The Analysis of Dust Storm Trend and the Impact on Public Health in Ilam Province

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Extended abstract
Introduction
Dust is one of the most important environmental events that can dramatically affect and destroy its living areas. 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 on recorded events of dusty days during the 1995-2015 statistical periods was taken for 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), in which total dust storms (including local and overflow and sandstorms and light to medium dust) are used in this research. With the fitting of a linear model at a confidence level of 0.95 (P_value = 0.05), the process of this time series was analyzed. In order to reveal the relationship between the time series of the annual registration of pulmonary and respiratory diseases, which were obtained from male and female patients of Shahid Mostafa Khomeini Hospital in Ilam during the statistical period of 1380-1384, 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 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 Ilam and the occurrence of a recession. In spite of the fact that in the years when the number of records of the higher gathering was recorded at two stations in Ilam and Dehloran, a record of the respiratory examination was significantly higher. Also, 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, respectively, of the variability of the time series of client hospital records. In the case of women with pulmonary and respiratory diseases, the model has been fitted, which according to the number of days with dust in Ilam and Dehloran stations showed that these models could define 0.70 and 0.83 of the number of female patients.
Conclusion
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 years Which had a higher number of dusty days recorded at two stations in Ilam and Dehloran, was significantly higher. The correlation matrix indicated only the direction and severity of the relationship, so that linear regression models were used to quantify this association and to be aware of the susceptibility function of the records of patients with pulmonary and respiratory diseases. The proposed model can be meaningfully and cognitively able to model the association between dust events (as independent variables) and the records of patients with respiratory diseases (as a dependent variable). A model for recording the number of female patient records during the period 2000-2014 based on the number of dusts recorded at Ilam station has been able to justify 0.62 times of the time records of women referring women in Shaheed Mostafa Khomeini Hospital, while The number of recorded events of the Dehloran Synoptic Station, based on the fitted model, has been able to justify about 0.58 of these changes. The fitted models on the relationship between the number of records of hospital male patients and the recorded dust events of two synoptic stations in Ilam and Dehloran showed that these two models were 0.79 and 0.69, respectively, of the variability of the time series of the records of male patient clients To explain. 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, which showed that these models also were 0.67 and 0.83 Describe the records of patients referring. Finally, comparing the results of this study with other researches, it was found that the results obtained in Ilam are in agreement with the results of other researchers in Kermanshah and Ahwaz.
Language:
Persian
Published:
Physical Geography Research Quarterly, Volume:51 Issue: 107, 2019
Pages:
123 to 134
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