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This study aimed to examine the mediating role of social capital in the association between perceived physical neighborhood environment and loneliness among older adults in urban China. Data were derived from face-to-face interviews with people (n = 472) aged 60 or older in urban communities of Shanghai, China, in 2020. Loneliness was measured by the 6-item De Jong Gierveld Scale. A multiple mediator model was adopted to examine the research hypotheses. Cognitive social capital played a full mediation role in the association between perceived community health care (β = −.061, p <.05), safety (β = −.168, p <.001), recreational services (β = −.058, p <.05), and loneliness. Structural social capital was associated with loneliness (β = −.102, p <.05), whereas its mediator effect was not significant. Perceived transportation convenience had neither a direct nor an indirect effect on loneliness among older adults. Findings indicate that older adults' perceptions of healthcare services, safety, and recreational resources could help alleviate their loneliness via fostering cognitive social capital. Interventions improving older adults' perceptions of community health care, safety, and recreation, and their social capital level could help reduce the prevalence of loneliness. [ABSTRACT FROM AUTHOR]

Purpose: The physical and social neighborhood environments are increasingly recognized as determinants for depression. There is little evidence on combined effects of multiple neighborhood characteristics and their importance. Our aim was (1) to examine associations between depression severity and multiple perceived neighborhood environments; and (2) to assess their relative importance.Methods: Cross-sectional data were drawn from a population-representative sample (N = 9435) from the Netherlands. Depression severity was screened with the Patient Health Questionnaire (PHQ-9) and neighborhood perceptions were surveyed. Supervised machine learning models were employed to assess depression severity-perceived neighborhood environment associations.Results: We found indications that neighborhood social cohesion, pleasantness, and safety inversely correlate with PHQ-9 scores, while increasing perceived distance to green space and traffic were correlated positively. Perceived distance to blue space and urbanicity seemed uncorrelated. Young adults, low-income earners, low-educated, unemployed, and divorced persons were more likely to have higher PHQ-9 scores. Neighborhood characteristics appeared to be less important than personal attributes (e.g., age, marital and employment status). Results were robust across different ML models.Conclusions: This study suggested that the perceived social environment plays, independent of socio-demographics, a role in depression severity. Contrasted with person-level and social neighborhood characteristics, the prominence of the physical neighborhood environment should not be overstated. [ABSTRACT FROM AUTHOR]

Although sociodemographic factors are one aspect of understanding the effects of neighborhood environments on health, equating neighborhood quality with socioeconomic status ignores the important role of physical neighborhood attributes. Prior work on neighborhood environments and health has relied primarily on level of socioeconomic disadvantage as the indicator of neighborhood quality without attention to physical neighborhood quality. A small but increasing number of studies have assessed neighborhood physical characteristics. Findings generally indicate that there is an association between living in deprived neighborhoods and poor health outcomes, but rigorous evidence linking specific physical neighborhood attributes to particular health outcomes is lacking. This paper discusses the methodological challenges and limitations of measuring physical neighborhood environments relevant to health and concludes with proposed directions for future work.

Although sociodemographic factors are one aspect of understanding the effects of neighborhood environments on health, equating neighborhood quality with socioeconomic status ignores the important role of physical neighborhood attributes. Prior work on neighborhood environments and health has relied primarily on level of socioeconomic disadvantage as the indicator of neighborhood quality without attention to physical neighborhood quality. A small but increasing number of studies have assessed neighborhood physical characteristics. Findings generally indicate that there is an association between living in deprived neighborhoods and poor health outcomes, but rigorous evidence linking specific physical neighborhood attributes to particular health outcomes is lacking. This paper discusses the methodological challenges and limitations of measuring physical neighborhood environments relevant to health and concludes with proposed directions for future work. [ABSTRACT FROM AUTHOR]

(1) Objectives: Using cross-sectional datasets, we investigated whether better self-perceived physical and social neighborhood environment was associated with perceived health status and health-related behaviors among Chinese rural residents. (2) Study Design: The study was based on the 2016 China Family Panel Studies (CFPS) survey. The sample consisted of 7191 rural residents over 18 in China. (3) Methods: The article measured physical neighborhood environment from the two aspects of dwelling environment (DE) and public facilities convenience (PFC), and social neighborhood environment from public security (PS) and neighborhood relationship (NR). Associations between health status/health-related behaviors and self-perceived physical/social neighborhood environment were analyzed using multivariable logistic regression models adjusted for socio-demographic characteristics. (4) Results: The results suggested that rural residents who live in a good neighborhood environment reported having a better health status. Specifically, rural residents who reported living in good DE were less likely to have a depressive mood and poor health conditions. Those who reported good PFC were less likely to have depressive mood, poor self-rated health and chronic diseases. Rural residents who reported having good PS were less likely to have a depressive mood. Those who reported good NR were less likely to have a depressive mood, poor self-rated health, chronic diseases and obesity. Regarding neighborhood environment and health-related behaviors, the results showed that rural residents who reported good PFC were more likely to do physical exercise. Notably, the regression results of the education level variable showed that education level significantly promoted the health-related behaviors (time sleeping weekday, physical exercise and smoking) of rural residents. (5) Conclusions: This article suggested that there was strong evidence for a relationship between physical and social neighborhood environment and the general health of rural residents due to all causes. According to the conclusion of this article, in order to improve the health of rural residents, policy interventions should give priority to improving the neighborhood environment. In addition, the improvement in the degree that rural residents are exposed to education is of the same importance, which helps more rural residents to maintain good health-related behaviors.