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Background: We sought to explore the associations of outdoor light at night (LAN) and air pollution with the risk of cerebrovascular disease (CeVD)., Methods: We included a total of 28 302 participants enrolled in Ningbo, China from 2015 to 2018. Outdoor LAN and air pollution were assessed by Satellite-derived images and land-use regression models. CeVD cases were confirmed by medical records and death certificates and further subdivided into ischemic and hemorrhagic stroke. Cox proportional hazard models were used to estimate hazard ratios and 95% CIs., Results: A total of 1278 CeVD cases (including 777 ischemic and 133 hemorrhagic stroke cases) were identified during 127 877 person-years of follow-up. In the single-exposure models, the hazard ratios for CeVD were 1.17 (95% CI, 1.06-1.29) for outdoor LAN, 1.25 (1.12-1.39) for particulate matter with an aerodynamic diameter ≤2.5 µm, 1.14 (1.06-1.22) for particulate matter with aerodynamic diameter ≤10 μm, and 1.21 (1.06-1.38) for NO 2 in every interquartile range increase. The results were similar for ischemic stroke, whereas no association was observed for hemorrhagic stroke. In the multiple-exposure models, the associations of outdoor LAN and PM with CeVD persisted but not for ischemic stroke. Furthermore, no interaction was observed between outdoor LAN and air pollution., Conclusions: Levels of exposure to outdoor LAN and air pollution were positively associated with the risk of CeVD. Furthermore, the detrimental effects of outdoor LAN and air pollution might be mutually independent., Competing Interests: Disclosures None.

To investigate the association of long-term exposure to ambient air pollution with the risk of allergic rhinitis (AR), we performed a longitudinal analysis of 379,488 participants (47.4% women) free of AR at baseline in the UK Biobank. The annual average concentrations of PM 2.5 , PM coarse , PM 10 , NO 2 , and NO x were estimated by land use regression models. Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). A weighted polygenic risk score was constructed. During a median follow-up period of 12.5 years, 3095 AR cases were identified. We observed significant associations between the risk of AR and PM 2.5 (HR: 1.51, 95% CI: 1.27-1.79, per 5 μg/m 3 ), PM coarse (HR: 1.28, 95% CI: 1.06-1.55, per 5 μg/m 3 ), PM 10 (HR: 1.45, 95% CI: 1.20-1.74, per 10 μg/m 3 ), NO 2 (HR: 1.14, 95% CI: 1.09-1.19, per 10 μg/m 3 ), and NO x (HR: 1.10, 95% CI: 1.05-1.15, per 20 μg/m 3 ). Moreover, participants with high air pollution combined with high genetic risk showed the highest risk of AR, although no multiplicative or additive interaction was observed. In conclusion, long-term exposure to air pollutants was associated with an elevated risk of AR, particularly in high-genetic-risk populations, emphasizing the urgent need to improve air quality.

Background: Neurodegenerative disease has a great adverse impact on population's death and disability worldwide. However, the association of air pollution and residential greenness with neurodegenerative disease and their potential mechanisms still remain uncertain., Methods: We used data from a population-based prospective cohort in Ningbo, China. Exposure to PM 2.5 , PM 10 and NO 2 were assessed by land-use regression (LUR) models and residential greenness was estimated by Normalized Difference Vegetation Index (NDVI). Our primary outcomes were all neurodegenerative diseases, Parkinson's disease (PD) and Alzheimer's disease (AD). Cox proportional hazards regression models were used to examine the association of air pollution and residential greenness with risk of incident neurodegenerative disease. Furthermore, we also explored the potential mediation relationship and effect modification between greenness and air pollutants., Results: During the follow-up period, we identified a total of 617 incident neurodegenerative diseases, 301 PD and 182 AD. In single-exposure models, PM 2.5 was positively associated with all outcomes (e.g. AD hazard ratio (HR): 1.41, 95 % confidence interval (CI): 1.09-1.84, per interquartile range (IQR) increment), whereas residential greenness showed protective effects (e.g. neurodegenerative disease, HR: 0.82, 95%CI: 0.75-0.90, per IQR increment for NDVI in 1000 m buffer). NO 2 was positively associated with risk of neurodegenerative disease and PM 10 was associated with neurodegenerative disease and AD. In two-exposure models, after adjustment for PM 2.5 , the association for greenness generally attenuated towards null. Moreover, we identified the significant modification effect of greenness on PM2.5 on additive and multiplicative scales., Conclusion: In this prospective study, we found that exposure to higher residential greenness and lower concentrations of particulate matter were associated with lower risk of neurodegenerative disease, PD and AD. Residential greenness could modify the association of PM 2.5 with neurodegenerative disease., Competing Interests: Declaration of competing interest The authors declare that there are no known competing financial interests., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Physical function (PF), such as muscle strength, performing daily activities, has gradually declined with the increase of age, causing the occurrence of disability and diseases burden. Air pollution exposure and physical activity (PA) were both linked to PF. We aimed to explore the individual and joint effects of particulate matter <2.5 μm (PM 2.5 ) and PA on PF., Methods: A total of 4537 participants and 12,011 observations aged ≥45 years old from the China Health and Retirement Longitudinal Study (CHARLS) cohort from 2011 to 2015 were included into the study. PF was assessed by a combined score of four tests, including grip strength, walking speed, sense of balance, and chair standing tests. Air pollution exposure data was from The ChinaHighAirPollutants (CHAP) dataset. The annual PM 2.5 exposure for each individual was estimated based on county-level resident addresses. We estimated the volume of moderate-to-vigorous physical activity (MVPA) by quoting metabolic equivalent (MET). Multivariate linear model was conducted for baseline analysis, and linear mixed model with random participant intercepts was constructed for cohort longitudinal analysis., Results: PM 2.5 was negatively associated with PF, while PA was positively associated with PF in baseline analysis. In cohort longitudinal analysis, a 10 μg/m 3 increase in PM 2.5 was associated to a 0.025 point (95 % CI: -0.047, -0.003) decrease in PF score, and a 10-MET-h/week increase in PA was related to a 0.004 point (95 % CI: 0.001, 0.008) increase in PF score. The association between PM 2.5 and PF decreased by increased PA intensity, and PA reversed the detrimental effects between PM 2.5 and PF., Conclusion: PA attenuated the association of air pollution with PF at both high and low levels of air pollution, implying that PA may be an effective behavior to reduce the adverse effects of poor air quality on PF., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Walkability has been considered to be associated with metabolic and cardiovascular diseases, but the relationship between walkability and chronic obstructive pulmonary disease (COPD) remains unclear. Moreover, fine particulate matter (PM 2.5 ), possibly positively correlated to walkability, may lead to an increased risk of COPD. The separate and joint effects of PM 2.5 and walkability on risk of COPD were explored in our study., Methods: We used prospective data of 29,572 participants from the Yinzhou cohort in Ningbo, China. COPD cases were diagnosed based on the Yinzhou Health Information System (YHIS). Walkability was measured using walk score in relation to the built environment based on geographic information systems (GIS). Air pollution levels were assessed by fitting land use regression (LUR) models. Cox proportional hazards models were used to evaluate the relationships of PM 2.5 and walkability with COPD. Furthermore, we also examined additive and multiplicative interactions between walkability and PM 2.5 ., Results: Overall, a total of 29,572 participants were included in the final analysis and 722 COPD incident cases were identified during 134,846 person-years of follow-up. Compared with subjects with lower walkability, individuals with higher walkability had a decreased risk of COPD (HR = 0.88, 95 % CI: 0.82-0.95) for every IQR increase. By contrast, exposure to PM 2.5 (every IQR increase) was associated with an elevated risk of COPD (HR = 1.21, 95 % CI: 1.06-1.37). No interaction between PM 2.5 and walkability was observed., Conclusions: Living in a highly walkable neighborhood could decrease risk of COPD, whereas high levels of PM 2.5 were positively associated with COPD. In addition, the beneficial effects of walkability were not attenuated by exposure to PM 2.5 ., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Epidemiological studies have reported an association between traffic-related pollution with risk of metabolic syndrome (MetS). However, evidence from prospective studies on the association of walkability and nitrogen dioxide (NO 2 ) with MetS is still scarce. We, therefore, aimed to evaluate the association of long-term exposure to NO 2 and walkability with hazards of incident MetS., Methods: A total of 17,965 participants without MetS diagnosed within one year at baseline were included in our study from a population-based prospective cohort in Yinzhou District, Ningbo, Zhejiang Province, China. Participants were followed up by the regional Health Information System (HIS) until December 15, 2021. MetS was defined based on the criteria of Chinese Diabetes Society (CDS2004). We used walkscore tools, calculating with amenity categories and decay functions, and spatial-temporal land-use regression (LUR) models to estimate walkability and NO 2 concentrations. We used Cox proportional hazards regression models to examine the association of walkability and NO 2 with hazards of MetS incidence reporting with hazard ratios (HRs) and 95% confidence intervals (CIs)., Results: Overall, we followed up 77,303 person-years and identified 4040 incident cases of MetS in the entire cohort. Higher walkability was inversely associated with incident MetS (HR = 0.94, 95 % CI: 0.91-0.99), whereas NO 2 was positively associated with MetS incidence (HR = 1.07, 95 %CI: 1.00-1.15) per interquartile range increment in two-exposure models. Furthermore, we found a significant multiplicative interaction between walkability and NO 2 . Stronger associations were observed for NO 2 and incident MetS among men, smokers, drinkers and participants who aged < 60 years and had higher levels of income., Conclusion: In summary, we found living in areas with lower walkability and higher concentrations of NO 2 were associated with increased incidence of MetS. The beneficial effect of higher walkability may be attenuated by exposure to NO 2 ., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Emissions from mobile sources and stationary sources contribute to atmospheric pollution in China, and its components, which include ultrafine particles (UFPs), volatile organic compounds (VOCs), and other reactive gases, such as NH 3 and NO x , are the most harmful to human health. China has released various regulations and standards to address pollution from mobile and stationary sources. Thus, it is urgent to develop online monitoring technology for atmospheric pollution source emissions. This study provides an overview of the main progress in mobile and stationary source monitoring technology in China and describes the comprehensive application of some typical instruments in vital areas in recent years. These instruments have been applied to monitor emissions from motor vehicles, ships, airports, the chemical industry, and electric power generation. Not only has the level of atmospheric environment monitoring technology and equipment been improving, but relevant regulations and standards have also been constantly updated. Meanwhile, the developed instruments can provide scientific assistance for the successful implementation of regulations. According to the potential problem areas in atmospheric pollution in China, some research hotspots and future trends of atmospheric online monitoring technology are summarized. Furthermore, more advanced atmospheric online monitoring technology will contribute to a comprehensive understanding of atmospheric pollution and improve environmental monitoring capacity., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Greener residential surroundings are associated with beneficial health outcomes, whereas higher air pollution exposure is linked with elevated risks of chronic diseases. To date, limited studies have explored the interaction between residential greenness and air pollution on the risk of ischemic heart disease (IHD). We performed a prospective cohort study that included 29,141 adult participants recruited from Yinzhou District, Ningbo, China. Normalized Difference Vegetation Index (NDVI) around each participant's residence was calculated to measure residential greenness exposure. Land-use regression models were conducted to estimate long-term individual exposure to air pollutants, including nitrogen dioxide (NO 2 ) and particulate matter with aerodynamic diameters ≤ 2.5 μm (PM 2.5 ) and ≤10 μm (PM 10 ). Cox proportional hazard models were used to calculate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the associations of residential greenness and air pollutants with the risk of incident IHD. During 101,172.5 person-years of follow-up, 1392 incident IHD cases were reported in the study population. Residential greenness, expressed as an interquartile range (IQR) increase in NDVI within 250 m, was inversely associated with incident IHD (HR = 0.89, 95%CI: 0.81,0.98). However, long-term exposures to air pollution were associated with higher IHD incidence (HR = 1.21, 95%CI:1.10,1.33 per IQR increase for PM 2.5 ; HR = 1.12, 95%CI:1.03,1.22 per IQR increase for PM 10 ; HR = 1.09, 95%CI:1.02,1.16 per IQR increase for NO 2 ). Mediation analyses suggested that the beneficial effect of residential greenness on incident IHD could be partly mediated by reducing the exposure to PM 2.5 . These findings suggested that higher greenness was associated with decreased risk of IHD, while air pollutants were positively associated with incident IHD. Meanwhile, residential greenness may decrease the risk of IHD by reducing exposure to PM 2.5 ., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Growing evidence has linked residential greenness to depression, the results from prospective cohort study are still limited. And it remains unclear whether particulate matter (PM) modify, mediate, or interact the greenness-depression relationship., Methods: We collected data from Yinzhou Cohort(N = 47,516) which was recruited between June 2015 and December 2017. Depression cases before April 2020 were ascertained from local Health Information System covered all residents' health care records. Residential greenness (the Normalized Difference Vegetation Index, NDVI, and the Enhanced Vegetation Index, EVI) and PM (particulate matters with diameters≤2.5 μm, PM 2.5 and particulate matters with diameters≤10 μm, PM 10 ) were estimated based on participants' residential coordinates. We conducted Cox models employing age as timescale to estimate the association between residential greenness within different buffers and incident depression. Furthermore, we explored the potential confounding, mediation and interaction relationship between greenness and PM., Results: During the 99,556 person-years of follow-up, 1043 incident depression cases occurred. In single exposure models, residential greenness was inversely associated with depression incidence (e.g. Hazard Ratio (HR) = 0.86, 95% confidence interval (CI): 0.79, 0.94 for per interquartile range (IQR) increase NDVI 250 m). The protective association between greenness was attenuated after introducing PM 2.5 and PM 10 into the models. We identified multiplicative interactions between greenness and PM exposure for depression (e.g. HR interaction  = 0.91, 95%CI: 0.85, 0.98 for per IQR decrease NDVI 250 m and per IQR increase PM 2.5 ). Besides, we found the protective association of greenness was partly mediated by PM (e.g. mediation proportion = 52.9% between NDVI 250 m and PM 2.5 )., Conclusions: In this longitudinal cohort study, residents living in greener neighborhoods had a lower risk of depression incidence and the benefits were interacted and partly mediated by PM. Improvement in residential greenness could be an actionable and planning intervention to prevent depression., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Long-term exposure to ambient air pollution was linked to depression incidence, although the results were limited and inconsistent., Objectives: To investigate the effects of long-term air pollution exposure on depression risk prospectively in China., Methods: The present study used data from Yinzhou Cohort on adults without depression at baseline, and followed up until April 2020. Two-year moving average concentrations of particulate matter with a diameter ≤ 2.5 μm (PM 2.5 ), ≤10 μm (PM 10 ) and nitrogen dioxide (NO 2 ) were measured using land-use regression (LUR) models for each participant. Depression cases were ascertained using the Health Information System (HIS) of the local health administration by linking the unique identifiers. We conducted Cox regression models with time-varying exposures to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of depression with each pollutant, after adjusting for a sequence of individual covariates as demographic characteristics, lifestyles, and comorbidity. Besides, physical activity, baseline potential depressive symptoms, cancer status, COVID-19 pandemic, different outcome definitions and air pollution exposure windows were considered in sensitivity analyses., Results: Among the 30,712 adults with a mean age of 62.22 ± 11.25, 1024 incident depression cases were identified over totaling 98,619 person-years of observation. Interquartile range increments of the air pollutants were associated with increased risks of depression, and the corresponding HRs were 1.59 (95%CI: 1.46, 1.72) for PM 2.5 , 1.49 (95%CI: 1.35, 1.64) for PM 10 and 1.58 (95%CI: 1.42, 1.77) for NO 2 . Subgroup analyses suggested that participants without taking any protective measures towards air pollution were more susceptible. The results remained robust in all sensitivity analyses., Conclusions: Long-term exposure to ambient air pollution was identified as a risk factor for depression onset. Strategies to reduce air pollution are necessary to decrease the disease burden of depression., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021. Published by Elsevier B.V.)

Background: Though growing evidence has linked air pollution to Parkinson's disease (PD), the results remain inconsistent. Less is known about the relevance of road proximity and surrounding green. We aimed to investigate the individual and joint associations of air pollution, road proximity and surrounding green with the incidence of PD in a prospective cohort study., Methods: We used data from a prospective cohort of 47,516 participants recruited from July 2015 to January 2018 in Ningbo, China. Long-term exposure to particulate matter with aerodynamic diameter ≤2.5 μm (PM 2.5 ) and ≤10 μm (PM 10 ) and nitrogen dioxide (NO 2 ) estimated by land-use regression models, road proximity and surrounding green assessed by Normalized Difference Vegetation Index (NDVI) were calculated based on the residential address for each participant. Cox proportional hazard models were used to analyze the individual and joint effects of air pollution, road proximity, and surrounding green on PD., Results: In single-exposure models, PM 2.5 , PM 10 , NO 2 and road proximity was associated with increased risk of PD (e.g. Hazard Ratio (HR) = 1.51, 95%CI:1.02, 2.24 per interquartile range (IQR) increase for PM 2.5 ) while surrounding green was associated with decreased risk of PD (e.g. HR = 0.80, 95%CI:0.65, 0.98 per IQR increase for NDVI in 300 m buffer). In two-exposure models, the associations of PM 2.5 and surrounding green persisted while the associations of NO 2 and road proximity attenuated towards unity., Conclusions: We found that PM 2.5 were associated with increased risk of incident PD while surrounding green was associated with decreased risk of PD. Future studies about PD etiology may benefit from including multiple environmental exposures to address potential joint associations., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Peptic ulcer disease (PUD) continued to be a source of significant morbidity and mortality worldwide. Recently, it has been reported that exposure to air pollution is a potential risk factor for PUD, but evidence on the association still remains inconsistent., Methods: We performed an ecological study to examine the association between short-term exposure to air pollution and daily hospital visits for PUD in Yinzhou, China from January 1st, 2017 to December 31st, 2019. Distributed lag nonlinear models were used to estimate the nonlinear and lag-response effects of air pollutants. Subgroup analyses stratified by sex, age and season were conducted to examine the effect modifications., Results: Overall, we found that short-term exposure to air pollution including SO 2 , NO 2 , CO, O 3 and PM 2.5 was significantly associated with hospital visits for PUD among all subjects. The lag-response effects of SO 2 , NO 2 and O 3 varied at different concentrations and lag days. The cumulative risk ratios of CO and PM 2.5 showed nearly linear adverse effects and increased to maxima of 2.68 (95% CI: 1.49-4.78) and 2.40 (95% CI: 1.36-4.24) with their ranges from the references to the maximum concentrations, respectively. Moreover, the cumulative risks of particulate matters on hospital visits for PUD increased significantly in cold seasons, but not in warm seasons., Conclusions: Our findings could provide growing evidence regarding the adverse health effects of air pollution on PUD, thereby strengthening the hypothesis that air pollutants have harmful impacts on digestive system., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Sleep disorders have been verified to be associated with adverse health outcomes. Recent studies have linked ambient air pollution to sleep disorders. However, evidence with large sample size and especially prospective studies is very limited., Methods: We used data from a prospective cohort study established from 2015 to 2018 in Ningbo, China. Participants were followed-up after baseline survey through linkage to the regional Health Information System (HIS). Sleep disorders were defined based on International Classification of Disease 10 (ICD-10). Spatial-temporal land-use regression (LUR) models were used to estimate the annual exposure to particulate matter with diameter ≤ 2.5 µm (PM 2.5 ), ≤ 10 µm (PM 10 ) and nitrogen dioxides (NO 2 ). The associations between long-term exposure to air pollutants and prevalence of sleep disorders were examined using logistic regression models, and Cox regression models for the effects of air pollution on the incidence of sleep disorders. A generalized weighted quantile sum (gWQS) regression was used in the multipollutant analysis., Results: A total of 38,775 participants were included in the final analysis. Based on baseline data, we observed significant positive associations between air pollution exposure and increased odds of prevalent sleep disorders (Odds Ratio (OR)= 1.48, 95% confidence interval (CI): 1.41-1.55 for PM 2.5 ; OR= 1.47,95%CI:1.38-1.57 for PM 10 ; OR= 1.38, 95%CI:1.31-1.46 for NO 2 ). In the longitudinal analysis, hazard ratios for incident sleep disorders associated with per interquartile range (IQR) increase in PM 2.5 , PM 10 and NO 2 were 1.14 (1.03, 1.25), 1.13 (1.01, 1.27) and 1.13 (1.04, 1.23), respectively. A gWQS regression analysis showed significant association between air pollution mixture and incident sleep disorders (OR=1.11, 95%CI: 1.03-1.20)., Conclusions: Long-term exposure to PM 2.5 , PM 10 and NO 2 were associated with increased risk of sleep disorders in a Chinese population. Our findings could provide evidence for a more general role in the adverse health impact of air pollution., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Ambient fine particulate matter (particle diameter < 2.5 μm, or PM 2.5 ) is a major public health concern in China. Exposure to PM 2.5 has been associated with a wide range of adverse health outcomes. The current study aimed to estimate the association between exposure to PM 2.5 and the risk of peptic ulcer diseases (PUDs). We conducted a hospital-based cross-sectional study of seven major cities in Zhejiang Province, China (combined population > 57 million people), which included a total of 647,092 subjects who underwent gastroscopy examination (86,852 subjects were diagnosed with PUDs) recorded in 13 large hospitals from 2014 to 2018. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the relationship between PM 2.5 and PUDs, including duodenal ulcers (DUs) and gastric ulcers (GUs). The overall estimated OR (95% CI) associated with every 10-μg/m 3 increase in the 1-month average PM 2.5 before the detection of PUDs was 1.050 (95% CI: 1.038, 1.063). The association between PM 2.5 concentration and the prevalence of PUDs tended to be attenuated but remained significant when considering different exposure periods (OR = 1.030, 95% CI = 1.018-1.043 for the 3-month moving average; OR = 1.020, 95% CI = 1.005-1.037 for the 6-month moving average). Stronger associations were observed for DUs than GUs. The observed positive association of PM 2.5 exposure with PUDs remained significant in the two-pollutant models after adjusting for other air pollutants. Our findings could provide scientific evidence for a more general adverse role of air pollution on PUDs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The coronavirus disease (COVID-19) has become a global public health threaten. A series of strict prevention and control measures were implemented in China, contributing to the improvement of air quality. In this study, we described the trend of air pollutant concentrations and the incidence of COVID-19 during the epidemic and applied generalized additive models (GAMs) to assess the association between short-term exposure to air pollution and daily confirmed cases of COVID-19 in 235 Chinese cities. Disease progression based on both onset and report dates as well as control measures as potential confounding were considered in the analyses. We found that stringent prevention and control measures intending to mitigate the spread of COVID-19, contributed to a significant decline in the concentrations of air pollutants except ozone (O 3 ). Significant positive associations of short-term exposure to air pollutants, including particulate matter with diameters ≤2.5 μm (PM 2.5 ), particulate matter with diameters ≤10 μm (PM 10 ), and nitrogen dioxide (NO 2 ) with daily new confirmed cases were observed during the epidemic. Per interquartile range (IQR) increase in PM 2.5 (lag0-15), PM 10 (lag0-15), and NO 2 (lag0-20) were associated with a 7% [95% confidence interval (CI): (4-9)], 6% [95% CI: (3-8)], and 19% [95% CI: (13-24)] increase in the counts of daily onset cases, respectively. Our results suggest that there is a statistically significant association between ambient air pollution and the spread of COVID-19. Thus, the quarantine measures can not only cut off the transmission of virus, but also retard the spread by improving ambient air quality, which might provide implications for the prevention and control of COVID-19., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Depression is one of the leading causes of disability, but the etiology remains unclear. Recently, it has been suggested that air pollution is a potential risk factor for depression. However, the results remained inconsistent. So we conducted this study to assess the association between short-term exposure to ambient air pollution and hospital visits for depression in China. Daily hospital visits for depression from January 18, 2013 to June 10, 2018 were extracted from a regional health information system (HIS) covered 1.34 million population in Ningbo, China. We collected daily air pollutant concentrations and meteorological data from environmental air quality monitoring sites and meteorological stations in the study area. Quasi-Poisson regression models with generalized additive models (GAM) were applied to explore the associations between air pollution and hospital visits for depression. Stratified analyses were also conducted by gender, age, and season to examine the effects modification. The results disclosed that air pollutants including PM 2.5 , PM 10 , SO 2 , CO, and NO 2 were positively correlated with hospital visits for depression. The strongest effects all occurred on lag0 (the same) day, and the corresponding excess risks (ERs) were 2.59 (95%CI: 0.72, 4.49) for PM 2.5 , 3.08 (95%CI: 1.05, 5.16) for PM 10 , 3.22 (95%CI: 1.16, 5.32) for SO 2 , 4.38 (95%CI: 1.83, 6.99) for CO, and 4.94 (95%CI: 2.03, 7.92) for NO 2 per IQR increase, respectively. The associations were found to be stronger in the elderly (≥65 years) and cold season. Furthermore, the effects of CO and NO 2 remained significant in most two-pollutant models, suggesting that traffic-related air pollutants might be more important triggers of depression., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Fine particulate matter (PM 2.5 ) is a mixture of multiple components, which is associated with several chronic diseases, including respiratory and cardiovascular diseases. We evaluated the association between daily PM 2.5 and PM 2.5-10 exposure and hospital visits for respiratory diseases. Hospital visits for respiratory diseases were collected from Yinzhou Health Information System database. We used generalized additive models to examine the excess relative risk (ERR) and 95% confidence interval for hospital visits for respiratory diseases associated with each 10-μg/m 3 increase in PM 2.5 and PM 2.5-10 concentration. Non-linear exposure-response relationship between PM exposure and hospital visits for respiratory diseases was evaluated by a smooth spline. The ERRs for hospital visits for respiratory diseases associated with a 10-μg/m 3 increase in the 6-day cumulative average concentration of PM 2.5 and PM 2.5-10 were 5.40 (95% CI 2.32, 8.57) and 6.37% (95% CI 1.84, 11.10), respectively. The findings remained stable when we adjusted other gaseous air pollution. PM 2.5 and PM 2.5-10 were associated with the increased visits for the acute upper respiratory infection, pneumonia, asthma, and COPD. In this time-series study, we found a positive association between daily particulate matter exposure and hospital visits for respiratory diseases.

Recently, air pollution has attracted a substantial amount of attention in China, which can be influenced by a variety of factors, but the association between air pollution and human activity is not quite clear. Based on real-time online data (January 1, 2014, to December 31, 2014) of air pollution and meteorology reported by official sites, and demographic, economic, and environmental reform data in a statistical yearbook, the influences of meteorological factors (temperature, relative humidity, precipitation intensity, and wind force) and human activities on PM 2.5 pollution were explored. After correlation analysis, logistic regression analysis, and a nonparametric test, weak negative correlations between temperature and PM 2.5 pollution were found. In most cases, festival and morning peak hours were protection and risk factors of PM 2.5 pollution, respectively. In addition, government actions, such as an afforestation project and increasing financial expenditure for energy saving and environmental protection, could greatly contribute to alleviating pollution of PM 2.5 . The findings could help officials formulate effective laws and regulations, and then PM 2.5 pollution related to the pattern of human activity would be ameliorated., Implications: Most of the time, festival and morning peak hours are protection and risk factors for PM 2.5 pollution, respectively. Increasing the percentage of afforestation area and financial expenditure for energy saving and environmental protection could significantly reduce PM 2.5 pollution. The findings can help officials formulate effective laws and regulations, and then PM 2.5 pollution related to the pattern of human activity, especially government action, will be ameliorated.

Objective: To explore the association between particulate matter (PM) and daily hospital visits of coronary heart diseases in Ningbo. Methods: Daily data of hospital visits from January 2014 to June 2015 (516 days in total) were obtained from the Yinzhou Health Information System in Ningbo. Daily air pollution data for PM and meteorological data were collected from the database of Ningbo Environmental Monitoring Center and Ningbo Meteorological Bureau. Time-series analysis by quasi-Poisson generalized additive model was used to examine the association between air pollution and hospital visits for coronary heart diseases by adjustment of long-term trends, seasonal patterns and meteorological variables (temperature, humidity), and day of week. Results: An increase of an IQR of PM 2.5 accounted for 1.98% (95% CI :-0.59%-4.63%) increase of hospital visits for coronary heart diseases. The associations between PM 2.5 and hospital visits for coronary heart diseases among female and the elderly (≥75 years) were stronger ( ER =2.70%,95% CI :0.01%-5.47%; ER =3.35%, 95% CI: 0.12%-6.69%). The effects of PM 2.5~10 attenuated after adjustment for PM 2.5. Conclusion: PM 2.5 had short-term effects on daily hospital visits for coronary heart diseases in Ningbo, and such association was stronger among female and the elderly.

Abstract Background Air pollution epidemiological studies increasingly rely on high-resolution exposure prediction models. However, to date, few models of this type exist for use in China. Objectives We produced a national land-use regression model (LUR) to estimate monthly average PM 2.5 , PM 10 and NO 2 from 2014 to 2016 in China. Methods We developed a spatiotemporal semi-parametric model using generalized additive mixed models. A variety of predictor variables were included in model: time varying meteorological data, high resolution land cover data from Globaland30, satellite measures of aerosol optical depth, and Geographic Information System (GIS)-derived predictors. We assessed model performance with two cross-validation (CV) approaches, including hold-out CV, and 10-fold CV. Results Over 22,000 monthly observations at 1382 monitoring locations were included to estimate the air pollution exposure. The time-varying spatial terms explained 87%, 71%, and 69% of variability with a hold-out cross-validated R2 of 0.85, 0.62, and 0.62 for PM 2.5 , PM 10 and NO 2 models, respectively. Models show that meteorological variables, population density, elevation, distance to road, and land cover types were important predictors for air pollution exposure. Conclusions we have developed a new nationwide model to estimate residence-level air pollution exposures, which can be used in studies of the chronic adverse effects of air pollution. Highlights • We developed national scale spatiotemporal land use models to estimate monthly PM 2.5 , PM 10 and NO 2 concentrations in China. • For the PM 2.5 , PM 10 and NO 2 models, predictors explained 87%, 71%, and 69% of variability of the pollutant distributions. • Meteorological, AOD, and GIS-derived covariates were important predictors for air pollution exposure. [ABSTRACT FROM AUTHOR]

To examine the association between short-term exposure to air pollution and ischemic stroke (IS) onset and the role of lifestyles on the association. We performed a time-stratified case-crossover study to estimate the association between short-term exposure to air pollution and IS onset in Yinzhou, China from July 1st, 2015 to May 31st, 2020. Conditional logistic regression models were used to assess the effect of air pollution on IS onset. Furthermore, we explored whether these effects were modified by lifestyle factors by using stratified analyses. A total of 700 subjects were included in analyses. We found that positive associations between exposure to O 3 and IS onset with the OR IQRs of 1.23 (95% CI: 1.01–1.49) at lag04 and 1.28 (95% CI: 1.03–1.59) at lag06, respectively. Stronger associations were observed between NO 2 at lag04 and lag06 and IS onset after adjusting for other air pollutants, and the corresponding OR IQRs were 2.08 (95% CI: 1.37–3.15) and 2.04 (95% CI: 1.27–3.27), respectively. However, no association was observed for exposure to particulate matters and IS onset. Stronger associations were observed for NO 2 and risk of IS onset among abnormal weight subjects, alcohol drinkers, smokers, and subjects who exercised 1–4 times per week or barely exercised every week. We also observed stronger associations of SO 2 , CO, PM 2.5 and PM 10 with IS onset among subjects who exercised 1–4 times per week. In this case-crossover study, we found positive associations between short-term exposure to air pollution, especially for NO 2 , and risk of IS onset. Moreover, our study highlighted that lifestyle factors, such as alcohol consumption and physical activity, had significant impacts on the association of ambient air pollution with risk of IS onset. • New evidence on the association between short-term exposure to air pollution and ischemic stroke from China. • O 3 and NO 2 were positively associated with risk of ischemic stroke onset. • Lifestyle factors could affect the association of short-term exposure to air pollution with risk of ischemic stroke onset. [ABSTRACT FROM AUTHOR]

Air pollution has already become a serious public health concern worldwide, while evidence for the association between air pollution and digestive disease is not consistent. To examine the association between air pollution and peptic ulcer bleeding (PUB). We performed a time-stratified case-crossover study among 1,246,270 gastroscopy records in Zhejiang, China from January 1st, 2013 to June 30th, 2019. Individual exposure to air pollution for each subject was estimated by using data from 55 fixed-sites with an inverse distance weighted method. Conditional logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (95% CIs) for PUB associated with an interquartile range (IQR) increase in air pollution on the entire population. Subgroup analyses were performed for season, age and sex. Totally 3543 patients diagnosed with PUB were included in the analyses. Significant associations were observed between NO 2 , CO and PM 2.5 and the risk of PUB. The effect was observed strongest measured as lag 06 and an IQR increase of 7-day moving average concentrations of NO 2 resulted in a 24.0% increase of getting PUB (95% CI: 2.6%–50.0%). Our findings strengthen the hypothesis that short-term air pollution exposure has adverse health effects on digestive system. • Air pollution has adverse health effects on respiratory and cardiovascular systems. • The effects of air pollutants on peptic ulcer bleeding are still unclear. • Short-term exposure to some air pollutants contribute to peptic ulcer bleeding. [ABSTRACT FROM AUTHOR]

• Positive associations between air pollution and sleep disorders were found. • The strongest effects of traffic-related pollutants were found with lag day 2–3. • Effect estimates for females and younger residents were somewhat stronger. • Hospital visits for sleep disorder of 395,651 older Chinese (≥60) were studied. Sleep disorders, oftentimes co-occurring with other mental and neurological disorders in the elderly, have been previously linked to short-term exposures to air pollution. Here we assessed such associations among 395,651 elderly Chinese in Ningbo, China where air pollution exposures are high and the proportion of elderly in the population is growing. We utilized a regional health information database in China (2008–2017) that collected information on hospital visits for sleep disorders among the elderly (age 60+). Measures of daily air pollution concentrations including nitrogen dioxide (NO 2), sulfur dioxide (SO 2), ozone (O 3), inhalable particles (PM 10), and ambient fine particulate matter (PM 2.5) were generated from seven environmental air quality monitoring sites in the study area. We used a generalized additive model to evaluate the associations between hospital visits for sleep disorders and short-term air pollution exposures for up to 7 days prior to a hospital visit. Short-term exposure to multiple air pollutants was associated with hospital visits for sleep disorders in an elderly population; with the strongest associations during 2–3 days prior to a clinic visits for traffic-related pollutants including air quality index (AQI), PM 2.5 , PM 10 , and NO 2 and for SO 2 and O 3 for 5 days prior to the visits. Our study based on large health care record system suggested that short-term air pollution exposures are associated with sleep disorders in the elderly. Considering the individual covariates that could not be adjusted in time-series analyses, future studies with individual level data and an ability to evaluate the severity of sleep disorders and their relation to mental and physical health in general and air pollution are needed. An aging population with increasing health problems and the frequency of high and very high air pollution events in China make our findings very health policy relevant. [ABSTRACT FROM AUTHOR]