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BACKGROUND: Ambient air pollution, including particulate matter (such as PM10 and PM2·5) and nitrogen dioxide (NO2), has been linked to increases in mortality. Whether populations' vulnerability to these pollutants has changed over time is unclear, and studies on this topic do not include multicountry analysis. We evaluated whether changes in exposure to air pollutants were associated with changes in mortality effect estimates over time. METHODS: We extracted cause-specific mortality and air pollution data collected between 1995 and 2016 from the Multi-Country Multi-City (MCC) Collaborative Research Network database. We applied a two-stage approach to analyse the short-term effects of NO2, PM10, and PM2·5 on cause-specific mortality using city-specific time series regression analyses and multilevel random-effects meta-analysis. We assessed changes over time using a longitudinal meta-regression with time as a linear fixed term and explored potential sources of heterogeneity and two-pollutant models. FINDINGS: Over 21·6 million cardiovascular and 7·7 million respiratory deaths in 380 cities across 24 countries over the study period were included in the analysis. All three air pollutants showed decreasing concentrations over time. The pooled results suggested no significant temporal change in the effect estimates per unit exposure of PM10, PM2·5, or NO2 and mortality. However, the risk of cardiovascular mortality increased from 0·37% (95% CI -0·05 to 0·80) in 1998 to 0·85% (0·55 to 1·16) in 2012 with a 10 µg/m3 increase in PM2·5. Two-pollutant models generally showed similar results to single-pollutant models for PM fractions and indicated temporal differences for NO2. INTERPRETATION: Although air pollution levels decreased during the study period, the effect sizes per unit increase in air pollution concentration have not changed. This observation might be due to the composition, toxicity, and sources of air pollution, as well as other factors, such as socioeconomic determinants or changes in population distribution and susceptibility. FUNDING: None.

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Although there is substantial evidence on the harmful effects of air pollution on human health, these are scarcely considered in the general clinical practice and also in the context of cardiovascular disease prevention. In light of the numerous epidemiological and basic research studies that have demonstrated the unfavorable impact of air pollution on the cardiovascular system, this review aims to bring this aspect to the attention of clinicians. This work describes the main air polluting components that can contribute to the onset and progression of cardiovascular diseases. The pathophysiological mechanisms underlying the impact of pollutants on the cardiovascular system and the available evidence regarding their effect on cardiovascular risk factors are reported. This article also examines the evidence relating to the correlation between environmental pollutants and some specific cardiovascular diseases, including acute coronary syndromes, cerebrovascular diseases, heart failure, and arrhythmias. Finally, the possible strategies to be implemented to limit pollution-induced cardiovascular damage are analyzed.

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Humans can be exposed to multiple pollutants in the air and surface water. These environments are non-static, trans-boundary and correlated, creating a complex network, and significant challenges for research on environmental hazards, especially in real-world cancer research. This article reports on a large study (377 million people in 30 provinces of China) that evaluated the combined impact of air and surface water pollution on cancer. We formulate a spatial evaluation system and a common grading scale for co-pollution measurement, and validate assumptions that air and surface water environments are spatially connected and that cancers of different types tend to cluster in areas where these environments are poorer. We observe "dose-response" relationships in both the number of affected cancer types and the cancer incidence with an increase in degree of co-pollution. We estimate that 62,847 (7.4%) new cases of cancer registered in China in 2016 were attributable to air and surface water pollution, and the majority (69.7%) of these excess cases occurred in areas with the highest level of co-pollution. The findings clearly show that the environment cannot be considered as a set of separate entities. They also support the development of policies for cooperative environmental governance and disease prevention.

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INTRODUCTION: Traffic-related air and noise pollution are important public health issues. The aim of this study was to estimate their effects on allergic/respiratory outcomes in adult and elderly subjects. MATERIALS AND METHODS: Six hundred and forty-five subjects living in Pisa (Tuscany, Italy) were investigated through a questionnaire on allergic/respiratory symptoms and diseases. Traffic-related air pollution and noise exposures were assessed at residential address by questionnaire, modelled annual mean NO2 concentrations (1 km and 200 m resolution), and noise level over a 24-h period (Lden). Exposure effects were assessed through logistic regression models stratified by age group (18-64 years, ≥65 years), and adjusted for sex, educational level, occupational exposure, and smoking habits. RESULTS: 63.6% of the subjects reported traffic exposure near home. Mean exposure levels were: 28.24 (±3.26 SD) and 27.23 (±3.16 SD) µg/m3 for NO2 at 200 m and 1 km of resolution, respectively; 57.79 dB(A) (±6.12 SD) for Lden. Exposure to vehicular traffic (by questionnaire) and to high noise levels [Lden ≥ 60 dB(A)] were significantly associated with higher odds of allergic rhinitis (OR 2.01, 95%CI 1.09-3.70, and OR 1.99, 95%CI 1.18-3.36, respectively) and borderline with rhino-conjunctivitis (OR 2.20, 95%CI 0.95-5.10, and OR 1.76, 95%CI 0.91-3.42, respectively) only in the elderly. No significant result emerged for NO2. CONCLUSIONS: Our findings highlighted the need to better assess the effect of traffic-related exposure in the elderly, considering the increasing trend in the future global population's ageing.

Global population is ageing.Allergic diseases are globally widespread even on adult population.The susceptibility due to ageing may increase the impact of air pollution on the elderly.Traffic-related air and noise pollution affects allergic status of the elderly.

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Importance: The role of air pollution in risk and progression of Parkinson disease (PD) is unclear. Objective: To assess whether air pollution is associated with increased risk of PD and clinical characteristics of PD. Design, Setting, and Participants: This population-based case-control study included patients with PD and matched controls from the Rochester Epidemiology Project from 1998 to 2015. Data were analyzed from January to June 2024. Exposures: Mean annual exposure to particulate matter with a diameter of 2.5 µm or less (PM2.5) from 1998 to 2015 and mean annual exposure to nitrogen dioxide (NO2) from 2000 to 2014. Main Outcomes and Measures: Outcomes of interest were PD risk, all-cause mortality, presence of tremor-predominant vs akinetic rigid PD, and development of dyskinesia. Models were adjusted for age, sex, race and ethnicity, year of index, and urban vs rural residence. Results: A total of 346 patients with PD (median [IQR] age 72 [65-80] years; 216 [62.4%] male) were identified and matched on age and sex with 4813 controls (median [IQR] age, 72 [65-79] years, 2946 [61.2%] male). Greater PM2.5 exposure was associated with increased PD risk, and this risk was greatest after restricting to populations within metropolitan cores (odds ratio [OR], 1.23; 95% CI, 1.11-1.35) for the top quintile of PM2.5 exposure compared with the bottom quintile. Greater NO2 exposure was also associated with increased PD risk when comparing the top quintile with the bottom quintile (OR, 1.13; 95% CI, 1.07-1.19). Air pollution was associated with a 36% increased risk of akinetic rigid presentation (OR per each 1-µg/m3 increase in PM2.5, 1.36; 95% CI, 1.02-1.80). In analyses among patients with PD only, higher PM2.5 exposure was associated with greater risk for developing dyskinesia (HR per 1-µg/m3 increase in PM2.5, 1.42; 95% CI, 1.17-1.73), as was increased NO2 exposure (HR per 1 µg/m3 increase in NO2, 1.13; 95% CI, 1.06-1.19). There was no association between PM2.5 and all-cause mortality among patients with PD. Conclusions and Relevance: In this case-control study of air pollution and PD, higher levels of PM2.5 and NO2 exposure were associated with increased risk of PD; also, higher levels of PM2.5 exposure were associated with increased risk of developing akinetic rigid PD and dyskinesia compared with patients with PD exposed to lower levels. These findings suggest that reducing air pollution may reduce risk of PD, modify the PD phenotype, and reduce risk of dyskinesia.

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This study investigates the impact of air pollution on health outcomes in Middle Eastern countries, a region facing severe environmental challenges. As such, these are important in an effort to add up to policy-level as well as interventional changes that can be put in practice in the area of public health. Numeration analysis and association with health parameters was carried out by using Analytical tools such as, AIR Data, ARIMA,ANN, SVM and Exponential smoothing. Amongst the models, Support Vector Machine came again on top, with high accuracy yielding Mean Absolute Percentage Error of approximately 1%. Mortality of Air pollution in Qat from the case of Mortality of Air Pollution in Qatar is 959 while Auto regressive Integrated Moving average is 11.096, Exponential Smoothing 9.892 and Artificial Neural Networks are the source of inspiration for the development of this paper 4.61. The above perceptions indicate that there is need to adapt modeling strategies depending on the context and establish that it is possible to implement ML models in public health planning basket. This paper publishes the methodological frameworks for the purpose of modeling and analysis of the EHDs and serves as policy prescription for the policy makers to intending to reduce the effects of air borne pollution on health.

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Background: Previous studies indicated that exposure to ambient fine particulate matter (PM2.5) could increase the risk of metabolic syndrome (MetS). However, the specific impact of PM2.5 chemical components remains uncertain. Methods: A national cross-sectional study of 12,846 Chinese middle-aged and older adults was conducted. Satellite-based spatiotemporal models were employed to determine the 3-year average PM2.5 components exposure, including sulfates (SO4 2-), nitrates (NO3 -), ammonia (NH4 +), black carbon (BC), and organic matter (OM). Generalized linear models were used to investigate the associations of PM2.5 components with MetS and the components of MetS, and restricted cubic splines curves were used to establish the exposure-response relationships between PM2.5 components with MetS, as well as the components of MetS. Results: MetS risk increased by 35.1, 33.5, 33.6, 31.2, 32.4, and 31.4% for every inter-quartile range rise in PM2.5, SO4 2-, NO3 -, NH4 +, OM and BC, respectively. For MetS components, PM2.5 chemical components were associated with evaluated risks of central obesity, high blood pressure (high-BP), high fasting glucose (high-FBG), and low high-density lipoprotein cholesterol (low-HDL). Conclusion: This study indicated that exposure to PM2.5 components is related to increased risk of MetS and its components, including central obesity, high-BP, high-FBG, and low-HDL. Moreover, we found that the adverse effect of PM2.5 chemical components on MetS was more sensitive to people who were single, divorced, or widowed than married people.

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Background: Air pollution is one of the biggest problems in societies today. The intensity of indoor and outdoor air pollutants and the urbanization rate can cause or trigger many different diseases, especially lung cancer. In this context, this study's aim is to reveal the effects of the indoor and outdoor air pollutants, and urbanization rate on the lung cancer cases. Methods: Panel data analysis method is applied in this study. The research includes the period between 1990 and 2019 as a time series and the data type of the variables is annual. The dependent variable in the research model is lung cancer cases per 100,000 people. The independent variables are the level of outdoor air pollution, air pollution level indoor environment and urbanization rate of countries. Results: In the modeling developed for the developed country group, it is seen that the variable with the highest level of effect on lung cancer is the outdoor air pollution level. Conclusions: In parallel with the development of countries, it has been determined that the increase in industrial production wastes, in other words, worsening the air quality, may potentially cause an increase in lung cancer cases. Indoor air quality is also essential for human health; negative changes in this variable may negatively impact individuals' health, especially lung cancer.

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Particulate matter with a diameter ≤2.5 µm (PM2.5) poses a substantial global challenge, with a growing recognition of pathogens contributing to diseases associated with exposure to PM2.5 Recent studies have focused on PM2.5, which impairs the immune cells in response to microbial infections and potentially contributes to the development of severe diseases in the respiratory tract. Accordingly, changes in the respiratory immune function and microecology mediated by PM2.5 are important factors that enhance the risk of microbial pathogenesis. These factors have garnered significant interest. In this review, we summarise recent studies on the potential mechanisms involved in PM2.5-mediated immune system disruption and exacerbation of microbial pathogenesis in the respiratory tract. We also discuss crucial areas for future research to address the gaps in our understanding and develop effective strategies to combat the adverse health effects of PM2.5.

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The escalating frequency of environmental pollution incidents has raised significant concerns regarding the potential health impacts of pollutant fluctuations. Consequently, a comprehensive study on the role of pollutants in the prevalence of viral hepatitis is indispensable for the advancement of innovative prevention strategies. Monthly incidence rates of viral hepatitis from 2005 to 2020 were sourced from the Chinese Center for Disease Control and Prevention Infectious Disease Surveillance Information System. Pollution data spanning 2014-2020 were obtained from the National Oceanic and Atmospheric Administration (NOAA), encompassing pollutants such as CO, NO2, and O3. Time series analysis models, including seasonal auto-regressive integrated moving average (SARIMA), Holt-Winters model, and Generalized Additive Model (GAM), were employed to explore prediction and synergistic effects related to viral hepatitis. Spearman correlation analysis was utilized to identify pollutants suitable for inclusion in these models. Concurrently, machine learning (ML) algorithms were leveraged to refine the prediction of environmental pollutant levels. Finally, a weighted quantile sum (WQS) regression framework was developed to evaluate the singular and combined impacts of pollutants on viral hepatitis cases across different demographics, age groups, and environmental strata. The incidence of viral hepatitis in Beijing exhibited a declining trend, primarily characterized by HBV and HCV types. In predicting hepatitis prevalence trends, the Holt-Winters additive seasonal model outperformed the SARIMA multiplicative model ((1,1,0) (2,1,0) [12]). In the prediction of environmental pollutants, the SVM model demonstrated superior performance over the GPR model, particularly with Polynomial and Besseldot kernel functions. The combined pollutant risk effect on viral hepatitis was quantified as ßWQS (95% CI) = 0.066 (0.018, 0.114). Among different groups, PM2.5 emerged as the most sensitive risk factor, notably impacting patients with HCV and HEV, as well as individuals aged 35-64. CO predominantly affected HAV patients, showing a risk effect of ßWQS (95% CI) = - 0.0355 (- 0.0695, - 0.0016). Lower levels of PM2.5 and PM10 were associated with heightened risk of viral hepatitis incidence with a lag of five months, whereas elevated levels of PM2.5 (100-120 µg/m3) and CO correlated with increased hepatitis incidence risk with a lag of six months. The Holt-Winters model outperformed the SARIMA model in predicting the incidence of viral hepatitis. Among machine learning algorithms, SVM and GPR models demonstrated superior performance for analyzing pollutant data. Patients infected with HAV and HEV were primarily influenced by PM10 and CO, whereas SO2 and PM2.5 significantly impacted others. Individuals aged 35-64 years appeared particularly susceptible to these pollutants. Mixed pollutant exposures were found to affect the development of viral hepatitis with a notable lag of 5-6 months. These findings underscore the importance of long-term monitoring of pollutants in relation to viral hepatitis incidence.

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BACKGROUND: Uncertainty remains about the long-term effects of air pollutants (AP) on multiple diseases, especially subtypes of cardiovascular disease (CVD). We aimed to assess the individual and joint associations of fine particulate matter (PM2.5), along with its chemical components, nitrogen dioxide (NO2) and ozone (O3), with risks of 32 health conditions. METHODS: A total of 17,566 participants in Sichuan Province, China, were included in 2018 and followed until 2022, with an average follow-up period of 4.2 years. The concentrations of AP were measured using a machine-learning approach. The Cox proportional hazards model and quantile g-computation were applied to assess the associations between AP and CVD. RESULTS: Per interquartile range (IQR) increase in PM2.5 mass, NO2, O3, nitrate, ammonium, organic matter (OM), black carbon (BC), chloride, and sulfate were significantly associated with increased risks of various conditions, with hazard ratios (HRs) ranging from 1.06 to 2.48. Exposure to multiple air pollutants was associated with total cardiovascular disease (HR 1.75, 95% confidence intervals (CIs) 1.62-1.89), hypertensive diseases (1.49, 1.38-1.62), cardiac arrests (1.52, 1.30-1.77), arrhythmia (1.76, 1.44-2.15), cerebrovascular diseases (1.86, 1.65-2.10), stroke (1.77, 1.54-2.03), ischemic stroke (1.85, 1.61-2.12), atherosclerosis (1.77, 1.57-1.99), diseases of veins, lymphatic vessels, and lymph nodes (1.32, 1.15-1.51), pneumonia (1.37, 1.16-1.61), inflammatory bowel diseases (1.34, 1.16-1.55), liver diseases (1.59, 1.43-1.77), type 2 diabetes (1.48, 1.26-1.73), lipoprotein metabolism disorders (2.20, 1.96-2.47), purine metabolism disorders (1.61, 1.38-1.88), anemia (1.29, 1.15-1.45), sleep disorders (1.54, 1.33-1.78), renal failure (1.44, 1.21-1.72), kidney stone (1.27, 1.13-1.43), osteoarthritis (2.18, 2.00-2.39), osteoporosis (1.36, 1.14-1.61). OM had max weights for joint effects of AP on many conditions. CONCLUSIONS: Long-term exposure to increased levels of multiple air pollutants was associated with risks of multiple health conditions. OM accounted for substantial weight for these increased risks, suggesting it may play an important role in these associations.

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Numerous studies have been conducted in other countries on the health effects of exposure to particulate matter with a diameter of 10 microns or less P M 10 , but little research has been conducted in Malaysia, particularly during the haze season. This study intends to investigate how exposure of P M 10 influenced hospital admissions for respiratory diseases during the haze period in peninsula Malaysia and it was further stratified by age group, gender and respiratory diseases categories. The study includes data from all patients with respiratory diseases in 92 government hospitals, as well as P M 10 concentration and meteorological data from 92 monitoring stations in Peninsula Malaysia starting from 1st January 2000 to 31st December 2019. A quasi-poison time series regression with distributed lag nonlinear model (DLNM) was employed in this study to examine the relationship between exposure of P M 10 and hospital admissions for respiratory diseases during the haze period. Haze period for this study has been defined from June to September each year. According to the findings of this study, P M 10 was positively associated with hospitalisation of respiratory disease within 30 lag days under various lag patterns, with lag 25 showing the strongest association (RR = 1.001742, CI 1.001029,1.002456). Using median as a reference, it was discovered that females were more likely than males to be hospitalized for P M 10 exposure. Working age group will be the most affected by the increase in P M 10 exposure with a significant cumulative RR from lag 010 to lag 030. The study found that P M 10 had a significant influence on respiratory hospitalisation in peninsula Malaysia, particularly for lung diseases caused by external agents(CD5). Therefore, it is important to implement effective intervention measures to control P M 10 and reduce the burden of respiratory disease admissions.

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BACKGROUND: Particulate matter with a diameter of < 2.5 µm (PM2.5) influences gene regulation via DNA methylation; however, its precise mechanism of action remains unclear. Thus, this study aimed to examine the connection between personal PM2.5 exposure and DNA methylation in CpG islands as well as explore the associated gene pathways. METHODS: A total of 95 male patients with chronic obstructive pulmonary disease (COPD) were enrolled in this study. PM2.5 concentrations were measured for 12 months, with individual exposure recorded for 24 h every 3 months. Mean indoor and estimated individual PM2.5 exposure levels were calculated for short-term (7 days), mid-term (35 days), and long-term (90 days). DNA methylation analysis was performed on the blood samples, which, after PCR amplification and hybridization, were finally sequenced using an Illumina NovaSeq 6000 system. Correlation between PM2.5 exposure and CpG methylation sites was confirmed via a mixed-effects model. Functional enrichment analysis was performed on unique CpG methylation sites associated with PM2.5 exposure to identify the relevant biological functions or pathways. RESULTS: The number of CpG sites showing differential methylation was 36, 381, and 182 for the short-, mid-, and long-term indoor models, respectively, and 3, 98, and 28 for the short-, mid-, and long-term estimated exposure models, respectively. The representative genes were TMTC2 (p = 1.63 × 10-3, R2 = 0.656), GLRX3 (p = 1.46 × 10-3, R2 = 0.623), DCAF15 (p = 2.43 × 10-4, R2 = 0.623), CNOT6L (p = 1.46 × 10-4, R2 = 0.609), BSN (p = 2.21 × 10-5, R2 = 0.606), and SENP6 (p = 1.59 × 10-4, R2 = 0.604). Functional enrichment analysis demonstrated that the related genes were mostly associated with pathways related to synaptic transmission in neurodegenerative diseases and cancer. CONCLUSION: A significant association was observed between PM2.5 exposure and DNA methylation upon short-term exposure, and the extent of DNA methylation was the highest upon mid-term exposure. Additionally, various pathways related to neurodegenerative diseases and cancer were associated with patients with COPD. GOV IDENTIFIER: NCT04878367.

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OBJECTIVE: Air pollution is a global public health issue, with particulate matter (PM) being the pollutant with the greatest impact on health. The main objective of this article was to estimate the impact of mortality attributable to particulate pollution in the city of Valencia during the period 2015-2017. METHODS: The Health Impact Assessment (HIA) methodology from the Aphekom project was used. Scenarios of a 5 µg/m3 reduction in the annual mean concentration of PM10 and PM2.5 were employed, along with the assumption of meeting the World Health Organization (WHO) recommendations in effect during the study period, to estimate both short- and long-term impacts. RESULTS: The estimated average concentrations for 2015-2017 were 18.4 µg/m3 for PM10 and 12.3 µg/m3 for PM2.5. The short-term HIA, assuming a reduction of 5 µg/m3 in the averages, resulted in a total of 65.4 premature deaths that could be postponed during that period (21.8 annually), corresponding to a rate of 2.8 deaths per 100,000 inhabitants. In the long term, if PM2.5 concentrations had been reduced by 5 µg/m3, 124 premature deaths could have been postponed annually. CONCLUSIONS: The annual average concentrations of these pollutants meet the limits set by European regulations. However, compared to WHO recommendations, PM2.5 levels are higher by 2.3 µg/m3. An air quality scenario in line with WHO recommendations would have resulted in a reduction of 122 premature deaths annually.

OBJETIVO: La contaminación del aire es un problema de Salud Pública de importancia global, siendo las partículas en suspensión (PM) el contaminante con mayor impacto en la salud. El objetivo principal de este artículo fue estimar el impacto en mortalidad atribuible a la contaminación por partículas en la ciudad de València en el periodo 2015-2017. METODOS: Se utilizó la metodología para la Evaluación del Impacto en Salud (EIS) del proyecto Aphekom. Se realizó un estudio descriptivo y para la correlación se emplearon los escenarios de reducción de la media anual de 5 µg/m3 en la concentración de PM10 y de PM2,5 y el supuesto de cumplir las recomendaciones de la Organización Mundial de la Salud (OMS) vigentes en el periodo a estudio para estimar el impacto a corto y largo plazo. RESULTADOS: Las concentraciones estimadas del promedio 2015-2017 para PM10 y PM2,5 fueron de 18,4 µg/m3 y 12,3 µg/m3, respectivamente. La EIS a corto plazo, en el supuesto de reducir en 5 µg/m3 las medias, tuvo como resultado un total de 65,4 muertes prematuras que se podrían posponer en ese periodo (21,8 anuales), correspondiendo con una tasa de 2,8 defunciones por cada 100.000 habitantes. A largo plazo, si se hubiesen reducido las concentraciones de PM2,5 en 5 µg/m3, se hubieran podido posponer 124 muertes prematuras anuales. CONCLUSIONES: Las concentraciones medias anuales de estos contaminantes se ajustan a los límites marcados por la normativa europea. Sin embargo, respecto a las recomendaciones de la OMS, los niveles de PM2,5 son superiores en 2,3 µg/m3. Un escenario de calidad del aire conforme a las recomendaciones de la OMS se hubiera traducido en una reducción de 122 defunciones prematuras anuales.

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BACKGROUND: Epidemiological and toxicological studies indicate that increased exposure to air pollutants can lead to neurodegenerative diseases. To further confirm this relationship, we evaluated the association between exposure to ambient air pollutants and corneal nerve measures as a surrogate for neurodegeneration, using corneal confocal microscopy. METHODS: We used population-based observational cross-sectional data from The Maastricht Study including N = 3635 participants (mean age 59.3 years, 51.6% were women, and 19.9% had type 2 diabetes) living in the Maastricht area. Using the Geoscience and hEalth Cohort COnsortium (GECCO) data we linked the yearly average exposure levels of ambient air pollutants at home address-level [particulate matter with diameters of ≤ 2.5 µm (PM2.5), and ≤ 10.0 µm (PM10), nitrogen dioxide (NO2), and elemental carbon (EC)]. We used linear regression analysis to study the associations between Z-score for ambient air pollutants concentrations (PM2.5, PM10, NO2, and EC) and Z-score for individual corneal nerve measures (corneal nerve bifurcation density, corneal nerve density, corneal nerve length, and fractal dimension). RESULTS: After adjustment for potential confounders (age, sex, level of education, glucose metabolism status, corneal confocal microscopy lag time, inclusion year of participants, smoking status, and alcohol consumption), higher Z-scores for PM2.5 and PM10 were associated with lower Z-scores for corneal nerve bifurcation density, nerve density, nerve length, and nerve fractal dimension [stß (95% CI): PM2.5 -0.10 (-0.14; -0.05), -0.04 (-0.09; 0.01), -0.11 (-0.16; -0.06), -0.20 (-0.24; -0.15); and PM10 -0.08 (-0.13; -0.03), -0.04 (-0.09; 0.01), -0.08 (-0.13; -0.04), -0.17 (-0.21; -0.12)], respectively. No associations were found between NO2 and EC and corneal nerve measures. CONCLUSIONS: Our population-based study demonstrated that exposure to higher levels of PM2.5 and PM10 are associated with higher levels of corneal neurodegeneration, estimated from lower corneal nerve measures. Our results suggest that air pollution may be a determinant for neurodegeneration assessed in the cornea and may impact the ocular surface health as well.

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Many researchers have studied the role of air pollutants on cognitive function, changes in brain structure, and occurrence of dementia. Due to the wide range of studies and often contradictory results, the present systematic review was conducted to try and clarify the relationship between air pollutants and dementia. To identify studies for this review, a systematic search was conducted in Scopus, PubMed, and Web of Science databases (without historical restrictions) until May 22, 2023. The PECO statement was created to clarify the research question, and articles that did not meet the criteria of this statement were excluded. In this review, animal studies, laboratory studies, books, review articles, conference papers and letters to the editors were avoided. Also, studies focused on the effect of air pollutants on cellular and biochemical changes (without investigating dementia) were also excluded. A quality assessment was done according to the type of design of each article, using the checklist developed by the Joanna Briggs Institute (JBI). Finally, selected studies were reviewed and discussed in terms of Alzheimer's dementia and non-Alzheimer's dementia. We identified 14,924 articles through a systematic search in databases, and after comprehensive reviews, 53 articles were found to be eligible for inclusion in the current systematic review. The results showed that chronic exposure to higher levels of air pollutants was associated with adverse effects on cognitive abilities and the presence of dementia. Studies strongly supported the negative effects of PM2.5 and then NO2 on the brain and the development of neurodegenerative disorders in old age. Because the onset of brain structural changes due to dementia begins decades before the onset of disease symptoms, and that exposure to air pollution is considered a modifiable risk factor, taking preventive measures to reduce air pollution and introducing behavioral interventions to reduce people's exposure to pollutants is advisable.

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Published studies on outdoor air pollution and tuberculosis risk have shown heterogeneous results. Discrepancies in prior studies may be partially explained by the limited geographic scope, diverse exposure times, and heterogeneous statistical methods. Thus, we conducted a multi-province, multi-city time-series study to comprehensively investigate this issue. We selected 67 districts or counties from all geographic regions of China as study sites. We extracted data on newly diagnosed pulmonary tuberculosis (PTB) cases, outdoor air pollutant concentrations, and meteorological factors in 67 sites from January 1, 2014 to December 31, 2019. We utilized a generalized additive model to evaluate the relationship between ambient air pollutants and PTB risk. Between 2014 and 2019, there were 172,160 newly diagnosed PTB cases reported in 67 sites. With every 10-µg/m3 increase in SO2, NO2, PM10, PM2.5, and 1-mg/m3 in CO, the PTB risk increased by 1.97% [lag 0 week, 95% confidence interval (CI): 1.26, 2.68], 1.30% (lag 0 week, 95% CI: 0.43, 2.19), 0.55% (lag 8 weeks, 95% CI: 0.24, 0.85), 0.59% (lag 10 weeks, 95% CI: 0.16, 1.03), and 5.80% (lag 15 weeks, 95% CI: 2.96, 8.72), respectively. Our results indicated that ambient air pollutants were positively correlated with PTB risk, suggesting that decreasing outdoor air pollutant concentrations may help to reduce the burden of tuberculosis in countries with a high burden of tuberculosis and air pollution.

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INTRODUCTION: While ambient formaldehyde (HCHO) concentrations are increasing worldwide, there was limited research on its health effects. OBJECTIVES: To assess the association of long-term exposure to ambient HCHO with the risk of respiratory (RESP) mortality and the associated mortality burden in China. METHODS: Annual and seasonal RESP death and tropospheric HCHO vertical columns data were collected in 466 counties/districts across China during 2013-2016. A difference-in-differences approach combined with a generalized linear mixed-effects regression model was employed to assess the exposure-response association between long-term ambient HCHO exposure and RESP mortality risk. Additionally, we computed the attributable fraction (AF) to gauge the proportion of RESP mortality attributable to HCHO exposure. RESULTS: This analysis encompassed 560,929 RESP deaths. The annual mean ambient HCHO concentration across selected counties/districts was 8.02×1015 ± 2.22×1015 molec.cm-2 during 2013-2016. Each 1.00×1015 molec.cm-2 increase in ambient HCHO was associated with a 1.61 % increase [excess risk (ER), 95 % confidence interval (CI): 1.20 %, 2.03 %] in the RESP mortality risk. The AF of RESP mortality attributable to HCHO was 12.16 % (95 %CI:9.33 %, 14.88 %), resulting in an annual average of 125,422 (95 %CI:96,404, 153,410) attributable deaths in China. Stratified analyses suggested stronger associations in individuals aged ≥65 years old (ER=1.87 %, 95 %CI:1.43 %, 2.32 %), in cold seasons (ER=1.00 %, 95 %CI:0.56 %, 1.44 %), in urban areas (ER=1.65 %, 95 %CI:1.15 %, 2.16 %), and in chronic obstructive pulmonary disease patients (ER=1.95 %, 95 %CI:1.42 %, 2.48 %). CONCLUSIONS: This study suggested that long-term HCHO exposure may significantly increase the risk of RESP mortality, leading to a substantial mortality burden. Targeted measures should be implemented to control ambient HCHO pollution promptly.

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INTRODUCTION: Air pollution is a major health risk factor. Ports might be an understudied source of air pollution. METHODS: We conducted a spatial health impact assessment (HIA) of port-sourced air pollution for Barcelona for 2017 at the neighbourhood level. Total NO2 and PM10 and port-sourced NO2, PM10 and PM2.5 concentrations were available through the ADMS-Urban model. Population data, mortality and morbidity data, and risk estimates were obtained. We followed standard HIA methodologies and calculated relative risks and impact fractions for 1.35 million adults living in 73 neighbourhoods. RESULTS: The city-wide mean total NO2 and PM10 concentrations were 37.88 µg/m3 (range: 19.61-52.17 µg/m3) and 21.68 µg/m3 (range: 17.33-26.69 µg/m3), respectively, of which 7% (range: 2-36%) and 1% (range: 0-7%) were port-sourced, respectively. The mean port-sourced PM2.5 concentration was 0.19 µg/m3 (range: 0.06-1.38 µg/m3). We estimated that 1,123 (PI: 0-3,060) and 1,230 (95% CI: 0-2,566) premature deaths were attributable to total NO2 and PM10, respectively, of which 8.1% (91; PI: 0-264) and 1.1% (13; 95% CI 0-29) were attributable to port-sourced NO2 and PM10, respectively. 20 (95% CI: 15-26) premature deaths were attributable to port-sourced PM2.5. Additionally, a considerable morbidity burden and losses in life expectancy were attributable to port-sourced air pollution. Neighbourhoods closest to the port in the south-east were most adversely affected, gradually decreasing towards the north-west. CONCLUSIONS: The port is an understudied air pollution source in Barcelona with strong health impacts. Cities need local insight into health risk factors, their sources, attributable burdens and distributions for defining targeted policies.

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