Person:

Koutrakis, Petros

Background: Many studies report significant associations between PM2.5 (particulate matter <2.5 micrometers) and hospital admissions. These studies mostly rely on a limited number of monitors which introduces exposure error, and excludes rural and suburban populations from locations where monitors are not available, reducing generalizability and potentially creating selection bias. Methods: Using prediction models developed by our group, daily PM2.5 exposure was estimated across the Mid-Atlantic (Washington D.C., and the states of Delaware, Maryland, New Jersey, Pennsylvania, Virginia, New York and West Virginia). We then investigated the short-term effects of PM2.5 exposures on emergency hospital admissions of the elderly in the Mid-Atlantic region.We performed case-crossover analysis for each admission type, matching on day of the week, month and year and defined the hazard period as lag01 (a moving average of day of admission exposure and previous day exposure). Results: We observed associations between short-term exposure to PM2.5 and hospitalization for all outcomes examined. For example, for every 10-µg/m3 increase in short-term PM 2.5 there was a 2.2% increase in respiratory diseases admissions (95% CI = 1.9 to 2.6), and a 0.78% increase in cardiovascular disease (CVD) admission rate (95% CI = 0.5 to 1.0). We found differences in risk for CVD admissions between people living in rural and urban areas. For every10-µg/m3 increase in PM 2.5 exposure in the ‘rural’ group there was a 1.0% increase (95% CI = 0.6 to 1.5), while for the ‘urban’ group the increase was 0.7% (95% CI = 0.4 to 1.0). Conclusions: Our findings showed that PM2.5 exposure was associated with hospital admissions for all respiratory, cardio vascular disease, stroke, ischemic heart disease and chronic obstructive pulmonary disease admissions. In addition, we demonstrate that our AOD (Aerosol Optical Depth) based exposure models can be successfully applied to epidemiological studies investigating the health effects of short-term exposures to PM2.5.

Background: Short-term particulate air pollution exposure is associated with reduced heart rate variability (HRV), a risk factor for cardiovascular morbidity and mortality, in many studies. Associations with sub-chronic or long-term exposures, however, have been sparsely investigated. We evaluated the effect of fine particulate matter (PM2.5) and black carbon (BC) exposures on HRV in an elderly cohort: the Normative Aging Study. Methods: We measured power in high frequency (HF) and low frequency (LF), standard deviation of normal-to-normal intervals (SDNN), and the LF:HF ratio among participants from the Greater Boston area. Residential BC exposures for 540 men (1161 study visits, 2000–2011) were estimated using a spatio-temporal land use regression model, and residential PM2.5 exposures for 475 men (992 visits, 2003–2011) were modeled using a hybrid satellite based and land-use model. We evaluated associations between moving averages of sub-chronic (3–84 day) and long-term (1 year) pollutant exposure estimates and HRV parameters using linear mixed models. Results: One-standard deviation increases in sub-chronic, but not long-term, BC were associated with reduced HF, LF, and SDNN and an increased LF:HF ratio (e.g., 28 day BC: −2.3 % HF [95 % CI:−4.6, −0.02]). Sub-chronic and long-term PM2.5 showed evidence of relations to an increased LF and LF:HF ratio (e.g., 1 year PM: 21.0 % LF:HF [8.6, 34.8]), but not to HF or SDNN, though the effect estimates were very imprecise and mostly spanned the null. Conclusions: We observed some evidence of a relation between longer-term BC and PM2.5 exposures and changes in HRV in an elderly cohort. While previous studies focused on short-term air pollution exposures, our results suggest that longer-term exposures may influence cardiac autonomic function. Electronic supplementary material The online version of this article (doi:10.1186/s12940-015-0074-z) contains supplementary material, which is available to authorized users.

Background: Short‐term exposure to elevated air pollution has been associated with higher risk of acute cardiovascular diseases, with systemic oxidative stress induced by air pollution hypothesized as an important underlying mechanism. However, few community‐based studies have assessed this association. Methods and Results: Two thousand thirty‐five Framingham Offspring Cohort participants living within 50 km of the Harvard Boston Supersite who were not current smokers were included. We assessed circulating biomarkers of oxidative stress including blood myeloperoxidase at the seventh examination (1998–2001) and urinary creatinine‐indexed 8‐epi‐prostaglandin F2α (8‐epi‐PGF 2α) at the seventh and eighth (2005–2008) examinations. We measured fine particulate matter (PM 2.5), black carbon, sulfate, nitrogen oxides, and ozone at the Supersite and calculated 1‐, 2‐, 3‐, 5‐, and 7‐day moving averages of each pollutant. Measured myeloperoxidase and 8‐epi‐PGF 2α were loge transformed. We used linear regression models and linear mixed‐effects models with random intercepts for myeloperoxidase and indexed 8‐epi‐PGF 2α, respectively. Models were adjusted for demographic variables, individual‐ and area‐level measures of socioeconomic position, clinical and lifestyle factors, weather, and temporal trend. We found positive associations of PM 2.5 and black carbon with myeloperoxidase across multiple moving averages. Additionally, 2‐ to 7‐day moving averages of PM 2.5 and sulfate were consistently positively associated with 8‐epi‐PGF 2α. Stronger positive associations of black carbon and sulfate with myeloperoxidase were observed among participants with diabetes than in those without. Conclusions: Our community‐based investigation supports an association of select markers of ambient air pollution with circulating biomarkers of oxidative stress.