Document Type : Original Article
Authors
1
PhD student in geography and urban planning, faculty of social sciences, university of mohaghegh ardabili, ardabil,iran
2
Professor in the department of geography and urban and rural planning, faculty of social sciences, university of mohaghegh ardabili, ardabil,iran
10.22034/gahr.2024.457726.2132
Abstract
Disability as a social phenomenon has always existed throughout history, which is caused by natural events, wars, traffic accidents genetic problems, etc. In the era of rapid urbanization, this issue has become more apparent due to the problems in cities, especially in third world cities.
this study, using documentary method, seeks to analyze the distribution of disabled people in the city of Ardabil, and for this purpose, it has used spatial statistics tools in GIS. The statistical population of the research is 6586 people with disabilities who receive services from the welfare centers. The results showed that 4302 people with 65.32% of the population are men and 2284 with 34.68% are women. Also, the districts 4 and 5 of the municipality have the highest number of disabled people with 18.94 and 13.57,respectively. Physically disabled with 41.86%, mentally with 24.59% respectively have the largest numbers. In terms of severity of disability, more than 41% have severe disability and 16% are classified as very severe. Spatial cluster analysis of multi-distance, nearest neighborhood and Moran with p-value 0.00 shows the cluster distribution of disabled people in the city of Ardabil, and the analysis of hot spots shows the concentration of disabled people in the Northwest area of the city, which is one of the peripheral areas of the city. In order to find the relationship between the population size and its effect on the high number of disabled people in the localities, we used geographic weighted regression and the result, considering the ratio of disabled people to the population in the localities, indicates that there is no significant relationship between the two components and it can be caused by other factors such as poverty; the spatial autocorrelation analysis shows that the fourth region neighborhoods (poor neighborhoods) are located in the HH cluster.
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