Fine particles and peak flow in children: acidity versus mass.

We assessed the impact of summertime haze episodes on twice daily peak flow measurements of children in Philadelphia, Pennsylvania. Height-adjusted peak flows were regressed on weather and air pollution concentrations. Lower morning peak flows were associated with exposure to inhalable particulate matter (-2.94 liters/minute/18 microg/m3, 95% confidence limits (CL) = -0.56, -5.33), and fine sulfate particles (-2.44 liters/minute/8 microg/m3, 95% CL = -0.36, -4.51). Particle-strong acidity and the coarse particle mass were weakly associated with lower peak flow. Acutely lower peak flows in children were associated with fine sulfate particles, but only weakly with the acidity of the fine particles.     

Residential exposure to motor vehicle emissions and the risk of wheezing among 7-8 year-old schoolchildren: a city-wide cross-sectional study in Nicosia,Cyprus

Background  

Several studies have reported associations between respiratory outcomes in children and a range of self-reported, administrative or geographical indicators of traffic pollution. First-time investigation into the frequency of asthmatic symptoms among 7-8 year-old Cypriot children in 1999-2000 showed increased prevalence in the capital Nicosia compared to other areas. Geographical differences on an island the size of Cyprus may reflect environmental and/or lifestyle factors. This study investigates the relationship between self-reported symptoms and residential exposure to motor vehicle emissions among Nicosia schoolchildren.     

Association of air pollution with increased incidence of ventricular tachyarrhythmias recorded by implanted cardioverter defibrillators

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.     

Assessing the importance of different exposure metrics and time-activity data to predict 24-H personal PM2.5 exposures

Personal PM(2.5) data from two recent exposure studies, the Scripted Activity Study and the Older Adults Study, were used to develop models predicting 24-h personal PM(2.5) exposures. Both studies were conducted concurrently in the summer of 1998 and the winter of 1999 in Baltimore, MD. In the Scripted Activity Study, 1-h personal PM(2.5) exposures were measured. Data were used to identify significant factors affecting personal exposures and to develop 1-h personal exposure models for five different micro-environments. By incorporating the time-activity diary data, these models were then combined to develop a time-weighted microenvironmental personal model (model M1AD) to predict the 24-h PM(2.5) exposures measured for individuals in the Older Adults Study. Twenty-four-hour time-weighted models were also developed using 1-h ambient PM(2.5) levels and time-activity data (model A1AD) or using 24-h ambient PM(2.5) levels and time-activity data (model A24AD). The performance of these three models was compared to that using 24-h ambient concentrations alone (model A24). Results showed that factors affecting 1-h personal PM(2.5) exposures included air conditioning status and the presence of environmental tobacco smoke (ETS) for indoor micro-environments, consistent with previous studies. ETS was identified as a significant contributor to measured 24-h personal PM(2.5) exposures. Staying in an ETS-exposed microenvironment for 1 h elevated 24-h personal PM(2.5) exposures by approximately 4 microg/m 3 on average. Cooking and washing activities were identified in the winter as significant contributors to 24-h personal exposures as well, increasing 24-h personal PM(2.5) exposures by about 4 and 5 microg/m 3 per hour of activity, respectively. The ability of 3 microenvironmental personal exposure models to estimate 24-h personal PM(2.5) exposures was generally comparable to and consistently greater than that of model A24. Results indicated that using time-activity data with 1-h exposure information, either as micro-environment-specific exposures (model M1AD) or as ambient concentrations (model A1AD), improves our ability to estimate 24-h personal PM(2.5) exposure over the model using 24-h averaged ambient levels alone (model A24). Model performance was higher in the summer than in the winter season. In addition, higher crude R(2) values were reported for subjects participating in both seasons, where the R(2) values equaled.53,.55,.46, and.38 for models M1AD, A1AD, A24AD, and A24, respectively. The low predictive ability of the microenvironmental exposure models in the winter might, in part, be attributed to the narrow dynamic range of personal PM(2.5) exposures.     

Sources of Fine Particulate Matter and Risk of Preterm Birth in Connecticut, 2000–2006: A Longitudinal Study

Background: Previous studies have examined fine particulate matter (≤ 2.5 μm; PM_2.5) 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 PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 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     

Use of the Adaptive LASSO Method to Identify PM2.5 Components Associated with Blood Pressure in Elderly Men: The Veterans Affairs Normative Aging Study

Background

PM_2.5 (particulate matter ≤ 2.5 μm) has been associated with adverse cardiovascular outcomes, but it is unclear whether specific PM_2.5 components, particularly metals, may be responsible for cardiovascular effects.

Objectives

We aimed to determine which PM_2.5 components are associated with blood pressure in a longitudinal cohort.

Methods

We fit linear mixed-effects models with the adaptive LASSO penalty to longitudinal data from 718 elderly men in the Veterans Affairs Normative Aging Study, 1999–2010. We controlled for PM_2.5 mass, age, body mass index, use of antihypertensive medication (ACE inhibitors, non-ophthalmic beta blockers, calcium channel blockers, diuretics, and angiotensin receptor antagonists), smoking status, alcohol intake, years of education, temperature, and season as fixed effects in the models, and additionally applied the adaptive LASSO method to select PM_2.5 components associated with blood pressure. Final models were identified by the Bayesian Information Criterion (BIC).

Results

For systolic blood pressure (SBP), nickel (Ni) and sodium (Na) were selected by the adaptive LASSO, whereas only Ni was selected for diastolic blood pressure (DBP). An interquartile range increase (2.5 ng/m³) in 7-day moving-average Ni was associated with 2.48-mmHg (95% CI: 1.45, 3.50 mmHg) increase in SBP and 2.22-mmHg (95% CI: 1.69, 2.75 mmHg) increase in DBP, respectively. Associations were comparable when the analysis was restricted to study visits with PM_2.5 below the 75th percentile of the distribution (12 μg/m³).

Conclusions

Our study suggested that exposure to ambient Ni was associated with increased blood pressure independent of PM_2.5 mass in our study population of elderly men. Further research is needed to confirm our findings, assess generalizability to other populations, and identify potential mechanisms for Ni effects.

Citation

Dai L, Koutrakis P, Coull BA, Sparrow D, Vokonas PS, Schwartz JD. 2016. Use of the adaptive LASSO method to identify PM_2.5 components associated with blood pressure in elderly men: the Veterans Affairs Normative Aging Study. Environ Health Perspect 124:120–125; http://dx.doi.org/10.1289/ehp.1409021