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An Association between Fine Particles and Asthma Emergency Department
Visits for Children in Seattle 

Gary Norris,1 Sharon N. YoungPong,2 Jane Q. Koenig,3 Timothy V. Larson,1
Lianne Sheppard,4 and James W. Stout5 

1Department of Civil and Environmental Engineering, University of
Washington, Seattle, Washington, USA

2CH2MHill, Portland, Oregon, USA

3Department of Environmental Health; 4Department of Biostatistics; and
5Department of Pediatrics and Health Services, University of Washington,
Seattle, Washington, USA

  HYPERLINK
"http://www.ehponline.org/members/1999/107p489-493norris/norris-full.htm
l" \l "intro#intro"  Introduction  

  HYPERLINK
"http://www.ehponline.org/members/1999/107p489-493norris/norris-full.htm
l" \l "met#met"  Methods  

  HYPERLINK
"http://www.ehponline.org/members/1999/107p489-493norris/norris-full.htm
l" \l "res#res"  Results  

  HYPERLINK
"http://www.ehponline.org/members/1999/107p489-493norris/norris-full.htm
l" \l "disc#disc"  Discussion  

Abstract

Asthma is the most common chronic illness of childhood and its
prevalence is increasing, causing much concern for identification of
risk factors such as air pollution. We previously conducted a study
showing a relationship between asthma visits in all persons < 65 years
of age to emergency departments (EDs) and air pollution in Seattle,
Washington. In that study the most frequent zip codes of the visits were
in the inner city. The Seattle-King County Department of Public Health
(Seattle, WA) subsequently published a report which showed that the
hospitalization rate for children in the inner city was over
600/100,000, whereas it was < 100/100,000 for children living in the
suburbs. Therefore, we conducted the present study to evaluate whether
asthma visits to hospital emergency departments in the inner city of
Seattle were associated with outdoor air pollution levels. ED visits to
six hospitals for asthma and daily air pollution data were obtained for
15 months during 1995 and 1996. The association between air pollution
and childhood ED visits for asthma from the inner city area with high
asthma hospitalization rates were compared with those from lower
hospital utilization areas. Daily ED counts were regressed against fine
particulate matter (PM) , carbon monoxide (CO) , sulfur dioxide, and
nitrogen dioxide using a semiparametric Poisson regression model.
Significant associations were found between ED visits for asthma in
children and fine PM and CO. A change of 11 µg/m3 in fine PM was
associated with a relative rate of 1.15 [95% confidence interval (CI) ,
1.08-1.23]. There was no stronger association between ED visits for
asthma and air pollution in the higher hospital utilization area than in
the lower utilization area. These findings were seen when estimated
PM2.5 concentrations were below the newly adopted annual National
Ambient Air Quality Standard of 15 µg/m3. Key words:   HYPERLINK
"http://www.ehponline.org/tagSearch/air+pollution"  air pollution ,  
HYPERLINK "http://www.ehponline.org/tagSearch/asthma"  asthma ,  
HYPERLINK "http://www.ehponline.org/tagSearch/carbon+monoxide"  carbon
monoxide ,   HYPERLINK "http://www.ehponline.org/tagSearch/children" 
children ,   HYPERLINK
"http://www.ehponline.org/tagSearch/emergency+departments"  emergency
departments ,   HYPERLINK
"http://www.ehponline.org/tagSearch/nitrogen+dioxide"  nitrogen dioxide
,   HYPERLINK "http://www.ehponline.org/tagSearch/particulate+matter" 
particulate matter . Environ Health Perspect 107:489-493 (1999) .
[Online 6 May 1999] 

  HYPERLINK
"http://www.ehponline.org/docs/1999/107p489-493norris/abstract.html" 
http://ehpnet1.niehs.nih.gov/docs/1999/107p489-493norris/ abstract.html 

Address correspondence to J.Q. Koenig, Department of Environmental
Health, 357234, University of Washington, 561A Health Sciences Building,
Room 7, PO Box 357234, Seattle, WA 98195-7234 USA. Telephone: (206)
543-2026. Fax: (206) 685-3990. E-mail:   HYPERLINK
"mailto:jkoenig@u.washington.edu"  jkoenig@u.washington.edu  

We thank N. Maykut for providing technical advice and the Puget Sound
Air Pollution Control Agency for continuing to support air pollution
health effects research in the Puget Sound region. We also thank the
participating hospitals for their assistance, A. Park of the Seattle
King County Department of Public Health for the population data, and
D.V. Bates for helpful comments regarding the manuscript. 

Funding for this research was from the Puget Sound Air Pollution Control
Agency, Seattle, Washington, and in part from NIEHS Center grant 1 P30
ES 07033. 

Received 16 November 1998 ; accepted 26 February 1999. 

Introduction

Asthma is the most common chronic illness in children and the cause of
most school absences (1). The rate of hospitalization for asthma has
been increasing in children < 18 years of age (2). The primary increases
in asthma morbidity are observed in minority populations in urban areas
(3). When focusing on the inner city, 8-12% of children under 18 years
of age have asthma (4). Many airborne factors can aggravate asthma,
including cigarette smoke (5), dust mites, molds, cold air, animal
dander (6), and cockroaches (7). Additionally, increases in air
pollution are associated with exacerbation of asthma as measured by
decreased lung function values and respiratory symptoms (8-10),
shortness of breath (11), emergency department (ED) visits (12-18), and
hospitalizations (19,20). Thus there is concern that air pollution is
aggravating childhood asthma (21,22). 

 2.5 µm in aerodynamic diameter (PM2.5), and the coarse fraction
PM10-PM2.5] (20). Sources of PM in Seattle include wood smoke, gasoline
and diesel vehicles, resuspended road dust, and industry (23). A source
apportionment study of PM10 in Seattle in 1991-1992 found that during
the heating season, 80% of PM in residential areas originated from
wood-burning devices (24). Concentrations of all measured air pollutants
have been decreasing in Seattle over the last decade (25). 

The Seattle-King County Health Department (Seattle, WA) carried out a
survey from 1987 to 1996 on asthma hospitalization rates for children in
Seattle and surrounding areas using the Comprehensive Hospital Abstract
Reporting System and found > 50% higher hospitalization rates in central
and southeast Seattle (the inner city) as compared to other districts
around Seattle (26). The present study examined whether there was a
stronger association between air pollution and ED visits for asthma for
children in the inner city area than for other children in Seattle using
the same hospitals and found that there was not. 

Methods

Health data. Daily ED visits for asthma were obtained from six hospitals
in central and southeast Seattle from 1 September 1995 to 31 December
1996. Permission for use of the hospital data was obtained from the
University of Washington Human Subjects Office in Seattle. Four of the
six hospitals were downtown; the other two were located within 12 km of
central Seattle (Figure 1). The total number of daily visits were
compiled based on the International Classification of Disease, Ninth
Revision (World Health Organization, Geneva) codes for asthma
(493.01-493.99). Only data for patients under the age of 18 who lived in
a 36-zip code region were used. The zip code region contained the six
hospitals and was limited to an area between the air monitoring stations
to the north and south of the central area identified in the
hospitalization survey (Figure 1). The 36 zip codes in that region were
divided into a high and low utilization density based on the childhood
ED visits for asthma. The top 20th percentile zip codes were designated
as the high ED asthma utilization areas (seven zip codes). The rest of
the zip codes were designated as the low ED asthma utilization areas (29
zip codes). The association between air pollution and ED asthma visits
was evaluated for the entire study region (36 zip codes), as well as
separately for the high and low ED utilization regions (Figure 1). 

  

 sp, dry light scattering. 

*Additional station that operated from February 1996 to January 1997. 

  sp) were available at three sites--north, central, and south Seattle.
Dry light scattering coefficient obtained from an integrating
nephelometer most efficiently measures particles between 0.2 and 0.9 µm
(27), which makes it a measure of the concentration of PM < 1 µm.
Carbon monoxide (CO) values were obtained from four sites within the
Seattle study region. Sulfur dioxide (SO2) concentrations were measured
at one site in central Seattle. Nitrogen dioxide (NO2) and ozone data
were obtained from the WDOE for a site in central Seattle and at a site
20 km east of Seattle, respectively. Because the health data collected
for this study only covered one ozone season (April-October) there were
sufficient ozone data for our model. In addition, the photochemical belt
where ozone concentrations are measured is 20 km east of the area where
children in this study resided. 

For pollutants measured at multiple sites, a daily arithmetic average
was calculated and used in the time-series analyses. The appropriate
averaging time for each pollutant was based on national and state air
quality standards. A 24-hr average was used for measures of PM. A 1-hr
average was used for SO2 to reflect the WDOE 1-hr standard of 400 ppb
for SO2. Because there is only an annual National Ambient Air Quality
Standard (NAAQS) for NO2, we selected the daily maximum 1 hr and daily
average concentration for this pollutant. A number of studies have used
the daily maximum 1 hr NO2 concentration for time-series analyses
(14,15,28). We assumed that CO was a general indicator of the build up
of air pollution and we used an averaging time that matched the PM
measurements (24 hr). Dew point temperature and average daily
temperature data were collected from the Seattle Tacoma International
Airport by the National Oceanic and Atmospheric Administration National
Climatic Data Center (Figure 1); 24-hr averages were used for these
meteorologic variables. 

Statistical analysis. The ED visits for asthma were regressed on
predictor and confounding variables using a semiparametric Poisson
regression model, a method of choice in recent studies (20,29). All
analyses were conducted with the S-PLUS statistical package (StatSci,
Seattle, WA) using a generalized additive model (30). Base models were
first constructed that adjusted for potential confounding factors using
day-of-week indicator variables, smooth functions for time trends,
temperature, and dew point temperature. The smooth function for time
trends used a smoothing spline (31) that was approximately equivalent to
a 2-month moving average. The degrees of freedom for the smoothing
splines for temperature and dew point temperature were selected based on
minimizing the degree of freedom adjusted deviance (32). After the base
models were created for each of the three utilization areas (high, low,
and entire area), the air pollution exposure variables were evaluated by
adding them individually into the model. The final models were evaluated
for overdispersion and autocorrelation. Additionally, the assumption of
a linear dose response was evaluated using a smooth function. 

The ED visits for asthma were assumed to be precipitated by either the
same-day air pollution or air pollution levels up to 4 days before the
visit (0- to 4-day lags). These lag times are consistent with that
reported by Canny and colleagues (33) who found 84% of the asthmatic
children had symptoms for 72 hr or less prior to arrival to the ED. 

Results

Table 1 shows a summary of pollutant concentrations in this study. Table
2 summarizes the correlations between the exposure variables that were
used. The PM10 and light-scattering measurements were highly correlated
(r = 0.82). CO was also correlated with these PM measurements, but not
with NO2 or SO2. An additional nephelometer was placed in south Seattle
prior to this study to determine whether the inner city area fine PM
values correlated with the other fixed PM monitors (Figure 1). The
light-scattering measurements from the inner city monitor were highly
correlated with the other monitors in the network, with a correlation
coefficients ranging from 0.75 to 0.85. 

  

  

The average number of ED visits for asthma in our study for children <
18 years of age was 1.8 per day, with a maximum of nine visits on any
day. This number is low because we restricted the study area to the
inner city and surrounding areas. The age distribution of the ED visits
for asthma in children < 18 years of age is shown in Table 3. The
majority of the ED visits were for children younger than 5 years of age.
This age group accounted for 55 and 54% of the asthma visits for the
high and low utilization regions, respectively. When comparing asthma ED
visits between the two study areas, the high utilization area accounted
for 41% of all the asthma ED visits (seven zip codes). 

  

  sp) were significantly associated with increased ED asthma visits in
children from all three zip code areas with relative rate increases
ranging from 1.13 to 1.16 across the study regions. PM10 and CO had
similar relative rates over the study regions and were significantly
associated with ED visits for asthma in the low utilization area and in
the total study area. The daily 1-hr maximum SO2 and NO2 were not
significantly associated with an increase in ED visits for asthma for
any of the study areas. The association between ED visits for asthma and
ozone was only determined for the entire study area because of the large
number of missing data (45% of the days). Ozone was not significantly
associated with ED visits for asthma; the relative rate was 1.02 [95%
confidence interval (CI), 0.98-1.05] for an IQR of 4.6 ppb in the
maximum daily running 8-hr average. 

  

Multipollutant models containing either PM measurement (light scattering
or PM10), SO2, and NO2 were also analyzed for the entire study region
using a 1-day lag. CO was excluded from the multipollutant model because
it was assumed to be a surrogate for stagnant conditions. The relative
rate for light scattering and PM10 remained significant with relative
rates of 1.17 (CI, 1.08-1.26) and 1.14 (CI, 1.04-1.26), whereas the SO2
and NO2 terms were not significantly associated with an increase in ED
visits for asthma (data not shown). 

The highest PM concentrations were observed during the winter heating
season, as was seen in three earlier studies in Seattle (8,12,20)
(Figure 2). Initial analyses showed that 24 and 25 December 1995 were
influential data points in the regression because of the high measured
PM concentrations. To assess the impact of these data, we repeated the
analyses with and without these 2 days to evaluate the effect of these
atypically high PM concentrations (Figure 2). The relative rates for
increased ED visits for asthma in the entire study area including and
excluding 24 and 25 December were 1.11 (CI, 1.02-1.20) and 1.14 (CI,
1.05-1.24), respectively, for an 11.5-µg/m3 increase in PM10. Relative
rates for inclusion and exclusion of those dates for associations with
light scattering were 1.10 (CI, 1.04-1.17) and 1.15 (CI, 1.07-1.23) for
an IQR increase. These results show the relative rates remained
significant with the inclusion of the influential dates, but the
relative rate for light scattering decreased 5% with the inclusion of
the two high concentration points. Additionally, the inclusion of 24 and
25 December 1995 caused the dose-response relationships for light
scattering to show nonlinear behavior above values approximately equal
to 40 µg/m3 PM2.5. Because these 2 days were holidays, the use of the
ED visits for asthma may have been different from other days in the
study. Based on the high influence and a potential holiday effect, these
2 days were not included in our primary analysis. 

  

 10 µm in aerodynamic diameter. 

aEstimated from light-scattering data. 

Discussion

We found significant associations between ED visits for asthma in
children and PM10, light-scattering measurement of fine PM, and CO.
Light scattering, which is a measure of fine PM primarily < 1.0 µm in
diameter, was significantly associated with ED visits for asthma in all
the analyses. Additionally, PM10 and CO were significant predictors of
ED asthma visits in the low utilization and for the combined utilization
areas. The higher relative risk in this study as compared to the earlier
results by Schwartz and colleagues (12) may be due to the fact that our
population was restricted to individuals under the age of 18, a more
susceptible group than the population at large. 

We recognize that ED data from hospitals contain some misdiagnoses.
Delfino and associates (34) found a good association between hospital
summary data and chart review. The majority of cases in our study came
from a single children's hospital specializing in diagnoses for
childhood diseases. 

The number of visits for the high utilization region (371) was less than
the low utilization area (529) and likely did not achieve statistical
significance for PM10 and CO because of the reduced number of events.
Otherwise, the high and low utilization areas did not appear to have
different associations between air pollution and increased ED visits for
asthma. The estimated numbers of children under 18 years of age in the
high utilization area and in the rest of Seattle were 6,921 and 100,895,
respectively. However, we cannot compare the absolute number of visits
for the two utilization areas because a given relative rate increase in
ED visits in the high utilization area caused more absolute visits than
in the low utilization area. 

In this study, relative rates for light scattering in the low and high
utilization areas were 13 and 16% for an IQR increase of approximately
10 µg/m3 of fine PM. The light-scattering IQR was converted to
represent PM2.5 gravimetric mass based on colocated nephelometer and
PM2.5 monitors at the southernmost PM monitoring site (224 days, r =
0.86). The average concentration for the 15-month period of this study
was approximately 12 µg/m3 PM2.5, a concentration below the new EPA
annual standard (15 µg/m3). PM10 was associated with a 14% increase in
ED asthma visits for an increase of 12 µg/m3 PM10. 

 The association between increased asthma visits and CO was investigated
in Anchorage, Alaska (35), Reno, Nevada (36), and Seattle (20). The
Anchorage and Reno studies did not find a significant association
between ED visits for asthma and CO; however, CO was associated with
hospital admissions in Seattle (20). The Reno study used the highest
hourly maximum level in their local air pollution network, and the
Anchorage study used the daily average 8-hr maximum concentration during
winter months. The Seattle hospital admission study (20) used the daily
average of four monitoring stations. In the present study, we used a
24-hr average of four sites in our study region for the entire 15
months. Because CO has no biologically plausible mechanism for the
exacerbation of asthma (37) we interpret it as a general indicator of
air pollution. The significant association between increased ED visits
for asthma and CO found in this analysis could result from the high
correlation between CO and PM10 (0.74) as well as light scattering
(0.74). To explore this possibility, a factor analysis of the physical
and chemical nature of air pollution in Seattle was conducted on both
the CO and particulate composition data collected previously (38) at the
southernmost PM site in this study. Factor analysis with a varimax
rotation has been used to both examine the colinearity among the various
air pollutant variables and to identify important features of the
variability in these pollutants (Table 5) (39,40). Main et al. (38)
measured the composition of PM2.5 or fine soil and coarse PM
(PM10-PM2.5). Coarse and fine soil mass were reconstructed by adding the
mass of the oxides of soil species (Si, Ca, Fe, and Ti) (41). Using
these data we derived three factors which explained 95% of the variance
and show that the variability in PM2.5 composition is influenced by
three factors: a) incomplete combustion products consisting of CO,
elemental carbon, organic carbon, and soluble potassium (wood smoke
marker); b) secondary aerosols consisting of ammonium and sulfate; and
c) fine and coarse soil (Table 5). The light scattering and PM10 data
are correlated with the first factor scores, with correlation
coefficients of 0.81 and 0.77, respectively. Note that CO is associated
with the buildup of incomplete combustion-derived products including
particulate organic carbon and particulate elemental carbon. 

This study did not find a significant association between NO2, SO2, or
ozone and increased ED asthma visits. The NO2, SO2, and ozone
measurements are only taken at one site in the network and may be
subject to a greater degree of exposure misclassification than the CO
and PM pollutant measures that represent averages of three to four sites
in the study area. In addition, the SO2 concentrations were low, with a
mean daily 1-hr maximum concentration of 6 ppb. Other investigators have
reported that the peak hourly NO2 concentration was significantly
associated with increased ED visits for asthma during winter months in
Northern California (15) and with increased ED visits and respiratory
admissions in Athens, Greece (28). Peak hourly NO2 was also associated
with increased ED visits for asthma during both the winter and summer
months in Barcelona, Spain (14). The average peak NO2 concentrations in
the Northern California, Athens, and Barcelona studies were 69 ppb, 50
ppb, and 58 ppb, respectively. These concentrations are significantly
higher than the average peak hourly NO2 concentration of 35 ppb observed
in this study. Our finding of no significant association between ED
asthma visits and maximum hourly SO2 is consistent with the earlier
Seattle study (12) and the study in Barcelona (14). The lack of a
significant association between ED visits for asthma and ozone in this
study may be due to the large number of missing measurements. 

In summary, this study found a small but significant association between
air pollution and increased ED visits for asthma in children in Seattle.
PM and CO concentrations in this study were associated with increased
childhood ED visits for asthma and represent the daily variation in
incomplete combustion products including elemental carbon and organic
carbon. Results from this study of a susceptible subpopulation show
significant increases of ED asthma visits for children with daily PM2.5
concentrations substantially below the newly adopted National Ambient
Air Quality Standard of 15 µg/m annually (42). 

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