The acute health effects of exposure to ambient ozone have been examined in many geographic regions. Although the findings are

inconsistent, potential adverse effects reported

include decrements in lung function, airway

inflammation, symptoms of asthma, increases

in hospitalization for respiratory diseases, and

excess mortality (Schwela 2000). On the

other hand, the health effects of chronic

exposure to ozone have been less studied, and

the results are inconclusive. Several studies

have reported that long-term exposure to

ozone may reduce lung function in school

children and adults (Galizia and Kinney

1999; Peters et al. 1999; Qian et al. 2005;

Rojas-Martinez et al. 2007) and increase the

prevalence of asthma and asthmatic symptoms (Hwang et al. 2005; Ramadour et al.

2000; Wang et al. 1999). In contrast, other

studies found an insignificant or negative

association between respiratory health effects

and chronic ozone exposure (Gauderman

et al. 2004; Karr et al. 2007; Zemp et al.

1999). No studies have examined health

effects of chronic ozone exposure among a

birth cohort. Biologic studies provided plausibility that chronic exposure to ozone is associated with elevated oxidative damage, which

might be involved in development of asthma

and decrement of lung function (Chen et al.

2007; Mudway and Kelly 2000).

In New York State, asthma hospitalization

rates remain considerably higher (20.4 per

10,000) than the U.S. rate of 16.9 per 10,000

population in 2002 (American Lung

Association 2004; New York State Department

of Health 2005). Young children are a vulnerable population with respect to air pollutants,

given their narrow airways, higher breathing

rate, developing lungs and immune systems,

and more time spent outdoors. Most prior

studies have focused on adults and school-age

children and analyzed less severe health outcomes than hospitalizations. The effect of

chronic exposure to high levels of air pollution

in early life and its subsequent impact on

childhood asthma admissions is unclear. In

addition, the interactive effects between maternal/birth characteristics and air pollution on

childhood asthma hospital admissions have

rarely been studied. The purpose of this study

was to investigate the association between

chronic exposure to ozone and childhood

asthma admissions. We also examined whether

maternal and birth characteristics interacted

with the impact of air pollution on asthma

hospitalization in early life.

Materials and Methods

Study population and health outcome. In

this retrospective cohort study we analyzed a

New York State birth cohort born between

1 January 1995 and 31 December 1999 and

followed each individual until the first asthma

hospital admission or 31 December 2000. We

defined asthma hospital admissions as children

who were first admitted to a hospital from

1 January 1996 through 31 December 2000

with a principal diagnosis of International

Classification of Diseases, 9th Revision, code 493

(U.S. Department of Health and Human

Services 1991). We excluded children residing

in Staten Island from the study cohort because

a substantial amount of data was missing for

ambient ozone in that area. We did not consider admitted children who were < 1 year of

age because of difficulties in differentiating

asthma from bronchiolitis in this age group

(Kramarz et al. 2000). This study was

approved by the New York State Department

of Health Institutional Review Board and

complied with all applicable U.S. regulations. 

We obtained information on hospital

admissions and maternal and birth characteristics from the New York State Integrated

Child Health Information System (ICHIS).

The ICHIS links various sources of New

York State data, including the immunization

records, birth certificates, hospital discharges,

and death certificates. The birth certificate

portion included individual-level information

on residential address, maternal demographics, and birth characteristics; the hospital discharge portion contained the cause and date

of hospital admission and home address at

admission. We obtained regional demographic information from the 2000 U.S.

Census (U.S. Census Bureau 2000), including land area, population density, hospital

density, percentage of individuals living

below poverty level, and median household

income. Thus, potentially important individual and neighborhood confounders can be

Environmental Health Perspectives • VOLUME 116 | NUMBER 12 | December 2008 1725

Research | Children’s Health

Address correspondence to S. Lin, Bureau of

Environmental and Occupational Epidemiology,

New York State Department of Health, 547 River

St., Room 200, Troy, NY 12180 USA. Telephone:

(518) 402-7990. Fax: (518) 402-7959. E-mail:

sxl05@health.state.ny.us

We thank R. Walker, M. Herdt-Losavio, W. Liu,

and R. Jones for their contributions to the manuscript. 

This work was supported by a grant from National

Environmental Public Health Tracking Program,

Centers for Disease Control and Prevention

(u50/ccu422440).

The authors declare they have no competing

financial interests.

Received 17 December 2007; accepted 10 September

2008.

Chronic Exposure to Ambient Ozone and Asthma Hospital Admissions

among Children

Shao Lin,1 Xiu Liu,1 Linh H. Le,2 and Syni-An Hwang1

1Center for Environmental Health, New York State Department of Health, Troy, New York, USA; 2Bureau of Healthcom Network System

Management, New York State Department of Health, Menands, New York, USA

BACKGROUND: The association between chronic exposure to air pollution and adverse health

outcomes has not been well studied.

OBJECTIVE: This project investigated the impact of chronic exposure to high ozone levels on

childhood asthma admissions in New York State. 

METHODS: We followed a birth cohort born in New York State during 1995–1999 to first asthma

admission or until 31 December 2000. We identified births and asthma admissions through the

New York State Integrated Child Health Information System and linked these data with ambient

ozone data (8-hr maximum) from the New York State Department of Environmental Conservation.

We defined chronic ozone exposure using three indicators: mean concentration during the followup period, mean concentration during the ozone season, and proportion of follow-up days with

ozone levels > 70 ppb. We performed logistic regression analysis to adjust for child’s age, sex, birth

weight, and gestational age; maternal race/ethnicity, age, education, insurance status, smoking

during pregnancy, and poverty level; and geographic region, temperature, and copollutants.

RESULTS: Asthma admissions were significantly associated with increased ozone levels for all

chronic exposure indicators (odds ratios, 1.16–1.68), with a positive dose–response relationship.

We found stronger associations among younger children, low sociodemographic groups, and New

York City residents as effect modifiers.

CONCLUSION: Chronic exposure to ambient ozone may increase the risk of asthma admissions

among children. Younger children and those in low socioeconomic groups have a greater risk of

asthma than do other children at the same ozone level.

KEY WORDS: air pollution, asthma, children, chronic, hospital admissions, ozone. Environ Health

Perspect 116:1725–1730 (2008). doi:10.1289/ehp.11184 available via http://dx.doi.org/ [Online

10 September 2008]
controlled when assessing the relationship

between childhood asthma admissions and

chronic exposure to ambient ozone.

Air pollution data and exposure indicators. We obtained hourly ambient ozone data

from the New York State Department of

Environmental Conservation (NYSDEC).

These data (reported in parts per billion) were

measured hourly for each day. We used the 8-

hr maximum hourly value during the peak

outdoor exposure time (1000 to 1800 hours)

in this study to represent the daily ozone level.

We included 32 ozone monitoring sites and

divided them into 11 ozone regions in New

York State (Figure 1) according to their spatial

and temporal correlations, wind direction, and

traffic pattern. In general, we used a linear

regression model with a fixed-origin intercept

to assess the spatial correlation among monitor

pairs as a function of distance. We performed

empirical semivariance analysis and a total

count of occurrences above a specific concentration to evaluate the spatial variation. The

resulting 11 ozone regions are very similar to

the air quality health advisory regions developed by NYSDEC (2008). If more than one

monitoring site was located in one ozone

region, we used the average value of the 8-hr

maximum from multiple monitoring sites to

represent the regional data. We assessed children’s chronic ozone exposure as both continuous and categorical variables by identifying

the individual ozone region based on their residential histories. The continuous ozone variable included the mean concentrations and

the exceedance proportion. Mean concentration was the arithmetic mean of the regional

8-hr ozone maximum for each child during

two different time periods: the entire followup period and ozone seasons (April–October)

during the follow-up period. For children who

had hospital admissions during the defined

periods, we calculated the mean concentration

between the date of birth and the date of

admission. For children who had no hospital

admissions, we calculated the mean concentration of the follow-up period and the ozone

season between the date of birth and the end

of the study. We assessed the risk of hospital

admissions associated with chronic ozone

exposure using a 1-ppb increase in mean concentration during the defined period. The

exceedance proportion is the proportion of

follow-up days with ozone levels > 70 ppb,

which is our 90th percentile of year-round

ozone over the entire follow-up period. This

indicator not only reflects the specific days

exposed to high ozone levels, but also includes

the proportion of days exposed to high ozone

levels for each child over the follow-up period.

Therefore, it captures both the cumulative and

chronic nature of exposures. We used the

interquartile range (IQR; 75th to 25th quartile) as the unit change in the models for the

continuous exceedance proportion exposure.

To estimate the potential dose–response

effect, we categorized children as having low,

medium, or high ozone exposure based on the

tertile ranking of their mean ozone concentration during the follow-up period in New York

City and the rest of New York State separately

to adjust for geographic differences. The ranges

for low, medium, and high exposure were

31.46–37.29 ppb, 37.30–38.11 ppb, and

38.12–50.13 ppb, respectively, for children living in New York City; and 33.50–42.57 ppb,

42.58–45.06 ppb, and 45.07–55.19 ppb for

children living in other New York State regions.

Data linkage methods and geocoding.

According to the enrollment criteria described

above, we identified 1,433,826 children from

the ICHIS database. We geocoded residential

addresses at birth (from the birth certificate

database) at the street level to determine the

geographic region of air pollution using Map

Marker (Mapinfo Corp., Troy, NY). In general, we geocoded 84% of the residential

addresses automatically; we could not

geocode 16% and excluded them from analysis. To assign an ozone region to individual

residential addresses, we overlaid the map of

geocoded addresses onto the map of ozone

regions using Mapinfo (Mapinfo Corp.).

Finally, we linked the ambient ozone data

from NYSDEC to the asthma outcome, individual risk factors from ICHIS data, and

regional level factors from the U.S. Census

(U.S. Census Bureau 2000). 

To evaluate study population dynamics,

we compared exposure regions based on the

original residential addresses retrieved from

the birth certificate database to the secondary

residences extracted from the immunization

record and hospital discharge databases. Our

study population was very stable, and we

found a consistent ozone region (i.e., change

in address did not affect exposure region classification) for 72.6% of children. For 27.2%

of children, address information could be

obtained from only one source: 18.9% from

the birth certificate only and 8.3% from the

immunization record only. For these children, we geocoded the residential address

from the unique database. Only 0.2% of children had address changes that placed them in

a different ozone region. For these children,

we calculated the effective exposure corresponding to the time window across these

regions. If a child was born in ozone region

“A” and was admitted to the hospital at a later

date in region “B,” we considered the child

spent half the time in region “A” and half the

time in region “B.”

Statistical analysis. In this study we aimed

to predict the risk of having asthma admissions

in a birth cohort, but the time to the first

admission in children that is usually analyzed in

survival models was not our primary interest.

We therefore used a multivariate logistic regression model rather than a survival analysis. By

incorporating children’s ages (at admission or

the end of the study) in the logistic regression

analysis, we also appropriately considered and

controlled the time dimension of exposure. We

computed adjusted odds ratios (ORs) and 95%

confidence intervals (CIs) while controlling for

birth and maternal confounding variables and

geographic regions. We fitted regression models

separately for continuous and categorical

chronic ozone exposures. We selected confounding variables based on the epidemiologic

literature and the exploratory results using univariate analyses that suggested possible associations with asthma admissions at p-values

≤ 0.05. These confounders included child’s sex,

birth weight (≤ 2,500 g, > 2,500 g), gestational

age (< 260 days, ≥ 260 days), age at admission

or end of the study (range, 1–6 years) maternal

Lin et al.

1726 VOLUME 116 | NUMBER 12 | December 2008 • Environmental Health Perspectives

Figure 1. Ozone exposure regions in New York State used in this study. NYC, New York City.

Miles

0 37.5 75

NYSDEC ozone monitors

Modified ozone advisory regions
age at delivery (< 20 or > 35 years, 20–35 years)

and smoking status during pregnancy (yes, no).

As a measure of sociodemographic status, we

controlled for individual-level risk factors such

as maternal race (black, other), ethnicity

(Hispanic, non-Hispanic), education level

(< 12 years, ≥ 12 years), insurance type during

pregnancy (Medicaid, self-paid, and other) and

geographic area (New York City vs. other). We

also ascertained census block–group information such as median household income, percentage of population living below poverty level

(the highest quartile vs. others), and hospital

density (i.e., number of hospitals per 100 km2

in each ozone region) to control for medical

care access at the neighborhood level. Because

hospital density was highly correlated with geographic region (Pearson correlation r = 0.99),

and median household income was correlated

with percent below poverty (Pearson correlation r = 0.69), we retained all confounders

except for hospital density and median household income in the final multivariate regression

models because of significant p-values (< 0.01).

We also adjusted the proportion of days during

the entire follow-up period with extreme temperatures, defined as the 90th percentile of the

daily average temperature (72.3°F), in the final

model, in which we compared children in the

highest quartile of extreme temperature days

(high-temperature group) with all others (lowtemperature group).

We also assessed and controlled for the

effects of copollutants by using the Air

Quality Index (AQI) (U.S. Environmental

Protection Agency 1999), which is a standard

system representing the levels of multiple air

pollutants, including ambient particulate

matter (particulate matter with aerodynamic

diameters ≤ 10 and 2.5 μm), nitrogen dioxide, carbon monoxide, and sulfur dioxide.

We calculated the AQI for each pollutant in

each ozone region and chose the maximum

value to represent the daily AQI for that

region. Cumulative AQI was the average level

of daily AQI during the follow-up period. We

used the AQI variable only in the analysis for

children born between 1996 and 1999, but

did not retain it in the final analysis model

because AQI data were not available for 1995

and we would have missed 250,000 eligible

births if we had included AQI.

We further added interaction terms to the

logistic regression model with continuous

ozone exposure to assess potential effect modifications. We used mean ozone concentration

during the entire follow-up period to create

the interaction terms with all dichotomous

confounders. Once we identified significant

interaction terms (p-value < 0.05), we performed stratified analysis to assess the differential impacts of birth and maternal risk on

the association between air pollution and

asthma admissions. The Hosmer–Lemeshow

test showed that the models fitted reasonably

well. We performed all statistical analyses

with SAS software, version 9.1 (SAS Institute,

Inc., Cary, NC).

Results

We included 1,204,396 eligible births in the

analysis, with 10,429 (0.87%) children

admitted to the hospital for asthma by

31 December 2000. Children in this study

were between 1 and 6 years of age. Overall,

the average follow-up time was 26.6 months

for children with asthma admissions and 42

months for all births. The mean ozone level

during the entire follow-up period (41.06

ppb) was lower than the mean concentration

in the ozone season (50.62 ppb) (data not

shown). The average exceedance proportion

was 9.72% among the study population,

ranging from 1.66% to 26.27%. Table 1

summarizes the average ozone levels, total

area of region, and key population characteristics by exposure regions. The western region

had the highest ozone level in New York State

(47.8 ppb), and New York City had the lowest ozone level among 10 New York State

regions (37.5 ppb). However, population

density, birth density, percentages of blacks

and Hispanics, and low level of maternal education in New York City were significantly

higher than in the rest of New York State.

As described in Table 2, we found significant positive associations between chronic

ozone level and asthma hospital admissions

for all exposure indicators after adjusting for

Impact of chronic ambient ozone on asthma hospitalizations

Environmental Health Perspectives • VOLUME 116 | NUMBER 12 | December 2008 1727

Table 1. Summary of ozone levels, land use, and population characteristics by ozone region in New York State.

Mean ozonea (ppb) Land areab Population densityb Birth density in Percent black Percent Percent maternal low 

Ozone region during follow-up (km2) (per km2) cohort (per km2) in cohort Hispanic in cohort education in cohort

Upper Adirondacks 44.45 21,820 18.0 0.20 3.46 3.20 15.52

Lower Adirondacks 43.86 16,806 23.5 0.26 4.70 2.67 17.27

Central 45.38 30,414 52.6 0.60 7.08 2.36 16.58

Upper Hudson Valley 46.21 15,118 73.0 0.81 7.97 4.17 14.15

Lower Hudson Valley 44.74 10,218 94.8 1.16 8.18 11.95 15.09

Western 47.78 16,699 95.3 1.15 12.96 4.11 14.47

Eastern Lake Ontario 41.84 5,741 165.7 2.16 16.33 6.87 16.64

New York City metroc 40.49 1,572 769.7 10.70 15.57 24.51 12.66

Long Island 42.69 3,105 886.9 11.76 10.15 16.14 10.49

New York Cityd 37.51 634 11929.4 174.76 34.32 41.27 25.49

aThe average of the maximum hourly concentration measured between 1000 and 1800 hours during the follow-up period (1 January 1995 to 31 December 2000). bWe used 2000 census

data (U.S. Census 2000) to obtain land area and population density information. cIncludes Rockland and Westchester Counties. dIncludes Bronx, New York, Kings, and Queens Counties.

Table 2. Association between ozone exposure indicators, birth and maternal risk factors, and asthma

hospitalizations.

Characteristic Adjusted OR (95% CI)

Ozone exposure (1-ppb increase/day)a

Mean concentration during the follow-up period 1.16 (1.15–1.17)

Mean concentration during the ozone season 1.22 (1.21–1.23)

Exceedance proportion (%) > 70 ppb with IQR increaseb 1.68 (1.64–1.73)

Other risk factorsc

Temperature 1.06 (1.00–1.13)

Child’s age (month) 0.93 (0.93–0.94)

Race: black vs. other 1.97 (1.88–2.07)

Sex: female vs. male 0.58 (0.56–0.61)

Ethnicity: Hispanic vs. non-Hispanic 1.99 (1.89–2.09)

Birth weight: low vs. normal 1.55 (1.44–1.67)

Gestational age: preterm vs. full term 1.36 (1.27–1.45)

Maternal education: < high school vs. ≥ high school 1.18 (1.12–1.24)

Maternal smoking during pregnancy: yes vs. no 1.39 (1.29–1.49)

Geographic region: New York City vs. other regions 4.21 (3.77–4.70)

Maternal age (years): < 20 or > 35 vs. 20–35 1.06 (1.00–1.11)

Poverty level: highest 25th quartile vs. other 1.21 (1.15–1.27)

Maternal insurance 

Medicaid vs. other 1.26 (1.19–1.33)

Self-paid vs. other 1.19 (1.10–1.29)

aAdjusted for geographic region, child’s sex, child’s age, birth weight, gestational age, maternal race, ethnicity, maternal

age, education, maternal insurance, smoking status during pregnancy, poverty level, and temperature. bIQR is a 2.51%

increase. cORs are from the model including the mean concentration during the follow-up period.
potential confounding variables (ORs =

1.16–1.68). The risk of hospital admissions

increased 22% with a 1-ppb increase in mean

ozone concentration during the ozone season.

Indicators using the entire follow-up period

(OR = 1.16) showed similar but weaker elevated risks for asthma admissions. When estimating the ozone effect using the exceedance

proportion, we observed a significant increase

(OR = 1.68; 95% CI, 1.64–1.73) in hospital

admissions associated with an IQR (2.51%)

increase in ozone.

Because the effects of other risk factors on

asthma admissions were similar when using

three ozone indicators, to simplify the results

Table 2 shows the effects of other risk factors

using only the mean concentration during the

entire follow-up period as the exposure

included in the model. Children who are black

or Hispanic, whose mother had a lower level of

education, Medicaid, or self-paid insurance,

and those residing in areas with a high percentage of below-poverty populations had a higher

risk of asthma admissions. Low birth weight,

preterm birth, and maternal smoking during

pregnancy were associated with increased

asthma admissions. Geographic region was the

strongest risk factor associated with asthma

admissions in this study. Children living

in New York City were 4.21 (95% CI,

3.77–4.70) times more likely to be admitted to

a hospital than children living in other regions

of New York State. Child’s age and female sex

were negatively associated with asthma admissions. Maternal age and extreme temperature

were not associated with increased asthma

admissions. Additionally, we also examined the

ozone–asthma association during the entire follow-up period after controlling for AQI and

other confounders. The adjusted OR after controlling for AQI increased slightly (data not

shown; OR = 1.24; 95% CI, 1.23–1.25) compared with the unadjusted OR of 1.16.

To control for the impacts of other confounders such as admission policy, home environment, and disease management, which are

unavailable in ICHIS data but are related to

hospital admissions, we used a “negative control,” admissions due to gastroenteritis, in a

sensitivity analysis. We found that chronic

exposure to ozone was not positively associated with hospital admissions due to gastroenteritis (OR = 0.57; 95% CI, 0.54–0.59)

after adjusting for confounders similar to those

used in the asthma analysis.

To address the relationship between ozone

dose and health effects, we analyzed dose

response separately with categorical exposures

in New York City and other regions of New

York State (Figure 2). After adjustment for

other covariates, we observed significantly

positive dose–response relationships in both

regions; that is, higher ozone exposure was

associated with a higher risk of admissions.

We first identified the interactive effect of

maternal/infant factors and chronic ozone levels on asthma hospital admissions from the

logistic regression model and then investigated

it using stratification analysis (Figure 3). We

found the largest disparity for geographic

regions; that is, the ozone-asthma association

was stronger among New York City residents

(OR = 1.43) than among other regions (OR =

1.11). Similarly, the effects of ozone on asthma

admission were significantly higher among

children 1–2 years of age (OR = 1.29), children living in poor neighborhoods (i.e., highest

quartile of percent below poverty; OR = 1.25),

children whose mothers had low education

(OR = 1.22), Medicaid/self-paid births (OR =

1.22), and Hispanics (OR = 1.27) compared

with older children (OR = 1.03), children in

good neighborhoods (OR = 1.14), mothers

with high school education (OR = 1.14), births

covered by other insurance (OR = 1.11), and

non-Hispanic children (OR = 1.13). However,

we found the ozone–asthma association to be

weaker among children born to smokers than

among those born to nonsmokers (OR = 1.10

and 1.18, respectively).

Discussion

In this study, we found that chronic exposure

to ambient ozone in early life was significantly

and positively associated with an increased risk

of asthma hospital admissions among a birth

cohort in New York State. Multivariate analyses using three different exposure indicators

produced similar results. We also observed

positive dose–response trends in New York

City and the remainder of New York State.

Many time-series studies have found that

hospitalizations or emergency visits due to

asthma may increase during the periods of

short-term exposure to increased ozone levels

(Burnett et al. 2001; Gent et al. 2003; Tolbert

et al. 2000). Although few other studies have

assessed the risk of childhood asthma hospitalizations associated with chronic ozone exposure, the findings of this study are consistent

with several previous studies among children.

Three cross-sectional studies observed a positive relationship between chronic exposure to

ozone, and prevalence of asthma and asthmatic symptoms in school children (Hwang

et al. 2005; Ramadour et al. 2000; Wang et al.

1999). Peters et al. (1999) and Rojas-Martinez

et al. (2007) have reported a reduction in lung

function associated with higher ozone concentration among school-age children in two

prospective studies. One cohort study in

Southern California found that in communities with high ozone levels, children who

played sports outdoors had 3.3 (95% CI,

1.9–5.8) times the risk of developing asthma

compared with children not playing sports

(McConnell et al. 2002). Another birth cohort

study by Brauer et al. (2007) also reported a

significant association (OR = 1.26) between

traffic-related pollution and both doctor-diagnosed asthma and self-reported wheeze among

children < 4 years of age, but ozone was not

measured in that project. No previous studies

examined a similar health effect from chronic

ozone exposure among young children in a

birth cohort for direct comparison with our

study. Taken together with the present study,

all study findings in the current literature indicate that ozone might have both acute and

chronic effects on the development of asthma

and cause a subsequent increase in asthma

Lin et al.

1728 VOLUME 116 | NUMBER 12 | December 2008 • Environmental Health Perspectives

Figure 2. Ozone–asthma dose–response relationship using the mean concentration during the entire

follow-up period, adjusted for child’s sex, age, birth

weight, and gestational age; maternal race, ethnicity, age, education, insurance, and smoking status

during pregnancy; and regional poverty level and

temperature. NYS, New York State. ref, referent.

1.43 (1.29–1.58)

1.69 (1.52–1.80)

1.00

(ref)

1.64

(1.48–1.82)

2.06

(1.87–2.27)

1.00

(ref)

3.0

2.5

2.0

1.5

1.0

0.5

0

OR (95% CI)

New York City Other NYS regions

Regions

Low exposure 0–33%

Medium exposure 34–66%

High exposure ≥ 67%

Figure 3. Stratified analysis of ozone–asthma association, using the mean concentration during the entire

follow-up period. NYC, New York City.

1.5

1.4

1.3

1.2

1.1

1.0

OR (95% CI)

NYC/other

regions

Risk factors

Significant difference

Nonsignificant difference

Black/other

race

Hispanic/

Nonhispanic

ethnicity

No/yes

high school

graduate

Yes/no

smoking

Medicaid,

self-paid/other

insurance

Top 25% /

other % below

poverty

F/M

sex

Low/normal

birth weight

Pre/full-term

gestational age

1–2 > 2

child’s age
hospital admissions. On the other hand, other

studies (Gauderman et al. 2004; Zemp et al.

1999) found no significant association

between exposure to ozone and respiratory

morbidity, and Karr et al. (2007) reported a

reduced risk (OR = 0.92; 95% CI, 0.88–0.97)

of hospitalization for infant bronchiolitis with

a 14-ppb increase in ozone exposure. Despite

these studies showing no effect, our study has

contributed another confirmation of positive

associations between ozone exposure and

respiratory outcomes.

Interestingly, in the present study, the associations between elevated ozone and increased

asthma hospital admissions were stronger in

young children, Medicaid/self-paid births,

Hispanics, children living in poor communities

or whose mothers had low education levels,

and New York City residents. These results

suggest that chronic exposure to ambient

ozone did not have an equal asthma effect on

children. Specifically, very young children were

more susceptible to ozone exposure, and children with low socioeconomic status (SES) had

a greater risk of asthma admissions at the same

ozone level. Children < 2 years of age have

been reported to be more susceptible to air pollutants compared with other children (Braga

et al. 2001). Son et al. (2006) found a similar

interactive effect of SES characteristics on the

relationship between short-term exposure to

high ozone levels and asthma hospital admissions. In New York State, Lin et al. (1999)

found that areas with a high proportion of lowincome, low-education level and high population density (i.e., crowded living conditions)

experience higher rates of asthma hospitalizations. In the present study, maternal smoking

status during pregnancy weakened the ozone

effect on asthma admissions. This finding has

not been reported in previous air pollution

studies and should be interpreted with caution

because maternal smoking information from

the birth certificate was based on self-report.

Smoking tends to be underreported by study

participants in general, and smoking while

pregnant is stigmatized. In addition, some

quitters might go back to smoking after their

children were born or some time before the

child’s hospital admission.

Although survival analysis is a method

commonly used to examine time-varying

events, logistic regression analysis has also been

widely used in many air pollution and environmental epidemiologic studies (Andersen et al.

2008; Brauer et al. 2007; Hwang et al. 2005;

Kumar et al. 2008; Morgenstern et al. 2008;

Ramadour et al. 2000; Wang et al. 1999).

Because the purpose of the present study is to

predict the probability of occurrence of a hospital admission for asthma rather than time to

disease occurrence, logistic regression analysis is

an appropriate option. Additionally, in a survival analysis of a birth cohort, time to event is

directly correlated with child’s age. However,

asthma hospital admissions are also strongly

associated with age. Therefore, by including

child’s age in our logistic regression model, we

could not only control for the confounding

(and/or independent) effect of age but also

incorporate the varying time dimension of

exposure—that is, the length of time exposed

for each child—which is the same as child’s

age. To validate our analytical method and the

findings, we conducted a proportional hazards

model for the same data in New York City.

This sensitivity analysis yielded similar results

between asthma admissions and chronic

exposure to ozone.

This is one of the largest studies (n =

1,204,396 births) to date examining the relationship between chronic exposure to ambient

ozone during early life and asthma hospital

admissions among children. Data obtained

from ICHIS had health, birth, and maternal

information and were then combined with air

pollution data. This integrated environmental

health database provides a unique birth cohort

to follow health end points and to estimate

incidence. We selected a vulnerable subgroup,

children < 6 years of age, as our study population. Unlike adults, children may be more

affected by air pollutants because of higher

vulnerability and different behavior (Trasande

and Thurston 2005). Children’s lungs and

immune systems are developing, and exposure

to high ozone levels may impair the normal

process of development (Plopper and Fanucchi

2000; Trasande and Thurston 2005). In addition, children are more active than adults are

and tend to be outside in the summer and the

afternoon, which may result in higher individual exposure to ozone (Trasande and Thurston

2005; U.S. Environmental Protection Agency

2002). This study also used asthma hospital

admissions from an existing file as the health

outcome, which comes from the hospitals and

is not subject to self-reporting bias. Although

some studies have used cumulative ozone as an

exposure indicator, to our knowledge this is

the first study to specifically examine the association between chronic exposure to ambient

ozone and first asthma hospital admission in

children. This study also assessed the interactive effects of maternal/infant factors on the

ozone–asthma association, the confounding

effects of temperature and AQI, and the ozone

effect on a control disease to estimate confounding bias.

Several limitations should be considered

when interpreting these findings. First, hospital admissions data capture only the most

severe cases of asthma and may not be representative of mild or less severe cases. Second,

we have no personal activity information, so

we are unable to calculate individual cumulative exposure accurately. Third, although

many important confounding variables have

been controlled in the analysis, further adjustment of other confounders such as genetic susceptibility may alter the associations. Finally,

ICHIS data can identify the address changes

over time only when a hospital admission

occurred or if immunization data are available.

For children who have a residential address

from only one database, the accuracy of their

exposure calculation is questionable. However,

this misclassification bias would be nondifferential and toward the null. Our data also suggested stability in the study population,

because most of the population did not

change their exposure region over time, and

few children lived in multiple ozone regions.

This study provides evidence of a positive

association between chronic exposure to ozone

and childhood asthma hospital admissions.

Children who are exposed to high ozone levels

over time are more likely to develop asthma

severe enough to be admitted to the hospital.

Further adjustment for temperature, AQI, and

maternal/birth factors did not alter the

ozone–asthma association. This study also

found that socioeconomic characteristics may

contribute to differential ozone–asthma associations and should be of special concern. The

findings from the present study not only will

help health professionals identify environmental risk factors for asthma admission, but also

will help discern the impairment from chronic

exposure to high ozone levels over time.

Minimizing outdoor exposure opportunities

on high-ozone days may be a viable strategy

for reducing the burden of asthma hospital

admissions in children. Further studies in a

birth cohort examining health effect of

chronic ozone exposure are needed to confirm

our findings.

REFERENCES

American Lung Association. 2004. Trends in Asthma Morbidity

and Mortality. American Lung Association Epidemiology

and Statistics Unit. Available: http://www.lungusa.org/atf/

cf/%7B7A8D42C2-FCCA-4604-8ADE-7F5D5E762256%7D/

ASTHMA1.PDF [accessed 1 June 2008].

Andersen ZJ, Loft S, Ketzel M, Stage M, Scheike T, Hermansen

MN, et al. 2008. Ambient air pollution triggers wheezing

symptoms in infants. Thorax 63(8):710–716.

Braga AL, Saldiva PH, Pereira LA, Menezes JJ, Conceicao GM,

Lin CA, et al. 2001. Health effects of air pollution exposure

on children and adolescents in São Paulo, Brazil. Pediatr

Pulmonol 31:106–113.

Brauer M, Hoek G, Smit HA, de Jongste JC, Gerritsen J,

Postma DS, et al. 2007. Air pollution and development of

asthma, allergy and infections in a birth cohort. Eur Respir

J 29:879–888.

Burnett RT, Smith-Doiron M, Stieb D, Raizenne ME, Brook JR,

Dales RE, et al. 2001. Association between ozone and hospitalization for acute respiratory diseases in children less

than 2 years of age. Am J Epidemiol 153:444–452.

Chen C, Arjomandi M, Balmes J, Tager I, Holland N. 2007.

Effects of chronic and acute ozone exposure on lipid peroxidation and antioxidant capacity in healthy young adults.

Environ Health Perspect 115:1732–1737.

Galizia A, Kinney PL. 1999. Long-term residence in areas of

high ozone: associations with respiratory health in a

nationwide sample of nonsmoking young adults. Environ

Health Perspect 107:675–679.

Gauderman WJ, Avol E, Gilliland F, Vora H, Thomas D, Berhane K,

Impact of chronic ambient ozone on asthma hospitalizations

Environmental Health Perspectives • VOLUME 116 | NUMBER 12 | December 2008 1729
et al. 2004. The effect of air pollution on lung development

from 10 to 18 years of age. N Engl J Med 351:1057–1067.

Gent JF, Triche EW, Holford TR, Belanger K, Bracken MB,

Beckett WS, et al. 2003. Association of low-level ozone

and fine particles with respiratory symptoms in children

with asthma. JAMA 290:1859–1867.

Hwang BF, Lee YL, Lin YC, Jaakkola JJ, Guo YL. 2005. Traffic

related air pollution as a determinant of asthma among

Taiwanese school children. Thorax 60:467–473.

Karr C, Lumley T, Schreuder A, Davis R, Larson T, Ritz B, et al.

2007. Effects of subchronic and chronic exposure to ambient air pollutants on infant bronchiolitis. Am J Epidemiol

165:553–560.

Kramarz P, DeStefano F, Gargiullo PM, Davis RL, Chen RT,

Mullooly JP, et al. 2000. Influenza vaccination in children

with asthma in health maintenance organizations. Vaccine

Safety Datalink Team. Vaccine 18:2288–2294.

Kumar R, Yu Y, Story RE, Pongracic JA, Gupta R, Pearson C,

et al. 2008. Prematurity, chorioamnionitis, and the development of recurrent wheezing: a prospective birth cohort

study. J Allergy Clin Immunol 121(4):878–884.

Lin S, Fitzgerald E, Hwang SA, Munsie JP, Stark A. 1999.

Asthma hospitalization rates and socioeconomic status in

New York State (1987–1993). J Asthma 36:239–251.

McConnell R, Berhane K, Gilliland F, London SJ, Islam T,

Gauderman WJ, et al. 2002. Asthma in exercising children

exposed to ozone: a cohort study. Lancet 359:386–391.

Morgenstern V, Zutavern A, Cyrys J, Brockow I, Koletzko S,

Krämer U, et al. 2008. Atopic diseases, allergic sensitization,

and exposure to traffic-related air pollution in children. Am

J Respir Crit Care Med. 2008 Jun 15;177(12):1331–1337.

Mudway IS, Kelly FJ. 2000. Ozone and the lung: a sensitive

issue. Mol Aspects Med 21:1–48.

New York State Department of Health. 2005. New York State

Asthma Surveillance Summary Report. Available:

http://www.health.state.ny.us/diseases/asthma/pdf/

asthmareport.pdf [accessed 1 June 2008].

NYSDEC (New York State Department of Environmental

Conservation). 2008. Air Quality Index (AQI) Forecast and

Current Observations for New York State. Available:

http://www.dec.ny.gov/chemical/34985.html [accessed

1 June 2008].

Peters JM, Avol E, Gauderman WJ, Linn WS, Navidi W, London

SJ, et al. 1999. A study of twelve southern California communities with differing levels and types of air pollution. II.

Effects on pulmonary function. Am J Respir Crit Care Med

159:768–775.

Plopper CG, Fanucchi MV. 2000. Do urban environmental pollutants exacerbate childhood lung diseases? Environ Health

Perspect 108:A252–A253.

Qian Z, Liao D, Lin HM, Whitsel EA, Rose KM, Duan Y. 2005.

Lung function and long-term exposure to air pollutants in

middle-aged American adults. Arch Environ Occup Health

60:156–163.

Ramadour M, Burel C, Lanteaume A, Vervloet D, Charpin D,

Brisse F, et al. 2000. Prevalence of asthma and rhinitis in

relation to long-term exposure to gaseous air pollutants.

Allergy 55:1163–1169.

Rojas-Martinez R, Perez-Padilla R, Olaiz-Fernandez G,

Mendoza-Alvarado L, Moreno-Macias H, Fortoul T, et al.

2007. Lung function growth in children with long-term

exposure to air pollutants in Mexico city. Am J Respir Crit

Care Med 176:377–384.

Schwela D. 2000. Air pollution and health in urban areas. Rev

Environ Health 15:13–42.

Son JY, Kim H, Lee JT, Kim SY. 2006. Relationship between the

exposure to ozone in Seoul and the childhood asthmarelated hospital admissions according to the socioeconomic status. J Prev Med Pub Health 39:81–86.

Tolbert PE, Mulholland JA, MacIntosh DL, Xu F, Daniels D,

Devine OJ, et al. 2000. Air quality and pediatric emergency

room visits for asthma in Atlanta, Georgia, USA. Am J

Epidemiol 151:798–810.

Trasande L, Thurston GD. 2005. The role of air pollution in

asthma and other pediatric morbidities. J Allergy Clin

Immunol 115:689–699.

U.S. Census Bureau. 2000. 2000 Census of Population and

Housing. Summary File 3. Available: http://www.census.

gov/prod/cen2000/doc/sf3.pdf [accessed 1 June 2008].

U.S. Department of Health and Human Services. 1991. The

International Classification of Diseases, 9th Revision.

Washington, DC:U.S. Department of Health and Human

Services.U.S. Environmental Protection Agency. 1999. Air

Quality Index Reporting: Final Rule. Available: http://www.

epa.gov/ttn/oarpg/t1/fr_notices/airqual.pdf [accessed

1 June 2008].

U.S. Environmental Protection Agency. 2002. Child-Specific

Exposure Factors Handbook. Available: http://fn.cfs.

purdue.edu/fsq/WhatsNew/KidEPA.pdf [accessed 1 June

2008].

Wang TN, Ko YC, Chao YY, Huang CC, Lin RS. 1999. Association

between indoor and outdoor air pollution and adolescent

asthma from 1995 to 1996 in Taiwan. Environ Res 81:239–247.

Zemp E, Elsasser S, Schindler C, Kunzli N, Perruchoud AP,

Domenighetti G, et al. 1999. Long-term ambient air pollution and respiratory symptoms in adults (SAPALDIA

Study). The SAPALDIA Team. Am J Respir Crit Care Med

159:1257–1266.

Lin et al.

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