Indoor particulate matter in rural, wood stove heated homes

Ambient particulate matter (PM) exposures have adverse impacts on public health, but research evaluating indoor PM concentrations in rural homes in the United States using wood as fuel for heating is limited. Our objectives were to characterize indoor PM mass and particle number concentrations (PNCs), quantify infiltration of outdoor PM into the indoor environment, and investigate potential predictors of concentrations and infiltration in 96 homes in the northwestern US and Alaska using wood stoves as the primary source of heating. During two forty-eight hour sampling periods during the pre-intervention winter of a randomized trial, we assessed PM mass (<2.5μm) and PNCs (particles/cm(3)) in six size fractions (0.30-0.49, 0.50-0.99, 1.00-2.49, 2.5-5.0, 5.0-10.0, 10.0+μm). Daily mean (sd) PM2.5 concentrations were 28.8 (28.5)μg/m(3) during the first sampling period and 29.1 (30.1)μg/m(3) during the second period. In repeated measures analyses, household income was inversely associated with PM2.5 and smaller size fraction PNCs, in particular. Time of day was a significant predictor of indoor and outdoor PM2.5 concentrations, and infiltration efficiency was relatively low (Finf (sd)=0.27 (0.20)). Our findings demonstrate relatively high mean PM concentrations in these wood burning homes and suggest potential targets for interventions for improving indoor air quality and health in rural settings.

Long-term exposure to traffic-related air pollution and progression of carotid artery atherosclerosis: a prospective cohort study

OBJECTIVES

Epidemiological studies have demonstrated associations between long-term exposure to traffic-related air pollution and coronary heart disease (CHD). Atherosclerosis is the principal pathological process responsible for CHD events, but effects of traffic-related air pollution on progression of atherosclerosis are not clear. This study aimed to investigate associations between long-term exposure to traffic-related air pollution and progression of carotid artery atherosclerosis.

SETTING

Healthy volunteers in metropolitan Vancouver, Canada.

PARTICIPANTS AND OUTCOME MEASURES

509 participants aged 30-65 years were recruited and followed for approximately 5 years. At baseline and end of follow-up, participants underwent carotid artery ultrasound examinations to assess atherosclerosis severity, including carotid intima-media thickness, plaque area, plaque number and total area. Annual change of each atherosclerosis marker during the follow-up period was calculated as the difference between these two measurements divided by years of follow-up. Living close to major roads was defined as ≤150 m from a highway or ≤50 m from a major road. Residential exposures to traffic-related air pollutants including black carbon, fine particles, nitrogen dioxide and nitric oxide were estimated using high-resolution land-use regression models. The data were analysed using general linear models adjusting for various covariates.

RESULTS

At baseline, there were no significant differences in any atherosclerosis markers between participants living close to and those living away from major roads. After follow-up, the differences in annual changes of these markers between these two groups were small and not statistically significant. Also, no significant associations were observed with concentrations of traffic-related air pollutants including black carbon, fine particles, nitrogen dioxide and nitric oxide.

CONCLUSIONS

This study did not find significant associations between traffic-related air pollution and progression of carotid artery atherosclerosis in a region with lower levels and smaller contrasts of ambient air pollution.

Sulphonylureas and risk of cardiovascular disease: systematic review and meta-analysis

AIMS

Sulphonylurea use has been linked with increased cardiovascular disease risk; however, previous studies have been inconsistent. Type 2 diabetes independently increases risk for cardiovascular disease, so understanding the link between longer-term use of anti-diabetic medications and cardiovascular disease has important clinical implications.

METHODS

Literature search in MEDLINE and CENTRAL was conducted throughout December 2011 for clinical and observational studies that reported the association between sulphonylurea and cardiovascular disease events. Ratios (relative risk, odds ratios or hazard ratios) adjusted for potential confounders (concomitant medications, baseline cardiovascular risk, diabetes severity) were pooled using a random-effects model to yield relative risks and associated 95% confidence intervals.

RESULTS

This meta-analysis included 33 studies (n = 1,325,446 patients), followed for a range of 0.46-10.4 years. In all studies, compared with other oral diabetes drugs, sulphonylurea use was associated with a significantly increased risk of cardiovascular death (relative risk 1.27, 95% confidence interval 1.18-1.34, n = 27 comparisons) and composite cardiovascular event (including myocardial infarction, stroke, cardiovascular-related hospitalization or cardiovascular death) (relative risk 1.10, 95% confidence interval 1.04-1.16, n = 43 comparisons). In studies comparing sulphonylurea vs. metformin, these relative risks were 1.26 (95% confidence interval 1.17-1.35, n = 17 comparisons) and 1.18 (95%confidence interval 1.13-1.24, n = 16 comparisons), respectively.

CONCLUSIONS

Results suggest that sulphonylurea use may elevate the risk of cardiovascular disease among patients with diabetes. This meta-analysis expands the pool of studies evaluating cardiovascular mortality compared with prior observations while using adjusted estimates, and assessing an additional outcome of a composite cardiovascular event. This finding warrants consideration in clinical practice when other treatment options may be available.

A new exposure metric for traffic-related air pollution? An analysis of determinants of hopanes in settled indoor house dust

BACKGROUND

Exposure to traffic-related air pollution (TRAP) can adversely impact health but epidemiologic studies are limited in their abilities to assess long-term exposures and incorporate variability in indoor pollutant infiltration.

METHODS

In order to examine settled house dust levels of hopanes, engine lubricating oil byproducts found in vehicle exhaust, as a novel TRAP exposure measure, dust samples were collected from 171 homes in five Canadian cities and analyzed by gas chromatography-mass spectrometry. To evaluate source contributions, the relative abundance of the highest concentration hopane monomer in house dust was compared to that in outdoor air. Geographic variables related to TRAP emissions and outdoor NO2 concentrations from city-specific TRAP land use regression (LUR) models were calculated at each georeferenced residence location and assessed as predictors of variability in dust hopanes.

RESULTS

Hopanes relative abundance in house dust and ambient air were significantly correlated (Pearson's r=0.48, p<0.05), suggesting that dust hopanes likely result from traffic emissions. The proportion of variance in dust hopanes concentrations explained by LUR NO2 was less than 10% in Vancouver, Winnipeg and Toronto while the correlations in Edmonton and Windsor explained 20 to 40% of the variance. Modeling with household factors such as air conditioning and shoe removal along with geographic predictors related to TRAP generally increased the proportion of explained variability (10-80%) in measured indoor hopanes dust levels.

CONCLUSIONS

Hopanes can consistently be detected in house dust and may be a useful tracer of TRAP exposure if determinants of their spatiotemporal variability are well-characterized, and when home-specific factors are considered.

A land use regression model for ultrafine particles in Vancouver, Canada

Methods to characterize chronic exposure to ultrafine particles (UFP) can help to clarify potential health effects. Since UFP are not routinely monitored in North America, spatiotemporal models are one potential exposure assessment methodology. Portable condensation particle counters were used to measure particle number concentrations (PNC) to develop a land use regression (LUR) model. PNC, wind speed and direction were measured for sixty minutes at eighty locations during a two-week sampling campaign. We conducted continuous monitoring at four additional locations to assess temporal variation. LUR modeling utilized 135 potential geographic predictors including: road length, vehicle density, restaurant density, population density, land use and others. A novel approach incorporated meteorological data through wind roses as alternates to traditional circular buffers. The range of measured (sixty-minute median) PNC across locations varied seventy-fold (1500-105000 particles/cm(3), mean [SD] = 18200 [15900] particles/cm(3)). Correlations between PNC and concurrently measured two-week average NOX concentrations were 0.6-0.7. A PNC LUR model (R(2) = 0.48, leave-one-out cross validation R(2) = 0.32) including truck route length within 50 m, restaurant density within 200 m, and ln-distance to the port represents the first UFP LUR model in North America. Models incorporating wind roses did not explain more variability in measured PNC.

A case-control study of medium-term exposure to ambient nitrogen dioxide pollution and hospitalization for stroke

Background

There are several plausible mechanisms whereby either short or long term exposure to pollution can increase the risk of stroke. Over the last decade, several studies have reported associations between short-term (day-to-day) increases in ambient air pollution and stroke. The findings from a smaller number of studies that have looked at long-term exposure to air pollution and stroke have been mixed. Most of these epidemiological studies have assigned exposure to air pollution based on place of residence, but these assignments are typically based on relatively coarse spatial resolutions. To date, few studies have evaluated medium-term exposures (i.e, exposures over the past season or year). To address this research gap, we evaluated associations between highly spatially resolved estimates of ambient nitrogen dioxide (NO₂), a marker of traffic pollution, and emergency department visits for stroke in Edmonton, Canada.

Methods

This was a case-control study with cases defined as those who presented to an Edmonton area hospital emergency department between 2007 and 2009 with an acute ischemic stroke, hemorrhagic stroke, or transient ischemic attack. Controls were patients who presented to the same emergency departments for lacerations, sprains, or strains. A land-use regression model provided estimates of NO₂ that were assigned to the place of residence. Logistic regression methods were used to estimate odds ratios for stroke in relation to an increase in the interquartile range of NO₂ (5 ppb), adjusted for age, sex, meteorological variables, and neighborhood effects.

Results

The study included 4,696 stroke (cases) and 37,723 injury patients (controls). For all strokes combined, there was no association with NO_2. Namely, the odds ratio associated with an interquartile increase in NO₂ was 1.01 (95% confidence interval {CI}: 0.94-1.08). No associations were evident for any of the stroke subtypes examined.

Conclusion

When combined with our earlier work in Edmonton, our findings suggest that day-to-day fluctuations in air pollution increase the risk of ischemic stroke during the summer season, while medium term exposures are unrelated to stroke risk. The findings for medium term exposure should be interpreted cautiously due to limited individual-level risk factor data.

An assessment of air pollution and its attributable mortality in Ulaanbaatar, Mongolia

Epidemiologic studies have consistently reported associations between outdoor fine particulate matter (PM_2.5) air pollution and adverse health effects. Although Asia bears the majority of the public health burden from air pollution, few epidemiologic studies have been conducted outside of North America and Europe due in part to challenges in population exposure assessment. We assessed the feasibility of two current exposure assessment techniques, land use regression (LUR) modeling and mobile monitoring, and estimated the mortality attributable to air pollution in Ulaanbaatar, Mongolia. We developed LUR models for predicting wintertime spatial patterns of NO₂ and SO₂ based on 2-week passive Ogawa measurements at 37 locations and freely available geographic predictors. The models explained 74% and 78% of the variance in NO₂ and SO₂, respectively. Land cover characteristics derived from satellite images were useful predictors of both pollutants. Mobile PM_2.5 monitoring with an integrating nephelometer also showed promise, capturing substantial spatial variation in PM_2.5 concentrations. The spatial patterns in SO₂ and PM, seasonal and diurnal patterns in PM_2.5, and high wintertime PM_2.5/PM₁₀ ratios were consistent with a major impact from coal and wood combustion in the city's low-income traditional housing (ger) areas. The annual average concentration of PM_2.5 measured at a centrally located government monitoring site was 75 μg/m³ or more than seven times the World Health Organization's PM_2.5 air quality guideline, driven by a wintertime average concentration of 148 μg/m³. PM_2.5 concentrations measured in a traditional housing area were higher, with a wintertime mean PM_2.5 concentration of 250 μg/m³. We conservatively estimated that 29% (95% CI, 12-43%) of cardiopulmonary deaths and 40% (95% CI, 17-56%) of lung cancer deaths in the city are attributable to outdoor air pollution. These deaths correspond to nearly 10% of the city's total mortality, with estimates ranging to more than 13% of mortality under less conservative model assumptions. LUR models and mobile monitoring can be successfully implemented in developing country cities, thus cost-effectively improving exposure assessment for epidemiology and risk assessment. Air pollution represents a major threat to public health in Ulaanbaatar, Mongolia, and reducing home heating emissions in traditional housing areas should be the primary focus of air pollution control efforts.

Prospective study of particulate air pollution exposures, subclinical atherosclerosis, and clinical cardiovascular disease: The Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

The Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) was initiated in 2004 to investigate the relation between individual-level estimates of long-term air pollution exposure and the progression of subclinical atherosclerosis and the incidence of cardiovascular disease (CVD). MESA Air builds on a multicenter, community-based US study of CVD, supplementing that study with additional participants, outcome measurements, and state-of-the-art air pollution exposure assessments of fine particulate matter, oxides of nitrogen, and black carbon. More than 7,000 participants aged 45-84 years are being followed for over 10 years for the identification and characterization of CVD events, including acute myocardial infarction and other coronary artery disease, stroke, peripheral artery disease, and congestive heart failure; cardiac procedures; and mortality. Subcohorts undergo baseline and follow-up measurements of coronary artery calcium using computed tomography and carotid artery intima-medial wall thickness using ultrasonography. This cohort provides vast exposure heterogeneity in ranges currently experienced and permitted in most developed nations, and the air monitoring and modeling methods employed will provide individual estimates of exposure that incorporate residence-specific infiltration characteristics and participant-specific time-activity patterns. The overarching study aim is to understand and reduce uncertainty in health effect estimation regarding long-term exposure to air pollution and CVD.

Modeling the residential infiltration of outdoor PM(2.5) in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND

Epidemiologic studies of fine particulate matter [aerodynamic diameter ≤ 2.5 μm (PM(2.5))] typically use outdoor concentrations as exposure surrogates. Failure to account for variation in residential infiltration efficiencies (F(inf)) will affect epidemiologic study results.

OBJECTIVE

We aimed to develop models to predict F(inf) for > 6,000 homes in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air), a prospective cohort study of PM(2.5) exposure, subclinical cardiovascular disease, and clinical outcomes.

METHODS

We collected 526 two-week, paired indoor-outdoor PM(2.5) filter samples from a subset of study homes. PM(2.5) elemental composition was measured by X-ray fluorescence, and F(inf) was estimated as the indoor/outdoor sulfur ratio. We regressed F(inf) on meteorologic variables and questionnaire-based predictors in season-specific models. Models were evaluated using the R² and root mean square error (RMSE) from a 10-fold cross-validation.

RESULTS

The mean ± SD F(inf) across all communities and seasons was 0.62 ± 0.21, and community-specific means ranged from 0.47 ± 0.15 in Winston-Salem, North Carolina, to 0.82 ± 0.14 in New York, New York. F(inf) was generally greater during the warm (> 18°C) season. Central air conditioning (AC) use, frequency of AC use, and window opening frequency were the most important predictors during the warm season; outdoor temperature and forced-air heat were the best cold-season predictors. The models predicted 60% of the variance in 2-week F(inf), with an RMSE of 0.13.

CONCLUSIONS

We developed intuitive models that can predict F(inf) using easily obtained variables. Using these models, MESA Air will be the first large epidemiologic study to incorporate variation in residential F(inf) into an exposure assessment.

Proximity of public elementary schools to major roads in Canadian urban areas

BACKGROUND

Epidemiologic studies have linked exposure to traffic-generated air and noise pollution with a wide range of adverse health effects in children. Children spend a large portion of time at school, and both air pollution and noise are elevated in close proximity to roads, so school location may be an important determinant of exposure. No studies have yet examined the proximity of schools to major roads in Canadian cities.

METHODS

Data on public elementary schools in Canada's 10 most populous cities were obtained from online databases. School addresses were geocoded and proximity to the nearest major road, defined using a standardized national road classification scheme, was calculated for each school. Based on measurements of nitrogen oxide concentrations, ultrafine particle counts, and noise levels in three Canadian cities we conservatively defined distances < 75 m from major roads as the zone of primary interest. Census data at the city and neighborhood levels were used to evaluate relationships between school proximity to major roads, urban density, and indicators of socioeconomic status.

RESULTS

Addresses were obtained for 1,556 public elementary schools, 95% of which were successfully geocoded. Across all 10 cities, 16.3% of schools were located within 75 m of a major road, with wide variability between cities. Schools in neighborhoods with higher median income were less likely to be near major roads (OR per $20,000 increase: 0.81; 95% CI: 0.65, 1.00), while schools in densely populated neighborhoods were more frequently close to major roads (OR per 1,000 dwellings/km²: 1.07; 95% CI: 1.00, 1.16). Over 22% of schools in the lowest neighborhood income quintile were close to major roads, compared to 13% of schools in the highest income quintile.

CONCLUSIONS

A substantial fraction of students at public elementary schools in Canada, particularly students attending schools in low income neighborhoods, may be exposed to elevated levels of air pollution and noise while at school. As a result, the locations of schools may negatively impact the healthy development and academic performance of a large number of Canadian children.

Comparing universal kriging and land-use regression for predicting concentrations of gaseous oxides of nitrogen (NOx) for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND: Epidemiological studies that assess the health effects of long-term exposure to ambient air pollution are used to inform public policy. These studies rely on exposure models that use data collected from pollution monitoring sites to predict exposures at subject locations. Land use regression (LUR) and universal kriging (UK) have been suggested as potential prediction methods. We evaluate these approaches on a dataset including measurements from three seasons in Los Angeles, CA. METHODS: The measurements of gaseous oxides of nitrogen (NOx) used in this study are from a "snapshot" sampling campaign that is part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). The measurements in Los Angeles were collected during three two-week periods in the summer, autumn, and winter, each with about 150 sites. The design included clusters of monitors on either side of busy roads to capture near-field gradients of traffic-related pollution. LUR and UK prediction models were created using geographic information system (GIS)-based covariates. Selection of covariates was based on 10-fold cross-validated (CV) R(2) and root mean square error (RMSE). Since UK requires specialized software, a computationally simpler two-step procedure was also employed to approximate fitting the UK model using readily available regression and GIS software. RESULTS: UK models consistently performed as well as or better than the analogous LUR models. The best CV R(2) values for season-specific UK models predicting log(NOx) were 0.75, 0.72, and 0.74 (CV RMSE 0.20, 0.17, and 0.15) for summer, autumn, and winter, respectively. The best CV R(2) values for season-specific LUR models predicting log(NOx) were 0.74, 0.60, and 0.67 (CV RMSE 0.20, 0.20, and 0.17). The two-stage approximation to UK also performed better than LUR and nearly as well as the full UK model with CV R(2) values 0.75, 0.70, and 0.70 (CV RMSE 0.20, 0.17, and 0.17) for summer, autumn, and winter, respectively. CONCLUSION: High quality LUR and UK prediction models for NOx in Los Angeles were developed for the three seasons based on data collected for MESA Air. In our study, UK consistently outperformed LUR. Similarly, the 2-step approach was more effective than the LUR models, with performance equal to or slightly worse than UK.

An air filter intervention study of endothelial function among healthy adults in a woodsmoke-impacted community

RATIONALE

Particulate air pollution is associated with cardiovascular morbidity. One hypothesized mechanism involves oxidative stress, systemic inflammation, and endothelial dysfunction.

OBJECTIVES

To assess an intervention's impact on particle exposures and endothelial function among healthy adults in a woodsmoke-impacted community. We also investigated the underlying role of oxidative stress and inflammation in relation to exposure reductions.

METHODS

Portable air filters were used in a randomized crossover intervention study of 45 healthy adults exposed to consecutive 7-day periods of filtered and nonfiltered air.

MEASUREMENTS AND MAIN RESULTS

Reactive hyperemia index was measured as an indicator of endothelial function via peripheral artery tonometry, and markers of inflammation (C-reactive protein, interleukin-6, and band cells) and lipid peroxidation (malondialdehyde and 8-iso-prostaglandin F(2α)) were quantified. Air filters reduced indoor fine particle concentrations by 60%. Filtration was associated with a 9.4% (95% confidence interval, 0.9-18%) increase in reactive hyperemia index and a 32.6% (4.4-60.9%) decrease in C-reactive protein. Decreases in particulate matter and the woodsmoke tracer levoglucosan were associated with reduced band cell counts. There was limited evidence of more pronounced effects on endothelial function and level of systemic inflammation among males, overweight participants, younger participants, and residents of wood-burning homes. No associations were noted for oxidative stress markers.

CONCLUSIONS

Air filtration was associated with improved endothelial function and decreased concentrations of inflammatory biomarkers but not markers of oxidative stress. Our results support the hypothesis that systemic inflammation and impaired endothelial function, both predictors of cardiovascular morbidity, can be favorably influenced by reducing indoor particle concentrations.

Exploring variation and predictors of residential fine particulate matter infiltration

Although individuals spend the majority of their time indoors, most epidemiological studies estimate personal air pollution exposures based on outdoor levels. This almost certainly results in exposure misclassification as pollutant infiltration varies between homes. However, it is often not possible to collect detailed measures of infiltration for individual homes in large-scale epidemiological studies and thus there is currently a need to develop models that can be used to predict these values. To address this need, we examined infiltration of fine particulate matter (PM(2.5)) and identified determinants of infiltration for 46 residential homes in Toronto, Canada. Infiltration was estimated using the indoor/outdoor sulphur ratio and information on hypothesized predictors of infiltration were collected using questionnaires and publicly available databases. Multiple linear regression was used to develop the models. Mean infiltration was 0.52 ± 0.21 with no significant difference across heating and non-heating seasons. Predictors of infiltration were air exchange, presence of central air conditioning, and forced air heating. These variables accounted for 38% of the variability in infiltration. Without air exchange, the model accounted for 26% of the variability. Effective modelling of infiltration in individual homes remains difficult, although key variables such as use of central air conditioning show potential as an easily attainable indicator of infiltration.

Small volume laboratory on a chip measurements incorporating the quartz crystal microbalance to measure the viscosity-density product of room temperature ionic liquids

A microfluidic glass chip system incorporating a quartz crystal microbalance (QCM) to measure the square root of the viscosity-density product of room temperature ionic liquids (RTILs) is presented. The QCM covers a central recess on a glass chip, with a seal formed by tightly clamping from above outside the sensing region. The change in resonant frequency of the QCM allows for the determination of the square root viscosity-density product of RTILs to a limit of approximately 10 kg m(-2) s(-0.5). This method has reduced the sample size needed for characterization from 1.5 ml to only 30 mul and allows the measurement to be made in an enclosed system.

Modeling residential fine particulate matter infiltration for exposure assessment

Individuals spend the majority of their time indoors; therefore, estimating infiltration of outdoor-generated fine particulate matter (PM(2.5)) can help reduce exposure misclassification in epidemiological studies. As indoor measurements in individual homes are not feasible in large epidemiological studies, we evaluated the potential of using readily available data to predict infiltration of ambient PM(2.5) into residences. Indoor and outdoor light scattering measurements were collected for 84 homes in Seattle, Washington, USA, and Victoria, British Columbia, Canada, to estimate residential infiltration efficiencies. Meteorological variables and spatial property assessment data (SPAD), containing detailed housing characteristics for individual residences, were compiled for both study areas using a geographic information system. Multiple linear regression was used to construct models of infiltration based on these data. Heating (October to February) and non-heating (March to September) season accounted for 36% of the yearly variation in detached residential infiltration. Two SPAD housing characteristic variables, low building value, and heating with forced air, predicted 37% of the variation found between detached residential infiltration during the heating season. The final model, incorporating temperature and the two SPAD housing characteristic variables, with a seasonal interaction term, explained 54% of detached residential infiltration. Residences with low building values had higher infiltration efficiencies than other residences, which could lead to greater exposure gradients between low and high socioeconomic status individuals than previously identified using only ambient PM(2.5) concentrations. This modeling approach holds promise for incorporating infiltration efficiencies into large epidemiology studies, thereby reducing exposure misclassification.

Approach to estimating participant pollutant exposures in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

Most published epidemiology studies of long-term air pollution health effects have relied on central site monitoring to investigate regional-scale differences in exposure. Few cohort studies have had sufficient data to characterize localized variations in pollution, despite the fact that large gradients can exist over small spatial scales. Similarly, previous data have generally been limited to measurements of particle mass or several of the criteria gases. The Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) is an innovative investigation undertaken to link subclinical and clinical cardiovascular health effects with individual-level estimates of personal exposure to ambient-origin pollution. This project improves on prior work by implementing an extensive exposure assessment program to characterize long-term average concentrations of ambient-generated PM2.5, specific PM2.5 chemical components, and copollutants, with particular emphasis on capturing concentration gradients within cities. This paper describes exposure assessment in MESA Air, including questionnaires, community sampling, home monitoring, and personal sampling. Summary statistics describing the performance of the sampling methods are presented along with descriptive statistics of the air pollution concentrations by city.

Fine particulate matter air pollution, proximity to traffic, and aortic atherosclerosis

BACKGROUND

The initiation and acceleration of atherosclerosis is hypothesized as a physiologic mechanism underlying associations between air pollution and cardiovascular effects. Despite toxicologic evidence, epidemiologic data are limited.

METHODS

In this cross-sectional analysis we investigated exposure to fine particulate matter (PM2.5) and residential proximity to major roads in relation to abdominal aortic calcification, a sensitive indicator of systemic atherosclerosis. Aortic calcification was measured by computed tomography among 1147 persons, in 5 US metropolitan areas, enrolled in the Multi-Ethnic Study of Atherosclerosis. The presence and quantity of aortic calcification were modeled using relative risk regression and linear regression, respectively, with adjustment for potential confounders.

RESULTS

We observed a slightly elevated risk of aortic calcification (RR = 1.06; 95% confidence interval = 0.96-1.16) with a 10 microg/m contrast in PM2.5. The PM2.5-associated risk of aortic calcification was stronger among participants with long-term residence near a PM2.5 monitor (RR = 1.11; 1.00-1.24) and among participants not recently employed outside the home (RR = 1.10; 1.00-1.22). PM2.5 was not associated with an increase in the quantity of aortic calcification (Agatston score) and no roadway proximity effects were noted. There was indication of PM2.5 effect modification by lipid-lowering medication use, with greater effects among users, and PM2.5 associations were observed most consistently among Hispanics.

CONCLUSIONS

Although we did not find persuasive associations across our full study population, associations were stronger among participants with less exposure misclassification. These findings support the hypothesis of a relationship between particulate air pollution and systemic atherosclerosis.

The spatial relationship between traffic-generated air pollution and noise in 2 US cities

Traffic-generated air pollution and noise have both been linked to cardiovascular morbidity. Since traffic is a shared source, there is potential for correlated exposures that may lead to confounding in epidemiologic studies. As part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air), 2-week NO and NO(2) concentrations were measured at up to 105 locations, selected primarily to characterize gradients near major roads, in each of 9 US communities. We measured 5-min A-weighted equivalent continuous sound pressure levels (L(eq)) and ultrafine particle (UFP) counts at a subset of these NO/NO(2) monitoring locations in Chicago, IL (N=69 in December 2006; N=36 in April 2007) and Riverside County, CA (N=46 in April 2007). L(eq) and UFP were measured during non-"rush hour" periods (10:00-16:00) to maximize comparability between measurements. We evaluated roadway proximity exposure surrogates in relation to the measured levels, estimated noise-air pollution correlation coefficients, and evaluated the impact of regional-scale pollution gradients, wind direction, and roadway proximity on the correlations. Five-minute L(eq) measurements in December 2006 and April 2007 were highly correlated (r=0.84), and measurements made at different times of day were similar (coefficients of variation: 0.5-13%), indicating that 5-min measurements are representative of long-term L(eq). Binary and continuous roadway proximity metrics characterized L(eq) as well or better than NO or NO(2). We found strong regional-scale gradients in NO and NO(2), particularly in Chicago, but only weak regional-scale gradients in L(eq) and UFP. L(eq) was most consistently correlated with NO, but the correlations were moderate (0.20-0.60). After removing the influence of regional-scale gradients the correlations generally increased (L(eq)-NO: r=0.49-0.62), and correlations downwind of major roads (L(eq)-NO: r=0.53-0.74) were consistently higher than those upwind (0.35-0.65). There was not a consistent effect of roadway proximity on the correlations. In conclusion, roadway proximity variables are not unique exposure surrogates in studies of endpoints hypothesized to be related to both air pollution and noise. Moderate correlations between traffic-generated air pollution and noise suggest the possibility of confounding, which might be minimized by considering regional pollution gradients and/or prevailing wind direction(s) in epidemiologic studies.

Draft protocol for testing calibration and quality control material used with automatic blood-counting apparatus

A large number of commercial preparations are now available for calibrating or checking the stability of automatic blood counters. Most of these preparations are supplied with 'stated' values though the methods for assigning these values are not described in sufficient detail to allow for an adequate assessment of the validity. The Haemocytometry Panel of the British Committee for Standards in Haematology are therefore proposing a draft protocol for testing calibration and quality control materials. Comments on the draft protocol are invited, either as letters to the Editor of Clinical and Laboratory Haematology or in confidence to the Chairman of the Haemocytometry Panel.

Changes in lung function and airway inflammation among asthmatic children residing in a woodsmoke-impacted urban area

Fine particulate matter (PM(2.5)) is associated with respiratory effects, and asthmatic children are especially sensitive. Preliminary evidence suggests that combustion-derived particles play an important role. Our objective was to evaluate effect estimates from different PM(2.5) exposure metrics in relation to airway inflammation and lung function among children residing in woodsmoke-impacted areas of Seattle. Nineteen children (ages 6-13 yr) with asthma were monitored during the heating season. We measured 24-h outdoor and personal concentrations of PM(2.5) and light-absorbing carbon (LAC). Levoglucosan (LG), a marker of woodsmoke, was also measured outdoors. We partitioned PM(2.5) exposure into its ambient-generated (E(ag)) and nonambient (E(na)) components. These exposure metrics were evaluated in relation to daily changes in exhaled nitric oxide (FE(NO)), a marker of airway inflammation, and four lung function measures: midexpiratory flow (MEF), peak expiratory flow (PEF), forced expiratory volume in the first second (FEV(1)), and forced vital capacity (FVC). E(ag), but not E(na), was correlated with combustion markers. Significant associations with respiratory health were seen only among participants not using inhaled corticosteroids. Increases in FE(NO) were associated with personal PM(2.5), personal LAC, and E(ag) but not with ambient PM(2.5) or its combustion markers. In contrast, MEF and PEF decrements were associated with ambient PM(2.5), its combustion markers, and E(ag), but not with personal PM(2.5) or personal LAC. FEV(1) was associated only with ambient LG. Our results suggest that lung function may be especially sensitive to the combustion-generated component of ambient PM(2.5), whereas airway inflammation may be more closely related to some other constituent of the ambient PM(2.5) mixture.

Pulmonary effects of indoor- and outdoor-generated particles in children with asthma

Most particulate matter (PM) health effects studies use outdoor (ambient) PM as a surrogate for personal exposure. However, people spend most of their time indoors exposed to a combination of indoor-generated particles and ambient particles that have infiltrated. Thus, it is important to investigate the differential health effects of indoor- and ambient-generated particles. We combined our recently adapted recursive model and a predictive model for estimating infiltration efficiency to separate personal exposure (E) to PM2.5 (PM with aerodynamic diameter < or = 2.5 microm) into its indoor-generated (Eig) and ambient-generated (Eag) components for 19 children with asthma. We then compared Eig and Eag to changes in exhaled nitric oxide (eNO), a marker of airway inflammation. Based on the recursive model with a sample size of eight children, Eag was marginally associated with increases in eNO [5.6 ppb per 10-microg/m3 increase in PM2.5; 95% confidence interval (CI), -0.6 to 11.9; p = 0.08]. Eig was not associated with eNO (-0.19 ppb change per 10 microg/m3). Our predictive model allowed us to estimate Eag and Eig for all 19 children. For those combined estimates, only Eag was significantly associated with an increase in eNO (Eag: 5.0 ppb per 10-microg/m3 increase in PM2.5; 95% CI, 0.3 to 9.7; p = 0.04; Eig: 3.3 ppb per 10-microg/m3 increase in PM2.5; 95% CI, -1.1 to 7.7; p = 0.15). Effects were seen only in children who were not using corticosteroid therapy. We conclude that the ambient-generated component of PM2.5 exposure is consistently associated with increases in eNO and the indoor-generated component is less strongly associated with eNO.

Prenatal genotyping for the RhD blood group antigen: considerations in developing an accurate test

Experience performing prenatal genotyping for RHD has shown that consideration must be given to developing a molecular test capable of detecting recombination/gene conversion events involving the RHD and RHCE genes that can lead to erroneous results. Out of 50 prenatal RHD tests performed over the past 5 years, four samples were encountered that gave false-positive results. In only one of the tests, incorrect results were issued to the physician. In the other three instances, the erroneous nature of the test results was revealed through the analysis of multiple regions of the RHD gene and, more importantly, because the mother, and sometimes the father, were tested in parallel with the fetus. In an extension of the observations obtained from the prenatal testing program, a large panel of RhD-negative blood donors were subjected to molecular analysis of the RHD gene. Of 1,183 donors screened, 187 were found to phenotype as RhD negative. Of the 187 donors confirmed RhD negative serologically, 22 (11.8%) were found to retain remnants of the RHD gene that, depending upon the characteristics of the molecular assay performed, could lead to a false-positive result in a genotyping assay. On the basis of the experience presented here, it is recommended that any molecular RHD assay include an analysis of multiple areas of the RHD gene so as to allow for the detection of recombination/gene conversion events between the RHD and RHCE genes. Moreover, it is strongly recommended that the mother (at a minimum) and father be subjected to molecular analysis simultaneously with the fetus to confirm that the known phenotypes of the parent(s) are consistent with their respective genotypes.