The impact of environmental toxicants on

children’s health is increasingly recognized as

significant (Faustman 2000; Greater Boston

Physicians for Social Responsibility 2000;

Landrigan et al. 1999; Perera et al. 2002).

Human and experimental studies indicate that

the fetus and infant are more sensitive than

adults to diverse environmental toxicants,

including lead, mercury, environmental

tobacco smoke (ETS), polycyclic aromatic

hydrocarbons (PAHs), and pesticides (National

Research Council 1993; Neri et al. 2006;

Perera et al. 2005b; Whyatt and Perera 1995;

World Health Organization 1986). Urban

minority populations represent high-risk

groups for adverse health and developmental

outcomes (Claudio et al. 1999; Federico and

Liu 2003; New York City Department of

Health 1998; Perera et al. 2002). Although

urban air pollution crosses geographic and

socioeconomic boundaries, these same populations are likely to be more heavily exposed to

indoor and outdoor air pollution and pesticides

(Breysse et al. 2005; Olden and Poje 1995;

Perera et al. 2002). As reported previously, the

present study cohort has had substantial

although variable exposure to multiple contaminants during pregnancy, with 100% of subjects having exposure to PAHs and pesticides in

the air during pregnancy and 40% reporting

ETS exposure (Perera et al. 2003; Rauh et al.

2004; Whyatt et al. 2002). PAH exposure in

this urban cohort of nonsmokers is largely due

to traffic sources and ETS (which was controlled for in analyses).

To our knowledge, there have been no

prior human studies of the effect of prenatal

exposure to airborne PAHs on child development. However, prenatal exposure to ETS has

been associated with reduced fetal growth and

cognitive functioning (Martinez et al. 1994;

Rauh et al. 2004; Schuster and Ludwig 1994;

Sexton et al. 1990; Windham et al. 1999;

Yolton et al. 2005). Associations have been

observed between prenatal exposure to the pesticide chlorpyrifos (CPF) and neurodevelopmental outcomes in experimental systems

(Aldridge et al. 2005). Lead and mercury are

known developmental toxicants affecting fetal

development (Agency for Toxic Substances and

Disease Registry 1999; Canfield et al. 2003;

Grandjean et al. 1997; Lanphear et al. 2000).

In addition to being genotoxic and carcinogenic, PAHs such as benzo[a]pyrene (BaP)

are endocrine disruptors (Bostrom et al. 2002;

Bui et al. 1986; Kazeto et al. 2004). Prior laboratory and human studies in Central Europe

and in our New York City cohort indicate that

transplacental exposure to PAHs is associated

with adverse birth outcomes (Barbieri et al.

1986; Bui et al. 1986; Dejmek et al. 2000;

Legraverend et al. 1984; Perera et al. 1998,

2005a). In the present analysis, we evaluated

the effects of prenatal exposure to airborne

PAHs, estimated by personal air sampling of

the mother during pregnancy, on mental and

psychomotor development of children

through 36 months of age, controlling for

physical, biologic, and psychosocial determinants of these outcomes.

Materials and Methods

Study subjects. The present cohort study is

being conducted by the Columbia Center for

Children’s Environmental Health (CCCEH)

(Perera et al. 2003). The study was approved

by the Institutional Review Board (IRB) of

Columbia University. Dominican and AfricanAmerican women (ethnicity classified by selfreport) residing in Washington Heights,

Central Harlem, and the South Bronx, New

York, who registered at the obstetrics/gynecology clinics at New York Presbyterian Medical

Center and Harlem Hospital by the 20th week

of pregnancy were approached in the clinics

for consent. At that time, the women agreeing

to participate in the prospective cohort study

signed the IRB-approved consent form.

Eligible women were nonsmokers during the

Environmental Health Perspectives • VOLUME 114 | NUMBER 8 | August 2006 1287

Research | Children’s Health

Address correspondence to F.P. Perera, Columbia

Center for Children’s Environmental Health,

Mailman School of Public Health, Columbia

University, 60 Haven Ave., B-109, New York, NY

10032 USA. Telephone: (212) 304-7280. Fax: (212)

544-1943. E-mail: fpp1@columbia.edu

We acknowledge H. Andrews, R. Garfinkel, Y.H.

Jin, L. Qu, J. Zhou, A. Reyes, and M. Borjas at the

Columbia Center for Children’s Environmental

Health, and L. Needham, T. Bernert, R. Jones, and

K. Caldwell at the Centers for Disease Control and

Prevention.

This study was supported by the National Institute

of Enviromental Health Sciences (5P01ES09600,

5RO1ES08977, RO1ES111158, RO1ES012468,

ES09089), the U.S. Environmental Protection Agency

(R827027, 8260901, RR00645), Educational

Foundation of America, Horace W. Goldsmith

Foundation, the Irving A. Hansen Memorial

Foundation, Gladys & Roland Harriman Foundation,

the New York Community Trust, the Bauman

Family Foundation, the Beldon Fund, and the

John Merck Fund.

The authors declare they have no competing

financial interests.

Received 10 February 2006; accepted 27 April 2006.

Effect of Prenatal Exposure to Airborne Polycyclic Aromatic Hydrocarbons on

Neurodevelopment in the First 3 Years of Life among Inner-City Children

Frederica P. Perera,1 Virginia Rauh,1 Robin M. Whyatt,1 Wei-Yann Tsai,1,2 Deliang Tang,1 Diurka Diaz,1

Lori Hoepner,1 Dana Barr,3 Yi-Hsuan Tu,1 David Camann,4 and Patrick Kinney1

1Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University, New York, New York,

USA; 2Department of Statistics, National Cheng Kung University, Taiwan, Republic of China; 3Centers for Disease Control and

Prevention, National Center for Environmental Health, Division of Laboratory Sciences, Atlanta, Georgia, USA; 4Department of Analytical

and Environmental Chemistry, Southwest Research Institute, San Antonio, Texas, USA

Our prospective cohort study of nonsmoking African-American and Dominican mothers and

children in New York City is evaluating the role of prenatal exposure to urban pollutants, including

polycyclic aromatic hydrocarbons (PAHs), environmental tobacco smoke (ETS), and pesticides, in

the pathogenesis of neurobehavioral disorders. We used the Bayley Scales of Infant Development to

evaluate the effects on child mental and psychomotor development of prenatal exposure to airborne

PAHs monitored during pregnancy by personal air sampling. Behavioral development was assessed

by the Child Behavior Checklist. We adjusted for potential confounders including sociodemographic factors and prenatal exposure to ETS and chlorpyrifos. Prenatal exposure to PAHs was not

associated with psychomotor development index or behavioral problems. However, high prenatal

exposure to PAHs (upper quartile) was associated with lower mental development index at age 3

[β = –5.69; 95% confidence interval (CI), –9.05 to –2.33; p < 0.01]. The odds of cognitive developmental delay were also significantly greater for children with high prenatal exposure (odds ratio =

2.89; 95% CI, 1.33 to 6.25; p = 0.01). General estimated equation analysis showed a significant age

× PAH effect on mental development (p = 0.01), confirming the age-specific regression findings.

Further adjustment for lead did not alter the relationships. There were no differences in effect sizes

by ethnicity. The results require confirmation but suggest that environmental PAHs at levels

recently encountered in New York City air may adversely affect children’s cognitive development at

3 years of age, with implications for school performance. Key words: air pollution, neurodevelopment, polycyclic aromatic hydrocarbons, prenatal. Environ Health Perspect 114:1287–1292 (2006).

doi:10.1289/ehp.9084 available via http://dx.doi.org/ [Online 24 April 2006]
current pregnancy; were free of diabetes, hypertension, and known HIV; had no documented

or reported drug abuse; and had resided in

the area for at least 1 year. At the time of this

report, of 648 consenting and eligible mother–

infant pairs, 536 were still participating in the

cohort study; 271 children had reached 3 years

of age. The retention rate for the full cohort was

83% at the 3-year follow-up. There were no

significant differences between women retained

in the study versus those who were lost to

follow-up, on maternal age, ethnicity, marital

status, education, income, gestational age, or

birth weight of the newborn.

In this report we focus on the 183 children

3 years of age who had valid prenatal PAH

monitoring data, all three annual developmental assessments, prenatal questionnaire data on

ETS, measurements of cotinine in maternal

and cord blood samples ≤ 25 ng/mL (to

exclude the possibility that the mother was an

active smoker), and CPF level in cord blood.

This group did not differ in any of the maternal or infant characteristics or prenatal exposures in Table 1 from the 80 children 3 years

of age excluded from the analysis because of

missing data. Of these, 64 children were

excluded because of missing developmental

testing data.

Personal interview. A 45-min questionnaire

was administered by a trained bilingual interviewer during the last trimester of pregnancy

(Perera et al. 2003). The questionnaire elicited

demographic information, residential, health,

and environmental history, including active and

passive smoking [household members who

smoke and estimated cigarettes smoked per day

by smoker(s)], and socioeconomic information

related to income and education. Postnatal

interviews were administered at 6 months,

annually, and every 3–6 months in between to

determine any changes in residence, exposure

to ETS, and other health or environmental

conditions.

Prenatal personal PAH assessment.

During the third trimester of pregnancy, personal monitoring was carried out as previously

described (Perera et al. 2003). Vapors and particles ≤ 2.5 μg in diameter were collected on a

precleaned quartz microfiber filter and a precleaned polyurethane foam cartridge backup.

The samples were analyzed at Southwest

Research Institute (San Antonio, TX) for

benz[a]anthracene, chrysene, benzo[b]fluroanthene, benzo[k]fluroanthene, BaP, indeno-

[1,2,3-cd]pyrene, disbenz[a,h]anthracene, and

benzo[g,h,i]perylene as described by Tonne

et al. (2004). For quality control, each personal monitoring result was assessed as to

accuracy in flow rate, time, and completeness

of documentation. All of the 183 subjects had

samples of acceptable quality.

Biologic sample collection and analysis. A

sample of umbilical cord blood (30–60 mL)

was collected at delivery by syringing blood

into a heparinized syringe to avoid clotting. A

sample of maternal blood (30–35 mL) was

collected within 2 days postpartum into

heparinized Vacutainer tubes (BD Medical,

Franklin Lakes, NJ) by hospital staff. Samples

were processed at the CCCEH laboratory, and

portions were sent to the Environmental

Health Laboratory at the Centers for Disease

Control and Prevention (CDC; Atlanta, GA)

for analysis of cotinine, heavy metals, and pesticides. Plasma cotinine was analyzed using

high-performance liquid chromatography

atmospheric-pressure ionization tandem mass

spectrometry as described by Bernert et al.

(1997, 2000). Plasma levels of CPF were analyzed using isotope-dilution gas chromatography–high-resolution mass spectrometry as

described by Barr et al. (2002). In a subset

(n = 135) of subjects, lead was analyzed by

inductively coupled plasma mass spectrometry

(CDC 2003).

Information on pregnancy outcomes.

Information was abstracted by the research

workers from mothers’ and infants’ medical

records after delivery, including gestational age

at birth, infant sex, birth weight, length, head

circumference, infant malformations, and pregnancy complications. Gestational age was based

on medical records for almost all subjects.

Where those data were missing, gestational age

was calculated from the last menstrual period.

Measures of child behavior and neurodevelopment. We used the Bayley Scales of

Infant Development–Revised (BSID-II) to

assess cognitive and psychomotor development

at 12, 24, and 36 months of age (Bayley 1993).

The BSID-II is the most widely used normreferenced developmental test for young children, can be used to diagnose developmental

delay, and is known to be sensitive to the developmental effects of toxic exposures such as lowlevel intrauterine lead. The stability of cognitive

assessments during the first few years of life is

limited, but the predictive power increases after

2 years. When administered at 3 years of age,

the BSID-II has moderate predictive power for

subsequent intelligence and school performance

and is clinically useful for the identification of

children performing in the subnormal range

(Bayley 1993; Burchinal et al. 2000; Sternberg

et al. 2001). Each test yields a developmental

quotient (raw score/chronologic age), which

generates a mental development index (MDI)

and a corresponding psychomotor development index (PDI). In addition, children are

classified as normal (> 85), moderately delayed

(> 70 and ≤ 85), or severely delayed (≤ 70)

based on standardized cut-points. Each child

was tested under controlled conditions at the

CCCEH by a bilingual research assistant,

trained and checked for reliability. In the present study, the interrater reliability for the

24-month MDI was r = 0.92, based on double

scoring of a random 5% of the sample (Rauh

et al. 2004). One hundred eighty-one children

had complete MDI at 1, 2, and 3 years of age;

181 had complete data on PDI, and 183 had

either complete MDI or PDI.

Behavior problems were measured by

maternal report on the 99-item Child Behavior

Checklist (CBCL) for children 1.5–5 years of

age, which collects information on child

behaviors occurring in the past 2 months

(Achenbach and Rescorla 2000). The CBCL is

well validated, easy to administer, and useful as

a screen for behavior problems. The Total

Problems (T) score is the sum of the scores on

Perera et al.

1288 VOLUME 114 | NUMBER 8 | August 2006 • Environmental Health Perspectives

Table 1. Characteristics of the study population by PAH exposure level (n = 183).a

Prenatal PAH exposure level

Characteristic High exposureb (n = 42) Low exposureb (n = 141)

Maternal characteristics

Ethnicity (%)

African American 40.5 47.5

Latino 59.5 52.5

Age (years) 25.03 ± 4.79 24.80 ± 5.53

Married (%) 11.9 15.1

No high school degree (%) 47.6 31.9

Maternal intelligence quotient 84.37 ± 10.27 86.27 ± 13.45

Caretaking home environment 37.55 ± 5.58* 39.82 ± 5.82*

Infant characteristics

Birth weight (g) 3,357.44 ± 529.69 3,413.16 ± 462.47

Birth length (cm) 50.73 ± 2.72 50.79 ± 3.85

Birth head circumference (cm) 34.01 ± 1.69 34.34 ± 1.95

Gestational age (week) 39.17 ± 1.25 39.40 ± 1.38

Percent male 47.6 45.4

Prenatal exposure

ETS [at least one smoker in house (%)] 38.1 39.7

CPF (pg/g) 5.94 ± 11.44 3.56 ± 4.45

Cord lead (μg/dL)c 1.01 ± 0.69 1.08 ± 0.79

Values are mean ± SD or percent.

aIncludes subjects with MDI and/or PDI (n = 183). bHigh exposure was defined as the fourth quartile of PAH; low exposure

was defined as all others (quartiles 1, 2, 3). There was no difference between the two exposure groups with respect to

any of the characteristics, except for the home environment. cCord lead was available in a subset of 135. *p < 0.05, by

Wilcoxon rank-sum test. 
the specific problem items plus the highest

score on any additional problems entered by

the respondent for the open-ended item 100,

and is computed by summing the scores for

the problems. T scores > 63 (> 90th percentile)

represent the clinical range, and T scores

between 60 and 63 (83rd to 90th percentile)

represent the borderline range. The CBCL also

yields scales derived from the Diagnostic and

Statistical Manual of Mental Disorders (2000)

that are intended to approximate clinical diagnoses, including affective, anxiety, pervasive

developmental, attention deficit/hyperactivity,

and oppositional defiant problems. All subscales are scored continuously and also categorically using a borderline or clinical

cut-point corresponding to the 98th percentile

for each domain. One hundred sixty-eight

children of the children with Bayley scores

also had CBCL data.

Maternal nonverbal intelligence was measured by the Test of Non-Verbal Intelligence,

second edition (Brown et al. 1990), a 15-min,

language-free measure of general intelligence,

relatively stable and free of cultural bias. The

test was administered when the child was 3

years of age. The quality of the proximal caretaking environment was measured by the

Home Observation for Measurement of the

Environment (Caldwell and Bradley 1979),

administered at 3 years of age. The instrument assesses physical and interactive home

characteristics (Bradley et al. 1989), is predictive of developmental scores in early childhood, and has been widely used in studies of

neurotoxicity (e.g., Bellinger et al. 1988).

Statistical analysis. As in prior analysis

(Perera et al. 2003), a composite PAH variable was computed from the eight intercorrelated PAH air concentration measures

(r values ranging from 0.34 to 0.94; all p-values < 0.001 by Spearman’s rank). This variable was dichotomized at the fourth quartile

(4.16 ng/m3) to obtain a measure of high/low

exposure that is more robust than the continuous variable. The CPF variable was also

dichotomized at the fourth quartile as previously described (Whyatt et al. 2004). The

concentration of lead in cord blood was

treated as a continuous variable.

We estimated the associations between prenatal PAH exposure (high/low) and developmental scores (cognitive and psychomotor) for

12, 24, and 36 months of age using multiple

linear regression for continuous outcomes

(MDI and PDI) and logistic regression for categorical outcomes (likelihood of being classified

as developmentally delayed). We estimated

associations between prenatal PAH exposure

(high/low) and behavior problems in the clinical range at 36 months of age using logistic

regression. We used general estimated equation

(GEE) (Liang and Zeger 1986) to estimate the

size of the PAH effect over time (through

36 months) and at specific time points. To

evaluate trends over time, the model compares

the two exposure groups in terms of the difference in MDI scores obtained at 1 year of age

(baseline) versus 2 years and 1 year versus

3 years, respectively. GEE has the advantage of

requiring fewer assumptions than other methods; thus, the results of GEE are more robust.

All effect estimates, 95% confidence intervals

(CIs), and p-values (α = 0.05) were generated

using SPSS (version 11.5; SPSS Inc., Chicago,

IL) and SAS (version 9.0; SAS Institute Inc.,

Cary, NC). Covariates were retained in the

models as potential confounders if they exhibited a relationship (p ≤ 0.1) with motor or mental development, regardless of their association

with PAH exposure. The final models included

an indicator for PAH exposure, the child’s exact

age at test administration, child’s sex, ethnicity,

gestational age at birth, quality of the home

(caretaking) environment, and prenatal exposure to ETS and CPF measured as described

above. In addition, the possible confounding

of prenatal exposure by lead was tested in the

subset of 135 children with available data.

Interactions of PAH exposure with other independent variables were tested as appropriate.

We assessed potential mediation of the

association between PAH exposure and development over time by including those fetal

growth parameters previously shown to be

affected by prenatal PAH exposure (birth

weight and head circumference) in the models. If the estimate of the PAH effect on

neurodevelopment was attenuated in the presence of a fetal growth parameter, mediation

was considered to be present.

Results

Table 1 describes the characteristics of the

sample stratified by level of PAH exposure.

There were no significant differences between

high- and low-exposure groups except for the

home environment, which was less favorable

in the high-exposure group. Prenatal PAH

exposures averaged 3.49 ng/m3, with a range

of 0.65–36.47 ng/m3; 39.3% of children had

prenatal ETS exposure. Table 2 shows the

mean ± SD or proportion for the developmental outcomes. These include the indices

of performance on the BSID-II, including

MDI, PDI, proportion moderately delayed

on the mental index, and proportion moderately delayed on the motor index for each of

the exposure groups at 12, 24, and 36 months

of age. Table 2 also shows the mean ± SD for

the CBCL score for total behavior problems.

In univariate analysis of children with all

three developmental measures, prenatal exposure to PAHs was significantly associated with

MDI at age 3 (β = –4.68; 95% CI, –8.13 to

–1.24; p = 0.01; n = 263) but not MDI at 1 or

2 years of age nor with PDI. Table 3 shows the

age-specific parameter estimates for prenatal

Effects of prenatal exposure to air pollution on child development

Environmental Health Perspectives • VOLUME 114 | NUMBER 8 | August 2006 1289

Table 2. Mean ± SD and proportion for developmental and behavioral outcomes at 12, 24, and 36 months.

Age at assessment

Domain 12 months 24 months 36 months

MDIa 94.25 ± 9.45 85.01 ± 12.59 89.66 ± 11.21

PDIb 95.85 ± 12.17 97.40 ± 11.59 100.80 ± 13.21

Total behavior problemsc NA NA 50.20 ± 10.47

Moderate mental development delay (%)a,d 14.9 48.1 33.1

Severe mental development delay (%)a,e 0.6 9.4 2.8

Moderate psychomotor development delay (%)b,f 14.4 13.3 10.5

Severe psychomotor development delay (%)b,g 1.7 1.7 1.7

NA, not applicable.

an = 181 with all 3 years of MDI data. bn = 181 with all 3 years of PDI data. cn = 168 with all 3 years of MDI and/or PDI and

behavioral data (T score). dMDI < 85. eMDI < 70. f

PDI < 85. gPDI < 70.

Table 3. Multiple linear regression models testing effects of prenatal PAH exposure at 12, 24, and 36

months using MDI and PDIa (n = 181).

Model 1: 12 months Model 2: 24 months Model 3: 36 months

β p-Value β p-Value β p-Value

MDI

Constant 74.52 < 0.01 37.73 0.16 52.79 0.02

PAHs 0.48 0.78 –1.73 0.41 –5.69 < 0.01

Ethnicity (1 = African American; 0 = others) 0.24 0.88 6.66 < 0.01 6.34 < 0.01

Sex (1 = male) –2.09 0.14 –4.51 0.01 –2.20 0.13

Gestational age 0.38 0.49 0.95 0.16 0.41 0.44

Home environment 0.13 0.30 0.28 0.08 0.54 < 0.01

PDI

Constant 95.34 < 0.01 109.77 < 0.01 54.00 0.06

PAHs 1.32 0.55 –2.08 0.32 –0.97 0.68

Ethnicity (1 = African American; 0 = others) –2.79 0.16 1.87 0.32 4.45 0.03

Sex (1 = male) 1.12 0.54 0.52 0.76 –1.24 0.52

Gestational age 0.15 0.82 –0.52 0.43 0.95 0.19

Home environment –0.10 0.56 0.16 0.30 0.25 0.15

aModels were also adjusted for prenatal ETS and CPF. Further inclusion of maternal IQ and maternal education as covariates did not alter the results.
PAH exposure effects on mental and motor

development, by multiple regression adjusting

for the covariates as described in statistical

analysis (n = 181). There was a significant effect

of prenatal PAH exposure on MDI at age 3

(β = –5.69; 95% CI, –9.05 to –2.33; p < 0.01)

but not 1 or 2 years of age. PDI was not associated with PAH exposure at any age. Altogether,

the exposures and covariates accounted for

approximately 31.2% of the variance in MDI

scores at 36 months. None of the interaction

terms of PAHs and the sociodemographic or

exposure variables was significant. There was

no significant interaction between PAH exposure level and home environment, suggesting

that the magnitude of the 36-month prenatal

PAH effect is not affected by the quality of the

caretaking environment.

In univariate logistic regression analysis,

the likelihood of a child experiencing moderate mental developmental delay at 3 years of

age was significantly increased as a function of

prenatal PAH exposure (odds ratio = 2.05;

95% CI, 1.15–3.63; p = 0.01), but again, the

relationship was not seen at 1 or 2 years of age

nor with psychomotor developmental delay.

Table 4 shows the results of the logistic

regression analysis adjusting for the relevant

covariates as described in statistical analyses.

The odds ratio for delayed mental development at 36 months of age was 2.89 (95% CI,

1.33–6.25; n = 181). PAH exposure was not a

significant predictor of psychomotor development. There were no significant interactions

between PAHs and the other covariates in

logistic regression.

Table 5 and Figure 1 show the results of

the GEE analysis of PAH effects on cognitive

development over the 3-year follow-up period.

The significant age × PAH effect on mental

development (p = 0.01) confirms the age-specific regression findings showing that an

adverse impact of prenatal PAH exposure on

this developmental domain was seen only over

time. For motor development, there was no

significant relationship (Table 5). At 3 years of

age, the decrease in MDI from baseline was

significantly greater for high-exposed compared to low-exposed children (p = 0.01),

whereas the difference was not significant at

2 years of age. The results of analyses using the

continuous measure of PAHs were generally

similar but less significant. Inclusion of fetal

growth parameters (birth weight or head circumference) did not alter the effect of PAHs

on 36 month MDI. Inclusion of cord lead as a

covariate did not materially alter the association between PAHs and development. The

results of regression of total CBCL behavior

problems on prenatal PAH exposure were not

significant, nor were any of the subscales

significantly related to PAH exposure.

Discussion

Previous results from this cohort have

indicated that exposure to PAH air pollutants

during pregnancy has produced DNA damage

and impaired fetal growth (Perera et al. 2003,

2005a, 2005b). The present analysis suggests a

further impact of prenatal PAH exposure on

cognitive development. The infants who had

been exposed prenatally to the highest PAH

levels scored significantly lower on MDI at

3 years of age than did those with lower levels

of PAH exposure. Although the adjusted

mean MDI scores of the high- and lowexposed PAH groups differed by only 5.69

points, among the highly exposed children the

odds of having MDI scores < 85 at 3 years of

age (indicating moderate delay) were 2.89

times greater than the odds among unexposed

children. This suggests that more exposed

children are potentially at risk for performance

deficits (language, reading, and math) in the

early school years. In fact, developmentally

delayed children are eligible for early intervention services designed for children who are at

possible risk for early school failure. The

observed magnitude of the PAH effect on

early development in this study is comparable

to that reported for low-level lead exposure

(Schwartz 1994). In this study, there was no

effect of PAHs on cognitive development at

1 and 2 years of age, nor were psychomotor

development and behavioral problems associated with PAHs. The impact of PAHs on

mental development at 3 years of age does not

appear to be mediated by birth weight or head

circumference, fetal growth parameters previously shown to be associated with prenatal

PAH exposure in this cohort (Perera et al.

2003). The children are being followed to

7–8 years of age, so subsequent testing will

Perera et al.

1290 VOLUME 114 | NUMBER 8 | August 2006 • Environmental Health Perspectives

Table 5. Cognitive mental development in children 12 months through 36 months of age by GEE (n = 543

measurements).a

MDI PDI

β p-Value β p-Value

Intercept 60.46 < 0.01 84.76 < 0.01

24 months –9.87 < 0.01 –2.12 0.20

36 months –4.29 0.01 3.53 0.08

PAHs 0.69 0.66 1.89 0.35

24 months × PAHs –1.12 0.62 –3.14 0.16

36 months × PAHs –5.57 0.01 –4.65 0.08

Ethnicity (1 = African American; 0 = others) –0.23 0.88 –3.38 0.07

24 months × ethnicity 6.80 < 0.01 5.71 0.01

36 months × ethnicity 7.14 < 0.01 7.91 < 0.01

Sex (1 = male) –2.80 0.01 0.08 0.95

Gestational age 0.56 0.16 0.23 0.62

Home environment 0.31 < 0.01 0.11 0.39

aModels were also adjusted for prenatal ETS and CPF.

Table 4. Logistic regression models testing effects of prenatal PAH exposure on the odds of mental and

psychomotor development delay at 12, 24, and 36 monthsa (n = 181).

Model 1: 12 months Model 2: 24 months Model 3: 36 months

β p-Value Exp(β) β p-Value Exp(β) β p-Value Exp(β)

Dependent variable: moderate delay (MDI < 85)

Constant 2.65 0.67 14.12 3.04 0.53 20.92 6.68 0.24 798.33 

PAHs –0.19 0.71 0.82 –0.16 0.68 0.86 1.06 0.01 2.89

Ethnicity (1 = African American; 0 = others) 0.32 0.50 1.37 –0.90 0.01 0.41 –0.77 0.06 0.46

Sex (1 = male) 0.66 0.12 1.94 0.84 0.01 2.31 0.50 0.16 1.65

Gestational age –0.07 0.67 0.93 –0.02 0.89 0.98 –0.10 0.47 0.90

Home environment –0.05 0.19 0.95 –0.06 0.03 0.94 –0.10 < 0.01 0.90

Dependent variable: moderate delay (PDI < 85)

Constant –1.50 0.82 0.22 –1.11 0.87 0.33 –2.30 0.79 0.10

PAHs –0.92 0.16 0.40 0.41 0.41 1.51 –0.22 0.72 0.80

Ethnicity (1 = African American; 0 = others) 0.39 0.41 1.48 –0.21 0.67 0.81 –0.65 0.28 0.52

Sex (1 = male) –0.18 0.68 0.83 –0.42 0.35 0.66 0.01 0.98 1.01

Gestational age –0.01 0.97 0.99 –0.02 0.89 0.98 0.04 0.85 1.04

Home environment –0.01 0.88 0.99 0.01 0.86 1.01 –0.05 0.25 0.95

aModels were also adjusted for prenatal ETS and CPF. Further inclusion of maternal IQ and maternal education as covariates did not alter the results.

Figure 1. Estimated effects of prenatal PAH exposure on cognitive development in children 12 months

through 36 months of age by GEE. The model was

adjusted for the child’s exact age at test administration, child’s sex, ethnicity, gestational age at birth,

quality of the (caretaking) home environment, and

prenatal exposure to ETS and CPF.

98

96

94

92

90

88

86

84

High PAH

Low PAH

12 24 36

Age (months)

BSID-II MDI scores
Effects of prenatal exposure to air pollution on child development

Environmental Health Perspectives • VOLUME 114 | NUMBER 8 | August 2006 1291

provide a picture of the developmental trajectory of this group.

To our knowledge, there have been no

prior studies of the role of prenatal exposure to

airborne PAHs in child neurodevelopment.

However, a study in the Czech Republic

reported that schoolchildren in the district of

Teplice, which had higher levels of PAHs and

other air pollutants from coal burning than

did the district of Prachatrice, had a significantly higher teacher referral rate for clinical

assessment compared to Prachatrice, although

most objective performance measures did not

differ (Sˇrám et al. 1996).

The mechanisms by which PAHs might

affect the developing brain are not known.

However, fetal toxicity may be caused by

antiestrogenic effects (Bui et al. 1986) binding to the human aryl hydrocarbon receptor

to induce P450 enzymes (Manchester et al.

1987), DNA damage resulting in activation

of apoptotic pathways (Meyn 1995; Nicol

et al. 1995; Wood and Youle 1995), or binding to receptors for placental growth factors

resulting in decreased exchange of oxygen and

nutrients (Dejmek et al. 2000).

In the present cohort, the mean developmental scores are below average for the normed

population, reflecting the low-income nature

of the catchment area in this study (e.g.,

Bradley and Corwyn 2002; Burchinal et al.

1997; Luster and McAdoo 1996). In addition,

children from homes with low levels of stimulation and mother–child interaction had significantly lower scores on the Bayley cognitive

scales, independent of PAH exposure.

This study has the advantage of being

based on individual prenatal exposure data

from personal monitoring and biomarker

analyses, as well as extensive medical record

and questionnaire data. However, it is limited

by the modest sample of subjects for whom

data from all relevant domains are currently

available. Moreover, relationships observed in

low-income minority women might be different in women of other races or ethnic, cultural,

or socioeconomic backgrounds. Further, it is

possible that high levels of PAHs may be associated with living near an exposure source such

as a bus route or garage leading to some

uncontrolled confounding by socioeconomic

status even within our low-income population.

Another limitation is that we lacked air

monitoring data for all three trimesters and

were therefore not able to compare exposures

across these three periods. We also lacked postnatal personal air monitoring data for PAHs

and were unable to control directly for postnatal PAH exposure. However, when we controlled for change in residence as a proxy for

variation in PAH exposure between the preand postnatal periods, the effects of prenatal

PAHs remained. We also lacked postnatal

environmental lead exposure data, which may

have been a critical period of exposure to this

known developmental toxicant. Additional

studies are needed to tease apart the effects of

prenatal and postnatal exposure to PAHs and

to confirm the present findings.

Conclusion

This study provides evidence that environmental PAHs at levels recently encountered in

the air of New York City may adversely affect

cognitive development of children. The results

require confirmation but are of potential concern because compromised mental performance in the preschool years is an important

precursor of subsequent educational performance deficits. PAHs are widespread in urban

environments worldwide largely as a result of

fossil fuel combustion. Fortunately, airborne

PAH concentrations can be reduced through

currently available pollution controls, greater

energy efficiency, and the use of alternative

energy sources (Wong et al. 2004).

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