Air quality and acute myocardial infarction in adults during the 2016 Hangzhou G20 summit

Wang, Ming Wei; Chen, Juan; Cai, Ran

doi:10.1007/s11356-017-1136-2

Cited by 7 publications

(4 citation statements)

References 29 publications

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“…Numerous health studies have indicated that the impacts of air quality improvements during large-scale sporting events have been associated with beneficial physiological health effects, including reductions in acute myocardial infarction rates and systematic inflammation, , as well as improvements in cardio-respiratory health . Other studies have found that changes in certain behaviors were mostly affected by individual ’s varying perception of smog pollution. , Individuals with higher perceived concerns, greater knowledge of smog pollution, and higher perceptions of its health risks were more likely to view air pollution as an unacceptable risk .…”

Section: Introductionmentioning

confidence: 99%

“…Assessments of the effects of these short-term intervening measures can provide critical insights into the main sources of air pollution as well as how to design the most effective environmental policies. 12 Numerous health studies have indicated that the impacts of air quality improvements during large-scale sporting events have been associated with beneficial physiological health effects, including reductions in acute myocardial infarction rates 17 and systematic inflammation, 18,19 as well as improvements in cardio-respiratory health. 20 Other studies have found that changes in certain behaviors were mostly affected by individual 's varying perception of smog pollution.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative Analysis of Health Risk Perception, Exposure Levels, and Willingness to Pay/Accept of PM_2.5 during the 2014 Nanjing Youth Olympic Games

Huang

et al. 2018

Environ. Sci. Technol.

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Local governments in China regularly implement short-term emission control measures to improve air quality during important sporting events. As a condition for hosting the 2014 Youth Olympic Games (YOG), the Nanjing government agreed to temporarily and substantially improve air quality. Regression analysis, Spearman correlation analysis, χ 2 test, and the contingent valuation method were used to explore the effects of robust, short-term air pollution control measures on risk perception, daily exposure to PM 2.5 , risk acceptance levels, and willingness to pay/accept (WTP/ WTA) for reductions in air pollution for the benefit of reducing health risks. Postimplementation, the respondents' risk perception levels presented the following changes: during the YOG, the respondents perceived the lowest effects of haze pollution while after the YOG, they perceived the highest effects. The changes in risk acceptance levels showed the same tendency. Furthermore, after the YOG, the respondents asked for the most economic compensation, and their willingness to pay for risk reduction also reached the highest level. This study reveals the need to increase the public's understanding of the health risks of air pollution, protect those populations most exposed to high levels of PM 2.5 , and take more effective long-term measures to meet local residents' demands for improved air quality.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Health Risk Perception, Exposure Levels, and Willingness to Pay/Accept of PM_2.5 during the 2014 Nanjing Youth Olympic Games

Huang

et al. 2018

Environ. Sci. Technol.

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“…8,9 Studies have shown that air pollution not only affects respiratory diseases, but also affects acute myocardial infarction, arrhythmia, conjunctivitis, and maletal disorders. 10,11 In addition, studies have shown that long-term exposure to PM 2.5 , PM 10 , and NO 2 is positively associated with the prevalence of the metabolic syndrome. [12][13][14] More and more evidence shows that environmental pollutants such as diesel exhaust particulates, suspended PM, metals, and polychlorinated compounds are important risk factors for the development of MAFLD.…”

Section: Introductionmentioning

confidence: 99%

Explore the Relationship Between Short-Term Ambient Air Pollution Exposure and Daily Outpatient Visits for Metabolic Related Fatty Liver

Wang¹,

Sun²,

Wen³

et al. 2022

RMHP

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Background: Many studies have shown that the pollution of fine particles in the air is related to the incidence of chronic diseases. However, research on air pollution and metabolism-associated fatty liver disease (MAFLD) is limited. Objective: The purpose of this study was to explore the relationship between short-term ambient air pollution and daily outpatient visits for metabolic-related fatty liver. Methods: We used a quasi-Poisson regression generalized additive model to stratify analyses by season, age, and gender. Results: From January 1, 2017, to August 31, 2019, 10,562 confirmed MAFLD outpatient visits were recorded. A 10 µg/m 3 increase of fine particular matter (PM10and PM2.5) and NO 2 concentrations corresponding with percent change were 0.82 (95% confidence interval [CI], 0.49-1.15), 0.57 (95% CI, 0.18-0.98), and 0.86 (95% CI, 0.59-1.13) elevation in MAFLD outpatient visits. In terms of season, the impact estimates of NO 2 and PM2.5% change were 3.55 (95% CI, 1.23-5.87) and 1.12 (95% CI, 0.78-1.46) in the hot season and transition season, respectively. Compared with the warm season, the impact estimates of PM10were more significant in the cool season: 2.88 (95% CI, 0.66-5.10). NO 2 has the greatest effect in the transition season, whereas PM10 has the greatest highest effect in the cool and hot seasons. Compared with other pollutants, PM2.5 has the greatest impact in the age stratification, which percent change are 2.69 (95% CI, 0.77-5.61) and 2.88 (95% CI, 0.37-6.40) respectively. The impact values of PM2.5 in male and female percent change were 3.60 (95% CI, 0.63-6.57) and 1.65 (95% CI, 1.05-2.25), respectively. Conclusion:This study shows that the air pollutants are related to the number of outpatient visits for MAFLD. The effects of different air pollutants on MAFLD outpatient visits were different by season, ages, and gender.

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“…China is now facing one of the worst air pollution problems, being the largest developing nation in the world [4]. We have previously reported that air quality improvement could reduce the number of hospital admissions due to acute myocardial infarction [5]. It was also reported that air pollution has short-term and lagging effects on lungs function in school-age children in the city of Hangzhou, in Zhejiang province, China [6].…”

Section: Introductionmentioning

confidence: 99%

Machine learning prediction on number of patient due to conjunctivitis based on air pollutants: A preliminary study

Cheng

Feng

Zhou

et al. 2020

Preprint

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Background Accurate prediction of the number of patients with conjunctivitis plays an important role in providing adequate treatment at the hospital, but such accurate predictive model currently does not exist. The current study sought to use machine learning (ML) prediction based on past patient for conjunctivitis and several air pollutants. The optimal machine learning prediction model was selected to predict conjunctivitis-related number patients. Methods The average daily air pollutants concentrations (CO, O3, NO2, SO2, PM10, PM2.5) and weather data (highest and lowest temperature) were collected. Data were randomly divided into training dataset and test dataset, and normalized mean square error (NMSE) was calculated by 10 fold cross validation, comparing between the ability of seven ML methods to predict the number of patient due to conjunctivitis (Lasso penalized liner model, Decision tree, Boosting regression, Bagging regression, Random forest, Support vector, and Neural network). According to the accuracy of impact prediction, the important air and weather factors that affect conjunctivitis were identified. Results A total of 84977 cases to treat conjunctivitis were obtained from the ophthalmology center of the Affiliated Hospital of Hangzhou Normal University. For all patients together, the NMSE of the different methods were as follows: Lasso penalized liner regression: 0.755, Decision tree: 0.710, Boosting regression: 0.616, Bagging regression: 0.615, Random forest: 0.392, Support vectors: 0.688, and Neural network: 0.476. Further analyses, stratified by gender and age at diagnosis, supported Random forest as being superior to others ML methods. The main factors affecting conjunctivitis were: O3, NO2, SO2 and air temperature. Conclusion Machine learning algorithm can predict number of patients due to conjunctivitis, among which, the Random forest algorithm had the highest accuracy. Machine learning algorithm could provide accurate information for hospitals dealing with conjunctivitis caused by air factors.

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Air quality and acute myocardial infarction in adults during the 2016 Hangzhou G20 summit

Cited by 7 publications

References 29 publications

Quantitative Analysis of Health Risk Perception, Exposure Levels, and Willingness to Pay/Accept of PM_2.5 during the 2014 Nanjing Youth Olympic Games

Quantitative Analysis of Health Risk Perception, Exposure Levels, and Willingness to Pay/Accept of PM_2.5 during the 2014 Nanjing Youth Olympic Games

Explore the Relationship Between Short-Term Ambient Air Pollution Exposure and Daily Outpatient Visits for Metabolic Related Fatty Liver

Machine learning prediction on number of patient due to conjunctivitis based on air pollutants: A preliminary study

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Air quality and acute myocardial infarction in adults during the 2016 Hangzhou G20 summit

Cited by 7 publications

References 29 publications

Quantitative Analysis of Health Risk Perception, Exposure Levels, and Willingness to Pay/Accept of PM2.5 during the 2014 Nanjing Youth Olympic Games

Quantitative Analysis of Health Risk Perception, Exposure Levels, and Willingness to Pay/Accept of PM2.5 during the 2014 Nanjing Youth Olympic Games

Explore the Relationship Between Short-Term Ambient Air Pollution Exposure and Daily Outpatient Visits for Metabolic Related Fatty Liver

Machine learning prediction on number of patient due to conjunctivitis based on air pollutants: A preliminary study

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Quantitative Analysis of Health Risk Perception, Exposure Levels, and Willingness to Pay/Accept of PM_2.5 during the 2014 Nanjing Youth Olympic Games

Quantitative Analysis of Health Risk Perception, Exposure Levels, and Willingness to Pay/Accept of PM_2.5 during the 2014 Nanjing Youth Olympic Games