Meta-analysis reveals how socio-economic factors influence urban green space attributes, suggesting implications for urban planning.
Urban green space (UGS) with multidimensional attributes provides crucial ecosystem services and public health benefits. However, there is no systemic knowledge on how these diverse UGS attributes meet needs with different socio-economic and demographic characteristics. This study conducts a meta-analysis of the existing UGS case studies from the Web of Science database to reveal the knowledge breadth, depth and applicability for future research and practice in UGS. We evaluated how 75 socio-economic and demographic indicators shape 73 UGS indicators across 48 global case studies using a combination of relational analysis, meta-analytical effect and spatiotemporal distribution. The relation analysis reveals significant imbalances of UGS knowledge across attributes (Accessibility, security and amenities) and users’ characteristics (e.g., age), the meta-analytical effect size analysis indicates that many associations have not yet received consistent and conclusive empirical support for direct application to UGS planning and design, and the spatiotemporal analysis indicates that the concentration of the sampled studies in China and the United States further constrains the external applicability of the synthesized evidence. These findings recognize the multidimensional nature of UGS and the need for context-sensitive consideration and highlight the urgency of developing a unified assessment framework to improve knowledge discovery and applicability in UGS planning for urban sustainability.
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Zheng et al. (2026) studied this question.
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