Social networks, social cohesion, and place attachment are positive social impacts that can stimulate people’s quality of life. High-rise apartment buildings are often criticized for their negative social impacts, such as social isolation and low levels of interaction and social cohesion. However, there is still insufficient empirical evidence on the relationships between neighborhood social networks, social cohesion, place attachment, and loneliness of high-rise apartment residents and how they are affected by the physical environment and neighborhood satisfaction. This study uses structural equation modeling (SEM) to investigate these relationships using data collected in four high-rise apartment complexes in Hanoi, Vietnam. While the number of neighbors in someone’s social network is found to stimulate social cohesion, which can foster neighborhood attachment and reduce feelings of loneliness, the possibility of improving these social impacts is affected by urban contexts, site properties, and the ability to provide communal spaces within and surrounding the buildings.
This essay is a contribution to the research project ‘From Prevention to Resilience’ funded by ZonMw. Motivated by the Covid-19 pandemic, this research project explored how public space and forms of civic engagement can contribute to working towards more resilient urban neighborhoods. The project engaged a community of practice (CoP) to inform the research and to disseminate and critically discuss research outcomes. This essay, and the bundle it is part of, is the outcome of one of these engagements. The authors of this specific essay were asked to offer their disciplinary perspective on a first version of the Human / Non-Human Public Spaces design perspective, at that time still titled Nexus Framework on Neighborhood Resilience (click here and a PDF of this version will be downloaded). The authors were asked to do so based on their field of expertise, being climate-resilient cities. The authors have written this essay in coordination with the research team. To grasp the content of this essay and to take lessons from it, we encourage readers to first get familiar with the first version of the design perspective.
This study explored associations between perceived neighborhood walkability and neighborhood-based physical activity (NB-PA) and assessed possible moderation effects of the amount of time spent in the home neighborhood and individual characteristics (i.e., educational level and health-related problems). In 2016 to 2017, 509 Dutch adults, living in the South Limburg area, were included. Context-specific PA levels were measured using the Actigraph GT3X+ accelerometer and the Qstarz BTQ1000XT GPS-logger. Perceived neighborhood walkability, level of education, work status, and health-related quality of life were measured with validated self-report instruments. Results showed that individuals with a lower level of education or health-related problems spent more time in the home neighborhood. The perceived neighborhood walkability only affected NB-PA for individuals spending a relatively large amount of time in their home neighborhood. PA-facilitating features in the home neighborhood, for example, aesthetics, were only associated with more NB-PA for individuals without health-related problems or with a higher level of education.
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
