Zhang De-Shan, Zhang Xuan, Ouyang Yu-Hui, Zhang Luo, Ma Shi-Lei, He Juan
Beijing Municipal Meteorological Observatory, Beijing, 100089, China.
School of Basic Medical Science, Beijing University of Chinese Medicine, Beijing, 100029, China.
Chin J Integr Med. 2016 Jun 21. doi: 10.1007/s11655-016-2588-9.
To analyze the correlations between the incidence of allergic rhinitis (AR) and meteorological variables of previous periods, so as to establish non-linear prediction equations of AR in Beijing area.
AR patients (10,478 cases) collected from Beijing Tongren Hospital during 2007-2010 and meteorological data (including daily average temperature, daily maximum temperature, daily minimum temperature, daily relative humidity, daily average vapor pressure, daily dew point temperature, daily precipitation, daily average wind speed, sea level pressure, and degree of comfort) collected from Beijing Municipal Meteorological Observatory in the same periods were used for the analysis. Non-linear correlation and regression were adopted to analyze the relationship between AR incidence and meteorological variables of former six-qi stage which was defined according to Yunqi theory of Chinese medicine. Comprehensive meteorological parameter was introduced to establish the predictive model.
The high incidence of AR appeared in the 4th qi stage (from the Beginning of Autumn to Autumn Equinox), while the changes of meteorological variables appeared in the 3rd qi stage (from Grain in Beard to Greater Heat), which advanced one phase. The incidence of AR was closely associated with vapor pressure. The correlation coeffifi cients of two predictive models were between 0.8931-0.9176 and all of them have passed signififi cant statistical tests, which showed a satisfactory fifi tting effect.
Comprehensive meteorological parameters can be used to forecast AR incidence, which is benefifi cial to AR prevention.
分析变应性鼻炎(AR)发病率与前期气象变量之间的相关性,以建立北京地区AR的非线性预测方程。
采用2007 - 2010年北京同仁医院收集的AR患者(10478例)以及同期北京市气象观测站收集的气象数据(包括日平均气温、日最高气温、日最低气温、日相对湿度、日平均水汽压、日露点温度、日降水量、日平均风速、海平面气压和舒适度)进行分析。采用非线性相关和回归分析AR发病率与根据中医运气理论定义的前六气阶段气象变量之间的关系。引入综合气象参数建立预测模型。
AR高发期出现在四之气阶段(立秋至秋分),而气象变量变化出现在三之气阶段(芒种至大暑),提前了一个阶段。AR发病率与水汽压密切相关。两个预测模型的相关系数在0.8931 - 0.9176之间,均通过了显著性统计检验,拟合效果良好。
综合气象参数可用于预测AR发病率,有利于AR的防治。