Can AI and Urban Design Optimization Mitigate Cardiovascular Risks Amid Rapid Urbanization? Unveiling the Impact of Environmental Stressors on Health Resilience
Mehdi Makvandi,
Zeinab Khodabakhshi,
Yige Liu,
Wenjing Li and
Philip F. Yuan ()
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Mehdi Makvandi: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Zeinab Khodabakhshi: College of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China
Yige Liu: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Wenjing Li: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Philip F. Yuan: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Sustainability, 2025, vol. 17, issue 15, 1-42
Abstract:
In rapidly urbanizing environments, environmental stressors—such as air pollution, noise, heat, and green space depletion—substantially exacerbate public health burdens, contributing to the global rise of non-communicable diseases, particularly hypertension, cardiovascular disorders, and mental health conditions. Despite expanding research on green spaces and health (+76.9%, 2019–2025) and optimization and algorithmic approaches (+63.7%), the compounded and synergistic impacts of these stressors remain inadequately explored or addressed within current urban planning frameworks. This study presents a Mixed Methods Systematic Review (MMSR) to investigate the potential of AI-driven urban design optimizations in mitigating these multi-scalar environmental health risks. Specifically, it explores the complex interactions between urbanization, traffic-related pollutants, green infrastructure, and architectural intelligence, identifying critical gaps in the integration of computational optimization with nature-based solutions (NBS). To empirically substantiate these theoretical insights, this study draws on longitudinal 24 h dynamic blood pressure (BP) monitoring (3–9 months), revealing that chronic exposure to environmental noise (mean 79.84 dB) increases cardiovascular risk by approximately 1.8-fold. BP data (average 132/76 mmHg), along with observed hypertensive spikes (systolic > 172 mmHg, diastolic ≤ 101 mmHg), underscore the inadequacy of current urban design strategies in mitigating health risks. Based on these findings, this paper advocates for the integration of AI-driven approaches to optimize urban environments, offering actionable recommendations for developing adaptive, human-centric, and health-responsive urban planning frameworks that enhance resilience and public health in the face of accelerating urbanization.
Keywords: urbanization; environmental stressors; AI-based optimization; cardiovascular risks; urban health resilience (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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