walking and grasping blocks or toys. These activities 

were easier to test and score because they were observed directly. Other questions depended on 

mother’s recall of events at home. Specifically the social skills section of the ASQ involved 

questions relating to how the child reacts to other children or siblings or how the child plays with

his or her toys at home. Given this, it is thus even more striking that differences were observed. 

The retrospective, questionnaire-based assessment of some confounders (including birthweight 

with many non-response/missing values) is subject to imperfect recall. Errors in recall may not 

be independent of exposure status, i.e., the potential for recall bias exists. Potential for bias is 

away from the null; magnitude of potential bias is judged to be small.

However, given that a proxy exposure assessments was used in this study, the pesticides used 

may have included not only OPs, but also pyrethroids, fungicides, and growth regulators. Given 

the uncertainty about whether OP exposure actually occurred in this studies and whether 

observed outcomes are associated with OP exposure or with other pesticides, this study was

excluded from further analysis in the final synthesis of the OP epidemiological literature review 

(add citation). 
Page 56 of 171

2007 analysis of community of residence on neurobehavioral development (ages 3-61 

months)

In this first report, community of residence is the exposure measure, resulting in potential for 

exposure misclassification. Children were grouped into two age categories (3–23 months and 

24–61 months) to account for some of the variability in development associated with age. These 

age groups were evaluated separately in subsequent reports. The sample size is acceptable for the 

main analysis, but small for breaking into smaller age groups. The researchers stated that ideally 

ages would be grouped in 1-year categories or, with infants, in months. The effect of community 

of residence on gross motor skill development in younger children was greater for stunted 

children than for non-stunted children; however, because cell sizes were small, these results 

should be interpreted cautiously.

Other factors such as attendance in child care and stimulation in the home may modify the effect 

of community of residence on neurobehavioral development. Children who attended child care in 

high-exposure communities scored significantly better in their fine motor skills. It may be that 

these children are exposed to more stimulating activities at child care that aid in fine motor 

development, compared with children who do not attend child care or who are more isolated and 

live in the rural sectors.

A larger percentage of mothers reporting low birth weight (LBW) lived in the high-exposure 

communities. LBW may also be associated with work in or proximity to the cut-flower industry. 

However, because there was considerable nonresponse to questions about birth weight, this 

potential association could not be explored. Future studies in this region should consider 

including LBW as an additional outcome.

There was information on types of pesticides used in the cut-flower industry, but data on 

quantities and possible mixtures were not available. Additionally, domestic pesticide use is 

reportedly common in this region. The researchers did not obtain information on the type or 

quantity of pesticides used, either in the work environment or at home, therefore leading to 

another potential source of measurement error. Future investigations should incorporate the use 

of biomarkers and environmental sampling to supplement information gathered by questionnaire. 

2007B analysis of neurodevelopment in children with exposure to pesticides (age 24-61 

months)
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Given the correlations among several of the exposure variables, this analysis focused on those 

variables that describe distinct exposure domains (e.g., maternal employment, pesticide use 

within and around the home, and child play activities). Such measures are all proxy exposure 

measures, gathered via a questionnaire – thus there is potential for exposure misclassification.

Pesticide use on domestic crops and their proximity to children’s outdoor play area were either 

not associated with developmental delay or were associated with better developmental outcomes. 

The researchers considered several explanations for these seemingly anomalous findings. The 

risk of children living and playing in close proximity to the flower farms might be offset by the 

benefits of having a mother employed in the flower industry, which corresponds to a higher 

monthly household income, higher parental educations, and better access to health care and 

daycare. 

Alternatively, there may be unmeasured confounders. For example, domestic pesticide use may 

correlate with economic security; pesticides are an added expense for the family and only those 

who can afford the chemicals may be using them at home.

Current maternal employment in the flower industry and maternal employment in the flower 

industry during pregnancy were associated with better communication and problem-solving 

skills. Previous studies have found that take-home exposures via contaminated parental work 

clothing and equipment contribute to household pesticide residue contamination. In this 

population, however, it is uncommon for flower farm workers to take home their work clothes 

and equipment. Therefore, assessing take-home pathways for exposure via parental work 

clothing may be less relevant for this population, whereas other aspects of maternal employment 

in the flower industry (i.e., increased monthly income, more education, better access to daycare 

and health services) may benefit the child’s health and development.

The results highlight the importance of social relationships and opportunities that may interact 

with adverse exposures to affect neurobehavioral development. Neurobehavioral development is 

a complex and dynamic process that is affected by numerous factors, including parent-child 

interaction, household relationships, maternal health, physical environment, the child’s physical 

and mental health, and social organization. Associated social opportunities that increase access to 

daycare or health care for the child may counteract the effects of pesticide exposure. In 
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researching effects of pesticide exposure on child neurobehavioral development, recognition of 

other environmental factors within a larger ecosystem is critical

2008 analysis of occupational exposure to pesticides during pregnancy and 

neurodevelopment of infants and toddlers (age 3-23 months)

In this final report, the researchers examined maternal-prenatal exposure and neurodevelopment. 

The review comments above apply to this report. Primarily, measures of pesticide exposure are 

proxy, the sample size was limited, and the ASQ is a screening tool. Domestic pesticide use is 

widespread in this region of Ecuador, and they were not able to obtain information on the type or 

quantity of pesticides used on domestic crops. It is possible that mothers who did not work in the 

flower industry were exposed through domestic pesticide use.

The attenuation of the effect of maternal occupation during pregnancy on neurobehavioral 

development when any work outside the home was considered suggests that work in the flower 

industry (as opposed to other employment) may explain the observed developmental delays. 

However, there was limited power to examine the independent effects of work in the flower 

industry compared with other types of paid work; the majority of the women who reported 

working outside of the home in a paid job during pregnancy reported working in the cut-flower 

industry and the majority of working women reported pesticide use at their workplace.

Developmental differences observed between children whose mother did or did not work in the 

flower industry during pregnancy may be due to factors other than pesticides. Approximately 

half of the mothers who worked in the flower industry during pregnancy reported working more 

than 45 hours per week, and almost three-quarters of those mothers reported working 6 months 

or more of their pregnancy. Long work days, job stress, and difficult work responsibilities where 

women are on their feet most of the day could contribute to adverse pregnancy outcomes. 

Furthermore, flower laborers work in a greenhouse setting where heat and exhaustion may also 

play a role in maternal and fetal health.

Protective equipment and clothing aid in reducing the harmful effects of exposure to pesticides 

on health of agricultural laborers. In the present study, mothers were asked about current use of 

protective gear and clothing in the workplace. The majority of working mothers reported using 

protective gloves and rubber boots. However, only about half reported having access to masks 

and plastic aprons. In the flower industry, the majority of women work either in harvest or 

packaging, where masks may help reduce exposure to pesticides by inhalation. There are 
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limitations in the assessment of the impact of using protective gear, data specific to the 

pregnancy period was not available.

References cited

Glascoe FP. 2000. Evidence-based approach to developmental and behavioural surveillance 

using parents’ concerns. Child Care Health Devel 26:137–149.
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Study 10. Llop et al. (2013)

Prenatal and postnatal insecticide use and infant neuropsychological development in a 

multicenter birth cohort study. Sabrina Llop, Jordi Julvez, Ana Fernandez-Somoano, 

Loreto Santa Marina, Esther Vizcaino, Carmen Iñiguez, Nerea Lertxundi, Mireia Gascón, 

Marisa Rebagliato, Ferran Ballester. Environment International 59:175–182, 2013.

Study Summary

The INMA study is a multicenter birth cohort study initiated to assess the effect of 

environmental exposures and diet during pregnancy on fetal and child development set in four 

regions in Spain. Llop et al. reported on an assessment that leveraged indoor pesticide use during 

and after pregnancy obtained from the INME study cohort and psychomotor development in 

infants during the second year of life. 

The original study population (n=2,644) was enrolled between 2003 and 2008, during which 

time pregnant women were recruited during their first trimester of pregnancy. Of these, 2,506 

women were followed until delivery of their children, who were enrolled in the study at birth. 

Pesticide use during pregnancy and during the first year of the child’s life was queried using a 

questionnaire delivered by trained interviewers during the third trimester, and again when the 

child was between 11 and 30 months of age. This evaluation was conducted on a further subset 

of 1,980 mother-child pairs for whom complete data on prenatal and postnatal insecticide use 

information as well as neuropsychological test scores at age 11-23 months were available. 

Use of indoor pesticides and method of application (pesticide spray or use of a plug-in device) 

were used to define exposure status. Fifty-four percent of the participating women used indoor 

insecticides at home during pregnancy; 47% used them postnatally. Covariate information, 

including socioeconomic, environmental, and lifestyle behaviors was queried via questionnaires 

delivered during the first trimester, again during the third trimester, and again when the infant 

was between 11-30 months of age. Covariate data ascertained by the first two of these 

questionnaires included maternal age, education, place of birth, body mass index prior to 

pregnancy, smoking status during pregnancy, maternal employment status, parity, having a 

garden at home, and residential proximity to agriculture. Duration of breast feeding, primary 

child-care provider, participation in day care, number of siblings, and maternal employment 
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status, and smoking status were obtained during the follow-up interview conducted when the 

child was between 11 and 30 months of age.

Infant neuropsychological development was assessed at an average age of 14 months using the 

Bayley Scales of Infant Development (BSID-1). The BSID-1 consists of a mental scale and a 

psychomotor scale. All outcome testing was conducted by specially trained psychologists at the 

regional health center, in the presence of the mother. 

Multivariate linear regression models of mental and psychomotor scores were constructed to 

assess associations with the mothers’ self-reported prenatal and postnatal indoor pesticide use. 

The model for the mental BSID-1 score adjusted for BMI prior to pregnancy, maternal age, 

education level, country of birth, social class, sex, low birth weight, weeks of gestation, main 

child-care provider, and psychologist. The psychomotor score model included BMI prior to 

pregnancy, maternal age, country of birth, social class, sex, low birth weight, weeks of gestation, 

and number of siblings, small length for gestational age, nursery attendance, paternal smoking 

during the child’s first year of life, and psychologist. The investigators also evaluated 

interactions between indoor pesticide exposure and child’s gender, breast feeding status, blood 

lead and PCB levels, socioeconomic status, and pesticide application method.

Overall, Llop et al. observed a small increase in mental development score in association with 

self-reported prenatal use of indoor pesticides, and a small decrease in psychomotor development 

score of the children at age 11-30 months, neither of which was statistically significant. Prenatal 

use of pesticide sprays was associated with an average decrease in psychomotor score on the 

BSID-1 that was statistically significant. A smaller observed increase in the psychomotor score 

associated with use of plug-in devices was not statistically significant. They observed no 

consistent or statistically significant associations between postnatal indoor pesticide use and 

either mental or psychomotor development. Statistically significant effect modification was 

observed between prenatal pesticide exposure and child gender, with decrements observed in 

psychomotor scores in association with prenatal and postnatal pesticide exposure among girls, 

but not among boys, and also with social class, with decrements in neuropsychologic test scores 

associated with indoor prenatal and postnatal pesticide exposure noted among those in the lowest 

social class (manual laborers), but not in the other social class strata. 

Study Review
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The INMA study is one of the first in Europe to explore the relationships between prenatal and 

early-life exposure to indoor insecticides and infants’ neurodevelopment. This prospective birth 

cohort study was well conducted, although it relied on self-reported exposure assessment and did 

not include objective measurements of pesticide levels or biomarkers, and did not address 

exposures to specific pesticide types (e.g. organophosphates). 

The recruitment and retention of participants in this multi-center study was noteworthy; the study 

sample was large relative to most similar assessments to date, and almost 80% of the children 

enrolled in the cohort at birth were followed-up at an average age of 14 months (range: 11-23 

months). Nevertheless, a degree of selection bias due to loss to follow-up is possible if drop out 

or retention are associated with both pesticide exposure and neuropsychological status. 

Objective measurements of indoor pesticide exposures and biomarker assessments were not 

conducted in this study. The prospective, questionnaire-based pesticide exposure assessment was 

well conducted, though subject to recall errors and other sources of misclassification, all of 

which are likely to be non-differential with respective to neuropsychological development. 

Though residual confounding is possible, the assessment of covariates and adjustment for 

potential confounders was reasonable, with information on a large set of likely determinants of 

neuropsychological development collected via questionnaire both prospectively, and at the time 

of the neuropsychological testing. The authors also assessed several modifiers of the association 

between prenatal and postnatal indoor pesticide exposures and neuropsychological outcomes. 

The assessment of interaction between indoor pesticide use and other environmental toxicants 

(PCBs and lead) was particularly noteworthy, though interaction effect estimates for these 

toxicants were not statistically significant. It appears from the report that these interaction effects 

were considered a priori, rather than as post hoc exploratory analyses. In general, the statistical 

modeling was appropriate, though no adjustment was made for multiple comparisons. 

Llop et al. conclude that their study provides some evidence of adverse effects of indoor 

insecticide spray use during pregnancy on the psychomotor development of children at 2 years of 

age in the INMA cohort. While true, the associations were small and not consistent. Moreover, 

postnatal pesticide use was not associated with decrements in neuropsychological development 

in this study.
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Furthermore, given that a proxy exposure assessments was used in this study, the pesticides used 

may have included not only OPs, but also pyrethroids, fungicides, and growth regulators. Given 

the uncertainty about whether OP exposure actually occurred in this studies and whether 

observed outcomes are associated with OP exposure or with other pesticides, this study was

excluded from further analysis in the final synthesis of the OP epidemiological literature review 

(add citation). 
Page 64 of 171

Study 11. Oulhote et al. (2013)

Urinary Metabolites of Organophosphate and Pyrethroid Pesticides and Behavioral 

Problems in Canadian Children. Youssef Oulhote and Maryse F. Bouchard; 

Environmental Health Perspectives. 121:1378-1384 (2013) 

Study Summary 

In this report, Oulhote et al. evaluate the association between the recent exposure to 

organophosphate and pyrethroid pesticides, indicated by urinary metabolites, and parentally 

reported behavioral problems in children in Canadian children aged 6-11 years.

For this study, data from the Canadian Health Measures Survey (CHMS; cycle 1, 2007–2009) 

was used. For cycle 1 of CHMS, data were collected from approximately 5,600 Canadians 6–79 

years of age, including 1,081 children 6–11 years of age, in 15 sites spread across Canada. 

Children were predominantly white (75%) and had parents with relatively high education levels 

(80% with at least a high school degree). The percentage of parents reporting using chemicals in 

the month before the interview for controlling roaches, ants, termites, or other insects indoors 

was 3.8%, and 4.3% reported using chemicals to treat head lice on family members or fleas and 

ticks on pets. In addition, 7.3% reported that their lawn or yard, or the surrounding fields, woods, 

or orchards, had been treated with chemicals to kill insects or weeds or control plant diseases. 

Overall, 14% of the children lived in a household where pesticides had been used for any of 

those purposes in the previous month. Out of the 1,081 children from cycle 1, children who were 

missing data on some of the covariates (sex, age, race/ethnicity, income, parental education, 

blood lead levels, maternal smoking during pregnancy, and others) were excluded from the 

study. The sample size for this study was 779 children. 

Each parent was asked three questions about pesticide use in the preceding month, specifically, 

chemicals used indoors to control roaches, ants, termites, or other insects; chemicals used to 

control head lice on family members or fleas on pets; and chemicals used on the lawn, yard, or 

the surrounding fields, woods, or orchards to kill insects or weeds, or to control plant diseases. A 

spot urine sample was collected from each child within 2 weeks of survey questionnaire 

completion and was analyzed at the Institut National de Santé Publique du Québec. In addition, 

urinary creatinine concentration was measured to account for urine dilution. Six urinary dialkyl 

phosphate (DAP) metabolites that result from the degradation of different organophosphates 
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were measured in urine, and concentrations were summed to provide an indicator of total 

exposure. The urinary DAP metabolites measured were three dimethyl alkylphosphate (DMAP) 

molecules [dimethylphosphate (DMP), dimethylthiophosphate (DMTP), 

dimethyldithiophosphate (DMDTP)] and three diethyl alkylphosphate (DEAP) molecules 

[diethylphosphate (DEP), diethylthiophosphate (DETP), diethyldithiophosphate (DEDTP)].

Behavioral problems were assessed using the parent version of the Strengths and Difficulties 

Questionnaire (SDQ). The SDQ is an internationally used, acceptable to parents, and validated 

screening questionnaire designed to assess the mental and behavioral difficulties and strengths of 

3- to 16-year-old children.

Blood lead levels (as a continuous value) and maternal smoking during pregnancy (parent report 

of smoking regularly during any stage of pregnancy) were used as a priori in models since they 

are considered important risk factors for behavioral problems in children. In addition, variables 

such as sex, age, race/ethnicity, family income, parental education, birth weight, maternal age at 

child’s birth, current exposure to environmental tobacco smoke (parent report of daily tobacco 

smoking inside the home), child’s body mass index (BMI; as a continuous value), and fasting 

status (fasting duration at urine collection > 10 hr/≤ 10 hr) were examined as potential 

confounders. Each variable was examined in a bivariate analysis for its association with high 

SDQ total difficulties score, and with concentrations of urinary pesticides metabolites 

(logarithmically transformed). Variables that predicted both the total difficulties score and the 

exposure with p < 0.2 (chi-square test, one-way analysis of variance, or Spearman correlation 

depending on whether variables were categorical or continuous) were retained as model 

covariates. In addition, urinary creatinine concentration was included as a covariate in models to 

account for urine dilution. This approach was chosen rather than standardizing urinary 

concentrations for creatinine to reduce potential bias that may be introduced by age, 

race/ethnicity, and sex-related variation in creatinine excretion.

Sensitivity analysis was also performed in three different ways; adjusting for the ratio of 

pesticide metabolite to creatinine level, adjusting for blood lead levels, and adjusting for 

variables used to define the weights (i.e. age, sex, and ethnicity).

At least one urinary metabolite for organophosphates was detected in 91% of children, and for 

pyrethroids in 97% of children. Organophosphate metabolites were not significantly associated 

with high SDQ scores. The pyrethroid metabolite cis-DCCA [3-(2,2-dichlorovinyl)-2,2-
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dimethylycyclopropane carboxylic acid] was significantly associated with high scores for total 

difficulties on the SDQ (OR for a 10-fold increase = 2.0; 95% CI: 1.1, 3.6), and there was a nonsignificant association with trans-DCCA (OR = 1.6; 95% CI: 0.9, 3.0).

In contrast with previous studies, this study did not find any association between exposure to 

organophosphate pesticides and behavioral scores in children. However, some pyrethroid urinary 

metabolites were associated with a high level of parent-reported behavioral problems. According 

to the author, this is the first study to suggest that exposure to certain pyrethroids might be 

associated with behavioral problems in children.

Study Review

This cross sectional study of recent OP pesticide exposure in Canadian children 6-11 years of 

age and behavioral problems has some strengths and few weaknesses. The study population was 

not mixed. There is a reference to analytic methods but is not described in the study. The 

statistical analysis was well specified and appropriate. The author’s approach to evaluating and 

adjusting for covariates were prudent. However, inferences from the results of this investigation 

are constrained by the limitations in study design and exposure assessment methodology as it is 

based on the assessment of single urine sample.

Characteristics of the study participants (n=779) is not provided in the study but according to the 

author, there was no significant difference (p > 0.05) between any of the characteristics for the 

whole group (n=1030) and the subset (n=779) included in the analysis. The study population was 

not mixed (79% white vs. 21% non-white) and only 14% (n=151) of the children were exposed 

to pesticides in the previous month. 

The exposure assessment method for OP pesticides and pyrethroids is not described in the article 

and refers to Institut national de santé publique du Québec (INSPQ) 2009a, 2009b] for laboratory 

methods. Exposure was assessed by measuring the metabolites in a spot urine sample. The use of 

a single urine sample to estimate exposure is likely to have resulted in an attenuation of 

associations, relative to those that would have been observed had the investigators used a timeintegrated marker of OP pesticide exposure. Also, the short elimination half-life, episodic nature 

of exposures to OP pesticides, and individual variation in metabolism, may contribute to 

variability in exposure measurement. 
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The outcome assessment method seems to be appropriate because according to the author, the 

SDQ is validated and accepted by parents. However, it should be noted that SDQ is a screening 

questionnaire only. 

On the whole, the investigators handling of confounding resulted was reasonable and aspects of 

the investigator’s approach to evaluating and adjusting for confounding were prudent. The 

statistical analysis appears to be appropriate. Sensitivity analysis was also performed and seems 

to be presented in the supplemental materials, but the references are not provided in the article. 

This study showed that there was no association between the recent exposure to organophosphate 

pesticides and behavioral scores in children which is in contrast with other similar studies. 

However, this study suggested that exposure to certain pyrethroids, at levels common in 

Canadian children, may be associated with behavioral problems. According to the author, the use 

of pyrethroids is increasing, but to date there is little information on potential health effects in 

children. The authors rightly conclude their paper by stating that longitudinal studies with a 

larger study population should be conducted to verify these findings.
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Study 12. Petit et al. (2010)

Impact on fetal growth of prenatal exposure to pesticides due to agricultural activities: a 

prospective cohort study in Brittany, France. Claire Petit, Cécile Chevrier, Gaël Durand, 

Christine Monfort, Florence Rouget, Ronan Garlantezec, Sylvaine Cordier. Environmental 

Health 9:71-83, 2010.

Study Summary

PELAGIE is a prospective birth cohort study designed to examine the role of environmental 

pollutants on prenatal and child developments in Brittany, France. Using this cohort, Petit et al. 

evaluated the relationship between level of urbanization, and the proportion of an area devoted to 

agricultural activity as indicators of prenatal exposures to pesticides, and three indicators of fetal 

growth: birth weight, head circumference, and fetal growth restriction. 

Enrollment of pregnant women into PELAGIE took place from the spring of 2002 through the 

winter of 2006 in three Breton districts. Women were recruited by their gynecologists, 

ultrasonographers, midwives, and obstetricians during routine prenatal care visits prior to 19 

weeks gestation. During these visits, women were informed of the study objectives, invited to 

participate, and consented, then provided a questionnaire which they were asked to complete at 

home and return. The authors estimated the participation proportion to be approximately 80%; 

3,592 women agreed to participate. They subsequently excluded 171 women who returned the 

questionnaire after 19 weeks of pregnancy and 22 women for whom birth outcomes were 

unavailable. The investigators restricted the study sample to singleton live births among women 

who lived within the three-district catchment area. They also excluded 42 women who were 

farmers, resulting in a study sample size of 3,159 women.

The authors used population size to characterize each mother’s municipality as either rural or 

urban using a cut point < 20,000 inhabitants to define areas as rural. Data on agricultural activity 

in the three study districts were obtained from the 2000 national general census collected and 

maintained by the statistics department of the Ministry of Agriculture. These Census data, 

originally provided by individual farmers, were aggregated at the level of municipality, 

providing an estimate of the percentage of the total area of each municipality used for 

agricultural activities, specific to crop, including corn, wheat, colza, peas, potatoes, fresh 

vegetables, strawberries and melons. These municipal-level data on agricultural usage were 
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matched to each of the participating mother’s municipalities of residence during early pregnancy. 

The authors characterized the percentage of municipal area used for agricultural into low, 

medium, and high categories using tertiles (0-63%, 63-74%, and >74%). Municipalities were 

similarly characterized by tertile with respect to the percentage of area used to grow corn (0-

13%, 13-20%, >20%) and wheat (0-9%, 9-15%, >15%). Because of the small percentage of 

municipal areas devoted to colza, peas, potatoes, and other vegetables, municipalities were 

characterized by a dichotomous indicator for presence/absence of each of these crops.

Indicators of fetal growth (weight, length, and head circumference) were obtained from hospital 

records. Live born singleton children of the PELAGIE study without major malformations were 

classified with fetal growth restriction (FGR) if their birth weight was below the 5th percentile of 

the distribution of expected birth weight. Small head circumference was defined as having a head 

circumference below the 5th percentile of the head circumference distribution at birth for a given 

gestational age and sex, using recent French reference curves.

Multivariate linear and logistic regression models were built to evaluate associations between 

indicators of fetal development and level of urbanization. Using data only from the subset of 

women living in rural areas, the authors similarly evaluated the relationship between fetal 

development and agricultural activities in the municipality of residence. The authors considered 

the following as potential confounders: year of inclusion, district of residence at inclusion, 

maternal age, maternal educational, maternal alcohol consumption and tobacco smoking status at 

inclusion, marital status, season in early pregnancy, high blood pressure during pregnancy, and 

maternal diabetes (gestational or preexisting). Maternal pre-pregnancy body mass index, 

maternal height, parity, child’s sex, quadratic gestational age were additionally considered as 

covariates for weight and head circumference at birth. For the small head circumference 

outcomes, the authors also considered adjustment by pre-pregnancy body mass index, maternal 

height, and parity, and cesarean delivery. Additional analyses adjusting for shellfish and fish 

intake were conducted, but not presented in the author’s report. Model building and covariate 

selection was conducted using backward selection, using a p-value for exclusion of 0.2. 

The authors estimated associations between many exposure metrics and several birth outcomes, 

and the findings of this study where largely negative (i.e. no observed association). Statistically 

significant associations were observed for head circumference and level of urbanization, with 

rural-dwelling mothers giving birth to children with statistically significantly smaller head 

circumference (0.1 cm, on average), and having 1.8x greater odds of having small head 
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circumference. Presence of pea crops in the municipality where the mother lived during early 

pregnancy was also significantly associated with smaller head circumference and a statistically 

significant 2.2x increase in the odds of having small head circumference.

Study Review

This was a large, well-conducted, but ultimately limited study that sought to evaluate the effects 

of pesticide exposure on fetal growth using a community-level, proxy indicator of pesticide 

exposure and birth outcome data obtained as part of a prospective birth cohort study conducted 

in a population of healthy mother-child pairs living in Brittany, France. The analytic methods, 

questionnaire, and statistical analysis were appropriate. However, inferences to be garnered from 

the results of this investigation are constrained by substantial limitations related primarily to the 

assessment of (pesticide) exposure. 

The authors employed a reasonable set of inclusion/exclusion criteria. Interestingly, the authors 

excluded farmers from the study, i.e. those with perhaps the greatest opportunity for exposure to 

agricultural pesticides. Although they did not justify this decision, presumably this was done to 

avoid the problem of highly exposed farm women living in areas with a low percentage of area 

used for agriculture; percent of area devoted to agricultural activity is almost certainly not a good 

proxy for pesticide exposure among farmers. The estimated proportion of women invited to 

participate was high (approximately 80%), and indication that the study results, if valid, are 

generalizable to the target population of pregnant French women. Only 22 of 3,421 women 

(0.64%) were lost to follow-up, indicating that selection bias in this prospective cohort is 

unlikely to have biased the study findings. 

The investigators used a questionnaire to prospectively collect demographic and other covariate 

information from participants. Covariate selection and model building proceeded appropriately; 

strong residual confounding by unmeasured or poorly measured confounders is unlikely in this 

study. Multiple comparisons were conducted for this evaluation, and the authors did not adjust 

for multiple testing. Given the number of associations estimated in this study, one should expect 

there to be a number of “false positive” findings due to chance alone. 

In summarizing the motivation for their investigation, the authors noted that, in 2004, France led 

all of Europe in pesticide sales (~76,000 tons of active ingredients sold), with 90% of these 

pesticides used in agricultural activities (Pingault et al., 2009). Moreover, 70% of the land area in 
Page 71 of 171

Brittany is devoted to agricultural activities. In short, the potential exists for exposure to 

agricultural pesticides. Nonetheless, the study design relies on the untested assumption that the 

percentage of a municipality’s area dedicated to agricultural activities is predictive of a fetus’ 

individual-level pesticide exposures if its mother lived in that municipality. 

The potential for a large degree of non-differential misclassification of pesticide exposure is a 

potential explanation for the largely null findings of this study. The assessment of residential 

proximity to crops is an aggregate exposure measurement on the scale of the municipality, 

whereas actual exposure occurs (or does not occur) on the level of the individual mother-child 

pair. A great deal of individual-level pesticide exposure is possible among pregnant women 

living in areas with little or no agricultural activity. Similarly, it is equally possible that very little 

pesticide exposure is sustained by women living in areas with a great deal of agricultural activity. 

This potential misclassification was likely the motivation for the investigators’ decision to 

exclude farmers from the study sample, despite farmers having perhaps the greatest opportunity 

for exposure to agricultural pesticides. 

There were, in fact, additional sources of potential exposure misclassification, including the twoto-six year interlude between the conduct of the agricultural census in the year 2000 and the 

enrollment of pregnant women as participants in PELAGIE in the years 2002-2006.

The investigators did not report having assessed effect modification by any factors. 

The fetal growth indicators (outcomes) were obtained from medical records and are unlikely to 

be misclassified. 

The authors conclude their report by stating that the study findings suggest that some adverse 

effects on cranial growth during fetal development are caused by prenatal exposure to 

agricultural activities in the municipality of residence, especially pea crops. They go on to state 

that their findings may be reason for concern, as the cranial growth may be predictive of future 

intelligence and cognitive ability. Although possible, an equally likely explanation for the few 

non-null studies is that they were false-positive associations expected to occur when conducting 

multiple comparisons as the authors have done. Although unstated by the authors, the primarily 

null findings may be similarly suggestive of there being no association between pesticide 

exposure and other indicators of fetal growth evaluated in the study. In fact, however, attenuation 
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of observed associations due to non-differential misclassification is an equally plausible 

explanation. 

Furthermore, given that a proxy exposure assessments was used in this study, the pesticides used 

may have included not only OPs, but also pyrethroids, fungicides, and growth regulators. Given 

the uncertainty about whether OP exposure actually occurred in this studies and whether 

observed outcomes are associated with OP exposure or with other pesticides, this study was

excluded from further analysis in the final synthesis of the OP epidemiological literature review 

(add citation). 

References cited

Pingault N, Pleyber E, Champeaux C, Guichard L, Omon B: Produits phytosanitaires et 

protection intégrée des cultures: l’indicateur de fréquence de traitement. Notes et études 

socio-économiques 2009, 32:61-94.
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Study 13. Ruckart et al. (2004)

Long-Term Neurobehavioral Health Effects of Methyl Parathion Exposure in Children in 

Mississippi and Ohio. Environmental Health Perspectives. 2004; 112(1):46-51.

Study Summary 

In this report, Ruckart et al. examine the association between methyl parathion (MP) exposure 

and neurobehavioral development in children exposed at age 6 years or younger in Mississippi 

(MS) and Ohio (OH) when their homes were sprayed with MP using a retrospective cohort study 

design with a single assessment of urinary para-nitrophenol (PNP) and various assessments of 

neurobehavioral development - cognitive, motor, sensory, and affect domains, child and family 

dysfunction, child's personality, communication, and daily living skills.

Potential participants were identified using data files provided to ATSDR by the MS and OH 

state health departments. These states were selected because environmental data collection and 

urine testing were available. Testing was done in OH in 1994 and in MS from late 1996 through 

mid-1997. Children residing in MS and OH who were 6 years or younger when their homes were 

illegally sprayed with MP were eligible for inclusion in the study. In one OH county, the 

spraying occurred in a multifamily, subsidized housing facility that was last sprayed in 1994. In 

MS, the spraying was more widespread and included 29 counties with residences sprayed as 

recently as late 1996. 

Results of environmental wipe samples for MP taken from residences (household MP) and urine 

testing for creatinine-adjusted PNP, a metabolite of MP, were provided by the state health 

departments. Household MP samples were analyzed by laboratories approved by the U.S. EPA 

employing the same analytical methods, and PNP samples were analyzed by the CDC. Exposure 

status was defined on the basis of the test results. Both household MP and urinary PNP levels 

were used to define exposure status. In MS, exposure was defined as at least one household MP 

sample ≥150 μg/100 cm2 or urinary PNP ≥100 ppb for at least one person in the household. For 

OH, exposure was defined as household MP ≥132.9 μg/100 cm2 or urinary PNP ≥100 ppb for at 

least one person in the household. To include enough exposed children in OH, it was necessary 

to set a lower cutoff value for household MP. Exposure was dichotomized into two groups: 

Highly exposed: household MP >1000 ug/100c cm2 or urinary PNP >300 ppb, and -Moderately 

exposed: all other exposed children.
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Comparison groups of unexposed children residing in the same communities as the exposed 

children were also identified. Local comparison groups were chosen to minimize confounding 

from sociocultural factors (e.g., regional variations in education, IQ, race, and cultural factors). 

In MS, unexposed children were selected through state records from houses that tested <25 

μg/100 cm2 for household MP; no urine testing was done for children at these levels of MP. In 

OH, unexposed children were selected in two ways: 1) houses that tested <35 μg/100 cm2 for 

household MP and where no one in the household had a urinary PNP level >25 ppb (the cutoff 

value for household MP in OH was increased to include enough unexposed children), and 2) a 

special census was done in the sprayed complex after it was remediated and in a nearby housing 

complex that was not sprayed, to identify additional unexposed children. 

A total of 365 children in MS (147 exposed and 218 unexposed) and 287children in OH (104 

exposed and 183 unexposed) were enrolled (range 1.9-12.5 years old at testing). The researchers 

attempted to enroll two unexposed children for every exposed child to ensure an adequate 

number of unexposed children for analysis in subsequent study years. All children who 

participated in year 1 (summer 1999) were invited to be retested in year 2 (summer 2000) to see 

whether any differences in neurobehavioral testing between exposed and unexposed children 

persisted or disappeared

Trained interviewers administered a CAPI questionnaire to obtain information on confounders –

parent’s and child’s medical history, pregnancy history, parental occupational histories, 

workplace chemical use, and child’s residential history. Neurobehavioral development was 

assessed using the following:

Performance-based tests (scored as expected, equivocal, below expected, undetermined):

• Pediatric Environmental Neurobehavioral Test Battery (PENTB): cognitive, motor, 

sensory, and affect domains (Zeitz et al., 2002) 

o Developmental Test of Visual-Motor Integration (VMI) measures the integration 

of visual and motor skills.

o Kaufman Brief Intelligence test (K-BIT) test (K-BIT) measures general 

intelligence, verbal ability, and nonverbal reasoning.

o Purdue Pegboard tests visual-motor coordination, manual dexterity, and motor 

speed.
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o Story Memory and Story Memory-Delay from Wide Range Assessment of 

Memory and Learning tests verbal memory; immediate and delayed recall of 

both specific and general items. 

o Trail-Making test, Part A and Part B assesses multistep processing involving 

more than one cognitive function area (visual perception, motor speed, sequential 

skills, and symbol recognition), administered to children 9 years and older.

o Verbal Cancellation test The Verbal Cancellation test measures sustained 

selective attention.

Informant-based tests:

• Parenting Stress Index (PSI) - Child domain, parent domain, total stress scores

• Personality Inventory for Children (PIC) - child’s personality

• Vineland Adaptive Behavior Scales (VABS) - Communication, daily living skills

To assess the relationship between MP exposure and performance on neurodevelopment tests, 

continuous test scores were analyzed using linear regression, and dichotomized test scores (worst 

10% for a test compared with other 90%) were analyzed using logistic regression. Raw 

(nonstandardized) test scores were adjusted for age. Unadjusted odds ratios (ORs) and 90% CIs 

were computed.

Performance-based tests. For overall PENTB outcome, a similar number of exposed and 

unexposed children were classified as below expected, while more exposed children were 

classified as expected, and fewer exposed children were classified as undetermined. When 

comparing overall PENTB score for year 1 vs year 2, 33% of exposed children classified as 

below expected did not improve in year 2 compared with 60% of unexposed children. These 

results indicated that MP exposure was not associated with persistent deficits in year 2 among 

children who performed lower than expected in year 1. This suggests that if there are 

neurobehavioral effects from subacute exposure to low levels of MP, they may be transient in 

children who were 6 years or younger when they were exposed. A previous study found major 

impairment of memory and concentration in workers who had organophosphates for several 

years, but the impairments disappeared 12 months after exposure ceased (ATSDR 1999).

No effects were seen for the K-BIT, VMI, or Trail-Making tests (ATSDR 2003). For the Verbal 

Cancellation test, an effect was seen for the mean difference only in OH (highly exposed ordered 

form adjusted β = –6.02, 90% CI, –11.27 to –0.78; highly exposed nonordered form adjusted β = 
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–8.09, 90% CI, –13.41 to –2.78), and there was a trend with exposure. When test scores were 

dichotomized, an effect was seen only in MS (ordered form OR = 2.27, 90% CI, 0.80–6.45; 

nonordered form OR = 10.29, 90% CI, 2.23–47.41). For the Story Memory tests, the only effect 

was seen for dichotomized Story Memory Difference scores (OR = 1.27, 90% CI, 0.61–2.67), 

and the effect was strongest in OH (OR = 1.71, 90% CI, 0.50–3.37). For the Purdue Pegboard 

test, the findings were not consistent across subtests or across sites. In OH, the only effect was 

seen for the nonpreferred hand (adjusted β = –1.82, 90% CI, –10.08 to 6.44; OR = 1.20, 90% CI, 

0.42–3.49). In MS, the only effect was seen for the dichotomized preferred hand score (OR = 

1.39, 90% CI, 0.66–2.94).

Informant-based tests. For informant-based tests, exposed children performed worse than 

unexposed children in year 1. The PSI was administered only in MS because no children among 

those tested in the study in OH were younger than 4 years at the time of testing. Effects were 

seen for mean difference scores on all domains. Effects were also seen when child domain and 

total stress scores were dichotomized (child domain OR = 1.90, 90% CI, 0.24–15.24; total stress 

OR = 4.22, 90% CI, 0.62–28.71). However, an OR could not be computed for the Parent domain 

because there were no unexposed children who scored in the worst 10% for this subtest. For the 

VABS, an effect was seen for the motor skills domain (highly exposed β = –9.05, 90% CI, –

15.50 to 2.60; OR = 3.10, 90% CI, 0.90–10.63), and there was a trend with exposure for the 

mean difference scores. In MS, an effect was seen for the mean difference and dichotomized test 

scores for all other subtests. For the mean difference, a trend with exposure was seen for all 

subtests except the communications domain; for dichotomized test scores, a trend with exposure 

was seen for the daily living skills and social skills domains. For the PIC, an effect was seen for 

the mean difference score for PIC factor 1, undisciplined/poor self-control (β = 2.73, 90% CI, –

1.16 to 6.62), and the effect was strongest among the highly exposed children in MS. In MS, an 

effect was seen among highly exposed children for the dichotomized test scores for PIC factor 4, 

cognitive development (OR = 1.79, 90% CI, 0.52–6.25). In OH, an effect was seen for PIC factor 

1 when scores were dichotomized and for PIC factor 3, internalization/somatic symptoms. A 

trend was present for the mean difference scores for PIC factor 3.

Overall, exposure to MP was not associated with poorer performance on most neurobehavioral 

tests, and effects were not consistently seen in both sites. Effects were seen for tasks that involve 

short-term memory and attention, and parents of exposed children reported that their children 

had more behavioral and motor skills problems than did parents of unexposed children. The 
Page 77 of 171

reported behavioral problems included children misbehaving, acting on impulse, having 

problems with anger, being sad or shy, and having problems relating to other children. 

Study Review

This was a moderate quality study. Sample size was sufficient, and having two different sites for 

comparison improved generalizability. Basic demographic information for participating and nonparticipating children was available (both groups were similar with respect to age and gender, 

participation rate in year 1 was 76% for exposed children and 57% for unexposed children), thus 

selection bias is deemed to be small. 

The use of two different types of exposure measures - environmental wipe samples for MP and 

urine testing for PNP - to quantify the children’s individual exposure to MP is generally 

considered to be a strength of the study. However, the percentage of participants in each 

eligibility category was not provided - urinary PNP levels are considered the better measure, as it 

is less certain whether those who lived in homes with elevated MP levels were actually exposed. 

It is also unclear if samples were collected, handled, and analyzed in the same manner in both 

sites (states). Though not explicitly stated that urine was sampled only once, the use of a single 

urine sample to estimate the participant’s OP pesticide exposure is likely to have resulted in an 

attenuation of associations, relative to those that would have been observed had the investigators 

used a time-integrated marker of OP pesticide exposure. PNP is a metabolite for methyl 

parathion, malathion, and other compounds, so there could be some misclassification if 

participants were exposed to the other compounds; however this is considered to be a less 

important concern in the study. 

The statistical methods used seem appropriate, and as mentioned above the sample size is 

adequate. This study obtained information on and included appropriate potential covariates in the 

models - demographic and personal characteristics such as parents’ and child’s medical history, 

mother’s pregnancy history with regard to the index child, parental occupational histories, 

workplace chemical use, and child’s residential history. Use of different exposure cut-off levels 

to get enough children in OH in exposed and unexposed groups seems questionable, but is not 

considered a major concern.

The test battery (PENTB) used was reportedly developed by a group of experts to examine the 

neurobehavioral effects of environmental exposures specifically in children. Extensive training 
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of PENTB examiners who were blinded to the exposure status of the child and a thorough review 

of the collected data also contributed to the strengths of this study.

The authors note limitations of the study include the fact that the length of time between the last 

MP spraying, sample collection, and neurobehavioral testing was not known and was different in 

the two study sites. The frequency and duration of spraying were also unknown. In this study, the 

time between the last spraying of the pesticide and the testing was at least 2.5 years in MS and at 

least 4.5 years in OH. Inconsistencies in the results between MS and OH may be due to the 

differences in length of time between the spraying and testing in the two sites (the last spraying 

in MS was in late 1996 and the last spraying in OH was in 1994; children in both sites were 

initially tested in 1999). Additionally, children in OH were older than children in MS at the time 

of testing, and the older children may have outgrown any neurobehavioral effects that were 

caused by MP. Also, the exposure assessment of MP in household samples and in urine for each 

child represents only a snapshot in time and may not reflect the total exposure received by the 

child. There were also inconsistencies in results within subtests of some tests. Additionally, there 

was a lack of trend with exposure for most tests. 

Results for a particular test could be lacking because the neurobehavioral effects are transient 

and were no longer measurable when the children were tested. It might also be possible that the 

PENTB was not the appropriate test battery to examine neurobehavioral effects from exposure to 

MP. For example, even with a large sample size, the standard errors for several tests were quite 

large, making it difficult to find subtle effects. 

The findings suggest that MP might cause subtle changes to short-term memory and attention 

and might contribute to problems with motor skills and some behaviors. However, the results of 

the study are not conclusive because these effects were not seen consistently in both sites. 

Although some domains essential to neurobehavioral development appear to have been affected 

by exposure to MP, the results are largely inconsistent. Furthermore, it is noted that samples 

were collected in locations from OH and MS where illegal spraying of methyl parathion is 

known to have occurred during the 1994-1996 time period. Based on the OP Cumulative Risk 

Assessment (USEPA, 2006), methyl parathion is known to be among the more potent OPs. It is 

unknown whether study participants were exposed to MP levels that would have induced 

cholinergic effects. Therefore, given the uncertainty around this illegal use combined with the 

high potency for cholinergic toxicity, the agency is not emphasizing this study further in the final 

synthesis of the OP epidemiological literature review (add citation). 
Page 79 of 171

References cited

ATSDR. 1999. Toxicological Profile for Methyl Parathion (update). Atlanta, GA: Agency for 

Toxic Substances and Disease Registry.

Zeitz P, Kakolewski K, Imtiaz R, Kaye W. 2002. Methods of assessing neurobehavioral 

development in children exposed to methyl parathion in Mississippi and Ohio. Environ 

Health Perspect 110(suppl 6):1079–1083.
Page 80 of 171

Study 14. Suarez-Lopez et al. (2012, 2013a, 2013)

• 2012 - Lower acetylcholinesterase activity among children living with flower plantation 

workers. Environmental Research. 2012; 114:53–59.

• 2013a - Acetylcholinesterase Activity, Cohabitation with Floricultural Workers, and 

Blood Pressure in Ecuadorian Children. Environmental Health Perspectives. 2013; 

121(5): 619-624.

• 2013 - Acetylcholinesterase Activity and Neurodevelopment in Boys and Girls. 

Pediatrics. 2013; 132(6):e1649-1658.

Study Summary

Suarez-Lopez et al. looked at participants of the Secondary Exposure to Pesticides among 

Infants, Children and Adolescents (ESPINA: Estudio de la Exposición Secundaria a Plaguicidas 

en Infantes, Ninos y Adolescentes) residing in Pedro Moncayo County, Pichincha, Ecuador, 

where there is an active fresh-cut flower industry, with the overarching aim to evaluate crosssectionally the effects of secondary post-natal exposure to pesticides on child development. The 

aim of the first report (Suarez-Lopez et al., 2012) was to evaluate the association between flower 

worker cohabitation and children’s AChE activity. The second report (Suarez-Lopez et al., 

2013a) examined whether lower AChE activity from secondary pesticide exposure and 

cohabitation with a flower plantation worker was associated with changes in blood pressure and 

heart rate among children. The third report in the series (Suarez-Lopez et al., 2013) looked at 

whether lower AChE activity is associated with lower neurodevelopment (particularly attention, 

inhibitory control, and memory) among children living in floricultural communities, with 

stronger associations among boys.

In 2008, Suarez et al. contacted 419 of 922 children who had participated in the 2004 Survey of 

Access and Demand of Health Services in Pedro Moncayo County, which had obtained socioeconomic status, demographic, occupational and health information (of all members in the 

household) of 18,187 residents (71% of Pedro Moncayo County’s population) and collected both 

height (or length) and weight of children younger than 5 years (27% of Pedro Moncayo County’s 

children younger than 5). Most losses were due to invalid or unlocatable addresses or because 

participants had moved to a different house. To supplement recruitment, new volunteers (child 
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and parent) living in Pedro Moncayo County were also recruited through community 

announcements and word of mouth. A total of 124 new volunteers registered to participate. 

Children were eligible if they met the following criteria: exposed group: (1) cohabitation with a 

flower worker for at least one year and (2) unexposed group: never cohabited with an 

agricultural worker, never inhabited a house where agricultural pesticides were stored and having 

no previous direct contact with pesticides. Multiple children per household were allowed to 

participate. Parents of 343 children agreed to participate: 259 child participants surveyed in 2004 

and 84 new volunteers. Twenty seven participants (47% of whom were cohabitants with a flower 

worker) did not show up for the examination appointments, 1 child did not assent to be 

examined, and two children refused their examination. In 2008, a total of 313 children 4–9 years 

of age were examined; interview information was obtained from 451 adults who cohabited with 

the examined children (at least one parent of each child). Of these children, 277 had all 

covariates of interest and were included in the 2012 report of cohabitation and AChE activity 

(57% cohabited with a flower plantation worker); 271 had all information for the 2013a report of 

cohabitation and heart rate and blood pressure; and 307 had all information for the 2013 report of 

AChE activity and neurodevelopment in boys and girls. 

In-person home interviews of children’s parents and other adults were used to obtain information 

on socioeconomic status, demographics, health, and direct and indirect pesticide exposures of 

household members (e.g., pesticide usage at home, child pesticide exposure history and duration 

of cohabitation with a flower worker, information regarding practices associated with secondary 

occupational exposures to pesticides). The distance from each child’s residence to the nearest 

flower plantation was calculated using ArcGIS 9.3. 

Examinations were conducted in seven schools centrally located to participants’ residences in all 

five parishes in Pedro Moncayo County. Examiners were unaware of exposure status of the 

participants. 

• Children’s height was measured using a height board, following recommendations 

by the World Health Organization (WHO 2008), and weight (standing) was 

measured using a digital scale. Height-for-age z-scores were calculated using the 

WHO growth standards. No examiner training was described.

• AChE activity was measured from single finger-stick blood samples using EQM 

AChE Erythrocyte Cholinesterase Assay Kit 470). Blood samples were analyzed 

immediately at ambient temperatures between 15.6 and 28.4 1C, which are within 
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the recommended range. Mean AChE activity was 3.14 U/ml, SD 0.49. No data 

examiner training was described.

• Hemoglobin was measured from single finger-stick blood samples. No examiner 

training was described.

• Resting heart rate was measured by a 30 sec auscultation, before the blood pressure 

measurement. No examiner training was described; however, AHA procedures were 

cited.

• Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured 

with a pediatric aneuroid sphygmomanometer (model BF683W; Omron Healthcare 

Inc.), following protocols recommended by the American Heart Association 

(Pickering et al., 2005). Measurements were taken after 3–5 min of rest. Children 

were in the seated position with the antecubital fossa supported at heart level, with 

uncrossed legs and both feet on the floor. Blood pressure was measured twice, and 

averages of the two SBP and DBP values were used in analyses. No examiner 

training was described; however, AHA procedures were cited.

• Neurobehavioral development was assessed by trained examiners using the NEPSYII general assessment battery of examinations that included 11 age-appropriate 

subtests in 5 domains: attention and executive functioning (subtests: auditory 

attention and response set (AARS), inhibition, statue), language (comprehension of 

instructions, speeded naming), memory and learning (memory-for-faces immediate 

and delayed, narrative memory), sensorimotor (visuomotor precision), and 

visuospatial processing (design copying, geometric puzzles). Most children 

completed the general assessment battery within 50 to 80 minutes. The NEPSY-II 

assesses different subtests or different items within a subtest at different ages, which 

explains the varying sample sizes for each subtest. Three subtests required 

translation into Spanish (AARS, comprehension of instructions, and narrative 

memory). Translation of the NEPSY test has been found to be relatively unaffected 

by language and culture (Garratt & Kelley, 2008).

2012 analysis of flower worker cohabitation and children’s AChE activity

The associations of flower worker cohabitation, duration of cohabitation and number of flower 

workers living at home with AChE activity among children were calculated using multiple linear 

regression (AChE continuous) and polychotomous logistic regression (AChE a 4 level 

polychotomous variable). In addition, a dose–response association of secondary pesticide 

exposure with AChE activity was obtained by analyzing duration of cohabitation both as a 

continuous variable and as a 3-level categorical variable: 0 = no cohabitation never, 1 = >0–4.9 

years, 2 = ≥5 years; number of flower workers concurrently living at home was treated 

continuously and categorically: 0 = none, 1 = 1 flower worker, 2 = ≥2 flower workers; and 
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flower worker practices that would likely influence the amounts of pesticide inadvertently 

brought home were coded 1-4 [the worst practice among all workers in the home (e.g., always 

bringing work clothes home) coded 1 and the best practice (e.g., never bringing work clothes 

home) coded 4, 0 assigned to children of non-flower workers]; and a 4 category variable was 

created for the number of “bad” worker practices: 0, 1–2, 3, and 4-6]. The association of the 4 

level AChE variable as predicted from the number of bad practices was analyzed using 

polychotomous logistic regression. Associations are presented according to levels of adjustment 

for pertinent covariates: (1) a minimum adjustment model included general confounders between 

secondary exposure and AChE activity (age, gender, race, hemoglobin concentration, and 

examination date); (2) a multiple adjustment model to account for chronic nutritional status and 

additional potential sources of pesticide exposure (minimum adjustment + z-score height-forage, income, pesticide use within household lot and pesticide use by contiguous neighbors); (3) a 

full adjustment model to control for potential pesticide drift from flower plantations (multiple 

adjustment + residence distance to the nearest flower plantation edge). 

Using the 4 level polychotomous AChE activity variable, flower worker cohabitation (vs. not) 

had an OR 3.39 (95% CI 1.19, 9.64) for being <15th percentile compared to the highest tertile. 

Children cohabitating for ≥5 years (vs. never) had an OR of 4.11 (95% CI: 1.17, 14.38) of AChE 

activity within <15th percentile compared to the highest tertile. AChE was lower by 0.09 U/ml 

(95% CI -0.19, -0.001) in children of flower workers (57% of participants) than non-flower 

workers’ children, after adjustment for gender, age, height-for-age, hemoglobin concentration, 

income, pesticide use within household lot, pesticide use by contiguous neighbors, examination 

date, and residence, distance to the nearest flower plantation. Flower worker cohabitation and 

AChE did not differ by gender, race, age, height-for-age, or number of flower workers 

cohabitating.

Duration of exposure: Every year of cohabitation with a flower worker was associated with a 

fully adjusted mean difference of -0.02 U/ml (95% CI: -0.03, -0.002). Every year of cohabitation 

was associated with an adjusted OR of 1.22 (95% CI: 1.02, 1.45) for AChE activity in the lowest 

15th percentile compared to the highest tertile. Children who cohabited with a flower worker for 

5 years or more (vs. never) had an OR of AChE within the lowest 15th percentile (compared to 

the highest tertile) of4.11 (95% CI: 1.17, 14.38) and within the 15th–33rd percentiles of 3.86 

(95% CI: 1.44, 10.37).
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Among the 277 children, worker practices information for 233 children: parents of 52% of nonflower worker children had 0 “bad” practices, 17% had 1–2 “bad” practices, 18% had 3 “bad” 

practices, and 13% had 4–6 “bad” practices 13%. The most common bad work practices were: 

washing work clothes at home (95%), never showering at work (45%), infrequent removal of 

(38%) and bringing work shoes (18%) home, and bringing tools (16%) home. The fully adjusted 

AChE activity means among children for the 4 level bad practices variable was: 0=3.19 U/ml 

(95% CI: 3.13, 3.26), 1–2=3.09 U/ml (95% CI: 2.97, 3.21), 3=3.09 U/ml (95% CI: 2.97, 3.20) 

and 4–6=3.02 U/ml (95% CI: 2.90, 3.15). Children whose parents had 4–6 bad practices had a 

lower mean AChE activity by 0.17U/ml (95% CI: -0.31, -0.02) compared to children with no bad 

practices.

Overall conclusions were that living with a flower worker was related to lower AChE activity in 

children, longer duration of cohabitation was associated with lower AChE activity; and 

cohabitation with workers with 4–6 bad work practices was associated with lower AChE activity. 

The findings support the hypothesis, i.e., that the amount of secondary pesticide exposure from 

cohabitation with a flower plantation worker is sufficient to decrease AChE activity in children. 

The study also demonstrated the utility of field AChE measurements as a marker of pesticide 

exposure in children.

2013a analysis of AChE activity from secondary pesticide exposure and cohabitation with a 

flower plantation worker and changes in blood pressure and heart rate 

Multiple linear regression models were used to examine the association of AChE activity 

(continuous) with SBP, DBP, standardized values for SBP and DBP, and HR (significance 

a=0.05). Model 1 included examination date, age, sex, race, and height-for-age z score, and 

hemoglobin concentration. Model 2 included the Model 1 covariates, HR (when not the outcome 

of interest), income, number of smokers living at home, distance from residence to nearest 

flower plantation, pesticide use in the home or on the household lot, and pesticide use by 

contiguous neighbors. When the predictor was AChE activity, flower worker cohabitation was 

added to model 2. The researchers also plotted BP as linear function of AChE, adjusted least 

square means SBP and DBP to octiles AChE activity, for a visual of model fit. 

AChE activity was positively associated with resting heart rate, but estimated decreases in mean 

values were not statistically significant. AChE activity was positively associated with blood 

pressure (SBP and DBP) even after adjustment for resting heart rate. In model 2, every 1-U/mL 
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decrease in AChE activity was associated with a 2.86 mmHg decrease in mean SBP (95% CI: –

5.20, –0.53, p<0.05) and a 2.89 mmHg decrease in mean DBP (95% CI: –5.00, –0.78, p<0.05), 

after adjustment for potential confounders. Each 1-U/mL decrease in AChE activity was 

associated with decreases in z-scores for SBP and DBP of –0.26 SD (95% CI: –0.48, –0.04) and 

–0.22 SD (95% CI: –0.40, –0.03), respectively. Adjusted least square means for SBP and DBP 

estimated for each octile of AChE activity were closely aligned with the estimated linear trends, 

thus providing visual evidence of good model fits. Findings suggest that subclinical secondary 

exposures to pesticides may affect vascular reactivity in children. 

Children living with flower workers and longer duration of cohabitation had lower SBP than 

other children, and practices that might increase exposure also were associated with lower SBP. 

This suggests that the amount of take-home pesticide exposure by flower workers may be 

sufficient to induce physiological changes in children. Additional evidence in support of this 

hypothesis includes the negative associations of SBP with the number of flower workers living at 

home and the number of “bad practices” that may increase the likelihood of take-home pesticide 

exposures by flower workers.

2013 analysis of AChE activity and neurodevelopment (particularly attention, inhibitory 

control, and memory) among children living in floricultural communities, with stronger 

associations among boys.

For this third report, associations between AChE level and neurodevelopment were analyzed 

using logistic models (dichotomous and polychotomous) and linear regression models. Effect 

modification according to gender was assessed among statistically significant associations by 

testing an interaction term and through stratification followed by formal statistical testing of the 

difference of the stratified coefficients. The models were adjusted for flower worker cohabitation 

status to control for potential secondary occupational exposures to other chemicals that might 

affect neurodevelopment but that do not inhibit AChE activity. A few variables were imputed for 

this report - a “missing” race category (n=14), maternal education (n=15), income (n=17), and 

residential distance to the nearest flower plantation (n=3). The model was defined a priori to 

include hemoglobin (to account for varying red blood cell compositions) and potential 

confounders (age, gender, race, height-for-age z score [to estimate long-term nutritional status], 

household income, maternal education, and flower worker cohabitation status).
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AChE activity had positive (although mostly non-significant) associations with all 

neurodevelopmental domains and subtests except with statue and visuomotor precision (nonsignificant and negative associations). There was significant effect modification according to 

gender in the associations between AChE activity and attention and executive functioning 

domain (P = 0.01) and AARS–response set (P =0 .002). Girls had higher mean scores than boys 

in all but 1 of the subtests within the attention and executive functioning domain, but only 

attention and executive functioning domain and AARS–auditory attention scores were 

significantly different.

Lower AChE activity was associated with lower total neurodevelopmental summary score 

among boys (–0.70 points per 1-U/mL [∼2 SD] AChE decrease [95% confidence interval (CI): –

1.36 to –0.04]) but not girls (0.17 point per 1-U/mL decrease [95% CI: –0.53 to 0.88]).

In boys only, there were increased ORs of low (<9th percentile) neurodevelopment among those 

in the lowest tertile versus the highest tertile of AChE activity (ORs: total neurodevelopment: 

5.14 [95% CI: 0.84, 31.48]; attention/executive functioning domain: 4.55 [95% CI: 1.19, 17.38], 

memory/learning domain: 6.03 [95% CI: 1.17, 31.05]). Within these domains, attention, 

inhibition and long-term memory subtests were most affected.

Overall, the associations between AChE activity and neurodevelopment were negligibly different 

when flower worker cohabitation status was not included in the adjustment model.

Low AChE activity, reflecting OP and carbamate pesticide exposure, was associated with 

deficits in neurodevelopment, particularly in attention, inhibition, and memory in boys but not in 

girls. These are critical cognitive skills that affect learning and academic performance. The 

findings suggest that boys have greater sensitivity than girls for neurodevelopmental delays from 

subclinical pesticide exposures. 

Study Review

This was a well-conducted study, in three reports, of pesticide (OP and carbamates) exposure on 

AChE level, heart rate, blood pressure, and neurodevelopment conducted in a population of 

healthy, young (4-9 year old) children in Ecuador. The study included most of current eligible 

population, 4-9 years of age (from 2004 census survey, plus new community volunteers), and so 

selection bias is unlikely to have occurred. A few more flower workers did not show up for the 
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examination than non-flower workers, but was a small proportion of overall population. The 

exposed and unexposed groups had comparable demographics, SES, etc.

The analytic methods, questionnaire, and analytic approach were appropriate in all three reports. 

Inferences to be garnered from the results are constrained by limitations of the cross-sectional 

study design (cannot assess temporality between exposure and outcome due to cross-sectional 

design), the exposure assessment, and the assessment of developmental and neurodevelopment 

outcomes. None of the exposure measures (cohabitation with flower worker, distance to fields, 

AChE activity) in this study allow differentiation of the contribution of specific pesticides or 

pesticide groups (OP or carbamate) on results.

In addition, the focus of this epidemiological literature review is on the neurodevelopmental 

outcomes from exposures to low levels of OPs (i.e. below exposures which would result in 10% 

or more AChE inhibition). These three studies conducted in Ecuador focused on child AChE 

inhibition and the potential association of AChE inhibition with other measures including 

parental occupation (Suarez-Lopez et al, 2012), as well as clinical autonomic nervous system 

(ANS) outcomes such as blood pressure and heart rate (Suarez-Lopez et al, 2013a), and 

neurodevelopmental outcomes (Suarez-Lopez et al, 2013). The range of AChE activity levels 

are lower in the 1st tertile (range of 1.44 to 2.93 U/mL) compared to the 3rd tertile (range from 

3.33 to 4.69 U/mL). Therefore, due to the outcomes assessed and the potentially toxic 

cholinergic effects that were associated with these outcomes, these studies are not considered to 

be relevant to this review and were not included in the final synthesis of the epidemiological 

literature review (add citation). 
Page 88 of 171

2012 analysis of flower worker cohabitation and children’s AChE activity

In this report, the exposure measure was flower worker cohabitation which does not prove that a 

child was exposed. The outcome - AChE level in a single blood sample – is a non-specific 

biomarker of OP pesticide exposure. However, the duration of cohabitation findings 

demonstrated a dose-response association. As this could be due to accumulating pesticides in the 

home over time and/or decreased safety practices with longer work experience, the inclusion of 

household distance to the nearest flower plantation in the analysis allowed researchers to 

disentangle the mechanisms of pesticide introduction into the home between pesticide drift from 

flower plantations and flower worker associated ‘‘take-home’’ pathways. The authors note that 

they did not ask about consumption of ‘‘organic’’ (pesticide-free) products as a possible source 

of reduced pesticide exposure given that such products are rarely available or advertised by local 

growers in the county. There was no reason to believe that consumption of non-‘‘organic’’ 

products would differ by flower worker cohabitation status. 

The authors point out that no ‘‘unexposed’’ baseline was available to calculate AChE 

suppression because most of the children who lived with a flower-worker were born into families 

with a flower worker (72%) and were potentially even exposed to pesticides in-utero. In addition, 

there is a lack of multiple AChE measurements to allow for tracking activity over time and 

provide more robust conclusions on the associations of AChE and flower worker cohabitation. 

However, the finding that duration of cohabitation was inversely related to AChE is internally 

valid and consistent with cumulative exposures. 

It is not known how much clinical impact AChE suppression equivalent to the ones observed can 

have on children in the short and long term neurodevelopment. Chronic pesticide exposures 

during childhood could effect multi-systemic developmental impairments including 

neurobehavioral delays; this is a gap in the literature that needs to be addressed and is a further 

aim of the ESPINA study.

2013a analysis of AChE activity from secondary pesticide exposure and cohabitation with a 

flower plantation worker and changes in blood pressure and heart rate 

In this second report, the researchers treated AChE activity, along with cohabitation with a 

flower plantation worker, as the exposure measure. While AChE measurement is an appropriate 

method to assess past exposures to carbamate and OP pesticides because it can reflect longer-
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term exposures than plasma cholinesterase (butyrylcholinesterase) or pesticide metabolite 

quantification, AChE is less sensitive in detecting pesticide exposures. Furthermore, AChE 

activity has a low intra-individual variability, in contrast with urinary metabolites of pesticides 

that have more intra-individual than inter-individual variability (Lefkowitz et al., 2007; Griffith 

et al., 2011). 

The models assumed that more exposed children have a more pronounced reduction in AChE 

than less exposed children, i.e., a larger effect size within lower levels of AChE activity than 

within higher levels. To the authors’ knowledge, no AChE standards exist for children. To assess 

this, they divided the sample into tertiles, then divided the lowest tertile of AChE activity into 

two categories: an upper half (33rd–15th percentiles, 2.68–2.93U/ml) and a bottom half (<15th 

percentile, 2.68 U/ml ~<10th percentile of children who do not live with a flower worker). 

Because children were examined during the months of July and August and AChE activity can 

reflect exposures to organophosphates within the previous 82 days, there was potential that 

children who were examined earlier in July may have lower AChE activity (from secondary 

sources) due to heightened fumigations for the Mother’s Day (May) surge of flower production. 

This exposure gap may be differential by exposure status given that the proportion of examined 

children who lived with a flower worker in early July does not necessarily represent the 

distribution of the overall group. Examination date was not an effect modifier for the association 

between flower worker cohabitation and AChE (p=0.12), and was controlled for in all models. 

Factors other than exposure to cholinesterase inhibitor pesticides may contribute to lower SBP 

among children who lived with a flower worker, given that associations persisted after adjusting 

for AChE activity. Agricultural workers are typically exposed to a mix of pesticides, and it is 

possible that non-cholinesterase inhibitor pesticides may also contribute to (or be responsible for) 

the decrease in SBP, because AChE inhibition could be acting as a proxy indicator of overall 

pesticide exposure. There is also an inability to account for factors related to BP such as prenatal 

toxicant exposures, concurrent and previous dietary patterns (e.g., salt and fat consumption), and 

perinatal health history.

The results of this investigation suggest a physiological disturbance associated with cohabitation 

with agricultural workers. This concept is corroborated by the previous finding in this study 

population, where children living with flower workers had lower AChE activity compared with 
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nonagricultural workers, and lower AChE was associated with longer duration of cohabitation 

and a greater number of bad practices (Suarez-Lopez et al., 2012).

Although there was a statistically significant interaction with race in the associations of flower 

worker cohabitation, duration of cohabitation, and number of flower workers living with DBP, 

the authors did not believe this association is important. With complementary and related 

information, these three exposure variables represent one exposure construct: cohabitation with a 

flower worker. Given the genetic similarities between indigenous and mestizos and the fact that 

there was evidence of effect modification of, in essence, one exposure–outcome relation, it is 

likely that the observed difference by race may be spurious.

The estimated average BP decreases were relatively small, but the amount of cholinesterase 

inhibitor pesticide exposure is also likely small due to the secondary nature of the exposure. The 

estimated association of cohabitation with a flower worker and blood pressure may be 

conservative because participants were examined in July and August, which are months of 

decreased flower production. The finding that lower AChE activity was associated with lower 

blood pressure and a small, non-significant decrease in heart rate suggests that cholinesterase 

inhibitor pesticides may primarily induce vasodilation in children. The researchers speculated 

that the blood pressure decreases may reflect a predominant stimulation of muscarinic M3 

receptors in the vascular endothelium.

The researchers note that flower worker children may have similar exposures as in similar 

communities in the US and other developed countries. For example, the mean AChE activity for 

children living with flower workers were consistent with mean levels reported for Hispanic 

children living in agricultural (3.0 U/mL) and nonagricultural families (3.1 U/mL) in Oregon 

(USA) (Higgins et al., 2001). Generally, lower BP is associated with better cardiovascular 

outcomes, but long-term cardiovascular effects of chronic low-dose pesticide exposures are 

unknown, and the possibility of any physiological effects of low-dose pesticide exposures in 

children is a concern. Additional research is needed to determine whether the associations that 

observed are evident in other populations.

2013 analysis of AChE activity and neurodevelopment (particularly attention, inhibitory 

control, and memory) among children living in floricultural communities, with stronger 

associations among boys.
Page 91 of 171

In this final report, the researchers examined AChE activity and neurodevelopment. The review 

comments above apply to this report. In addition, while NESPY-II seems to be an appropriate 

neurodevelopment tool and was administered by trained examiners, scores were overall lower

than the NESPY-II normative sample. This could be due to differences in cultural and social 

practices, test-taking abilities, nutrition, or environmental exposures. This analysis did control 

for nutrition and anemia. 

The findings support the hypothesis that AChE inhibition is an important mechanism of 

neurotoxicity of cholinesterase inhibitor pesticides. Other studies of children (Marks et al., 2010; 

Horton et al., 2012), as well as animal studies, have reported greater detrimental neurochemical 

and behavioral effects, including working memory, among males after early postnatal exposure 

to OP pesticides. However, AChE inhibition is an indicator of exposure, and other neurotoxic 

mechanisms may also be present but unidentified. The reason for the gender interaction is not 

understood and is a topic for future research. However, for the research question of interest, i.e., 

does OP pesticide exposure affect neurodevelopment, these findings are less relevant than 

studies which measure OP pesticides directly or their exposure biomarkers. 

References cited

Garratt LC, Kelly TP. To what extent does bilingualism affect children’s performance on the 

NEPSY? Child Neuropsychol. 2008;14(1):71–81.

Griffith W, Curl CL, Fenske RA, Lu CA, Vigoren EM, Faustman EM. 2011. Organophosphate 

pesticide metabolite levels in pre-school children in an agricultural community: withinand between-child variability in a longitudinal study. Environ Res 111(6):751–756.

Horton MK, Kahn LG, Perera F, Barr DB, Rauh V. Does the home environment and the sex of 

the child modify the adverse effects of prenatal exposure to chlorpyrifos on child working 

memory? Neurotoxicol Teratol. 2012;34(5):534–541.

Lefkowitz LJ, Kupina JM, Hirth NL, Henry RM, Noland GY, Barbee JY Jr, et al., 2007. 

Intraindividual stability of human erythrocyte cholinesterase activity. Clin Chem 

53(7):1358–1363.

Marks AR, Harley K, Bradman A, et al. Organophosphate pesticide exposure and attention in 

young Mexican-American children: the CHAMACOS study. Environ Health Perspect. 

2010;118(12):1768–1774.

Richardson JR, Chambers JE. Effects of repeated oral postnatal exposure to chlorpyrifos on 

cholinergic neurochemistry in developing rats. Toxicol Sci. 2005;84(2): 352–359.
Page 92 of 171

World Health Organization, 2008. Training Course on Child Growth Assessment. WHO, 

Geneva.
Page 93 of 171

Study 15. Wang et al. (2012)

Organophosphate pesticide exposure and perinatal outcomes in Shanghai, China. Pei 

Wang, Ying Tian, Xiao-Jin Wang, Yu Gao, Rong Shi, Guo-Quan Wang, Guo-Hua Hu, 

Xiao-Ming Shen. 4 Environment International 2:100–104, 2012.

Study Summary

In this report, Wang et al. evaluate the relationship between maternal prenatal OP pesticide 

exposure and perinatal outcomes in a cross-sectional birth cohort study set in Shanghai, China 

using both questionnaire-derived and biomarker-based pesticide exposure assessments. 

To evaluate associations between indicators of fetal growth and prenatal OP pesticide exposure, 

healthy pregnant women between the ages of 18 and 45 years were recruited from the obstetric 

wards of two major hospitals between September, 2006 and the end of January, 2007. Women 

with diabetes (gestational or preexisting), hypertension, HIV/AIDS, or who had used illicit drugs 

in the preceding year were identified during a brief screening exam and excluded from 

participation. Of 193 eligible women, 187 consented to participate in the study. 

After delivery, the participating women received a questionnaire-guided interview conducted by 

a specially trained nurse to solicit information on pesticide exposure, to include whether pest 

control measures were used by the woman herself or other household members during 

pregnancy, the types of pesticides used in the home, and the frequency of use. Paternal OP 

pesticide exposures and occupational history were also queried. Demographics, medical history, 

and socioeconomic indicators including maternal age, education and income level, reproductive 

history, smoking history, occupational history, and alcohol and drug consumption during 

pregnancy were also obtained. 

A single urine sample was collected from the participating mothers at the onset of labor. 

Specimens were processed and shipped to the Shanghai Centers for Disease Control and 

Prevention for quantification of dialkylphosphate (DAP) metabolites. DAP metabolites including 

dimethylphosphate (DMP), dimethyldithiophosphate (DMTP), diethylphosphate (DEP), 

diethylthiophosphate (DETP), and diethyldithiophosphate (DEDTP) were quantified using gas 

chromatography. DAP observations below the (unspecified) limit of detection (LOD) were 
Page 94 of 171

assigned a value equal to the LOD/√2. DAP concentrations were estimated with and without 

creatinine adjustment, and were log transformed for analysis.

Data on the neonates were ascertained from the infants’ medical records, to include gestational 

age at birth, sex, birth weight, birth length, presence of birth defects, Apgar score, pregnancy and 

delivery complications, as well as maternal anthropometric measures such as height, weight, and 

weight gain during pregnancy. LBW was conventionally defined as birth weight less than 2,500 

grams; only six infants met this criterion. Preterm delivery was defined as birth at less than 37 

weeks of completed gestation; only four neonates met this criterion. 

Multivariate linear regression models were constructed to examine the relationship between 

exposure to OP pesticides and birth outcomes adjusted for potential confounders. The following 

covariates were included in final models: maternal height, pregnancy weight gain and family 

income. Smoking, alcohol use, illicit drug use, maternal education, reproductive history, and 

other information about previous pregnancies, paternal OP pesticide exposure and paternal 

occupation were found not to be significant predictors of outcomes (alpha=0.1) and were not 

included in final models. To evaluate effect modification by gender, separate models were 

constructed for boys and girls. The authors also conducted a sensitivity analyses excluding 

preterm infants form the analytic sample.

No associations between any of the OP pesticide exposure measures and gestational age, birth 

weight and birth length outcomes were observed in primary analyses. The authors observed a 

statistically significant 1.79 week average decrease in gestational age associated with a log 

increase in urinary DEP among girls, but did not observe a similar association among boys. 

Study Review

This was a well-conducted study of prenatal OP pesticide exposure effects on birth outcomes in a 

population of healthy, young Chinese mothers and their newborn children. The analytic methods, 

questionnaire, and analytic approach were appropriate. The study was limited by the crosssectional ascertainment of pesticide exposure and birth outcomes, a small sample size, and low 

prevalence of LBW and PTD outcomes (precluding their analysis).

The authors employed a reasonable set of inclusion/exclusion criteria. Almost all (97%) of the 

eligible women recruited for participation in the study agreed to participate and were enrolled. 

Selection bias is unlikely to have occurred. 
Page 95 of 171

The investigators collected participant OP pesticide exposure and a large set of potential 

covariate information via a questionnaire-guided interview which was conducted after the 

delivery. It is therefore possible that self-reported exposures were not independent of birth 

outcomes. 

Objective biomarkers of OP pesticide exposure were quantified in a single maternal spot urine 

sample obtained at the onset of labor. Specimen collection and biomarker quantification methods 

appear to be appropriate. DAP concentrations were noted to be higher in this Chinese study 

population, relative to those observed in other Western populations. The use of urinary DAP 

metabolite biomarkers of exposure likely provide a more objective, sensitive, and likely also 

more accurate and reliable indicators of OP pesticide exposure, relative to the exposure 

assessment relying on maternal self-report after delivery. The biomarker based prenatal OP 

pesticide exposure assessment also has limitations. Because they are non-specific, urinary DAP 

concentrations can be considered an integrated biomarker of exposure to many OP pesticides. 

Because of the often intermittent nature of pesticide exposure, urinary DAP metabolite levels can 

exhibit considerable temporal variability (i.e. day-to-day fluctuations) which could not be 

evaluated in this study in which a urine sample was collected at one time point. Urinalysis for 

DAP metabolites, therefore provides a biomarker of very recent exposure, i.e., in the 24 to 48 

hour period prior to the collection of the urine sample. In this study, that equates to the day or 

two just prior to delivery. Exposures in this short time period late in gestation may not be 

representative of a participant’s usual prenatal OP pesticide exposure or exposures during more 

relevant time-window(s) for exposure effects. Finally, OP pesticides can break down into DAPs 

in the environment, and urinary concentrations may therefore also reflect exposure to preformed 

(non-toxic) environmental DAPs. 

Collection of the fetal development outcomes was straightforward and unlikely to have been 

conducted with error. To the extent that they did occur, outcome measurement errors were likely 

independent of DAP concentrations but, as mentioned above, may not be independent of selfreported exposures. 

The statistical methods used in this study were conventional and appropriate. Covariate 

adjustment was also appropriate, though residual confounding by mismeasured or unmeasured 

determinants of fetal development is possible. Correction of hypothesis test results for multiple 

comparisons was not conducted. 
Page 96 of 171

The only findings observed in this report where within strata of gender, and specifically among 

girls. It was unclear whether the hypothesis of interaction between prenatal OP pesticide 

exposure and child gender was developed a priori, or if stratification by gender was an ad hoc

exploratory analysis conducted after associations were not observed in the study population as a 

whole. However, the small size of the study sample is an indication that the decision to stratify 

by gender was not driven by an a priori hypothesis.

The results of this study were largely null. Errors in the estimation of prenatal OP pesticide 

exposure are a possible explanation for the lack of observed association. The authors’ conclusion 

that high pesticide levels might adversely affect duration of gestation is not well supported, given 

the solitary finding of an association between increasing DEP concentrations and decreasing 

gestational age only among girls, the potentially exploratory nature of this evaluation of effect 

modification by gender, and the small sample size. The findings of this investigation are 

generally not consistent with the hypothesis that prenatal OP pesticide exposure is associated 

with adverse perinatal outcomes. 
Page 97 of 171

Study 16. Zhang et al. (2014)

Prenatal exposure to organophosphate pesticides and neurobehavioral development of 

neonates: A birth cohort study in Shenyang, China. Ying Zhang, Song Han, Duohong 

Liang, Xinzhu Shi, Fengzhi Wang, Wei Liu, Li Zhang, Lixin Chen, Yingzi Gu, Ying Tian. 

PlosOne 47:80–85, 2014.

Study Summary

In this report, Zhang et al. evaluate the relationship between maternal prenatal OP pesticide 

exposure and neonatal neurodevelopment prospective birth cohort study set in Shenyang, China 

using urinary markers of OP pesticide exposure.

In order to investigate the effects of prenatal OP pesticide exposures on neonatal 

neurodevelopment, 249 healthy pregnant women between the ages of 18 and 45 years were 

recruited from the hospital associated with the Shenyang Medical College. Women living in 

Shenyang for less than 3 years, and those with hypertension, diabetes, thyroid disorders, heart 

disease, or other non-specified chronic diseases prior to pregnancy were excluded from 

participation in the study. Women with “heavy” pregnancy complications including diabetes, 

anemia, and hypertension were also excluded, as where those with a family or medical history of 

mental retardation, phenylketonuria, or Pompe’s syndrome. Infants with traumatic brain injury, 

meningitis, or severe illnesses were also excluded from analyses. Of 307 eligible pregnant 

women, 249 consented to participate and were enrolled in the study with their neonates.

After delivery, the participating women received a questionnaire-guided interview conducted by 

a specially trained nurse to solicit information on pesticide exposure, to include whether pest 

control measures were used by the woman herself during pregnancy, or by a family member, the 

types of pesticides used in the home, and the frequency of use. Demographic information, and 

the information regarding home characteristics, residential history, reproductive history, smoking 

history, diet, and alcohol and drug consumption during pregnancy were also obtained. 

A single urine sample was collected from the participating mothers. The time of the urine 

sampling relative to gestational age or delivery was not specified in the report. Urine specimens 

were processed and shipped to the Shanghai Centers for Disease Control and Prevention for 

quantification of five dialkylphosphate (DAP) metabolites; Dimethylphosphate (DMP), 
Page 98 of 171

dimethyldithiophosphate (DMTP), diethylphosphate (DEP), diethylthiophosphate (DETP), and 

diethyldithiophosphate (DEDTP) were quantified using gas chromatography. The lower limit of 

detection (LOD) was 2.0 μg/L for DMP and 1.0 μg/L for DMTP, DEP, DETP, and DEDTP. 

DAP observations below the limit of detection (LOD) were assigned a value equal to the 

LOD/√2. DAP concentrations were estimated with and without creatinine adjustment, and were 

log transformed for analysis.

Infant neurodevelopment was assessed three days after birth using a neonatal behavioral 

neurological assessment conducted by two trained examiners who were blinded to the exposure 

status of the children. (NBNA, Bao et al., 1991) The NBNA assesses functional abilities, 

reflexes and responses, and stability of behavioral status using five scales: Behavior, Passive, 

Tone, Active Tone, Primary Reflexes, and General Assessment. The items from each of these 

scales were summarized in a total score with a maximum score of 40. Neonates with a total score 

greater than 37 were considered well developed, those with a total score lower than 34 were 

classified as abnormal, and those with scores in between were considered as acceptable range. 

Pearson Correlations were calculated to summarize the univariate linear relationship between 

maternal prenatal urinary OP pesticide metabolites neonatal neurobehavioral assessments scores. 

Multivariate linear regressions were then constructed to estimate the association between 

maternal DAP concentrations during pregnancy and the neurodevelopment of neonates, adjusted 

for potential confounders. Separate models were built with each of the scores of the five NBNA 

scales and the total NBNA score as dependent variables, and each of the log-transformed 

concentrations of total DAP, total DMP and total DEP as continuously distributed predictor 

variables. The following covariates were evaluated for inclusion in these models using a stepwise 

modeling approach: maternal age, maternal education, gestational age, prenatal BMI, neonatal 

bodyweight, and cord blood lead concentration. Statistical significance (alpha) level was set at 

0.10 for inclusion of covariates and 0.20 for exclusion in the stepwise process. Potential 

exposure-response relationships between maternal prenatal OP pesticide exposure and neonatal 

neurodevelopment outcomes were assessed by categorizing DAP concentrations by quintile and 

comparing mean neurodevelopment scores from the lowest quintile of DAP concentration (as the 

reference group) to those in the second through fifth quintiles. Multivariate analyses were also 

stratified by gender.

Maternal prenatal urinary DAP, DMP, and DEP concentrations were significantly negatively 

correlated with summary NBNA scores. In multivariate analyses, higher prenatal DAP 
Page 99 of 171

concentrations were associated with lower scores in all NBNA scales. A 10-fold increase in total 

DAP concentration was associated with an average decrease in NBNA Summary scores of 1.78 

points (95% CI: -2.12 to -1.45). No evidence of departure from linearity of the exposureresponse relationship between maternal DAP concentrations and NBNA scores was observed. 

Statistically significant effect modification by gender was not observed, though associations 

were generally stronger among girls. 

Study Review

This was a well-conducted study of prenatal OP pesticide exposure effects on neonatal 

neurodevelopment in a population of healthy, young Chinese mothers and their newborn 

children. The analytic methods, questionnaire, and analytic approach were appropriate. Study 

strengths include the prospective study design, objective measurement of OP pesticide exposure, 

and use of a sensitive instrument for assessing neonatal neurodevelopment. 

The authors employed a reasonable set of inclusion/exclusion criteria. A high percentage (81%) 

of the eligible women recruited for participation was enrolled in the study. Selection bias is 

unlikely to have occurred. 

Objective biomarkers of OP pesticide exposure were quantified in a single maternal spot urine 

sample. The timing of the specimen collection was not clearly reported. The biomarker 

quantification methods appear to be appropriate. The use of urinary DAP metabolite biomarkers 

of exposure likely provide a more objective, sensitive, and likely also more accurate and reliable 

indicators of OP pesticide exposure, relative to assessments relying on self-report of pesticide 

exposure. However, the biomarker-based prenatal OP pesticide exposure assessment also has 

limitations. Because they are non-specific, urinary DAP concentrations can be considered an 

integrated biomarker of exposure to many OP pesticides. In humans, DAPs have a half-life of 

less than 24 hours, so urinary concentrations reflect only recent exposure. The combination of 

the short elimination half-life and the episodic nature of exposures to OP pesticides can result in 

a high degree of day-to-day variability in urinary DAP concentrations. Also, urinary DAP 

concentrations cannot be used to quantify exposure to a specific pesticide. Exposures in this 

short time period late in gestation may not be representative of a participant’s usual prenatal OP 

pesticide exposure or exposures during more relevant time-window(s) for exposure effects. 

Finally, OP pesticides can break down into DAPs in the environment, and urinary concentrations 

may therefore also reflect exposure to preformed (non-toxic) environmental DAPs. 
Page 100 of 171

Errors in the estimation of prenatal OP pesticide exposure are likely to be non-differential with 

respect to the neurodevelopment outcome scores, and thus are not a likely explanation for the 

observed associations. 

The neonatal behavioral neurological assessment used to evaluate infant’s neurodevelopment at 

three days of age has been used previously in several cohort studies conducted in China, and 

demonstrated “distinct stability and reliability” in these settings. It appears to be a highly 

sensitive indicator of neurodevelopment. 

Covariate adjustment appeared appropriate, though residual confounding by mismeasured or 

unmeasured determinants of fetal neurodevelopment is possible. Correction of hypothesis test 

results for multiple comparisons was not conducted. 

Consistent statistically significant associations were observed between all of the quantified 

urinary biomarkers of prenatal OP pesticide exposure and neonatal neurodevelopment assessed 3 

days after birth. Higher DAP concentrations were associated with lower summary NBNA scores 

(indicating increasing neurodevelopmental deficits). The associations observed in this study by 

Zhang et al. are consistent with the hypothesis that prenatal OP pesticide exposure affects fetal 

neurodevelopment.

References cited

Bao XL, Yu RJ, Li ZS, Zhang BL (1991) Twenty-item behavioral neurological assessment for 

normal newborns in 12 cities of China. Chin Med J. 104:742–746.
Study 17. Shelton et al. (2014)

Neurodevelopmental disorders and prenatal residential proximity to agricultural 

pesticides: The CHARGE Study. Janie F. Shelton, Estella M. Geraghty, Daniel J. Tancredi, 

Lora D. Delwiche, Rebecca J. Schmidt, Beate Ritz, Robin L. Hansen, and Irva HertzPicciotto. Environmental Health Perspectives 122:1103–1109, 2014.

Study Summary

The CHARGE study is a population-based case-control study of child development specifically 

focused on evaluating potential risk factors for autism spectrum disorders and developmental 

delay. In this paper, Shelton et al. report on an evaluation of the association between residential 

proximity to agricultural pesticides during pregnancy and neurodevelopmental outcomes, 

specifically the risks of autism spectrum disorders and developmental delay among children of 

families eligible for inclusion in the California Department of Developmental Services (DDS) 

system. An estimated 75-80% of all children with these diagnoses living in California are 

enrolled in the DDS system (Croen et al., 2002). Beginning in 2003, the CHARGE study has 

recruited more than 1,600 child participants whose parents completed extensive questionnaires 

concerning potential environmental exposures during pregnancy. Cases (children with diagnosed 

with full-syndrome Autism Spectrum Disorders and Developmental Delay) were recruited either 

from one of several regional centers of the DDS or through referrals from other clinics, selfreferral or unspecified “general outreach.” The Autism Diagnostic Observation Schedule (Lord 

et al. 2000, 2003) was used to either confirm the ASD diagnosis or reclassify the children for the 

purposes of the study.

Control participants were recruited from the general California population, having been 

identified through birth records maintained by the State of California. Children were eligible to 

participate in the CHARGE study as controls if they were between two and five years of age, 

were born in California, live with a biological parent who speaks either English or Spanish, and 

reside in a CHARGE study catchment area (mainly within a 2-hour drive from the Sacramento 

area). Children potentially eligible to participate in the study in either the developmental delay 

group or the general population control group were administered the Social Communications 

Questionnaire (Rutter et al., 2003) to rule out an autism-spectrum disorder diagnosis.

Shelton et al. used publically available commercial agricultural pesticide application data from 

the California Department of Pesticide Regulation's annual Pesticide Use Report (CDPR 2014) 
to estimate prenatal pesticide exposures. This report includes agricultural pesticide applications 

in the State (in pounds of active ingredient applied, by date) for square-mile areas known as 

meridian-township-range-sections (MTRS). The authors used GIS-mapping software to create a 

geographic centroid for each MTRS. The investigators then mapped the residential addresses of 

participant's mothers during pregnancy, collected on the CHARGE questionnaire and created 

three buffers with radii of 1.25 km, 1.5 km, and 1.75 km around each residence. Pregnancies of 

participants' mothers where then assigned a pesticide exposure profile corresponding to the 

pesticides applied to the MTRS nearest the mother's home and during her pregnancy on which 

the pesticide applications occurred. Pesticides were grouped into organophosphate, carbamate, 

pyrethoid, or organochlorine classes. Chlorpyrifos was examined independently because of 

previous evidence of its associations with neurodevelopmental outcomes. Most of the 

participants’ homes received a pesticide exposure level of zero, as no pesticides had been applied 

within the buffer zone; approximately a third of the study participants' mothers lived within 

1.5km of an agricultural pesticide application during their pregnancy.

Controls were frequency matched to autism cases on sex, age, and catchment area. Potential 

additional confounders were initially identified using directed acyclic graphs (DAGS, Rothman 

et al., 2008) as potential determinants of autism spectrum disorders or developmental delays and 

which may influence exposure to pesticides (without consideration of statistical associations in 

univariate assessments). A 10% change-in-estimate criterion was established to exclude potential 

confounders from the final models. The final models included adjustment for paternal education, 

home ownership, maternal country of birth, child race/ethnicity, maternal prenatal vitamin use, 

and year of birth. The authors additionally constructed models adjusting pesticide class-specific 

associations for indicators of exposure to the other pesticide classes considered in this 

investigation.

The independent associations between risk of the neurodevelopmental outcomes (i.e. autism 

spectrum disorder and development delay) and the different classes of pesticides were examined, 

as well as potential interactions between the different classes of pesticides.

Multinomial multivariate logistic regression models (with appropriate survey weights) were 

constructed for each developmental outcome. Agricultural pesticide exposure was defined as a 

dichotomous (yes/no) variable, according to presence or absence of pesticide applications within 

the buffer zone during the pregnancy time period.
Proximity to OP pesticide application at some time during pregnancy was associated with a 60% 

increase in the risk of autism spectrum disorder (OR=1.6; 95% CI: 1.02–2.51), compared to 

those whose mothers who those who did not live in close proximity (within 1.5 km) to any 

agricultural pesticide applications during their pregnancy. Elevations in risk were greater for 

exposures that occurred specifically in the third-trimester (OR=2.0; 95% CI: 1.1-3.6). No 

statistically significant associations were observed between proximity to OP pesticide 

applications during pregnancy and risk of developmental delay.

Study Review

This was a largely well conducted case-control study that leveraged publically available 

agricultural pesticide application data aggregated to one-square mile areas, in combination with 

questionnaire-based residential location information and GIS mapping techniques to evaluate 

risk of autism spectrum disorder and developmental delay in a population based case-control 

study set in California.

The study was large, with a case sample of 486 children with autism spectrum disorder, 168 

children with developmental delay, and a study base drawn from the catchment area of the 

CHARGE study (mainly the area within a two hour drive from the Sacramento area, and also 

included a portion from Southern California), represented by 316 normally developing control 

participants. 

No actual environmental pesticide measurements or biomarkers of pesticide exposure where 

evaluated in this study. The exposure assessment used distance from the mother’s home during 

pregnancy to areas associated with specific agricultural pesticide applications as a proxy for 

pesticide exposure. The investigators took care to minimize misclassification of addresses in the 

study. However, misclassification of actual pesticide exposure is likely to have occurred, as it is 

possible that those living near locations with agricultural pesticides applied where not, in fact, 

exposed to the pesticides while those living far from sites where agricultural pesticides where 

applied may have been exposed. The exposure assessment did not consider many potential 

sources of pesticide exposure, including non-agricultural institutional applications, residential 

indoor and outdoor pesticide use, and dietary sources. Other sources of potential exposure errors 

discussed by Shelton et al. in their report include errors in reporting in the CDPR annual 

Pesticide Use Report, the assumption of homogeneity of pesticide exposures a buffer zone, and 

potential GIS geocoding errors. All of these sources of exposure classification errors were likely 

independent of case/control status. 
The autism and developmental delay case statuses were well defined. Outcome misclassification 

was likely minimized by the study protocol which included using validated instruments to 

provide diagnostic confirmation at the time of enrollment. 

Control selection was appropriate and likely represented the study base from which the cases 

arose. The authors mentioned having difficulty with recruitment of general population controls in 

Southern California early in the study, due to “logistical difficulties,” and thus terminated 

recruitment in this area. The impact of these difficulties and the halting of recruitment in 

Southern California on the representativeness of the controls selected from this region (and 

corresponding selection bias) were not discussed in the report. Inverse probability of 

participation weights were used in an attempt to adjust the multinomial models for differential 

probabilities of enrollment in the study by case or control groups. The authors argued that the 

weighted exposure frequency distributions and regression models more accurately represent 

findings that are generalizable to the study base. This weighting also likely decreased the 

potential for selection bias that could be induced if the estimated pesticide exposure distributions 

among the control participants do not represent those of the population (or more formally, the 

study base) that gave rise to the autism spectrum disorder and developmental delay cases.

The statistical analyses and evaluation of potential confounding factors were appropriate. In 

addition to the multivariate modeling, control subjects were frequency matched to autism 

spectrum disorder cases on sex, age, and catchment area, and this matching was appropriately 

addressed in the statistical analysis. Matching of controls to developmental delay cases was not 

discussed in the report and, presumably, was not conducted.

The results of the study support the authors’ conclusion that children exposed to OP pesticides 

during gestation may be at increased risk for neurodevelopmental disorders. However, selection 

bias, residual confounding, and chance remain alternative explanations of the associations 

observed in the study. 

References cited

CDPR (California Department of Pesticide Regulation). 2014. Pesticide Use Reporting (PUR). 

Available: http://www.cdpr.ca.gov/docs/pur/purmain.htm

Croen LA, Grether JK, Hoogstrate J, Selvin S. 2002. The changing prevalence of autism in 

California. J Autism Dev Disord 32(3):207–215.
Lord C, Rutter M, DiLavore PC, Risi S. 2000. The Autism Diagnostic Observation Schedule 

(ADOS). Los Angeles: Western Psychological Services.

Lord C, Rutter M, DiLavore PC, Risi S. 2003. Autism Diagnostic Observation Schedule Manual. 

Los Angeles: Western Psychological Services.

Rothman KG, Greenland S, Lash T. Modern epidemiology. Philadelphia, PA: Lippincott 

Williams & Wilkins; 2008.

Rutter M, Bailey A, Berument SK, Lord C, Pickles A. 2003. Social Communication 

Questionnaire (SCQ). Los Angeles: Western Psychological Services.
Study 18. Acosta-Maldonado et al. (2009)

Effects of exposure to pesticides during pregnancy on placental maturity and weight of 

newborns: A cross-sectional pilot study in women from the Chihuahua State, Mexico. 

Brenda Acosta-Maldonado, Blanca Sánchez-Ramírez, Sandra Reza-López, and Margarita 

Levario-Carrillo. Human and Experimental Toxicology 28(8) 451–459, 2009.

Study Summary

Acosta-Maldonado et al. reported on a study evaluating the association between third-trimester 

pesticide exposure and an index of placental maturity based on microscopic assessment of 

placental tissue morphology. The study was set among pregnant women in Chihuahua, Mexico. 

The primary objective of this cross-sectional pilot study was to assess the effects of 

cholinesterase inhibitor pesticides during pregnancy and placental maturity. The investigators 

compared placental morphology of nine women determined to have 3rd-trimester pesticide 

exposure to forty-five women without explicit pesticide exposure. The authors excluded women 

with multiple pregnancies and those “with diseases, either previous or developed during 

gestation.” 

Acytelcholinesterase (AChE) activity was quantified in a venous blood sample obtained from the 

women at the time of admission to the hospital for delivery. The authors defined AChE ≤ 4.96 

U/mL as a marker of pesticide exposure effect. Participating women were asked to complete a 

previously validated structured questionnaire to garner information on clinical characteristics and 

pesticide exposure history. 

Women (n=9) were defined as exposed to pesticides if they presented with more than one of the 

following: 1) residence in an eminently agricultural community in which pesticides had 

continuously been applied during agricultural cycles; 2) home located less than five kilometers 

from a pesticide application zone; 3) or a spouse or any person cohabitating at subject's address 

who worked with pesticides or in agricultural labor. Although the specific pesticide(s) to which 

the women were exposed was not assessed, the investigators noted that the most commonly used 

pesticides were organophosphates, and of these, methylparathion was the most common. Fortyfive mothers of full-term infants without an explicit pesticide exposure served as the primary 

comparison group. To investigate the relationships between gestational age, birth weight, and 

placental maturity, the placentas of an additional thirty-one mothers of pre-term babies 
determined not to have had pesticide exposure during the third trimester of pregnancy were also 

included in the comparison group.

The sampling and processing of placental tissue was done in an appropriate and consistent 

manner for all women. The morphometric analysis was conducted by two investigators who were 

blinded to the exposure status of the women. The outcome, a placental maturity index (PMI) was 

calculated by dividing the number of epithelial plates in terminal villi to their thickness. PMI was 

calculated in central and peripheral regions of the placenta.

For their primary analyses, the authors built an initial multivariate adjusted linear regression 

model of PMI, predicted by pesticide exposure status and adjusted for gestational age, number of 

terminal villi per 1 mm2

, number of capillaries, diameter of capillaries, diameter of the sinusoids, 

placenta weight, and weight of the newborn. Covariates that were not significantly associated 

with PMI (α=0.05) were removed from the model. Collinearity of the placental characteristics 

covariates was assessed by evaluating variance inflation, and p-values were adjusted for multiple 

comparisons. 

There was a statistically significant relationship observed between pesticide and PMI in central 

region, with PMI of pesticide-exposed women being, on average, 7.38 units higher than those of 

the women not exposed to pesticides (p=0.01), after adjusting for number of terminal villi, 

number of terminal capillaries, terminal capillary diameter, sinusoids diameter of terminal villi 

and placental weight. Among pesticide exposed women, the PMI was greater in samples from 

the central region, relative to the peripheral region, of the placentas, while the estimated PMI 

were the same in central and peripheral regions for non-pesticide-exposed women. In this study, 

pesticide exposure was associated with higher placental maturity index, on average. Although 

not assessed explicitly, the implication of the finding is that pesticide exposure may affect 

nutrient transfer across the placenta by disrupting placental morphology. The implication of a 

lack of observed differences in PMI in peripheral areas of the placenta were not discussed in 

detail.

Study Review

The interpretation of the results of this study of pesticide exposure and placental maturity among 

pregnant women living in Chihuahua City, Mexico, is constrained by the small sample size, the 

cross sectional study design, and the imprecise nature of the definition of pesticide exposure. 
The rationale and specifics of participant selection and exclusion criteria were not detailed in the 

report. Authors excluded women with multiple pregnancies and women with prevalent diseases 

was most likely because both of these affect placental morphology, although this was not stated 

specifically. 

AChE enzyme activity was evaluated using conventional, and appropriate methods, in a single 

venous blood sample obtained at the time of delivery. The definition of pesticide exposure using 

a questionnaire and AChE activity likely resulted in misspecification of pesticide exposure that 

was non-differential with respect to PMI. Investigators did not correlate the two measures; 

however, AChE concentration in women residing in agricultural areas was lower than levels 

detected in women residing in urban areas (4.29 + 0.54 vs 5.26 + 1.07 U/mL, p = .01, 

respectively).

Though the processing of the placentas can affect the quality of the specimens obtained, it 

appears that the sampling and subsequent morphometric analysis was well conducted. The 

placentas assessed in the study were all processed in a similar and appropriate manner. 

Classification of placental maturity involves counting and evaluating the average diameter of 

terminal villi in an area of the slide selected by the researcher; although the multistep process is 

subject to errors, intraclass correlation coefficients in the range of 0.82-1.0 indicate a high degree 

of agreement across the two reviewers. Errors in assignment of the placental maturity index are 

likely to have been independent of exposure status, as the investigators conducting the PMI 

assessment were blinded to the pesticide exposure status of the women. 

The statistical methods were appropriate. Selection and assessment of covariates and subsequent 

model building was appropriate. The authors evaluated their final linear regression models for 

violation of OLS model assumptions (i.e. normality of residuals and homoscedasticity). They 

also appropriately corrected their hypothesis test results (i.e. p-values) for multiple comparisons. 

However, the modeling results were not adequately presented in the paper; they were not 

presented in tabular form, nor in figures. Confidence intervals were not presented, nor were the 

model results comparing PMI for peripheral placental regions between pesticide exposed and 

non-exposed women.

The generalizability and inference to be garnered from the study results is limited by the small 

sample size of the study, as well as the cross-sectional evaluation of the pesticide-PMI 

relationship. Due to sampling variability, the nine pesticide-exposed women may not be 

representative of pesticide-exposed women generally. Overall, this study provides some evidence 
consistent with the hypothesis that third-trimester OP pesticide exposure is associated with 

placental maturity, particular in central regions of the placenta. 
Study 19. Dabrowski et al. (2003)

Pesticide exposure and birthweight: An epidemiological study in Central Poland. Sławomir 

Dąbrowski, Wojciech Hanke, Kinga Polańska, Teresa Makowiec-Dąbrowska, and 

Wojciech Sobala. International Journal of Occupational Medicine and Environmental 

Health 16(1): 31-39, 2003.

Study Summary

In this report, Dabrowski et al. evaluate the relationship between maternal exposure to pesticides 

in the 1st and 2nd trimesters of pregnancy and low birth weight (LBW) in a case-control study set 

in the Łódź region of Poland. 

In order to investigate the prevalence of risk factors for poor pregnancy outcomes, the authors 

originally invited 389 Polish women who delivered at one of 25 maternity hospitals on a 

randomly selected set of 70 days between February 1998 and the end of December, 2000 to 

participate in their research project. Noting the high prevalence of pesticide exposure in the area, 

the investigators subsequently hypothesized that pesticide exposure may be associated with low 

birth weight in this rural population and constructed a case-control study to evaluate this 

hypothesis. To increase the number of cases, enrollment in the study was extended to mothers 

who delivered LBW infants in two maternity hospitals during an additional six month period 

(January, 2001 through June 2001). The study population was restricted to women involved in 

farm activities for at least seven days during their pregnancy. Other exclusion criteria included 

complicated pregnancies, maternal diabetes, hypertension, infectious diseases, and “other 

pathologies” that increase the risk of fetal growth restriction or preterm delivery. 

A questionnaire-guided interview was conducted by a physician 1-2 days after delivery in order 

to ascertain demographic information as well as occupational and other exposure histories from 

the mothers. During this interview, pesticide use in each trimester of pregnancy was reported by 

each participant. Although trimester-specific pesticide exposure was queried, the investigators 

found that most of the exposed women (83.6%) reported exposure in both trimesters; the authors 

therefore combined these two groups. Thus, self-reported pesticide exposure during the 1st and/or 

2nd trimesters was the primary exposure variable analyzed in this study. Confirmation of 

pesticide exposure was conducted 6-12 months after delivery, during which time an interviewer 

visited the husbands of the 49 women who had previously reported pesticide use on their farms 

during pregnancy. During this follow-up interview, specific active ingredients were identified for 
both occupational and residential exposures. Pesticide use most frequently reported included: 

phenoxyacetic acid derivatives, organophosphates, ureas, triazines, synthetic pyrethroids and Nphenylamides (anilides). Associations between specific pesticides and LBW were not estimated, 

however, reportedly due to the small number of participants reporting exposure to specific 

pesticides. 

LBW case status was conventionally defined as a child with a birth weight of less 2,500 grams. 

117 infants in the study met this definition, and the remaining 377 infants with birthweight ≥ 

2,500 grams served as controls. 

The authors ascertained covariate information during the questionnaire-based interview, and 

adjusted LBW models for maternal age, marital status, pre-pregnancy maternal weight, parity, 

maternal smoking, physical work during pregnancy, and place of residence.

In a univariate (unadjusted) model, the authors observed a greater than 5-fold increase in the 

odds of LBW among women exposed to pesticides during the 1st and 2nd trimesters, relative to 

women not exposed to pesticides during pregnancy (OR: 5.84; 95% CI: 3.61-9.47), the 

association was markedly attenuated, and not statistically significant, after adjustment for 

potential confounders (OR: 1.29; 95% CI: 0.63-2.65). The authors also constructed a multivariate 

linear model of infant birthweight and pesticide exposure, adjusted for other determinants of 

birth weight and pregnancy duration. Average birth weight of children of women reporting 

pesticide exposure was 100 grams lower than that of children born to women who did not report 

pesticide exposure. The authors also noted that women reporting pesticide exposure during the 

first or second trimester delivered, on average, half a week earlier than women without reported 

pesticide exposure. Average birth weight among women with organophosphate exposure was 35 

grams less than expected, although this difference was not statistically significant (p=0.19).

Study Review

This investigation was originally designed to evaluate the prevalence of risk factors for adverse 

birth outcomes in a population of pregnant women living in a rural region of Central Poland. To 

conduct this investigation, the authors attempted to recruit all women giving birth on randomly 

selected days. In this manner, they conducted a population-based study. They then adapted and 

augmented the study in order to evaluate a specific hypothesis regarding pesticide exposure 

during early pregnancy and (low) birth weight. The design was thus a bit confused, with the 
authors switching between methodologic approaches appropriate for cross-sectional retrospective 

cohort study designs, and those appropriate for a case-control study. 

The recruitment of study subjects occurred in two distinct phases and, importantly, from two 

different source populations. Pregnant mothers and their children who participated in the initial 

implementation of the study were recruited from 25 hospitals, and included all women delivering 

on randomly selected days. The second set of women were recruited during a later time period, 

from two hospitals, and included only women delivering low birth weight infants. The 

inclusion/exclusion criteria were appropriate, given the study’s objectives. 

The pesticide (and covariate) exposure assessment occurred by means of a questionnaire-guided 

interview, conducted by a physician 1-2 days after the delivery of the child. The investigators 

attempted to validate these self-reported exposures by visiting the homes of the mothers, albeit 6-

12 months after delivery (i.e. up to 18 months after the relevant time window of exposure – the 

first and second trimesters of pregnancy). Considerable misclassification of pesticide exposure is 

therefore likely to have occurred, both due to the retrospective self-recall of exposure by the 

mothers, and potentially complicated by the timing of the exposure ascertainment with respect to 

the birth of the child. No biomarkers of pesticide exposure were evaluated in this study.

The assessment of the birth weight and LBW outcomes based on medical records was 

straightforward, and was likely to have been conducted without substantial error. 

A small degree of residual confounding is likely in this study. The covariates included in 

multivariate models appear to have been appropriate, i.e. determinants of birth weight that may 

be associated with pesticide exposure, although covariate selection and model building processes 

were not discussed in detail. The authors included an analysis adjusting the association between 

first or second trimester pesticide exposure and birth weight for length of gestation; the 

association between pesticide exposure and (lower) birth weight persisted, though the association 

was attenuated. 

Several biases are likely to have influenced the associations being evaluated in this study. The 

controls in this study (women who delivered children with birth weights ≥ 2,500 grams) were 

recruited only during the first phase of the study. While LBW cases were recruited during both 

periods. Notably, LBW cases enrolled during the case-augmentation portion of the study were 

recruited from different areas than the controls. As such, it is possible that the prevalence of 

pesticide exposures among the control participants was not representative of the exposure 
distribution in the populations that gave rise to the cases. In fact, the authors noted that 

participants were recruited from “different source populations with different prevalence of 

pesticide exposure.” Selection bias is thus likely to have occurred, to the extent that the controls 

did not reflect pesticide exposure in the study base. In an attempt to offset this potential bias, the 

authors included place of residence as a covariate in their multivariate models. Nonetheless, 

some degree of selection bias in this study is probable. The direction and magnitude of this bias 

are not easily determined, could be substantial, and were not discussed by the authors.

Information bias due to differential errors in the self-reporting of pesticide exposure during 

pregnancy was also possible, as the exposure was ascertained by maternal self-report shortly 

after birth (mothers were likely aware of the LBW status when recalling exposures). The attempt 

by the investigators to validate self-reported pesticide exposures is a potential strength of the 

study, though the validation was conducted up to a year after the birth and 1-1.5 years after the 

exposure-time window of interest. 

Therefore, it is unclear that the sampling of cases and controls was independent of exposure 

status. The statistical analysis included both linear regression, as might be appropriate in a cross 

sectional or cohort study, and logistic regression which is appropriate for analysis of case-control 

study data, in addition to data from cross-sectional and cohort designs. 

The sample size and corresponding statistical power of this study was adequate, although the 

investigators were compelled to expand enrollment in the study to increase the number of 

participating cases, at the potential expense validity (i.e., increasing the potential for selection 

bias, as discussed above). 

The study results, if valid, are likely generalizable to populations of rural families and farmers 

exposed to similar farm activities and risk factors as those participating in the study. The 

contribution of this study to the overall evidence of pesticide exposure during pregnancy on 

adverse birth outcomes, LBW in particular, is limited by the likely effects of selection bias and 

(differential) information bias. The study was largely null, in that a statistically significant 

increase in the odds of LBW, after adjusting for length of gestation, was not observed in relation 

to self-reported pesticide exposure during early pregnancy. It is difficult to determine from the 

report whether the true association (in the absence of residual confounding, information bias, and 

selection bias) is larger or smaller than the small observed increase in the odds of LBW among 

the pesticide exposed participants cannot be determined empirically.
Study 20. Grandjean et al. (2006), Harari et al. (2010)

• 2006. Pesticide exposure and stunting as independent predictors of neurobehavioral 

deficits in Ecuadorian school children. Philippe Grandjean, Raul Harari, MD, Dana B. 

Barr, PhD, Frodi Debes. Pediatrics 117(3):e546-e556.

• 2010. Neurobehavioral Deficits and Increased Blood Pressure in School-Age Children 

Prenatally Exposed to Pesticides. Raul Harari, Jordi Julvez, Katsuyuki Murata, Dana 

Barr, David C. Bellinger, Frodi Debes, and Philippe Grandjean. Environmental Health 

Perspectives 118(6): 890-896.

Study Summary

In these reports, Grandjean et al. evaluate the relationship between reported prenatal and 

estimated recent organophosphate pesticide (OP) exposure, as well as a measure of physiologic 

stunting, in relation to a large set of neurobehavioral, clinical, and anthropomorphic outcomes 

among school-age children participating in a cross-sectional study in Tabacundo, Ecuador. 

Children in the lowest two grades of one of the two elementary schools in Tabacundo were 

invited to participate in the study. All eligible children were allowed to participate in the 

examinations: In Grandjean (2006) report, 1 child with an acute respiratory infection, 3 children 

with prevalent (unspecified) clinical abnormalities, and 3 children older than 9 years of age were 

excluded from the analysis, resulting in an analytic subset of 72 participating children. In the 

Harari (2010) report, 3 children were excluded from the study because 1 child had clinical 

history of meningitis and 2 were older than 9 years of age, resulting in an analytic subset of 84 

participating children. 

Examinations, scheduled to be completed in 2 hours, were conducted at a nearby health clinic, 

and included the neurobehavioral testing and clinical assessment. To ascertain data on 

occupational exposure history, social and demographic characteristics, the child’s medical 

history and current health status, a 150-item questionnaire was administered to the mothers at the 

time of the examination. Mothers were not aware of the neurobehavioral and clinical 

examination results at the time they completed the questionnaire. A public health and 

occupational medicine specialist blinded to the children’s’ clinical statuses reviewed the 

mothers’ completed questionnaires and scored their responses for potential maternal pesticide 

exposure during pregnancy. In Grandjean (2006), prenatal exposure to pesticides was determined 
by mothers’ self-reporting and treated as a dichotomous (yes/no) variable. In Harari (2010), 

prenatal exposure to pesticide was separated into three categories (no parental exposure, paternal 

exposure only, and maternal exposure irrespective of paternal status).

Spot urine samples were collected from the children at the time of the examination in order to 

quantify urinary OP metabolites as indicators of recent OP pesticide exposure. Collected samples 

were shipped on dry ice to the CDC in Atlanta, USA, where they were analyzed for six 

dialkylphosphate (DAP) metabolites - three dimethylphosphate (DMP) metabolites 

(dimethylphosphate, dimethyldithiophosphate, dimethylthiophosphate) and three 

diethylphosphate (DEP) metabolites (diethylphosphate, diethyldithiophosphate, 

diethylthiophosphate) - using gas chromatography–tandem mass spectrometry. The level of 

detection was 0.3 μg/L for dimethylphosphate and dimethylthiophosphate and 0.1 μg/L for all of 

the other DAP metabolites. Urinary DAP metabolite concentrations were creatinine-adjusted and 

log-transformed; children’s individual exposures were then estimated using calculated daily 

creatinine-excretion levels. Metabolite excretion rates below the lower LOD were assigned a rate 

of 0.05 nmol/kg per day. Molar concentrations of the DMP metabolites were summed together, 

as were the DEP metabolites, to create composite indicators of recent pesticide exposure. Recent 

OP pesticide exposure was then defined as a dichotomous variable by assuming that summed 

DMP or DEP excretion rates greater than 1 nmol/kg per day were indicative of recent OP 

pesticide exposure, based on a reference dose of 0.3 μg/kg per day, and a molecular weight of 

approximately 300 g/mol. 

In the Harari study, in addition to a sport urine sample, a blood sample (one drop from finger 

prick) was obtained to measure erythrocyte acetylcholine esterase (AChE) activity using Testmate equipment and test solutions from EQM Research, Inc. (Cincinnati, OH, USA). 

Anthropometric measurements and clinical outcomes, including age, height, weight, head 

circumference, hematocrit, acetylcholinesterase, and blood pressure were taken during the 

physical examination.

Neurobehavioral status was assessed on several domains, using multiple instruments, including 

intelligence (the Wechsler Intelligence Scale for Children-Revised Digit Span), simple reaction 

time (Catsys equipment), motor coordination (Santa Ana Form Board), and visuospatial and 

visuoconstructional function (Stanford-Binet Copying Test). In the Harari study, attention 

(Conners’s Kiddie Continuous Performance Test (K-CPT, version 5) and general intelligence 

(Raven’s Colored Progressive Matrices) were also included.

Granjean et al. (2010)

Tests of differences in mean outcomes (i.e., t-tests) and their non-parametric equivalents (i.e., 

comparison of difference in medians outcomes, Mann-Whitney tests), and multivariate linear 

regression were used to compare children determined to have had prenatal pesticide exposure 

due to their mother’s occupation to those determined not to have had prenatal pesticide exposure. 

A similar set of analyses was conducted comparing those defined as having had recent exposure 

to OP pesticides to those without recent exposure, based on DAP metabolite urinary excretion 

rates. For their multivariate regression analysis, the investigators initially identified potential 

confounders by a priori consideration of factors which may influence nervous system 

development in this Ecuadorian community. Factors observed to be statistically associated with 

pesticide exposure in this population were included in multivariate regression analyses. Child’s 

age and sex were obligatory covariates in the models of neurobehavioral outcomes; body weight 

was a mandatory covariate in the blood pressure models. Trauma, other injury, and meningitis in 

the past medical history were considered as a joint and mandatory covariate of the 

neuropsychological outcomes, along with maternal education and an indicator of current 

nutrition. Socioeconomic variables considered by the investigators included maternal race, 

housing type, presence of running water in the home, sewage drainage, number of siblings, and 

access to health care. Maternal smoking and alcohol use during pregnancy was also considered 

as potential confounders.

Based on maternal self-report of occupational exposure to pesticides during pregnancy, thirtyseven children were considered to have had prenatal pesticide exposure, and thirty-five were 

considered to not have had prenatal pesticide exposure. Similarly, Grandjean et al. reported over 

twenty associations between prenatal pesticide exposure and neurobehavioral or clinical 

outcomes, and found very little evidence of significant or substantial associations; the children 

deemed to have been prenatally exposed and those deemed not exposed to pesticides were quite 

similar to each other in most respects. Prenatal pesticide exposure was associated with a higher 

systolic blood pressure (though blood pressure did not differ significantly by recent pesticide 

exposure status). Score on the Stanford-Binet copying test was lower for copying designs among 

children with prenatal pesticide exposure, compared to the reference group with no reported 

prenatal exposure to pesticides. 

Anthropometric measures were quite similar comparing the children classified as exposed to 

those not unexposed to prenatal pesticides children.
Recent pesticide exposure, as indicated by increased total DEP and DMP excretion was

associated only with a statistically significant increase in simple reaction time. 

The investigators examined associations between the neurobehavioral and clinical outcomes 

among subgroups of children defined as having, or not having stunted growth. Systolic blood 

pressure was highest among the children with both stunting and history of prenatal pesticide 

exposure. The authors constructed multivariate models including an interaction term for the joint 

effect of pesticide exposure and stunting, though the results were not presented in tabular form. 

In no instance were the interaction variables statistically significant. 

Grandjean et al. reported an association between prenatal pesticide exposures and increased 

systolic blood pressure in this population of 2nd and 3rd grade schoolchildren living in northern 

Ecuador. On average, systolic blood pressure was significantly, higher, by 4.6mmHg, among 

those with prenatal pesticide exposure, compared to those without prenatal pesticide exposure 

(p=0.02). Recent exposure to OP pesticides was significantly associated only with a slight 

increase in mean reaction time of 74 milliseconds, on average (p=0.01). However, with respect to 

most of the neurobehavioral and clinical outcomes, the children identified as having prenatal 

exposure to pesticides due to their mother’s occupation, and children identified as having recent 

OP pesticide exposure as defined by urinary excretion of DAP metabolites were similar to their 

counterparts classified as non-exposed. No other significant differences in the clinical and 

neurobehavioral outcomes were observed by reported (maternal) occupational exposure to 

pesticides during pregnancy or recent pesticide exposure. These results provide weak evidence of 

a relationship between prenatal OP pesticide use and subsequent neurobehavioral and clinical 

impairment at age 7-9 years of age.

Harari et al. (2010)

In the Harari study, 35 children were exposed to pesticides during pregnancy via maternal 

occupational exposure, 23 children had indirect exposure from paternal work, and 22 children 

had detectable current exposure irrespective of their prenatal exposure status. Only children with 

prenatal exposure from maternal greenhouse work showed consistent deficits after covariate 

adjustment, which included stunting and socioeconomic variables. Exposure-related deficits 

were the strongest for motor speed (Finger Tapping Task), motor coordination (Santa Ana Form 

Board), visuospatial performance (Stanford-Binet Copying Test), and visual memory (StanfordBinet Copying Recall Test). These associations corresponded to a developmental delay of 1.5–2 

years. Prenatal pesticide exposure was also significantly associated with an average increase of 

3.6 mmHg in systolic blood pressure and a slight decrease in body mass index of 1.1 kg/m2. The 
investigators initially identified potential confounders by a priori consideration of factors which 

may influence nervous system development in this Ecuadorian community. Factors observed to 

be statistically associated with pesticide exposure in this population were included in the 

analyses. Child’s age, sex, and school grade were obligatory covariates in the models of 

neurobehavioral outcomes; body weight was a mandatory covariate in the blood pressure 

models. Other potential cofactors were child’s trauma, other injury, meningitis in the past 

medical history, current hematocrit, having repeated one school grade, parental education 

(primary school only or above), current nutrition (number of meals per day), and sociodemographic covariates that comprised race, housing (traditional or other), running water at 

home, house connected to a central sewer line, number of siblings, marital status, maternal 

access to health care (i.e., childbirth taking place at home or at the hospital), and maternal 

smoking and alcohol use during pregnancy.

Reaction time (milliseconds) on the CPT was the only neuropsychological outcome on which the 

scores of children with current exposure and no exposure appeared to differ, although only with a 

borderline statistical significance (p = 0.098). Neurophysiologic measurements, including evoked 

potential latencies and heart variability, were not associated with either prenatal or current 

exposures.

Thus, the authors conclude that that prenatal exposure to pesticide even at levels not producing 

adverse health outcomes in the mother can cause lasting adverse effects on brain development in 

children contributing to a “silent pandemic” of developmental neurotoxicity.

Study Review

Grandjean et al. (2006)

This cross-sectional study of prenatal and recent pesticide exposure and subsequent 

neurobehavioral and clinical status of children at age 7-9 years of age in a town in northern 

Ecuador has substantial limitations, the most serious of which relate to the assessment and 

classification of exposure. Correspondingly, inferences from the results of this investigation are 

constrained by these limitations in the study design and exposure assessment methodology. 

The authors employed a reasonable set of exclusion criteria (having other diseases or being older 

than age 9 years). The investigators cross-sectionally collected maternal and child covariate 

information. 
Selection bias is unlikely to have occurred in the study. 

Errors in classification of prenatal pesticide exposure status are likely to have occurred. Prenatal 

pesticide exposure was evaluated by maternal self-report at the time of the clinical and 

neurobehavioral exam (i.e. when the children where in 2nd or 3rd grade). Although 37 children 

were defined as having prenatal pesticide exposure due to the mother's occupation, none of the 

mothers had worked as a pesticide applicator; all mothers reported that they had followed normal 

safety precautions in handling of pesticides, and none of the participating mothers reported 

having been poisoned by pesticides. Furthermore, paternal occupation and pesticide exposure 

was not a consideration in characterizing prenatal pesticide exposure status, although the authors 

noted that 19 fathers of the children considered to have prenatal exposure and 16 fathers of the 

children considered not prenatally exposed to pesticides had worked in floriculture or agriculture 

during the pregnancy. Recall of symptoms potentially associated with pesticides was “weak, 

nonspecific, and without clear association to occupational exposures.” Thus, it is probable that 

children both of mothers classified as exposed, and mothers classified as not exposed may have 

had very similar prenatal pesticide exposure profiles. As a consequence of these sources of nondifferential exposure misclassification, observed associations with clinical and neurobehavioral 

outcomes are likely biased toward the null. Potential for differential exposure misclassification is 

also possible because, although mothers were blinded to the clinical and neurobehavioral test 

results, they were likely aware of the neurobehavioral status of their children, and it is plausible 

that this knowledge of outcome status may have impacted the questionnaire-guided recall of 

prenatal pesticide exposure in this cross-sectional study, although there are no data to 

substantiate this possibility.

The urine sampling and quantification of pesticide metabolites in the children’s urine samples 

appears to have been conducted appropriately. The use of non-specific biomarkers of prenatal 

OP pesticide exposure, as were assessed in this study, are likely more objective, sensitive, and 

likely also more accurate and reliable indicators of pesticide exposure, relative to exposure 

assessment methodologies that rely on self-report. However, to the extent that OP pesticide 

exposure is the true exposure of interest, the assessment of non-specific organophosphate 

pesticide metabolites in a single maternal sample of urine is a primary potential source of 

exposure measurement error. Urinalysis of non-specific OP metabolites, as was conducted in this 

study, is a marker only of very recent exposure, i.e., in the 24 to 48 hour period prior to the 

collection of the urine sample (Walker & Nidiry, 2002). The single measurement of urinary DAP 

metabolite levels may reflect exposure not only to OP parent compounds, but also to potentially 
nontoxic pre-formed metabolites in the environment. The use of a single urine sample to estimate 

maternal OP pesticide exposure is likely to have resulted in an attenuation of associations, 

relative to those that would have been observed had the investigators used a time-integrated 

marker of OP pesticide exposure. Interestingly, children classified as not having had prenatal 

pesticide exposure had slightly higher current exposure levels than those classified as having had 

prenatal pesticide exposure. 

On the whole, the investigators handling of confounding resulted was reasonable. Confounders 

were identified from the authors’ a priori consideration of determinants of nervous system 

development in this target population. Age and sex were included as covariates in models for all 

clinical and neurobehavioral outcomes. The study population was relatively homogeneous with 

respect to medical history and most other characteristics evaluated by the authors. This 

homogeneity – a weakness of the study with respect to pesticide exposure profile – is a strength 

of the study in that is likely that confounding was, to some extent, controlled by design. 

The statistical analysis was appropriate largely appropriate, although the authors did not include 

the results of multivariate analysis in the report, except those for two outcomes (blood pressure 

and Stanford-Binet Copying Scores) for which statistically significant associations were 

observed in univariate comparisons of means between children with, and without, prenatal 

pesticide exposure. Also, the authors evaluated a large number of associations between pesticide 

exposure and clinical and neurobehavioral outcomes; as a result, false positives due to multiple 

comparisons are to be expected, though the authors did not adjust the results of their hypothesis 

tests for multiple comparisons. 

The investigators evaluated a priori hypotheses regarding effect modification of the association 

between OP pesticide exposure and neurobehavioral and clinical outcomes by “stunted” growth. 

However, the small sample size limited the statistical power of the tests of these hypotheses; the 

authors did not report observing any statistically significant effect modification (as evidenced by 

interaction term p-values in multivariate models). The results of this model were not presented in 

tabular form.

The tests and tools used to assess neurobehavioral status are easy-to implement, and rapidly 

conducted screening tools. It is possible that these tools do not have the sensitivity to resolve 

subtle differences caused by pesticide exposure, even if such effects were in fact present.
The authors rightly conclude their paper by stating that a large, longitudinal study with repeated 

measurement of urinary biomarkers of OP pesticide exposure is needed to further examine the 

relationship between OP pesticide exposure and child neurodevelopment in this population. Due 

to limitations of the study design and exposure assessment, this largely null study provides little 

evidence supporting the hypothesis that prenatal (or recent) OP pesticide exposure is associated 

with neurodevelopment in children attending 2nd or 3rd grade.

Harari et al. (2010)

Researchers examined the child neurobehavioral function and blood pressure in school-age 

children prenatally exposed to pesticides. The review comments above apply to this report. 

Unlike the Grandjean study, paternal occupation and pesticide exposure was considered in 

characterizing prenatal pesticide exposure status. However, errors in classification of prenatal 

pesticide exposure status are likely to have occurred since it was based on the maternal selfreport and although 35 children were defined as having prenatal pesticide exposure due to the 

mother's occupation, none of the mothers reported any adverse effects that could be linked to 

pesticide exposures in the greenhouses. The consequences of this misclassification and mothers 

likely being aware of the neurobehavioral status of their children are discussed under the 

Grandjean study. 

The child current exposure to pesticides was ascertained by analyzing a spot urine sample for 

pesticide metabolites and blood to measure erythrocyte acetylcholine esterase (AChE) activity. 

The strengths and weaknesses of a spot urine sample for exposure to OP pesticide are described 

under Grandjean study. But unlike Grandjean study, this study also included AChE measurement 

which represents a longer-term average exposure. Interestingly, current exposure, whether based 

on individual metabolites or groups of metabolites, did not differ between children with and 

without prenatal exposure.

The instruments used for blood pressure measurements and neurophsychologic measures seem 

appropriate. Based on the authors, the instruments used for neurophsychologic measures were 

validated to avoid cross-cultural influences.

On the whole, the investigator’s approach to evaluating and adjusting for confounding were 

prudent as discussed above. This study included child’s age, sex, and school grade as covariates 

in models for all clinical and neurobehavioral outcomes. School grade was not included as a 
covariate in the Grandjean study. The small sample size reduces the statistical power of the 

study.

Due to limitations of the study design and exposure assessment, a large longitudinal study with 

repeated measurement of urinary biomarkers of OP pesticide exposure is needed to further 

confirm the findings of this study.
References cited

Walker, B. Jr., & Nidiry, J. (2002). Current concepts: Organophosphate toxicity. Inhalation 

Toxicology, 14, 975–990.
Study 21. Kofman et al. (2006)

Motor Inhibition and Learning Impairments in School-Aged Children Following Exposure 

to Organophosphate Pesticides in Infancy. Ora Kofman, Andrea Berger, Ali Massarwa, 

Alon Friedman, and Abed Abu Jaffar. Pediatric Research. 60:88-92, 2006.

Study Summary 

Kofman et al. conducted a study to investigate the relationship between organophosphate 

pesticide exposure during infancy and child neurodevelopment in school aged children who were 

6 to 12 years of age at the time of study. In this study, authors report a neuropsychological 

assessment of healthy school-aged children, who had been hospitalized in infancy (before age 3) 

following exposure to organophosphate pesticides. They were also compared with children 

exposed to other toxins such as kerosene, and age- and sex-matched non-exposed children.

All children enrolled in this study (total of 52) were native speakers of Arabic and from the 

Bedouin population of the Negev region of Israel, attending regular schools. The exposed 

children were located after screening hospital records of children who were hospitalized for 

acute poisoning in Soroka Medical Center and treated with standard emergency procedures. 

Exposed children were further divided into two categories; exposed to organophosphates and 

exposed to kerosene or similar substances such as paint thinner (referred to as the kerosene 

group).Children from the unexposed control group were recruited through friends and relatives 

of the exposed children in the same community, matched according to age and sex. 

OP poisoning was confirmed by low serum butyrylcholinesterase activity in all but one child, 

who was reported to have inhaled insecticide. The mean butyrylcholinesterase level for the 

children exposed to OP poisoning was (Mean ± SD) 3,631 ± 3,701, and the median value was 

1,769 IU/Lit. (normal range ± 6,100 –15,000 IU/Lit).

The outcome, child neurodevelopment, was assessed using neuropsychological evaluation 

conducted by the examiners who were native speakers of Arabic, B.A. or M.A. level 

psychologists who had experience working in the educational psychology service of the Negev 

Bedouin community. Evaluation included long-term verbal memory test, working memory and 

attention span test, and inhibitory control/motor inhibition test. First they performed trials one 

through seven of the long-term verbal memory test, followed by the Statue, Knock Tap, Digit 

Span and Corsi Blocks tests. Last, they performed trials eight and nine of the memory test 
(Delayed recall of List A, and Recognition). The list of words for long-term verbal memory test 

was based on an Arabic translation of the word list in the NEPSY (20), with some culturerelevant changes for a desert-dwelling community. The children were tested individually in a 

quiet room. Some of the children from all groups were tested within the local medical clinic in 

Rahat and the others were tested in their homes. Each child was tested on the same day and in the 

same place as his matched control.

Parents were given a structured interview by the testing psychologist, asking if the child was on 

medication or had chronic health problems, if they had been hospitalized since the index 

incident, had repeated a grade, had trouble in any particular subject at school, or had conduct 

problems in school. In addition, questions concerning the child’s pastimes and issues not related 

to learning problems were included and the child’s general demeanor was noted. The interview 

was not meant to be diagnostic, but was intended to alert to overt signs of serious developmental 

delay. 

Confounders such as age, sex, background (cultural and demographic) between the exposed and 

unexposed groups were matched. Data analysis showed that there was no difference between the 

exposed and unexposed groups based on age and sex, confirming that the matching was 

appropriate. Family rearing practices and perinatal complications were not included in the study 

but the fact that the exposed and unexposed groups were chosen from similar backgrounds 

mitigates the likelihood that these and other uncontrolled factors contributed to the differences 

between the groups.

Statistical analyses of the relationship between exposure to organophosphate pesticides in 

infancy and motor inhibition and learning impairments in school were conducted using 

ANCOVA. 

The structured interview did not reveal any conduct disorders, health or academic problems. The 

WISC-R scores were compared between the seven children who had been poisoned (three 

kerosene, four OP) and the matched comparison group. No differences were found between these 

exposed children and their matched controls. Analysis of the verbal memory indicated that both

groups of children who had been exposed to toxic substances were impaired in verbal learning. 

No difference between the groups was found for the recognition test or the delayed recall test. 

No differences between the exposed children and controls were found in the Digit Span and 

Corsi Blocks test. The effects of poison exposure appeared only in the repeated free recall but 
not in the delayed or recognition tasks, suggesting that the children did eventually learn the list, 

even though they had trouble retrieving words in the acquisition phase.

The authors concluded that although the children seem to have overcome the acute one-time 

exposure and they all attend regular schools, a finer assessment of specific cognitive abilities 

indicates impairment in the verbal learning and motor inhibition tasks in the exposed compared 

with matched control children. The long-term effects of OP poisoning on cognitive behavior in 

children suggests that subtle behavioral changes may occur, even if they go undetected in school.

Study Review

This retrospective cohort study of pesticide exposure in infancy and subsequent neurobehavioral 

status of children aged 6 to 12 in Negev region of Israel has multiple limitations, the most serious 

of which is sample size. 

The time period when the study was conducted is not provided in the article. This study was 

limited to children aged 6 to 12 at the time of study, who were victims of poisoning before age 

three. There is no discussion on how the participant age was decided but the age range seems to 

be appropriate for the assessment of neurodevelopment in children. This is because in another 

similar study (Oulhote et al, 2013), that examined the association between exposure to 

organophosphate and pyrethroid pesticides, and parentally reported behavioral problems in 

children, the participants were children aged 6-11 years of age. Based on the author of that study, 

the analysis was limited to these children because information on early-life factors important for 

neurodevelopment was available only for children in this age range. 

The fact that both the exposed (exposed to OP and kerosene) and unexposed groups were 

matched and chosen from similar backgrounds mitigates the likelihood that other factors (family 

rearing practices, environmental factors etc.) contributed to the differences between the groups. 

However, because of the life style of this community, psychologists who administered the tests 

were blind to the type of poisoning (OP or kerosene) but knew which children were exposed. 

This may have introduced some bias in the study.

Exposed population that was divided into two groups (exposed to OP and exposed to Kerosene) 

had its corresponding control group. It is not clear from the article if both unexposed groups 

(unexposed to OP and unexposed to Kerosene) were not exposed to either OP or kerosene. For 

example, there were 9 participants who were exposed to OP and 9 participants who were not 
exposed to OP pesticides. However, it is not clear from the article whether or not the participants 

who were not exposed to OP pesticides were also not exposed to kerosene. 

Errors in classification of pesticide exposure are unlikely to have occurred since OP poisoning 

was confirmed by the hospital records. However, as mentioned above, sample size was small 

(n=9) for both the exposed and control groups for OP. This low sample size reduces the 

statistical power of this study. The statistical analysis (difference in means) used to assess the 

associations between the exposure and neurodevelopment were appropriate given the small 

sample size.

The methods used for neuropsychological evaluation seems appropriate. Outcome of the 

exposure was assessed by the neuropsychological evaluation of the children and by conducting 

structured interview of the parents. Errors in outcome assessment were minimized as the 

psychologists were qualified individuals and had experience working in the educational 

psychology service of the Negev Bedouin population, language and cultural differences were 

taken into considerations when administering the tests, and each child was tested on the same 

day and in the same place as his matched control.

Overall, the study showed that there was no difference between the exposed and control groups. 

Only a finer assessment showed differences between exposed and control groups in regards to 

verbal learning and motor inhibition. The article suggests that these associations were significant 

but it is not clear if the same will be true if the study is conducted with a large sample size.

Inferences from the results of this study are constrained by the limitations in sample size and also 

because of the culture of the study population which is specific to their community. 

The authors rightly conclude their paper by stating that a large long-term follow-up prospective 

study including a more specific battery of tests focusing on memory and regulation of behavior is 

needed. 

References cited

Urinary Metabolites of Organophosphate and Pyrethroid Pesticides and Behavioral Problems in 

Canadian Children. Youssef Oulhote and Maryse F. Bouchard; Environmental Health 

Perspectives. 121:1378-1384 (2013).

Study 22. Koutroulakis et al. (2014)

Dialkyl phosphates in amniotic fluid as a biomarker of fetal exposure to organophosphates 

in Crete, Greece; association with fetal growth. D. Koutroulakis, S. Sifakis, M.N. 

Tzatzarakis, A.K. Alegakis, E. Theodoropoulou, M.P. Kavvalakis, D. Kappou, A.M. 

Tsatsakis. Reproductive Toxicology 46 (2014) 98–105.

Study Summary

In this prospective cohort study by Koutroulakis et al., the authors evaluate fetal exposure to OP 

pesticides by measuring the non-specific dialkyl-phosphate metabolites (DAPs) in a single 

amniotic fluid (AF) sample, and examine the potential association between prenatal exposure 

and fetal growth in pregnant women living in Crete, Greece.

The study population consisted of 415 women with singleton pregnancies, who were permanent 

residents of Crete for at least two years. Women were recruited at the time of referral for 

amniocentesis to the Fetal-Maternal Unit, Department of Obstetrics and Gynecology, University 

Hospital of Heraklion, Crete, Greece. The indications for referral included increased risk for 

chromosomal abnormalities (based on advanced maternal age or the results of the first trimester 

combined test for fetal aneuploidies, or sonographically detected markers or abnormalities 

between 18 and 22 weeks of gestation), suspicion of genetic syndromes or increased risk for 

single gene dis-orders (based on history or sonographic findings), abnormal fetal growth, and 

suspicion of congenital infection. Mean maternal age was 32.7 (SD = 5.7) and mean gestational 

age at amniocentesis was 18.5 weeks (SD = 2.5).

Maternal/fetal exposure to organophosphate pesticides was assessed by measurement of 

organophosphate dialkyl phosphates in a single AF collected at either 16th or 20th weeks of 

gestation. The dialkyl phosphates metabolites (DAPs) measured were dimethylphosphate, 

dimethyldithiophosphate, dimethylthiophosphate (DMPs), diethylphosphate, 

diethyldithiophosphate, and diethylthiophosphate (DEPs). Total DAPs, DMPs, and DEPs were 

available for 406, 298, and 401women, respectively. Quantification of organophosphate 

metabolites was done by using gas chromatography mass spectrometry. In addition, the 

participants were asked to complete a detailed questionnaire about their medical history, 

demographic data, socioeconomic status, occupational and residential status and exposure to 

other potentially embryotoxic factors. 
The association between the levels of ΣDMPs, ΣDEPs and ΣDAPs and birth weight and head 

circumference was evaluated by using multiple linear regression models. The association was 

adjusted for the confounding effect of neonatal gender, maternal age, agricultural activities, and 

gestational age at amniocentesis. The authors found that ΣDMP was positively related with birth 

weight centile and the remaining DAPs were not correlated with biometric indices. Similar 

results were found after missing data imputation with LOD/2 values. 

Based on the results, the authors concluded that DAPs in AF may be considered as a potential 

biomarker for the assessment of fetal exposure to OP. The findings add to the growing body of 

literature regarding the sensitivity of developing fetus to OP pesticide exposure. 

Study Review

This was a well-conducted but poorly written study. The aim of this study was first, to determine 

the presence of OP non-specific metabolites (DAPs) in amniotic fluid (AF) as an index for in 

utero exposure to these contaminants and second, to evaluate any potential link between prenatal 

exposure to OPs and fetal growth. The study was conducted in a population of women who were 

identified as having high risk pregnancies. According to the article “82.5% of the amniocenteses 

were carried out between 16th and 20th weeks of gestation and an additional volume of 8–10 ml 

of AF was obtained during each procedure” which suggests additional burden and risk was 

placed on the participants even though the participants consented for the study and the ethics 

committee of the University Hospital of Crete approved the study’s protocol. The analytic 

methods, questionnaire, analytic approach, and statistical analysis were appropriate. However, it 

is unclear how the outcome (birth weight and head circumference) information was obtained and 

the rationale for confounder selection. 

This study had a novel biomarker (AF) for exposure assessment. The exposure measurement 

methods employed for the measurements of OP pesticides in AF were appropriate and are 

defined in the study. However, there are not many literatures on using AF as a potential 

biomarker. According to the author, there is only one study prior to this study that evaluated OP 

metabolite levels in AF. Therefore, comparing the exposure measurements in AF against known 

biomarker (e.g., OP metabolite levels in urine) would have validated AF as the potential 

biomarker for OP exposure. 
The authors do not provide information on how the data on birth weight and head circumference 

was assessed. There are also some ethical concerns with the large volume of amniotic fluid 

collected. 

Results of multiple linear regressions to evaluate the relationships between ΣDMPs, ΣDEPs and 

ΣDAPs levels by biometric indices after adjustment for maternal age, agricultural activities, 

gestational week at sampling, and neonatal gender showed that there is a positive linear 

association between ΣDMP and birth weight centile, which is contrary to what other studies have 

shown, i.e., higher exposure to OP metabolite results in lower birth weight. In addition, the 

rationale for confounder selections is not defined in the study. It may be worthwhile to note that 

the smoking status of the participants (48.2% of participants smoked before pregnancy and 

31.9% of participants smoked during pregnancies), participants being women with high risk 

pregnancies (reason for referral for amniocentesis), gestational diabetes (information not 

available), PON1 enzyme activity in the fetuses (information not available) could also have 

contributed to the outcome. 

The statistical analysis appears to be appropriate. The large sample size (n = 415) compared to 

other similar studies increased the statistical power.

The authors conclude that DAPs in AF may be considered as a potential biomarker for the 

assessment of fetal exposure to OPs and sum levels of DMPs appear to be associated with birth 

weight. The authors do point out the need for further studies to determine the persistence of these 

associations and their generalizability to other populations and to address concerns about the 

potential health effects of pre- and postnatal exposure to pesticides and develop suitable 

regulatory reference doses.
Study 23. Lizardi et al. (2008)

The effects of organophosphate pesticide exposure on Hispanic children’s cognitive and 

behavioral functioning. Patricia Sanchez Lizardi, PHD, Mary Kay O’Rourke, PHD, and 

Richard J. Morris, PHD. Journal of Pediatric Psychology 33(1): 91–101, 2008.

Study Summary

Lizardi et al. selected a subset of children from the Children Pesticide Survey (CPS) of southern 

Arizona (O’Rourke et al., 2000) to evaluate whether recent organophosphate (OP) pesticide 

exposure affects the cognitive and behavioral functioning of Hispanic children (average age=7 

years old) living in an agricultural community in Southern Arizona. The CPS, conducted in 

1998-2000, was itself built upon two studies previously conducted in Yuma, Arizona: the 

National Human Exposure Assessment Survey and the Arizona Border Survey. Child 

participants who had provided a urine sample during the screening stage of the CPS study were 

eligible to participate in the present study. The data for this investigation was collected in 2002.

A first-void urine sample was collected from each child on the day of the neurobehavioral 

assessments. Gas chromatography with flame photometric detection (GC-FPD) was used to 

estimate non-specific OP metabolites (dialkylphosphate) concentrations. These included 

dimethylphosphate (DMP), dimethylphosphorothioate, dimethylphosphorodithioate, 

diethylphosphate, diethylphosphorothioate, diethylphosphorodithioate. The sum of the six OP 

metabolite concentrations was used for all data analyses. Absence of recent OP pesticide 

exposure was defined as having urinary metabolite concentrations below the level of detection 

limit (25 μg/l).

In the original CPS study, children were selected for participation based on the presence or 

absence of OP pesticide metabolites in urine samples collected during the screening phase. 

However, all of the children (n=48) from the original PCS study (both exposed and non-exposed 

to pesticides) that participated in the current study had detectable DMP levels in urine samples 

provided in 2002. The authors did observe that the exposed group, as defined in the CPS, had 

significantly higher levels of urinary DMP measured in 2002 (and therefore DAP 

concentrations), relative to the original non-exposed group.

Neurocognitive and behavioral assessments were selected by the investigators based on their 

demonstrated validity and reliability. Cognitive assessments included a short form of the 
Wechsler Intelligence Scale for Children, Third Edition, the Children’s Memory Scale; 

Wisconsin Card Sorting Test; and Trail Making Test A & B. The behavioral measures were the 

Child Behavior Checklist/4-18 (CBCL/4-18) and The Teacher Report Form (TRF). The tests 

instructions were administered in the child’s preferred language – Spanish or English. In addition 

to the neurobehavioral assessments, a structured interview was conducted with parents of all 

participating children, in order to ascertain additional information about the child and the family. 

The authors presented box plots to compare urinary OP metabolite (DAP) concentrations among 

the children and correlation coefficients to parameterize the associations between DAP 

metabolite levels and cognitive test performance. 

DAP concentrations were presented primarily in figures (boxplots, stratified by the original nonexposed and exposed status). The mean DMP in urine sampled at the time of the neurocognitive 

assessments was 65.5 mcg/l (95% CI: 43–88 5 mcg/l). The authors contrasted this finding with 

the corresponding average DMP concentration at the time of the original CPS screening (110.8 

mcg/l; 95% CI: 56–164 mcg/l); the mean national value estimated by NHANES (21.7 mcg/l; 

95% CI: 10–41 mcg/l), and the NHANES average for the Mexican-American population ages 6–

59 (15 mcg/l; 95% CI: 10–23 mcg/l). (DHHS, 2003)

The authors observed only one statistically significant difference between children grouped by 

presence or absence of pesticide exposure as originally determined by DAP urinalysis during the 

screening phase of the CPS and cognitive and behavioral performance at age 6-8 years of age. A 

statistically significant difference between the groups were observed for the TMTB, with 

children in the pesticide-exposed group taking more time to complete the measure (average: 283 

seconds; 95% CI: 224–341 seconds), relative to the non-exposed children (average: 204 seconds; 

95% CI: 172–236 seconds). No other differences were reported by the authors, other than noting 

that statistically significant differences were not observed for the other cognitive and behavioral 

measures.

The authors observed very few statistically significant correlations between DAP concentration 

levels measured in urine sampled on the day of the cognitive assessment and performance of 

children on the WISC-III SF, the CMS, the TMTA, or the TMTB. They did note statistically 

significant correlations with some of the measures of the Wisconsin Card Sorting Test, 

specifically with the total number of errors made (r=0.31, p=0.03); the number of perseverative 

responses (r=0.34, p=0.01); the number of perseverative errors (r=0.35, p=0.01); the conceptual 

level responses provided (r=0.38, p=0.01); and the failure to maintain set (r=0.38, p=0.02). 
Study Review

This study was originally conceived to evaluate a primary hypothesis that cognitive and 

behavioral test performance of children prenatally and recently exposed to OP pesticides would 

be diminished relative to the test performance of children who had not been exposed to OP 

pesticides. The investigators also hypothesized that higher levels of recent OP pesticide exposure 

would be associated with poorer performance on the neurocognitive assessments. Their study 

sample included a roughly equal number of children with, and without, prenatal OP pesticide 

exposure. However, contrary to their expectations, they found that all children participating in 

the current study had detectable levels of OP pesticide metabolites in urine samples collected just 

prior to the outcome assessment. As a result, they were not able to evaluate their primary 

hypothesis. They also chose not to evaluate associations between urinary OP pesticide biomarker 

levels and behavioral test performance. Thus, their report was limited to a cross-sectional 

evaluation of the association between urinary DAP concentrations and cognitive test 

performance. 

Use of urinary DAP metabolites as a marker of OP pesticide exposure is both a strength and a 

limitation of the study. Considering the prohibitive logistical effort required to ascertain serial 

urine samples in a large epidemiologic study of children, the lack of sensitive and specific 

pesticide biomarker assays (such assays are available only for a few pesticide-specific urinary 

metabolites, e.g., TCPy for chlorpyrifos), and a lack of biomarkers for time-integrated pesticide 

exposures, the exposure assessment used in this study was reasonable, and certainly logistically 

expedient. Because they are non-specific, urinary DAP concentrations can be considered an 

integrated biomarker of exposure to many OP pesticides. But urinalysis and quantification of 

DAP metabolite concentrations in a single urine sample, as was done in this study, may not be 

representative of a participant’s usual pesticide exposure over an extended period of time. 

Because of the often intermittent nature of pesticide exposure, urinary DAP metabolite levels can 

exhibit considerable temporal variability (i.e. day-to-day fluctuations). OP pesticides can break 

down into DAPs in the environment, and urinary concentrations may therefore also reflect 

exposure to preformed environmental DAPs. Urinalysis of the non-specific OP metabolites, as 

was conducted in this study, may be a marker only of very recent exposure, i.e., in the 24 to 48 

hour period prior to the collection of the urine sample.(Walker & Nidiry, 2002) That said, DAP 

concentrations in a single urine sample have been demonstrated to correlate reasonable well with 

90-day average levels in adult men (Meeker et al., 2005). In this study, the exposure assessment 

was conducted one to two days prior to the conducting of the neurocognitive and behavioral 
assessments. It is unlikely that exposures in this time frame are representative of exposures 

during the critical time window for neurocognitive development, unless exposures occur 

uniformly over time. 

These aspects of urinary DAP biomarkers of OP pesticide exposure are all potential sources of 

exposure misclassification. 

The authors noted that the instruments used to assess cognitive (and behavioral) status in this 

study were selected because of their frequent use in previous studies of adult populations. 

Although perhaps standard tools to evaluate adult populations, they may not be the most 

sensitive or appropriate tests to detect differences neurocognitive and behavioral functioning of 

primarily Spanish-speaking, Hispanic children living in a rural, primarily agricultural, 

community.

Statistical adjustment for potential confounders of the relationship between pesticide exposure 

and neurocognitive status was not conducted. The behavioral outcomes were not included in this 

analysis. The authors justified this omission by stating that the behavioral measures refer to a 6-

month period (prior to the assessment). 

The statistical methods used in the study were not well described in the report. The authors 

presented only correlation coefficients and associated p-values to parameterize the association 

between urinary OP metabolites and performance on cognitive tests. The authors did not identify 

what type of correlation coefficients were estimated (e.g. Pearson or Spearman). The 

investigators excluded two outliers with suspiciously high OP metabolite concentrations from 

their analyses. They did not specify how inclusion of these outliers would have altered the 

observed associations.

The authors noted that the two groups of children (with and without detectable urinary OP 

metabolite concentrations at the time of the original CPS screening) had “nearly identical 

demographic characteristics.” However, this observation is not evidence that the profile of 

determinants neurocognitive performance was similar between those with varying degrees of 

recent pesticide exposure. Confounding is thus a possible explanation for the few associations 

observed in this study. That said, it is likely that the study population is relatively homogeneous. 

The pesticide exposure misclassification discussed above was very likely non-differential with 

respect to the cognitive outcomes assessed in this study. One may thus expect that, on average, 

associations observed in the presence of such OP pesticide exposure measurement error are 
attenuated (i.e. closer to the null correlation of zero), relative to the true association, assuming no 

other bias or confounding, and apart from random error. Such errors are a potential explanation 

of the null findings with respect to WISC-III SF, CMS, TMTA, and TMTB performance.

The study findings, if valid, are likely generalizable to rural, primarily agricultural communities 

of Hispanic children. However, the study findings were largely null; the findings are not 

consistent with the hypothesis that recent OP pesticide exposure adversely affects cognitive and 

behavioral functioning at seven years of age. This could be due to considerable misclassification 

of true pesticide exposure during the relevant time period for cognitive development.

References cited

Meeker JD, Barr DB, Ryan L, Herrick RF, Bennett DH, Bravo R, Hauser R. Temporal variability 

of urinary levels of nonpersistent insecticides in adult men. J. Expo. Anal. Environ. 

Epidemiol. 2005;15:271–281.

Walker, B. Jr., & Nidiry, J. Current concepts: Organophosphate toxicity. Inhalation Toxicology. 

2002;14, 975–990.
Study 24. Lu et al. (2012)

Assessing the association between pesticide exposure and cognitive development in rural 

Costa Rican children living in organic and conventional coffee farms. Int J Adolesc Med 

Health. 2009; 21(4): 609-621

Study Summary 

In this report, Lu et al. examine the association between urinary concentrations of OP and 

pyrethroid metabolites and cognitive development in Costa Rican children whose parents worked 

in organic or conventional coffee farms using a cross-sectional study design with a single 

assessment of selected urinary OP, pyrethroid, and other pesticide metabolites and a single 

assessment of cognitive development.

A convenience sample was recruited in June-August, 2007. The investigators invited parents 

(primarily fathers) at an organic coffee farm (La Amistad group) to participate. Participants 

(primarily mothers) from conventional coffee farms (Las Mellizas group) were recruited at 

community meetings and through referral. A total of 17 La Amistad children and 18 Las 

Mellizas children between the ages of 4 and 10 years were enrolled, age and gender matched. 

Two spot urine samples were collected by each parent/child participant, before bedtime the 

evening of Day 1 and the first morning void of Day 2. Collected samples were stored in a 

refrigerator or cooler with ice packs until picked up by researchers on Day 2. Samples were 

transported on ice packs to the La Amistad Lodge for total volume and specific gravity 

measurement and aliquotting. Aliqoutted samples were kept at −4 °C, until shipment (on frozen 

gel packs) to the CDC/NCEH in Atlanta. All samples arrived partially frozen at CDC, and were 

analyzed for specific metabolites of selected OPs, pyrethroids, herbicides, and DEET by LC-MSMS (Olsson et al., 2004). Urinary OP, herbicide and pyrethroid metabolite concentrations (ug/L) 

in each sample and daily volume weighted average (DVWA) urinary OP, herbicide and 

pyrethroid metabolite concentrations (ug/L) for each sample set were calculated. 

Urinary pesticide levels did not vary considerably in La Amistad and Las Mellizas children. Of 

20 analytes detected, only 7 were found at greater than the LOD. OP metabolites detected above 

the LOD were:
• 4-nitrophenol (PNP - malathion, methyl parathion, others) (Most frequently detected 

metabolite, Freq detection 99%, no levels reported)

• IMPY (diazinon) (Freq detection 23%, range 0-7.79 ug/L, higher in Organic farm/La 

Amistad children, paired t-test p=NR)

• TCPy (chlorpyrifos) (Freq detection 14% (x4), range 0-6.71 ug/L (x5), marginally 

higher in Conventional farms/Las Mellizas children, paired t-test p=0.065)

Other urinary pesticide metabolites detected were 2,4-D (Freq detection 71%), d, N,N-diethyl-mtoluamide (DEET) (Freq detection 56%), and 3-BPA (pyrethroids) (Freq detection 16%).

Cognitive development was assessed using the following: 

• Computerized Behavioral Assessment and Research System (BARS) (Rohlman et 

al., 2001), Spanish version: Digit Span, Finger Tapping, Match-to-Sample, 

Continuous Performance; Divided Attention (17 total measures) – A 9-button 

response unit overlaying the keyboard simplified response for young children and 

those unfamiliar with computers. Detailed instructions and a practice session 

preceded each test. Instructions were spoken by the researcher and the computer, and 

could also be read on the computer screen. Interaction was provided as needed, 

especially with younger children. A 97% response rate was attained. 

• Figure drawing task: To assess child's perception and dexterity, children were asked 

to draw a picture of their family. Scores were assigned by a researcher with no 

knowledge of the participants’ exposure status. Scores were rated 1-11 (one point for 

eyes, ears, nose, mouth, hair, head, legs, feet, arms, hands, and trunk; averaged if 

more than one person in drawing).

• Long-term memory test: At the beginning of a test session, the child was told they 

would receive a pencil as a prize at the end. After the BARS and figure drawing, the 

child was asked what prize they were to receive. 

The testing usually took place at the child’s home. It took about 40 minutes to administer. 

For 8 of 17 neurobehavioral measures, performance did not differ between groups. Conventional 

farms/Las Mezillas children performed better on 9 measures, 3 significantly better (Long-term 

memory, Continuous performance percent hits, Continuous performance average false alarm 

latency) and also had higher scores in the Figure Drawing Test (average 15% more complete 

drawings or 1.6 more body parts than La Amistad children).
To assess the relationship between pesticide exposure and performance on cognitive 

development tests, linear mixed effect models for 4 significant test outcomes from paired t-test 

analyses (Figure drawing score, Long term memory, Continuous performance test percent of 

correct responses to target, Continuous performance test average false alarm latency) were used. 

Significance was set at <0.10 due to small sample size. Models included age, gender, group 

(conventional, organic), handedness, and grade.

Age (p=0.094) and group (organic vs conventional farm) (p=0.018) were significant contributors 

to figure drawing scores. (Note: Conventional farm/Las Mellizas children performed better).

Gender (p=0.039) and group (organic vs conventional farm) (p=0.016) were significant 

contributors to Continuous performance percent hits. (Note: Conventional farm/Las Mellizas 

children performed better).

Exposures were low for both groups of children. Children in rural Costa Rica are exposed at 

lower levels than US children. Performance on the neurobehavioral tests was about equal 

between the two groups, with Conventional farms/Las Mezillas children generally performing 

better. Pesticide exposure did not affect cognitive development. The researchers concluded that 

differences in the groups that would lead to cognitive development disparities may likely result 

from families' SES and demographic characteristics.

Study Review

The study lacked a clear design and analytic strategy. The basic assumption of a difference in 

exposures between the groups was flawed as the Conventional/Las Mellizas farms in reality used 

very little pesticides due to ideal growing conditions, having less money, small farms, different 

pest management agricultural practices, etc. In addition, the assumption of similar demographic 

characteristics, schooling, nutrition, and lifestyle between groups was also flawed – the La 

Amistad families lived in shacks provided by the employer, some without electricity or 

refrigerators, the parents (about 2/3) were usually illiterate, and children started school at 5-6 

years old, while the Las Mellizas families owned farms, homes had basic appliances, most 

owned vehicles, only about 1/3 parents were illiterate, and children started preschool at 3-4 years 

old. Therefore no conclusions can be drawn with respect to the relationship between OP 

pesticide exposure and cognitive development from this research. 
Recruitment methods were different for the two groups and no discussion was presented as to 

participation rate differences or selection bias between the groups.

The exposure measurement methods employed were appropriate. In fact, collection of an 

evening and next day first morning void urine sample is considered a good approach to a spot 

collection as it allows for calculation of a weighted average concentration. Measured pesticide 

metabolites are not listed - only those found above LOD. In Table 1, ‘CIT’ is listed but never 

defined or discussed. While the researchers measured specific gravity, it is not indicated whether 

urinary values were adjusted for specific gravity. The potential for contamination due to 

collection by participants is not discussed and appears not to have been evaluated. 

As the authors point out, a limitation of the cross-sectional design is the reliance on the 

untestable assumption that (even valid) biomarkers of OP pesticide exposure measured in urine 

sampled at the time of the neurodevelopmental assessment are indicative of ‘usual’ OP pesticide 

exposure, or, more to the point, accurately reflect OP pesticide exposure at the critical timewindow(s) for exertion of deleterious effects on neurodevelopment. Moreover, the use of a single 

day’s urine sample to estimate the participant’s OP pesticide exposure is likely to have resulted 

in an attenuation of associations, relative to those that would have been observed had the 

investigators used a time-integrated marker of OP pesticide exposure. 

The instrument used to assess cognitive development (i.e., the BARS) has been used in Spanish 

in a number of farmworker populations in US and other countries, including pre-school and 

school age children. Adequate instructions, a practice session, and interaction to motivate 

younger children were employed. However, differential interaction with children without clear 

guidelines may bias results, usually towards better performance. This is not evaluated. No 

training of data collectors is described. 

The figure drawing and long term memory tests are not cited seem full of potential, unmeasured 

biases, e.g., whether the child had ever drawn a picture of their family before and feedback given 

if they had, whether a pencil was a desirable prize, etc. The authors consider the 11-point scale 

for the figure drawing test to allow a more detailed assessment than a 5-point scale used 

previously (Guillette et al., 1998). The long term memory test is not cited in the methods section.

The statistical analysis was not specified in great detail, but appears to be appropriate. 

Confounders such as possible dietary exposure or pesticide use in homes are not considered. The 

small sample size reduces statistical power. 
The authors rightly conclude that covariates such as maternal education, years working in 

agriculture, pesticide handling, breastfeeding, nutritional breastfeeding information, SES (such 

as having computers at home) may all affect performance on cognitive tests. Unfortunately they 

conclude they found a positive association between family SES and cognitive development in 

children living in rural Costa Rica, when in fact they do not actually report any SES 

measurement method or data other than after-the-fact observations. For example, they reported 

estimated mother illiteracy rates based on whether the mother asked to be read the consent form. 

In conclusion, this study does not add the weight of evidence that OP pesticide exposure affects 

neurological development. 

References cited

Guillette, EA, Meza, MM, Aquilar, MG, et al. (1998). An anthropological approach to the 

evaluation of preschool children exposed to pesticides in Mexico. Enviro Health Perspect 

106:347-53.

Olsson AO, Baker, SE, Nguyen JV, et al. (2004). A liquid-chromatography tandem mass 

spectrometry multiresidue method for quantification of specific metabolites of 

organophosphorus pesticides, synthetic pyrethroids, selected herbicides, and DEET in 

human urine. Anal Chem 76:2453-61. 

Rohlman, DS, Anger, WK, Tamulinas, A, et al. (2001). Development of a neurobehavioral 

battery for children exposed to neurotoxic chemicals. Neurotoxicology 22:657-65.
Study 25. Moreno-Banda et al. (2009)

Maternal exposure to floricultural work during pregnancy, PON1 Q192R polymorphisms 

and the risk of low birth weight. G. Moreno-Banda, J. Blanco-Muñoz, M. Lacasaña, S.J. 

Rothenberg C. Aguilar-Garduño, R. Gamboa, O. Pérez-Méndez. Science of the Total 

Environment 407: 5478–5485, 2009.

Study Summary

Moreno-Banda et al. reported on the results of a cross-sectional study assessing the association 

between floricultural work during pregnancy, as proxy for prenatal pesticide exposure, and 

prevalence of low birth weight among women living in two states in Mexico. They evaluated 

whether this association is modified by the maternal paraoxonase (PON1) Q192R polymorphism. 

Between January and July, 2005, floricultural workers and their spouses were recruited to 

participate in the study if they had worked for at least one year in floricultural activity. Female 

workers and female spouses of male workers who reported having had at least one pregnancy 

between 1995 and 2005 were eligible to participate in the study. 

Of 585 floricultural workers or spouses who completed a screening interview to determine 

eligibility, 219 were ineligible. The vast majority (>90%) of these workers/spouses were not 

eligible because they had not had a pregnancy in the 10 years prior to the interview. Of the 366 

women who were eligible, 38 declined the invitation to participate without giving a specific 

reason. In total, 328 (90%) women agreed to participate, and reported a total number of 658 

pregnancies in the 10 years prior to the study, 467 of which were included in subsequent 

analyses. The 191 excluded pregnancies were not analyzed for one of the following reasons: 

pregnancy ended in a miscarriage or abortion, premature birth, twins, presence of congenital 

malformations, or missing exposure, outcome, or genetic polymorphism data. 

Study participants completed a structured questionnaire collecting retrospective information on 

sociodemographic characteristics, exposure to chemical substances at home and at work, 

characteristics of their work activities, reproductive history, medical history, reproductive 

history, and maternal alcohol and tobacco consumption. Separately, the women completed a food 

frequency questionnaire. Paternal occupation, alcohol use, and tobacco use were also queried.
The following two exposure groups were defined for the purpose of this analysis: Exposed, 

defined as women who worked in floriculture during the studied pregnancy; and not exposed, 

defined as women who did not work in floriculture during studied pregnancy.

Birth weight data were derived from birth certificate (if available) or by maternal report. Low 

birth weight was defined conventionally as birth weight less than 2,500 grams.

No differences in birth weight were observed between QQ and QR genotypes. Maternal PON1 

Q192R polymorphism (QQ, QR and RR) genotypes were therefore collapsed into two groups: 

QQ or QR genotype and the RR genotype.

The authors evaluated the risk of low birth weight associated with prenatal occupational 

pesticide exposure using GEE (General Estimating Equations) models with a logit link function 

(equivalent to logistic regression model, but accounting for correlation due to repeated 

measures). Modification of LBW risk by maternal PON1 polymorphism (gene–environment 

interaction) was assessed with an interaction variable. Models were also constructed within the 

two strata of the PON1 polymorphism. Multivariate models were adjusted for infant sex, and 

presence of a history of adverse reproductive outcomes. Maternal smoking and alcohol 

consumption during pregnancy were also considered as potential confounders but, appropriately, 

were not included in final models, due to an observed low prevalence of these factors in this 

study population.

After adjustment for potential confounders, Moreno-Banda observed a statistically significant 

interaction between maternal exposure to flower growing work during pregnancy and PON1 

Q192R polymorphisms on risk of low birth weight. Among mothers with QQ or QR PON1 

genotype, those exposed to floricultural work during their pregnancy had a lower risk of having a 

child with LBW than those who were not exposed (OR: 0.42; CI 95%: 0.14-1.24). Among 

mothers with the RR PON1 genotype, those exposed to floricultural work during pregnancy had, 

on average, twice the risk of having a child with LBW, relative to those who were not exposed 

(OR: 2.62, CI 95%: 0.89-7.69). Although the stratum-specific odds ratios were not statistically 

significant, the interaction effect in a multivariate adjusted model of LBW including the gene by 

environment interaction and the main effects of floricultural occupation status (exposed or not) 

and maternal PON1 polymorphism was statistically significant. 

In summary, a gene by environment interaction was observed between maternal exposure to

floricultural work during pregnancy and maternal PON1 genotype: the group with the greatest 
probability of having a child with LBW was women exposed to floricultural work and who had 

PON1 192RR. 

Study Review

This study relied on a proxy indicator of prenatal occupational exposure to pesticides to evaluate 

differences in risk of low birth weight comparing exposed to unexposed women-infant pairs, and 

additionally evaluated modification of this association by PON1 polymorphism status. This was 

a cross-sectional study with retrospective recall of occupational exposure during pregnancies up 

to 10 years prior to the conduct of the study. The investigators also relied on retrospective selfreporting of birth weights for a portion of the study participants for whom birth certificates were 

unavailable. The study design, particularly the use of an imperfect proxy for OP pesticide 

exposure, limits the strength of the evidence contributed by this investigation.

The recruitment procedures and inclusion/exclusion criteria were appropriate, though a large 

proportion of potential participants were not included, or did not agree to participate in the study. 

This is a potential source of selection bias. Twelve of the workers who declined to participate 

agreed to complete a brief questionnaire for nonparticipants; these individuals were similar to 

participants with respect to sociodemographic characteristics (e.g. age, education and income), 

although the data were not included in the report. The exclusion of pregnancies occurring more 

than 10 years prior to the initiation of the study is also a potential source of selection bias. In 

sensitivity analyses, the authors attempted to evaluate potential for selection bias by comparing 

the distribution of characteristics of newborns for whom complete (exposure, outcome, covariate, 

and maternal PON1 Q192R polymorphism) information was available with those of newborns 

for whom this information was incomplete. Also, they specifically compared infants for whom 

maternal genotype information was available with those without this information.

No objective (bio)markers of pesticide exposure were evaluated in this study. Non-differential 

misclassification of pesticide exposure is likely in this study. For example, spouses who report 

not working in floriculture, often help with fieldwork, live near fields, wash spouse's clothing, 

etc., and may therefore experience para-occupational exposure to pesticides, to varying degrees. 

Such errors in exposure classification would likely bias observed associations towards the null 

(OR of 1).

The assessment of birth outcome (in part) by maternal self-report leaves open the possibility 

errors in classification of the LBW outcome that are differential with respect to exposure. The 
investigators validated the self-reported birth weight information using a subsample of 107 

pregnancies for which birth weight data were available from both birth certificates and selfreport. From this analysis, they concluded that there was adequate agreement between the data 

obtained by maternal self-report and the information obtained from the birth certificate 

(rho=0.93). Additionally, the classification of birthweight into a dichotomous indicator of low 

birth weight likely attenuated errors in birth weight, as LBW is likely to be correctly classified 

even in the presence of small errors in birth weight reporting.

The evaluation of the gene by environment interaction was limited by small sample size. Effect 

estimates from stratum specific models were not statistically significant, though statistically 

significant interaction was observed in a multivariate model including an interaction variable.

The assessment and adjustment for potential confounders was appropriate, but not particularly 

strong. There is potential for residual confounding due to mismeasured or missing confounders. 

Risk factors for LBW that are related to floricultural work/pesticide exposure would bias the 

results in this study, for example by differences in the ethnic makeup of the exposed and 

unexposed groups. Other such factors may be related to socioeconomic status of the study 

participants, a cofactor which is difficult to define, no less measure in an epidemiologic study. 

The magnitude of potential bias due to residual confounding is judged to be small. 

The finding of effect modification of pesticide exposure effects by PON1 was dramatic in this 

study, with qualitatively different results observed by polymorphism status (i.e. observed OR>1 

among those with RR genotype, and an observed OR<1 among those with QQ or QR genotype). 

If replicated in a large, high-quality study, this gene-specific relationship may add substantially 

to the understanding of pesticide exposure effects. Unfortunately, the study limitations 

(information bias, selection bias, confounding, and inadequate sample size) limit the inference to 

be drawn from the study findings. 
Study 26. Nevison (2014)

A comparison of temporal trends in United States autism prevalence to trends in suspected 

environmental factors. Environmental Health. 2014; 13(73): 16 pp

Study Summary 

In this ecological study, Nevison tests the hypothesis that autism is a constant-prevalence 

condition that simply has been underdiagnosed in the past. The author does this by 

systematically reviewing temporal trends in the top ten environmental compounds list (and some 

other exposures) and identifying those that are most and least consistent with the temporal trends 

in autism. The implicit assumptions are: 1) environmental exposures around the time of birth (± 

1.5 years) are most important, since autism by definition is either present from birth or develops 

within the first few years of life, and 2) that the rise in autism is driven by one or more 

environmental influences whose collective temporal trend resembles the trend in autism.

Temporal exposure trends were derived for the top 10 environmental compounds suspected of 

causing autism or related pervasive developmental delay (PDD) with increased exposure (and 

other factors). The top 10 toxins were compiled during an extensive literature survey: lead, 

methylmercury, PCBs, OP pesticides, organochlorine pesticides, endocrine disruptors, 

automotive exhaust, PAHs, polybrominated diphenyl ethers, and perfluorinated compounds. This 

list was expanded to include other suspected factors: general air pollution indices, a broad range 

of mercury exposures, including fish, high fructose corn syrup, atmospheric mercury, and 

vaccine-administered thimerosal, maternal obesity, vaccine-related indices, and autoimmune 

disorders.

OP pesticide “exposure” was estimated at 25-95 million lbs/year (5 major food crops) for 1965-

2005, with peak use 1975-1980, from EPA data for U.S. annual agricultural pesticide 

consumption data, partitioned into total insecticides, total herbicides, etc., supplemented with 

USDA survey data on insecticide use dating back to 1964 for 5 major crops (corn, cotton, wheat, 

soybean and potatoes) plus various additional fruits and vegetables. The total insecticide use data 

were multiplied by % share of OP insecticides (compiled for the 5 major crops only) to roughly 

estimate the time trend in U.S. agricultural OP consumption. OP pesticide usage over time is 

mixed but recently decreasing. Overall, OP pesticide usage is negatively (but not significantly) 

correlated with autism prevalence. (Note: Glyphosate, an OP herbicide, “exposure” was 

estimated and presented separately.)
Temporal trends in autism for birth years 1970–2005 were derived from a combination of data 

from the United States Individuals with Disabilities Education Act (IDEA, 50 states plus DC) 

and California Department of Developmental Services (CDDS) reports. 

• Using IDEA data, autism prevalence vs. birth year trends were calculated 

independently from snapshots of data from the most recent annual report, and by 

tracking prevalence at a constant age over many years of reports. The ratio of the 

snapshot:tracking trend slopes was used to estimate the “real” fraction of the increase 

in autism.

• From CDDS, autism prevalence data for birth years 1970–1997, effectively a 2002 

age-resolved snapshot of individuals 5 years of age or older receiving services for 

autism, and autism prevalence data tracking 5 year-olds from 1995–2006, 

corresponding to birth years 1990–2001, were obtained. The CDDS tracking data set 

overlaps with California IDEA data tracking 5 year-olds for birth years 1995–2001, 

providing a means for assessing whether the IDEA definition of autism has expanded 

from the CDDS definition to include milder ASDs. Since children in private schools 

are included in IDEA autism counts but not in NCES total public school population 

data, the IDEA/NCES ratio will tend to overestimate autism prevalence, by 

underestimating the denominator. To correct for this effect in all figures in which 

CDDS and California IDEA data are combined, the NCES total populations for 

California were revised upward by 14% based on available U.S. census data.

A monotonic “composite” curve was constructed by combining CDDS 2002 snapshot data for 

birth years 1970–1994 with California IDEA 5 year-old tracking data for birth years 1995–2005. 

These data sets blend continuously, albeit for somewhat fortuitous reasons. The primary motive 

for combining them is to allow examination of concurrent trends in toxins and autism over the 

longest birth year window possible, 1970–2005. The California data were assumed to be broadly 

representative of the rest of US.

The composite curve and the temporal trend in each suspected causal agent were compared by 

visual inspection. The correlation coefficient was also computed between the temporal trend in 

each suspected agent and the composite autism prevalence curve using the longest overlapping 

time period possible. However, these quantitative statistics are not emphasized, due to the 

multiple uncertainties involved in defining the long-term trend in autism.

The author concludes that the increase in diagnosed autism prevalence is a true occurence and 

has occurred mostly since the late 1980s. The slope ratios for the California IDEA age-resolved 

snapshot and constant-age tracking trends suggest that about 80% of the tracked increase in 

California autism is “real” as opposed to due to better diagnosis, both for birth year intervals 
1988 to 1994–1997 and 1993 to 1999–2002. The CA results are similar to and within the 

standard deviation of the mean results across the US. The latter suggest that 77 ± 8% of the 

tracked increase over birth years 1988 to 1994–1997 is real and that about 74 ± 8% of the tracked 

increase over birth years 1993 to 1999–2002 is real. In nearly all states, the snapshot slopes are 

flatter than the tracking slopes, indicating an ongoing, retroactive expansion in the diagnosis of 

autism among older students who were not identified as younger children. CDDS data probably 

includes at least some milder ASDs, despite reports to the contrary, while the IDEA data do not 

appear to include all ASDs.

In contrast to the increase in autism rates, children’s exposure to most of the top ten toxic 

compounds has remained flat or decreased over this same time frame. Some, including lead, 

organochlorine pesticides and vehicular emissions, have strongly decreasing trends. Among the 

suspected toxins surveyed, polybrominated diphenyl ethers, aluminum adjuvants, and the 

herbicide glyphosate have increasing trends that correlate positively to the rise in autism. OP 

pesticide usage over time is mixed but recently decreasing. Overall, OP pesticide usage is 

negatively (but not significantly) correlated with autism prevalence. 

Study Review

As an ecologic study, this study was well performed and has merits; however it suffers from the 

ecological fallacy in that it is not possible to link exposure (or timing or level of exposure) to 

individual children, i.e., those with autism may not be the same children who are exposed. 

Further, the exposure measure – OP pesticide usage per year, based on crops, not specified by 

specific OP or application location - is a proxy for actual exposure and may vary geographically. 

Additionally, home use of OP pesticides is not considered. While chlorpyrifos was banned for 

residential use in 2001, other OPs continue to be used in household applications, e.g., as pet flea 

products, with temporal trends that are not resolved by this study. The potential confounders 

examined are exposures to nine other suspected environmental contaminants (and a few other 

exposures) but again these are proxy exposure measures which cannot be linked to individual 

children, and there is no statistical control for these exposures. Therefore no conclusions can be 

drawn with respect to the relationship between OP pesticide exposure and autism from this 

research.

The author explains in clear detail the differences between the two databases used, how constant 

age snapshots are generated (most common and straightforward way to quantify trend), and what 

the snapshot-based trend means (i.e., if autism is truly a constant-prevalence condition, fully 
diagnosed at all ages in the snapshot, the slope ratio will be 0). The author clearly discusses bias 

correction for under-ascertainment of autism in younger children, discarding the youngest ages: 

5, 6 and 7, in calculating the snapshot trend slopes, thus considering a range of start ages from 8 

to 11 years old. Further she describes slope errors in the data, using < 10% (tracking) and < 15% 

(snapshot) error as criteria to filter out states with erratic data and to identify those for which the 

temporal trend could be approximated well as a linear slope. CDDS data are one of the most 

reliable, long-term U.S. autism records available (include only verified cases of full-syndrome 

autistic disorder (AD), the most severe and unambiguous ASD). Although she points out that 

some older children may remain undiagnosed, her conclusion that autism is increasing seems 

well-supported. The finding of qualitative consistency between two data sets, CDDS and IDEA, 

further suggests a strong increase in autism prevalence over recent decades. She also compares 

this study results to Finnish data, which shows similar increases.

While epidemiology has linked ASD and PDD in children to both prenatal and postnatal 

exposure to cholinesterase-inhibiting OP insecticides, the biological plausibility of these 

insecticides as a cause of autism has been described, and wheat and corn have been identified as 

the most important sources of OP pesticide exposure among U.S. children – according to data 

provided in the article, this study shows that the temporal trend in total OP insecticide use does 

not correlate well to the trend in autism. It is possible that other compounds or a mixture of 

compounds is responsible for the autism increase (the top 10 compounds comprise only a small 

subset of the > 80,000 synthetic chemicals developed over the past 50 years, many of which have 

never been assessed for potential toxicity). 

It should be noted that this study is limited to autism and does not address other possible 

neurodevelopment effects of the compounds. 
Study 27. Rohlman et al. (2005)

Neurobehavioral performance in preschool children from agricultural and nonagricultural communities in Oregon and North Carolina. Diane S. Rohlman, Thomas A. 

Arcury, Sara A. Quandt, Michael Lasarev, Joan Rothlein, Rachelle Travers, Alys 

Tamulinas, Jennifer Scherer, Julie Early, Antonio Marín, Jacki Phillips, Linda McCauley. 

Neurotoxicology 26:895-598, 2005.

Study Summary

Rohlman et al. reported on the results of a community-based research project comparing 

neurobehavioral test performance of Latino children of immigrant parents living and working in 

agricultural communities to that of Latino children of immigrant parents not living or working in 

non-agricultural communities. Their cross-sectional study examined 48-71 month old children 

living in Oregon and North Carolina. The primary objective of the study was to compare the two 

groups’ performance on neurobehavioral tests. The investigators also compared the groups’ 

ability to learn test instructions and complete neurobehavioral test components.

The investigators were interested in the effects of low-level chronic exposures to OP pesticides 

on neurobehavioral development in an understudied population of immigrant farm workers. They 

used a proxy indicator of OP pesticide exposure; children living in communities in highly 

agricultural regions of Oregon (Hood River County) and North Carolina (Johnston, Harnett, 

Sampson Counties), were defined as ‘exposed’. The children recruited from the two agricultural 

communities had at least one parent working in agriculture at the time of the study. The 

comparison population was comprised of Latino children born to immigrant parents living in 

non-agricultural communities in Oregon (Lincoln County) or North Carolina (Wilkes County). 

Neither parent of these children worked in agriculture in the year prior to the study. No objective 

markers of pesticide exposure were obtained. 

Enrollment took place during the summers of 2002 (Oregon) and 2003 (North Carolina), during 

which times the authors attempted to recruit every child that met eligibility criteria and that were 

referred by community members. The target population is described by the investigators as a 

“difficult to access population of immigrant families.” The children living in the agricultural 

locales were recruited from Migrant Head Start facilities. In Oregon, referent children were 

recruited from a local community program, Centro de Ayuda, while in North Carolina, referent 

children were recruited from the community and from the Smart Start preschool program. In all, 
78 children were enrolled in the study; 43 from the agricultural communities, and 35 from the 

non-agricultural areas.

Neurobehavioral tests were administered to each child participant during two testing periods 

scheduled approximately 1 month apart. Comparisons of neurobehavioral test performance 

between children from agricultural and non-agricultural areas were reported only for results from 

the second testing session. The authors stated that the repeat testing permitted examination of 

differences in learning between the two groups, and also maximized the number of children who 

were able to complete the tests. In addition, parents were asked to complete a questionnaire to 

collect information on parental age, education, years in the United States, and work 

characteristics. Information on the children’s computer and video game experience was also 

collected for the subset of children living in North Carolina. 

The neurobehavioral tests evaluated the following domains of neurobehavioral development: 

memory and attention, response speed and coordination, visual memory, attention, divided 

attention, recall and recognition memory, dexterity, hand-eye coordination. The neurobehavioral 

evaluation consisted of five computerized tests from the Behavioral Assessment and Research 

System (BARS) and three non-computerized tests (Object Memory, Purdue Pegboard, and 

Visual Motor Integration). The authors noted that the BARS was developed for use with a broad 

range of working populations of varied educational levels and diverse cultural backgrounds. The 

BARS tests used were the Digit Span, Finger Tapping, Match-to-Sample, Continuous 

Performance, and Divided Attention. Group test performance in all domains was reported as 

standardized means and associated standard errors, except the Continuous Performance and 

Divided Attention tests, which were omitted from analyses due to observed difficulties in 

completion of these tests. 

The authors compared differences in average neurobehavioral test performance between the two 

groups of children using separate multivariate linear regression models for each test, adjusting 

for child age and maternal education. Because they were interested in evaluating whether 

average performance of children from agricultural communities was lower than, rather than 

simply different from, performance of children from non-agricultural communities, the 

investigators reported one-tailed p values corresponding to one-sided hypothesis tests of the 

adjusted differences in mean neurobehavioral test performance.
In addition to adjusting performance results for differences in age and maternal education, the 

authors additionally adjusted specific associations for, and examined effect modification by, 

location (Oregon versus North Carolina) and gender. 

The authors did not observe any statistically significant differences in any of the tests of 

neurobehavioral performance when comparing all children from agricultural communities to 

those from non-agricultural communities. Two statistically significant differences were observed 

in comparing sex- subgroups of exposed and non-exposed boys: Male children from agricultural 

communities in Oregon performed significantly worse than the male children from nonagricultural communities on right hand Finger Tapping. The male children from agricultural 

communities in North Carolina had significantly longer latencies on the Match-to-Sample test 

than boys from non-agricultural communities. Although percent completion improvements were 

seen in children from both agricultural and non-agricultural communities, the children from nonagricultural areas showed greater improvement in test completion between the two 

neurobehavioral performance testing sessions.

Study Review

This was a small cross-sectional study conducted using community-based research practices to 

engage with members of the participating communities of immigrant Latino families. The study 

design, particularly the use of an imperfect proxy for OP pesticide exposure, limits the strength 

of the evidence contributed by this investigation. The conduct and presentation of only a subset 

of the planned comparisons in the paper was not ideal, as was the choice of statistical methods. 

This poorly statistically powered and flawed study contributes little evidence consistent with the 

hypothesis that chronic, low-level OP pesticide exposure effects neurobehavioral status at 48-71 

months of age among Latino children of immigrant parents. 

The authors noted that the target population of immigrant Latino families was “difficult to 

access.” Despite their efforts to enroll every child meeting the reasonable set of study criteria, 

they managed to recruit only 78 children in total, 37 of whom were defined as exposed; the total 

eligible population was not enumerated. This small sample size limited the statistical power of 

the study. The inclusion/exclusion criteria were not clearly reported; presumably, they were 

being Latino, age 48–71 months of age, and, having parents who were immigrants to the United 

States. 

The authors used living in an area with a high concentration of agricultural activity as a proxy 

indicator of OP pesticide exposure. There is likely some degree of misclassification of true OP 
pesticide exposure that is likely independent of neurobehavioral test performance (i.e. nondifferential). The authors did not provide estimates of the prevalence of OP pesticide use in the 

area with a high concentration of agricultural activity, though they did reference an earlier report 

by McCauley et al. (2003).

The outcome assessment was flawed in several respects. The authors did not present 

comparisons of test performance from the first test session. Two of the five planned BARS 

neurobehavioral tests (Continuous Performance and Divided Attention) were not analyzed. A 

varying subset of children from both the agricultural and the non-agricultural communities were 

not able to complete all of the tests, despite BARS being designed for use in similar populations.

The authors did not account for multiple comparisons. Without sufficient justification, they 

evaluated one-sided hypotheses and presented corresponding one-tailed p-values and, 

nevertheless did not observe statistically significant differences between groups in their primary 

analyses. Confidence intervals were not reported.

The approach to confounding was not described in detail. Familiarity and use of computers, a 

potential confounder in this population, was assessed in only a subset of the population. 

Although the study was not sufficiently powered to examine associations among subsets of the 

study population, the authors stratified some of their results by gender and location. It was not 

clear from the report that effect modification by these factors was considered a priori. 

It was not clear from the report that the authors’ assessment of improvement in completion of 

tests between sessions (observed in children from both agricultural and non-agricultural areas, 

but greater in children from non-agricultural communities) was conducted to test an a priori 

hypothesis. 

No statistically significant differences for any of the tests of neurobehavioral performance were 

observed when comparing all children from agricultural communities to those from nonagricultural areas. The interpretation of the two statistically significant differences observed in 

male children is limited by issues of multiple testing of one-sided hypotheses, and the specter of 

residual confounding. Issues concerning validity aside, the study is likely generalizable to other 

immigrant communities in agricultural areas of the US. Overall, this study provides little 

evidence consistent with the hypothesis that OP pesticide exposure is associated with 

neurobehavioral function at age four to six years of age.
References cited

McCauley LA, Michaels S, Rothlein J, Muniz J, Lasarev MR, Ebbert C. Pesticide exposure and 

self-reported home hygiene practices in agricultural families. Am Assoc Occup Health 

Nurses J 2003;51:113–9.
Study 28. Samarawickrema et al. (2008)

Fetal effects of environmental exposure of pregnant women to organophosphorus 

compounds in a rural farming community in Sri Lanka. Nirma Samarawickrema, 

Arunasalam Pathmeswaran, Rajitha Wickremasinghe, Roshini Peiris-John, Madawa 

Karunaratna, Nick Buckley, Andrew Dawson, and Janaka De Silva. Clinical Toxicology 

46:489–495, 2008.

Study Summary

Samarawickrema et al. conducted a cross-sectional study of pregnant women from a rural 

farming community in Southern Sri Lanka. The objective of the study was to evaluate the effects 

of chronic, low level OP pesticide exposure on biomarkers of neonatal health including 

antioxidant status, oxidative stress, and fragmentation of fetal DNA.

Pregnant women age 20-30 years of age who lived in a farming area for the duration of their 

pregnancy, and who had not directly handled or been knowingly exposed to OP pesticides were 

recruited for participation in the study when they presented for delivery at the hospital serving 

the rural farming community.

Forty-one women enrolled during two spray seasons (July-August, 2005, and January-February 

2006) constituted the OP-exposed group. An additional 25 women recruited at the end of the “inbetween spray season” were defined as the unexposed comparison group.

An interview-guided questionnaire was completed at the time of admission for delivery to 

determine eligibility for the study, and also to collect information on gestational age, distance 

from place of residence to closest OP pesticide spraying site, approximate frequency of spraying 

during the month prior to the interview, and diet.

Maternal and cord blood samples were obtained at delivery, and a breast milk sample was 

collected within 24 hours of delivery. (Maternal blood samples were not obtained for exposed 

women enrolled between July and August, 2005, i.e. during the first of the two spray seasons.)

Breast milk and plasma from maternal and cord blood samples were assayed for the presence of 

four OP pesticides chlorpyrifos, diazinon, dimethoate, and fenthion. Quantification of these OP 

pesticides was conducted using HPLC-Tandem mass spectrometry, a method with a level of 
detection of 0.5 μg/L. In addition, serum chlorpyrifos and diazinon levels were quantified using 

gas chromatography with minimum levels of detection listed as 40 μg/L and 20 μg/L, 

respectively. The investigators also quantified oxidative butyrylcholiesterase (BChE) activity 

inhibition in blood and breast milk samples as a marker of OP pesticide exposure.

The antioxidant status of the fetus was characterized by superoxide dismutase (SOD) activity 

assayed in maternal and cord blood samples as well as in breast milk samples. Fetal oxidative 

stress was characterized by quantifying malondialdehyde (MDA) concentrations in cord blood. 

Fetal DNA fragmentation was assessed by electrophoresis of DNA extracted from erythrocytes 

from cord blood samples. The authors noted that the assessment of DNA damage was conducted 

by a researcher blinded to the exposure status of the samples. A similar statement was not made 

with respect to assessment of the other fetal outcomes.

The authors did not describe their statistical methods in the report. The investigators compared 

the exposed and non-exposed groups with respect to unspecified demographic and clinical 

measures, levels of the four OP pesticide biomarkers in blood and breast milk samples, as well as 

BChE, SOD, and MDA concentrations in the collected biological media using t-tests and Chisquare tests.

Statistically significant differences in clinical and demographic characteristics were not observed 

between the women characterized as OP-exposed (delivered during a spray season) and not 

exposed to OP pesticide (delivered in between spray seasons). Similarly, the women 

characterized as OP-exposed and not exposed were similar with respect to the OP-residues 

quantified in the collected biological media. In fact, OP residues were detected in only two 

participants - chlorpyrifos in maternal and cord blood samples obtained from one exposed 

women, and dimethoate in breast milk of one unexposed women. BChE activity in cord blood 

samples collected from women delivering during the spray seasons was significantly decreased, 

relative to that observed among the women who delivered in-between spray seasons.

Slightly higher SOD observed in cord blood samples of the women classified as OP-exposed 

were not statistically significant (p=0.5) On average, cord blood MDA concentration, a marker of 

lipid peroxidation and oxidative stress, was significantly higher among the women who delivered 

during the spray seasons, relative to those who delivered in between spray seasons. The 

proportion of fetal DNA breakage was also significantly higher among the OP-exposed group.
Study Review

Limited inference can be garnered from this small cross-sectional study. Although the use of OPexposure and fetal effect biomarkers was reasonable, limitations of the study design, particularly 

the lack of true differences in OP pesticide exposures between the two comparison groups, likely 

account for the largely null findings. Moreover, it is unclear whether the differences observed in 

markers of fetal oxidative stress can be ascribed to differences in OP pesticide exposure, given 

the similarities in exposure profiles between the two groups.

Inclusion and exclusion criteria were generally reasonable, though the decision to exclude 

women who directly handled or were knowingly exposed to pesticides (in order to focus on lowlevel exposures) limited the statistical power of the study. By design, the exposed and nonexposed women were likely to have similar OP pesticide exposure profiles. Indeed, the two 

groups could not be distinguished based on of BCHE activity levels of OP residues in blood or 

breast milk samples. This is evidence that notable OP pesticide exposure episodes did not occur 

prior to delivery. The OP residue biomarker assessment methods were likely not sensitive 

enough to resolve the low-level environmental (rather than occupational) exposures that were the 

subject of this investigation.

By design, OP pesticide exposures were low, if they occurred at all. Moreover, the exact types of 

pesticides used in spray activities were not identified. That said, the investigators' decision to 

quantify four specific OPs in biological media was guided by information from the Sri Lanka 

Department of Agriculture and the findings of a previous study that characterized types of 

pesticides used during different seasons in the study area. These sources identified chlorpyrifos, 

diazinon, dimethoate, and fenthion.

Given the similarity in OP pesticide exposure profiles between the two groups, the sample size of 

this study was likely inadequate to detect small differences in the fetal outcomes between them. 

This issue was compounded by the failure to collect maternal blood samples for the exposed 

group recruited during the first of the two growing seasons assessed in this investigation.

The timing of the collection of biological media for exposure biomarker assessment (during or 

just after delivery) in this cross-sectional study may not resolve OP pesticide exposures at 

biologically relevant time windows for fetal exposure effects.
The assessment of fetal outcomes were appropriately selected and substantiated by adequate 

discussions of biological plausibility. Errors in their measurement are likely to have been nondifferential with respect to exposure.

In their report, Samarawickrema et al. did not adequately detail the statistical analysis conducted 

in this investigation. The T-tests used to evaluate mean differences in continuously distributed 

variables between the exposed and non-exposed groups was likely reasonable, though evaluation 

of the distribution of the variables being compared were not described in the report. Chi-square 

tests were used to evaluate categorical variables. This test relies on large sample sizes, and the 

use of the test to compare DNA damage in the two groups, was not appropriate, as only two 

individuals in the non-exposed group had observed DNA fragmentation.

The authors did not find statistical differences between the exposed and non-exposed women 

with respect to demographic and clinical details, and did not conduct multivariate adjusted 

analyses. Though the lack of observed differences between the two groups with respect to 

measured baseline characteristics provides some evidence of comparability of the two groups, 

there was no description in the report a detailed assessment of potential confounding factors. As 

such, residual confounding of the associations between fetal outcomes and indicators of OP 

pesticide exposure is possible.

The findings of increased markers of fetal oxidative stress and DNA fragmentation among 

mother-infant pairs delivered during spray seasons, along with the finding of lower BChE in this 

group, relative to those delivering during the in-between spray periods, led the authors to 

conclude that these infants may be at “increased risk for health problems,” though they add that 

the nature and extent of the risk is unknown.” The strength of the authors’ conclusion is 

diminished by the failure to observe direct evidence of differences in OP pesticide exposure 

between the two groups. In fact, no measurable maternal OP pesticide exposure or BChE 

inhibition was observed, indicating low levels of, or absence of, recent OP pesticide exposure. 

This study therefore provides weak evidence consistent with the hypothesis that chronic, lowlevel OP pesticide exposure is associated with fetal decreased antioxidant status, increased 

oxidative stress, and fragmentation of fetal DNA. 
Study 29. Savitz et al. (1997)

Male pesticide exposure and pregnancy outcome. David A. Savitz, Tye Arbuckle, Diane 

Kaczor, and Kathryn M. Curtis. American Journal of Epidemiology 146(12):1025-1036, 

1997.

Study Summary

Savitz et al. reported on results of the Ontario Farm Family Health Study, one of the few studies 

specifically evaluating male pesticide exposure during the peri-conception period and subsequent 

pregnancy outcomes in a large retrospective cohort study. Set in Ontario, Canada, the study 

leveraged the 1986 Canadian Census of Agriculture to identify couples operating full-time, 

family run farms. Couples identified who were subsequently provided a survey on which to 

report farm activities, chemical applications, and birth outcomes.

The objective of the study, conducted in 1991-1992, was to assess associations between male 

exposure to agricultural pesticides, as indicated by self-reported farm activities (to application of 

OP pesticides) in the 3 months prior to conception through the month of conception, and adverse 

pregnancy outcomes (miscarriage, pre-term delivery, and small-for-gestational-age birth, and 

altered sex ratio). Although a large number of chemical applications (e.g. insecticides, 

fungicides, herbicides) and farm activities (e.g., mixing/use of chemicals for crops yard, 

buildings, and livestock, use of personal protective equipment) were reported, this summary will 

focus on the associations reported between birth outcomes (miscarriage, pre-term delivery, and 

small-for-gestational-age birth) and self-reported farm activities specific to OP pesticides.

7,379 farms were sampled from the Canadian agriculture census, 2,693 of which met the 

eligibility criteria. Farm couples were eligible if they were living year-round on or near the farm 

and the woman was younger than age 45 years old (at the time of the screening interview); 2,946 

couples met these eligibility criteria, of whom 1,898 (64%) completed and provided survey 

forms for the farm operator, husband, and wife. These couples reported on 5,853 pregnancies, of 

which 3,984 (68%) were included in the analysis. Among these, there were 1,548 live births 

reported (417 women with a single birth, 595 reporting two births, 354 with three, and 182 with 

more than three births).

Exposure was defined through self-reporting of engagement in any activities associated with 

direct pesticide exposure for one or more months in the 3-month period prior to conception by 
male study participants. Frequency of adverse birth outcomes among pregnancies classified as 

exposed were compared to those of a reference group of couples for whom the man reported no 

exposure to any activities associated with direct pesticide exposure. This review focuses on OP 

insecticide use for crops, livestock, and buildings, though the study evaluated and reported on a 

wider set of farm-related chemical use and related activities. Objective measures or biomarkers 

of pesticide exposure were not obtained in this large, retrospective survey study. 

Adverse birth outcomes were recalled and self-reported by the female of each farm family. The 

recall interval was in the range of 5-15 years, for the post part (the actual range was not 

reported). Births were classified as a miscarriage if a recognized pregnancy was lost prior to 20 

weeks of completed gestation and stillbirth if pregnancy loss occurred after 20 weeks of 

completed gestation. Pre-term delivery (PTD) was defined as birth prior to completion of 37 

weeks of gestation and small for gestational age (SGA) was defined as the newborn falling 

below the 10th percentile of birth weight for gestational age based on Canadian percentiles. 

Evaluation of PTD and SGA were restricted to the subset of singleton live births.

For their primary analyses, the authors built a multivariate adjusted logistic regression model for 

each of the pregnancy outcomes. The authors approached model building by first estimated crude 

(unadjusted) risk ratios for each outcome and each of the following potential confounders: 

Mother's age, parity, mother's education, father's education, per capita income, mother's off-farm 

job, father's off-farm job, mother's smoking during pregnancy, mother's alcohol use during 

pregnancy, conception-to-interview time interval, father's age, tobacco use, alcohol use, caffeine 

use, mother's language, ethnicity, religion, and child's sex. They then retained only those 

potential covariates, and collapsed categories of covariates, that yielded risk ratios less than 0.8 

or greater than 1.2. Subsequent elimination and re-specification of covariates occurred “as 

appropriate,” but the rationale was not specified by the authors. All covariates except for the last 

8 listed above were adjusted for in final models of the relationship between adverse birth 

outcomes and self-reported indicators of peri-conception pesticide exposure.

The authors also built “several” models using generalized estimating equations (GEE) and a logit 

link to evaluate the degree to which including multiple pregnancies per woman (i.e., potential 

non-independence of observed outcomes) resulted in biased estimation of variances and 

corresponding 95% confidence intervals. They concluded that the overall impact of failure to 

account for within-family correlations among pregnancies was minimal and reported only the 

results of the conventional logistic regression models.
The authors did not observe any statistically significant associations between peri-conception 

pesticide exposure among male farm workers and risk of miscarriage, stillbirth, PTD, or SGA. 

The highest elevation in relative risk was observed for PTD in association with reported 

exposure to livestock organophosphate pesticide exposure (OR=2.7; 95% CI: 0.7-11). 

Study Review

The interpretation of the results of this cohort study of pesticide exposure and birth outcomes 

conducted among farm families living in Ontario, Canada is constrained by limitations of the 

retrospective study design, particularly the methods used to assess male pesticide exposure and 

birth outcomes. Some degree of both differential and non-differential errors in recall of 

exposures and outcomes is probable. The potential for selection bias, and, to a lesser extent, an 

inappropriate choice of statistical methods and potential for residual confounding further limit 

the study. Finally, the (fortunately) low prevalence of adverse birth outcomes in this study 

population results in relatively imprecise estimation of odds ratios, as reflected in the observed 

confidence intervals, despite the relatively large size of the study. 

The inclusion/exclusion criteria employed in the study were appropriate and likely resulted in 

recruitment of a study population that was relatively homogeneous with respect to confounders 

of the male pesticide exposure-pregnancy outcome relationship, and the potential for 

confounding was thus limited by design. The study was large, relative to other similar studies, 

and employed a detailed questionnaire to obtain detailed information on both farm-related 

exposures and pregnancy outcomes. 

The retrospective design and the reliance on survey-derived indicators of pesticide exposure and 

birth outcomes are two of study features that, although logistically efficient, may have resulted in 

errors in classification. The authors referred to their assignment of exposure as “probabilistic.” 

That is, men who engaged in specific farm activities were more likely to be truly pesticideexposed than men who did not engage; Men classified as unexposed may nevertheless have been 

exposed to pesticides and men classified as exposed may nevertheless have not been exposed to 

pesticides. This exposure classification scheme likely resulted in ‘exposed’ and ‘not exposed’ 

groups being more similar to each other with respect to their true pesticide exposures, relative to 

a 100% accurate and precise exposure measurement scheme. The effect of this design element on 

the association estimates (i.e., the estimated odds ratios) is attenuation toward the null – no 

observed effect. Moreover, quantitative inferences regarding dose are not attainable. Frank errors 

in recall of exposure are also a potential problem. For example, the authors note that the lengthy 
recall interval between pregnancies and completion of the study survey may have adversely 

impacted the quality both pesticide exposure and birth outcome information; most of the 

pregnancies occurred greater than 5 years prior to the start of the study, and some occurred as 

much as 15 years prior to the completion of the questionnaires by the study participants. On 

average, errors in recall of OP pesticide exposure that are independent of the occurrence of 

adverse pregnancy outcomes result in observed odds ratio estimates that are attenuated (i.e. 

closer to the null value of 1.0), relative to odds ratios estimated in the absence of such errors. 

These errors may result in ‘false-negative’ findings, and are a potential alternative explanation 

for the largely null findings of this study. Although perhaps less likely, similarly non-differential 

errors in the recall of pregnancy outcomes would also engender ‘false negative’ findings 

consistent with the observed odds ratios reported in the study. The authors cite a previous study, 

for example, that noted increasing errors in reporting of miscarriage after approximately 10 years 

(Wilcox and Horney 1984). It is also possible that the probability that participants’ imperfect 

recall of pesticide exposure in this study is not independent of the occurrence of a birth outcome. 

If, for example, fathers who have experienced an adverse pregnancy outcome are more likely to 

incorrectly recall exposure to pesticides, relative to fathers who have not had a similar 

experience, the observed odds ratio would overestimate the true odds ratio. Finally, similar errors 

and subsequent classification of self-recalled exposure to confounding factors may have resulted 

in some degree of residual confounding, despite efforts of the investigators to control for 

confounding in their statistical analyses. 

The investigators’ intent to ascertain information regarding exposure to specific pesticides, rather 

than just reporting on associations between birth outcomes and agricultural use of chemicals, 

generally, is laudable. However, the attempt at specificity likely impacts both the validity and the 

statistical efficiency (power) of the study; the efficiency with which odds ratios were estimated is 

adversely impacted because the number of men exposed to specific pesticide classes is smaller 

than the aggregate indicators of exposure. The validity is adversely affected because, although 

men may accurately recall that they were exposed to a chemical, they may imperfectly recall the 

actual chemical to which they were exposed during the pre-conception period.

Only 64% of eligible couples completed the study surveys. It is not possible to determine the 

degree to which those who chose not to participate are represented by those who did chose to 

participate in the study. Bias due to differential errors in the selection of study participants is 

likely to have occurred in this study, the magnitude of which is dependent on the degree to which 

participation in the study was dependent on both exposure and outcome. Although many 

scenarios are plausible, it is possible, for example, that couples are more likely to have 
completed the study surveys if the male is concerned about his past pesticide exposures and the 

female is motivated to participate due to her having experienced an adverse pregnancy outcome, 

relative to those that have not had similar experiences. 

Two aspects of the statistical methods employed in this investigation were not optimal. First, the 

investigators did not report having accounted for multiple testing, despite evaluating associations 

between five pregnancy outcomes and more than two dozen indicators of farm-related activities 

associated with pesticide exposure. Second, the conventional variance estimator calculated by 

the standard logistic regression model and used by the authors was not appropriate. The 

investigators were aware of potential bias in estimation of variances due to their inclusion of 

multiple pregnancies per couple, and they explored the impact of their model by employing the 

correct statistical technique (i.e. GEE with empirical variance estimators) in an unspecified 

subset of the analyses they conducted. The authors reported that the influence on the width of the 

confidence intervals was “quite modest” for both indicators of pesticide exposure and included 

covariates. They noted that all of the confidence intervals estimated using GEE were within 20% 

of the estimates observed using conventional logistic regression models. The authors also 

observed that around 40% percent of the confidence intervals estimated using the GEE models 

were narrower than those estimated with conventional logistic regression. However, regardless 

of whether it generates a confidence interval that is wider or narrower than the corresponding 

empirical variance estimate, the conventional variance estimator is not appropriate in the 

presence of correlated outcomes. 

The investigators’ approach to evaluating and adjusting for potential confounders was generally 

appropriate, although certain aspects of the final steps of the model building process were not 

reported in sufficient detail. 

Assuming they are valid, the study results are largely generalizable to similar populations of 

families living on or near, and operating, family farms. However, overall, this study provides 

very little evidence consistent with the hypothesis that OP pesticide exposure among males 

causes an increase in the risk of miscarriage, stillbirth, pre-term delivery or small-for-gestational 

age outcomes. Some, but not all of the observed odds ratio estimates of the association between 

OP pesticides and adverse birth outcomes were greater than one, but most were small in 

magnitude, and none were statistically significant. Selection bias, confounding, and information 

bias are potential explanations for the negative findings, as is the limited statistical power to 

assess rare outcomes in this study. The information bias, in particular, is likely to have resulted 

in attenuation of the true (unobserved) associations, toward (observed) associations that are 
relatively smaller, or null. Differential recall bias, and the other biases too, may have also 

resulted in observed associations that are greater in magnitude than the true association between 

male pre-conception exposure to agricultural OP pesticides and subsequent adverse birth 

outcomes. 

References cited

Wilcox AJ, Horney LF. Accuracy of spontaneous abortion recall. American Journal of 

Epidemiology. 1984;120:727-33.

Study 30. Wickerham et al. (2012)

Reduced birth weight in relation to pesticide mixtures detected in cord blood of full-term 

infants. Erin L. Wickerham, Betsy Lozoff, Jie Shao, Niko Kaciroti, Yankai Xia, John D. 

Meeker. Environment International 47:80–85, 2012.

Study Summary

Wickerham et al. reported on results of a cross-sectional pilot study evaluating differences in 

birth weight associated with prenatal OP and other non-persistent pesticides quantified in 

umbilical cord blood samples of children born to healthy mothers living in a rural area of China. 

This pilot study was set in Zhejiang Province, using data collected from a subset of healthy 

pregnant women participating in a previously initiated study of iron deficiency and 

neurodevelopment. Pregnant women at 36 weeks gestation with an apparently healthy, 

uncomplicated, singleton pregnancy were recruited from a Maternal and Children's hospital and 

invited to participate in the study. Exclusion criteria included prevalent chronic diseases, 

complicated pregnancies, and hereditary or metabolic diseases. Over 99% of eligible pregnant 

women agreed to participate in the original study. Consecutive participants in the original iron 

deficiency study with due dates between April and June, 2009 were included in this pilot study 

of pesticide exposure effects on birth weight. The final study sample consisted of 112 of 116 

pregnant women who gave birth to full-term infants and for whom cord blood samples were 

analyzed for pesticides; Two women for whom demographic information was unavailable, one 

woman with missing maternal hemoglobin levels at delivery, and one women whose data were 

observed to be highly influential were excluded from the multivariate analyses. 

The mother’s demographic information and medical history were gathered from medical records 

during two prenatal visits (~16 weeks and ~36 weeks gestation), and additional maternal and 

neonate characteristics, including birth weight, were obtained from medical records from the 

delivery.

A 30 ml umbilical cord blood sample was collected after delivery of the child, processed, and 

shipped to Institute of Toxicology at Nanjing Medical University for pesticides residue 

quantification. The 20 pesticides evaluated were chosen based on pesticide usage data as well as 

availability of analytical standards, method compatibility, and preliminary data. The OP 

pesticides included chlorpyrifos, diazinon, fonofos, malathion, parathion-ethyl, parathion-
methyl, profenofos, and terbufos. Concentrations of the pesticides in cord serum were analyzed 

by GC and DSQ mass spectrometry. More than half of all OP pesticide concentrations in the 

cord blood samples were below the lower level of detection (LOD); For 5 of 8 OP pesticides 

analyzed, 75% of the concentrations were not detectable in the cord blood samples. For the 

analyses in which individual pesticide concentrations were included in a model as a continuous 

variable, levels below the lower LOD were assigned a value of the LOD/√2.

Three pesticide exposure metrics were defined for subsequent analysis: the number of pesticides 

detected in the cord blood sample, presence or absence of individual pesticides (assessed only for 

pesticides detected in samples from at least four subjects), and a 3-level ordinal variable 

(concentrations below the LOD, medium concentrations, and high concentrations defined by the 

median among detectable pesticide levels).

 

Multivariate linear regression models constructed that adjusted a priori for gestational age, 

maternal age, maternal BMI at early pregnancy, and maternal hemoglobin at delivery. Newborn 

sex and newborn serum ferritin were also considered as covariates but were not empirically 

associated with both pesticide exposure and birth weight in the study sample and where therefore 

not included in final models. Regression diagnostics were conducted, including assessment of 

influential observations; those with a studentized residual greater than 3 or less than −3 were 

considered influential. As mentioned earlier, one observation with a residual greater than 3 was 

not included in final models.

No statistically significant associations were observed between the number of OP pesticides 

detected in cord blood and birth weight. Similarly, no differences in mean birth weight were 

observed between those with OP pesticides classified as a dichotomous variable or as a threelevel ordinal variable. 

Study Review

The interpretation of the null results of this pilot study conducted among healthy Chinese women 

and their babies living in a rural area of China is hampered by the cross-sectional design and 

especially by the large proportion of cord blood samples in which OP pesticide residues were not 

detectable. 

Selection of participants was reasonable, though based largely on convenience. The sample size 

was small but adequate for a pilot study. 
The cord blood pesticide biomarker assessment was well conducted, though the exposure 

classification based on the number of detectable pesticide residues present in the sample is not 

directly applicable to the assessment of OP pesticide exposure effects. The authors reasoning for 

using the number of pesticides detected as their primary exposure metric was based on the 

observation that humans are exposed to multiple environmental toxicants which may exert 

synergistic effects. More likely, though, this decision was one of convenience, and guided by the 

observation of very few detectable levels of many of the pesticides in the cord blood samples. 

The selection and consideration of covariates for inclusion in multivariate regression models was 

appropriate. The multivariate modeling process was also reasonable.

This study provides no evidence consistent with the hypothesis that prenatal OP pesticide 

exposures affect birth weight. The quantification of a large number of pesticide residues in cord 

blood specimens is a novel approach to evaluating prenatal exposure effects on birth outcomes. 

However, the sensitivity of the analytic methodology was largely insufficient to detect pesticide 

residues in this population.
Study 31. Naksen et al (2005)

Naksen W, Prapamontol T, Mangklabruks A, Chantara S, Thavornyutikarn P, Srinual N, 

Panuwet P, Ryan PB, Riederer AM, Barr DB. Associations of maternal organophosphate 

pesticide exposure and PON1 activity with birth outcomes in SAWASDEE birth cohort, 

Thailand. Environmental Research142: 288–296, 2015.

Study Summary

Naksen W., et al., (2015) evaluated the environmental chemical exposures and their relation to 

birth outcomes and infant neurodevelopment in 52 pregnant farmworkers in Fang district, 

Chiang Mai province, Thailand. This cohort is named, the Study of Asian Women and 

Offspring's Development and Environmental Exposures (SAWASDEE) cohort. A large dataset 

was collected during pregnancy including urine samples, three blood samples, and by using a 

questionnaire. The authors investigated the paraoxonase1 (PON1) activities, changes in maternal 

acetylcholinesterase (AChE) and their relation to urinary dialkylphosphates (DAPs) metabolites 

of OP pesticides, during pregnancy. Maternal AChE, butyrylcholinesterase (BChE), and (PON1) 

activities were measured three times (at enrollment; 32 weeks of pregnancy and at delivery) 

during pregnancy, and six urinary DAP concentrations [including di- methylphosphate (DMP), 

dimethylthiophosphate (DMTP), di- methydithiophosphate (DMDTP), diethylphosphate (DEP), 

diethylthiophosphate (DETP), and diethydithiophosphate (DEDTP)] were measured in urine 

samples on average 8 times during pregnancy (from enrollment until delivery). In this study, a 

direct correlation between maternal biomarkers of pesticide exposure (as measured by urinary 

DAPs) and negative birth outcomes (head circumference and birth weight) was only observed 

after stratification by PON1 phenotype. However, an association between maternal enzyme 

activities and negative birth outcomes was not observed. Among the individuals in the group 

with low maternal PON1 activity (n=23), new born head circumference was inversely correlated 

with log10 maternal ΣDEAP (molar sum of DEP, DETP and DETDP) and ΣDAP (molar sum of 

all six DAPs), at enrollment (gestational age = 12 ± 3 weeks; β= -1.0 cm, p= 0.03 and β= -1.8 

cm, p< 0.01, respectively), and at 32 weeks pregnancy (β = - 1.1cm, p = 0.04 and β = - 2.6 cm, 

p= 0.01, respectively). Furthermore, among these mothers, new born birthweight was also 

inversely associated with log10 maternal ΣDEAP and ΣDAP at enrollment (β= - 219.7g, p= 0.05 

and β= - 371.3 g, p= 0.02, respectively). Associations between maternal DAP levels and 

newborn outcomes (birth weight, length and head circumference) were not observed in the group 

of mothers with high PON1 activity. This study highlights the finding of the negative 

association of prenatal OP exposure and birth outcomes especially in low PON1 activity 

mothers.

Study Review
In reviewing this study, a few errors (for example, accuracy of statistical analysis of association 

between urine cumulative DAPs and birth outcomes, stratified by maternal PON1 phenotype; 

and authors did not show adjustment for multiple comparisons) were identified in the data tables, 

raising concerns about the validity of the study results. Given these errors, the small sample size 

(N=59), and the lack of discussion of study weaknesses, this study was rated to be of low quality 

overall.