Spatial Patterns of Multiple Deprivation and Their Association with Distance from the Provincial Capital: A case study of East Azerbaijan

Document Type : Research Paper

Authors

1 Department of Regional Planning, Faculty of Urban Planning, University of Tehran, Tehran, Iran

2 Department of Landscape Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

Abstract

A B S T R A C T
The unbalanced concentration of development opportunities plays an essential role in shaping patterns of regional deprivation. However, the impact of spatial distance on various dimensions of deprivation has not been distinctly examined. This research aims to analyze the relationship between distance from the provincial capital and various dimensions of multiple deprivation at the city level in East Azerbaijan Province (2016), utilizing indicators derived from international literature. Therefore, Exploratory Factor Analysis was primarily employed to extract the dimensions of deprivation and calculate factor scores for each city. The variance explained for each dimension reached acceptable levels (0.5–0.7), while KMO values confirmed the interpretability of the model, resulting in standardized factor scores for each city. Subsequently, a Simple Linear Regression model was utilized to investigate the relationship between spatial distance and each deprivation dimension. Additionally, Moran’s I test was applied to assess spatial autocorrelation within the data. Regression results varied across dimensions, with the coefficient of determination (R2) ranging from 0.05 to 0.65. The results indicate that spatial distance exerts a positive and significant influence on deprivation in employment, education, and housing. Conversely, the relationship between distance and health deprivation was weak, and no significant relationship was observed for access-related deprivation. These findings suggest that the impact of spatial distance on deprivation is non-uniform, as not all dimensions are equally affected by spatial positioning. This study provides a more nuanced understanding of the spatial mechanisms underlying regional inequality.
 
Extended Abstract
Introduction
Spatial inequality, as one of the fundamental issues of regional development, has attracted extensive attention in recent years, because significant differences has delineated in the level of development among various regions. These spatial inequalities have devitalized the development and resilience capacities of disadvantage districts and intensified regional gaps by restricting access to basic services such as education, health care, infrastructure, and economic opportunities. Thus, spatial deprivation and unbalanced concentration of development opportunities play a vital role in shaping patterns of regional deprivations. The spatial situation of the regions and their distance from the chief centers of economic activities, in the meantime, has been brought up as one of the potential factors affecting deprivation. However, the effect of spatial distance on different dimensions of deprivation has not been investigated equally. The purpose of this study is to analyze the relationship between the distance from the center of the province and the diverse dimensions of multiple deprivation in the cities of East Azerbaijan province by using indicators extracted from the world literature in 2016. The discrepancy between advantage and disadvantage districts is obvious in the province. Tabriz, as the hub of population and economic activities, has attracted an immense share of infrastructure and investments that increased the gap between the center and the periphery.
 
Methodology
In this regard, using exploratory factor analysis method, initially, various dimensions of deprivation including employment, education, housing, healthcare and accessibility extracted and factor score of each city calculated. It should be noted that the normality of the data has been examined to initiate factor analysis in each dimension. Factor analysis, according to the existing literature, has been conducted considering the non-normality of 20 percent of the data. The percentage of variance has been obtained for each of the appropriate and acceptable dimensions (0.5-0.7) and on the other hand, the appropriate values of KMO, modeled interpretability and standardized factor scores have been calculated for each city. These scores are normalized between 0 and 1 to enable the comparability between the index and the various dimensions. Meanwhile, the spatial distribution maps of these factor privileges have been prepared to spot the geographical location of different dimensions of deprivation. A simple linear regression model has been use in order to investigate the relationship between the spatial distance and each of the dimensions of deprivation. Moran's I test has also used to measure spatial autocorrelation in data. The calculated value of (R-Score) is 2.59, which indicates a confidence level of 99 percent. The obtained values from the regression results were unique for each dimension, so that the determine coefficients numbers (R) were in the range (0.05-0.65). For example, healthcare deprivation with R² of 0.070 has a weak relationship and accessibility deprivation has a non-significant relationship with distance and correlation.
 
Results and Discussion
This result demonstrated that spatial distance, although an essential factor, is not able to explain all the dimensions of deprivation alone. Autocorrelation could be described with Watson's camera test. These values vary in different dimensions. The presence of spatial autocorrelation in the accessibility dimension with the Watson camera value of 0.859 means that the values of this index in neighboring cities are not independent and have a dependent spatial pattern; In such circumstances, the assumption of independence of observations in the linear regression model is violated and, as a result, estimating the coefficients and statistical significance may be associated with error. The results indicated, on the other hand, that the spatial distance has a positive and significant effect on the deprivations of employment, education and housing, so that with increasing the distance from the provincial center, the level of these deprivations increases. In contrast, the relationship between distance and healthcare deprivation was weak and no significant relationship was observed for accessibility deprivation.
 
Conclusion
The results illustrated that the center-peripheral model does not work the same in all aspects of development, but is more prominent in economic and production sects such as employment and housing. Second, the findings indicated that some dimensions of deprivation, particularly healthcare and accessibility, are not necessarily subject to spatial distance. This outcome does not necessarily confirm other conducted studies that have introduced distance as a dominant factor in the formation of regional inequalities. Consequently, the effect of spatial distance on deprivation has a multidimensional and non-uniform nature and not all dimensions of deprivation are equally affected by the spatial position. These results paved the way to prioritize the intervention for cities with inferior conditions. This study introduced a more precise understanding of the spatial mechanisms of regional inequality by providing a separate analysis of the dimensions of deprivation, which could be a basis for targeted policy-making in reducing regional inequalities.
Keywords: Multiple Deprivation, Spatial Inequality, Spatial Distance, Factor Analysis, Linear Regression.
 
Funding
There is no funding support.
 
Authors’ Contribution
(First author) worked and contributed to the introduction, theoretical foundations, data collection, and methodology sections. The second author also collaborated and contributed to the analysis of results, discussion, and conclusion sections.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
We are grateful to all the scientific consultants of this paper.

Keywords

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Journal of Geography and Spatial Development
Volume 2, Issue 3
November 2025
Pages 33-49

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