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An Association between Fine Particles and Asthma Emergency 

Department Visits for Children in Seattle

Gary Norris,1Sharon N. YoungPong,2Jane Q. Koenig,3 Timothy V. Larson,1 Lianne 

Sheppard,4and 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

 Introduction

 Methods

 Results

 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/m3in 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: air pollution, asthma, carbon monoxide, 

children, emergency departments, nitrogen dioxide, particulate matter. Environ 

Health Perspect 107:489-493 (1999) . [Online 6 May 1999] 

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: 

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). 

Seattle, Washington, is a hilly coastal city with a moderate climate. It is currently in 
compliance with all U.S. Environmental Protection Agency (EPA) air pollution standards. 

In Seattle, three studies have been conducted that found associations between the 

exacerbation of asthma and airborne particulate matter (PM). A study conducted during the 

heating season in a wood smoke impacted area found a significant association between 

decreased lung function in elementary school children with asthma and dry light scattering 

( sp), a measure of fine PM (8). Another study carried out in Seattle from 1989 to 1990 

found significant associations between both PM 10 μm in aerodynamic diameter (PM10) 

and light-scattering values (particles approximately 1.0 μm) and ED visits for asthma for 

patients aged 65 years and younger (12). Most recently, a study of hospital admissions for 

asthma found an estimated 4-5% increase in admission rate associated with several 

measures of PM air pollution [PM10, particulate matter 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). 
Figure 1. Map of study area showing the air pollution monitoring sites and the high and 

low emergency department asthma utilization regions. Abbreviations: PM10, particulate 

matter 10μm in aerodynamic diameter; sp, dry light scattering. 

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

Atmospheric data. Air quality data were obtained from the Puget Sound Air Pollution 

Control Agency (Seattle, WA) and the state of Washington Department of Ecology

(WDOE, Olympia, WA). Daily PM10 and dry light scattering data ( 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). 

The association between air pollution and increased ED visits for asthma was evaluated in 

the three utilization regions. Significant associations between increased ED visits for 

asthma and air pollution were found across the utilization regions (Table 4). Relative rates 

were calculated for an interquartile range (IQR; 75-25th percentile) increase in pollutant 

concentration. Fine particles measured as light-scattering coefficient ( 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/m3increase 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/m3PM2.5. 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. 

Figure 2. Time series of PM10 and PM2.5 data. Abbreviations: PM2.5, particulate matter 

2.5 μm in aerodynamic diameter; PM10, particulate matter 10 μm in aerodynamic 

diameter. 

a

Estimated 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/m3of 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/m

3

). 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 combustionderived 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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