Background and objectives: Many studies have been carried out on the negative health effects of exposure to PM10, PM 2.5, NO2, CO, SO2 and B[a]P for small populations. The main purpose of this study was to explore the association of air pollution to diagnosis of asthma for the whole huge population of school children between 7-17 years in Vilnius (Lithuania) using geographical information system analysis tools. Material and Methods: In the research, a child population of 51,235 individuals was involved. From this large database, we identified children who had asthma diagnosis J45 (ICD-10 AM). Residential pollution concentrations and proximity to roads and green spaces were obtained using the ArcGIS spatial analysis tool from simulated air pollution maps. Multiple stepwise logistic regression was used to explore the relation between air pollution concentration and proximity between the roads and green spaces where children with asthma were living. Further, we explored the interaction between variables. Results: From 51,235 school children aged 7-17 years, 3065 children had asthma in 2017. We investigated significant associations, such as the likelihood of getting sick with age (odds ratio (OR) = 0.949, p < 0.001), gender (OR = 1.357, p = 0.003), NO2 (OR = 1.013, p = 0.019), distance from the green spaces (OR = 1.327, p = 0.013) and interactions of age × gender (OR = 1.024, p = 0.051). The influence of gender on disease is partly explained by different age dependency slopes for boys and girls. Conclusions: According to our results, younger children are more likely to get sick, more cases appended on the lowest age group from 7 to 10 years (almost half cases (49.2%)) and asthma was respectively nearly twice more common in boys (64.1%) than in girls (35.9%). The risk of asthma is related to a higher concentration of NO2 and residence proximity to green spaces.
Keywords: GIS; air pollution; asthma; children; logistic regression; residential exposure.