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 da ta in risk assessment and regulatory decisionmaking has received considerable attention in rece nt years and continues to be vetted by the U.S. Environmental Protection Agency (USEPA) wh en evaluating chemical risk to human populations ( e.g., SAP 2010). For the insecticide chlorpyrif os, there exists a growing number of studies that may inform the risk assessment fo r 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 a nd perspectives reveals th at findings from this singular cohort have limitations, including reliability of reported results, exposure to other risk factors, lack of repr oducibility of findings in other stud ies, 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 stud ies 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 nu mber of deficiencies in the available data (Ntzani et al., 2013). This EFSA review included neur odevelopment/IQ studies on chlorpyrifos that were published in 2006 and la ter. The totality of problems re lating 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 questio n of whether neurodevelopmental effects occur at exposure levels lower than those associated with acetylcholinesterase inhibition or for "bounding" dose-response estima tes 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 Columb ia study subjects. Also, the exposure assessment picture is incomplete for chlorpyrifos (and other chemical exposures), given that the re ported effects on neurodevelopmen t (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 sc ientific evidence to support the biological pl ausibility of the Columbia cohort findings at the exposures repor ted. The animal database for chlorpyrifos is one of the most robust across all chemistr ies and it is not possibl e to explain adverse neurodevelopmental effects o ccurring below the threshol d point of departure for acetylcholinesterase without signifi cant speculation and conjecture.

3. Chlorpyrifos cannot reliably be deemed as a causal factor for the reported neurodevelopmental effects. There are credible alternative explanat ions for the observed effects. In particular, influences of ot her chemical and nonchemical stressors could contribute to or account for the reported asso ciations of impaired neurodevelopment in the Columbia study. Also many of the outco mes reported may be chance occurrences, given the methods used to assess cognitive function.

4. When considering the specificity of biomarke rs for chlorpyrifos exposure and lack of concordance across reported outcomes, the re sults reported in the Columbia study have not, in effect, been replicated or c onfirmed in other independent studies.

5. Although sufficient information is available to identify the serious limitations with the Columbia study, nonetheless the data on whic h 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 inve stigators. This is not only counter to the principles of transparency in federally f unded 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 Co lumbia cohort are below the validated limit of detection (LOD) for chlorpyrifos anal ysis in plasma/serum, any conclusions regarding outcomes and associated expos ure based on chlorpyrifos levels < 15 picograms (pg)/gram (g) are not reliable. This impacts the reliabil ity of the correlation analyses between exposures and most outco mes 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 pr ocess that researcher s must show that a quantitative exposure measurement is accura te, precise, and reproducible across the range of values determined within a st udy. 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 duri ng 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: authors3 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 th an 80% of the Columbia subjects had levels below this validation level. Further, th ere 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 tr ace levels reported fo r this cohort. Note that Barr et al. (2002) also reported background chlorpyr ifos 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. Finall y, 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 bas is 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 fo r deriving points of departure for chlorpyrifos (EPA SAP 2012, p. 28). Currently, there is no established biological mode of action to explain the potential neurod evelopmental 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 thre shold 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 desi gn, sometimes lack of control for litter effects, oversampling issues , behavioral methods used, and lack of doseresponse findings. At doses exceeding 1 mg/kg, th e data show somewhat more consistency, but even here, dose response experiments are the exception.”

The threshold of 1 mg/kg/day is 30-fold hi gher than the threshol d 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-pre gnant 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 pren atal 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 th at the neurodevelopmen tal 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 ne urodevelopmental outcomes only occur at exposures that inhibit AChE in pregnant rats or offspring (Li et al. , 2012; Prueitt et al

., 2011). Thus, the scientific da ta support that neurodevelopm ental effects attributed to chlorpyrifos in the rodent o ccur at doses at or above 1 mg/kg/day. Based on the animal model, it would take significant conjecture and speculation to c onclude that altered neurodevelopment in humans resulting from non-choliner gic pathway perturbations would occur at doses lower than those associated with AChE inhibition.

3. There are credible alternative explanations fo r the neurodevelopmental effects observed in the Columbia study:

Chlorpyrifos cannot reliably be deemed a cau sal factor for the neurodevelopmental effects reported by Columbia University. Alternative explanations are cr edible and present themselves logically when considering exposure measurem ent 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 belo w and in Attachment B), exposure to other toxic chemicals, including neurotoxicants, and the publis hed 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 in ner-city cohort, such as maternal perinatal smoking and alcohol; nevertheless, it is difficult to di smiss the contribution of these and perhaps other confounding factors ” (Eaton et al., 2008).

The mothers and children with in the Columbia study who ha d measurable exposures to chlorpyrifos were also exposed to other chemical s 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 fa milies living at or near the poverty level. Blood lead levels have consistently b een 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 chlorpyr ifos and neurodevelopmental effects could be partially or wholly attributable to lead (see Attachment B).

Poverty and pesticide exposure are highly correlated. Mothers a nd children who live in crowded, substandard housing are more likely to encount er 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 e xposure (regardless of the chemical ) may be a marker for insect infestation (and other related factors) and ma y not itself be the causal agent driving the neurodevelopmental results (Burns et al., 2013). In fact, the Colu mbia authors reported an5 5 association with the Bayley Scales of Infant Development (BSID) and piperonyl butoxide, a synergist used with pyrethrins a nd synthetic pyrethroid insecticid es, which replaced the use of chlorpyrifos in reside ntial settings after 2001.

It is well documented in the literature that so cial 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 on ly observed at 3 years of age, not before. As the children age from birth to 3 ye ars, there are a number of other well-known nonchemical risk factors that affect brain deve lopment. Efforts were made by the Columbia study investigators to account for certain risk fact ors, including the influence of race/ethnicity, gestational age, maternal educat ion and maternal IQ (albeit, there were missing IQ data for several dozen women in the study). Observatio nal data on the quality of the home care-taking environment were also considered, but it is unc lear to what extent key risk factors were addressed. For example, information was collect ed on mothers’ feelings and state of mind but there is no indication that these potential risk f actors were explicitly addressed. Interestingly, maternal depression was a significant factor for influencing childhood be havior, as modeled by the UC Berkeley investigators (Eskenazi et al. , 2007; Marks et al ., 2010).

Despite efforts made by the Columbia study investig ators to account for ot her risk factors, the influences of other chemical and nonchemical st ressors which could contribute to or account for the observed associations of impaired neurode velopment 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, pa rticularly 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 sepa rated easily from other risk factors, and thus the study cannot be used to relia bly address the question of wh ether chlorpyrifos can cause neurodevelopmental effects at the ex posure levels reported. Although it is legitimate for academic scientists to propose and investigate hy potheses, the Columbia study cannot serve as a reliable basis for addressing key questions rega rding a single chemical in a regulatory risk

assessment.

Another significant weakness of the Colu mbia study relates to the exposure data, i.e., measurements of chlorpyrifos do not refl ect exposure over time. Evaluations of neurodevelopmental scores/function on the c ohort continued into childhood and early adolescence, which is well beyond th e single snapshot in time of chlorpyrifos measurement. This is especially pertinent since ne urodevelopment occurs both prenata lly and postnatally, essentially a continuous process thro ughout early infant and childhood years (Selevan et al., 2000). The Columbia University study focused exclusiv ely on prenatal exposure as measured by cord/maternal blood measures of chlorpyrifos wi thin two days of birth. Furthermore, the maternal and cord blood measurements re present a single sample, or snapshot ( i.e., only one point in time), collected for convenience (at bi rth) 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 sing le sample obtained at the time of delivery or shortly after would have little rela tionship or meaning to exposure levels that were present during6 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 hydrocar bons, lead, etc .) results in an incomp lete 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 repo rted associations w ith 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 “multip le simultaneous” comparisons in Rauh et al. 2006 and 2011 can lead to chance errors (see A ttachment 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 di fferent populations. Chlorpyrifos is measured in different ways across studies, with some measuring chlorpyrifos itself, and others measuring other biomarkers that represent exposure to chlor pyrifos and other chemicals, such that exposure to chlorpyrifos itself cannot be teased out. The order of reliabil ity 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 re liability of biomarkers, the resu lts 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 e t al ., 2007; Marks et al ., 2010; Bouchard et al ., 2011) studies report some neurodevel opmental effects associated only with DEP, a less specific biomarker. Outcomes associated with the more specific biomarker, TCPy, are either not tested or not anal yzed. Further, there are two ne w epidemiology studies that have not observed consistent associatio ns with birth weight or developmental outcomes. Two of these studies measured chlorpyrifos or TCPy with re ported exposure levels higher than (China cohort; Wickerham et al., 2012) or comparable to (Mex ico City cohort; Fortenberry et al., 2013) the Columbia or UC Berkeley studies. Although these studies did not investig ate all of the outcomes measured in the Columbia study, findings for endpoints that were ev aluated 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 ne urodevelopmental 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 Pr ograms has a long history of transparency as well as data disclosure in risk assessment s to ensure the credibility of its registration and reevaluation decisions. OPP’s transparen cy 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 ur inary TCPy after age two. Access to and independent analyses of these data woul d also be informative to determine the reliability of the Columbia results.

OPP has indicated publicly, “ The studies that are the most re levant and informative to risk assessment are those that clearl y and fully describe study design, conduct and methods, as well as providing access to the underlying data ” (http://www.epa.gov/pestic ides/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, i ndependent verification of the analyses (including an evaluation of different cutoff point s for exposure and BSID outcomes) and the ability to answer specific questions regardi ng the Columbia study ( e.g., other risk factors) are not possible by DowAgroSciences, EPA scientists, or the public. Th is 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 li ne 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 th e importance of protectin g the privacy of the subjects in epidemiology studies, but there ar e well-recognized and accepted ways to provide data on cohort subjects while protec ting 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 multidiscip linary scientific review is needed, which provides some access to the data and includes pedi atricians, epidemiologists, clinicians and neuropsychologists experienced in eval uation 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 in form whether neurodevelopm ental effects occur at exposure levels lower than those associated with AChEI. This is because of the difficulty of8 8 disentangling the potential of other chemical and nonchemical stressors to account for or contribute to the observed associa tions. Further, the analytical method used in collecting plasma biomonitoring data to address th e 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 biol ogical plausibility for chlorpyrifos causing neurodevelopmental outcomes in ch ildren at estimated exposure levels, as well as the lack of consistency with other populations , indicate that any reported statis tical associations within the Columbia study are likely due to factors other th an chlorpyrifos exposure. The data are not accessible for public viewing and independent analys is, which is counter to the basic tenets of transparency in government-funded research. Confid ence in the reliability of the conclusions for risk assessment-based decisions is inseparably tied to transparen cy and transparency cannot be achieved when data access is denied. Collect ively, these represent very compelling and independent bases for precluding the use of the Co lumbia study data in an evaluation of exposure and effect for chlorpyrifos or for calling into question the robust a nd comprehensive animal database on pre- and postnatal to xicity and its adequacy to characterize the dose-response curve at lower dose levels for the young.

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Rauh, V., Arunajadai, S., Horton, M., Perera, F ., Hoepner, L., Barr, D.B., and Whyatt, R. (2011). Seven-year neurodevelopmental scores an d prenatal exposure to chlorpyrifos, a common agricultural pesticide. Environ. Health. Perspect. 119(8) 1196-1201.

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US EPA guidelines for Exposure and Risk Asse ssment Calculations (1998), Series 875- Occupational and Residential Exposure Test Guid elines: Group B- Post application Exposure Monitoring Test Guidelines, Version 5.4, Wo rking Draft of February 10, 1998, Method Validation criteria pp. C6-7.

US EPA Office of Pesticide Program. (2011). Ch lorpyrifos:Preliminary Human Health Risk Assessment for Registration Review. DP No. D388070.

US EPA, FIFRA Scientific Adviso ry Panel. (2008). A Set of Scie ntific Issues Being Considered by the Environmental Protection Agency Regardi ng: The Agency's Evaluation of the Toxicity Profile of Chlorpyrifos: Minutes of the FI FRA 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: Mi nutes 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 Agen cy 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 Le ngth among an Urban Minority Cohort. Environ Health Perspect 112:1125-1132.1 2 12 Whyatt, R. M., Camann, D., Perera, F. P., Rauh, V. A.,Tang, D. et al . (2005). Biomarkers in Assessing Residential Insecticid e 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 provid e additional explanation s upporting the prediction, based on the available biomonitoring data, that al l blood concentrations for the Columbia study subjects, as well as those of ot her epidemiology cohorts, were we ll 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 we re developed for blood CPF that are associated with a predicted maximum of 10% inhibition of red blood cell acetylchol inesterase (RBC AChE) using a physiologically based pharmacokinetic/ pharmacodynamic (PBPK/PD) model (Arnold et
al ., 2013). Inhibition of RBC AChE, wh ile not part of the choliner gic toxicity pathway in the central nervous system, is a conservative marker of inhibition of brain AC hE, 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 chlorpyrif os 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 th e graph below. Since the levels declined appreciably over time in the Columbia study, the le vels are shown by year of birth (as reported in Whyatt et al ., 2004 and Eaton et al., 2009). Also shown is the ra nge 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 con centrations 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., Velovitc h, J., Juberg, D., Price, P., et al . (2013). Derivation of Biomonitoring Equivalents for Chlorpyrifos Us ing a Pharmacokinetic/Pharmacodynamic Model of Oral Exposures. The Toxicologist. 52 nd Society of Toxicology Annual Meeting and ToxExpo. March 10-14, 2013, San Antonio, TX p. 268.

Eaton, D.L., Daroff, R. B., Autr up, H., Bridges, J., Buffler, P. et al. (2008). Review of the toxicology of chlorpyrifos with an emphasi s 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 a nd 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 leng th among an urban minority cohort. Environ Health Perspect

112:1125-32. 0.1

1 10 100 1000 10000 100000Plasmalevels(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 Detect ed 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 Matr ices Collected in the Perinatal Period in a Population of Pregnant Women and Newborns in New Jersey, USA, Human Ecolog Risk Asses

15:948 - 9671 Attachment B: Scientific perspective on sp ecific Columbia study parameters and analyses

The purpose of this attachment is to provid e additional points contributed by Dr. Alan S. Kaufman (Clinical Professor of Ps ychology 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 broade r context of developmental/cognitive testing and assessment. Personal Communication, November 6, 2013.

Columbia Cohort and Lead Exposure

Please comment on exposure of the Columbia c ohort to lead and its impact on the exposureresponse relationship to chlorpyr ifos in the Columbia study?

Lead levels are an important va riable in the Columbia study, especially for low-income families living at or near the poverty leve l. Blood lead levels have consiste ntly 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 s ubset, there was no signific ant relationship between prenatal lead levels and chlorpyr ifos levels (r = -0.08; P = .49). " (Rauh et al., 2006). However, an important question regarding l ead that is not addressed in th e 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 th e Columbia study for the entire sample, and it is plausible that significant relati onships could have emerged be tween 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 WI SC-IV scores. Nonetheless, th ere was cord blood information on too few mothers to be able to co ntrol 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 dichotom izing of the subjects into tw o 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 dichot omized 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 wa s a "U-shaped" relationship between the Bayley scores and level of chlorpyrifos exposure. The "undetectable" group a nd the "high exposure"2 group both scored lowest on the mental and motor s cales of the Bayley. There is no scientific justification for combining the two middle groups with the "undete ctable" group. Further, it is inappropriate to examine the Bayl ey 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 pr actice to examine data on the outcome variables before deciding how to analyze the data.

Columbia Cohort and Mental/Psychomot or Performance Across Exposure Groups

Please comment on the mental and psychomotor delay at ag e 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 Ind ex and 3.3 points lower on the Bayley Mental Development Index at 3 years of age compared w ith those with lower levels of exposure. Children exposed to higher, compared with lower, chlorpyrifos levels were also significantly more likely to experience Psychomotor Devel opment Index and Mental Development Index delays, attention problems, atte ntion-deficit/hyperactivity di sorder 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 inappr opriate to speak of significant mental “delays” as in the Rauh et al., 2006 paper. First, th e significance level = 0.048 (Table 2; Rauh et al., 2006) is barely under the p < 0.05 guide line. Nonetheless, that probability has no meaning because of the “multiple simulta neous” 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 ex ercise some type of c ontrol 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 separa te 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 diagnos tic 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, us es 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 testi ng very young children tested on tests developed for infants and toddlers. For example, Black and Matula (2000) point out that for th e 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 of3 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 in adequate to identify children as normal or with "delays." Such an arbitrary approach takes unf air advantage of the known errors of measurement that characterize even the best measures of me ntal 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 an d WISC-IV scores appears sound. However, the multiple comparisons (as mentioned a bove) 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 ch ance 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 betw een 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., a nd 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 Hea lth 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 Neurodevelopm ent in the First 3 Years of Life among InnerCity Children. Pediatrics 118:e1845-1859.

Rauh, V., Arunajadai, S., Horton, M., Perera, F., Ho epner, L., Barr, D.B., and Whyatt, R. (2011). Seven-year neurodevelopmental scores and pr enatal exposure to ch lorpyrifos, a common agricultural pesticide. Env. Hlth. Perspect. 119(8) 1196-1201.1 Attachment C: Epidemiology Data for Chlorp yrifos – 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 causal ity, namely using chlorpyrifos and/or urinary TCPy compared to less specific metabolites. De monstration of reproducib ility between studies (not within) is critical fo r risk assessment decisions

.

To support causality, associations between exposur es to the chemical of interest and health outcomes should be found in different populatio ns. 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; Wick erham 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 si gnificant 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 urin ary 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 OP s that are comprised of diethylphosphates (DEPs) and dimethyl phosphate s (DMPs). The DEPs include two metabolites of chlorpyrifos, diazinon and ot her diethyl-OPs (Table 2). In contrast, the DMPs are not biomarkers for chlorpyrifos but can be biomar kers of many dimethyl-OPs (Table 2). These urinary metabolites of OPs can al so be a result of exposure to th ese metabolites in food or the environment rather than to chlorpyrifos or ot her 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 DAP s “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 becau se of its specificity (EPA SAP, P. 58). EPA SAP also

concluded that “the next biomarker of c hoice is TCPy, then DETP/DEP in urine,” although both are present in the environment as degradates of the active ingredient2 (USEPA SAP, p. 58). Thus, this table omits DAPs but includes DEPs. The columns are shaded to reflect the order of priority base d 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 w ith a p value<0.1. Values were calculated from the confidence interval when p values were not provided (A ltman and Bland, 2011). The table is only a brief synopsis; for more in depth analysis including tables of the magnitude and direction of ef fects and all statistical tes ting conducted, we direct the

reader to one of severa l 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, a lthough these data ar e available (Huen et al . 2012). For example, the UC Berkeley study ha s not evaluated any neurodevelopmental outcomes using available cord blood chlorpyr ifos levels or reported any results using TCPy in children over 2 years of age. It is unknown why th e UC Berkeley investigators have not published any health results using these data th at 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 diag nosed in the Table 1 studies. Rather, they were based on checklists completed by the moth er. 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 methodologi cal differences, most of the findings of the Columbia study are not replicated. After age 2 years, it might appear that the UC Berk eley 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 fo r TCPy or chlorpyrifos in older children. Notably, there was no significant overall asso ciation found with ADHD and other attention3 problems and TCPy in the Mexico cohort. Both the UC Berkeley and Mexico investigators conducted multiple tests for attention and behavi oral problems without control for multiple testing. For example, in Table 5 of the Mexico cohort, 27 tests for tr end were presented for

which two were considered borderline statis tically significant (p<0.1) while none was statistically significant at the sta ndard p-level (i.e., (p<0.05). Over all, 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 ADH D association and less support for any effects attributable to chlorpyrifos.

Both the UC Berkeley and Mount Sinai cohorts sh ow some consistency with Full Scale IQ with DEPs (0.05<p<0.1), which are not specific to chlo rpyrifos. Again, no testing was reported for TCPy or chlorpyrifos in the other cohorts. Thus, although one could selectively focus on the statistically significant DEPs a ssociation from the UC Berkeley study and the findings in the Columbia study as evidence of consistency acro ss 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 fa lse 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 N ot teste d Not tested Not tested Not tested Not tested N.I. N.I.

Pervasive Development Disorder (PDD) Positive (36 mo) N ot teste d Not 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) N ot teste d Not tested Collected, analysis not

available Null (24 mo) Null (3.5 yr) Positive (5 yr) 1 Null 2 (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 significan t (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 z 2 ) (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 outcom e measured but associations never publicly released5 Table 2. Urinary biomarkers of pesticide exposure.

Pesticide Dimethylphosphate Dimethylthiophosphate Dimethyldithiophosphate Diethylphosphate Diethylthiophosphate DiethyldithioPhosphate 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 in secticides responsible for these metabolites. DAPs measures all six of these me tabolites, 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., Pere ra, F. P., Andrews, H. F., et al. (2011). Chlorpyrifos Exposure and Urban Residential Environment Characte ristics as Determinants of Early Childhood Neurodevelopment. Am J Public Health 101:63-70.

Rauh V., Arunajadai S., Horton M., Perera F., Ho epner L., Barr D.B., Whyatt R. (2011). Sevenyear neurodevelopmental scores and prenatal ex posure 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 chlorpyrif os exposure on neurodevelopment in the first 3 years of life among inner-ci ty children. Pediat rics 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. E nviron 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 Expos ure, 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., Wolf f 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 Ch ildren. Environ Health Perspect 119:1189-1195.

Eskenazi B., Harley K., Brad man A., Weltzien E., Jewell N.P., Barr D.B., Furlong C.E., Holland N.T. (2004). Association of in utero organophospha te 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 neurodevelopmen t in young MexicanAmerican children. Environ H ealth Perspect 115:792-8.7 Huen, K.;Bradman, A.;Harley, K.;Yousefi, P.;B oyd Barr, D., et al. (2012). Organophosphate Pesticide Levels in Blood a nd 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 pre gnant 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.

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