Introduction

The significant increase in the elderly population is a key characteristic of the demographic outlook in contemporary societies (Yang & Yaman & Ismail, 2024:5). According to the World Population Prospects 2022 report, it is predicted that the global population will reach approximately 8.5 billion by 2030 and 9.7 billion by 2050. The rapid growth of the elderly population has become a global and social phenomenon (Jelokhani-Niaraki et al., 2019:2). In this context, the continuous increase in life expectancy, coupled with the decline in fertility rates, exacerbates global population aging (Van Hoof et al., 2018:1; DESA, 2022). Population aging is one of the most significant challenges of the 21st century, and the proportion of the elderly population is continuously rising in every country. For example, individuals aged 60 and above constituted 12.3% of the world’s population in 2017, and this percentage is projected to rise to over 22% by 2050 (United Nations, 2017). In other words, by 2050, nearly two billion people will be aged 60 and above. The aging trend in Iran has already begun, and if this trend continues, by 2031, between 25% and 30% of the population will be aged 50 and above, leading to an aging explosion in the country (Rezvani Khaledi & Pedram, 2019). In this regard, the proportion of elderly individuals aged 60 and above, currently around 7%, is expected to increase to 14% by 2036 and 22% by 2046 (Faraji Sabkbar & colleagues, 2019). In the city of Saqqez, the total population is 165,258, and the aging rate is 5.73%. This indicates that aging is a significant issue in this city, requiring attention and further investigation. Therefore, the aforementioned situation and its related processes are the primary focus of this research. The study aims to analyze the spatial distribution of the aging phenomenon in the neighborhoods of Saqqez. The research seeks to answer the following question: How is the spatial distribution of aging indicators manifested in the neighborhoods of Saqqez?
 

Methodology

The research method, in terms of nature and purpose, is applied. Regarding the data collection process, the level of supervision and control over the data is descriptive-analytical, using a survey method and case study (neighborhoods of Saqqez). The spatial data collection has been done through the 2016 census of population and housing, urban master and detailed plans, as well as research reports and plans. The research variables include aging indicators (aging ratio, dependency ratio, aging index, and old-age index), which are operationally defined in Table (2). For data analysis, the Moran's I spatial autocorrelation index is used to detect spatial patterns, and the Hot Spot method in Arc/GIS is applied for spatial clustering analysis.
 

Results

The status of aging indicators in the neighborhoods: The status of the elderly population in the neighborhoods of Saqqez city, based on the 2016 census, shows that the neighborhoods of this city have different statuses in terms of the aging population (Table 2). In this regard, the neighborhoods of Jame'eh Vejotiyaran, Saheli, Bazaar, and Hazrat Omar have the highest aging ratios, with 9.91%, 9.48%, and 9.33%, respectively. The Jame'eh Vejotiyaran neighborhood has the highest elderly dependency ratio at 13.86%, indicating the significant burden the elderly population places on the working population. The aging index also reflects the condition of the elderly's health and quality of life in each neighborhood. Jame'eh Vejotiyaran has the highest aging index at 53.33. The aging index reflects the number of elderly individuals compared to the total population of the neighborhood. Hazrat Omar neighborhood has the highest aging index at 10.29. The spatial patterns of aging indicators across the neighborhoods of Saqqez city were analyzed using Moran's I index to determine the spatial distribution pattern (dispersed, random, or clustered). The results, according to Table 3, showed that the aging ratio index (Moran's value = 0.192087, Z-value = 86.655391) follows a clustered pattern; the elderly dependency ratio index (Moran's value = 0.103852, Z-value = 50.189312) also follows a clustered pattern; the aging index (Moran's value = 0.141576, Z-value = 64.627469) follows a clustered pattern; and the aging index (Moran's value = 0.121444, Z-value = 58.154252) follows a clustered pattern. The results, according to Figure 5, showed that the clusters formed in the aging indicators in Saqqez city are primarily in the neighborhoods of Shafi'i, Hazrat Omar, Shahnaz, Saadi, Tepe Malan, Ustad Shirazi, Karimabad, Saheli, Bazaar, Jame'eh Vejotiyaran, Boulevard Enqelab, and Tamin Ejtemai.
 

Discussion

The aging population has become one of the significant challenges in the social, economic, and urban domains. The increasing proportion of elderly people in many countries, including Iran, necessitates special attention to the spatial analysis of this phenomenon at the neighborhood level. Analyzing the spatial patterns of the aging population in different neighborhoods of the city can provide valuable information for urban planners and policymakers. This information helps them design and implement more targeted actions to improve the living conditions of the elderly, based on a better understanding of the current situation in each neighborhood. The spatial analysis of the aging population phenomenon in Saqqez city reveals the geographical relationship between this challenging issue and the physical environment. Meaningful spatial patterns in the aging ratio indicate the influence of neighborhood-specific spatial and geographic factors on the distribution of the elderly population. The Moran spatial connections highlight special patterns in Saqqez, which not only help in identifying the vulnerabilities of the elderly population but also open opportunities for improvement and optimization.
 

Conclusion

The results from the spatial analysis play a crucial role in formulating urban policies and programs for managing the aging phenomenon in Saqqez city. These analyses not only reveal the issues and challenges present in the geographical distribution of the elderly population but also clearly highlight spatial discrepancies and different spatial patterns. Therefore, a thorough understanding of the role of geography in population aging is of paramount importance. Spatial analysis enables policymakers to devise solutions tailored to the needs and characteristics of each area. In other words, by avoiding uniform strategies and leveraging the unique spatial patterns and features of each region, the quality of life for the elderly can be enhanced throughout the city. Thus, urban policymakers must carefully consider spatial differences and implement comprehensive, targeted programs based on these analyses.
Extensive, multidimensional actions can have the most significant impact on improving the living conditions of the elderly in each neighborhood. As a result, these spatial differences should be seen as both opportunities and challenges in the path to improving the living standards of the elderly. Policies and programs should be updated based on this spatial understanding.
To achieve this, future research orientations in the field of aging populations can focus on key topics. These include the development and optimization of geographical models, examining the role of cultural and social factors in the spatial patterns of the elderly, creating integrated geographical standards, conducting comparative studies between urban and rural areas, designing spatially informed projects to enhance elderly health and quality of life, and assessing the effectiveness of modern technologies in addressing the needs of this demographic group. These research approaches can contribute to a deeper understanding and more effective management of the aging population phenomenon at the neighborhood level. This will enable policymakers and urban planners to design and implement targeted actions based on a more precise understanding of the spatial and environmental characteristics of each neighborhood. This, in turn, can improve the quality of life for the elderly across various neighborhoods of the city.
In conclusion, the following practical and actionable recommendations are proposed:

Implement constructive and social policies that emphasize the interactions between elderly and younger populations. This can help foster stronger social bonds and enhance the sense of local attachment among different generations.
Improve and increase access to healthcare and medical services in neighborhoods with high elderly populations. This will lead to better health and well-being for the elderly in these areas.
Create suitable green and recreational spaces for elderly activities in various neighborhoods. These spaces can help improve the physical and mental health of the elderly and enhance their social interactions.
Organize cultural and social programs based on the specific needs and interests of the elderly. These programs can improve the quality of life for the elderly and strengthen their local identity.
Provide opportunities for the active participation of the elderly in decision-making processes related to the city and local communities. This can empower the elderly and increase their role in local development. By implementing these recommendations across different neighborhoods of Saqqez city, significant improvements in the quality of life for the elderly can be achieved, leading to dynamic and sustainable elderly communities.

 
Acknowledgments
At the end, I would like to express my gratitude for the efforts of my advisor and consultant.