Paper Information

Journal:   JOURNAL OF HEALTH AND CARE   FALL 2017 , Volume 19 , Number 3 #E0024; Page(s) 168 To 181.
 
Paper: 

SPATIAL STATISTICS APPLICATION IN COMPARATIVE STUDY OF ARDABIL PROVINCE COUNTIES STATUS IN THE BASIS OF HOSPITALIZATION RATE DUE TO CORONARY DISEASE

 
 
Author(s):  GAMISSI J., HOSEINIAN A., MASUMI M.T.*
 
* DEPARTMENT OF GEOGRAPHY, ARDABIL BRANCH, ISLAMIC AZAD UNIVERSITY, ARDABIL, IRAN
 
Abstract: 

Background and aim: Coronary artery disease (CAD) increased due to lifestyle changes.
Awareness of health status and distribution of disease have major role in the health planning.
This study aimed to determine hospitalization rate due to coronary artery disease in Ardabil Province by GIS.
Methods: This cross-sectional study was performed by using the data belonging to 60156 patients with history of admission in the hospital due to CAD in Ardabil Province over the years 2010-2015. Hospitalization Rate (HR) was calculated after classification of the data in terms of location and date of hospitalization. Data were analyzed by descriptive statistics, ANOVA and repeated measure in SPSS v23. Then centralization of disease in the province was studied by Spatial Autocorrelation Analysis.
Results: The pattern of disease distribution was indicated the random distribution in Ardabil province. In cluster and outlier analysis was observed outlier in Khalkhal and Kosar city, that was indicated the hospitalization rate in the Khalkhal city was higher than the surrounding cities and in the city of Kosar was lower than the surrounding cities.
In Hot Spots analysis was observed cold spot in the cities of Ardebil and Nir that was showed a low distribution of disease in comparison with other cities of the province.
Conclusion: The results of this study showed that in spite of the randomized distribution of coronary artery disease in Ardabil province, this disease is more prevalent in Khalkhal city.
Identification of high risk areas, spatial clustering and determination of hot and cold spots will help to clarify the spatial aspects of internal and external correlations of cardiovascular disease and to assess and control the risk factors of space and screening. This is effective in planning health policies and implementing health services and identifying priority areas for disease prevention.

 
Keyword(s): CORONARY ARTERY DISEASE, SPATIAL STATISTICS, SPATIAL AUTOCORRELATION, GIS, ARDABIL
 
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