Ambient air pollution and the risk of acute ischemic stroke

BACKGROUND

The link between daily changes in level of ambient fine particulate matter (PM) air pollution (PM <2.5 μm in diameter [PM(2.5)]) and cardiovascular morbidity and mortality is well established. Whether PM(2.5) levels below current US National Ambient Air Quality Standards also increase the risk of ischemic stroke remains uncertain.

METHODS

We reviewed the medical records of 1705 Boston area patients hospitalized with neurologist-confirmed ischemic stroke and abstracted data on the time of symptom onset and clinical characteristics. The PM(2.5) concentrations were measured at a central monitoring station. We used the time-stratified case-crossover study design to assess the association between the risk of ischemic stroke onset and PM(2.5) levels in the hours and days preceding each event. We examined whether the association with PM(2.5) levels differed by presumed ischemic stroke pathophysiologic mechanism and patient characteristics.

RESULTS

The estimated odds ratio (OR) of ischemic stroke onset was 1.34 (95% CI, 1.13-1.58) (P < .001) following a 24-hour period classified as moderate (PM(2.5) 15-40 μg/m(3)) by the US Environmental Protection Agency's (EPA) Air Quality Index compared with a 24-hour period classified as good (≤15 μg/m(3)). Considering PM(2.5) levels as a continuous variable, we found the estimated odds ratio of ischemic stroke onset to be 1.11 (95% CI, 1.03-1.20) (P = .006) per interquartile range increase in PM(2.5) levels (6.4 μg/m(3)). The increase in risk was greatest within 12 to 14 hours of exposure to PM(2.5) and was most strongly associated with markers of traffic-related pollution.

CONCLUSION

These results suggest that exposure to PM(2.5) levels considered generally safe by the US EPA increase the risk of ischemic stroke onset within hours of exposure.

Opposing effects of particle pollution, ozone, and ambient temperature on arterial blood pressure

BACKGROUND

Diabetes increases the risk of hypertension and orthostatic hypotension and raises the risk of cardiovascular death during heat waves and high pollution episodes.

OBJECTIVE

We examined whether short-term exposures to air pollution (fine particles, ozone) and heat resulted in perturbation of arterial blood pressure (BP) in persons with type 2 diabetes mellitus (T2DM).

METHODS

We conducted a panel study in 70 subjects with T2DM, measuring BP by automated oscillometric sphygmomanometer and pulse wave analysis every 2 weeks on up to five occasions (355 repeated measures). Hourly central site measurements of fine particles, ozone, and meteorology were conducted. We applied linear mixed models with random participant intercepts to investigate the association of fine particles, ozone, and ambient temperature with systolic, diastolic, and mean arterial BP in a multipollutant model, controlling for season, meteorological variables, and subject characteristics.

RESULTS

An interquartile increase in ambient fine particle mass [particulate matter (PM) with an aerodynamic diameter of ≤ 2.5 μm (PM2.5)] and in the traffic component black carbon in the previous 5 days (3.54 and 0.25 μg/m3, respectively) predicted increases of 1.4 mmHg [95% confidence interval (CI): 0.0, 2.9 mmHg] and 2.2 mmHg (95% CI: 0.4, 4.0 mmHg) in systolic BP (SBP) at the population geometric mean, respectively. In contrast, an interquartile increase in the 5-day mean of ozone (13.3 ppb) was associated with a 5.2 mmHg (95% CI: -8.6, -1.8 mmHg) decrease in SBP. Higher temperatures were associated with a marginal decrease in BP.

CONCLUSIONS

In subjects with T2DM, PM was associated with increased BP, and ozone was associated with decreased BP. These effects may be clinically important in patients with already compromised autoregulatory function.

Ambient particulate matter and the response to orthostatic challenge in the elderly: the Maintenance of Balance, Independent Living, Intellect, and Zest in the Elderly (MOBILIZE) of Boston study

Short-term elevations in ambient fine particulate matter (PM(2.5)) may increase resting systolic (SBP) and diastolic (DBP) blood pressures, but whether PM(2.5) alters hemodynamic responses to orthostatic challenge has not been studied in detail. We repeatedly measured SBP and DBP during supine rest and 1 and 3 minutes after standing among 747 elderly (aged 78.3±5.3 years, mean±SD) participants from a prospective cohort study. We used linear mixed models to assess the association between change in SBP (ΔSBP=standing SBP-supine SBP) and DBP (ΔDBP) on standing and mean PM(2.5) levels over the preceding 1 to 28 days, adjusting for meteorologic covariates, temporal trends, and medical history. We observed a 1.4-mm Hg (95% CI: 0.0-2.8 mm Hg; P=0.046) higher ΔSBP and a 0.7-mm Hg (95% CI: 0.0-1.4 mm Hg; P=0.053) higher ΔDBP at 1 minute of standing per interquartile range increase (3.8 μg/m(3)) in mean PM(2.5) levels in the past 7 days. ΔSBP and ΔDBP measured 3 minutes after standing were not associated with PM(2.5). Resting DBP (but not SBP or pulse pressure) was positively associated with PM(2.5) at longer averaging periods. Responses were more strongly associated with black carbon than sulfate levels. These associations did not differ significantly according to hypertension status, obesity, diabetes mellitus, or sex. These results suggest that ambient particles can increase resting DBP and exaggerate blood pressure responses to postural changes in elderly people. Increased vasoreactivity during posture change may be responsible, in part, for the adverse effect of ambient particles on cardiovascular health.

Chemical properties of air pollutants and cause-specific hospital admissions among the elderly in Atlanta, Georgia

BACKGROUND

Health risks differ by fine particle (aerodynamic diameter ≤ 2.5 μm) component, although with substantial variability. Traditional methods to assess component-specific risks are limited, suggesting the need for alternative methods.

OBJECTIVES

We examined whether the odds of daily hospital admissions differ by pollutant chemical properties.

METHODS

We categorized pollutants by chemical properties and examined their impacts on the odds of daily hospital admissions among Medicare recipients > 64 years of age in counties in Atlanta, Georgia, for 1998-2006. We analyzed data in two stages. In the first stage we applied a case-crossover analysis to simultaneously estimate effects of 65 pollutants measured in the Aerosol Research and Inhalation Epidemiology Study on cause-specific hospital admissions, controlling for temperature and ozone. In the second stage, we regressed pollutant-specific slopes from the first stage on pollutant properties. We calculated uncertainty estimates using a bootstrap procedure. We repeated the two-stage analyses using coefficients from first-stage models that included single pollutants plus ozone and meteorological variables only. We based our primary analyses on exposures on day of admission.

RESULTS

We found that 24-hr transition metals and alkanes were associated with increased odds [0.26%; 95% confidence interval (CI), 0.02-0.48; and 0.37%; 95% CI, 0.04-0.72, respectively] of hospital admissions for cardiovascular disease (CVD). Transition metals were significantly associated with increased hospital admissions for ischemic heart disease, congestive heart failure, and atrial fibrillation. Increased respiratory-related hospital admissions were significantly associated with alkanes. Aromatics and microcrystalline oxides were significantly associated with decreased CVD- and respiratory-related hospital admissions.

CONCLUSIONS

The two-stage approach showed transition metals to be consistently associated with increased odds of CVD-related hospital admissions.

Particulate air pollution and socioeconomic position in rural and urban areas of the Northeastern United States

OBJECTIVES

Although differential exposure by socioeconomic position (SEP) to hazardous waste and lead is well demonstrated, there is less evidence for particulate air pollution (PM), which is associated with risk of death and illness. This study determined the relationship of ambient PM and SEP across several spatial scales.

METHODS

Geographic information system-based, spatio-temporal models were used to predict PM in the Northeastern United States. Predicted concentrations were related to census tract SEP and racial composition using generalized additive models.

RESULTS

Lower SEP was associated with small, significant increases in PM. Annual PM(10) decreased between 0.09 and 0.93 micrograms per cubic meter and PM(2.5) between 0.02 and 0.94 micrograms per cubic meter for interquartile range increases in income. Decrements in PM with SEP increased with spatial scale, indicating that between-city spatial gradients were greater than within-city differences. The PM-SEP relation in urban tracts was not substantially modified by racial composition.

CONCLUSIONS

Lower compared with higher SEP populations were exposed to higher ambient PM in the Northeastern United States. Given the small percentage change in annual PM(2.5) and PM(10), SEP was not likely a major source of confounding in epidemiological studies of PM, especially those conducted within a single urban/metropolitan area.

Hourly measurements of fine particulate sulfate and carbon aerosols at the Harvard-U.S. Environmental Protection Agency Supersite in Boston

Hourly concentrations of ambient fine particle sulfate and carbonaceous aerosols (elemental carbon [EC], organic carbon [OC], and black carbon [BC]) were measured at the Harvard-U.S. Environmental Protection Agency Supersite in Boston, MA, between January 2007 and October 2008. These hourly concentrations were compared with those made using integrated filter-based measurements over 6-day or 24-hr periods. For sulfate, the two measurement methods showed good agreement. Semicontinuous measurements of EC and OC also agreed (but not as well as for sulfate) with those obtained using 24-hr integrated filter-based and optical BC reference methods. During the study period, 24-hr PM2.5 (particulate matter [PM] < or = 2.5 microm in aerodynamic diameter) concentrations ranged from 1.4 to 37.6 microg/m3, with an average of 9.3 microg/m3. Sulfate as the equivalent of ammonium sulfate accounted for 39.1% of the PM2.5 mass, whereas EC and OC accounted for 4.2 and 35.2%, respectively. Hourly sulfate concentrations showed no distinct diurnal pattern, whereas hourly EC and BC concentrations peaked during the morning rush hour between 7:00 and 9:00 a.m. OC concentrations also exhibited nonpronounced, small peaks during the day, most likely related to traffic, secondary organic aerosol, and local sources, respectively.

Systemic inflammation, heart rate variability and air pollution in a cohort of senior adults

OBJECTIVES

Short-term elevation of ambient particulate air pollution has been associated with autonomic dysfunction and increased systemic inflammation, but the interconnections between these pathways are not well understood. We examined the association between inflammation and autonomic dysfunction and effect modification of inflammation on the association between air pollution and heart rate variability (HRV) in elderly subjects.

METHODS

25 elderly subjects in Steubenville, Ohio, were followed up to 24 times with repeated 30-min ECG Holter monitoring (545 observations). C-reactive protein (CRP), fibrinogen, interleukin-6 (IL-6), soluble inter-cellular adhesion molecule 1 (sICAM-1), and white blood cell and platelet counts were measured in peripheral blood samples collected in the first month of the study. Increased systemic inflammation was defined for subjects within the upper 20% of the distribution for each marker. A central ambient monitoring station provided daily fine particle (PM(2.5)) and sulphate (SO(4)(2-)) data. Linear mixed models were used to identify associations between inflammatory markers and HRV and to assess effect modification of the association between air pollution and HRV due to inflammatory status.

RESULTS

A 5.8 mg/l elevation in CRP was associated with decreases of between -8% and -33% for time and frequency domain HRV outcomes. A 5.1 microg/m(3) increase in SO(4)(2-) on the day before the health assessment was associated with a decrease of -6.7% in the SD of normal RR intervals (SDNN) (95% CI -11.8% to -1.3%) in subjects with elevated CRP, but not in subjects with lower CRP (p value interaction=0.04), with similar findings for PM(2.5).

CONCLUSIONS

Increased systemic inflammation is associated with autonomic dysfunction in the elderly. Air pollution effects on reduced SDNN are stronger in subjects with elevated systemic inflammation.

Traffic-related air pollution and QT interval: modification by diabetes, obesity, and oxidative stress gene polymorphisms in the normative aging study

BACKGROUND

Acute exposure to ambient air pollution has been associated with acute changes in cardiac outcomes, often within hours of exposure.

OBJECTIVES

We examined the effects of air pollutants on heart-rate-corrected QT interval (QTc), an electrocardiographic marker of ventricular repolarization, and whether these associations were modified by participant characteristics and genetic polymorphisms related to oxidative stress.

METHODS

We studied repeated measurements of QTc on 580 men from the Veterans Affairs Normative Aging Study (NAS) using mixed-effects models with random intercepts. We fitted a quadratic constrained distributed lag model to estimate the cumulative effect on QTc of ambient air pollutants including fine particulate matter <or= 2.5 microm in aerodynamic diameter (PM2.5), ozone (O3), black carbon (BC), nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2) concentrations during the 10 hr before the visit. We genotyped polymorphisms related to oxidative stress and analyzed pollution-susceptibility score interactions using the genetic susceptibility score (GSS) method.

RESULTS

Ambient traffic pollutant concentrations were related to longer QTc. An interquartile range (IQR) change in BC cumulative during the 10 hr before the visit was associated with increased QTc [1.89 msec change; 95% confidence interval (CI), -0.16 to 3.93]. We found a similar association with QTc for an IQR change in 1-hr BC that occurred 4 hr before the visit (2.54 msec change; 95% CI, 0.28-4.80). We found increased QTc for IQR changes in NO2 and CO, but the change was statistically insignificant. In contrast, we found no association between QTc and PM2.5, SO2, and O3. The association between QTc and BC was stronger among participants who were obese, who had diabetes, who were nonsmokers, or who had higher GSSs.

CONCLUSIONS

Traffic-related pollutants may increase QTc among persons with diabetes, persons who are obese, and nonsmoking elderly individuals; the number of genetic variants related to oxidative stress increases this effect.

Reduction in heart rate variability with traffic and air pollution in patients with coronary artery disease

INTRODUCTION

Ambient particulate pollution and traffic have been linked to myocardial infarction and cardiac death risk. Possible mechanisms include autonomic cardiac dysfunction.

METHODS

In a repeated-measures study of 46 patients 43-75 years of age, we investigated associations of central-site ambient particulate pollution, including black carbon (BC) (a marker for regional and local traffic), and report of traffic exposure with changes in half-hourly averaged heart rate variability (HRV), a marker of autonomic function measured by 24-hr Holter electrocardiogram monitoring. Each patient was observed up to four times within 1 year after a percutaneous intervention for myocardial infarction, acute coronary syndrome without infarction, or stable coronary artery disease (4,955 half-hour observations). For each half-hour period, diary data defined whether the patient was home or not home, or in traffic.

RESULTS

A decrease in high frequency (HF; an HRV marker of vagal tone) of 16.4% [95% confidence interval (CI), 20.7 to 11.8%] was associated with an interquartile range of 0.3-microg/m3 increase in prior 5-day averaged ambient BC. Decreases in HF were independently associated both with the previous 2-hr averaged BC (10.4%; 95% CI, 15.4 to 5.2%) and with being in traffic in the previous 2 hr (38.5%; 95% CI, 57.4 to 11.1%). We also observed independent responses for particulate air matter with aerodynamic diameter < or = 2.5 microm and for gases (ozone or nitrogen dioxide).

CONCLUSION

After hospitalization for coronary artery disease, both particulate pollution and being in traffic, a marker of stress and pollution, were associated with decreased HRV.

Effects of exposure measurement error in the analysis of health effects from traffic-related air pollution

In large epidemiological studies, many researchers use surrogates of air pollution exposure such as geographic information system (GIS)-based characterizations of traffic or simple housing characteristics. It is important to evaluate quantitatively these surrogates against measured pollutant concentrations to determine how their use affects the interpretation of epidemiological study results. In this study, we quantified the implications of using exposure models derived from validation studies, and other alternative surrogate models with varying amounts of measurement error on epidemiological study findings. We compared previously developed multiple regression models characterizing residential indoor nitrogen dioxide (NO(2)), fine particulate matter (PM(2.5)), and elemental carbon (EC) concentrations to models with less explanatory power that may be applied in the absence of validation studies. We constructed a hypothetical epidemiological study, under a range of odds ratios, and determined the bias and uncertainty caused by the use of various exposure models predicting residential indoor exposure levels. Our simulations illustrated that exposure models with fairly modest R(2) (0.3 to 0.4 for the previously developed multiple regression models for PM(2.5) and NO(2)) yielded substantial improvements in epidemiological study performance, relative to the application of regression models created in the absence of validation studies or poorer-performing validation study models (e.g., EC). In many studies, models based on validation data may not be possible, so it may be necessary to use a surrogate model with more measurement error. This analysis provides a technique to quantify the implications of applying various exposure models with different degrees of measurement error in epidemiological research.

The relationship between averaged sulfate exposures and concentrations: results from exposure assessment panel studies in four U.S. cities

This analysis examines differences between measured ambient indoor, and personal sulfate concentrations across cities, seasons, and individuals to elucidate how these differences may impact PM2.5 exposure measurement error. Data were analyzed from four panel studies conducted in Atlanta, Baltimore, Boston, and Steubenville (OH). Among the study locations, 1912 person-days of personal sulfate data were collected over 396 days involving 245 individual sampling sessions. Long-term differences in ambient and personal levels averaged over time are examined. Differences between averaged ambient and personal sulfate among and within cities were observed, driven by between subject and city differences in sulfate infiltration, F(inf), from outdoors to indoors. Neglecting this source of variability in associations may introduce bias in studies examining long-term exposures and chronic health. Indoor sulfate was highly correlated with and similar in magnitude to personal sulfate, suggesting indoor PM monitoring may be another means of characterizing true exposure variability.

Factors influencing relationships between personal and ambient concentrations of gaseous and particulate pollutants

Previous exposure studies have shown considerable inter-subject variability in personal-ambient associations. This paper investigates exposure factors that may be responsible for inter-subject variability in these personal-ambient associations. The personal and ambient data used in this paper were collected as part of a personal exposure study conducted in Boston, MA, during 1999-2000. This study was one of a group of personal exposure panel studies funded by the U.S. Environmental Protection Agency's National Exposure Research Laboratory to address areas of exposure assessment warranting further study, particularly associations between personal exposures and ambient concentrations of particulate matter and gaseous co-pollutants. Twenty-four-hour integrated personal, home indoor, home outdoor and ambient sulfate, elemental carbon (EC), PM(2.5), ozone (O(3)), nitrogen dioxide (NO(2)) and sulfur dioxide were measured simultaneously each day. Fifteen homes in the Boston area were measured for 7 days during winter and summer. A previous paper explored the associations between personal-indoor, personal-outdoor, personal-ambient, indoor-outdoor, indoor-ambient and outdoor-ambient PM(2.5), sulfate and EC concentrations. For the current paper, factors that may affect personal exposures were investigated, while controlling for ambient concentrations. The data were analyzed using mixed effects regression models. Overall personal-ambient associations were strong for sulfate during winter (p<0.0001) and summer (p<0.0001) and PM(2.5) during summer (p<0.0001). The personal-ambient mixed model slope for PM(2.5) during winter but was not significant at p=0.10. Personal exposures to most pollutants, with the exception of NO(2), increased with ventilation and time spent outdoors. An opposite pattern was found for NO(2) likely due to gas stoves. Personal exposures to PM(2.5) and to traffic-related pollutants, EC and NO(2), were higher for those individuals living close to a major road. Both personal and indoor sulfate and PM(2.5) concentrations were higher for homes using humidifiers. The impact of outdoor sources on personal and indoor concentrations increased with ventilation, whereas an opposite effect was observed for the impact of indoor sources.

Rapid DNA methylation changes after exposure to traffic particles

RATIONALE

Exposure to particulate air pollution has been related to increased hospitalization and death, particularly from cardiovascular disease. Lower blood DNA methylation content is found in processes related to cardiovascular outcomes, such as oxidative stress, aging, and atherosclerosis.

OBJECTIVES

We evaluated whether particulate pollution modifies DNA methylation in heavily methylated sequences with high representation throughout the human genome.

METHODS

We measured DNA methylation of long interspersed nucleotide element (LINE)-1 and Alu repetitive elements by quantitative polymerase chain reaction-pyrosequencing of 1,097 blood samples from 718 elderly participants in the Boston area Normative Aging Study. We used covariate-adjusted mixed models to account for within-subject correlation in repeated measures. We estimated the effects on DNA methylation of ambient particulate pollutants (black carbon, particulate matter with aerodynamic diameter < or = 2.5 microm [PM2.5], or sulfate) in multiple time windows (4 h to 7 d) before the examination. We estimated standardized regression coefficients (beta) expressing the fraction of a standard deviation change in DNA methylation associated with a standard deviation increase in exposure.

MEASUREMENTS AND MAIN RESULTS

Repetitive element DNA methylation varied in association with time-related variables, such as day of the week and season. LINE-1 methylation decreased after recent exposure to higher black carbon (beta = -0.11; 95% confidence interval [CI], -0.18 to -0.04; P = 0.002) and PM2.5 (beta = -0.13; 95% CI, -0.19 to -0.06; P < 0.001 for the 7-d moving average). In two-pollutant models, only black carbon, a tracer of traffic particles, was significantly associated with LINE-1 methylation (beta = -0.09; 95% CI, -0.17 to -0.01; P = 0.03). No association was found with Alu methylation (P > 0.12).

CONCLUSIONS

We found decreased repeated-element methylation after exposure to traffic particles. Whether decreased methylation mediates exposure-related health effects remains to be determined.

Predicting chronic fine and coarse particulate exposures using spatiotemporal models for the Northeastern and Midwestern United States

BACKGROUND

Chronic epidemiologic studies of particulate matter (PM) are limited by the lack of monitoring data, relying instead on citywide ambient concentrations to estimate exposures. This method ignores within-city spatial gradients and restricts studies to areas with nearby monitoring data. This lack of data is particularly restrictive for fine particles (PM with aerodynamic diameter < 2.5 microm; PM(2.5)) and coarse particles (PM with aerodynamic diameter 2.5-10 microm; PM(10-2.5)), for which monitoring is limited before 1999. To address these limitations, we developed spatiotemporal models to predict monthly outdoor PM(2.5) and PM(10-2.5) concentrations for the northeastern and midwestern United States.

METHODS

For PM(2.5), we developed models for two periods: 1988-1998 and 1999-2002. Both models included smooth spatial and regression terms of geographic information system-based and meteorologic predictors. To compensate for sparse monitoring data, the pre-1999 model also included predicted PM(10) (PM with aerodynamic diameter < 10 microm) and extinction coefficients (km(-1)). PM(10-2.5) levels were estimated as the difference in monthly predicted PM(10) and PM(2.5), with predicted PM(10) from our previously developed PM(10) model.

RESULTS

Predictive performance for PM(2.5) was strong (cross-validation R2 = 0.77 and 0.69 for post-1999 and pre-1999 PM(2.5) models, respectively) with high precision (2.2 and 2.7 microg/m3, respectively). Models performed well irrespective of population density and season. Predictive performance for PM(10-2.5) was weaker (cross-validation R2 = 0.39) with lower precision (5.5 microg/m3). PM(10-2.5) levels exhibited greater local spatial variability than PM(10) or PM(2.5), suggesting that PM(2.5) measurements at ambient monitoring sites are more representative for surrounding populations than for PM(10) and especially PM(10-2.5).

CONCLUSIONS

We provide semiempirical models to predict spatially and temporally resolved long-term average outdoor concentrations of PM(2.5) and PM(10-2.5) for estimating exposures of populations living in the northeastern and midwestern United States.

Weather and air pollution as triggers of severe headaches

BACKGROUND

The roles of weather conditions and air pollution as triggers of headache have been inconsistent in previous, generally small studies.

METHODS

We performed a case-crossover study of 7,054 patients seen in a single emergency department between May 2000 and December 2007 with a primary discharge diagnosis of headache. We compared levels of temperature, barometric pressure, humidity, fine particulate matter, black carbon, and nitrogen and sulfur dioxides during the three 24-hour periods preceding presentation with corresponding levels on the remaining occurrences of that day of the week in a given month, using local meteorologic and pollutant monitors.

RESULTS

Higher mean ambient temperature in the 24 hours preceding hospital presentation positively and linearly increased the acute risk of headache (odds ratio [OR] for a 5 degrees C increment 1.075; 95% confidence interval [CI], 1.021-1.133; p = 0.006) [corrected]. Higher risk was observed for cases with and without a discharge diagnosis of migraine and for cases between October and March or between April and September. Lower barometric pressure also increased the risk of nonmigraine cases in the 48 to 72 hours before hospitalization (OR 0.939 per 5 mm Hg; 95% CI, 0.902-0.978; p = 0.002). Current levels of pollutants did not influence the risk of headache.

CONCLUSIONS

Higher ambient temperature and, to a lesser degree, lower barometric pressure led to a transient increase in risk of headache requiring emergency department evaluation. We did not find clear association of air pollutants with risk, but cannot exclude effects of air pollution of the magnitude previously observed for stroke and other cardiovascular events.

Rapid DNA methylation changes after exposure to traffic particles

RATIONALE

Exposure to particulate air pollution has been related to increased hospitalization and death, particularly from cardiovascular disease. Lower blood DNA methylation content is found in processes related to cardiovascular outcomes, such as oxidative stress, aging, and atherosclerosis.

OBJECTIVES

We evaluated whether particulate pollution modifies DNA methylation in heavily methylated sequences with high representation throughout the human genome.

METHODS

We measured DNA methylation of long interspersed nucleotide element (LINE)-1 and Alu repetitive elements by quantitative polymerase chain reaction-pyrosequencing of 1,097 blood samples from 718 elderly participants in the Boston area Normative Aging Study. We used covariate-adjusted mixed models to account for within-subject correlation in repeated measures. We estimated the effects on DNA methylation of ambient particulate pollutants (black carbon, particulate matter with aerodynamic diameter < or = 2.5 microm [PM2.5], or sulfate) in multiple time windows (4 h to 7 d) before the examination. We estimated standardized regression coefficients (beta) expressing the fraction of a standard deviation change in DNA methylation associated with a standard deviation increase in exposure.

MEASUREMENTS AND MAIN RESULTS

Repetitive element DNA methylation varied in association with time-related variables, such as day of the week and season. LINE-1 methylation decreased after recent exposure to higher black carbon (beta = -0.11; 95% confidence interval [CI], -0.18 to -0.04; P = 0.002) and PM2.5 (beta = -0.13; 95% CI, -0.19 to -0.06; P < 0.001 for the 7-d moving average). In two-pollutant models, only black carbon, a tracer of traffic particles, was significantly associated with LINE-1 methylation (beta = -0.09; 95% CI, -0.17 to -0.01; P = 0.03). No association was found with Alu methylation (P > 0.12).

CONCLUSIONS

We found decreased repeated-element methylation after exposure to traffic particles. Whether decreased methylation mediates exposure-related health effects remains to be determined.

Whole house particle removal and clean air delivery rates for in-duct and portable ventilation systems

A novel method for determining whole house particle removal and clean air delivery rates attributable to central and portable ventilation/air cleaning systems is described. The method is used to characterize total and air-cleaner-specific particle removal rates during operation of four in-duct air cleaners and two portable air-cleaning devices in a fully instrumented test home. Operation of in-duct and portable air cleaners typically increased particle removal rates over the baseline rates determined in the absence of operating a central fan or an indoor air cleaner. Removal rates of 0.3- to 0.5-microm particles ranged from 1.5 hr(-1) during operation of an in-duct, 5-in. pleated media filter to 7.2 hr(-1) for an in-duct electrostatic air cleaner in comparison to a baseline rate of 0 hr(-1) when the air handler was operating without a filter. Removal rates for total particulate matter less than 2.5 microm in aerodynamic diameter (PM2.5) mass concentrations were 0.5 hr(-1) under baseline conditions, 0.5 hr(-1) during operation of three portable ionic air cleaners, 1 hr(-1) for an in-duct 1-in. media filter, 2.4 hr(-1) for a single high-efficiency particle arrestance (HEPA) portable air cleaner, 4.6 hr(-1) for an in-duct 5-in. media filter, 4.7 hr(-1) during operation of five portable HEPA filters, 6.1 hr(-1) for a conventional in-duct electronic air cleaner, and 7.5 hr(-1) for a high efficiency in-duct electrostatic air cleaner. Corresponding whole house clean air delivery rates for PM2.5 attributable to the air cleaner independent of losses within the central ventilation system ranged from 2 m3/min for the conventional media filter to 32 m3/min for the high efficiency in-duct electrostatic device. Except for the portable ionic air cleaner, the devices considered here increased particle removal indoors over baseline deposition rates.

Ambient site, home outdoor and home indoor particulate concentrations as proxies of personal exposures

Despite strong longitudinal associations between particle personal exposures and ambient concentrations, previous studies have found considerable inter-personal variability in these associations. Factors contributing to this inter-personal variability are important to identify in order to improve our ability to assess particulate exposures for individuals. This paper examines whether ambient, home outdoor and home indoor particle concentrations can be used as proxies of corresponding personal exposures. We explore the strength of the associations between personal, home indoor, home outdoor and central outdoor monitoring site ("ambient site") concentrations of sulfate, fine particle mass (PM(2.5)) and elemental carbon (EC) by season and subject for 25 individuals living in the Boston, MA, USA area. Ambient sulfate concentrations accounted for approximately 70 to 80% of the variability in personal and indoor sulfate levels. Correlations between ambient and personal sulfate, however, varied by subject (0.1-1.0), with associations between personal and outdoor sulfate concentrations generally mirroring personal-ambient associations (median subject-specific correlations of 0.8 to 0.9). Ambient sulfate concentrations are good indicators of personal exposures for individuals living in the Boston area, even though their levels may differ from actual personal exposures. The strong associations for sulfate indicate that ambient concentrations and housing characteristics are the driving factors determining personal sulfate exposures. Ambient PM(2.5) and EC concentrations were more weakly associated with corresponding personal and indoor levels, as compared to sulfate. For EC and PM(2.5), local traffic, indoor sources and/or personal activities can significantly weaken associations with ambient concentrations. Infiltration was shown to impact the ability of ambient concentrations to reflect exposures with higher exposures to particles from ambient sources during summer. In contrast in the winter, lower infiltration can result in a greater contribution of indoor sources to PM(2.5) and EC exposures. Placing EC monitors closer to participants' homes may reduce exposure error in epidemiological studies of traffic-related particles, but this reduction in exposure error may be greater in winter than summer. It should be noted that approximately 20% of the EC data were below the field limit of detection, making it difficult to determine if the weaker associations with the central site for EC were merely a result of methodological limitations.

Spatio-temporal modeling of chronic PM10 exposure for the Nurses' Health Study

Chronic epidemiological studies of airborne particulate matter (PM) have typically characterized the chronic PM exposures of their study populations using city- or countywide ambient concentrations, which limit the studies to areas where nearby monitoring data are available and which ignore within-city spatial gradients in ambient PM concentrations. To provide more spatially refined and precise chronic exposure measures, we used a Geographic Information System (GIS)-based spatial smoothing model to predict monthly outdoor PM(10) concentrations in the northeastern and midwestern United States. This model included monthly smooth spatial terms and smooth regression terms of GIS-derived and meteorological predictors. Using cross-validation and other pre-specified selection criteria, terms for distance to road by road class, urban land use, block group and county population density, point- and area-source PM(10) emissions, elevation, wind speed, and precipitation were found to be important determinants of PM(10) concentrations and were included in the final model. Final model performance was strong (cross-validation R(2)=0.62), with little bias (-0.4 mug m(-3)) and high precision (6.4 mug m(-3)). The final model (with monthly spatial terms) performed better than a model with seasonal spatial terms (cross-validation R(2)=0.54). The addition of GIS-derived and meteorological predictors improved predictive performance over spatial smoothing (cross-validation R(2)=0.51) or inverse distance weighted interpolation (cross-validation R(2)=0.29) methods alone and increased the spatial resolution of predictions. The model performed well in both rural and urban areas, across seasons, and across the entire time period. The strong model performance demonstrates its suitability as a means to estimate individual-specific chronic PM(10) exposures for large populations.

Associations between measures of socioeconomic position and chronic nitrogen dioxide exposure in Worcester, Massachusetts

Census block-group-specific predicted outdoor nitrogen dioxide (NO(2); a marker of traffic pollution) levels and four census block group socioeconomic position (SEP) measures were used to evaluate whether chronic exposures to traffic-related air pollutants are higher in areas with lower SEP, after controlling for spatial autocorrelation in mixed models. NO(2) levels were predicted using a geographic information system (GIS)-based spatiotemporal model that was validated with measured NO(2) concentrations. The GIS-based model predicted weekly NO(2) concentrations with high accuracy (slope of 0.98 from regression of held-out observations on predictions) and precision (cross-validation mean absolute error of 2.2 ppb). The model performed well in both rural and urban areas and warm and cold seasons. Estimated mean block group NO(2) concentrations were significantly negatively associated with median household income, and positively associated with poverty, crowding, and low educational attainment rates after controlling for spatial autocorrelation. Results indicated that a standard deviation (3.5 ppb) increase in block group NO(2) concentrations was associated with a $9090 decrease in median household income. Results suggest that on average those with lower SEP experience higher chronic exposure to outdoor NO(2).

Effects of ambient air pollution on functional status in patients with chronic congestive heart failure: a repeated-measures study

BACKGROUND

Studies using administrative data report a positive association between ambient air pollution and the risk of hospitalization for congestive heart failure (HF). Circulating levels of B-type natriuretic peptide (BNP) are directly associated with cardiac hemodynamics and symptom severity in patients with HF and, therefore, serves as a marker of functional status. We tested the hypothesis that BNP levels would be positively associated with short-term changes in ambient pollution levels among 28 patients with chronic stable HF and impaired systolic function.

METHODS

BNP was measured in whole blood at 0, 6, and 12 weeks. We used linear mixed models to evaluate the association between fine particulate matter (PM2.5), carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and black carbon and log(BNP). Lags of 0 to 3 days were considered in separate models. We calculated the intraclass correlation coefficient and within-subject coefficient of variation as measures of reproducibility.

RESULTS

We found no association between any pollutant and measures of BNP at any lag. For example, a 10 microg/m3 increase in PM2.5 was associated with a 0.8% (95% CI: -16.4, 21.5; p = 0.94) increase in BNP on the same day. The within-subject coefficient of variation was 45% on the natural scale and 9% on the log scale.

CONCLUSION

These results suggest that serial BNP measurements are unlikely to be useful in a longitudinal study of air pollution-related acute health effects. The magnitude of expected ambient air pollution health effects appears small in relation to the considerable within-person variability in BNP levels in this population.

Short-Term Effects of Air Pollution on Heart Rate Variability in Senior Adults in Steubenville, Ohio

OBJECTIVE

We examined the association between ambient air pollution levels and heart rate variability (HRV) in a panel study of 32 subjects.

METHODS

We used linear mixed models to analyze the effects of fine particles (PM2.5), sulfate (SO4), elemental carbon (EC), and gases on log-transformed standard deviation of normal RR intervals (SDNN), mean square of differences between adjacent RR intervals (r-MSSD), and high- and low-frequency power (HF, LF).

RESULTS

An interquartile range (IQR) increase of 5.1 mug/m in SO4 on the previous day was associated with a decrease of -3.3% SDNN (95% confidence = -6.0% to -0.5%), -5.6% r-MSSD (-10.7% to -0.2%), and -10.3% HF (-19.5% to -0.1%). Associations with total PM2.5 were similar. HRV was not associated with EC, NO2, SO2, or O3.

CONCLUSION

In addition to traffic-related particles, elevated levels of sulfate particles may also adversely affect autonomic function.