Short-term relation between air pollutants and hospitalizations for respiratory diseases: analysis by temporal association rules

This study investigates the relation between exposure to critical air pollution events with multipollutant (CO, PM₁₀, PM_2.5, NO₂, O₃, and SO₂) and hospitalizations for respiratory diseases in the metropolitan area of São Paulo (RMSP) and in the countryside and coastline, from 2017 to 2021. Data mining analysis by temporal association rules searched for frequent patterns of respiratory diseases and multipollutants associated with time intervals. In the results, pollutants PM₁₀, PM_2.5, and O₃ showed high concentration values in the three regions, SO₂ on the coast, and NO₂ in the RMSP. Seasonality was similar between pollutants and between cities and concentrations significantly higher in winter, except for O₃, which was present in warm seasons. Hospitalizations were recurrent during the transition from summer to colder periods. In approximately 35% of the total days with hospitalization greater than the annual average, one or more pollutants had a high concentration. The rules showed that PM_2.5, PM₁₀, and O₃ pollutants are strongly associated with increased hospitalizations in the RMSP (PM_2.5 and PM₁₀ with 38.5% support and 77% confidence) and in Campinas (PM_2.5 with 66.1% support and 94% confidence) and the pollutant O₃ with maximum support of 17.5%. On the coast, SO₂ was related to high hospitalizations (43.85% support and 80% confidence). The pollutants CO and NO₂ were not associated with the increase in hospitalizations. The ratio delay indicates the pollutants that were associated with hospitalizations, having concentration remained above the limit for three days, oscillating in smaller hospitalizations on the 1st day and again higher on the 2^nd and 3^rd days of delay, in a decreasing way. In conclusion, high pollutant exposure is significantly associated with daily hospitalization for respiratory problems. The cumulative effect of air pollutants increased hospitalization in the following days, in addition to identifying the pollutants and which pollutant combinations are most harmful to health in each region.