In the era of digital economy, the new retail consumption space, in which consumers’ experience can be enhanced through the creation of consumption scenes, is having an increasingly important influence on urban spatial development. From the perspective of spatial field, revealing the complex economic and social mechanisms behind scene creation in the new retail experience consumption space contributes to a deeper understanding of consumption space formation mechanisms. Utilizing data from Dianping and Baidu Street View apps, this paper applies spatial syntax and spatial econometric models to assess the spatial effects of consumption scenes. It explores the mechanisms through which street environment, as a narrative means for consumption scenes, influences the distribution of new retail experience consumption space, thereby further extending the scope of consumption space research. The findings reveal that: ① the economic value of the consumption scene is central to the street environment’s impact on the distribution of new retail experience consumption space. This spatial effect extends the relationship between physical elements in the street environment into the network relationship within the spatial field. ② Consumers’ behavioral preference for consumption space arises from a dependence relationship, while merchants’ construction of such space is shaped by a heterogeneity-based relationship. ③ In the interaction between physical and virtual spaces, consumers exercise their spatial rights, while merchants respond to consumers’ spatial demand. The compression of physical and virtual spaces alters the logic behind consumers’ scene attachment and merchants’ scene creation. ④ Urban planning can facilitate scene narration and promote the development of the consumer economy by developing a business-friendly street environment, coordinating the relationship between local and neighboring spaces, and optimizing the scale relations of the street environment.

Chronic non-communicable diseases have become a significant threat to the health of middle-aged and older adults in urban areas. The allocation of health resources in urban communities is associated with the prevalence of chronic diseases. This study conducts an empirical analysis using threshold regression methods based on data from the China Health and Retirement Longitudinal Study (CHARLS). It explores the nonlinear impact of community health resource allocation on chronic disease management among middle-aged and older adults across different age groups. The goal is to allocate health resources scientifically based on the health and activity needs of specific age groups. The results reveal staged differences across distinct age intervals. Specifically, the allocation of community health resources has a negative impact on the management of chronic diseases of respondents under 58 years old, an insignificant impact for those aged between 58 and 73 years, and a significant positive impact for those aged above 73 years old. The threshold effect of age is closely related to the health resource preference and activity pattern of different age groups. The alignment between health resource supply and demand within these groups determines their effectiveness in improving health outcomes. These findings could help optimize the spatial allocation of health resources, enhance planning standards, and address existing disparities across communities, thereby providing an evidence-based solution for urban planning decisions.