The impacts of visual street environments on obesity: The mediating role of walking behaviors

As obesity is emerging as a serious social issue, urban planners and public health practitioners are making efforts to establish urban environments that can help to reduce obesity. Despite many studies on the correlation between built environments and obesity, little attention has been devoted to micro-scale street environments related to obesity. This study fills this gap by empirically analyzing the effects of both micro- and macro-scale walkable environments on obesity through the mediating factor of walking behaviors. In particular, we employed the deep learning technique of semantic segmentation based on Google Street View panorama images, to estimate visual street environments at the pedestrian eye level. Based on an online survey collected from 1000 respondents in Seoul, Korea, this study used the Structural Equation Model to examine the systematic relationships between walkable environments, walking behaviors, and obesity. Our findings revealed that walkable environments had an indirect effect on obesity through the mediating factor of walking behaviors. Specifically, utilitarian walking behavior had no significant effect on obesity while leisure walking behavior had an effect on reducing obesity. Moreover, visual street environments (i.e., street greenery and sidewalk pavement) and macro-scale built environments (i.e., land-use mix and intersection density) had significant indirect effects on obesity. The results of this study provide the evidence for policymakers, urban planners, and public health practitioners to effectively retrofit built environments to be more physically active-friendly, so as to reduce obesity.