## 4 Results
The lowest values of the regression coefficient adjusted R\({}^{2}\) (within the statistically significant, i.e., with adjusted R\({}^{2}\)\(>\) 30%) are given in Madrid Barrio de Salamanca station, 32.7335%, in 2014 (Table A1); in Madrid Facultad de Farmacia, with value of 30.5163% (the lowest adjusted R\({}^{2}\) value in this study for allergic conjunctivitis), for the year 2015 (Table A2); in the Alcobendas area, with an adjusted R\({}^{2}\) value of 32.0685%, in the year 2016 (Table A3); and in Alcala de Henares, with a value of 33.3049% in the year 2017 (Table A4). 6. In most of the models calculated, there is an interrelation of the dependent variables with at least one of the pollen types under study and at least one of the atmospheric pollutants. Only in 10 of the 88 total regression calculations performed was one of the two types of independent variables not represented. In none of the cases were both types of explanatory variables missing simultaneously, thus invalidating the model. In 9 of the 10 cases cited, the atmospheric pollutants do not appear in the resulting equation, so only some of the pollen types maintain a relationship with the dependent variable. In 9 of the 10 cases in which there is only one type of independent variable in the equation, the dependent variable is allergic conjunctivitis. In the other case, it is allergic rhinitis. Among them, seven are models with adjusted R\({}^{2}\) value > 30%, all with the absence of air pollution variables, specifically for allergic conjunctivitis: in Leganes in 2014 (Table A1); in the stations of Alcobendas, Madrid Ayuntamiento, and Getafe in 2015 (Table A2); in the areas of Alcobendas and Coslada in 2017 (Table A4). For allergic rhinitis, there was an absence of air pollution variables only in the Las Rozas station in 2015 (Table A2). There were no cases in 2016. 7. In most models with adjusted R\({}^{2}\) > 30% (specifically in 63 of the 72), the presence of pollen types is greater than that of atmospheric pollutants. In only six of them are there more air pollutant concentration variables than pollen types. Moreover, only in three cases are both variables equal in number (Tables A1-A4). What has already been pointed out regarding the lack of meters for different pollutants in the sampling stations should be considered. For this reason, it is not surprising that, in general, there is a more significant presence of pollen-type variables in the calculated models and that, thus, there is a greater probability of interrelation of these variables with those of episodes of attention of the allergic pathologies under study. However, there is the circumstance of the existence of three exceptions, all of them with allergic conjunctivitis. Thus, for the Farolillo Air Quality station (corresponding to the Ayuntamiento de Madrid pollen station) in 2014, the model obtained contains four atmospheric pollutants and three types of pollen, despite the lack of PM\({}_{2.5}\) in the station above (Table A1). For the Alcala de Henares station, in 2016, the model obtained contained five atmospheric pollutants and three pollen types (a circumstance that also occurred in 2017, this time in the ratio of four versus two), despite the lack of PM\({}_{2.5}\) measurement (Tables A3 and A4, respectively). The presence of the different independent variables for the models obtained with adjusted R\({}^{2}\) > 30% is quantified in Tables 2 and 3.