|
Abstract
|
The present study aims to fill the research gap in the research literature with the aim of investigating the relationship between housing price increases as an independent variable with housing pattern indicators, building density and household density, and mental health with depression and stress variables of citizens. The Beck and Cohen Depression Inventory was used to measure the data. In this regard, to analyze the spatial distribution of housing prices and independent and continuous variables, two models, Hot spot and Cold spot (Getis-OrdGi) and Moran's spatial autocorrelation model (I) were used in the ArcGIS software environment, and finally, the stepwise linear regression method was used to model changes in stress and depression based on quantitative housing indicators in the SPSS software environment. The results of quantitative and statistical analyses showed that independent variables or quantitative housing indicators have a significant relationship with mental health indicators, namely depression and stress. Qualitative analyses also indicate that the relationship between housing planning experts and psychologists should be strengthened more than ever before to control the negative impact of rising prices and building density on mental health indicators. Developing social programs to provide affordable and reliable housing, especially for low-income groups, can be considered as a comprehensive recommendation of the present study.
|