Summary for Library of Congress control number 2007406196

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Many previous studies of acute asthma exacerbations and ambient air pollution have examined effects of
only a few of the many contaminants that are found in urban air, making it difficult to determine which
specific air pollutant or group of pollutants is most important in triggering hospital visits. In particular,
ambient particulate matter is usually characterized based only on mass concentration, despite the
knowledge that many particulate matter components such as acidity, metals or different carbon fractions
might have different effects on asthma morbidity. In addition, whereas numerous studies have reported
associations between daily air pollution concentrations and counts of hospital visits for asthma or other
respiratory diseases, few studies have evaluated whether risks for air pollution-related hospital visits vary
across communities that differ in their baseline health status. To investigate these issues, we conducted the
study reported below. The study's primary goals were to assess whether ambient air quality differed in two
New York City locations and to relate daily variation in the ambient concentrations of various air
contaminants to daily variation in acute asthma exacerbations in both communities.
Mid-town Manhattan and the South Bronx are separated by less than 5 miles. However, the two regions of
New York City differ greatly in levels of asthma morbidity. Although these differences are likely to be
caused by multiple factors, including differential access to primary care for asthma, the present study was
not designed to investigate these differences. Rather, we investigated whether day-to-day variations in air
pollution were associated with asthma emergency department (ED) visits in each community and compared
the magnitude of the air pollution effect between the two communities. To investigate this question, we
analyzed daily counts of ED asthma visits to hospitals serving two distinct communities, one in Manhattan
and the other in the South Bronx, and related those data to daily enhanced air monitoring data in each
We analyzed air quality and weather data collected over about a two year period, from January 1999
through November 2000, at two centrally located measurement stations sampling a broad range of
contaminants (Figure 1). In addition to data on many commonly measured chemical air pollutants,
information was collected on several components of airborne particulate matter that had not previously
been assessed for their possible association with asthma exacerbations. Emergency department data on
asthma visits for the corresponding dates were collected from the 22 hospitals throughout New York that
served the communities surrounding the air monitoring stations. Data for hospital patients who lived in zip
code areas within approximately 1.5 miles of either measurement site were extracted,
The study measured 24-hour average ambient air concentrations of acetone, aldehydes, chromium, iron,
nickel, manganese, hydrogen ion, sulfate, pollen and mold spores. One-hour average concentrations were
measured for ozone (03) sulfur dioxide (SO), nitrogen oxides (NO), number of particles measuring 0.007
to 2.5 micrometers, particulate matter <2.5 micrometers (PM2.5) and particulate matter < 10 micrometers
(PMoj). Three-hour average concentrations were measured for PM2.5 elemental and organic carbon. The
hourly data were used for calculating daily averages, maximum concentrations and, for ozone, eight-hour
moving averages. Meteorological data (temperature, wind speed and direction, humidity) were also
collected. Ambient air data were collected from one site in Manhattan from January 1999 through
November 2000, from one site in the Bronx from January 1999 through August 1999 and from a second
nearby site in the Bronx from September 1999 through November 2000.
Table 1. Mean Concentrations of Air Pollutants and Bioaerosols Measured in Bronx and
Manhattan. The values are summary statistics of all daily observations from January 1999 through
November 2000, including days with missing values that were imputed by regression modeling for the
time-series analysis of health data.
Air Contaminant                 Bronx                   Manhattan
Max 8-hour 03 (ppm)*                 0.027                     0.021
NO2 ppm)*                            0.031                     0.036
SOz ppm)*                            0.011                     0.012
PM     (g/mS)*                        14.5                      16.6
Max PM2. ( g/m 3)                     27.3                      27.5
Coarse PM (pg/ 3)t                    7.69                      7.10
Sulfate (g/m)*                        3.6                        4.0
pH *                                  5.15                      5.04
Elemental Carbon (tg/m3               1.19                      1.32
Oranic Carbon      m                  3.17                      3.09
Total Metals (ng/m)** r101                                      94.0
Total Aldehydes (/m3)                1 6.6                     16.2
Total Pollen (#/m3)                   22.3                      13.2
Total Mold (#/m )                      . 448                   490
"* Mean levels significantly different l(P < 005, paired t-test) between the two communities over the entire
study period.
"** Nickel was significantly higher in Manhattan compared to Bronx over entire study period
SCoarse PM (= PM10 - PM25) was not included in statistical comparisons of air quality in Bronx and
Manhattan, but was included as a key pollutant variable in the asthma ED visit analysis
SBronx was significantly higher than Manhattan for two of three pollen sub-categories; Manhattan was
significantly higher than Bronx for one of seven mold spore sub-categories.
Mean levels of PM2.5s, PM25. acidity, PM2s sulfate, PM25 nickel, acid gases, ammonia, sulfur dioxide and
nitrogen oxides were significantly higher in Manhattan than in the Bronx over the entire study period
(Table 1). Mean levels of ozone, ragweed pollen and grass pollen were significantly higher in the Bronx.
Statistical tests had power to detect small mean differences because of large sample sizes. Therefore,
although several mean comparisons were significantly different, the absolute differences in analyte
concentrations between the two sites were generally not large. For example, for most comparisons, the
higher mean was no more than about 1.6-fold larger than the lower meai, and many of the significant mean
differences were less than 1.2-fold.
Exploratory temporal analyses of certain air contaminants were conducted. PM 1 and PM2:, organic carbon
and elemental carbon were evaluated by the hour and day of week. Both sites exhibited a daily temporal
pattern in PM.0 and PM25 levels. Lowest levels were seen in the middle of the night (2 A.M.). The highest
levels were seen in the morning, with a smaller peak in the early evening. Particulate matter elemental
carbon concentrations peaked at 9 A.M. at both sites. The particulate organic carbon fraction increased
modestly in concentration from early in the morning to a high in the evening for Manhattan, whereas the
Bronx organic carbon levels remained nearly constant throughout the day. Acetone, elemental carbon,
nitrogen oxides, PM10 and particulate Fe were the only variables showing a noticeable day-of-week trend,
with somewhat lower daily means on Sundays, increasing through the week to Thursdays.
Table 2. Relative Riskst and 95% Confidence Intervals for Asthma ED Visits as Function of 5-Day
Mean Air Pollution and Bioaerosols from Single-Pollutant Models. Bold text indicates statistical
significance at the 0.05 level.
Air Contaminant               Bronx            Manhattan         Concentration
Max 8-hour 03                     1.06 (1.01, 1.10)  1.06 (0.94, 1.19)       0.024
Max 8-hour 03 (warm season)       1.08 (1.03, 1.12)  1.04 (0.91, 1.19)       0.024
N02                               1.10 (1.01, 1.18)  0.95 (0.72, 1.25)       0.034
SOl                               1.11 (1.06, 1.17)  0.99 (0.88, 1.12)       0.011
M215                             1.05 (1.01, 110)  1.04(0.94, 1.15)         15.9
Max PM2.5                        109 (1.03, 1.15)  1.04 (091, 1.18)          27.6
Coarse PM                         1.02 (1.00, 1.04)  1.02 (0.98, 1.07)        7.4
Sulfate                           1.03 (1.00, .06)  1.05 (0.98, 1.13)         3.9
pH                               0.99 (0.98, 1.00)  0.99 (0.95, 1.02)        5.07
Elemental Carbon                  1.04 (0.99, 1.09)  1.06 (0.94, 1.19)        125
rganic Carbon                   1.05 (0.93, 1.17)  1.20 (0.96, 1.49)        3.14
otal Metals                      1.02 (0.99, 1.05)  102 (0.91, 1.15)        93.5
otal Aldehydes                   1.02 (1.00, 1.04)  1.03 (0.96, 1.10)       16.1
Total Pollen                      1.00 (1.00, 1.00)t  1.01 (1.00, 1.02)       17.0
otal Mold                      1.01(0.99, 1.03)    1.01 (0.97, 1,06)         504
"* A mean Relative Risk of 1.10 indicates that an increase in the daily pollutant concentration equal to the
Pollutant Concentration Increment is associated, on average, with a 10% increase in daily asthma ED visits.
"** Increment value used to calculate relative risks in Tables 2 and 3 were based on the mean pollutant level
combining all data from both communities. Same units as in Table 1.
tWhen RR and CI bounds appear equal, it is due to rounding.
The air monitoring study was not designed to attribute air contaminant variability to particular sources.
However, air mass back-trajectory analysis was used to compare local and long-distance transport
contributions to total contaminant levels.' On an annual average basis, 39 - 47 percent of measured sulfate
concentrations was associated with long-distance transport from the west and southwest of New York. In
comparison, long-distance transport from those directions contributed 26 - 32 percent of PM2.5 and 11 -- 17
percent of sulfur dioxide. Nitrous acid (HONO) and ammonia levels appeared unrelated to long-distance
air trajectories, suggesting that atmospheric transport did not contribute significantly to their
Mean daily crude rates of asthma ED Visits were over eight fold higher in the Bronx study area (16.9 per
100,000 persons) than in the Manhattan area (2.02 per 100,000 persons). Exploring reasons for these
differences was beyond the scope of the present study. Among 14 key pollutants examined individually in
regression analyses, five had statistically significant effects on asthma ED visits in the Bronx, including
daily eight-hour maximum 03, mean daily NO2, SO2, PM5. and maximum one-hour PMi.5 (Table 2). No
statistically significant pollution effects were observed in the Manhattan community.
In two-pollutant and three-pollutant regression models, 03 and SO2, and to a lesser extent maximum one-
hour PM2.5, were the most robust pollutants (Table 3). In other words, these pollutants exhibited less
change in their effect estimates as additional pollutants were added to the models. it is of particular interest
that we observed more robust health impacts of the daily maximum PM25 concentration than for the 24-
hour mean, suggesting that peak exposures may have larger health impacts.
In analyses restricted to the warm season (April through October), 03 effects in the Bronx were larger and
more significant than in the full-year analysis, and they were approximately double those seen in
Manhattan, suggesting greater susceptibility and/or exposure to this airway irritant and pro-inflammatory
agent in the Bronx. Ozone effects in the Bronx also remained significant after removing daily maximum 8-
hour average concentrations that exceeded the ozone National Ambient Air Quality Standard (NAAQS)
from the data set (<1% of all observations). Analyses by sex suggested that the air pollution effects in the
Bronx were greater among females than males. No strong differences in effects were observed with age
strata, though there was some indication of larger effects in older adults,
Our findings of significant air pollution effects in the Bronx, but not Manhattan, are likely to relate in part
to greater statistical power for identifying effects in the Bronx where baseline ED visits were greater, but
they may also reflect greater sensitivity to air pollution effects in the Bronx. For example, the mean effect
estimates (expressed as relative risks) for the associations of average daily ozone with asthma ED visits
were the same in the Bronx and Manhattan, although the Bronx relative risk was statistically significant,
1 Bari A, Dutkiewicz VA, Judd CD, Wilson LR, Luttinger D, Husain L. 2003. Regional sources of particulate sulfate,
S02, PM2.5, HC1, and HNO3, in New York, NY. Atmospheric Environment 37: 2837-2844.
Table 3. Relative Risks (95% Confidence Intervals) for Asthma ED Visits as Function of 5-Day
Mean Air Pollution from Two-Pollutant Models. Note: Pollutants included here were those that were
significant predictors of ED visits in single-pollutant models Exposure increments used to compute RRs
were the same as in Table 2. Bold text indicates statistical significance at the 0.05 level.
Contaminant       Controlled with          RR, Bronx               RR, Manhattan
Max 8-hour 03      PM2.5                   1.06 (1,01, 1.10)          .05 (0.93, 1.19)
Max PM.s5               1.04 (1.00, 1.09)          1.05 (0.93, 1.19
NO2                     1.05 (1.01, 1.10)          1 07 (0.94, 1.2 1)
SO,2                    1.05 (1.01 1.10)           1.06 (0.93, 1.20)
PM2,s              Max 8-hour 03           105 (1.01, 1.10           103 (0.94, .14
Max PM2.5               0.99 (0.92, 1.06)          1.04 (0.89, 1.23)
NO                       1.03 (0.98, 1.09)         1.08 (0.95, 1.23)
SSO2                                 1.01 ( 0.96, 1.06)        1.05 (0.94, 1.17)
Max PM2.5          Max 8-hour 03    .      1.07 (1.02, 1.13)         1.02 (0.89, 1.17)
PM25,                    1.09 (1.00, 1.20)        0.99 (0.79, 1.23)
NO22                    1.07 (1.01, 1.14)          1.10 (0.92, 1.3 1)
SO2                     1 .05 (099, 1.11)         1.05 (0.90, 1.21)
NO?                Max 8-hour             1.08 (1.0, 1.17          . 091 (0.68, 1.21)
PM25                     1.06 (0.97, 1.16)        0.83 (0.59, 1.17)
Max PM25                 1.04 (096, 1.14)         0.84 0.59, 1.20
SO2                     1.02 (0.94, 1.12)         0.95 (0.69 1.30)
SO,                Max 8-hour 03           1.11(1.05, 117)   .       099 (088, 1.12)
PM25                      11 1.04 118           . 0.97 (0.85, 1.1)
Max PM5                  .09 (1.03,1.16)  .    _  0.98 (0.85, 1.12)
NO                     1..1  1.04, 1.17)          1. 01 87, 11 6
while the Manhattan estimate was not. In contrast, Bronx relative risks for average daily NO, and SO2 and
maximum hourly PM2.5 were statistically significant in the Bronx and were also substantially larger than
the corresponding Manhattan effect estimates.
To evaluate the specificity of the air pollution effects observed for asthma visits; we analyzed the
relationships between air pollutants and ED visits for outcomes thought a priori to be unrelated to air
pollution (e.g., urinary tract infections, acute gastroenteritis). Of the five pollutants that had significant
univariate effects on asthma in the Bronx, one, 24-hour PM25, had significant effects on the control
outcome. Positive but non-significant effects were seen for the remaining pollutants, except ozone. There
was no evidence of any effect of ozone on control ED counts. These results could suggest some degree of
overestimating risk in the analysis.
The observed associations between specific pollutants and asthma ED visits do not necessarily indicate
cause and effect. It is possible that unmeasured confounders related to indoor environmental exposures or
socio-economic status variables might be contributing to variability in acute asthma exacerbations.
However, within each study area, the time-series design at least partially controls for unmeasured
confounders because each case acts essentially as its own control. The analysis detects marginal changes in
the outcome variable relative to the baseline rate that are associated with the measured exposure variables,
and the baseline rate would include effects due to unmeasured variables, such as local or indoor exposures.
Estimating exposure based on centrally located ambient monitors also adds some uncertainty to the results
reported here due to potential exposure misclassification compared to actual personal exposure. However,
the relatively high population density of the Bronx and Manhattan allowed for the central monitors to be
used as an indicator for exposure for a relatively small area (i.e., the population residing within
approximately 1.5 miles of the monitoring site). Furthermore, the correlation between the two monitoring
sites was relatively high (i.e., greater than 0.6) and mean levels were very similar for most analytes,
perhaps partially mitigating against exposure misclassification biases that might occur because of
movement of residents throughout the greater New York City area.
Mean levels of most air contaminants did not differ substantially between the two New York City
monitoring sites over the course of the study. When differences were observed, mean levels in Manhattan
tended to be modestly higher than mean levels in the Bronx for most pollutants. Mean ozone and pollen
levels were somewhat higher in the Bronx.
The health analysis results suggest that the criteria pollutants PM25, SO2, 03 and NO2 had a statistically
detectable impact on acute asthma ED visits in a community with a relatively high baseline rate of acute
asthma exacerbations. In two-pollutant and three-pollutant regression models, 03 and SO2, and to a lesser
extent maximum one-hour PM2.5, were the most robust pollutants. Robust effects of 03 have been seen in
previous ED asthma studies and in hospital admissions studies of asthma and other respiratory diseases. It
is of particular interest that we observed more robust health impacts of daily maximum PM2.5 concentration
than of the 24-hour mean, suggesting that peak exposures may have larger health impacts.
The following recommendations are suggested based on the study results:
I. EPA should consider the findings in this study and others identifying respiratory health effects
associated with SO2 concentrations below current standards during their review of the SO2 NAAQS.
The results of this study were submitted in response to a Call for Information issued by EPA in May,
2006 to initiate review of the SO? NAAQS.
2. Future time-series studies examining associations between ambient air pollutants and health outcomes
would benefit from direct evaluation of the relationship between personal exposure and regional
monitoring data.
3. More research should be conducted to try to determine if peak, short-term (e.g. hourly) elevated
concentrations of PM.5 are more strongly associated than daily average concentrations with asthma
and other health endpointst If the science is sufficiently strong, consideration should be given to the
effects of short-term PM.5 excursions in future reviews of the particulate matter NAAQS.
4. The high correlations between pollutants (including components of PM2.5) make it difficult in these
epidemiologic studies to confidently identify critical compounds. Alternative strategies to address this
question should be considered in the fuiture.
5   Further evaluation of the statistical methods employed in time-series epideriological studies is
warranted, based on the suggestion of possible model bias indicated by our analysis of control
6. To the extent that targeted community based asthma interventions are planned with respect to air
pollution messages, higher priority should be given to communities with larger asthma burdens.

Library of Congress subject headings for this publication:
Air -- Pollution -- Research -- New York (State) -- New York,
Air quality -- New York (State) -- New York -- Measurement,
Asthma -- New York (State) -- New York,