Can green spaces function as a mitigating factor for mental health during periods of policy transition?

The Shanghai Key Laboratory of Urban Design and Urban Science (LOUD) has, for the first time, employed a quasi-experimental approach to investigate the impact of green space accessibility on residents’ mental health during the transition period of COVID-19 containment policies. The study reveals that green spaces play a buffering role in supporting mental wellbeing during policy shifts. However, this effect exhibits a “moderate distance effect” as well as variability based on the visibility of greenery. This empirical evidence provides critical insights for urban planning and public health strategies in the post-pandemic era.

The study was conducted in collaboration with research teams led by Professor Longfeng Wu from Peking University, Professor Xuanyi NIE from the State University of New York at Buffalo, Professor Seung Kyum Kim from the Korea Advanced Institute of Science and Technology (KAIST), and Professor Yuhan Shao from Tongji University. The findings have been published in Cities, a leading journal in the field of urban planning, under the title: "Buffering effects of green space on residents' mental wellbeing: A regression discontinuity analysis during COVID containment policy shift."

Figure: Estimated effects based on a Regression Discontinuity Design (RDD), covering four dimensions of psychological outcomes: CES-D mental health scores, self-rated health (SRH), perceived wellbeing, and the frequency of negative emotional experiences.

During the COVID-19 pandemic, access to green space played a critical role in supporting mental health, particularly in urban areas under lockdown. However, research focusing on the transitional period—from strict containment measures to policy relaxation—remains limited. This period, while lifting mobility restrictions and allowing freer access to green spaces, also heightened infection risks, posing a dilemma for public health management.

This study employs a quasi-experimental method—Regression Discontinuity Design (RDD)—to examine the impact of COVID-19 policy shifts on mental health and green space exposure. Using a unique dataset (N = 2,545) from two major Chinese cities, Beijing and Shanghai, the study investigates differences in mental wellbeing during the transition period, based on varying levels of green space exposure among respondents.

Findings suggest that the policy shift did not lead to short-term improvements in mental health. Across multiple dimensions—including the CES-D depression scale, self-rated health (SRH), subjective wellbeing, and the frequency of negative emotions—no statistically significant enhancements were observed. Notably, the study identifies a “moderate distance effect”: residents living 400–1200 meters from parks experienced mental health benefits, whereas those in closer proximity (within 400 meters) did not show the expected positive effects. Additionally, visibility of green views from windows was associated with improved mental wellbeing, albeit with smaller effect sizes compared to physical proximity. These results underscore the buffering role of urban green spaces during major policy transitions and provide valuable empirical evidence for urban planning and public health strategies in the post-pandemic era.

Professor Longfeng Wu from Peking University remarked, “This study has taken more than two years to complete, undergoing multiple rounds of rigorous peer review and substantial revisions. From initial design to data collection and methodological refinement, every step has been a collaborative effort. In particular, the application of RDD required careful validation of the exogeneity of the policy shift, ensuring the robustness of our causal inference. Beyond revealing the nuanced relationship between green space and mental health, the study offers spatially precise recommendations for urban planners: proximity alone is not sufficient—optimal distance matters. We are grateful to our collaborators and to the reviewers and editors for their constructive feedback, which helped bring this research to fruition.”

Postdoctoral researcher Yichun Zhou from the LOUD Lab added, “This international collaborative project has been a valuable academic journey. From its inception in 2023 to its publication in 2025, the study went through several major revisions and extensive robustness checks. The biggest challenge was ensuring the validity of the RDD identification strategy in the unique context of a pandemic, and accurately capturing the causal effect of policy shocks on mental wellbeing. I’m deeply thankful for the guidance of Professors Wu, Nie, Kim, Shao, and Guan, and the research support provided by the LOUD Lab. This study deepened my understanding of urban green spaces as ‘health infrastructure.’ I hope our findings can inform evidence-based green space planning in high-density cities, and I look forward to continuing research in this field.”

Citation:
Wu, L., Zhou, Y., Nie, X., Kim, S. K., Shao, Y., & Guan, C.* (2025). Buffering effects of green space on residents’ mental wellbeing: A regression discontinuity analysis during COVID containment policy shift. Cities. https://doi.org/10.1016/j.cities.2025.105607