Department of Otolaryngology Head and Neck Surgery and department of Allergy, Beijing TongRen Hospital, Affiliated to the Capital University of Medical Science, Beijing, 100730, China.
Beijing Key Laboratory of Nasal Diseases, Beijing Institute of Otolaryngology, Beijing, 100005, China.
Sci Rep. 2017 Aug 30;7(1):10006. doi: 10.1038/s41598-017-10721-3.
Meteorological factors have been shown to affect the physiology, distribution, and amounts of inhaled allergens. The aim of this study was to develop a model to predict the trends for onset of allergic rhinitis (AR) patients. A total of 10,914 consecutive AR outpatients were assessed for the number of daily patient visits over a period of 4 years. Meteorological data were used to assess the relationship between meteorological factors and AR incidence by time-series data and regression analysis. Predictive models for incidence of AR were established in pollen-, dust mite- and mould-sensitive groups of patients, and the predictive performances of meteorological factors on the incidence of AR were estimated using root mean squared errors (RMSEs). The incidence of pollen-, dust mites- and mould-sensitive AR patients was significantly correlated with minimum temperature, vapour pressure, and sea-level pressure, respectively. The correlation between comprehensive meteorological parametric (CMP) and incidence of AR was higher than the correlation between the individual meteorological parameters and AR incidence. CMP had higher performance than individual meteorological parameters for predicting the incidence of AR patients. These findings suggest that the incidence of pollen-, dust mites- and mould-sensitive AR can be predicted employing models based on prevailing meteorological conditions.
气象因素已被证明会影响过敏原的吸入生理、分布和数量。本研究旨在建立一个预测变应性鼻炎（AR）患者发病趋势的模型。对 10914 例连续的 AR 门诊患者进行了为期 4 年的每日就诊次数评估。气象数据用于通过时间序列数据和回归分析评估气象因素与 AR 发生率之间的关系。在花粉、尘螨和霉菌敏感组患者中建立了 AR 发生率的预测模型，并使用均方根误差（RMSE）估计气象因素对 AR 发生率的预测性能。花粉、尘螨和霉菌敏感型 AR 患者的发病率与最低温度、蒸汽压和海平面气压分别呈显著相关。综合气象参数（CMP）与 AR 发生率的相关性高于个别气象参数与 AR 发生率的相关性。CMP 对预测 AR 患者发病率的表现优于个别气象参数。这些发现表明，可以利用基于当前气象条件的模型来预测花粉、尘螨和霉菌敏感型 AR 的发病率。
