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Increased Particulate Air Pollution and the Triggering of Myocardial Infarction

Originally published 2001;103:2810–2815


    Background—Elevated concentrations of ambient particulate air pollution have been associated with increased hospital admissions for cardiovascular disease. Whether high concentrations of ambient particles can trigger the onset of acute myocardial infarction (MI), however, remains unknown.

    Methods and Results—We interviewed 772 patients with MI in the greater Boston area between January 1995 and May 1996 as part of the Determinants of Myocardial Infarction Onset Study. Hourly concentrations of particle mass <2.5 μm (PM2.5), carbon black, and gaseous air pollutants were measured. A case-crossover approach was used to analyze the data for evidence of triggering. The risk of MI onset increased in association with elevated concentrations of fine particles in the previous 2-hour period. In addition, a delayed response associated with 24-hour average exposure 1 day before the onset of symptoms was observed. Multivariate analyses considering both time windows jointly revealed an estimated odds ratio of 1.48 associated with an increase of 25 μg/m3 PM2.5 during a 2-hour period before the onset and an odds ratio of 1.69 for an increase of 20 μg/m3 PM2.5 in the 24-hour period 1 day before the onset (95% CIs 1.09, 2.02 and 1.13, 2.34, respectively).

    Conclusions—The present study suggests that elevated concentrations of fine particles in the air may transiently elevate the risk of MIs within a few hours and 1 day after exposure. Further studies in other locations are needed to clarify the importance of this potentially preventable trigger of MI.

    Epidemiological analyses throughout the world have shown that high 24-hour average levels of ambient particulate air pollution are associated with an increase in all-cause, respiratory, and cardiovascular disease mortality1234 ; nevertheless, little information is available on the effect of shorter-term exposures. The harmful effects of elevation of ambient concentrations of particulate matter are well documented in multiple studies of hospital admissions and emergency department visits for respiratory diseases.14 In addition, increased hospital admissions for cardiovascular diseases have been associated with particulate air pollution in studies of numerous American, Canadian, and European cities.56789 These results indicate that ambient particulate air pollution is a risk factor not only for respiratory diseases but also for acute cardiovascular events.

    Inhaled particles could lead to acute exacerbation of cardiovascular disease through pulmonary inflammation triggering systemic hypercoagulability.10 Increases in plasma viscosity11 and C-reactive protein12 were observed in randomly selected healthy adults after episodes of high particulate air pollution. Increased heart rate,1314 decreased heart rate variability,151617 and increased risk of implanted cardioverter-defibrillator discharges18 associated with episodes of particulate air pollution indicate an autonomic nervous system response.

    The US Environmental Protection Agency has promulgated a new ambient air quality standard for fine particles (particulate matter <2.5 μm aerodynamic diameter, PM2.5).19 This new standard regulates 24-hour and annual average concentrations and does not address transient elevations (minutes to hours) in fine-particle concentration. There are no published data on the risk of myocardial infarction (MI) in human populations after transient exposures to elevated concentrations of ambient fine particles.

    We therefore evaluated the effect of short-term exposure to fine-particulate air pollution on the risk of acute MIs, comparing data from the Determinants of Myocardial Infarction Onset Study (Onset Study) with hourly measurements of fine particles in Boston. We used a case-crossover design2021 to specifically assess the risk of exposure to high levels of PM2.5 and the timing of the impact of this exposure on the onset of MI.


    Study Design

    The design of the Onset Study has been described in detail elsewhere.20212223 In brief, we used a case-crossover study design to assess the change in risk of acute MI during a brief “hazard period” after exposure to potential triggers of MI onset. An important feature of the case-crossover design is that control information for each patient is based on his or her own past exposure experience. Self-matching results in freedom from confounding by risk factors that are stable over time within an individual but often differ between study subjects.

    Patient Population

    The Onset Study is a multicenter case-crossover study conducted between 1989 and 1996 in 64 centers throughout the United States.24 Participants were interviewed a median of 4 days after their MI. We analyzed data from 772 Onset Study participants living in the greater Boston area collected between January 20, 1995, and May 25, 1996. Data were collected in 6 centers with ≥50 cases (455 cases), 6 centers with 25 to 49 cases (209 cases), and 14 centers with <25 cases (108 cases).

    Interviewers identified eligible cases by reviewing coronary care unit admission logs and patients’ charts. For inclusion in the study, patients were required to meet all of the following criteria: symptom onset while in the greater Boston area, ≥1 creatine kinase level above the upper limit of normal for the clinical laboratory performing the test, positive MB isoenzymes, an identifiable onset of pain or other symptoms typical of infarction, and the ability to complete a structured interview. The protocol was approved by the Institutional Review Board at each participating center, and informed consent was obtained from each patient.

    Detailed chart reviews and patient interviews were conducted by trained research personnel.2223 Data were collected on standard demographic variables as well as risk factors for coronary artery disease. The interview identified the time, place, and characteristics of MI pain and other symptoms.

    Air Pollution Measurements

    Daily air pollution measurements were collected at a Harvard School of Public Health–operated monitoring site in South Boston starting January 15, 1995.18 PM2.5 and PM10 concentrations were measured continuously with a Tapered Element Oscillating Microbalance (Rupprecht and Patashnick model 1400A TEOM). Elemental carbon concentration was determined continuously with an Aethalometer (Magee Scientific Inc), a light-absorption method to measure “black carbon.” Ozone concentration was measured with a UV photometer analyzer (TECO model 49, Thermal Environmental). CO concentration was measured with a continuous nondispersive infrared analyzer (Bendix model 8501-5CA). Relative humidity and temperature were measured continuously (Vaisala model MP113Y). The Massachusetts Department of Environmental Protection measured concentrations of sulfur dioxide and nitrogen dioxide hourly in Chelsea, which is ≈7.5 km north of the South Boston site. We calculated 24-hour mean values when ≥16 valid hourly measurements were available.

    Statistical Analyses

    The analysis of case-crossover data is an application of standard methods for stratified data analysis.2021 The stratifying variable is the individual patient, as in a crossover experiment. For each subject, 1 case period was matched to 3 control periods exactly 24 hours apart. Thus, by matching time of day for case and control periods, potential confounding by the circadian pattern of MI onset or diurnal patterns in the air pollution were controlled.

    Conditional logistic regression analyses were used to analyze the data. Exposure to particles and gases were entered into the model as continuous variables. Odds ratios are expressed for a change in air pollution concentrations from the 5th to the 95th percentile for all measurements available. Separate models were constructed to evaluate the impact of hourly and 24-hour average air pollution concentrations on the onset of MI.

    We also evaluated the effect of hourly (2-hour average) and daily (24-hour average) exposures jointly in 1 model. Control periods were selected as multiples of 24 hours starting 3 days before the date and time of the onset of the symptoms. In addition, multivariate analyses adjusting for season, day of the week, and meteorological parameters on the same time scales were estimated. The final model included sine and cosine functions with periods of 1 year plus 1/2, 1/3, 1/4, 1/5, and 1/6 of a year. It also included quadratic terms for minimum temperature and relative humidity during the 2-hour and 24-hour period of exposure and an indicator for the day of week. Results are presented as odds ratios (OR) and 95% CI.

    The unidirectional case-crossover analyses might be sensitive to trends in the outcome and the exposure.2526 Therefore, control periods close to the event were chosen to minimize the impact of a potential trend. Particulate air pollution concentrations increased over time (0.4 μg/m3 per 100 days, P=0.0002). Although there was weak evidence of a linear downward trend in the number of cases (−0.05 cases per 100 days, P=0.23), the sampling fraction of cases decreased substantially during 1996. Consequently, a downward bias of the estimates would have been expected. This could be demonstrated by choosing control periods >5 days before the event. The bidirectional design has been shown to give unbiased estimates when full case ascertainment was present.26 Analyses of the present data, however, indicated a bias with the bidirectional design due to incomplete case ascertainment during 1996.


    The baseline characteristics of the study population are shown in Table 1. The distribution of 24-hour average and 1-hour average concentrations of the particulate and gaseous air pollutants is presented in Table 2. PM2.5 and PM10 were highly correlated, whereas the coarse fraction of PM10, ie, difference of PM10 and PM2.5, and the gaseous pollutants were only moderately correlated with PM2.5.

    Figures 1 and 2 show results from the conditional logistic regression models, in which PM2.5 was entered as a linear continuous variable. Odds ratios are expressed for an hourly change of 25 μg/m3 in PM2.5 (Figure 1) or a daily change of 20 μg/m3 PM2.5 (Figure 2) corresponding the 5th to 95th percentile intervals (Table 2).

    A positive association between the onset of MI and the concentrations of PM2.5 was observed within the first 3 hours (Figure 1) that was statistically significant for the PM2.5 concentrations 1 hour and 2 hours before the onset of symptoms of an MI. Exposures before this time period seemed to have little impact on the risk of acute MI. In addition, a more delayed response to air pollution was observed when 24-hour averages of the particles were considered (Figure 2). A positive association was observed with elevated concentrations between 24 and 48 hours before the onset of the symptoms.

    A combined analysis considered 2-hour averages (between 60 and 180 minutes before the onset of symptoms) and 24-hour averages (between 24 and 48 hours before the onset of the symptoms) jointly, with pollution levels divided into quintiles (Table 3). When concentrations of PM2.5 were elevated immediately before the onset of symptoms as well as 1 day before the onset of symptoms, the risk of an MI was increased.

    Table 4 summarizes the association between ambient air pollution as a continuous measure and the risk of onset of MI. The estimates of the combined analyses of 2-hour averages and 24-hour averages were larger than the analyses considering the time periods individually. Statistically significantly elevated risks of MI were observed for PM2.5. The coarse fraction of PM10, black carbon, and the gaseous air pollutants including carbon monoxide, NO2, SO2, and ozone showed positive associations, but none were statistically significant.

    A strong seasonal pattern was observed, with increased risks of MI between May and December. Temperature and humidity immediately before the onset of symptoms were not associated with the onset of symptoms, but the 24-hour averages of higher temperatures and lower humidity 1 day before the onset of symptoms showed an increased risk. After adjustment for seasonal and meteorological conditions, the association of PM2.5 with the onset of MI was sustained (Table 4).


    Elevated concentrations of fine particles (PM2.5) were associated with a transient risk of acute MI onset. High 24-hour average concentrations of fine particles were also associated with an elevated risk of MI with a 24-hour delay. The elevated risks during 2 separate time periods appear to be independent of each other. In addition, even changes from low to moderate ambient concentrations were associated with an increased risk of MI, although PM2.5 concentrations were below the new standards.23 Particles >2.5 μm, which consist primarily of resuspended crustal material, showed a substantially smaller association than particles <2.5 μm. Other pollutants, such as black carbon, carbon monoxide, nitrogen dioxide, and sulfur dioxide, showed positive associations, but none of them achieved statistical significance in the single-pollutant multivariate analyses.

    These results are consistent with time-series analyses on hospital admissions for cardiac diseases.56789 Hospital admission data collected for administrative purposes were positively associated with 24-hour average particle mass concentrations collected for regulatory compliance monitoring. The effect of ambient particles on hospital admissions was reported to vary between an immediate response on the same day5679 and a 1-day lagged response.8

    There are several biological effects of ambient particles that may lead to cardiac events. First, particles deposited in the alveoli lead to activation of cytokine production by alveolar macrophages27 and epithelial cells28 and to recruitment of inflammatory cells.29 Second, increases in plasma viscosity11 and C-reactive protein12 have been observed in randomly selected healthy adults in association with episodes of high particulate air pollution. Third, acceleration of heart rates and diminished heart rate variability in association with air pollution have been documented in elderly persons13151617 and in a random population sample.14 One study reported that heart rate variability started to decrease within hours of exposure.17 Controlled-exposure experiments in dogs exposed to concentrated ambient particles indicated changes in the ECG within an hour of the onset of exposure.30 Fourth, ambient concentrations of PM2.5 have been associated with ventricular fibrillation and an increased number of therapeutic interventions in patients with implanted cardioverter-defibrillators.18

    A proposed mechanism for triggering of MI is that onset occurs when a vulnerable but not necessarily stenotic atherosclerotic plaque disrupts in response to hemodynamic stress; thereafter, hemostatic and vasoconstrictive forces determine whether the resultant thrombus becomes occlusive.31 As reviewed above, particulate air pollution is associated with hemodynamic and hemostatic alterations, which may contribute to MI onset.

    Previous studies have shown that physical2332 and psychological24 stress as well as substances such as cocaine22 can trigger the onset of MI. In this report, we demonstrate that transient exposures to an environmental factor, ie, ambient air pollution, appear to increase the risk of an acute MI.

    The available evidence suggests that the mechanisms responsible for the impact of ambient particles on MI may be similar to the mechanisms responsible for triggering by other stressors. If these findings are substantiated, susceptible subgroups could be identified and possible pharmacological interventions could be developed to protect the public from transient exposures to ambient particles, such as that experienced during rush-hour traffic.


    The case-crossover design controls for chronic risk factors for MI such as sex, age, and hypertension. Confounding may occur because of time-varying risk factors,26 such as time of day, season, or weather. These potential confounders, however, were considered in the multivariate analyses.

    Another potential limitation of the study is that only 1 air pollution monitoring site was available. Air pollution measurements throughout the east coast indicate that the elevated concentrations of particulate matter during the summer months are due to regional transport.33 For 11 months, starting in October 1995, concurrent PM2.5 measurements were collected every other day in South Boston and 3 other sites in eastern Massachusetts. There was high concordance between these 24-hour samples, with Pearson correlation between South Boston and downtown Boston (Beacon Hill, 3 km northwest) of 0.86, Lynn (16 km north) of 0.86, and Brockton (27 km south) of 0.81. On a larger scale, a high correlation (0.76) was found between daily concentrations of fine particles measured at sites 200 km apart in Washington and Philadelphia.33 Data on the correlation between hourly concentrations of fine particles at different locations within a metropolitan area are not available.


    Knowledge of the induction time between the exposure to particulate air pollution and adverse health effects is crucial to understanding the biological mechanisms responsible for these associations and to setting of standards that reduce the risk for the population. The present study suggests that elevated concentrations of fine particles may transiently increase the risk of MI for several hours as well as for several days after exposure. As a consequence, 24-hour averages might underestimate the association between air pollution and acute cardiovascular events.

          Figure 1.

    Figure 1. Univariate analyses for association between onset of MI and hourly concentrations of PM2.5. Odds ratios and 95% CIs for an increase of 25 μg/m3 PM2.5.

          Figure 2.

    Figure 2. Univariate analyses for association between onset of MI and 24-hour average concentrations of PM2.5. Odds ratios and 95% CIs for an increase of 20 μg/m3 PM2.5.

    Table 1. Characteristics of the Study Population (n=772)

    Age, y
    <50164 (21)
    50–69365 (47)
    70+243 (32)
    Male489 (63)
    Female283 (37)
    Medical history
    Prior myocardial infarction237 (31)
    Prior angina174 (23)
    Any coronary artery disease302 (39)
    Hypertension319 (41)
    Diabetes mellitus143 (19)
    Obese261 (34)
    Ever smoker558 (72)
    Current smoker246 (32)

    Values are n (%).

    Table 2. Distribution of the Air Pollutants for the Time Period January 15, 1995, to May 25, 1996, in Boston, Mass

    nMeanSD5%50%95%Correlation With PM2.5
    PM2.5, μg/m3
    1-hour11 45712.
    PM10, μg/m3
    1-hour11 69819.412.84.516.743.70.87
    Coarse mass, μg/m3
    1-hour11 3577.36.6−
    Black carbon, μg/m3
    1-hour11 4661.341.210.270.973.710.68
    Ozone, ppb
    1-hour10 88419.814.811846−0.03
    Carbon monoxide, ppm
    1-hour11 8431.090.580.301.002.100.54
    Nitrogen dioxide, ppm
    1-hour11 6710.0230.0130.0070.0210.0470.51
    Sulfur dioxide, ppm
    1-hour11 7960.0070.01000.0050.0230.38

    Table 3. Odds Ratios for 2-Hour (1 Hour Before Onset) and 24-Hour Average (on the Previous Day) Concentrations of PM2.5 Considered Jointly

    QuintileTrend Test P
    2-hour average PM2.5
    Range, μg/m30–5.25.3–7.97.9–11.511.6–17.017.1–74.8
    Odds ratios (CI)1.001.15 (0.90, 1.48)1.09 (0.84, 1.41)1.27 (0.99, 1.64)1.44 (1.12, 1.87)0.025
    24-hour average PM2.5
    Range, μg/m31.6–6.46.5–8.68.7–11.511.6–16.216.3–52.2
    Odds ratios (CI)1.001.12 (0.87, 1.45)1.15 (0.89, 1.48)1.31 (1.01, 1.69)1.32 (1.01, 1.72)0.008

    Table 4. Odds Ratios for 2-Hour and 24-Hour Average Concentrations of Single Pollutants Estimated Jointly.

    Increase (5th to 95th Percentile)Unadjusted OR (95% CI) (n=772)Adjusted1 OR (95% CI) (n=764)
    PM2.5, μg/m3
    2-hour251.43 (1.13, 1.81)1.48 (1.09, 2.02)
    24-hour201.44 (1.11, 1.86)1.62 (1.13, 2.34)
    PM10, μg/m3
    2-hour401.45 (1.11, 1.88)1.51 (1.06, 2.15)
    24-hour301.31 (0.99, 1.73)1.66 (1.11, 2.49)
    Coarse mass, μg/m3
    2-hour151.13 (0.92, 1.40)1.16 (0.89, 1.51)
    24-hour151.18 (0.85, 1.64)1.39 (0.89, 2.15)
    Black carbon, μg/m3
    2-hour31.32 (1.06, 1.65)1.27 (0.97, 1.68)
    24-hour21.08 (0.84, 1.39)1.21 (0.87, 1.70)
    Ozone, ppb
    2-hour451.05 (0.76, 1.46)1.31 (0.85, 2.03)
    24-hour301.21 (0.88, 1.67)0.94 (0.60, 1.49)
    Carbon monoxide, ppm
    2-hour1.01.27 (0.98, 1.63)1.22 (0.89, 1.67)
    24-hour0.60.99 (0.77, 1.27)0.98 (0.70, 1.36)
    Nitrogen dioxide, ppm
    2-hour0.0401.20 (0.91, 1.59)1.08 (0.76, 1.53)
    24-hour0.0301.03 (0.77, 1.39)1.19 (0.81, 1.77)
    Sulfur dioxide, ppm
    2-hour0.0201.00 (0.87, 1.14)0.96 (0.83, 1.12)
    24-hour0.0200.92 (0.71, 1.20)0.91 (0.67, 1.23)

    Estimates are calculated for a change from 5th to 95th percentile of the pollutants.

    1Adjusted for season, meteorological parameters, and day of the week.

    The Determinants of Myocardial Infarction Onset Study was supported by grants from the National Heart, Lung, and Blood Institute (HL-41016) and the American Heart Association (9630115N). Dr Peters was supported in part by HEI Research Agreement 98-1. Dr Dockery was supported in part by Enivornmental Protection Agency grant R827353 and National Institute of Environmental Health Sciences grant ES 00002. The authors acknowledge the access to the air pollution data and advice of Dr Petros Koutrakis, George Allen, and Annie Oh of the Harvard School of Public Health Department of Environmental Health.


    Correspondence to Annette Peters, PhD, GSF-National Research Center for Environment and Health, PO Box 1129, 85758 Neuherberg, Germany.


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