Baja et al. may be particularly at risk from traffic-related exposures. Our findings are supported by those from previous studies that also show evidence of greater cardiovascular effects for traffic-related pollutants than for regional nontraffic-related pollutants (Laden et al. 2000, 2006; Schwartz et al. 2005a). In the Six City Study, for example, the estimated effect of particles from mobile sources on mortality was greater than that from coal power plants (Laden et al. 2000, 2006). Consistent with these findings, ambient BC concentrations have been associated in several Boston-area stud- ies with mortality (Maynard et al. 2007) as well as a variety of intermediate cardiovascular indicators, including heart rate variability (Schwartz et al. 2005a), ST-segment depres- sion (Chuang et al. 2008; Gold et al. 2005), and homocysteine (Park et al. 2008). Few studies have been conducted that have examined pollution-mediated effects on QTc. In a prospective panel study in East Germany, Henneberger et al. (2005) examined pollution- induced repolarization changes in 56 males (mean age, 66 years) with ischemic heart dis- ease. They found no significant association at alpha = 0.05 between QTc and elemental carbon, but found significant associations with NO2 and CO during 6–11 hr and with SO2 during the whole 0–23 hr before ECG record- ing. Insignificant findings for EC in the East Table 3. Adjusted effect estimates for change in mean QTc with an IQR increase in traffic pollutant expo- sures (cumulative during the 10 hr before ECG measurement) by patient characteristics (diabetic, obesity, and smoking status). Status/pollutant Diabetic status Obesity status Smoking Status BC NO2 CO BC NO2 CO BC NO2 CO 15 ) 12 (m 9 nQ 6 in 3 han 0 –3 844 Modifier DM DM DM Non-DM Non-DM Non-DM Obese Nonobese Obese Nonobese Obese Nonobese Never Ever Never Ever Never Ever Change in mean QTc [msec (95% CI)] 5.28 (0.67 to 9.90) 1.43 (–0.79 to 3.65) 7.10 (–0.12 to 14.32) 1.22 (–2.67 to 5.12) 3.78 (–3.59 to 11.14) 3.91 (–0.62 to 8.44) 3.97 (–0.07 to 8.01) 1.23 (–1.14 to 3.60) 4.02 (–3.01 to 11.04) 2.28 (–1.65 to 6.21) 3.38 (–4.27 to 11.02) 3.90 (–0.57 to 8.37) 4.32 (0.54 to 8.09) 0.57 (–1.83 to 2.98) 4.18 (–2.41 to 10.77) 1.97 (–2.02 to 5.95) 4.67 (–2.33 to 11.68) 3.27 (–1.41 to 7.96) 15 ) 12 (m 9 nQ 6 in 3 han 0 –3 QCDL model p-Value 0.03 0.21 0.054 0.54 0.31 0.09 0.054 0.31 0.26 0.25 0.38 0.09 0.03 0.64 0.21 0.33 0.19 0.17 * p-Value interaction 0.26 < 0.01 < 0.01 0.15 0.54 0.29 0.74 < 0.01 0.14 * ** ** DM, diabetic (diagnosis of diabetes mellitus). c c e e s s c c T T a a e e m m e e g g C C A 4-hr-lag model B QCDL model BC NO2 CO High Low High Low High Low Genetic susceptibility score High Low High Low High Low Genetic susceptibility score Figure 4. Adjusted change in mean QTc per IQR change of traffic-related pollutant: hourly exposure with a 4-hr lag (A) or cumulative exposure during 10 hr before ECG measurement (B), by GSS (low GSS, high GSS). Error bars indicate 95% CI. *p-Value interaction < 0.01; **p-value interaction < 0.10. Germany study may be due to its smaller sam- ple size or its younger study population com- pared with our study, in which we estimated significant main effects of BC 4 hr before ECG recording (Figure 2) in our population of 580 men with a mean age of 74.8 years. Plausible pathophysiologic mechanisms. Our observed associations can be explained by plausible pathophysiological mechanisms. Toxicity of traffic particles may have a direct effect on the blood, cardiovascular system, and lung receptors (Brook et al. 2004; Simkhovich et al. 2008). Deposition in the airways and lung alveoli may trigger proinflammatory sig- naling via a reactive oxygen species (ROS)- dependent mechanism (Donaldson and Stone 2003; Ghio and Devlin 2001; Ghio et al. 2000; Li et al. 1999). Moreover, traffic par- ticles may also cross the pulmonary epithe- lium and may be able to reach the heart via the vasculature (Nemmar et al. 2001, 2002; Oberdörster et al. 2002), where they may induce oxidative stress and proinflammatory changes in the vasculature and myocardial substrate (Simkhovich et al. 2008). The gen- erated proinflammatory cytokines and ROS may subsequently affect a variety of health measures, including autonomic cardiac control (Simkhovich et al. 2008). Changes in auto- nomic control may in turn cause a prolonga- tion in ventricular repolarization and QTc interval through the altering of the function of the sodium and calcium channels (Goldenberg et al. 2008; Moss and Kass 2005; Utell et al. 2002; Zareba et al. 2001). Effect modification by participant charac- teristics. Our observation of effect modifi- cation by diabetic status in the associations between the cumulative effect and 4 hr before ECG measurement lag effect of BC and NO2 exposure and prolonged QTc for the QCDL and hourly lag models may be due to a higher likelihood of persons with diabetes to have prolonged QTc than those without diabe- tes. In addition, the greater baseline oxida- tive stress among persons with diabetes has been shown to mediate the autonomic effects of particles (Chahine et al. 2007; Schwartz et al. 2005b; Rhoden et al. 2005). Both the QCDL and hourly lag models showed a con- sistent pattern in the acute estimated effects of BC and NO2 on QTc. These results are supported by those from a population based cohort study that showed a high prevalence of prolonged QTc among participants with type 2 diabetes (Veglio et al. 2002). We also observed evidence of effect modi- fication by obesity on associations between cumulative (for the 10 hr before ECG meas- urement) and hourly (lagged 4 hr before) BC and NO2 exposures and prolonged QTc. Obesity and the cardiac autonomic nervous system are related, an increase in body weight is associated with a decline in parasympathetic ovlume 118 | number 6 | June 2010 • Environmental Health Perspectives