Health Effects Of Air Pollution Research Articles

Chemical Composition of PM2.5-0.3 and PM0.3 Collected in Southern Lebanon and Assessment of Their Toxicity in BEAS-2B Cells

Fine particles (PM2.5) have generally been reported as the major contributor to the adverse health effects of air pollution. Lebanon is characterized by a high density of transport, the production of electricity by generators, and a problem of uncontrolled incineration of household waste. For the purpose of this paper, the physico-chemical properties of fine (PM2.5-0.3) and quasi-ultrafine (PM0.3) particulate matter sampled in Southern Lebanon, were studied. Then, an evaluation and comparison of the toxicity of the different extracted fractions from PM (i.e., native PM2.5-0.3 vs. organic extractable matter fraction (OEM2.5-0.3), and non-extractable matter fraction (NEM2.5-0.3)) was performed. Also, an examination of the toxicity of PM0.3 was conducted indirectly through the evaluation of the OEM0.3 harmfulness. The physico-chemical analysis showed that PM0.3 was much more concentrated than PM2.5-0.3 in organic compounds such as polycyclic aromatic hydrocarbons (PAHs) (28-fold) and their nitrated (N-PAHs, 14-fold) and oxygenated (O-PAHs, 10-fold) derivatives. Normal human bronchial epithelial cells (BEAS-2B) were exposed to PM2.5-0.3, its derived fractions (i.e., OEM2.5-0.3 and NEM2.5-0.3), and OEM0.3 before evaluating the global cytotoxicity, metabolic activation of organic compounds, genotoxicity, and inflammatory response. Different responses were observed depending on the considered fraction of particles. The global cytotoxicity showed a pronounced response related to ATP and LDH activities after exposure to the quasi-ultrafine organic extractable matter fraction (OEM0.3). There was no significant induction of the AhR cell-signaling pathway by NEM2.5-0.3. Despite the apparent difference in the kinetics of induction of the toxicological endpoints under study, OEM0.3 provoked a higher overall cytotoxicity and genotoxicity than OEM2.5-0.3 and total PM2.5-0.3. Taken together, these results clearly showed that the finest particles are more damaging to BEAS-2B cells than PM2.5-0.3 because they are richer in organic compounds, thereby inducing more remarkable toxic effects.

Emission characteristics and health effects of PM2.5 from vehicles in typical areas.

Vehicle emissions have become an important source of urban air pollution, and the assessment of air pollution emission characteristics and health effects caused by specific pollution sources can provide scientific basis for air quality management. In this paper, vehicle PM2.5 pollution in typical urban agglomerations of China (the Beijing-Tianjin-Hebei urban agglomeration (BTHUA), the triangle of the Central China urban agglomeration (TCCUA) and the Chengdu-Chongqing urban agglomeration (CCUA)) were used as research samples to evaluate the emission characteristics, health effects and economic losses of vehicle PM2.5 pollution based on the emission inventory, air quality model and exposure-response function from 2010 to 2020. The results indicated that PM2.5 emissions from vehicles in the three urban agglomerations during 2010-2020 first showed an upward yearly trend and then showed a slow decrease in recent years. Heavy-duty trucks and buses are the main contribution vehicles of PM2.5, and the contribution rates of light-duty vehicles to PM2.5 is increasing year by year. The contribution rate of PM2.5 in Beijing decreased significantly. In addition to capital cities and municipalities directly under the central Government, the emission of pollutants in other cities cannot be ignored. The evaluation results of the impact of PM2.5 pollution from vehicles on population health show that: the number of each health endpoint caused by PM2.5 pollution from vehicles in the BTHUA and CCUA showed an overall upward trend, while the TCCUA showed a downward trend in recent years. Among them, PM2.5 pollution from vehicles in the three major urban agglomerations cause about 78,200 (95% CI: 20,500-138,800) premature deaths, 122,800 (95% CI: 25,600-220,500) inpatients, and 628,400 (95% CI: 307,400-930,400) outpatients and 1,332,400 (95% CI: 482,700-2,075,600) illness in 2020. The total health economic losses caused by PM2.5 pollution from vehicles in the three major urban agglomerations in 2010, 2015 and 2020 were 68.25 billion yuan (95% CI: 21.65-109.16), 206.33 billion yuan (95% CI: 66.20-326.20) and 300.73 billion yuan (95% CI: 96.79-473.16), accounting for 0.67% (95% CI: 0.21-1.07%), 1.19% (95% CI: 0.38%-1.88%) and 1.21% (95% CI: 0.39%-1.90%) of the total GDP of these cities. Due to the differences in vehicle population, PM2.5 concentration, population number and economic value of health terminal units, there are differences in health effects and economic losses among different cities in different regions. Among them, the problems of health risks and economic losses were relatively prominent in Beijing, Chengdu, Chongqing, Tianjin and Wuhan.

Long-term health effects of outdoor air pollution on asthma and respiratory symptoms among adults in low-and middle-income countries (LMICs): a systematic review and meta-analysis

BackgroundFew studies have investigated the association between long-term exposure to outdoor air pollution and the risk of asthma and respiratory symptoms in low-and middle-income countries (LMICs).ObjectiveTo systematically evaluate the epidemiological evidence regarding the associations between long-term exposure to outdoor air pollution and respiratory symptoms in LMICs.MethodsWe searched for literature published between January 1946 and September 2022 in Embase (Ovid), Medline (Ovid), and Web of Science (Core Collection). The air and gaseous pollutants studied included particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and black carbon (BC), and exposure was 1-year duration or more. We conducted a systematic review and meta-analysis with a random-effects model to calculate the relative risk (RR) estimates. A rerun of the databases was conducted in November 2023 with no eligible studies found.ResultsOf the 1,346 studies identified, only six met our inclusion criteria, and these six reported PM2.5, PM10, and NO2 with asthma as the main outcome. Three of these included studies were further included in the meta-analysis because they had data on the same exposure and outcome (PM2.5 and asthma). The main result of our study showed a borderline significant association between a 10 µg/m3 increase in exposure to PM2.5 and an increased risk of asthma (RR 1.21, 95% CI 0.93, 1.50). There was evidence of considerable heterogeneity (I2 = 75.87%). The regression-based Egger test for small-study effects showed no significant publication bias among these three studies.ConclusionOur results indicate that long-term exposure to PM2.5 increases the risk of asthma in LMICs, but studies are scarce and there is a large need for more research in LMICs in this field.Systematic Review Registrationhttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0288667, PROSPERO (CRD42022311326).

Unveiling the health consequences of air pollution in the world’s most polluted nations

Air pollution poses a persuasive threat to global health, demonstrating widespread detrimental effects on populations worldwide. Exposure to pollutants, notably particulate matter with a diameter of 2.5 µm (PM2.5), has been unequivocally linked to a spectrum of adverse health outcomes. A nuanced understanding of the relationship between them is crucial for implementing effective policies. This study employs a comprehensive investigation, utilizing the extended health production function framework alongside the system generalized method of moments (SGMM) technique, to scrutinize the interplay between air pollution and health outcomes. Focusing on a panel of the top twenty polluted nations from 2000 to 2021, the findings yield substantial insights. Notably, PM2.5 concentration emerges as a significant factor, correlating with a reduction in life expectancy by 3.69 years and an increase in infant mortality rates by 0.294%. Urbanization is found to increase life expectancy by 0.083 years while concurrently decreasing infant mortality rates by 0.00022%. An increase in real per capita gross domestic product corresponds with an improvement in life expectancy by 0.21 years and a decrease in infant mortality rates by 0.00065%. Similarly, an elevated school enrollment rate is associated with a rise in life expectancy by 0.17 years and a decline in infant mortality rates by 0.00032%. However, a higher population growth rate is found to modestly decrease life expectancy by 0.019 years and slightly elevate infant mortality rates by 0.000016%. The analysis reveals that per capita greenhouse gas emissions exert a negative impact, diminishing life expectancy by 0.486 years and elevating infant mortality rates by 0.00061%, while per capita energy consumption marginally reduces life expectancy by 0.026 years and increases infant mortality rates by 0.00004%. Additionally, economic volatility shock presents a notable decrement in life expectancy by 0.041 years and an increase in infant mortality rates by 0.000045%, with inflationary shock further exacerbating adverse health outcomes by lowering life expectancy by 0.70 years and elevating infant mortality rates by 0.00025%. Moreover, the study scrutinizes the role of institutional quality, revealing a constructive impact on health outcomes. Specifically, the institutional quality index is associated with an increase in life expectancy by 0.66% and a decrease in infant mortality rates by 0.0006%. Extending the analysis to examine the nuanced dimensions of institutional quality, the findings discern that economic institutions wield a notably stronger positive influence on health outcomes compared to political and institutional governance indices. Finally, the results underscore the pivotal moderating role of institutional quality in mitigating the deleterious impact of PM2.5 concentration on health outcomes, counterbalancing the influence of external shocks, and improving the relationships between explanatory variables and health outcome indicators. These findings offer critical insights for guiding evidence-based policy implications, with a focus on fostering resilient, sustainable, and health-conscious societies.

Understanding the Cardiovascular and Metabolic Health Effects of Air Pollution in the Context of Cumulative Exposomic Impacts.

Poor air quality accounts for more than 9 million deaths a year globally according to recent estimates. A large portion of these deaths are attributable to cardiovascular causes, with evidence indicating that air pollution may also play an important role in the genesis of key cardiometabolic risk factors. Air pollution is not experienced in isolation but is part of a complex system, influenced by a host of other external environmental exposures, and interacting with intrinsic biologic factors and susceptibility to ultimately determine cardiovascular and metabolic outcomes. Given that the same fossil fuel emission sources that cause climate change also result in air pollution, there is a need for robust approaches that can not only limit climate change but also eliminate air pollution health effects, with an emphasis of protecting the most susceptible but also targeting interventions at the most vulnerable populations. In this review, we summarize the current state of epidemiologic and mechanistic evidence underpinning the association of air pollution with cardiometabolic disease and how complex interactions with other exposures and individual characteristics may modify these associations. We identify gaps in the current literature and suggest emerging approaches for policy makers to holistically approach cardiometabolic health risk and impact assessment.

Analyzing Air Pollution in Urban Delhi: A Quantitative Assessment of Particulate Matter (PM) Concentrations

Air pollution poses significant challenges to urban environments, with particulate matter (PM) concentrations being a major concern due to their adverse effects on public health and the environment. This research paper aims to quantitatively assess PM concentrations in urban Delhi, focusing on spatial, temporal, and seasonal variations across diverse urban microenvironments. The research design involved mobile air quality monitoring using real-time PM sensors mounted on a vehicle, coupled with Geographic Information System (GIS) analysis to map pollution hotspots and assess correlations with urban features. The key findings of the study reveal significant spatial variability in PM concentrations, with industrial zones and busy intersections emerging as hotspots for pollution. Seasonal variations in PM levels, with elevated concentrations during winter months and lower levels during the monsoon season, underscore the influence of meteorological factors on air quality dynamics. The study also identifies correlations between PM concentrations and respiratory disease cases, highlighting the adverse health effects of air pollution. The implications of these findings extend to air quality management strategies and public health interventions, emphasizing the need for targeted measures to mitigate pollution levels and protect public health in urban environments.

Quantitative analysis of air pollution levels and its health implications in Delhi-NCR: A longitudinal study

Air pollution is a pressing global issue, particularly acute in rapidly urbanizing regions like Delhi-NCR. This research presents a longitudinal study to quantitatively analyze air pollution levels and their health implications in Delhi-NCR. The research objectives include assessing air quality trends, examining the relationships between various pollutants, and investigating the impact of air pollution on respiratory admissions. Data was sourced from the Ambient Air Quality Monitoring Network, covering the years 2020 to 2022, focusing on key pollutants, including PM2.5, PM10, NO2, SO2, CO, and O3. A range of data analysis techniques, including correlation analysis, regression analysis, longitudinal data analysis, spatial analysis, and compliance with WHO guidelines, were applied. Key findings highlight persistently high levels of air pollutants, strong interrelations among pollutants, and consistent respiratory admissions, especially in winter. Regression analysis confirms a significant link between PM2.5 and respiratory admissions. Longitudinal analysis demonstrates the long-term health consequences of air pollution, and spatial analysis reveals district-wise variations in air quality. The study also emphasizes seasonal strategies, compliance with international guidelines, and socioeconomic disparities in health outcomes. This research has broader implications for evidence-based policymaking, emphasizing the urgency of addressing air quality concerns. It calls for targeted interventions, district-level strategies, season-specific measures, and equitable access to healthcare. These findings offer a comprehensive basis for addressing the air quality crisis in Delhi-NCR, ultimately promoting the well-being of its residents.

Trends in air toxics cancer risk in Southern California, 1998-2018

Air toxics are an important category of air pollutants that are known to cause adverse health effects, including increased cancer risk. Regulatory efforts at federal, state, and local levels have aimed to decrease air toxics emissions over the past several decades. This study evaluated trends in air toxics cancer risks in Southern California using data from 1998 to 2018. We estimated air toxics cancer risk for each of four iterations of the South Coast Air Quality Management District’s Multiple Air Toxics Exposure Study, which included at least one year of measurements at 10 stations and air toxics modeling for each iteration. Cancer risks were calculated using the measured and modeled air toxics concentrations averaged over a one to two year period and multiplied by the corresponding cancer potency factor and combined exposure factor that accounted for multiple exposure pathways and children’s increased sensitivity to the health effects of air pollution. We examined temporal trends in overall air toxics cancer risks and evaluated changes in the air toxics species that contributed most to cancer risk in the region. Both measurement and modeling results show that air toxics cancer risk in Southern California decreased by more than 80% between 1998 and 2018, including a decrease of about 50% from 2012 to 2018. Diesel particulate matter was the main risk driver, followed by benzene, 1,3-butadiene, and formaldehyde. We found that more densely populated communities showed larger decreases than sparsely populated areas. The substantial decrease in air toxics levels over this 20-year period points to the success of air pollution policies aimed at addressing air toxics emissions and can inform future policy efforts to further reduce air toxics health impacts.

Toxicity of particles derived from combustion of Ethiopian traditional biomass fuels in human bronchial and macrophage-like cells

The combustion of traditional fuels in low-income countries, including those in sub-Saharan Africa, leads to extensive indoor particle exposure. Yet, the related health consequences in this context are understudied. This study aimed to evaluate the in vitro toxicity of combustion-derived particles relevant for Sub-Saharan household environments. Particles (< 2.5 µm) were collected using a high-volume sampler during combustion of traditional Ethiopian biomass fuels: cow dung, eucalyptus wood and eucalyptus charcoal. Diesel exhaust particles (DEP, NIST 2975) served as reference particles. The highest levels of particle-bound polycyclic aromatic hydrocarbons (PAHs) were found in wood (3219 ng/mg), followed by dung (618 ng/mg), charcoal (136 ng/mg) and DEP (118 ng/mg) (GC–MS). BEAS-2B bronchial epithelial cells and THP-1 derived macrophages were exposed to particle suspensions (1–150 µg/mL) for 24 h. All particles induced concentration-dependent genotoxicity (comet assay) but no pro-inflammatory cytokine release in epithelial cells, whereas dung and wood particles also induced concentration-dependent cytotoxicity (Alamar Blue). Only wood particles induced concentration-dependent cytotoxicity and genotoxicity in macrophage-like cells, while dung particles were unique at increasing secretion of pro-inflammatory cytokines (IL-6, IL-8, TNF-α). In summary, particles derived from combustion of less energy dense fuels like dung and wood had a higher PAH content and were more cytotoxic in epithelial cells. In addition, the least energy dense and cheapest fuel, dung, also induced pro-inflammatory effects in macrophage-like cells. These findings highlight the influence of fuel type on the toxic profile of the emitted particles and warrant further research to understand and mitigate health effects of indoor air pollution.

Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach.

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5-18%). Annual average levels in different zones ranged between 39.7 μg/m3 (interquartile range: 29.8-46.8) in 2008 and 30.4 μg/m3 (interquartile range: 22.7-37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 μg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3-16.5 μg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.

Direct Measurement of Aerosol Liquid Water Content: A Case Study in Summer in Nanjing, China.

Aerosol liquid water content (ALWC) affects the mass loading, optical properties, and toxicity of aerosols. However, the measurement of ALWC is very rare due to its requirement of sophisticated instruments and its high operational costs. In this work, we improved on our previous simple, low-cost method by using a combination of one real-time fine particulate matter (PM2.5) monitor and two turbidimeters and successfully applied these for the direct measurement of ALWC in PM2.5 in Nanjing during the summer of 2023. The average ALWC during this measurement period occupied ~1/6 of the total PM2.5 mass, and this contribution was even greater with the elevation in the PM2.5 concentration. The ALWC was, as anticipated, closely related to the relative humidity (RH) and PM2.5 concentrations, but it did not always increase with the air quality index (AQI) due to the fact that polluted periods in summer were often governed by high O3 levels, not PM2.5 levels. The ALWC also had a great impact on visibility; it could decrease the visibility rapidly to hazy conditions when the dry PM2.5 was not high (~30 μg m-3) or the AQI was "good" (75~100), indicating that the air quality classified as "good" using the dry PM2.5 concentration might actually be "lightly polluted" if the ALWC is included. We also found that the air mass originating from Northeast China had the lowest PM2.5 mass concentration yet the highest ALWC values due to its high RH. Moreover, the quantification of ALWC levels can help us understand the solubility/bioavailability and thus the toxic effects of some specific components (for example, heavy metals or organics). Moreover, the influence of ALWC on air quality classifications should also be considered in the assessment of the health effects of air pollution and in public health early warning and protection.

What is the role of activism in air pollution politics? Understanding policy change in Poland

There has been growing awareness across the world of the negative health effects of air pollution. Poland is the European country that is worst affected by this problem, and the Polish government has in recent years adopted a number of measures designed to reduce coal use. This paper explores the role of civil society activism in this shift, investigating the extent to which local activists played a catalytic role in shaping popular awareness of air pollution and accounting for policy developments in this area. We draw on individual-level data from two Eurobarometer surveys together with qualitative data from a series of original elite interviews and the analysis of related policy documents, and we find little evidence that activism was a driver of variations in local popular awareness of air pollution, but support for the supposition that activism played a major role in shaping policy change at local level.

Adapting non-parametric spline representations of outdoor air pollution health effects associations for use in public health benefits assessment

AbstractThe magnitude and shape of the association between outdoor air pollution concentrations and health need to be characterized in order to estimate public health benefits from proposed mitigation strategies. Specialized parametric functions have been proposed for this characterization. However, non-parametric spline models offer more flexibility, less bias, and predictive power, in describing these associations and are thus preferred over relatively simple parametric formulations. Unrestricted spline representations are often reported but many are not suitable for benefits analysis due to their erratic concentration-response behavior and are usually not presented in a format consistent with the requirements necessary to conduct a benefits analysis. We propose a method to adapt non-parametric spline representations of concentration-response associations that are suitable for public health benefits analysis by transforming spline predictions and its uncertainty over the study exposure range to a new spline formulation that is both monotonically increasing and restricted to concentration-response patterns suitable for use in health benefits assessment. We selected two examples of the association between long-term exposure to fine particulate matter and mortality in Canada and the USA that displayed spline fits that were neither monotonically increasing nor suitable, we suggest, for benefits analysis. We suggest our model is suitable for benefits analysis and conduct such analyses for both Canada and the USA, comparing benefits estimates to traditional models. Finally, we provide guidance on how to report spline fitting results such they can be used either in benefits analysis directly, or to fit our new model.

Levels and sources of polycyclic aromatic hydrocarbons (PAHs) near hospitals and schools using leaves and barks of Sambucus nigra and Acacia melanoxylon

Polycyclic aromatic hydrocarbons (PAHs) are among the most studied organic compounds in urban environments, due to their known threat to human health. This study extends the current knowledge regarding the ability of different vegetative parts of different tree species to accumulate PAHs. Moreover, exposure intensity to PAHs in areas frequented by population susceptible to adverse health effects of air pollution is evaluated. For this, leaves and barks of Sambucus nigra (S. nigra) and Acacia melanoxylon (A. melanoxylon) were collected at urban areas in the Andean city of Quito, at seven points near hospitals and schools. A methodology, previously developed, for the extraction, purification, and quantification of PAHs associated with the leaves and bark of S. nigra was employed and also validated for leaves and bark of A. melanoxylon. The total PAH level varied from 119.65 ng g−1 DW (dry weight) to 1969.98 ng g−1 DW (dry weight) with naphthalene (Naph), fluoranthene (Flt), pyrene (Pyr), chrysene (Chry), and benzo[a]pyrene (BaP) predominating in all samples. The results indicate that the leaves and bark of tree species studied have certain abilities to bio-accumulate PAH according to their molecular weight. The leaves of S. nigra and bark of A. melanoxylon showed the highest ability to accumulate PAHs, mainly those with high and medium molecular weight, respectively. The highest incidence of light molecular weight PAHs was found in the leaves of A. melanoxylon. Furthermore, coal combustion, biomass burning, and vehicle emissions were identified as the main PAHs sources. Concentrations of PAHs associated with tree species suggest an affectation in areas frequented by populations susceptible to air pollution. This fact shows the importance of regulatory scheme to significantly improve the air quality in the city integrating a knowledge-based decision-making.

The Burden of Cardiovascular Disease from Air Pollution in Rwanda.

Rwanda, like many countries in sub-Saharan Africa, is still relatively early in development. Industrialization and urbanization are major drivers of the county's economic growth. Rwanda is also undergoing an epidemiological transition, from a pattern of morbidity and mortality dominated by infectious diseases to a pattern shaped by non-communicable diseases (NCDs). The rise in NCDs is due, in part, to increasing exposures to environmental hazards. These include emissions from the growing number of motor vehicles and toxic occupational exposures. Cardiovascular disease (CVD) is now an increasingly important cause of death in Rwanda, and ambient air pollution is a CVD risk factor of growing importance. To quantify the burden of CVD attributable to air pollution in Rwanda and identify opportunities for prevention and control of air pollution and pollution-related disease. We relied on the 2019 Global Burden of Disease (GBD) study for information on levels, sources, and trends in household and ambient air pollution and the burden of pollution-related disease in Rwanda. Information on pollution sources was obtained from the Health Effects Institute State of Global Air 2019 report. An estimated 3,477 deaths (95% Uncertainty Interval [UI]: 2,500-4,600) in Rwanda in 2019 were attributable to air pollution-related CVD. Of these, 689 (UI: 283-1,300) deaths were from ambient air pollution-related CVD, while 2,788 (UI: 1,800-3,800) deaths were from household air pollution-related CVD. Rwanda is experiencing increased rates of disease and premature death from NCDs, including CVD, as the country grows economically. While household air pollution is still the top pollution-related cause of disease and premature death, rising levels of ambient air pollution are an increasingly important CVD risk factor. Actions taken now to curb rising levels of ambient air pollution will improve health, reduce CVD, increase longevity, and produce great economic benefit for Rwanda. The single most effective intervention against air pollution will be a rapid nationwide transition to renewable energy. We recommend additionally that Rwanda prioritize air pollution prevention and control, establish a robust, nationwide air monitoring network, support research on the health effects of air pollutants, and build national research capacity. The allocation of increased resources for rural and urban public health and health care will complement air pollution control measures and further reduce CVD. To incentivize a rapid transition to renewable energy in Rwanda and other nations, we recommend the creation of a new Global Green Development Fund.

Observational studies generate misleading results about the health effects of air pollution: Evidence from chronic air pollution and COVID-19 outcomes.

Several observational studies from locations around the globe have documented a positive correlation between air pollution and the severity of COVID-19 disease. Observational studies cannot identify the causal link between air quality and the severity of COVID-19 outcomes, and these studies face three key identification challenges: 1) air pollution is not randomly distributed across geographies; 2) air-quality monitoring networks are sparse spatially; and 3) defensive behaviors to mediate exposure to air pollution and COVID-19 are not equally available to all, leading to large measurement error bias when using rate-based COVID-19 outcome measures (e.g., incidence rate or mortality rate). Using a quasi-experimental design, we explore whether traffic-related air pollutants cause people with COVID-19 to suffer more extreme health outcomes in New York City (NYC). When we address the previously overlooked challenges to identification, we do not detect causal impacts of increased chronic concentrations of traffic-related air pollutants on COVID-19 death or hospitalization counts in NYC census tracts.

Seasonal variations in respiratory morbidity in primary care and its correlation with the quality of air in urban Odisha, India.

Poor air quality, especially in urban regions among low-and middle-income countries such as India poses a significant healthcare challenge. Amongst urban areas, metropolitan cities garner the utmost importance for air quality related policies and studies with limited studies from tier II cities which are thought to be relatively immune to air pollution. Hence, we aimed to identify the most frequent respiratory morbidities and explore its correlation with exposure to ambient PM2.5 particles in Bhubaneswar (a tier II city in coastal India), Odisha. A chart review was carried out through data extracted from the records of urban health centres. Data on PM2.5 concentrations were obtained from Odisha State Pollution Control Board. The morbidities were coded by using the International Classification of Primary Care‑2 system (ICPC-2). Descriptive statistics such as incidence of respiratory illnesses was computed across seasons. The ecological correlation between respiratory morbidity patterns and corresponding concentration of PM2.5 in air was analysed for each season. A positive correlation (r = o.94) between PM2.5 and respiratory morbidities was observed. The incidence of respiratory morbidities was 183.31 per 1000 person year. We identified 21 out of 43 respiratory diseases classified under ICPC-2. Upper Respiratory Tract Infection was the most commonly (116.8 per 1000 person year) incident condition. We observed one-fourth increase in the incidence of respiratory illnesses during winters. Respiratory morbidities are common in urban Bhubaneswar which follows a seasonal pattern and are possibly linked with the seasonal variations in levels of PM2.5 particles. Our study highlights that tier II cities are equally prone to health effects of air pollution. Future programmes and policies should take these cities into consideration too.

Comparison of Air Pollution Exposures and Health Effects Associations Using 11 Different Modeling Approaches in the Women's Health Initiative Memory Study (WHIMS).

Many approaches to quantifying air pollution exposures have been developed. However, the impact of choice of approach on air pollution estimates and health-effects associations remains unclear. Our objective is to compare particulate matter with aerodynamic diameter () concentrations and resulting health effects associations using multiple estimation approaches previously used in epidemiologic analyses. We assigned annual exposure estimates from 1999 to 2004 derived from 11 different approaches to Women's Health Initiative Memory Study (WHIMS) participant addresses within the contiguous US. Approaches included geostatistical interpolation approaches, land-use regression or spatiotemporal models, satellite-derived approaches, air dispersion and chemical transport models, and hybrid models. We used descriptive statistics and plots to assess relative and absolute agreement among exposure estimates and examined the impact of approach on associations between and death due to natural causes, cardiovascular disease (CVD) mortality, and incident CVD events, adjusting for individual-level covariates and climate-based region. With a few exceptions, relative agreement of approach-specific exposure estimates was high for concentrations across the contiguous US. Agreement among approach-specific exposure estimates was stronger near monitors, in certain regions of the country, and in 2004 vs. 1999. Collectively, our results suggest but do not quantify lower agreement at local spatial scales for . There was no evidence of large differences in health effects associations with among estimation approaches in analyses adjusted for climate region. Different estimation approaches produced similar spatial patterns of concentrations across the contiguous US and in areas with dense monitoring data, and effects associations were similar among estimation approaches. estimates and effects associations may differ more in samples drawn from smaller areas or areas without substantial monitoring data, or in analyses with finer adjustment for participant location. Our results can inform decisions about estimation approach in epidemiologic studies, as investigators balance concerns about bias, efficiency, and resource allocation. Future work is needed to understand whether these conclusions also apply in the context of other air pollutants of interest. https://doi.org/10.1289/EHP12995.

Optimizing prevention strategies for PM2.5-related health risks in Nakhon Ratchasima

The detrimental effects of PM2.5 on the health of urban populations, especially in developing countries, are being carefully addressed by governments worldwide. To mitigate the adverse health effects of air pollution, this paper presents a case study and suggests a three-phase plan for implementing a prediction and control approach in the Thai metro region of Nakhon Ratchasima (NRM). A data-driven assessment of the region's air pollution situation is conducted in the initial phase, which is then followed by an analysis of the health risks related to PM2.5 concentrations. It is therefore imperative to determine which machine learning model has the best capabilities to estimate PM2.5 concentration. With the help of this advanced predictive capability, decision-makers will have an important window of opportunity to put preventive measures in place to safeguard the population from the adverse effects of air pollution. The study showed that there were respiratory diseases in the NRM area because of high concentrations of PM2.5 particles, primarily from vehicle exhaust, which far exceeded Thailand's threshold of 15 μg m−3. A total of 10,379 people, or 16.91% of the affected population, lived in zones with PM2.5 concentrations >38 μg m−3 in 2019. Another 741 people, or 1.21% of the population, lived in zones with PM2.5 values between 36 and 37 μg m−3. The study finds that Extra-Trees regression combined with AdaBoost has the best-predicting capacity for PM2.5 ambient concentration in the NRM area out of the 13 machine-learning regression models examined. This case study presents an additional tool for policymakers to employ in controlling adverse health effects in urban areas.

The combined effect of air pollution and non-optimal temperature on mortality in Shandong Province, China: establishment of air health index.

The air health index (AHI) captures the combined effects of air pollution and non-optimal temperatures and helps assess the atmospheric environment's overall health risk. Shandong Province is a crucial industrial base in China, and the health effects of air pollution and non-optimal temperature cannot be ignored. To construct an AHI for Shandong Province and assess the district-level mortality burden due to AHI in the study area. Daily district-specific mortality, meteorological, and air pollution data over 2013-2018 were collected in Shandong Province, China. The AHI construction eventually incorporated PM2.5 and NO2, O3, and non-optimal temperatures. Attributable fraction (AF) and attributable number (AN) were used to estimate the district-specific mortality burden attributable to AHI. The average AHI value observed in Shandong Province was 6. Our research revealed a positive association between the total AHI and total mortality, with an overall trend of a slow increase followed by a rapid increase. The exposure-response curves, when stratified by gender, age, and cause of death, were approximately consistent with the overall trend. The provincial attributable fraction (AF) was 5.31% (95% CI 4.58%, 5.91%), and the attributable number (AN) was 188,246 (95% CI 162,396, 209,533). Overall, higher ANs mainly appeared in the southwestern area, while higher values of AF were observed in the central-eastern and central-northern areas. The air health index performs well in predicting death burden and can convey health risks related to exposure to the ambient environment to the public.