New Aging-in-Place Model with Spatial Analytical Framework to Evaluate Aging-in-Place Policy : Evidence from a City State of Singapore

The rising concern of aging has promoted aging-in-place (AIP) a popular public policy tool for creating elderly-friendly cities. This study utilizes Singapore’s urban regeneration practices as a case study to propose a new AIP model and introduce a novel spatial mismatch index (SMI) to evaluate the effectiveness of AIP policies. For the first time, we extend the gravity model from spatial network analysis to the context of aging and estimate accessibility to a comprehensive range of aging facilities. We then construct a spatial mismatch index to measure the extent of oversupply or shortage of aging facilities relative to senior population in the neighborhood. Comparing the Singapore AIP model to the US-San Francisco and Japan-Tokyo ones, it demonstrates advantages in terms of convenience and affordability for the seniors. However, there is a potential issue of spatial mismatch if urban planning is not optimized. Applying machine-learning algorithms to analyze 10,679 news articles, we highlight the importance of coordination among government agencies in implementing AIP policies. The Singapore’s AIP model, either in its entirety or as a hybrid with existing models, holds potential for generalization to other global cities