Although rapid urbanization and associated rural-to-urban migration has brought in enormous economic benefits in Chinese cities, one of the negative externalities include adverse effects upon the migrant workers’ mental health. The links between housing conditions and mental health are well-established in healthy city and community planning scholarship. Nonetheless, there has thusfar been no Chinese study deciphering the links between housing conditions and mental health accounting for macro-level community environments, and no study has previously examined the nature of the relationships in locals and migrants. To overcome this research gap, we hypothesized that housing conditions may have a direct and indirect effects upon mental which may be mediated by neighbourhood satisfaction. We tested this hypothesis with the help of a household survey of 368 adult participants in Nanxiang Town, Shanghai, employing a structural equation modeling approach. Our results point to the differential pathways via which housing conditions effect mental health in locals and migrants. For locals, housing conditions have direct effects on mental health, while as for migrants, housing conditions have indirect effects on mental health, mediated via neighborhood satisfaction. Our findings have significant policy implications on building an inclusive and harmonious society. Upstream-level community interventions in the form of sustainable planning and designing of migrant neighborhoods can promote sense of community, social capital and support, thereby improving mental health and overall mental capital of Chinese cities.

One of the primary aims of China’s territory spatial planning is to control the urban sprawl of local municipals and prevent regional competition and the negative consequences on the environment—which emphasizes the top-down spatial regulation. Indeed, the traditional cellular automaton (CA) model still has limitations when applied to the whole administration area since it may ignore the differences among cities and towns. Thus, this paper proposed a CM-CA (clustering, multi-level logit regression, integrated with cellular automaton) framework to simulate urban growth boundaries for cities and towns simultaneously. The significant novelty of this framework is to integrate several urban growth modes for all cities and towns. We applied our approach to the city of Xi’an, China, and the results showed satisfactory simulation accuracy of a CM-CA model for multiple cities and towns, and the clusters’ effects contributed 74% of the land change variance. Our study provides technical support for urban growth boundary delineation in China’s spatial planning.

Neighbourhood social capital has long been regarded as protective for mental health through everyday face-to-face interaction. At the same time, rapid digitalization is reshaping patterns of social connection in ways that may reorganize the distribution of these place-based protections and contribute to urban mental health inequalities. This study examines the associations between multidimensional digital engagement, neighbourhood social capital, and depressive symptoms in China, and assesses whether these relationships differ by gender and marital status. The analysis draws on 13,443 adults from the 2016 and 2020 waves of the China Family Panel Studies. Pooled cross-sectional ordinary least squares models with wave controls are estimated, followed by subgroup analyses stratified by gender and marital status. Neighbourhood social capital is consistently associated with lower levels of depressive symptoms after adjustment for socioeconomic characteristics and multiple dimensions of internet use, indicating that local social environments remain relevant under conditions of widespread connectivity. In contrast, the associations between digital engagement and depression vary by activity type. Internet use oriented toward maintaining contact with family and friends is associated with fewer depressive symptoms, whereas longer online time and work-oriented, business-oriented, and entertainment-oriented uses are more often associated with higher depressive symptoms. These patterns differ across social groups. The protective association of neighbourhood social capital is strongest and most consistent among married men. In contrast, internet-use-related correlates of depressive symptoms are generally more pronounced among women, especially married women, although the specific forms of internet use associated with depressive symptoms vary by marital status and across survey waves. The findings indicate that digital participation and neighbourhood social capital are jointly associated with depressive symptoms, but their associations are socially differentiated by gender and marital status. Strengthening neighbourhood-based social infrastructure remains central to reducing mental health inequalities in the digital era.