) 6 c e s (m 4 c T Q n 2 a e m in 0 e g han –2 C ) 6 c e s (m 4 c T Q an 2 e m in 0 e g n ha –2 C 15 )ce 10 s m ( c T Q an 5 e m n i e g an 0 h C –5 A 0 D A * 4-hr-lag model * ** ** Traffic-related air pollution and QT interval “high polymorphism” group had the unfavor- able polymorphism of HFE C282Y, GSTP1 A114V, and HFE H63D, respectively. Figure 4 shows the results of the analysis of effect modification by GSS for BC, NO2, and CO. Cumulative BC exposure (over the previous 10 hr) was associated with a 3.85 msec (95% CI, 0.78–6.93) increase in mean QTc in participants with a high GSS, but no association was evident among participants with a low GSS (–0.56 msec; 95% CI, –3.90 to 2.78; LRT, p-value for interaction = 0.57; for details, see Table 4). Discussion This study provides evidence that the traffic- related pollution markers BC, CO, and NO2 are associated with prolongation of QTc, a marker of ventricular repolarization and a risk factor for ventricular arrhythmias (e.g., torsades de pointes) and sudden cardiac death. In con- trast, we found no significant associations with PM2.5, O3, or SO2, generally indicators of non- traffic pollution. Our results further suggest that diabetic, nonsmoker, and obese partici- pants and individuals with a high number of unfavorable genotypes related to oxidative stress Black carbon Nitrogen dioxide C Carbon monoxide 4 6 Lag (hr) Black carbon 4 Lag (hr) 6 Nitrogen dioxide 2 8 10 0 2 8 10 0 2 4 6 8 10 0 2 4 Lag (hr6) 8 10 0 2 4Lag (hr)6 8 10 0 2 4 Lag (hr)6 8 10 Figure 2. Effect estimates of change in mean QTc per IQR change of traffic-related pollutant. Error bars and hatch-marked regions indicate 95% CI. (A–C) Single- pollutant model of cumulative exposure for a 10-hr time window with random intercept using QCDL with hourly lags: BC (A), NO2 (B), and CO (C). (D–F) Single- pollutant model of hourly exposure with random intercept using hourly lags: BC (D), NO2 (E), and CO (F). ) 6 c e s (m 4 c T Q an 2 e m in 0 e g han –2 C )c 6 e s (m 4 c T Q an 2 e m in 0 e g n ha –2 C B DiabNeotincdiabeticObeNseonNoebveesresmEovkeerrsmokerDiaNbeotnicdiabeticObeNseonNoebveesresmEovkeerrsmokerDiaNbeotnicdiabeticObeNsoenNoebveesresmEovkeerrsmoker DiabNeotincdiabeticObeNsoenNoebveesresmEovkeerrsmokerDiaNbeotnicdiabetic ObNesoenNoebveesresmEovkeerrsmoker DiaNbeotnicdiabetic ObNesoenNoebveesresmEovkeerrsmoker Participant characteristic Participant characteristic Figure 3. 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 participant characteristics [diabetic status (doctor’s diagnosis of diabetes or FBG > 126 mg/dL, vs. no diagnosis or FBG ≤ 126 mg/dL), smoking (never, ever), and obesity (BMI ≥ 30, < 30)]. Error bars indicate 95% CI. *p-Value interaction < 0.01; **p-Value interaction < 0.05. Environmental Health Perspectives • volume 118 | number 6 | June 2010 843 ) 6 c e s (m 4 c T Q n 2 a e m in 0 e g han–2 C ) 6 c e s (m 4 c T Q an 2 e m in 0 e g n ha–2 C Lag (hr) Carbon monoxide * * * * * BC NO2 CO B QCDL model * 15 )c10 e s m ( c T Q an 5 e m n i e g an 0 h C –5