Environmental Health Perspectives • VOLUME 110 | NUMBER 12 | December 2002 1247

Air Pollution and Hospital Admissions for Ischemic Heart Disease in Persons

with Congestive Heart Failure or Arrhythmia

Jennifer K. Mann,1 Ira B. Tager,1 Fred Lurmann,2 Mark Segal,3 Charles P. Quesenberry, Jr.,4 Marlene M. Lugg,5 Jun

Shan,4 and Stephen K. Van Den Eeden4

1Department of Epidemiology, University of California, Berkeley, Berkeley, California, USA; 2Sonoma Technology, Inc., Petaluma,

California, USA; 3Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA; 4Division of Research, Northern California Kaiser Permanente, Oakland, California, USA; 5Panorama City Medical Center, Southern

California Kaiser Permanente, Panorama City, California, USA

Over the past 15 years, epidemiologic studies

consistently have demonstrated an association

between ambient levels of ambient air pollutants and daily cardiovascular mortality, hospital admissions, and emergency room visits.

Associations often have been observed at levels

below the National Ambient Air Quality

Standards (NAAQS) for various pollutants

(Burnett et al. 1999; Linn et al. 2000; Mar et

al. 2000; Moolgavkar 2000; Morris and

Naumova 1998; Morris et al. 1995; Poloniecki

et al. 1997; Schwartz 1997, 1999; Schwartz

and Morris 1995). Particle air pollutants, in

particular, have been associated with cardiac

outcomes (Samet et al. 2000; Schwartz 1999;

Schwartz and Morris 1995; Zanobetti et al.

2000), but gaseous pollutants such as carbon

monoxide (Morris et al. 1995), nitrogen dioxide (Linn et al. 2000; Moolgavkar 2000;

Poloniecki et al. 1997), and ozone (Burnett et

al. 1999; Goldberg et al. 2001; Wong et al.

1999) also have been associated. Toxicologic

studies in diseased animals and monitoring

studies in humans indicate that preexisting

heart or respiratory disease might be related to

the association of respirable particulate matter

and cardiac outcomes (Godleski 2000; Gold

et al. 2001; Gordon and Riebman 2000; Pope

et al. 1999b; Watkinson et al. 1998). Recent

epidemiologic studies also have shown that

persons with preexisting cardiopulmonary conditions are at increased risk for adverse cardiac

health events (Kwon et al. 2001; Zanobetti et

al. 2000) associated with ambient particulate

matter. The present study investigates the

modifying effect of secondary diagnoses of

arrhythmia (sARR) and congestive heart failure

(sCHF) on the relationship between hospital

admissions for ischemic heart disease (IHD)

and ambient air pollutants among members of

a large health maintenance organization who

reside in Southern California.

Methods

Subjects. This study included residents who

were Southern California Kaiser Permanente

(SCKP) members at any point from 1988 to

1995 and who lived within 20 km of one of

five particle air pollution monitors used in a

1995 intensive particulate matter monitoring

data collection. The study area included the

most densely populated areas of the South

Coast Air Basin (SoCAB), which includes the

city of Los Angeles, and contained an annual

average of 1,515,776 members over the 8-year

study period (70.3% of SCKP membership).

The air basin is known both for summertime

photochemical smog and relatively high 

wintertime NO2 and particulate matter concentrations. The study area extended from

the Pacific coast of California east to the

Riverside/San Bernadino metropolitan areas,

and from the San Fernando Valley to the

north to Newport Beach to the south.

Outcomes. Daily hospital admissions for

IHD [International Classification of Diseases,

Revision 9 (ICD-9) codes 410–414] alone (no

secondary diagnosis; sNO) or with accompanying diagnoses of sCHF (ICD-9 code 428)

and/or sARR (ICD-9 codes 426 and 427)

were the main outcomes studied. Discharge

diagnoses were used to classify each admission.

Almost half of those with sCHF also had

sARR. To evaluate the effect of each secondary diagnosis, admissions among those

with either secondary condition were divided

into three mutually exclusive groups: those

with either an sARR or sCHF diagnosis, and

those with both secondary diagnoses. ICD-9

codes 410 [myocardial infarction (MI)] and

411 (other acute and subacute forms of

IHD) were the primary diagnoses in 71.6%

of admissions. These two diagnoses were not

evenly distributed among sCHF, sARR, and

sNO admission groups. Therefore, these specific admission diagnoses were also studied.

Air pollutants/exposure assignment.

Routine monitoring data for criteria air pollutants from 1988 to 1995 in the SoCAB were

acquired from the South Coast Air Quality

Management District (SCAQMD). Hourly

concentration data for O3, NO2, and CO

were obtained from a network of 25–35 monitoring stations in the SoCAB. Daily mass

concentrations of particles with aerodynamic

diameters ≤ 10 μm (PM10) were measured at

20 sites every 6 days. Hourly meteorologic

data for temperature and relative humidity

were acquired from a network of 15 monitoring stations in the region [from the National

Climatic Data Institute (Asheville, NC) and

SCAQMD] (Figure 1). 

Address correspondence to I.B. Tager, UC Berkeley

School of Public Health, 140 Warren Hall, Berkeley,

CA 94720-7360 USA. Telephone: (510) 642-9533.

Fax: (510) 643-5163. E-mail: ibt@uclink4.berkeley.edu

We thank B. McDonnell, U.S. Environmental

Protection Agency Toxic Substances Program, and S.

Prasad, California Air Resources Board, for support

in funding this study. U.S. EPA Cooperative

Agreements 820463 and 824102 and contract 96107

from the South Coast Air Quality Management

District supported this work.

Received 1 February 2002; accepted 21 May 2002.

Articles

We examined whether ischemic heart disease (IHD) hospital admissions were associated with air

pollutants in those with and without secondary diagnoses of arrhythmia (ARR) or congestive heart

failure (CHF). We assessed the occurrence of increased vulnerability among persons with these

conditions to daily variations in ozone, carbon monoxide, nitrogen dioxide, or particulate matter

≤ 10 μm in aerodynamic diameter (PM10). The study population consisted of members of a large

health maintenance organization residing in the South Coast Air Basin of California from 1988 to

1995. After adjustment for day of week, study year, and smoothing splines for day of study, temperature, and relative humidity, CO and NO2 were both associated with admissions with the

greatest effects for CO. A 1-ppm increase in 8-hr average CO was associated with a 3.60% [95%

confidence interval (CI), 1.62–5.63%] increase in same-day IHD admissions in persons with a

secondary diagnosis of CHF, a 2.99% (95% CI, 1.80–4.19%) increase in persons with a secondary diagnosis of ARR, and a 1.62% (95% CI, 0.65–2.59%) increase in IHD admissions in

persons without either secondary diagnosis. Air pollution was most strongly associated with

myocardial infarction hospital admissions. The vulnerability of the secondary CHF subgroup may

be due to a greater prevalence of myocardial infarction primary diagnoses and not the modifying

effect of CHF. This study suggests that people with IHD and accompanying CHF and/or ARR

constitute a sensitive subgroup in relation to the effects of criteria ambient air pollutants associated with motor vehicle combustion. Key words: air pollution, arrhythmia, carbon monoxide, congestive heart failure, hospital admissions, ischemic heart disease, nitrogen dioxide. Environ Health

Perspect 110:1247–1252 (2002). [Online 29 October 2002]

http://ehpnet1.niehs.nih.gov/docs/2002/110p1247-1252mann/abstract.html
This analysis uses daily maximum 8-hr

average O3 (ultraviolet photometry) and CO

concentrations (nondispersive infrared photometry) and 24-hr average NO2 (gas-phase

chemoluminescence) and PM10 concentrations (gravimetric analysis with a size-selective

inlet sampler).

To assign daily exposure for each pollutant, the air basin was divided into 10 km × 10

km grids. Each Kaiser Permanente member in

the study area was assigned to a grid based on

the centroid of his or her residential ZIP code

on 1 January of each year. The study area

included 84 grids with SCKP members. Daily

pollutant exposures were interpolated to grid

centroids from up to three monitors weighted

by the inverse of distance to the grid centroid.

Each grid was assigned to one of seven meteorologic subregions based on temperature and

humidity patterns in January and July over

the 8-year period. A recent article that presented a conceptual model of exposure measurement error in time-series studies of air

pollution showed that measurement error was

reduced when exposures were weighted by

baseline risk levels (Zeger et al. 2000). For

IHD admissions, persons ≥ 60 years of age

have been suggested to be at greatest risk.

Therefore, the annual population of members

≥ 60 years of age residing in each grid was

used for risk-weighting daily exposures.

Analysis. Poisson regression with allowance

for overdispersion was used to model the relationships between daily health outcomes and

daily concentrations of ambient air pollutants.

Separate base models were developed for each

diagnostic subgroup within each region

because temporal patterns of outcomes differed

across the regions. Generalized additive models

(S-Plus; Insightful; Seattle, WA), with air pollutants omitted, were developed with cubic Bspline–smoothed terms for study day,

temperature, and relative humidity. Fixed

effects terms for year and day of week also were

evaluated. Each model included an offset term,

the log of the number of members residing in

the region on 1 January of each year, so that

effects could be interpreted as relative rates.

The base model was selected on the basis of

Akaike’s information criterion. After selection

of the base model, each pollutant was regressed

against daily admission counts in each of the

seven regions. Because there was no evidence

of heterogeneity where effect estimates were

statistically significant, effect estimates were

pooled based on inverse variance weights.

Pollutants lagged from 0 to 5 days, and 2–5-

day moving averages were tested.

Single pollutant analyses were repeated

for all pollutants restricted to days on which

PM10 was measured. Analyses also were

restricted to April through October of each

year, the months in which O3 concentrations

were elevated. Base models were developed

for the ozone season to account for the differences in periodicity and trend in the outcome

series. To examine potential effect modification by age group, admissions in those ≥ 40

years of age were divided into two age groups,

40–59 years and ≥ 60 years. Finally, analyses

with the mutually exclusive diagnostic groups

were conducted to help elucidate the modifying effect of each cardiac condition.

Results

Over the 8-year period, there were 54,863

IHD admissions among SCKP members in

the study area. In 34.5% (n = 18,935) and

14.1% (n = 7,754) of admissions, there was a

diagnosis of sARR and/or sCHF, respectively.

Admissions were most frequent in those without either secondary diagnosis (sNO; n =

31,760). The mean number of daily admissions in each region was 1.6, 0.93, and 0.38

for the sNO, sARR, and sCHF subgroups,

respectively. About one-half of those with a

diagnosis of sCHF also had a diagnosis of

sARR (n = 3,766) (Table 1). Specific IHD

admission diagnoses were not evenly distributed among the diagnostic subgroups. Persons

with sCHF were more likely to have a primary

diagnosis of MI (61.9%) than were those with

a diagnosis of sARR (37.8%) or with sNO

(28.8%). The annual rate of IHD admissions

was 10-fold greater in the older age stratum

(29.9/1,000 vs. 2.5/1,000). However, the distribution of specific IHD diagnoses was similar

in each age stratum (Table 2).

IHD admission counts among people

with sARR diagnoses rose from 1988 to 1992

and then declined. IHD admissions with

sCHF diagnoses increased in winter and

decreased in summer, whereas admissions in

those with sNO diagnoses had little seasonality but increased over the 8-year period.

Admissions were most likely to occur on

Articles • Mann et al.

1248 VOLUME 110 | NUMBER 12 | December 2002 • Environmental Health Perspectives

Table 1. Distribution of events and rates for each outcome among IHD hospital admissions.

Mean admissions per Percent region-days Total Average annual

Diagnoses region-day (range) with 0 admissions admissions rate/1,000

Main secondary outcomes

sNO 1.6 (0.14–3.3) 34.8 31,760 2.62

sARR 0.93 (0.12–2.0) 50.4 18,935 1.56

sCHF 0.38 (0.03–0.87) 71.7 7,754 0.64

Mutually exclusive secondary outcomes

sARR, not sCHF 0.74 (0.10–1.7) 56.4 15,169 1.25

sCHF, not sARR 0.20 (0.06–0.45) 83.3 3,988 0.33

sARR and sCHF 0.18 (0.02–0.35) 84.3 3,766 0.31

Specific primary admission diagnoses

Acute MI 0.96 (0.28–2.12) 48.0 19,690 1.62

Other acute forms of IHD 0.95 (0.11–2.05) 49.7 19,460 1.60

Angina pectoris 0.26 (0.01–0.58) 79.0 5,327 0.79

Other forms of chronic IHD 0.50 (0.07–1.06) 69.4 10,199 0.69

Figure 1. Map of the study area with the locations of meteorologic (Met) regions and stationary air pollution

monitors.

N 0 5 10 20 30 40

km

Cities

CO

PM10

NO2

O3

Met

regions

10 km grid

Elevation (m)

0–300

300–900

900–2100

> 2100
Mondays and least likely to occur on

Saturdays. Regions 1 and 3 contained 59.9%

of the population and contributed more than

one-half of the admissions for each subgroup.

Only 11.7% of the study population lived in

regions 2, 6, and 7. Admission rates were

highest in region 2 and lowest in region 4 for

each outcome (data not shown).

Table 3 shows the mean, median,

interquartile range, and range for each

weather and pollutant variable. Annual PM10

and daily O3 concentrations frequently

exceeded NAAQS. Annual PM10 concentrations were > 50 μg/m3 25% of the time.

Eight-hour average O3 levels were > 80 ppb

on 16.5% of region-days. In contrast, daily

CO and annual NO2 concentrations rarely, if

ever, surpassed federal guidelines (0.09% and

0.00%, respectively). Concentrations for all

air pollutants declined over the study period.

Pollutant concentrations varied by

region, which reflects regional differences in

motor vehicle traffic, land use, and climate.

O3 concentrations were higher in the eastern

regions where temperatures were higher in

summer. CO and NO2 concentrations were

greatest in regions 3 and 4, partly because of

motor vehicle traffic in those regions

(SCAQMD 1997), and PM10 concentrations

were highest in region 5. CO and O3 had the

largest spatial variation and NO2 had the

least as measured by a comparison of mean

concentrations from 1988 to 1995 (data not

shown).

Partial correlations between pollutants are

presented in Table 4. PM10 was modestly

associated with CO (r = 0.15–0.40) and NO2

(r = 0.36–0.60) in all regions. NO2 was

highly correlated with CO (0.64–0.86). NO2

was positively associated with O3 in all but

region 6 (r = –0.16 to 0.42). PM10 was most

correlated with O3 in region 2 (r = 0.57), CO

in region 5, and NO2 in region 7 (r = 0.60).

Partial correlations of O3 and CO varied in

both sign and magnitude across the regions

but were generally low.

Table 5 presents the results of single pollutant models based on same-day concentrations. PM10 was not significantly related to

admissions at any of the lags and moving averages tested. O3 coefficients were all negative

and generally nonsignificant. CO and NO2

were both related to admissions in each subgroup across a range of lags and moving averages, with strongest effects found for a 0-day

lag or 2-day moving average; effects were no

longer evident with days lagged 4 days or

more and 5-day moving averages. A 1-ppm

increase in 8-hr average CO was associated

with a 3.60% increase [95% confidence interval (CI), 1.62–5.63] in daily hospitalizations

for sCHF and a 2.99% change (95% CI,

1.80–4.19) in those with a diagnosis of sARR.

By contrast, in the group with sNO diagnosis,

hospital admissions increased only 1.6% with

a 1-ppm increase in CO. A 10-ppb increase in

NO2 was associated with a 2.3% change in

sCHF, a 1.8% change in sARR, and a 1.3%

change in sNO admissions. Two pollutant

models with CO and NO2 would have been

unstable because of their high correlation in

some regions and so were not evaluated.

Associations were reduced in magnitude

and were nonsignificant for CO and NO2 on

days on which PM10 was measured (21% of

region-days). O3 coefficients remained nonsignificant. Because there might not have been

sufficient days of analysis to detect PM10 associations, given the number of daily admissions

in this population, PM10 was not included in

other sensitivity analyses.

O3 coefficients remained nonsignificant

even when the analysis was restricted to

months in which O3 was elevated (April

through October). However, CO and NO2

associations were generally reduced in magnitude and were nonsignificant possibly because

of the large loss of days and/or loss of temporal variability in CO and NO2 concentrations

during the O3 season.

When the analysis was restricted to persons ≥ 60 years of age, CO and NO2 relationships with sARR and sCHF admissions

were similar to the main analysis, whereas

effects with the sNO subgroup were greater

(Table 6). A 10-ppb increase in NO2 was

associated with a 2.4% (95% CI, 1.02–3.71)

increase in admissions. When comparing the

three subgroups, the percentage increase in

admissions with CO was still greatest among

those with sCHF. A 1-ppm increase in 8-hr

average CO concentrations was associated with

a 2.9% increase in sCHF admissions (95% CI,

0.79–5.1). In the younger age group, CO

effects were slightly greater in the sARR subgroup (3.06%; 95% CI, 0.56–5.61%) and

much greater in persons with sCHF (8.02%;

95% CI, 2.95–13.3%) relative to the older

age group. Air pollutants were not associated

with sNO admissions in the 40–59-year age

group.

Effects on sCHF admissions were not due

to associated ARR. The effects of CO and

NO2 were similar when admissions in those

with ARR were removed from the analysis.

Effect sizes among those with both secondary

conditions were not greater than those for

having sCHF or sARR alone (Table 7). Based

on mutually exclusive diagnostic groups, the

same rank order in magnitude of effects was

observed, with the strongest effects in those

with diagnoses of sCHF without sARR and

the smallest effects in the sNO subgroup.

Although the magnitude of effect for a

1-ppm increase in CO was greater than that

for a 10-ppb NO2 increase, an increase in

NO2 of 10 ppb or more occurred almost

twice as often (15.0% of region-days) as a

1-ppm CO increase (8.3% of region-days).

Increases equal to or greater than the span of

the interquartile range occurred about half as

often for both of these pollutants (Table 8).

Articles • Air pollution and ischemic heart disease

Environmental Health Perspectives • VOLUME 110 | NUMBER 12 | December 2002 1249

Table 2. Distribution of IHD primary diagnoses by secondary diagnosis and age group.

ICD-9 Secondary diagnosis (%) Age group (%)

Primary diagnosis code sARR sCHF sNO 40–59 years ≥ 60 years

Acute MI 410 37.8 61.9 28.8 34.5 36.6

Other acute and subacute forms of IHD 411 33.5 21.9 39.9 35.8 35.6

Angina pectoris 413 8.5 4.4 11.6 10.1 9.5

Other forms of chronic IHD 414 20.1 11.8 19.6 19.5 18.3

Table 3. Distribution of air pollutants and weather variables.

Pollutant n Mean ± SD Median IQR Range

8-Hr average CO (ppm) 20,454 2.07 ± 1.29 1.70 1.14–2.61 0.30–11.8

24-Hr average NO2 (ppb) 20,447 37.2 ± 15.7 34.8 25.6–45.8 3.68–138

8-Hr average O3 (ppb) 20,454 50.3 ± 30.1 43.2 27.6–67.2 0.00–206

PM10 (μg/m3) 4,311 43.7 ± 27.7 40.6 24.0–58.4 0.22–251

Minimum temperature (°F) 20,454 53.8 ± 8.41 54.4 47.8–60.4 15.8–77.2

24-Hr average relative humidity (%) 20,440 54.1 ± 13.8 56.1 45.2–63.4 11.9–89.5

Abbreviations: IQR, interquartile range; n, number of region-days of measurements.

Table 4. Partial correlations for each pollutant pair.a

Region

Pollutant pair 1 2 3 4 5 6 7

CO/NO2 0.83 0.65 0.84 0.72 0.80 0.86 0.64

CO/O3 0.06 –0.30 0.13 –0.20 0.28 –0.37 –0.23

CO/PM10 0.28 0.15 0.36 0.27 0.40 0.33 0.28

O3/NO2 0.27 0.25 0.42 0.34 0.54 –0.16 0.34

O3/PM10 0.20 0.57 0.30 0.33 0.43 0.20 0.48

NO2/PM10 0.36 0.53 0.46 0.50 0.53 0.42 0.60

aCorrelation remaining after adjustment for day of week, year, and smoothing splines of study day, minimum temperature,

and average relative humidity using the base model for ischemic heart disease admissions.
Discussion

Numerous studies have demonstrated an association between ambient air pollutants and

hospital admissions for cardiovascular diseases.

Few studies have investigated the subsets of

such patients who might be at particular risk

for hospital admission. This study demonstrates that, among persons admitted to the

hospital with a primary diagnosis of IHD, the

presence of sCHF or sARR substantially

increases the risk of hospitalization associated

with air pollution, with greatest susceptibility

among those with a diagnosis of sCHF.

CO and NO2, at concentrations well

below NAAQS, were associated with admissions in each diagnostic subgroup of IHD

admissions. The greatest effects were found

for both pollutants with same-day and 2-day

moving average concentrations. Because ambient concentrations of these two pollutants

were highly correlated, the independent contribution of each could not be evaluated in

two pollutant models. O3 was not associated

with admissions in any subgroup, even when

the analysis was restricted to months when

ambient O3 concentrations were at their highest levels. Although PM10 was not associated

with IHD admissions, it was only measured

every 6 days. When analyses were restricted to

the days on which PM10 was measured, none

of the pollutants were associated with admissions. Because there might have been an

insufficient number of monitoring days for

particulate air pollution (an average of 615

noncontiguous days for each series), a PM10

association cannot be ruled out. CO and

NO2 were probably not surrogates of PM10

exposure, however, because PM10 was less

correlated with CO and NO2 than the two

pollutants were with one another.

Almost one-half of persons with sCHF

admissions also had a diagnosis of sARR.

However, larger effects in the sCHF subgroup

were not due to associated sARR diagnoses;

sCHF effects were similar when persons who

also had diagnoses of sARR were removed

from the analysis. In addition, persons with

both secondary diagnoses were not at

increased risk relative to persons with either

sCHF or sARR.

Two primary diagnoses accounted for

72% of all admissions, MI and “other acute

IHD.” Persons with a diagnosis of sCHF

were about twice as likely to have a primary

diagnosis of MI than were persons from the

other two subgroups. Effect estimates were

71% greater for MI than for other acute

IHD. Therefore, the vulnerability of the

sCHF subgroup may be due to the greater

prevalence of the MI diagnosis and not the

modifying effect of CHF.

The greater effect estimates among the

sCHF and sARR subgroups could reflect

solely the independent associations between

air pollution and CHF and ARR. There are

two arguments against this explanation. First,

effects, although smaller, were present among

persons with sNO diagnoses. Second, in earlier studies, hospital admissions for CHF and

ARR were not more strongly associated with

CO or NO2 than MI, angina, or the group of

IHD admissions (Linn et al. 2000; Poloniecki

et al. 1997).

Levy et al. (2001) used a case–crossover

design to examine the association of particle air

pollution with out-of-hospital cardiac arrest.

Patients with a history of cardiac disease,

including ARR, CHF, or prior MI, were

excluded. In this relatively healthy population,

none of the air pollutants was associated with

subsequent MI. Presumably their cases were

healthier than any of the subgroups in this

study, including the sNO subgroup, because

only cases of first MI were included. More than

half of their study population was younger than

61 years. In this study, air pollution was not

significantly related to admissions in persons

younger than 60 years without ARR or CHF.

Zanobetti et al. (2000) examined the

modifying effect of secondary diagnoses and

prior cardiorespiratory hospitalizations in

associations between PM10 and cardiorespiratory admissions. No other pollutants were

investigated. Associations of daily PM10 and

cardiovascular hospitalizations were modified

by previous hospital admissions for conduction disorders or dysrhythmias. Prior admission for CHF and MI did not increase risk of

a subsequent PM-associated cardiovascular

hospitalization.

CO has been associated with primary

admissions for CHF, IHD, and ARR in several studies (Burnett et al. 1997; Morris and

Naumova 1998; Morris et al. 1995; Schwartz

and Morris 1995). Increases in daily NO2

concentrations have also been associated with

increased admissions for specific cardiac conditions (Burnett et al. 1999; Linn et al. 2000;

Ye et al. 2001). In most of these studies, sameday or 1-day lagged concentrations had the

strongest association with admissions. CO at

the monitor is poorly correlated with personal

exposure relative to other criteria air pollutants

in cross-sectional studies (Akland et al. 1985).

The lack of association of particles with

IHD admissions in this study is in contrast to

several other epidemiologic studies (Burnett

et al. 1995; Linn et al. 2000; Lippmann et al.

2000). However, particulate matter was not

associated with admissions in London

(Atkinson et al. 1999) or Birmingham (UK)

(Wordley et al. 1997). 

Recently, mechanisms have been proposed

to explain observed associations of particle air

pollution with cardiovascular morbidity and

mortality. One hypothesis is that particles

trigger the production of inflammatory mediators, which in turn affects procoagulants

(e.g., fibrinogen, factor VII) and viscosity

Articles • Mann et al.

1250 VOLUME 110 | NUMBER 12 | December 2002 • Environmental Health Perspectives

Table 5. Percentage increase (95% CI) in IHD hospital admissions with increasing concentrations of air pollutants,a 0–2-day lags, and 2–4-day moving averages.

Lags Moving averages

Type of admission/pollutant 0-day 1-day 2-day 2-day 3-day 4-day

sARR admissions

CO (ppm) 2.99 (1.80–4.19)* 1.51 (0.37–2.66)* 1.26 (0.15–2.38)* 2.66 (1.40–3.94)* 2.59 (1.27–3.92)* 2.25 (0.90–3.63)*

NO2 (ppb) 1.81 (0.78–2.85)* 0.84 (–0.18–1.87) 0.61 (–0.41–1.64) 1.43 (0.32–2.55)* 1.50 (0.31–2.70)* 1.35 (0.09–2.62)*

O3 (ppb) –0.43 (–1.07–0.21) –0.40 (–1.04–0.25) –0.80 (–1.44––0.15)* –0.47 (–1.14–0.21) –0.67 (–1.37–0.03) –0.91 (–1.63––0.18)

PM10 (μg/m3) 0.59 (–0.71–1.91) 0.46 (–0.86–1.80) –0.04 (–1.37–1.31)

sCHF admissions

CO (ppm) 3.60 (1.62–5.63)* 3.34 (1.48–5.22)* 1.90 (0.11–3.72)* 4.23 (2.13–6.37)* 4.14 (1.96–6.37)* 4.07 (1.81–6.38)*

NO2 (ppb) 2.32 (0.69–3.98)* 2.13 (0.52–3.77)* 0.90 (–0.70–2.52) 2.63 (0.87–4.41)* 2.47 (0.59–4.39)* 2.24 (0.26–4.22)*

O3 (ppb) –0.08 (1.25–1.10) –0.30 (–1.50–0.93) –0.10 (–1.31–1.13) –0.22 (–1.50–1.07) –0.24 (–1.61–1.14) –0.60 (–2.03–0.85)

PM10 (μg/m3) –0.62 (–1.77–0.55) –0.45 (–1.60–0.71) –0.36 (–1.52–0.82)

sNO admissions

CO (ppm) 1.62 (0.65–2.59)* 1.45 (0.54–2.37)* 0.92 (0.04–1.82)* 1.83 (0.80–2.86)* 1.79 (0.72–2.87)* 1.82 (0.71–2.94)*

NO2 (ppb) 1.30 (0.51–2.10)* 1.43 (0.65–2.22)* 0.75 (–0.03–1.53) 1.63 (0.77–2.49)* 1.35 (0.43–2.27)* 1.30 (0.30–2.31)*

O3 (ppb) –0.61 (–1.23–0.02) –0.21 (–0.76–0.34) –0.25 (–0.80–0.30) –0.40 (–0.97–0.18) –0.40 (–1.00–0.21) –0.62 (–1.26–0.02)

PM10 (μg/m3) –0.25 (–1.23–0.75) 0.04 (–0.97–1.06) 0.18 (–0.82–1.20)

aPercentage increase in admissions with a 1 ppm increase in CO, a 10 ppb increase in NO2 or O3 or a 10 μg/m3 increase in PM10; for example, a 1-ppm increase in same-day CO is associated with a 2.99% increase in IHD admissions in persons with a sARR. For each lag, pollutant coefficients from seven regions were pooled weighted by the inverse of the standard error.

Before pooling, estimates were adjusted for day of week, year, and region-specific cubic B-spline smooths of study day, temperature, and relative humidity.

*Statistically significant association (p < 0.05).
(Seaton et al. 1995). Similarly, particles have

been hypothesized to affect autonomic function of the heart (Peters et al. 2000a). Both

hypotheses are supported by several studies in

animals and humans (Creason et al. 2001;

Liao et al. 1999; Peters et al. 1997, 2000a,

2000b; Pope et al. 1999a, 1999b; Schwartz

2001; Watkinson et al. 1998).

Although these hypotheses were developed

to explain cardiovascular morbidity and mortality associated with particulate air pollution,

similar mechanisms might be true for both

CO and NO2. In controlled human exposure

studies using broncheoalveolar lavage, acute

NO2 exposures as dilute as 1 mg/m3 were associated with increased production of inflammatory mediators (Jeffrey 1999). Both NO2 and

CO have been associated with increased concentrations of inflammatory markers in human

exposure and epidemiologic studies. In

London office workers, NO2 and CO levels on

the day before were associated with increased

fibrinogen concentrations (Pekkanen et al.

2000). Plasma viscosity was increased during

an air pollution episode in Germany in which

levels of sulfur dioxide and total suspended

particles were elevated. However, in that

study, CO concentrations were also positively

associated with plasma viscosity over the

whole study period (CO did not increase

appreciably during the air pollution episode)

(Peters et al. 1997). Based on data from the

Third National Health and Nutrition

Examination Survey (NHANES III), a representative sample of the U.S. adult population,

NO2 was associated with increased platelet

counts and fibrinogen but not increased white

blood cells, whereas PM10 was associated with

all three outcomes (Schwartz 2001).

Particles have been associated with

decreased heart rate variability and slightly

increased heart rate in two small studies (Gold

et al. 2001; Pope et al. 1999b). CO and NO2

were not associated with increased heart rate

and decreased heart rate variability, however

(Gold et al. 2001). Peters et al. (2000a) examined the relationship of air pollution to cardiac ARR incidence among 100 cardiac

patients with implanted defribillators.

Particles, O3, CO, SO2, and NO2 were studied. Only NO2 (lagged 1 day or a 5-day moving average) was associated with ARRs that

triggered the defibrillator in these patients.

Carboxyhemoglobin (COHb) levels of 2%

(produced in 10% of the population in

response to 8-hr average 9-ppm CO concentrations) were associated with shorter time to

exercise-induced angina and shorter ST intervals among 62 nonsmoking volunteers with

IHD (Allred et al. 1989). CO also has been

shown to impair myoglobin’s oxygen transport

and storage capacity. The resulting reduction

in oxygen in the myocardial circulation could

increase the likelihood of angina and MI.

Allred et al. (1989) hypothesized that COassociated decreases in pO2 (partial pressure of

O2) might raise the risk of ventricular fibrillation in patients with preexisting ischemia.

However, CO was not associated with

increased ectopic beats at COHb of 3% or 5%

(Maynard and Waller 1999). 

The known increase in wall tension in

CHF and its associated effects on epicardial

circulation certainly also could place persons

with CHF at greater risk for air pollution

associated acute MI.

Conclusions 

This is the first epidemiologic study showing

that people with IHD and accompanying

CHF and/or ARR constitute a sensitive subgroup in relation to the effects of criteria air

pollutants associated with motor vehicle combustion. Persons with a diagnosis of sCHF

were at greatest risk. There was insufficient

power to determine whether a higher proportion of MI diagnoses in those groups explained

the added risk of these comorbid conditions.

This study should be repeated in an area with

sufficient events to analyze MI admissions in

persons with and without diagnoses for sCHF

or sARR. Although an effect of PM10 could

not be ruled out, same-day and 2-day moving

average concentrations of CO and NO2 were

consistently associated with admissions in each

subgroup. The major source of ambient CO

and NO2 in the study area is motor vehicles.

Therefore, either or both pollutants might be

surrogates for the pollution mix associated

with motor vehicle combustion.

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Environmental Health Perspectives • VOLUME 110 | NUMBER 12 | December 2002 1251

Table 6. Percentage increase (95% CI) in IHD hospital admissions with increasing concentrations of air

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