4.4 Article

The effect of weather, air pollution and seasonality on the number of patient visits for epileptic seizures: A population-based time-series study

期刊

EPILEPSY & BEHAVIOR
卷 115, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.yebeh.2020.107487

关键词

Epileptic seizure; Weather; Air pollution; Seasonality; Time series data

资金

  1. Development Association of Hungkuang University [HK-KTOH-108-02]

向作者/读者索取更多资源

This study explored the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures in Taiwan. Factors such as ambient temperature, CH4, and NO were found to have a significant impact on hospital visits. The study emphasized the necessity of rigorous monitoring and early warning of air pollutants and climate changes, and provided a basis for establishing prediction models for other countries or diseases.
Objective: The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures. Methods: Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7 days' lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined. Results: The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH4, and NO. Six air pollutants, namely CH4, NO, CO, NO2, PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R-2 = 0.422). Conclusion: The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases. (C) 2020 Elsevier Inc. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据