Epidemiologic studies report associations between particulate air pollution and cardiopulmonary morbidity and mortality. Although the underlying pathophysiologic mechanisms remain unclear, it has been hypothesized that altered autonomic function and pulmonary/systemic inflammation may play a role. In this study we explored the effects of air pollution on autonomic function measured by changes in heart rate variability (HRV) and blood markers of inflammation in a panel of 88 elderly subjects from three communities along the Wasatch Front in Utah. Subjects participated in multiple sessions of 24-hr ambulatory electrocardiographic monitoring and blood tests. Regression analysis was used to evaluate associations between fine particulate matter [aerodynamic diameter ≤ 2.5 µm (PM 2.5 )] and HRV, C-reactive protein (CRP), blood cell counts, and whole blood viscosity. A 100-µg/m 3 increase in PM 2.5 was associated with approximately a 35 (SE = 8)-msec decline in standard deviation of all normal R-R intervals (SDNN, a measure of overall HRV); a 42 (SE = 11)-msec decline in square root of the mean of the squared differences between adjacent normal R-R intervals (r-MSSD, an estimate of short-term components of HRV); and a 0.81 (SE = 0.17)-mg/dL increase in CRP. The PM 2.5 -HRV associations were reasonably consistent and statistically robust, but the CRP association dropped to 0.19 (SE = 0.10) after excluding the most influential subject. PM 2.5 was not significantly associated with white or red blood cell counts, platelets, or whole-blood viscosity. Most short-term variability in temporal deviations of HRV and CRP was not explained by PM 2.5 ; however, the small statistically significant associations that were observed suggest that exposure to PM 2.5 may be one of multiple factors that influence HRV and CRP.

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[1] Field studies have been performed in Lindon, Utah (February 2003) and Rubidoux, California (July 2003) to determine if the Rupprecht and Patashnick (R&P) Filter Dynamic Measurement System (FDMS) determines total fine particulate mass, including the semivolatile ammonium nitrate and organic material. Collocated measurements were made with the FDMS, a conventional tapered element oscillating microbalance (TEOM) monitor with a heated filter, an R&P differential TEOM monitor, the Brigham Young University (BYU) Real-Time Total Ambient Mass Sampler (RAMS), the BYU particle concentrator-organic sampling system (PC-BOSS), a PM 2.5 Federal Reference Method (FRM), a PM 2.5 speciation sampler, an R&P continuous nitrate monitor, and two Sunset continuous carbon monitors (one to measure quartz filter-retained particulate carbon and one to measure particulate semivolatile carbonaceous material lost from the particles on a filter during sampling). The RAMS and PC-BOSS samplers have been shown to determine fine particulate material, including both the semivolatile and the nonvolatile components. Linear regression analysis at the Lindon site between the FDMS (X) and the PC-BOSS (Y), and the FDMS (X) and the RAMS (Y), resulted in zero-intercept slopes of 1.01 ± 0.06 (r 2 = 0.63) and 1.00 ± 0.01 (r 2 = 0.69), respectively. At the Rubidoux sampling site, linear regression analysis between the PC-BOSS (X) and the FDMS (Y) gave a zero-intercept slope of 0.96 ± 0.02 (r 2 = 0.90). Linear regression analysis between the FDMS (X) and the RAMS (Y) resulted in a zero-intercept slope of 0.99 ± 0.01 (r 2 = 0.80). Measurements made at the two sites indicate that the FDMS and the R&P differential TEOM monitors do measure total fine particulate mass, including the semivolatile ammonium nitrate and organic material. Both the heated TEOM monitor and PM 2.5 FRM did not measure the semivolatile material. The difference between the FDMS and a heated TEOM monitor was explained by the semivolatile ammonium nitrate and organic material measured by the various chemical composition monitors.