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Background: Ambient PM2.5 is associated with asthma exacerbation. The association between the concentration of PM2.5 and the severity of asthma exacerbation has yet to be thoroughly clarified. The study aims to explore the association between the piror 30 days average concentration of PM2.5 and the severity of acute asthma exacerbation in hospitalized children., Methods: A total of 269 children with acute exacerbation of asthma were enrolled and divided into three groups according to the PM2.5 exposure concentrations: group 1 (PM2.5: <37.5 μg/m 3 ), group 2 (PM2.5: 37.5-75 μg/m 3 ), group 3 (PM2.5: ≥75 μg/m 3 ), respectively. The ordered logistic regression modeling was conducted to explore the influence of daily PM2.5 concentration on the clinical severity of children's asthma exacerbation. Multiple linear regression was conducted to explore the association between the concentration of PM2.5 and the length of stay in the hospital (LOS). We also conducted a receiver operating characteristic (ROC) curve analysis to explore the cutoff value of PM2.5 to predict the children's asthma exacerbation., Results: There was no statistical difference among the three groups of children in gender, age, body mass index, ethnicity, the first diagnosis of asthma, allergic history, passive smoke exposure, or family history of asthma. There was a statistically significant difference in many hospitalization characteristics (p < 0.05) among the three groups of children. Significant differences were found in terms of accessory muscles of respiration (p = 0.005), respiratory failure (p = 0.012), low respiratory tract infectious (p = 0.020), and the severity of asthma exacerbation (p < 0.001) among the three groups. PM2.5 concentration was primarily positively correlated to neutrophile inflammation. The ordered multivariate logistic regression model showed that higher PM2.5 concentrations were significantly associated with greater odds of more severe asthma exacerbation in one and two-pollutant models. The adjusted odds ratio of severe asthma exacerbation was 1.029 (1.009, 1.049) in the one-pollutant model. The most significant odds ratio of severe asthma exacerbation was 1.050 (1.027, 1.073) when controlling NO 2 in the two-pollutant models. Multiple linear regression showed that PM2.5 concentration was significantly associated with longer LOS in both one-pollutant and two-pollutant models. By performing ROC analysis, the average daily concentration of 44.5 µg/m 3 of PM2.5 (AUC = 0.622, p = 0.002) provided the best performance to predict severe asthma of children exacerbation with a sensitivity of 59.2% and a specificity of 63.8%., Conclusion: The increased prior 30 days average concentration of PM2.5 was associated with greater asthma exacerbation severity and longer length of stay in the hospital of children with asthma exacerbation., (© 2023 Wiley Periodicals LLC.)

Epidemiological studies found that exposure to air pollution increases cardiovascular hospitalizations. However, studies on rural-urban differences in associations between hospitalizations for cardiovascular diseases and air pollution are limited. The generalized linear model (GLM) was applied to investigate the associations between cardiovascular hospitalizations and air pollution (SO 2 , NO 2 , PM 2.5 , PM 10 , CO, and O 3 ) in Guangxi, southwest China, in 2015 (January 1-December 31). The relative risk of pollutants (SO 2 , NO 2 ) on cardiovascular hospital admissions was significantly different between urban and rural areas. The effect of SO 2 on cardiovascular hospitalizations was higher in urban areas than in rural areas at lag0 to lag3 and cumulative lag01 to lag03. In urban areas, there were positive associations between NO 2 and cardiovascular hospitalizations at lag0, lag1 and cumulative lag01, lag02. In contrast, the effect of NO 2 on cardiovascular hospitalizations was not significant in rural areas. Urban residents were more sensitive than rural residents to SO 2 and NO 2 . Subgroup analyses showed statistically significant differences between rural and urban areas in the association between SO 2 and NO 2 and cardiovascular hospitalizations for males. For age groups, people aged ≥ 65 years appeared to be more vulnerable to SO 2 and NO 2 in urban areas. The effects of PM 2.5 PM 10 , CO, and O 3 on cardiovascular hospitalizations were consistently negative for all groups. Our findings indicated that there were rural-urban differences in associations between cardiovascular hospitalizations and air pollutants. In rural areas, the risk of cardiovascular hospitalizations was mainly influenced by SO 2 . Therefore, we expect to pay attention to protecting people from air pollution, particularly for those aged ≥ 65 years in urban areas., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objective: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China., Setting: Guangxi, China., Participants: This study was done among 7804 asthma patients., Primary and Secondary Outcome Measures: Spearman correlation coefficient was used to estimate correlation between environmental factors and asthma hospitalisation rates in multiple regions. Generalised additive model (GAM) with Poisson regression was used to estimate effects of environmental factors on asthma hospitalisation rates in 14 regions of Guangxi., Results: The strongest effect of carbon monoxide (CO) was found on lag1 in Hechi, and every 10 µg/m 3 increase of CO caused an increase of 25.6% in asthma hospitalisation rate (RR 1.26, 95% CI 1.02 to 1.55). According to the correlation analysis, asthma hospitalisations were related to the daily temperature, daily range of temperature, CO, nitrogen dioxide (NO 2 ) and particulate matter (PM 2.5 ) in multiple regions. According to the result of GAM, the adjusted R 2 was high in Beihai and Nanning, with values of 0.29 and 0.21, which means that environmental factors are powerful in explaining changes of asthma hospitalisation rates in Beihai and Nanning., Conclusion: Asthma hospitalisation rate was significantly and more strongly associated with CO than with NO 2 , SO 2 or PM 2.5 in Guangxi. The risk factors of asthma exacerbations were not consistent in different regions, indicating that targeted measures should differ between regions., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Particulate matter (PM) has become the main air pollutant in most cities of in China, which greatly threatens the human health. Numerous studies have reported that PM concentrations could be accurately predicted from previous days' meteorological conditions. However, the hysteretic or lagged effects of meteorological factors on PM concentrations are not clear. In this study, the GeoDetector q statistic method was used to quantify the hysteretic influences of meteorological conditions and their interactions on concentrations of PM 2.5 (particles < 2.5 μm in aerodynamic diameter) and PM 10 (particles < 10 μm in aerodynamic diameter) and the ratio of PM 2.5 to PM 10 (PM 2.5 /PM 10) at multiple spatial and temporal scales in China. We found that the temperature, precipitation, and relative humidity had primary impacts on PM 2.5 concentrations, PM 10 concentrations, and the PM 2.5 /PM 10 ratios, respectively, at both national and annual time scales. At the seasonal time scale, precipitation and relative humidity had hysteretic effects on PM concentrations in spring and summer, respectively. Moreover, precipitation and wind speed were dominant hysteretic factors in autumn and winter, respectively. At the regional scale, the dominant hysteretic effects of meteorological factors showed large variations across all regional subdivisions. The interactions between any two meteorological factors had an enhanced hysteretic effect on PM concentrations compared to a single factor. These findings could help us to develop scientific measures to reduce the emissions of air pollution and improve the performance of air pollution prediction models. Image 1 • Hysteretic effects of meteorological factors on particulate matter were identified. • Temperature, rainfall, and humidity are main lagged factors of particulate matter. • Regional and seasonal variations of hysteretic factors were identified in China. • Urgent need to explore mechanisms of lagged effects of meteorological factors on PM. [ABSTRACT FROM AUTHOR]