Endocrine Disruptor Neurodevelopmental Effects

8/6/2019 Endocrine Disruptor Neurodevelopmental Effects

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Review of the Literature Concerning Human Epidemiological Studies on the Neurodevelopmental Effects

of Fetal in utero Exposure to Endocrine Disruptors

by Susan Kinkead-Acree, MD

May 2005

Much has been learned about the neurodevelopmental effects of in utero fetal exposure toendocrine disruptors through toxicological models. These studies have been motivated byevidence from wildlife studies that exposure to even low levels of endocrine disruptors at critical

points in fetal development can have profound reproductive, behavioral, and neurologicaleffects. While chemical sensitivities and toxicokinetics can differ widely among animal speciesand between animals and humans, the potential of some chemicals for significant functionalendocrine disruption has raised concern about their impact on human health. The humanepidemiological studies carried out to date have demonstrated small but statistically significant

adverse fetal developmental effects, but because most have used different methods of chemicalanalysis, measures of exposure, and statistical methodologies, it is often difficult to comparetheir results. By looking to these studies, investigators can obtain guidance on ways to improvechemical detection methods, outcome assessment tools, and statistical methodologies so as tooptimize the data quality and the inter-study comparability of future investigations.

Introduction

History of Endocrine Disruptors

Since Silent Spring was published in 1962 (Carson 1962) there has been a growing recognitionthat chemicals in the environment can cause deleterious health effects on wildlife and humans(The International Programme on Chemical Safety 2002). In Our Stolen Future (Colborn et al..1996), the authors presented compelling scientific evidence that these ubiquitous environmentalcontaminants may interfere with the endocrine hormonal signals that orchestrate fetaldevelopment, resulting in reproductive and developmental defects. Laboratory studies haveconfirmed that chemicals can affect the endocrine system in animals (U.S. EPA 2004b). Thesechemicals came to be termed endocrine disruptors.

Although much controversy exists among scientists regarding the magnitude of the potentialimpact of endocrine disruptors on human health, concern was great enough that Congress

amended the Federal Food, Drug, and Cosmetic Act with the Food Quality Protection Act of 1996, requiring that the Environmental Protection Agency Administrator develop a screening program, using appropriate validated test systems and other scientifically relevant information, todetermine whether certain substances may have an effect in humans that is similar to an effect

produced by a naturally occurring estrogen, or such other endocrine effect as the Administrator may designate (United States Congress 1996). The EPA screening program assays and testingmethods are currently under development. The Presidents National Science and TechnologyCouncils Committee on Environment and Natural Resources (CENR) has established a Working


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Group on Endocrine Disruptors with representatives from 14 federal agencies to assess, plan, andcoordinate research on endocrine disruptors in the United States.

International coordination of endocrine disruptor assessment is provided by the Organization for Economic Cooperation and Development (OECD), which established in 1996 a Special Activity

on Endocrine Disrupter Testing and Assessment to ensure that testing and assessmentapproaches for endocrine disrupters would not substantially differ among countries(Organization for Economic Cooperation and Development 2004).

Properties of Endocrine Disruptors

Endocrine disruptors have been defined as exogenous agents that interfere with the production,release, transport, metabolism, binding, action, or elimination of natural hormones in the bodyresponsible for the maintenance of homeostasis and the regulation of developmental processes(Kavlock et al.. 1996; Tilson et al.. 1997; cited in Tilson 1998). Because the endocrine systemregulates all biological processes in the body from conception to death, including brain and

nervous system development, growth and function of the reproductive system, and metabolism,endocrine malfunction caused by environmental contaminants has grave implications for humanhealth.

The list of potential endocrine disruptors is long and comprises many classes of compounds (TheInternational Programme on Chemical Safety 2002). Known endocrine disruptors include heavymetals like methyl mercury and lead; chlorinated pesticides; natural or synthetic hormones; anddioxin-like compounds (DLCs), a diverse group of halogen substituted multi-ring structuresincluding polychlorinated dibenzodioxins (PCDD's), polychlorinated dibenzofurans (PCDF's),hexachlorobenzene (HCB), and polychlorinated biphenyls (PCB's) that exhibit similar

biochemical properties (Hauser et al. 1998).

Some degrade quickly, but most endocrine disruptors are biostable and persist in theenvironment for decades. Many are lipophilic and accumulate in animal adipose tissues. In thisway, the body burden of these compounds increases exponentially up the food chain. A major source of human exposure is thought to be consumption of fish, fish products, and animal fats(Cicchetti et al. 2004; Ribas-Fit et al. 2001). With widespread contamination of the food chain,virtually all humans have measurable quantities of PCBs in their body tissues (Nicholson et al.1994).

Endocrine Disruptors and Neurodevelopment

Because these compounds cross the placenta, maternal exposure to endocrine disruptors canaffect the developing fetus. Disruption of the hypothalamic-pituitary axis can result in alteredreproductive behaviors, sexual differentiation, and cognitive and psychomotor development(Tilson 1998). Thyroid hormones play a particularly critical role in brain development, as theyregulate neuronal proliferation and migration, synaptic development and myelin formation(Porterfield et al. 1998). Moderate to severe alterations in thyroid hormone concentrationsduring development result in motor dysfunction, cognitive deficits, and other neurologicabnormalities (Tilson 1998). The nature of the nervous system deficit depends not only on the


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severity of the thyroid disruption, but on the specific fetal developmental period when thedisturbance occurs (Tilson 1998). Because their molecular structure is very similar to the activeform of thyroid hormone, T 3, dioxin-like compounds are of particular concern for neurodevelopmental toxicity (Porterfield et al. 1998; Leatherland 1998). They bind with highaffinity to thyroid hormone transport proteins and T 3 receptors, as well as the selenoprotein

deiodinases, 5- and 5 monodeiodinase; these compounds thus affect thyroid hormone kinetics,transport, and neuronal intracellular production of T 3 (Leatherland 1998).

Epidemiological Studies and Reported Results

The major human epidemiological studies investigating the neurodevelopmental effects of inutero exposure to known endocrine disruptors were reviewed, as well as the major reviews

published concerning these studies. The databases Medline, Toxnet, and PsychInfo weresearched using the following search terms: endocrine disruptors; dioxins; PCBs; pesticides;

prenatal exposure; fetus; pregnancy; neurological effects; neurodevelopment; neurotoxicity; brain. Publications of governmental agencies and international organizations were also

reviewed. Further sources were identified from the citations in these documents. Englishlanguage documents only were reviewed.

The primary source of human data on neurobehavioral and developmental toxicity of in utero fetal exposure to endocrine disruptors is from epidemiological studies undertaken on a number of cohorts of women who had consumed food contaminated with dioxin-like compounds,

principally PCBs. Some of the cohorts were also evaluated for exposure to heavy metals (leadand mercury). Laboratory and wildlife studies had demonstrated the endocrine disrupting

potential of these substances. One of the objectives of the infant and child portions of thesestudies was to determine whether human fetal exposure to these compounds caused intellectual,neuropsychological, and and/or behavioral problems in the children.

Yusho and Yu-Cheng cohorts In 1968, thousands of Japanese were exposed to thermallydegraded PCB's that contained high concentrations of extremely toxic congeners of

polychlorinated dibenzofurans (PCDFs) and polychlorinated napthalenes through consumption of rice oil contaminated during the manufacturing process (Schantz May-June 1996). In 1979, asimilar poisoning incident occurred in Taiwan, also traced to contaminated rice oil (Chen et al.1992). Rice oil disease is called Yusho in Japan and Yu-Cheng in Taiwan.

Pregnant Japanese women suffering from Yusho gave birth to children with various physicaldysmorphologies, and a follow-up study of a subset of the children reported mental, motor, and

behavioral deficits including slowness, clumsy movement, apathy, and IQs averaging around 70(Harada 1976; cited in Schantz 1996). Harada did not report quantitative data, nor did he usestandardized tests, and no control children were included in his study (Lai et al. 2001; Ribas-Fitet al. 2001). Mean PCB concentration of exposed childrens blood was 6.0 ppb (Jensen 1987,cited in Ribas-Fit et al. 2001).

In Taiwan, 118 children born to women with Yu-Cheng between June 1978 and March 1985were matched with controls and tested annually for six years from 1985 to 1991 (Chen et al.1994). The studies on this cohort are presented below.


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Measures of exposure --Serum PCB levels in the Yu-Cheng cohort were not measured at the timeof birth in either the mothers or children; blood samples were drawn and PCB levels measuredin 34 mothers and 36 children in 1991--11 years after exposure (Yuet al. 1991). Exposure indiceswere estimated from the median PCB concentration in exposed childrens blood: 0.99 ppb(Ribas-Fitet al. 2001). However, umbilical cord PCB levels are considered to be the most direct

measure of in utero exposure (Schantz et al. 2003). Outcome measurements for the Yu-chengcohort included mental, motor, and behavioral deficits.

Instruments and Outcome Measures --Cognitive development was measured using Bayley Scalesfor Infant Development (6-30 months of age), Stanford-Binet IQ Test (30 months-6 years), andWechsler Intelligence Scale for Children-Revised (WISC-R) (age > 6 years) (Yu, Hsu, Gladenand others March-April 1991). Neurophysiological assessment was also performed at age > 6years with auditory event-related potentials (P300), pattern visual evoked potentials (P-VEPs),and short-latency somatosensory evoked potentials (SSEPs). P300 latencies evaluate the speedof information processing, and P-VEPs and SSEPs evaluate the sensory pathways of the

peripheral and central nervous systems (Chen et al. 1994). The WISC-R and neurophysiological

tests were given to 79 of the original cohort of 118 Yu-Cheng children and their controls in 1991.

Results --Compared with the controls, the exposed children exhibited statistically significantdelays in reaching developmental milestones as measured by parental report, clinical evaluationand formal developmental testing. Interestingly, there was no relationship between maternalserum PCB levels and developmental scores in the child, but children with detectable serumPCBs had lower developmental scores than those without (Y et al. 1991). Further exposure tothese chemicals through breast-feeding did not have any apparent effect (Gladen et al. 1988,cited in Yu et al. 1991). IQ scores of the exposed children averaged 5 points lower than thecontrols, but did not correlate with either maternal or child serum PDB levels (Chen et al. 1992;Schantz 1996).

Spatial abilities were assessed annually using the Ravin Colored and Standard ProgressiveMatrices. The Yu-Cheng children scored lower than their matched control through 12 years of age, after which they appeared to catch up to the controls (Lai et al. 2001). Interestingly, when

broken down by gender, Yu-Cheng boys showed decreased spatial abilities compared withcontrols, while girls showed no differences, leading the investigators to hypothesize that PCBexposure may have caused male-specific cognitive deficits (Schantz et al. 2003).

Behavioral development was measured using the Rutter Child Behavior Scale(emotional/behavioral disorders) and the Werry-Weiss-Peters Activity Scale (activity level). Theexposed children consistently scored higher on both scales, indicating more behavioral problemsand higher activity levels. Similar effects on behavior and attention are seen in children bornwith congenital hypothyroidism, even after early hormone replacement therapy (Porterfield et al.1998). There was no correlation between maternal or child serum PCB levels and scale results(Schantz 1996).

The WISC-R and neurophysiological studies showed that, compared with the controls, the Yu-Chen group again showed lower IQ scores (average 5 points), but as before, there was noapparent relationship between a childs IQ score and either his or his mothers serum PCB


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concentration. The mean P300 latencies were longer with lower amplitude in the Yu-Chengroup, indicating slow cognitive processing and attention deficits; these correlated with lower IQscores (Lai et al. 2001; Chen et al. 1994).There were no significant differences in P-VEP or SSEP sensory pathway performance between exposed children and controls, nor were theresignificant differences on the general neurological exams or the motor tests (Chen et al. 1994;

Schantz 1996). The authors concluded that in utero PCB exposure affected high corticalfunctioning rather than sensory pathways (Chen et al. 1994).

Criticisms The fact that Harada did not use quantitative data, standardized measuringinstruments or controls in his study precludes the possibility to compare his results with later studies.

Because the Yu-Cheng PCB exposure measurements were based on samples drawn, not fromumbilical cord blood, but from children 11 years after exposure, it is difficult to interpret the lack of correlation between serum PCB levels and IQ because the exposure indices used may notaccurately reflect in utero exposure (Schantz 1996). Schantz also notes that the childrens

behavioral differences might also be due to parental perception of them as damaged or to thestress of growing up in a family traumatized by the poisoning.

Unlike later cohorts studied, the Yusho and Yu-Cheng populations were exposed to highconcentrations of PCDF congeners that are much more toxic than PCBs (Schantz 1996).Because of this, some experts believe that the measured effects might be due more to the PCDFsthan PCBs, and therefore the study results of the rice oil disease population should not becompared with those of later cohorts exposed only to lower background levels of PCBs in theenvironment (Schantz 1996; Lai et al. 2001; Cicchetti et al. 2004).

Michigan cohort Jacobson, Jacobson, and colleagues carried out an 11-year prospective

longitudinal study on a cohort of 313 women formed in 1980-81 relating low-level maternal PCBexposure from Lake Michigan fish to developmental outcomes in children (Schantz et al. 2003).In interviews one day post-partum, mothers estimated from long-term recall the total amount,source, yearly rate of consumption and specific species of fish consumed for a number of years(up to 16) (Schell et al. 2001). All of the exposed women had reported eating at least 26 poundsof Lake Michigan fish over the preceding six years, while the controls had never eaten LakeMichigan fish. The control sample was selected randomly, not matched to the exposed group(Seegal 1996), and was one third the size of the exposed sample (Schantz 1996).

Measures of exposure --PCB exposure measurements included lifetime species-weightedmaternal fish consumption as recalled by mothers (PCB contamination levels of different fishspecies were taken into account, based on EPA data), PCB concentrations in umbilical cord andmaternal blood at birth, and breast milk concentrations at birth and 5 months post-partum(Jacobson et al. 1996; Schantz 1996). Blood samples were taken again when the children werefour and 11 years of age. However, cord serum samples were collected in only 198 of 313 (63%)of the newborns (Schwartz et al. 1983). The umbilical cord blood samples were analyzed for PCBs and polybrominated biphenyls, while the blood samples drawn at 4 and 11 years were alsoanalyzed for seven organochlorine pesticides (only DDT was detected) and lead. At 11 years


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old, the childrens serum PCB concentration was found to have decreased substantially; mercurylevels in hair were also measured at 11 years old (Jacobson et al. 1996).

PCB levels were analyzed by the Michigan Department of Public Health using packed columngas chromatography and the Webb-McCall method. PCB levels were quantitated by summing

10 Webb-McCall peaks. No data on specific congeners are available. Values matched to thePCB Aroclors 1016 (lower chlorinated congeners) and 1260 (highly chlorinated congeners) wereused as standards. The PCB detection limit for the 1016 standard was 5 ppb, and for the 1260standard it was 3 ppb. The means for the more highly chlorinated congeners matched to the1260 standard were higher than the lower chlorinated congeners matched to the 1016 standard.Additionally, most of the cord and maternal sera PCB levels matched to the 1016 standard were

below the laboratorys quantification limits, presumably because lower chlorinated congeners aresusceptible to more rapid environmental degradation and are metabolized more quickly by livingorganisms. The investigators used the values matched to the 1260 standard (i.e., the more highlychlorinated congeners) for their analyses because they provided a more reliable measure of body

burden (Schwartz et al. 1983).

The reported mean PCB concentration values (1260 standard) were: cord serum = 2.5 ppb;maternal serum =5.5 ppb; and neonatal breast milk = 812.7 ng/g fat (Schwartz et al. 1983). Noexplanation was found in the literature concerning how the investigators ascertained the cord

blood PCB concentration of 2.5 ppb when the reported quantification limit was 3 ppb. The PCBconcentrations were positively skewed, so they were logarithmically transformed.

To improve reliability and sensitivity of fetal exposure assessment, PCB concentrations in cordserum, maternal serum and milk were converted to z-scores and averaged together to provide acomposite measure of prenatal exposure in the 1996 study (Jacobson et al. 1996). According tothe authors, Because placental transfer provides the sole route of fetal exposure to these

compounds, which are in equilibrium in fat deposits throughout the body, maternal serum andmilk concentrations provide alternatives to cord serum for evaluating prenatal exposure (Roganet al. 1986, cited in Jacobson et al. 1996).

No correlation was found between fish consumption and cord serum PCBs. However, significant positive correlations were found between all three fish consumption measures and PCB levels inmaternal serum (all p < .001) and breast milk (all p < .01).

Instruments and Outcome Measures --Neuropsychological assessments were performed on thechildren with the Brazelton Neonatal Behavioral Assessment Scale (NABS) at birth (Jacobson etal. 1984a). Cognitive development was assessed with the Bayley Scales of Infant Developmentat five months of age (Jacobson et al. 1990) and with the Fagan Test of Infant Intelligence (FTII)at seven months of age (Jacobson et al. 1985). They were reassessed at four years of age(Jacobson et al. 1990) with the McCarthy Scales of Childrens abilities, supplemented by twostandardized tests, the Beery Test of Visual-Motor Integration and the Peabody PictureVocabulary Test-Revised; and finally, at 11 years of age (Jacobson et al. 1996) using the WISC-R, the spelling and arithmetic subtests of the Wide Range Achievement Test-Revised, and theword and passage comprehension subtests of the Woodcock Reading Mastery Tests-Revised.


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Maternal intelligence was evaluated using the Peabody Picture Vocabulary Test-Revised (PPVT-R), a measure of receptive vocabulary, that has shown little correlation with IQ (Maxwell et al.Wise 1984). The potential confounding effect of home environment on childrens cognitivedevelopment was controlled through administering the Home Observation for Measurement of the Environment (HOME) scale (Cicchetti et al. 2004).

Control variables and analysis The investigators used a multivariate statistical approach tocontrol for potential confounders that were known or suspected to be related to the outcomesconsidered and controlled for variables that related to exposure at p


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McCarthy Scales of Childrens Abilities . At four years of age (n=219), a dose-dependentassociation was found between increasing cord serum PCB levels and poorer performance on theVerbal (p < .05) and Memory scales (measure of verbal and numerical short-term memory) ( p =.02), with the most highly exposed children scoring 6.6 points (0.66 SD) lower than the leastexposed children, after adjusting for confounders. The magnitude of this deficit is modest (0.66

to 0.92 on the average), and there was no evidence of mental retardation or gross impairment.There were no significant effects on the Beery VMI or the PPVT-R, indicating no adverse effectson visual-motor scores or long-term memory (Jacobson et al. 1990). Exposures to lead, PBBsand seven organochlorine pesticides were also evaluated in this study, and statistically controlledfor, when necessary.

Cognitive Assessments . Higher prenatal exposure to PCBs was associated at age 11 (n=212)with significantly lower full-scale and verbal IQ scores (6.2-6.5 points lower in the most highlyexposed group), as well as poorer verbal and numeric memory and attention span. Prenatal PCBexposure was associated with poorer verbal comprehension, particularly on the vocabulary,information and similarities subtests, as well as poorer performance on the freedom-from-

distractibility scale, which assesses focused attention, short-term memory, and executivefunction (Jacobson et al. 1996).

Assessment with academic achievement tests also showed a dose-related association between prenatal PCB exposure and poorer word and reading comprehension after controlling withseparate regression analyses for school district score variations, postnatal PCB and DDTexposure, and lead exposure (Jacobson et al. 1996).

The importance of controlling for heavy metal exposure in endocrine disruptor neurodevelopmental studies is illustrated by findings in this study: It was shown that lead andmercury were significantly related to poorer performance after controlling for confounding

variablesa blood lead level of > 10 mcg/dl at four years of age was associated with lower IQ, poorer verbal comprehension, and poorer reading comprehension (p< .05), while a higher mercury concentration was associated with poorer spelling at 11 years of age (p=.006) (Jacobsonet al. 1996).

Postnatal PCB exposure from breast milk was not associated with poorer performance on any of the tests administered, nor was the childrens serum PCB concentration at 11 years old related toany of the IQ or achievement measures (Jacobson et al. 1996).

Criticisms The Jacobson studies have been reviewed thoroughly by several authors (Paneth1991; Seegal 1996; Cicchetti et al. 2004; Schell, Budinsky et al. 2001; Schantz 1996) and have

been shown to have some methodological flaws, although many of their findings have beenreplicated in later studies.

The method of exposure assessment is widely considered to be inaccurate. As noted by theJacobsons themselves, maternal recall at one day postpartum of lifetime quantity and species of fish consumption was subject to significant recall bias and inaccuracy (Jacobson et al. 1983,cited in Schell et al. 2001). Indeed, the measure of self-reported fish consumption did notcorrelate with the other measures of tissue PCB concentrations, confirming the inaccuracy of this


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measure (Schell et al. 2001). Schantz notes (Schantz 1996) that a later study used a similar weighting approach (Dar et al. 1992), but women were asked to recall the type and quantity of fish consumption for only the past 12 months. In this case, fish consumption correlated morehighly with serum PCB levels.

It should be noted, however, that the misclassification bias of recall studies does not increase the probability of finding significant results, nor does it produce systematic patterns of data (Stewartet al. 2004). On the contrary, it tends to decrease the likelihood of finding an association andreduce the power of the study. Therefore, the weak positive associations found in the study mayactually represent an underestimation of the effects.

Although the investigators attempted to improve the accuracy of PCB exposure indices bymeasuring PCB levels in cord serum, maternal serum and breast milk, critics hold that thedetection limitations of the gas chromatograph, the low percentage of cord serum samplesobtained, and the high attrition rate of women from the highest fish consumption category,resulted in weak data (Schantz 1996). The validity of the composite score developed in 1996 has

been questioned because the authors failed to account for pharmacokinetic differences in thevarious fluid compartments, and because the PCB levels of the tissues used (cord serum,maternal serum, breast milk) had not always been correlated in the previous studies (Cicchetti etal. 2004). The Jacobsons have also been criticized for their pick and choose approach toapplying the four exposure indicators to the various endpoints measured (Schell et al. 2001;Schantz 1996).

The control sample has also been found to have shortcomings with respect to control for confounding variables. According to Paneth, the fact that the control sample was only one-thirdthe size of the exposed sample reduced the studys statistical power by 50% compared withsamples of equal numbers (Paneth 1991, cited in Schantz 1996). In prospective studies, the

larger the control group, the greater the ability to detect statistically significant differences between sample groups (Mausner and Kramer 1985, cited in Schell et al. 2001). Schantz alsoargues that, because exposure was not randomly assigned in this study, controls should have

been carefully matched on as many potential confounders as possible. She notes that matchingis particularly important in studies of neurodevelopmental outcomes because they can beinfluenced by a wide variety of socioeconomic and maternal factors (Schantz 1996). Significantdifferences in lifestyle variables were later found (e.g., alcohol consumption and smokingquantity), while others were not ever considered (e.g., diabetes and gestational diabetes) (Schellet al. 2001). Paneth notes (Paneth 1991, cited in Schell et al. 2001) that if several measuredvariables differ substantially between the two sample groups then it is likely that other,unmeasured, differences might account for the findings.

Cicchetti et al. (2004) note that the crucial variable of parental IQ was not adequately controlledas a potentially confounder despite the fact that childrens IQ is affected by both geneticendowment and environment. Environment was controlled through administration of the HOMEscale. Maternal intelligence was measured using the PPVT-R, a measure only of vocabulary, notIQ (Maxwell et al. 1984), and there was no control for parents academic achievement. In their opinion, this lack of appropriate control of parents IQ and academic achievement, coupled witha failure to control for chance findings, makes the conclusion of IQ and academic deficits


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associated with PCB exposure insupportable. However, it was later shown (Stewart et al. 2004)that the PPVT controlled adequately for maternal IQ in the Oswego cohort study. Whencompared with a more direct measure of maternal IQ, the Kaufmann Brief Intelligence test(KBIT), the PPVT controlled for maternal IQ the same or better, both by itself and whenincluded with other potential confounders that evidence colinearity with IQ, such as HOME

scores, maternal education, and substance use/abuse. This tends to lend credence to thearguments supporting the validity of using PPVT to control for maternal IQ in these studies.

Environmental confounders like methylmercury were not controlled for, either, because theJacobsons considered the correlation between serum PCBs and methylmercury to be too low,even though primate studies had shown that fetal exposure to low levels of methylmercury

produced similar neurodevelopmental effects to those reported in the Jacobson study (Schell etal. 2001). In studies on the Faroese cohort, for example, neuropsychological results showing asignificant relationship to PCB exposure before adjusting for methylmercury dropped out after controlling for methylmercury intake (Grandjean et al. July-August 2001, cited in Cicchetti et al.2004).

Cicchetti et al. (2004) also criticize the Fagen Test for poor reliability (Cicchetti et al. 2004).Responses (Stewart et al. 2004) to Cicchetti et al.s criticisms of the test-retest reliability of theFTII have acknowledged that the test-retest reliability of the FTII mean novelty preference score,in particular, has not been as reliable over time as first suggested and that more stable andinternally consistent measures of infant visual recognition memory need to be employed. Inaddition, they have even questioned whether or not psychometric assumptions of internalconsistency and stability over time apply to a measure like the FTII.

However, regardless of the validity of Cicchetti et al.s (2004) criticisms, the central question iswhether it is possible that the PCB associations are due to chance or residual confounding. The

less reliable the test, the less likely that significant relationships will be observed and thus biasresults in favor of the null hypothesis. This makes the fact that the Michigan study foundsignificant associations all the more meaningful, especially since the results were later replicatedin the Oswego study (Stewart et al. 2004).

The Jacobson study series of the Lake Michigan cohort is the most recognized study reportingneurodevelopmental effects of PCBs in humans. Its technical limitations in study design andexposure measurements leave some uncertainties that preclude definitive conclusions regarding acause and effect relationship (Schell et al. 2001). However, as Stewart et al. (2004) articulatelyexplain,

The reality in epidemiology is that no single study is ever definitive, as there is alwaysthe possibility that results may be due to residual confounding or, as yet, unknown or unmeasured sources of bias...The evaluation of a significant finding...is whether or notthe finding is replicated. Therefore, multiple studies are conducted and the resultscompared to examine replicable findings. To the extent that an association is replicated,it gains credibility as a scientifically defensible association. In the unlikely event that anassociation is falsely judged significant in a single study, it is incredibly unlikely thatchance will operate in the same way to produce identical results in a second study. This


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Bayley Scales of Infant Development was administered to the children at 6 months, 12 months,18 months, and 24 months (Gladen et al. 1988; Rogan et al. 1991). The McCarthy Scales of Childrens Abilities (cognitive ability, gross and fine motor abilities) were administered at ages3, 4, and 5 years (Gladen et al. 1991). Tests were administered at three different centers, andthere were several examiners at each centerthe authors did not carry out formal intra- or inter-

rater testing, only monitored scores and discussed any drift at staff meetings (Gladen et al. 1988).

Control variables and analysis For the neonates, multiple regression analysis was used toassess the correlations between BNBAS scores to PCB and DDE exposure levels (Rogan et al.1986b). The following potential confounders with p .05 were considered for the BNBASmultiple regression analyses: the childs race (white, black, other), sex, birth weight, headcircumference, age at which the test was administered, number of hours since last nursing, and

jaundice status; the mothers age, education, and occupation, tobacco and alcohol use in general,consumption of sport fish during pregnancy, and if she had received general anesthesia (Rogan etal. 1986b). Parental IQs and home environment were not controlled for.

For the Bayley assessments, the authors identified potential confounding variables a priori, based on the analyses performed on the neonates and variables considered in other studies(Gladen et al. 1988). These included the childs sex, gestational age, birth weight, headcircumference, jaundice, duration of breast feeding, number of older siblings, number of abnormal reflexes on the BNBAS, and age at which the Bayley exam was given; and maternalage, race, education, occupation, tobacco and alcohol use (Gladen et al. 1988). Parental IQs andhome environment were not controlled for.

Covariates for the McCarthy Scales analyses included were maternal age, race, occupation,education, smoking, drinking, childs gender, number of older siblings, bottle feeding vs. breast-feeding of short, medium, long, or very long duration. Statements that differences were not

significant indicated p values >.10. Results The NBAS assessments showed that higher PCB exposure correlated significantly withlower muscle tone and lower activity levels, while both PCBs and DDE were associated withhyporeflexia (Rogan et al. 1986b). When only children assessed within three days of birth wereconsidered, the effect of PCBs on tonicity no longer achieved statistical significance, but theauthors attribute this to insufficient sample size rather than to confounding from the age at testadministration (Rogan et al. 1986b).

The Bayley psychomotor index (PDI) showed statistically significant downward trends at six andtwelve months that correlated with increasing PCB exposure (a 0.96 point drop per 1 ppmincrease in PCB exposure) (Gladen et al. 1988). The adjusted scores on the psychomotor scalesat 18 and 24 months showed a statistically significant decrease at 24 months only (four to nine

points lower among children in the top fifth percentile of in utero PCB exposure) (Rogan et al.1991).

These results differ from the Lake Michigan cohort, which showed no decrease in the Bayley psychomotor scores with increasing PCB exposure. However, because the Jacobsons assessed psychomotor function only at five months and four years of age, not between six months and two


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years, the discrepancy of results was thought to be due to differences in timing of the assessment(Schantz 1996). However, later studies testing children at the same age would also showdiscrepancies.

The mental index scores at six and twelve months were not related to in utero PCB exposure,

while the DDE showed a relationship at six months that disappeared at 12 months (Gladen et al.1988). There was no evidence of an effect through in utero exposure to DDE (Rogan et al.1991).

There was no association at any year found between in utero exposure to PCBs and any of theMcCarthy scales, including psychomotor and memory (Gladen et al. 1991). Thus, the delay in

psychomotor development measured with the Bayley scales did not persist beyond two years of age (Schantz 1996), and the verbal and memory deficits found in the Jacobsons Lake Michigancohort were not confirmed (Schantz et al. 2003).

Criticisms Just as with the Lake Michigan studies, North Carolina studies are criticized for

unreliable measurement of serum PCB levels due to the limitations of the packed column gaschromatography technique used (Cicchetti et al. 2004; Schantz1996). No congener-specific datais available for these studies because of this.

As mentioned above, the authors method for estimating PCB exposure based on milk PCBlevels may have overestimated the actual PCB concentration by a factor of two (Jensen 1987,cited in Schantz et al. 2003). Due to the different analytical methods used to assess exposureindices in the Lake Michigan and North Carolina cohorts, it is not possible to compare theexposure levels directly, making it difficult to assess the discrepancies between the two studies(Schantz 1996).

Like Jacobson and colleagues, Rogan and Gladen did not include as potential confoundersmaternal IQ and the home rearing environment, important predictors of cognitive outcome(Cicchetti et al. 2004). Unlike the Michigan researchers, who controlled for alcohol and tobaccouse specifically during pregnancy, the North Carolina researchers questionnaire asked only aboutuse of these substances in general, thus making it difficult to assess reliably the prenatal effectsof these potential confounders (Cicchetti et al. 2004).

Dutch cohort The first study to assess the effects of specific PCB congeners was initiated in1989 in the Netherlands by the Dutch government. Contamination of breast milk with PCBs anddioxins in the Netherlands is among the highest in the world (WHO 1989, cited in Patandin et al.1999). The Dutch PCB/Dioxin study is a prospective, longitudinal study designed to assess the

possible adverse effects of in utero and lactational PCB and dioxin exposure. It was carried outin two widely separated areas in the Netherlands: Groningen, a semi-urban area; and Rotterdam,a highly industrialized region (Koopman-Esseboom et al. 1996).

The initial cohort consisted of 418 pregnant women non-randomly recruited through their midwife or obstetrician between 1990 and 1992; 211 of the women came from Gronigan, 207from Rotterdam. They were visited in their homes for an explanation of the study protocol. Onehalf of each group planned to breast feed for at least six weeks, while the other half planned to


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formula feed and agreed to use the same brand from one batch as a reference (Huisman et al.1995b). To participate in the study the women and their children had to meet certain criteria.They were all healthy Caucasians who had suffered no complications during pregnancy or delivery. All of the 418 children were first- or second-born via spontaneous vaginal delivery at37-42 weeks of gestation with no forceps or vacuum extraction. Mothers agreed to provide a

maternal blood sample in the last month of pregnancy and a cord blood sample from the baby at birth (Huisman et al. 1995b). The study reported on the childrens neurodevelopment at 3, 7, 18,42, and 84 months of age.

Measures of exposure In utero PCB exposure was assessed by measuring maternal and cord blood levels of the four non-planar PCB congeners 118, 138, 153, and 180 (International Unionof Pure and Applied Chemistry (IUPAC) nomenclature) by gas chromatography with electroncapture detection (GC-ECD). The samples were centrifuged and stored at -20 until analysis(Huisman et al. 1995b). The sum of the four congener levels in cord ( PCB cord ) and maternal(PCB maternal ) blood were calculated (Koopman-Esseboom et al. 1996). These four congenersare the predominant ones found in human tissue worldwide, typically account for around 50-60%

of the total PCB's, and are high enough to measured very accurately (Schantz et al. 2003;Koopman-Esseboom et al. 1996). The detection limit for the four congeners was 0.01ppb(Huisman et al. 1995b).

The breast fed group was studied using additional exposure variables generated from breast milk PCB and dioxin measurements. A 24-hour representative breast milk sample was collected fromthe nursing mothers two weeks post partum and analyzed for the 17 ubiquitous 2,3,7,8-substituted polychlorinated dibenzo- p-dioxins (PCDD) and dibenzofuran (PCDF) dioxincongeners, which are usually found in biotic samples; three planar PCBs (77, 126, 169); threemono- ortho PCBs (105, 118, 156); two di- ortho PCBs (170, 180); and 18 other non-planar PCBs(28, 52, 66, 70, 99, 101, 128, 137, 138, 141, 151, 153, 177, 183, 187, 194, 195, 202) (Patandin et

al. 1998).These compounds were measured in breast milk rather than blood because plasma has arelatively low fat content compared with human milk, and too large a volume of blood wouldhave been necessary to measure all of the PCDD, PCDF, and PCB congeners (Huisman et al.1995b). This approach was considered valid because dioxin levels in human milk have beenshown to correlate highly with the dioxin levels in maternal plasma and adipose tissue (Van denBerg et al. 1994, cited in Koopman-Esseboom et al. 1996; and Schantz et al. 2003). The four PCB congeners 118, 138, 153, and 180 were also measured in the breast milk of the nursingmothers and served as additional indicators of prenatal exposure ( PCB milk ). Levels in theformula given to bottle-fed infants were below the limits of determination (Huisman et al.1995b). Another exposure variable for the breast fed infants was formed by summing all of thenon-dioxin-like PCB congener levels, including those in PCB milk .

The 17 dioxins and three planar PCB congeners were measured by gas chromatography-high-resolution mass spectrometry, and the 23 non-planar PCB congeners were measured by GC-ECD(Huisman et al. 1995b). The samples were analyzed at the Nutrition and Food ResearchInstitute, Zeist, the Netherlands (Vreugdenhil et al. 2002).


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The toxic equivalency factor (TEF) approach was used to express the toxicity, or total toxicequivalent (TEQ), of the dioxins and dioxin-like PCBs in the breast milk. The TEF reflects agiven dioxin compound's Ah receptor-mediated toxicity relative to 2,3,7,8-TCDD, which isassigned the maximum toxicity designation of one. Other dioxin and dioxin-like compounds aregiven equal or lower numbers, with each number roughly proportional to its toxicity relative to

that of 2,3,7,8-TCDD. The TEF approach was developed by the WHO (Van den Berg et al.1998) after experts deemed that there was sufficient evidence from both in vivo and in vitro studies supporting the dose or concentration-additivity model for Ah receptor-mediatedresponses. It is used extensively by scientists around the world.

However, as noted earlier, PCBs and dioxins have also been shown to exert effects by alteringhormone and neurotransmitter levels; thus their neurotoxicity via endocrine disruption likelyoccurs by other routes than Ah receptor agonism, and the TEQ may not be the best predictor of endocrine disruptor-mediated neurotoxicity of the dioxin-like compounds. However, the TEFapproach is currently the only method of assessing toxicity of mixtures of dioxin-likecompounds.

The 26 PCB congeners measured included dioxin-like (77, 105, 118, 126, 156, 169), and non-dioxin-like (28, 52, 66, 70, 99, 101, 128, 137, 138, 141, 151, 153, 177, 183, 187, 194, 195, and202), based on their Ah receptor agonist activity (Patandin et al. 1998). Interestingly, the studieson the Dutch children are inconsistent in their classification of the di- ortho congeners 170 and180: They are classified as dioxin-like in all studies published in 1998 or earlier, but wereclassified as non-dioxin-like in the studies published in 1999 and after. It is possible that the later studies reflected the WHO recommendation to discontinue use of the toxic equivalency factors(TEFs) established previously for di- ortho PCBs 170 and 180 because of insufficient in vivo evidence for Ah receptor-agonist activity (Van den Berg et al. 1998). However, no mention of the discrepancy was found in the literature.

Using the TEF approach, the authors calculated total PCB-dioxin toxic equivalent (TEQ) values by multiplying the milk concentrations by the TEFs of the compounds measured. They thenformed five exposure variables based on the TEQs: Total PCB-dioxin TEQs, dioxin TEQs,

planar PCB TEQs, mono- ortho PCB TEQs, di- ortho PCB-TEQs (Lanting et al. 1998). For thestudies published in 1999 and after, the di- ortho PCBs were not included in the PCB-dioxinTEQ, but were included in the sum with the other 18 non-dioxin-like PCBs.

Although this review focuses on neurological effects of prenatal exposure, it should be noted that postnatal exposure was also assessed using the PCB milk for PCB congeners 118, 138, 153, and180. As mentioned above, the formula used for the bottle-fed infants was tested, and no PCBswere detectable (Koopman-Esseboom et al. 1996; Huisman et al. 1995b). The breast milk PCB-dioxin TEQ levels calculated for the other compounds used to estimate in utero exposure werealso used to estimate postnatal exposure through breastfeeding. Both values were multiplied bythe number of weeks of breastfeeding to give a total exposure estimate.

Only 105 milk samples were obtained, of which 80 could be measured accurately for the totalPCB-dioxin TEQ level, and 100 for the PCB milk sum, due to either inadequate sample amountsor chromatogram interferences (Koopman-Esseboom et al. 1996).


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The PCB maternal averaged 2.2 1 ppb, about five times higher than the PCB cord , whichaveraged 0.5 0.3 ppb, but they were highly correlated (r=0.72, p < .001) (Koopman-Esseboomet al. 1996). When the values were adjusted for the differences in lipid content between maternaland cord blood, the levels were similar (Schantz et al. 2003). The mean PCB milk based on thefour congeners measured in blood was 428.5 ng/g of milk fat, whereas the mean PCBs based

on all 23 congeners measured in milk was 455.9 ng/g (Koopman-Esseboom et al. 1996). Thiswas lower than the levels reported for Michigan (812 ng/g) and North Carolina (1770 ng/g).However, as discussed earlier, these studies used packed-column gas chromatography to measurePCB levels, and the analytic method used in the North Carolina study may have overestimatedthe PCB levels by a factor of two, so comparisons may not be valid (Schwartz et al. 1983; Roganet al. 1986a; Jensen 1987, cited in Schantz et al. 2003). However, the Dutch study authors statethat, despite the differences in analytical methods in the Michigan and North Carolina studies,the estimated levels of exposure on the basis of maternal milk samples are reasonablycomparable (Huisman et al. 1995b).

The total PCB-dioxin TEQs averaged 66.6 24.2 pg TEQ/g milk fat, of which dioxins and

furans represented 46%, planar PCBs 24%, mono- ortho PCBs 23%, and di- ortho PCBs 7%(Koopman-Esseboom et al. 1994a, cited in Schantz et al. 2003, Table 1). The total dioxin TEQsare higher than in the United States, but are comparable to other highly industrialized WesternEuropean countries such as West Germany and the United Kingdom (WHO 1989, cited inSchantz et al. 2003).

At 42 months of age, plasma samples were obtained from the children and the current PCB body burden was assessed using the sum of PCBs 118, 138, 153, and 180 ( PCB 42 mo ). These samples,also, were analyzed at the Nutrition and Food Research Institute, Zeist, the Netherlands(Vreugdenhil et al. 2002).

No differences were found between the Rotterdam and Groningen groups with respect to PCBconcentrations measured in maternal, cord, and 42-month-old plasma, nor in breast milk PCBand dioxin concentrations (Patandin et al. 1999).

Other measures -Lead and cadmium were measured at 18 months of age in a subgroup (n = 151)to study the neurotoxic influence of these heavy metals along with PCBs and dioxins.

The effect of PCBs and dioxins on thyroid hormone status on the mother-infant pairs was alsostudied in a breastfeeding subgroup of the Rotterdam cohort (n = 105) (Koopman-Esseboom etal. 1994b). TSH, total T3, total T4, free T4 levels were measured in the mothers in the lastmonth of pregnancy and two weeks post-partum; and in the infants at weeks and three months of age.

Instruments and Outcome Measures Neurological Assessments. The neurological condition of the infants was assessed at 10 to 21 days of age by two different observers (one in Rotterdam, theother in Groningen) using the Prechtl neurological exam. The exam measures postural tone,reflexes, and responses and has proven to be predictive for later major and minor neurologicaldysfunction (Huisman et al. 1995b). The Prechtl leads to a diagnostic classification of normal,suspect, or abnormal. The infants were also given a neurological optimality score (NOS) based


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on the infants cluster scores and on individual items for which an optimal range was defined(Schantz et al. 2003).

The childrens neurological condition was assessed again at 18 months (Huisman et al. 1995a)and 42 months (Lanting et al. 1998) by two examiners (one in each city) using the

Touwen/Hemple method, an age-specific neurological examination that yields a qualitativeappraisal of brain function (Lanting et al. 1998). It assesses motor functions like grasping,sitting, crawling, standing, and walking (Huisman et al. 1995a). The examiners were blind to thechildrens exposure levels. The children were classified as normal, mildly abnormal, or abnormal. As in the neonatal assessments, the neurological findings were also evaluated in termsof optimality (NOS) in which a list of 57 neurological items, most describing the fluency of movements as an indicator of brain function integrity, were assigned an optimal range. Thechildren would receive one point for each item scored as optimal.

Bayley Scales of Infant Development . The childrens mental developmental index (MDI) and psychomotor developmental index (PDI) were measured in the Rotterdam group only (n = 207)

with the Dutch standardized version of the Bayley Scales of Infant Development (BOS 2-30) at3, 7, and 18 months of age. All Bayley tests were performed at the infants homes in the presenceof the parent(s) by one examiner who was blind to the infants PCB and dioxin exposures(Koopman-Esseboom et al. 1996).

Cognitive Assessments . The childrens cognitive abilities were assessed at 42 months of age bytwo different examiners (one in each study center) with the Kaufman Assessment Battery for Children (K-ABC) (n=395, 94%) (Patandin et al. 1999). The K-ABC is a standardized test of intellectual function similar to the McCarthy Scales of Childrens Abilities. It yields an overallcognitive score as well as scaled scores for sequential and simultaneous processing abilities. Thesequential subtests include hand movement, number recall, arithmetic and gross and fine motor

skills; and the simultaneous subtests include the Magic Window, face recognition, Gestaltclosure, vocabulary, faces and places, and riddles (Patandin et al. 1999). For logistical reasons,only the Rotterdam sample (n=193) was assessed for verbal comprehension with the ReynellLanguage Developmental Scales (RDLS). Because language ability, and verbal comprehension,in particular, is a measure of mental ability, the RDLS is considered to be a measure of generalmental ability (Patandin et al. 1999).

At 84 months (6.5 years) of age, 376 (90%) of the original cohort of 418 children werereassessed (Vreugdenhil et al. 2002) using the Dutch version of the McCarthy Scales of Childrens Abilities which, as noted earlier, measures cognitive ability, as well as gross and finemotor abilities.

Control variables and analysis Obstetrical variables were evaluated according to anobstetrical optimality list (Touwen et al. 1980, cited in Huisman et al. 1995b) consisting of 72items that measure socioeconomic situation, and pre-, intra- and post-partum conditions. Anoptimality score was calculated by counting the number of items that fulfilled preset criteria for optimality.


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Potential confounders identified with univariate analyses included the study center (Rotterdam or Groningen) to adjust for inter-rater variability, parents educational level (high vs. low accordingto if at least secondary education was completed), profession (three categories includingstudent/unskilled/unemployed vs. skilled/middle class employee vs. independent middleclass/higher profession), maternal smoking and alcohol consumption during pregnancy (yes or

no), parity (first or second), maternal age, duration of gestation, birth weight, Apgar score at oneminute and five minutes, sex of infant, weeks of breast-feeding, thyroid hormone levelsmeasured in maternal blood in the last month of pregnancy, cord blood at birth, infant blood attwo at weeks , three months, and 18 months of age. The HOME inventory was carried out at 18months of age to control for differences in home environment. The verbal IQ of the principalcaregiver parent (usually the mother) was assessed only for Patandin et al.s (1999) 42-month K-ABC study using the Information and Vocabulary subtests of the Dutch Wechsler AdultIntelligence Scale.

For the infant Prechtl and NOS assessments, low, medium and high exposure were defined as the5th, 50 th, and 90 th percentiles, respectively, of measured congener concentration. The chi-square

and Wilcox on rank sum tests were performed at the 5% level for a univariate comparison of theresults in Groningen and Rotterdam. Both univariate analysis and logistic regression analysiswere used to examine the relation between test outcome on one hand, and levels of PCB anddioxin exposure, and obstetrical variables, on the other hand. The NOS and the Prechtl posturaltone and reflex and response clusters were dichotomized at the median of the pooled population.The PCB and dioxin values were logarithmically transformed to normalize for positive skew.After adjusting for obstetrical variables, the effect of each chemical compound and total TEQscores was examined. The results were reported as odds ratios associated with doubling of concentrations, together with 95% confidence intervals, without any correction for multiplehypothesis testing (Huisman et al. 1995b).

Data analysis for the Bayley Scale results was performed using the Statistical Package for theSocial Sciences (SPSS/PC, Cary, NC), and studied the relationship between mean Bayley scoresand perinatal PCB/dioxin exposure (low, medium, and high exposure) (Koopman-Esseboom etal. 1996). Multiple regression analysis was used to study the effects of pre- and post-natalexposure to PCBs and dioxins separately as well as combined.

The analysis for the Touwen/Hemple method and NOS assessments at 18 months used the chi-square, Students t -test, and the Mann-Whitney U -test to compare groups. Multiple linear regression analysis was used to assess the effects of PCB and dioxin exposure on brain function.The dependent variables were the NOS and the fluency cluster score at 18 months. The NOSscore distribution was skewed to the left, so it was transformed to achieve normality. The PCBand dioxin levels were logarithmically transformed. The other independent variables weresocial, perinatal and obstetrical variables from the obstetric optimality list, and the study center (Huisman et al. 1995a). A p value of .05 was considered significant.

Data analysis for the Touwen/Hemple and NOS neurological assessments at 42 months of agewas the same as that used for the 18 month assessment described above, including normalizationof a left-skewed NOS distribution (Lanting et al. 1998). Because the plasma PCB values were

positively skewed, they were normalized by natural logarithm (Patandin et al. 1999). The K-


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ABC and RDLS data analysis used the chi-squared, the Students t -, and the Mann-Whitney teststo perform single variable comparisons of the two groups. Multiple regression analyses adjustedfor covariables were used to assess exposure effects. Dependent variables were scores on theoverall cognitive scale, and the sequential and simultaneous processing scales of the K-ABC, andon the verbal comprehension scale of the RDLS. Covariables entered in the final regression

analyses are listed above, and included the HOME score and parental verbal IQ.

As in the previous assessments, the effect of prenatal PCB exposure estimated from the PCBsin maternal and cord blood was examined in the whole group. The breast-fed group wasadditionally studied for the effect of prenatal exposure to dioxin TEQs, dioxin-like PCB TEQsand 20 nondioxin-like PCBs (here including the di- ortho PCBs 170 and 180) measured from

breast milk concentrations (Patandin et al. 1999).

The data analysis on the McCarthy scale assessments at 84 months of age used the chi-square,Student t -, and the Mann-Whitney U tests to compare groups for a single variable. PCB anddioxin levels were normalized for positive skew by a natural logarithmic transformation. Effects

of PCB and dioxin exposure on cognitive and motor abilities were studied using multipleregression analyses. The list of covariables in the final regression relevant to prenatal exposureeffect assessment included study center, sex, parity, maternal age at birth, parental educationlevel, parental verbal IQ and HOME score, and age at examination. To evaluate effects of

prenatal PCB exposure in the two feeding groups separately, an interaction variable (the productof feeding type and PCB) was included in the regression model. The authors note that nocorrection for multiple testing was made because of the exploratory nature of the study, and two-tailed p values


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The significant associations could simply be due to higher prevalence of the congeners in thesample population, or due to more reliable measurement afforded by higher concentrations(Schantz et al. 2003). No insight into human in vivo structure-activity relationships of the dioxinand PCB congeners was provided by this study.

Unlike the neonatal findings, the neurological assessments at 18 months (Huisman et al. 1995c)and 42 months (Lanting et al. 1998) using the Touwen/Hemple method showed no association between the NOS and PCB or dioxin levels in breast milk at either age. However, at 18 months,a small two-point difference in NOS (49.9 vs. 47.9) was found between children with low cordPCB cord or maternal PCB maternal blood exposure variables at the 5 th percentile (e.g. 0.18 ppb)and those with high exposure in the 95 th percentile (i.e. 0.86 ppb). No adverse effects of prenatalPCB exposure on the neurological condition found at birth and 18 months of age could bedetected at 42 months of age.

Bayley Scales of Infant Development. A significant negative association between prenatal PCBexposure and psychomotor development was found at 3 months of age: A doubling of the

maternal blood sum PCB maternal was associated with a three point decrease in the psychomotor development index (PDI). No effect could be found when the cord blood sum PCB cord wasused, even in cases in which the PCB maternal still had a negative influence. When used as themeasure of prenatal exposure for the breastfed group, the total PCB-dioxin TEQ level also wasnegatively associated with psychomotor development at three months, but did not achievestatistical significance ( = -7.4, SE = 4.0, p = .07). There was no relationship found betweenexposure and the mental development index (MDI) (Koopman-Esseboom et al. 1996).

At 7 months of age, no significant association was found between prenatal exposure and PDI or MDI scores. The only significant result related to a strongly positive association between PDIscores and duration of breastfeeding, the effect of which was decreased in the children with

medium and high postnatal total dioxin TEQ exposures (Koopman-Esseboom et al. 1996).At 18 months, no relation was found between prenatal exposure and PDI or MDI scores. Aswould be expected, positive relationships were found between the childrens mental developmentand the HOME score, as well as with the mothers level of education (Koopman-Esseboom et al.1996).

The Dutch study Bayley Scale negative effect on PDI at three months cannot be compared withMichigan or North Carolina studies because the children were not tested at three months of agewith the Bayley Scale instrument. The Dutch Bayley Scale results at seven months are consistentwith those of the Michigan Bayley Scale assessment (Jacobson et al. 1986) at five and sevenmonths of age, which showed no association between prenatal PCB exposure and either MDI or PDI scores.

In contrast, the North Carolina studies (Gladen et al. 1988; Rogan et al. 1991), showed a negativerelationship between prenatal PCB exposure and PDI scores at the ages of 6, 12, and 24 months.As noted earlier, the negative trend shown at 18 months was not statistically significant. Schantzsuggests that, because the North Carolina cohort was much larger (880 children) it provides more


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statistical power than the Dutch Rotterdam or the Michigan cohorts, which comprised 207 and313 children, respectively (Schantz et al. 2003).

Cognitive assessments. The Kaufman Assessment Battery for Children (K-ABC) cognitiveassessment at 42 months of age showed that, after controlling for confounders, prenatal PCB

exposure measured from maternal blood ( PCB maternal ) was significantly associated with lower scores on the overall cognitive scale, as well as the sequential and simultaneous processingscales (p < .05). The score on all three scales in the highest exposed group ( PCB maternal 3 ppb)was four points lower than that in the lowest exposed group ( PCB maternal < 1.5 ppb). Nonegative effects on K-ABC performance were found to be related to prenatal PCB or PCB-dioxinTEQ exposure. A negative association was also found between PCB maternal and the ReynellDevelopmental Language Scales (RDLS) scores in the Rotterdam cohort, but the association wasnot statistically significant (p = .08) (Patandin et al. 1999).

When the breast fed and formula fed children were assessed separately, the effects of prenatalPCB exposure on cognitive abilities at 42 months of age were more pronounced in the formula

fed group than in the breast fed group, even though the breast fed children had higher prenatalexposure levels. The analyses showed that the differences in vulnerability to prenatal PCBexposure related more to differences in parental and home environmental characteristics than to

beneficial effects of breast-feeding (Vreugdenhil et al. 2002). When the results were adjusted for these covariables, the scores of the two feeding groups no longer differed.

A discrepancy appears to exist between the neurological and 42 month cognitive assessmentresults. The adverse effects of prenatal exposure on neurological condition at birth and 18months could not be detected at 42 months of age, while cognitive abilities at 42 months werenegatively associated with in utero exposure. The authors suggest that this difference can beexplained by the testing procedures, insofar as the K-ABC measures cognitive abilities in a

quantitative fashion and the neurological examination is a qualitative measure of braindevelopment (Patandin et al. 1999).

The McCarthy Scales assessment at 84 months showed no relationship between prenatal PCBexposure PCB maternal and the general cognitive index (GCI), memory, or motor skills, after adjustment for covariables. There was no relationship when the breast fed and bottle fed wereconsidered separately.

Interestingly, when prenatal PCB exposure PCB maternal was analyzed with the interactionvariables of maternal age, parental IQ, and parental education level, negative effects were seen inchildren born to younger mothers and to parents with lower verbal IQ scores and education level.In formula fed children, higher PCB

maternalwas related with lower motor scores in children

whose parents had lower verbal IQ scores or lower HOME scores. These results further supportthe evidence that favorable parental and home characteristics could compensate for or mask developmental delays (Vreugdenhil et al. 2002).

Exposure to non-dioxin-like PCBs and PCB milk showed negative relationships, but were notstatistically significant.


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Other measures. Lead and Cadmium- The concentrations of lead and cadmium were very lowand not related to outcome variables (Patandin et al. 1999).

Thyroid hormone -Elevated levels of dioxins and PCBs were shown to alter the human thyroidhormone status. Except for one mother with an elevated TSH level, all thyroid hormone levels of

the mothers and infants were within the normal limits. However, some subtle but significant (all p < .05) effects were found. Higher total dioxin-PCB TEQs correlated significantly with lower plasma levels of maternal total T3 and total T4, and with higher levels of TSH in the infants attwo weeks and three months of age. Infants exposed to higher TEQs also had lower total T4 andfreeT4 at two weeks of age. Higher PCB maternal and PCB cord were also associated with higher TSH levels in infants at two weeks of age (Koopman-Esseboom et al. 1994b; Schantz et al.2003).

However, although other animal and human studies have also demonstrated that exposure todioxin-like compounds can alter thyroid hormone homeostasis concurrently withneurobehavioral changes, it remains to be definitively established that changes in thyroid

function are responsible for the neurobehavioral effects of DLCs (Hauser et al. 1998).

Criticisms -- The Dutch study results are complex because many different outcomes wereassessed in relation to so many different exposure variables (Schantz et al. 2003). One criticismthat has been raised about the statistical analyses used is that there was failure to control for thenumber of significant findings that could have been expected by chance alone. Cicchetti et al.(2004) illustrate this issue, using as an example the more than 40 multiple regression analysesKoopman-Esseboom et al. (1996) performed to relate Bayley Scale MDI and PMI scores at agesthree months, seven months, and 18 months with various prenatal and post-natal exposurevariables, resulting in only three significant findings, one of which was not toxin-related.Cicchetti et al. (2004) argue that two toxin-related findings out of 40 analyses might very well be

chance occurrences.However, based on the North Carolina Bayley studies, the investigators had reason to predict asmall but negative association between prenatal PCB exposure and decreased performance on theBayley assessments. If, as Cicchetti et al. (2004) proposed, the investigators had employedBonferroni adjustments to the analyses without regard to prior prediction or theory, this wouldhave moved the critical region from p=.05 to less than .00125, forcing the investigators to retainthe null hypothesis of no relationship.

The Bonferroni correction is a statistical adjustment for multiple comparisons in which the 0.05alpha level is divided by the number of comparisons (n) that are being made on a data set (.05/n).The data are then tested at the resulting alpha value to ensure that the overall chance of making aType I error is still less than .05. It can also be applied to the p value by multiplying it by thenumber of outcomes being tested, and is rounded down to 1.0 if the adjusted p value is greater than 1.0 (Simon 2005).

As Stewart et al. (2004) point out, this is counterproductive in epidemiological studies, becausethe truth of any association is not evaluated in a single study, but rather, by whether or not it isreplicated. Since the effects of background levels of PCBs are thought to be small, extremely


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conservative alpha levels imposed by Bonferroni corrections would greatly limit the possibilityof uncovering real relationships. As noted earlier, if an association is falsely judged significantin one study, chances are minutely small that identical results would be produced in a secondstudy (Stewart et al. 2004).

Another criticism raised by Cicchetti et al. (2004) is the issue of statistical vs. clinicalsignificance, which they illustrate with the 4-point difference in K-ABC scores found betweenthe highest and lowest PCB exposure groups in the Dutch cohort at 42 months of age (Patandinet al. 1999). This difference was presented as clinically meaningful, but a difference this small(0.27 SD) can be expected to occur in the test-retest reliability of the same child on two separateevaluations (Cicchetti et al. 2004). Kaufman (2001, cited in Cicchetti et al. 2004) notes that to

be 90% or 95% certain that you have captured a persons true IQ, the confidence interval must be expanded to 5 or 6 points. In addition, when using standard deviation units as the basis of effect sizes, an effect size of less than 0.50 is small and probably not meaningful (McLean 1995,cited in Cicchetti et al. 2004). Furthermore, Patandin et al. (1999) controlled for covariates onthe whole sample, which they divided into five subgroups based on exposure levels. They then

compared only the two extreme subgroups after deleting the three middle subgroups without re-controlling the extremes for the covariates. Thus, according to Cicchetti et al. (2004), not onlyis four points too small of a difference to be clinically meaningful, but that number of points isnot an actual outcome of the significant results they obtained for the total sample; it is based on agreatly reduced sample that includes only the extremes.

On the other hand, the fact that all participants in the study had some level of PCB and dioxinexposure means that there was no true control population. This is likely to bias the resultsagainst finding an effect (Colborn et al. 1996). Thus, the small negative associations found on theK-ABC might have been larger if true controls had been used.

Other limitations of the study relate to the exposure estimates. Because dioxin TEQs weremeasured in breast milk due to small maternal and cord blood samples, no exposure data wereavailable to evaluate DLC neurodevelopmental effects on the formula fed children. This reducedthe power to detect associations. Moreover, as discussed earlier, breast feeding may have

protected the nursing children from DLC neurotoxic effects and biased the results against findingan effect. Advances in analytic techniques that allow PCB and dioxin congeners in smaller samples will be needed to address this limitation (Schantz et al. 2003).

The European Union provided funding to expand the Dutch study into a transnational,multicenter cooperative study, which included a German cohort in Dsseldorf and a Danishcohort in the Faroe Islands (Schantz et al. 2003).

German Cohort The German cohort consisted of 171 healthy mother-infant pairs frommiddle and upper class families non-randomly -recruited between 1993 and 1995 from theobstetrical wards of three Dsseldorf hospitals. Inclusion criteria included healthy first andsecond born infants born at term with no complications during pregnancy or delivery, and aminimum five-minute Apgar score of seven. The objectives of the study were to assessindependently the neurodevelopmental effects of prenatal and early postnatal PCB exposure on


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one hand, and effects of the home environment on neurodevelopment, on the other. Previousstudies had treated home environment only as a potential confounder (Winneke et al. 1998).

Measures of exposure PCB exposure was based on the sum of PCB congeners 138, 153, and180 ( PCB cord ) measured in umbilical cord blood to assess prenatal exposure and venous blood

PCB 42 at 42 months of age to assess postpartum exposure through breast milk. Samples werecentrifuged and stored at -18 C. The first step of PCB measurement consisted of a column liquidchromatographic sample clean up without a prior solvent extraction step, and the determinationwas done by dual-column capillary gas chromatography with electron capture detector (ECD) or gas chromatograph-mass spectrometer (GC-MS). Ring tests between two analytical laboratoriesin Kiel and Dsseldorf revealed excellent comparability for PCB (r > 0.95) (Walkowiak et al.2001).

Breast milk samples were also collected at two and four weeks post partum to provide anadditional prenatal exposure variable. They were stored at -18 C until they were analyzed for the same congeners ( PCB milk ) (at the Institute of Environmental Toxicology in Kiel using high

resolution gas chromatography with a capillary column and ECD. The two and four week valueswere combined to yield mean values. Ring tests revealed good comparability for lipid-adjustedPCB (r > 0.80) (Winneke et al. 1998). The PCB congener detection limits were 0.01 ppb(serum) and 5 ng/g fat (milk). The correlations between PCBs in cord blood and milk were

positive and highly significant ( r = 0.57, p < .0001) (Walkowiak et al. 2001).

Although the cohort comprised 171 mother-infant pairs, only 169 cord blood samples and 131 breast milk samples were available for PCB analysis. The mean PCB cord was 0.55 ppb, themean PCB milk was 426.5 ng/g fat (Winneke et al. 1998). These are comparable to the Dutchstudy levels which were 0.5 0.3 ppb for cord blood, and 428.5 ng/g fat for breast milk (Koopman-Esseboom et al. 1996). Values for the 42 month levels will not be discussed, as this

review addresses only prenatal exposure effects.The lead levels found in cord blood were very low, with a mean value of 20.3 ppb (Walkowiak etal. 2001).

Instruments and Outcome Measures Home Environment. An infant (0-3 yr) version of theHOME score adapted to fit the German cultural context was administered at 18 months of age athome in the presence of the child. The German HOME consists of 45 items. Inter-rater reliabilityfor two independent observers from the Dsseldorf team at two 11 month intervals, were r =0.61-0.81 (Winneke et al. 1998; Walkowiak et al. 2001).

Psychodevelopmental tests . The childrens psychomotor and cognitive development wereassessed with the Fagan Test of Infant Intelligence (FTII) at seven months of age; the BayleyPDI and MDI at seven, 18, and 30 months of age; and with the K-ABC at 42 months of age.Schantz et al. (2003) state that the children were also assessed with the Heidelberg Test for Language Development at 42 months of age, but these results have not yet been discussed in theliterature.


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Control variables and analysis The children were examined by one examiner who was blindto the childrens PCB levels. By exchanging videotapes with another experienced group inter-rater reliabilities were calculated and found to be satisfactory for both the MDI ( r = 0.85) and thePDI ( r = 0.98). The re-test reliability of the FTII novelty score for the mobile test version after two weeks for two observers and 10 children was found to be zero and even negative ( r = -0.195)

(Winneke et al. 1998).

Potential confounders included age at examination, gestational age, alcohol/smoking during pregnancy (separately scored as yes/no), Apgar score at five minutes, neonatal illness/jaundice,spontaneous delivery, parity, lead in cord blood, chronic diseases during past year, duration of

breastfeeding, parental education (maximum years of schooling of either parent) parentaloccupation (10 categories, highest of either parent), maternal BMI, and maternal verbal IQmeasured with the German form of the Wechsler Adult Intelligence Scale vocabulary subtest(Walkowiak et al. 2001).

From recruitment until 42 months of age, the sample size decreased from 171 to 116; however,

the only significant difference in the remaining sample with regard to the potential confounderswas that the families tended to be better educated (Walkowiak et al. 2001).

The data was analyzed with the statistical data analysis software program SAS 8.01. The PCBdistributions were skewed so all values were logarithmically transformed to yield normalizeddistributions (Walkowiak et al. 2001). Multiple linear regression analysis was used to analyze theassociation of HOME and PCBs with the target variables. The initial regression model includedvariables selected based on priority (e.g., lead in cord blood, maternal age) or those withsignificant association with the outcome (e.g., HOME or Apgar score). In the second model,selection of variables was data-driven. Only variables with correlations at p < .20 with both theexposure index and two or more of the outcome variables were selected after including the initial

variables. The second variables were parity, smoking in pregnancy, and maternal BMI. Alloutcome variables were uniformly adjusted for these variables. Additionally, repeatedmeasurements analysis was done on the Bayley Scales data. One-tailed probabilities were usedthroughout. The basis of the authors justification for using one-tailed probabilities was that thehypotheses were directional (Winneke et al. 1998; Walkowiak et al. 2001).

Results There was no negative association found between cord blood PCBs ( PCB cord ) andany of the outcome measures. However, significant negative associations were found betweenoutcome measures and maternal blood PCBs ( PCB milk ).

Fagan Test of Infant Intelligence. The FTII assessment at seven months of age showedcomplete lack of association between neonatal PCB exposure and visual recognition-memoryscores (Winneke et al. 1998). This result is at variance with the Michigan FTII results at sevenmonths, which showed a dose-dependent negative association with prenatal PCB exposure(Jacobson et al. 1985). The authors suggest that, given the very low test-retest and inter-rater reliabilities of the mobile FTII in this study, the results might not be valid (Winneke et al. 1998).

Bayley Scales of Infant Development. The only negative association found for the Bayley Scaleassessment at seven months after controlling for confounding variables was between the Bayley


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MDI and PCB milk (one-tailed p < 0.048) (Winneke et al. 1998). This result is not consistentwith the Michigan and Dutch Bayley Scale assessment results at seven months of age, whichshowed no relation between prenatal PCB exposure and either the MDI or PDI (Jacobson et al.1996; Koopman-Esseboom et al. 1996). It is also at variance with the North Carolina BayleyScale assessment at six months of age, in which PDI, not MDI, had a negative association with

prenatal PCB exposure (Gladen et al. 1988).

At seven and 18 months, borderline negative associations were found between PCB milk and both the Bayley Scale MDI and PDI, but became significant at 30 months (one-tailed p = 0.035for the 30 month MDI and p =.05 for the MDI). When the seven to 30 month age range wastreated as a time-series, prenatal PCB exposure showed significant negative overall associationswith mental and motor development that increased with age (Walkowiak et al. 2001).

The seven month German Bayley Scale result is at variance with that of the Michigan study(Jacobson et al. 1986), which showed no association between prenatal PCB exposure and either the MDI or PDI. The 18 month and 30 month German Bayley Scale results cannot be compared

with the Michigan study because the cohort was not tested again with the Bayley Scaleinstrument until four years of age. These results are also inconsistent with the North CarolinaBayley Scale assessment at six months (Gladen et al. 1988), which showed no association

between prenatal PCB exposure and MDI, but did show a negative impact on PDI. The Dutchstudy Bayley Scale assessment at seven months showed no association with either MDI or PDI(Koopman-Esseboom et al. 1996).

At 42 months of age, a significant negative association between PCB milk and the MentalProcessing Composite Index of the K-ABC was found ( p = 0.028) (Walkowiak et al. 2001). Thisfinding is consistent with the Dutch K-ABC assessment at 42 months of age (Patandin et al.1999), which found a negative association between the K-ABC scores and PCB maternal .

However, the Michigan Bayley MDI results at four years of age showed no negative association between prenatal PCB exposure and mental developmental effects.

The HOME score analyses showed a positive impact on mental/motor development. The slopesof both variables over the range of observed HOME scores or PCB milk are similar, but themagnitude of the overall positive impact of the home environment on mental/motor developmentwas stronger than the negative effect of neonatal PCB exposure: The positive effect size of thehome environment on Bayley scale and K-ABC scores was approximately twice that of thenegative effect size of PCB milk on these measures. For example, an increase of 17.7 pointsassociated with increasing HOME score on the 30 month Bayley PDI contrasts with a 9.9 pointdecrease associated with increasing PCB milk . These effect size differences were less

pronounced, however, when the data were treated with the time-series approach (Walkowiak etal. 2001).

Schantz et al. (2003) note that the German study findings add to the overall weight of theevidence that prenatal PCB exposure can cause neurodevelopmental effects.

Criticisms The sharpest criticisms of the German studies found in the literature relate to theinvestigators failure to control for chance results when conducting multiple comparisons, and


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the investigators use of one-tailed significance tests for interpreting the significance of their results.

According to Cicchetti et al. (2004), one-tailed tests do not permit a valid interpretation of studyresults when they occur in a direction opposite to the one predicted. Their contention is that one-

tailed tests are appropriate for studying effects that biologically can vary in only one direction,such as survival rates associated with graded cancer stages. In addition, Cicchetti et al. (2004)note that one-tailed tests essentially double the odds of obtaining a statistically significantfinding, as a probability level of .10 in a two tailed test will be interpreted as one of .05.

For example, Winneke et al. (1998) reported a significant negative association between PCB milk and the Bayley Scale MDI. However, Cicchetti et al. (2004) note that, not only did theinvestigators run six analyses simultaneously without controlling for chance findings, they used aone-tailed significance test. The resulting one-tailed p value of .048 transforms to a p value of about .10 when a traditional two-tailed test is applied to the same dataa result that does notapproach significance. In the words of Cicchetti et al. (2004), to employ one-tailed tests,

accompanied by no control for multiple comparisons, solely in the service of maximizing theodds of finding statistical significance, is a scientifically indefensible methodological strategy.

In response to Cicchetti et al.s criticisms, Winneke and colleagues replied:

Domenic Cicchetti and Alan Kaufman suggest inappropriate testing of non-directionalhypotheses, with no adjustment for multiple testing or quality of the home environment.Our hypotheses were directional. We tested for adversity of prenatal and neonatal PCBexposure, because the assumption of a beneficial impact of PCBs on motor and mentaldevelopment is not biologically plausible. We also tested for a beneficial effect of thehome environment because, for psychological reasons, good parental caretaking supportsrather than impairs psychodevelopment. Thus, one-tailed testing is mandatory (Winnekeet al. 2002).

Additionally, as has been noted earlier, the truth of the small associations found in the PCBepidemiological studies lies in their replicability (Stewart et al. 2004), and should be evaluated inthe context of many studies using similar methodologies and outcome measures. When viewedfrom this perspective, the tone of Cicchetti et al.s criticisms sounds somewhat harsh andsnappish.

Schantz et al. (2003), however, believe that the German studies add to the overall weight of evidence that prenatal exposure to PCBs can cause adverse neurodevelopmental effects.However, they note that these studies are limited in that only three marker PCB congeners were

measured. Thus, the studies are unlikely to contribute to our understanding of the effects of individual PCB congeners or classes of congeners.

Oswego cohort The Oswego Newborn and Infant Development Project was the first large-scale replication and extension of the Lake Michigan study (Daly et al. 1996; Lonky et al. 1996).The Oswego cohort was intentionally designed to replicate and extend the Michigan cohort interms of cohort characteristics, exposure metric, and assessment protocols to measure the sameendpoints as the Michigan study, at similar ages. Additionally, the investigators sought to


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improve the quality and degree of covariate control relative to the Michigan study (Stewart et al.2004).

New York State had issued advisories recommending restrictions in Lake Ontario fishconsumption because of the large quantities of PCBs, organochlorine insecticides, and other

chemicals found in Lake Ontario sport fish during the early 1980s. These advisoriesrecommended that pregnant women completely eliminate Lake Ontario fish from their diets(Stewart et al. 1999). Despite the advisories, pregnant women continued to consume largeamounts of the fish; in a survey of over 650 pregnant women in the Oswego, New York area,Lonky et al. (1996) found that 8.2% of pregnant women in the area had consumed over 26

pounds in the previous six years, with 46% indicating they had eaten some fish from LakeOntario.

To corroborate and extend the Michigan study findings suggesting that prenatal PCB exposureexerted adverse effects on fetal neurodevelopment, a prospective longitudinal study was carriedout on mother-infant pairs recruited between June 1991 and June 1994 during the physicians

required 20 week sonogram visit at the countys only obstetrical practice (Lonky et al. 1996).The original cohort consisted of 602 pregnant women, most of whom were fish eaters, but thecohort included a randomly selected control subset of non-fish eaters. Attrition reduced thenumber to 559 (395 fish eaters and 164 non-fish eaters). A subset of 309 of the women and their children were followed longitudinally; the rest of the children were evaluated only at birth.

Most of the participants were Caucasian and, unlike previous cohorts, were of low to middlesocioeconomic status. The cohort

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