Exhaled nitric oxide in children with asthma and short-term PM2.5 exposure in Seattle

A Comparative Analysis on Indoor and Outdoor PM2.5 and Their Hourly Associations with Acute Respiratory Inflammation Among College Students in Lhasa

Ambient concentrations are commonly used as proxies for personal PM2.5 exposure in epidemiological studies, despite indoor settings being the places where people spend most of their time. In a panel study of 110 nonsmoking, healthy college students in Lhasa, Tibet, indoor PM2.5 was monitored using calibrated low-cost sensors for two multiweek periods, in over 40 dormitories where participants resided. We also repeatedly measured fractional exhaled nitric oxide (FeNO), an acute respiratory inflammation biomarker, for each participant. Time-averaged indoor PM2.5 concentrations in individual dormitories ranged from 3.2 to 30 μg/m3 in the summer and from 3.6 to 57 μg/m3 in the fall, in most cases exceeding the outdoor level (4.3 and 4.9 μg/m3, respectively). The hourly mean indoor PM2.5 concentrations displayed a clear trimodal diel pattern, with peaks coincident with periods of increased activities. Further questionnaire-based analysis suggests that incense burning and smoking contributed to elevated levels of indoor PM2.5. Overnight PM2.5 levels in the dormitories were significantly associated with increased FeNO the following morning, with the effects attenuated as the hourly lag increased. In contrast, inconclusive associations were observed for ambient PM2.5. The results demonstrate that disregarding indoor exposure can result in biased estimates of acute health effects of PM2.5 in low PM2.5 areas.

Association between respiratory tract deposited dose of size-segregated PM and FeNO based on individual exposure assessment for Korean children

FeNO (fractional exhaled nitric oxide) is a crucial marker to understand children's respiratory diseases such as asthma, and severity may vary depending on PM diameter and respiratory tract region. This study investigates the relationship between size-segregated respiratory deposited PM dose and FeNO for children. Size-segregated PM (PM1.0, PM1.0-2.5, and PM2.5-10.0) and FeNO were measured for eighty children based on individual exposure assessment in five consecutive days. Individual physical activity was measured by an accelerometer device. Accordingly, a dosimetry model estimated the respiratory deposited dose by PM diameter in the extrathoracic (ET), tracheobronchial (TB), and pulmonary (PUL) regions. A linear mixed model (LMM) with distributed lag non-linear model (DLNM) was used for analysis. The effects of home environment and traffic-related factors were also examined for sensitivity analysis. We found that IQR increases of PM2.5-10.0 and PM1.0 were associated with 15.1 % (95 % CI: 3.5, 28.1) and 15.9 % (95 % CI: 2.7, 30.9) FeNO increase in respiratory Total region in 0-12 h lag. In cumulative lag 0-24 h, PM1.0 was only associated with FeNO increase: 16.6 % (95 % CI: 1.5, 34.1) in total region. No association was observed in lag 12-24 h. PM2.5-10.0 was related to short-term airway inflammation in the upper respiratory tract whereas PM1.0 has a cumulative effect on both the upper and lower respiratory tract. In sensitivity analysis, PM2.5-10.0 was associated with a 0-12 h lag, whereas both PM2.5-10.0 and PM1.0 were associated with a cumulative lag of 0-24 h. Both home environment and traffic-related factors showed a synergetic effect with PM1.0 in short-term exposure and an antagonistic effect with PM2.5-10.0 in long-term exposure. This study highlights that airway inflammation depends on PM sizes, exposure durations, and respiratory tract regions.

Short-term, lagged association of airway inflammation, lung function, and asthma symptom score with PM2.5 exposure among schoolchildren within a high air pollution region in South Africa

Background

Asthma affects millions of people globally, and high levels of air pollution aggravate asthma occurrence. This study aimed to determine the association between short-term lagged PM2.5 exposure and airway inflammation, lung function, and asthma symptom scores among schoolchildren in communities in the Highveld high-pollution region in South Africa.

Methods

A cross-sectional study was conducted among schoolchildren aged 9-14 years in six communities in the Highveld region in South Africa, between October 2018 and February 2019. A NIOX 200 instrument was used to measure fractional exhaled nitric oxide (FeNO). Lung function indices (forced expiratory volume in one second [FEV1]; forced vital capacity [FVC] and FEV1/FVC) were collected using spirometry and the percent of predicted of these was based on the reference equations from the Global Lung Initiative, without ethnic correction. These values were further analyzed as binary outcomes following relevant thresholds (lower limits of normal for lung function and a cutoff of 35 ppb for FeNO). Asthma symptoms were used to create the asthma symptom score. Daily averages of PM2.5 data for the nearest monitoring station located in each community, were collected from the South African Air Quality Information System and created short-term 5-day lag PM2.5 concentrations. Additional reported environmental exposures were collected using standardized instruments.

Results

Of the 706 participating schoolchildren, only 1.13% of the participants had doctor-diagnosed asthma, compared to a prevalence of 6.94% with an asthma symptom score suggestive of asthma. Lag 1 (odds ratio [OR]: 1.01; 95% confidence interval [CI]: 1.00, 1.02, P = 0.039) and 5-day average lagged PM2.5 (OR: 1.02; 95% CI: 0.99, 1.04, P = 0.050) showed increased odds of the FeNO > 35 ppb. Lung function parameters (FEV1 < lower limit of normal [LLN] [OR: 1.02, 95% CI: 1.00, 1.03, P = 0.018], and FEV1/FVC < LLN [OR: 1.01; 95% CI: 1.00, 1.02, P < 0.001]) and asthma symptom score ≥ 2 (OR: 1.02; 95% CI: 1.00, 1.04, P = 0.039) also showed significant associations with lag 2, lag 4 and lag 1 of PM2.5, respectively.

Conclusion

Lagged PM2.5 exposure was associated with an increased odds of airway inflammation and an increased odds of lung function parameters below the LLN particularly for the later lags, but a significant dose-response relationship across the entire sample was not consistent.

Associations between fine particulate air pollution with small-airway inflammation: A nationwide analysis in 122 Chinese cities

Alveolar nitric oxide is a non-invasive indicator of small-airway inflammation, a key pathophysiologic mechanism underlying lower respiratory diseases. However, no epidemiological studies have investigated the impact of fine particulate matter (PM2.5) exposure on the concentration of alveolar nitric oxide (CANO). To explore the associations between PM2.5 exposure in multiple periods and CANO, we conducted a nationwide cross-sectional study in 122 Chinese cities between 2019 and 2021. Utilizing a satellite-based model with a spatial resolution of 1 × 1 km, we matched long-term, mid-term, and short-term PM2.5 exposure for 28,399 individuals based on their home addresses. Multivariable linear regression models were applied to estimate the associations between PM2.5 at multiple exposure windows and CANO. Stratified analyses were also performed to identify potentially vulnerable subgroups. We found that per interquartile range (IQR) unit higher in 1-year average, 1-month average, and 7-day average PM2.5 concentration was significantly associated with increments of 17.78% [95% confidence interval (95%CI): 12.54%, 23.26%], 8.76% (95%CI: 7.35%, 10.19%), and 4.00% (95%CI: 2.81%, 5.20%) increment in CANO, respectively. The exposure-response relationship curves consistently increased with the slope becoming statistically significant beyond 20 μg/m3. Males, children, smokers, individuals with respiratory symptoms or using inhaled corticosteroids, and those living in Southern China were more vulnerable to PM2.5 exposure. In conclusion, our study provided novel evidence that PM2.5 exposure in long-term, mid-term, and short-term periods could significantly elevate small-airway inflammation represented by CANO. Our results highlight the significance of CANO measurement as a non-invasive tool for early screening in the management of PM2.5-related inflammatory respiratory diseases.

Genetic susceptibility to airway inflammation and exposure to short-term outdoor air pollution

BACKGROUND

Air pollution is a large environmental health hazard whose exposure and health effects are unequally distributed among individuals. This is, at least in part, due to gene-environment interactions, but few studies exist. Thus, the current study aimed to explore genetic susceptibility to airway inflammation from short-term air pollution exposure through mechanisms of gene-environment interaction involving the SFTPA, GST and NOS genes.

METHODS

Five thousand seven hundred two adults were included. The outcome measure was fraction of exhaled nitric oxide (FeNO), at 50 and 270 ml/s. Exposures were ozone (O₃), particulate matter < 10 µm (PM₁₀), and nitrogen dioxide (NO₂) 3, 24, or 120-h prior to FeNO measurement. In the SFTPA, GST and NOS genes, 24 single nucleotide polymorphisms (SNPs) were analyzed for interaction effects. The data were analyzed using quantile regression in both single-and multipollutant models.

RESULTS

Significant interactions between SNPs and air pollution were found for six SNPs (p < 0.05): rs4253527 (SFTPA1) with O₃ and NO_x, rs2266637 (GSTT1) with NO₂, rs4795051 (NOS2) with PM₁₀, NO₂ and NO_x, rs4796017 (NOS2) with PM₁₀, rs2248814 (NOS2) with PM₁₀ and rs7830 (NOS3) with NO₂. The marginal effects on FeNO for three of these SNPs were significant (per increase of 10 µg/m³):rs4253527 (SFTPA1) with O₃ (β: 0.155, 95%CI: 0.013-0.297), rs4795051 (NOS2) with PM₁₀ (β: 0.073, 95%CI: 0.00-0.147 (single pollutant), β: 0.081, 95%CI: 0.004-0.159 (multipollutant)) and NO₂ (β: -0.084, 95%CI: -0.147; -0.020 (3 h), β: -0.188, 95%CI: -0.359; -0.018 (120 h)) and rs4796017 (NOS2) with PM₁₀ (β: 0.396, 95%CI: 0.003-0.790).

CONCLUSIONS

Increased inflammatory response from air pollution exposure was observed among subjects with polymorphisms in SFTPA1, GSTT1, and NOS genes, where O₃ interacted with SFTPA1 and PM10 and NO₂/NO_x with the GSTT1 and NOS genes. This provides a basis for the further exploration of biological mechanisms as well as the identification of individuals susceptible to the effects of outdoor air pollution.

Association of inflammation and lung function decline caused by personal PM2.5 exposure: a machine learning approach in time-series data

Numerous studies focused on the association between lung function impairment and inflammation caused by fine particulate matter (PM_2.5), but the causal relationships are difficult to clarify. In the current study, twenty healthy Chinese young adults who participated in 7 days of observation every four seasons were enrolled, and autoregression models (AM) and classification and regression trees (CART) in a machine learning framework were applied to analyze the association among PM_2.5 exposure, inflammation, and lung function from a data structure perspective. There were strong cross-correlations between personal dose of PM_2.5 (Dw) and lung functions (vital capacity (VC), forced vital capacity (FVC), etc.). These cross-correlation coefficients were associated with inflammatory indicators (uteroglobin (UG), serum amyloid (SAA), and fractional exhaled nitric oxide (FeNO)). CART reported that inflammatory indicators UG and SAA had the predictive ability of the directional association between Dw and FVC at 1-day lag and that high levels of UG and SAA predicted that PM_2.5 exposure induced lung function decline. Consistently, lower lung function indicators at a 2-day lag after personal PM_2.5 exposure predicted the high value of inflammatory indicator FeNO. Taken together, we applied machine learning algorithms to analyze repeated measurement data, finding that inflammation and lung function decline caused by PM_2.5 could affect each other.

A systematic review and meta-analysis of intraday effects of ambient air pollution and temperature on cardiorespiratory morbidities: First few hours of exposure matters to life

BACKGROUND

A growing number of studies have reported an increased risk of cardiovascular disease (CVD) and respiratory disease (RD) within hours after exposure to ambient air pollution or temperature. We assemble published evidence on the sub-daily associations of CVD and RD with ambient air pollution and temperature.

METHODS

Databases of PubMed and Web of Science were searched for original case-crossover and time-series designs of English articles examining the intra-day effects of ambient air pollution [particulate matter with aerodynamic diameter ≤2.5 μm (PM_2.5), ≤10 μm (PM₁₀), 2.5-10μm (PM_10-2.5), and < 7 μm (SPM), O₃, SO₂, NO₂, CO, and NO] and temperatures (heat and cold) on cardiorespiratory diseases within 24 h after exposure in the general population by comparing with exposure at different exposure levels or periods. Meta-analyses were conducted to pool excess risks (ERs, absolute percentage increase in risk) of CVD and RD morbidities associated with an increase of 10 μg/m³ in particulate matters, 0.1 ppm in CO, and 10 ppb in other gaseous pollutants.

FINDINGS

Final analysis included thirty-three papers from North America, Europe, Oceania, and Asia. Meta-analysis found an increased risk of total CVD morbidity within 3 h after exposure to PM_2.5 [ER%: 2.65% (95% CI: 1.00% to 4.34%)], PM_10-2.5 [0.31% (0.02% to 0.59%)], O₃ [1.42% (0.14% to 2.73%)], and CO [0.41% (0.01% to 0.81%)]. The risk of total RD morbidity elevated at lag 7-12 h after exposure to PM_2.5 [0.69% (0.14% to 1.24%)] and PM₁₀ [0.38% (0.02% to 0.73%)] and at lag 12-24 h after exposure to SO₂ [2.68% (0.94% to 4.44%)]. Cause-specific CVD analysis observed an increased risk of myocardial infarction morbidity within 6 h after exposure to PM_2.5, PM₁₀, and NO₂, and an increased risk of out-of-hospital cardiac arrest morbidity within 12 h after exposure to CO. Risk of total CVD also increased within 24 h after exposure to heat.

INTERPRETATION

This study supports a sudden risk increase of cardiorespiratory diseases within a few hours after exposure to air pollution or heat, and some acute and highly lethal diseases such as myocardial infarction and cardiac arrest could be affected within a shorter time.

FUNDING

The National Natural Science Foundation of China (Grant No. 42105165; 81773518), the High-level Scientific Research Foundation of Anhui Medical University (Grant No. 0305044201), and the Discipline Construction of Anhui Medical University (Grant No. 0301001836).

Associations of short-term PM2.5 exposures with nasal oxidative stress, inflammation and lung function impairment and modification by GSTT1-null genotype: A panel study of the retired adults

PM_2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) is a major urban air pollutant worldwide. Its effects on the respiratory system of the susceptible population have been less characterized. This study aimed to estimate the association of short-term PM_2.5 exposure with respiratory outcomes of the retired adults, and to examine whether these associations were stronger among the subjects with GSTT-null genotype. 32 healthy subjects (55-77 years) were recruited for five follow-up examinations. Ambient concentrations of PM_2.5 were monitored consecutively for 7 days prior to physical examination. Pulmonary outcomes including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV₁), peak expiratory flow (PEF), and fractional exhaled nitric oxide (FeNO), and nasal fluid concentrations of 8-epi-prostaglandin F2 alpha (8-epi-PGF2α), tumor necrosis factor-α (TNF-α), interleukin-8 (IL-8) and IL-1β were measured. A linear mixed-effect model was introduced to evaluate the associations of PM_2.5 concentrations with respiratory outcomes. Additionally, GSTT1 genotype-based stratification was performed to characterize modification on PM_2.5-related respiratory outcomes. We found that a 10 μg/m³ increase in PM_2.5 was associated with decreases of 0.52 L (95% confidence interval [CI]: -1.04, -0.002), 0.64 L (95% CI: -1.13, -0.16), 0.1 (95% CI: -0.23, 0.04) and 2.87 L/s (95% CI: -5.09, -0.64) in FVC, FEV₁, FEV₁/FVC ratio and PEF at lag 2, respectively. Meanwhile, marked increases of 80.82% (95% CI: 5.13%, 156.50%) in IL-8, 77.14% (95% CI: 1.88%, 152.40%) in IL-1β and 67.87% (95% CI: 14.85%, 120.88%) in 8-epi-PGF2α were observed as PM_2.5 concentration increased by 10 μg/m³ at lag 2. Notably, PM_2.5-associated decreases in FVC and PEF and increase in FeNO were stronger among the subjects with GSTT1-null genotype. In summary, short-term exposure to PM_2.5 is associated with nasal inflammation, oxidative stress and lung function reduction in the retired subjects. Lung function reduction and inflammation are stronger among the subjects with GSTT1-null genotype.

The effect of weather, air pollution and seasonality on the number of patient visits for epileptic seizures: A population-based time-series study

OBJECTIVE

The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures.

METHODS

Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7 days' lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined.

RESULTS

The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH₄, and NO. Six air pollutants, namely CH₄, NO, CO, NO₂, PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R² = 0.422).

CONCLUSION

The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases.

Intraday effects of outdoor air pollution on acute upper and lower respiratory infections in Australian children

Children's respiratory health are particularly vulnerable to outdoor air pollution, but evidence is lacking on the very acute effects of air pollution on the risk of acute upper respiratory infections (AURI) and acute lower respiratory infections (ALRI) in children. This study aimed to evaluate the risk of cause-specific AURI and ALRI, in children within 24 h of exposure to air pollution. We obtained data on emergency cases, including 11,091 AURI cases (acute pharyngitis, acute tonsillitis, acute obstructive laryngitis and epiglottitis, and unspecified acute upper respiratory infections) and 11,401 ALRI cases (pneumonia, acute bronchitis, acute bronchiolitis, unspecified acute lower respiratory infection) in Brisbane, Australia, 2013-2015. A time-stratified case-crossover analysis was used to examine the hourly association of AURI and ALRI with high concentration (95th percentile) of four air pollutants (particulate matters with aerodynamic diameter <10 μm (PM₁₀) and <2.5 μm (PM_2.5), ozone (O₃), nitrogen dioxide (NO₂)). We observed increased risk of acute tonsillitis associated with PM_2.5 within 13-24 h (odds ratio (OR), 1.45; 95% confidence interval [CI], 1.02-2.06) and increased risk of unspecified acute upper respiratory infections related to O₃ within 2-6 h (OR, 1.38, 95%CI, 1.12-1.70), NO₂ within 1 h (OR, 1.19; 95%CI, 1.01-1.40), and PM_2.5 within 7-12 h (OR, 1.21; 95%CI, 1.02-1.43). Cold season and nigh-time air pollution has greater effects on AURI, whereas greater risk of ALRI was seen in warm season and daytime. Our findings suggest exposures to particulate and gaseous air pollution may transiently increase risk of AURI and ALRI in children within 24 h. Prevention measures aimed at protecting children's respiratory health should consider the very acute effects of air pollution.

Factors affecting variability in gaseous and particle microenvironmental air pollutant concentrations in Hong Kong primary and secondary schools

School-age children are particularly susceptible to exposure to air pollutants. To quantify factors affecting children's exposure at school, indoor and outdoor microenvironmental air pollutant concentrations were measured at 32 selected primary and secondary schools in Hong Kong. Real-time PM₁₀ , PM_2.5 , NO_2, and O₃ concentrations were measured in 76 classrooms and 23 non-classrooms. Potential explanatory factors related to building characteristics, ventilation practice, and occupant activities were measured or recorded. Their relationship with indoor measured concentrations was examined using mixed linear regression models. Ten factors were significantly associated with indoor microenvironmental concentrations, together accounting for 74%, 61%, 46%, and 38% of variations observed for PM_2.5 , PM₁₀ , O_3, and NO₂ microenvironmental concentrations, respectively. Outdoor concentration is the single largest predictor for indoor concentrations. Infiltrated outdoor air pollution contributes to 90%, 70%, 75%, and 50% of PM_2.5 , PM₁₀ , O_3, and NO₂ microenvironmental concentrations, respectively, in classrooms during school hours. Interventions to reduce indoor microenvironmental concentrations can be prioritized in reducing ambient air pollution and infiltration of outdoor pollution. Infiltration factors derived from linear regression models provide useful information on outdoor infiltration and help address the gap in generalizable parameter values that can be used to predict school microenvironmental concentrations.

Comparison of Different Missing-Imputation Methods for MAIAC (Multiangle Implementation of Atmospheric Correction) AOD in Estimating Daily PM2.5 Levels

The immense problem of missing satellite aerosol retrievals (Aerosol Optical Depth, (AOD)) detrimentally affects the prediction ability of ground-level PM2.5 concentrations and may lead to unavoidable biases. An appropriate missing-imputation method has not been well developed to date. This study developed a two-stage approach (AOD-imputation stage and PM2.5-prediction stage) to predict short-term PM2.5 exposure in mainland China from 2013–2018. At the AOD-imputation stage, geostatistical methods and machine learning (ML) algorithms were examined to interpolate 1 km satellite aerosol retrievals. At the PM2.5-prediction stage, the daily levels of PM2.5 were predicted at a resolution of 1 km, based on interpolated AOD and meteorological data. The statistical performances of the different interpolation methods were comprehensively compared at each stage. The original coverage of retrieved AOD was 15.46% on average. For the AOD-imputation stage, ML methods produced a higher coverage (98.64%) of AOD than geostatistical methods (21.43–87.31%). Among ML algorithms, random forest (RF) or extreme gradient boosted (XG-interpolated) AOD produced better interpolated quality (CV R2 = 0.89 and 0.85) than other algorithms (0.49–0.78), but XGBoost required only 15% of the computing time of RF. For the PM2.5 predicted stage, neither RF-AOD nor XG-AOD could guarantee higher accuracy in PM2.5 estimations (CV R2 = 0.88 (RF or XG-AOD) compared to 0.85 (original)), or more stable spatial and temporal extrapolation (spatial, (temporal) CV R2 = 0.83 (0.83), 0.82 (0.82), and 0.65 (0.61) for RF, XG, and original). For the AOD-imputation stage, the missing-filled efficiency depended more on external information, while the missing-filled accuracy relied more on model structure. For the PM2.5 predicted stage, efficient AOD interpolation (or the ability to eliminate the missing data) was a precondition for the stable spatial and temporal extrapolation, while the quality of interpolated AOD showed less significant improvements. It was found that XG-AOD is a better choice to estimate daily PM2.5 exposure in health assessments.

Sub-Daily Exposure to Fine Particulate Matter and Ambulance Dispatches during Wildfire Seasons: A Case-Crossover Study in British Columbia, Canada

BACKGROUND

Exposure to fine particulate matter (PM2.5) during wildfire seasons has been associated with adverse health outcomes. Previous studies have focused on daily exposure, but PM2.5 levels in smoke events can vary considerably within 1 d.

OBJECTIVES

We aimed to assess the immediate and lagged relationship between sub-daily exposure to PM2.5 and acute health outcomes during wildfire seasons in British Columbia.

METHODS

We used a time-stratified case-crossover study design to evaluate the association between modeled hourly PM2.5 and ambulance dispatches during wildfire seasons from 2010 to 2015. Distributed lag nonlinear models were used to estimate the lag-specific and cumulative odds ratios (ORs) at lags from 1 to 48 h. We examined the relationship for all dispatches and dispatches related to respiratory, circulatory, and diabetic conditions, identified by codes for ambulance dispatch (AD), paramedic assessment (PA) or hospital diagnosis (HD).

RESULTS

Increased respiratory health outcomes were observed within 1 h of exposure to a 10-μg/m3 increase in PM2.5. The 48-h cumulative OR [95% confidence interval (CI)] was 1.038 (1.009, 1.067) for the AD code Breathing Problems and 1.098 (1.013, 1.189) for PA code Asthma/COPD. The point estimates were elevated within 1 h for the PA code for Myocardial Infarction and HD codes for Ischemic Heart Disease, which had 24-h cumulative ORs of 1.104 (0.915, 1.331) and 1.069 (0.983, 1.162), respectively. The odds of Diabetic AD and PA codes increased over time to a cumulative 24-h OR of 1.075 (1.001, 1.153) and 1.104 (1.015, 1.202) respectively.

CONCLUSIONS

We found increased PM2.5 during wildfire seasons was associated with some respiratory and cardiovascular outcomes within 1 h following exposure, and its association with diabetic outcomes increased over time. Cumulative effects were consistent with those reported elsewhere in the literature. These results warrant further investigation and may have implications for the appropriate time scale of public health actions. https://doi.org/10.1289/EHP5792.

Effect of industrial point-source air pollutants on fractional exhaled nitric oxide in healthy volunteers

BACKGROUND

Few studies have examined the effects of industrial, fixed-site sources of air pollution on lung inflammation in nearby residents. We investigated the effects of short-term exposure to ambient air near a steel plant on the fractional exhaled concentration of nitric oxide (FeNO), a measure of airway inflammation, in healthy volunteers.

METHODS

A cross-over study design was used. Fifty-nine non-smoking participants (mean age 24 years) were randomly assigned to each of two 5-day exposure scenarios: breathing ambient air adjacent to a steel plant or 5 km away at a college campus site. FeNO and on-site air pollutants were measured daily. Mixed effects linear regression models were used for data analysis, adjusting for sex, temperature, humidity and day of week.

RESULTS

Compared with the college site, PM _2.5, ultrafine PM, SO₂, NO₂ and CO levels were significantly greater near the steel plant. FeNO was 15.3% (95% CI, 6.6%, 24.8%) higher near the plant compared to the college site.

CONCLUSIONS

Exposure to ambient air near a steel plant was associated with increased airway inflammation as measured by exhaled nitric oxide.

Investigation of Drug for Pulmonary Administration-Model Pulmonary Surfactant Monolayer Interactions Using Langmuir-Blodgett Monolayer and Molecular Dynamics Simulation: A Case Study of Ketoprofen

Pulmonary administration is widely used for the treatment of lung diseases. The interaction between drug molecules and pulmonary surfactants affects the efficacy of the drug directly. The location and distribution of drug molecules in a model pulmonary surfactant monolayer under different surface pressures can provide vivid information on the interaction between drug molecules and pulmonary surfactants during the pulmonary administration. Ketoprofen is a nonsteroidal anti-inflammatory drug for pulmonary administration. The effect of ketoprofen molecules on the lipid monolayer containing 1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine (DPPC) and 1,2-dipalmitoyl-sn-glycero-3-phospho-rac-glycerol (DPPG) is studied by surface pressure (π)-area (A) isotherms and compressibility modulus (C_s^-1)-surface pressure (π) isotherms. The location and distribution of ketoprofen molecules in a lipid monolayer under different surface pressures are explored by surface tension, density profile, radial distribution function (RDF), and the potential of mean force (PMF) simulated by molecular dynamics (MD) simulation. The introduction of ketoprofen molecules affects the properties of DPPC/DPPG monolayers and the location and distribution of ketoprofen molecules in monolayers with various surface pressures. The existence of ketoprofen molecules hinders the formation of liquid-condensed (LC) films and decreases the compressibility of DPPC/DPPG monolayers. The location and distribution of ketoprofen molecules in the lipid monolayer are affected by cation-π interaction between the choline group of lipids and the benzene ring of ketoprofen, the steric hindrance of the lipid head groups, and the hydrophobicity of ketoprofen molecule itself, comprehensively. The contact state of lipid head group with water is determined by surface pressure, which affects the interaction between drug molecules and lipids and further dominates the location and distribution of ketoprofen in the lipid monolayer. This work confirms that ketoprofen molecules can affect the property and the inner structure of DPPC/DPPG monolayers during breathing. Furthermore, the results obtained using a mixed monolayer containing two major pulmonary surfactants DPPC/DPPG and ketoprofen molecules will be helpful for the in-depth understanding of the mechanism of inhaled administration therapy.

PM2.5 affects establishment of immune tolerance in newborn mice by reducing PD-L1 expression

This study was conducted to determine whether exposure to particulate matter 2.5 (PM_2.5) affects the immune tolerance of neonatal mice via the regulation of PD-L1 expression. One-week-old BALB/c mice were exposed to PM_2.5 for 8 days. From day 8 to day 18, the mice were treated with 5 μg house dust mite (HDM) (i. n.) every two days. Adenovirus-carried PD-L1 overexpression vectors were infected into mice via nasal inhalation 6 days after exposure to PM_2.5. Airway hyperresponsiveness (AHR) was examined in mice 19 days after exposure to PM_2.5, and the related parameters of airway inflammation were studied on day 22. Co-exposure to PM_2.5 and HDM reduced PD-L1 expression but greatly increased infiltration of inflammatory cells, which was reversed by PD-L1 overexpression. Co-exposure to PM_2.5 and HDM also elevated serum IL-4, IL-5 and IL-13 levels and reduced TGF-β level. Exposure to PM_2.5 alone slightly increased the numbers of dendritic cells (DCs) but reduced the numbers of antigen-presenting cells expressing PD-L1 and Treg cells. Therefore, early exposure to PM_2.5 reduced PD-L1 expression in the lungs of neonatal mice, which interfered with immune tolerance establishment and subsequently resulted in allergic airway inflammation.

Different metrics (number, surface area, and volume concentration) of urban particles with varying sizes in relation to fractional exhaled nitric oxide (FeNO)

Background

There have been increasing concerns on potential health effects of ultrafine particles (UFP); but little is known as to what are the most biologically relevant metrics for these particles that make up very little mass concentration. We examined a range of particle metrics (number, surface area, active surface area, and volume concentration) in relation to fractional exhaled nitric oxide (FeNO), a well-established biomarker of pulmonary inflammation.

Methods

We conducted a panel study in 17 non-asthmatic children who attended schools and resided near a monitoring site at which particles in the size range of 3-800 nm were measured using a TDMPS and particles in the size range of 0.5 to 10 µm were measured using an APS. Particles were classified by size into the nucleation, Aitken, accumulation, or coarse mode, respectively, for calculating mode-specific number, surface area, active surface area, and volume concentrations. Each participating child was measured for FeNO daily for 30 days. We used linear mixed-effects models to assess the associations between various particle metrics and FeNO.

Results

In terms of number concentration, ambient particles in the Aitken mode and in the accumulation mode were significantly and positively associated with FeNO; but particles in the nucleation mode were significantly and negatively associated with FeNO. Moreover, UFP as a lump sum of both nucleation-mode and Aikten-mode particles did not show a significant association with FeNO. In terms of surface area concentration, ambient particles only in the accumulation mode were significantly and positively associated with FeNO. In terms of volume concentration, ambient particles in both the accumulation mode and the coarse mode were significantly and positively associated with FeNO. Analyses of the relationships between FeNO and metrics for particles deposited in the respiratory tract generated consistent findings, showing a negative association for the number concentration of deposited particles (driven by nucleation-mode particles), a positive association for the surface area concentration of deposited particles (driven by accumulation-mode particles), and a positive association for the volume concentration of deposited particles (driven by accumulation-mode and coarse-mode particles).

Conclusions

Particles contributing largely to the surface area concentration and/or the volume concentration of ambient particles or particles deposited in the respiratory tract had a significant positive association with pulmonary inflammation. Nucleation-mode particles, that have large number concentrations but contribute little to the surface area or volume concentration of ambient or deposited particles, had a significant negative association with FeNO. This may indicate a different biological process or may simply be due to the negative and strong correlation between nucleation-mode and accumulation-mode particles. Given that particles in different modes may have different biological actions, measuring UFP as a whole may not necessarily be useful from a biological effect standpoint.

A Panel Study on Lung Function and Bronchial Inflammation among Children Exposed to Ambient SO₂ from an Oil Refinery

To determine the acute effects on respiratory function of children exposed to sulphur dioxide (SO₂), we conducted two population-based longitudinal investigations near a major oil refinery. We enrolled 233 children, age 8–14, in Sarroch (Italy). The first study entailed five monthly spirometric visits (Panel 5). In a subgroup, children positive for history of respiratory symptoms were tested weekly (20 times) with spirometry and fractional exhaled nitric oxide (FeNO) measurement (Panel 20). Baseline questionnaires and daily diaries were recorded. SO₂, NO₂, PM₁₀ and O₃ were measured by monitoring stations. Multiple regression models were fitted. Using a multipollutant model, we found that a 10 µg/m³ SO₂ increase at lag0–2 days determined a percent variation (PV) of −3.37 (90% confidence interval, CI: −5.39; −1.30) for forced expiratory volume after one second (FEV1) in Panel 5 and a PV = −3.51 (90% CI: −4.77; −2.23) in Panel 20. We found a strong dose-response relation: 1-h SO₂ peaks >200 µg/m³ at lag2 days = FEV1 PV −2.49. For FeNO, we found a PV = 38.12 (90% CI: 12.88; 69.01) for each 10 µg/m³ SO₂ increase at 8-h time lag and a strong dose-response relation. Exposure to SO₂ is strongly associated with reduction of lung function and an increase in airway inflammation. This new evidence of harmful effects of SO₂ peaks should induce regulatory intervention.

Association of short-term exposure to ambient air pollutants with exhaled nitric oxide in hospitalized patients with respiratory-system diseases

BACKGROUND

Previous studies have suggested that exposure to ambient air pollutants may adversely affect human health. However, few studies have examined the health effects of exposure to ambient air pollutants in hospitalized patients.

OBJECTIVES

To evaluate the association between short-term exposure to ambient air pollutants and exhaled nitric oxide fraction (FeNO) in a large cohort of hospitalized patients.

METHODS

FeNO was detected for 2986 hospitalized patients (ages 18-88 years). Daily average concentrations of SO₂, NO₂, O₃, CO, PM_2.5 and PM₁₀ in 2014 and 2015 were obtained from nine fixed-site monitoring stations. Multiple linear regression models were chosen to assess the associations of exposure to ambient air pollutants with FeNO while adjusting for confounding variables. Lagged variable models were selected to determine the association between FeNO and ambient air pollutants concentrations with lags of up to 7 days prior to FeNO testing.

RESULTS

Interquartile-range (IQR) increases in the daily average SO₂ (8.00 μg/m³) and PM_2.5 (37.0 μg/m³) were strongly associated with increases in FeNO, with increases of 3.41% [95% confidence interval (CI), 0.94-5.93%] and 2.72% (95%CI, -0.09% to 5.61%), respectively. However, FeNO levels were not statistically associated with PM₁₀, NO₂, O₃ or CO. In the two-pollutant models, the maximum correlation was for ambient SO₂. We also found that FeNO was associated with IQR increases in daily average ambient concentrations of SO₂ up to 3 and 4 days after the exposure events.

CONCLUSIONS

Short-term exposure to SO₂ and PM_2.5 were positively correlated with FeNO levels in hospitalized patients in Shanghai.

Air pollution and resistance to inhaled glucocorticoids: Evidence, mechanisms and gaps to fill

Substantial evidence indicates that cigarette smoke exposure induces resistance to glucocorticoids, the primary maintenance medication in asthma treatment. Modest evidence also suggests that air pollution may reduce the effectiveness of these critical medications. Cigarette smoke, which has clear parallels with air pollution, has been shown to induce glucocorticoid resistance in asthma and it has been speculated that air pollution may have similar effects. However, the literature on an association of air pollution with glucocorticoid resistance is modest to date. In this review, we detail the evidence for, and against, the effects of air pollution on glucocorticoid effectiveness, focusing on results from epidemiology and controlled human exposure studies. Epidemiological studies indicate a correlation between increased air pollution exposure and worse asthma symptoms. But these studies also show a mix of beneficial and harmful effects of glucocorticoids on spirometry and asthma symptoms, perhaps due to confounding influences, or the induction of glucocorticoid resistance. We describe mechanisms that may contribute to reductions in glucocorticoid responsiveness following air pollution exposure, including changes to phosphorylation or oxidation of the glucocorticoid receptor, repression by cytokines, or inflammatory pathways, and epigenetic effects. Possible interactions between air pollution and respiratory infections are also briefly discussed. Finally, we detail a number of therapies that may boost glucocorticoid effectiveness or reverse resistance in the presence of air pollution, and comment on the beneficial effects of engineering controls, such as air filtration and asthma action plans. We also call attention to the benefits of improved clean air policy on asthma. This review highlights numerous gaps in our knowledge of the interactions between air pollution and glucocorticoids to encourage further research in this area with a view to reducing the harm caused to those with airways disease.

Applicability of internet search index for asthma admission forecast using machine learning

OBJECTIVE

This study aimed to determine whether a search index could provide insight into trends in asthma admission in China. An Internet search index is a powerful tool to monitor and predict epidemic outbreaks. However, whether using an internet search index can significantly improve asthma admissions forecasts remains unknown. The long-term goal is to develop a surveillance system to help early detection and interventions for asthma and to avoid asthma health care resource shortages in advance.

METHODS

In this study, we used a search index combined with air pollution data, weather data, and historical admissions data to forecast asthma admissions using machine learning.

RESULTS

Results demonstrated that the best area under the curve in the test set that can be achieved is 0.832, using all predictors mentioned earlier.

CONCLUSION

A search index is a powerful predictor in asthma admissions forecast, and a recent search index can reflect current asthma admissions with a lag-effect to a certain extent. The addition of a real-time, easily accessible search index improves forecasting capabilities and demonstrates the predictive potential of search index.

Genetic and epigenetic susceptibility of airway inflammation to PM2.5 in school children: new insights from quantile regression

BACKGROUND

The fractional concentration of exhaled nitric oxide (FeNO) is a biomarker of airway inflammation that has proved to be useful in investigations of genetic and epigenetic airway susceptibility to ambient air pollutants. For example, susceptibility to airway inflammation from exposure to particulate matter with aerodynamic diameter < =2.5 μm (PM_2.5) varies by haplotypes and promoter region methylation in inducible nitric oxide synthase (iNOS encoded by NOS2). We hypothesized that PM2.5 susceptibility associated with these epigenetic and genetic variants may be greater in children with high FeNO from inflamed airways. In this study, we investigated genetic and epigenetic susceptibility to airborne particulate matter by examining whether the joint effects of PM2.5, NOS2 haplotypes and iNOS promoter methylation significantly vary across the distribution of FeNO in school children.

METHODS

The study included 940 school children in the southern California Children's Health Study who provided concurrent buccal samples and FeNO measurements. We used quantile regression to examine susceptibility by estimating the quantile-specific joint effects of PM_2.5, NOS2 haplotype and methylation on FeNO.

RESULTS

We discovered striking differences in susceptibility to PM_2.5 in school children. The joint effects of short-term PM_2.5 exposure, NOS2 haplotypes and methylation across the FeNO distribution were significantly larger in the upper tail of the FeNO distribution, with little association in its lower tail, especially among children with asthma and Hispanic white children.

CONCLUSION

School-aged children with higher FeNO have greater genetic and epigenetic susceptibility to PM_2.5, highlighting the importance of investigating effects across the entire distribution of FeNO.

Acute effects of ambient temperature and particulate air pollution on fractional exhaled nitric oxide: A panel study among diabetic patients in Shanghai, China

Background

Epidemiological studies have shown the associations of ambient temperature and particulate matter (PM) air pollution with respiratory morbidity and mortality. However, the underlying mechanisms have not been well characterized. The aim of this study is to investigate the associations of temperature and fine and coarse PM with fractional exhaled nitric oxide (FeNO), a well-established biomarker of respiratory inflammation.

Methods

We conducted a longitudinal panel study involving six repeated FeNO tests among 33 type 2 diabetes mellitus patients from April to June 2013 in Shanghai, China. Hourly temperature and PM concentrations were obtained from a nearby fixed-site monitoring station. We then explored the associations between temperature, PM, and FeNO using linear mixed-effect models incorporated with distributed lag nonlinear models for the lagged and nonlinear associations. The interactions between temperature and PM were evaluated using stratification analyses.

Results

We found that both low and high temperature, as well as increased fine and coarse PM, were significantly associated with FeNO. The cumulative relative risk of FeNO was 1.75% (95% confidence interval [CI], 1.04–2.94) comparing 15 °C to the referent temperature (24 °C) over lags 0–9 days. A 10 μg/m³ increase in fine and coarse PM concentrations were associated with 1.18% (95% CI, 0.18–2.20) and 1.85% (95% CI, 0.62–3.09) FeNO in lag 0–1 days, respectively. PM had stronger effects on cool days than on warm days.

Conclusions

This study suggested low ambient temperature, fine PM, and coarse PM might elevate the levels of respiratory inflammation. Our findings may help understand the epidemiological evidence linking temperature, particulate air pollution, and respiratory health.

•

Both low and high temperatures were significantly associated with FeNO.

•

The increases of fine and coarse PM concentrations were associated with FeNO.

•

Both fine and coarse PM had stronger effects in cool days.

An Ensemble Spatiotemporal Model for Predicting PM2.5 Concentrations

Although fine particulate matter with a diameter of <2.5 μm (PM2.5) has a greater negative impact on human health than particulate matter with a diameter of <10 μm (PM10), measurements of PM2.5 have only recently been performed, and the spatial coverage of these measurements is limited. Comprehensively assessing PM2.5 pollution levels and the cumulative health effects is difficult because PM2.5 monitoring data for prior time periods and certain regions are not available. In this paper, we propose a promising approach for robustly predicting PM2.5 concentrations. In our approach, a generalized additive model is first used to quantify the non-linear associations between predictors and PM2.5, the bagging method is used to sample the dataset and train different models to reduce the bias in prediction, and the variogram for the daily residuals of the ensemble predictions is then simulated to improve our predictions. Shandong Province, China, is the study region, and data from 96 monitoring stations were included. To train and validate the models, we used PM2.5 measurement data from 2014 with other predictors, including PM10 data, meteorological parameters, remote sensing data, and land-use data. The validation results revealed that the R² value was improved and reached 0.89 when PM10 was used as a predictor and a kriging interpolation was performed for the residuals. However, when PM10 was not used as a predictor, our method still achieved a CV R² value of up to 0.86. The ensemble of spatial characteristics of relevant factors explained approximately 32% of the variance and improved the PM2.5 predictions. The spatiotemporal modeling approach to estimating PM2.5 concentrations presented in this paper has important implications for assessing PM2.5 exposure and its cumulative health effects.

Particulate Oxidative Burden as a Predictor of Exhaled Nitric Oxide in Children with Asthma

BACKGROUND

Epidemiological studies have provided strong evidence that fine particulate matter (PM2.5; aerodynamic diameter ≤ 2.5 μm) can exacerbate asthmatic symptoms in children. Pro-oxidant components of PM2.5 are capable of directly generating reactive oxygen species. Oxidative burden is used to describe the capacity of PM2.5 to generate reactive oxygen species in the lung.

OBJECTIVE

In this study we investigated the association between airway inflammation in asthmatic children and oxidative burden of PM2.5 personal exposure.

METHODS

Daily PM2.5 personal exposure samples (n = 249) of 62 asthmatic school-aged children in Montreal were collected over 10 consecutive days. The oxidative burden of PM2.5 samples was determined in vitro as the depletion of low-molecular-weight antioxidants (ascorbate and glutathione) from a synthetic model of the fluid lining the respiratory tract. Airway inflammation was measured daily as fractional exhaled nitric oxide (FeNO).

RESULTS

A positive association was identified between FeNO and glutathione-related oxidative burden exposure in the previous 24 hr (6.0% increase per interquartile range change in glutathione). Glutathione-related oxidative burden was further found to be positively associated with FeNO over 1-day lag and 2-day lag periods. Results further demonstrate that corticosteroid use may reduce the FeNO response to elevated glutathione-related oxidative burden exposure (no use, 15.8%; irregular use, 3.8%), whereas mold (22.1%), dust (10.6%), or fur (13.1%) allergies may increase FeNO in children with versus children without these allergies (11.5%). No association was found between PM2.5 mass or ascorbate-related oxidative burden and FeNO levels.

CONCLUSIONS

Exposure to PM2.5 with elevated glutathione-related oxidative burden was associated with increased FeNO.

CITATION

Maikawa CL, Weichenthal S, Wheeler AJ, Dobbin NA, Smargiassi A, Evans G, Liu L, Goldberg MS, Godri Pollitt KJ. 2016. Particulate oxidative burden as a predictor of exhaled nitric oxide in children with asthma. Environ Health Perspect 124:1616-1622; http://dx.doi.org/10.1289/EHP175.

Associations of oxidative stress and inflammatory biomarkers with chemically-characterized air pollutant exposures in an elderly cohort

BACKGROUND

Exposure to air pollution has been associated with cardiorespiratory morbidity and mortality. However, the chemical constituents and pollution sources underlying these associations remain unclear.

METHOD

We conducted a cohort panel study involving 97 elderly subjects living in the Los Angeles metropolitan area. Airway and circulating biomarkers of oxidative stress and inflammation were measured weekly over 12 weeks and included, exhaled breath condensate malondialdehyde (EBC MDA), fractional exhaled nitric oxide (FeNO), plasma oxidized low-density lipoprotein (oxLDL), and plasma interleukin-6 (IL-6). Exposures included 7-day personal nitrogen oxides (NOx), daily criteria-pollutant data, five-day average particulate matter (PM) measured in three size-fractions and characterized by chemical components including transition metals, and in vitro PM oxidative potential (dithiothreitol and macrophage reactive oxygen species). Associations between biomarkers and pollutants were assessed using linear mixed effects regression models.

RESULTS

We found significant positive associations of airway oxidative stress and inflammation with traffic-related air pollutants, ultrafine particles and transition metals. Positive but nonsignificant associations were observed with PM oxidative potential. The strongest associations were observed among PM variables in the ultrafine range (PM <0.18µm). It was estimated that an interquartile increase in 5-day average ultrafine polycyclic aromatic hydrocarbons was associated with a 6.3% (95% CI: 1.1%, 11.6%) increase in EBC MDA and 6.7% (95% CI: 3.4%, 10.2%) increase in FeNO. In addition, positive but nonsignificant associations were observed between oxLDL and traffic-related pollutants, ultrafine particles and transition metals while plasma IL-6 was positively associated with 1-day average traffic-related pollutants.

CONCLUSION

Our results suggest that exposure to pollutants with high oxidative potential (traffic-related pollutants, ultrafine particles, and transition metals) may lead to increased airway oxidative stress and inflammation in elderly adults. This observation was less clear with circulating biomarkers.

Trace metal exposure is associated with increased exhaled nitric oxide in asthmatic children

BACKGROUND

Children with asthma experience increased susceptibility to airborne pollutants. Exposure to traffic and industrial activity have been positively associated with exacerbation of symptoms as well as emergency room visits and hospitalisations. The effect of trace metals contained in fine particulate matter (aerodynamic diameter 2.5 μm and lower, PM2.5) on acute health effects amongst asthmatic children has not been well investigated. The objective of this panel study in asthmatic children was to determine the association between personal daily exposure to ambient trace metals and airway inflammation, as measured by fractional exhaled nitric oxide (FeNO).

METHODS

Daily concentrations of trace metals contained on PM2.5 were determined from personal samples (n = 217) collected from 70 asthmatic school aged children in Montreal, Canada, over ten consecutive days. FeNO was measured daily using standard techniques.

RESULTS

A positive association was found between FeNO and children's exposure to an indicator of vehicular non-tailpipe emissions (8.9 % increase for an increase in the interquartile range (IQR) in barium, 95 % confidence interval (CI): 2.8, 15.4) as well as exposure to an indicator of industrial emissions (7.6 % increase per IQR increase in vanadium, 95 % CI: 0.1, 15.8). Elevated FeNO was also suggested for other metals on the day after the exposure: 10.3 % increase per IQR increase in aluminium (95 % CI: 4.2, 16.6) and 7.5 % increase per IQR increase in iron (95 % CI: 1.5, 13.9) at a 1-day lag period.

CONCLUSIONS

Exposures to ambient PM2.5 containing trace metals that are markers of traffic and industrial-derived emissions were associated in asthmatic children with an enhanced FeNO response.

Spatial patterning in PM2.5 constituents under an inversion-focused sampling design across an urban area of complex terrain

Health effects of fine particulate matter (PM2.5) vary by chemical composition, and composition can help to identify key PM2.5 sources across urban areas. Further, this intra-urban spatial variation in concentrations and composition may vary with meteorological conditions (e.g., mixing height). Accordingly, we hypothesized that spatial sampling during atmospheric inversions would help to better identify localized source effects, and reveal more distinct spatial patterns in key constituents. We designed a 2-year monitoring campaign to capture fine-scale intra-urban variability in PM2.5 composition across Pittsburgh, PA, and compared both spatial patterns and source effects during "frequent inversion" hours vs 24-h weeklong averages. Using spatially distributed programmable monitors, and a geographic information systems (GIS)-based design, we collected PM2.5 samples across 37 sampling locations per year to capture variation in local pollution sources (e.g., proximity to industry, traffic density) and terrain (e.g., elevation). We used inductively coupled plasma mass spectrometry (ICP-MS) to determine elemental composition, and unconstrained factor analysis to identify source suites by sampling scheme and season. We examined spatial patterning in source factors using land use regression (LUR), wherein GIS-based source indicators served to corroborate factor interpretations. Under both summer sampling regimes, and for winter inversion-focused sampling, we identified six source factors, characterized by tracers associated with brake and tire wear, steel-making, soil and road dust, coal, diesel exhaust, and vehicular emissions. For winter 24-h samples, four factors suggested traffic/fuel oil, traffic emissions, coal/industry, and steel-making sources. In LURs, as hypothesized, GIS-based source terms better explained spatial variability in inversion-focused samples, including a greater contribution from roadway, steel, and coal-related sources. Factor analysis produced source-related constituent suites under both sampling designs, though factors were more distinct under inversion-focused sampling.

Design and characterization of human exposure to generated sulfate and soot particles in a pilot chamber study

A number of literatures have documented adverse health effects of exposure to fine particulate matter (PM2.5), and secondary sulfate aerosol and black carbon may contribute to health impacts of PM2.5 exposure. We designed an exposure system to generate sulfate and traffic soot particles, and assessed the feasibility of using it for human exposure assessment in a pilot human exposure study. In the designed exposure system, average mass concentrations of generated sulfate and soot particles were 74.19 μg/m3 and 11.54 μg/m3 in the chamber and did not vary significantly during two-hour human exposure sessions. The size ranges of generated sulfate were largely between 20 to 200 nm, whereas those of generated soot particles were in the size ranges of 50 to 200 nm. Following two-hour exposure to generated sulfate and soot particles, we observed significant increases in fractional exhaled NO (FeNO) in young and health subjects. Building on established human exposure system and health response follow-up methods, future full-scale studies focusing on the effects of mixed particulates and individual PM2.5 components would provide data in understanding the underpinning cardio-respiratory outcomes in relation to air pollution mixture exposure.

IMPLICATIONS

Controlled exposure is a useful design to measure the biological responses repeatedly following particulate exposures of target components and set exposure at target levels of health concerns. Our study provides rational and establishes method for future full-scale studies to focus on examining the effects of mixed particulates and individual PM2.5 components.

AIR POLLUTION INFLUENCES ON EXHALED NITRIC OXIDE AMONG PEOPLE WITH TYPE II DIABETES

OBJECTIVE

In a population with type 2 diabetes mellitus (T2DM), we examined associations of short-term air pollutant exposures with pulmonary inflammation, measured as fraction of exhaled pulmonary nitric oxide (FeNO).

METHODS

Sixty-nine Boston Metropolitan residents with T2DM completed up to 5 bi-weekly visits with 321 offline FeNO measurements. We measured ambient concentrations of particle mass, number and components at our stationary central site. Ambient concentrations of gaseous air pollutants were obtained from state monitors. We used linear models with fixed effects for participants, adjusting for 24-hour mean temperature, 24-hour mean water vapor pressure, season, and scrubbed room NO the day of the visit, to estimate associations between FeNO and interquartile range increases in exposure.

RESULTS

Interquartile increases in the 6-hour averages of black carbon (BC) (0.5 μg/m³) and particle number (PN) (1,000 particles/cm³) were associated with increases in FeNO of 3.84% (95% CI 0.60% to 7.18%) and 9.86 % (95% CI 3.59% to 16.52%), respectively. We also found significant associations of increases in FeNO with increases in 24-hour moving averages of BC, PN and nitrogen oxides (NOx).

CONCLUSION

Recent studies have focused on FeNO as a marker for eosinophilic pulmonary inflammation in asthmatic populations. This study adds support to the relevance of FeNO as a marker for pulmonary inflammation in diabetic populations, whose underlying chronic inflammatory status is likely to be related to innate immunity and proinflammatory adipokines.

The impact of PM2.5 on asthma emergency department visits: a systematic review and meta-analysis

Although the relationship between asthma and exposure to fine particulate matter (PM2.5) has been frequently measured, reported conclusions have not been consistent. As emergency department (ED) visits are an effective way to estimate health outcomes for people with asthma and short-term exposure to PM2.5, this review systematically searched five databases without language or geographical restrictions from inception to January 13, 2015 to study the impact of PM2.5 on asthma ED visits. A random-effects model was used to calculate the pooled risk ratio (RR) and 95% confidence intervals (CI). With respect to short-term effects, asthma ED visits increased at higher PM2.5 concentrations (RR 1.5% per 10 μg/m(3); 95% CI 1.2-1.7%), and children were more susceptible (3.6% per 10 μg/m(3); 95% CI 1.8, 5.3%) than adults (1.7, 95% CI 0.7%, 2.8%) to increased PM2.5; the ED visits increased during the warm season by 3.7% (95% CI 0.5, 6.9%) per 10 μg/m(3) increase in PM2.5, which was higher than the corresponding increase during the cold season (2.6, 95% CI 0.7-4.6%). This demonstrates that ambient PM2.5 has an adverse impact on asthma ED visits after short-term exposure and that children are a high-risk population when PM2.5 concentrations are high, particularly in warm seasons, during which measures should be taken to prevent PM2.5.

Estimates of community exposure and health risk to sulfur dioxide from power plant emissions using short-term mobile and stationary ambient air monitoring

To estimate plausible health effects associated with peak sulfur dioxide (SO₂) levels from three coal-fired power plants in the Baltimore, Maryland, area, air monitoring was conducted between June and September 2013. Historically, the summer months are periods when emissions are highest. Monitoring included a 5-day mobile and a subsequent 61-day stationary monitoring study. In the stationary monitoring study, equipment was set up at four sites where models predicted and mobile monitoring data measured the highest average concentrations of SO₂. Continuous monitors recorded ambient concentrations each minute. The 1-min data were used to calculate 5-min and 1-hr moving averages for comparison with concentrations from clinical studies that elicited lung function decrement and respiratory symptoms among asthmatics. Maximum daily 5-min moving average concentrations from the mobile monitoring study ranged from 70 to 84 ppb (183-220 µg/m³), and maximum daily 1-hr moving average concentrations from the mobile monitoring study ranged from 15 to 24 ppb (39-63 µg/m³). Maximum 5-min moving average concentrations from stationary monitoring ranged from 39 to 229 ppb (102-600 µg/m³), and maximum daily 1-hr average concentrations ranged from 15 to 134 ppb (40-351 µg/m³). Estimated exposure concentrations measured in the vicinity of monitors were below the lowest levels that have demonstrated respiratory symptoms in human clinical studies for healthy exercising asthmatics. Based on 5-min and 1-hr monitoring, the exposure levels of SO₂ in the vicinity of the C.P. Crane, Brandon Shores, and H.A. Wagner power plants were not likely to elicit respiratory symptoms in healthy asthmatics.

IMPLICATIONS

Mobile and stationary air monitoring for SO2 were conducted to quantify short-term exposure risk, to the surrounding community, from peak emissions of three coal-fired power plants in the Baltimore area. Concentrations were typically low, with only a few 5-min averages higher than levels indicated during clinical trials to induce changes in lung capacity for healthy asthmatics engaged in exercise outdoors.

The role of non-invasive biomarkers in detecting acute respiratory effects of traffic-related air pollution

The role of non-invasive methods in the investigation of acute effects of traffic-related air pollution is not clearly established. We evaluated the usefulness of non-invasive biomarkers in detecting acute air pollution effects according to the age of participants, the disease status, their sensitivity compared with lung function tests and their specificity for a type of pollutant. Search terms lead to 535 titles, among them 128 had potentially relevant abstracts. Sixtynine full papers were reviewed, while 59 articles were excluded as they did not meet the selection criteria. Methods used to assess short-term effects of air pollution included analysis of nasal lavage (NAL) for the upper airways, and induced sputum (IS), exhaled breath condensate (EBC) and exhaled nitric oxide (FeNO) for central and lower airways. There is strong evidence that FeNO evaluation is useful independently from subject age, while IS analysis is suitable almost for adults. Biomarker changes are generally observed upon pollutant exposure irrespective of the disease status of the participants. None of the biomarkers identified are specific for a type of pollutant exposure. Based on experimental exposure studies, there is moderate evidence that IS analysis is more sensitive than lung function tests, whereas this is not the case for biomarkers obtained by NAL or EBC. Cells and some cytokines (IL-6, IL-8 and myeloperoxidase) have been measured both in the upper respiratory tract (NAL) and in the lower airways (IS). Overall, the response to traffic exposure seems different in the two compartments. In conclusion, this survey of current literature displays the complexity of this research field, highlights the significance of short-term studies on traffic pollution and gives important tips when planning studies to detect acute respiratory effects of air pollution in a non-invasive way.

Exhaled nitric oxide and the management of childhood asthma--yet another promising biomarker "has been" or a misunderstood gem

Childhood asthma is a common chronic condition. Approximately five percent of all children in western countries are prescribed treatment with inhaled corticosteroids (ICS) to prevent asthma symptoms. Current guidelines advocate titrating ICS dose to symptoms but this approach is not without problem, e.g. how to discern asthmatic from non-asthmatic symptoms? And when to reduce ICS dose? This review describes the strengths and weaknesses of fractional exhaled nitric oxide (FENO) as an objective index for individualising asthma control in children. Epidemiological and mechanistic evidence suggest that FENO should be a promising biomarker for eosinophilic airway inflammation (a hall mark for asthma) but somewhat surprisingly, clinical trials in children have not consistently found benefit from adding FENO to a symptom-based approach to ICS treatment in children. There are a number of reasons why FENO has apparently failed to translate from promising biomarker to clinically useful tool, and one reason may be a lack of understanding of what merits a significant intrasubject change in FENO. This review describes the rise and apparent fall of FENO as biomarker for asthma and then focuses on more recent evidence which suggest that FENO may prove to have a role in the management of childhood asthma, and in particular preventing exacerbations.

Comparison of sources of variability in school age children exposure to ambient PM₂.₅

School age children are particularly susceptible to exposure to ambient fine particle (PM2.5). To provide insight into factors affecting variability in ambient PM2.5 exposure, distributions of daily PM2.5 exposures for school age children are estimated for four seasons in three climatic zones of the United States using a stochastic microenvironmental exposure model, based on ambient concentration, air exchange rate, penetration factor, deposition rate, census data, meteorological data, and time pattern data. Estimated daily individual exposure varies largely among seasons, regions, and individuals. The mean ratio of ambient exposure to ambient concentration (Ea/Ca) ranges from 0.46 to 0.61 among selected regions and seasons, resulting from differences in air exchange rate. The individual Ea/Ca varies by a factor of 2 to 3 over a 95% frequency range among simulated children, resulting from variability in children's time patterns. These patterns are similar among age groups, but vary with the day of the week and outdoor temperature. Variability in exposure is larger between individuals than between groups. The high end ratio of the Ea/Ca, at the 95th percentile of inter-individual variability, is 30% to 50% higher than the mean Ea/Ca ratio. Results can be used to intepret and adjust exposure errors in epidemiology and to assist in development of exposure mitigation strategies.

Insulin signaling regulates the toxicity of traffic-related PM2.5 on intestinal development and function in nematode Caenorhabditis elegans

Insulin signaling pathway may act as an important molecular basis for the toxicity of traffic-related PM_2.5 in Caenorhabditis elegans, a non-mammalian toxicological model.

Acute effects of summer air pollution on pulmonary function and airway inflammation in healthy young women

Background

Exposure to air pollution has been reported to be associated with asthma exacerbation. However, little is known about the effects of air pollutant exposure in healthy people. A panel study was conducted to evaluate the acute effects of air pollutants on pulmonary function and airway inflammation in healthy subjects.

Methods

Exhaled breath condensate (EBC) pH, fractional concentration of exhaled nitric oxide (FeNO), and pulmonary function were measured in 21 healthy young women repeatedly for two weeks in the summer in Tokyo, Japan. The concentrations of air pollutants were obtained from the monitoring stations in the neighborhoods where the subjects lived. Statistical analyses were performed using generalized estimating equations.

Results

EBC pH decreased significantly with a 10-ppb increase in the 4-day average ozone (O₃) concentration and a 10-µg/m³ increase in the 4-day average suspended particulate matter (SPM) concentration (−0.07 [95% confidence interval {CI} −0.11 to −0.03] and −0.08 [95% CI −0.12 to −0.03], respectively). Subjects with a history of rhinitis showed marked decreases in EBC pH associated with increases in O₃ and SPM. The changes in forced expiratory volume in 1 second (FEV₁) were also significantly associated with a 10-µg/m³ increase in the 3-day average concentration of SPM (−0.09 L [95% CI −0.17 to −0.01]). FeNO increased significantly in relation to the increase in O₃ and SPM among only subjects with a history of asthma.

Conclusions

Over the course of the study, EBC became significantly acidic with increases in O₃ and SPM concentrations. Furthermore, higher SPM concentrations were associated with decreased FEV₁. Subjects with a history of rhinitis or asthma are considered to be more susceptible to air pollutants.

Acute effects of black carbon and PM₂.₅ on children asthma admissions: a time-series study in a Chinese city

Epidemiologic evidence for an association between black carbon (BC) and health outcomes is limited. We estimated associations and exposure-response relationships between childhood asthma admission and concentration of BC and PM2.5 (particle less than 2.5mm in aerodynamic diameter) in ambient air in Shanghai using a lag distributed model. The PM2.5 and the BC were significantly associated with childhood asthma admissions in single-pollution model. However, the effects of BC on asthma attacks were slightly stronger than those of PM2.5 after adjusting or not adjusting for NO2 and SO2. In conclusion, our study suggests combustion-associated particles are important in China. Black carbon should be considered as one of the air quality indicators in China.

Effects of ambient air pollution on respiratory tract complaints and airway inflammation in primary school children

Respiratory health effects of ambient air pollution were studied in 605 school children 9 to 13 years in Eskişehir, Turkey. Each child performed a fractional exhaled nitric oxide (FENO) measurement and a lung function test (LFT). Self-reported respiratory tract complaints (having cold, complaints of throat, runny nose and shortness of breath/wheezing) in the last 7 days and on the day of testing were also recorded. As acute health outcomes were investigated, weekly average ambient concentrations of ozone (O3), nitrogen dioxide (NO2) and sulfur dioxide (SO2) were determined by passive sampling in the school playgrounds simultaneously with the health survey. Effects of air pollution on respiratory tract complaints and exhaled NO/lung function were estimated by multivariate logistic regression and multivariate linear mixed effects models, respectively. Upper respiratory tract complaints were significantly (p<0.05) associated with weekly average O3 concentrations during the health survey (adjusted odds ratios (OR) of 1.21 and 1.28 for a 10 μgm(-3) increment for having cold and a runny nose on day of testing, respectively). FENO levels were significantly (p<0.05) increased in children with various upper respiratory tract complaints (ratio in FENO varied between 1.16 and 1.40). No significant change in FENO levels was detected in association with any of the measured pollutants (p ≥ 0.05). Lung function was not associated with upper respiratory tract complaints and FENO levels. Peak Expiratory Flow (PEF) levels were negatively associated with weekly average O3 levels for children without upper respiratory tract complaints. In summary, elevated levels of air pollutants increased respiratory tract complaints in children.

Increased ultrafine particles and carbon monoxide concentrations are associated with asthma exacerbation among urban children

OBJECTIVES

Increased air pollutant concentrations have been linked to several asthma-related outcomes in children, including respiratory symptoms, medication use, and hospital visits. However, few studies have examined effects of ultrafine particles in a pediatric population. Our primary objective was to examine the effects of ambient concentrations of ultrafine particles on asthma exacerbation among urban children and determine whether consistent treatment with inhaled corticosteroids could attenuate these effects. We also explored the relationship between asthma exacerbation and ambient concentrations of accumulation mode particles, fine particles (≤2.5 micrograms [μm]; PM2.5), carbon monoxide, sulfur dioxide, and ozone. We hypothesized that increased 1-7 day concentrations of ultrafine particles and other pollutants would be associated with increases in the relative odds of an asthma exacerbation, but that this increase in risk would be attenuated among children receiving school-based corticosteroid therapy.

METHODS

We conducted a pilot study using data from 3 to 10 year-old children participating in the School-Based Asthma Therapy trial. Using a time-stratified case-crossover design and conditional logistic regression, we estimated the relative odds of a pediatric asthma visit treated with prednisone (n=96 visits among 74 children) associated with increased pollutant concentrations in the previous 7 days. We re-ran these analyses separately for children receiving medications through the school-based intervention and children in a usual care control group.

RESULTS

Interquartile range increases in ultrafine particles and carbon monoxide concentrations in the previous 7 days were associated with increases in the relative odds of a pediatric asthma visit, with the largest increases observed for 4-day mean ultrafine particles (interquartile range=2088p/cm(3); OR=1.27; 95% CI=0.90-1.79) and 7-day mean carbon monoxide (interquartile range=0.17ppm; OR=1.63; 95% CI=1.03-2.59). Relative odds estimates were larger among children receiving school-based inhaled corticosteroid treatment. We observed no such associations with accumulation mode particles, black carbon, fine particles (≤2.5μm), or sulfur dioxide. Ozone concentrations were inversely associated with the relative odds of a pediatric asthma visit.

CONCLUSIONS

These findings suggest a response to markers of traffic pollution among urban asthmatic children. Effects were strongest among children receiving preventive medications through school, suggesting that this group of children was particularly sensitive to environmental triggers. Medication adherence alone may be insufficient to protect the most vulnerable from environmental asthma triggers. However, further research is necessary to confirm this finding.

Recent advances in asthma biomarker research

Asthma is characterized by recurrent and reversible airflow obstruction, which is routinely monitored by history and physical examination, spirometry and home peak flow diaries. As airway inflammation is central to asthma pathogenesis, its monitoring should be part of patient management plans. Fractional exhaled nitric oxide level (FeNO) is the most extensively studied biomarker of airway inflammation, and FeNO references were higher in Chinese (Asians) than Whites. Published evidence was inconclusive as to whether FeNO is a useful management strategy for asthma. Other biomarkers include direct (histamine, methacholine) and indirect (adenosine, hypertonic saline) challenges of bronchial hyperresponsiveness (BHR), induced sputum and exhaled breath condensate (EBC). A management strategy that normalized sputum eosinophils among adult patients resulted in reductions of BHR and asthma exacerbations. However, subsequent adult and pediatric studies failed to replicate these benefits. Asthma phenotypes as defined by inflammatory cell populations in sputum were also not stable over a 12-month period. A recent meta-analysis concluded that induced sputum is not accurate enough to be applied in routine monitoring of childhood asthma. There is poor correlation between biomarkers that reflect different asthma dimensions: spirometry (airway caliber), BHR (airway reactivity) and FeNO or induced sputum (airway inflammation). Lastly, EBC is easily obtained noninvasively by cooling expired air. Many biomarkers ranging from acidity (pH), leukotrienes, aldehydes, cytokines to growth factors have been described. However, significant overlap between groups and technical difficulty in measuring low levels of inflammatory molecules are the major obstacles for EBC research. Metabolomics is an emerging analytical method for EBC biomarkers. In conclusion, both FeNO and induced sputum are useful asthma biomarkers. However, they will only form part of the clinical picture. Longitudinal studies with focused hypotheses and well-designed protocols are needed to establish the roles of these biomarkers in asthma management. The measurement of biomarkers in EBC remains a research tool.

Cardiorespiratory biomarker responses in healthy young adults to drastic air quality changes surrounding the 2008 Beijing Olympics

Associations between air pollution and cardiorespiratory mortality and morbidity have been well established, but data to support biologic mechanisms underlying these associations are limited. We designed this study to examine several prominently hypothesized mechanisms by assessing Beijing residents' biologic responses, at the biomarker level, to drastic changes in air quality brought about by unprecedented air pollution control measures implemented during the 2008 Beijing Olympics. To test the hypothesis that changes in air pollution levels are associated with changes in biomarker levels reflecting inflammation, hemostasis, oxidative stress, and autonomic tone, we recruited and retained 125 nonsmoking adults (19 to 33 years old) free of cardiorespiratory and other chronic diseases. Using the combination of a quasi-experimental design and a panel-study approach, we measured biomarkers of autonomic dysfunction (heart rate [HR*] and heart rate variability [HRV]), of systemic inflammation and oxidative stress (plasma C-reactive protein [CRP], fibrinogen, blood cell counts and differentials, and urinary 8-hydroxy-2'-deoxyguanosine [8-OHdG]), of pulmonary inflammation and oxidative stress (fractional exhaled nitric oxide [FeNO], exhaled breath condensate [EBC] pH, EBC nitrate, EBC nitrite, EBC nitrite+nitrate [sum of the concentrations of nitrite and nitrate], and EBC 8-isoprostane), of hemostasis (platelet activation [plasma sCD62P and sCD40L], platelet aggregation, and von Willebrand factor [vWF]), and of blood pressure (systolic blood pressure [SBP] and diastolic blood pressure [DBP]). These biomarkers were measured on each subject twice before, twice during, and twice after the Beijing Olympics. For each subject, repeated measurements were separated by at least one week to avoid potential residual effects from a prior measurement. We measured a large suite of air pollutants (PM2.5 [particulate matter < or = 2.5 microm in aerodynamic diameter] and constituents, sulfur dioxide [SO2], carbon monoxide [CO], nitrogen dioxide [NO2], and ozone [O3]) throughout the study at a central Beijing site near the residences and workplaces of the subjects on a daily basis. Total particle number (TPN) was also measured at a separate site. We used a time-series analysis to assess changes in pollutant concentration by period (pre-, during-, and post-Olympics periods). We used mixed-effects models to assess changes in biomarker levels by period and to estimate changes associated with increases in pollutant concentrations, controlling for ambient temperature, relative humidity (RH), sex, and the day of the week of the biomarker measurements. We conducted sensitivity analyses to assess the impact of potential temporal confounding and exposure misclassification. We observed reductions in mean concentrations for all measured pollutants except O3 from the pre-Olympics period to the during-Olympics period. On average, elemental carbon (EC) changed by -36%, TPN by -22%, SO2 by -60%, CO by -48%, and NO2 by -43% (P < 0.05 for all these pollutants). Reductions were observed in mean concentrations of PM2.5 (by -27%), sulfate (SO4(2-)) (by -13%), and organic carbon (OC) (by -23%); however, these values were not statistically significant. Both 24-hour averages and 1-hour maximums of O3 increased (by 20% and 17%, respectively) from the pre-Olympics to the during-Olympics period. In the post-Olympics period after the pollution control measures were relaxed, mean concentrations of most pollutants (with the exception of SO4(2-) and O3) increased to levels similar to or higher than pre-Olympics levels. Concomitantly and consistent with the hypothesis, we observed, from the pre-Olympics to the during-Olympics period, statistically significant (P < or = 0.05) or marginally significant (0.05 < P < 0.1) decreases in HR (-1 bpm or -1.7% [95% CI, -3.4 to -0.1]), SBP (-1.6 mmHg or -1.8% [95% CI, -3.9 to 0.4]), 8-OHdG (-58.3% [95% CI, -72.5 to -36.7]), FeNO (-60.3% [95% CI, -66.0 to -53.6]), EBC nitrite (-30.0% [95% CI, -39.3 to -19.3]), EBC nitrate (-21.5% [95% CI, -35.5 to -4.5]), EBC nitrite+nitrate (-17.6% [95% CI, -28.4 to -5.1]), EBC hydrogen ions (-46% [calculated from EBC pH], or +3.5% in EBC pH [95% CI, 2.2 to 4.9]), sCD62P (-34% [95% CI, -38.4 to -29.2]), sCD40L (-5.7% [95% CI, -10.5 to -0.7]), and vWF (-13.1% [95% CI, -18.6 to -7.5]). Moreover, the percentages of above-detection values out of all observations were significantly lower for plasma CRP and EBC 8-isoprostane in the during-Olympics period compared with the pre-Olympics period. In the post-Olympics period, the levels of the following biomarkers reversed (increased, either with or without statistical significance) from those in the during-Olympics period: SBP (10.7% [95% CI, 2.8 to 18.6]), fibrinogen (4.3% [95% CI, -1.7 to 10.2), neutrophil count (4.7% [95% CI, -7.7 to 17.0]), 8-OHdG (315% [95% CI, 62.0 to 962]), FeNO (130% [95% CI, 62.5 to 225]), EBC nitrite (159% [95% CI, 71.8 to 292]), EBC nitrate (161% [95% CI, 48.0 to 362]), EBC nitrite+nitrate (124% [95% CI, 50.9 to 233]), EBC hydrogen ions (146% [calculated from EBC pH] or -4.8% in EBC pH [95% CI, -9.4 to -0.21), sCD62P (33.7% [95% CI, 17.7 to 51.8]), and sCD40L (9.1% [95% CI, -3.7 to 23.5]). Furthermore, these biomarkers also showed statistically significant associations with multiple pollutants across different lags after adjusting for meteorologic parameters. The associations were in the directions hypothesized and were consistent with the findings from the comparisons between periods, providing further evidence that the period effects were due to changes in air quality, independent of season and meteorologic conditions or other potential confounders. Contrary to our hypothesis, however, we observed increases in platelet aggregation, red blood cells (RBCs) and white blood cells (WBCs) associated with the during-Olympics period, as well as significant negative associations of these biomarkers with pollutant concentrations. We did not observe significant changes in any of the HRV indices and DBP by period. However, we observed associations between a few HRV indices and pollutant concentrations. Changes in air pollution levels during the Beijing Olympics were associated with acute changes in biomarkers of pulmonary and systemic inflammation, oxidative stress, and hemostasis and in measures of cardiovascular physiology (HR and SBP) in healthy, young adults. These changes support the prominently hypothesized mechanistic pathways underlying the cardiorespiratory effects of air pollution.

Differentiating the associations of black carbon and fine particle with daily mortality in a Chinese city

There is only limited monitoring data of black carbon for epidemiologic analyses. In the current study, we used the distributed lag models to evaluate the association between mortality outcomes (both total and cause-specific) and exposure to black carbon and fine particle (PM(2.5)) in Shanghai, China. During our research period, the mean daily concentrations of black carbon and PM(2.5) were 3.9 μg/m3 and 53.9 μg/m3, respectively. The regression results showed that black carbon was significantly associated with total and cardiovascular mortality, but not with respiratory mortality. An inter-quartile range increase (2.7 μg/m3) of black carbon corresponded to a 2.3% (95% confidence interval [CI]: 0.6-4.1), 3.2% (95% CI: 0.6-5.7), and 0.6% (95% CI: -4.5 to 5.7) increase in total, cardiovascular and respiratory mortality, respectively. When adjusted for PM(2.5), the effects of black carbon increased and remained statistically significant; in contrast, the associations of PM(2.5) with daily mortality decreased and became statistically insignificant after adjustment for black carbon. To our knowledge, this is the first study in China, or even in Asian developing countries, to report the acute effect of black carbon and PM(2.5) on daily mortality simultaneously. Our findings suggest that black carbon is a valuable additional air quality indicator to evaluate the health risks of ambient particles.