668 volume 117 | number 4 | April 2009 • Environmental Health Perspectives

Research | Children’s Health

Asthma is one of the most prevalent chronic 

health conditions in Canadian children. The 

1998–1999 National Population Health 

Survey found that the prevalence of physician-diagnosed asthma is 8.4% among the 

whole population and 10.7% among children 

and teenagers, corresponding to approximately 845,000 children (Canadian Institute 

for Health Information et al. 2001). Asthma 

compromises the quality of life for patients 

and their families and imposes a burden on 

the nation’s health care expenditure. In 1990, 

the economic costs of asthma for Canada 

were estimated to fall between $504 and $648 

million (Krahn et al. 1996).

Epidemiologic studies have shown that 

air pollution is associated with asthma-related 

increases in hospital admissions (Burnett 

et al. 1999; Wong et al. 2001), emergency 

department visits (Stieb et al. 2000; Sunyer 

et al. 1997; Villeneuve et al. 2007), and 

respiratory symptoms (Brauer et al. 2002; 

Vichit-Vadakan et al. 2001), and decreases 

in pulmonary function (Delfino et al. 2004; 

Gielen et al. 1997). However, there is a dearth 

of information about whether these associations can be attributed to lung tissue injury in 

an asthmatic population, partly because of the 

lack of appropriate non-invasive biomarkers 

indicating lung inflammation and tissue 

injury. In recent years, some researchers have 

used fractional exhaled nitric oxide (FeNO) to 

investigate the relationship between exposure 

to air pollutants and airway inflammation 

(Delfino et al. 2006; Mar et al. 2005). 

Measurements of mediators in exhaled 

breath condensate have been used to better 

understand the pathological mechanisms of airway diseases such as asthma, chronic obstructive 

pulmonary disease, and cystic fibrosis (Horvath 

et al. 2005; Montuschi 2005). Recently, analysis of mediators in condensed breath has been 

extended to include lung diseases caused by 

occupational exposure (Lehtonen et al. 2007; 

Pelclová et al. 2007). Asthma is a chronic airway inflammatory disease involving a variety 

of inflammatory cell types and proinflammatory mediators. Reactive oxygen species are 

also thought to play an active role in inducing 

airway inflammation and hyperresponsivness 

(Hulsmann et al. 2007). Reactive oxygen species 

result from an increased burden of exogenous 

oxidants, endogenous lipid peroxidation, as 

well as from inflammatory cells (Halliwell and 

Gutteridge 1989). The level of reactive oxygen 

species in the airways can be determined by 

assaying concentrations of oxidative stress markers in breath condensate (Horvath et al. 2005).

We designed this longitudinal study to 

test the hypothesis that an acute increase 

in ambient air pollutants is associated with 

increased levels of markers of oxidative stress 

and inflammation in breath condensate of 

children with asthma, and that changes of 

breath markers are consistent with changes in 

pulmonary function and FeNO.

Materials and Methods

Study subjects. The study protocol was 

approved by the Research Ethics Board of 

Health Canada. The parent of each child gave 

written informed consent before the child’s 

participation in this study.

The study was conducted between 

October and December of 2005 in Windsor, 

Ontario, Canada. Asthmatic children, 9 to 

14 years of age, from nonsmoking households, 

were identified from a questionnaire survey 

of grades one to eight of elementary schoolchildren whose parents were asked whether or 

not the child had doctor-diagnosed asthma. 

The parents who gave a positive response were 

telephoned to confirm the child’s current status of doctor-diagnosed asthma and whether 

there was any smoking of tobacco products 

in the household. One hundred eighty two 

subjects agreed to participate in this longitudinal study. Information on family income and 

family asthma history was extracted from the 

survey questionnaire. For logistical purposes, 

children were studied in two test periods, 

either between 11 October and 11 November 

(95 children), or between 14 November and 

9 December 2005 (87 children). We did not 

advise parents to alter their children’s daily 

activity and the use of asthma medications.

Ambient air pollution monitoring. Hourly 

measures of particulate matter ≤ 2.5 μm in 

Address correspondence to L. Liu, Health Canada. 

A.L. 4903B, 269 Laurier Ave., Ottawa, Ontario, 

Canada K1A 0K9. Telephone: (613) 954-4457. Fax: 

(613) 948-8482. E-mail: ling_liu@hc-sc.gc.ca

Supplemental Material is available online at http://

www.ehponline.org/members/2008/11813/suppl.pdf

We gratefully acknowledge S. De Pauw of Health 

Canada for coordinating the study, B. Nadeau and 

K.L. Ku for running laboratory assays, M. SmithDoiron for preparing the map, and D. Stieb and 

P. Villeneuve for reviewing the manuscript. 

This study was funded by the Canada-the United 

States Border Air Quality Strategy.

The authors declare they have no competing 

financial interests.

Received 17 June 2008; accepted 28 November 2008.

Acute Effects of Air Pollution on Pulmonary Function, Airway Inflammation, 

and Oxidative Stress in Asthmatic Children

Ling Liu,1 Raymond Poon,1 Li Chen,1 Anna-Maria Frescura,1 Paolo Montuschi,2 Giovanni Ciabattoni,2

Amanda Wheeler,1 and Robert Dales1

1Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada; 2Department of Pharmacology, Faculty 

of Medicine, Catholic University of the Sacred Heart, Rome, Italy

Background: Air pollution is associated with respiratory symptoms, lung function decrements, and 

hospitalizations. However, there is little information about the influence of air pollution on lung injury. 

Objective: In this study we investigated acute effects of air pollution on pulmonary function and 

airway oxidative stress and inflammation in asthmatic children.

Methods: We studied 182 children with asthma, 9–14 years of age, for 4 weeks. Daily ambient concentrations of sulfur dioxide, nitrogen dioxide, ozone, and particulate matter ≤ 2.5 μm 

in aerodynamic diameter (PM2.5) were monitored from two stations. Once a week we measured 

spirometry and fractional exhaled nitric oxide (FeNO), and determined thiobarbituric acid reactive 

substances (TBARS) and 8-isoprostane—two oxidative stress markers—and interleukin-6 (IL-6) 

in breath condensate. We tested associations using mixed-effects regression models, adjusting for 

confounding variables.

Results: Interquartile-range increases in 3-day average SO2 (5.4 ppb), NO2 (6.8 ppb), and PM2.5

(5.4 μg/m3) were associated with decreases in forced expiratory flow between 25% and 75% of forced 

vital capacity, with changes being –3.1% [95% confidence interval (CI), –5.8 to –0.3], –2.8% (95% 

CI, –4.8 to –0.8), and –3.0% (95% CI, –4.7 to –1.2), respectively. SO2, NO2, and PM2.5 were associated with increases in TBARS, with changes being 36.2% (95% CI, 15.7 to 57.2), 21.8% (95% CI, 

8.2 to 36.0), and 24.8% (95% CI, 10.8 to 39.4), respectively. Risk estimates appear to be larger in 

children not taking corticosteroids than in children taking corticosteroids. O3 (5.3 ppb) was not associated with health end points. FeNO, 8-isoprostane, and IL-6 were not associated with air pollutants. 

Conclusion: Air pollution may increase airway oxidative stress and decrease small airway function of 

asthmatic children. Inhaled corticosteroids may reduce oxidative stress and improve airway function.

Key words: air pollution, asthma, children, exhaled breath condensate, inflammation, oxidative 

stress, pulmonary function. Environ Health Perspect 117:668–674 (2009). doi:10.1289/ehp.11813 

available via http://dx.doi.org/ [Online 28 November 2008]
Air pollution is linked to lung injury in asthmatic children

Environmental Health Perspectives • volume 117 | number 4 | April 2009 669

aerodynamic diameter (PM2.5), sulfur dioxide, 

nitrogen dioxide, and ozone were available 

from the National Air Pollution Surveillance 

network of Environment Canada (http://www.

etc-cte.ec.gc.ca/NapsData). There were two 

monitoring stations representing Windsor, 

located upwind from the prevailing winds. Of 

182 participating children, 180 of them lived 

within a 10-km radius from the air monitoring 

sites, and one lived 12 km and another 17 km 

from the air sampling sites (Figure 1). Values 

from these two monitors were averaged. SO2

was measured using ultraviolet fluorescence 

and the electrical conductivity from changes in 

chemical composition of a bromine solution, 

NO2 measured using chemiluminescence, O3

measured using ultraviolet absorbance, and 

PM2.5 measured using tapered element oscillating microbalance monitor. Pollutant concentrations were averaged over a 24-hr period. 

Measurement of spirometry and FeNO. 

Once a week, registered respiratory technologists visited the children’s schools, and 

conducted tests of spirometry and FeNO and 

collected exhaled breath condensate on study 

participants. These tests were run on the same 

day of the week for each child.

Spirometry was performed according to 

American Thoracic Society criteria (American 

Thoracic Society 1995). KoKo Spirometers

(Ferraris CardioRespiratory; Pulmonary Data 

Services, Inc. Louiseville, CO, USA) were calibrated daily and results adjusted for temperature and barometric pressure. A maximum 

of eight forced vital capacity (FVC) maneuvers were carried out in an attempt to achieve 

three acceptable flow-volume loops and two 

being within 0.20 L for FVC and forced expiratory volume in one second (FEV1), and 

within 0.20 L/sec for the mean forced expiratory flow between 25% and 75% of the FVC 

(FEF25–75%). The value assigned to the child 

was the largest acceptable value within 200 

mL of a second value.

Single-breath on-line measures of FeNO

were carried out according to American 

Thoracic Society and European Respiratory 

Society Guidelines (American Thoracic 

Society 2005) using an Eco Physics CLD 

AL MED chemiluminescence analyzer (Eco 

Medics AG, Duernten, Switzerland). Before 

performing a slow vital capacity maneuver 

over at least 6 sec at 0.05 L/sec, subjects took 

three tidal volume breaths through a DENOX 

88 (Eco Medics AG, Duernten, Switzerland) 

which contains an NOx absorber cartridge to 

scrub the ambient air to a value of between 

0 and 1.5 ppb. The test was repeated a maximum of eight times in an attempt to obtain 

at least two acceptable plateau FeNO values 

within 10%. The value assigned to the subject 

was the mean of the two values. We calculated 

FeNO statistics using spiroWare 88 software 

(Eco Medics AG, Duernten, Switzerland). 

Collection of exhaled breath condensate, 

and measurement of amylase, oxidative stress, 

and inflammation. Exhaled breath condensate 

was collected using an RTube (Respiratory 

Research Inc., Charlottesville, VA, USA). 

Participants sat and breathed at tidal volumes orally into a mouthpiece attached to a 

cold condenser, for 10 min. Approximately 

1 mL of breath condensate was collected. The 

condensed breath was then transferred into 

a microtube and stored at –20°C and then 

–80°C until use.

To determine saliva contamination, we 

measured α-amylase activity in breath condensate using an assay kit (Pointe Scientific, MI, 

USA), which follows the increase in absorbance 

at 405 nm as the artificial substrate 2-chloro-pnitrophenyl-α-d-maltotrioside is hydrolyzed. 

Thiobarbituric acid reactive substances 

(TBARS) were determined in duplicate by 

a fluorescence method adapted from Yagi 

(1982). We used malonaldehyde bis-(dimethyl 

acetal) (Aldrich Chemical Co., Milwaukee, 

WI, USA) to construct a standard curve. To 

reduce the background interference with the 

very low levels of TBARS present in exhaled 

breath condensates, all glassware was washed 

in soap-free detergent followed by rinsing 

with distilled water and ethanol before use. 

We used butanol (OmniSolv, 99.95%; EM 

Science, Darmstadt, Germany) for extraction. 

The n-butanol extract was transferred to a 

Whatman glass bottom microplate (Whatman, 

NJ, USA), previously washed with ethanol, 

and the fluorescence measured at 530 nm/590 

nm, excitation/emission, with a Cytofluor 

2350 reader (Millipore, Billerica, MA, USA). 

The detection limit was 0.02 μM (three times 

the standard deviation above the blank). The 

within-run coefficient of variation was 8%.

A colorimetric enzyme immunoassay kit 

(Cayman Chemical, Ann Arbor, MI, USA) 

was used to measure 8-isoprostane concentrations in breath condensate. The assays were 

done in triplicate. A modified standard curve 

for 8-isoprostane was established for concentrations between 0.975 and 62.5 pg/mL. We 

were able to detect 8-isoprostane at a concentration as low as 0.975 pg/mL (three times 

the standard deviation above the blank). The 

within-run coefficient of variation was 5%. 

We also measured 8-isoprostane on 8 random 

samples using radioimmunoassay, a procedure previously described by Montuschi et al. 

(2003), and compared the results from both 

methods [see Supplemental Material, Table 1 

(available online at http://www.ehponline.org/

members/2008/11813/suppl.pdf)]. Pearson 

correlation coefficient for results from two 

methods was 0.744 (p = 0.055), with a mean 

positive bias of approximately 35% in favor 

of the radioimmunoassay. Such a difference 

may be attributed to variations in the avidity 

and specificity of the antibodies used and the 

inherent variation during extrapolation from 

calibration curves at very low levels that were 

typical of exhaled breath condensates. 

We determined the level of interleukin-6 

(IL-6) using an ELISA kit from R&D Systems 

(Minneapolis, MN, USA). We conducted the 

ELISA assays in duplicate by following manufacturer’s instructions accompanying the kit. 

The detection limit was 0.48 pg/mL.

Statistical analysis. We analyzed the correlations among environmental factors, daily use 

of inhaled corticosteroids (ICS) or short-acting 

Figure 1. Map of Windsor, Ontario, Canada. 

Detroit

Windsor

Wind direction

60204

60211

Ambassador Bridge

Huron Church

E.C. Row Expressway

Highway 401

NAPS monitors

0 2 1 4 6 Children’s homes

Kilometers
Liu et al.

670 volume 117 | number 4 | April 2009 • Environmental Health Perspectives

β-agonist (SABA), and testing period, using 

Spearman rank order correlation, because 

some variables were not normally distributed. 

We used mixed-effects regression models to 

account for repeated measures and to analyze 

the associations between pollutants and health 

end points, assuming random slope and random intercepts, and accounting for intraindividual correlation using S-PLUS (version 6.1; 

Insightful Corporation, Seattle, WA, USA). 

Data for FeNO, TBARS, and 8-isoprostane 

were log-transformed to fit a normal distribution. Because > 99% of the samples gave a 

value > 0 for TBARS and 8-isoprostane, and 

most of them were above the detection limit, 

data points below the detection limit were not 

given special treatment. For exposure variables, 

we tested models for multiday moving averages to examine potentially delayed response. 

Models were adjusted for time-dependent 

covariates that were statistically associated with 

either the exposure or response. We adjusted 

for testing period (as an indicator variable) 

to reduce the impact of seasonality. We also 

included product terms for the interaction of 

pollutant concentrations with sex and with the 

use of ICS to test potential modifying effects 

of sex and ICS. Since subjects served as their 

own control, we did not adjust for factors 

which remained constant during the study 

period such as age, race, family income, and 

family asthma history. Because health testing 

was kept on the same day of week for each 

child, we did not adjust for the effect of dayof-week in the models. 

When interactions were detected between 

pollutants and sex or the use of ICS, the participants were stratified for further analyses. 

We also ran two-pollutant models to adjust 

for potential confounding effects of co-pollutants. Results were expressed as percent 

change in FEV1, FEF25–75%, FeNO, TBARS 

and 8-isoprostane nd 8-isoprostane per increase in inter- per increase in inter per increase in interquartile-range concentration of a pollutant. 

A two-tailed value of p ≤ 0.05 was considered 

statistically significant.

Results

A total of 182 asthmatic children participated 

in the study, for a total of 691 spirometry test 

results, 672 FeNO test results, and 616 breath 

samples. Seven children had 5 measurement 

days, 142 had 4 days, 27 had 3 days, and 6 had 

2 days. In total, there were 39 measurement 

days during the study period, and no missing 

day for air monitoring to match health testing 

days. The characteristics of this cohort are presented in Table 1. We measured the concentration of amylase in 25% of breath samples to 

determine saliva contamination. The median 

amylase concentration was 0.60 unit/L, with 

the 95th percentile being 1.46 unit/L. None 

of the samples had amylase concentrations 

near the reported salivary amylase concentration of 1,250 unit/L (Brand et al. 2006). We 

estimated that saliva contamination was likely 

< 0.1%, and therefore interference of breath 

analysis by saliva was negligible. In 616 breath 

samples, only 2 samples had detectable IL-6 

levels. We therefore did not conduct further 

analysis on IL-6. 

The environmental conditions and daily 

concentrations of air pollutants measured during the study period are presented in Table 2. 

Because Spearman rank order correlation 

analyses showed that daily temperature, relative humidity and testing period were significantly correlated with some of the pollutants 

(Table 3), we included these variables in models to adjust for any confounding/modifying 

effects. We also included daily use of SABA 

and ICS to adjust for their potential confounding effects. Because pollutants were correlated 

with each other (Table 3), we also ran twopollutant models to adjust for confounding.

Results from single-pollutant regression 

models. Table 4 presents percentage changes 

of health end points in relation to an increase 

in interquartile range concentrations of pollutants in a single-pollutant model which also 

included interaction terms of ICS and sex 

with pollutants. FEV1 and FEF25–75% exhibited a consistent trend of negative associations with all four pollutants, with FEF25–75%

Table 1. Selected characteristics of 182 asthmatic children from Windsor, Ontario, Canada.

Characteristic Value

Age (years) [median (range)] 11 (9–14)

Sex [no. (%)]

Female 68 (37.4)

Male 114 (62.6)

Race [no. (%)]

Caucasian 160 (87.9)

Other 22 (12.1)

Parental asthma [no. (%)]

No 11 (6.0)

Yes 70 (38.5)

Unknown 101 (55.5)

Self-reported medication usea [no. (%)]

ICS 68 (37.4)

SABA 64 (35.2)

Other asthma medications 33 (18.1)

None 77 (42.3)

FEV1 (L) [median (5th– 95th percentile)] 2.4 (1.7–3.3)

Percent predicted FEV1 (%) [median (5th– 95th percentile)]b 90.5 (68.6–107.1)

FEF25–75% (L/sec) [median (5th– 95th percentile)] 2.5 (1.3–3.9)

Percent predicted FEF25–75% (%) [median (5th– 95th percentile)]b 78.2 (45.3–118.0)

FeNO (ppb) [median (5th– 95th percentile)] 19.4 (4.5–81.6)

TBARS (μM) [median (5th– 95th percentile)] 0.26 (0.03–1.53)

8-Isoprostane (pg/mL) [median (5th– 95th percentile)] 1.43 (0.30–4.20)

aMore than one medication could be used. bPredicted normal values were calculated based on a given height, age, sex, 

and race/ethnicity (Hankinson et al. 1999).

Table 2. Values for selected environmental conditions during study period.

Median [interquartile range (5th–95th percentile)]

Environmental variable 1-day average 2-day average 3-day average

SO2 (ppb) 4.5 [6.5 (0.5 to 15.5)] 5.0 [5.6 (1.0 to 13.0)] 5.6 [5.4 (1.3 to 13.8)]

NO2 (ppb) 19.8 [9.8 (9.5 to 29.5)] 18.3 [9.0 (11.3 to 28.0)] 18.3 [6.8 (12.3 to 27.0)]

O3 (ppb) 13.0 [9.0 (6.5 to 26.5)] 14.1 [6.4 (6.8 to 23.3)] 14.0 [5.3 (7.5 to 21.0)]

PM2.5 (μg/m3) 6.5 [6.0 (2.0 to 19.0)] 6.6 [6.4 (2.0 to 15.0)] 6.9 [5.4 (2.7 to 14.3)]

Temperature (°C) 6.6 [13.0 (–7.7 to 15.4)] 7.4 [12.0 (–5.5 to 14.7)] 7.4 [11.2 (–5.9 to 14.5)]

Relative humidity (%) 67.4 [11.6 (53.3 to 87.9)] 65.6 [9.7 (54.4 to 75.6)] 65.7 [7.3 (54.9 to 74.2)]

Air quality was monitored between 8 October and 9 December 2005, 62 sampling days.

Table 3. Spearman rank order correlation coefficients of variables.

Relative

Variable Temperature humidity SO2 NO2 O3 PM2.5 SABA ICS

Testing period –0.73* 0.01 0.35* –0.30* 0.06 –0.07 0.10* –0.07

Temperature 0.18* –0.17* 0.00 0.18* 0.10* –0.10* –0.02

Relative humidity –0.04 0.03 –0.51* 0.20* 0.01 –0.02

SO2 0.18* –0.02 0.56* 0.04 0.05

NO2 –0.51* 0.71* –0.04 0.07

O3 –0.41* 0.00 –0.10*

PM2.5 –0.05 0.07

SABA 0.27*

*p < 0.05.
Air pollution is linked to lung injury in asthmatic children

Environmental Health Perspectives • volume 117 | number 4 | April 2009 671

having a statistically significant association 

with NO2 and PM2.5. The significant associations for FEF25–75% persisted for at least 

3 days. FeNO had a trend of positive associations with SO2, NO2, and PM2.5, but the 

associations were not statistically significant. 

FeNO had a statistically significant negative 

association with O3. TBARS was significantly 

positively associated with SO2, NO2, and 

PM2.5, but not with O3. The associations for 

TBARS persisted for at least 3 days. 8-Isoprostane was significantly positively associated 

with same-day SO2, but not associated with 

other pollutants.

Modifying effects by the use of ICS and 

sex. Product terms between pollutants and the 

use of ICS showed significant interactions for 

some of the health end points. For example, 

the product term for SO2 and ICS was positively associated with TBARS (p = 0.04), but 

negatively associated with FEV1 (p < 0.01), 

FEV25–75% (p = 0.02), and 8-isoprostane (p

= 0.01), indicating that the use of ICS was a 

significant effect modifier. The participants 

were then stratified by the use of ICS during the study period to adjust for modifying 

effects of use of ICS (Figure 2). Children who 

did not use ICS appeared to have larger risk 

estimates for pollutants than did those who 

used ICS. Among children not taking ICS, 

risk estimates for pollutants were statistically 

significant with respect to FEV1, FEF25–75%, 

and TBARS. Risk estimates for FeNO and 

8-isoprostane were not very different between 

the two groups of children (data not shown).

Product terms for pollutants and sex 

showed no significant interaction (p > 0.05), 

suggesting that sex was not a significant modifier for the associations between air pollutants 

and health end points. We therefore did 

not run further analysis on boys and girls 

separately.

Results from two-pollutant models. 

Because we found consistent associations with 

pollutants for FEV1, FEF25–75%, FeNO, and 

TBARS, we ran two-pollutant models on 

these end points to adjust for confounding 

effects of co-pollutants (Figure 3). For FEV1 

and FEF25–75%, although two-pollutant models did not result in marked changes in risk 

estimates for PM2.5 and O3, including PM2.5

in models did somewhat change risk estimates for SO2 and NO2, suggesting that the 

effects of SO2 and NO2 on pulmonary function were influenced by PM2.5. For FeNO and 

TBARS, including two pollutants in models 

did not markedly change the regression results, 

Table 4. Percent change (95% confidence interval) in health end points of 182 asthmatic children, in association with an interquartile-range increase of a pollutant, in single–pollutant models with various lag times. 

Air pollutant FEV1 FEF25–75% FeNO TBARS 8–Isoprostane

SO2

Same day –0.3 (–1.3 to 0.7) –1.0 (–3.1 to 1.3) 5.8 (–5.0 to 17.8) 17.4 (0.3 to 37.4)* 14.1 (2.5 to 26.9)*

Lag 1 day 0.1 (–1.1 to 1.2) –0.9 (–3.1 to 1.4) 1.6 (–9.3 to 13.9) 14.1 (–1.8 to 32.5) –2.4 (–11.7 to 7.9)

2-day average –0.1 (–1.4 to 1.3) –1.8 (–4.7 to 1.1) 5.9 (–9.3 to 23.7) 35.1 (9.5 to 66.8)* 9.4 (–5.2 to 26.2)

3-day average –0.3 (–1.9 to 1.4) –2.3 (–5.5 to 1.0) 1.7 (–14.1 to 20.3) 61.8 (24.9 to 109.5)* –0.3 (–16.4 to 18.9

NO2

Same day –0.6 (–1.6 to 0.3) –2.4 (–4.3 to –0.4)* 8.2 (–2.9 to 20.6) 21.2 (1.9 to 44.2)* 0.0 (–10.7 to 12.1)

Lag 1 day –0.3 (–1.1 to 0.6) –1.4 (–3.1 to 0.3) 3.7 (–6.1 to 14.6) 10.2 (–5.6 to 28.7) –5.6 (–14.8 to 4.5)

2-day average –0.6 (–1.6 to 0.4) –2.4 (–4.3 to –0.3)* 7.4 (–4.6 to 21.0) 20.3 (–0.4 to 45.3) –4.7 (–1.1 to 8.1)

3-day average –0.8 (–1.9 to 0.3) –2.8 (–5.0 to –0.5)* 0.5 (–12.1 to 14.9) 32.9 (7.2 to 64.6)* –4.0 (–16.3 to 10.2)

O3

Same day –0.4 (–1.6 to 0.7) 0.2 (–2.1 to 2.5) –12.2 (–22.3 to –0.8)* 5.0 (–13.2 to 27.0) 7.0 (–6.5 to 22.4)

Lag 1 day –0.2 (–1.1 to 0.7) 0.1 (–1.7 to 1.9) –8.3 (–16.0 to 0.2) 7.3 (–6.7 to 23.4) 6.6 (–3.4 to 17.6)

2-day average –0.4 (–1.6 to 0.9) 0.4 (–2.2 to 3.0) –16.0 (–26.4 to –4.1)* 14.4 (–8.5 to 43.0) 12.0 (–3.8 to 30.5)

3-day average –0.5 (–2.0 to 1.0) –0.4 (–3.5 to 2.7) –1.6 (–16.7 to 16.1) 8.8 (–17.4 to 43.4) 15.9 (–3.5 to 39.1)

PM2.5

Same day –0.5 (–1.3 to 0.3) –1.9 (–3.5 to –0.3)* 5.3 (–3.6 to 15) 16.9 (2.2 to 33.6)* 5.1 (–3.6 to 14.5)

Lag 1 day –0.3 (–1.1 to 0.5) –1.2 (–2.8 to 0.3) 1.7 (–6.3 to 10.4) 14.6 (0.8 to 30.4)* –3.8 (–12.1 to 5.3)

2-day average –0.6 (–1.5 to 0.4) –2.0 (–3.8 to –0.2)* 4.3 (–5.4 to 15.1) 22.0 (4.8 to 42.1)* 0.1 (–9.8 to 11.1)

3-day average –1.1 (–3.1 to 0.9) –3.3 (–7.2 to 0.8) –17.3 (–33.5 to 2.9) 69.1 (20.1 to 138.2)* 5.8 (–15.8 to 33.0)

2-day average: the median concentration of a pollutant collected on the day and 1 day before the clinical testing was done. 3-day average: the median concentration of a pollutant collected on the day and 2 days before the clinical testing was done. Models were adjusted for testing period, daily temperature, relative humidity, and use of SABA and ICS. Interaction 

terms were included in the models to test modifying effects of taking ICS (a binary indicator) and sex (binary indicator) on air pollutants. 

*p < 0.05.

Figure 2. Percent changes and 95% confidence intervals in FEV1 (A), FEF25–75%(B), FeNO (C), and breath 

TBARS (D) of asthmatic children taking or not taking ICS during the study period, in association with an 

interquartile-range increase in a pollutant. Sixty-eight asthmatic children took (Yes), and 114 children did 

not take (No) ICS. Pollutant concentrations were averaged over 3 days including the same day and 2 days 

before the clinical testing was done. Models were adjusted for testing period, daily temperature, relative 

humidity, and use of SABA. 

8

6

4

2

0

–2

–4

–6

Percent change in FEV1

No No No No Yes Yes Yes Yes

SO2 NO2 PM2.5

No No No No Yes Yes Yes Yes

Percent change in FEF25–75%

12

8

4

0

–4

–8

SO2 NO2 O3 PM2.5

No No No No Yes Yes Yes Yes No No No No Yes Yes Yes Yes

Use of ICS Use of ICS

Use of ICS Use of ICS

Percent change in FeNO

Percent change in TBARS

SO2 NO2 O3 PM2.5 SO2 NO2 O3 PM2.5

80

60

40

20

0

–20

–40

120

100

80

60

40

20

0

–20

–40

A B

C D

O3
Liu et al.

672 volume 117 | number 4 | April 2009 • Environmental Health Perspectives

suggesting that the results of each pollutant 

were independent of other pollutants.

Discussion

Principal findings of this study are that SO2, 

NO2, and PM2.5 in ambient air were significantly associated with decrements in FEV1 and 

FEF25–75%, and increases in TBARS in breath 

condensate among children with asthma. The 

risk estimates were larger for pollutant concentrations averaged over 3 days than over a 

shorter term. Clinically FEF25–75% has been 

considered to be sensitive in detecting small 

airway dysfunction (Lebecque et al. 1993). 

These associations were robust after inclusion 

of daily temperature, relative humidity, study 

period, and the use of asthma medications 

SABA and ICS in models. The associations for 

O3 and PM2.5 were not sensitive to inclusion 

of co-pollutants, as adjusting for other pollutants in the model did not markedly change 

the strength of the risk estimates for O3 and 

PM2.5. The associations between pulmonary 

function decrements and SO2 and NO2 were 

sensitive to the inclusion of PM2.5 in models, 

suggesting that PM2.5 may have confounded 

some of the effects of SO2 and NO2. Adverse 

changes in FEF25–75% were consistent with 

those of TBARS in response to SO2, NO2, 

and PM2.5 with a similar lag structure, suggesting a coherent outcome for small airway 

function and oxidative stress. Our results on 

pulmonary function changes were similar 

to those published previously (Delfino et al. 

2004; Epton et al. 2008; Gielen et al. 1997; 

Romieu et al. 2008), although air pollutant 

levels in the present study were low compared 

to those studies.

Exhaled breath condensate has been 

used in clinical settings to study pathological mechanisms of respiratory illness such as 

asthma, chronic obstructive pulmonary disease, and cystic fibrosis (Baraldi et al. 2003; 

Horvath et al. 2005). Elevated concentrations of oxidant nitrate (Balint et al. 2001), 

IL-6 and leukotriene B4 (Carpagnano et al. 

2003), and 8-isoprostane (Montuschi et al. 

2000), have been found in breath condensate 

of adult smokers. Markers of inflammation 

and oxidative stress in breath were associated 

with occupational exposure to cobalt and 

tungsten (Goldoni et al. 2004), chromium 

(Caglieri et al. 2006), silica (Pelclová et al. 

2007), and asbestos (Lehtonen et al. 2007). 

Montuschi et al. (2002) exposed healthy 

nonsmoking adults to high concentration of 

O3 (400 ppb) and clean air for 2 hr on separate occasions in a laboratory setting, and 

reported that exposure to O3 led to a significant increase in 8-isoprostane concentrations 

in breath condensate. Barregard et al. (2008) 

exposed adult human subjects to wood smoke 

in a controlled environment and reported an 

increase in malondialdehyde levels in breath 

for at least 20 hr postexposure. However, little work has been done to use biomarkers in 

breath condensate to examine the effects of 

ambient air pollutants on airway inflammation and oxidative stress among asthmatic 

children. Very recently, Epton et al. (2008) 

reported a cohort study on 12- to 18-year-old 

male healthy and asthmatic students in a New 

Zealand boarding school, where they found 

small effects of PM10 (PM with aerodynamic 

diameter < 10 μm) in ambient air on FEV1, 

but no effect on pH and hydrogen peroxide 

in exhaled breath. However, with a panel of 

asthmatic children living in Mexico City, 

Romieu et al. found an association between 

malondialdehyde in exhaled breath and PM2.5

and O3 in ambient air (Romieu et al. 2008). 

A 14.2-μg/m3 (interquartile-range) increase 

in 8-hr moving average PM2.5 was significantly associated with a 1.12-nmol increase 

in malondialdehyde, while a 15.9-ppb (interquartile-range) increase in 8-hr moving average O3 was significantly associated with a 

1.16-nmol increase in malondialdehyde. Our 

results are consistent with these findings in 

that inhaled ambient air pollutants were significantly associated with an increase in an 

oxidative stress marker in breath condensate. 

Oxidative stress–inducing reactive oxygen 

species are physiologically active mediators 

that can be induced by air pollutants. PM2.5, 

SO2, NO2, and O3 have been demonstrated 

to cause formation of excessive amount of 

reactive oxygen species in airways and in the 

cardiovascular system in experimental animals, 

leading to tissue inflammation and cell death 

(Dye et al. 1997; Meng et al. 2003; Persinger 

et al. 2002). Oxidative stress has been linked 

to clinical phenotypes such as asthma and 

atherosclerosis (Chuang et al. 2007; Walter 

et al. 2004). TBARS are a group of lowmolecular-weight chemicals that are formed 

during the decomposition of lipid peroxidation products (Halliwell and Chirico 1993), 

and thus are often used as an index of lipid 

peroxidation and oxidative stress (Kodavanti 

et al. 2000; Rhoden et al. 2004; Walter et al. 

2004). 8-Isoprostane is a prostaglandin F2α–

like compound produced by free radicals via 

the nonenzymatic peroxidation of arachidonic 

acid in membrane phospholipids (Morrow 

et al. 1990). Because TBARS are derived 

from oxidative degradation of a broader range 

of biological substances including lipids and 

sugars than is 8-isoprostane (Halliwell and 

Gutteridge 1981; Janero 1990), and because 

we observed an increase in TBARS but not 

8-isoprostane in breath samples in relation to 

elevated air pollutants, it appears that TBARS 

may be a more sensitive biomarker than 8-isoprostane in breath condensate as a useful tool 

for investigating air pollution-related oxidative 

stress among asthmatic children, especially for 

acute exposures. It remains to be seen whether 

immunoassays with significantly higher sensitivity and specificity can improve the efficacy 

of 8-isoprostane as a biomarker of oxidative 

stress in exhaled breath condensate. 

ICS are thought to reduce inflammation and oxidative stress in airways (Baraldi 

et al. 2003; Khor et al. 2007). Children with 

asthma exacerbation have reduced 8-isoprostane in breath condensate after ICS treatment 

(Baraldi et al. 2003). In the present study, we 

found that ICS seems to be able to reduce 

some of the adverse effects of air pollutants, 

Figure 3. Percent changes and 95% confidence intervals in FEV1 (A), FEF25–75%(B), FeNO (C), and breath 

TBARS (D) of asthmatic children, in association with an interquartile-range increase in a pollutant, in oneand two-pollutant models. Pollutant concentrations were averaged over 3 days including the same day 

and 2 days before the clinical testing was done. Models were adjusted for testing period, daily temperature, relative humidity, and use of SABA and ICS. 

6

4

2

0

–2

–4

Percent change in FEV1

Single

SO2 NO2 O3 PM2.5

Percent change in FEF25–75% 12

8

4

0

–4

–8

SO2 NO2 O3 PM2.5 A B

C D + NO2 + O3 + PM2.5 Single + SO2 + O3 + PM2.5 Single + SO2 + NO2 + PM2.5 Single + SO2 + NO2 + O3 Single

+ NO2

+ O3

+ PM2.5

Single

+ SO2

+ O3

+ PM2.5

Single

+ SO2

+ NO2

+ PM2.5

Single

+ SO2

+ NO2

+ O3

Single

+ NO2

+ O3

+ PM2.5

Single

+ SO2

+ O3

+ PM2.5

Single

+ SO2

+ NO2

+ PM2.5

Single

+ SO2

+ NO2

+ O3

Single

+ NO2

+ O3

+ PM2.5

Single

+ SO2

+ O3

+ PM2.5

Single

+ SO2

+ NO2

+ PM2.5

Single

+ SO2

+ NO2

+ O3

40

30

20

10

0

–10

–20

–30

–40

Percent change in FeNO

SO2 NO2 O3 PM2.5

100

80

60

40

20

0

–20

Percent change in TBARS

–40

SO2 NO2 O3 PM2.5
Air pollution is linked to lung injury in asthmatic children

Environmental Health Perspectives • volume 117 | number 4 | April 2009 673

as the risk estimates appear to be larger for 

the children who did not take ICS during the 

study period. Consistent with our findings, 

previous studies have also reported stronger 

associations between exposure to air pollutants 

and decrements in pulmonary function and 

increases in FeNO for children not taking antiinflammatory medications than for children 

taking the medications (Delfino et al. 2006, 

2008; Mar et al. 2005). In the present study 

only 37% of children used ICS, which could 

result in a reduced statistical power to detect 

associations with pollutants in this group. 

Oxidative stress often occurs along with 

tissue inflammation, which induces the 

release of reactive oxygen species to cause tissue injury (Chuang et al. 2007; Dye et al. 

1997; Kodavanti et al. 2000). Unlike previously published studies (Delfino et al. 2006; 

Mar et al. 2005), in our study we did not 

find statistically significant adverse changes in 

inflammatory marker FeNO associated with 

air pollution, and the level of IL-6 in breath 

condensate was too low to be detectable. One 

interpretation for the results of inflammation markers was that we might need a larger 

sample size to detect significant changes in 

airway inflammation. Another possible explanation might be that the inflammation in 

lower airways of the children was not captured 

by FeNO measured at a flow rate of 0.05 L/

sec; Barregard et al. (2008) reported that 

exposure to wood smoke particles resulted 

in significant increase in FeNO measured at a 

flow rate of 0.27 L/sec, but not at 0.05 L/sec. 

Alternatively, this group of asthmatic children might have been in such a state of airway 

inflammation that it overwhelmed the effects 

of air pollution, particularly when exposure 

concentrations were lower than those in other 

studies (Delfino et al. 2006; Mar et al. 2005). 

We did not find a consistent adverse effect 

of O3. O3 exhibited a significantly negative 

association with FeNO (Table 4), but a positive 

association with TBARS (Figure 3). The negative association between O3 concentration and 

FeNO is counterintuitive, because laboratory 

studies have shown that O3 at high concentrations (200–400 ppb) caused inflammation in 

the airways of human subjects (Balmes et al. 

1996; Frampton et al. 1997). In the present 

study, adjusting for co-pollutants and study 

periods in the models did not change the 

results. A sound interpretation for this result 

remains to be found at this point in time.

When a large number of regression models are run on a data set, some statistically 

significant associations may occur by chance. 

To reduce the possibility of spurious relationships due to multiple comparisons, we limited 

sensitivity analyses to those that consistently 

demonstrated statistical significance in base 

models, and considered only results showing a 

consistent pattern as actual effects.

Conclusion

Results from our study demonstrate a significant decrement in small airway function 

and an increase in airway oxidative stress in 

asthmatic children in association with SO2, 

NO2, and PM2.5 in ambient air. TBARS in 

breath condensate may be a useful tool for 

investigating air pollution-related oxidative 

stress among asthmatic children. ICS seems to 

be able to reduce some of the adverse respiratory response to air pollutants.

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