INVESTIGATING THE RELATION BETWEEN PREVALENCE OF ASTHMATIC ALLERGY WITH THE CHARACTERISTICS OF THE ENVIRONMENT USING ASSOCIATION RULE MINING

The prevalence of allergic diseases has highly increased in recent decades due to contamination of the environment with the allergy stimuli. A common treat is identifying the allergy stimulus and, then, avoiding the patient to be exposed with it. There are, however, many unknown allergic diseases stimuli that are related to the characteristics of the living environment. In this paper, we focus on the effect of air pollution on asthmatic allergies and investigate the association between prevalence of such allergies with those characteristics of the environment that may affect the air pollution. For this, spatial association rule mining has been deployed to mine the association between spatial distribution of allergy prevalence and the air pollution parameters such as CO, SO₂, NO₂, PM₁₀, PM_2.5, and O₃ (compiled by the air pollution monitoring stations) as well as living distance to parks and roads. The results for the case study (i.e., Tehran metropolitan area) indicates that distance to parks and roads as well as CO, NO₂, PM₁₀, and PM_2.5 is related to the allergy prevalence in December (the most polluted month of the year in Tehran), while SO₂ and O₃ have no effect on that