Epidemiology Studies Pertaining to Chlorpyrifos Exposures: 

Considerations of Reliability and Utility 

Debra Edwards, Ph.D., Independent Consultant 

Daland Juberg, Ph.D., ATS, Dow AgroSciences 

Carol Burns, Ph.D., MPH, The Dow Chemical Company 

Julie Goodman, Ph.D., DABT, Gradient 

Abby Li, Ph.D., Exponent 

Michael Bartels, Ph.D., The Dow Chemical Company 

Darin Lickfeldt, Ph.D., Dow AgroSciences 

Summary 

The utility and application of epidemiology data in risk assessment and regulatory decisionmaking has received considerable attention in recent years and continues to be vetted by the U.S. 

Environmental Protection Agency (USEPA) when evaluating chemical risk to human 

populations (e.g., SAP 2010). For the insecticide chlorpyrifos, there exists a growing number of 

studies that may inform the risk assessment for this chemical, although one cohort investigated 

by Columbia University is being considered by the USEPA as providing evidence for the 

relationship between chlorpyrifos exposure and children’s development and cognitive function 

(i.e., Rauh et al., 2006, Rauh et al., 2011; Whyatt et al., 2004). A critical analysis of published 

information from varying scientific disciplines and perspectives reveals that findings from this 

singular cohort have limitations, including reliability of reported results, exposure to other risk 

factors, lack of reproducibility of findings in other studies, and incompatibility with the 

voluminous toxicology database for chlorpyrifos (Eaton et al., 2008; Prueitt et al., 2011; Li et 

al., 2012; Burns et al., 2013). In fact, the European Food Safety Authority (EFSA) recently 

concluded in its review on epidemiological studies linking exposure to pesticides and health 

effects that there is “no evidence” to suggest an association between pesticide exposure and 

neurodevelopmental related outcomes, due to a number of deficiencies in the available data 

(Ntzani et al., 2013). This EFSA review included neurodevelopment/IQ studies on chlorpyrifos 

that were published in 2006 and later. The totality of problems relating to the reliability of the 

reported findings on the Columbia cohort renders the study inappropriate for risk assessment. 

The study is not useful for informing the question of whether neurodevelopmental effects occur 

at exposure levels lower than those associated with acetylcholinesterase inhibition or for 

"bounding" dose-response estimates from animal studies. 

The following are key reasons for our position: 

1. The analytical method used in the Columbia study has not been validated at the low 

concentrations reported in maternal/cord blood from Columbia study subjects. Also, the 

exposure assessment picture is incomplete for chlorpyrifos (and other chemical 

exposures), given that the reported effects on neurodevelopment (which is a continuous 

process throughout pregnancy and during early infant and childhood years) are predicated 

upon a single exposure measurement (snapshot in time). 
2

2

2. There is a lack of credible scientific evidence to support the biological plausibility of the 

Columbia cohort findings at the exposures reported. The animal database for chlorpyrifos 

is one of the most robust across all chemistries and it is not possible to explain adverse 

neurodevelopmental effects occurring below the threshold point of departure for 

acetylcholinesterase without significant speculation and conjecture. 

3. Chlorpyrifos cannot reliably be deemed as a causal factor for the reported 

neurodevelopmental effects. There are credible alternative explanations for the observed 

effects. In particular, influences of other chemical and nonchemical stressors could 

contribute to or account for the reported associations of impaired neurodevelopment in 

the Columbia study. Also many of the outcomes reported may be chance occurrences, 

given the methods used to assess cognitive function. 

4. When considering the specificity of biomarkers for chlorpyrifos exposure and lack of 

concordance across reported outcomes, the results reported in the Columbia study have 

not, in effect, been replicated or confirmed in other independent studies. 

5. Although sufficient information is available to identify the serious limitations with the 

Columbia study, nonetheless the data on which the Columbia study findings are based 

have not been shared in a public format for further independent evaluation by either 

government agencies or other interested investigators. This is not only counter to the 

principles of transparency in federally funded research, but precludes further scientific 

analysis which could ultimately assist in rendering a more informed and objective 

analysis of the data. 

1. The analytical method used in the Columbia study has not been validated at the low 

concentrations reported in blood:

Because a majority of samples from the Columbia cohort are below the validated limit 

of detection (LOD) for chlorpyrifos analysis in plasma/serum, any conclusions 

regarding outcomes and associated exposure based on chlorpyrifos levels < 15 

picograms (pg)/gram (g) are not reliable. This impacts the reliability of the correlation 

analyses between exposures and most outcomes since the study dichotomized exposure 

as “low” and “high” using 6.17 pg/g as its cut point (Whyatt et al., 2004; Rauh et al., 

2006). When all values are used in linear analyses, such as when evaluating IQ (Rauh 

et al., 2011), there may be substantial misclassification of exposure. 

It is a basic foundation of the scientific process that researchers must show that a 

quantitative exposure measurement is accurate, precise, and reproducible across the 

range of values determined within a study. For example, the USEPA method validation 

guidelines call for replicate determinations of analyte recovery from a given matrix 

(substrate) down to the stated LOD (USEPA 1998). However, this has not occurred 

within the Columbia study. There were no data generated during validation of the 

plasma/serum analysis method (Barr et al., 2002) or during the subsequent analysis of 

the Columbia cohort samples to show that chlorpyrifos levels could be accurately 

measured in plasma/serum matrix down to the stated LOD of 0.5-1 pg/g (note: authors 
3

3

use LOD term when discussing limit of quantitation). The lowest concentration for 

which analyte recovery in plasma/serum was determined using this method was 15 

pg/g. This is a critical point, as more than 80% of the Columbia subjects had levels 

below this validation level. Further, there was no evaluation of possible sample 

contamination during blood collection in the hospital, processing to plasma, or during 

shipment to the CDC. Analysis of sample integrity is a critical parameter of all 

biomonitoring studies, especially those at the trace levels reported for this cohort. Note 

that Barr et al. (2002) also reported background chlorpyrifos levels of 9 pg/g in control 

serum samples, 50% higher than the “high” exposure Columbia cohort criteria, the 

source of which was never determined. Finally, the CDC has stated that chlorpyrifos 

blood measurements from the 2003-2004 NHANES survey will not be released because 

the CDC lab was not able to meet its own QC/QA (Quality Control/Quality Assurance) 

criteria for the assay (personal communication, CDC). This is the same method used in 

the Columbia study, so any decisions based on the use of such methodology should be 

highly scrutinized. 

2. There is not a supportable basis for biological plausibility: 

Based on a consideration of all available data, acetylcholinesterase inhibition (AChEI) data 

remain the most sensitive and robust source of dose-response data for deriving points of 

departure for chlorpyrifos (EPA SAP 2012, p. 28). Currently, there is no established biological 

mode of action to explain the potential neurodevelopmental effects reported in the Columbia 

study (EPA SAP 2012, p.30). Based on reliable animal experimentation, neurodevelopmental 

and/or behavioral effects have been reported at higher exposures, i.e., at or above 1.0 mg/kg 

body weight per day which appears to be a threshold below which neurodevelopmental effects 

have not been reported (Li et al., 2012; Maurissen et al., 2000; EPA SAP 2012, p. 36). As noted 

by the SAP in 2012 (p.36), ” . . . effects of CPF at 1 mg/kg are difficult to interpret because of 

methodological limitations, inconsistencies, and variation in study design, sometimes lack of 

control for litter effects, oversampling issues, behavioral methods used, and lack of doseresponse findings. At doses exceeding 1 mg/kg, the data show somewhat more consistency, but 

even here, dose response experiments are the exception.” 

The threshold of 1 mg/kg/day is 30-fold higher than the threshold of 0.03 mg/kg/day for 

the most sensitive red blood cell (RBC) AChEI metric (USEPA 2011 p. 25). The 

quantitative dose response data for AChEI are especially robust and comprehensive, 

and include data at the time of peak effect from different ages including rat fetus, young 

pups, and pregnant and non-pregnant adult rats (Mattsson et al., 2000; Maurissen et al.,

2000, Marty and Andrus, 2010). 

This threshold of 1 mg/kg/day is also at least 5,000 times higher than estimated 

exposures from the Columbia study. Lowe et al. (2009) estimated prenatal chlorpyrifos 

exposure levels in the Columbia study to be 0.15 ug/kg/day based on mean maternal 

and cord blood concentrations reported by Whyatt et al., 2005. These dose levels do 

not produce RBC AChEI in humans (Garabrant et al., 2009; Farahat et al., 2011). 

Using a biomonitoring equivalent approach, all blood concentrations for the Columbia 

study subjects, as well as those of other epidemiology cohorts, were predicted to be 

well below the level of RBC AChE inhibition (see Attachment A). 
4

4

One hypothesis that has been put forth is that the neurodevelopmental effects at these 

low dose levels are a result of hypothetical non-cholinergic modes of action reported in 

the animal literature. However, as discussed previously, the animal literature indicates 

that dose levels that cause adverse neurodevelopmental outcomes only occur at 

exposures that inhibit AChE in pregnant rats or offspring (Li et al., 2012; Prueitt et al., 

2011). Thus, the scientific data support that neurodevelopmental effects attributed to 

chlorpyrifos in the rodent occur at doses at or above 1 mg/kg/day. Based on the animal 

model, it would take significant conjecture and speculation to conclude that altered 

neurodevelopment in humans resulting from non-cholinergic pathway perturbations 

would occur at doses lower than those associated with AChE inhibition. 

3. There are credible alternative explanations for the neurodevelopmental effects observed in the 

Columbia study: 

Chlorpyrifos cannot reliably be deemed a causal factor for the neurodevelopmental effects 

reported by Columbia University. Alternative explanations are credible and present themselves 

logically when considering exposure measurement error (as discussed under point #1 and 

below), the incompatibility with the rodent model (as discussed under point #2), methodological 

issues with analysis of data (as discussed below and in Attachment B), exposure to other toxic 

chemicals, including neurotoxicants, and the published literature documenting that children who 

grow up in poverty or low income households have difficulties with neurocognitive function. In 

commenting on the Columbia University study findings, an independent group of experts 

acknowledged, “The authors attempted to control for confounding factors, including other 

known neurodevelopmental risk factors in this inner-city cohort, such as maternal perinatal 

smoking and alcohol; nevertheless, it is difficult to dismiss the contribution of these and perhaps 

other confounding factors” (Eaton et al., 2008). 

The mothers and children within the Columbia study who had measurable exposures to 

chlorpyrifos were also exposed to other chemicals that have the potential to subtly or profoundly 

affect child neurodevelopment. For example, the Columbia cohort was exposed to polycyclic 

aromatic hydrocarbons (PAHs), which were reported to be associated with neurodevelopmental 

effects in these same children (Perera et al., 2006). Also, lead levels are an important variable in 

the Columbia study, especially for low-income families living at or near the poverty level. Blood 

lead levels have consistently been correlated with IQ loss (Healey et al., 2010), as well as 

achievement and behavioral deficits (Chandramouli et al., 2009). Lead levels were not properly 

controlled in the Columbia study (Rauh et al., 2006; 2011) for the entire sample, and it is 

plausible that associations between chlorpyrifos and neurodevelopmental effects could be 

partially or wholly attributable to lead (see Attachment B). 

Poverty and pesticide exposure are highly correlated. Mothers and children who live in crowded, 

substandard housing are more likely to encounter exposure to multiple and heavily applied 

pesticides, both legal and illegal (e.g., Morbidity and Mortality Weekly,1997). Indeed, a survey 

of the Columbia cohort indicated that pesticide use was frequent (Whyatt et al., 2002). It has 

been proposed that insecticide exposure (regardless of the chemical) may be a marker for insect 

infestation (and other related factors) and may not itself be the causal agent driving the 

neurodevelopmental results (Burns et al., 2013). In fact, the Columbia authors reported an 
5

5

association with the Bayley Scales of Infant Development (BSID) and piperonyl butoxide, a 

synergist used with pyrethrins and synthetic pyrethroid insecticides, which replaced the use of 

chlorpyrifos in residential settings after 2001. 

It is well documented in the literature that social hardships related to poverty and maternal 

depression can affect scores on intelligence tests and other measures of cognitive ability (e.g., 

Luby et al., 2013; Duncan and Brooks-Gunn, 1997; Feinstein, 2003; Canadian Paediatric 

Society, 2004; center on the Developing Child at Harvard University, 2009). In the Columbia 

study (Rauh et al., 2006), neurodevelopmental effects were only observed at 3 years of age, not 

before. As the children age from birth to 3 years, there are a number of other well-known 

nonchemical risk factors that affect brain development. Efforts were made by the Columbia 

study investigators to account for certain risk factors, including the influence of race/ethnicity, 

gestational age, maternal education and maternal IQ (albeit, there were missing IQ data for 

several dozen women in the study). Observational data on the quality of the home care-taking 

environment were also considered, but it is unclear to what extent key risk factors were 

addressed. For example, information was collected on mothers’ feelings and state of mind but 

there is no indication that these potential risk factors were explicitly addressed. Interestingly, 

maternal depression was a significant factor for influencing childhood behavior, as modeled by 

the UC Berkeley investigators (Eskenazi et al., 2007; Marks et al., 2010). 

Despite efforts made by the Columbia study investigators to account for other risk factors, the 

influences of other chemical and nonchemical stressors which could contribute to or account for 

the observed associations of impaired neurodevelopment cannot easily be attributed to the 

independent effects of a single chemical (i.e., chlorpyrifos) in the multi-chemical exposure 

scenario experienced by the Columbia cohort, particularly spanning a multi-year period that 

encompasses an important period of sequential neurodevelopment (e.g., SAP, 2012; Eaton et al., 

2008). Any inferences based on the Columbia study regarding the degree to which chlorpyrifos 

contributes to the measured outcomes cannot be separated easily from other risk factors, and thus 

the study cannot be used to reliably address the question of whether chlorpyrifos can cause 

neurodevelopmental effects at the exposure levels reported. Although it is legitimate for 

academic scientists to propose and investigate hypotheses, the Columbia study cannot serve as a 

reliable basis for addressing key questions regarding a single chemical in a regulatory risk 

assessment. 

Another significant weakness of the Columbia study relates to the exposure data, i.e.,

measurements of chlorpyrifos do not reflect exposure over time. Evaluations of 

neurodevelopmental scores/function on the cohort continued into childhood and early 

adolescence, which is well beyond the single snapshot in time of chlorpyrifos measurement. This 

is especially pertinent since neurodevelopment occurs both prenatally and postnatally, essentially 

a continuous process throughout early infant and childhood years (Selevan et al., 2000). The 

Columbia University study focused exclusively on prenatal exposure as measured by 

cord/maternal blood measures of chlorpyrifos within two days of birth. Furthermore, the 

maternal and cord blood measurements represent a single sample, or snapshot (i.e., only one 

point in time), collected for convenience (at birth) and with no information regarding the 

chlorpyrifos home application. Given the rapid metabolism of chlorpyrifos in humans and 

subsequent short residence time in the body, a single sample obtained at the time of delivery or 

shortly after would have little relationship or meaning to exposure levels that were present during 
6

6

most of the pregnancy (or thereafter). Also, as discussed earlier in this paper (Point #1), the 

chlorpyrifos blood measurements cannot be deemed accurate. The inadequate investigation on 

exposures to either chlorpyrifos or other pesticides and chemicals (e.g., polycyclic aromatic 

hydrocarbons, lead, etc.) results in an incomplete exposure picture. 

Lastly, there are issues regarding how cognitive testing was assessed in the Columbia cohort 

(Rauh et al., 2006) raising the question of whether the reported associations with chlorpyrifos are 

real or not. Briefly, the cohort was inappropriately dichotomized into two exposure groups and 

use of a cut-off of a standard score of “85” for BSID scores to denote children as “High Risk” is 

an arbitrary decision. Also, the “multiple simultaneous” comparisons in Rauh et al. 2006 and 

2011 can lead to chance errors (see Attachment B for more details). 

4. Adverse results reported in the Colombia study are not found in other populations: 

An important aspect of determining the validity of an epidemiology study is whether findings 

can be reproduced; that is, associations between similar outcomes and exposures to the chemical 

of interest should be found in different populations. Chlorpyrifos is measured in different ways 

across studies, with some measuring chlorpyrifos itself, and others measuring other biomarkers 

that represent exposure to chlorpyrifos and other chemicals, such that exposure to chlorpyrifos 

itself cannot be teased out. The order of reliability of biomarkers is as follows: chlorpyrifos > 

3,5,6-trichloro-2-pyridinol (TCPy) > diethylphosphates (DEPs). The metabolite DEP can reflect 

exposure to pesticides other than chlorpyrifos. TCPy and DEPs in urine can also result from 

exposure to these OP metabolites in food or the environment rather than to chlorpyrifos or other 

OPs. 

When considering the order of reliability of biomarkers, the results are not consistent across the 

existing epidemiology studies. (See Attachment C of this document for details). Specifically, 

studies at Mount Sinai Hospital and the University of California (UC) at Berkeley do not confirm 

the results reported by the Columbia University researchers (Eaton et al., 2008; Prueitt et al., 

2011; Li et al., 2012; Burns et al. 2013). The Mount Sinai (Berkowitz et al., 2004; Engel et al.,

2011) and UC Berkeley (Eskenazi et al., 2004: Eskenazi et al., 2007; Marks et al., 2010; 

Bouchard et al., 2011) studies report some neurodevelopmental effects associated only with 

DEP, a less specific biomarker. Outcomes associated with the more specific biomarker, TCPy, 

are either not tested or not analyzed. Further, there are two new epidemiology studies that have 

not observed consistent associations with birth weight or developmental outcomes. Two of these 

studies measured chlorpyrifos or TCPy with reported exposure levels higher than (China cohort; 

Wickerham et al., 2012) or comparable to (Mexico City cohort; Fortenberry et al., 2013) the 

Columbia or UC Berkeley studies. Although these studies did not investigate all of the outcomes 

measured in the Columbia study, findings for endpoints that were evaluated do not confirm 

findings from the Columbia study (Rauh et al., 2006 and 2011; Whyatt et al., 2004). Based on 

epidemiological data published through 2007, Eaton et al. (2008) also concluded that there were 

no consistent associations observed when neurodevelopmental outcomes of the Columbia, 

Mount Sinai, and Berkley studies were compared. 

 

 
7

7

5. Data access has not been provided: 

Transparency and documentation of the decision process are at the core of a credible 

risk assessment. EPA’s Office of Pesticide Programs has a long history of transparency 

as well as data disclosure in risk assessments to ensure the credibility of its registration 

and reevaluation decisions. OPP’s transparency in its risk assessments and decisionmaking adheres to President Barack Obama’s January 21, 2009 Memorandum to Heads 

of Executive Departments and Agencies on “Transparency and Open Government” 

(Obama, 2009). Given the concerns about the reliability of exposure assessment in the 

Columbia study, there would be value in accessing the data for the purposes of 

exposure (dose) reconstruction and review of the health effect analyses. Similarly, the 

UC Berkeley and Mount Sinai studies (Eskenazi et al., 2007; Marks et al., 2010; 

Bouchard et al., 2011; Engel et al., 2011) conducted no health analyses using 

chlorpyrifos in cord blood or with urinary TCPy after age two. Access to and 

independent analyses of these data would also be informative to determine the 

reliability of the Columbia results. 

OPP has indicated publicly, “The studies that are the most relevant and informative to risk 

assessment are those that clearly and fully describe study design, conduct and methods, as well 

as providing access to the underlying data” (http://www.epa.gov/pesticides/science/literaturestudies.html). OPP has considered the Columbia study, which is a federally funded study, as a 

source of data intended for consideration in its chlorpyrifos risk assessment (see SAP 2008; 

2012). However, though DowAgroSciences has made repeated requests through the Freedom of 

Information Act (FOIA) to the Agency to obtain the Columbia data, there is a restriction placed 

on data access by the authors. Thus, independent verification of the analyses (including an 

evaluation of different cutoff points for exposure and BSID outcomes) and the ability to answer 

specific questions regarding the Columbia study (e.g., other risk factors) are not possible by 

DowAgroSciences, EPA scientists, or the public. This lack of access is counter to the recent 

February 22, 2013 John P. Holdren Memorandum to Heads of Executive Departments and 

Agencies on “Increasing Access to the Results of Federally Funded Scientific Research” 

(Holdren, 2013). Thus, any significant cited line of evidence in OPP’s chlorpyrifos risk 

assessment should be based on accessible data sets that allow for independent analysis and 

verification of conclusions. We acknowledge the importance of protecting the privacy of the 

subjects in epidemiology studies, but there are well-recognized and accepted ways to provide 

data on cohort subjects while protecting the privacy of the subjects. Given the problems and 

complex issues involved with the chlorpyrifos cohort data, including the type of cognitive 

assessment used, a more thorough and multidisciplinary scientific review is needed, which 

provides some access to the data and includes pediatricians, epidemiologists, clinicians and 

neuropsychologists experienced in evaluation of pediatric cognitive function. 

Conclusions: 

Despite not having access to the data published by Columbia University, there is sufficient 

information available to conclude that there are serious limitations that impact their utility and 

reliability in risk assessment. The Columbia study is not suitable as a basis to "bound" doseresponse estimates from animal studies or to inform whether neurodevelopmental effects occur at 

exposure levels lower than those associated with AChEI. This is because of the difficulty of 
8

8

disentangling the potential of other chemical and nonchemical stressors to account for or 

contribute to the observed associations. Further, the analytical method used in collecting plasma 

biomonitoring data to address the issue of whether any health outcome could potentially occur 

below exposure levels resulting in AChEI has not been adequately validated. The incompatibility 

with the rodent model and the lack of biological plausibility for chlorpyrifos causing 

neurodevelopmental outcomes in children at estimated exposure levels, as well as the lack of 

consistency with other populations, indicate that any reported statistical associations within the 

Columbia study are likely due to factors other than chlorpyrifos exposure. The data are not 

accessible for public viewing and independent analysis, which is counter to the basic tenets of 

transparency in government-funded research. Confidence in the reliability of the conclusions for 

risk assessment-based decisions is inseparably tied to transparency and transparency cannot be 

achieved when data access is denied. Collectively, these represent very compelling and 

independent bases for precluding the use of the Columbia study data in an evaluation of exposure 

and effect for chlorpyrifos or for calling into question the robust and comprehensive animal 

database on pre- and postnatal toxicity and its adequacy to characterize the dose-response curve 

at lower dose levels for the young. 

References Cited: 

Barr, D. B., Barr, J. R., Maggio, V. L., Whitehead, R. D., Jr., Sadowski, M. A., et al. (2002). A 

Multi-Analyte Method for the Quantification of Contemporary Pesticides in Human Serum and 

Plasma Using High-Resolution Mass Spectrometry. J Chromatogr B Analyt Technol Biomed 

Life Sci 778:99-111. 

Berkowitz, G.S., Wetmur, J., Birman-Deych, E., Obel, J., Lapinski, R.H., Godbold, J.H., 

Holzman, I.R., Wolff, M.S. (2004). In utero pesticide exposure, maternal paraoxonase activity, 

and head circumference. Environ Health Perspect, 112:388–391. 

Bouchard M. F., Chevrier J., Harley K.G., Kogut K., Vedar M., Calderon N., Trujillo C., 

Johnson C., Bradman A., Barr D.B., Eskenazi B. (2011). Prenatal Exposure to Organophosphate 

Pesticides and IQ in 7-Year Old Children. Environ Health Perspect. 119:1189-1195. 

Burns, C. J., McIntosh, L. J., Mink, P. J., Jurek, A. M., Li, A. A. (2013)., Pesticide Exposure and 

Neurodevelopmental Outcomes: Review of the Epidemiologic and Animal Studies. J Toxicol 

Environ Health B Crit Rev 16:127-283. 

Canadian Paediatric Society. (2004). Maternal depression and child development. Paediatr. Child 

Health 9(8):575-583. 

Center on the Developing Child at Harvard University (2009). Maternal Depression Can 

Undermine the Development of Young Children. Working Paper No. 8, 

http:/www.developingchild.harvard.edu. 

Chandramouli, K., Steer, C. D., Ellis, M., and Emond, A. M. (2009). Effects of early childhood 

lead exposure on academic performance and behaviour of school age children. Archives of 

Disease in Childhood, 2009. 94:844-8. 
9

9

Duncan, G.J. and J. Brooks-Gunn (eds) (1997), Consequences of growing up poor. New York, 

N.Y.: Russell Sage Foundation. 

Eaton D.L., Daroff R.B., Autrup H., Bridges J., Buffler P., Costa L.G., Coyle J., McKhann G., 

Mobley W.C., Nadel L., Neubert D., Schulte-Hermann R., Spencer P.S. (2008). Review of the 

toxicology of chlorpyrifos with an emphasis on human exposure and neurodevelopment. Crit 

Rev Toxicol. 38 Suppl 2:1-125. 

Engel, S.M., Wetmur, J., Chen, J., Zhu, C., Barr, D.B., Canfield, R.L., Wolff, M.S. (2011). 

Prenatal exposure to organophosphates, paraoxonase 1, and cognitive development in childhood. 

Environ Health Perspect. 118:1182-8. 

Eskenazi, B., Harley, K., Bradman, A., Weltzien, E., Jewell, N. P.,et al. (2004). Association of in 

utero organophosphate pesticide exposure and fetal growth and length of gestation in an 

agricultural population. Environ Health Perspect. 112(10):1116-24. 

Eskenazi,B., Marks, A.R., Bradman, A., Harley, K., Barr, D.B., Johnson, C., Morga, N., and 

Jewell N.P. (2007). Organophosphate pesticide exposure and neurodevelopment in young 

Mexican-American children. Environ Health Perspect. 115(5):792-798. 

Farahat, F.M., Ellison, C.A., Bonner, M.R., McGarrigle, B.P., Crane, A.L., et al., (2011). 

Biomarkers of chlorpyrifos exposure and effect in Egyptian cotton field workers. Environ. 

Health Perspect. 119(6):801-6. 

Feinstein, L. (2003). Inequality in the early cognitive development of British children in the 1970 

cohort. Economica,70(277),73-98. doi: 10.1111/1468-0335.t01-1-00272. 

Fortenberry, G. Z., Meeker, J. D., Sanchez, B. N., Barr, D. B., Panuwet, P., et al. (2013). 

Urinary 3,5,6-Trichloro-2-Pyridinol (Tcpy) in Pregnant Women from Mexico City: Distribution, 

Temporal Variability, and Relationship with Child Attention and Hyperactivity. Int J Hyg 

Environ Health. pii: S1438-4639(13)00112-0. doi: 10.1016/j.ijheh.2013.07.018. 

Garabrant, D.H., Aylward, L.L., Berent, S., Chen, Q., Timchalk, C; et al. (2009). Cholinesterase 

inhibition in chlorpyrifos workers: Characterization of biomarkers of exposure and response in 

relation to urinary TCPy. J. Expo. Sci. Environ. Epidemiol. 19(7):634-42. 

Healey, N., Jones-Otazo, H., Walker, M., and Knafla, A. (2010). Toxicological Review and 

Recommended Toxicological Reference Values for Environmental Lead Exposure in Canada. 

FINAL REPORT. Prepared under contract to Health Canada. Prepared for the Contaminated 

Sites Division, Safe Environments Directorate, Healthy Environment and Consumer Safety 

Branch, Health Canada, Ottawa. 

Holdren, John P. (2013), Memorandum for Heads of Executive Departments and Agencies: 

Increasing Access to the Results of Federally Funded Scientific Research. February 22. 
10 10

Horton, M. K., Rundle, A., Camann, D. E., Barr, D., Rauh, V. A., et al. (2011). Impact of 

Prenatal Exposure to Piperonyl Butoxide and Permethrin on 36-Month Neurodevelopment. 

Pediatrics 127:699-706. 

Li, A., Lowe, K.A., McIntosh, L.J., Mink, P.J. (2012). Evaluation of epidemiology and animal 

data for risk assessment: chlorpyrifos developmental and neurobehavioral outcomes. J. Toxicol. 

Env. Health. Part B. 15:109-184. 

Lowe, E. R., Poet, T. S., Rick, D. L., Marty, M. S., Mattsson, J. L., et al. (2009). The Effect of 

Plasma Lipids on the Pharmacokinetics of Chlorpyrifos and the Impact on Interpretation of 

Blood Biomonitoring Data. Toxicol Sci 108:258-272. 

Luby, J. V., Belden, A., Botteron, K., Marrus, N., Harms, M.P. et al. (2013). The Effects of 

Poverty on Childhood Brain Development: The Mediating Effect of Caregiving and Stressful 

Life Events. O JAMA Pediatr. Published online October 28, 2013. 

doi:10.1001/jamapediatrics.2013.3139. 

Marty, M.S., Andrus, A.K., Bell, M.P., Passage, J.K., et. al. (2012). Cholinesterase inhibition and 

toxicokinetics in immature and adult rats after acute or repeated exposures to chlorpyrifos or 

chlorpyrifos-oxon. Reg. Toxicol. Pharmacol. 63:209-224. 

Mattsson, J.L., Maurissen, J.P.J., Nolan, R.J., and Brzak, K.A. (2000). Lack of differential 

sensitivity to cholinesterase inhibition in fetuses and neonates compared to dams treated 

perinatally with chlorpyrifos. Tox. Sci. 53:438-446. 

Maurissen, J.P.J., Hoberman, A.M., Garman, R.H., and Hanley Jr., T.R. (2000). Lack of 

selective developmental neurotoxicity in rat pups from dams treated by gavage with chlorpyrifos. 

Tox. Sci. 57:250-263. 

Marks, A.R., Harley, K., Bardman, A., Kogut, K., Barr, D.B., Johnson, C., Calderon, N., 

Eskenazi, B. (2010). Organophosphate pesticide exposure and attention in young MexicanAmerican children: the CHAMACOS study. Environ. Health Perspect. 118:1768-74. 

Morbidity and Mortality Weekly (1997). Poisonings associated with illegal use of aldicarb as a 

rodenticide - New York City. 1994-1997. 46:961-963. 

Ntzani, E.E., Chondrogiorgi, M., Ntritsos, G., Evangelou, E., Tzoulaki, I. (2013). Literature 

review on epidemiological studies linking exposure to pesticides and health effects. EFSA 

supporting publication 2013:EN-497, 159 pp. 

Perera, F. P., Rauh V., Whyatt, R. M. et al. (2006). Effect of prenatal exposure to airborne 

polycyclic aromatic hydrocarbons on neurodevelopment in the first 3 years of life among innercity children. Environ. Health Perspect. 114(8):1287-1292. 

President Barack Obama (2009). Memorandum for the Heads of Executive Departments and 

Agencies: Transparency and Open Government. January 21. 
11 11

Prueitt, R.L., Goodman, J.E., Bailey, L.A., Rhomberg, L.R. (2011). Hypothesis-based weight-ofevidence evaluation of the neurodevelopmental effects of chlorpyrifos. Crit. Rev. Toxicol. 

41(10):822-903. 

Rauh, V. A., Garfinkel, R., Perera, F. P., Andrews, H. F., Hoepner, L. et al. (2006). Impact of 

Prenatal Chlorpyrifos Exposure on Neurodevelopment in the First 3 Years of Life among InnerCity Children. Pediatrics 118:e1845-1859. 

 Rauh, V., Arunajadai, S., Horton, M., Perera, F., Hoepner, L., Barr, D.B., and Whyatt, R. 

(2011). Seven-year neurodevelopmental scores and prenatal exposure to chlorpyrifos, a common 

agricultural pesticide. Environ. Health. Perspect. 119(8) 1196-1201. 

Selevan, S. G., Kimmel, C. A., Mendola P. (2000). Identifying critical windows of exposure for 

children's health. Environ. Health Perspect. (June); 108 (Suppl 3): 451-455. 

US EPA guidelines for Exposure and Risk Assessment Calculations (1998), Series 875- 

Occupational and Residential Exposure Test Guidelines: Group B- Post application Exposure 

Monitoring Test Guidelines, Version 5.4, Working Draft of February 10, 1998, Method 

Validation criteria pp. C6-7. 

US EPA Office of Pesticide Program. (2011). Chlorpyrifos:Preliminary Human Health Risk 

Assessment for Registration Review. DP No. D388070. 

US EPA, FIFRA Scientific Advisory Panel. (2008). A Set of Scientific Issues Being Considered 

by the Environmental Protection Agency Regarding: The Agency's Evaluation of the Toxicity 

Profile of Chlorpyrifos: Minutes of the FIFRA Science Advisory Panel Meeting held on 

September 16-18, 2008. SAP Minutes No. 2008-04. 80p. 

US EPA, FIFRA Scientific Advisory Panel. (2010). Incorporation of Epidemiology and Human 

Incident Data into Human Risk Assessment: Minutes of the FIFRA Science Advisory Panel 

Meeting held on February 2 - 4, 2010, at 

http://www.epa.gov/scipoly/sap/meetings/2010/020210meeting.html

US EPA, FIFRA Scientific Advisory Panel. (2012). A Set of Scientific Issues Being 

Considered by the Environmental Protection Agency Regarding Chlorpyrifos Health Effects: 

Minutes of the FIFRA Science Advisory Panel Meeting held on April 10-12, 2012. SAP 

Minutes No. 2012-04. 108p. 

Whyatt, R. M., Camann, D. E., Kinney, P. L., et al. (2002)., Resdiential pesticide use during 

pregnancy among a cohort of urban miority women. Environ. Health Perspect. 110:507-514. 

Whyatt, R. M., Rauh, V., Barr, D. B., Camann, D. E., Andrews, H. F. et al. (2004). Prenatal 

Insecticide Exposures and Birth Weight and Length among an Urban Minority Cohort. Environ 

Health Perspect 112:1125-1132. 
12 12

Whyatt, R. M., Camann, D., Perera, F. P., Rauh, V. A.,Tang, D. et al. (2005). Biomarkers in 

Assessing Residential Insecticide Exposures During Pregnancy and Effects on Fetal Growth. 

Toxicol Appl Pharmacol 206:246-254. 

Wickerham, E. L., Lozoff, B., Shao, J., Kaciroti, N., Xia, Y. et al. (2012). Reduced Birth Weight 

in Relation to Pesticide Mixtures Detected in Cord Blood of Full-Term Infants. Environ Int 

47:80-85. 
Attachment A: Consideration of AChE depression in Columbia study subjects 

The purpose of this attachment is to provide additional explanation supporting the prediction, 

based on the available biomonitoring data, that all blood concentrations for the Columbia study 

subjects, as well as those of other epidemiology cohorts, were well below the level of RBC AChE 

inhibition. 

It is cumbersome to compare chronic dose levels administered to animals with concentration 

levels observed in spot samples collected in humans. Biomonitoring equivalents (BE) address 

this problem. For chlorpyrifos, BE values were developed for blood CPF that are associated 

with a predicted maximum of 10% inhibition of red blood cell acetylcholinesterase (RBC AChE) 

using a physiologically based pharmacokinetic/ pharmacodynamic (PBPK/PD) model (Arnold et 

al., 2013). Inhibition of RBC AChE, while not part of the cholinergic toxicity pathway in the 

central nervous system, is a conservative marker of inhibition of brain AChE, since inhibition of 

these blood enzymes occurs pre-systemically in the liver during CPF metabolism, and is the 

USEPA regulated endpoint. 

There are four human studies in which chlorpyrifos was measured in cord blood and or maternal 

serum (Whyatt et al., 2004; Yan et al., 2009; Huen et al., 2012; Wickerham et al., 2012). The 

cord blood levels are shown for each study in the graph below. Since the levels declined 

appreciably over time in the Columbia study, the levels are shown by year of birth (as reported in 

Whyatt et al., 2004 and Eaton et al., 2009). Also shown is the range of plasma chlorpyrifos 

concentrations predicted to cause 10% inhibition of RBC AChE (RBC AChE 10%). A few 

subjects in the UC Berkeley study (Huen et al., 2012) may have had concentrations near the 

lowest estimate for 10% RBC AChE inhibition. All other study subjects were well below all 

estimates for RBC AChE inhibition. 
2

AChE: Acetylcholinesterase; Eaton 2008 1 – 4 (birth years 1999, 2000, 2001, 2002) 

References: 

Arnold, S., Morriss, A., Velovitch, J., Juberg, D., Price, P., et al. (2013). Derivation of 

Biomonitoring Equivalents for Chlorpyrifos Using a Pharmacokinetic/Pharmacodynamic Model 

of Oral Exposures. The Toxicologist. 52nd Society of Toxicology Annual Meeting and 

ToxExpo. March 10-14, 2013, San Antonio, TX p. 268. 

Eaton, D.L., Daroff, R. B., Autrup, H., Bridges, J., Buffler, P. et al. (2008). Review of the 

toxicology of chlorpyrifos with an emphasis on human exposure and neurodevelopment. Crit 

Rev Toxicol 38 Suppl 2:1-125. 

Huen, K.,Bradman, A., Harley, K., Yousefi, P., Boyd Barr, D., et al. (2012). Organophosphate 

Pesticide Levels in Blood and Urine of Women and Newborns Living in an Agricultural 

Community. Environ Res 117:8-16. 

Whyatt R.M., Rauh V., Barr D.B., Camann D.E., Andrews H.F., Garfinkel R., Hoepner L.A., 

Diaz D., Dietrich J., Reyes A., Tang D., Kinney P.L., Perera F.P. (2004). Prenatal insecticide 

exposures and birth weight and length among an urban minority cohort. Environ Health Perspect

112:1125-32. 

0.1

1

10

100

1000

10000

100000

Plasma levels (pg/g)
3

Wickerham, E. L.;Lozoff, B.;Shao, J.;Kaciroti, N.;Xia, Y., et al. (2012). Reduced Birth Weight 

in Relation to Pesticide Mixtures Detected in Cord Blood of Full-Term Infants. Environ Int

47:80-85 

Yan, X., Lashley, S., Smulian, J. C., Ananth, C. V., Barr, D. B., Ledoux, T. A., Hore, P., Robson, 

M. G. (2009). Pesticide Concentrations in Matrices Collected in the Perinatal Period in a 

Population of Pregnant Women and Newborns in New Jersey, USA, Human Ecolog Risk Asses

15:948 - 967 
1

Attachment B: Scientific perspective on specific Columbia study parameters and analyses 

The purpose of this attachment is to provide additional points contributed by Dr. Alan S. 

Kaufman (Clinical Professor of Psychology at the Yale Child Study Center at the Yale University 

School of Medicine) related to the Columbia study findings (Rauh et al., 2006 and Rauh et al., 

2011) and reported interpretation within the broader context of developmental/cognitive testing 

and assessment. Personal Communication, November 6, 2013.

Columbia Cohort and Lead Exposure 

Please comment on exposure of the Columbia cohort to lead and its impact on the exposureresponse relationship to chlorpyrifos in the Columbia study? 

Lead levels are an important variable in the Columbia study, especially for low-income families 

living at or near the poverty level. Blood lead levels have consistently been correlated with IQ 

loss (Healey et al., 2010), as well as achievement and behavioral deficits (Chandramouli et al.,

2009). In the Columbia cohort, it was reported "Lead levels were available, however, for only a 

subset of children (n = 89). Within this subset, there was no significant relationship between 

prenatal lead levels and chlorpyrifos levels (r = -0.08; P = .49)." (Rauh et al., 2006). However, 

an important question regarding lead that is not addressed in the Columbia study is how did high 

prenatal lead levels correlate with changes in the Bayley mental and motor development scores? 

Lead levels were not properly controlled in the Columbia study for the entire sample, and it is 

plausible that significant relationships could have emerged between lead levels and high 

chlorpyrifos levels and also between lead levels and Bayley scores. Thus, it is feasible that lead - 

uncontrolled in this study - played an unknown role in the subjects with "high" chlorpyrifos 

levels. 

Although Rauh et al. in the 2006 study neglected to examine the relationship between cord lead 

and Bayley scores, in their 2011 study, Rauh et al. did determine whether cord lead was related 

to both chlorpyrifos and the WISC-IV scores. Nonetheless, there was cord blood information on 

too few mothers to be able to control this important variable and blood lead levels of the children 

in the study were lacking, which should have been done when the children were 1-3 years old. 

Columbia Cohort and Cognitive Testing Assessment

Please comment on the use of dichotomized scores on the Bayley Scales of Infant 

Development (BSID) outcomes. 

Regarding the dichotomizing of the Columbia cohort into two portions: Rauh et al. (2006) say 

the issue concerns the dichotomizing of the subjects into two portions. Rauh et al. (2006) 

indicate: "The most highly exposed group and the undetectable group had lower mean MDI and 

PDI scores than did the 2 middle levels. On the basis of these preliminary analyses, and 

consistent with our previous reports, a dichotomized exposure variable was used, classifying 

subjects into high exposure (>6.17 pg/g) or lower exposure (<6.17 pg/g)." The four groups 

should have been analyzed separately. There was a "U-shaped" relationship between the Bayley 

scores and level of chlorpyrifos exposure. The "undetectable" group and the "high exposure" 
2

group both scored lowest on the mental and motor scales of the Bayley. There is no scientific 

justification for combining the two middle groups with the "undetectable" group. Further, it is 

inappropriate to examine the Bayley scores for the four groups before making the decision of 

how to combine the data. The Bayley scores are the dependent variable for the study (i.e., the 

outcome variables). It is not good scientific practice to examine data on the outcome variables 

before deciding how to analyze the data. 

Columbia Cohort and Mental/Psychomotor Performance Across Exposure Groups

Please comment on the mental and psychomotor delay at age 3 when comparing high to low 

exposure groups within the Columbia cohort. 

Regarding the loss of mental function at age 3 years, Rauh et al., (2006) report that "Highly 

exposed children (chlorpyrifos levels of ≥ 6.17 pg/g plasma) scored, on average, 6.5 points lower 

on the Bayley Psychomotor Development Index and 3.3 points lower on the Bayley Mental 

Development Index at 3 years of age compared with those with lower levels of exposure. 

Children exposed to higher, compared with lower, chlorpyrifos levels were also significantly 

more likely to experience Psychomotor Development Index and Mental Development Index 

delays, attention problems, attention-deficit/hyperactivity disorder problems, and pervasive 

developmental disorder problems at 3 years of age." Thus, the motor and mental results were 

treated as if they are the same, which they are not. A 3.3 point discrepancy on the mental index 

is not a meaningful difference, and that difference did not even approach statistical significance 

at the 0.05 level (p = 0.155 in Table 2; Rauh et al., 2006). It is inappropriate to speak of 

significant mental “delays” as in the Rauh et al., 2006 paper. First, the significance level = 0.048 

(Table 2; Rauh et al., 2006) is barely under the p < 0.05 guideline. Nonetheless, that probability 

has no meaning because of the “multiple simultaneous” comparisons in Table 2 (12 comparisons, 

to be exact - four contrasts at each of three ages). Whenever more than one comparison is made 

at a time, it is incumbent on the researcher to exercise some type of control over the chance error 

that inevitably occurs when many comparisons are made at once. Rauh et al. made no such 

control (e.g., demanding that each separate probability must be p < 0.02 or p < 0.01 to achieve a 

"family-wise" error rate of 0.05). In short, the value of 0.048 is “not” significant, but likely a 

result of making so many comparisons such that a few will be "significant" just by chance 

occurrence. Secondly, the use of a cut-off of a standard score of “85” to denote children as “High 

Risk” is an arbitrary decision. Scoring below 85 is not a diagnostic category. It is not even a 

common "cut" score for determining who is at high risk; values below 85 are much more 

common. Harrison (1990, pp. 53-56), for example, uses cut-off scores of 70, 75, and 80 (but not 

85) to illustrate the use of the Early Screening Profiles for identifying high risk children between 

the ages of 2 to 6 years. Changing categories, in any event, is not meaningful. IQ and 

motor development tests have a built-in standard error of measurement of 3 or 4 points--and that 

error is even higher when testing very young children tested on tests developed for infants and 

toddlers. For example, Black and Matula (2000) point out that for the second edition of the 

Bayley Scales (normed for ages 1-42 months): “The average standard error of measurement is 

5.21 for the Mental Scale and 6.01 for the Motor Scale” (pp. 68-69); those values are far lower 

than the values of about 3.00 for Wechsler’s IQ scales at ages 3-7 years (Pearson, 2012, Table 

4.3; Psychological Corporation, 2003, Table 4.3). Categories such as “High Risk” will change 

dramatically from Test 1 to Test 2 when the same child is tested twice simply due to errors of 
3

measurement. Whether a child scores 82 or 83 or 84 or 85 or 86 or 87 is just pure chance due to 

measurement error. A single arbitrary cut-off is inadequate to identify children as normal or with 

"delays." Such an arbitrary approach takes unfair advantage of the known errors of measurement 

that characterize even the best measures of mental and motor ability; 85 is just an arbitrary 

number that may or may not mean delay or high risk. 

In the 2011 study, the Rauh et al. analysis of chlorpyrifos and WISC-IV scores appears sound. 

However, the multiple comparisons (as mentioned above) are still an issue. In Table 2, there are 

five adjusted value comparisons; the authors made no attempt to control for errors that occur 

when several comparisons are made at once. Consequently, the p = 0.048 value for Full Scale IQ 

is suspect and most likely a chance finding. Nonetheless, the significant finding for working 

memory is robust and not likely due to chance. However, whenever only one of four mental 

indexes is found to be significant, such a finding should be replicated with independent samples 

to verify that it is a "real" relationship between chlorpyrifos and intelligence, not a chance 

finding. 

References: 

Black, M. M., & Matula, K. (2000). Essentials of Bayley Scales of Infant Development-II 

assessment. Hoboken, NJ: Wiley 

Chandramouli, K., Steer, C. D., Ellis, M., and Emond, A. M. (2009). Effects of early childhood 

lead exposure on academic performance and behaviour of school age children. Archives of 

Disease in Childhood, 2009. 94:844-8. 

Harrison, P. L. (1990). Early Screening Profiles manual. Minneapolis, MN: Pearson. 

Healey, N., Jones-Otazo, H., Walker, M., and Knafla, A. (2010). Toxicological Review and 

Recommended Toxicological Reference Values for Environmental Lead Exposure in Canada. 

FINAL REPORT. Prepared under contract to Health Canada. Prepared for the Contaminated 

Sites Division, Safe Environments Directorate, Healthy Environment and Consumer Safety 

Branch, Health Canada, Ottawa. 

Pearson. (2012). Wechsler Preschool and Primary Scale of Intelligence–Fourth Edition. San 

Antonio, TX. 

Psychological Corporation. (2003). WISC-IV technical and interpretive manual. San Antonio, 

TX. 

Rauh, V. A., Garfinkel, R., Perera, F. P., Andrews, H. F., Hoepner, L., et al. (2006). Impact of 

Prenatal Chlorpyrifos Exposure on Neurodevelopment in the First 3 Years of Life among InnerCity Children. Pediatrics 118:e1845-1859. 

Rauh, V., Arunajadai, S., Horton, M., Perera, F., Hoepner, L., Barr, D.B., and Whyatt, R. (2011). 

Seven-year neurodevelopmental scores and prenatal exposure to chlorpyrifos, a common 

agricultural pesticide. Env. Hlth. Perspect. 119(8) 1196-1201. 
1

Attachment C: Epidemiology Data for Chlorpyrifos – Considerations of Reproducibility 

The purpose of this attachment is to explain the importance of type and specificity of exposure 

when evaluating evidence for and against causality, namely using chlorpyrifos and/or urinary 

TCPy compared to less specific metabolites. Demonstration of reproducibility between studies 

(not within) is critical for risk assessment decisions. 

To support causality, associations between exposures to the chemical of interest and health 

outcomes should be found in different populations. The summary Table 1 presented below, 

which uses the format of EPA’s Table 10 (USEPA 2012, page 59), includes recent data from two 

new cohorts (China cohort; Wickerham et al., 2012; Mexico City cohort; Fortenberry et al., 

2013) that have exposure levels higher than or comparable to the Columbia and University of 

California (UC) Berkeley studies. Another study conducted in New Jersey (Yan et al., 2009; Barr 

et al., 2010) did not observe any significant associations for fetal growth; however, in this study, 

chlorpyrifos was near the limit of detection in most maternal and cord blood samples. 

A major challenge in determining reproducibility of the Columbia study is a lack of consistency 

of exposure metrics. Some other cohort studies measured urinary biomarkers of 

organophosphate (OP) exposure that have different levels of specificity as a biomarker for 

chlorpyrifos exposure. The most specific urinary biomarker of chlorpyrifos exposure is 3,5,6-

trichloro-2-pyridinol (TCPy), but this also can be a metabolite of chlorpyrifos-methyl. 

Dialkylphosphates (DAPs) are non-specific biomarkers of OPs that are comprised of 

diethylphosphates (DEPs) and dimethyl phosphates (DMPs). The DEPs include two metabolites 

of chlorpyrifos, diazinon and other diethyl-OPs (Table 2). In contrast, the DMPs are not 

biomarkers for chlorpyrifos but can be biomarkers of many dimethyl-OPs (Table 2). These 

urinary metabolites of OPs can also be a result of exposure to these metabolites in food or the 

environment rather than to chlorpyrifos or other OPs. Thus, in evaluating consistency across 

studies it is necessary to consider the studies in terms of the level of information they provide 

about chlorpyrifos specifically, as opposed to information about OPs generally, as well as what is 

meant by “consistent findings” in the context of these different biomarkers of exposure (Li et al., 

2012; Mink et al., 2012). The summary Table 1 in this attachment differs from EPA’s Table 10 

in that associations with DEPs are tabulated instead of those for DAPs. 

Points to Note in Reviewing the Table 1:

1. EPA’s 2012 SAP clearly stated that total DAPs “are not selective enough to be a useful 

biomarker for chlorpyrifos” (EPA SAP, P. 58). Chlorpyrifos is the biomarker deemed to 

be the highest priority because of its specificity (EPA SAP, P. 58). EPA SAP also 

concluded that “the next biomarker of choice is TCPy, then DETP/DEP in urine,” 

although both are present in the environment as degradates of the active ingredient 
2

(USEPA SAP, p. 58). Thus, this table omits DAPs but includes DEPs. The columns are 

shaded to reflect the order of priority based on specificity of the biomarker as described 

above. 

2. We define null findings as those with a p value >0.1, non-significant findings as those 

with a p value>0.5, and present the direction (either as positive for score increased or 

inverse for score decreased) for findings with a p value<0.1. Values were calculated 

from the confidence interval when p values were not provided (Altman and Bland, 2011). 

The table is only a brief synopsis; for more in depth analysis including tables of the 

magnitude and direction of effects and all statistical testing conducted, we direct the 

reader to one of several published reviews (Prueitt et al, 2011; Li et al., 2012; Mink et al., 

2012, Burns et al., 2013). 

3. Table 1 only includes associations reported for prenatal exposures (i.e. maternal DEPs 

and TCPy) to be comparable to the Columbia cohort study, which only measured 

cord/maternal blood at birth. 

4. Few findings of the Columbia cohort have been tested by independent investigators using 

TCPy and/or chlorpyrifos in blood, although these data are available (Huen et al. 2012). 

For example, the UC Berkeley study has not evaluated any neurodevelopmental 

outcomes using available cord blood chlorpyrifos levels or reported any results using 

TCPy in children over 2 years of age. It is unknown why the UC Berkeley investigators 

have not published any health results using these data that would contribute more 

informed data for use in decision-making relevant to chlorpyrifos. 

5. Pervasive Development Disorder (PDD) and Attention-Deficit Hyperactivity Disorderlike behaviors (ADHA) were not clinically diagnosed in the Table 1 studies. Rather, they 

were based on checklists completed by the mother. Furthermore, maternal depression, a 

potential confounder of maternal reporting of behavioral problems in children, was not 

controlled by the Columbia or Mexico City investigators, although it was a significant 

factor in the UC Berkeley study. 

Analysis of summary table

Table 1 is a high level summary of many analyses and purely looks at statistical associations. 

Even without discussing methodological differences, most of the findings of the Columbia study 

are not replicated. After age 2 years, it might appear that the UC Berkeley cohort shows limited 

consistency with the Columbia cohort because of the association with mothers’ report of 

Attention-Deficit Hyperactivity Disorder-like behaviors (ADHD) and DEPs. Unfortunately, the 

UC Berkeley study did not report any testing for TCPy or chlorpyrifos in older children. 

Notably, there was no significant overall association found with ADHD and other attention 
3

problems and TCPy in the Mexico cohort. Both the UC Berkeley and Mexico investigators 

conducted multiple tests for attention and behavioral problems without control for multiple 

testing. For example, in Table 5 of the Mexico cohort, 27 tests for trend were presented for 

which two were considered borderline statistically significant (p<0.1) while none was 

statistically significant at the standard p-level (i.e., (p<0.05). Overall, since positive results were 

only reported for DEP and only at age 5 in the UC Berkeley study, and not for TCPy, there is 

little support for a consistent exposure and ADHD association and less support for any effects 

attributable to chlorpyrifos. 

Both the UC Berkeley and Mount Sinai cohorts show some consistency with Full Scale IQ with 

DEPs (0.05<p<0.1), which are not specific to chlorpyrifos. Again, no testing was reported for 

TCPy or chlorpyrifos in the other cohorts. Thus, although one could selectively focus on the 

statistically significant DEPs association from the UC Berkeley study and the findings in the 

Columbia study as evidence of consistency across cohorts, the null findings with the more 

specific biomarker TCPy significantly weakens the weight of evidence. The observations in the 

Columbia study have not been sufficiently tested with chlorpyrifos exposure in other studies to 

confirm if these are true or false observations. Without robust replication, the Columbia data 

should not be used for risk assessment. 
4

Table 1. Summary of findings from key epidemiology studies for chlorpyrifos. 

Columbia Mount Sinai UC Berkeley Mexico 

City 

China 

Markers of 

exposure 

CPF TCPy DEPs CPF TCPy DEPs TCPy CPF 

Birth Length Inverse 

(Null post 

2000) 

Null Null Collected, 

analysis not 

available 

Null Null N.I. N.I. 

Birth Weight Inverse 

(Null post 

2000) 

Null Inverse Collected, 

analysis not 

available 

Null Null N.I. Null 

Bayley Scores 

12 months 

(MDI/PDI) 

Null/Null Collected, 

analysis 

not 

available

Null/null Collected, 

analysis not 

available 

Null/Null Null/Null N.I. N.I. 

Bayley Scores 

24 months 

(MDI/PDI) 

Null/Null Collected, 

analysis 

not 

available

Null/Null Collected, 

analysis not 

available 

Null/Null Null/Null N.I. N.I. 

Bayley Scores 

36 months 

(MDI/PDI) 

Inverse/ 

Inverse 

Not testedNot tested Not tested Not tested Not tested N.I. N.I. 

Pervasive 

Development 

Disorder (PDD) 

Positive 

(36 mo) 

Not testedNot tested Collected, 

analysis not 

available 

Null 

(24 mo) 

Null (24 mo) N.I. N.I. 

ADHD/ 

attention and 

behavior problems 

ages 2 - 7 years 

Positive 

 (36 mo) 

Not testedNot tested Collected, 

analysis not 

available 

Null 

(24 mo) 

Null (3.5 yr) 

Positive 

(5 yr)1

Null2

(6-11 yr) 

N.I. 

Mental 

Development 

(WISC-IV, age 7 – 

9 years) 

Inverse 

(Full-scale 

IQ and 

Working 

Memory);Nu

ll (Others) 

Collected, 

analysis 

not 

available

Inverse 

(NS) 

FSIQ, 

Working 

memory

Collected, 

analysis not 

available 

Collected, 

analysis 

not 

available

Inverse 

(FSIQ) 

Null 

(working 

memory) 

N.I. N.I. 

1. P< 0.1 for a single test at 3.5 years. All testing for other attention and behavioral problems at age 5 years were 

not statistically significant (Marks et al., 2010). 

2. P < 0.1 for a single ADHD index in boys and Hit RT block change in all subjects. All testing for other models for 

changes in psychometric assessment scores were not statistically significant (Fortenberry, et al., 2013). 

NS=Not statistically significant, [0.1>p>0.05]. p values calculated from confidence interval using following 

equation: SE = (u – l)/(2 x 1.96); z = Est/SE; P = exp(-0.717 x z – 0.416 x z2

) (Altman and Bland, 2011)): 

Inverse= higher levels of exposure associated with adverse health outcomes (score decreased) 

Positive= higher levels of exposure associated with adverse health outcome (score increased) 

Null = No association observed, p> 0.1 

MDI = Mental development index 

PDI = Psychomotor development index 

Not tested = study did not measure the outcome at the age listed 

N.I. = no information available 

Collected, analysis not available = biomarker and outcome measured but associations never publicly released 
5

Table 2. Urinary biomarkers of pesticide exposure. 

Pesticide Dimethylphosphate

DimethylthiophosphateDimethyldithiophosphateDiethylphosphateDiethylthiophosphateDiethyldithioPhosphate

Azinphos methyl X X X 

Chlorethoxyphos X X 

Chlorpyrifos X X 

Chlorpyrifos methyl X X 

Coumaphos X X 

Dichlorvos X 

Diazinon X X 

Dicrotophos X 

Dimethoate X X 

Disulfoton X X X 

Ehtion X X X 

Fenitrothion X X 

Fenthion X X 

Isazaphos-methyl X X 

Malathion X X X 

Methidation X X X 

Methyl parathion X X 

Naled X 

Oxydemeton-methyl X X 

Parathion X X 

Phorate X X X 

Phosmet X X X 

Pirimiphos-methyl X X 

Sulfotepp X X 

Temephos X X 

Terbufos X X X 

Tetrachlorviphos X 

Trichlorfon X 

The table shows the six urinary metabolites and the parent organophosphate insecticides responsible for 

these metabolites. DAPs measures all six of these metabolites, only two of which are associated with 

chlorpyrifos. (CDC Fourth National Report on Human Exposure to Environmental Chemical, 2009) 

 
6

REFERENCES 

Columbia Study

Lovasi, G. S., Quinn, J. W., Rauh, V. A., Perera, F. P., Andrews, H. F., et al. (2011). 

Chlorpyrifos Exposure and Urban Residential Environment Characteristics as Determinants of 

Early Childhood Neurodevelopment. Am J Public Health 101:63-70. 

Rauh V., Arunajadai S., Horton M., Perera F., Hoepner L., Barr D.B., Whyatt R. (2011). Sevenyear neurodevelopmental scores and prenatal exposure to chlorpyrifos, a common agricultural 

pesticide. Environ Health Perspect 119:1196-201. 

Rauh V.A., Garfinkel R., Perera F.P., Andrews H.F., Hoepner L., Barr D.B., Whitehead R., Tang 

D., Whyatt R.W. (2006). Impact of prenatal chlorpyrifos exposure on neurodevelopment in the 

first 3 years of life among inner-city children. Pediatrics 118:e1845-59. 

Whyatt R.M., Rauh V., Barr D.B., Camann D.E., Andrews H.F., Garfinkel R., Hoepner L.A., 

Diaz D., Dietrich J., Reyes A., Tang D., Kinney P.L., Perera F.P. (2004). Prenatal insecticide 

exposures and birth weight and length among an urban minority cohort. Environ Health Perspect 

112:1125-32. 

Mt. Sinai

Berkowitz G., Wetmur J.G., Birman-Deych E., Obel J., Lapinski R.H., Godbold J., Holzman 

I.R., Wolff M. (2004). In Utero Pesticide Exposure, Maternal Paraoxonase Activity, and Head 

Circumference. Environ Health Persp 112:388-391. 

Engel S.M., Wetmur J., Chen J., Zhu C., Barr D.B., Canfield R.L., Wolff M.S. (2011). Prenatal 

exposure to organophosphates, paraoxonase 1, and cognitive development in childhood. Environ 

Health Perspect 119:1182-8. 

Berkeley (CHAMACOS) 

Bouchard M.F., Chevrier J., Harley K.G., Kogut K., Vedar M., Calderon N., Trujillo C., Johnson 

C., Bradman A., Barr D.B., Eskenazi B. (2011). Prenatal Exposure to Organophosphate 

Pesticides and IQ in 7-Year Old Children. Environ Health Perspect 119:1189-1195. 

Eskenazi B., Harley K., Bradman A., Weltzien E., Jewell N.P., Barr D.B., Furlong C.E., Holland 

N.T. (2004). Association of in utero organophosphate pesticide exposure and fetal growth and 

length of gestation in an agricultural population. Environ Health Perspect 112:1116-24. 

Eskenazi B., Marks A.R., Bradman A., Harley K., Barr D.B., Johnson C., Morga N., Jewell N.P. 

(2007). Organophosphate pesticide exposure and neurodevelopment in young MexicanAmerican children. Environ Health Perspect 115:792-8. 
7

Huen, K.;Bradman, A.;Harley, K.;Yousefi, P.;Boyd Barr, D., et al. (2012). Organophosphate 

Pesticide Levels in Blood and Urine of Women and Newborns Living in an Agricultural 

Community. Environ Res 117:8-16. 

Marks A.R., Harley K., Bradman A., Kogut K., Barr D.B., Johnson C., Calderon N., Eskenazi B. 

(2010). Organophosphate pesticide exposure and attention in young Mexican-American children: 

the CHAMACOS study. Environ Health Perspect 118:1768-74. 

Other

Altman D.G., Bland J.M (2011). How to obtain a confidence interval from a P value. Brit Med J

342:d2090. 

Barr D.B., Ananth C.V., Yan X., Lashley S., Smulian J.C., Ledoux T.A., Hore P., Robson M.G. 

(2010). 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 

408:790-5. 

Burns, C. J.;McIntosh, L. J.;Mink, P. J.;Jurek, A. M.;Li, A. A. (2013). Pesticide Exposure and 

Neurodevelopmental Outcomes: Review of the Epidemiologic and Animal Studies. J Toxicol 

Environ Health B Crit Rev 16:127-283. 

Fortenberry, G. Z.;Meeker, J. D.;Sanchez, B. N.;Barr, D. B.;Panuwet, P., et al. (2013). Urinary 

3,5,6-Trichloro-2-Pyridinol (Tcpy) in Pregnant Women from Mexico City: Distribution, 

Temporal Variability, and Relationship with Child Attention and Hyperactivity. Int J Hyg 

Environ Health (in press). 

Li, A. A.;Lowe, K. A.;McIntosh, L. J.;Mink, P. J. (2012). Evaluation of Epidemiology and 

Animal Data for Risk Assessment: Chlorpyrifos Developmental Neurobehavioral Outcomes. J 

Toxicol Environ Health B 15:109-184. 

Mink, P. J.;Kimmel, C. A.;Li, A. A. (2012). Potential Effects of Chlorpyrifos on Fetal Growth 

Outcomes: Implications for Risk Assessment. J Toxicol Environ Health B 15:281-316. 

Prueitt, R. L.;Goodman, J. E.;Bailey, L. A.;Rhomberg, L. R. (2011). Hypothesis-Based Weightof-Evidence Evaluation of the Neurodevelopmental Effects of Chlorpyrifos. Crit Rev Toxicol

41:822-903 

US EPA, FIFRA Scientific Advisory Panel. (2012). "A Set of Scientific Issues Being Considered 

by the Environmental Protection Agency Regarding Chlorpyrifos Health Effects: Minutes of the 

FIFRA Science Advisory Panel Meeting held on April 10-12, 2012." SAP Minutes No. 2012-04. 

108p. 

US EPA, (2012). “Draft issue paper: Scientific issues concerning health effects of chlorpyrifos “ 

April 10 – 13, 2012. 
8

Wickerham, E. L.;Lozoff, B.;Shao, J.;Kaciroti, N.;Xia, Y., et al. (2012). Reduced Birth Weight 

in Relation to Pesticide Mixtures Detected in Cord Blood of Full-Term Infants. Environ Int

47:80-85. 

Yan, X., Lashley, S., Smulian, J. C., Ananth, C. V., Barr, D. B., Ledoux, T. A., Hore, P., Robson, 

M. G. (2009). Pesticide Concentrations in Matrices Collected in the Perinatal Period in a 

Population of Pregnant Women and Newborns in New Jersey, USA, Human Ecolog Risk Asses

15:948 – 967.