Relationship between meteorological variability and pollen sensitization over the past 10 years.

BACKGROUND

Meteorological changes can influence the type and concentration of allergenic pollen in the atmosphere.

OBJECTIVE

This study aimed to investigate the relationship between the diversity of pollen sensitivity based on skin prick test (SPT) reactions and meteorological changes over the past 10 years in Konya, Türkiye.

METHODS

A total of 23,111 patients who underwent skin prick testing (SPT) between January 2015 and December 2024 were included in the study. Meteorological data, including temperature, sunlight exposure, relative humidity, rainfall, and wind speed, were obtained from the 8th Regional Directorate of Meteorology.

RESULTS

Our analysis revealed significant relationships between meteorological parameters and pollen sensitivity. Sunlight duration was positively correlated with sensitivity to tree pollen (r = 0.608, p < 0.001). Wind speed was positively correlated with sensitivity to tree pollen (r = 0.433, p = 0.002) but negatively correlated with sensitivity to Chenopodium (r = -0.353, p = 0.013). Humidity was positively correlated with sensitivity to weed and grass pollen (r = 0.367, p = 0.022; r = 0.305, p = 0.033) and negatively correlated with sensitivity to tree pollen (r = -0.605, p < 0.001). Temperature was positively correlated with sensitivity to Artemisia vulgaris (r = 0.317, p = 0.034) and negatively correlated with sensitivity to weed pollen (r = -0.734, p < 0.001). Rainfall was negatively correlated with sensitivity to grass pollen (r = -0.296, p = 0.039), tree pollen (r = -0.850, p < 0.001), and Chenopodium (r = -0.408, p = 0.004).

CONCLUSIONS

Our results revealed intricate interactions between pollen sensitivity and meteorological parameters. Notably, rainfall consistently exhibited a negative correlation with specific pollen types, suggesting a potential mitigating effect on pollen-related sensitization. These findings underscore the importance of considering meteorological variability in the management and prediction of allergic diseases.