Exploring non-linear built environment effects on urban vibrancy under COVID-19: The case of Hong Kong.

The coronavirus disease (COVID-19) pandemic has enormously changed the way people perceive and use urban spaces, exacerbating some pre-existing issues including urban vibrancy decline. This study aims to explore built environment effects on urban vibrancy under COVID-19, which will help recalibrate planning models and design principles. Based on multi-source geo-tagged big data of Hong Kong, this study reveals variations in urban vibrancy and employs machine learning modeling and interpretation methods to examine built environment effects on urban vibrancy before, during, and after the outbreak of COVID-19, with review volume of restaurants & food retailers as the indicator for urban vibrancy and built environment depicted from five dimensions (i.e., building form, street accessibility, public transport accessibility, functional density, and functional mixture). We found that (1) urban vibrancy concussively decreased during the outbreak and slowly recovered afterwards; (2) built environment's capability to stimulate urban vibrancy was weakened during the outbreak and restored afterwards; (3) the relationships between built environment and urban vibrancy were non-linear and moderated by the pandemic. This research enriches our understandings of the role of the pandemic in influencing urban vibrancy and its correlation with built environment, enlightening decision makers with nuanced criteria for pandemic-adaptive urban planning and design.

Perceived Neighborhood Environment Impacts on Health Behavior, Multi-Dimensional Health, and Life Satisfaction.

The impacts of perceived neighborhood environment on adults' health and life satisfaction have drawn increasing academic attention. However, previous studies usually examine multi-dimensional (physical, mental, and perceived) health and life satisfaction separately, and few studies dealt with them simultaneously. Moreover, limited research revealed the mechanisms behind the effects of perceived neighborhood environment on health and life satisfaction, as well as how such effects are moderated by socio-demographics. Therefore, employing the 2016 China Family Panel Study Dataset and using structural equation modeling, this study delves into the complicated relationships among perceived neighborhood environment, health behavior, health outcomes (i.e., body mass index, self-rated health status, and depression), and life satisfaction. Notably, it considers mediation and moderation simultaneously. It finds: (1) Better perceived neighborhood environment significantly promotes physical activity and reduces sedentary behavior, smoking, and drinking; (2) Health behavior fully mediates the effects of perceived neighborhood environment on health; (3) Perceived neighborhood environment significantly affects life satisfaction both directly and indirectly (through health behavior and health outcomes); (4) Socio-demographics moderate the above relationships. This study disentangles the complicated impacts of perceived neighborhood environment on adults' multi-dimensional health and life satisfaction, thus providing policy makers and practitioners with nuanced knowledge for intervention.