An investigation into the impact of variations of ambient air pollution and meteorological factors on lung cancer mortality in Yangtze River Delta

Ambient air pollution as a time-varying covariate in the survival probability of childhood cancer patients in the upper Northern Thailand

The objective of this study is to determine the possible association between exposure to air pollution and the risk of death from cancer during childhood in upper northern Thailand. Data were collected on children aged 0-15 years old diagnosed with cancer between January 2003 and December 2018 from the Chiang Mai Cancer Registry. Survival rates were determined by using Kaplan-Meier curves. Cox proportional hazard models were used to investigate associations of potential risk factors with the time-varying air pollution level on the risk of death. Of the 540 children with hematologic cancer, 199 died from any cause (overall mortality rate = 5.3 per 100 Person-Years of Follow-Up (PYFU); 95%CI = 4.6-6.0). Those aged less than one year old (adjusted hazard ratio [aHR] = 2.07; 95%CI = 1.25-3.45) or ten years old or more (aHR = 1.41; 95%CI = 1.04-1.91) at the time of diagnosis had a higher risk of death than those aged one to ten years old. Those diagnosed between 2003 and 2013 had an increased risk of death (aHR = 1.65; 95%CI = 1.13-2.42). Of the 499 children with solid tumors, 214 died from any cause (5.9 per 100 PYFU; 95%CI = 5.1-6.7). Only the cancer stage remained in the final model, with the metastatic cancer stage (HR = 2.26; 95%CI = 1.60-3.21) and the regional cancer stage (HR = 1.53; 95%CI = 1.07-2.19) both associated with an increased risk of death. No association was found between air pollution exposure and all-cause mortality for either type of cancer. A larger-scale analytical study might uncover such relationships.

Facile synthesis of multi-layer Co(OH)2/CeO2-g-C3N4 ternary synergistic heterostructure for efficient photocatalytic oxidation of NO under visible light

In this work, we report a one-step synthesis of ternary Z-scheme Co(OH)2/CeO2-g-C3N4 (CoCe-CN) heterostructure via hydrothermal method. Owing to the modification of Co(OH)2 and CeO2, the existence of Co(OH)2 as an electron acceptor-donor center between CeO2 and g-C3N4 accelerates the electron transfer and provides extra OH- reaction pathway for photocatalytic oxidation of NO. As a result, 50CoCe-CN (Co and Ce accounting for 25% mass ratio separately) achieved a 53.5% conversion efficiency of NO at 600 ppb concentration, which is 1.82 times that of g-C3N4 under visible light. The results of the DFT analysis and element distribution of cobalt and ceria provide convincing evidence supporting the existence of a novel multi-layer structure in the CoCe-CN photocatalyst. This structure involves the loading of CeO2 and Co(OH)2 on the g-C3N4 surface, and Co(OH)2 as a co-catalyst introduced between CeO2 and g-C3N4 realizes the synergy between CeO2 and Co(OH)2 which further improve the photocatalytic properties. The higher photocatalytic efficiencies observed in the CoCe-CN photocatalysts compared to those containing only cobalt (Co-CN) or ceria (Ce-CN) provide further evidence of the synergistic effect of these two elements. This work demonstrates a more efficient and effective ternary photocatalytic system, with greater practical potential for photocatalytic oxidation of NO.

Vaping, Environmental Toxicants Exposure, and Lung Cancer Risk

Lung cancer (LC) is the second-most prevalent tumor worldwide. According to the most recent GLOBOCAN data, over 2.2 million LC cases were reported in 2020, with an estimated new death incident of 1,796,144 lung cancer cases. Genetic, lifestyle, and environmental exposure play an important role as risk factors for LC. E-cigarette, or vaping, products (EVPs) use has been dramatically increasing world-wide. There is growing concern that EVPs consumption may increase the risk of LC because EVPs contain several proven carcinogenic compounds. However, the relationship between EVPs and LC is not well established. E-cigarette contains nicotine derivatives (e.g., nitrosnornicotine, nitrosamine ketone), heavy metals (including organometal compounds), polycyclic aromatic hydrocarbons, and flavorings (aldehydes and complex organics). Several environmental toxicants have been proven to contribute to LC. Proven and plausible environmental carcinogens could be physical (ionizing and non-ionizing radiation), chemicals (such as asbestos, formaldehyde, and dioxins), and heavy metals (such as cobalt, arsenic, cadmium, chromium, and nickel). Air pollution, especially particulate matter (PM) emitted from vehicles and industrial exhausts, is linked with LC. Although extensive environmental exposure prevention policies and smoking reduction strategies have been adopted globally, the dangers remain. Combined, both EVPs and toxic environmental exposures may demonstrate significant synergistic oncogenicity. This review aims to analyze the current publications on the importance of the relationship between EVPs consumption and environmental toxicants in the pathogenesis of LC.

Effect of high-level PM2.5 on survival in lung cancer: a multicenter cohort study from Hebei Province, China

Globally, air pollution is the fourth leading risk factor for death, while lung cancer (LC) is the leading cause of cancer-related death. The aim of this study was to explore the prognostic factors of LC and the influence of high fine particulate matter (PM_2.5) on LC survival. Data on LC patients were collected from 133 hospitals across 11 cities in Hebei Province from 2010 to 2015, and survival status was followed up until 2019. The personal PM_2.5 exposure concentration (μg/m³) was matched according to the patient's registered address, calculated from a 5-year average for every patient, and stratified into quartiles. The Kaplan-Meier method was used to estimate overall survival (OS), and Cox's proportional hazard regression model was used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). The 1-, 3-, and 5-year OS rates of the 6429 patients were 62.9%, 33.2%, and 15.2%, respectively. Advanced age (75 years or older: HR = 2.34, 95% CI: 1.25-4.38), subsite at overlapping (HR = 4.35, 95% CI: 1.70-11.1), poor/undifferentiated differentiation (HR = 1.71, 95% CI: 1.13-2.58), and advanced stages (stage III: HR = 2.53, 95% CI: 1.60-4.00; stage IV: HR = 4.00, 95% CI: 2.63-6.09) were risk factors for survival, while receiving surgical treatment was a protective factor (HR = 0.60, 95% CI: 0.44-0.83). Patients exposed to light pollution had the lowest risk of death with a 26-month median survival time. The risk of death in LC patients was greatest at PM_2.5 concentrations of 98.7-108.9 μg/m³, especially for patients at advanced stage (HR = 1.43, 95% CI: 1.29-1.60). Our study indicates that the survival of LC is severely affected by relatively high levels of PM_2.5 pollution, especially in those with advanced-stage cancer.

Short-term association of air pollution with lung cancer mortality in Osaka, Japan

Long-term air pollution exposure has been linked to increased lung cancer mortality. However, little is known about whether day-to-day fluctuations in air pollution levels are in relation to lung cancer mortality, particularly in low-exposure settings. This study aimed to evaluate the short-term associations between air pollution and lung cancer mortality. Daily data on lung cancer mortality, fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and weather conditions were collected from Osaka Prefecture, Japan, from 2010 to 2014. Generalized linear models were combined with quasi-Poisson regression were applied to evaluate the associations between each air pollutant and lung cancer mortality after adjusting for potential confounders. Mean (standard deviation) concentrations of PM_2.5, NO₂, SO₂, and CO were 16.7 (8.6) μg/m³, 36.8 (14.2) μg/m³, 11.1 (4.0) μg/m³, and 0.51 (0.16) mg/m³, respectively. Interquartile range increases in concentrations of PM_2.5, NO₂, SO₂, and CO (2-d moving average) were associated with 2.65% (95% confidence intervals [CIs]: 0.96%-4.37%), 4.28% (95% CIs: 2.24%-6.36%), 3.35% (95% CIs: 1.03%-5.73%), and 4.60% (95% CIs: 2.19%-7.05%) increased risk of lung cancer mortality, respectively. Stratified analyses showed that the associations were strongest in the older population and men. Exposure‒response curves showed a continuously increasing mortality risk from lung cancer with elevation of air pollution levels, without discernible thresholds. In summary, we found evidence of increased lung cancer mortality in relation to short-term elevations in ambient air pollution. These findings may merit further research to better understand this issue.

Will information interventions affect public preferences and willingness to pay for air quality improvement? An empirical study based on deliberative choice experiment

Environmental information is a prerequisite for public participation in air quality improvement, and the choice of such participation behavior is influenced by the intervention of environmental information. Nonetheless, there has been insufficient analysis of how information interventions affect public preferences and willingness to pay for air quality improvement. The combination of deliberative and choice experiment is used to explore the importance of information interventions for public participation in air quality improvement, and the changes in public preferences and willingness to pay for air quality improvement before and after information interventions are compared to analyze the impact of information interventions on evaluation results of air quality value. The results suggest that information interventions do alter the preferences and willingness of the public to pay for air quality improvement, significantly increasing the choice certainty of respondents and decreasing the protest response. In addition, women and high-income groups showed a stronger willingness to improve air quality after the information interventions, with 35.15 CNY, 44.07 CNY and 46.75 CNY increases in willingness to pay for improved urban green coverage rate, fewer haze days and reduced morbidity. The combination of deliberative information interventions and choice experiment will help improve the effectiveness of air quality value evaluation, stimulate public environmental awareness and willingness to participate, and the results will aid government environmental management.

The influence of meteorological factors and total malignant tumor health risk in Wuhu city in the context of climate change

With the increasing severity of the malignant tumors situation worldwide, the impacts of climate on them are receiving increasing attention. In this study, for the first time, all-malignant tumors were used as the dependent variable and absolute humidity (AH) was innovatively introduced into the independent variable to investigate the relationship between all-malignant tumors and meteorological factors. A total of 42,188 cases of malignant tumor deaths and meteorological factors in Wuhu City were collected over a 7-year (2014-2020) period. The analysis method combines distributed lagged nonlinear modeling (DLNM) as well as generalized additive modeling (GAM), with prior pre-analysis using structural equation modeling (SEM). The results showed that AH, temperature mean (T mean) and diurnal temperature range (DTR) all increased the malignant tumors mortality risk. Exposure to low and exceedingly low AH increases the malignant tumors mortality risk with maximum RR values of 1.008 (95% CI: 1.001, 1.015, lag 3) and 1.016 (95% CI: 1.001, 1.032, lag 1), respectively. In addition, low and exceedingly low T mean exposures also increased the risk of malignant tumors mortality, the maximum RR was 1.020 (95% CI: 1.006, 1.034) for low T mean and 1.035 (95% CI: 1.014, 1.058) for exceedingly low T mean. As for DTR, all four levels (exceedingly low, low, high, exceedingly high, from low to high) of exposure increased the risk of death from malignant tumors, from exceedingly low to exceedingly high maximum RR values of 1.018 (95% CI: 1.004, 1.032), 1.011 (95% CI: 1.005, 1.017), 1.006 (95% CI: 1.001, 1.012) and 1.019 (95% CI: 1.007, 1.031), respectively. The results of the stratified analysis suggested that female appear to be more sensitive to humidity, while male require additional attention to reduce exposure to high level of DTR.

Exploring Health Effects under Specific Causes of Mortality Based on 90 Definitions of PM2.5 and Cold Spell Combined Exposure in Shanghai, China

In this study, a total of 90 definitions were set up based on six air pollution definitions, five cold spell definitions, and three combined exposure scenarios. The relative risks (RRs) on all-cause, circulatory, and respiratory mortality were explored by a model combining a distributed linear lag model with quasi-Poisson regression. The definition in which daily PM_2.5 increases more than 75 μg/m³ for at least 2 days and the average temperature falls below the 10th percentile for at least 2 days produced the best model fit performance in all-cause mortality. The high peaks of the health effect were generally observed around the lag days 6-9. The cumulative relative risks (CRRs) were more significant in the simultaneous-exposure scenario and higher in respiratory mortality, where the highest CRR (12.15, 3.69-40.03) was observed in definition P1T5, in which daily PM_2.5 increases more than 75 μg/m³, and the average temperature falls below the 2.5th percentile for at least two days. For relative risk due to interaction (RERI), we found positive additive interactions (RERI > 0) between PM_2.5 pollution and cold spell, especially in respiratory mortality. Clarifying the definition of combined events can help policymakers to capture health risks and construct more effective risk warning systems.

Histological types of lung cancer attributable to fine particulate, smoking, and genetic susceptibility

BACKGROUND

Fine particulate matter (PM_2.5), smoking, and genetic factors are associated with lung cancer. However, the relationship between PM_2.5, smoking and subtypes of lung cancer remains unclear. Moreover, it is unclear whether genetic risk modifies the impact of PM_2.5 and smoking on incident lung cancer.

METHODS

A total of 298,069 participants from the UK Biobank study without lung cancer at baseline were included in this study. Hazard ratios (HRs) with 95 % confidence intervals (CIs) were estimated using multivariable Cox proportional models for the association of lung cancer and its subtypes with PM_2.5, smoking, and genetic risk. Potential gene-smoking or gene-PM_2.5 interactions were also estimated. We further estimated population attributable fractions for incident lung cancer.

RESULTS

During 10.4 years of follow-up, 1683 incident lung cancer cases were identified. Our analysis found that genetic variants, smoking, and PM_2.5 were significantly associated with incident lung cancer. For different histological types of lung cancer, the HRs for squamous cell lung carcinoma associated with PM_2.5 (per 5 μg/m³ increment) and current smoking were 2.76 (95 % CI: 1.72, 4.42, p < 0.001) and 48.64 (95 % CI: 27.96, 84.61, p < 0.001), while the HRs for lung adenocarcinoma were 1.59 (95 % CI: 1.13, 2.23, p < 0.001) and 9.89 (95 % CI: 7.91, 12.36, p < 0.001), respectively. We further found that participants with high levels of PM_2.5 pollution and high genetic risk had the highest risk of incident lung cancer (HR = 1.81, 95 % CI: 1.39, 2.35, p < 0.001), while the interaction between PM_2.5 and genetic risk was not statistically significant. We observed that the population attributable fractions of lung cancer attributable to current smoking and high PM_2.5 exposure were estimated to be 67.45 % and 17.59 %.

CONCLUSION

Genetic susceptibility, smoking, and PM_2.5 are important risk factors for lung cancer. Both smoking and PM_2.5 are more closely associated with an elevated risk of squamous cell lung cancer.

A novel mathematical model for estimating the relative risk of mortality attributable to the combined effect of ambient fine particulate matter (PM2.5) and cold ambient temperature

Exposures to ambient fine particulate matter (PM_2.5) and cold ambient temperatures have been identified as important risk factors in contributing towards the global mortality from chronic obstructive pulmonary disease (COPD). Despite China currently being the country with the largest population in the world, previous relative risk (RR) models have considered little or no information from the ambient air pollution related cohort studies in the country. This likely provides a less accurate picture of the trend in air pollution attributable mortality in the country over time. A novel relative risk model called pollutant-temperature exposure (PTE) model is proposed to estimate the RR attributable to the combined effect of air pollution and ambient temperature in a population. In this paper, the pollutant concentration-response curve was extrapolated from the cohort studies in China, whereas the temperature response curve was extracted from a study in Yangtze River Delta (YRD) region. The performance of the PTE model was compared with the integrated exposure-response (IER) model using the data of YRD region, which revealed that the estimated relative risks of the PTE model were noticeably higher than the IER model during the winter season. Furthermore, the predictive ability of the PTE model was validated using actual data of Ningbo city, which showed that the estimated RR using the PTE model with 1-month moving average data showed a good result with the trend of actual COPD mortality, indicated by a lower root mean square error (RMSE = 0.956). By considering the combined effect of ambient air pollutant and ambient temperature, the PTE model is expected to provide more accurate relative risk estimates for the regions with high levels of ambient PM_2.5 and seasonal variation of ambient temperature.

In vivo tracking of toxic diesel particulate matter in mice using radiolabeling and nuclear imaging

Exposure to diesel particulate matter (DPM) is associated with several adverse health effects, including severe respiratory diseases. Quantitative analysis of DPM in vivo can provide important information on the behavior of harmful chemicals, as well as their toxicological impacts in living subjects. This study presents whole-body images and tissue distributions of DPM in animal models, using molecular imaging and radiolabeling techniques. The self-assembly of the ⁸⁹Zr-labeled pyrene analog with a suspension of DPM efficiently produced ⁸⁹Zr-incorporated DPM (⁸⁹Zr-DPM). Positron emission tomography images were obtained for mice exposed to ⁸⁹Zr-DPM via three administration routes: intratracheal, oral, and intravenous injection. DPM was largely distributed in the lungs and only slowly cleared after 7 days in mice exposed via the intratracheal route. In addition, a portion of ⁸⁹Zr-DPM was translocated to other organs, such as the heart, spleen, and liver. Uptake values in these organs were also noticeable following exposure via the intravenous route. In contrast, most of the orally administered DPM was excreted quickly within a day. These results suggest that continuous inhalation exposure to DPM causes serious lung damage and may cause toxic effects in the extrapulmonary organs.

Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review

This review paper covers an overview of air pollution-related disease burden in China and a literature review on the previous studies which have recently adopted a mathematical modeling approach to demonstrate the relative risk (RR) of air pollution-related disease burden. The associations between air pollution and disease burden have been explored in the previous studies. Therefore, it is necessary to quantify the impact of long-term exposure to ambient air pollution by using a suitable mathematical model. The most common way of estimating the health risk attributable to air pollution exposure in a population is by employing a concentration-response function, which is often based on the estimation of a RR model. As most of the regions in China are experiencing rapid urbanization and industrialization, the resulting high ambient air pollution is influencing more residents, which also increases the disease burden in the population. The existing RR models, including the integrated exposure-response (IER) model and the global exposure mortality model (GEMM), are critically reviewed to provide an understanding of the current status of mathematical modeling in the air pollution-related health risk assessment. The performances of different RR models in the mortality estimation of disease are also studied and compared in this paper. Furthermore, the limitations of the existing RR models are pointed out and discussed. Consequently, there is a need to develop a more suitable RR model to accurately estimate the disease burden attributable to air pollution in China, which contributes to one of the key steps in the health risk assessment. By using an updated RR model in the health risk assessment, the estimated mortality risk due to the impacts of environment such as air pollution and seasonal temperature variation could provide a more realistic and reliable information regarding the mortality data of the region, which would help the regional and national policymakers for intensifying their efforts on the improvement of air quality and the management of air pollution-related disease burden.

Spatial patterns and temporal variations of pollutants at 56 air quality monitoring stations in the state of São Paulo, Brazil

This study applied two data mining tasks: clustering and association rules to a dataset of pollutants in the state of São Paulo. The clustering task was applied to temporal patterns and geospatial distributions of pollutants, and the association rules were used to identify prevailing meteorological conditions when there were high concentrations of pollutants from 2017 to 2019. The results indicated good adequacy of the cluster, indicating different pollution levels per group, with a silhouette coefficient from 0.26 to 0.72. In the spatial evaluation, the groups severely polluted were located in the metropolitan region, on the coast and, some inland cities, by industrial, vehicular, burning, agriculture, and other emissions. The cluster identified a strong presence of O₃ and PM_2.5 in 65% and 72% of the monitored stations in several areas of the state. As for the distance between the sources of pollution, the groups of PM₁₀ and NO₂ were geographically distant, while PM_2.5, CO, SO₂, and O₃ were closer, suggesting a spatial relationship of exposure. Seasonality was similar between groups, with significantly higher concentrations in winter, except for O₃, for which higher concentrations occurred in summer. Meteorological conditions contributed to critical episodes of pollution (support and confidence greater than 80%), with low temperature and humidity, low rainfall, and milder wind associated with increased pollutants. In conclusion, investigating spatial representativeness allows revealing spatial and temporal patterns of pollutants and unfavorable meteorological conditions to diffusion. Thus, ideal and effective measures can be taken to avoid critical periods of exposure based on the behavior of pollutants in different regions and related climate changes.

PM2.5 exposure and cervical cancer survival in Liaoning Province, northeastern China

Particulate matter with a diameter of 2.5 μm or less (PM_2.5) has frequently been reported to be associated with an increased incidence of cancer, but few studies have explored the association between PM_2.5 exposure and cancer survival. We retrospectively analyzed the association between PM_2.5 exposure and the overall survival (OS) of cervical cancer patients residing in 14 urban areas of Liaoning Province, northeastern China, during January 2014-October 2021. Patients from urban areas who completed the recommended treatments with complete follow-up information were included. The PM_2.5 monitoring data of each urban area of Liaoning Province were retrieved, and individual exposure to PM_2.5 after diagnosis was calculated as the average daily concentration in the city of residence from the date of discharge to the date of death or the last follow-up. Log-rank tests and Cox regression were performed to examine the relationship between PM_2.5 exposure and cervical cancer survival. A total of 1753 cervical cancer patients were finally included, among whom 804 (45.9%) were from Shenyang City, the capital of Liaoning Province. The median average daily concentration of PM_2.5 to which the patients were exposed was 45.0 (interquartile range 38.2-50.0) μg/m³. Both log-rank tests (grouped by quartiles, p < 0.001) and Cox regression (continuous, HR = 1.06, 95% CI 1.04-1.08) indicated that PM_2.5 was significantly associated with shorter OS. Sensitivity analysis also confirmed the robustness of our findings. From the subgroup analysis, only the OS of stage II and stage III patients was associated with PM exposure. Our findings provide the insight that PM_2.5 exposure might be associated with shorter OS of cervical cancer patients.

Correlation between lung cancer markers and air pollutants in western China population

The relationship between serum lung cancer markers and the air pollution remains unclear. To further reveal the correlation between air pollutants and lung cancer, a retrospective analysis of 446,032 asymptomatic healthy people and symptomatic healthy people from the Health Management Center of the First Affiliated Hospital of Chongqing Medical University from 2014 to 2019 was performed. The distribution characteristics of serum lung cancer markers, cancer embryo antigens (CEA), cytokeratin 19 fragment (CYFRA211), squamous cell carcinoma antigen (SCC), and nerve-specific enolase (NSE) was analyzed in these population. Two independent sample man-Whitney U test was used to analyze the correlation of lung cancer markers and age, and a Chi-square test was used to analyze the relationship between lung cancer markers and gender. The daily change trend was profiled for six main air quality indicators PM₁₀, PM_2.5, SO₂, NO₂, CO, O₃ during the same period. The correlation between lung markers and air pollutants was investigated by Spearman and multiple linear regression. The results showed that CYFRA211 had the highest excess rate in the screening population. There were differences in the number of cases with concentrated expression of lung cancer markers in the different age groups. Among them, the people with NSE exceeding the standard were the youngest, and most of them were 40-55 years old. Besides SCC, the expression levels of other markers increased with age, and the expression levels of the four markers in males were significantly higher than those in females. Although the levels of PM₁₀ and PM_2.5 exceeded the WHO standard (World Health Organization. 2011), they were not correlated with lung cancer markers. Multiple comparisons showed that the air pollutants SO₂ and CYFRA211, as well as NO₂ and NSE were closely related, but there was no significant linear relationship between CEA, SCC, and air pollutants. In conclusion, among the four lung cancer markers, CYFRA211 had the highest abnormal excess rate in total screening population, and the expression levels of these markers varied by gender and age, with males showing significantly higher expression levels than females, and they increased significantly with age except for SCC. The differential expression of these lung cancer markers may provide more strategies for lung cancer screening in the corresponding population. Lung cancer markers, CYFRA211 and NSE, can be used as sensitive biomarkers for exposure to certain air pollutants and provide references for the prevention and management of air pollution.

Inhalation Bioaccessibility and Risk Assessment of Metals in PM2.5 Based on a Multiple-Path Particle Dosimetry Model in the Smelting District of Northeast China

PM2.5 can deposit and partially dissolve in the pulmonary region. In order to be consistent with the reality of the pulmonary region and avoid overestimating the inhalation human health risk, the bioaccessibility of PM2.5 heavy metals and the deposition fraction (DF) urgently needs to be considered. This paper simulates the bioaccessibility of PM2.5 heavy metals in acidic intracellular and neutral extracellular deposition environments by simulating lung fluid. The multipath particle dosimetry model was used to simulate DF of PM2.5. According to the exposure assessment method of the U.S. Environmental Protection Agency, the inhalation exposure dose threshold was calculated, and the human health risk with different inhalation exposure doses was compared. The bioaccessibility of heavy metals is 12.1−36.2%. The total DF of PM2.5 in adults was higher than that in children, and children were higher than adults in the pulmonary region, and gradually decreased with age. The inhalation exposure dose threshold is 0.04−14.2 mg·kg−1·day−1 for the non-carcinogenic exposure dose and 0.007−0.043 mg·kg−1·day−1 for the carcinogenic exposure dose. Cd and Pb in PM2.5 in the study area have a non-carcinogenic risk to human health (hazard index < 1), and Cd has no or a potential carcinogenic risk to human health. A revised inhalation health risk assessment may avoid overestimation.

The effects of air pollution on the lung cancer mortality in rural areas of eastern China: a multi-region study

Recently, the burden of lung cancer (LC) has attracted global attention. Meanwhile, LC has become the leading cause of death in China. Many studies found a strong link between air pollutants and the risk of LC mortality in some large cities, but the results have been inconsistent, and most studies have only focused on the daily effects of six pollutants in large cities, ignoring their potential cumulative effects. This study was to investigate the weekly effects of six air pollutants (CO, NO₂, O₃, PM_2.5, PM₁₀, and SO₂) on LC mortality in rural areas of eastern China and to further clarify which population groups were susceptible to air pollution and seasonal trends. First, a generalized additive model was combined with a distributed lag nonlinear model to evaluate the individual impact of air pollution on LC deaths in each area. The random-effect model was then used to pool the associations between air pollutants and LC mortality risk in ten counties or districts. The results showed that six air pollutants had a statistically significant effect on the risk of LC mortality at different lag weeks. The effects of NO₂, PM₁₀, and CO on weekly LC mortality were strongest at a cumulative lag of 1, 0, and 1 week, respectively, the maximum cumulative risk ratio (RR) of 1.37 (95%CI: 1.23 to 1.52), 1.30 (95%CI: 1.15 to 1.46), and 1.30 (95%CI: 1.17 to 1.43), with interquartile concentrations increasing. In summary, air pollution was an important factor in LC mortality, and the effect was stronger on males, the elderly, and during cold season. It was suggested that relevant departments should formulate air pollution management measures for the elderly, males, and in different seasons in rural areas and reduce the burden of lung cancer caused by air pollution.

CTBP1-AS2 promoted non-small cell lung cancer progression via sponging the miR-623/MMP3 axis

Mounting evidence indicates that lncRNAs (long noncoding RNAs) are involved in the initiation and development of tumors, including non-small cell lung cancer (NSCLC). However, the involvement of C-terminal binding protein-antisense RNA 2 (CTBP1-AS2) in NSCLC remains to be studied. RT-qPCR was carried out to detect CTBP1-AS2 and miR-623 expression in NSCLC cells and tissues. CCK-8 and flow cytometry were performed to measure cell proliferation and cell cycle progression. Luciferase reporter analysis was performed to study the potential target of CTBP1-AS2. We found that CTBP1-AS2 expression was upregulated in NSCLC cells (SPC-A1, A549, H23, and H1299) compared to 16HBE cells. We demonstrated that the CTBP1-AS2 level was higher in NSCLC specimens than in paired non-tumor specimens. Elevated expression of CTBP1-AS2 increased cell growth and induced cell cycle progression and epithelial-mesenchymal transition (EMT). We also found that ectopic expression of CTBP1-AS2 inhibited miR-623 expression. MMP3 was a direct target of miR-623, and luciferase reporter assays suggested that miR-623 overexpression suppressed the luciferase expression driven by the MMP3 wild-type reporter but not the mutant reporter. Overexpression of miR-623 suppressed MMP3 expression in A549 cells, and overexpression of CTBP1-AS2 increased MMP3 expression in A549 cells. Moreover, the miR-623 level was lower in NSCLC specimens than in paired non-tumor specimens, and CTBP1-AS2 expression was negatively correlated with miR-623 expression in NSCLC samples. Furthermore, overexpression of CTBP1-AS2 enhanced cell growth, cell cycle progression, and EMT progression by modulating MMP3 expression.

Impact of Residential Concentration of PM2.5 Analyzed as Time-Varying Covariate on the Survival Rate of Lung Cancer Patients: A 15-Year Hospital-Based Study in Upper Northern Thailand

Air pollutants, especially particulate matter (PM) ≤ 2.5 µm (PM2.5) and PM ≤ 10 µm (PM10), are a major concern in upper northern Thailand. Data from a retrospective cohort comprising 9820 lung cancer patients diagnosed from 2003 to 2018 were obtained from the Chiang Mai Cancer Registry, and used to evaluate mortality and survival rates. Cox proportional hazard models were used to identify the association between the risk of death and risk factors including gender, age, cancer stage, smoking history, alcohol-use history, calendar year of enrollment, and time-updated PM2.5, PM10, NO₂ and O₃ concentrations. The mortality rate was 68.2 per 100 persons per year of follow-up. In a multivariate analysis, gender, age, cancer stage, calendar year of enrollment, and time-varying residential concentration of PM2.5 were independently associated with the risk of death. The lower the annually averaged PM2.5 and PM10 concentrations, the higher the survival probability of the patient. As PM2.5 and PM10 were factors associated with a higher risk of death, lung cancer patients who are inhabitant in the area should reduce their exposure to high concentrations of PM2.5 and PM10 to increase survival rates.

Does air pollution contribute to urban-rural disparity in male lung cancer diseases in China?

It remains unknown whether exposure to ambient air pollution can be a mediator linking socioeconomic indicator to health outcome. The present study aims to examine the mediation effect of PM2.5 air pollution on the association between urban-rural division and the incidence (mortality) rate of male lung cancer. We performed a nationwide analysis in 353 counties (districts) of China between 2006 and 2015. A structural equation model was developed to determine the mediation effect of exposure to PM2.5. We also tested whether the findings of the mediation effect of exposure to PM2.5 are sensitive to the controls of smoking factors and additional air pollutant, and PM2.5 exposures with different lag structures. According to the results, we found that exposure to PM2.5 significantly mediated the association between urban-rural division and the incidence rate of male lung cancer. Specifically, there were significant associations between urban-rural division, exposure to PM2.5, and the incidence rate of male lung cancer, with PM2.5 exposure accounting for 29.80% of total urban-rural difference in incidence rates of male lung cancer. A similar pattern of results was observed for the mortality rate of male lung cancer. That is, there was a significant mediation effect by PM2.5 on the association of the mortality rate with urban-rural division. The findings of exposure to PM2.5 as a mediator were robust in the three sensitivity analyses. In conclusion, urban-rural difference in exposures to PM2.5 may be a potential factor that contributes to urban-rural disparity in male lung cancer diseases in China. The findings inform that air pollution management and control may be effective measures to alleviate the great difference in male lung cancer diseases between urban and rural areas in China.

Can respondent uncertainty be ignored when exploring heterogeneity in public preferences for air pollution treatment policies? Comparative results from choice experiment analysis

Based on choice experiment (CE), evaluating the public's heterogeneous preferences and willingness to pay (WTP) for air pollution treatment policies can provide useful social views for the reasonable formulation of treatment schemes. However, the application of CE contains an implicit assumption that respondents understand their real preferences and can make choices with complete certainty. In reality, for a variety of reasons, not all respondents are absolutely certain about their responses, this assumption distinctly is hard to be consistent with reality. To explore the impact of respondent uncertainty on the public's WTP and heterogeneous preferences for air pollution treatment policies, this study introduces the critical point and exponential weighting methods to deal with this uncertainty in the context of CE and conducts comparative analysis based on the random parameters logit (RPL) and latent classes models (LCM). The results show that, ignoring uncertainty leads to distortions in the public's WTP and preference characteristics. In the RPL models, on average, the WTP for attributes is overstated by 32.10%. Our results also reveal that, whether to consider uncertainty does not affect the ranking of the implicit prices of these attributes. After incorporating uncertainty into the analysis, respondents were divided into two potential groups with different preferences, namely the environment-focused group (79.44%) and the price-focused group (20.56%), which is quite distinct from research results of ignoring the uncertainty. Contribution of this study is not only to provide theoretical insights for exploring the effects of uncertainty on public preferences based on CE, but also to provide valuable guidance for policy makers to formulate more accurate and effective treatment measures.

Analysis of Spatio-Temporal Heterogeneity and Socioeconomic driving Factors of PM2.5 in Beijing–Tianjin–Hebei and Its Surrounding Areas

Due to rapid urbanization and socio-economic development, fine particulate matter (PM2.5) pollution has drawn very wide concern, especially in the Beijing–Tianjin–Hebei region, as well as in its surrounding areas. Different socio-economic developments shape the unique characteristics of each city, which may contribute to the spatial heterogeneity of pollution levels. Based on ground fine particulate matter (PM2.5) monitoring data and socioeconomic panel data from 2015 to 2019, the Beijing–Tianjin–Hebei region, and its surrounding provinces, were selected as a case study area to explore the spatio-temporal heterogeneity of PM2.5 pollution, and the driving effect of socioeconomic factors on local air pollution. The spatio-temporal heterogeneity analysis showed that PM2.5 concentration in the study area expressed a downward trend from 2015 to 2019. Specifically, the concentration in Beijing–Tianjin–Hebei and Henan Province had decreased, but in Shanxi Province and Shandong Province, the concentration showed an inverted U-shaped and U-shaped variation trend, respectively. From the perspective of spatial distribution, PM2.5 concentrations in the study area had an obvious spatial positive correlation, with agglomeration characteristics of “high–high” and “low–low”. The high-value area was mainly distributed in the junction area of Henan, Shandong, and Hebei Provinces, which had been gradually moving to the southwest. The low values were mainly concentrated in the northern parts of Shanxi and Hebei Provinces, and the eastern part of Shandong Province. The results of the spatial lag model showed that Total Population (POP), Proportion of Urban Population (UP), Output of Second Industry (SI), and Roads Density (RD) had positive driving effects on PM2.5 concentration, which were opposite of the Gross Domestic Product (GDP). In addition, the spatial spillover effect of the PM2.5 concentrations in surrounding areas has a positive driving effect on local pollution levels. Although the PM2.5 levels in the study area have been decreasing, air pollution is still a serious problem. In the future, studies on the spatial and temporal heterogeneity of PM2.5 caused by unbalanced social development will help to better understand the interaction between urban development and environmental stress. These findings can contribute to the development of effective policies to mitigate and reduce PM2.5 pollutions from a socio-economic perspective.