Multifaceted Evaluating Elderly Health Perceptions in Public Environments for Age-Friendly Urban Planning
Description
The global surge in elderly populations necessitates a reevaluation of urban spaces to cater to their unique needs. This research aims to understand how individual characteristics of the elderly influence their perceptions and interactions with urban open spaces, focusing on mental, social, and physical health aspects. It employs a hybrid approach combining Dynamic Grey Relational Analysis (DGRA) and GM(1,N) grey models with traditional regression analysis, offering a novel perspective in gerontological urban studies. Data were collected from elderly residents in Shiraz, Iran, through a structured questionnaire and analyzed to identify critical urban space criteria and their correlation with individual characteristics. The findings indicate that living arrangements, education, and physical activities like walking and exercising are key factors shaping the elderly's perceptions. Living with family and higher education levels emerged as significant enhancers of psychological restoration, ease of access, and connection with the natural environment, while also playing a role in reducing stress and anxiety and enhancing social supervision. The GM(1,N) model's predictive accuracy provides a reliable tool for urban planners and policymakers to understand and cater to the diverse needs of the elderly. This study contributes to the urban planning and gerontology fields by offering a comprehensive analysis method and insightful findings for designing inclusive urban spaces that improve the quality of life for the elderly.