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[气象要素主导的变应性鼻炎发病机制分级预测研究]

[Grading forecast research for pathogenesis of allergic rhinitis directed by meteorological elements].

作者信息

Ouyang Yu-Hui, Ding Yi, Li Jin, Zhang De-Shan, Zhang Luo

机构信息

Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Affiliated to the Capital University of Medical Science, Key Laboratory of Otorhinolaryngology Head and Neck Surgery, Ministry of Education (Capital University of Medical Science), Beijing Institute of Otorhinolaryngology, Beijing 100730, China.

出版信息

Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi. 2013 Jul;48(7):539-43.

PMID:24313200
Abstract

OBJECTIVE

To analyze the correlation between meteorological factors and onset of allergic rhinitis (AR), and to establish the prediction of AR epideminlogical trend.

METHODS

According to skin prick test (SPT) data of AR from Beijing Tongren Hospital and meteorological data of Beijing Observatory (2007 -2010) , analyzed the relationship between meteorological factors and onset in patients with AR. To analyze the probability distribution of onset in AR patients, and establish the grade of AR epideminlogical trend index. SPSS 16. O software was used to analyze the data.

RESULTS

The peak of onset in patients with AR appeared in 15 - 30 th August. There was significant correlation between the onset of AR patients and air temperature and vapor pressure(r = 0. 7473, F = 206. 13; r =0. 8465, F = 321. 04; all P < 0. 001) , and the peak of air temperature and vapor pressure were one month earlier than the peak of onset AR patients in 4 years. According to the above correlation, nonlinear prediction models of AR were established; used probability grading method, onset index of AR was divided into 4 grades.

CONCLUSION

Index grade forecast of AR onset has important guiding significance for AR diagnosis and prophylaxis, offers objective reference information for health departments.

摘要

目的

分析气象因素与变应性鼻炎(AR)发病的相关性,建立AR流行病学趋势预测。

方法

依据北京同仁医院AR皮肤点刺试验(SPT)数据及北京天文台气象数据(2007 - 2010年),分析气象因素与AR患者发病的关系。分析AR患者发病的概率分布,建立AR流行病学趋势指数分级。采用SPSS 16.0软件进行数据分析。

结果

AR患者发病高峰出现在8月15 - 30日。AR患者发病与气温、水汽压存在显著相关性(r = 0.7473,F = 206.13;r = 0.8465,F = 321.04;均P < 0.001),4年中气温和水汽压高峰比AR患者发病高峰早1个月。根据上述相关性,建立AR的非线性预测模型;采用概率分级法,将AR发病指数分为4级。

结论

AR发病指数分级预测对AR的诊断和防治具有重要指导意义,为卫生部门提供客观参考信息。

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