Long-term exposure to air pollution and mortality in a Danish nationwide administrative cohort study: Beyond mortality from cardiopulmonary disease and lung cancer

Long-term exposure to air pollution and chronic kidney disease-associated mortality - results from the pooled cohort of the European multicentre ELAPSE-study

Despite the known link between air pollution and cause-specific mortality, its relation to chronic kidney disease (CKD)-associated mortality is understudied. Therefore, we investigated the association between long-term exposure to air pollution and CKD-related mortality in a large multicentre population-based European cohort. Cohort data were linked to local mortality registry data. CKD-death was defined as ICD10 codes N18-N19 or corresponding ICD9 codes. Mean annual exposure at participant's home address was determined with fine spatial resolution exposure models for nitrogen dioxide (NO2), black carbon (BC), ozone (O3), particulate matter ≤2.5μm (PM2.5) and several elemental constituents of PM2.5. Cox regression models were adjusted for age, sex, cohort, calendar year of recruitment, smoking status, marital status, employment status and neighbourhood mean income. Over a mean follow-up time of 20.4 years, 313 of 289 564 persons died from CKD. Associations were positive for PM2.5 (hazard ratio (HR) with 95% confidence interval (CI) of 1.31 (1.03-1.66) per 5μg/m3, BC (1.26 (1.03-1.53) per 0.5×10- 5/m), NO2 (1.13 (0.93-1.38) per 10μg/m3) and inverse for O3 (0.71 (0.54-0.93) per 10μg/m3). Results were robust to further covariate adjustment. Exclusion of the largest sub-cohort contributing 226 cases, led to null associations. Among the elemental constituents, Cu, Fe, K, Ni, S and Zn, representing different sources including traffic, biomass and oil burning and secondary pollutants, were associated with CKD-related mortality. In conclusion, our results suggest an association between air pollution from different sources and CKD-related mortality.

Enhancing vehicular emissions monitoring: A GA-GRU-based soft sensors approach for HDDVs

Vehicle emissions have a serious impact on urban air quality and public health, so environmental authorities around the world have introduced increasingly stringent emission regulations to reduce vehicle exhaust emissions. Nowadays, PEMS (Portable Emission Measurement System) is the most widely used method to measure on-road NOx (Nitrogen Oxides) and PN (Particle Number) emissions from HDDVs (Heavy-Duty Diesel Vehicles). However, the use of PEMS requires a lot of workforce and resources, making it both costly and time-consuming. This study proposes a neural network based on a combination of GA (Genetic Algorithm) and GRU (Gated Recurrent Unit), which uses CC (Pearson Correlation Coefficient) to determine and simplify OBD (On-board Diagnosis) data. The GA-GRU model is trained under three real driving conditions of HDDVs, divided by vehicle driving parameters, and then embedded as a soft sensor in the OBD system to monitor real-time emissions of NOx and PN within the OBD system. This research addresses the existing research gap in the development of soft sensors specifically designed for NOx and PN emission monitoring. In this study, it is demonstrated that the described soft sensor has excellent R2 values and outperforms other conventional models. This research highlights the ability of the proposed soft sensor to eliminate outliers accurately and promptly while consistently tracking predictions throughout the vehicle's lifetime. This method is a groundbreaking update to the vehicle's OBD system, permanently adding monitoring data to the vehicle's OBD, thus fundamentally improving the vehicle's self-monitoring capabilities.

Using particle dimensionality-based modeling to estimate lung carcinogenicity of 3D printer emissions

The use of 3D printing technologies by industry and consumers is expanding. However, the approaches to assess the risk of lung carcinogenesis from the emissions of 3D printers have not yet been developed. The objective of the study was to demonstrate a methodology for modeling lung cancer risk related to specific exposure levels as derived from an experimental study of 3D printer emissions for various types of filaments (ABS, PLA, and PETG). The emissions of 15 filaments were assessed at varying extrusion temperatures for a total of 23 conditions in a Class 1,000 cleanroom following procedures described by ANSI/CAN/UL 2904. Three approaches were utilized for cancer risk estimation: (a) calculation based on PM2.5 and PM10 concentrations, (b) a proximity assessment based on the pulmonary deposition fraction, and (c) modeling based on the mass-weighted aerodynamic diameter of particles. The combined distribution of emitted particles had the mass median aerodynamic diameter (MMAD) of 0.35 μm, GSD 2.25. The average concentration of PM2.5 was 25.21 μg/m3 . The spline-based function of aerodynamic diameter allowed us to reconstruct the carcinogenic potential of seven types of fine and ultrafine particles (crystalline silica, fine TiO2 , ultrafine TiO2 , ambient PM2.5 and PM10, diesel particulates, and carbon nanotubes) with a correlation of 0.999, P < 0.00001. The central tendency estimation of lung cancer risk for 3D printer emissions was found at the level of 14.74 cases per 10,000 workers in a typical exposure scenario (average cumulative exposure of 0.3 mg/m3 - years), with the lowest risks for PLA filaments, and the highest for PETG type.

Assessment of cellular senescence potential of PM2.5 using 3D human lung fibroblast spheroids in vitro model

Background

Epidemiological studies demonstrate that particulate matter 2.5 (PM2.5) exposure closely related to chronic respiratory diseases. Cellular senescence plays an important role in many diseases. However, it is not fully clear whether PM2.5 exposure could induce cellular senescence in the human lung. In this study, we generated a three-dimensional (3D) spheroid model using isolated primary human lung fibroblasts (HLFs) to investigate the effects of PM2.5 on cellular senescence at the 3D level.

Methods

3D spheroids were exposed to 25-100 μg/ml of PM2.5 in order to evaluate the impact on cellular senescence. SA-β-galactosidase activity, cell proliferation, and the expression of key genes and proteins were detected.

Results

Exposure of the HLF spheroids to PM2.5 yielded a more sensitive cytotoxicity than 2D HLF cell culture. Importantly, PM2.5 exposure induced the rapid progression of cellular senescence in 3D HLF spheroids, with a dramatically increased SA-β-Gal activity. In exploiting the mechanism underlying the effect of PM2.5 on senescence, we found a significant increase of DNA damage, upregulation of p21 protein levels, and suppression of cell proliferation in PM2.5-treated HLF spheroids. Moreover, PM2.5 exposure created a significant inflammatory response, which may be at least partially associated with the activation of TGF-β1/Smad3 axis and HMGB1 pathway.

Conclusions

Our results indicate that PM2.5 could induce DNA damage, inflammation, and cellular senescence in 3D HLF spheroids, which may provide a new evidence for PM2.5 toxicity based on a 3D model which has been shown to be more in vivo-like in their phenotype and physiology than 2D cultures.

Long-term ozone exposure and all-cause mortality: Cohort evidence in China and global heterogeneity by region

BACKGROUND

Cohort evidence linking long-term ozone (O3) exposure to mortality remained largely mixed worldwide and was extensively deficient in densely-populated Asia. This study aimed to assess the long-term effects of O3 exposure on all-cause mortality among Chinese adults, as well as to examine potential regional heterogeneity across the globe.

METHODS

A national dynamic cohort of 42153 adults aged 16+ years were recruited from 25 provinces across Chinese mainland and followed up during 2010-2018. Annual warm-season (April-September) O3 and year-round co-pollutants (i.e., nitrogen dioxide [NO2] and fine particulate matter [PM2.5]) were simulated through validated spatial-temporal prediction models and were assigned to each enrollee in each calendar year. Cox proportional hazards models with time-varying exposures were employed to assess the O3-mortality association. Concentration-response (C-R) curves were fitted by natural cubic spline function to investigate the potential nonlinear association. Both single-pollutant model and co-pollutant models additionally adjusting for PM2.5 and/or NO2 were employed to examine the robustness of the estimated association. The random-effect meta-analysis was adopted to pool effect estimates from the current and prior population-based cohorts (n = 29), and pooled C-R curves were fitted through the meta-smoothing approach by regions.

RESULTS

The study population comprised of 42153 participants who contributed 258921.5 person-years at risk (median 6.4 years), of whom 2382 death events occurred during study period. Participants were exposed to an annual average of 51.4 ppb (range: 22.7-74.4 ppb) of warm-season O3 concentration. In the single-pollutant model, a significantly increased hazard ratio (HR) of 1.098 (95% confidence interval [CI]: 1.023-1.179) was associated with a 10-ppb rise in O3 exposure. Associations remained robust to additional adjustments of co-pollutants, with HRs of 1.099 (95% CI: 1.023-1.180) in bi-pollutant model (+PM2.5) and 1.093 (95% CI: 1.018-1.174) in tri-pollutant model (+PM2.5+NO2), respectively. A J-shaped C-R relationship was identified among Chinese general population, suggesting significant excess mortality risk at high ozone exposure only. The combined C-R curves from Asia (n = 4) and North America (n = 17) demonstrated an overall increased risk of all-cause mortality with O3 exposure, with pooled HRs of 1.124 (95% CI: 0.966-1.307) and 1.023 (95% CI: 1.007-1.039) per 10-ppb rise, respectively. Conversely, an opposite association was observed in Europe (n = 8, HR: 0.914 [95% CI: 0.860-0.972]), suggesting significant heterogeneity across regions (P < 0.01).

CONCLUSIONS

This study provided national evidence that high O3 exposure may curtail long-term survival of Chinese general population. Great between-region heterogeneity of pooled O3-mortality was identified across North America, Europe, and Asia.

Long-term NO2 exposure and mortality: A comprehensive meta-analysis

In response to the World Health Organization's (WHO) revised annual mean nitrogen dioxide (NO2) standard from 40 μg/m3 to 10 μg/m3, reflecting the growing evidence linking long-term exposure to ambient NO2 and excess mortality, we conducted a comprehensive meta-analysis incorporating 11 new studies published since the WHO analysis. Our investigation involved a systematic search of three major databases (PubMed, Web of Science, and Scopus) for articles published until July 1, 2022. We employed random effects models to calculate summarized risk ratios (RR) along with 95% confidence intervals (CIs) for overall and subgroup analyses. Sensitivity analyses were conducted to assess result robustness, and publication bias was evaluated using funnel plots and Egger's linear regression. Out of 2799 identified articles, 56 were included in our meta-analysis. The findings indicate a heightened risk of all-cause, cardiovascular, and respiratory mortality associated with long-term exposure to ambient NO2, with pooled RR values of 1.03 (95% CI: 1.02, 1.05), 1.07 (95% CI: 1.04, 1.10), and 1.03 (95% CI: 1.02, 1.05) per 10 μg/m3 increase, respectively. Substantial heterogeneity (I2 = 84%-96%) among studies was observed. Subgroup analysis revealed significantly elevated RR values in Asia and Oceania (p-value <0.05). The aggregated values for all-cause and cardiovascular mortality were slightly larger than those reported in previous studies. Our study emphasizes the imperative to develop more patient cohorts and conduct age-refined analyses to explore the impact of existing chronic diseases on these associations. Further, additional cohorts in Asia and Oceania are essential to fortify evidence in these regions. Lastly, we recommend using fused multi-source data with higher spatiotemporal resolution for individual exposure representation to minimize heterogeneity among studies in future research.

Aerial monitoring of atmospheric particulate matter produced by open-pit mining using low-cost airborne sensors

Mining is an economic activity that entails the production and displacement of significant amounts of atmospheric particulate matter (PM) during operations involving intense earthcrushing or earthmoving. As high concentrations of PM may have adverse effects on human health, it is necessary to monitor and control the fugitive emissions of this pollutant. This paper presents an innovative methodology for the online monitoring of PM10 concentrations in air using a low-cost sensor (LCS, <300 USD) onboard an unmanned aerial vehicle. After comprehensive calibration, the LCS was horizontally flown over seven different areas of the large Riotinto copper mine (Huelva, Spain) at different heights to study the PM10 distribution at different longitudes and altitudes. The flights covered areas of zero activity, intense mining, drilling, ore loading, waste discharge, open stockpiling, and mineral processing. In the zero-activity area, the resuspension of PM10 was very low, with a weak wind speed (3.6 m/s). In the intense-mining area, unhealthy concentrations of PM10 (>51 μgPM10/m3) could be released, and the PM10 can reach surrounding populations through long-distance transport driven by several processes being performed simultaneously. Strong dilution was also observed at high altitudes (> 50 m). Mean concentrations were found to be 22-89 μgPM10/m3, with peaks ranging from 86 to 284 μgPM10/m3. This study demonstrates the potential applicability of airborne LCSs in the high-resolution online monitoring of PM in mining, thus supporting environmental managers during decision-making against fugitive emissions in a cost-effective manner.

Associations of long-term fine particulate matter exposure with all-cause and cause-specific mortality: results from the ChinaHEART project

Background

The chronic effects of fine particulate matter (PM2.5) at high concentrations remains uncertain. We aimed to examine the relationship of long-term PM2.5 exposure with all-cause and the top three causes of death (cardiovascular disease [CVD], cancer, and respiratory disease), and to analyze their concentration-response functions over a wide range of concentrations.

Methods

We enrolled community residents aged 35-75 years from 2014 to 2017 from all 31 provinces of the Chinese Mainland, and followed them up until 2021. We used a long-term estimation dataset for both PM2.5 and O3 concentrations with a high spatiotemporal resolution to assess the individual exposure, and used Cox proportional hazards models to estimate the associations between PM2.5 and mortalities.

Findings

We included 1,910,923 participants, whose mean age was 55.6 ± 9.8 years and 59.4% were female. A 10 μg/m3 increment in PM2.5 exposure was associated with increased risk for all-cause death (hazard ratio 1.02 [95% confidence interval 1.012-1.028]), CVD death (1.024 [1.011-1.037]), cancer death (1.037 [1.023-1.052]), and respiratory disease death (1.083 [1.049-1.117]), respectively. Long-term PM2.5 exposure nonlinearly related with all-cause, CVD, and cancer mortalities, while linearly related with respiratory disease mortality.

Interpretation

The overall effects of long-term PM2.5 exposure on mortality in the high concentration settings are weaker than previous reports from settings of PM2.5 concentrations < 35 μg/m³. The distinct concentration-response relationships of CVD, cancer, and respiratory disease mortalities could facilitate targeted public health efforts to prevent death caused by air pollution.

Funding

The Chinese Academy of Medical Sciences Innovation Fund for Medical Science, the National High Level Hospital Clinical Research Funding, the Ministry of Finance of China and National Health Commission of China, the 111 Project from the Ministry of Education of China.

Long-Term Exposure to Low-Level PM2.5 and Mortality: Investigation of Heterogeneity by Harmonizing Analyses in Large Cohort Studies in Canada, United States, and Europe

BACKGROUND

Studies across the globe generally reported increased mortality risks associated with particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) exposure with large heterogeneity in the magnitude of reported associations and the shape of concentration-response functions (CRFs). We aimed to evaluate the impact of key study design factors (including confounders, applied exposure model, population age, and outcome definition) on PM 2.5 effect estimates by harmonizing analyses on three previously published large studies in Canada [Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE), 1991-2016], the United States (Medicare, 2000-2016), and Europe [Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), 2000-2016] as much as possible.

METHODS

We harmonized the study populations to individuals 65 + years of age, applied the same satellite-derived PM 2.5 exposure estimates, and selected the same sets of potential confounders and the same outcome. We evaluated whether differences in previously published effect estimates across cohorts were reduced after harmonization among these factors. Additional analyses were conducted to assess the influence of key design features on estimated risks, including adjusted covariates and exposure assessment method. A combined CRF was assessed with meta-analysis based on the extended shape-constrained health impact function (eSCHIF).

RESULTS

More than 81 million participants were included, contributing 692 million person-years of follow-up. Hazard ratios and 95% confidence intervals (CIs) for all-cause mortality associated with a 5 - μ g / m 3 increase in PM 2.5 were 1.039 (1.032, 1.046) in MAPLE, 1.025 (1.021, 1.029) in Medicare, and 1.041 (1.014, 1.069) in ELAPSE. Applying a harmonized analytical approach marginally reduced difference in the observed associations across the three studies. Magnitude of the association was affected by the adjusted covariates, exposure assessment methodology, age of the population, and marginally by outcome definition. Shape of the CRFs differed across cohorts but generally showed associations down to the lowest observed PM 2.5 levels. A common CRF suggested a monotonically increased risk down to the lowest exposure level. https://doi.org/10.1289/EHP12141.

Antagonism between ambient ozone increase and urbanization-oriented population migration on Chinese cardiopulmonary mortality

Ever-increasing ambient ozone (O3) pollution in China has been exacerbating cardiopulmonary premature deaths. However, the urban-rural exposure inequity has seldom been explored. Here, we assess population-scale O3 exposure and mortality burdens between 1990 and 2019 based on integrated pollution tracking and epidemiological evidence. We find Chinese population have been suffering from climbing O3 exposure by 4.3 ± 2.8 ppb per decade as a result of rapid urbanization and growing prosperity of socioeconomic activities. Rural residents are broadly exposed to 9.8 ± 4.1 ppb higher ambient O3 than the adjacent urban citizens, and thus urbanization-oriented migration compromises the exposure-associated mortality on total population. Cardiopulmonary excess premature deaths attributable to long-term O3 exposure, 373,500 (95% uncertainty interval [UI]: 240,600-510,900) in 2019, is underestimated in previous studies due to ignorance of cardiovascular causes. Future O3 pollution policy should focus more on rural population who are facing an aggravating threat of mortality risks to ameliorate environmental health injustice.

The impact of air pollution on respiratory diseases in an era of climate change: A review of the current evidence

The impacts of climate change and air pollution on respiratory diseases present significant global health challenges. This review aims to investigate the effects of the interactions between these challenges focusing on respiratory diseases. Climate change is predicted to increase the frequency and intensity of extreme weather events amplifying air pollution levels and exacerbating respiratory diseases. Air pollution levels are projected to rise due to ongoing economic growth and population expansion in many areas worldwide, resulting in a greater burden of respiratory diseases. This is especially true among vulnerable populations like children, older adults, and those with pre-existing respiratory disorders. These challenges induce inflammation, create oxidative stress, and impair the immune system function of the lungs. Consequently, public health measures are required to mitigate the effects of climate change and air pollution on respiratory health. The review proposes that reducing greenhouse gas emissions contribute to slowing down climate change and lessening the severity of extreme weather events. Enhancing air quality through regulatory and technological innovations also helps reduce the morbidity of respiratory diseases. Moreover, policies and interventions aimed at improving healthcare access and social support can assist in decreasing the vulnerability of populations to the adverse health effects of air pollution and climate change. In conclusion, there is an urgent need for continuous research, establishment of policies, and public health efforts to tackle the complex and multi-dimensional challenges of climate change, air pollution, and respiratory health. Practical and comprehensive interventions can protect respiratory health and enhance public health outcomes for all.

Long-term exposure to air pollution and incidence of mental disorders. A large longitudinal cohort study of adults within an urban area

BACKGROUND

Recent epidemiological evidence suggests associations between air pollution exposure and major depressive disorders, but the literature is inconsistent for other mental illnesses. We investigated the associations of several air pollutants and road traffic noise with the incidence of different categories of mental disorders in a large population-based cohort.

METHODS

We enrolled 1,739,277 individuals 30 + years from the 2011 census in Rome, Italy, and followed them up until 2019. In detail, we analyzed 1,733,331 participants (mean age 56.43 +/- 15.85 years; 54.96 % female) with complete information on covariates of interest. We excluded subjects with prevalent mental disorders at baseline to evaluate the incidence (first hospitalization or co-pay exemption) of schizophrenia spectrum disorders, bipolar, anxiety, personality, or substance use disorders. In addition, we studied subjects with first prescriptions of antipsychotics, antidepressants, and mood stabilizers. Annual average concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO₂), Black Carbon (BC), ultrafine particles (UFP), and road traffic noise were assigned to baseline residential addresses. We applied Cox regression models adjusted for individual and area-level covariates.

RESULTS

Each interquartile range (1.13 µg/m3) increase in PM2.5 was associated with a hazard ratio (HR) of 1.070 (95 % confidence interval [CI]: 1.017, 1.127) for schizophrenia spectrum disorder, 1.135 (CI: 1.086, 1.186) for depression, 1.097 (CI: 1.030, 1.168) for anxiety disorders. Positive associations were also detected for BC and UFP, and with the three categories of drug prescriptions. Bipolar, personality, and substance use disorders did not show clear associations. The effects were highest in the age group 30-64 years, except for depression.

CONCLUSIONS

Long-term exposure to ambient air pollution, especially fine and ultrafine particles, was associated with increased risks of schizophrenia spectrum disorder, depression, and anxiety disorders. The association of the pollutants with the prescriptions of specific drugs increases the credibility of the results.

Long-term exposure to low-level air pollution and greenness and mortality in Northern Europe. The Life-GAP project

BACKGROUND

Air pollution has been linked to mortality, but there are few studies examining the association with different exposure time windows spanning across several decades. The evidence for the effects of green space and mortality is contradictory.

OBJECTIVE

We investigated all-cause mortality in relation to exposure to particulate matter (PM2.5 and PM10), black carbon (BC), nitrogen dioxide (NO2), ozone (O3) and greenness (normalized difference vegetation index - NDVI) across different exposure time windows.

METHODS

The exposure assessment was based on a combination of the Danish Eulerian Hemispheric Model and the Urban Background Model for the years 1990, 2000 and 2010. The analysis included a complete case dataset with 9,135 participants from the third Respiratory Health in Northern Europe study (RHINE III), aged 40-65 years in 2010, with mortality follow-up to 2021. We performed Cox proportional hazard models, adjusting for potential confounders.

RESULTS

Altogether, 327 (3.6 %) persons died in the period 2010-2021. Increased exposures in 1990 of PM2.5, PM10, BC and NO2 were associated with increased all-cause mortality hazard ratios of 1.40 (95 % CI1.04-1.87 per 5 μg/m3), 1.33 (95 % CI: 1.02-1.74 per 10 μg/m3), 1.16 (95 % CI: 0.98-1.38 per 0.4 μg/m3) and 1.17 (95 % CI: 0.92-1.50 per 10 μg/m3), respectively. No statistically significant associations were observed between air pollution and mortality in other time windows. O3 showed an inverse association with mortality, while no association was observed between greenness and mortality. Adjusting for NDVI increased the hazard ratios for PM2.5, PM10, BC and NO2 exposures in 1990. We did not find significant interactions between greenness and air pollution metrics.

CONCLUSION

Long term exposure to even low levels of air pollution is associated with mortality. Opening up for a long latency period, our findings indicate that air pollution exposures over time may be even more harmful than anticipated.

Air pollution perception bias: Mismatch between air pollution exposure and perception of air quality in real-time contexts

Air pollution perception biases hinder the public's awareness of actual air quality. Past studies that examined the association and mismatch between actual and perceived air quality neglected individuals' dynamic exposure and their activity, travel, spatial, temporal, and social contexts. Using data collected with real-time air pollutant sensors and ecological momentary assessment (EMA), this study investigated the association and mismatch between momentary air pollution exposure and perceived air quality. It also examined how activity type, travel mode, spatial and temporal contexts, and social factors contribute to this disparity. The results show that exposure to air pollution is significantly higher in residential areas (1.777 μg/m3) and transportation land-use areas (2.863 μg/m3) compared to commercial areas. Exposure in the evening is 1.308 μg/m3 higher than in the afternoon. Working or studying activities are associated with 2.863 μg/m3 lower exposure, and individuals perceive air quality as good when working or studying and in residential areas. Conversely, individuals assess air quality as poor in railway travel contexts and being accompanied by friends. This study also reveals the nonstationary association between air pollution exposure and perceived air quality. The odds of underestimating air pollution are 1.8-2.7 times as high as that in residential areas and 2.1 to 2.6 times that in transportation land-use areas when compared to commercial areas. Implementing targeted mitigation measures in these contexts can enhance public awareness of air pollution.

Association of long-term exposure to air pollution with chronic sleep deprivation in South Korea: A community-level longitudinal study, 2008-2018

BACKGROUND AND OBJECTIVE

Although there are many findings about the effects of fine particulate matter (PM_2.5) and sleep deprivation on health respectively, the association between PM_2.5 and chronic sleep deprivation has rarely been investigated. Thus, we aimed to investigate this association using a nationwide survey in South Korea.

METHOD

We examined the association between long-term exposure to PM_2.5 and chronic sleep deprivation using a national cross-sectional health survey covering the entire 226 districts in inland South Korea from 2008 to 2018, with a machine learning-based national air pollution prediction model with 1 km² spatial resolution.

RESULTS

Chronic sleep deprivation was positively associated with PM_2.5 in the total population (odds ratio (OR): 1.09, 95% confidence interval (CI): 1.05-1.13) and sub-population (low, middle, high population density areas with OR: 1.127, 1.09, and 1.059, respectively). The association was consistently observed in both sexes (males with OR: 1.09, females with OR: 1.09)) and was more pronounced in the elderly population (OR: 1.12) than in the middle-aged (OR: 1.07) and young (OR: 1.09) populations.

CONCLUSIONS

Our results are consistent with the hypothesis regarding the relationship between long-term PM_2.5 exposure and chronic sleep deprivation, and the study provides quantitative evidence for public health interventions to improve air quality that can affect chronic sleep conditions.

Long-term exposure to air pollution and risk of SARS-CoV-2 infection and COVID-19 hospitalisation or death: Danish nationwide cohort study

BACKGROUND

Early ecological studies have suggested links between air pollution and risk of coronavirus disease 2019 (COVID-19), but evidence from individual-level cohort studies is still sparse. We examined whether long-term exposure to air pollution is associated with risk of COVID-19 and who is most susceptible.

METHODS

We followed 3 721 810 Danish residents aged ≥30 years on 1 March 2020 in the National COVID-19 Surveillance System until the date of first positive test (incidence), COVID-19 hospitalisation or death until 26 April 2021. We estimated residential annual mean particulate matter with diameter ≤2.5 μm (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) in 2019 by the Danish DEHM/UBM model, and used Cox proportional hazards regression models to estimate the associations of air pollutants with COVID-19 outcomes, adjusting for age, sex, individual- and area-level socioeconomic status, and population density.

RESULTS

138 742 individuals were infected, 11 270 were hospitalised and 2557 died from COVID-19 during 14 months. We detected associations of PM2.5 (per 0.53 μg·m-3) and NO2 (per 3.59 μg·m-3) with COVID-19 incidence (hazard ratio (HR) 1.10 (95% CI 1.05-1.14) and HR 1.18 (95% CI 1.14-1.23), respectively), hospitalisations (HR 1.09 (95% CI 1.01-1.17) and HR 1.19 (95% CI 1.12-1.27), respectively) and death (HR 1.23 (95% CI 1.04-1.44) and HR 1.18 (95% CI 1.03-1.34), respectively), which were strongest in the lowest socioeconomic groups and among patients with chronic respiratory, cardiometabolic and neurodegenerative diseases. We found positive associations with BC and negative associations with O3.

CONCLUSION

Long-term exposure to air pollution may contribute to increased risk of contracting severe acute respiratory syndrome coronavirus 2 infection as well as developing severe COVID-19 disease requiring hospitalisation or resulting in death.

Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study

BACKGROUND

Fine particulate matter (PM_2.5) is a well-recognized risk factor for premature death. However, evidence on which PM_2.5 components are most relevant is unclear.

METHODS

We evaluated the associations between mortality and long-term exposure to eight PM_2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM_2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM_2.5 mass.

RESULTS

Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03-1.05), RF-Si (1.01; 1.00-1.02), SLR-K (1.03; 1.02-1.04), and RF-K (1.06; 1.05-1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality.

CONCLUSIONS

We present novel results of the relevance of different PM_2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark.

Short and long-term association of exposure to ambient black carbon with all-cause and cause-specific mortality: A systematic review and meta-analysis

Black carbon (BC) is a product of incomplete or inefficient combustion and may be associated with a variety of adverse effects on human health. The objective of this study was to analyze the association between various mortalities and long-/short-term exposure to BC as an independent pollutant. In this systematic review, we searched 4 databases for original research in English up to 6^th October 2022, that investigated population-wide mortality due to BC exposure. We pooled mortality estimates and expressed them as relative risk (RR) per 10 μg/m³ increase in BC. We used a random-effect model to derive the pooled RRs. Of the 3186 studies identified, 29 articles met the eligibility criteria, including 18 long-term exposure studies and 11 short-term exposure studies. In the major meta-analysis and sensitivity analysis, positive associations were found between BC and total mortality and cause-specific disease mortalities. Among them, the short-term effects of BC on total mortality, cardiovascular disease mortality, respiratory disease mortality, and the long-term effects of BC on total mortality, ischemic heart disease mortality, respiratory disease mortality and lung cancer mortality were found to be statistically significant. The heterogeneity of the meta-analysis results was much lower for short-term studies than for long-term. Few studies were at a high risk of bias in any domain. The certainty of the evidence for most of the exposure-outcome pairs was moderate. Our study showed a significantly positive association between short-/long-term BC exposure and various mortalities. We speculate that BC has a higher adverse health effect on the respiratory system than on the cardiovascular system. This is different from the effect of PM_2.5. Therefore, more studies are needed to consider BC as a separate pollutant, and not just as a component of PM_2.5.

Ambient air pollution and clinical dementia: systematic review and meta-analysis

OBJECTIVE

To investigate the role of air pollutants in risk of dementia, considering differences by study factors that could influence findings.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

EMBASE, PubMed, Web of Science, Psycinfo, and OVID Medline from database inception through July 2022.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies that included adults (≥18 years), a longitudinal follow-up, considered US Environmental Protection Agency criteria air pollutants and proxies of traffic pollution, averaged exposure over a year or more, and reported associations between ambient pollutants and clinical dementia. Two authors independently extracted data using a predefined data extraction form and assessed risk of bias using the Risk of Bias In Non-randomised Studies of Exposures (ROBINS-E) tool. A meta-analysis with Knapp-Hartung standard errors was done when at least three studies for a given pollutant used comparable approaches.

RESULTS

2080 records identified 51 studies for inclusion. Most studies were at high risk of bias, although in many cases bias was towards the null. 14 studies could be meta-analysed for particulate matter <2.5 µm in diameter (PM2.5). The overall hazard ratio per 2 μg/m3 PM2.5 was 1.04 (95% confidence interval 0.99 to 1.09). The hazard ratio among seven studies that used active case ascertainment was 1.42 (1.00 to 2.02) and among seven studies that used passive case ascertainment was 1.03 (0.98 to 1.07). The overall hazard ratio per 10 μg/m3 nitrogen dioxide was 1.02 ((0.98 to 1.06); nine studies) and per 10 μg/m3 nitrogen oxide was 1.05 ((0.98 to 1.13); five studies). Ozone had no clear association with dementia (hazard ratio per 5 μg/m3 was 1.00 (0.98 to 1.05); four studies).

CONCLUSION

PM2.5 might be a risk factor for dementia, as well as nitrogen dioxide and nitrogen oxide, although with more limited data. The meta-analysed hazard ratios are subject to limitations that require interpretation with caution. Outcome ascertainment approaches differ across studies and each exposure assessment approach likely is only a proxy for causally relevant exposure in relation to clinical dementia outcomes. Studies that evaluate critical periods of exposure and pollutants other than PM2.5, and studies that actively assess all participants for outcomes are needed. Nonetheless, our results can provide current best estimates for use in burden of disease and regulatory setting efforts.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42021277083.

Short-term exposure to ozone and cause-specific mortality risks and thresholds in China: Evidence from nationally representative data, 2013-2018

BACKGROUND

Ambient ozone pollution is steadily increasing and becoming a major environmental risk factor contributing to the global disease burden. Although the association between short-term ozone exposure and mortality has been widely studied, results are mostly reported on deaths from non-accidental or total cardiopulmonary disease rather than a spectrum of causes. In particular, a knowledge gap still exists for the potential thresholds in mortality risks.

METHODS

This nationwide time-series study in China included 323 counties totaling 230,266,168 residents. Daily maximum 8-hour average was calculated as the ozone exposure metric. A two-stage statistical approach was adopted to assess ozone effects on 21 cause-specific deaths for 2013-2018. The subset approach and threshold approach were utilized to explore potential thresholds, and stratification analysis was used to evaluate population susceptibility.

RESULTS

On average, the annual mean ozone concentration was 93.4 μg/m³ across 323 counties. A 10-μg/m³ increase in lag 0-1 day of ozone was associated with increases of 0.12 % in mortality risk from non-accidental disease, 0.11 % from circulatory disease, 0.09 % from respiratory disease, 0.29 % from urinary system disease, and 0.20 % from nervous system disease. There may be a "safe" threshold in the ozone-mortality association, which may be between 60 and 100 μg/m³, and vary by cause of death. Women and older adults (especially those over 75) are more affected by short-term ozone exposure. Populations in North China had a higher risk of ozone-related circulatory mortality, while populations in South China had a higher risk of ozone-related respiratory mortality.

CONCLUSIONS

National findings link short-term ozone exposure to premature death from circulatory, respiratory, neurological, and urinary diseases, and provide evidence for a potential "safe" threshold in the association of ozone and mortality. These findings have important implications for helping policymakers tighten the relevant air quality standards and developing early warning systems for public health protection in China.

Causal effect of PM1 on morbidity of cause-specific respiratory diseases based on a negative control exposure

BACKGROUND

Extensive studies have linked PM_2.5 and PM₁₀ with respiratory diseases (RD). However, few is known about causal association between PM₁ and morbidity of RD. We aimed to assess the causal effects of PM₁ on cause-specific RD.

METHODS

Hospital admission data were obtained for RD during 2014 and 2019 in Beijing, China. Negative control exposure and extreme gradient boosting with SHapley Additive exPlanation was used to explore the causality and contribution between PM₁ and RD. Stratified analysis by gender, age, and season was conducted.

RESULTS

A total of 1,183,591 admissions for RD were recorded. Per interquartile range (28 μg/m³) uptick in concentration of PM₁ corresponded to a 3.08% [95% confidence interval (CI): 1.66%-4.52%] increment in morbidity of total RD. And that was 4.47% (95% CI: 2.46%-6.52%) and 0.15% (95% CI: 1.44%-1.78%), for COPD and asthma, respectively. Significantly positive causal associations were observed for PM₁ with total RD and COPD. Females and the elderly had higher effects on total RD, COPD, and asthma only in the warm months (Z = 3.03, P = 0.002; Z = 4.01, P < 0.001; Z = 3.92, P < 0.001; Z = 2.11, P = 0.035; Z = 2.44, P = 0.015). Contribution of PM₁ ranked first, second and second for total RD, COPD, and asthma among air pollutants.

CONCLUSION

PM₁ was causally associated with increased morbidity of total RD and COPD, but not causally associated with asthma. Females and the elderly were more vulnerable to PM₁-associated effects on RD.

Lung function decline associated with individual short-term exposure to PM1, PM2.5 and PM10 in patients with allergic rhinoconjunctivitis

BACKGROUND

The susceptibility of allergic rhinoconjunctivitis (ARC) patients to air pollution has yet to be clarified.

OBJECTIVES

Based on a repeated measurement panel study, we explored the association of short-term PM exposure with lung function in ARC patients and to further identify the susceptible populations.

METHODS

Personal PM exposure, including PM₁, PM_2.5 and PM₁₀, was monitored consecutively for three days before outcomes measurements. Lung function indices including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV₁), peak expiratory flow (PEF), and forced expiratory flow at 25-75 % of the vital capacity (FEF_25-75) were measured. Serum total immunoglobulin E (IgE), specific-allergen IgE, blood eosinophil and basophils, and the symptoms severe scores were tested in each visit. Linear mixed effect models were applied to estimate the association between PM exposure and lung function. Furthermore, stratified and overlapping grouped populations based on IgE levels were implemented to characterize the modification role and the modulating threshold of IgE at which the association turned significantly negative.

RESULTS

Short-term PM personal exposure was associated with a significant decrease in lung function in ARC patients, especially for small airway respiratory indexes. The highest estimates occurred in PM₁, specifically a 10 μg/m³ increase reduced FEV₁/FVC, PEF and FEF_25-75 by 1.36 % (95 %CI: -2.29 to -0.43), 0.23 L/s (95 %CI: -0.42 to -0.03) and 0.18 L/s (95 %CI: -0.30 to -0.06), respectively. Notably, PM-induced decreases in lung function were stronger in patients with higher IgE levels (IgE ≥ 100 IU/mL), which were related to higher inflammatory cytokines and symptoms scores. Further, PM-associated lung function declines enhanced robustly and monotonically with increasing IgE concentration. Potential modulating thresholds of IgE occurred at 46.8-59.6 IU/mL for significant PM-lung function associations.

CONCLUSION

These novel findings estimated the short-term effects of PM on lung function in ARC patients, and the threshold values of IgE for the significant and robust associations.

Long-term exposure to ambient ozone and mortality in a population-based cohort of South Korea: Considering for an alternative exposure time metric

Studies on the health effects of long-term ozone exposure remain limited with mixed results. One potential source of this inconsistency is the difference in exposure time metrics. This study aimed to investigate the association between long-term exposure to ambient ozone and mortality in South Korea, using different exposure metrics. We also examined whether heterogeneity between previous studies was due to the different exposure metrics. The study population comprised 179,806 participants from the National Health Insurance Service-National Sample Cohort (2002-2015) residing in seven major cities in South Korea. Several ozone exposure metrics (year-round 24-h, year-round 8-h, warm-season 24-h, and warm-season 8-h) were calculated. Time-varying Cox proportional hazards models were used to estimate the association between ozone and all-cause and cause-specific mortalities. Random-effect meta-analysis and meta-regression analysis were performed to pool the effect estimates of previous studies and examine whether the exposure metric can explain the between-study heterogeneity. The hazard ratios (HRs) per 10 ppb increment in year-round 24-h ozone for all-cause (HR, 1.18; 95% CI, 1.07-1.29) and circulatory (HR, 1.52; 95% CI, 1.25-1.84) mortality were higher than those of the other metrics. Year-round 8-h ozone exhibited the largest association with respiratory mortality (HR, 1.43; 95% CI, 1.04-1.96). A meta-analysis of 29 previous studies and the present study showed the largest HR for all-cause mortality from studies using year-round 8-h exposure (HR, 1.014; 95% CI, 0.994-1.033). The exposure metric was significantly associated with effect estimates in the multivariable meta-regression model. In conclusion, in the population-based cohort in South Korea, we found positive associations between several long-term ozone exposure metrics and mortality. The different ozone exposure metrics exhibited heterogeneous effect estimates. A year-round 24-h average ozone metric also could be considered an alternative long-term standard for ozone.

Air Pollution and Human Health: Investigating the Moderating Effect of the Built Environment

Air pollution seriously threatens human health and even causes mortality. It is necessary to explore effective prevention methods to mitigate the adverse effect of air pollution. Shaping a reasonable built environment has the potential to benefit human health. In this context, this study quantified the built environment, air pollution, and mortality at 1 km × 1 km grid cells. The moderating effect model was used to explore how built environment factors affect the impact of air pollution on cause-specific mortality and the heterogeneity in different areas classified by building density and height. Consequently, we found that greenness played an important role in mitigating the effect of ozone (O3) and nitrogen dioxide (NO2) on mortality. Water area and diversity of land cover can reduce the effect of fine particulate matter (PM2.5) and NO2 on mortality. Additionally, gas stations, edge density (ED), perimeter-area fractal dimension (PAFRAC), and patch density (PD) can reduce the effect of NO2 on mortality. There is heterogeneity in the moderating effect of the built environment for different cause-specific mortality and areas classified by building density and height. This study can provide support for urban planners to mitigate the adverse effect of air pollution from the perspective of the built environment.

Functional Kriging for Spatiotemporal Modeling of Nitrogen Dioxide in a Middle Eastern Megacity

Long-term hour-specific air pollution exposure estimates have rarely been of interest in epidemiological research. However, this can be relevant for studies that aim to estimate the residential exposure for the hours that subjects mostly spend time there, or for those hours that they may work in another location. Here, we developed a model by spatially predicting the long-term diurnal curves of nitrogen dioxide (NO2) in Tehran, Iran, one of the most polluted and populated megacities in the Middle East. We used the statistical framework of functional data analysis (FDA) including ordinary kriging for functional data (OKFD) and functional analysis of variance (fANOVA) for modeling. The long-term NO2 diurnal curves had two distinct maxima and minima. The absolute minimum value of the city average was 40.6 ppb (around 4:00 p.m.) and the absolute maximum value was 52.0 ppb (around 10:00 p.m.). The OKFD showed the concentrations, the diurnal maximum/minimum values, and their corresponding occurring times varied across the city. The fANOVA highlighted that the effect of population density on the NO2 concentrations is not constant and depends on time within the diurnal period. The provided estimation of long-term hour-specific maps can inform future epidemiological studies to use the long-term mean for specific hour(s) of the day. Moreover, the demonstrated FDA framework can be used as a set of flexible statistical methods.