Associations between long-term exposure to chemical constituents of fine particulate matter (PM2.5) and mortality in Medicare enrollees in the eastern United States

Synergic effect between high temperature and air pollution on mortality in Northeast Asia

High temperature and air pollutants have been reported as potential risk factors of mortality. Previous studies investigated interaction between the two variables; however, the excess death risk due to the synergic effect (i.e. interaction on the additive scale) between the two variables has not been investigated adequately on a multi-country scale. This study aimed to assess the excess death risk due to the synergism between high temperature and air pollution on mortality using a multicity time-series analysis. We collected time-series data on mortality, weather variables, and four air pollutants (PM₁₀, O₃, NO₂, and CO) for 16 metropolitan cities of three countries (Japan, Korea, and Taiwan) in Northeast Asia (1979-2015). Quasi-Poisson time-series regression and meta-analysis were used to estimate the additive interaction between high temperature and air pollution. The additive interaction was measured by relative excess risk due to interaction (RERI) index. We calculated RERI with relative risks (RR) of the 99th/10th, 90th/90th, and 99th/90th percentiles of temperature/air pollution metrics, where risk at the 90th/10th percentiles of temperature/air pollution metrics was the reference category. This study showed that there may exist positive and significant excess death risks due to the synergism between high temperature and air pollution in the total population for all pollutants (95% lower confidence intervals of all RERIs>0 or near 0). In final, we measured quantitatively the excess death risks due to synergic effect between high temperature and air pollution, and the synergism should be considered in public health interventions and a composite warning system.

Value Assessment of Health Losses Caused by PM2.5 in Changsha City, China

With the advancement of urbanization, the harm caused to human health by PM2.5 pollution has been receiving increasing attention worldwide. In order to increase public awareness and understanding of the damage caused by PM2.5 in the air and gain the attention of relevant management departments, Changsha City is used as the research object, and the environmental quality data and public health data of Changsha City from 2013 to 2017 are used. All-cause death, respiratory death, cardiovascular death, chronic bronchitis, and asthma were selected as the endpoints of PM2.5 pollution health effects, according to an exposure-response coefficient, Poisson regression model, and health-impact-assessment-related methods (the Human Capital Approach, the Willingness to Pay Approach, and the Cost of Illness Approach), assessing the health loss and economic loss associated with PM2.5. The results show that the pollution of PM2.5 in Changsha City is serious, which has resulted in extensive health hazards and economic losses to local residents. From 2013 to 2017, when annual average PM2.5 concentrations fell to 10 μg/m3, the total annual losses from the five health-effect endpoints were $2788.41 million, $2123.18 million, $1657.29 million, $1402.90 million, and $1419.92 million, respectively. The proportion of Gross Domestic Product (GDP) in the current year was 2.69%, 1.87%, 1.34%, 1.04% and 0.93%, respectively. Furthermore, when the concentration of PM2.5 in Changsha City drops to the safety threshold of 10 μg/m3, the number of affected populations and health economic losses can far exceed the situation when it falls to 35 μg/m3, as stipulated by the national secondary standard. From 2013 to 2017, the total loss under the former situation was 1.48 times, 1.54 times, 1.86 times, 2.25 times, and 2.33 times that of the latter, respectively. Among them, all-cause death and cardiovascular death are the main sources of health loss. Taking 2017 as an example, when the annual average concentration dropped to 10 μg/m3, the health loss caused by deaths from all-cause death and cardiovascular disease was 49.16% of the total loss and 35.73%, respectively. Additionally, deaths as a result of respiratory disease, asthma, and chronic bronchitis contributed to 7.31%, 7.29%, and 0.51% of the total loss, respectively. The research results can provide a reference for the formulation of air pollution control policies based on health effects, which is of great significance for controlling air pollution and protecting people's health.

PM2.5 aggravates the lipid accumulation, mitochondrial damage and apoptosis in macrophage foam cells

Epidemiological evidence showed that the particulate matter exposure is associated with atherosclerotic plaque progression, which may be related to foam cell formation, but the mechanism is still unknown. The study was aimed to investigate the toxic effects and possible mechanism of PM_2.5 on the formation of macrophage foam cells induced by oxidized low density lipoprotein (ox-LDL). Results showed that PM_2.5 induced cytotoxicity by decreasing the cell viability and increasing the LDH level in macrophage foam cells. PM_2.5 aggravated the lipid accumulation in ox-LDL-stimulated macrophage RAW264.7 within markedly increasing level of intracellular lipid by Oil red O staining. The level of ROS increased obivously after co-exposure to PM_2.5 and ox-LDL than single exposure group. In addition, serious mitochondrial damage such as the mitochondrial swelling, cristae rupturing and disappearance were observed in macrophage foam cells. The loss of the mitochondrial membrane potential (MMP) further exacerbated the mitochondrial damage in PM_2.5-induced macrophage foam cells. The apoptotic rate increased more severely via up-regulated protein level of Bax, Cyt C, Caspase-9, Caspase-3, and down-regulated that of Bcl-2, indicating that PM_2.5 activated the mitochondrial-mediated apoptosis pathway. In summary, our results demonstrated that PM_2.5 aggravated the lipid accumulation, mitochondrial damage and apoptosis in macrophage foam cells, suggesting that PM_2.5 was a risk factor of atherosclerosis progression.

Particulate Matter Mortality Rates and Their Modification by Spatial Synoptic Classification

Air pollution levels are highly correlated with temperature or humidity, so we investigated the relationship between PM₁₀ and the spatial synoptic classification (SSC) scheme on daily mortality, according to age group and season. Daily death data for 2000-2014 from Seoul, Korea, were acquired, and time-series analysis was applied with respect to season and to each of seven distinct SSC types: dry moderate (DM); dry polar (DP); dry tropical (DT); moist moderate (MM); moist polar (MP); moist tropical (MT); and transition (T). Modification effects were estimated for daily, non-accidental, cardiovascular, and respiratory mortality between PM₁₀ and SSC types. The following SSC-type-specific increased mortalities were observed, by cause of death: non-accidental mortality: DT (1.86%) and MT (1.86%); cardiovascular mortality: DT (2.83%) and MM (3.00%); respiratory mortality: MT (3.78%). Based on simplified weather types, increased PM₁₀ effects in non-accidental mortality rates were observed in dry (1.54%) and moist (2.32%) conditions among those aged 40-59 years and were detected regardless of conditions in other age groups: 60-74 (1.11%), 75-84 (1.55%), and 85+ (1.75%). The effects of particulate air pollution, by SSC, suggest the applicability of SSC to the comparison and understanding of acute effects of daily mortality based on weather type.

Epigenetic marks of prenatal air pollution exposure found in multiple tissues relevant for child health

BACKGROUND

Prenatal air pollution exposure has been linked to many adverse health conditions in the offspring. However, little is known about the mechanisms underlying these associations. Epigenetics may be one plausible biologic link. Here, we sought to identify site-specific and global DNA methylation (DNAm) changes, in developmentally relevant tissues, associated with prenatal exposure to nitrogen dioxide (NO₂) and ozone (O₃). Additionally, we assessed whether sex-specific changes in methylation exist and whether DNAm changes are consistently observed across tissues.

METHODS

Genome-scale DNAm measurements were obtained using the Infinium HumanMethylation450k platform for 133 placenta and 175 cord blood specimens from Early Autism Risk Longitudinal Investigation (EARLI) neonates. Ambient NO₂ and O₃ exposure levels were based on prenatal address locations of EARLI mothers and the Environmental Protection Agency's AirNOW monitoring network using inverse distance weighting. We computed sample-level aggregate methylation measures for each of 5 types of genomic regions including genome-wide, open sea, shelf, shore, and island regions. Linear regression was performed for each genomic region; per-sample aggregate methylation measures were modeled as a function of quantitative exposure level with covariate adjustment. In addition, bumphunting was performed to identify differentially methylated regions (DMRs) associated with prenatal O₃ and NO₂ exposures in each tissue and by sex, with adjustment for technical and biological sources of variation.

RESULTS

We identified global and locus-specific changes in DNA methylation related to prenatal exposure to NO₂ and O₃ in 2 developmentally relevant tissues. Neonates with increased prenatal O₃ exposure had lower aggregate levels of DNAm at CpGs located in open sea and shelf regions of the genome. We identified 6 DMRs associated with prenatal NO₂ exposure, including 3 sex-specific. An additional 3 sex-specific DMRs were associated with prenatal O₃ exposure levels. DMRs initially detected in cord blood samples (n = 4) showed consistent exposure-related changes in DNAm in placenta. However, the DMRs initially detected in placenta (n = 5) did not show DNAm differences in cord blood and, thus, they appear to be tissue-specific.

CONCLUSIONS

We observed global, locus, and sex-specific methylation changes associated with prenatal NO₂ and O₃ exposures. Our findings support DNAm is a biologic target of prenatal air pollutant exposures and highlight epigenetic involvement in sex-specific differential susceptibility to environmental exposure effects in 2 developmentally relevant tissues.

Characterization and quantification of PM2.5 emissions and PAHs concentration in PM2.5 from the exhausts of diesel vehicles with various accumulated mileages

Road traffic is one of the main sources of particulate matter in the atmospheric environment. Notwithstanding its significance, there are noteworthy challenges in quantitative assessment of its contribution to the concentrations of airborne. This study reports on the characterization and quantification of PM_2.5 emissions and PAHs concentration in PM_2.5 from the exhausts of on-road diesel vehicles with various accumulated mileages in Kaohsiung City, Taiwan. Urban areas could be a subject matter not just in connection to deprived air quality, but similarly to pollution of other significant environmental media by air contaminants. To that end, our study intends to estimate the PM_2.5 emissions from diesel vehicles using diesel fuels and to analyze the PM_2.5 emissions and PAHs concentration in PM_2.5. In this study, particulate matters (PM_2.5) were characterized and quantified from a place impacted by diesel vehicles fueled with diesel in Kaohsiung City, Taiwan. The tested diesel vehicles with various accumulated mileages overs the model year comprising of the vehicles registered from 1984 to 2012 from different manufacturers (or brands) ranging from 8733 to 965,026 km (average 445,433 km) accumulative mileages. Exhaust constituents include CO, NOx, PM_2.5 and particle phase PAHs. The concentrations of twenty-one (21) priority polycyclic aromatic hydrocarbons (PAHs) were studied in the samples by their relationship with atmospheric PM_2.5. However, in relations to cumulative mileages, lower cumulative mileage (mileage <20,000 km) has the lowest CO and NOx emission factors. The mileage ranged from 20,001 to 30,000 km had an increased CO and NOx emission factors, respectively. Interestingly, with the increased high number of mileages ranged from 30,001 to 50,000 km, CO and NOx emission factor was observed to be declining, respectively. This could be attributed to the technological changes on new diesel vehicle models. But nonetheless, the trend of CO emission factor was found to be higher with an increasing of cumulative mileages as compared to the mileage that reached lower than 30,000 km.

Short-term and long-term exposures to fine particulate matter constituents and health: A systematic review and meta-analysis

BACKGROUND

Fine particulate matter (Particulate matter with diameter ≤ 2.5 μm) is associated with multiple health outcomes, with varying effects across seasons and locations. It remains largely unknown that which components of PM_2.5 are most harmful to human health.

METHODS

We systematically searched all the relevent studies published before August 1, 2018, on the associations of fine particulate matter constituents with mortality and morbidity, using Web of Science, MEDLINE, PubMed and EMBASE. Studies were included if they explored the associations between short term or long term exposure of fine particulate matter constituents and natural, cardiovascular or respiratory health endpoints. The criteria for the risk of bias was adapted from OHAT and New Castle Ottawa. We applied a random-effects model to derive the risk estimates for each constituent. We performed main analyses restricted to studies which adjusted the PM_2.5 mass in their models.

RESULTS

Significant associations were observed between several PM_2.5 constituents and different health endpoints. Among them, black carbon and organic carbon were most robustly and consistently associated with all natural, cardiovascular mortality and morbidity. Other potential toxic constituents including nitrate, sulfate, Zinc, silicon, iron, nickel, vanadium, and potassium were associated with adverse cardiovascular health, while nitrate, sulfate and vanadium were relevant for adverse respiratory health outcomes.

CONCLUSIONS

Our analysis suggests that black carbon and organic carbon are important detrimental components of PM_2.5, while other constituents are probably hazardous to human health. However, more studies are needed to further confirm our results.

Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors

An accurate fine-resolution surface of the chemical composition of fine particulate matter (PM_2.5) would offer valuable information for epidemiological studies and health impact assessments. We develop geoscience-derived estimates of PM_2.5 composition from a chemical transport model (GEOS-Chem) and satellite observations of aerosol optical depth, and statistically fuse these estimates with ground-based observations using a geographically weighted regression over North America to produce a spatially complete representation of sulfate, nitrate, ammonium, black carbon, organic matter, mineral dust, and sea-salt over 2000-2016. Significant long-term agreement is found with cross-validation sites over North America (R² = 0.57-0.96), with the strongest agreement for sulfate (R² = 0.96), nitrate (R² = 0.90), and ammonium (R² = 0.86). We find that North American decreases in population-weighted fine particulate matter (PM_2.5) concentrations since 2000 have been most heavily influenced by regional changes in sulfate and organic matter. Regionally, the relative importance of several chemical components are found to change with PM_2.5 concentration, such as higher PM_2.5 concentrations having a larger proportion of nitrate and a smaller proportion of sulfate. This data set offers information for research into the health effects of PM_2.5 chemical components.

Effects of neonatal inhalation exposure to ultrafine carbon particles on pathology and behavioral outcomes in C57BL/6J mice

Background

Recent epidemiological studies indicate early-life exposure to air pollution is associated with adverse neurodevelopmental outcomes. Previous studies investigating neonatal exposure to ambient fine and ultrafine particles have shown sex specific inflammation-linked pathological changes and protracted learning deficits. A potential contributor to the adverse phenotypes from developmental exposure to particulate matter observed in previous studies may be elemental carbon, a well-known contributor to pollution particulate. The present study is an evaluation of pathological and protracted behavioral alterations in adulthood following subacute neonatal exposure to ultrafine elemental carbon. C57BL/6J mice were exposed to ultrafine elemental carbon at 50 μg/m³ from postnatal days 4–7 and 10–13 for 4 h/day. Behavioral outcomes measured were locomotor activity, novel object recognition (short-term memory), elevated plus maze (anxiety-like behavior), fixed interval (FI) schedule of food reward (learning, timing) and differential reinforcement of low rate (DRL) schedule of food reward (impulsivity, inability to inhibit responding). Neuropathology was assessed by measures of inflammation (glial fibrillary-acidic protein), myelin basic protein expression in the corpus callosum, and lateral ventricle area.

Results

Twenty-four hours following the final exposure day, no significant differences in anogenital distance, body weight or central nervous system pathological markers were observed in offspring of either sex. Nor were significant changes observed in novel object recognition, elevated plus maze performance, FI, or DRL schedule-controlled behavior in either females or males.

Conclusion

The limited effect of neonatal exposure to ultrafine elemental carbon suggests this component of air pollution is not a substantial contributor to the behavioral alterations and neuropathology previously observed in response to ambient pollution particulate exposures. Rather, other more reactive constituent species, organic and/or inorganic, gas-phase components, or combinations of constituents may be involved. Defining these neurotoxic components is critical to the formulation of better animal models, more focused mechanistic assessments, and potential regulatory policies for air pollution.

Electronic supplementary material

The online version of this article (10.1186/s12989-019-0293-5) contains supplementary material, which is available to authorized users.

Water soluble and insoluble components of PM2.5 and their functional cardiotoxicities on neonatal rat cardiomyocytes in vitro

A growing number of epidemiological surveys show that PM_2.5 is an important promoter for the cardiovascular dysfunction induced by atmospheric pollution. PM_2.5 is a complex mixture of solid and liquid airborne particles and its components determine the health risk of PM_2.5to a great extent. However, the individual cardiotoxicities of different PM_2.5 fractions are still unclear, especially in the cellular level. Here we used the neonatal rat cardiomyocytes (NRCMs) to evaluate the cardiac toxicity of PM_2.5 exposure. The cytotoxicities of Total-PM_2.5, water soluble components of PM_2.5 (WS-PM_2.5) and water insoluble components of PM_2.5 (WIS-PM_2.5), which include the cell viability, cell membrane damage, reactive oxygen species (ROS) generation, were examined with NRCMs in vitro. The results indicated that Total-PM_2.5 or WIS-PM_2.5 exposure significantly decreased the cell viability, induced the cell membrane damage and increased the ROS level in NRCMs at concentrations above 50 µg/mL. However, WS-PM_2.5 exposure could induce the cytotoxicity on NRCMs until the concentration of WS-PM_2.5 was raised to a higher concentration (75 µg/mL). Furthermore, the DNA damage was detected in NRCMs after 48 h of exposure with Total-PM_2.5, WS-PM_2.5 or WIS-PM_2.5 (75 µg/mL) and the adverse effects on mitochondrial function and action potentials of NRCMs were detected only both in the Total-PM_2.5 and WIS-PM_2.5 treatment group. In summary, our project not only estimates the risk of PM_2.5 on cardiac cells but also reveal that Total-PM_2.5 and WIS-PM_2.5 exposure were predominantly associated with the functional cardiotoxicities in NRCMs.

Radiocarbon determination of fossil and contemporary carbon contribution to aerosol in the Pacific Islands

Combustion emissions are of growing concern across all Pacific Island Countries, which account for >10,000 km² of the earth's surface area; as for many other small island states globally. Apportioning emissions inputs for Suva, the largest Pacific Island city, will aid in development of emission reduction strategies. Total suspended particulate (TSP) and fine particulate (PM_2.5) samples were collected for Suva City, a residential area (Kinoya, TSP) and a mainly ocean-influenced site (Suva Point, TSP) from 2014 to 2015. Percentages of contemporary and fossil carbon were determined by radiocarbon analysis (accelerator mass spectrometry); for non‑carbonate carbon (NCC), elemental carbon (EC) and organic carbon (OC). Source contributions to particulate matter were identified and the accuracy of previous emissions inventory and source apportionment studies was evaluated. Suva Point NCC concentrations (2.7 ± 0.4 μg/m³) were four times lower than for City (13 ± 2 μg/m³ in TSP) and Kinoya (13 ± 1 μg/m³ in TSP); demonstrating the contribution of land-based emissions activities in city and residential areas. In Suva City, total NCC in air was 81% (79%-83%) fossil carbon, from vehicles, shipping, power generation and industry; whilst in the residential area, 48% (46%-50%) of total NCC was contemporary carbon; reflecting the higher incidence of biomass and waste burning and of cooking activities. Secondary organic fossil carbon sources contributed >36% of NCC mass at the city and >29% at Kinoya; with biogenic carbon being Kinoya's most significant source (approx. 30% of NCC mass). These results support the previous source apportionment studies for the city area; yet show that, in line with emissions inventory studies, biomass combustion contributes more PM_2.5 mass in residential areas. Hence air quality management strategies need to target open burning activities as well as fossil fuel combustion.

Integrative analysis of methylome and transcriptome variation of identified cardiac disease-specific genes in human cardiomyocytes after PM2.5 exposure

PM_2.5 exposure is strongly linked to cardiac disease. Subtle epigenetic or transcriptional alterations induced by PM_2.5 might contribute to pathogenesis and disease susceptibility of cardiac disease. It is still a major challenge to identify biological targets in human genetics. Human cardiomyocytes AC16 was chosen as cell model. Epigenetic effect of PM_2.5 in AC16 was analyzed using Illumina HumanMethylation 450 K BeadChip. Meanwhile the transcriptomic profiling was performed by Affymetrix^® microarray. PM_2.5 induced genome wide variation of DNA methylation pattern, including differentially methylated CpGs in promoter region. Then gene ontology analysis demonstrated differentially methylated genes were significantly clustered in pathways in regulation of apoptotic process, cell death and metabolic pathways, or associated with ion binding and shuttling. Correlation of the methylome and transcriptome revealed a clear bias toward transcriptional suppression by hypermethylation or activation by hypomethylation. Identified 386 genes which exhibited both differential methylation and expression were functionally associated with pathways including cardiovascular system development, regulation of blood vessel size, vasculature development, p53 pathway, AC-modulating/inhibiting GPCRs pathway and cellular response to metal ion/inorganic substance. Disease ontology demonstrated their prominent role in cardiac diseases and identified 14 cardiac-specific genes (ANK2, AQP1 et al.). PPI network analysis revealed 6 novel genes (POLR2I, LEP, BRIX1, ADCY6, INSL3, RARS). Those genes were then verified by qRT-PCR. Thus, in AC16, PM_2.5 alters the methylome and transcriptome of genes might be relevant for PM_2.5-/heart-associated diseases. Result gives additional insight in PM_2.5 relative cardiac diseases/associated genes and the potential mechanisms that contribute to PM_2.5 related cardiac disease.

Space-time trends of PM2.5 constituents in the conterminous United States estimated by a machine learning approach, 2005-2015

Particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5) is a complex mixture of chemical constituents emitted from various emission sources or through secondary reactions/processes; however, PM_2.5 is regulated mostly based on its total mass concentration. Studies to identify the impacts on climate change, visibility degradation and public health of different PM_2.5 constituents are hindered by limited ground measurements of PM_2.5 constituents. In this study, national models were developed based on random forest algorithm, one of machine learning methods that is of high predictive capacity and able to provide interpretable results, to predict concentrations of PM_2.5 sulfate, nitrate, organic carbon (OC) and elemental carbon (EC) across the conterminous United States from 2005 to 2015 at the daily level. The random forest models achieved high out-of-bag (OOB) R² values at the daily level, and the mean OOB R² values were 0.86, 0.82, 0.71 and 0.75 for sulfate, nitrate, OC and EC, respectively, over 2005-2015. The long-term temporal trends of PM_2.5 sulfate, nitrate, OC and EC predictions agreed well with their corresponding ground measurements. The annual mean of predicted PM_2.5 sulfate and EC levels across the conterminous United States decreased substantially from 2005 to 2015; while concentrations of predicted PM_2.5 nitrate and OC decreased and fluctuated during the study period. The annual prediction maps captured the characterized spatial patterns of the PM_2.5 constituents. The distributions of annual mean concentrations of sulfate and nitrate were generally regional in the extent that sulfate decreased from east to west smoothly with enhancement in California and nitrate had higher concentration in Midwest, Metro New York area, and California. OC and EC had regional high concentrations in the Southeast and Northwest as well as localized high levels around urban centers. The spatial patterns of PM_2.5 constituents were consistent with the distributions of their emission sources and secondary processes and transportation. Hence, the national models developed in this study could provide supplementary evaluations of spatio-temporal distributions of PM_2.5 constituents with full time-space coverages in the conterminous United States, which could be beneficial to assess the impacts of PM_2.5 constituents on radiation budgets and visibility degradation, and support exposure assessment for regional to national health studies at county or city levels to understand the acute and chronic toxicity and health impacts of PM_2.5 constituents, and consequently provide scientific evidence for making targeted and effective regulations of PM_2.5 pollution.

Metabolic impact induced by total, water soluble and insoluble components of PM2.5 acute exposure in mice

Fine particulate matter (PM_2.5) has been listed as an important environmental risk factor for human health. However, the systemic biological effects on metabolic responses induced by PM_2.5 and its components were poorly understood. This study was aimed to evaluate the toxicity of different components of PM_2.5 at molecular level via metabolomics approach. In the present study, we adopted a ¹H NMR-based metabolomics approach to evaluate metabolic profiles in mice after acute exposure to Total-PM_2.5, water soluble components of PM_2.5 (WS-PM_2.5) and water insoluble components of PM_2.5 (WIS-PM_2.5). First, we characterized the morphological features and chemical composition of PM_2.5. Then, the metabolites changes of serum and urine in mice were systematically analyzed using 800 MHz ¹H NMR techniques in combination with multivariate statistical analysis. Total-PM_2.5 exposure affected metabolites mainly involved in amino acid metabolism, protein biosynthesis, energy metabolism and metabolism of cofactors and vitamins. WS-PM_2.5 exposure influenced lipid metabolism and carbohydrate metabolism. WIS-PM_2.5 exposure mainly perturbed amino acid metabolism and energy metabolism. The results suggested that acute exposure to the Total-PM_2.5, WS-PM_2.5 and WIS-PM_2.5 in mice exhibited marked systemic metabolic changes. In addition, the insoluble fraction of PM_2.5 contributed greatly to the toxicity of PM_2.5.

Environmental exposure mixtures: questions and methods to address them

PURPOSE OF THIS REVIEW

This review provides a summary of statistical approaches that researchers can use to study environmental exposure mixtures. Two primary considerations are the form of the research question and the statistical tools best suited to address that question. Because the choice of statistical tools is not rigid, we make recommendations about when each tool may be most useful.

RECENT FINDINGS

When dimensionality is relatively low, some statistical tools yield easily interpretable estimates of effect (e.g., risk ratio, odds ratio) or intervention impacts. When dimensionality increases, it is often necessary to compromise this interpretablity in favor of identifying interesting statistical signals from noise; this requires applying statistical tools that are oriented more heavily towards dimension reduction via shrinkage and/or variable selection.

SUMMARY

The study of complex exposure mixtures has prompted development of novel statistical methods. We suggest that further validation work would aid practicing researchers in choosing among existing and emerging statistical tools for studying exposure mixtures.

Reducing mortality risk by targeting specific air pollution sources: Suva, Fiji

Health implications of air pollution vary dependent upon pollutant sources. This work determines the value, in terms of reduced mortality, of reducing ambient particulate matter (PM_2.5: effective aerodynamic diameter 2.5μm or less) concentration due to different emission sources. Suva, a Pacific Island city with substantial input from combustion sources, is used as a case-study. Elemental concentration was determined, by ion beam analysis, for PM_2.5 samples from Suva, spanning one year. Sources of PM_2.5 have been quantified by positive matrix factorisation. A review of recent literature has been carried out to delineate the mortality risk associated with these sources. Risk factors have then been applied for Suva, to calculate the possible mortality reduction that may be achieved through reduction in pollutant levels. Higher risk ratios for black carbon and sulphur resulted in mortality predictions for PM_2.5 from fossil fuel combustion, road vehicle emissions and waste burning that surpass predictions for these sources based on health risk of PM_2.5 mass alone. Predicted mortality for Suva from fossil fuel smoke exceeds the national toll from road accidents in Fiji. The greatest benefit for Suva, in terms of reduced mortality, is likely to be accomplished by reducing emissions from fossil fuel combustion (diesel), vehicles and waste burning.

A Global Perspective of Fine Particulate Matter Pollution and Its Health Effects

Fine particulate matter (PM) in the ambient air is implicated in a variety of human health issues throughout the globe. Regulation of fine PM in the atmosphere requires information on the dimension of the problem with respect to variations in concentrations and sources. To understand the current status of fine particles in the atmosphere and their potential harmful health effects in different regions of the world this review article was prepared based on peer-reviewed scientific papers, scientific reports, and database from government organizations published after the year 2000 to evaluate the global scenario of the PM_2.5 (particles <2.5 μm in aerodynamic diameter), its exceedance of national and international standards, sources, mechanism of toxicity, and harmful health effects of PM_2.5 and its components. PM_2.5 levels and exceedances of national and international standards were several times higher in Asian countries, while levels in Europe and USA were mostly well below the respective standards. Vehicular traffic has a significant influence on PM_2.5 levels in urban areas; followed by combustion activities (biomass, industrial, and waste burning) and road dust. In urban atmosphere, fine particles are mostly associated with different health effects with old aged people, pregnant women, and more so children being the most susceptible ones. Fine PM chemical constituents severely effect health due to their carcinogenic or mutagenic nature. Most of the research indicated an exceedance of fine PM level of the standards with a diverse array of health effects based on PM_2.5 chemical constituents. Emission reduction policies with epidemiological studies are needed to understand the benefits of sustainable control measures for fine PM mitigation.

Vascular and cardiac autonomic function and PM2.5 constituents among the elderly: A longitudinal study

BACKGROUND

Although epidemiologic studies have shown an association between the total mass of particulate matter <2.5μm in aerodynamic diameter (PM_2.5) and cardiovascular disease, few studies have examined PM_2.5 constituents associated with vascular and cardiac autonomic dysfunction.

METHODS

In this longitudinal study, we investigated the relationship between PM_2.5 constituents and blood pressure (BP), and markers of the autonomic nervous system. In 466 elderly subjects residing in communities in Seoul, Korea, we examined 16 constituents, seven sources, and total mass concentrations of PM_2.5. We measured the BP, heart rate (HR), and indices of heart rate variability (HRV), such as the standard deviation of normal-to-normal intervals (SDNN), square root of the mean squared differences of successive NN intervals (rMSSD), and two frequency-domain variables (low frequency [LF] and high frequency [HF]). We used linear mixed effects models to assess the association of PM_2.5 constituents and sources with cardiovascular markers.

RESULTS

BP, HR, and rMSSD were associated with concentration of total mass of PM_2.5. For each increase of the interquartile range in PM_2.5 constituents, systolic and diastolic BP, and HR increased by 2.1-3.3mmHg, 1.2-2.3mmHg, and 1.2-1.9bpm, respectively, while the rMSSD, LF, and HF decreased by 8.1-9.3%, 16.6%, and 20.4%, respectively. Particularly, elemental carbon, sulfate, ammonium, lead, and strontium in the PM_2.5 constituents and emissions from oil combustion and incineration were associated with increased BP, HR, and decreased HRV.

CONCLUSIONS

Our results suggest an association between specific PM_2.5 constituents and vascular and cardiac autonomic functions. These findings may provide supportive evidence for developing a pollution reduction plan to prevent cardiovascular diseases.

Design of an Air Pollution Monitoring Campaign in Beijing for Application to Cohort Health Studies

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources.

Aerosol Health Effects from Molecular to Global Scales

Poor air quality is globally the largest environmental health risk. Epidemiological studies have uncovered clear relationships of gaseous pollutants and particulate matter (PM) with adverse health outcomes, including mortality by cardiovascular and respiratory diseases. Studies of health impacts by aerosols are highly multidisciplinary with a broad range of scales in space and time. We assess recent advances and future challenges regarding aerosol effects on health from molecular to global scales through epidemiological studies, field measurements, health-related properties of PM, and multiphase interactions of oxidants and PM upon respiratory deposition. Global modeling combined with epidemiological exposure-response functions indicates that ambient air pollution causes more than four million premature deaths per year. Epidemiological studies usually refer to PM mass concentrations, but some health effects may relate to specific constituents such as bioaerosols, polycyclic aromatic compounds, and transition metals. Various analytical techniques and cellular and molecular assays are applied to assess the redox activity of PM and the formation of reactive oxygen species. Multiphase chemical interactions of lung antioxidants with atmospheric pollutants are crucial to the mechanistic and molecular understanding of oxidative stress upon respiratory deposition. The role of distinct PM components in health impacts and mortality needs to be clarified by integrated research on various spatiotemporal scales for better evaluation and mitigation of aerosol effects on public health in the Anthropocene.

Pregnancy and Lifetime Exposure to Fine Particulate Matter and Infant Mortality in Massachusetts, 2001-2007

Many studies have found associations between particulate matter having an aerodynamic diameter of ≤2.5 μm (PM2.5) and adult mortality. Comparatively few studies evaluated particles and infant mortality, although infants and children are particularly vulnerable to pollution. Moreover, existing studies mostly focused on short-term exposure to larger particles. We investigated PM2.5 exposure during pregnancy and lifetime and postneonatal infant mortality. The study included 465,682 births with 385 deaths in Massachusetts (2001-2007). Exposures were estimated from PM2.5-prediction models based on satellite imagery. We applied extended Cox proportional hazards modeling with time-dependent covariates to total, respiratory, and sudden infant death syndrome mortality. Exposure was calculated from birth to death (or end of eligibility for outcome, at age 1 year) and pregnancy (gestation and each trimester). Models adjusted for sex, birth weight, gestational length, season of birth, temperature, relative humidity, and maternal characteristics. Hazard ratios for total, respiratory, and sudden infant death syndrome mortality per-interquartile-range increase (1.3 μg/m3) in lifetime PM2.5 exposure were 2.66 (95% confidence interval (CI): 2.11, 3.36), 3.14 (95% CI: 2.39, 4.13), and 2.50 (95% CI: 1.56, 4.00), respectively. We did not observe a statistically significant relationship between gestational exposure and mortality. Our findings provide supportive evidence that lifetime exposure to PM2.5 increases risk of infant mortality.

Residential particulate matter and distance to roadways in relation to mammographic density: results from the Nurses' Health Studies

BACKGROUND

High mammographic density is a strong, well-established breast cancer risk factor. Three studies conducted in various smaller geographic settings reported inconsistent findings between air pollution and mammographic density. We assessed whether particulate matter (PM) exposures (PM2.5, PM2.5-10, and PM10) and distance to roadways were associated with mammographic density among women residing across the United States.

METHODS

The Nurses' Health Studies are prospective cohorts for whom a subset has screening mammograms from the 1990s (interquartile range 1990-1999). PM was estimated using spatio-temporal models linked to residential addresses. Among 3258 women (average age at mammogram 52.7 years), we performed multivariable linear regression to assess associations between square-root-transformed mammographic density and PM within 1 and 3 years before the mammogram. For linear regression estimates of PM in relation to untransformed mammographic density outcomes, bootstrapped robust standard errors are used to calculate 95% confidence intervals (CIs). Analyses were stratified by menopausal status and region of residence.

RESULTS

Recent PM and distance to roadways were not associated with mammographic density in premenopausal women (PM2.5 within 3 years before mammogram β = 0.05, 95% CI -0.16, 0.27; PM2.5-10 β = 0, 95%, CI -0.15, 0.16; PM10 β = 0.02, 95% CI -0.10, 0.13) and postmenopausal women (PM2.5 within 3 years before mammogram β = -0.05, 95% CI -0.27, 0.17; PM2.5-10 β = -0.01, 95% CI -0.16, 0.14; PM10 β = -0.02, 95% CI -0.13, 0.09). Largely null associations were observed within regions. Suggestive associations were observed among postmenopausal women in the Northeast (n = 745), where a 10-μg/m3 increase in PM2.5 within 3 years before the mammogram was associated with 3.4 percentage points higher percent mammographic density (95% CI -0.5, 7.3).

CONCLUSIONS

These findings do not support that recent PM or roadway exposures influence mammographic density. Although PM was largely not associated with mammographic density, we cannot rule out the role of PM during earlier exposure time windows and possible associations among northeastern postmenopausal women.

China's Air Quality and Respiratory Disease Mortality Based on the Spatial Panel Model

Background: Air pollution has become an important factor restricting China's economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods: Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM_2.5. Respiratory disease mortality in 31 Chinese provinces from 2004 to 2008 is taken as the main variable to study the spatial effect and impact of air quality and respiratory disease mortality on a large scale. Results: It was found that there is a spatial correlation between the mortality of respiratory diseases in Chinese provinces. The spatial correlation can be explained by the spatial effect of PM_2.5 pollutions in the control of other variables. Conclusions: Compared with the traditional non-spatial model, the spatial model is better for describing the spatial relationship between variables, ensuring the conclusions are scientific and can measure the spatial effect between variables.

Health benefits of PM10 reduction in Iran

Air pollution contains a complex mixture of poisonous compounds including particulate matter (PM) which has wide spectrum of adverse health effects. The main purpose of this study was to estimate the potential health impacts or benefits due to any changes in annual PM₁₀ level in four major megacities of Iran. The required data of PM₁₀ for AirQ software was collected from air quality monitoring stations in four megacities of Iran. The preprocessing was carried out using macro coding in excel environment. The relationship between different presumptive scenarios and health impacts was determined. We also assessed the health benefits of reducing PM₁₀ to WHO Air Quality Guidelines (WHO-AQGs) and National Ambient Air Quality Standards (NAAQSs) levels with regard to the rate of mortality and morbidity in studied cities. We found that the 10 μg/m³ increase in annual PM₁₀ concentration is responsible for seven (95% CI 6-8) cases increase in total number of deaths per 2 × 10⁵ person. We also found that 10.7, 7.2, 5.7, and 5.3% of total death is attributable to short-term exposure to air pollution for Ahvaz, Isfahan, Shiraz, and Tehran, respectively. We found that by attaining the WHO's proposed value for PM₁₀, the potential health benefits of 89, 84, 79, and 78% were obtained in Ahvaz, Isfahan, Shiraz, and Tehran, respectively. The results also indicated that 27, 10, 3, and 1% of health impacts were attributed to dust storm days for Ahvaz, Isfahan, Shiraz, and Tehran, respectively.

1H NMR-based metabolomics study on repeat dose toxicity of fine particulate matter in rats after intratracheal instillation

Systemic metabolic effects and toxicity mechanisms of ambient fine particulate matter (PM_2.5) remain uncertain. In order to investigate the mechanisms in PM_2.5 toxicity, we explored the endogenous metabolic changes and possible influenced metabolic pathways in rats after intratracheal instillation of PM_2.5 by using a ¹H nuclear magnetic resonance (NMR)-based metabolomics approach. Liver and kidney histopathology examinations were also performed. Chemical characterization demonstrated that PM_2.5 was a complex mixture of elements. Histopathology showed cellular edema in liver and glomerulus atrophy of the PM_2.5 treated rats. We systematically analyzed the metabolites changes of serum and urine in rats using ¹H NMR techniques in combination with multivariate statistical analysis. Significantly reduced levels of lactate, alanine, dimethylglycine, creatine, glycine and histidine in serum, together with increased levels of citrate, arginine, hippurate, allantoin and decreased levels of allthreonine, lactate, alanine, acetate, succinate, trimethylamine, formate in urine were observed of PM_2.5 treated rats. The mainly affected metabolic pathways by PM_2.5 were glycine, serine and threonine metabolism, glyoxylate and dicarboxylate metabolism, citrate cycle (TCA cycle), nitrogen metabolism and methane metabolism. Our study provided important information on assessing the toxicity of PM_2.5 and demonstrated that metabolomics approach can be employed as a tool to understand the toxicity mechanism of complicated environmental pollutants.

Evaluation of coarse and fine particles in diverse Indian environments

The estimates of airborne fine particle (PM_2.5) concentrations are possible through rigorous empirical correlations based on the monitored PM₁₀ data. However, such correlations change depending on the nature of sources in diverse ambient environments and, therefore, have to be environment specific. Studies presenting such correlations are limited but needed, especially for those areas, where PM_2.5 is not routinely monitored. Moreover, there are a number of studies focusing on urban environments but very limited for coal mines and coastal areas. The aim of this study is to comprehensively analyze the concentrations of both PM₁₀ and PM_2.5 and develop empirical correlations between them. Data from 26 different sites spread over three distinct environments, which are a relatively clean coastal area, two coal mining areas, and a highly urbanized area in Delhi were used for the study. Distributions of PM in the 0.43-10-μm size range were measured using eight-stage cascade impactors. Regression analysis was used to estimate the percentage of PM_2.5 in PM₁₀ across distinct environments for source identification. Relatively low percentage of PM_2.5 concentrations (21, 28, and 32%) in PM₁₀ were found in clean coastal and two mining areas, respectively. Percentage of PM_2.5 concentrations in PM₁₀ in the highly urbanized area of Delhi was 51%, indicating a presence of a much higher percentage of fine particles due to vehicular combustion in Delhi. The findings of this work are important in estimating concentrations of much harmful fine particles from coarse particles across distinct environments. The results are also useful in source identification of particulates as differences in the percentage of PM_2.5 concentrations in PM₁₀ can be attributed to characteristics of sources in the diverse ambient environments.

Assessment of health and economic effects by PM2.5 pollution in Beijing: a combined exposure-response and computable general equilibrium analysis

Assessment of the health and economic impacts of PM2.5 pollution is of great importance for urban air pollution prevention and control. In this study, we evaluate the damage of PM2.5 pollution using Beijing as an example. First, we use exposure-response functions to estimate the adverse health effects due to PM2.5 pollution. Then, the corresponding labour loss and excess medical expenditure are computed as two conducting variables. Finally, different from the conventional valuation methods, this paper introduces the two conducting variables into the computable general equilibrium (CGE) model to assess the impacts on sectors and the whole economic system caused by PM2.5 pollution. The results show that, substantial health effects of the residents in Beijing from PM2.5 pollution occurred in 2013, including 20,043 premature deaths and about one million other related medical cases. Correspondingly, using the 2010 social accounting data, Beijing gross domestic product loss due to the health impact of PM2.5 pollution is estimated as 1286.97 (95% CI: 488.58-1936.33) million RMB. This demonstrates that PM2.5 pollution not only has adverse health effects, but also brings huge economic loss.

Chemical constituents and sources of ambient particulate air pollution and biomarkers of endothelial function in a panel of healthy adults in Beijing, China

BACKGROUND

Exposure to ambient air pollution has been associated with endothelial dysfunction as reflected by short-term alterations in circulating biomarkers, but the chemical constituents and pollution sources behind the association has been unclear.

METHODS

We investigated the associations between various ambient air pollutants including gases and 31 chemical constituents and seven sources of fine particles (PM2.5) and biomarkers of endothelial function, including endothelin-1 (ET-1), E-selectin, soluble intercellular adhesion molecule 1 (ICAM-1) and vascular cell adhesion molecule 1 (VCAM-1), based on 462 repeated measurements in a panel of 40 college students who were followed for three study periods before and after relocating from a suburban area to an urban area in Beijing, China in 2010-2011. Air pollution data were obtained from central air-monitoring stations. Linear mixed-effects models were used to estimate the changes in biomarkers associated with exposures.

RESULTS

Total PM2.5 mass showed few appreciable associations with examined biomarkers. However, several PM2.5 constituents and related sources showed significant associations with examined biomarkers. PM2.5 from dust/soil and several crustal and transition metals, including strontium, iron, titanium, cobalt and magnesium, were significantly associated with increases in ET-1 at 1-day average; manganese and potassium were significantly associated with increases in ICAM-1 at 2-day average; and PM2.5 from industry and metal cadmium were significantly associated with decreases in VCAM-1 at 1-day average. In addition, carbon monoxide was significantly associated with increasing ICAM-1 at 1-day and 2-day averages, whereas nitric oxide was significantly associated with decreasing ICAM-1 at 1-day and 3-day averages.

CONCLUSIONS

Our results suggest that certain PM2.5 metal constituents were more closely associated with circulating biomarkers of endothelial function than PM2.5, and therefore highlight the research necessity to examine pollution chemical constituents in future studies.

Current Methods and Challenges for Epidemiological Studies of the Associations Between Chemical Constituents of Particulate Matter and Health

Epidemiological studies have been critical for estimating associations between exposure to ambient particulate matter (PM) air pollution and adverse health outcomes. Because total PM mass is a temporally and spatially varying mixture of constituents with different physical and chemical properties, recent epidemiological studies have focused on PM constituents. Most studies have estimated associations between PM constituents and health using the same statistical methods as in studies of PM mass. However, these approaches may not be sufficient to address challenges specific to studies of PM constituents, namely assigning exposure, disentangling health effects, and handling measurement error. We reviewed large, population-based epidemiological studies of PM constituents and health and describe the statistical methods typically applied to address these challenges. Development of statistical methods that simultaneously address multiple challenges, for example, both disentangling health effects and handling measurement error, could improve estimation of associations between PM constituents and adverse health outcomes.

A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components

Most studies on the association between exposure to fine particulate matter (PM2.5) and mortality have considered only total concentration of PM2.5 or individual components of PM2.5, and not the combined effects of concentration and particulate composition. We sought to develop a method to estimate the risk of death from long-term exposure to PM2.5 and the distribution of its components, namely: sulphate, nitrate, ammonium, organic mass, black carbon, and mineral dust. We decomposed PM2.5 exposure into the sum of total concentration and the proportion of each component. We estimated the risk of death due to exposure using a cohort of ~2.4 million Canadians who were followed for vital status over 16 years. Modelling the concentration of PM2.5 with the distribution of the proportions of components together was a superior predictor for mortality than either total PM2.5 concentration alone, or all component concentrations modelled together. Our new approach has the advantage of characterizing the toxicity of the atmosphere in its entirety. This is required to fully understand the health benefits associated with strategies to improve air quality that may result in complex changes not only in PM2.5 concentration, but also in the distribution of particle components.

Ambient particulate air pollution and circulating antioxidant enzymes: A repeated-measure study in healthy adults in Beijing, China

The association of systemic antioxidant activity with ambient air pollution has been unclear. A panel of 40 healthy college students underwent repeated blood collection for 12 occasions under three exposure scenarios before and after relocating from a suburban area to an urban area in Beijing, China in 2010-2011. We measured various air pollutants including fine particles (PM2.5) and determined circulating levels of antioxidant enzymes extracellular superoxide dismutase (EC-SOD) and glutathione peroxidase 1 (GPX1) in the laboratory. An interquartile range increase of 63.4 μg/m(3) at 3-d PM2.5 moving average was associated with a 6.3% (95% CI: 0.6, 12.4) increase in EC-SOD and a 5.5% (95% CI: 1.3, 9.8) increase in GPX1. Several PM2.5 chemical constituents, including negative ions (nitrate and chloride) and metals (e.g., iron and strontium), were consistently associated with increases in EC-SOD and GPX1. Our results support activation of circulating antioxidant enzymes following exposure to particulate air pollution.

Respiratory Health Effects of Ultrafine Particles in Children: A Literature Review

By convention, airborne particles ≤0.1 μm (100 nm) are defined as ultrafine particles (UFPs). UFPs can comprise a large number of particles in particulate matter with aerodynamic diameters ≤2.5 μm (PM_2.5). Despite the documented respiratory health effects of PM_2.5 and concerns that UFPs might be more toxic than larger particular matter, the effects of UFPs on the respiratory system are not well-described. Even less is known about the respiratory health effects of UFPs among particularly vulnerable populations including children. We reviewed studies examining respiratory health effects of UFPs in children and identified 12 relevant articles. Most (8/12) studies measured UFP exposure using central ambient monitors, and we found substantial heterogeneity in UFP definitions and study designs. No long-term studies were identified. In single pollutant models, UFPs were associated with incident wheezing, current asthma, lower spirometric values, and asthma-related emergency department visits among children. Also, higher exhaled nitric oxide levels were positively correlated with UFP dose among children with asthma or allergy to house dust mites in 1 study. Multivariate models accounting for potential co-pollutant confounding yielded no statistically significant results. Although evidence for a relationship between UFPs and children's respiratory is accumulating, the literature remains inconclusive. Interpretation of existing data is constrained by study heterogeneity, limited accounting for UFP spatial variation, and lack of significant findings from multi-pollutant models.

Pre-exposure to fine particulate matters may induce endotoxin tolerance in a mouse model

Exposure to low or moderate doses of lipopolysaccharides (LPS) renders the host tolerance to a subsequent lethal dose of LPS, which is termed as endotoxin tolerance. It is characterized as the decrease in production of pro-inflammatory cytokines and the increase in production of anti-inflammatory mediators in response to a second LPS challenge. The alteration of cytokine profile protects LPS-primed hosts against a normally lethal dose of subsequent LPS challenge. Nevertheless, whether other environmental factors also trigger endotoxin tolerance remains unclear. Both epidemiologic and experimental studies have provided a link between particulate matter and human health. Here, we speculated on the effect of fine particles priming on endotoxin tolerance in a mouse model.