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Previously, we found increased rates of ST-elevation myocardial infarction (STEMI) associated with increased ultrafine particle (UFP;100 nm) concentrations in the previous few hours in Rochester, New York. Relative rates were higher after air quality policies and a recession reduced pollutant concentrations (2014-2016 versus 2005-2013), suggesting PM composition had changed and the same PM mass concentration had become more toxic. Tier 3 light duty vehicles, which should produce less primary organic aerosols and oxidizable gaseous compounds, likely making PM less toxic, were introduced in 2017. Thus, we hypothesized we would observe a lower relative STEMI rate in 2017-2019 than 2014-2016.Using STEMI events treated at the University of Rochester Medical Center (2014-2019), UFP and other pollutants measured in Rochester, a case-crossover design, and conditional logistic regression models, we estimated the rate of STEMI associated with increased UFP and other pollutants in the previous hours and days in the 2014-2016 and 2017-2019 periods.An increased rate of STEMI was associated with each 3111 particles/cmGreater rates of STEMI were associated with short term increases in concentrations of UFP and other motor vehicle related pollutants before Tier 3 introduction (2014-2016), but not afterwards (2017-2019). This change may be due to changes in PM composition after Tier 3 introduction, as well as to increased exposure misclassification and greater underestimation of effects from 2017 to 2019.

In the past several decades, a variety of efforts have been made in the United States to improve air quality, and ambient particulate matter (PM) concentrations have been used as a metric to evaluate the efficacy of environmental policies. However, ambient PM concentrations result from a combination of source emission rates and meteorological conditions, which also change over time. Dispersion normalization was recently developed to reduce the influence of atmospheric dispersion and proved an effective approach that enhanced diel/seasonal patterns and thus provides improved source apportionment results for speciated PM mass and particle number concentration (PNC) measurements. In this work, dispersion normalization was incorporated in long-term trend analysis of 11-500 nm PNCs derived from particle number size distributions (PNSDs) measured in Rochester, NY from 2005 to 2019. Before dispersion normalization, a consistent reduction was observed across the measured size range during 2005-2012, while after 2012, the decreasing trends slowed down for accumulation mode PNCs (100-500 nm) and reversed for ultrafine particles (UFPs, 11-100 nm). Through dispersion normalization, we showed that these changes were driven by both emission rates and dispersion. Thus, it is important for future studies to assess the effects of the changing meteorological conditions when evaluating policy effectiveness on controlling PM concentrations. Before and after dispersion normalization, an evident increase in nucleation mode particles was observed during 2015-2019. This increase was possibly enabled by a cleaner atmosphere and will pose new challenges for future source apportionment and accountability studies.

Background: Previous work reported increased rates of acute cardiovascular hospitalizations associated with increased PM2.5 concentrations in the previous few days across urban centers in New York State from 2005 to 2016. These relative rates were higher after air quality policies and economic changes resulted in decreased PM2.5 concentrations and changes in PM composition (e.g. increased secondary organic carbon), compared to before and during these changes. Changes in PM composition and sources may explain this difference. Objectives: To estimate the rate of acute cardiovascular hospitalizations associated with increases in source specific PM2.5 concentrations. Methods: Using source apportioned PM2.5 concentrations at the same NYS urban sites, a time-stratified case-crossover design, and conditional logistic regression models adjusting for ambient temperature and relative humidity, we estimated the rate of these acute cardiovascular hospitalizations associated with increases in mean source specific PM2.5 concentrations in the previous 1, 4, and 7 days. Results: Interquartile range (IQR) increases in spark-ignition emissions (GAS) concentrations were associated with increased excess rates of cardiac arrhythmia hospitalizations (2.3%; 95% CI = 0.4%, 4.2%; IQR = 2.56 μg/m3) and ischemic stroke hospitalizations (3.7%; 95% CI = 1.1%, 6.4%; 2. 73 μg/m3) over the next day. IQR increases in diesel (DIE) concentrations were associated with increased rates of congestive heart failure hospitalizations (0.7%; 95% CI = 0.2% 1.3%; 0.51 μg/m3) and ischemic heart disease hospitalizations (0.8%; 95% CI = 0.3%, 1.3%; 0.60 μg/m3) over the next day, as hypothesized. However, secondary sulfate PM2.5 (SS) was not. Increased acute cardiovascular hospitalization rates were also associated with IQR increases in concentrations of road dust (RD), residual oil (RO), and secondary nitrate (SN) over the previous 1, 4, and 7 days, but not other sources. Conclusions: These findings suggest a role of several sources of PM2.5 in New York State (i.e. traffic emissions, non-traffic emissions such as brake and tire wear, residual oil, and nitrate that may also reflect traffic emissions) in the triggering of acute cardiovascular events. Keywords: Cardiovascular hospitalizations, Air pollution, Source apportionment, Traffic emissions

Effect estimates of prenatal exposure to ambient PM

PURPOSE: Long-term exposure to ambient fine particle (PM(2.5)) concentrations has been associated with an increased rate or risk of neurodegenerative conditions but individual PM sources have not been previously examined in relation to neurodegenerative diseases. METHODS: Using the Statewide Planning and Research Cooperative System database, we studied 63,287 hospital admissions with a primary diagnosis of either Alzheimer’s disease (AD), dementia, or Parkinson’s disease (PD) for New York State (NYS) residents living within 15 miles from six PM(2.5) monitoring sites. In addition to PM(2.5) concentrations, we studied seven specific PM(2.5) sources: secondary sulfate, secondary nitrate, biomass burning, diesel, spark-ignition emissions, pyrolyzed organic rich, and road dust. We estimated the rate of neurodegenerative hospital admissions associated with increased concentration of PM(2.5) and individual PM(2.5) sources average concentrations in the previous 0–29, 0–179, and 0–364 days. RESULTS: Increases in ambient PM(2.5) concentrations were not consistently associated with increased hospital admissions rates. Increased source-specific PM2.5 concentrations were associated with both increased (e.g., secondary sulfates and diesel emissions) and decreased rates (e.g., secondary nitrate and spark-ignition vehicular emissions) of neurodegenerative admissions. CONCLUSIONS: We did not observe clear associations between overall ambient PM(2.5) concentrations or source apportioned ambient PM(2.5) contributions and rates of neurologic disease hospitalizations.

BACKGROUND: Emissions control programs targeting certain air pollution sources may alter PM(2.5) composition, as well as the risk of adverse health outcomes associated with PM(2.5). OBJECTIVES: We examined temporal changes in the risk of emergency department (ED) visits for cardiovascular diseases (CVDs) and asthma associated with short-term increases in ambient PM(2.5) concentrations in Los Angeles, California. METHODS: Poisson log-linear models with unconstrained distributed exposure lags were used to estimate the risk of CVD and asthma ED visits associated with short-term increases in daily PM(2.5) concentrations, controlling for temporal and meteorological confounders. The models were run separately for three predefined time periods, which were selected based on the implementation of multiple emissions control programs (EARLY: 2005-2008; MIDDLE: 2009-2012; LATE: 2013-2016). Two-pollutant models with individual PM(2.5) components and the remaining PM(2.5) mass were also considered to assess the influence of changes in PM(2.5) composition on changes in the risk of CVD and asthma ED visits associated with PM(2.5) over time. RESULTS: The relative risk of CVD ED visits associated with a 10 μg/m(3) increase in 4-day PM(2.5) concentration (lag 0-3) was higher in the LATE period (rate ratio = 1.020, 95% confidence interval = [1.010, 1.030]) compared to the EARLY period (1.003, [0.996, 1.010]). In contrast, for asthma, relative risk estimates were largest in the EARLY period (1.018, [1.006, 1.029]), but smaller in the following periods. Similar temporal differences in relative risk estimates for CVD and asthma were observed among different age and season groups. No single component was identified as an obvious contributor to the changing risk estimates over time, and some components exhibited different temporal patterns in risk estimates from PM(2.5) total mass, such as a decreased risk of CVD ED visits associated with sulfate over time. CONCLUSIONS: Temporal changes in the risk of CVD and asthma ED visits associated with short-term increases in ambient PM(2.5) concentrations were observed. These changes could be related to changes in PM(2.5) composition (e.g., an increasing fraction of organic carbon and a decreasing fraction of sulfate in PM(2.5)). Other factors such as improvements in healthcare and differential exposure misclassification might also contribute to the changes.

To address limitations of observational epidemiology studies of air pollution and health effects, including residual confounding by temporal and spatial factors, several studies have taken advantage of ‘natural experiments’, where an environmental policy or air quality intervention has resulted in reductions in ambient air pollution concentrations. Researchers have examined whether the population impacted by these air quality improvements, also experienced improvements in various health indices (e.g. reduced morbidity/mortality). In this paper, I review key accountability studies done previously and new studies done over the past several years in Beijing, Atlanta, London, Ireland, and other locations, describing study design and analysis strengths and limitations of each. As new ‘natural experiment’ opportunities arise, several lessons learned from these studies should be applied when planning a new accountability study. Comparison of health outcomes during the intervention to both before and after the intervention in the population of interest, as well as use of a control population to assess whether any temporal changes in the population of interest were also seen in populations not impacted by air quality improvements, should aid in minimizing residual confounding by these long term time trends. Use of either detailed health records for a population, or prospectively collected data on relevant mechanistic biomarkers coupled with such morbidity/mortality data may provide a more thorough assessment of if the intervention beneficially impacted the health of the community, and if so by what mechanism(s). Further, prospective measurement of a large suite of air pollutants may allow a more thorough understanding of what pollutant source(s) is/are responsible for any health benefit observed. The importance of using multiple statistical analysis methods in each paper and the difference in how the timing of the air pollution/outcome association may impact which of these design features is most important is also discussed. Based on these and other lessons learned, researchers may provide a more epidemiologically rigorous evaluation of cause-specific health impacts of an air quality intervention or action. Keywords: Air pollution, Epidemiology, Accountability, Natural experiment, Confounding

The response of respiratory infections to source-specific particulate matter (PM) is an area of active research. Using source-specific PM2.5 concentrations at six urban sites in New York State, a case-crossover design, and conditional logistic regression, we examined the association between source-specific PM and the rate of hospitalizations and emergency department (ED) visits for influenza or culture-negative pneumonia from 2005 to 2016. There were at most N = 14 764 influenza hospitalizations, N = 57 522 influenza ED visits, N = 274 226 culture-negative pneumonia hospitalizations, and N = 113 997 culture-negative pneumonia ED visits included in our analyses. We separately estimated the rate of respiratory infection associated with increased concentrations of source-specific PM2.5, including secondary sulfate (SS), secondary nitrate (SN), biomass burning (BB), pyrolyzed organic carbon (OP), road dust (RD), residual oil (RO), diesel (DIE), and spark ignition vehicle emissions (GAS). Increased rates of ED visits for influenza were associated with interquartile range increases in concentrations of GAS (excess rate [ER] = 9.2%; 95% CI: 4.3%, 14.3%) and DIE (ER = 3.9%; 95% CI: 1.1%, 6.8%) for lag days 0–3. There were similar associations between BB, SS, OP, and RO, and ED visits or hospitalizations for influenza, but not culture-negative pneumonia hospitalizations or ED visits. Short-term increases in PM2.5 from traffic and other combustion sources appear to be a potential risk factor for increased rates of influenza hospitalizations and ED visits.

Prior work found increased rates for emergency department (ED) visits for asthma and hospitalizations for chronic obstructive pulmonary disease per unit mass of PM(2.5) across New York State (NYS) during 2014 to 2016 after major reductions in ambient PM2.5 concentrations had occurred following implementation of various policy actions and major economic disruptions. The associations of source-specific PM(2.5) concentrations with these respiratory diseases were assessed with a time-stratified case-control design and logistic regression models to identify the changes in the PM(2.5) that have led to the apparently increased toxicity per unit mass. The rates of ED visits and hospitalizations for asthma and COPD associated with increases in source-specific PM2.5 concentrations in the prior 1, 4, and 7 days were estimated for 6 urban sites in New York State. Overall, there were similar numbers of significantly increased (n=9) and decreased rates (n=8) of respiratory events (asthma and COPD hospitalizations and ED visits) associated with increased source-specific PM(2.5) concentrations in the previous 1, 4, and 7 days. Associations of source-specific PM(2.5) concentrations with excess rates of hospitalizations for COPD for spark- and compression ignition vehicles increased in the 2014–2016 period, but the values were not statistically significant. Other source types showed inconsistent patterns of excess rates. For asthma ED visits, only biomass burning and road dust showed consistent positive associations with road dust having significant values for most lag times. Secondary nitrate also showed significant positive associations with asthma ED visits in the AFTER period compared to no associations in the prior periods. These results suggest that the relationships of asthma and COPD exacerbation with source-specific PM(2.5) are not well defined and further work will be needed to determine the causes of the apparent increases in the per unit mass toxicity of PM(2.5) in New York State in the 2014–16 period.

Prior studies reported that exposure to increased concentrations of fine particulate matter (PM

The northeastern United States has experienced significant emissions reductions in the last two decades leading to a decrease in PM2.5, major gaseous pollutants (SO2, CO, NOx) and ultrafine particles (UFPs) concentrations. Emissions controls were implemented for coal-fired power plants, and new heavy-duty diesel trucks were equipped with particle traps and NOx control systems, and ultralow sulfur content is mandatory for both road and non-road diesel as well as residual oil for space heating. At the same time, economic changes also influenced the trends in air pollutants. Investigating the influence of these changes on ultrafine particle sources is fundamental to determine the success of the mitigation strategies and to plan future actions. Particle size distributions have been measured in Rochester, NY since January 2002. The particle sources were investigated with positive matrix factorization (PMF) of the size distributions (11&ndash, 470 nm) and measured criteria pollutants during five periods (2002&ndash, 2003, 2004&ndash, 2007, 2008&ndash, 2010, 2011&ndash, 2013, and 2014&ndash, 2016) and three seasons (winter, summer, and transition). Monthly, weekly, and hourly source contributions patterns were evaluated.

Rationale: Fine particulate matter air pollution of 2.5 μm or less in diameter (PM2.5) has been associated with an increased risk of respiratory disease, but assessments of specific respiratory infections in adults are lacking. Objectives: To estimate the rate of respiratory infection healthcare encounters in adults associated with acute increases in PM2.5 concentrations. Methods: Using case–crossover methods, we studied 498,118 adult New York State residents with a primary diagnosis of influenza, bacterial pneumonia, or culture-negative pneumonia upon hospitalization or emergency department (ED) visit (2005–2016). We estimated the relative rate of healthcare encounters associated with increases in PM2.5 in the previous 1–7 days and explored differences before (2005–2007), during (2008–2013), and after (2014–2016) implementation of air quality policies and economic changes. Results: Interquartile range increases in PM2.5 over the previous 7 days were associated with increased excess rates (ERs) of culture-negative pneumonia hospitalizations (2.5%; 95% confidence interval [CI], 1.7–3.2%) and ED visits (2.5%; 95% CI, 1.4–3.6%), and increased ERs of influenza ED visits (3.9%; 95% CI, 2.1–5.6%). Bacterial pneumonia hospitalizations, but not ED visits, were associated with increases in PM2.5 and, though imprecise, were of a similar magnitude to culture-negative pneumonia (Lag Day 6 ER, 2.3%; 95% CI, 0.3–4.3). Increased relative rates of influenza ED visits and culture-negative pneumonia hospitalizations were generally larger in the “after” period (P

Conditional probability functions are commonly used for source identification purposes in air pollution studies. CBPF (conditional bivariate probability function) categorizes the probability of high concentrations being observed at a location by wind direction/speed and investigate the directionality of local sources. PSCF (potential source contribution function), a trajectory-ensemble method, identifies the source regions most likely to be associated with high measured concentrations. However, these techniques do not allow the direct identification of areas where changes in emissions have occurred. This study presents an extension of conditional probability methods in which the differences between conditional probability values for temporally different sets of data can be used to explore changes in emissions from source locations. The differential CBPF and differential PSCF were tested using a long-term series of air quality data (12 years; 2005/2016) collected in Rochester, NY. The probability functions were computed for each of 4 periods that represent known changes in emissions. Correlation analyses were also performed on the results to find pollutants undergoing similar changes in local and regional sources. The differential probability functions permitted the identification of major changes in local and regional emission location. In Rochester, changes in local air pollution were related to the shutdown of a large coal power plant (SO2) and to the abatement measures applied to road and off-road traffic (primary pollutants). The concurrent effects of these changes in local emissions were also linked to reduced concentrations of nucleation mode particles. Changes in regional source areas were related to the decreases in secondary inorganic aerosol and organic carbon. The differential probabilities for sulfate, nitrate, and organic aerosol were consistent with differences in the available National Emission Inventory annual emission values. Changes in the source areas of black carbon and PM2.5 mass concentrations were highly correlated.

Previous studies have reported increased risks of myocardial infarction in association with elevated ambient particulate matter (PM) in the previous hour(s). However, whether PM can trigger mechanisms that act on this time scale is still unclear. We hypothesized that increases in PM are associated with rapid changes in measures of heart rate variability and repolarization. We used data from panel studies in Augsburg, Germany, and Rochester, New York, USA, and two controlled human exposure studies in Rochester. Data included ECG recordings from all four studies, controlled exposures to (concentrated) ultrafine particles (UFP; particles with an aerodynamic diameter 2.5, aerodynamic diameter 2.5 concentrations in the preceding six hours in both panel studies. We did not find consistent associations between particle metrics and T-wave complexity. This study provided consistent evidence that recent exposures to UFP and PM2.5 can induce acute pathophysiological responses.

Background Previous studies have reported that fine particle (PM2.5) concentrations triggered ST elevation myocardial infarctions (STEMI). In Rochester, NY, multiple air quality policies and economic changes/influences from 2008 to 2013 led to decreased concentrations of PM2.5 and its major constituents (SO42−, NO3−, elemental and primary organic carbon). This study examined whether the rate of STEMI associated with increased ambient gaseous and PM component concentrations was different AFTER these air quality policies and economic changes (2014–2016), compared to DURING (2008–2013) and BEFORE these polices and changes (2005–2007). Methods Using 921 STEMIs treated at the University of Rochester Medical Center (2005–2016) and a case-crossover design, we examined whether the rate of STEMI associated with increased PM2.5, ultrafine particles (UFP

BACKGROUND: Previous studies have reported associations between ambient fine particle (PM(2.5)) concentrations and hypertensive disorders of pregnancy (HDP). However, none have examined whether ultrafine particles (UFP

Background Previous studies reported triggering of acute cardiovascular events by short-term increasedPM2.5 concentrations. From 2007 to 2013, national and New York state air quality policies and economic influences resulted in reduced concentrations of PM2.5 and other pollutants across the state. We estimated the rate of cardiovascular hospital admissions associated with increased PM2.5 concentrations in the previous 1–7 days, and evaluated whether they differed before (2005–2007), during (2008–2013), and after these concentration changes (2014–2016). Methods Using the Statewide Planning and Research Cooperative System (SPARCS) database, we retained all hospital admissions with a primary diagnosis of nine cardiovascular disease (CVD) subtypes, for residents living within 15 miles of PM2.5 monitoring sites in Buffalo, Rochester, Albany, Queens, Bronx, and Manhattan from 2005 to 2016 (N = 1,922,918). We used a case-crossover design and conditional logistic regression to estimate the admission rate for total CVD, and nine specific subtypes, associated with increased PM2.5 concentrations. Results Interquartile range (IQR) increases in PM2.5 on the same and previous 6 days were associated with 0.6%–1.2% increases in CVD admission rate (2005–2016). There were similar patterns for cardiac arrhythmia, ischemic stroke, congestive heart failure, ischemic heart disease (IHD), and myocardial infarction (MI). Ambient PM2.5 concentrations and annual total CVD admission rates decreased across the period. However, the excess rate of IHD admissions associated with each IQR increase in PM2.5 in previous 2 days was larger in the after period (2.8%; 95%CI = 1.5%–4.0%) than in the during (0.6%; 95%CI = 0.0%–1.2%) or before periods (0.8%; 95%CI = 0.2%–1.3%), with similar patterns for total CVD and MI, but not other subtypes. Conclusions While pollutant concentrations and CVD admission rates decreased after emission changes, the same PM2.5 mass was associated with a higher rate of ischemic heart disease events. Future work should confirm these findings in another population, and investigate whether specific PM components and/or sources trigger IHD events.

Land-use regression (LUR) models provide location and time specific estimates of exposure to air pollution and thereby improve the sensitivity of health effects models. However, they require pollutant concentrations at multiple locations along with land-use variables. Often, monitoring is performed over short durations using mobile monitoring with research-grade instruments. Low-cost PM monitors provide an alternative approach that increases the spatial and temporal resolution of the air quality data. LUR models were developed to predict hourly PM concentrations across a metropolitan area using PM concentrations measured simultaneously at multiple locations with low-cost monitors. Monitors were placed at 23 sites during the 2015/16 heating season. Monitors were externally calibrated using co-located measurements including a reference instrument (GRIMM particle spectrometer). LUR models for each hour of the day and weekdays/weekend days were developed using the deletion/substitution/addition algorithm. Coefficients of determination for hourly PM predictions ranged from 0.66 and 0.76 (average 0.7). The hourly-resolved LUR model results will be used in epidemiological studies to examine if and how quickly, increases in ambient PM concentrations trigger adverse health events by reducing the exposure misclassification that arises from using less time resolved exposure estimates.

Land use regression modeling (LUR) through local scale circular modeling domains has been used to predict traffic-related air pollution such as nitrogen oxides (NOX). LUR modeling for fine particulate matters (PM), which generally have smaller spatial gradients than NOX, has been typically applied for studies involving multiple study regions. To increase the spatial coverage for fine PM and key constituent concentrations, we designed a mobile monitoring network in Monroe County, New York to measure pollutant concentrations of black carbon (BC, wavelength at 880 nm), ultraviolet black carbon (UVBC, wavelength at 3700 nm) and Delta-C (the difference between the UVBC and BC concentrations) using the Clarkson University Mobile Air Pollution Monitoring Laboratory (MAPL). A Deletion/Substitution/Addition (D/S/A) algorithm was conducted, which used circular buffers as a basis for statistics. The algorithm maximizes the prediction accuracy for locations without measurements using the V-fold cross-validation technique, and it reduces overfitting compared to other approaches. We found that the D/S/A LUR modeling approach could achieve good results, with prediction powers of 60%, 63%, and 61%, respectively, for BC, UVBC, and Delta-C. The advantage of mobile monitoring is that it can monitor pollutant concentrations at hundreds of spatial points in a region, rather than the typical less than 100 points from a fixed site saturation monitoring network. This research indicates that a mobile saturation sampling network, when combined with proper modeling techniques, can uncover small area variations (e.g., 10 m) in particulate matter concentrations.

Prior work has reported acute associations between ST-elevation myocardial infarction (STEMI) and short-term increases in airborne particulate matter. Subsequently, the association between STEMI and hourly measures of Delta-C (marker of woodsmoke) and black carbon (marker of traffic pollution) measured at a central site in Rochester, NY, were examined, but no association was found. Therefore, land use regression estimates of Delta-C and black carbon concentrations at each patient’s residence were developed for 246 STEMI patients treated at the University of Rochester Medical Center during the winters of 2008–2012. Using case-crossover methods, the rate of STEMI associated with increased Delta-C and BC concentration on the same and previous 3 days was estimated after adjusting for 3-day mean temperature and relative humidity. Non-statistically significant increased rates of STEMI associated with interquartile range increases in concentrations of BC in the previous 2 days (1.10 μg/m3; OR = 1.12; 95% CI 0.93, 1.35) and Delta-C in the previous 3 days (0.43 μg/m3; OR = 1.16; 95% CI 0.96, 1.40) were found. Significantly increased rates of STEMI associated with interquartile range increases in concentrations of BC (1.23 μg/m3; OR = 1.04; 95% CI = 0.87, 1.24) or Delta-C (0.40 μg/m3; OR = 0.94; 95% CI = 0.85, 1.09) on the same day were not observed likely due, in part, to temporal misalignment. Therefore, sophisticated spatial-temporal models will be needed to minimize exposure error and bias by better predicting concentrations at individual locations for individual hours, especially for outcomes with short-term responses to air pollution (

We previously reported an increased risk of stillbirth associated with increases in trimester-specific ambient air pollutant concentrations. Here, we consider whether sudden increase in the mean ambient air pollutant concentration immediately before delivery triggers stillbirth.We used New Jersey linked fetal death and hospital discharge data and hourly ambient air pollution measurements from particulate matter ≤ 2.5 mm (PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2) monitors across New Jersey for the years 1998-2004. For each stillbirth, we assigned the concentration of air pollutants from the closest monitoring site within 10 km of the maternal residence. Using a time-stratified case-crossover design and conditional logistic regression, we estimated the relative odds of stillbirth associated with interquartile range (IQR) increases in the mean pollutant concentrations on lag day 2 and lag days 2 through 6 before delivery, and whether these associations were modified by maternal risk factors.The relative odds of stillbirth increased with IQR increases in the mean concentrations of CO (odds ratio [OR] = 1.20, 95% confidence interval [CI] = 1.05-1.37), SO2 (OR = 1.11, 95% CI = 1.02-1.22), NO2 (OR = 1.11, 95% CI = 0.97-1.26), and PM2.5 (OR = 1.07, 95% CI = 0.93-1.22) 2 days before delivery. We found similar associations with increases in pollutants 2 through 6 days before delivery. These associations were not modified by maternal risk factors.Short-term increases in ambient air pollutant concentrations immediately before delivery may trigger stillbirth.

Rationale: Unprecedented pollution control actions during the Beijing Olympics provided a quasi-experimental opportunity to examine biologic responses to drastic changes in air pollution levels.Objectives: To determine whether changes in levels of biomarkers reflecting pulmonary inflammation and pulmonary and systemic oxidative stress were associated with changes in air pollution levels in healthy young adults.Methods: We measured fractional exhaled nitric oxide, a number of exhaled breath condensate markers (H+, nitrite, nitrate, and 8-isoprostane), and urinary 8-hydroxy-2-deoxyguanosine in 125 participants twice in each of the pre- (high pollution), during- (low pollution), and post-Olympic (high pollution) periods. We measured concentrations of air pollutants near where the participants lived and worked. We used mixed-effects models to estimate changes in biomarker levels across the three periods and to examine whether changes in biomarker levels were associated with changes in pollutant concentrations...

Background: Mechanisms underlying previously reported air pollution and cardiovascular (CV) morbidity associations remain poorly understood. Objectives: We examined associations between markers of pathways thought to underlie these air pollution and CV associations and ambient particle concentrations in postinfarction patients. Methods: We studied 76 patients, from June 2006 to November 2009, who participated in a 10-week cardiac rehabilitation program following a recent (within 3 months) myocardial infarction or unstable angina. Ambient ultrafine particle (UFP; 10–100 nm), accumulation mode particle (AMP; 100–500 nm), and fine particle concentrations (PM2.5; ≤ 2.5 μm in aerodynamic diameter) were monitored continuously. Continuous Holter electrocardiogram (ECG) recordings were made before and during supervised, graded, twice weekly, exercise sessions. A venous blood sample was collected and blood pressure was measured before sessions. Results: Using mixed effects models, we observed adverse changes in rMSSD [square root of the mean of the sum of the squared differences between adjacent normal-to-normal (NN) intervals], SDNN (standard deviation of all NN beat intervals), TpTe (time from peak to end of T-wave), heart rate turbulence, systolic and diastolic blood pressures, C-reactive protein, and fibrinogen associated with interquartile range increases in UFP, AMP, and PM2.5 at 1 or more lag times within the previous 5 days. Exposures were not associated with MeanNN, heart-rate–corrected QT interval duration (QTc), deceleration capacity, and white blood cell count was not associated with UFP, AMP, and PM2.5 at any lag time. Conclusions: In cardiac rehabilitation patients, particles were associated with subclinical decreases in parasympathetic modulation, prolongation of late repolarization duration, increased blood pressure, and systemic inflammation. It is possible that such changes could increase the risk of CV events in this susceptible population.

International audience; BACKGROUND: The findings of prior studies of air pollution effects on adverse birth outcomes are difficult to synthesize because of differences in study design. OBJECTIVES: The International Collaboration on Air Pollution and Pregnancy Outcomes was formed to understand how differences in research methods contribute to variations in findings. We initiated a feasibility study to a) assess the ability of geographically diverse research groups to analyze their data sets using a common protocol and b) perform location-specific analyses of air pollution effects on birth weight using a standardized statistical approach. METHODS: Fourteen research groups from nine countries participated. We developed a protocol to estimate odds ratios (ORs) for the association between particulate matter ≤ 10 μm in aerodynamic diameter (PM₁₀) and low birth weight (LBW) among term births, adjusted first for socioeconomic status (SES) and second for additional location-specific variables. RESULTS: Among locations with data for the PM₁₀ analysis, ORs estimating the relative risk of term LBW associated with a 10-μg/m³ increase in average PM₁₀ concentration during pregnancy, adjusted for SES, ranged from 0.63 [95% confidence interval (CI), 0.30-1.35] for the Netherlands to 1.15 (95% CI, 0.61-2.18) for Vancouver, with six research groups reporting statistically significant adverse associations. We found evidence of statistically significant heterogeneity in estimated effects among locations. CONCLUSIONS: Variability in PM₁₀-LBW relationships among study locations remained despite use of a common statistical approach. A more detailed meta-analysis and use of more complex protocols for future analysis may uncover reasons for heterogeneity across locations. However, our findings confirm the potential for a diverse group of researchers to analyze their data in a standardized way to improve understanding of air pollution effects on birth outcomes.

Background Epidemiologic studies consistently demonstrate an association between acute cardiopulmonary events and changes in air pollution; however, the mechanisms that underlie these associations are not completely understood. Oxidative stress and inflammation have been suggested to play a role in human responses to air pollution. The proteasome is an intracellular protein degradation system linked to both of these processes and may help mediate air pollution effects. Objectives In these studies, we determined whether acute experimental exposure to two different aerosols altered white blood cell (WBC) or red blood cell (RBC) proteasome activity in human subjects. One aerosol was fresh diesel exhaust (DE), and the other freshly generated secondary organic aerosol (SOA). Methods Thirty-eight healthy subjects underwent 2-hr resting inhalation exposures to DE and separate exposures to clean air (CA); 26 subjects were exposed to DE, CA, and SOA. CA responses were subtracted from DE or SOA responses, and mixed linear models with F-tests were used to test the effect of exposure to each aerosol on WBC and RBC proteasome activity. Results WBC proteasome activity was reduced 8% (p = 0.04) after exposure to either DE or SOA and decreased by 11.5% (p = 0.03) when SOA was analyzed alone. RBCs showed similar 8–10% declines in proteasome activity (p = 0.05 for DE alone). Conclusions Air pollution produces oxidative stress and inflammation in many experimental models, including humans. Two experimental aerosols caused rapid declines in proteasome activity in peripheral blood cells, supporting a key role for the proteasome in acute human responses to air pollution.

Most previous studies (D’Ippoliti et al. 2003; Peters et al. 2001, 2005; Pope et al. 2006; Zanobetti and Schwartz 2005), but not all (Sullivan et al. 2005), that have investigated the triggering of myocardial infarction (MI) by particulate matter (PM) air pollution concentrations in the hours and days before MI onset have reported an association. Other studies have reported increased mortality due to MI or increased mortality or cardiovascular admissions among MI survivors associated with increases in PM over the previous few days (Braga et al. 2001; von Klot et al. 2005; Zanobetti and Schwartz 2007). Several studies have investigated whether certain subgroups are particularly susceptible and have reported increased cardiovascular effects among those with diabetes (Dubowsky et al. 2006; Goldberg et al. 2001; Liu et al. 2007; O’Neill et al. 2005; Zanobetti and Schwartz 2002) and among patients with chronic obstructive pulmonary disease (COPD) (Naess et al. 2007; Zanobetti and Schwartz 2005; Zanobetti et al. 2000). However, Zanobetti and Schwartz (2005) reported increased susceptibility among patients with COPD but not among persons with diabetes. Numerous researchers have reported that the percentage of infarctions that are nontransmural has been increasing (Goff et al. 2000; Hellermann et al. 2003; Kostis et al. 2007; Myerson et al. 2009; Roger et al. 2006, 2010; Rogers et al. 2008). More recently, Shao (2008) noted a similar secular trend in clinical presentation of MI to emergency departments (EDs) in New Jersey. In short, 72% of persons admitted to hospitals in New Jersey from 1990 through 1992 for MI had had transmural infarctions, and only 28% had had nontransmural infarctions. Since then, however, this pattern has reversed. From 2002 through 2004, most of the admissions for MI were for nontransmural infarctions (63%), with only 37% for transmural infarctions (Shao 2008). These changes may be due in part to improvements in preventive pharmacotherapies (statins, beta blockers, aspirin), interventional procedures [angioplasty, coronary artery bypass graft (CABG)], more sensitive diagnostic tests (troponins), and treatment of the MI upon ED arrival (reperfusion therapy, increased use of antiplatelet agents). It has not been reported whether PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) triggers all infarctions, whether PM–MI associations differ in magnitude, or whether these associations are restricted to PM–transmural or PM–nontransmural infarctions alone. Such investigations may provide insight into the mechanisms by which PM may trigger cardiovascular events. Using the same data as Shao (2008), we attempted to replicate, in New Jersey, previous MI–PM2.5 studies that were conducted in other U.S. and European cities. We hypothesized that increases in mean PM2.5 concentration on the same day and a few days before ED arrival for MI may be associated with increased risk of MI and that these effect estimates would be greater for persons with diabetes and those with COPD than for individuals without these conditions. Further, we explored whether there were differences in risks associated with increases in ambient PM2.5 concentration between transmural and nontransmural infarctions.

Ambient air pollution has been linked to cardiovascular and respiratory morbidity and mortality in epidemiology studies. Frequently, oxidative and nitrosative stress are hypothesized to mediate these pollution effects, however precise mechanisms remain unclear. This paper describes the methodology for a major panel study to examine air pollution effects on these and other mechanistic pathways. The study took place during the drastic air pollution changes accompanying the 2008 Olympics in Beijing, China. After a general description of air pollution health effects, we provide a discussion of panel studies and describe the unique features of this study that make it likely to provide compelling results. This study should lead to a clearer and more precise definition of the role of oxidative and nitrosative stress, as well as other mechanisms, in determining acute morbidity and mortality from air pollution exposure.

Objectives We explored the association between acute changes in daily mean pulmonary artery (PA) and right ventricular (RV) pressures and concentrations of ambient fine particulate matter [PM with aerodynamic diameter ≤2.5 μm (PM2.5)] as an explanation for previous associations between congestive heart failure (HF) hospital admissions and PM. Materials and methods In the Chronicle Offers Management to Patients with Advanced Signs and Symptoms of Heart Failure (COMPASS-HF) trial, to see whether management of ambulatory HF could be improved by providing continuous right heart pressure monitoring to physicians, the Chronicle Implantable Hemodynamic Monitor (Medtronic, Inc., Minneapolis, MN, USA) continuously measured multiple right heart hemodynamic parameters, heart rate, and activity trends in subjects with moderate/severe HF. Using these trial data, we calculated daily mean pressures, using only those time intervals where the subject was not physically active (n = 5,807 person-days; n = 11 subjects). We then studied the association between mean daily PA/RV pressures and mean ambient PM2.5 concentrations on the same day and previous 6 days. Results Each 11.62-μg/m3 increase in same-day mean PM2.5 concentration was associated with small but significant increases in estimated PA diastolic pressure [0.19 mmHg; 95% confidence interval (CI), 0.05–0.33] and RV diastolic pressure (0.23 mmHg; 95% CI, 0.11–0.34). Although we saw considerable differences in the magnitude of response by COMPASS-HF randomization group (total data access for physicians vs. blocked clinician access), season, left ventricular ejection fraction, and obesity, these effects were not significantly different. Conclusions These pilot study findings provide a potential mechanism for previous findings of increased risk of HF associated with ambient PM. However, because of the small number of subjects, a larger study is needed for confirmation.

Taking advantage of the natural experiment of the 2008 Beijing Olympics (August 8 to September 24), when air pollution levels decreased by 13% to 60%, the authors assessed whether having ≥1 pregnancy month during the Olympics was associated with decreased risks of hypertensive disorders (HDs) and/or fetal-placental conditions (FPCs). Singleton births to mothers with ≥1 pregnancy month in 2008 or 2009 (N = 56,155) were included. Using generalized additive models, the authors estimated the risk of HDs and FPCs associated with (1) the 2008 Olympics compared with the same dates in 2009, and (2) increased mean ambient PM10 (particulate matter with an aerodynamic diameter

Increased particulate matter (PM) air pollutant concentrations have been associated with platelet activation. It was postulated that elevated air pollutant concentrations would be associated with increases in measures of platelet function and that responses would be blunted when taking aspirin and/or fish oil. Data from a sequential therapy trial (30 subjects with type 2 diabetes mellitus), with 4 clinic visits (first: no supplements, second: aspirin, third: omega-3 fatty acid supplements, fourth: aspirin and omega-3 fatty acids) per subject, were utilized. Using linear mixed models, adjusted for relative humidity, temperature, visit number, and season, changes in three platelet function measures including (1) aggregation induced by adenosine diphosphate (ADP), (2) aggregation induced by collagen, and (3) thromboxane B2 production were associated with interquartile range (IQR) increases in mean concentrations of ambient PM2.5, black carbon, ultrafine particles (UFP; 10–100 nm), and accumulation mode particles (AMP; 100–500 nm) in the previous 1–96 h. IQR increases in mean UFP and AMP concentrations were associated with significant decreases in platelet response, with the largest being a –0.43 log(pg/ml) decrease in log(thromboxane B2) (95% CI = –0.8, –0.1) associated with each 582-particles/cm3 increase in AMP, and a –1.7 ohm reduction in collagen-induced aggregation (95% CI = –3.1, –0.3) associated with each 2097-particles/cm3 increase in UFP in the previous 72 h. This UFP effect on thromboxane B2 was significantly muted in diabetic subjects taking aspirin (–0.01 log[pg/ml]; 95% CI = –0.4, 0.3). The reason for this finding remains unknown, and needs to be investigated in future studies.

Background It remains unclear whether fine particulate (PM2.5) exposure affects risk of preterm birth and prelabor rupture of membranes. Unmeasured, poorly measured, and undiscovered individual-level confounders might have introduced bias into past studies that relied on between-women comparisons. Methods This was a longitudinal study of preterm birth and prelabor rupture of membranes in Rochester, NY, 2004-2012 (N = 3,264 women, N = 7,121 singleton births). We used conditional logistic regression to match pregnancies to the same woman and estimate the odds of each outcome associated with average PM2.5 concentrations during each trimester and whole pregnancy. Results For preterm birth, adjusted odds ratios (95% confidence interval) for 1 μg/m increase in PM2.5 in the first trimester, second trimester, third trimester, and whole pregnancy were 1.11 (1.04, 1.18), 1.09 (1.02, 1.16), 1.06 (1.00, 1.13), and 1.17 (1.07, 1.28), respectively. For prelabor rupture of membranes, corresponding odds ratios were 1.00 (0.97, 1.04), 0.99 (0.96, 1.02), 0.99 (0.96, 1.03), and 0.99 (0.94, 1.04), respectively. Conclusion Risk of preterm birth was greater for pregnancies with elevated PM2.5 exposure than other pregnancies to the same women at lower exposure. We did not observe an association between PM2.5 concentrations and prelabor rupture of membranes.

We previously observed increased odds of ST-elevation myocardial infarctions (STEMIs) associated with increased ambient fine particulate matter (PM2.5) in the previous hour. However, data are lacking on the effects of specific PM sources. Using data from 362 patients, a case-crossover design, and conditional logistic regression, we estimated the relative odds of STEMI associated with increased Delta-C (wood smoke), black carbon (BC; traffic), PM2.5, and gaseous pollutants in the previous 1-72 h. We did not observe increased odds of STEMIs associated with increased Delta-C or BC. We did observe increased odds associated with each 7.1 μg/m3 increase in PM2.5 (OR (95% CI): 1.17 (0.99, 1.39)) and each 19.9 p.p.b. increase in ozone (O3; 1.27 (1.00, 1.63)) in the previous hour, and each 0.22 p.p.m. increase in 48-h carbon monoxide (CO) concentrations (1.32 (1.00, 1.73]). Larger relative odds were associated with PM2.5 in May-October, and O3 and CO in November-April. Increased PM2.5, O3, and CO, but not wood smoke or BC, were associated with increased odds of STEMI, and effects may differ by season. Studies using spatially adjusted pollution estimates are needed, as well as studies further examining O3 and CO effects on the risk of STEMI.

Objectives: We reported previously that 24-hr moving average ambient air pollution concentrations were positively associated with ventricular arrhythmias detected by implantable cardioverter defibrillators (ICDs). ICDs also detect paroxysmal atrial fibrillation episodes (PAF) that result in rapid ventricular rates. In this same cohort of ICD patients, we assessed the association between ambient air pollution and episodes of PAF. Design: We performed a case–crossover study. Participants: Patients who lived in the Boston, Massachusetts, metropolitan area and who had ICDs implanted between June 1995 and December 1999 (n = 203) were followed until July 2002. Evaluations/Measurements: We used conditional logistic regression to explore the association between community air pollution and 91 electrophysiologist-confirmed episodes of PAF among 29 subjects. Results: We found a statistically significant positive association between episodes of PAF and increased ozone concentration (22 ppb) in the hour before the arrhythmia (odds ratio = 2.08; 95% confidence interval = 1.22, 3.54; p = 0.001). The risk estimate for a longer (24-hr) moving average was smaller, thus suggesting an immediate effect. Positive but not statistically significant risks were associated with fine particles, nitrogen dioxide, and black carbon. Conclusions: Increased ambient O3 pollution was associated with increased risk of episodes of rapid ventricular response due to PAF, thereby suggesting that community air pollution may be a precipitant of these events.

The authors evaluated the association between ventricular arrhythmias detected by implantable cardioverter defibrillators and ambient air pollution concentrations in the hours immediately before the arrhythmia. Patients given implantable cardioverter defibrillators at the New England Medical Center in Boston, Massachusetts, between mid-1995 and 1999 who lived within 40 km of a central monitoring site (n = 203) were followed until July 2002. The authors used a case-crossover design to study the association between ambient air pollution and up to 798 confirmed ventricular arrhythmias among 84 subjects. The authors found that interquartile range increases in 24-hour moving average particulate matter less than 2.5 mum in aerodynamic diameter and ozone were associated with 19% and 21% increased risks of ventricular arrhythmia, respectively. For each, there was evidence of a linear exposure response, and the associations appeared independent. These associations were stronger than associations with mean concentrations on the same calendar day and previous calendar days. The authors did not find associations with pollutant concentrations less than 24 hours before the arrhythmia. Cases with a prior ventricular arrhythmia within 72 hours had greater risk associated with air pollutants than did cases without a recent arrhythmia. These results confirm previous findings and suggest that matching of pollution periods to arrhythmias is important in detecting such associations.

Epidemiologic studies have demonstrated a consistent link between sudden cardiac deaths and particulate air pollution. We used implanted cardioverter defibrillator (ICD) records of ventricular tachyarrhythmias to assess the role of air pollution as a trigger of these potentially life-threatening events. The study cohort consisted of 203 cardiac patients with ICD devices in the Boston metropolitan area who were followed for an average of 3.1 years between 1995 and 2002. Fine particle mass and gaseous air pollution plus temperature and relative humidity were measured on almost all days, and black carbon, sulfate, and particle number on a subset of days. Date, time, and intracardiac electrograms of ICD-detected arrhythmias were downloaded at the patients' regular follow-up visits (about every 3 months). Ventricular tachyarrhythmias were identified by electrophysiologist review. Risk of ventricular arrhythmias associated with air pollution was estimated with logistic regression, adjusting for season, temperature, relative humidity, day of the week, patient, and a recent prior arrhythmia. We found increased risks of ventricular arrhythmias associated with 2-day mean exposure for all air pollutants considered, although these associations were not statistically significant. We found statistically significant associations between air pollution and ventricular arrhythmias for episodes within 3 days of a previous arrhythmia. The associations of ventricular tachyarrhythmias with fine particle mass, carbon monoxide, nitrogen dioxide, and black carbon suggest a link with motor vehicle pollutants. The associations with sulfate suggest a link with stationary fossil fuel combustion sources.

Background We and others have shown that increases in particulate air pollutant (PM) concentrations in the previous hours and days have been associated with increased risks of myocardial infarction, but little is known about the relationships between air pollution and specific subsets of myocardial infarction, such as ST-elevation myocardial infarction (STEMI) and non ST-elevation myocardial infarction (NSTEMI). Methods Using data from acute coronary syndrome patients with STEMI (n = 338) and NSTEMI (n = 339) and case-crossover methods, we estimated the risk of STEMI and NSTEMI associated with increased ambient fine particle (

Background: Epidemiological studies of air pollution have traditionally relied upon surrogates of personal exposures, such as ambient concentration measurements from central-site monitoring station...

During the 1980s the Republic of Ireland experienced repeated severe pollution episodes. Domestic coal burning was a major source of this pollution. In 1990 the Irish government introduced a ban on the marketing, sale, and distribution of coal in Dublin. The ban was extended to Cork in 1995 and to 10 other communities in 1998 and 2000. We previously reported decreases in particulate black smoke (BS*) and sulfur dioxide (SO2) concentrations, measured as total gaseous acidity, in Dublin after the 1990 coal ban (Clancy et al. 2002). In the current study we explored and compared the effectiveness of the sequential 1990, 1995, and 1998 bans in reducing community air pollution and in improving public health. We compiled records of daily BS, total gaseous acidity (SO2), and counts of cause-specific deaths from 1981 to 2004 for Dublin County Borough (1990 ban), county Cork (1995 ban), and counties Limerick, Louth, Wexford, and Wicklow (1998 ban). We also compiled daily counts of hospital admissions for cardiovascular, respiratory, and digestive diagnoses for Cork County Borough (1991 to 2004) and counties Limerick, Louth, Wexford, and Wicklow (1993 to 2004). We compared pre-ban and post-ban BS and SO2 concentrations for each city. Using interrupted time-series methods, we estimated the change in cause-specific, directly standardized mortality rates in each city or county after the corresponding local coal ban. We regressed weekly age- and sex-standardized mortality rates against an indicator of the post- versus pre-ban period, adjusting for influenza epidemics, weekly mean temperature, and a season smooth of the standardized mortality rates in Coastal counties presumably not affected by the bans. We compared these results with similar analyses in Midlands counties also presumably unaffected by the bans. We also estimated the change in cause-specific, directly standardized, weekly hospital admissions rates normalized for underreporting in each city or county after the 1995 and 1998 bans, adjusting for influenza epidemics, weekly mean temperature, and local admissions for digestive diagnoses. Mean BS concentrations fell in all affected population centers post-ban compared with the pre-ban period, with decreases ranging from 4 to 35 microg/m3 (corresponding to reductions of 45% to 70%, respectively), but we observed no clear pattern in SO2 measured as total gaseous acidity associated with the bans. In comparisons with the pre-ban periods, no significant reduction was found in total death rates associated with the 1990 (1% reduction), 1995 (4% reduction), or 1998 (0% reduction) bans, nor for cardiovascular mortality (0%, 4%, and 1% reductions for the 1990, 1995, and 1998 bans, respectively). Respiratory mortality was reduced in association with the bans (17%, 9%, and 3%, respectively). We found a 4% decrease in hospital admissions for cardiovascular disease associated with the 1995 ban and a 3% decrease with the 1998 ban. Admissions for respiratory disease were not consistently lower after the bans; admissions for pneumonia, chronic obstructive pulmonary disease (COPD), and asthma were reduced. However, underreporting of hospital admissions data and lack of control and comparison series tempered our confidence in these results. The successive coal bans resulted in immediate and sustained decreases in particulate concentrations in each city or town; with the largest decreases in winter and during the heating season. The bans were associated with reductions in respiratory mortality but no detectable improvement in cardiovascular mortality. The changes in hospital admissions for respiratory and cardiovascular disease were supportive of these findings but cannot be considered confirming. Detecting changes in public health indicators associated even with clear improvements in air quality, as in this case, remains difficult when there are simultaneous secular improvements in the same health indicators.

Many epidemiologic studies of the health effects of exposure to ambient air pollution use measurements from central-site monitors as their exposure estimate. However, measurements from central-site monitors may lack the spatial and temporal resolution required to capture exposure variability in a study population, thus resulting in exposure error and biased estimates. Articles in this dedicated issue examine various approaches to predict or assign exposures to ambient pollutants. These methods include combining existing central-site pollution measurements with local- and/or regional-scale air quality models to create new or "hybrid" models for pollutant exposure estimates and using exposure models to account for factors such as infiltration of pollutants indoors and human activity patterns. Key findings from these articles are summarized to provide lessons learned and recommendations for additional research on improving exposure estimation approaches for future epidemiological studies. In summary, when compared with use of central-site monitoring data, the enhanced spatial resolution of air quality or exposure models can have an impact on resultant health effect estimates, especially for pollutants derived from local sources such as traffic (e.g., EC, CO, and NO(x)). In addition, the optimal exposure estimation approach also depends upon the epidemiological study design. We recommend that future research develops pollutant-specific infiltration data (including for PM species) and improves existing data on human time-activity patterns and exposure to local source (e.g., traffic), in order to enhance human exposure modeling estimates. We also recommend comparing how various approaches to exposure estimation characterize relationships between multiple pollutants in time and space and investigating the impact of improved exposure estimates in chronic health studies.

Previous studies have reported an increased risk of myocardial infarction (MI) associated with acute increases in PM concentration. Recently, we reported that MI/fine particle (PM2.5) associations may be limited to transmural infarctions. In this study, we retained data on hospital discharges with a primary diagnosis of acute myocardial infarction (using International Classification of Diseases ninth Revision [ICD-9] codes), for those admitted January 1, 2004 to December 31, 2006, who were ≥ 18 years of age, and were residents of New Jersey at the time of their MI. We excluded MI with a diagnosis of a previous MI and MI coded as a subendocardial infarction, leaving n = 1563 transmural infarctions available for analysis. We coupled these health data with PM2.5 species concentrations predicted by the Community Multiscale Air Quality chemical transport model, ambient PM2.5 concentrations, and used the same case-crossover methods to evaluate whether the relative odds of transmural MI associated with increased PM2.5 concentration is modified by the PM2.5 composition/mixture (i.e., mass fractions of sulfate, nitrate, elemental carbon, organic carbon, and ammonium). We found the largest relative odds estimates on the days with the highest tertile of sulfate mass fraction (OR = 1.13; 95% CI = 1.00, 1.27), nitrate mass fraction (OR = 1.18; 95% CI = 0.98, 1.35), and ammonium mass fraction (OR = 1.13; 95% CI = 1.00 1.28), and the lowest tertile of EC mass fraction (OR = 1.17; 95% CI = 1.03, 1.34). Air pollution mixtures on these days were enhanced in pollutants formed through atmospheric chemistry (i.e., secondary PM2.5) and depleted in primary pollutants (e.g., EC). When mixtures were laden with secondary PM species (sulfate, nitrate, and/or organics), we observed larger relative odds of myocardial infarction associated with increased PM2.5 concentrations. Further work is needed to confirm these findings and examine which secondary PM2.5 component(s) is/are responsible for an acute MI response.

Epidemiologic studies of air pollution have traditionally relied upon surrogates of personal pollutant exposures, such as ambient concentration measurements from fixed-site pollutant monitors. This study evaluates the performance of alternative measured and modeled exposure metrics for multiple particulate and gaseous pollutants, in the context of different epidemiologic studies performed by EPA, Rutgers/Rochester/LBNL and Emory/Georgia Tech researchers. Alternative exposure estimation approaches used, included: central site or interpolated monitoring data, regional pollution levels based on measurements or models (CMAQ) and local scale (AERMOD) air quality models, hybrid models, statistically blended modeling and measurement data, concentrations adjusted by home infiltration rates based on LBNL algorithms, and population human exposure (SHEDS and APEX) model predictions. The Emory/Georgia Tech team examined the acute morbidity effects of ambient traffic-related pollutants (CO, NOx, PM2.5 and PM2.5 EC) and ozone using time series analyses of emergency department (ED) visits and case-crossover analysis of implantable cardioverter defibrillator (ICD) detected ventricular arrhythmias in Atlanta, GA. The Rutgers/Rochester/LBL team examined the associations between PM2.5 mass and its species with myocardial infarction (case-crossover study) and adverse birth outcomes (cohort study) in New Jersey. Initially, the various exposure indicators/metrics were compared in terms of their ability to characterize the spatial and temporal variations of multiple ambient air pollutants across the different study areas. These metrics were then used to examine associations between ambient air pollution and adverse health effects. Next, pollutant–specific relative risks (RRs) obtained from epidemiologic analyses of the alternative exposure metrics were evaluated against those obtained from using a conventional approach (i.e., central site data alone). Pollutant and metric dependent exposure prediction differences were found in some cases, indicating a non-uniform exposure prediction error structure across pollutants. Results suggest the need for additional refinements to methods used to estimate exposures in support of different types of air pollution epidemiologic studies.

Background: A growing body of evidence has associated maternal exposure to air pollution with adverse effects on fetal growth; however, the existing literature is inconsistent. Objectives: We aimed to quantify the association between maternal exposure to particulate air pollution and term birth weight and low birth weight (LBW) across 14 centers from 9 countries, and to explore the influence of site characteristics and exposure assessment methods on between-center heterogeneity in this association. Methods: Using a common analytical protocol, International Collaboration on Air Pollution and Pregnancy Outcomes (ICAPPO) centers generated effect estimates for term LBW and continuous birth weight associated with PM10 and PM2.5 (particulate matter ≤ 10 and 2.5 µm). We used meta-analysis to combine the estimates of effect across centers (~ 3 million births) and used meta-regression to evaluate the influence of center characteristics and exposure assessment methods on between-center heterogeneity in reported effect estimates. Results: In random-effects meta-analyses, term LBW was positively associated with a 10-μg/m3 increase in PM10 [odds ratio (OR) = 1.03; 95% CI: 1.01, 1.05] and PM2.5 (OR = 1.10; 95% CI: 1.03, 1.18) exposure during the entire pregnancy, adjusted for maternal socioeconomic status. A 10-μg/m3 increase in PM10 exposure was also negatively associated with term birth weight as a continuous outcome in the fully adjusted random-effects meta-analyses (–8.9 g; 95% CI: –13.2, –4.6 g). Meta-regressions revealed that centers with higher median PM2.5 levels and PM2.5:PM10 ratios, and centers that used a temporal exposure assessment (compared with spatiotemporal), tended to report stronger associations. Conclusion: Maternal exposure to particulate pollution was associated with LBW at term across study populations. We detected three site characteristics and aspects of exposure assessment methodology that appeared to contribute to the variation in associations reported by centers.

The purpose of the present study was to examine the risk of stillbirth associated with ambient air pollution during pregnancy. Using live birth and fetal death data from New Jersey from 1998 to 2004, the authors assigned daily concentrations of air pollution to each birth or fetal death. Generalized estimating equation models were used to estimate the relative odds of stillbirth associated with interquartile range increases in mean air pollutant concentrations in the first, second, and third trimesters and throughout the entire pregnancy. The relative odds of stillbirth were significantly increased with each 10-ppb increase in mean nitrogen dioxide concentration in the first trimester (odds ratio (OR) = 1.16, 95% confidence interval (CI): 1.03, 1.31), each 3-ppb increase in mean sulfur dioxide concentration in the first (OR = 1.13, 95% CI: 1.01, 1.28) and third (OR = 1.26, 95% CI: 1.03, 1.37) trimesters, and each 0.4-ppm increase in mean carbon monoxide concentration in the second (OR = 1.14, 95% CI: 1.01, 1.28) and third (OR = 1.14, 95% CI: 1.06, 1.24) trimesters. Although ambient air pollution during pregnancy appeared to increase the relative odds of stillbirth, further studies are needed to confirm these findings and examine mechanistic explanations.

Using a case-crossover study design and conditional logistic regression, we compared the relative odds of transmural (full-wall) myocardial infarction (MI) calculated using exposure surrogates that account for human activity patterns and the indoor transport of ambient PM(2.5) with those calculated using central-site PM(2.5) concentrations to estimate exposure to PM(2.5) of outdoor origin (exposure to ambient PM(2.5)). Because variability in human activity and indoor PM(2.5) transport contributes exposure error in epidemiologic analyses when central-site concentrations are used as exposure surrogates, we refer to surrogates that account for this variability as "refined" surrogates. As an alternative analysis, we evaluated whether the relative odds of transmural MI associated with increases in ambient PM(2.5) is modified by residential air exchange rate (AER), a variable that influences the fraction of ambient PM(2.5) that penetrates and persists indoors. Use of refined exposure surrogates did not result in larger health effect estimates (ORs=1.10-1.11 with each interquartile range (IQR) increase), narrower confidence intervals, or better model fits compared with the analysis that used central-site PM(2.5). We did observe evidence for heterogeneity in the relative odds of transmural MI with residential AER (effect-modification), with residents of homes with higher AERs having larger ORs than homes in lower AER tertiles. For the level of exposure-estimate refinement considered here, our findings add support to the use of central-site PM(2.5) concentrations for epidemiological studies that use similar case-crossover study designs. In such designs, each subject serves as his or her own matched control. Thus, exposure error related to factors that vary spatially or across subjects should only minimally impact effect estimates. These findings also illustrate that variability in factors that influence the fraction of ambient PM(2.5) in indoor air (e.g., AER) could possibly bias health effect estimates in study designs for which a spatiotemporal comparison of exposure effects across subjects is conducted.