T-Wave Alternans, Air Pollution and Traffic in High-Risk Subjects

Article Outline

• Abstract
• Methods
• Results
• Discussion
• Supplementary Data
• References
• Copyright

Particulate pollution has been linked to risk for cardiac death; possible mechanisms include pollution-related increases in cardiac electrical instability. T-wave alternans (TWA) is a marker of cardiac electrical instability measured as differences in the magnitude between adjacent T waves. In a repeated-measures study of 48 patients aged 43 to 75 years, associations of ambient and home indoor particulate pollution, including black carbon (BC) and reports of traffic exposure, with changes in 0.5-hourly maximum TWA (TWA-MAX), measured by 24-hour Holter electrocardiographic monitoring, were investigated. Each patient was observed up to 4 times within 1 year after percutaneous intervention for myocardial infarction, acute coronary syndromes without infarction, or stable coronary artery disease, for a total of 5,830 0.5-hour observations. Diary data for each 0.5-hour period defined whether a patient was home or not home, or in traffic. Increases in TWA-MAX were independently associated with the previous 2-hour mean ambient BC (2.1%, 95% confidence interval 0.9% to 3.3%) and with being in traffic in the previous 2 hours (6.1%, 95% confidence interval 3.4% to 8.8%). When subjects were home, indoor home BC effects were largest and most precise; when subjects were away from home, ambient central site BC effects were strongest. Increases in pollution increased the odds of TWA-MAX ≥75th percentile (odds ratio 1.4, 95% confidence interval 1.2 to 1.6 for a 1 μg/m³ increase in 6-hour mean BC). In conclusion, after hospitalization for coronary artery disease, being in traffic and short-term ambient or indoor BC exposure increased TWA, a marker of cardiac electrical instability.

Traffic has been proposed as a specific source of pollution that may trigger myocardial infarction,¹ ventricular arrhythmia, and cardiac death. In a recent European study by Peters et al,¹ the adverse cardiac effects of having been in traffic in the previous hour on the risk for myocardial infarction were similar regardless of type of transportation. The risk for implantable cardioverter-defibrillator shock for ventricular tachycardia or ventricular fibrillation was transiently elevated in the 30-minute period after driving in the Triggers of Ventricular Arrhythmias (TOVA) study.² The emotional stress of being in traffic, as well as the toxic effects of traffic pollution, may have been responsible for the increased traffic-associated cardiac risk. We investigated the associations of ambient and indoor black carbon (BC; a marker of traffic particulate pollution) and reports of being in traffic with the risk for increase in T-wave alternans (TWA) in a population of patients with coronary artery disease, after hospital admission with percutaneous intervention for myocardial infarction, acute coronary syndromes without infarction, or stable coronary artery disease. Using our indoor measures of BC, we assessed whether pollution from traffic sources might increase TWA, not only when patients with coronary artery disease were outside the home or in traffic but also when they were indoors at home.

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Methods 

The study design has been previously described.³ Briefly, before discharge, we recruited a panel of patients with documented coronary artery disease from the greater Boston area (within Interstate 495, a 40-km radius of our central monitoring site) who had undergone percutaneous coronary intervention for acute coronary syndromes (acute myocardial infarctions or unstable angina pectoris) or for worsening stable coronary artery disease. We excluded those with atrial fibrillation and left bundle branch block, coronary artery bypass graft surgery within the past 3 months, and psychiatric illnesses or drug-abuse problems. Active cigarette smoking was an exclusion criterion at entry to the study, and no participant reported current smoking at the time of recruitment. Although we did have 4 subjects who reported recidivist smoking, each reported smoking only at 1 visit, and only 1 reported >0 cigarettes per day at that visit (Table 1). Analyses excluding these subjects did not significantly change the associations of pollution with TWA. Given these findings, we chose to keep the data of all subjects in the analyses, because it provided us with more observations and more power to evaluate interactions and to perform the subanalyses of interest. The protocol included a home visit within 2 to 4 weeks after hospital discharge, followed by 3 additional follow-up visits at approximately 3-month intervals. At the first visit, a baseline screening questionnaire was administered regarding medications, pulmonary and cardiac symptoms, and smoking history.

Table 1. Participant characteristics (n = 48)

Characteristic	Value
Age (years)	56.8(43.2–75.5)
Heart rate (beats/min)	63.7(40.9–129.9)
TWA-MAX	21.1(1.7–61.2)
Men	39(81%)
Women	9(19%)
Hospital discharge diagnosis
MI	19(40%)
Acute coronary syndromes, no MI	19(40%)
Stable coronary artery disease, no MI	10(20%)
Initial no. of coronary arteries ≥50% occluded at catheterization
0	0(0%)
1	26(54%)
2	17(36%)
3	5(10%)
Final no. of coronary arteries ≥50% narrowed
0	37(77%)
1	6(13%)
2	5(10%)
3	0(0%)
Ever used medication
β blockers	44(92%)
Calcium channel blockers	5(10%)
Angiotensin-converting enzyme inhibitors	25(52%)
Theophylline or β antagonists	2(4%)
Digoxin	2(4%)
Statins	44(92%)
Diabetes
No	36(75%)
Yes	12(25%)
Cigarette smoking
Never	17(36%)
Former	29(60%)
Current	2(4%)
White	45(94%)
Black	1(2%)
Asian and other	2(4%)
Ever had MI	30(63%)

Data are expressed as median (range) or as number (percentage).

MI = myocardial infarction.

Twenty-four-hour 3-lead Holter electrocardiographic monitoring (Marquette Seer Digital Recorder; Marquette, Inc., Milwaukee, Wisconsin) was also performed with electrodes in modified V₅ and aVF positions. For subsequent visits, participants were administered a brief questionnaire regarding cardiac and respiratory symptoms and medication use and then underwent 24-hour Holter monitoring. The study design was reviewed and approved by the human subjects committees of the Brigham and Women's Hospital and the Harvard School of Public Health.

Modified moving-average analysis is a time-domain nonspectral technique that was developed to allow TWA measurement in ambulatory subjects. Briefly, a stream of beats is divided into odd and even bins, and the morphology of the beats in each bin is averaged over a few beats successively to create a moving-average complex.⁴ TWA is computed as the maximum difference in magnitude between the odd-beat and the even-beat average complexes from the J point to the end of the T wave. This analysis can be performed from standard Holter monitoring records.⁵ Because of the greater variability in measured electrocardiographic outcomes, we present the results of analyses using the Holter data from the modified V₅ precordial lead position. Each 24-hour Holter monitoring period was divided into 30-minute intervals, and the maximum TWA magnitude in the 30-minute interval was computed (TWA-MAX).

From diary data, the location of each participant was determined for each 0.5-hour period, with location noted as home or not home and in traffic defined as in a car or riding a bus, subway, or train. In relation to each 0.5-hour TWA-MAX measurement, we classified each subject as either home or not home in the previous 2 hours or at home only part of the previous 2 hours.

Ambient concentrations of particulate air matter with aerodynamic diameter <2.5 μm (PM_2.5) and BC were measured at a central monitoring site located on the roof of Countway Library, Harvard Medical School, in downtown Boston. PM_2.5 concentrations were measured using a tapered-element oscillation microbalance (model 1400 A; Rupprecht and Pastashnick, East Greenbush, New York). Ambient BC was measured using an aethalometer (model 8021; Magee Scientific Corporation, Berkeley, California). The median distance of participants' homes from the central site monitoring station was 17.6 km.

PM_2.5 and BC concentrations were summarized in 0.5-hour intervals with analyses based on the 0.5-hour period up to and including 12-hour lagged and cumulative averaged pollution exposures as predictors of TWA-MAX.

Indoor PM_2.5 and indoor and outdoor BC concentrations were also measured continuously at the homes of participants using the tapered-element oscillation microbalance and a model AE-14 aethalometer (Magee Scientific Corporation), respectively. For BC, identical measurement methods were used to measure corresponding concentrations outside the home. Technicians installed the equipment in the house, placing the equipment in the family room or in the room with the greatest activity. Hourly temperature was obtained from the National Weather Service First Order Station at Logan Airport.

We analyzed the association of TWA-MAX with air pollution using generalized additive regression models. The models included indicator variables for each subject, which removed the potential for confounding of subject-specific (time-invariant) factors. The model also controlled for time-varying factors, including day of the week and being in traffic as categorical variables. The factors average heart rate for the relevant 0.5-hour period of TWA measurement, hour of the day, date, and mean temperature were included as smooth penalized spline terms to account for potential nonlinear associations between these continuous factors and the outcome.⁶ TWA-MAX was log transformed to achieve normality and was specified as a continuous outcome in primary analyses. After assessing the main effects of pollution, we evaluated whether the TWA effects of pollution (centrally measured or measured in the home) were modified by whether subjects were at home, not at home, or at home during only part of the exposure period of interest.

In sensitivity analyses, with a focus on potential clinical implications of our findings,⁷ TWA-MAX was treated as a binary outcome, evaluating pollution effects on the probability of TWA-MAX ≥75th percentile compared to <75th percentile of all subject observations. The odds of TWA-MAX ≥75th percentile were estimated by fitting logistic regression models, controlling for the same covariates as specified previously.

Results are presented as percentage change, scaling the PM_2.5 effects to 10 μg/m³ and the BC effects to 1 μg/m³. The analysis was performed using the statistical package R (The R Project for Statistical Computing, Vienna, Austria).

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Results 

Table 1 lists the median and range for TWA-MAX and 0.5-hour averaged heart rate for the 48 subjects, who had a total of 5,830 0.5-hour observations. The range of values for TWA-MAX ≥75th percentile was 26 to 61 μV. At the first home visit, 13 of 48 subjects described ≥1 episode of pain or discomfort in their chest since hospital discharge; 11 of the 13 with any chest pain described chest pain at rest. Over the subsequent visits 2 to 4, as activity levels increased, when asked “Since we last saw you, have you had any pain or discomfort in your chest?” 29 patients (36%) described any chest pain or discomfort, with 7 of the 29 describing chest pain or discomfort walking uphill or hurried, 13 describing chest pain or discomfort walking at a regular pace on the level, and 19 describing chest pain or discomfort at rest over the interim period since the previous visit. However, discrete episodes of ischemia were infrequent during the Holter electrocardiographic recordings.³ Diabetes was most strongly linked to chest pain or discomfort. At the first visit, 5 of 12 subjects with diabetes had experienced chest pain (42%), whereas 8 of 36 patients without diabetes (22%) had experienced chest pain.

In Table 2, we list the distributions of temperature, of PM_2.5 and BC measurements from the ambient central site, and of PM_2.5 and BC measurements from inside and outside each participant's home. The mean level for the 24-hour averages of the criteria pollutant PM_2.5 at 24-hour averaging time was less than the current or proposed National Air Quality Standards.⁸ Compared to the ambient central site data, fewer indoor home measurements were available for analysis. PM_2.5 was measured only at the ambient central site and inside the home; BC was measured at the ambient central site and inside and outside of the home. Ambient PM_2.5 levels measured at the central site were similar to levels inside the home and were correlated, reflecting the regional distribution of particle mass. In contrast, BC levels varied markedly between the ambient and the home sites, reflecting the variation in local sources for this traffic-derived pollutant. BC concentrations measured at the home of the participants (indoors or outdoors) were half that measured at the central site, which was located near a busy road in downtown Boston. BC concentrations inside homes were, on average, slightly lower than outside homes, although indoor maximal 0.5-hour BC values exceeded maximal values outside the home, likely because of transient indoor sources such as cooking.

Table 2. Ambient (measured at the central site), indoor at home, and outdoor at home measurements of air pollution and temperature among all 48 subjects

Variable	No. of Observations	25th Percentile	50th Percentile	75th Percentile	Maximum
Ambient PM2.5 (μg/m3)
0–30 min	5,830	5.44	9.05	13.87	49.96
2-h mean	5,830	5.71	9.06	13.71	46.50
6-h mean	5,830	5.97	9.03	13.54	43.47
Indoor PM2.5 (μg/m3)
0–30 min	3,825	4.50	7.88	12.37	170.50
2-h mean	3,825	4.74	8.16	12.49	124.40
6-h mean	3,825	5.07	8.47	12.84	113.60
Ambient BC (μg/m3)
0–30 min	5,830	0.41	0.70	1.07	6.66
2-h mean	5,830	0.43	0.71	1.07	5.77
6-h mean	5,830	0.47	0.72	1.07	4.59
Indoor BC (μg/m3)
0–30 min	2,993	0.22	0.39	0.63	12.04
2-h mean	2,993	0.22	0.40	0.63	8.90
6-h mean	2,993	0.24	0.41	0.65	5.80
Outdoor BC (μg/m3)
0–30 min	2,993	0.26	0.48	0.79	3.43
2-h mean	2,993	0.27	0.50	0.79	2.98
6-h mean	2,993	0.30	0.50	0.80	2.55
Mean temperature (°C)	5,830	2.8	10.0	18.3	34.4

Regarding the mode of transportation for our study participants, 90% of transportation time consisted of driving a car and the remaining 10% of using public transportation.

Figure 1 shows the circadian rhythm of TWA-MAX. TWA magnitude was lowest early in the morning, increased during the day, and reached a maximum at approximately 10 am.

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• Figure 1. 

  Twenty-four-hour estimated circadian pattern of TWA-MAX, plotted as the mean of TWA-MAX values for each 0.5-hour period of the day, controlling for subject, day of the week, being in traffic, average heart rate, hour of the day, date, mean temperature, and BC. The curve and pointwise 95% confidence intervals (dotted line) were estimated using a penalized spline.

We found significant associations between TWA-MAX and ambient pollutants and the pollutants measured indoors, adjusting for time of day and other potential confounders (see “Methods”). Particularly for BC, up to 6 hours before TWA measurement, these pollution effects increased with the averaging time (Figure 2). TWA-MAX increased by 1.7% (95% confidence interval 0.6% to 2.8%) for a 10 μg/m³ increase in PM_2.5 and by 2.9% (95% confidence interval 1.5% to 4.3%) for a 1 μg/m³ increase in central-site BC for cumulative 6-hour exposure. We found significant associations between outdoor BC and TWA-MAX, and these effects were similar to the associations with central-site BC, even if measurements were available in a subset of days.

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• Figure 2. 

  Percentage change in TWA-MAX for increasing averaging times for ambient PM_2.5 and BC. PM_2.5 effects are scaled to 10 μg/m³; BC effects are scaled to 1 μg/m³.

Traffic exposure in the 2 hours before and including the TWA measurement was associated with a 6% increase in 0.5-hour averaged TWA-MAX (Table 3). The effects of being in traffic and of ambient central site–measured BC or PM_2.5 were independent of each other. When subjects were away from home, 2-hour averaged ambient central-site BC effects were stronger than when subjects were at home (p for interaction >0.001). When patients were home, indoor BC measurements were associated with larger and more precise estimates of change in TWA than ambient central-site BC measurements. Compared to the effects of indoor PM_2.5, indoor BC associations with TWA-MAX were greater.

Table 3. Relation of maximum T-wave alternans to ambient and indoor pollution and to being in traffic

Exposure	Change in TWA	95% Confidence Interval
Models including ambient PM2.5
Model 1
30-min mean ambient PM2.5	1.48%	(0.58to2.40)
In traffic, past 2 h	6.00%	(3.33to8.74)
Model 2
30-min mean ambient PM2.5	1.58%	(0.67to2.49)
Model 3
2-h mean ambient PM2.5	1.67%	(0.68to2.66)
In traffic, past 2 h	5.97%	(3.30to8.71)
Model 4
2-h mean ambient PM2.5	1.78%	(0.79to2.77)
Model 5
2-h mean ambient PM2.5, not home	2.97%	(1.08to4.91)
2-h mean ambient PM2.5, home	1.49%	(0.30to2.70)
2-h mean ambient PM2.5, home part of time	0.11%	(−2.05to2.32)
Models including indoor PM2.5 at home
Model 6
30-min mean indoor PM2.5	1.83%	(1.01to2.66)
Model 7
2-h mean indoor PM2.5	1.47%	(0.57to2.37)
Models including ambient BC
Model 1
30-min mean ambient BC	1.66%	(0.60to2.74)
In traffic, past 2 h	6.09%	(3.41to8.83)
Model 2
30-min mean ambient BC	1.73%	(0.67to2.80)
Model 3
2-h mean ambient BC	2.07%	(0.89to3.26)
In traffic, past 2 h	6.12%	(3.45to8.86)
Model 4
2-h mean ambient BC	2.12%	(0.94to3.31)
Model 5
2-h mean ambient BC, not home	5.19%	(3.14to7.29)
2-h mean ambient BC, home	0.30%	(−1.24to1.85)
2-h mean ambient BC, home part of time	1.34%	(−1.39to4.13)
Models including indoor BC at home
Model 6
30-min mean indoor BC	3.23%	(1.59to4.89)
Model 7
2-h mean indoor BC	3.47%	(1.66to5.32)

All models control for subject, day of the week, being in traffic, heart rate, hour of the day, date, and mean temperature (see “Methods”). PM_2.5 effects scaled to 10 μg/m³; BC effects scaled to 1 μg/m³.

In sensitivity analyses, increases in PM_2.5 and BC were associated with an increased risk for TWA-MAX ≥75th percentile for all averaging times (Table 4). Although heart rate variability (the time-domain variable square root of the mean of the squared differences between adjacent normal RR intervals and the frequency-domain variable high-frequency measure) and ST-segment level were correlated with TWA, the association of pollution with TWA was independent of these electrocardiographic measures (Supplementary Table 1).

Table 4. Odds ratios and 95% confidence intervals for maximum T-wave alternans ≥26 μV for different averaging times for ambient particulate air matter with aerodynamic diameter <2.5 μm and black carbon

PM_2.5 effects scaled to 10 μg/m³; BC effects scaled to 1 μg/m³.

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Discussion 

In the first 1 to 2 weeks after a myocardial infarction, the American College of Cardiology and American Heart Association guidelines recommend avoiding driving, particularly under stressful circumstances such as heavy traffic.⁹ These recommendations are based on studies suggesting that stress,⁹ including the stress of driving in traffic, may increase the risk for post–myocardial infarction complications. Our findings suggest that the particulate pollution from traffic sources itself, not only the stress of driving in traffic, may increase the risk for cardiac electrical instability in the period after myocardial infarction and also in the period after successful percutaneous procedures for acute coronary syndromes without myocardial infarction or worsening symptoms with stable coronary artery disease.

We found that when subjects were away from home, increases in the repolarization abnormality TWA were independently associated with 2 measures of traffic exposure: (1) a report of being in local traffic in the previous 2 hours and (2) ambient central site–measured BC, which is used to estimate a combination of regional and local traffic pollution. When subjects were at home, indoor BC was a better predictor of TWA than ambient BC.

In a German cohort of 56 men with stable ischemic heart disease, investigators¹⁰, ¹¹ showed pollution effects on another measure of T-wave repolarization abnormality, demonstrating a significant increase in QT duration and in the variability of T-wave complexity in response to increases in organic carbon, as well as a significant decrease in T-wave amplitude and an increase in T-wave complexity in response to increases in PM_2.5. TWA has been demonstrated to be the first step in a progression of T-wave complexity, cardiac electrical instability, and ventricular fibrillation.¹² In the TOVA study, Albert et al² found that in patients with implantable cardioverter-defibrillators, the risk for shocks for ventricular tachycardia or ventricular fibrillation was greater in the 30 minutes after driving. Analyses suggested that exertion or anger could not explain the entire association between driving and implantable cardioverter-defibrillator shocks for ventricular tachycardia or ventricular fibrillation; pollution exposure may have been a contributing factor.² Peters et al¹ also found consistent effects for patients traveling in cars or using public transportation, motorcycles, or bicycles, evidence supporting the hypothesis that the traffic effect was not due entirely to the stress of driving in heavy traffic.¹³

Limitations of this study included the size of the cohort, the lack of longer term follow-up to evaluate clinical (e.g., sudden death) rather than subclinical outcomes, and the characterization of the cohort by amount of coronary artery atherosclerosis but not by the ejection fraction. A further limitation was the lack of subject- and visit-specific cotinine levels, with reduced precision in estimations of personal smoking effects. Another potential limitation of our study may be the difficulty generalizing the results to a population of patients with more baseline cardiac electrical instability. However, it is worth noting that the circadian pattern of TWA (Figure 1) parallels the early morning increase in frequency of sudden cardiac death in the classic study by Muller et al.¹⁴

The electrophysiologic basis for the link between TWA and arrhythmogenesis is that the alternating repolarization waveform indicates instabilities in cardiac membrane voltage and of disruptions in intracellular calcium cycling dynamics. TWA-associated electrophysiologic instabilities may be influenced by pollution-linked changes in autonomic tone,¹⁵, ¹⁶ pulmonary or systemic inflammation¹⁷, ¹⁸ leading to myocardial or coronary artery inflammation, oxidative stress,¹⁹, ²⁰ or thrombosis and myocardial ischemia.²¹ Pollution has been shown to lead to changes in autonomic tone, as reflected by reduced heart rate variability and increased heart rate,²², ²³ and to increased risk for ST-segment depression consistent with ischemia.³, ²⁴

Although our study participants did not have ventricular fibrillation or clinical adverse cardiac events during the periods of Holter monitoring, the range of values of maximal TWA that were ≥75th percentile (26 to 61 μV) was comparable to levels ≥75th percentile (42 to 53 μV) demonstrated to confer a four- to sevenfold odds of life-threatening arrhythmias in the post–myocardial infarction studies by Verrier et al.⁷ Thus, the clinical relevance of our study is suggested by our findings that higher pollution levels predicted increased risk for having levels of TWA ≥75th percentile. Thus, our data support the hypothesis that an important pathway by which pollution may increase the risk for ventricular fibrillation or sudden death may be through the repolarization abnormality TWA.

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Supplementary Data 

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References 

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