ABSTRACT Against the dual backdrop of China's rapid urbanization and deep population aging, a profound mismatch has emerged between the physical environments of old urban neighborhoods and the growing aspirations of older adults for a better quality of life. Developing a scientific evaluation system for age‐friendly community environments has therefore become a task of both theoretical value and pressing practical significance. Using Guangzhou—a prototypical high‐density metropolis—as a case study, this research constructs and empirically validates an evaluation model for age‐friendly community environments, composed of four dimensions (“road systems,” “social spaces,” “landscape configuration,” and “public facilities”) and 26 specific indicators. Taking the Huaqiao Garden Community in Yuexiu District as an empirical case, the study employs questionnaire surveys and statistical analysis to yield three key findings. First, the community road system is the most critical predictor of overall satisfaction among older adults ( β = 0.294), exerting a significantly greater influence than “public facilities,” “social spaces,” or “landscape configuration.” This confirms that an accessible, safe, and continuous circulation environment constitutes the essential foundation for seniors’ autonomy within the community. Second, the study identifies strong heterogeneity in environmental needs across different elderly groups, highlighting the ineffectiveness of “one‐size‐fits‐all” construction models. Third, a pronounced “expectation–perception gap” is revealed: seniors’ expectations for age‐friendly community environments consistently exceed their actual experiences, particularly in terms of health and safety facilities. The study concludes that future age‐friendly community retrofitting must adopt a “road‐rights‐first” principle as its core philosophy, thereby promoting precise and differentiated renewal strategies. These findings not only provide empirical evidence from a major Chinese metropolis for environmental gerontology but also offer a rigorous decision‐making framework and practical guidance for urban managers seeking to optimize resource allocation and enhance the aging‐support capacity of older urban communities.
Li et al. (2025) studied this question.