عنوان مقاله [English]
Dust is one of the most important environmental events that can dramatically affect and destroy living areas of a region. The environmental problems of dust can cause many health diseases for many people especially those with background records. The purpose of this study was to investigate the long-term trends in dust events and to investigate the effects of these events in the city of Ilam on the record of respiratory diseases.
Materials and methods
In this regard, data of recorded events of dusty days during the 1995-2015 statistical periods was taken from two synoptic stations in Ilam and Dehloran. The relationship between time series of dust events could be detected throughout the day as TDE (Total Dust Event). Using TDE, the total dust storms, including local and overflow and sandstorms and light to medium dust, are used in this research. Fitting a linear model at a confidence level of 0.95 (P_value = 0.05), the process of this time series was analyzed. The annual registration of pulmonary and respiratory diseases was obtained from male and female patients of Shahid Mostafa Khomeini Hospital in Ilam during the statistical period of 1380-1384. In order to reveal the relationship between the time series of the diseases, two methods of Pearson correlation of matrix at confidence level of 0.95 (P_value = 0.05) and linear model is used at confidence level.
Results and discussion
The results of this study showed that the increase of dust records in Ilam and Dehloran stations was 0.8 and 0.96 records per year, respectively. Correlation matrix indicates that at the confidence level, a significant direct correlation was found between the annual number of patients with pulmonary and perfused patients registered in Shahid Mostafa Khomeini Hospital. In spite of the fact that the number of records in the two stations in Ilam and Dehloran, a record of the respiratory examination was significantly higher than other stations. The models based on the relationship between the number of male patient admissions and the events recorded in the two waves of two synoptic stations in Ilam and Dehloran indicate that these two models, respectively, verified 0.79 and 0.69, of the variability of the time series of client hospital records. In the case of the women with pulmonary and respiratory diseases, the model has been fitted with dust in Ilam and Dehloran stations. This showed that these models could define 0.70 and 0.83 of the number of female patients.
The correlation matrix indicated that at the confidence level, a significant direct relationship was established between these two time series so that the number of annual records of patients with respiratory diseases recorded in Shaheed Mostafa Khomeini Hospital in Ilam during the period. This had a higher number of dusty days recorded in the two stations in Ilam and Dehloran. The correlation matrix indicated that only the direction and severity of the relationship were used to quantify this association. The proposed model can be meaningfully able to model the association between dust events (as independent variables) and the records of patients with respiratory diseases, as a dependent variable. there were a positive correlation between the number of refers of the people to the hospitl and the number of dust events in the city. For the total population of patients with pulmonary and respiratory diseases (without attention), the model was also fitted according to the number of days with dust in Ilam and Dehloran stations. This showed that these models were 0.67 and 0.83 for the two Ilam and Dehloran stations, respectively. Comparing the results of this study with other researches revealed that the results obtained in Ilam are in agreement with the results of other researchers in Kermanshah and Ahwaz.