Asthma Exacerbations, Meteorological Variables, and Multipollutant Concentrations: Uncovering Short-term Patterns Through Association Rule Mining

Abstract

.

Asthma is a major global health issue, affecting millions of people and contributing significantly to disability-adjusted life years. This study investigates the short-term impacts of outdoor multi-pollutant mixture, pollen, and climate conditions on asthma exacerbations by identifying specific interval concentrations of pollutants that may increase asthma risk. Using a time-stratified case-crossover design combined with Association Rule Mining, a data mining technique, we analyzed data from adult patients who visited the emergency departments in 2019 and 2022 of La Paz University Hospital and Ramón y Cajal University Hospital in Madrid, Spain, and the data on PM10, PM2.5, O3, NO2, NO and SO2 from 52 monitoring stations. Our findings revealed that specific pollutant concentrations, such as ozone (O3; 65.3–100 μg/m3) and PM10 (45–50 μg/m3), significantly increased asthma exacerbation risk. These exposures occurred simultaneously or with a time lag of up to three days. Notably, interactions between pollutants, such as O3 and PM2.5 or PM2.5 and pollen, were strongly associated with asthma exacerbations, even when individual pollutant concentrations remained below WHO safety guidelines. Relative risks for these combinations ranged from 1.12 to 1.23, suggesting a cumulative effect. These results underscore the importance of considering pollutant interactions and their time-lagged effects in understanding asthma risks, rather than evaluating pollutants in isolation. Our findings provide mechanistic evidence that future air quality warning systems should account for multi-pollutant exposure patterns, particularly to protect vulnerable populations during critical exposure windows.