Background: Migrants experience substantial changes in their neighborhood physical and social environments along their migration journeys, but little is known about how perceived changes in their neighborhood environment pre- and post-migration correlate with their mental health. Our aim was to examine the associations between recalled changes in the perceived neighborhood physical and social environments and migrants’ mental health in the host city. Methods: We used cross-sectional data on 591 migrants in Shenzhen, China. We assessed their risk of mental illness using the General Health Questionnaire (GHQ). Neighborhood perceptions were collected retrospectively pre- and post-migration. We used random forests to analyze possibly non-linear associations between GHQ scores and changes in the neighborhood environment, variable importance, and for exploratory analysis of variable interactions. Results: Perceived changes in neighborhood aesthetics, safety, and green space were non-linearly associated with migrants’ mental health: A decline in these characteristics was associated with poor mental health, while improvements in them were unrelated to mental health benefits. Variable importance showed that change in safety was the most influential neighborhood characteristic, although individual-level characteristics—such as self-reported physical health, personal income, and hukou (i.e., the Chinese household registration system)—appeared to be more important to explain GHQ scores and also strongly interacted with other variables. For physical health, we found different associations between changes in the neighborhood provoked by migration and mental health. Conclusion: Our findings suggest that perceived degradations in the physical environment are related to poorer post-migration mental health. In addition, it seems that perceived changes in the neighborhood environment play a minor role compared to individual-level characteristics, in particular migrants’ physical health condition. Replication of our findings in longitudinal settings is needed to exclude reverse causality.

Although migration trajectories over people's life courses seem to be associated with mental health outcomes, previous studies have considered migration at only one point in time when correlating migration with mental health. However, people can migrate multiple times during their life courses. The decision to migrate can be triggered by several life course development events, such as education, entry to the labour market, marriage, or retirement. The present study addressed this research gap by focusing on the trajectories of migration and their relationship to mental health among internal migrants in China. Data were collected from a cross‐sectional survey (N = 534) in Shenzhen, China, in 2017. People's migration trajectories were aligned into migration groups using sequence alignment method. Binary logistic regression models were estimated to assess the associations between each migration trajectory group and the prevalence of mental health problems, controlling for sociodemographics and self‐reported physical health. The results show that migration trajectories—namely, the sequence of multiple migrations between migrants' places of origin and their final destinations—are significantly related to mental health outcomes. Our findings suggest that treating migration as a one‐time transition could be problematic because many migrants undertake multiple migration trips.

Against the backdrop of global ageing, a growing empirical literature highlights associations between age-friendly environments (AFEs) and older adults' well-being. However, the evidence is difficult to cumulate because AFE measurement is fragmented, characterized by heterogeneous operational approaches and uneven domain coverage. Importantly, this measurement heterogeneity is not merely a methodological limitation; it acts as a structuring force that shapes inference, comparability, and policy learning across studies. This systematic review aims to map how AFEs are operationalized and how they are connected to older adults' well-being. Following PRISMA, four databases were searched to April 2025; 5305 records were screened, and 58 studies were included. We classified AFE measures as subjective (n = 37), objective (n = 11), and mixed (n = 10) and mapped indicators to the WHO Age-Friendly Cities and Communities (AFCC) domains. Our synthesis reveals that AFE measurement is skewed to physical domains, such as transportation, outdoor spaces and buildings, and health services, with social domains underspecified. Associations are often positive for features such as reliable public transport, proximate everyday services, and opportunities for social participation; however, magnitudes and even directions vary by context and by how AFEs are operationalized. We also observe non-linear patterns (for example, in street connectivity or greenness), and occasional negative associations, particularly in disadvantaged settings where higher service density may signal unmet need rather than support. Some of this heterogeneity likely reflects analytic choices, including denominator selection, buffer size and shape, and the omission of micro-scale features and barriers. We recommend a comprehensive AFE assessment that combines subjective and objective approaches, balances physical and social domains, and improves transparency on validity and cross-cultural equivalence. Emerging tools such as street-view imagery and other fine-scale urban data can help capture micro-spatial features with greater precision.