Environmental Health Perspectives • volume 119 | number 6 | June 2011 873

Research | Children’s Health

Autism is a developmental disorder characterized by significant deficits in social interaction and communication, accompanied by 

repetitive behaviors (American Psychiatric 

Association 2000). Data from family and twin 

studies have long supported the role of genetics 

in autism etiology (Abrahams and Geschwind 

2008; Muhle et al. 2004). Results from linkage, 

copy number variation, and genomewide association studies further support the importance 

of genetic risk in this disease (Abrahams and 

Geschwind 2008; Ma et al. 2009; Wang et al. 

2009). Over the last 10 years, the prevalence of 

diagnoses of autism, and all autism spectrum 

disorders, has increased (Centers for Disease 

Control and Prevention 2007a, 2007b, 2009). 

Although changes in diagnostic criteria and 

improved ascertainment have been thought 

to contribute to this increase, recent reports 

suggest that these factors may not fully explain 

the rising incidence of autism spectrum disorders (Hertz-Picciotto and Delwiche 2009; King 

and Bearman 2009). Therefore, it is likely that 

environmental factors may augment the strong 

genetic risks implicated in autism etiology.

Air pollution exposure during pregnancy 

has been reported to have physical and developmental effects on the fetus. High levels of air 

pollution, including carbon monoxide, nitrogen dioxide, and ambient particulate matter 

(PM), have been associated with very low and 

low birth weight, preterm birth, and infant 

mortality (Currie et al. 2009; Ritz and Yu 

1999). Specific pollutants, including ozone, 

sulfur dioxide, PM, and carbon monoxide, 

have also been associated with significant differences in biparietal diameter and head circumference measured both during pregnancy 

and at birth (Hansen et al. 2008; Vassilev 

et al. 2001). Maternal exposure to polycyclic aromatic hydrocarbons (PAHs) during 

pregnancy has been associated with impaired 

cortical function and cognitive developmental 

delay (Bocskay et al. 2005; Perera et al. 2003, 

2004, 2006, 2007).

Exposure to air pollution and its components, not only in the prenatal period but also 

in early postnatal life, has been linked to poor 

developmental outcomes as well. A recent epidemiologic study reported that use of gas appliances and increased nitrogen dioxide in the 

home during the first 3 months of life are associated with decreased cognitive test scores and 

increased inattention at 4 years of age (Morales 

et al. 2009). In a separate study, Suglia et al. 

(2008) estimated lifetime residential exposure 

to black carbon, a proxy for traffic-related PM, 

among 8- to 11-year-old children and reported 

decreased performance on intelligence and 

memory tasks with increasing black carbon 

levels. Additionally, autism has been associated with estimated regional concentrations of 

hazardous air pollutants, including arsenic and 

nickel, and with diesel PM exposure in early 

childhood (Windham et al. 2006).

Thus, an emerging literature suggests that 

near roadways, traffic-related air pollutants, 

possibly influenced by specific components 

such as PM or PAHs, affect neurodevelopment. However, the role of timing for this 

exposure during pregnancy or early life is not 

clear, nor has the relationship between trafficrelated air pollutants and autism been tested. 

In this study, we examined the relationship 

between autism and traffic proximity (a 

marker of traffic-related air pollution) during 

the prenatal period and at the time of birth.

Materials and Methods

We used data from 304 autism cases and 259 

typically developing general-population controls from the Childhood Autism Risks from 

Genetics and the Environment (CHARGE) 

study, a population-based case–control study 

of preschool children. The study design is 

described in detail elsewhere (Hertz-Picciotto 

et al. 2006). Briefly, CHARGE subjects 

were between 24 and 60 months of age at 

the time of recruitment, which occurred 

during 2003–2009; lived with at least one 

English- or Spanish-speaking biological parent; were born in California; and resided in 

one of the study catchment areas at the time 

of enrollment. Recruitment was facilitated by 

the California Department of Developmental 

Services (DDS) and the regional centers with 

which they contract to coordinate services for 

Address correspondence to H.E. Volk, Keck School 

of Medicine, University of Southern California, 

1540 Alcazar St. CHP 209G, Los Angeles, CA 

90033 USA. Telephone: (323) 442-5101. Fax: (323) 

442-3272. E-mail: hvolk@usc.edu

This work was supported by National Institute of 

Environmental Health Sciences grants ES019002, 

ES009581, ES013578, ES007048, ES11269, 

ES015359, and RD831861; U.S. Environmental 

Protection Agency Science to Achieve Results 

(STAR) grants R-823392 and R-833292; the MIND 

Institute matching funds and pilot grant program; 

and Autism Speaks.

F.L. is employed by Sonoma Technology Inc., 

which provided expert services in exposure assessment 

for this work. The other authors declare they have no 

actual or potential competing financial interests.

The authors declare they have no actual or potential 

competing financial interests.

Received 6 August 2010; accepted 13 December 

2010.

Residential Proximity to Freeways and Autism in the CHARGE Study

Heather E. Volk,1 Irva Hertz-Picciotto,2 Lora Delwiche,2 Fred Lurmann,3 and Rob McConnell 4

1Departments of Preventive Medicine and Pediatrics, Zilkha Neurogenetic Institute, Keck School of Medicine, Children’s Hospital 

Los Angeles, University of Southern California, Los Angeles, California, USA; 2Department of Public Health Sciences, University of 

California–Davis, Davis, California, USA; 3Sonoma Technology Inc., Petaluma, California, USA; 4Department of Preventive Medicine, 

Keck School of Medicine, University of Southern California, Los Angeles, California, USA

Background: Little is known about environmental causes and contributing factors for autism. 

Basic science and epidemiologic research suggest that oxidative stress and inflammation may play 

a role in disease development. Traffic-related air pollution, a common exposure with established 

effects on these pathways, contains substances found to have adverse prenatal effects.

Objectives: We examined the association between autism and proximity of residence to freeways 

and major roadways during pregnancy and near the time of delivery, as a surrogate for air pollution 

exposure.

Methods: Data were from 304 autism cases and 259 typically developing controls enrolled in the 

Childhood Autism Risks from Genetics and the Environment (CHARGE) study. The mother’s 

address recorded on the birth certificate and trimester-specific addresses derived from a residential 

history obtained by questionnaire were geocoded, and measures of distance to freeways and major 

roads were calculated using ArcGIS software. Logistic regression models compared residential proximity to freeways and major roads for autism cases and typically developing controls.

Results: Adjusting for sociodemographic factors and maternal smoking, maternal residence at the 

time of delivery was more likely be near a freeway (≤ 309 m) for cases than for controls [odds ratio 

(OR) = 1.86; 95% confidence interval (CI), 1.04–3.45]. Autism was also associated with residential 

proximity to a freeway during the third trimester (OR = 2.22; CI, 1.16–4.42). After adjustment for 

socioeconomic and sociodemographic characteristics, these associations were unchanged. Living 

near other major roads at birth was not associated with autism.

Conclusions: Living near a freeway was associated with autism. Examination of associations with 

measured air pollutants is needed.

Key words: autism, epidemiology, gene–environment interaction, roadway proximity, traffic 

emissions. Environ Health Perspect 119:873–877 (2011). doi:10.1289/ehp.1002835 [Online 

16 December 2010]
Volk et al.

874 volume 119 | number 6 | June 2011 • Environmental Health Perspectives

persons with autism and other developmental 

disabilities. Population-based controls were 

recruited from the sampling frame of birth 

files from the State of California and were 

frequency matched by sex, age, and broad geographic area to the autism cases. All births 

were between 1997 and 2006.

Each participating family was evaluated 

in person. Children with a DDS diagnosis 

of autism were evaluated using the Autism 

Diagnostic Observation Schedules (ADOS),

and parents were administered the Autism 

Diagnostic Interview–Revised (ADI-R) 

(Le Couteur et al. 2003; Lord et al. 2003). 

Children with a diagnosed developmental delay 

and general population controls were given the 

Social Communication Questionnaire (SCQ) 

to screen for the presence of autistic features 

(Rutter et al. 2003). If the SCQ score was 

≥ 15, the ADOS was then administered to 

the child and the ADI-R to the parent. In our 

study, autism cases were children with a diagnosis of autism from both the ADOS and the 

ADI-R. All children were also assessed using 

the Mullen Scales of Early Learning and the 

Vineland Adaptive Behavior Scales to collect 

information on motor skills, language, socialization, and daily living skills (Mullen 1995; 

Sparrow et al. 1984). Controls were children 

sampled from the general population with typical development, defined as having received a 

score ≤ 15 on the SCQ and who scored in the 

normal range on the Mullen Scales of Early 

Learning and Vineland Adaptive Behavior 

Scales, thereby showing no evidence of other 

types of delay (cognitive or adaptive).

Parents were also interviewed extensively 

to evaluate household exposures and demographic and medical information and to assess 

reproductive, occupational, and residential 

histories. The residential history captured 

addresses and corresponding dates the mother 

and child lived at each location beginning 

3 months before conception and extending 

to the most recent place of residence. Further 

details about the collection of clinical and 

exposure data have been previously reported 

(Hertz-Picciotto et al. 2006).

We examined associations of autism with 

traffic-related pollutant exposure using two 

broad proxies: distance to the nearest freeway and distance to the nearest major road. In 

accord with our previous research, a freeway 

was defined as a state highway or interstate 

highway (Gauderman et al. 2007). A major 

road was defined as a state highway, interstate 

highway, or major arterial (McConnell et al. 

2006). Mother’s residential address at birth, as 

recorded on the birth certificate, was geocoded, 

and distances to the nearest interstate highway, state highway, and major arterial road 

were estimated based on the shortest distance 

from the residence to the middle of the nearest side of each of the three road types using 

ArcGIS software (version 9.2; Environmental 

Systems Research Institute Inc., Redlands, 

CA). For each subject, freeway distance was 

then assigned as the shorter of the distances 

from the birth residence to a state or interstate 

highway. Similarly, major road distance was 

assigned as the shortest of the three distances: 

from a state highway, interstate highway, or 

major arterial. Under these definitions, it was 

possible for freeway and major road distances 

to be the same should the same road type (e.g.,

state highway) provide the shortest distance 

measure for a given address. For freeway and 

major road distances, we examined the distribution of values among the 563 subjects in 

our study and determined exposure cut points 

based on the top 10%, next 15%, and subsequent 25% of distance values for freeways and 

for major roads. The remaining 50% served as 

a reference category in each analysis.

Information from the residential history 

was used to estimate exposure to residential 

traffic during the first, second, and third trimesters of gestation for a subset of subjects 

with complete data (n = 485; 257 cases and 

228 controls). We determined the conception 

date for each child using gestational age from 

ultrasound measurements or the date of last 

menstrual period, as determined from prenatal 

records. Then we calculated dates corresponding to each trimester and selected the appropriate address from the residential history. If 

more than one address fell into a trimester, we 

chose the address where the subjects had spent 

the most time. Addresses were geocoded and 

distances estimated as described above.

We used logistic regression to estimate the 

association between distance to the nearest freeway or major road and autism. Pertinent covariates were included in the model to adjust for 

potential confounding due to sociodemographic 

or lifestyle characteristics. Specifically, we 

included child’s sex and ethnicity, maximum 

education level of the parents, maternal age, 

gestational age at birth, and maternal smoking 

during pregnancy. We obtained 95% confidence intervals (CIs) as measures of precision 

and determined statistical significance using an 

alpha level of 0.05.

Results

Description of sample. The study population was 84% male, and most participants 

were Caucasian (51%) or Hispanic (29%). 

We found no significant differences between 

cases and controls for any demographic or 

socioeconomic variables examined (Table 1). 

For most participants, geocoded birth certificate addresses (mother’s residence at delivery) indicated that residences at birth were 

concentrated in the areas around Sacramento, 

Los Angeles, and the San Francisco East and 

North Bay.

Distance to freeway. We examined the 

distribution of distance from the nearest freeway among subjects in our study and determined exposure cut-points to define the closest 

10% (< 309 m), the next 15% (309–647 m), 

and the next 25% (647–1,419 m) as exposure groups. The remaining 50% (> 1,419 m) 

served as the reference group in our analysis. 

Living within 309 m of a freeway at birth was 

associated with autism [odds ratio (OR) = 

1.86; 95% CI, 1.04–3.45]. This association 

was not altered by adjustment for child sex or 

ethnicity, maximum education in the home, 

maternal age, or maternal smoking during 

pregnancy (Table 2). When we categorized 

our distance measure into deciles, only the top 

10%, corresponding to the < 309-m category, 

showed evidence of an increased autism risk 

compared with those living farthest from the 

freeway (lowest decile, > 5,150 m; unadjusted 

OR = 2.48; 95% CI, 1.17–5.39).

Among the subset of subjects with available residential history data, measures for 

Table 1. Demographic characteristics of CHARGE cases with autism and controls with typical development (n = 563).

Percent (n) Chi-square 

Demographic variable Cases (n = 304) Controls (n = 259) p-value

Male sex 87 (263) 81 (211) 0.10

Child race/ethnicity 0.21

White 51 (154) 51 (131)

Hispanic 29 (88) 30 (77)

Black 3 (8) 2 (5)

Asian 7 (21) 3 (8)

Othera 11 (33) 15 (38)

Maximum education in home 0.88

High school or less 7 (22) 8 (22)

Some college 31 (95) 31 (79)

Bachelor degree 35 (107) 36 (93)

Graduate or professional degree 26 (80) 25 (65)

Maternal smoking during pregnancyb 9 (27) 7 (18) 0.40

Maternal age ≥ 35 years 28 (85) 25 (65) 0.44

Preterm delivery (< 259 days)c 11 (32) 10 (25) 0.73

a“Other” refers to mixed race/ethnicity or other reported race/ethnicity, including Native American, Indian, East Indian, 

Cuban, or Mexican American. bMother reported smoking at any time during pregnancy. cEquivalent to 37 completed 

weeks.
Freeway proximity and autism risk

Environmental Health Perspectives • volume 119 | number 6 | June 2011 875

distance to the freeway were highly correlated 

across trimesters, reflecting the limited number of subjects who changed residence during 

pregnancy (n = 17 between first and second, 

13 between second and third, 30 between first

and third). In each trimester, living closest to 

the freeway (< 309 vs. > 1,419 m) was associated with autism, but the OR reached statistical significance only during the third trimester 

(adjusted OR = 1.96; 95% CI, 1.01–3.93). 

Effect estimates for the first and second trimesters were slightly lower in magnitude 

(first trimester: adjusted OR = 1.66; 95% CI,

0.91–3.10; second trimester: adjusted OR 

= 1.65; 95% CI, 0.85–3.28). After restricting the sample with birth certificate addresses 

to those with residential history data for all 

three trimesters (n = 485; 257 cases and 228 

controls), the OR for autism was more than 

doubled among those living within 309 m of 

a freeway versus > 1,419 m (adjusted OR = 

2.22; 95% CI, 1.16–4.42), consistent with a 

late-pregnancy or early-life effect.

Distance to major road. The distribution 

of distance from a major road among subjects in our study was reflected in exposure 

cut-points corresponding to ≤ 42 m (the closest 10%), 42–96 m (subsequent 15%), and 

96–209 m (next 25%) as exposure groups. 

The remaining 50% (> 209 m) served as the 

reference group in our analysis. We found 

no consistent pattern of association of autism 

with proximity to a major road, and results 

were changed only slightly after adjusting for 

distance to the freeway (Table 3). Inclusion 

of child sex or ethnicity, maximum education 

in home, maternal age, or prenatal smoking 

in the model did not alter these associations. 

Results were similar for the three trimesters.

Discussion

We observed an increased risk of autism 

among the 10% of children living within 

309 m of a freeway around the time of 

birth. Our findings appeared to be limited 

to only this group because analysis of further 

distances did not demonstrate associations. 

Analysis of trimester-specific residential information yielded associations of roughly similar 

magnitude, although only the effects for the 

third trimester and at birth reached statistical significance. The high correlations across 

trimesters, and lack of analysis of postnatal 

residences, imply that we cannot precisely 

define a potentially critical window.

The association of autism with proximity to 

freeway, and not to major road, may be related 

to the larger volume of traffic and concentrations of pollutants observed near freeways. In 

Los Angeles, for example, some freeways have 

more than 300,000 vehicles daily and high 

concentrations of traffic-related pollutants 

with steep gradients extending several hundred 

meters from the traffic corridor (Caltrans 2008; 

Zhu et al. 2002, 2006). Specifically, studies 

measuring concentration and size distribution 

of ultrafine PM near a major California freeway demonstrate that the PM is high nearest 

the freeway and becomes closer to background 

levels at distances ≥ 300 m (Zhu et al. 2002). 

Thus, our findings are consistent with the relationship between freeway proximity and PM 

exposures in California. Our study did not 

find evidence of associations with residential 

proximity beyond the 300-m range, and we 

currently lack adequate sample size to estimate 

the effect of living in even closer proximity to 

the freeway (< 100 m) where high concentrations of PM have been detected. To examine the effects of proximity at closer distances 

to major roadways, we estimated autism risk 

among subjects living within 96 m (the top 

quartile of exposure vs. > 96 m) and among 

those living within 300 m (corresponding to 

the region of highest exposure vs. > 300 m) 

and found slightly elevated non-statistically significant risks (within 96 m: OR = 1.17; 95%

CI, 0.80–1.72; within 300 m: OR = 1.19;

95% CI, 0.84–1.68).

The traffic volumes on the classes of other 

major roadways used in this analysis are likely 

to be highly variable across California, so 

exposure to traffic-related pollutants on the 

spatial scale of interest may be less well classified by residential proximity to other major 

roadways than by proximity to freeways. For 

example, we found that the average distance to 

a freeway among subjects living in the second 

major road exposure group (42–96 m), with 

slightly increased risk of autism, was much 

shorter (mean ± SD = 1,481 ± 1,761 m) than 

in other major road categories (major road 

< 42 m, 2,643 ± 2,245 m to freeway; major 

road 96–209 m, 1,917 ± 3,946 m). Residential 

traffic proximity has been associated with 

childhood asthma and lung function growth 

in previous studies we have conducted in 

Southern California, and some of these 

associations have been restricted to freeway 

proximity or traffic modeled from freeway 

traffic volume (Gauderman et al. 2005, 2007; 

McConnell et al. 2006, 2010).

We found little evidence of confounding 

by the socioeconomic and sociodemographic 

characteristics included in this analysis. We 

hypothesized these confounders a priori based 

on literature reporting increased autism rates 

in higher socioeconomic areas, whereas lower 

socioeconomic areas are more likely to have 

higher levels of air pollutants (Sexton et al. 

1993). In our study, we observed no difference in level of education in the home among 

autism cases and controls, and adjusting for 

these factors had little effect on the traffic and 

autism association, suggesting that our results 

were not biased by such factors. In California, 

clusters of autism tend to have higher levels 

of parental education, and in countries with 

highly variable access to health care, diagnosed cases of autism tend to be in families 

with higher socioeconomic status than the 

general population; at the same time, controls 

that participate in studies are almost always of 

higher socioeconomic status than nonparticipants (Van Meter et al. 2010).

To date, little research has examined the 

association of air pollutants and autism. Using 

the U.S. Environmental Protection Agency 

Hazardous Air Pollutants monitoring network, Windham et al. (2006) identified an 

increased autism risk with modeled estimates 

of regional census tract ambient exposure to 

diesel exhaust particles, as well as metals (mercury, cadmium, and nickel) and chlorinated 

solvents, in the San Francisco Bay Area of 

northern California. Additional research using 

Table 2. Exposure ORs (95% CIs) for autism, by category of distance from residence to the nearest freeway at time of birth (n = 563). 

Exposure category n (cases/controls) Crude Adjusteda

 < 309 m from freeway (closest 10%) 38/19 1.86 (1.04–3.45) 1.86 (1.03–3.45)

309–647 m from freeway (10th to 25th percentile) 43/41 0.98 (0.60–1.59) 0.96 (0.58–1.56)

647–1,419 m from freeway (25th to 50th percentile) 77/63 1.14 (0.76–1.71) 1.11 (0.73–1.67)

 > 1,419 m from freeway (further 50%) 146/136 Reference Reference

aModel was adjusted for child sex (male vs. female), child race/ethnicity (Hispanic vs. white, black/Asian/other vs. 

white), maximum education of parents (parent with highest of four levels: college degree or higher vs. some high school, 

high school degree, or some college education), maternal age (> 35 years vs. ≤ 35 years), and maternal smoking during 

pregnancy (mother reported any smoking during pregnancy vs. mother reported no smoking during pregnancy)

Table 3. Exposure ORs (95% CIs) for autism, by category of distance from residence to the nearest major 

road at time of birth (n = 563).

Exposure category n (cases/controls) Crude Adjusteda 

≤ 42 m from major road (closest 10%) 28/30 0.80 (0.45–1.41) 0.71 (0.39–1.26)

42–96 m from major road (10th to 25th percentile) 54/32 1.44 (0.88–2.39) 1.29 (0.77–2.18)

96–209 m from major road (25th to 50th percentile) 71/68 0.89 (0.59–1.34) 0.83 (0.55–1.26)

 > 209 m from major road (further 50%) 151/129 Reference Reference

aModel was adjusted for child sex (male vs. female), child race/ethnicity (Hispanic vs. white, black/Asian/other vs. 

white), maximum education of parents (parent with the highest of four levels: college degree or more education vs. 

some high school, high school degree, or some college education), maternal age (> 35 years vs. ≤ 35 years), and maternal smoking during pregnancy (mother reported any smoking during pregnancy vs. mother reported no smoking during 

pregnancy), and freeway distance categories (< 309 m, 309–647 m, 647–1,419 m vs. referent of > 1,419 m).
Volk et al.

876 volume 119 | number 6 | June 2011 • Environmental Health Perspectives

models from the Hazardous Air Pollutants 

program found associations between autism 

and air toxics at the birth residence of children from North Carolina and West Virginia 

(Kalkbrenner et al. 2010). Our analysis builds 

on this work by examining associations with 

individual-level indicators of exposure based 

on traffic proximity, prenatally and at birth.

Toxicologic studies suggest a biologically 

plausible role of air pollution in disrupting 

brain development and function during critical 

time points in gestation and early life. Diesel 

exhaust particles present in traffic-related pollution have been shown to have endocrinedisrupting activity and to transplacentally affect 

sexual differentiation and alter cognitive function in mice (Hougaard et al. 2008; Watanabe 

and Kurita 2001). Prenatal exposure to ozone 

in rats has been seen to alter monoamine content in the cerebellum, which may then alter 

neural circuitry formation (Gonzalez-Pina et al. 

2008). Recent work examining the effects of 

benzo[a]pyrene, a common PAH, indicates 

that prenatal oral exposure in mice results in 

decreased neuronal plasticity and behavioral 

deficits (Brown et al. 2007). Specifically, prenatal exposure was associated with reduced 

glutamate receptor development when synapses are formed. Additionally, exposure to 

benzo[a]pyrene via breast-feeding in mice during the early postnatal period, corresponding 

to the rapid human brain development taking 

place during the third trimester, affected neuromaturation as measured by classic developmental behavior tests and to reduce expression of 

the serotonin receptor 5HT1A (Bouayed et al. 

2009; Pan et al. 2009).

Traffic-related air pollutants have been 

observed to induce inflammation and oxidative stress after both short-term and long-term 

exposures in toxicologic and human studies, 

and these pathways are thought to mediate 

effects of air pollution on respiratory and cardiovascular disease, and perhaps on neurologic 

outcomes (Block and Calderon-Garciduenas 

2009; Calderon-Garciduenas et al. 2009; 

Castro-Giner et al. 2009; Gilliland et al. 2004; 

Künzli et al. 2010). The emerging evidence 

that oxidative stress and inflammation are also 

involved in the pathogenesis of autism may 

suggest a biologically plausible rationale for 

the observed associations in our study (Boso 

et al. 2006; Enstrom et al. 2009a, 2009b; 

James et al. 2004, 2006, 2009). In particular, 

research examining serum biomarkers reported

increased levels of the proinflammatory cytokines tumor necrosis factor-α, interleukin 

(IL)-6, IL-8, and colony-stimulating factor II, 

as well as two markers of T-helper 1 immune 

response (interferon-γ and IL-8), in postmortem brain tissue of autism cases compared with 

controls (Li et al. 2009). Additional research 

from the CHARGE study has shown increased 

plasma levels of immunoglobulin (Ig) G-4

and reduced concentrations of tumor growth 

factor-β, related to immune response and 

inflammatory processes, in plasma of children 

with autism compared with typically developing controls and children with developmental 

delay (Ashwood et al. 2008; Enstrom et al. 

2009a, 2009b). Other recent work indicates 

that exposure to air pollution exposure during 

pregnancy is associated with changes in IgE 

and in lymphocytes measured from cord blood,

supporting the idea that maternal exposure to 

air pollution is associated with altered immune 

profiles in the fetus (Herr et al. 2010a, 2010b). 

Moreover, published evidence links maternal 

antibodies to fetal brain tissue with a subset of 

autism cases (Braunschweig et al. 2008).

Genetic variation in oxidative stress and 

inflammatory pathways has also been associated with autism. Oxidative stress endophenotypes and corresponding genotypes related 

to metabolism of methionine transmethylation and transsulfuration were significantly 

decreased in children with autism compared 

with controls, indicating increased susceptibility to oxidative stress (Boso et al. 2006; James 

et al. 2004, 2006). Markers of lipid peroxidation have also been associated with autism, as 

have increased levels of nitric oxide and mitochondrial dysfunction, which may be related 

to the formation of reactive oxygen species 

(Chauhan and Chauhan 2006; Filipek et al. 

2004; Ming et al. 2005; Sogut et al. 2003; 

Yao et al. 2006). Polymorphisms in glutathione S-transferase mu 1 (GSTM1), glutathione 

S-transferase pi 1 (GSTP1), and glutathione 

peroxidase 1 (GPX1), which modulate the 

response to oxidative stress, have been associated with increased autism risk (Buyske et al. 

2006; Ming et al. 2009; Williams et al. 2007). 

These genetic variants have also been shown 

to modify the association between exposure 

to air oxidant pollutant associations and respiratory outcomes (Islam et al. 2009; Salam 

et al. 2007). Examination of the interaction 

between these oxidant-associated genes and 

environmental exposures may help to clarify 

susceptibilities to environmental pollutants 

among children with autism.

We recognize that the moderate relative 

risks associated with freeway proximity in our 

study may have been attributable to chance or 

bias. The study is currently limited by sample 

size and potential exposure misclassification. 

Analysis of larger data sets would provide 

additional valuable insight into these findings 

and the potential for replication. Although we 

used a residential history questionnaire (available for a subset of the study participants) to 

choose the appropriate address for trimester, 

there still may be misclassification of exposure 

in these data due to inaccurate date reporting 

on the part of the mother, or in our choice 

among multiple addresses in each trimester. 

We could not distinguish the potential effect 

of noise from that due to pollutant exposures, 

both resulting from residential location near a 

freeway or other road in this study. Addresses 

on the birth certificate could also be in error, 

but this would probably be less likely. We 

were not able to examine specific pollutant 

concentrations in this study, and the traffic 

proximity metrics were subject to misclassification of exposure because they did not 

account for traffic volume or prevailing wind 

speed and direction. However, this exposure 

misclassification was unlikely to have been 

systematically related to disease, and our 

results may therefore have underestimated the 

magnitude of a true causal association.

Despite these limitations, this study has 

several strengths. We assessed autism through 

well-validated instruments that are recognized 

as the gold standard in the field. We examined 

exposure prenatally and at birth, two pivotal 

times in gestational development, whereas 

prior work on air pollution has been limited 

to the birth address or a cumulative lifetime 

exposure measure. To our knowledge, these 

results are the first to show an association of 

autism with residential traffic proximity.

Conclusions

Little is known about potential environmental 

contributions to autism. The observed associations with traffic proximity merit further 

research to determine whether these results are 

reproducible in populations with improved 

estimates of exposure to specific ambient air 

pollutants. Examination of gene–pollution 

interactions may also help us learn about causal 

pathways involved in autism and identify 

potentially susceptible populations and may 

lead to prevention strategies. Our analysis is the 

first step in examining a hypothesized relationship between air pollutants and autism. It has 

been estimated that 11% of the U.S. population lives within 100 m of a four-lane highway, 

so a causal link to autism or other neurodevelopmental disorders would have broad public 

health implications (Brugge et al. 2007).

References

Abrahams BS, Geschwind DH. 2008. Advances in autism genetics: on the threshold of a new neurobiology. Nat Rev Genet 

9(5):341–355.

American Psychiatric Association. 2000. Diagnostic and 

Statistical Manual of Mental Disorders. 4th ed, Text Revision. 

Washington, DC:American Psychiatric Association.

Ashwood P, Enstrom A, Krakowiak P, Hertz-Picciotto I, 

Hansen RL, Croen LA, et al. 2008. Decreased transforming 

growth factor beta1 in autism: a potential link between 

immune dysregulation and impairment in clinical behavioral outcomes. J Neuroimmunol 204(1–2):149–153.

Block ML, Calderon-Garciduenas L. 2009. Air pollution: mechanisms of neuroinflammation and CNS disease. Trends 

Neurosci 32(9):506–516.

Bocskay KA, Tang D, Orjuela MA, Liu X, Warburton DP, 

Perera FP. 2005. Chromosomal aberrations in cord blood 

are associated with prenatal exposure to carcinogenic 

polycyclic aromatic hydrocarbons. Cancer Epidemiol 

Biomarkers Prev 14(2):506–511.

Boso M, Emanuele E, Minoretti P, Arra M, Politi P, Ucelli di Nemi S, 
Freeway proximity and autism risk

Environmental Health Perspectives • volume 119 | number 6 | June 2011 877

et al. 2006. Alterations of circulating endogenous secretory 

RAGE and S100A9 levels indicating dysfunction of the AGERAGE axis in autism. Neurosci Lett 410(3):169–173.

Bouayed J, Desor F, Rammal H, Kiemer AK, Tybl E, Schroeder H, 

et al. 2009. Effects of lactational exposure to benzo[alpha]

pyrene (B[alpha]P) on postnatal neurodevelopment, neuronal receptor gene expression and behaviour in mice. 

Toxicology 259(3):97–106.

Braunschweig D, Ashwood P, Krakowiak P, Hertz-Picciotto I, 

Hansen R, Croen LA, et al. 2008. Autism: maternally derived 

antibodies specific for fetal brains. Neurotoxicology 

29(2):226–231.

Brown LA, Khousbouei H, Goodwin JS, Irvin-Wilson CV, 

Ramesh A, Sheng L, et al. 2007. Down-regulation of early 

ionotrophic glutamate receptor subunit developmental 

expression as a mechanism for observed plasticity deficits following gestational exposure to benzo(a)pyrene. 

Neurotoxicology 28(5):965–978.

Brugge D, Durant JL, Rioux C. 2007. Near-highway pollutants in 

motor vehicle exhaust: a review of epidemiologic evidence 

of cardiac and pulmonary health risks. Environ Health 6:23; 

doi: 10.1186/1476-069X-6-23 [Online 9 August 2007].

Buyske S, Williams TA, Mars AE, Stenroos ES, Ming SX, 

Wang R, et al. 2006. Analysis of case-parent trios at a 

locus with a deletion allele: association of GSTM1 with 

autism. BMC Genet 7:8; doi:10.1186/1471-2156-7-8 [Online 

10 February 2006].

Calderon-Garciduenas L, Macias-Parra M, Hoffmann HJ, 

Valencia-Salazar G, Henriquez-Roldan C, Osnaya N, et al. 

2009. Immunotoxicity and environment: immunodysregulation and systemic inflammation in children. Toxicol Pathol 

37(2):161–169.

Caltrans. 2008. Traffic and Vehicle Data Systems Unit: All 

Traffic Volumes on the California State Highway System. 

Available: http://www.dot.ca.gov/hq/traffops/saferesr/

trafdata/2008all.htm [accessed 27 July 2010].

Castro-Giner F, Künzli N, Jacquemin B, Forsberg B, de Cid R, 

Sunyer J, et al. 2009. Traffic-related air pollution, oxidative stress genes, and asthma (ECHRS). Environ Health 

Perspect 117:1919–1924.

Centers for Disease Control and Prevention. 2007a. Prevalence 

of autism spectrum disorders—autism and developmental 

disabilities monitoring network, 14 sites, United States, 

2002. MMWR Surveill Summ 56(1):12–28.

Centers for Disease Control and Prevention. 2007b. Prevalence 

of autism spectrum disorders—autism and developmental 

disabilities monitoring network, six sites, United States, 

2000. MMWR Surveill Summ 56(1):1–11.

Centers for Disease Control and Prevention. 2009. Prevalence

of autism spectrum disorders—autism and developmental disabilities monitoring network, United States, 2006. 

MMWR Surveill Summ 58(10):1–20.

Chauhan A, Chauhan V. 2006. Oxidative stress in autism. 

Pathophysiology 13(3):171–181.

Currie J, Neidell M, Schmieder JF. 2009. Air pollution and 

infant health: lessons from New Jersey. J Health Econ 

28(3):688–703.

Enstrom A, Krakowiak P, Onore C, Pessah IN, Hertz-Picciotto I, 

Hansen RL, et al. 2009a. Increased IgG4 levels in children 

with autism disorder. Brain Behav Immun 23(3):389–395.

Enstrom AM, Lit L, Onore CE, Gregg JP, Hansen RL, Pessah IN, 

et al. 2009b. Altered gene expression and function of 

peripheral blood natural killer cells in children with autism. 

Brain Behav Immun 23(1):124–133.

Filipek PA, Juranek J, Nguyen MT, Cummings C, Gargus JJ. 

2004. Relative carnitine deficiency in autism. J Autism Dev 

Disord 34(6):615–623.

Gauderman WJ, Avol E, Lurmann F, Kuenzli N, Gilliland F, 

Peters J, et al. 2005. Childhood asthma and exposure to 

traffic and nitrogen dioxide. Epidemiology 16(6):737–743.

Gauderman WJ, Vora H, McConnell R, Berhane K, Gilliland F, 

Thomas D, et al. 2007. Effect of exposure to traffic on lung 

development from 10 to 18 years of age: a cohort study. 

Lancet 369(9561):571–577.

Gilliland FD, Li YF, Saxon A, Diaz-Sanchez D. 2004. Effect of glutathione-S-transferase M1 and P1 genotypes on xenobiotic 

enhancement of allergic responses: randomised, placebocontrolled crossover study. Lancet 363(9403):119–125.

Gonzalez-Pina R, Escalante-Membrillo C, Alfaro-Rodriguez A, 

Gonzalez-Maciel A. 2008. Prenatal exposure to ozone 

disrupts cerebellar monoamine contents in newborn rats. 

Neurochem Res 33(5):912–918.

Hansen CA, Barnett AG, Pritchard G. 2008. The effect of 

ambient air pollution during early pregnancy on fetal 

ultrasonic measurements during mid-pregnancy. Environ 

Health Perspect 116:362–369.

Herr CEW, Dostal M, Ghosh R, Ashwood P, Lipsett M, 

Pinkerton KE, et al. 2010b. Air pollution exposure during critical time periods in gestation and alterations in 

cord blood lymphocyte distribution: a cohort of livebirths. 

Environ Health 9:46; doi:10.1186/1476-069X-9-46 [Online 

2 August 2010].

Herr CEW, Ghosh R, Dostal M, Skokanova V, Ashwood P, 

Lipsett M, et al. 2010a. Exposure to air pollution in critical 

prenatal time windows and IgE levels in newborns. Pediatr 

Allergy Immunol; doi: 10.1111/j.1399-3038.2010.01074.x 

[Online 1 July 2010].

Hertz-Picciotto I, Croen LA, Hansen R, Jones CR, van de Water J, 

Pessah IN. 2006. The CHARGE study: an epidemiologic 

investigation of genetic and environmental factors contributing to autism. Environ Health Perspect 114:1119–1125.

Hertz-Picciotto I, Delwiche L. 2009. The rise in autism and the 

role of age at diagnosis. Epidemiology 20(1):84–90.

Hougaard KS, Jensen KA, Nordly P, Taxvig C, Vogel U, 

Saber AT, et al. 2008. Effects of prenatal exposure to diesel exhaust particles on postnatal development, behavior, 

genotoxicity and inflammation in mice. Part Fibre Toxicol 

5:3; doi:10.1186/1743-8977-5-3 [Online 11 March 2008].

Islam T, Berhane K, McConnell R, Gauderman WJ, Avol E, 

Peters JM, et al. 2009. Glutathione-S-transferase (GST) P1, 

GSTM1, exercise, ozone and asthma incidence in school 

children. Thorax 64(3):197–202.

James SJ, Cutler P, Melnyk S, Jernigan S, Janak L, Gaylor DW, 

et al. 2004. Metabolic biomarkers of increased oxidative 

stress and impaired methylation capacity in children with 

autism. Am J Clin Nutr 80(6):1611–1617.

James SJ, Melnyk S, Jernigan S, Cleves MA, Halsted CH, 

Wong DH, et al. 2006. Metabolic endophenotype and 

related genotypes are associated with oxidative stress in 

children with autism. Am J Med Genet B Neuropsychiatr 

Genet 141B(8):947–956.

James SJ, Rose S, Melnyk S, Jernigan S, Blossom S, Pavliv O, 

et al. 2009. Cellular and mitochondrial glutathione redox 

imbalance in lymphoblastoid cells derived from children 

with autism. FASEB J 23(8):2374–2383.

Kalkbrenner AE, Daniels JL, Chen JC, Poole C, Emch M, 

Morrissey J. 2010. Perinatal exposure to hazardous 

air pollutants and autism spectrum disorders at age 8. 

Epidemiology 21(5):631–641.

King M, Bearman P. 2009. Diagnostic change and the increased 

prevalence of autism. Int J Epidemiol 38(5):1224–1234.

Künzli N, Jerrett M, Garcia-Esteban R, Basagana X, Beckermann B, 

Gilliland F, et al. 2010. Ambient air pollution and the progression of atherosclerosis in adults. PLoS One 5(2):e9096.

Le Couteur A, Lord C, Rutter M. 2003. Autism Diagnostic 

Interview–Revised (ADI-R). Los Angeles:Western 

Psychological Services.

Li X, Chauhan A, Sheikh AM, Patil S, Chauhan V, Li XM, et al. 

2009. Elevated immune response in the brain of autistic 

patients. J Neuroimmunol 207(1–2):111–116.

Lord C, Rutter M, DiLavore P, Risi S. 2003. Autism Diagnostic 

Observation Schedule Manual. Los Angeles:Western 

Psychological Services.

Ma D, Salyakina D, Jaworski JM, Konidari I, Whitehead PL, 

Andersen AN, et al. 2009. A genome-wide association 

study of autism reveals a common novel risk locus at 

5p14.1. Ann Hum Genet 73(pt 3):263–273.

McConnell R, Berhane K, Yao L, Jerrett M, Lurmann F, 

Gilliland F, et al. 2006. Traffic, susceptibility, and childhood 

asthma. Environ Health Perspect 114:766–772.

McConnell R, Islam T, Shankardass K, Jerrett M, Lurmann F, 

Gilliland F, et al. 2010. Childhood incident asthma and 

traffic-related air pollution at home and school. Environ 

Health Perspect 118:1021–1026.

Ming X, Johnson WG, Stenroos ES, Mars A, Lambert GH, 

Buyske S. 2009. Genetic variant of glutathione peroxidase 1 in autism. Brain Dev 32(2):105–109.

Ming X, Stein TP, Brimacombe M, Johnson WG, Lambert GH, 

Wagner GC. 2005. Increased excretion of a lipid peroxidation biomarker in autism. Prostaglandins Leukot Essent 

Fatty Acids 73(5):379–384.

Morales E, Julvez J, Torrent M, de Cid R, Guxens M, 

Bustamante M, et al. 2009. Association of early-life exposure to household gas appliances and indoor nitrogen 

dioxide with cognition and attention behavior in preschoolers. Am J Epidemiol 169(11):1327–1336.

Muhle R, Trentacoste SV, Rapin I. 2004. The genetics of autism. 

Pediatrics 113(5):e472–e486.

Mullen E. 1995. Mullen Scales of Early Learning. Circle Pines, 

MN:American Guidance Services Inc.

Pan IJ, Daniels JL, Goldman BD, Herring AH, Siega-Riz AM, 

Rogan WJ. 2009. Lactational exposure to polychlorinated 

biphenyls, dichlorodiphenyltrichloroethane, and dichlorodiphenyldichloroethylene and infant neurodevelopment: 

an analysis of the pregnancy, infection, and nutrition 

babies study. Environ Health Perspect 117:488–494.

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

2003. Effects of transplacental exposure to environmental 

pollutants on birth outcomes in a multiethnic population. 

Environ Health Perspect 111:201–205.

Perera FP, Rauh V, Whyatt RM, Tsai WY, Bernert JT, Tu YH, et al. 

2004. Molecular evidence of an interaction between prenatal environmental exposures and birth outcomes in a multiethnic population. Environ Health Perspect 112:626–630.

Perera FP, Rauh V, Whyatt RM, Tsai WY, Tang D, Diaz D, et al. 

2006. Effect of prenatal exposure to airborne polycyclic 

aromatic hydrocarbons on neurodevelopment in the first 

3 years of life among inner-city children. Environ Health 

Perspect 114:1287–1292.

Perera FP, Tang D, Rauh V, Tu YH, Tsai WY, Becker M, et al. 

2007. Relationship between polycyclic aromatic hydrocarbon–DNA adducts, environmental tobacco smoke, and child 

development in the World Trade Center cohort. Environ 

Health Perspect 115:1497–1502.

Ritz B, Yu F. 1999. The effect of ambient carbon monoxide on low 

birth weight among children born in Southern California 

between 1989 and 1993. Environ Health Perspect 107:17–25.

Rutter M, Bailey A, Lord C. 2003. A Social Communication 

Questionnaire (SCQ). Los Angeles:Western Psychological 

Services.

Salam MT, Lin PC, Avol EL, Gauderman WJ, Gilliland FD. 2007. 

Microsomal epoxide hydrolase, glutathione S-transferase 

P1, traffic and childhood asthma. Thorax 62(12):1050–1057.

Sexton K, Gong H Jr, Bailar JC III, Ford JG, Gold DR, 

Lambert WE, et al. 1993. Air pollution health risks: do class 

and race matter? Toxicol Ind Health 9(5):843–878.

Sogut S, Zoroglu SS, Ozyurt H, Yilmaz HR, Ozugurlu F, Sivasli E, 

et al. 2003. Changes in nitric oxide levels and antioxidant 

enzyme activities may have a role in the pathophysiological 

mechanisms involved in autism. Clin Chim Acta 331(1–

2):111–117.

Sparrow S, Cicchettim D, Balla D. 1984. Vineland Adaptive 

Behavior Scales Interview Edition Expanded Form Manual. 

Circle Pines, MN:American Guidance Services Inc.

Suglia SF, Gryparis A, Wright RO, Schwartz J, Wright RJ. 2008. 

Association of black carbon with cognition among children in a prospective birth cohort study. Am J Epidemiol 

167(3):280–286.

Van Meter KC, Christiansen LE, Delwiche LD, Azari R, 

Carpenter TE, Hertz-Picciotto I. 2010. Geographic distribution of autism in California: a retrospective birth cohort 

analysis. Autism Res 3(1):19–29.

Vassilev ZP, Robson MG, Klotz JB. 2001. Outdoor exposure to 

airborne polycyclic organic matter and adverse reproductive outcomes: a pilot study. Am J Ind Med 40(3):255–262.

Wang K, Zhang H, Ma D, Bucan M, Glessner JT, Abrahams BS, 

et al. 2009. Common genetic variants on 5p14.1 associate 

with autism spectrum disorders. Nature 459(7246):528–533.

Watanabe N, Kurita M. 2001. The masculinization of the fetus 

during pregnancy due to inhalation of diesel exhaust. 

Environ Health Perspect 109:111–119.

Williams TA, Mars AE, Buyske SG, Stenroos ES, Wang R, FacturaSantiago MF, et al. 2007. Risk of autistic disorder in affected 

offspring of mothers with a glutathione S-transferase P1 

haplotype. Arch Pediatr Adolesc Med 161(4):356–361.

Windham GC, Zhang L, Gunier R, Croen LA, Grether JK. 2006. 

Autism spectrum disorders in relation to distribution of 

hazardous air pollutants in the San Francisco Bay Area. 

Environ Health Perspect 114:1438–1444.

Yao Y, Walsh WJ, McGinnis WR, Pratico D. 2006. Altered 

vascular phenotype in autism: correlation with oxidative 

stress. Arch Neurol 63(8):1161–1164.

Zhu Y, Hinds WC, Kim S, Sioutas C. 2002. Concentration and 

size distribution of ultrafine particles near a major highway. J Air Waste Manag Assoc 52(9):1032–1042.

Zhu Y, Kuhn T, Mayo P, Hinds WC. 2006. Comparison of daytime 

and nighttime concentration profiles and size distributions 

of ultrafine particles near a major highway. Environ Sci 

Technol 40(8):2531–2536.