ArticleBMC public health2025
Exploring the complex associations between community public spaces and healthy aging: an explainable analysis using catboost and SHAP.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Development and validation of an interpretable predictive model for short-term rebleeding after endoscopic hemostasis in peptic ulcer: a retrospective single-center cohort study.Surgical endoscopy · 2026Article
- Machine Learning-Identified Potential Interaction Between Clazosentan and Nicardipine in Patients with Subarachnoid Hemorrhage.Journal of clinical medicine · 2026Article
- What neighbourhood factors support more transport walking as adults age? A five-wave longitudinal multilevel cohort study in Brisbane, Australia.BMJ public health · 2026Article
- Predictors of Unfavorable Outcomes in Diabetic Foot Ulcers.Diagnostics (Basel, Switzerland) · 2025Article
- A machine learning algorithm to predict treatment effectiveness for Kawasaki disease in China: a retrospective model development and validation study.Frontiers in immunology · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundAs global aging accelerates, community public spaces (CPS) are increasingly recognized as vital for promoting healthy aging. However, existing research often employs linear analytical methods or focuses on single health dimensions, overlooking how CPS features are non-linearly and interactively related to multiple aspects of elderly well-being.
methodsThis study analyzed data from 2,508 older adults in Shanghai to examine the associations between 13 CPS environmental features and physical, mental, and social health. An explainable machine learning approach, incorporating CatBoost and SHAP, was used to identify key correlates and patterns of interaction among features.
resultsDestination accessibility, public transport, residential density, and walking infrastructure were positively associated with all health dimensions, while traffic complexity and crime rate showed consistent negative associations. SHAP interaction analysis revealed that health benefits often emerge from synergistic combinations of features, rather than from the effects of individual features in isolation.
conclusionsThis study provides new insights into the multidimensional and non-linear relationships between CPS features and elderly health. The findings offer empirical evidence to guide community planning and intervention strategies that foster health-supportive environments for aging populations.
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