Person:

Koutrakis, Petros

Background: Many studies have reported significant associations between exposure to (PM_{2.5}) and hospital admissions, but all have focused on the effects of short-term exposure. In addition all these studies have relied on a limited number of (PM_{2.5}) monitors in their study regions, which introduces exposure error, and excludes rural and suburban populations from locations in which monitors are not available, reducing generalizability and potentially creating selection bias. Methods Using our novel prediction models for exposure combining land use regression with physical measurements (satellite aerosol optical depth) we investigated both the long and short term effects of (PM_{2.5}) exposures on hospital admissions across New-England for all residents aged 65 and older. We performed separate Poisson regression analysis for each admission type: all respiratory, cardiovascular disease (CVD), stroke and diabetes. Daily admission counts in each zip code were regressed against long and short-term (PM_{2.5}) exposure, temperature, socio-economic data and a spline of time to control for seasonal trends in baseline risk. Results: We observed associations between both short-term and long-term exposure to (PM_{2.5}) and hospitalization for all of the outcomes examined. In example, for respiratory diseases, for every10-µg/m(^3) increase in short-term (PM_{2.5}) exposure there is a 0.70 percent increase in admissions (CI = 0.35 to 0.52) while concurrently for every10-µg/m(^3) increase in long-term (PM_{2.5}) exposure there is a 4.22 percent increase in admissions (CI = 1.06 to 4.75). Conclusions: As with mortality studies, chronic exposure to particles is associated with substantially larger increases in hospital admissions than acute exposure and both can be detected simultaneously using our exposure models.

Background: Epidemiological studies have examined the association between PM2.5 and mortality, but uncertainty remains about the seasonal variations in PM2.5-related effects and the relative importance of species. Objectives: We estimated the effects of PM2.5 species on mortality and how infiltration rates may modify the association. Methods: Using city–season specific Poisson regression, we estimated PM2.5 effects on approximately 4.5 million deaths for all causes, cardiovascular disease (CVD), myocardial infarction (MI), stroke, and respiratory diseases in 75 U.S. cities for 2000–2006. We added interaction terms between PM2.5 and monthly average species-to-PM2.5 proportions of individual species to determine the relative toxicity of each species. We combined results across cities using multivariate meta-regression, and controlled for infiltration. Results: We estimated a 1.18% (95% CI: 0.93, 1.44%) increase in all-cause mortality, a 1.03% (95% CI: 0.65, 1.41%) increase in CVD, a 1.22% (95% CI: 0.62, 1.82%) increase in MI, a 1.76% (95% CI: 1.01, 2.52%) increase in stroke, and a 1.71% (95% CI: 1.06, 2.35%) increase in respiratory deaths in association with a 10-μg/m3 increase in 2-day averaged PM2.5 concentration. The associations were largest in the spring. Silicon, calcium, and sulfur were associated with more all-cause mortality, whereas sulfur was related to more respiratory deaths. County-level smoking and alcohol were associated with larger estimated PM2.5 effects. Conclusions: Our study showed an increased risk of mortality associated with PM2.5, which varied with seasons and species. The results suggest that mass alone might not be sufficient to evaluate the health effects of particles. Citation: Dai L, Zanobetti A, Koutrakis P, Schwartz JD. 2014. Associations of fine particulate matter species with mortality in the United States: a multicity time-series analysis. Environ Health Perspect 122:837–842; http://dx.doi.org/10.1289/ehp.1307568

Climate change may affect human health, particularly for elderly individuals who are vulnerable to temperature changes. While many studies have investigated the acute effects of heat, only a few have dealt with the chronic ones. We have examined the effects of seasonal temperatures on survival of the elderly in the Southeastern USA, where a large fraction of subpopulation resides. We found that both seasonal mean temperature and its standard deviation (SD) affected long-term survival among the 13 million Medicare beneficiaries (aged 65+) in this region during 2000–2013. A 1 °C increase in summer mean temperature corresponded to an increase of 2.5% in death rate. Whereas, 1 °C increase in winter mean temperature was associated with a decrease of 1.5%. Increases in seasonal temperature SD also influence mortality. We decomposed seasonal mean temperature and its temperature SD into long-term geographic contrasts between ZIP codes and annual anomalies within ZIP code. Effect modifications by different subgroups were also examined to find out whether certain individuals are more vulnerable. Our findings will be critical to future efforts assessing health risks related to the future climate change.

Background: Exposure to ambient particulate matter (PM) has been associated with reduced lung function. Elemental components of PM have been suggested to have critical roles in PM toxicity, but their contribution to respiratory effects remains under-investigated. We evaluated the effects of traffic-related PM2.5 and its elemental components on lung function in two highly exposed groups of healthy adults in Beijing, China. Methods: The Beijing Truck Driver Air Pollution Study (BTDAS) included 60 truck drivers and 60 office workers evaluated in 2008. On two days separated by 1-2 weeks, we measured lung function at the end of the work day, personal PM2.5, and nine elemental components of PM2.5 during eight hours of work, i.e., elemental carbon (EC), potassium (K), sulfur (S), iron (Fe), silicon (Si), aluminum (Al), zinc (Zn), calcium (Ca), and titanium (Ti). We used covariate-adjusted mixed-effects models including PM2.5 as a covariate to estimate the percentage change in lung function associated with an inter-quartile range (IQR) exposure increase. Results: The two groups had high and overlapping exposure distributions with mean personal PM2.5 of 94.6 μg/m3 (IQR: 48.5-126.6) in office workers and 126.8 μg/m3 (IQR: 73.9-160.5) in truck drivers. The distributions of the nine elements showed group-specific profiles and generally higher levels in truck drivers. In all subjects combined, forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) did not significantly correlate with PM2.5. However, FEV1 showed negative associations with concentrations of four elements: Si (-3.07%, 95% CI: -5.00; -1.11, IQR: 1.54), Al (-2.88%, 95% CI: -4.91; -0.81, IQR: 0.86), Ca (-1.86%, 95% CI: -2.95; -0.76, IQR: 1.33), and Ti (-2.58%, 95% CI: -4.44; -0.68, IQR: 0.03), and FVC showed negative associations with concentrations of three elements: Si (-3.23%, 95% CI: -5.61; -0.79), Al (-3.26%, 95% CI: -5.73; -0.72), and Ca (-1.86%, 95% CI: -3.23; -0.47). In stratified analysis, Si, Al, Ca, and Ti showed associations with lung function only among truck drivers, and no significant association among office workers. Conclusion: Selected elemental components of PM2.5 showed effects on lung function that were not found in analyses of particle levels alone. Electronic supplementary material The online version of this article (doi:10.1186/s12989-014-0051-7) contains supplementary material, which is available to authorized users.

Background: Previous studies have examined fine particulate matter (≤ 2.5 μm; PM2.5) and preterm birth, but there is a dearth of longitudinal studies on this topic and a paucity of studies that have investigated specific sources of this exposure. Objectives: Our aim was to assess whether anthropogenic sources are associated with risk of preterm birth, comparing successive pregnancies to the same woman. Methods: Birth certificates were used to select women who had vaginal singleton live births at least twice in Connecticut during 2000–2006 (n = 23,123 women, n = 48,208 births). We procured 4,085 daily samples of PM2.5 on Teflon filters from the Connecticut Department of Environmental Protection for six cities in Connecticut. Filters were analyzed for chemical composition, and Positive Matrix Factorization was used to determine contributions of PM2.5 sources. Risk estimates were calculated with conditional logistic regression, matching pregnancies to the same women. Results: Odds ratios of preterm birth per interquartile range increase in whole pregnancy exposure to dust, motor vehicle emissions, oil combustion, and regional sulfur PM2.5 sources were 1.01 (95% CI: 0.93, 1.09), 1.01 (95% CI: 0.92, 1.10), 1.00 (95% CI: 0.89, 1.12), and 1.09 (95% CI: 0.97, 1.22), respectively. Conclusion: This was the first study of PM2.5 sources and preterm birth, and the first matched analysis, that better addresses individual-level confounding potentially inherent in all past studies. There was insufficient evidence to suggest that sources were statistically significantly associated with preterm birth. However, elevated central estimates and previously observed associations with mass concentration motivate the need for further research. Future studies would benefit from high source exposure settings and longitudinal study designs, such as that adopted in this study. Citation: Pereira G, Bell ML, Lee HJ, Koutrakis P, Belanger K. 2014. Sources of fine particulate matter and risk of preterm birth in Connecticut, 2000–2006: a longitudinal study. Environ Health Perspect 122:1117–1122; http://dx.doi.org/10.1289/ehp.1307741

Aerosol optical thickness (AOT) data retrieved by the Multiangle Imaging Spectroradiometer (MISR) in 2001 were compared with AOT measurements from 16 Aerosol Robotic Network (AERONET) sites over the contiguous United States. Overall, MISR and AERONET AOTs were strongly correlated (r = 0.73). Regression analysis showed that the root mean square error (RMSE) of MISR AOT was 0.05. The overall retrieval error of MISR AOT was within ±0.04 ± 0.18 × AOT. This result as well as the regression slope and intercept were comparable with previous results using AOT retrievals from MISR or Moderate Resolution Imaging Spectroradiometer (MODIS). The agreement between MISR and AERONET AOTs was improved (R2 = 0.90, RMSE = 0.04) when data from three western inland sites were excluded. A paired t test indicated that MISR systematically overestimated AOT by 0.02 ± 0.007. It was also shown that this positive bias in MISR AOT was greater during the spring and summer as well as in western United States. Together, these results suggest that MISR AOT measurements may be suitable for quantitative analysis of aerosol abundance. Finally, it is unlikely that the current results will vary when using alternative MISR AOT parameters since our analysis also showed the MISR AOT parameters (best fit, regional mean, and weighted regional mean AOTs) to be highly comparable.

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.

Epidemiologic studies of particulate sources and adverse health do not account for the uncertainty in the source contribution estimates. Our goal was to assess the impact of uncertainty on the effect estimates of particulate sources on emergency cardiovascular (CVD) admissions. We examined the effects of PM2.5 sources, identified by positive matrix factorization (PMF) and absolute principle component analysis (APCA), on emergency CVD hospital admissions among Medicare enrollees in Boston, MA, during 2003–2010, given stronger associations for this period. We propagated uncertainty in source contributions using a block bootstrap procedure. We further estimated average across-methods source-specific effect estimates using bootstrap samples. We estimated contributions for regional, mobile, crustal, residual oil combustion, road dust, and sea salt sources. Accounting for uncertainty, same-day exposures to regional pollution were associated with an across-methods average effect of 2.00% (0.18, 3.78%) increase in the rate of CVD admissions. Weekly residual oil exposures resulted in an average 2.12% (0.19, 4.22%) increase. Same-day and 2-day exposures to mobile-related PM2.5 were also associated with increased admissions. Confidence intervals when accounting for the uncertainty were wider than otherwise. Agreement in PMF and APCA results was stronger when uncertainty was considered in health models. Accounting for uncertainty in source contributions leads to more stable effect estimates across methods and potentially to fewer spurious significant associations.

Background: Few studies have been performed on pulmonary effects of air pollution in the elderly—a vulnerable population with low reserve capacity—and mechanisms and susceptibility factors for potential effects are unclear. Objectives: We evaluated the lag structure of air pollutant associations with lung function and potential effect modification by DNA methylation (< or ≥ median) at 26 individual CpG sites in nine candidate genes in a well-characterized cohort of elderly men. Methods: We measured forced vital capacity (FVC), forced expiratory volume in 1 sec (FEV1), and blood DNA methylation one to four times between 1999 and 2009 in 776 men from the Normative Aging Study. Air pollution was measured at fixed monitors 4 hr to 28 days before lung function tests. We used linear mixed-effects models to estimate the main effects of air pollutants and effect modification by DNA methylation. Results: An interquartile range (IQR) increase in subchronic exposure (3 to 28 days cumulated), but not in acute exposure (during the previous 4 hr, or the current or previous day), to black carbon, total and nontraffic particles with aerodynamic diameter ≤ 2.5 μm (PM2.5), carbon monoxide, and nitrogen dioxide was associated with a 1–5% decrease in FVC and FEV1 (p < 0.05). Slope estimates were greater for FVC than FEV1, and increased with cumulative exposure. The estimates slopes for air pollutants (28 days cumulated) were higher in participants with low (< median) methylation in TLR2 at position 2 and position 5 and high (≥ median) methylation in GCR. Conclusions: Subchronic exposure to traffic-related pollutants was associated with significantly reduced lung function in the elderly; nontraffic pollutants (particles, ozone) had weaker associations. Epigenetic mechanisms related to inflammation and immunity may influence these associations. Citation: Lepeule J, Bind MAC, Baccarelli AA, Koutrakis P, Tarantini L, Litonjua A, Sparrow D, Vokonas P, Schwartz JD. 2014. Epigenetic influences on associations between air pollutants and lung function in elderly men: the Normative Aging Study. Environ Health Perspect 122:566–572; http://dx.doi.org/10.1289/ehp.1206458

Background: Extreme weather and air pollution are associated with increased cardiovascular risk in people with diabetes. Objectives: In a population with diabetes, we conducted a novel assessment of vascular brachial artery responses both to ambient pollution and to weather (temperature and water vapor pressure, a measure of humidity). Methods: Sixty-four 49- to 85-year-old Boston residents with type 2 diabetes completed up to five study visits (279 repeated measures). Brachial artery diameter (BAD) was measured by ultrasound before and after brachial artery occlusion [i.e., flow-mediated dilation (FMD)] and before and after nitroglycerin-mediated dilation (NMD). Ambient concentrations of fine particulate mass (PM2.5), black carbon (BC), organic carbon (OC), elemental carbon, particle number, and sulfate were measured at our monitoring site; ambient concentrations of carbon monoxide, nitrogen dioxide, and ozone were obtained from state monitors. Particle exposure in the home and during each trip to the clinic (home/trip exposure) was measured continuously and as a 5-day integrated sample. We used linear models with fixed effects for participants, adjusting for date, season, temperature, and water vapor pressure on the day of each visit, to estimate associations between our outcomes and interquartile range increases in exposure. Results: Baseline BAD was negatively associated with particle pollution, including home/trip–integrated BC (–0.02 mm; 95% CI: –0.04, –0.003, for a 0.28 μg/m3 increase in BC), OC (–0.08 mm; 95% CI: –0.14, –0.03, for a 1.61 μg/m3 increase) as well as PM2.5, 5-day average ambient PM2.5, and BC. BAD was positively associated with ambient temperature and water vapor pressure. However, exposures were not consistently associated with FMD or NMD. Conclusion: Brachial artery diameter, a predictor of cardiovascular risk, decreased in association with particle pollution and increased in association with ambient temperature in our study population of adults with type 2 diabetes. Citation: Zanobetti A, Luttmann-Gibson H, Horton ES, Cohen A, Coull BA, Hoffmann B, Schwartz JD, Mittleman MA, Li Y, Stone PH, de Souza C, Lamparello B, Koutrakis P, Gold DR. 2014. Brachial artery responses to ambient pollution, temperature, and humidity in people with type 2 diabetes: a repeated-measures study. Environ Health Perspect 122:242–248; http://dx.doi.org/10.1289/ehp.1206136