A novel method of using sound waves and artificial intelligence for the detection of vehicle's proximity from cyclists and E-scooters

Outdoor air pollution has been found to have a significant adverse effect on health. When the authors attempted to monitor air quality that cyclists or e-scooter users' breath during commuting in different locations for health and safety analysis, it was found that the existence of internal combustion engine (ICE) cars has a significant effect on the pollution levels and the monitoring process. To comprehensively study the effect of cars and traffic on air quality that cyclists and e-scooters users experience, a low-cost and reliable system was needed to detect the proximity of cars that have diesel or petrol engines. Video cameras can be used to visually detect vehicles, but in the modern age with the existence of many electric and hybrid vehicles and the need to reduce the cost of instrumentation, there was a need to determine the passing of vehicles near e-scooter and bike users from the combined engine and tires sounds. To address this issue, this study suggests a novel approach of using sound waves of internal combustion engines and tire sounds during the passing of cars, combined with AI techniques (neural networks), to detect the proximity of cars from cyclists and e-scooter users. Audio-visual data was collected using Go-Pro cameras in order to combine the data with GPS location and pollution levels. Geographical data maps were produced to demonstrate the density of cars that cyclists encounter when on or near the road. This method will enable air quality monitoring research to detect the existence of ICE cars for future correlation with measured pollution levels. The proposed method allows for:•The automated selection of sensitive features from sound waves to detect vehicles.•Low-cost hardware which is independent of orientation that can be integrated with other air quality and GPS sensors.•The successful application of sensor fusion and neural networks.

Estimating the health impacts of exposure to Air pollutants and the evaluation of changes in their concentration using a linear model in Iran

In big and industrial cities of developing countries, illness and mortality from long-term exposure to air pollutants have become a serious issue. This research was carried out in 2019-2020 to estimate the health impacts of PM10, NO2 and O3 pollutants by using AirQ+ and R statistical programming software in Arak, Isfahan, Tabriz, Shiraz, Karaj, and Mashhad. Mortality statistics, number of people in required age groups, and amount of pollutants were gathered respectively from different agencies like Statistics and Information Technology of the Ministry of Health, Statistical Center, and Department of Environment and by using Excel, the average 24-hour and 1-hour concentration and maximum 8-hour concentration for PM10, NO2 and O3 pollutants were gathered. We used linear mixed impacts model to account for the longitudinal observations and heterogeneity of the cities. The results of the study showed high number of deaths due to chronic bronchitis in adults, premature death of infants, and respiratory diseases in Mashhad. This research highlights the importance of estimation of health impacts from exposure to air pollutants on residents of the studied cities.

Particulate matter 1µm (PM1) dataset collected by low-cost sensors in residential and industrial areas at the neighborhood level

The incursion of low-cost sensors (LCS) for monitoring particulate matter in different fractions of particles (PM10, PM2.5, and PM1) allows the characterization of the concentration levels of specific sources or events, including the analysis of ultrafine fractions (PM1). Several studies have documented adverse effects on human health due to exposure to PM1, such as morbidity and mortality from respiratory, cardiovascular, and, in some cases, carcinogenic diseases. Hence, studying the concentration levels and the sources that cause PM1 is imperative. LCS is an alternative to understanding contaminant concentration levels by considering spatial and temporal community dynamics by monitoring critical zones. Furthermore, collecting and managing large amounts of data through automatic processing and analysis generates information to support decision-making to reduce exposure and risks to people's health. The dataset presents the concentration level of PM1 (µg/m3) calculated from the particles of size 0.03 µm, 0.05 µm, and 1.0 µm recorded and counted by the sensor in a sample per minute for 24 h for seven continuous days. The values of the meteorological factors of relative humidity, temperature, and heat index complement these attributes. The dataset comprises records collected (in the same period) at four particulate matter monitoring stations, which compose an LCS network supported by Internet of Things (IoT) technologies. The data collection points were located in different areas of Reynosa, Mexico, considering strategic places for monitoring environmental pollution, such as industrial parks, residential areas, avenues with high vehicular traffic and transportation of heavy cargo, and an airport.

A novel free-air diesel and ozone enrichment (FADOE) research platform

Air pollution is an escalating concern in the modern world, posing substantial threats to ecosystem processes. While the importance of comprehending the impact of pollutants on natural environments is evident, conducting rigorous field-based experiments presents formidable challenges. Elevating pollutant concentrations within open air environments in a controlled manner is complex. Nonetheless, such real-world experiments are invaluable for revealing the genuine influence of air pollutants on ecosystems and their functioning. Field-scale measurements have emerged as a pivotal avenue for advancing our understanding of the interactions between air pollutants and the natural world, providing unique insights into ecosystem dynamics, including critical processes like pollination and natural pest regulation. In atmospheric and ecological research, free-air exposure systems have proven effective in elevating carbon dioxide (CO2) and ozone (O3) concentrations, facilitating the exploration of their ecological consequences. Yet, nitrogen oxides (NOx), a class of pollutants with significant ecological and atmospheric relevance, have largely eluded field-based ecological investigations. This paper introduces the recently developed FADOE (Free-Air Diesel and Ozone Enrichment) platform, which allows the elevation of O3 and diesel exhaust (including NOx) within a field-scale context. Comprehensive information on the system's design, construction, and performance data from the 2023 summer season is presented.•Air pollution and ecosystem functioning•Elevated ozone and nitrogen oxides (NOx)•Free-air exposure systems for field scale measurements.

Association of the external environmental exposome and obesity: A comprehensive nationwide study in 2019 among Chinese children and adolescents

OBJECTIVE

Children and adolescents are particularly vulnerable to the effects of various environmental factors, which could disrupt growth processes and potentially lead to obesity. Currently, comprehensive and systematic assessments of these environmental exposures during developmental periods are lacking. Therefore, this study aims to evaluate the association between external environmental exposures and the incidence of obesity in children and adolescents.

METHODS

Data was collected from the 2019 Chinese National Survey on Students' Constitution and Health, including 214,659 Han children aged 7 to 19. Body Mass Index (BMI) and BMI-for-age z-score (zBMI) were the metrics used to assess overweight and obesity prevalence. The study assessed 18 environmental factors, including air pollutants, natural space, land cover, meteorological conditions, built environment, road conditions, and artificial light at night. Exposome-wide association study (ExWAS) to analyze individual exposures' associations with health outcomes, and Weighted Quantile Sum (WQS) to assess cumulative exposure effects.

RESULTS

Among the children and adolescents, there were 24.2 % participants classified as overweight or obesity. Notably, 17 out of 18 environmental factors exhibited significant associations with zBMI and overweight/obesity. Seven air pollutants, road conditions, and built density were positively correlated with higher zBMI and obesity risk, while NDVI, forests, and meteorological factors showed negative correlations. Co-exposure analysis highlighted that SO2, ALAN, PM10, and trunk road density significantly increased zBMI, whereas rainfall, grassland, and forest exposure reduced it. Theoretically reduction in the number and prevalence of cases was calculated, indicating potential reductions in prevalence of up to 4.51 % for positive exposures and 5.09 % for negative exposures. Notably, substantial reductions were observed in regions with high pollution levels.

CONCLUSION

This large-scale investigation, encompassing various environmental exposures in schools, highlights the significant impact of air pollution, road characteristics, rainfall, and forest coverage on childhood obesity.

Assessing developmental and transcriptional effects of PM2.5 on zebrafish embryos

Investigating fine particulate matter (PM2.5) toxicity is crucial for health risk assessment and pollution control. This study explores the developmental toxicity of two PM2.5 sources: standard reference material 2786 (NIST, USA) and PM2.5 from Chakri Naruebodindra Medical Institute (CNMI, Thailand) located in the Bangkok Metropolitan area. Zebrafish embryos exposed to these samples exhibited embryonic mortality, with 50% lethal concentration (LC50) values of 1476 µg/mL for standard PM2.5 and 512 µg/mL for CNMI PM2.5. Morphological analysis revealed malformations, including pericardial and yolk sac edema, and blood clotting in both groups. Gene expression analysis highlighted source-specific effects. Standard PM2.5 downregulated sod1 and cat while upregulating gstp2. Inflammatory genes tnf-α and il-1b were upregulated, and nfkbi-αa was downregulated. Apoptosis-related genes bax, bcl-2, and casp3a were downregulated. CNMI PM2.5 consistently downregulated all examined genes. These findings underscore PM2.5 source variability's significance in biological system impact assessment, providing insights into pollutant-gene expression interactions. The study emphasizes the need for source-specific risk assessment and interventions to address PM2.5 exposure's health impacts effectively.

Particulate matter 2.5 exposure during pregnancy and birth outcomes: Evidence from Colombia

Particulate matter is a type of air pollution that consists of fine particles with a diameter <2.5 μm (PM2.5), which can easily penetrate the respiratory system and enter the bloodstream, increasing health risks for pregnant women and their unborn babies. Recent reports have suggested that there is a positive association between PM2.5 exposure and adverse pregnancy outcomes. However, most evidence of this relationship comes from Western countries. Thus, the objective of this study was to evaluate the association between PM2.5 exposure during pregnancy and birth outcomes among pregnant women in Colombia. This study included 542,800 singletons born in 2019 to Colombian women, aged 15+ years, residing in 981 municipalities. Data on parental, child and birth characteristics were extracted from anonymized live birth records. Satellite-based estimates of monthly PM2.5 concentrations at the surface level were extracted for each municipality from the Atmospheric Composition Analysis Group (ACAG). PM2.5 exposure during pregnancy was indicated by the monthly average of PM2.5 concentrations across the pregnancy duration for the municipality where the child was born. The associations of municipality-level PM2.5 concentration during pregnancy with pre-term birth (PTB) and low birth weight (LBW) were tested in separate two-level logistic regression models, with babies nested within municipalities. The prevalence of PTB and LBW were 8.6 % and 8.3 %, respectively. The mean PM2.5 concentration across the 981 municipalities was 18.26 ± 3.30 μg/m3, ranging from 9.11 to 31.44 μg/m3. Greater PM2.5 concentration at municipality level was associated with greater odds of PTB (1.05; 95%CI: 1.04-1.06) and LBW (1.04; 95%CI: 1.03-1.05), after adjustment for confounders. Our findings provide new evidence on the association between PM2.5 on adverse pregnancy outcomes from a middle-income country.

Emerging concern on air pollution and health: Trade-off between air pollution exposure and physical activity

Air pollution is a major contributor to the global disease burden, especially affecting respiratory and cardiovascular health. However, physical activity is associated with improved lung function, a slower decline in lung function, and lower mortality. The public is more likely to be exposed to air pollution during outdoor physical activity. However, studies on how long-term and short-term exposure to air pollution interacts with physical activity yield inconsistent results, and the thresholds for air pollution and physical activity remain unclear. Thus, more studies are needed to provide sufficient evidence to guide the public to safely engage in outdoor physical activity when exposed to air pollution.

Associations of fine particulate matter with incident cardiovascular disease; comparing models using ZIP code-level and individual-level fine particulate matter and confounders

BACKGROUND

PM2.5 has been positively associated with cardiovascular disease (CVD) incidence. Most evidence has come from cohorts and administrative databases. Cohorts typically have extensive information on potential confounders and residential-level exposures. Administrative databases are usually more representative but typically lack information on potential confounders and often only have exposures at coarser geographies (e.g., ZIP code). The weaknesses in both types of studies have been criticized for potentially jeopardizing the validity of their findings for regulatory purposes.

METHODS

We followed 101,870 participants from the US-based Nurses' Health Study (2000-2016) and linked residential-level PM2.5 and individual-level confounders, and ZIP code-level PM2.5 and confounders. We used time-varying Cox proportional hazards models to examine associations with CVD incidence. We specified basic models (adjusted for individual-level age, race and calendar year), individual-level confounder models, and ZIP code-level confounder models.

RESULTS

Residential- and ZIP code-level PM2.5 were strongly correlated (Pearson r = 0.88). For residential-level PM2.5, the hazard ratio (HR, 95 % confidence interval) per 5 μg/m3 increase was 1.06 (1.01, 1.11) in the basic and 1.04 (0.99, 1.10) in the individual-level confounder model. For ZIP code-level PM2.5, the HR per 5 μg/m3 was 1.04 (0.99, 1.08) in the basic and 1.02 (0.97, 1.08) in the ZIP code-level confounder model.

CONCLUSION

We observed suggestive positive, but not statistically significant, associations between long-term PM2.5 and CVD incidence, regardless of the exposure or confounding model. Although differences were small, associations from models with individual-level confounders and residential-level PM2.5 were slightly stronger than associations from models with ZIP code-level confounders and PM2.5.

Integrating traffic pollution dispersion into spatiotemporal NO2 prediction

Accurately predicting ambient NO2 concentrations has great public health importance, as traffic-related air pollution is of major concern in urban areas. In this study, we present a novel approach incorporating traffic contribution to NO2 prediction in a fine-scale spatiotemporal model. We used nationally available traffic estimate dataset in a scalable dispersion model, Research LINE source dispersion model (RLINE). RLINE estimates then served as an additional input for a validated spatiotemporal pollution modeling approach. Our analysis uses measurement data collected by the Multi-Ethnic Study of Atherosclerosis and Air Pollution in the greater Los Angeles area between 2006 and 2009. We predicted road-type-specific annual average daily traffic (AADT) on road segments via national-level spatial regression models with nearest-neighbor Gaussian processes (spNNGP); the spNNGP models were trained based on over half a million point-level traffic volume measurements nationwide. AADT estimates on all highways were combined with meteorological data in RLINE models. We evaluated two strategies to integrate RLINE estimates into spatiotemporal NO2 models: 1) incorporating RLINE estimates as a space-only covariate and, 2) as a spatiotemporal covariate. The results showed that integrating the RLINE estimates as a space-only covariate improved overall cross-validation R2 from 0.83 to 0.84, and root mean squared error (RMSE) from 3.58 to 3.48 ppb. Incorporating the estimates as a spatiotemporal covariate resulted in similar model improvement. The improvement of our spatiotemporal model was more profound in roadside monitors alongside highways, with R2 increasing from 0.56 to 0.66 and RMSE decreasing from 3.52 to 3.11 ppb. The observed improvement indicates that the RLINE estimates enhanced the model's predictive capabilities for roadside NO2 concentration gradients even after considering a comprehensive list of geographic covariates including the distance to roads. Our proposed modeling framework can be generalized to improve high-resolution prediction of NO2 exposure - especially near major roads in the U.S.

Speed limits and their effect on air pollution in Mexico City: A quasi-experimental study

Speed limits are an evidence-based intervention to prevent traffic collisions and deaths, yet their impact on air pollution in cities is understudied. The objective of this study was to investigate the association between lower speed limits and air pollution. We leverage the introduction of a new road safety policy in Mexico City in December 2015 which lowered speed limits, increased fines, and installed speed radars to enforce compliance. We tested whether the policy had an impact on particulate matter (PM2.5) and nitrogen dioxide (NO2) at the city level, and whether air-quality monitoring stations' proximity to speed radars moderated this effect due to more acceleration and deceleration around radars. NO2 and PM2.5 concentrations from January 2014 to December 2018 were obtained from the National System of Air Quality Information. Air-quality monitoring stations were classified as in close-proximity or far-from-speed radars. Interrupted time series analyses were conducted for each outcome separately, using linear mixed models and adjusting for seasonality and time-varying confounders: registered vehicles, temperature, wind-speed and relative humidity. The results suggest improvement in both contaminants after the speed limits policy. For NO2, the pre-policy trend was flat, while the post-policy trend showed a decline in concentrations of 0.04 ppb/week. For PM2.5, concentrations were increasing pre-policy by 0.08 μg/m3 per week, then this trend flattened in the post-policy period to a weekly, non-significant, increase of 0.03 μg/m3 (p = 0.08). Air-quality monitors' proximity to speed radars did not moderate the effect of the policy on either of the pollutants. In conclusion, the speed limits policy implemented in Mexico City in 2015 was associated with improvements in air pollution.

Future fire-smoke PM2.5 health burden under climate change in Paraguay

Recent years have seen a rise in wildfire and extreme weather activity across the globe, which is projected to keep increasing with climate-induced conditions. Air pollution, especially fine particulate matter (PM2.5) concentration, is heavily affected by PM2.5 emissions from wildfire activity. Paraguay has been historically suffering from fires, with an average of 2.3 million hectares burnt per year during the 2003-2021 period. Annual PM2.5 concentration in Paraguay is 13.2 μg/m3, more than double the recommended by the WHO. We estimate that, historically, almost 40 % of fine air particulates can be attributed to fires. Using a random forest algorithm, we estimate future fire activity and fire related PM2.5 under different climate change scenarios. With global warming, we calculate that fire activity could increase by up to 120 % by 2100. Annual fire smoke PM2.5 from fires is expected to increase by 7.7 μg/m3 by 2100. Under these conditions, Paraguay is expected to suffer an increase in 3500 deaths per year attributable to fire smoke PM2.5 by 2100. We estimate the economic cost of fire smoke-related mortality by 2100 at US $ 5600 million, equivalent to 2.6 % of Paraguay's GDP, excluding other health- and productivity-related impacts on society.

Particulate matter deposition and its impact on tuberculosis severity: A cross-sectional study in Taipei

The objective of this study was to examine the association between the lung lobe-deposited dose of inhaled fine particulate matter (PM2.5) and chest X-ray abnormalities in different lung lobes of pulmonary tuberculosis (TB), multidrug-resistant tuberculosis (MDR-TB), and non-tuberculosis mycobacteria infections (NTM). A cross-sectional study was conducted between 2014 and 2022, comprising 1073 patients who were recruited from chest department clinic in a tertial refer hospital in Taipei City, Taiwan. Ambient 1-, 7-, and 30-day PM2.5 exposure and the deposition of PM2.5 in different lung lobes were estimated in each subject. The β coefficient for PM2.5 and deposited PM2.5 in lungs with the outcome variables (pulmonary TB, MDR-TB, and NTM infection) was derived through regression analysis and adjusted for age, gender, BMI, smoking status, and family income. We observed that a 1 μg/m3 increase in ambient PM2.5 was associated with an increase of MDR-TB infections of 0.004 times (95%CI: 0.001-0.007). A 1 μg/m3 increase in 1-day and 7-day PM2.5 deposition in left upper lobe and left lower lobe was associated with an increase in chest X-ray abnormalities of 9.19 % and 1.18 % (95%CI: 0.87-17.51 and 95%CI: 0.08-2.28), and 4.52 % and 5.20 % (95%CI: 0.66-8.38 and 95%CI: 0.51-9.89) in left lung of TB patients, respectively. A 1 μg/m3 increase in 30-day PM2.5 deposition in alveolar region was associated with an increase in percent abnormality of 2.50 % (95%CI: 0.65-4.35) in left upper lobe and 3.33 % (95%CI: 0.65-6.01) in right middle lobe, while in total lung was 0.63 % (95%CI: 0.01-1.27) in right upper lobe and 0.37 % (95%CI, 0.06-0.81) in right lung of MDR-TB patients. Inhaled PM2.5 deposition in lungs was associated with an exacerbation of the radiographic severity of pulmonary TB, particularly in pulmonary MDR-TB patients in upper and middle lobes. Particulate air pollution may potentially exacerbate the radiographic severity and treatment resistance in individuals with pulmonary TB.

Association between air pollution and male sexual function: A nationwide observational study in China

This study aimed to explore the associations between air pollution and male sexual function. A total of 5047 male subjects in China were included in this study. The average air pollution exposure (PM2.5, PM10, SO2, CO, NO2, and O3) for the preceding 1, 3, 6, and 12 months before the participants' response was assessed. Male sexual function was evaluated using the International Index of Erectile Function-5 (IIEF-5) and the Premature Ejaculation Diagnostic Tool (PEDT). Generalized linear models were utilized to explore the associations between air pollution and male sexual function. K-prototype algorithm was conducted to identify the association among specific populations. Significant adverse effects on the IIEF-5 score were observed with NO2 exposure during the preceding 1, 3, and 6 months (1 m: β = -5.26E-05; 3 m: β = -4.83E-05; 6 m: β = -4.23E-05, P < 0.05). PM2.5 exposure during the preceding 12 months was found to significantly negatively affect the PEDT after adjusting for confounding variables. Our research indicated negative correlations between air pollutant exposures and male sexual function for the first time. Furthermore, these associations were more pronounced among specific participants who maintain a normal BMI, exhibit extroverted traits, and currently engage in smoking and alcohol consumption.

The key characteristics of cardiotoxicity for the pervasive pollutant phenanthrene

The key characteristic (KCs) framework has been used previously to assess the carcinogenicity and cardiotoxicity of various chemical and pharmacological agents. Here, the 12 KCs of cardiotoxicity are used to evaluate the previously reported cardiotoxicity of phenanthrene (Phe), a tricyclic polycyclic aromatic hydrocarbon (PAH), and major component of fossil fuel-derived air pollution. Phe is a semi-volatile pollutant existing in both the gas phase and particle phase through adsorption onto or into particulate matter (PM). Phe can translocate across the airways and gastrointestinal tract into the systemic circulation, enabling body-wide effects. Our evaluation based on a comprehensive literature review, indicates Phe exhibits 11 of the 12 KCs for cardiotoxicity. These include adverse effects on cardiac electromechanical performance, the vasculature and endothelium, immunomodulation and oxidative stress, and neuronal and endocrine control. Environmental agents that have similarly damaging effects on the cardiovascular system are heavily regulated and monitored, yet globally there is no air quality regulation specific for PAHs like Phe. Environmental monitoring of Phe is not the international standard with benzo[a]pyrene being frequently used as a proxy despite the two PAH species exhibiting significant differences in sources, concentration variations and toxic effects. The evidence summarised in this evaluation highlights the need to move away from proxied PAH measurements and develop a monitoring network capable of measuring Phe concentration. It also stresses the need to raise awareness amongst the medical community of the potential cardiovascular impact of PAH exposure. This will allow the production of mitigation strategies and possibly the development of new policies for the protection of the societal groups most vulnerable to cardiovascular disease.

DNA methylation mediates the effects of PM2.5 and O3 on ceramide metabolism: A novel mechanistic link between air pollution and insulin resistance

Insulin resistance (IR), linked to air pollution, is an initial stage of early-onset Type 2 diabetes mellitus (T2DM). While ceramide metabolism plays an important role in IR pathogenesis, the effects of air pollution on this process and its mechanisms remain unclear. We recruited young adults aged 18-30 years to a panel study in Wuhan, China. Using personal portable devices and stationary monitoring stations, we tracked particulate matter with aerodynamic diameters≤ 2.5 µm (PM2.5) and Ozone (O3) levels. Liquid chromatography/mass spectrometry (LC-MS) based metabolomics quantified ceramide metabolism, and Illumina Infinium Human Methylation 850 kBeadChip assay measured deoxyribonucleic acid (DNA) methylation. Linear mixed-effects models assessed relationships of air pollution with i) IR indexes, ii) ceramide metabolism, and iii) DNA methylation. Mediation analysis was subsequently performed to evaluate the potential mediating effect of DNA methylation in the association between air pollution and ceramide metabolism. PM2.5 and O3 were associated with elevated IR. Specifically, each 10 μg/m3 increase in PM2.5 and O3 at lag0-12 h significantly increased triglyceride‑glucose index (TyG index) and TyG-BMI (TyG - Body mass index) by 0.88%, 0.89% and 0.26%, 0.26%, respectively. Furthermore, levels of eight ceramides were altered by air pollution exposure, and nine methylated CpG sites in inflammation genes mediated the effects of air pollution on ceramide metabolism. Our findings imply the existence of a novel mechanism connecting air pollution to IR.

Establishment of a system to analyze effects of airborne ultra-fine particulate matter from brake wear on plants under realistic exposure conditions

Research on airborne ultrafine particles (UFP) is driven by an increasing awareness of their potential effects on human health and on ecosystems. Brake wear is an important UFP source releasing largely metallic and potentially hazardous emissions. UFP uptake into plant tissues could mediate entry into food webs. Still, the effects of these particles on plants have barely been studied, especially in a realistic setting with aerial exposure. In this study, we established a system designed to mimic airborne exposure to ultrafine brake dust particles and performed experiments with the model species Arabidopsis thaliana. Using advanced analytical methods, we characterized the conditions in our exposure experiments. A comparison with data we obtained on UFP release at different outdoor stations showed that our controlled exposures are within the same order of magnitude regarding UFP deposition on plants at a traffic-heavy site. In order to assess the physiological implications of exposure to brake derived-particles we generated transcriptomic data with RNA sequencing. The UFP treatment led to diverse changes in gene expression, including the deregulation of genes involved in Fe and Cu homeostasis. This suggests a major contribution of metallic UFPs to the elicitation of physiological responses by brake wear derived emissions.

Causal association between long-term exposure to air pollution and incident Parkinson's disease

Epidemiological evidence for long-term air pollution exposure and Parkinson's disease (PD) is controversial, and analysis of causality is limited. We identified 293,888 participants who were free of PD at baseline in the UK Biobank (2006-2010). Time-varying air pollution [fine particulate (PM2.5) and ozone (O3)] exposures were estimated using spatio-temporal models. Incident cases of PD were identified using validated algorithms. Four methods were used to investigate the associations between air pollution and PD, including (1) standard time-varying Cox proportional-hazard model; (2) Cox models weighted by generalized propensity score (GPS) and inverse-probability weights (IPW); (3) instrumental variable (IV) analysis; and (4) negative control outcome analysis. During a median of 11.6 years of follow-up, 1822 incident PD cases were identified. Based on standard Cox regression, the hazard ratios (95% confidence interval) for a 1 µg/m3 or ppb increase in PM2.5 and O3 were 1.23 (1.17, 1.30) and 1.02 (0.98, 1.05), respectively. Consistent results were found in models weighted by GPS and IPW, and in IV analysis. There were no significant associations between air pollution and negative control outcomes. This study provides evidence to support a causal association between PM2.5 exposure and PD. Mitigation of air pollution could be a protective measure against PD.

Exploring the impact of socioeconomic and natural factors on pulmonary tuberculosis incidence in China (2013-2019) using explainable machine learning: A nationwide study

Pulmonary tuberculosis (PTB) stands as a significant and prevalent infectious disease in China. Integrating 13 natural and socioeconomic factors, we conduct nine machine learning (ML) models alongside the Tree-Structured Parzen Estimator to predict the monthly PTB incidence rate from 2013 to 2019 in mainland China. With explainable ML techniques, our research highlights that population size, per capita GDP, and PM10 concentration emerge as the primary determinants influencing the PTB incidence rate. We delineate both the independent and interactive impacts of these factors on the PTB incidence rate. Furthermore, crucial thresholds associated with factors influencing the PTB incidence rate are identified. Taking factors that have a positive effect on reducing the incidence rate of PTB as an example, the thresholds at which the effects of factors PM2.5, PM10, O3, and RH on the incidence rate change from increase to decrease are 105.5 µg/m3, 75.5 µg/m3, 90.8 µg/m3, and 72.3 % respectively. Our work will contribute valuable insights for public health interventions.

Association between long-term ozone exposure and readmission for chronic obstructive pulmonary disease exacerbation

The relationship between long-term ozone (O₃) exposure and readmission for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) remains elusive. In this study, we collected individual-level information on AECOPD hospitalizations from a standardized electronic database in Guangzhou from January 1, 2014, to December 31, 2015. We calculated the annual mean O₃ concentration prior to the dates of the index hospitalization for AECOPD using patients' residential addresses. Employing Cox proportional hazards models, we assessed the association between long-term O₃ concentration and the risk of AECOPD readmission across several time frames (30 days, 90 days, 180 days, and 365 days). We estimated the disease and economic burden of AECOPD readmissions attributable to O₃ using a counterfactual approach. Of the 4574 patients included in the study, 1398 (30.6%) were readmitted during the study period, with 262 (5.7%) readmitted within 30 days. The annual mean O₃ concentration was 90.3 μg/m3 (standard deviation [SD] = 8.2 μg/m3). A 10-μg/m3 increase in long-term O₃ concentration resulted in a hazard ratio (HR) for AECOPD readmission within 30 days of 1.28 (95% confidence interval [CI], 1.09 to 1.49), with similar results for readmission within 90, 180, and 365 days. Older patients (aged 75 years or above) and males were more susceptible (HR, 1.33; 95% CI, 1.10-1.61 and HR, 1.29; 95% CI, 1.09-1.53, respectively). The population attributable fraction for 30-day readmission due to O₃ exposure was 29.0% (95% CI, 28.4%-30.0%), and the attributable mean cost per participant was 362.3 USD (354.5-370.2). Long-term exposure to elevated O₃ concentrations is associated with an increased risk of AECOPD readmission, contributing to a significant disease and economic burden.

Air quality and cancer risk in the All of Us Research Program

INTRODUCTION

The NIH All of Us Research Program has enrolled over 544,000 participants across the US with unprecedented racial/ethnic diversity, offering opportunities to investigate myriad exposures and diseases. This paper aims to investigate the association between PM2.5 exposure and cancer risks.

MATERIALS AND METHODS

This work was performed on data from 409,876 All of Us Research Program participants using the All of Us Researcher Workbench. Cancer case ascertainment was performed using data from electronic health records and the self-reported Personal Medical History questionnaire. PM2.5 exposure was retrieved from NASA's Earth Observing System Data and Information Center and assigned using participants' 3-digit zip code prefixes. Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI). Generalized additive models (GAMs) were used to investigate non-linear relationships.

RESULTS

A total of 33,387 participants and 46,176 prevalent cancer cases were ascertained from participant EHR data, while 20,297 cases were ascertained from self-reported survey data from 18,133 participants; 9,502 cancer cases were captured in both the EHR and survey data. Average PM2.5 level from 2007 to 2016 was 8.90 μg/m3 (min 2.56, max 15.05). In analysis of cancer cases from EHR, an increased odds for breast cancer (OR 1.17, 95% CI 1.09-1.25), endometrial cancer (OR 1.33, 95% CI 1.09-1.62) and ovarian cancer (OR 1.20, 95% CI 1.01-1.42) in the 4th quartile of exposure compared to the 1st. In GAM, higher PM2.5 concentration was associated with increased odds for blood cancer, bone cancer, brain cancer, breast cancer, colon and rectum cancer, endocrine system cancer, lung cancer, pancreatic cancer, prostate cancer, and thyroid cancer.

CONCLUSIONS

We found evidence of an association of PM2.5 with breast, ovarian, and endometrial cancers. There is little to no prior evidence in the literature on the impact of PM2.5 on risk of these cancers, warranting further investigation.

Who will Spend more Pollution Abatement Costs: does Size Matter?

This paper looks at the relationship between enterprise size and pollution abatement costs using firm-level datasets in China, where size-dependent distortions may exist in the distribution of enterprises of different sizes. We find that the pollution abatement costs decrease with enterprise size. Compared to the smallest size, the magnitudes of marginal decreases in pollution abatement costs per 1000 CNY of industrial output in the largest size are 3.29 CNY, 0.54 CNY and 2.60 CNY for gas, SO2 and dust, respectively. Moreover, we further explore the potential mechanisms for the decrease of pollution abatement costs from three perspectives: environmental protection-related investment, regulation intensity, and technological capability. Our findings suggest that the decrease in the intensity of environmental protection-related investment for large enterprises may be directly reduce the intensity of pollution abatement costs. Although large enterprises have low intensity of pollution abatement costs, this does not mean that they are subject to weaker environmental regulation. More importantly, we find that large enterprises may have more adoption of abatement technologies. For SO2 and dust, the pollutant removal efficiency of the largest enterprises is 4.92% and 1.82% higher than that of the smallest enterprises, respectively. Our results are robust to different specifications. These findings help us enact appropriate policies for enterprises based on their size, thereby improving the efficacy of pollution abatement and achieving the optimal level of pollution abatement for the entire society.

Early-life exposure to ambient air pollutants and kidney function in adolescents: a cohort study based on the 'Children of 1997' Hong Kong birth cohort

OBJECTIVES

Air pollution is increasingly linked to impaired kidney function in adults. However, little is known about how early-life exposure to air pollutants affects kidney function in adolescents.

STUDY DESIGN

Cohort study.

METHODS

We leveraged data from the 'Children of 1997' Hong Kong population-representative birth cohort (N = 8327). Residential exposure to average ambient levels of four air pollutants, including inhalable particle (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and nitrogen monoxide (NO), during in utero, infancy, and childhood periods was estimated using the inverse distance weighting. Kidney function was assessed using estimated glomerular filtration rate (eGFR) calculated from age-adjusted equations for adolescents. Generalized linear regression was used to examine the association of air pollutant exposure in each period with kidney function at 17.6 years. Two-pollutant models tested the robustness of the association.

RESULTS

Of the 3350 participants included, 51.4% were boys. Exposure to PM10 was associated with poorer kidney function. Each interquartile range increment in PM10 was inversely associated with eGFR (β: -2.933, 95% confidence interval -4.677 to -1.189) in utero, -2.362 (-3.992 to -0.732) infancy, -2.708 (-4.370 to -1.047) childhood, and -2.828 (-4.409 to -1.247) overall. Exposure to PM10 and SO2in utero had a stronger inverse association with kidney function in males. The associations were robust to PM10 exposure in two-pollutant models.

CONCLUSIONS

Our findings suggest that early-life exposure to ambient PM10 and SO2 is associated with reduced kidney function in adolescents, especially exposure in utero.

Effects of COVID-19 on coastal and marine environments: Aggravated microplastic pollution, improved air quality, and future perspective

The COVID-19 pandemic during 2020-2023 has wrought adverse impacts on coastal and marine environments. This study conducts a comprehensive review of the collateral effects of COVID-19 on these ecosystems through literature review and bibliometric analysis. According to the output and citation analysis of these publications, researchers from the coastal countries in Asia, Europe, and America payed more attentions to this environmental issue than other continents. Specifically, India, China, and USA were the top three countries in the publications, with the proportion of 19.55%, 18.99%, and 12.01%, respectively. The COVID-19 pandemic significantly aggravated the plastic and microplastic pollution in coastal and marine environments by explosive production and unproper management of personal protective equipment (PPE). During the pandemic, the estimated mismanaged PPE waste ranged from 16.50 t/yr in Sweden to 250,371.39 t/yr in Indonesia. In addition, the PPE density ranged from 1.13 × 10-5 item/m2 to 2.79 item/m2 in the coastal regions worldwide, showing significant geographical variations. Besides, the emerging contaminants released from PPE into the coastal and marine environments cannot be neglected. The positive influence was that the COVID-19 lockdown worldwide reduced the release of air pollutants (e.g., fine particulate matter, NO2, CO, and SO2) and improved the air quality. The study also analyzed the relationships between sustainable development goals (SDGs) and the publications and revealed the dynamic changes of SDGs in different periods the COVID-19 pandemic. In conclusion, the air was cleaner due to the lockdown, but the coastal and marine contamination of plastic, microplastic, and emerging contaminants got worse during the COVID-19 pandemic. Last but not least, the study proposed four strategies to deal with the coastal and marine pollution caused by COVID-19, which were regular marine monitoring, performance of risk assessment, effective regulation of plastic wastes, and close international cooperation.

Global air pollution exposure and congenital anomalies: an updated systematic review and meta-analysis of epidemiological studies

A systematic review and meta-analysis was conducted to evaluate recent epidemiological evidence on the association of air pollution with congenital anomalies (CAs). Of 11,014 records, 49 were finally included in this meta-analysis. Per 10 μg/m3 increase in air pollutant, PM10 exposure during the 1st month of pregnancy and at the first trimester (T1) was associated with increased overall CAs. Further, exposure to PM10 was associated with congenital heart disease (OR = 1.055, 95% CI: 1.035, 1.074) and patent ductus arteriosus (OR = 1.094, 95% CI: 1.020, 1.168) at T1, with chromosomal anomalies during the entire pregnancy and with nervous system anomalies when exposure occurred 3 months prior to pregnancy, during the 1st, 2nd months of pregnancy and at T1. Besides, a significant association with overall CAs was observed for a combined exposure of PM10 and SO2 during the 1st month of gestation (OR: 1.101, 95% CI: 1.023, 1.180). A combined exposure of PM10 and CO was also associated with tetralogy of Fallot during 3-8 weeks of gestation (OR: 1.016, 95% CI: 1.005, 1.027). No significant associations were observed between PM2.5, NO2, and O3 exposure and CAs.

Longitudinal assessment of oxidative stress markers and their relationship with exposure to PM2.5 and its bound metals in healthy participants

OBJECTIVE

Exposure to ambient PM2.5 and its bound metals poses a risk to health and disease, via, in part, oxidative stress response. A variety of oxidative stress markers have been used as markers of response, but their relevance to environmental exposure remains to be established. We evaluated, longitudinally, a battery of oxidative stress markers and their relationship with the exposure of PM2.5 and its bound metals in a panel of healthy participants.

MATERIAL AND METHODS

Levels of residence- and personal-based ambient air PM2.5 and its bound metals, as well as of lung function parameters, were assessed in a total of 58 questionnaire-administered healthy never smoker participants (male, 39.7%). Levels of urinary oxidative stress markers, including Nε-(hexanoyl)-lysine (HEL; an early lipid peroxidation product), 4-hydroxynonenal (4-HNE), N7-methylguanine (N7-meG), and 8-hydroxy-2-deoxyguanosine (8-OHdG), plasma antioxidants [superoxide dismutase (SOD) and glutathione peroxidase (GPx), and urinary metals were measured by ELISA, LC-MS, and ICP-MS, respectively. The results of three repeated measurements at two-month intervals were analyzed using the Generalized Estimating Equation (GEE).

RESULTS

After adjusting for confounders, residence- and personal-based PM2.5 levels were positively associated with HEL (β = 0.22 and 0.18) and N7-meG (β = 0.39 and 0.13). Significant correlations were observed between personal air PM2.5-Pb and urinary Pb with HEL (β = 0.08 and 0.26). While FVC, FEV1, FEV1/FVC, MMF, and PEFR predicted% were normal, a negative interaction (pollutant*time, P < 0.05) was noted for PM2.5-V, Mn, Co, Ni, Zn, As, and Pb. Additionally, a negative interaction was found for N7-meG (β = -21.35, -18.77, -23.86) and SOD (β = -26.56, -26.18, -16.48) with FEV1, FVC, and PEFR predicted%, respectively.

CONCLUSION

These findings emphasize potential links between environmental exposure, internal dose, and health effects, thereby offering valuable markers for future research on metal exposure, oxidative stress, and health outcomes.

Joint effects of air pollution and neighborhood socioeconomic status on cognitive decline - Mediation by depression, high cholesterol levels, and high blood pressure

Air pollution and neighborhood socioeconomic status (N-SES) are associated with adverse cardiovascular health and neuropsychiatric functioning in older adults. This study examines the degree to which the joint effects of air pollution and N-SES on the cognitive decline are mediated by high cholesterol levels, high blood pressure (HBP), and depression. In the Emory Healthy Aging Study, 14,390 participants aged 50+ years from Metro Atlanta, GA, were assessed for subjective cognitive decline using the cognitive function instrument (CFI). Information on the prior diagnosis of high cholesterol, HBP, and depression was collected through the Health History Questionnaire. Participants' census tracts were assigned 3-year average concentrations of 12 air pollutants and 16 N-SES characteristics. We used the unsupervised clustering algorithm Self-Organizing Maps (SOM) to create 6 exposure clusters based on the joint distribution of air pollution and N-SES in each census tract. Linear regression analysis was used to estimate the effects of the SOM cluster indicator on CFI, adjusting for age, race/ethnicity, education, and neighborhood residential stability. The proportion of the association mediated by high cholesterol levels, HBP, and depression was calculated by comparing the total and direct effects of SOM clusters on CFI. Depression mediated up to 87 % of the association between SOM clusters and CFI. For example, participants living in the high N-SES and high air pollution cluster had CFI scores 0.05 (95 %-CI:0.01,0.09) points higher on average compared to those from the high N-SES and low air pollution cluster; after adjusting for depression, this association was attenuated to 0.01 (95 %-CI:-0.04,0.05). HBP mediated up to 8 % of the association between SOM clusters and CFI and high cholesterol up to 5 %. Air pollution and N-SES associated cognitive decline was partially mediated by depression. Only a small portion (<10 %) of the association was mediated by HBP and high cholesterol.

Air pollution and bronchiolitis: a case-control study in Antwerp, Belgium

This case-control study aimed to investigate the association between short-term (1 to 5 days) and medium-term (31 days) exposure to air pollutants (PM2.5, PM10, BC, NO2) at home/daycare and the risk of 'severe bronchiolitis' (defined as 'requiring hospitalization for bronchiolitis') in children under 2 years in Antwerp, Belgium. We included 118 cases and 79 controls admitted to three general hospitals from October 2020 to June 2021. Exposure levels were predicted using an interpolation model based on fixed measuring stations. We used unconditional logistic regression analysis to assess associations, with adjustment for potential confounders. There were hardly any significant differences in the day-to-day air pollution values between cases and controls. Medium-term (31 days) exposure to PM2.5, PM10, and NO2 was however significantly higher in cases than controls in univariate analysis. Logistic regression revealed an association between severe bronchiolitis and interquartile range (IQR) increases of PM2.5 and PM10 at home and in daycare, as well as IQR increases of NO2 in daycare. Controls were however overrepresented in low pollution periods. Time-adjustment reduced the odds ratios significantly at home for PM2.5 and PM10 (aOR 1.54, 95%CI 0.51-4.65; and 2.69, 95%CI 0.94-7.69 respectively), and in daycare for. PM2.5 (aOR 2.43, 95%CI 0.58-10.1). However, the association between severe bronchiolitis and medium-term air pollution was retained in daycare for IQR increases of PM10 (aOR 5.13, 95%CI 1.24-21.28) and NO2 (aOR 3.88, 95%CI 1.56-9.61) in the time-adjusted model.  Conclusion: This study suggests a possible link between severe bronchiolitis and medium-term (31 days) air pollution exposure (PM10 and NO2), particularly in daycare. Larger studies are warranted to confirm these findings. What is Known: • Bronchiolitis is a leading cause of hospitalization in infants globally and causes a yearly seasonal wave of admissions in paediatric departments worldwide. • Existing studies, mainly from the USA, show heterogeneous outcomes regarding the association between air pollution and bronchiolitis. What is New: • There is a possible link between severe bronchiolitis and medium-term (31 days) air pollution exposure (PM10 and NO2), particularly in daycare. • Larger studies are needed to validate these trends.

Associations of ambient ozone exposure and CD4+ T cell levels with mortality among people living with HIV: An eight-year longitudinal study

There has been a consistent upward trend in ground-level ozone (O3) concentration in China. People living with HIV (PLWH) may be more vulnerable to the health impacts of O3 exposure due to their immunosuppressed state. This study aims to investigate the association between ambient O3 exposure and mortality among PLWH, as well as the potential exacerbating effects of a decreased CD4+ T cell level. Daily maximum 8-hour O3 concentrations were assigned to 7270 PLWH at a county level in Guangxi, China. Every 10-unit increase in ambient O3 concentration was associated with a significant rise in all-cause mortality ranging from 7.3 % to 28.7 % and a significant rise in AIDS-related mortality ranging from 8.4 % to 14.5 %. When PLWH had a higher CD4+ count (≥350 cells/μL), elevated O3 concentration was associated with increased blood CD4+ count at lag0 [percent change with 95 % confidence interval, 0.20(0.00, 0.40)], lag1 [0.26(0.06, 0.47)], and lag2 [0.23(0.03, 0.44)]; however, an opposite association was observed when CD4+ count was <350 cells/μL for half-year average [-2.45(-4.71, -0.14)] and yearly average [-3.42(-5.51, -1.29)] of O3 exposure. The association of O3 exposure with all-cause and AIDS-related mortality was more prominent among those with higher CD4+ count. Exploratory analysis revealed possible associations between O3 exposure and respiratory infections and clinical symptoms. These findings suggest potential synergistic effects between a compromised immune status and elevated O3 exposure levels on mortality risk among PLWH. Ambient O3 exposure should be considered as an emerging mortality risk factor for PLWH in the era of antiretroviral therapy, requiring further attention from researchers and healthcare professionals.

A systematic review and meta-analysis of the association between air pollutants and the incidence of tuberculosis

Objective

To investigate the association between air pollutants and the incidence of tuberculosis (TB) through a systematic review and meta-analysis, and to provide directions for future research and prevention of TB.

Methods

A search was conducted for all literature related to the incidence of TB and air pollution in the database. We screened the retrieved articles and proceeded statistical analyses using random effects models to investigate the relationships between five air pollutants (PM2.5, PM10, SO2, NO2 and O3) and the incidence of TB.

Results

The initial search identified 100 pieces of literature and 9 studies met the screening criteria after the screening. The single-day lagged risk ratio (RR) and 95% Confidence Intervals (CIs) for the combined effects estimates are as follows: PM2.5: 1.059 (0.966, 1.160); PM10: 1.000 (0.996, 1.004); SO2: 0.980 (0.954, 1.007); NO2: 1.011 (0.994, 1.027); O3: 0.994 (0.980,1.008). The cumulative lagged results for these five pollutants are listed like this: PM2.5: 1.095 (0.983, 1.219); PM10: 1.035 (1.006, 1.066); SO2: 0.964 (0.830, 1.121); NO2: 1.037 (1.010, 1.065); O3: 0.982 (0.954, 1.010).

Conclusion

The single-day lag effects of PM2.5, PM10, SO2, NO2, and O3 are not statistically significantly relevant for the occurrence of TB. However, the cumulative lag results show that both PM10 and NO2 contribute to the prevalence of TB, while the statistical relationship between the cumulative lag effects of PM2.5, SO2, and O3 and the onset of TB remains unknown.

Biomonitoring potentially toxic elements in atmospheric particulate matter of greater Dhaka region using leaves of higher plants

In this study, four different plant species, namely Artocarpus heterophyllus, Mangifera indica, Psidium guajava, and Swietenia mahagoni, were selected from seven different locations to assess the feasibility of using them as a cost-effective alternative for biomonitoring air quality. Atmospheric coarse particulate matter (PM10), soil samples, and leaf samples were collected from residential, industrial, and traffic-congested sites located in the greater Dhaka region. The heavy metal concentrations (Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) in the leaves of the different species, PM10, and soil samples were analyzed. The highest Pb (718 ng/m3) and Zn (15,956 ng/m3) concentrations were found in PM10 of Kodomtoli which is an industrial area. On the other hand, the highest Fe (6,152 ng/m3) and Ni (61.1 ng/m3) concentrations were recorded in the PM10 of Gabtoli, a heavy-traffic area. A significant positive correlation (r = 0.74; p < 0.01) between Pb content in plant leaves and PM fraction was found which indicated that atmospheric PM-bound Pb may contribute to the uptake of Pb by plant leaves. The analysis of the enrichment factor (EF) revealed that soils were contaminated with Cd, Ni, Pb, and Zn. The abaxial leaf surfaces of Psidium guajava growing at the polluted site exhibited up to a 40% decrease in stomatal pores compared to the control site. Saet's summary index (Zc) demonstrated that Mangifera indica had the highest bioaccumulation capacity. The metal accumulation index (MAI) was also evaluated to assess the overall metal accumulation capacity of the selected plants. Of the four species, Swietenia mahagoni (3.05) exhibited the highest MAI value followed by Mangifera indica (2.97). Mangifera indica and Swietenia mahagoni were also found to accumulate high concentrations of Pb and Cr in their leaves and are deemed to be good candidates to biomonitor Pb and Cr contents in ambient air.

Associations between long-term exposure to air pollution and kidney function utilizing electronic healthcare records: a cross-sectional study

BACKGROUND

Chronic kidney disease (CKD) affects more than 38 million people in the United States, predominantly those over 65 years of age. While CKD etiology is complex, recent research suggests associations with environmental exposures.

METHODS

Our primary objective is to examine creatinine-based estimated glomerular filtration rate (eGFRcr) and diagnosis of CKD and potential associations with fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) using a random sample of North Carolina electronic healthcare records (EHRs) from 2004 to 2016. We estimated eGFRcr using the serum creatinine-based 2021 CKD-EPI equation. PM2.5 and NO2 data come from a hybrid model using 1 km2 grids and O3 data from 12 km2 CMAQ grids. Exposure concentrations were 1-year averages. We used linear mixed models to estimate eGFRcr per IQR increase of pollutants. We used multiple logistic regression to estimate associations between pollutants and first appearance of CKD. We adjusted for patient sex, race, age, comorbidities, temporality, and 2010 census block group variables.

RESULTS

We found 44,872 serum creatinine measurements among 7,722 patients. An IQR increase in PM2.5 was associated with a 1.63 mL/min/1.73m2 (95% CI: -1.96, -1.31) reduction in eGFRcr, with O3 and NO2 showing positive associations. There were 1,015 patients identified with CKD through e-phenotyping and ICD codes. None of the environmental exposures were positively associated with a first-time measure of eGFRcr < 60 mL/min/1.73m2. NO2 was inversely associated with a first-time diagnosis of CKD with aOR of 0.77 (95% CI: 0.66, 0.90).

CONCLUSIONS

One-year average PM2.5 was associated with reduced eGFRcr, while O3 and NO2 were inversely associated. Neither PM2.5 or O3 were associated with a first-time identification of CKD, NO2 was inversely associated. We recommend future research examining the relationship between air pollution and impaired renal function.

Outdoor air pollution as a risk factor for testing positive for SARS-CoV-2: A nationwide test-negative case-control study in the Netherlands

Air pollution is a known risk factor for several diseases, but the extent to which it influences COVID-19 compared to other respiratory diseases remains unclear. We performed a test-negative case-control study among people with COVID-19-compatible symptoms who were tested for SARS-CoV-2 infection, to assess whether their long- and short-term exposure to ambient air pollution (AAP) was associated with testing positive (vs. negative) for SARS-CoV-2. We used individual-level data for all adult residents in the Netherlands who were tested for SARS-CoV-2 between June and November 2020, when only symptomatic people were tested, and modeled ambient concentrations of PM10, PM2.5, NO2 and O3 at geocoded residential addresses. In long-term exposure analysis, we selected individuals who did not change residential address in 2017-2019 (1.7 million tests) and considered the average concentrations of PM10, PM2.5 and NO2 in that period, and different sources of PM (industry, livestock, other agricultural activities, road traffic, other Dutch sources, foreign sources). In short-term exposure analysis, individuals not changing residential address in the two weeks before testing day (2.7 million tests) were included in the analyses, thus considering 1- and 2-week average concentrations of PM10, PM2.5, NO2 and O3 before testing day as exposure. Mixed-effects logistic regression analysis with adjustment for several confounders, including municipality and testing week to account for spatiotemporal variation in viral circulation, was used. Overall, there was no statistically significant effect of long-term exposure to the studied pollutants on the odds of testing positive vs. negative for SARS-CoV-2. However, significant positive associations of long-term exposure to PM10 and PM2.5 from specifically foreign and livestock sources, and to PM10 from other agricultural sources, were observed. Short-term exposure to PM10 (adjusting for NO2) and PM2.5 were also positively associated with increased odds of testing positive for SARS-CoV-2. While these exposures seemed to increase COVID-19 risk relative to other respiratory diseases, the underlying biological mechanisms remain unclear. This study reinforces the need to continue to strive for better air quality to support public health.

Statistical data pre-processing and time series incorporation for high-efficacy calibration of low-cost NO2 sensor using machine learning

Air pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given its adverse effects on health and the environment, accurate monitoring of NO2 levels becomes imperative for devising effective risk mitigation strategies. However, the precise measurement of NO2 poses challenges as it traditionally relies on costly and bulky equipment. This has prompted the development of more affordable alternatives, although their reliability is often questionable. The aim of this article is to introduce a groundbreaking method for precisely calibrating cost-effective NO2 sensors. This technique involves statistical preprocessing of low-cost sensor readings, aligning their distribution with reference data. Central to this calibration is an artificial neural network (ANN) surrogate designed to predict sensor correction coefficients. It utilizes environmental variables (temperature, humidity, atmospheric pressure), cross-references auxiliary NO2 sensors, and incorporates short time series of previous readings from the primary sensor. These methods are complemented by global data scaling. Demonstrated using a custom-designed cost-effective monitoring platform and high-precision public reference station data collected over 5 months, every component of our calibration framework proves crucial, contributing to its exceptional accuracy (with a correlation coefficient near 0.95 concerning the reference data and an RMSE below 2.4 µg/m3). This level of performance positions the calibrated sensor as a viable, cost-effective alternative to traditional monitoring approaches.

Estimating the probability of occurrence of African dust outbreaks over regions of the western Mediterranean basin from thermodynamic atmospheric parameters

Desert dust is currently recognized as a health risk factor. Therefore, the World Health Organization (WHO) is actively promoting the establishment of early warning systems for sand and dust storms. This study introduces a methodology to estimate the probability of African dust outbreaks occurring in eight different regions of the Iberian Peninsula and the Balearic Islands. In each region, a multilinear regression model was developed to calculate daily probabilities of dust events using three thermodynamic variables (geopotential thickness in the 1000-500 hPa layer, mean potential temperature between 925 and 700 hPa, and temperature anomalies at 850 hPa) as assessment parameters. All days with African dust transport over each study region were identified in the period 2001-2021 using a proven procedure. This information was then utilized to establish a functional relationship between the values of the thermodynamic parameters and the probability of African dust outbreaks occurring. The validation of this methodology involved comparing the daily probabilities of dust events generated by the models in 2001-2021 with the daily African dust contributions to PM10 regional background levels in each region. On average, daily dust contributions increased proportionally with the increase in daily probabilities, reaching zero for days with low probabilities. Furthermore, a well-defined seasonal evolution of probability values was observed in all regions, with the highest values in the summer months and the lowest in the winter period, ensuring the physical relevance of the models' results. Finally, upward trends were observed in all regions for the three thermodynamic parameters over 1940-2021. Thus, the probability of dust events development also increased in this period. It demonstrates that the aggravation of warm conditions in southern Europe in the last decades, have modified the frequency of North-African dust outbreaks over the western Mediterranean basin.

Impact of comprehensive air pollution control policies on six criteria air pollutants and acute myocardial infarction morbidity, Weifang, China: A quasi-experimental study

Comprehensive air pollution control policies may reduce pollutant emissions. However, the impact on disease morbidity of the change for the concentration of air pollutants following the policies has been insufficiently studied. We aim to assess the impact of comprehensive air pollution control policies on the levels of six criteria air pollutants and acute myocardial infarction (AMI) morbidity in Weifang, China. This study performed an interrupted time series analysis. The linear model with spline terms and generalized additive quasi-Poisson model were used to estimate the immediate change from 2016 to 2019 in the daily concentration of six air pollutants (PM2.5, PM10, SO2, NO2, O3, and, CO) and AMI incident cases (Age ≥35) associated with the implementation of air pollution control policies in Weifang, respectively. After the implementation of air pollution control policies, air quality in Weifang had been improved. Specifically, the daily concentrations of PM2.5, PM10, SO2, and, CO immediately decreased by 27.9 % (95 % CI: 6.6 % to 44.3 %), 32.9 % (95 % CI: 17.5 % to 45.5 %), 14.6 % (95 % CI: 0.4 % to 26.8 %), and 33.9 % (95 % CI: 22.0 % to 44.0 %), respectively. In addition, the policies implementation was also associate with the immediate decline in the AMI morbidity (-6.5 %, 95 % CI: -10.4 % to -2.3 %). And subgroup analyses indicate that the health effects of the policy intervention were only observed in female (-9.4 %, 95 % CI: -14.4 % to -4.2 %) and those aged ≥65 years (-10.5 %, 95 % CI: -14.6 % to -6.2 %). During the final 20 months of the study period, the policy intervention was estimated to prevent 1603 (95 % CI: 574 to 2587) cases of incident AMI in Weifang. Our results provide strong rationale that the policy intervention significantly reduced ambient pollutant concentrations and AMI morbidity, which highlighted the importance for a comprehensive and rigorous air pollution control policy in regions with severe air pollution.

The Environment and Headache: a Narrative Review

PURPOSE OF REVIEW

In this narrative review, we summarize the peer-reviewed literature published between 2017 and 2022 that evaluated ambient environmental risk factors for primary headache disorders, which affect more than half of the population globally. Primary headache disorders include migraine, tension-type headache (TTH), and trigeminal and autonomic cephalalgias (TAC).

RECENT FINDINGS

We identified 17 articles that met the inclusion criteria via PubMed or Google Scholar. Seven studies (41%) relied on data from US populations. The remaining studies were conducted in China, Taiwan, Germany, Ghana, Japan, the Netherlands, South Korea, and Turkey. Air pollution was the most frequently assessed environmental risk factor. Most studies were cross-sectional and focused on all-cause or migraine headaches; one study included TTH, and none included TAC. Short-term exposure to fine particulate matter (PM2.5) was not consistently associated with headache endpoints, but long-term exposure to PM2.5 was associated with migraine headache prevalence and severity across multiple studies. Elevated ambient temperature, changes in weather, oil and gas well exposure, and less natural greenspace, but not noise pollution, were also associated with headache. No studies considered water pollution, metal exposure, ultrafine particulate matter, or wildfire smoke exposure. There is a need for ongoing research focused on headache and the environment. Study designs with the greatest explanatory power may include longitudinal studies that capture the episodic nature of headache and case-crossover analysis, which control for time-invariant individual-level confounders by design. There is also a clear need for research that considers comorbid psychiatric illness and socioeconomic position as powerful modifiers of the effect of the environment on headache.

Prenatal Exposure to Air Pollutants Associated with Allergic Diseases in Children: Which Pollutant, When Exposure, and What Disease? A Systematic Review and Meta-analysis

This systematic review aims to identify the association between prenatal exposure to air pollutants and allergic diseases in children, focusing on specific pollutants, timing of exposure, and associated diseases. We searched PubMed, Scopus, and Web of Science for English articles until May 1, 2023, examining maternal exposure to outdoor air pollutants (PM1, PM2.5, PM10, NO, NO2, SO2, CO, and O3) during pregnancy and child allergic diseases (atopic dermatitis (AD), food allergy (FA), asthma (AT) and allergic rhinitis (AR)/hay fever (HF)). The final 38 eligible studies were included in the meta-analysis. Exposure to PM2.5 and NO2 during pregnancy was associated with the risk of childhood AD, with pooled ORs of 1.34 (95% confidence interval (CI), 1.10-1.63) and 1.10 (95%CI, 1.05-1.15) per 10 µg/m3 increase, respectively. Maternal exposure to PM1, PM2.5, and NO2 with a 10 µg/m3 increase posed a risk for AT, with pooled ORs of 1.34 (95%CI, 1.17-1.54), 1.11 (95%CI, 1.05-1.18), and 1.07 (95%CI, 1.02-1.12), respectively. An increased risk of HF was observed for PM2.5 and NO2 with a 10 µg/m3 increase, with ORs of 1.36 (95%CI, 1.17-1.58) and 1.26 (95%CI, 1.08-1.48), respectively. Traffic-related air pollutants (TRAP), particularly PM2.5 and NO2, throughout pregnancy, pose a pervasive risk for childhood allergies. Different pollutants may induce diverse allergic diseases in children across varying perinatal periods. AT is more likely to be induced by outdoor air pollutants as a health outcome. More research is needed to explore links between air pollution and airway-derived food allergies.

New insight into air pollution-related cardiovascular disease: an adverse outcome pathway framework of PM2.5-associated vascular calcification

Despite the air quality has been generally improved in recent years, ambient fine particulate matter (PM2.5), a major contributor to air pollution, remains one of the major threats to public health. Vascular calcification is a systematic pathology associated with an increased risk of cardiovascular disease. Although the epidemiological evidence has uncovered the association between PM2.5 exposure and vascular calcification, little is known about the underlying mechanisms. The adverse outcome pathway (AOP) concept offers a comprehensive interpretation of all of the findings obtained by toxicological and epidemiological studies. In this review, reactive oxygen species (ROS) generation was identified as the molecular initiating event (MIE), which targeted subsequent key events (KE) such as oxidative stress, inflammation, endoplasmic reticulum (ER) stress, and autophagy, from the cellular to the tissue/organ level. These KEs eventually led to the adverse outcome (AO), namely increased incidence of vascular calcification and atherosclerosis morbidity. To the best of our knowledge, this is the first AOP framework devoted to PM2.5-associated vascular calcification, which benefits future investigations by identifying current limitations and latent biomarkers.

Co-exposure to multiple air pollutants, genetic susceptibility, and the risk of myocardial infarction onset: a cohort analysis of the UK Biobank participants

AIMS

The relationship between the long-term joint exposure to ambient air pollution and incidence of myocardial infarction (MI) and modification by genetic susceptibility remain inconclusive.

METHODS AND RESULTS

We analysed 329 189 UK Biobank participants without MI at baseline. Exposure concentrations to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were obtained. Air pollution score assessing the joint exposure was calculated, and its association with MI was evaluated via Cox model under the P value aggregation framework. Genetic susceptibility to MI was evaluated by incorporating polygenic risk score (PRS) into models. Risk prediction models were also established. During a median follow-up of 13.4 years, 9993 participants developed MI. Per interquartile range increase of PM2.5, PM10, NO2, and NOx resulted in 74% [95% confidence intervals (CIs) 69%-79%], 67% (63%-72%), 46% (42%-49%), and 38% (35%-41%) higher risk of MI. Compared with the lowest quartile (Q1) of air pollution score, the multivariable adjusted hazard ratio (HR) (95%CIs) of Q4 (the highest cumulative air pollution) was 3.50 (3.29-3.72) for MI. Participants with the highest PRS and air pollution score possessed the highest risk of incident MI (HR = 4.88, 95%CIs 4.35-5.47). Integrating PRS, air pollution exposure, and traditional factors substantially improved risk prediction of MI.

CONCLUSION

Long-term joint exposure to air pollutants including PM2.5, PM10, NO2, and NOx is substantially associated with increased risk of MI. Genetic susceptibility to MI strengthens such adverse joint association. Air pollutions together with genetic and traditional factors enhance the accuracy of MI risk prediction.

Grouped mixtures of air pollutants and seasonal temperature anomalies and cardiovascular hospitalizations among U.S. Residents

BACKGROUND

Air pollution is a recognized risk factor for cardiovascular disease (CVD). Temperature is also linked to CVD, with a primary focus on acute effects. Despite the close relationship between air pollution and temperature, their health effects are often examined separately, potentially overlooking their synergistic effects. Moreover, fewer studies have performed mixture analysis for multiple co-exposures, essential for adjusting confounding effects among them and assessing both cumulative and individual effects.

METHODS

We obtained hospitalization records for residents of 14 U.S. states, spanning 2000-2016, from the Health Cost and Utilization Project State Inpatient Databases. We used a grouped weighted quantile sum regression, a novel approach for mixture analysis, to simultaneously evaluate cumulative and individual associations of annual exposures to four grouped mixtures: air pollutants (elemental carbon, ammonium, nitrate, organic carbon, sulfate, nitrogen dioxide, ozone), differences between summer and winter temperature means and their long-term averages during the entire study period (i.e., summer and winter temperature mean anomalies), differences between summer and winter temperature standard deviations (SD) and their long-term averages during the entire study period (i.e., summer and winter temperature SD anomalies), and interaction terms between air pollutants and summer and winter temperature mean anomalies. The outcomes are hospitalization rates for four prevalent CVD subtypes: ischemic heart disease, cerebrovascular disease, heart failure, and arrhythmia.

RESULTS

Chronic exposure to air pollutant mixtures was associated with increased hospitalization rates for all CVD subtypes, with heart failure being the most susceptible subtype. Sulfate, nitrate, nitrogen dioxide, and organic carbon posed the highest risks. Mixtures of the interaction terms between air pollutants and temperature mean anomalies were associated with increased hospitalization rates for all CVD subtypes.

CONCLUSIONS

Our findings identified critical pollutants for targeted emission controls and suggested that abnormal temperature changes chronically affected cardiovascular health by interacting with air pollution, not directly.

Ambient PM2.5 and specific sources increase inflammatory cytokine responses to stimulators and reduce sensitivity to inhibitors

Ambient exposure to fine particulate matter (PM2.5) is associated with increased morbidity and mortality from multiple diseases. Recent observations suggest the hypothesis that trained immunity contributes to these risks, by demonstrating that ambient PM2.5 sensitizes innate immune cells to mount larger inflammatory response to subsequent bacterial stimuli. However, little is known about how general and durable this sensitization phenomenon is, and whether specific sources of PM2.5 are responsible. Here we consider these issues in a longitudinal study of children. The sample consisted of 277 children (mean age 13.92 years; 63.8% female; 38.4% Black; 32.2% Latinx) who completed baseline visits and were re-assessed two years later. Fasting whole blood was ex vivo incubated with 4 stimulating agents reflecting microbial and sterile triggers of inflammation, and with 2 inhibitory agents, followed by assays for IL-1β, IL-6, IL-8, and TNF-α. Blood also was assayed for 6 circulating biomarkers of low-grade inflammation: C-reactive protein, interleukin-6, -8, and -10, tumor necrosis factor-α, and soluble urokinase-type plasminogen activator receptor. Using machine learning, levels of 15 p.m.2.5 constituents were estimated for a 50 m grid around children's homes. Models were adjusted for age, sex, race, pubertal status, and household income. In cross-sectional analyses, higher neighborhood PM2.5 was associated with larger cytokine responses to the four stimulating agents. These associations were strongest for constituents released by motor vehicles and soil/crustal dust. In longitudinal analyses, residential PM2.5 was associated with declining sensitivity to inhibitory agents; this pattern was strongest for constituents from fuel/biomass combustion and motor vehicles. By contrast, PM2.5 constituents were not associated with the circulating biomarkers of low-grade inflammation. Overall, these findings suggest the possibility of a trained immunity scenario, where PM2.5 heightens inflammatory cytokine responses to multiple stimulators, and dampens sensitivity to inhibitors which counter-regulate these responses.

The impact of co-exposure to air and noise pollution on the incidence of metabolic syndrome from a health checkup cohort

Previous studies have found associations between the incidence of metabolic syndrome (MetS) and exposure to air pollution or road traffic noise. However, investigations on environmental co-exposures are limited. This study aimed to investigate the association between co-exposure to air pollution and road traffic noise and MetS and its subcomponents. Participants living in Taipei City who underwent at least two health checkups between 2010 and 2016 were included in the study. Data were sourced from the MJ Health database, a longitudinal, large-scale cohort in Taiwan. The monthly traffic noise exposure (Lden and Lnight) was computed using a dynamic noise map. Monthly fine particulate data at one kilometer resolution were computed from satellite imagery data. Cox proportional hazards regression models with month as the underlying time scale were used to estimate hazard ratios (HRs) for the impact of PM2.5 and road traffic noise exposure on the risk of developing MetS or its subcomponents. Data from 10,773 participants were included. We found significant positive associations between incident MetS and PM2.5 (HR: 1.88; 95% CI 1.67, 2.12), Lden (HR: 1.10; 95% CI 1.06, 1.15), and Lnight (HR: 1.07; 95% CI 1.02, 1.13) in single exposure models. Results further showed significant associations with an elevated risk of incident MetS in co-exposure models, with HRs of 1.91 (95% CI 1.69, 2.16) and 1.11 (95% CI 1.06, 1.16) for co-exposure to PM2.5 and Lden, and 1.90 (95% CI 1.68, 2.14) and 1.08 (95% CI 1.02, 1.13) for co-exposure to PM2.5 and Lnight. The HRs for the co-exposure models were higher than those for models with only a single exposure. This study provides evidence that PM2.5 and noise exposure may elevate the risk of incident MetS and its components in both single and co-exposure models. Therefore, preventive approaches to mitigate the risk of MetS and its subcomponents should consider reducing exposure to PM2.5 and noise pollution.

Maternal exposure to ambient ozone and fetal conotruncal heart defects in China: A multicenter cohort study

BACKGROUND

The relationships between maternal genetic and environmental exposure and conotruncal heart defects (CTDs) have been extensively investigated. Nevertheless, there is limited knowledge regarding the impact of ozone (O3) on the risk of CTDs.

OBJECTIVE

To explore the correlation between maternal exposure to O3 and CTDs in China.

METHODS

Pregnant women who underwent fetal echocardiography at Beijing Anzhen Hospital between January 2013 and December 2021 were enrolled. Their sociodemographic characteristics and lifestyle information, along with fetal data, were systematically collected. Fetal echocardiography was used to detect CTDs. Maternal exposure to ambient O3 during the embryonic period, the first trimester, the three months preceding the last menstrual period, and the perinatal period was estimated using residential addresses or hospital addresses associated with prenatal visits. The concentration of O3 was divided by quartiles, with the first quartile serving as a reference. Adjusted logistic regression models were employed to examine the associations between every 10 μg/m3 increase or quartile increase in ambient O3 exposure and CTDs.

RESULTS

Among 24,278 subjects, 1069 exhibited fetuses with CTDs. Maternal exposure to ambient O3 during three pregnancy periods was associated with increased CTD risk. The adjusted odds ratio (OR) and 95% confidence interval (CI) were 1.271 (1.189-1.360) per 10 μg/m3 increase in O3 during the perinatal period. For each quartile of O3, the risk increased with increasing exposure concentration, particularly during the perinatal period (OR = 2.206 for quartile 2, 2.367 for quartile 3, and 3.378 for quartile 4, all P<0.05).

CONCLUSIONS

Elevated maternal exposure to O3 during pregnancy, particularly in the perinatal period, is linked to an increased risk of fetal CTDs. Further longitudinal analyses are needed to validate these results.

Air pollution changes due to COVID-19 lockdowns and attributable mortality changes in four countries

COVID-19 lockdowns reduced nitrogen dioxide (NO2) and fine particulate matter (PM2.5) emissions in many countries. We aim to quantify the changes in these pollutants and to assess the attributable changes in mortality in Jiangsu, China; California, U.S.; Central-southern Italy; and Germany during COVID-19 lockdowns in early 2020. Accounting for meteorological impacts and air pollution time trends, we use a machine learning-based meteorological normalization technique and the difference-in-differences approach to quantify the changes in NO2 and PM2.5 concentrations due to lockdowns. Using region-specific estimates of the association between air pollution and mortality derived from a causal modeling approach using data from 2015 to 2019, we assess the changes in mortality attributable to the air pollution changes caused by the lockdowns in early 2020. During the lockdowns, NO2 reductions avoided 1.41 (95% empirical confidence interval [eCI]: 0.94, 1.88), 0.44 (95% eCI: 0.17, 0.71), and 4.66 (95% eCI: 2.03, 7.44) deaths per 100,000 people in Jiangsu, China; California, U.S.; and Central-southern Italy, respectively. Mortality benefits attributable to PM2.5 reductions were also significant, albeit of a smaller magnitude. For Germany, the mortality benefits attributable to NO2 changes were not significant (0.11; 95% eCI: -0.03, 0.25), and an increase in PM2.5 concentrations was associated with an increase in mortality of 0.35 (95% eCI: 0.22, 0.48) deaths per 100,000 people during the lockdown. COVID-19 lockdowns overall improved air quality and brought attributable health benefits, especially associated with NO2 improvements, with notable heterogeneity across regions. This study underscores the importance of accounting for local characteristics when policymakers adapt successful emission control strategies from other regions.

Impact of ambient air pollution on colorectal cancer risk and survival: insights from a prospective cohort and epigenetic Mendelian randomization study

BACKGROUND

This study investigates the associations between air pollution and colorectal cancer (CRC) risk and survival from an epigenomic perspective.

METHODS

Using a newly developed Air Pollutants Exposure Score (APES), we utilized a prospective cohort study (UK Biobank) to investigate the associations of individual and combined air pollution exposures with CRC incidence and survival, followed by an up-to-date systematic review with meta-analysis to verify the associations. In epigenetic two-sample Mendelian randomization analyses, we examine the associations between genetically predicted DNA methylation related to air pollution and CRC risk. Further genetic colocalization and gene-environment interaction analyses provided different insights to disentangle pathogenic effects of air pollution via epigenetic modification.

FINDINGS

During a median 12.97-year follow-up, 5767 incident CRC cases among 428,632 participants free of baseline CRC and 533 deaths in 2401 patients with CRC were documented in the UK Biobank. A higher APES score was associated with an increased CRC risk (HR, 1.03, 95% CI = 1.01-1.06; P = 0.016) and poorer survival (HR, 1.13, 95% CI = 1.03-1.23; P = 0.010), particularly among participants with insufficient physical activity and ever smokers (Pinteraction > 0.05). A subsequent meta-analysis of seven observational studies, including UK Biobank data, corroborated the association between PM2.5 exposure (per 10 μg/m3 increment) and elevated CRC risk (RR,1.42, 95% CI = 1.12-1.79; P = 0.004; I2 = 90.8%). Genetically predicted methylation at PM2.5-related CpG site cg13835894 near TMBIM1/PNKD and cg16235962 near CXCR5, and NO2-related cg16947394 near TMEM110 were associated with an increased CRC risk. Gene-environment interaction analysis confirmed the epigenetic modification of aforementioned CpG sites with CRC risk and survival.

INTERPRETATION

Our study suggests the association between air pollution and CRC incidence and survival, underscoring the possible modifying roles of epigenomic factors. Methylation may partly mediate pathogenic effects of air pollution on CRC, with annotation to epigenetic alterations in protein-coding genes TMBIM1/PNKD, CXCR5 and TMEM110.

FUNDING

Xue Li is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001), the National Nature Science Foundation of China (No. 82204019) and Healthy Zhejiang One Million People Cohort (K-20230085). ET is supported by a Cancer Research UK Career Development Fellowship (C31250/A22804). MGD is supported by the MRC Human Genetics Unit Centre Grant (U127527198).

Long-term exposure to air pollution and precocious puberty in South Korea

BACKGROUND AND AIM

The increasing prevalence of precocious puberty (PP) has emerged as a significant medical and social problem worldwide. However, research on the relationship between long-term air pollution exposure and PP has been relatively limited. We thus investigated the association between long-term air pollution exposure and the onset of PP in South Korea.

METHODS

We investigated a retrospective cohort using the Korea National Health Insurance Database. Six-year-old children born from 2007 to 2009 were examined (2013-2015). We included boys ≤10 years and girls aged ≤9 years who visited hospitals for early pubertal development, were diagnosed with PP per the ICD-10 (E228, E301, and E309), and received gonadotropin-releasing hormone agonist treatment. We analyzed data for boys up until 10 years old (60-month follow-up) and for girls up to 9 years old (48-month follow-up). We assessed the association between long-term air pollution exposure and the onset of PP using a Cox proportional hazard model. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) per 1 μg/m3 increase in fine particulate matter (PM2.5) and particulate matter (PM10) and per 1 ppb increase in sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3).

RESULTS

This study included 1,205,784 children aged six years old between 2013 and 2015. A positive association was found between the 48-month moving average PM2.5 (HR: 1.019; 95% CI: 1.012, 1.027), PM10 (HR: 1.009; 95% CI: 1.006, 1.013), SO2 (HR: 1.037; 95% CI: 1.018, 1.055), and O3 (HR: 1.006; 95% CI: 1.001, 1.010) exposure and PP in girls but not boys.

CONCLUSIONS

This study provides valuable insights into the harmful effects of air pollution during childhood and adolescence, emphasizing that air pollution is a risk factor that should be managed and reduced.

Comparative in vitro toxicological effects of water-soluble and insoluble components of atmospheric PM2.5 on human lung cells

Fine particulates in city air significantly impact human health, but the hazardous compositional mechanisms are still unclear. Besides the toxicity of environmental PM2.5 to in vitro human lung epithelial cells (A549), the independent cytotoxicity of PM2.5-bound water-soluble (WS-PM2.5) and water-insoluble (WIS-PM2.5) fractions were also compared by cell viability, oxidative stress (reactive oxygen species, ROS), and inflammatory injury (IL-6 and TNF-α). The cytotoxicity of PM2.5 varied significantly by sampling season and place, with degrees greater in winter and spring than in summer and autumn, related to corresponding trend of air PM2.5 level, and also higher in industrial than urban site, although their PM2.5 pollution levels were comparable. The PM2.5 bound metals (Ni, Cr, Fe, and Mn) may contribute to cellular injury. Both WS-PM2.5 and WIS-PM2.5 posed significant cytotoxicity, that WS-PM2.5 was more harmful than WIS-PM2.5 in terms of decreasing cell viability and increasing inflammatory cytokines production. In particular, industrial samples were usually more toxic than urban samples, and those from summer were generally less toxic than other seasons. Hence, in order to mitigate the health risks of PM2.5 pollution, the crucial targets might be components of heavy metals and soluble fractions, and sources in industrial areas, especially during the cold seasons.

The relationship of climate change to rhinitis

Evidence is mounting that climate change is having a significant impact on exacerbations of rhinitis. Concomitantly, the prevalence of allergic rhinitis is increasing at an accelerated rate. We herein explore the impact of carbon dioxide, barometric pressure and humidity changes, anthropogenic pollutants, on aeroallergens and rhinitis hypersensitivity. Important immune mechanisms underlying the climate-driven effects on rhinitis are discussed. Also, climate change is shifting ecological zones and seasons, increasing weather extremes, and altering regional atmospheric and environmental conditions. The direct impact of these factors on promoting allergic and nonallergic rhinitis are reviewed.

Childhood exposure to outdoor air pollution in different microenvironments and cognitive and fine motor function in children from six European cohorts

BACKGROUND

Exposure to air pollution during childhood has been linked with adverse effects on cognitive development and motor function. However, limited research has been done on the associations of air pollution exposure in different microenvironments such as home, school, or while commuting with these outcomes.

OBJECTIVE

To analyze the association between childhood air pollution exposure in different microenvironments and cognitive and fine motor function from six European birth cohorts.

METHODS

We included 1301 children from six European birth cohorts aged 6-11 years from the HELIX project. Average outdoor air pollutants concentrations (NO2, PM2.5) were estimated using land use regression models for different microenvironments (home, school, and commute), for 1-year before the outcome assessment. Attentional function, cognitive flexibility, non-verbal intelligence, and fine motor function were assessed using the Attention Network Test, Trail Making Test A and B, Raven Colored Progressive Matrices test, and the Finger Tapping test, respectively. Adjusted linear regressions models were run to determine the association between each air pollutant from each microenvironment on each outcome.

RESULTS

In pooled analysis we observed high correlation (rs = 0.9) between air pollution exposures levels at home and school. However, the cohort-by-cohort analysis revealed correlations ranging from low to moderate. Air pollution exposure levels while commuting were higher than at home or school. Exposure to air pollution in the different microenvironments was not associated with working memory, attentional function, non-verbal intelligence, and fine motor function. Results remained consistently null in random-effects meta-analysis.

CONCLUSIONS

No association was observed between outdoor air pollution exposure in different microenvironments (home, school, commute) and cognitive and fine motor function in children from six European birth cohorts. Future research should include a more detailed exposure assessment, considering personal measurements and time spent in different microenvironments.