Short-term exposure to air pollution and conjunctivitis outpatient visits: A multi-city study in China

Lu, Peng; Zhang, Yongming; Xia, Guoxin; Zhang, Wenyi; Li, Shanshan; Guo, Yuming

doi:10.1016/j.envpol.2019.113030

Cited by 40 publications

(21 citation statements)

References 30 publications

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“…Serious eye diseases may result in adverse consequences such as vision loss, which would greatly affect the life quality of the patients (Wang et al 2018). Most self-limited cases, meanwhile, are also disturbed by the constant symptoms and uncomfortable feelings (Lu et al 2019). Therefore, eye diseases are one of the upcoming health issues at the global scale.…”

Section: Discussionmentioning

confidence: 99%

“…In this study, we found significant associations of PM 2.5, PM 10 , CO, and NO 2 , but not O 3 or SO 2 with increased emergency room visits for total eye diseases and conjunctivitis. The differences might in part be explained by the variations in geographical settings, for most of previous studies were conducted in developed regions with relatively lower pollution concentrations (Lu et al 2019). Meanwhile, the study design and statistical methods used may also be a source of differences, for the auto-correlation of emergency room visit data could not be addressed if time-dependent variables were not well considered (Bhaskaran et al 2013).…”

Section: Discussionmentioning

confidence: 99%

“…Some serious cases may progress to vision loss, which is the third largest cause of impairment and greatly impact on quality of life (Xu et al 2020). Meanwhile, despite that most eye diseases are usually self-limited, they still affect daily activities of the patients due to their distressing symptoms (Lu et al 2019). For instance, the conjunctivitis, an ocular surface inflammation characterized by dilation of conjunctival vessels, is typically associated with constant symptoms of diffuse redness, gritty eye sensation, itching, tearing, and eye discharge (Chen et al 2021).…”

Section: Introductionmentioning

confidence: 99%

“…However, these finding were inconsistent, which might be partly attributable to the variations in population characteristics and geographical settings. Meanwhile, most previous studies used outpatient visits as the outcome indicator, which is less sensitive to evaluate the acute effects of air pollutants exposure (Lu et al 2019, Song et al 2021. In addition, investigations on health effects of ambient air pollution should consider the heterogeneity of weather condition, particularly temperature, which has been found to be a strong modifier for air pollution-health associations (Bergmann et al 2020, Song et al 2021.…”

Section: Introductionmentioning

confidence: 99%

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Association between air pollution and emergency room visits for eye diseases and effect modification by temperature in Beijing, China

Wang

Zhang

et al. 2021

Environ Sci Pollut Res

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The growing burden of eye disease worldwide has aroused increasing concern upon its environmental etiology. This study aims to evaluate the associations of air pollutants with emergency room visits for eye diseases and the effect modification by temperature. Based on 24,389 cases from a general hospital during 2014-2019 in Beijing, China, this study used generalized additive models to examine the associations of air pollutants and emergency room visits for total eye diseases (ICD10: H00-H59) and conjunctivitis (ICD10: H10). Short-term exposures to PM 2.5 , PM 10 , CO, and NO 2 were associated with increased visits for total eye diseases and conjunctivitis, and stronger effect estimates were observed in high (>75th) temperature group for PM 2.5 , PM 10 , CO, and NO 2 and low (<75th) temperature group for CO and NO 2 . For instance, a 10 μg/m 3 increase in PM 2.5 at lag0-1 were associated with a 0.73% (95% CI: 0.23%, 1.24%) increase in total eye disease visits and a 1.34% (95% CI: 0.55%, 2.13%) increase in conjunctivitis visits, respectively. Meanwhile, a 10 μg/m 3 increase in PM 2.5 was associated with a 1.57% (95% CI: 0.49%, 2.64%) change in high temperature group and a 0.48% (95% CI: −0.24%, 1.19%) change in medium temperature group (P for interaction = 0.04) in total eye disease visits. Our study emphasizes the importance of controlling the potential hazards of air pollutants on eyes, especially on days with relatively higher or colder temperature.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Association between air pollution and emergency room visits for eye diseases and effect modification by temperature in Beijing, China

Wang

Zhang

et al. 2021

Environ Sci Pollut Res

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“…A meta-analysis study has shown that females and youth are more vulnerable to PM2.5, NO 2 , and O 3 [7]. Several studies have further provided signi cant evidence that, in China, patient due to conjunctivitis are associated with air pollution [8][9][10].…”

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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Ambient air pollution and its influence on human health and welfare: an overview

Almetwally

Bin-Jumah

Allam

2020

Environ Sci Pollut Res

188

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Short-term exposure to air pollution and conjunctivitis outpatient visits: A multi-city study in China

Cited by 40 publications

References 30 publications

Association between air pollution and emergency room visits for eye diseases and effect modification by temperature in Beijing, China

Association between air pollution and emergency room visits for eye diseases and effect modification by temperature in Beijing, China

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

Ambient air pollution and its influence on human health and welfare: an overview

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