Makra László, Matyasovszky István, Bálint Beatrix, Csépe Zoltán
Department of Climatology and Landscape Ecology, University of Szeged, POB 653, 6701, Szeged, Hungary,
Int J Biometeorol. 2014 Jul;58(5):753-68. doi: 10.1007/s00484-013-0656-9. Epub 2013 Apr 5.
The effect of biological (pollen) and chemical air pollutants on respiratory hospital admissions for the Szeged region in Southern Hungary is analysed. A 9-year (1999-2007) database includes--besides daily number of respiratory hospital admissions--daily mean concentrations of CO, PM10, NO, NO2, O3 and SO2. Two pollen variables (Ambrosia and total pollen excluding Ambrosia) are also included. The analysis was performed for patients with chronic respiratory complaints (allergic rhinitis or asthma bronchiale) for two age categories (adults and the elderly) of males and females. Factor analysis was performed to clarify the relative importance of the pollutant variables affecting respiratory complaints. Using selected low and high quantiles corresponding to probability distributions of respiratory hospital admissions, averages of two data sets of each air pollutant variable were evaluated. Elements of these data sets were chosen according to whether actual daily patient numbers were below or above their quantile value. A nonparametric regression technique was applied to discriminate between extreme and non-extreme numbers of respiratory admissions using pollen and chemical pollutants as explanatory variables. The strongest correlations between extreme patient numbers and pollutants can be observed during the pollen season of Ambrosia, while the pollen-free period exhibits the weakest relationships. The elderly group with asthma bronchiale is characterised by lower correlations between extreme patient numbers and pollutants compared to adults and allergic rhinitis, respectively. The ratio of the number of correct decisions on the exceedance of a quantile resulted in similar conclusions as those obtained by using multiple correlations.
分析了生物（花粉）和化学空气污染物对匈牙利南部塞格德地区呼吸道疾病住院人数的影响。一个9年（1999 - 2007年）的数据库除了包含呼吸道疾病每日住院人数外，还包括一氧化碳（CO）、可吸入颗粒物（PM10）、一氧化氮（NO）、二氧化氮（NO2）、臭氧（O3）和二氧化硫（SO2）的日平均浓度。还纳入了两个花粉变量（豚草花粉和不包括豚草花粉的总花粉量）。针对患有慢性呼吸道疾病（过敏性鼻炎或支气管哮喘）的男性和女性两个年龄组（成年人和老年人）进行了分析。进行因子分析以阐明影响呼吸道疾病的污染物变量的相对重要性。利用对应于呼吸道疾病住院人数概率分布的选定低、高分位数，对每个空气污染物变量的两个数据集的平均值进行了评估。这些数据集的元素根据实际每日患者人数是低于还是高于其分位数值来选择。应用非参数回归技术，以花粉和化学污染物作为解释变量，区分呼吸道疾病住院人数的极端值和非极端值。在豚草花粉季节，可以观察到极端患者人数与污染物之间的最强相关性，而无花粉期的相关性最弱。与成年人和过敏性鼻炎患者相比，患有支气管哮喘的老年组极端患者人数与污染物之间的相关性较低。关于分位数超标正确决策数量的比例得出了与使用多重相关性得出的结论相似的结论。
