The Novel Relationship between Urban Air Pollution and Epilepsy: A Time Series Study

• Published in: PloS one 2016-08, Vol.11 (8), p.e0161992-e0161992
• Main Authors: Xu, Chen, Fan, Yan-Ni, Kan, Hai-Dong, Chen, Ren-Jie, Liu, Jiang-Hong, Li, Ya-Fei, Zhang, Yao, Ji, Ai-Ling, Cai, Tong-Jian
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Air Pollutants - adverse effects; Air pollution; Air Pollution - adverse effects; Analysis; Atmospheric pollution; China - epidemiology; Disease prevention; Earth Sciences; Ecology and Environmental Sciences; Engineering and Technology; Environmental aspects; Environmental Exposure - adverse effects; Environmental health; Environmental pollution; Epidemiology; Epilepsy; Epilepsy - epidemiology; Epilepsy - etiology; Exposure; Female; Gene expression; Health care; Humans; Humidity; Ischemia; Male; Medical records; Medicine and Health Sciences; Middle Aged; Nervous system; Nitrogen dioxide; Particulate matter; Particulate Matter - adverse effects; People and Places; Physical Sciences; Poisson density functions; Pollutants; Pollution; Preventive medicine; Psychological aspects; Public health; Regression analysis; Regression models; Risk factors; Risk reduction; Seasons; Statistical analysis; Studies; Sulfur dioxide; Time series; Trends; Urban air; Urban areas; Weather; Young Adult
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0161992

The data concerning the association between environmental pollution and epilepsy attacks are limited. The aim of this study was to explore the association between acute air pollution exposure and epilepsy attack. A hospital record-based study was carried out in Xi'an, a heavily-polluted metropolis in China. Daily baseline data were obtained. Time-series Poisson regression models were applied to analyze the association between air pollution and epilepsy. A 10 μg/m3 increase of NO2, SO2, and O3 concentrations corresponded to 3.17% (95%Cl: 1.41%, 4.93%), 3.55% (95%Cl: 1.93%, 5.18%), and -0.84% (95%Cl: -1.58%, 0.09%) increase in outpatient-visits for epilepsy on the concurrent days, which were significantly influenced by sex and age. The effects of NO2 and SO2 would be stronger when adjusted for PM2.5. As for O3, a -1.14% (95%Cl: -1.90%, -0.39%) decrease was evidenced when adjusted for NO2. The lag models showed that the most significant effects were evidenced on concurrent days. We discovered previously undocumented relationships between short-term air pollution exposure and epilepsy: while NO2 and SO2 were positively associated with outpatient-visits of epilepsy, O3 might be associated with reduced risk.