Citizens' mental health in interaction with housing price changes: Tehran, Iran

ABSTRACT
The present study aimed to investigate the relationship between housing prices and related quantitative indicators, including housing pattern, building density, and household density, with the mental health of citizens in District 18 of Tehran. The statistical population consisted of 180 households from urban neighborhoods of this district, whose levels of stress and depression were measured using the standardized Cohen Stress Questionnaire and Beck Depression Inventory, respectively. To analyze the spatial distribution of housing prices and quantitative housing variables, Hot Spot and Cold Spot models (Getis-Ord Gi*) and Moran’s I spatial autocorrelation index were applied in ArcGIS. Furthermore, modeling the variations in stress and depression based on housing indicators was conducted using stepwise linear regression in SPSS. The findings revealed a significant relationship between quantitative housing variables and mental health indicators, indicating that higher housing prices and density were associated with elevated levels of stress and depression. Qualitative analyses also highlighted the necessity of collaboration between urban planners and psychologists in managing the psychological consequences of housing. Finally, practical recommendations were proposed, including the development of affordable housing for low-income groups, reconsideration of density policies with a mental health-oriented approach, establishment of counseling centers in vulnerable neighborhoods, and the use of data-driven systems to monitor the psychological impacts of housing market fluctuations continuously.
Extended Abstract
Introduction
Urban society, with all its diversity, is full of issues and problems whose social roots seem more colorful and stronger than other dimensions. Many social harms are formed in cities and, due to population density, most of them remain hidden from view. Social problems of housing, environment, traffic, public health, employment, education, marginalization and informal settlements, divorce, addiction, murder, robbery, etc., are often major issues of urban life. Following the increasing growth of the urban population, creating housing, necessary facilities, and infrastructure, and increasing the quality of life for city residents are among the most important concerns of national and local governments. Therefore, due to economic inequalities and urban poverty, the weak and vulnerable segments of society face many problems in terms of housing and welfare. The housing issue mainly affects low-income and middle-income groups and classes. The history of studies related to affordable housing and mental health is quite long, but the documented and academic approach to this issue is not very old. According to the proposed enlightenment, the present study aims to investigate the extent to which housing prices affect residents' psychological well-being and assess the impact of housing on their mental health.
 
Methodology
The present study is applied in terms of purpose and descriptive-analytical method, and a combination of economic models, which has been conducted quantitatively. In this regard, the independent variables include various housing patterns (price of apartment and villa housing), building density, and household density in the residential unit, as well as depression and perceived stress, which are the dependent variables of the study. Data related to independent variables were obtained from the Ministry of Housing and Urban Development website and statistical blocks, as well as data related to dependent variables of the study using a questionnaire (Cohen and Beck). To examine the relationship between the research variables, a questionnaire with standard questions of Cohen's perceived stress and Beck's depression with a Likert scale or 4-point scoring scale was used.
 
Results and discussion
The results of the study indicate that the increase in prices (apartment and villa housing) and building density enhance stress and depression among residents of District 18 of Tehran, especially in eastern neighborhoods. One of the reasons for this is the social isolation in high-density apartment buildings, where public and open spaces often do not exist or are out of reach of residents. In these buildings, the sense of belonging, responsibility, participation, and social interactions are at a very low level. All of these issues increase social isolation and, as a result, stress and depression among residents of these buildings. Another quantitative housing indicator that has social and psychological dimensions is the density of households in residential units. This indicator is used to identify the share of each household in the number of rooms in residential units. An increase in the number of rooms available to each household indicates an improvement in the biological well-being of residents. Increased biological well-being leads to greater comfort and tranquility for residents and, as a result, reduces mental and psychological disorders. This is important because people spend a significant amount of time in their homes. The increase in households in residential units, combined with the low number of rooms, prevents people from having the solitude and peace necessary to work effectively.
 
Conclusion
The results of the Moran spatial autocorrelation model showed that the price of apartment and villa housing is the most important independent variable for the variables of depression and perceived stress, and follows a cluster pattern. In summary, it can be stated that all quantitative housing indicators examined in this article have a significant relationship with the depression and perceived stress indices. Also, the results of stepwise linear regression analysis for the depression index showed that two models can be proposed for changes in this index. In the first model, the price of apartment and villa housing is the only predictor that predicts 64.9% of the changes in depression. In addition, the second model can predict depression with 34.8%. Increasing housing prices and building density lead to greater crowding and higher prices.  Increasing building density and housing prices reduce social support. In fact, crowded environments and living in apartment housing reduce social interactions and activities. This increases psychological pressures such as depression and stress. On the other hand, household density in residential units, which is calculated based on the number of rooms in each unit, indicates the independence of individuals within residential units.
 
Funding
There is no funding support.
 
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
We are grateful to all the scientific consultants of this paper.