Context Vehicle exhaust is a major source of ozone and other air pollutants.
Although high ground-level ozone pollution is associated with transient increases
in asthma morbidity, the impact of citywide transportation changes on air
quality and childhood asthma has not been studied. The alternative transportation
strategy implemented during the 1996 Summer Olympic Games in Atlanta, Ga,
provided such an opportunity.
Objective To describe traffic changes in Atlanta, Ga, during the 1996 Summer Olympic
Games and concomitant changes in air quality and childhood asthma events.
Design Ecological study comparing the 17 days of the Olympic Games (July 19–August
4, 1996) to a baseline period consisting of the 4 weeks before and 4 weeks
after the Olympic Games.
Setting and Subjects Children aged 1 to 16 years who resided in the 5 central counties of
metropolitan Atlanta and whose data were captured in 1 of 4 databases.
Main Outcome Measures Citywide acute care visits and hospitalizations for asthma (asthma events)
and nonasthma events, concentrations of major air pollutants, meteorological
variables, and traffic counts.
Results During the Olympic Games, the number of asthma acute care events decreased
41.6% (4.23 vs 2.47 daily events) in the Georgia Medicaid claims file, 44.1%
(1.36 vs 0.76 daily events) in a health maintenance organization database,
11.1% (4.77 vs 4.24 daily events) in 2 pediatric emergency departments, and
19.1% (2.04 vs 1.65 daily hospitalizations) in the Georgia Hospital Discharge
Database. The number of nonasthma acute care events in the 4 databases changed
–3.1%, +1.3%, −2.1%, and +1.0%, respectively. In multivariate
regression analysis, only the reduction in asthma events recorded in the Medicaid
database was significant (relative risk, 0.48; 95% confidence interval, 0.44-0.86).
Peak daily ozone concentrations decreased 27.9%, from 81.3 ppb during the
baseline period to 58.6 ppb during the Olympic Games (P<.001). Peak weekday morning traffic counts dropped 22.5% (P<.001). Traffic counts were significantly correlated
with that day's peak ozone concentration (average r
= 0.36 for all 4 roads examined). Meteorological conditions during the Olympic
Games did not differ substantially from the baseline period.
Conclusions Efforts to reduce downtown traffic congestion in Atlanta during the
Olympic Games resulted in decreased traffic density, especially during the
critical morning period. This was associated with a prolonged reduction in
ozone pollution and significantly lower rates of childhood asthma events.
These data provide support for efforts to reduce air pollution and improve
health via reductions in motor vehicle traffic.
Despite advances in asthma therapy, asthma remains a substantial public
health problem. In the United States, asthma is a leading cause of childhood
morbidity, with an estimated prevalence of 6.9% in children and youth younger
than 18 years.1 Numerous studies have documented
a rise in the morbidity, mortality, and prevalence of asthma in different
populations.2-8
The cause or causes of this trend remain controversial.9-11
Experimental, laboratory, and epidemiologic studies in the last several
years have linked high concentrations of known air pollutants to respiratory
health problems, most notably exacerbations of asthma.12-23
However, opportunities to study the health effects of anthropogenic improvements
in air quality are rare. One study found a decrease in particulate pollution
and respiratory hospital admissions associated with the closure of an industrial
factory in that community.24 To our knowledge,
no study has examined the impact of improved ozone pollution for an extended
period of time on asthma exacerbations or other markers of asthma morbidity.
Also, the extent to which moderate concentrations of ozone (ie, daily peak
of 50-100 ppb) during various exposure lengths affects asthma morbidity remains
controversial.12-16
The main sources of ambient air pollutants are vehicle exhaust, industry,
power generation plants, and background contamination. Compared with emissions
from nonvehicle sources, the relative amounts of nitrogen oxides, carbon monoxide,
and small particulate matter emitted from vehicles have increased disproportionately
due to the dramatic increase in worldwide automobile use in the past 30 years.12,15 Many studies have found positive
associations between traffic density on street of residence and either asthma
events or asthma prevalence.25-29
However, the impact of citywide automobile use and traffic flow on ambient
air pollution and asthma morbidity has not been studied.
The 1996 Summer Olympic Games in Atlanta, Ga, provided a unique opportunity
to study the relationship between automobile traffic, air quality, and asthma
morbidity. Preparations for the Olympic Games required a strategy for minimizing
road traffic congestion and ensuring that spectators could reach Olympic events
in a reasonable amount of time. Additionally, the more than 1 million visitors
to Atlanta (resulting in increased regional transportation demands) could
have magnified the region's existing air quality violations for ozone pollution
that occur each summer. Atlanta's strategy was similar to that used in Los
Angeles, Calif, for the 1984 Summer Olympic Games.30
It included the development and use of an integrated 24-hour-a-day public
transportation system, the addition of 1000 buses for park-and-ride services,
local business use of alternative work hours and telecommuting, closure of
the downtown sector to private automobile travel, altered downtown delivery
schedules, and public warnings of potential traffic and air quality problems.31-33
We used an ecological study design and compared the 17 days of the 1996
Summer Olympic Games (July 19–August 4) to a summertime baseline period
defined as the 4-week periods before and after the Olympic Games (June 21–July
18 and August 5–September 1). We measured the number of asthma acute
care events, number of nonasthma acute care events, air pollution, meteorological
conditions, and amount of vehicular traffic. The specific dates for study
were determined before any data were analyzed. Four-week baseline periods
were used to avoid the spring and fall seasons, which can affect ozone levels12,13 and asthma exacerbation rates.34
Medical Definitions and Data Collection
Our primary outcome measure was the number of hospitalizations, emergency
department visits, and urgent care center visits for asthma. The study population
included persons aged 1 through 16 years residing in the 5 central counties
of metropolitan Atlanta (ie, Fulton, DeKalb, Cobb, Gwinnett, and Clayton).
Because of their central location, these densely populated counties were more
likely to experience dramatic changes in air quality in response to changes
in driving and commuting behaviors (ie, greater access to public transportation
as an alternative). Visitors to Atlanta were excluded from the study.
Data regarding asthma acute care events were collected from Georgia's
Medicaid claims file, the patient database of a health maintenance organization
(HMO), computerized emergency department records from 2 of the 3 pediatric
hospitals in Atlanta (combined to create a single emergency department data
source), and the Georgia Hospital Discharge Database, which includes hospitalization
records from all metropolitan Atlanta hospitals. Medical records at the 1
publicly funded pediatric hospital in Atlanta were not available for review.
However, 60% to 66% of children seeking emergency care at that hospital were
receiving Medicaid in 1996 (Robert J. Geller, MD, written communication, January
17, 2001). Therefore, we believe that the Medicaid files captured clinical
information on most of this population. For the Georgia Hospital Discharge
Database, a child admitted to a metropolitan Atlanta hospital during the study
period with a primary diagnosis of asthma (International
Classification of Diseases, Ninth Revision [ICD-9], code 493) met our
study definition for an asthma acute care event. For the other 3 data sources,
a child seen in an emergency department or urgent care center with a primary
diagnosis of asthma met our study definition for an asthma acute care event,
regardless of whether the child was hospitalized.
To determine if the study population was more, less, or as likely to
seek emergency services in general during the Olympic period compared with
the periods before and after the Olympic Games, or if the size of the study
population significantly changed during the Olympic Games, we collected and
analyzed data on the day-by-day total number of all nonasthma-related acute
care events during the study period among Atlanta residents aged 1 through
16 years from the same 4 data sources.
Air Quality Data Collection
All data on primary pollutants (ie, particulate matter of 10 µm
or smaller [PM10], carbon monoxide, nitrogen dioxide, and sulfur
dioxide) and secondary pollutants (ozone) were obtained jointly from the Environmental
Protection Agency (EPA) and the Environmental Protection Division of Georgia's
Department of Natural Resources. All air quality measurement sites used in
the study were located in the 5 central counties of Atlanta and were state
operated and EPA regulated (Figure 1).
The ozone concentration chosen to represent each day's exposure was
the average of the peak 1-hour ozone concentrations from the 3 monitoring
sites in the study area. The daily 1-hour peak ozone levels for the same time
periods in 1997-1998 were used for comparison. To see if other areas in the
region with similar weather patterns experienced similar ozone patterns during
the 1996 summer, we obtained daily 1-hour peak ozone concentrations at 3 other
Georgia sites (Fannin County, Augusta, and Columbus), all 60 to 150 miles
from Atlanta.
We used the EPA's standard method of measuring the 4 major primary pollutants.35 Data on PM10 were collected at the 1 site
capable of continuous 24-hour monitoring and expressed as the cumulative total
for each 24-hour period. The mean 8-hour running daily peak carbon monoxide
level, the 24-hour daily mean sulfur dioxide level, and the 1-hour daily peak
nitrogen dioxide level were collected at 1, 2, and 3 monitoring sites, respectively.
The daily levels obtained at the 2 sulfur and 3 nitrogen dioxide sites were
then averaged. Allergen exposure was determined by total daytime mold counts
(the predominant summertime allergen in Atlanta) collected weekdays during
the study period at the Atlanta Allergy and Asthma Clinic.
We obtained hourly data for 5 weather-related variables (temperature,
wind speed, relative humidity, barometric pressure, and solar radiation) from
a state-run weather monitoring site located east of downtown Atlanta. These
5 variables have a direct or indirect impact on the rate of ozone formation
and clearance in the lower atmosphere and, to a lesser extent, can affect
levels of the primary pollutants.12 For each
day and for each variable, we calculated the mean of the 12 readings from
6 AM to 6 PM.
We obtained hourly traffic data collected by the Georgia Department
of Transportation from the 4 functioning sites (2 highways and 2 local roads)
located within Atlanta's perimeter interstate highway. Total 24-hour and 1-hour
morning peak bidirectional traffic counts were available for analysis for
92% of the study weekdays and 85% of the study weekend days.
Public Transportation Data
We examined the total number of passenger trips per day on Atlanta's
public buses and rail lines during the study period. The Metro Atlanta Rapid
Transit Authority provided data for average weekday and weekend daily ridership
totals for the pre- and post-Olympic Games periods. For the Olympic period,
totals for each of the 17 days were available for analysis.33
We collected and compared total gallons of gasoline purchased in the
state of Georgia in June, July, and August 1991-1997. The Georgia State Department
of Revenue routinely calculates these gallon totals based on receipts of the
state fuel tax. The month of purchase was determined by the month in which
the fuel distributors delivered the gasoline to individual filling stations.
We analyzed all collected data to determine the percentage change in
mean values during the Olympic period compared with the 1996 summertime baseline
period. One-way analysis of variance t testing was
used to determine if the daily air pollutant, meteorological, and traffic
count values differed significantly between the 2 study periods. Significance
was defined as P≤.05.
Further analysis of the asthma event data was performed using a time-series
Poisson regression model. Univariate and adjusted relative risk (RR) (with
95% confidence intervals [CIs]]) of asthma acute care events during the Olympic
period compared with the baseline period was calculated for each of the 4
sources of data. The univariate analysis was based on the fraction of total
acute care events with a primary diagnosis of asthma. The multivariate time-series
Poisson model was fitted using generalized estimating equations to address
possible serial (auto) correlation in the number of asthma events.36 Models were implemented using the GENMOD procedure
in SAS with AR(1) (SAS Institute Inc, Cary, NC) to account for correlation
in asthma events on a given day with the previous day's events. The Durbin-Watson
statistic was 1.96-2.01, which indicates minimal residual serial correlation.
This model was adjusted for day of the week (weekday vs weekend) and minimum
temperature (lagged 1 day to improve the fit of the model). Total mold counts
were only collected on weekdays, and therefore, were not included in the multivariate
model. Seasonality and time trends were not included in this model due to
the very short study period covering only the summer season. The Olympic period
was modeled here instead of ozone or PM10 levels due to the correlation
between these variables and because we wanted to emphasize the changes directly
associated with the Olympic Games.
A second autoregressive time-series model analyzed the change in ozone
concentrations in Atlanta and the other 3 Georgia sites during the Olympic
Games. The model was used to adjust for day of the week (weekday vs weekend)
and trends in weather conditions (mean daytime wind speed, temperature, solar
radiation, and barometric pressure). Relative humidity was not included because
it was strongly correlated with solar radiation (inverse relationship). The
model (using AR[1]) found minimal serial correlation in daily ozone levels
(Durbin-Watson statistic, 1.94).
In a separate analysis, Pearson coefficients were used to measure the
correlation between morning peak–total traffic counts and that day's
peak ozone concentration. Significance was defined as P≤.05.
In addition to our analyses comparing the Olympic period with the baseline
period, data for all 73 study days were used to examine the relationship between
ozone accumulation and daily asthma acute care events. The mean number of
asthma events was determined for days in which the peak ozone concentrations
for that day plus the previous 2 days averaged less than 60 ppb (low cumulative
exposure), 60 to 89 ppb (moderate cumulative exposure), or 90 ppb or more
(high cumulative exposure). Controlling for day of the week and minimum temperature
(lagged 1 day) in a Poisson regression model, the RR of asthma events was
determined at cumulative ozone concentrations of 60 to 89 ppb and 90 ppb or
more compared with ozone concentrations less than 60 ppb.
To test our hypothesis that cumulative exposures to air pollutants for
2 to 3 days are more strongly associated with asthma acute care events than
traditional single-day exposures, we compared the RR of asthma events per
50 ppb incremental change in ozone and 10-µg/m3 incremental
change in PM10 levels based on a same-day, 2-day, and 3-day cumulative
exposure measure. We used time-series regression models similar to our primary
asthma event model except that the dependent variable (Olympic vs baseline
period) was replaced by a single pollutant exposure variable.
Among children aged 1 through 16 years in the Medicaid claims file database,
the number of asthma emergency care visits and hospitalizations decreased
from 4.23 events per day during the baseline period to 2.47 events per day
during the Olympic period, a 41.6% overall decrease (Table 1). The number of asthma-related emergency department, urgent
care visits, and hospitalizations among HMO enrollees decreased 44.1% during
the same time period. Asthma-related visits to 2 large pediatric emergency
departments in Atlanta decreased 11.1%, and citywide hospitalizations for
asthma were reduced 19.1%. Using our 4 data sources, this equates to respectively
30, 10, 9, and 7 fewer emergency asthma events during the Olympic Games than
would have been expected based on the pre- and post-Olympic period averages.
The total number of nonasthma-related acute care events per day decreased
only 3.1% in the Medicaid database and 2.1% at the pediatric emergency departments;
this number increased 1.3% among HMO enrollees. Nonelective nonasthma hospitalizations
increased 1.0% during the Olympics.
As illustrated in Table 2,
the univariate RR of asthma acute care events during the Olympics compared
with the baseline period was significantly reduced in the Medicaid database
(RR, 0.61; 95% CI, 0.44-0.85) and approached statistical significance in the
HMO database (RR, 0.56; 95% CI, 0.31-1.02). Although less than 1, the RR at
the 2 pediatric emergency departments and among those hospitalized was not
significant (RR, 0.91 and 0.81, respectively). Adjusting the RR to control
for minimum temperature and day of the week did not alter these findings.
The data from Atlanta's Medicaid database remained statistically significant
(adjusted RR, 0.48; 95% CI, 0.44-0.86).
Figure 2 shows the daily time
series of each of the 5 measured pollutants and mold counts during the Olympic
and baseline periods. The 1-hour peak ozone concentration in Atlanta decreased
27.9% from an average daily peak of 81.3 ppb during the baseline period to
58.6 ppb during the Olympic Games (P<.001). The
daily ozone concentrations at the 3 monitoring sites in Atlanta were highly
correlated (r = 0.91-0.97). Combined ozone data for
the 1997 and 1998 summer seasons did not show a similar decrease—the
average peak ozone concentration was 77.2 ppb during July 19–August
4 and 78.8 ppb during the remainder of the study dates.
Ozone concentrations at Georgia sites outside of Atlanta decreased 11.1%
in Augusta (58.8 ppb vs 66.2 ppb; P = .11), 17.5%
in Fannin County (50.5 ppb vs 61.2 ppb; P = .003),
and 18.5% in Columbus (52.2 ppb vs 64.1 ppb; P =
.01) during the Olympic Games. These ozone reductions were, respectively,
60%, 37%, and 34% less than the ozone reductions experienced in Atlanta during
the same period with similar weather conditions. After controlling for the
4 weather variables, serial correlation, and day of the week in a time-series
regression model, the reduction in Atlanta's ozone concentrations during the
Olympic Games was 13% (P = .06). Comparatively, the
reduction in ozone was calculated at 2% in Augusta (P
= .71), 7% in Fannin County (P = .12), and 6% in
Columbus (P = .30).
During the Olympic period, Atlanta additionally experienced significant
reductions in daily carbon monoxide levels (1.26 vs 1.54 ppm, 18.5% decrease; P = .02) and PM10 concentrations (30.8 vs 36.7
µg/m3, 16.1% decrease; P = .01).
Nitrogen dioxide levels decreased 6.8% (36.5 vs 39.2 ppb; P = .49), whereas sulfur dioxide levels increased 22.1% (4.29 vs. 3.52
ppb; P = .65). Figure
3 summarizes these findings relative to the EPA National Ambient
Air Quality Standards for each of these pollutants.35
Data for the baseline period are divided into pre- and post-Olympic time periods
demonstrating the uncharacteristic decrease in air pollution levels during
the Olympic Games.
Mean daytime weather conditions in Atlanta were determined for both
the Olympic and baseline periods. Temperature decreased 0.67°C, wind speed
increased 0.19 m/sec, and solar radiation decreased 29.6 W/m2 during
the Olympic Games. These changes were not statistically significant. Barometric
pressure did not change. Total mold counts did not differ significantly during
the Olympic vs the baseline period (daily mean, 597 vs 551 molds/m3; P = .58; Figure 2).
Moreover, mold counts were not correlated with same-day asthma events (average r = −0.15).
Weekday 1-hour morning peak traffic counts decreased 22.5% overall during
the Olympic Games (range, 17.5%-23.6%; P<.001
for all 4 sites). This amounted to a reduction of 4260 vehicle trips during
the peak morning traffic hour on these 4 roads. Weekend morning peak traffic
counts decreased 9.7% overall (range, 3.6%-12.3%), although only the change
in traffic counts at the site closest to downtown was significant. Weekday
total 24-hour traffic counts decreased 2.8% overall (range, 1.3%-3.6%), with
the significant changes occurring at the 2 sites closest to downtown. Public
transportation ridership increased 217% (190% on weekdays; 334% on weekends)
during the Olympic Games. A total of 17.5 million more trips occurred on public
transportation throughout the Olympic Games than would be expected based on
the baseline period ridership.
Weekly total gallons of gasoline purchased in Atlanta were not available
for analysis. The number of gallons of gasoline purchased statewide in July
1996 was 3.9% lower than June and August 1996. In contrast, July sales for
1995 and 1997 were 1.2% higher than the June and August sales for those 2
years.
To explore whether automobile traffic is a critical factor in urban
ozone accumulation, we analyzed the relationship between weekday traffic counts
and peak ozone concentrations on that day. We found a significant correlation
between 1-hour morning peak traffic counts and peak ozone concentrations at
all 4 traffic-count sites (Pearson r = 0.29, 0.42,
0.34, and 0.39, respectively; average r = 0.36).
No difference in this correlation was seen between the Olympic and baseline
periods. An equally strong and significant correlation was found between total
24-hour traffic counts and ozone concentrations (average r = 0.38; range, 0.33-0.48).
We used data from the entire 73-day study period to analyze the relationship
between the number of asthma acute care events on a given day and the average
daily peak ozone concentration during the preceding 48 to 72 hours. For data
from the Medicaid, HMO, and emergency department databases, the RR of asthma
events increased stepwise at cumulative ozone concentrations 60 to 89 ppb
and 90 ppb or more compared with ozone concentrations of less than 60 ppb
(Table 3). This trend was significant
for the Medicaid and emergency department data.
A 3-day cumulative exposure measure was selected for the analysis shown
in Table 3 instead of a single-day
or 2-day exposure measure because it was found to be more consistently correlated
with asthma events (Table 4).
For data from the Medicaid and pediatric emergency department databases, the
RR of asthma events per incremental changes in ozone and PM10 levels
increased as the number of cumulative exposure days included increased from
1 to 2. The RR per incremental change in PM10 further increased
when the number of cumulative exposure days increased from 2 to 3. However,
increasing the cumulative exposure from 2 to 3 days did not further increase
the RR per incremental change in ozone.
Evidence linking air quality to respiratory health has been accumulating
in recent years. Many studies, including 2 conducted in Atlanta,16,37
have demonstrated significant associations between days with high ozone levels
and increased rates of asthma exacerbations.12-15,20-23
Our results support these previous findings and also indicate that extended
reductions in ozone and PM10 concentrations at levels considerably
below the EPA's National Ambient Air Quality Standards can reduce asthma morbidity
in children. Furthermore, our findings suggest that by decreasing automobile
emissions through citywide changes in transportation and commuting practices,
a substantial number of asthma exacerbations requiring medical attention can
be prevented.
We found variation in the relative change in asthma acute care events
during the Olympic Games among the 4 sources of medical data. All showed a
decrease in asthma events, ranging from 11% to 44%. Only the data from the
Georgia Medicaid claims file reached statistical significance, which may be
related to the low power of this short-term intervention. Based on a power
of 80% and the number of events in each database, the percent reduction in
asthma events needed to detect a significant difference between the baseline
and Olympic periods was 37% for the Georgia Medicaid claims file, 58% for
the health maintenance organization database, 33% for the pediatric emergency
room database, and 51% for the Georgia Hospital Discharge database (without
adjustment for serial correlation). Other possible explanations include differences
between the study population in the 4 data sources in asthma severity, medication
use,38 exposure to other allergens, particularly
those that could synergistically worsen the untoward effects of ozone and
other air pollutants,39,40 extent
of indoor ozone exposure,41 and of outdoor
exposure.
The observed reductions in asthma events require us to address the following
potentially confounding situation: did enough Atlanta children leave the city
during the Olympics to significantly reduce the number of children with asthma
who would seek medical attention for an acute asthma exacerbation? If true,
this could account, in whole or in part, for the reduction in asthma events
observed. However, for all 4 data sources, use of nonasthma-related urgent
and emergency medical services by Atlanta children changed minimally. This
suggests that neither the size of the study population nor use of emergency
medical services by this population changed significantly during the Olympic
games.
Of the factors potentially affecting asthma morbidity that we could
readily assess, air quality remains the likely cause for the decline in asthma
acute care events. Our analysis demonstrated a large and significant decrease
in ozone concentrations, and to a lesser extent, PM10, and carbon
monoxide concentrations. Of all the pollutants, Atlanta's ozone concentrations
in the summer most frequently violate the National Ambient Air Quality Standards.42 These standards attempt to set a maximum pollution
level, which, if exceeded, may be hazardous to the general public's health.
The standards are based, in part, on the available information regarding the
health effects of the 5 major air pollutants. However, pollution levels below
these standards may be harmful to certain, high-risk populations (such as
individuals with asthma and the elderly). Therefore, the 28% drop in ozone
concentrations during the Olympic Games represented a substantial decrease
in a potential health hazard.
Our study design and findings make it difficult to determine to what
degree the observed reductions in ozone, PM10, carbon monoxide,
and nitrogen dioxide pollution individually contributed to the observed changes
in health. As controlled studies of human exposure to multiple pollutants
have demonstrated,12,13,19
the effects of reduced levels of ozone and these primary pollutants likely
were additive. This is supported by the finding that both ozone and PM10 levels were similarly correlated with asthma events. The fact that
ozone and PM10 levels were highly correlated with each other (r = 0.58-0.69) additionally limits our ability to determine
which pollutant(s) accounted for the reduction in asthma events. This correlation
between ozone and PM10 levels should have been expected, given
that the environmental changes occurring during the study period (ie, decreased
automobile emissions and weather variability) would have had a strong influence
on the daily levels of both these pollutants.
The more immediate question is what accounted for this change in air
quality. We suggest that it was caused by changes in both meteorological conditions
and automobile emissions, with decreases in peak morning rush hour traffic
playing a major role. Weather conditions during the Olympic Games (increased
wind speed and decreased temperature and solar radiation) favored less accumulation
of ozone, but the degree of weather improvements was measurably small and
not statistically significant. Even when controlling for these weather variables
in a multivariate regression model, ozone levels in Atlanta during the Olympic
Games were reduced 13% whereas the changes in ozone levels at the other 3
Georgia sites with the same prevailing weather patterns were reduced between
2% and 7%.
Other indirect evidence supports our conclusion. The concentration of
carbon monoxide, which is primarily emitted directly from automobiles and
is much less dependent on weather conditions for its accumulation in the lower
atmosphere, decreased significantly during the Olympic Games. The small increase
in sulfur dioxide levels (far below health hazard levels) during the Olympic
Games is consistent with the increased use of diesel-powered buses,31,32 and should not have increased if
the prevailing weather conditions had indeed prevented the normal accumulation
of air pollutants in Atlanta. The amount of emissions from stationary sources
(eg, power plants and industry) did not change during the Olympic Games.31,32 The additional electrical needs required
during the Olympic Games came from power stations outside the immediate Atlanta
area and, therefore, would not have caused the increase in sulfur dioxide
observed.
Evidence of changes in automobile traffic and emissions include the
marked decreases in weekday and weekend morning peak traffic counts at all
4 traffic-count sites, the statistically significant decreases in weekday
total traffic counts at the 2 traffic-count sites closest to downtown Atlanta,
the statistically significant correlation between weekday morning peak and
24-hour total traffic counts and that day's peak ozone concentration, the
3.9% decrease in statewide gasoline sales in July compared with June and August,
and the 217% increase in overall public transportation use. These traffic
data probably underestimate the impact of the alternative transportation strategies
on local residents of Atlanta because they include automobile use by the estimated
1 million visitors during the Olympic intervention period. Using this same
logic, however, the increase in public transportation use is probably an overestimation
of the behaviors of local residents since it also includes use by visitors
to Atlanta.
The science of ozone formation helps explain our findings. The moderate
alterations in morning traffic levels (and probably traffic flow) experienced
during the Olympic Games would have decreased the buildup of ozone precursors
emitted into the atmosphere from 7 AM through 2 PM. Without sufficient atmospheric
concentrations of these precursors being present during this time of maximum
sunlight and heat, rapid ozone production and accumulation could not occur,
thus leading to lower than anticipated peak ozone levels. During a period
of 17 days, this appeared to have contributed to the improved respiratory
health of children with asthma residing in Atlanta. What motivated businesses
and individuals to change their transportation and commuting behaviors temporarily
is a crucial question, which has not been properly addressed. Fear of traffic
and lack of parking, and social pressures to conform certainly played a role.
How this can be adapted to more routine conditions remains a major public
health challenge. For example, Atlanta's Clean Air Campaign43
(largely initiated after the Olympic Games) has been shown to increase use
of alternative commuting methods within 3 companies that promoted this.44 But the effects of this citywide campaign on air
pollution to date appear to be small compared with what was observed during
the Olympic Games.
The weight of evidence linking air quality to respiratory health continues
to grow. Our findings suggest that efforts to decrease ozone and PM10 concentrations from moderate to low levels can decrease the burden
of asthma. Consistent with our findings for the Olympic period, we found an
increasing correlation between daily asthma events and ozone and PM10 levels as the period of exposure was increased from less than 24 hours
preceding the asthma event to the 48 to 72 hours preceding the event. When
using this 3-day cumulative exposure measure, the risk of asthma exacerbations
increased substantially after only moderate levels of ozone exposure (60-89
ppb). These data suggest that the cumulative effect of moderate levels of
ozone and other pollutants during a more extended period is as or more important
to respiratory health than single-day levels exceeding the national standards
(ie, 1-hour peak ozone >120 ppb or 8-hour peak >80 ppb). Recent research with
PM10 supports the important effect of extended exposure to pollutants
on respiratory health.45,46
Our study methods and findings have several limitations. The special
nature of the Olympic Games, the relatively short intervention period and
limited statistical power, the lack of an updated traffic counting system,
and the limited number of air pollution monitoring sites (for PM10
and carbon monoxide) make firm conclusions difficult. Unmeasured medical or
social factors may have influenced our findings. A citywide alternative transportation
and commuting intervention, not associated with a special event, would provide
a better study situation. However, the power of the Olympic Games to transform
behavioral norms should not be underestimated and deserves close scrutiny
for its lessons.
We conclude that the alternative transportation plan in Atlanta during
the Olympic Games reduced ozone and other air pollutants and was associated
with a significant, albeit temporary, decrease in the burden of asthma among
Atlanta's children.
1.Centers for Disease Control and Prevention. Measuring childhood asthma prevalence before and after the 1997 redesign
of the National Health Interview Survey—United States.
MMWR Morb Mortal Wkly Rep.2000;49:908-911.Google Scholar 2.Mannino DM, Homa DM, Pertowski CA, Ashizawa A, Nixon LL, Johnson CA, Ball LB, Jack E, Kang DS.Centers for Disease Control and Prevention. Surveillance for asthma—United States, 1960-1995: CDC surveillance
summaries.
Mor Mortal Wkly Rep CDC Surveill Summ.1998;47:1-27.Google Scholar 3.Centers for Disease Control and Prevention. Asthma—United States, 1982-1992.
MMWR Morb Mortal Wkly Rep.1995;43:952-955.Google Scholar 4.Centers for Disease Control and Prevention. Asthma mortality and hospitalization among children and young adults—United
States, 1980-1993.
MMWR Morb Mortal Wkly Rep.1996;45:350-353.Google Scholar 5.Abramson MJ, Kutin J, Czarny D, Walters EH. The prevalence of asthma and respiratory symptoms among young adults:
is it increasing in Australia?
J Asthma.1996;33:189-196.Google Scholar 6.Anderson HR. Increase in hospital admissions for childhood asthma: trends in referral,
severity and readmissions from 1970 to 1985 in a health region of the United
Kingdom.
Thorax.1989;44:614-619.Google Scholar 7.Goren AI, Hellmann S. Has the prevalence of asthma increased in children? evidence from a
long term study in Israel.
J Epidemiol Community Health.1997;51:227-232.Google Scholar 8.Mullaly DI, Howard WA, Hubbard TJ.
et al. Increased hospitalizations for asthma among children in the Washington,
DC area during 1961-1981.
Ann Allergy.1984;53:15-19.Google Scholar 9.Becklake MR, Ernst P. Environmental factors.
Lancet.1997;350 Suppl 2:SII10-SII13.Google Scholar 10.Schenker M. Air pollution and mortality.
N Engl J Med.1993;329:1807-1808.Google Scholar 11.Abramson MJ, Marks GB, Pattemore PK. Are non-allergenic environmental factors important in asthma?
Med J Aust.1995;163:542-545.Google Scholar 12.Holgate ST, Samet JM, Koren HS, Maynard RL. Air Pollution and Health. London, England: Academic Press; 1999.
13.Committee of the Environmental and Occupational Health Assembly, American
Thoracic Society. Health effects of outdoor air pollution.
Am J Respir Crit Care Med.1996;153:3-50.Google Scholar 14.Brunekreef B, Dockery DW, Krzyzanowski M. Epidemiologic studies on short-term effects of low levels of major
ambient air pollution components.
Environ Health Perspect.1995;103(suppl 2):3-13.Google Scholar 15.Tatterfield AE. Air pollution: brown skies research.
Thorax.1996;51:13-22.Google Scholar 16.White MC, Etzel RA, Wilcox WD, Lloyd C. Exacerbations of childhood asthma and ozone pollution in Atlanta.
Environ Res.1994;65:56-68.Google Scholar 17.Anderson HR, Ponce de Leon A, Bland JM.
et al. Air pollution and daily mortality in London: 1987-92.
BMJ.1996;312:665-669.Google Scholar 18.Buchdahl R, Parker A, Stebbings T, Babiker A. Association between air pollution and acute childhood wheezy episodes:
prospective observational study.
BMJ.1996;312:661-665.Google Scholar 19.Avol EL, Linn WS, Shamoo DA.
et al. Respiratory effects of photochemical oxidant air pollution in exercising
adolescents.
Am Rev Respir Dis.1985;132:619-622.Google Scholar 20.Cody RP, Weisel CP, Birnbaum G, Lioy PJ. The effect of ozone associated with summertime photochemical smog on
the frequency of asthma visits to hospital emergency departments.
Environ Res.1992;58:184-194.Google Scholar 21.Romieu I, Meneses F, Sienra-Monge JJ.
et al. Effects of urban air pollutants on emergency visits for childhood asthma
in Mexico City.
Am J Epidemiol.1995;141:546-553.Google Scholar 22.Romieu I, Meneses F, Ruiz S.
et al. Effects of air pollution on the respiratory health of asthmatic children
living in Mexico City.
Am J Respir Crit Care Med.1996;154:300-307.Google Scholar 23.Thurston GD, Lippmann M, Scott MB, Fine JM. Summertime haze air pollution and children with asthma.
Am J Respir Crit Care Med.1997;155:654-660.Google Scholar 24.Pope CA. Respiratory disease associated with community air pollution and a steel
mill, Utah Valley.
Am J Public Health.1989;79:623-628.Google Scholar 25.Livingstone AE, Shaddick G, Grundy C, Elliott P. Do people living near inner city main roads have more asthma needing
treatment? case-control study.
BMJ.1996;312:676-677.Google Scholar 26.Edwards J, Walters S, Griffiths RC. Hospital admissions for asthma in pre-school children: relationship
to major roads in Birmingham UK.
Arch Environ Health.1994;49:223-237.Google Scholar 27.Wjst M, Reitmeir P, Dold S.
et al. Road traffic and adverse effects on respiratory health in children.
BMJ.1993;307:596-600.Google Scholar 28.Weiland SK, Mundt KA, Ruckmann A, Keil U. Self-reported wheezing and allergic rhinitis in children and traffic
density on street of residence.
Ann Epidemiol.1994;4:243-247.Google Scholar 29.Murakami M, Ono M, Tamura K. Health problems of residents along heavy traffic roads.
J Hum Ergol (Tokyo).1990;19:101-106.Google Scholar 30. What You Can Do to Reduce Air Pollution . Washington, DC: United States Environmental Protection Agency Office
of Air and Radiation; 1992;12. EPA 450-K-92-002.
31.Balagas R. Improved Air Quality in Atlanta During the 1996 Olympic
Summer Games. Atlanta: Georgia Environmental Protection Division, Georgia Department
of Natural Resources; 1996.
32.Porter C. Changes in Air Quality and Transportation Associated
With the 1996 Atlanta Summer Olympics. Cambridge, Mass: Cambridge Systematics Inc; 1997. Prepared for: National
Cooperative Highway Research Program (NCHRP 8-33).
33.Metropolitan Atlanta Rapid Transit Authority. The Way to the Games: A Report on Mass Transit During
the 1996 Summer Olympic Games. Atlanta, Ga: MARTA; 1996.
34.Busse WW, Holgate ST. Asthma and Rhinitis. Cambridge, Mass: Blackwell Science; 1995.
35. Measuring Air Quality: The Pollutant Standards Index . Washington, DC: Environmental Protection Agency Office of Air Quality
Planning and Standards; 1994. EPA 451-K-94-001.
36.Zeger SL, Liang KY. Longitudinal data analysis for discrete and continuous outcomes.
Biometrics.1986;42:121-130.Google Scholar 37.Tolbert P, Mulholland JA, MacIntosh DL.
et al. Air quality and pediatric emergency room visits for asthma in Atlanta,
Georgia.
Am J Epidemiol.2000;151:798-810.Google Scholar 38.Hartert TV, Windom HH, Peebles RS, Friedhoff LR, Togias A. Inadequate outpatient medical therapy for patients with asthma admitted
to two urban hospitals.
Am J Med.1996;100:386-394.Google Scholar 39.Jorres R, Nowak D, Magnussen H. The effect of ozone exposure on allergen responsiveness in subjects
with asthma or rhinitis.
Am J Respir Crit Care Med.1996;153:56-64.Google Scholar 40.Molfino NA, Wright SC, Katz I.
et al. Effect of low concentrations of ozone on inhaled allergen responses
in asthmatic subjects.
Lancet.1991;338:199-203.Google Scholar 41.Hayes SR. Use of an indoor air quality model (IAQM) to estimate indoor ozone
levels.
J Air Waste Manage Assoc.1991;41:171-181.Google Scholar 44.Centers for Disease Control and Prevention. Corporate action to reduce air pollution—Atlanta, Georgia, 1998-1999.
MMWR Morb Mortal Wkly Rep.2000;49:153-156.Google Scholar 45.Delfino RJ, Zeiger RS, Seltzer JM, Street DH. Symptoms in pediatric asthmatics and air pollution: differences in
effects by symptom severity, anti-inflammatory medication use and particulate
averaging time.
Environ Health Perspect.1998;106:751-761.Google Scholar 46.Schwartz J. The distributed lag between air pollution and daily deaths.
Epidemiology.2000;11:320-326.Google Scholar