Reducing Indoor Particulate Air Pollution Improves Student Test Scores: A Randomized Double-Blind Crossover Study.

Short-term exposure to air pollution is associated with a decline in cognitive function. Standardized test scores have been employed to evaluate the effects of air pollution exposure on cognitive performance. Few studies aimed to prove whether air pollution is responsible for reduced test scores; none have implemented a "gold-standard" method for assessing the association such as a randomized, double-blind intervention. This study used a "gold-standard" method─randomized, double-blind crossover─to assess whether reducing short-term indoor particle concentrations results in improved test scores in college students in Tianjin, China. Participants (n = 162) were randomly assigned to one of two similar classrooms and completed a standardized English test on two consecutive weekends. Air purifiers with active or sham (i.e., filter removed) particle filtration were placed in each classroom. The filtration mode was switched between the two test days. Linear mixed-effect models were used to evaluate the effect of the intervention mode on the test scores. The results show that air purification (i.e., reducing PM) was significantly associated with increases in the z score for combined (0.11 [95%CI: 0.02, 0.21]) and reading (0.11 [95%CI: 0.00, 0.22]) components. In conclusion, a short-term reduction in indoor particle concentration led to improved test scores in students, suggesting an improvement in cognitive function.

Blood Pressure Effect of Traffic-Related Air Pollution : A Crossover Trial of In-Vehicle Filtration.

BACKGROUND: Ambient air pollution, including traffic-related air pollution (TRAP), increases cardiovascular disease risk, possibly through vascular alterations. Limited information exists about in-vehicle TRAP exposure and vascular changes. OBJECTIVE: To determine via particle filtration the effect of on-roadway TRAP exposure on blood pressure and retinal vasculature. DESIGN: Randomized crossover trial. (ClinicalTrials.gov: NCT05454930). SETTING: In-vehicle scripted commutes driven through traffic in Seattle, Washington, during 2014 to 2016. PARTICIPANTS: Normotensive persons aged 22 to 45 years (n = 16). INTERVENTION: On 2 days, on-road air was entrained into the vehicle. On another day, the vehicle was equipped with high-efficiency particulate air (HEPA) filtration. Participants were blinded to the exposure and were randomly assigned to the sequence. MEASUREMENTS: Fourteen 3-minute periods of blood pressure were recorded before, during, and up to 24 hours after a drive. Image-based central retinal arteriolar equivalents (CRAEs) were measured before and after. Brachial artery diameter and gene expression were also measured and will be reported separately. RESULTS: Mean age was 29.7 years, predrive systolic blood pressure was 122.7 mm Hg, predrive diastolic blood pressure was 70.8 mm Hg, and drive duration was 122.3 minutes (IQR, 4 minutes). Filtration reduced particle count by 86%. Among persons with complete data (n = 13), at 1 hour, mean diastolic blood pressure, adjusted for predrive levels, order, and carryover, was 4.7 mm Hg higher (95% CI, 0.9 to 8.4 mm Hg) for unfiltered drives compared with filtered drives, and mean adjusted systolic blood pressure was 4.5 mm Hg higher (CI, -1.2 to 10.2 mm Hg). At 24 hours, adjusted mean diastolic blood pressure (unfiltered) was 3.8 mm Hg higher (CI, 0.02 to 7.5 mm Hg) and adjusted mean systolic blood pressure was 1.1 mm Hg higher (CI, -4.6 to 6.8 mm Hg). Adjusted mean CRAE (unfiltered) was 2.7 µm wider (CI, -1.5 to 6.8 µm). LIMITATIONS: Imprecise estimates due to small sample size; seasonal imbalance by exposure order. CONCLUSION: Filtration of TRAP may mitigate its adverse effects on blood pressure rapidly and at 24 hours. Validation is required in larger samples and different settings. PRIMARY FUNDING SOURCE: U.S. Environmental Protection Agency and National Institutes of Health.

Improving Air Pollution Predictions of Long-Term Exposure Using Short-Term Mobile and Stationary Monitoring in Two US Metropolitan Regions.

Mobile monitoring is increasingly employed to measure fine spatial-scale variation in air pollutant concentrations. However, mobile measurement campaigns are typically conducted over periods much shorter than the decadal periods used for modeling chronic exposure for use in air pollution epidemiology. Using the regions of Los Angeles and Baltimore and the time period from 2005 to 2014 as our modeling domain, we investigate whether including mobile or stationary passive sampling device (PSD) monitoring data collected over a single 2-week period in one or two seasons using a unified spatio-temporal air pollution model can improve model performance in predicting NO2 and NOx concentrations throughout the 9-year study period beyond what is possible using only routine monitoring data. In this initial study, we use data from mobile measurement campaigns conducted contemporaneously with deployments of stationary PSDs and only use mobile data collected within 300 m of a stationary PSD location for inclusion in the model. We find that including either mobile or PSD data substantially improves model performance for pollutants and locations where model performance was initially the worst (with the most-improved R2 changing from 0.40 to 0.82) but does not meaningfully change performance in cases where performance was already very good. Results indicate that in many cases, additional spatial information from mobile monitoring and personal sampling is potentially cost-efficient inexpensive way of improving exposure predictions at both 2-week and decadal averaging periods, especially for the predictions that are located closer to features such as roadways targeted by the mobile short-term monitoring campaign.

Ambient air pollution, traffic proximity and coronary atherosclerotic phenotype in China.

BACKGROUND: Exposure to ambient air pollution is associated with cardiovascular risk, potentially via atherosclerosis promotion. The disease mechanisms underlying these associations remain uncertain. OBJECTIVES: We aim to investigate the relationship of air pollution and traffic proximity with subclinical atherosclerosis, using coronary plaque phenotypes to gain insight into potential mechanisms. METHODS: Coronary plaque total and component volumes, high-risk plaque (HRP) appearance, and luminal stenosis were characterized by coronary computed tomography angiography in 2279 patients with atherosclerosis at baseline between 2014 and 2017. Annual average exposure to air pollutants including fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) was estimated by air pollution models for individual participants. Multiple linear regression models were used to assess the association of each exposure with plaque phenotypes and coronary stenosis, controlling for potential confounders. Multiple logistic regression models were used to estimate associations with plaque vulnerability. RESULTS: The studied population was 60.2±9.2 years old. PM2.5 and NO2 concentrations were significantly associated with a 5.0% (95%CI: 0.3, 9.9%, per 15 µg/m3 increase for PM2.5), 12.0% (95%CI: 2.5, 22.5% per 20 µg/m3 for NO2) larger volume of non-calcified plaque, respectively. Increase in O3 concentration was associated with a 12.2% (95%CI: 2.2, 23.2%, per 5 µg/m3 O3) larger volume of calcified plaque and a 12.8% (95%CI: 0.9, 26.2%) greater lumen narrowing. Increased PM2.5 and NO2, was also associated with increase in HRP, determined by the napkin ring sign (odds ratio: 1.41 [95%CI: 1.10, 1.80] for PM2.5 and 1.78 [95%CI: 1.20, 2.63] for NO2) and positive remodeling index (OR: 1.11 [95%CI: 1.01, 1.21] for PM2.5 and 1.20 [95%CI: 1.02, 1.42] for NO2), respectively, indicating increased plaque vulnerability. CONCLUSION: Long-term exposures to air pollution were associated with greater plaque volume and luminal stenosis, and increased plaque vulnerability with attendant risk of plaque rupture and erosion.

Association Between Long-term Exposure to Ambient Air Pollution and Change in Quantitatively Assessed Emphysema and Lung Function.

Importance: While air pollutants at historical levels have been associated with cardiovascular and respiratory diseases, it is not known whether exposure to contemporary air pollutant concentrations is associated with progression of emphysema. Objective: To assess the longitudinal association of ambient ozone (O3), fine particulate matter (PM2.5), oxides of nitrogen (NOx), and black carbon exposure with change in percent emphysema assessed via computed tomographic (CT) imaging and lung function. Design, Setting, and Participants: This cohort study included participants from the Multi-Ethnic Study of Atherosclerosis (MESA) Air and Lung Studies conducted in 6 metropolitan regions of the United States, which included 6814 adults aged 45 to 84 years recruited between July 2000 and August 2002, and an additional 257 participants recruited from February 2005 to May 2007, with follow-up through November 2018. Exposures: Residence-specific air pollutant concentrations (O3, PM2.5, NOx, and black carbon) were estimated by validated spatiotemporal models incorporating cohort-specific monitoring, determined from 1999 through the end of follow-up. Main Outcomes and Measures: Percent emphysema, defined as the percent of lung pixels less than -950 Hounsfield units, was assessed up to 5 times per participant via cardiac CT scan (2000-2007) and equivalent regions on lung CT scans (2010-2018). Spirometry was performed up to 3 times per participant (2004-2018). Results: Among 7071 study participants (mean [range] age at recruitment, 60 [45-84] years; 3330 [47.1%] were men), 5780 were assigned outdoor residential air pollution concentrations in the year of their baseline examination and during the follow-up period and had at least 1 follow-up CT scan, and 2772 had at least 1 follow-up spirometric assessment, over a median of 10 years. Median percent emphysema was 3% at baseline and increased a mean of 0.58 percentage points per 10 years. Mean ambient concentrations of PM2.5 and NOx, but not O3, decreased substantially during follow-up. Ambient concentrations of O3, PM2.5, NOx, and black carbon at study baseline were significantly associated with greater increases in percent emphysema per 10 years (O3: 0.13 per 3 parts per billion [95% CI, 0.03-0.24]; PM2.5: 0.11 per 2 µg/m3 [95% CI, 0.03-0.19]; NOx: 0.06 per 10 parts per billion [95% CI, 0.01-0.12]; black carbon: 0.10 per 0.2 µg/m3 [95% CI, 0.01-0.18]). Ambient O3 and NOx concentrations, but not PM2.5 concentrations, during follow-up were also significantly associated with greater increases in percent emphysema. Ambient O3 concentrations, but not other pollutants, at baseline and during follow-up were significantly associated with a greater decline in forced expiratory volume in 1 second per 10 years (baseline: 13.41 mL per 3 parts per billion [95% CI, 0.7-26.1]; follow-up: 18.15 mL per 3 parts per billion [95% CI, 1.59-34.71]). Conclusions and Relevance: In this cohort study conducted between 2000 and 2018 in 6 US metropolitan regions, long-term exposure to ambient air pollutants was significantly associated with increasing emphysema assessed quantitatively using CT imaging and lung function.

Mobile and Fixed-Site Measurements To Identify Spatial Distributions of Traffic-Related Pollution Sources in Los Angeles.

Mobile monitoring and fixed-site monitoring using passive sampling devices (PSD) are popular air pollutant measurement techniques with complementary strengths and weaknesses. This study investigates the utility of combining data from concurrent 2-week mobile monitoring and fixed-site PSD campaigns in Los Angeles in the summer and early spring to identify sources of traffic-related air pollutants (TRAP) and their spatial distributions. There were strong to moderate correlations between mobile and fixed-site PSD measurements of both NO2 and NO x in the summer and spring (Pearson's r between 0.43 and 0.79), suggesting that the two data sets can be reliably combined for source apportionment. PCA identified the major TRAP sources as light-duty vehicle emissions, diesel exhaust, crankcase vent emissions, and an independent source of combustion-derived ultrafine particle emissions. The component scores of those four sources at each site were significantly correlated across the two seasons (Pearson's r between 0.58 and 0.79). Spatial maps of absolute principal component scores showed all sources to be most prominent near major roadways and the central business district and the ultrafine particle source being, in addition, more prominent near the airport. Mobile monitoring combined with fixed-site PSD sampling can provide high spatial resolution estimates of TRAP and can reveal underlying sources of exposure variability.

Occupational Exposures and Subclinical Interstitial Lung Disease. The MESA (Multi-Ethnic Study of Atherosclerosis) Air and Lung Studies.

RATIONALE: The impact of a broad range of occupational exposures on subclinical interstitial lung disease (ILD) has not been studied. OBJECTIVES: To determine whether occupational exposures to vapors, gas, dust, and fumes (VGDF) are associated with high-attenuation areas (HAA) and interstitial lung abnormalities (ILA), which are quantitative and qualitative computed tomography (CT)-based measurements of subclinical ILD, respectively. METHODS: We performed analyses of participants enrolled in MESA (Multi-Ethnic Study of Atherosclerosis), a population-based cohort aged 45-84 years at recruitment. HAA was measured at baseline and on serial cardiac CT scans in 5,702 participants. ILA was ascertained in a subset of 2,312 participants who underwent full-lung CT scanning at 10-year follow-up. Occupational exposures were assessed by self-reported VGDF exposure and by job-exposure matrix (JEM). Linear mixed models and logistic regression were used to determine whether occupational exposures were associated with log-transformed HAA and ILA. Models were adjusted for age, sex, race/ethnicity, education, employment status, tobacco use, and scanner technology. MEASUREMENTS AND MAIN RESULTS: Each JEM score increment in VGDF exposure was associated with 2.64% greater HAA (95% confidence interval [CI], 1.23-4.19%). Self-reported vapors/gas exposure was associated with an increased odds of ILA among those currently employed (1.76-fold; 95% CI, 1.09-2.84) and those less than 65 years old (1.97-fold; 95% CI, 1.16-3.35). There was no consistent evidence that occupational exposures were associated with progression of HAA over the follow-up period. CONCLUSIONS: JEM-assigned and self-reported exposures to VGDF were associated with measurements of subclinical ILD in community-dwelling adults.

Air pollution and subclinical interstitial lung disease: the Multi-Ethnic Study of Atherosclerosis (MESA) air-lung study.

We studied whether ambient air pollution is associated with interstitial lung abnormalities (ILAs) and high attenuation areas (HAAs), which are qualitative and quantitative measurements of subclinical interstitial lung disease (ILD) on computed tomography (CT).We performed analyses of community-based dwellers enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA) study. We used cohort-specific spatio-temporal models to estimate ambient pollution (fine particulate matter (PM2.5), nitrogen oxides (NOx), nitrogen dioxide (NO2) and ozone (O3)) at each home. A total of 5495 participants underwent serial assessment of HAAs by cardiac CT; 2671 participants were assessed for ILAs using full lung CT at the 10-year follow-up. We used multivariable logistic regression and linear mixed models adjusted for age, sex, ethnicity, education, tobacco use, scanner technology and study site.The odds of ILAs increased 1.77-fold per 40 ppb increment in NOx (95% CI 1.06 to 2.95, p = 0.03). There was an overall trend towards an association between higher exposure to NOx and greater progression of HAAs (0.45% annual increase in HAAs per 40 ppb increment in NOx; 95% CI -0.02 to 0.92, p = 0.06). Associations of ambient fine particulate matter (PM2.5), NOx and NO2 concentrations with progression of HAAs varied by race/ethnicity (p = 0.002, 0.007, 0.04, respectively, for interaction) and were strongest among non-Hispanic white people.We conclude that ambient air pollution exposures were associated with subclinical ILD.

Combining Land-Use Regression and Chemical Transport Modeling in a Spatiotemporal Geostatistical Model for Ozone and PM2.5.

Assessments of long-term air pollution exposure in population studies have commonly employed land-use regression (LUR) or chemical transport modeling (CTM) techniques. Attempts to incorporate both approaches in one modeling framework are challenging. We present a novel geostatistical modeling framework, incorporating CTM predictions into a spatiotemporal LUR model with spatial smoothing to estimate spatiotemporal variability of ozone (O3) and particulate matter with diameter less than 2.5 µm (PM2.5) from 2000 to 2008 in the Los Angeles Basin. The observations include over 9 years' data from more than 20 routine monitoring sites and specific monitoring data at over 100 locations to provide more comprehensive spatial coverage of air pollutants. Our composite modeling approach outperforms separate CTM and LUR models in terms of root-mean-square error (RMSE) assessed by 10-fold cross-validation in both temporal and spatial dimensions, with larger improvement in the accuracy of predictions for O3 (RMSE [ppb] for CTM, 6.6; LUR, 4.6; composite, 3.6) than for PM2.5 (RMSE [µg/m(3)] CTM: 13.7, LUR: 3.2, composite: 3.1). Our study highlights the opportunity for future exposure assessment to make use of readily available spatiotemporal modeling methods and auxiliary gridded data that takes chemical reaction processes into account to improve the accuracy of predictions in a single spatiotemporal modeling framework.

Characteristics of atmospheric single particles during haze periods in a typical urban area of Beijing: A case study in October, 2014.

To investigate the composition and possible sources of particles, especially during heavy haze pollution, a single particle aerosol mass spectrometer (SPAMS) was deployed to measure the changes of single particle species and sizes during October of 2014, in Beijing. A total of 2,871,431 particles with both positive and negative spectra were collected and characterized in combination with the adaptive resonance theory neural network algorithm (ART-2a). Eight types of particles were classified: dust particles (dust, 8.1%), elemental carbon (EC, 29.0%), organic carbon (OC, 18.0%), EC and OC combined particles (ECOC, 9.5%), Na-K containing particles (NaK, 7.9%), K-containing particles (K, 21.8%), organic nitrogen and potassium containing particles (KCN, 2.3%), and metal-containing particles (metal, 3.6%). Three haze pollution events (P1, P2, P3) and one clean period (clean) were analyzed, based on the mass and number concentration of PM2.5 and the back trajectory results from the hybrid single particle Lagrangian integrated trajectory model (Hysplit-4 model). Results showed that EC, OC and K were the major components of single particles during the three haze pollution periods, which showed clearly increased ratios compared with those in the clean period. Results from the mixing state of secondary species of different types of particles showed that sulfate and nitrate were more readily mixed with carbon-containing particles during haze pollution episodes than in clean periods.

Ambient Ammonia Exposures in an Agricultural Community and Pediatric Asthma Morbidity.

BACKGROUND: Large-scale animal feeding operations compromise regional air quality in the rural US through emission of pollutants, such as ammonia gas. Exposure to airborne pollution from animal feeding operations may cause pediatric asthma exacerbations in surrounding communities. OBJECTIVES: To describe spatial and temporal patterns in ambient ammonia concentrations in an agricultural region, and to investigate associations between short-term fluctuations in ammonia and subsequent changes in respiratory health in children with asthma. METHODS: For 13 months in the Yakima Valley of Washington State, 14 monitors sampled ammonia in outdoor air for 24-hour periods every 6 days. School-age children with asthma (n = 51) were followed for two health outcomes: biweekly reports of asthma symptoms and quick relief medication usage, and daily measurements of forced expiratory volume in 1 second. We assessed associations between each outcome and ammonia using generalized estimating equations. RESULTS: Twenty-four-hour ammonia concentrations varied from 0.2 to 238.1 µg/m during the study period and displayed a strong correlation with proximity to animal feeding operations. The percentage of forced expiratory volume in 1 second was 3.8% lower (95% confidence interval = 0.2, 7.3) per interquartile increase in 1-day lagged ammonia concentration and 3.0% lower (95% confidence interval = 0.5, 5.8) for 2-day lagged concentration. We observed no associations between self-reported asthma symptoms or medication usage and estimated ammonia exposure. CONCLUSIONS: Ammonia concentrations were elevated in this community and strongly predicted by proximity to animal feeding operations. Ammonia's association with acute lung function decrements in children with asthma in the surrounding community may be causal or, alternatively, ammonia may be a marker for other pollutants from animal feeding operations associated with respiratory effects.

Long-term exposure to air pollution and markers of inflammation, coagulation, and endothelial activation: a repeat-measures analysis in the Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: Air pollution is associated with cardiovascular disease, and systemic inflammation may mediate this effect. We assessed associations between long- and short-term concentrations of air pollution and markers of inflammation, coagulation, and endothelial activation. METHODS: We studied participants from the Multi-Ethnic Study of Atherosclerosis from 2000 to 2012 with repeat measures of serum C-reactive protein (CRP), interleukin-6 (IL-6), fibrinogen, D-dimer, soluble E-selectin, and soluble Intercellular Adhesion Molecule-1. Annual average concentrations of ambient fine particulate matter (PM2.5), individual-level ambient PM2.5 (integrating indoor concentrations and time-location data), oxides of nitrogen (NOx), nitrogen dioxide (NO2), and black carbon were evaluated. Short-term concentrations of PM2.5 reflected the day of blood draw, day prior, and averages of prior 2-, 3-, 4-, and 5-day periods. Random-effects models were used for long-term exposures and fixed effects for short-term exposures. The sample size was between 9,000 and 10,000 observations for CRP, IL-6, fibrinogen, and D-dimer; approximately 2,100 for E-selectin; and 3,300 for soluble Intercellular Adhesion Molecule-1. RESULTS: After controlling for confounders, 5 µg/m increase in long-term ambient PM2.5 was associated with 6% higher IL-6 (95% confidence interval = 2%, 9%), and 40 parts per billion increase in long-term NOx was associated with 7% (95% confidence interval = 2%, 13%) higher level of D-dimer. PM2.5 measured at day of blood draw was associated with CRP, fibrinogen, and E-selectin. There were no other positive associations between blood markers and short- or long-term air pollution. CONCLUSIONS: These data are consistent with the hypothesis that long-term exposure to air pollution is related to some markers of inflammation and fibrinolysis.

The short-term association of selected components of fine particulate matter and mortality in the Denver Aerosol Sources and Health (DASH) study.

BACKGROUND: Associations of short-term exposure to fine particulate matter (PM2.5) with daily mortality may be due to specific PM2.5 chemical components. Daily concentrations of PM2.5 components were measured over five years in Denver to investigate whether specific PM2.5 components are associated with daily mortality. METHODS: Daily counts of total and cause-specific deaths were obtained for the 5-county Denver metropolitan region from 2003 through 2007. Daily 24-hour concentrations of PM2.5, elemental carbon (EC), organic carbon (OC), sulfate and nitrate were measured at a central residential monitoring site. Using generalized additive models, we estimated relative risks (RRs) of daily death counts for daily PM2.5 and four PM2.5 component concentrations at single and distributed lags between the current and three previous days, while controlling for longer-term time trend and meteorology. RESULTS: RR of total non-accidental mortality for an inter-quartile increase of 4.55 µg/m(3) in PM2.5 distributed over 4 days was 1.012 (95 % confidence interval: 0.999, 1.025); RRs for EC and OC were larger (1.024 [1.005, 1.043] and 1.020 [1.000, 1.040] for 0.33 and 1.67 µg/m(3) increases, respectively) than those for sulfate and nitrate. We generally did not observe associations with cardiovascular and respiratory mortality except for associations with ischemic heart disease mortality at lags 3 and 0-3 depending on the component. In addition, there were associations with cancer mortality, particularly for EC and OC, possibly reflecting advanced deaths of a frail population. CONCLUSIONS: PM2.5 components possibly from combustion-related sources are more strongly associated with daily mortality than are secondary inorganic aerosols.

Development of Long-term Spatiotemporal Models for Ambient Ozone in Six Metropolitan regions of the United States: The MESA Air Study.

BACKGROUND: Current epidemiologic studies rely on simple ozone metrics which may not appropriately capture population ozone exposure. For understanding health effects of long-term ozone exposure in population studies, it is advantageous for exposure estimation to incorporate the complex spatiotemporal pattern of ozone concentrations at fine scales. OBJECTIVE: To develop a geo-statistical exposure prediction model that predicts fine scale spatiotemporal variations of ambient ozone in six United States metropolitan regions. METHODS: We developed a modeling framework that estimates temporal trends from regulatory agency and cohort-specific monitoring data from MESA Air measurement campaigns and incorporates land use regression with universal kriging using predictor variables from a large geographic database. The cohort-specific data were measured at home and community locations. The framework was applied in estimating two-week average ozone concentrations from 1999 to 2013 in models of each of the six MESA Air metropolitan regions. RESULTS: Ozone models perform well in both spatial and temporal dimensions at the agency monitoring sites in terms of prediction accuracy. City-specific leave-one (site)-out cross-validation R2 accounting for temporal and spatial variability ranged from 0.65 to 0.88 in the six regions. For predictions at the home sites, the R2 is between 0.60 and 0.91 for cross-validation that left out 10% of home sites in turn. The predicted ozone concentrations vary substantially over space and time in all the metropolitan regions. CONCLUSION: Using the available data, our spatiotemporal models are able to accurately predict long-term ozone concentrations at fine spatial scales in multiple regions. The model predictions will allow for investigation of the long-term health effects of ambient ozone concentrations in future epidemiological studies.

Ambient air pollution exposure and incident adult asthma in a nationwide cohort of U.S. women.

RATIONALE: Limited prior data suggest an association between traffic-related air pollution and incident asthma in adults. No published studies assess the effect of long-term exposures to particulate matter less than 2.5 µm in diameter (PM2.5) on adult incident asthma. OBJECTIVES: To estimate the association between ambient air pollution exposures (PM2.5 and nitrogen dioxide, NO2) and development of asthma and incident respiratory symptoms. METHODS: The Sister Study is a U.S. cohort study of risk factors for breast cancer and other health outcomes (n = 50,884) in sisters of women with breast cancer (enrollment, 2003-2009). Annual average (2006) ambient PM2.5 and NO2 concentrations were estimated at participants' addresses, using a national land-use/kriging model incorporating roadway information. Outcomes at follow-up (2008-2012) included incident self-reported wheeze, chronic cough, and doctor-diagnosed asthma in women without baseline symptoms. MEASUREMENTS AND MAIN RESULTS: Adjusted analyses included 254 incident cases of asthma, 1,023 of wheeze, and 1,559 of chronic cough. For an interquartile range (IQR) difference (3.6 µg/m(3)) in estimated PM2.5 exposure, the adjusted odds ratio (aOR) was 1.20 (95% confidence interval [CI] = 0.99-1.46, P = 0.063) for incident asthma and 1.14 (95% CI = 1.04-1.26, P = 0.008) for incident wheeze. For NO2, there was evidence for an association with incident wheeze (aOR = 1.08, 95% CI = 1.00-1.17, P = 0.048 per IQR of 5.8 ppb). Neither pollutant was significantly associated with incident cough (PM2.5: aOR = 0.95, 95% CI = 0.88-1.03, P = 0.194; NO2: aOR = 1.00, 95% CI = 0.93-1.07, P = 0.939). CONCLUSIONS: Results suggest that PM2.5 exposure increases the risk of developing asthma and that PM2.5 and NO2 increase the risk of developing wheeze, the cardinal symptom of asthma, in adult women.

Individual-level concentrations of fine particulate matter chemical components and subclinical atherosclerosis: a cross-sectional analysis based on 2 advanced exposure prediction models in the multi-ethnic study of atherosclerosis.

Long-term exposure to outdoor particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) has been associated with cardiovascular morbidity and mortality. The chemical composition of PM2.5 that may be most responsible for producing these associations has not been identified. We assessed cross-sectional associations between long-term concentrations of PM2.5 and 4 of its chemical components (sulfur, silicon, elemental carbon, and organic carbon (OC)) and subclinical atherosclerosis, measured as carotid intima-media thickness (CIMT) and coronary artery calcium, between 2000 and 2002 among 5,488 Multi-Ethnic Study of Atherosclerosis participants residing in 6 US metropolitan areas. Long-term concentrations of PM2.5 components at participants' homes were predicted using both city-specific spatiotemporal models and a national spatial model. The estimated differences in CIMT associated with interquartile-range increases in sulfur, silicon, and OC predictions from the spatiotemporal model were 0.022 mm (95% confidence interval (CI): 0.014, 0.031), 0.006 mm (95% CI: 0.000, 0.012), and 0.026 mm (95% CI: 0.019, 0.034), respectively. Findings were generally similar using the national spatial model predictions but were often sensitive to adjustment for city. We did not find strong evidence of associations with coronary artery calcium. Long-term concentrations of sulfur and OC, and possibly silicon, were associated with CIMT using 2 distinct exposure prediction modeling approaches.

Infants suspected to have very-long chain acyl-CoA dehydrogenase deficiency from newborn screening.

Very long-chain acyl-CoA dehydrogenase deficiency (VLCADD) is a fatty acid oxidation disorder with widely varying presentations that has presented a significant challenge to newborn screening (NBS). The Western States Regional Genetics Services Collaborative developed a workgroup to study infants with NBS positive for VLCADD. We performed retrospective analysis of newborns with elevated C14:1-acylcarnitine on NBS in California, Oregon, Washington, and Hawai'i including available confirmatory testing and clinical information. Overall, from 2,802,504 children screened, there were 242 cases screen-positive for VLCADD. There were 34 symptomatic true positive cases, 18 asymptomatic true positives, 112 false positives, 55 heterozygotes, 11 lost to follow-up, and 12 other disorders. One in 11,581 newborns had an abnormal NBS for suspected VLCADD. Comparison of analytes and analyte ratios from the NBS demonstrated statistically significant differences between true positive and false positive groups for C14:1, C14, C14:1/C2, and C14:1/C16. The positive predictive value for all true positive cases was 94%, 54%, and 23% when C14:1 was ≥2.0 µM, ≥1.0 µM, and ≥0.7 µM, respectively. Sequential post-analytical analysis could reduce the referral rate in 25.8% of cases. This study is the largest reported follow-up of infants with NBS screen-positive results for suspected VLCADD and demonstrates the necessity of developing comprehensive and consistent long-term follow-up NBS systems. Application of clinical information revealed differences between symptomatic and asymptomatic children with VLCADD. Comparison of NBS analytes and analyte ratios may be valuable in developing more effective diagnostic algorithms.

Fine particulate air pollution and the progression of carotid intima-medial thickness: a prospective cohort study from the multi-ethnic study of atherosclerosis and air pollution.

BACKGROUND: Fine particulate matter (PM2.5) has been linked to cardiovascular disease, possibly via accelerated atherosclerosis. We examined associations between the progression of the intima-medial thickness (IMT) of the common carotid artery, as an indicator of atherosclerosis, and long-term PM2.5 concentrations in participants from the Multi-Ethnic Study of Atherosclerosis (MESA). METHODS AND RESULTS: MESA, a prospective cohort study, enrolled 6,814 participants at the baseline exam (2000-2002), with 5,660 (83%) of those participants completing two ultrasound examinations between 2000 and 2005 (mean follow-up: 2.5 years). PM2.5 was estimated over the year preceding baseline and between ultrasounds using a spatio-temporal model. Cross-sectional and longitudinal associations were examined using mixed models adjusted for confounders including age, sex, race/ethnicity, smoking, and socio-economic indicators. Among 5,362 participants (5% of participants had missing data) with a mean annual progression of 14 µm/y, 2.5 µg/m(3) higher levels of residential PM2.5 during the follow-up period were associated with 5.0 µm/y (95% CI 2.6 to 7.4 µm/y) greater IMT progressions among persons in the same metropolitan area. Although significant associations were not found with IMT progression without adjustment for metropolitan area (0.4 µm/y [95% CI -0.4 to 1.2 µm/y] per 2.5 µg/m(3)), all of the six areas showed positive associations. Greater reductions in PM2.5 over follow-up for a fixed baseline PM2.5 were also associated with slowed IMT progression (-2.8 µm/y [95% CI -1.6 to -3.9 µm/y] per 1 µg/m(3) reduction). Study limitations include the use of a surrogate measure of atherosclerosis, some loss to follow-up, and the lack of estimates for air pollution concentrations prior to 1999. CONCLUSIONS: This early analysis from MESA suggests that higher long-term PM2.5 concentrations are associated with increased IMT progression and that greater reductions in PM2.5 are related to slower IMT progression. These findings, even over a relatively short follow-up period, add to the limited literature on air pollution and the progression of atherosclerotic processes in humans. If confirmed by future analyses of the full 10 years of follow-up in this cohort, these findings will help to explain associations between long-term PM2.5 concentrations and clinical cardiovascular events.

Particulate matter components and subclinical atherosclerosis: common approaches to estimating exposure in a Multi-Ethnic Study of Atherosclerosis cross-sectional study.

BACKGROUND: Concentrations of outdoor fine particulate matter (PM2.5) have been associated with cardiovascular disease. PM2.5 chemical composition may be responsible for effects of exposure to PM2.5. METHODS: Using data from the Multi-Ethnic Study of Atherosclerosis (MESA) collected in 2000-2002 on 6,256 US adults without clinical cardiovascular disease in six U.S. metropolitan areas, we investigated cross-sectional associations of estimated long-term exposure to total PM2.5 mass and PM2.5 components (elemental carbon [EC], organic carbon [OC], silicon and sulfur) with measures of subclinical atherosclerosis (coronary artery calcium [CAC] and right common carotid intima-media thickness [CIMT]). Community monitors deployed for this study from 2007 to 2008 were used to estimate exposures at baseline addresses using three commonly-used approaches: (1) nearest monitor (the primary approach), (2) inverse-distance monitor weighting and (3) city-wide average. RESULTS: Using the exposure estimate based on nearest monitor, in single-pollutant models, increased OC (effect estimate [95% CI] per IQR: 35.1 µm [26.8, 43.3]), EC (9.6 µm [3.6,15.7]), sulfur (22.7 µm [15.0,30.4]) and total PM2.5 (14.7 µm [9.0,20.5]) but not silicon (5.2 µm [-9.8,20.1]), were associated with increased CIMT; in two-pollutant models, only the association with OC was robust to control for the other pollutants. Findings were generally consistent across the three exposure estimation approaches. None of the PM measures were positively associated with either the presence or extent of CAC. In sensitivity analyses, effect estimates for OC and silicon were particularly sensitive to control for metropolitan area. CONCLUSION: Employing commonly-used exposure estimation approaches, all of the PM2.5 components considered, except silicon, were associated with increased CIMT, with the evidence being strongest for OC; no component was associated with increased CAC. PM2.5 chemical components, or other features of the sources that produced them, may be important in determining the effect of PM exposure on atherosclerosis. These cross-sectional findings await confirmation in future work employing longitudinal outcome measures and using more sophisticated approaches to estimating exposure.

Positive matrix factorization of a 32-month series of daily PM2.5 speciation data with incorporation of temperature stratification.

This study presents source apportionment results for PM2.5 from applying positive matrix factorization (PMF) to a 32-month series of daily PM2.5 compositional data from Denver, CO, including concentrations of sulfate, nitrate, bulk elemental carbon (EC) and organic carbon (OC), and 51 organic molecular markers (OMMs). An optimum 8-factor solution was determined primarily based on the interpretability of the PMF results and rate of matching factors from bootstrapped PMF solutions with those from the base case solution. These eight factors were identified as inorganic ion, n-alkane, EC/sterane, light n-alkane/polycyclic aromatic hydrocarbon (PAH), medium alkane/alkanoic acid, PAH, winter/methoxyphenol and summer/odd n-alkane. The inorganic ion factor dominated the reconstructed PM2.5 mass (sulfate + nitrate + EC + OC) in cold periods (daily average temperature < 10 °C; 43.7% of reconstructed PM2.5 mass) whereas the summer/odd n-alkane factor dominated in hot periods (> 20 °C; 53.1%). The two factors had comparable relative contributions of 26.5% and 27.1% in warm periods with temperatures between 10 °C and 20 °C. Each of the seven factors resolved in a previous study (Dutton et al., 2010b) using a 1-year data set from the same location matches one factor from the current work based on comparing factor profiles. Six out of the seven matched pairs of factors are linked to similar source classes as suggested by the strong correlations between factor contributions (r = 0.89 - 0.98). Temperature-stratified source apportionment was conducted for three subsets of the data in the current study, corresponding to the cold, warm and hot periods mentioned above. The cold period (7-factor) solution exhibited a similar distribution of reconstructed PM2.5 mass as the full data set solution. The factor contributions of the warm period (7-factor) solution were well correlated with those from the full data set solution (r = 0.76 - 0.99). However, the reconstructed PM2.5 mass was distributed more to inorganic ion, n-alkane and medium alkane/alkanoic acid factors in the warm period solution than in the full data set solution. For the hot period (6-factor) solution, PM2.5 mass distribution was quite different from that of the full data set solution, as illustrated by regression slopes as low as 0.2 and as high as 4.8 of each matched pair of factors across the two solutions.