Parental stress increases the effect of traffic-related

air pollution on childhood asthma incidence

Ketan Shankardassa, Rob McConnellb,1, Michael Jerrettc, Joel Milamb, Jean Richardsonb, and Kiros Berhaneb

aCentre for Research on Inner City Health, The Li Ka Shing Knowledge Institute of St. Michael’s Hospital, 30 Bond Street, Toronto, ON, Canada M5B 1W8;

bDepartment of Preventive Medicine, Keck School of Medicine, University of Southern California, 1540 Alcazar Street, Suite 236, Los Angeles, CA

90089-9013; and c

School of Public Health, Division of Environmental Health Science, University of California, Berkeley, 50 University Hall #7360, Berkeley, CA

94720-7360

Edited by Roger E. Kasperson, Clark University, Worcester, MA, and approved June 10, 2009 (received for review December 19, 2008)

Exposure to traffic-related pollution (TRP) and tobacco smoke have

been associated with new onset asthma in children. Psychosocial

stress-related susceptibility has been proposed to explain social disparities in asthma. We investigated whether low socioeconomic

status (SES) or high parental stress modified the effect of TRP and in

utero tobacco smoke exposure on new onset asthma. We identified

2,497 children aged 5–9 years with no history of asthma or wheeze at

study entry (2002–2003) into the Children’s Health Study, a prospective cohort study in southern California. The primary outcome was

parental report of doctor-diagnosed new onset asthma during 3 years

of follow-up. Residential exposure to TRP was assessed using a line

source dispersion model. Information about maternal smoking during

pregnancy, parental education (a proxy for SES), and parental stress

were collected in the study baseline questionnaire. The risk of asthma

attributable to TRP was significantly higher for subjects with high

parental stress (HR 1.51 across the interquartile range for TRP; 95% CI

1.16 –1.96) than for subjects with low parental stress (HR 1.05, 95% CI

0.74 –1.49; interaction P value 0.05). Stress also was associated with

larger effects of in utero tobacco smoke. A similar pattern of increased

risk of asthma was observed among children from low SES families

who also were exposed to either TRP or in utero tobacco smoke.

These results suggest that children from stressful households are

more susceptible to the effects of TRP and in utero tobacco smoke on

the development of asthma.

socioeconomic status  tobacco smoke

Asthma is the most common chronic childhood illness in developed countries and a growing concern worldwide (1). It is

considered to be a complex disease with a multifactorial etiology as

established risk factors have failed to explain trends in the global

epidemiology of asthma (2). The incidence of asthma has been

associated with environmental factors, including combustion products in tobacco smoke, especially in utero, and in air pollution (3–5).

Several studies suggest that increased severity of asthma among low

socioeconomic status (SES) children and adults may be explained

by stress (6, 7), yet few studies have examined whether these factors

modify the risk for asthma attributable to environmental pollution.

It is generally recognized that air pollution exacerbates asthma in

children (8), and some studies suggest an effect on induction of

asthma (9, 10).We have recently reported associations of residential

traffic-related pollution (TRP) with both prevalent and new onset

asthma during follow-up in the Southern California Children’s

Health Study (CHS) (5, 11, 12). Effects of pollution are biologically

plausible given emerging evidence from human experimental,

animal, and in vitro studies suggesting that ambient particulate

matter and gaseous co-pollutants cause oxidative stress and inflammation, which are important features of asthma pathogenesis (13).

We have also shown asthma to be associated with another oxidant

pollutant, in utero tobacco smoke (4, 14–16), results which are

consistent with other studies of in utero and second hand smoke

(SHS) exposure (17, 18).

Effects of air pollution on asthma and other respiratory conditions have been found to be greater among individuals of lower SES

(19, 20). A possible mechanism by which SES may modify the

effects of air pollution is psychological stress (6, 21). Stress has

pro-oxidant effects that can increase airway inflammation (22), and

high levels of stress in both children and parents predict onset of

wheeze and asthma morbidity (e.g., severity, subsequent attacks) in

children (23–27). Stress may also increase vulnerability to antigens

through direct effects on the endocrine system, autonomic control

of airways, and immune function (28, 29). Stress may thus increase

vulnerability to environmental factors associated with asthma and

may explain the observed susceptibility to asthma attributed to SES.

Epidemiological support for this hypothesis is provided by a recent

cross-sectional study showing that effects of TRP on lifetime

asthma were larger in children who reported exposure to violence,

a source of stress (30).

We hypothesized that low SES and high parental stress would

increase childhood susceptibility for new onset asthma from 2

sources of oxidant pollution, residential TRP and maternal smoking

during pregnancy. Residential exposure to TRP was assessed at

study entry based on a line source dispersion model (31). Parental

education was used as a proxy for SES, and parental stress was

assessed using the Perceived Stress Scale (PSS), which is a widely

used measure of the degree to which respondents believed their

lives were unpredictable, uncontrollable, or overwhelming (32).

Results

The study population included children enrolled in a prospective

cohort study of air pollution and respiratory health and followed for

3 years (11). Age ranged from 5 to 9 years at study entry; 80% of

subjects were at least 6 years old (Table 1). There were slightly more

girls (52%) than boys. The majority of subjects were of Hispanic

ethnicity (55%), and the plurality of the remainder was nonHispanic white (36%); there were few subjects who were African

American (3%) or of other race or ethnicity (6%). The mean score

for parental stress using the PSS was 3.85 (standard deviation, 2.79),

with a median value of 4. In ascending order, the 4 quartiles of the

PSS distribution included values of 0 to 1, 2 to 3, 4 to 5, and 6 to 15

(See Materials and Methods for details). Approximately 21% of

children had parents who had not finished high school (‘‘low SES’’),

while almost 79% had parents with a high school diploma or greater

(‘‘high SES’’). There were 120 cases of new onset asthma during

follow-up (5). Significantly increased risk of new onset asthma was

associated with being African American (in comparison to Hispanic

children) or underweight, having a history of chest illness or allergy,

parental asthma, and musty odor in the home (Table 1). There was

no association of asthma with parental stress categorized into

quartiles or with a continuous stress index [hazard ratio (HR) 1.02;

95% confidence interval (CI) 0.78–1.33], and children from low

Author contributions: K.S., R.M., M.J., J.M., J.R., and K.B. designed research; K.S., R.M., and

M.J. performed research; M.J. contributed new reagents/analytic tools; K.S., R.M., M.J.,

J.M., J.R., and K.B. analyzed data; and K.S., R.M., M.J., J.M., J.R., and K.B. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

1To whom correspondence should be addressed. E-mail: rmcconne@usc.edu.

12406 –12411  PNAS  July 28, 2009  vol. 106  no. 30 www.pnas.orgcgidoi10.1073pnas.0812910106
SES homes had risk identical to those with a high school education

or at least some college.

The distribution of traffic-related exposure in this population has

been previously described (5, 11). As shown in Table 2, the risk of

asthma onset increased with exposure to TRP [HR 1.31, 95% CI

1.07–1.61, across of the interquartile range (IQR) of 21 ppb of

nitrogen oxide (NOX), an indicator of the near-source mixture of

TRP]. The risk associated with TRP was higher in low SES subjects

(HR 1.55, 95% CI 1.09–2.19) than in those of high SES (HR 1.20,

95% CI 0.93–1.55; P value for interaction  0.25). Traffic-related

risk of asthma was also increased in subjects with parental stress

above the median (HR 1.51, 95% CI 1.16–.1.96), but there was little

risk associated with TRP among subjects with parental stress below

the median (HR 1.05, 95% CI 0.74–1.49, P value for interaction 

0.05). The risk of asthma associated with TRP increased monotonically across quartiles of parental stress (Fig. 1). When the interaction between parental stress and TRP was adjusted for the

interaction between SES and TRP, the coefficient for the stressrelated interaction was unchanged; on the other hand, the coefficient related to the interaction with SES was reduced by 27%. The

overall pattern of susceptibility to traffic pollutant exposure based

on parental stress was not changed by adjusting for other potential

confounding susceptibility factors shown in Table 1, and the interaction P value from the model not adjusted for these factors (see

Table 2) remained significant in adjusted models.

In utero tobacco smoke exposure was associated with a modest

increased risk of asthma (HR 1.49, 95% CI 0.79–2.80, Table 3).

However, maternal smoking during pregnancy was associated with

a large increased risk of asthma among subjects with low SES (HR

5.69, 95% CI 1.88–17.3), while there was little indication of an effect

among high SES subjects (HR 1.10, 95% CI 0.51–2.41, P value for

interaction  0.03). Subjects with high parental stress had an

increased risk of asthma associated with in utero exposure (HR

2.66, 95% CI 1.33–5.33). The HR was less than unity with wide CIs

among subjects with low parental stress (HR 0.30, 95% CI 0.04–

2.18), but the effect was significantly different from that observed

in children with more parental stress (P value for interaction 

0.03). Because there were relatively few participants who reported

maternal smoking in utero (156, 6.3%) and small numbers in

subgroups based on other potentially relevant confounders (from

Table 1), we were not able to co-adjust interactions related to SES

and to parental stress. We found a consistent, but weaker, pattern

of susceptibility based on SHS in the home at the time of study

entry. The HRs for SHS were 1.20 (95% CI 0.51, 2.80) and 0.35

(95% CI 0.05, 2.50) in the high and low stress strata, respectively,

and there was little difference in the effect of SHS based on SES.

An earlier analysis based on the same study population found

that the effect of parental stress on wheeze onset was modified by

family history of asthma and gender, where the effect of stress was

limited to males with no family history of asthma (26). The effect

of regular smoking and of TRP on asthma has also been reported

to be modified by personal history of allergy or by gender (4, 11).

Therefore, we examined whether stress-related susceptibility to

TRP varied by gender, family history of asthma, and personal

history of allergy. In separate models, we reparameterized TRP into

strata created by combinations of high and low parental stress with

either family history of asthma, personal history of allergy and

gender (i.e., 3 models, each with 4 strata-specific effects of TRP).

The interaction between stress and TRP was similar within strata

of family history of asthma and personal history of allergy. Effect

modification by stress appeared to be stronger for male subjects. In

a model that estimated the effect of TRP in subjects with high versus

low parental stress, for males and females separately (i.e., 4 strata

total), the HR for TRP among males with high parental stress was

1.60 (95% CI 1.16–2.22) compared to 0.98 (95% CI 0.61–1.59)

among males with low parental stress (P value for interaction

among males  0.02). Within the same model, an HR of 1.36 (95%

CI .87–2.11) was observed for females with high parental stress

Table 1. Subject characteristics and associations with new onset

asthma

Risk factor N (%)*

Hazard ratio

(95% confidence

interval)†

Subject characteristics

Age at baseline

5 years 496 (19.9) 1.00‡

6 years 1,178 (47.1) 1.12 (0.69–2.83)

7–9 years 823 (33.0) 1.11 (0.66–1.87)

Male gender 1,190 (47.7) 1.07 (0.75–1.53)

Race/ethnicity

Hispanic ethnicity 1,380 (55.3) 1.00‡

African-American race 77 (3.1) 2.44 (1.05–5.67)§

White non-Hispanic race 905 (36.2) 1.08 (0.73–1.59)

Other race 135 (5.4) 1.67 (0.86–3.27)

Spanish language questionnaire 610 (24.4) 0.81 (0.49–1.35)

Body mass index

Underweight 92 (4.0) 2.50 (1.28–4.89)§

Healthy weight 1,587 (68.3) 1.00‡

At risk of overweight 337 (14.5) 1.36 (0.79–2.34)

Overweight 308 (13.3) 1.45 (0.85–2.46)

Chest-related illness

None 1,932 (85.0) 1.00‡

Before age 2 129 (5.7) 1.93 (0.96–3.86)

After age 2 126 (5.6) 2.76 (1.58–4.84)§

Before and after age 2 85 (3.7) 2.98 (1.48–5.98)§

Allergies 764 (33.6) 2.27 (1.54–3.33)§

Child resides in more than one home 178 (7.3) 0.60 (0.24–1.46)

Parental characteristics

Parental history of asthma 389 (17.0) 2.05 (1.35–3.12)§

Parental stress (PSS)

Quartile 1 563 (23.8) 1.00‡

Quartile 2 605 (25.6) 1.00 (0.59–1.70)

Quartile 3 531 (22.5) 1.21 (0.72–2.04)

Quartile 4 664 (28.1) 0.97 (0.57–1.64)

Medical care & SES

Medical insurance coverage 2,135 (87.7) 1.36 (0.70–2.63)

Type of medical insurance coverage

HMO/PPO 1,591 (65.3) 1.00‡

Social assistance 547 (22.4) 1.28 (0.82–2.01)

No insurance coverage 300 (12.3) 0.79 (0.82–2.01)

Parental education

Did not finish high school 508 (21.2) 1.00 (0.61–1.64)

High school diploma or some college 1,318 (55.1) 1.00‡

College diploma or greater 567 (23.7) 0.74 (0.45–1.19)

Home characteristics

Mildew in home 532 (21.8) 1.22 (0.80–1.86)

Cockroaches in home 257 (10.8) 1.53 (0.90–2.63)

Water damage/flooding in home 321 (13.1) 1.42 (0.88–2.30)

Musty odor in home 84 (3.5) 2.15 (1.05–4.42)§

Humidifier/vaporizer in home 484 (20.1) 1.06 (0.67–1.67)

Any daily smoker inside home 164 (6.7) 0.88 (0.41–1.90)

Carpet in child’s bedroom 2,090 (85.8) 1.09 (0.63–1.88)

Any pets in home 1,313 (53.9) 0.84 (0.57–1.23)

Dogs in home 730 (30.0) 0.79 (0.52–1.21)

Cats in home 462 (19.0) 0.73 (0.43–1.24)

Gas stove in home 2,042 (84.5) 1.18 (0.70–2.02)

Air conditioning in home 1,448 (60.0) 1.16 (0.79–1.72)

Type of home

Single-family house 1,938 (79.5) 1.00‡

Apartment (2–10 units) 328 (13.5) 1.30 (0.76–2.23)

Apartment (10 units) 102 (4.2) 1.71 (0.73–3.96)

Mobile home/trailer/other 69 (2.8) 1.52 (0.55–4.15)

*Numbers may not total to 2,497 because of missing values.

†Adjusted for race/ethnicity with baseline strata for age and gender (where

appropriate), and community random effects.

‡Denotes reference group.

§Denotes statistically significant finding, i.e., P  0.05.

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compared with 1.14 (95% CI 0.68–1.90) for females with low

parental stress (P value for interaction among females  0.84). The

P value for a 3-way ‘‘gender-parental stress-TRP’’ interaction term

was 0.10. When parental education was substituted for stress, there

was no evidence of a 3-way interaction.

Discussion

Children whose parents perceived their lives as unpredictable,

uncontrollable, or overwhelming had increased risk of new onset

asthma associated with TRP and maternal smoking during pregnancy. Furthermore, susceptibility to TRP attributable to parental

education was markedly attenuated after accounting for the susceptibility attributable to parental stress. While parental stress may

influence the development of asthma in a child due to biological

and behavioral pathways other than psychological stress in children

(26), the observed pattern of susceptibility to air pollution based on

stress was not explained by potentially relevant history of illness and

a range of behavioral, socioeconomic, and environmental risk

factors for asthma. Although there were relatively few children with

a history of in utero tobacco smoke exposure, significantly larger

effects were observed both among children with low parental

education and with high parental stress. Thus, common biological

pathways may underlie the relationship of asthma to stress and

combustion products common to both air pollution and cigarette

smoke. Previous studies have reported effects of stress on lifetime

asthma (30), asthma severity (33), and incident wheeze (27, 34).

Particulate and gaseous air pollutants can promote inflammatory

responses in the airways, which are a central feature of asthma

(34–36). The mechanisms linking exposure to inflammation have

been intensively studied in recent years. Exposure to ambient

particulate matter has been associated with the generation of

reactive oxygen species, which are mediators of inflammation

(37–40). Air pollution may also have an adjuvant effect with

common allergens that favors the development of a T helper cell 2

response, a hallmark of allergic asthma (41, 42). Finally, these

pollutants may also directly increase inflammation by enhancing

mast cell degranulation and cytokine release (43, 44).

Emerging evidence indicates that individual variation in the

inflammatory response to oxidative stress is important in the

pathogenesis of asthma associated with oxidant air pollutants (45).

Chronic psychological stress may modulate the response to oxidative burden, possibly due to the development of hypothalamicpituitary-adrenal axis hyporesponsiveness resulting in a shift toward

a proinflammatory T helper cell 2 phenotype (22, 29, 46). Therefore, an increase in oxidative stress and associated inflammatory

response is 1 possible explanation for the stronger associations of air

pollution and tobacco smoke with asthma in children with chronic

psychological stress. Chronic psychological stress may also explain

the larger effects of air pollution in individuals of lower SES

reported elsewhere (19), as low SES is associated with more

stressful environments (47).

In utero exposure to tobacco smoke has been found to increase

the risk of asthma in several studies including a limited number of

Table 2. Associations of traffic-related pollution (TRP) with incident asthma, by parental education and parental stress

Risk factor Stratum N (%)* Mean (SD)†

25th–75th

percentile†

Hazard ratio

(95% confidence interval)‡

Interaction

P value§

TRP All subjects 2456 (100) 18.41 (16.04) 6.19–27.11 1.31 (1.07, 1.61)¶

Low parental education 1845 (78.4) 20.36 (17.15) 7.53–29.24 1.55 (1.09, 2.19)¶ 0.25

High parental education 507 (21.6) 17.79 (15.58) 5.71–26.48 1.20 (0.93, 1.55)

High parental stress 1179 (50.7) 18.99 (16.42) 6.85–27.61 1.51 (1.16, 1.96)¶ 0.05

Low parental stress 1145 (49.3) 17.81 (15.79) 5.76–26.90 1.05 (0.74, 1.49)

*Denominator varies due to missing data about TRP, parental education and parental stress.

†TRP in parts per billion NOx.

‡All models are adjusted for race/ethnicity with baseline strata for age and gender and community random effects. Hazard ratios and 95% confidence intervals

are scaled across the interquartile range of exposure to TRP in all subjects (21 ppb).

§P value based on the 2 statistic using the likelihood ratio test to compare a model with base terms only to a model also containing the multiplicative interaction

term. Interactions involving parental stress are based on a continuous variable describing the PSS.

¶Indicates P value  0.05.

0.00

0.50

1.00

1.50

2.00

2.50

1 2 3 4

Parental Stress Quartile

Hazard Ratio (95% Confidence Interval)

Fig. 1. Effect of traffic-related pollution

on incident asthma across parental stress

quartiles.

12408  www.pnas.orgcgidoi10.1073pnas.0812910106 Shankardass et al.
prospective studies (4, 18, 48). Although the main effect of this

exposure was not statistically significant by itself, our results suggest

that oxidant pollutant exposures to tobacco smoke early in life may

have increased the susceptibility to later asthma onset due to effects

of co-exposure to stress and to factors associated with low parental

education. Differences in susceptibility to effects of SHS at the time

of study entry were less marked. However, the strong effect of in

utero or early life tobacco smoke exposure on subsequent asthma

is consistent with previous findings from the CHS and elsewhere (4,

14, 49–52). In utero exposure leads to more direct exposure to, and

possibly a higher dose of, combustion products of tobacco than

second hand exposure during an especially vulnerable period of

lung development.

Although the rates of maternal smoking during pregnancy in our

study sample (6.3%) were somewhat lower than in the greater

California population (9.5%) (53), this was largely explained by the

exclusion by design of participants with wheeze at study entry, who

had a higher rate of maternal smoking in utero (11.3%) than our

longitudinal study sample. Lower rates of maternal smoking during

pregnancy were observed in low (3.2%) than in high SES subjects

(7.3%; see Table 3), which is opposite to the relationship reported

elsewhere (54). This may be explained by the large proportion of

Hispanics in our population who were of low SES (35.0%) compared with non-Hispanic subjects (4.0%), and the low rates of

smoking during pregnancy among Hispanic (2.9%) compared with

non-Hispanic mothers (10.8%). However, we found no evidence

that Hispanic ethnicity explained the increased risk of asthma

associated with the joint exposure to stress (or SES) and to in utero

tobacco smoke. Although these results are consistent with the

robust joint effects of TRP exposure and stress, the effects of in

utero tobacco smoke exposure should be interpreted with caution

due to small sample size in some strata of exposure and the low

smoking rates among the largest ethnic group in our cohort.

Our results may not be generalizable to age groups beyond our

primary school age range as risk factors for asthma, including atopy

and the effect of variation in genes involved in modulating the

response to oxidative stress, depend on age of asthma onset (55, 56).

In addition, children’s responses to psychological stress are agedependent. For example, preschool children in a stressful situation

are more likely to seek support from a caregiver, intervene by

hitting someone, or play as a distracting behavior. School children

are more likely to seek support from friends, to have developed

cognitive and behavioral intervention strategies based on talking,

and to have other problem solving skills less dependent on parents

(57). Therefore, the relationship between psychological stress, air

pollution exposure, and asthma might not be the same at different

ages.

Differences in susceptibility by gender that we observed may

reflect differences in the development of asthma, because boys tend

to experience asthma onset earlier in childhood than girls (58). On

the other hand, boys in our study may have been more likely to be

negatively affected by parental stress than girls. In particular, boys

may be more sensitive to dysphoria (e.g., mood disorders, sadness)

in parents compared to girls (59). Also, there may be differences in

behavioral responses to stress between males and females; for

example, it has been suggested that girls tend to seek social support

when responding to stress, while the reflexive ‘‘fight-or-flight’’

response may be more predominant among boys (60).

Case ascertainment was done by parental report of physiciandiagnosed asthma without clinical examination, which is widely

used in epidemiological studies (61), is reproducible (62, 63), and is

a valid measure of what physicians actually report to patients (64,

65). Examinations of stress and asthma using cross-sectional measurement have limitations, because sick children may cause stress in

parents. However, the prospective study design and the restriction

at baseline to children with no history of wheeze makes it unlikely

that parental stress at study baseline resulted from earlier undiagnosed asthma. Also, in a sensitivity analysis, we excluded cases

occurring during the first year of follow-up and the pattern of effects

of stress and TRP was not substantially changed. Physician diagnosis of asthma is a relatively specific but somewhat insensitive

method of detection of incident asthma and may be subject to bias

due to access to care or to differences in assessment between

physicians. Therefore, we also examined the effects of stress and

TRP on new onset asthma based on either new report of physician

diagnosis or first report of severe symptoms suggestive of asthma (4

or more attacks of wheeze, 1 or more nights per week of wheeze,

or wheeze with shortness of breath so severe as to interfere with

speech). There were 52 new cases of asthma added using this

definition. We found a similar pattern of effects, suggesting that

diagnostic bias or access to care did not explain our results.

Mean levels of TRP were higher among subjects with higher

parental stress and lower parental education, although the ranges

of exposure in these strata overlapped. If the main effect of TRP on

asthma onset was nonlinear, e.g., quadratic, then the larger effects

of TRP observed among subjects with higher parental stress may

have reflected exposure to higher levels of TRP. However, a

previous analysis found the main effect of TRP on asthma onset was

linear over the range of exposure (5), which suggests that the

stress-related TRP susceptibility was not simply a reflection of

larger effects of TRP at higher exposure levels.

Parental stress measured with the PSS was 1 of the few indicators

available for assessment of psychological stress in a large population-based survey of young school children. Although we did not

directly measure stress in the children, previous research has

demonstrated a relationship between parental, especially maternal,

stress and psychological stress in children (66, 67). When we limited

the analysis to children whose biological mother responded to the

baseline questionnaire (81% of subjects), the interaction between

TRP and parental stress grew stronger (interaction term HR 1.41

versus 1.36 in the total sample). The effect of TRP in high maternal

stress children was 2.04 (95% CI 1.31–3.16) and was 0.84 (95% CI

0.50–1.40) in children of low maternal stress. These results are

consistent with the intensive caregiving role that mothers traditionTable 3. Associations of in utero tobacco smoke with incident asthma, by parental education and parental stress

Risk factor Stratum N (%)*

Hazard ratio

(95% confidence interval)† Interaction P value‡

Maternal smoking in utero All subjects 156 (6.3) 1.49 (0.79, 2.80)

Low parental education 16 (3.2) 5.69 (1.88, 17.3)§ 0.03

High parental education 137 (7.3) 1.10 (0.51, 2.41)

High parental stress 89 (7.5) 2.66 (1.33, 5.33)§ 0.03

Low parental stress 62 (5.4) 0.30 (0.04, 2.18)

*Denominator varies due to missing data about maternal smoking in utero, parental education and parental stress. †All models are adjusted for race/ethnicity with baseline strata for age and gender and community random effects. ‡P value based on the 2 statistic using the likelihood ratio test to compare a model with base terms only to a model also containing the multiplicative interaction

term. Interactions involving parental stress are based on a continuous variable describing the PSS.

§Indicates P value  0.05.

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ally play during childhood (68). Parental PSS in other studies

predicted asthma-related outcomes in children prospectively. For

example, high parental stress measured in the months immediately

following birth predicted increased severity of asthma and onset of

wheeze among children (27, 69). The joint effects of stress and

traffic or tobacco smoke exposure were not examined in these

studies.We observed little effect of stress in the absence of exposure

to oxidant pollutants, so it is possible that the children in these

studies were in high pollution environments or that the effect of

stress varies by age, requiring co-exposure to oxidant pollutants in

children of school age, but not in younger children.

This study provides evidence that parental stress increases

susceptibility to new onset childhood asthma associated with

traffic-related air pollution. The similarity in the pattern of

susceptibility to maternal smoking in utero suggests that

biological pathways common to the response to combustion

products may explain this susceptibility. Further study is

warranted to evaluate the role of stress induced by characteristics of life in low SES environments as a potential explanation

for disparities in the health impact of air pollution observed in

low SES populations. More broadly, understanding the role of

air pollution in the causation of complex diseases like asthma

requires consideration of how social factors may modify the

effects of environmental exposures.

Materials and Methods

Study Population. The CHS cohort enrolled students in kindergarten and first

grade (ages 5–9) from participating schools in 13 southern California communities in 2002 and 2003 (11). All students in kindergarten and first grade at selected

schools in the 13 study communities were invited to participate, and 5,349 (65%)

returned valid questionnaires. In order to remove subjects with previously undiagnosed asthma from follow-up, children were excluded if they had a history of

physician diagnosed asthma at study entry (715), a history of wheezing episodes

(1,505), and missing or ‘‘don’t know’’ responses about history of asthma (397) or

wheeze (261). Of the 3,372 children classified as ‘‘disease free’’ at baseline, 340

children had no information about residential TRP because their home address

could not be geo-coded, and another 535 children were lost before 1 year of

follow-up. Therefore, the study population for this analysis included 2,497 children with no history of asthma or wheeze at study entry. Informed consent was

obtainedfromparents,andthestudywasapprovedbytheUniversityofSouthern

California Institutional Review Board.

Assessment of New Onset Asthma and Covariates. Assessment of new onset

asthma and covariates was based on questionnaires at study entry and annually

during follow-up by parents of children enrolled in the study. Children with new

onset asthma were identified by parental report of physician-diagnosed asthma

onannualquestionnairesduring3yearsoffollow-up.HouseholdexposuretoTRP

was assessed based on a line source dispersion model of total NOX (see below),

and information was collected at study entry from responses given by parents on

a baseline questionnaire about in utero exposure to tobacco smoke. Variables

describing potential effect modifiers were also measured from responses on the

baseline questionnaire. Educational attainment in parents was used as a measure

of SES. The PSS, which was used to measure parental stress, has been validated as

ameasureofnegativeaffectivestatesandphysicalsymptomsofstress(70,71).We

used a 4-item version of the scale that has been previously used to predict

incidence of wheeze in children (26, 27). Items included: ‘‘In the last month, how

often have you felt’’: (i) ‘‘that you were unable to control the important things in

your life;’’ (ii) ‘‘confident about your ability to handle your personal problems;’’

(iii) ‘‘that things were going your way;’’ and (iv) ‘‘your difficulties were piling up

so high that you could not overcome them.’’ Each item is scored on a scale of 0–4,

and the PSS gives equal weight to each item, resulting in scores ranging from 0 to

16. A representative U.S. sample found an overall mean and standard deviation

of 4.49 and 2.96, respectively (32).

Potential confounders in this study were defined as variables that could

plausibly explain increased effects of TRP or in utero exposure to tobacco smoke

on new onset asthma in subjects with lower SES or with higher parental stress.

Covariatesconsideredaspotentialconfoundersinthisstudyweremeasuredfrom

responses given by parents on the baseline questionnaire at study entry. In

addition to race and ethnicity, English- or Spanish-language questionnaire response was recorded for each subject. Characteristics of the child’s current residence included mold or mildew on household surfaces, history of water damage

or flooding, presence of a musty odor, history of cockroaches and other pests, use

of a gas stove, air conditioner, humidifier or vaporizer, carpet in the child’s

bedroom, type of dwelling, and whether the child lived at another dwelling for

more than 50 days per year. Exposure to SHS was assessed by asking whether

anyone currently living in the child’s home smoked cigarettes, cigars, or pipes

inside the home on a daily basis. Type of medical insurance coverage, history of

chest-related illness and allergies, and family history of asthma were reported,

and body mass index was calculated based on measurements of height and

weight at study baseline using the Centers for Disease Control and Prevention

gender-specific body mass index-for-age reference values for the year 2000.

Accordingly, subjects with a body mass index below the 5th percentile of the

reference values were classified as underweight, while those between 85th and

95th percentile were at risk for becoming overweight, and those above the 95th

percentile were overweight.

Air Pollution Exposure Assessment. Methods to estimate exposure to local TRP in

this cohort have been described elsewhere (11). Briefly, household exposure to

total NOX from traffic on local roads was estimated as a marker for pollutants

from traffic exhaust using the CALINE4 dispersion model (31). Estimates of TRP

representedannualaverageincrementalincreasesduetoprimaryemissionsfrom

local vehicular traffic independent of background ambient levels (11). Because

there was a high correlation between measures of TRP and other pollutants

generated using the same model (e.g., carbon monoxide, nitrogen dioxide,

elemental and organic carbon, and particulate matter with aerodynamic diameter less than 10 and less than 2.5 g/m3) (R 0.90), measures of TRP represented

not only primary local NOX from vehicular traffic, but a mixture of other pollutants related to near-source traffic exposure (11).

Statistical Methods. Risk factors for asthma onset were assessed using multilevel

Cox proportional hazards models (72). All models contained age and gender

stratifications of the baseline hazard, adjustment for race and ethnicity, and

random effects for community of residence, which allowed for clustering and

assessment of residual community variation in time to asthma onset. Analyses

were conducted using R software (73) and software designed to run within R for

implementing random effects Cox proportional hazards models (72, 74). The

multilevel Cox proportional hazards model took the following form:

hij (t)  h0s(t) j exp(Xij  TZij);

hij(t): hazard function for the ith subject in jth community;

h0s(t) : the baseline hazard function for stratum s(i.e., age at study entry and

gender);

j : positive random effects for community j with expectation 1 and variance

2;

Zij : risk factors (e.g., race and ethnicity) for individual i in community j; and

Xij : TRP or maternal smoking in utero for individual i in community j.

Modification of the effect of TRP and maternal smoking during pregnancy by

SES and parental stress was assessed by modeling multiplicative interaction terms

along with base terms. We evaluated confounding of pollutant interactions with

parental stress using a 2-step process. For example, for TRP, all relevant covariates

were first screened for 2-way interactions with TRP on asthma onset using an

alpha level of 0.20. Second, the 2-way interaction models for parental stress with

TRP were co-adjusted for relevant interactions from the first step (i.e., P  0.20),

and confounding was identified where the coefficient for the stress-specific

interaction term was changed by more than 10%.

ACKNOWLEDGMENTS. This work was supported by National Institute of EnvironmentalHealthSciencesGrants5R03ES014046,1R01ES016535,5P01ES009581,

5P01ES011627, and 5P30ES007048; U.S. Environmental Protection Agency Grants

R831845, RD831861, and R826708; National Cancer Institute Grant

1U54CA116848- 01; the Hastings Foundation; and the Canadian Institutes of

Health Research.

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