Adjani A Peralta1, Joel Schwartz2, Diane R Gold3, Brent Coull4, Petros Koutrakis5. 1. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States. Electronic address: aperalta@hsph.harvard.edu. 2. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Channing Division of Network Medicine Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States. 3. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Channing Division of Network Medicine Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States. 4. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States. 5. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
Abstract
BACKGROUND: Several studies have found associations between increases in QT interval length, a marker of cardiac electrical instability, and short-term fine particulate matter (PM2.5) exposures. To our knowledge, this is the first study to examine the association between specific PM2.5 metal components and QT interval length. METHODS: We measured heart-rate corrected QT interval (QTc) duration among 630 participants in the Normative Aging Study (NAS) based in Eastern Massachusetts between 2000 and 2011. We utilized time-varying linear mixed-effects regressions with a random intercept for each participant to analyze associations between QTc interval and moving averages (0-7 day moving averages) of 24-h mean concentrations of PM2.5 metal components (vanadium, nickel, copper, zinc and lead) measured at the Harvard Supersite monitoring station. Models were adjusted for daily PM2.5 mass estimated at a 1 km × 1 km grid cell from a previously validated prediction model and other covariates. Bayesian kernel machine regression (BKMR) was utilized to assess the overall joint effect of the PM2.5 metal components. RESULTS: We found consistent results with higher lead (Pb) associated with significant higher QTc intervals for both the multi-pollutant and the two pollutant (PM2.5 mass and a PM2.5 component) models across the moving averages. The greatest effect of lead on QTc interval was detected for the 4-day moving average lead exposure. In the multi-pollutant model, each 2.72 ng/m3 increase in daily lead levels for a 4-day moving average was associated with a 7.91 ms (95% CI: 3.63, 12.18) increase in QTc interval. In the two-pollutant models with PM2.5 mass and lead, each 2.72 ng/m3 increase in daily lead levels for a 4-day moving average was associated with an 8.50 ms (95% CI: 4.59, 12.41) increase in QTc interval. We found that 4-day moving average of copper has a negative association with QTc interval when compared to the other PM2.5 metal components. In the multi-pollutant model, each 1.81 ng/m3 increase in daily copper levels for a 4-day moving average was associated with an -3.89 ms (95% CI: -6.98, -0.79) increase in QTc interval. Copper's essential function inside the human body could mediate its cardiotoxicity on cardiac conductivity and explain why we found that copper in comparison to the other metals was less harmful for QTc interval. CONCLUSIONS: Exposure to metals contained in PM2.5 are associated with acute changes in ventricular repolarization as indicated by QT interval characteristics.
BACKGROUND: Several studies have found associations between increases in QT interval length, a marker of cardiac electrical instability, and short-term fine particulate matter (PM2.5) exposures. To our knowledge, this is the first study to examine the association between specific PM2.5 metal components and QT interval length. METHODS: We measured heart-rate corrected QT interval (QTc) duration among 630 participants in the Normative Aging Study (NAS) based in Eastern Massachusetts between 2000 and 2011. We utilized time-varying linear mixed-effects regressions with a random intercept for each participant to analyze associations between QTc interval and moving averages (0-7 day moving averages) of 24-h mean concentrations of PM2.5 metal components (vanadium, nickel, copper, zinc and lead) measured at the Harvard Supersite monitoring station. Models were adjusted for daily PM2.5 mass estimated at a 1 km × 1 km grid cell from a previously validated prediction model and other covariates. Bayesian kernel machine regression (BKMR) was utilized to assess the overall joint effect of the PM2.5 metal components. RESULTS: We found consistent results with higher lead (Pb) associated with significant higher QTc intervals for both the multi-pollutant and the two pollutant (PM2.5 mass and a PM2.5 component) models across the moving averages. The greatest effect of lead on QTc interval was detected for the 4-day moving average lead exposure. In the multi-pollutant model, each 2.72 ng/m3 increase in daily lead levels for a 4-day moving average was associated with a 7.91 ms (95% CI: 3.63, 12.18) increase in QTc interval. In the two-pollutant models with PM2.5 mass and lead, each 2.72 ng/m3 increase in daily lead levels for a 4-day moving average was associated with an 8.50 ms (95% CI: 4.59, 12.41) increase in QTc interval. We found that 4-day moving average of copper has a negative association with QTc interval when compared to the other PM2.5 metal components. In the multi-pollutant model, each 1.81 ng/m3 increase in daily copper levels for a 4-day moving average was associated with an -3.89 ms (95% CI: -6.98, -0.79) increase in QTc interval. Copper's essential function inside the human body could mediate its cardiotoxicity on cardiac conductivity and explain why we found that copper in comparison to the other metals was less harmful for QTc interval. CONCLUSIONS: Exposure to metals contained in PM2.5 are associated with acute changes in ventricular repolarization as indicated by QT interval characteristics.
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