Designing Aging-Friendly Urban Living Spaces: A GNN-Based Approach to Promote Psychological Well-Being and Physical Activity in Sports Contexts

Abstract

As urban populations age, designing living spaces in high-rise residential buildings requires addressing the unique physiological, psychological, and social needs of elderly residents. This study examines the suitability of urban living environments for aging populations, focusing on the interplay between aging-related factors and the potential of advanced computational methods to enhance design strategies. By leveraging graph neural network (GNN) technology, the research treats each housing unit as a graph node, constructing a large-scale network to evaluate and quantify the age-friendliness of living spaces. The results reveal that the proposed GNN-based model provides actionable insights, outperforming baseline methods in predictive accuracy and offering a robust framework for assessing and improving aging-friendly designs. From a sports psychology perspective, the study emphasizes the role of integrating recreational and communal spaces into urban living environments. These spaces not only support physical health through opportunities for exercise and s engagement but also promote psychological well-being and social interaction. The findings highlight the importance of creating environments that facilitate physical activity, community bonding, and emotional resilience among elderly residents. This research contributes to the development of sustainable urban spaces that foster holistic well-being, providing a blueprint for enhancing the quality of life through thoughtful integration of sports and recreation into aging-friendly designs.