Background Grass pollen is the most prevalent sensitizing aeroallergen to cause respiratory allergies in northern China. Air pollutants have a substantial effect on respiratory health and some pollens. This study aimed to investigate relationships among airborne grass pollen, air pollutants and allergic diseases, in order to determine their effects on patients with grass pollen allergies in Beijing, China, during the period from 2013 to 2016. Methods Data regarding autumnal grass pollens and air pollutants measured in Beijing from 2012 to 2016 were obtained from local governmental agencies. Patient data regarding specific immunoglobulin E (IgE) analyses from 2013 to 2016 were obtained from the Department of Allergy in Beijing Tongren Hospital. Spearman's rank correlation analysis was used to assess associations between the daily number of grass pollen allergen–positive patients and the following parameters: 3 clinically‐relevant grass pollen genera (Artemisia, Humulus, and Chenopodium) and inhalable pollutants. Results Correlation analysis indicated that the daily number of grass pollen‐positive patients was significantly associated with the peak period of grass pollens, as well as pollutants SO2 and NOx. Moreover, concentrations of air pollutants (eg, ozone, oxides of nitrogen [NOx], and SO2) were consistently and significantly associated with concentrations of grass pollens; particulate matter 2.5 µm in diameter was negatively associated with Artemisia and Chenopodium pollens. Conclusion Grass pollens exhibited substantial impact on allergic disease morbidity. Air pollutants impacted allergic disease and grass pollen. Thus, public health and clinical approaches to anticipate and reduce allergic disease morbidity from pollen and pollutants are needed.
Background: Artemisia pollen is the most prevalent outdoor aeroallergen causing respiratory allergies in Beijing, China. Pollen allergen concentrations have a direct impact on the quality of life of those suffering from allergies. Artemisia pollen deposition grading predictions can provide early warning for the protection and treatment of patients as well as provide a scientific basis for allergen specific clinical immunotherapy.Objective: To develop a model of Artemisia pollen grading to predict development in patients with pollen allergy.Methods: Artemisia pollen data from four pollen monitoring stations in Beijing as well as the number of Artemisia pollen allergen serum specific immunoglobulin E positive cases in Beijing Tongren Hospital from 2014 to 2016 were used to develop a statistical model of pollen deposition and provide optimised threshold values. Results: A logarithmic correlation existed between the number of patients withArtemisia pollen allergy and Artemisia pollen deposition, and the average pollen deposition for three consecutive days was most correlated with the number of allergic patients. Based on the threshold of the number of patients and the characteristics of Artemisia pollen, a five-stage pollen deposition grading model was developed to predict the degree of pollen allergy.Conclusions: Graded prediction of pollen deposition may help pollen allergic populations benefit from preventive interventions before onset.
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