Particulate air pollution episodes have been associated with increased hospital admissions for cardiovascular disease 1–4 and increased cardiovascular mortality 5–11 in epidemiologic studies. Persons with underlying heart disease appear to be at increased risk for the adverse health effects of particulate air pollution. 1–11
Controlled exposure of animals and natural exposures of humans to particulate pollution have shown possible effects of air pollution on the heart. Instillation of 250 micrograms of combustion particles into the lungs of rats with pharmacologically induced pulmonary hypertension produced arrhythmia and doubled their mortality rate. 12 Dogs inhaling concentrated ambient particles showed changes in heart rate variability and electrocardiographic morphology consistent with increased sympathetic nervous system activity. 13,14 Heart rates of elderly subjects in Utah Valley increased in association with elevated concentrations of inhalable particulates (particulate matter less than 10 micrometers in aerodynamic diameter; PM10). 15 In a subset of these subjects, heart rate variability decreased with increasing PM10 concentrations. 15 Increased heart rate and decreased heart rate variability are indicators of altered autonomic control, specifically increased sympathetic stress. Raised sympathetic activity increases the risk of ventricular fibrillation, a severe form of arrhythmia that, without intervention, leads to sudden death. 16
We tested the hypothesis that patients with a history of serious arrhythmia requiring implanted cardioverter defibrillators (ICDs) would experience potentially life-threatening arrhythmia associated with air pollution episodes. Traditionally, ventricular arrhythmia is treated with drug therapies. 17 Implantable cardioverter defibrillators monitor electrocardiographic abnormalities and initiate therapeutic interventions. On detection of ventricular fibrillation or ventricular tachycardia, the ICD device will initiate pacing and/or shock therapy to restore a normal cardiac rhythm. Several recent clinical trials have suggested that ICD devices are more effective at preventing death from heart rhythm abnormalities than medications alone. 18,19 The ICD devices provide objective and accurate records of the occurrence and timing of arrhythmic events. We report the results of a pilot study to assess the feasibility of linking cardiac arrhythmias detected by ICD devices with air pollution exposures.
Subjects and Methods
Events of Cardiac Arrhythmia and Patient Follow-Up
We abstracted records of cardiac device clinic patients who had a device implanted before September 1997, survived until December 1997, had more than 30 days of follow-up, and lived in eastern Massachusetts (zip code areas 01800–02799). The 2 months after surgical implantation of the device were excluded to avoid effects of implantation and initial adjustment of programmable device settings. One hundred of the 120 patients seen at the clinic met the inclusion criteria.
Patients return to the clinic approximately every 3 to 6 months for follow-up. Records of detected arrhythmias and therapeutic interventions are downloaded from the implanted defibrillators, printed, and reviewed by the nurse managers. We copied the Episode Summary Report listing the date, time, type, and intervention for each detected arrhythmia. We restricted the analysis to defibrillator discharges precipitated by ventricular tachycardias or fibrillation and tabulated the subject- and day-specific arrhythmic interventions.
Air Pollution Measurements
We measured particulate air pollution concentrations in South Boston starting in January 1995. We measured PM2.5 (mass of particles with an aerodynamic diameter below 2.5 μm) and PM10 (mass of particles with an aerodynamic diameter below 10 μm) concentrations with a tapered element oscillating microbalance (Rupprecht and Patashnick, model 1400A, Albany, NY). Elemental carbon was measured by the attenuation of light (effective center wavelength, 820 nm) of particles collected on a prefired quartz fiber filter (Aethalometer, Magee Scientific Inc, Berkeley, CA). Ozone (O3) concentration was measured using an ultraviolet photometer analyzer (model 49, Thermal Environmental Co, Franklin, MA). Carbon monoxide (CO) concentration was measured by a continuous nondispersive infrared analyzer (Bendix model 8501-5CA, Lewisburg, WV). Relative humidity and temperature were measured continuously using an in-line probe (Vaisala model MP113Y, Woburn, MA). Sulfur dioxide (SO2) and nitrogen dioxide (NO2) were measured hourly in Chelsea (approximately 7.5 kilometers north of South Boston) by the Massachusetts Department of Environmental Protection.
We calculated 24-hour means (midnight to midnight) for days with 16 or more valid hourly measurements. We calculated 5-day running means of the air pollutants when at least three 24-hour means were available.
Defibrillator discharge interventions were analyzed by logistic regression models using fixed effect models with individual intercepts for each patient. We used multivariate analysis to evaluate confounding by trend, season, meteorologic conditions and day of the week. The final model included a linear trend; sine and cosine terms with periods of one, one-half, one-third, and one-quarter year; quadratic functions of minimum temperature and humidity; and indicators for day of the week. We selected this model without considering air pollutants on the basis of a comparison of the log likelihood of nested models. We conducted sensitivity analyses for the subgroup of patients who had more than ten events using robust logistic regression in a generalized linear model. 4 We also assessed the potential nonlinear dependence of defibrillator discharges on season or weather using nonparametric smooth functions.
We considered mean air pollution concentrations on the same day and lags of 1, 2, and 3 days. We evaluated possible cumulative effects of the air pollutants on the basis of the 5-day mean concentration. The linearity of the air pollution defibrillator discharge associations were assessed through categorical analysis, in which residuals of a linear regression analyses of the pollutant concentrations were divided into quintiles after adjusting for season, trend, meteorology, and day of the week as in the logistic regression model.
We present odds ratios (ORs) and 95% confidence intervals (CIs) based on an increase in each air pollution concentration from the 5th to the 95th percentile. The magnitude of estimates for different pollutants is therefore based on comparable increments of exposure for the study period.
The study population was predominantly male (79%), with a mean age of 62.2 years. During 63,628 person-days of follow-up over 3 years in 100 patients, we observed 223 defibrillator discharges (Table 1). No discharges were recorded in 67 persons followed for a mean of 601 days (40,248 person-days). Ten or more events per follow-up occurred in 6 patients (18% of 33 patients with any discharge), accounting for a total of 136 events (61% of all interventions). Patients with 10 or more events were slightly younger on average and predominantly male (Table 1). Separate analyses were conducted for this group.
Particle concentrations were modest, with mean concentrations of 19.3 μg/m 3 for PM10 and 12.7 μg/m 3 for PM2.5 at the South Boston site (Table 2). Black carbon contributed on average 11% of PM2.5. The concentrations of the gaseous pollutants—CO, O3, and NO2—were moderate, whereas sulfur dioxide concentrations were low. The concentrations of PM2.5 and PM10 were highly correlated (Table 3). Black carbon was strongly correlated with PM2.5, PM10, CO, and NO2. CO and NO2, however, were only moderately correlated with PM10 and PM2.5. In contrast, both SO2 and O3 were weakly correlated with the other pollutants, suggesting different seasonal patterns and sources. The highest PM2.5, PM10, O3, and SO2 concentrations were recorded during the summer, whereas black carbon, CO, and NO2 had elevated peak concentrations throughout the year (Figure 1).
The rate of defibrillator discharge per person-day decreased over time in both the whole sample and a subgroup of persons with repeated events. Season was a strong predictor of the defibrillator discharges, with the highest frequency during the summer months and a second peak during the second half of the winter. In contrast, daily minimum temperature and daily relative humidity were only weak predictors of defibrillator discharges. No clear day-of-the-week pattern was observed. We found no consistent evidence of increased defibrillator discharges associated with the concentration of the air pollutants on the same day for the sample of patients with any discharges (Table 4). A positive association was observed between the defibrillator discharges and the NO2 concentrations on the previous day as well as with a 5-day mean. All other pollutants showed weaker and less consistent effects than NO2.
Among the six patients who experienced ten or more discharges, defibrillator discharges were associated with exposures to PM10 as well as PM2.5 lagged by 2 days (Table 4). Consistent positive association was observed with black carbon and CO. The strongest associations were observed for NO2 (Table 4). Elevated concentrations of NO2 1 and 2 days before and the mean over the previous 5 days were associated with defibrillator discharges. No association was observed between the defibrillator discharges and SO2. The odds of defibrillator discharge increased monotonically with quintile of PM2.5 and NO2 lagged by 2 days (Figure 2).Including both pollutants into one model reduced the effect estimate of PM2.5 effectively to 0, whereas the effect estimate of NO2 was unchanged. Black carbon lagged by 2 days showed a linear increase in the odds ratio below 1.5 μg/m 3 with a potential plateau above 1.5 μg/m 3. There was weaker evidence for a linear association between the 5-day means of CO or black carbon and the defibrillator discharges. Discharge was as strongly associated with NO2 2 days before as it was with the 5-day mean. Two-pollutant models including 5-day means of NO2 and CO or black carbon found a consistent effect estimate for NO2 but not for CO or black carbon.
Additional analyses, including nonparametric functions for season (9.9 degrees of freedom) and meteorologic variables (2.3 degrees of freedom for minimum temperature and 2.7 degrees of freedom for relative humidity) improved the model fit. The effect estimates of NO2 were reduced (OR = 2.03; 95% CI = 0.66–6.20) for 26 ppb NO2 (lagged 2 days) whereas the effect estimate for PM2.5 increased (OR = 1.87; 95% CI = 0.77–4.55) for 22 μg/m 3 PM2.5 (lagged 2 days).
Analyses of only those days with PM2.5 less than 30 μg/m 3 gave an effect estimate of 1.90 (95% CI = 0.99–3.68) for 22 μg/m 3 PM2.5 (lagged 2 days).
We observed increased risk of a cardiac arrhythmia in association with elevated concentrations of air pollutants in patients with ICDs. The odds of a therapeutic intervention to treat ventricular fibrillation or tachycardia in patients with at least 10 discharges nearly tripled in association with an increase of 26 ppb NO2 and increased 60% in association with an increase in PM2.5 concentrations of 22 μg/m 3. These associations were monotonic and close to linear. Defibrillator discharges did not follow exposures immediately but required an induction time of 1 or 2 days.
The subgroup of patients with repeated potentially life-threatening arrhythmias was most susceptible to exposure to ambient air pollution. Repeated discharges indicate that these patients belong to a subgroup of patients who experience acute arrhythmia in response to triggers. 20 This subgroup might be especially sensitive to air pollution. This group also provides most of the power for the analyses, because other potent triggers, such as transient ischemia, 20 add noise to the association of interest. Therefore, we would be more likely to detect an air pollution association in patients with repeated events than in patients who only experienced one or two events during the 3-year follow-up.
There was an induction period of 1–2 days between the exposure to air pollution and the observed defibrillator discharges. This is consistent with a hypothesized mechanism in which the deposition of particles in the lung elicit inflammatory responses resulting in a systemic signal. 21,22
Possible Pathophysiologic Mechanisms
Most sudden cardiac deaths are caused by acute fatal arrhythmias—ventricular tachycardia/fibrillation. 17 Clinical trials that have evaluated the implantation of cardioverter defibrillator devices have shown that persons with known malignant arrhythmias benefit from the ICD devices compared with traditional drug therapy. 18,19
Time series analyses have shown an association between mortality and hospital admissions for coronary disease with episodes of elevated levels of air pollution. 1–4,23 Stratification by diagnosis showed specific associations between air pollution and ischemic heart diseases 2,3,5 and congestive heart diseases. 2,3,23 Both ischemic and congestive heart disease are chronic diseases that are risk factors for acute tachycardia and ventricular fibrillation. 20 Arrhythmias might have been the acute event leading to the hospitalization. Admissions for dysrhythmia were positively associated with particulate air pollution concentrations, but the CIs were broad. 2,3 In London, Fairley 5 found an association between hospital admissions for dysrhythmia and NO2 exposure. Hospital admission for arrhythmia increased 50% during a 1985 air pollution episode in Germany compared with a nonepisode period. 24
Increased plasma viscosity also was observed during this 1985 European air pollution episode, 25 which suggests a systemic response in association with exposure to air pollution. Increased plasma viscosity might lead to transient ischemic events in persons with severe coronary artery disease. Ischemic events are responsible for approximately 80% of sudden deaths. 20 Direct activation of the autonomic nervous system and the altered excitability of the heart cells caused by air pollution exposures may lead to fibrillation. Therefore, an altered sympathetic or diminished parasympathetic tone of the heart in response to particle exposures might result in life-threatening tachycardias, as observed in this study.
Whereas concentrations of individual air pollutants are correlated day to day, differences by season suggest different sources of particulate air pollution. The highest concentrations of PM2.5 were recorded in Boston during the summer months. Measurements throughout the east coast region indicate that these summer particulate air pollution episodes are caused by regional transport. 26 In contrast, NO2 was higher during the winter. Black carbon and CO were highly variable throughout the year. In the colder months local emissions are the dominant source of particulate air pollution. The primary hypothesis of the study was that PM2.5 would be associated with the incidence of defibrillator discharges. We found support for this hypothesis; however, a stronger association was found for NO2 and black carbon than for PM2.5. NO2 and black carbon might be markers for local traffic-related pollution, whereas PM2.5 is influenced both by local and by regional transported particulate matter. 27
Strengths and Limitations
One major advantage of these data is the complete, passive monitoring of cardiac arrhythmias. On the other hand, discharges might be initiated in cases of normal rather than life-threatening events, because screening of cardiac arrhythmias is optimized to avoid underdetection of ventricular tachyarrhythmias. 28 For this pilot study, clinical review of detected arrhythmias was not included in the abstraction of the data. If misclassification of defibrillator discharges is independent of air pollution exposure, we would expect a loss of power (that is, wider CIs) but not any bias in the estimated association.
ICD discharges were rare events in this follow-up of 100 patients. The small number of subjects with multiple defibrillator discharges is a limitation. In particular, the power to adequately adjust for confounding might be limited in multivariate analyses. These patients clearly represent a highly selected cohort, and these results would not be generalizable to the entire population. On the other hand, this cohort is of special interest, because their previous history of cardiovascular disease might make them particularly sensitive to the effects of air pollution episodes. Indeed, effects were seen most strongly among the six subjects with repeated arrhythmias. Data on baseline clinical characteristics and prescribed antiarrhythmic medications were not available in this pilot study to determine the characteristics associated with increased (or decreased) responsiveness.
Misclassification of air pollution exposure is another potential source of bias in this study. Whereas patients were living in eastern Massachusetts, air pollution exposure was estimated based on a single monitor in Boston. The day-to-day correlations of fine-particle concentrations between sites is high across large regions in the eastern United States. Suh et al.27 reported correlations of more than 0.90 between fine-particle monitoring stations across the Washington, DC, metropolitan area and a correlation of 0.76 between monitors in Washington and Philadelphia. For the gaseous pollutants, there might be only weak correlation between monitoring sites within a region. 27 We would expect any exposure misclassification to be nondifferential with respect to ICD discharges and to bias the estimates toward the null.
We thank Mark Josephson, Nanette Hallette, and Marianne Daoust of the Beth Israel Deaconess Medical Center Device Clinic.
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