According to the WHO, mental health is generally defined as a state of well-being in which an individual realizes his/her abilities, copes with the normal stresses of life, works productively, and can contribute to his/her community (21). It encompasses emotional, psychological, and social well-being, influencing how individuals think, feel, and behave across different stages of life (22). In older adults, mental health is particularly important, as it significantly affects quality of life, functional independence, and overall well-being. This highlights the need for targeted interventions that promote positive mental health and prevent related issues in this age group (23). As an abstract concept, mental health is often assessed using multiple indicators, which are identified through both subjective and objective approaches. Internationally recognized scales that are frequently used include the Symptom Checklist-90 (SCL-90), the Positive and Negative Affect Schedule (PANAS), the Center for Epidemiological Studies Depression (CES-D) Scale, and the Self-Rating Depression Scale (SDS). At the same time, advances in technology have enabled digital health tools, including smartphone applications and wearable devices, to play an increasing role in real-time mental health monitoring (24).Among them, the CES-D-20 is a reliable, valid, easy-to-administer tool that is sensitive to changes in depressive symptoms, making it ideal for both large-scale studies and clinical settings (25–28). Thus, we derived our information from questionnaire data of the 2018 China Labor Dynamics Survey (CLDS), in which the assessment of mental health was based on the CES-D Scale as a reference. Currently, research on the mental health of older adults revolves around four main pathways: individual factors (e.g., medical history, age, gender, habits) (29, 30), family factors (31, 32), community factors (33), and aging care services (34, 35). Different family structures have varying effects on the mental health of older adults. Important social relationships with family can have both positive and negative health effects, depending on the quality, frequency, and strength of that connection (36). Moreover, residents’ subjective perceptions of the neighborhood environment have a strong impact on their well-being and health status. People who live in a cohesive community can obtain information and support from their neighbors, thereby benefiting their mental health (37, 38). In addition, with the decline in physical function and mobility as well as the shrinking of social networks, older adults’ dependence on the community increases with age. Hence, neighborhood ties in the community help to alleviate loneliness and anxiety in older adults and provide emotional value through neighborhood interactions (39). Further, with the community being the basic unit of China’s current social governance, the older adult care model is rooted in home-based care, supported by community-based care, and supplemented by institutional care. Community-based care for older adults is more effective at mitigating physical and mental health problems caused by aging (40, 41).

To date, numerous studies have examined the effects of neighborhood environments on mental health. From the standpoint of person-environment fit theory, the neighborhood environment mostly affects older adults’ mental health through interactions involving functional ability (42, 43). Some studies suggest that although the functioning of older adults may have declined, the neighborhood environment meets their social needs and enhances their sense of belonging. This helps reduce loneliness and social anxiety in older adults, which positively affects their mental health (44). Neighborhood environments primarily include social and built environments. The social environment reflects interactions between neighbors, which encourages older adults to participate in social interactions and disseminate and share information. Neighbors with abundant facilities offer them the opportunity to communicate, which improves active social interaction and formulates excellent neighborhood ties (45, 46). Liu et al. emphasized the important role of the social environment in neighborhood attachment and alleviating feelings of exclusion and isolation (40); they asserted that a cohesive, supportive community provides neighborhood support to residents and reduces stress in their lives. Stressors inside socioeconomically deprived neighborhoods (such as anti-social behavior or environmental disorders) stimulate negative emotions, thus influencing mental health. Baranyi et al. proposed that living in a high-crime neighborhood may directly or indirectly impact mental health (47). Social trust can promote engagement with social networks, thereby improving mental health (48). Moreover, individuals who interact with trustworthy neighbors or are willing to help their neighbors may develop a positive psychological state by acquiring a sense of security and acceptance within the community and by recognizing their self-worth (49, 50).

The built environment is defined as an objective material setting constructed by humans for living and production activities in cities (51). Thus far, several studies have been grounded in the “5Ds” theory, which holds that density (e.g., building density, population density, etc.), diversity (e.g., diverse leisurely activities), design (e.g., sidewalk coverage, street trees, average street widths, etc.), destination accessibility (e.g., points of interest, accessibility to the nearest parks and squares, etc.), and distance to transit (e.g., the distance between transit stops) are significantly associated with the mental health of older adults (52–54). Under the current development trend of urban spatial agglomeration, scholars are paying more attention to and finding evidence of a positive relationship between green space and mental health. Urban greenness provides a safe, attractive, and accessible walking place for surrounding residents, potentially alleviating depressive symptoms (55). Green spaces, such as parks and gardens, have been widely studied for their positive effects on mental health. Research suggests that exposure to green spaces can reduce stress, enhance mood, and improve overall mental well-being (56, 57). These spaces offer restorative environments, encouraging relaxation and physical activity, which are beneficial for both cognitive function and emotional regulation (58). In older populations, the mental health benefits of green spaces are particularly significant. Older adults often face increased risks of depression and cognitive decline due to reduced social interaction and physical activity. Green spaces can mitigate these risks by providing opportunities for social engagement, exercise, and sensory stimulation (59). Walking in parks or spending time in green areas has been linked to lower levels of anxiety and depression among older individuals, improving their overall quality of life (60). Moreover, studies have shown that accessibility and proximity to green spaces are crucial for older populations, as these factors determine the likelihood of frequent visits and engagement (61). Urban planning initiatives that increase access to green areas have the potential to promote healthier aging by supporting both mental and physical health in older adults. Additionally, green spaces contribute to a sense of community, helping alleviate feelings of isolation, which is a common challenge among older adults (62). Furthermore, satisfaction with neighborhood green space encourages people to use green areas more frequently, resulting in greater esthetics, pleasure, and relaxation (63). At the same time, some scholars believe that there are potential variables in the moderating and mediating roles between them.

The mental health of older adults has become a significant issue investigated in the fields of health psychology, genealogy, and other areas (64). In light of the recent strides in positive psychology, SWB has turned into one of its crucial contents (65). Studies have shown that is an important index to measure the mental health and life quality of older adults. Factors affecting SWB are subjectivity, stability, and wholeness (66). Research indicates that long-term physical health problems often lead to mental health problems like depression and anxiety, reducing SWB and quality of life under the conditions of China’s rapid aging (67). With regard to mental health, it not only prevents depression but also contributes to SWB. For instance, people with better mental health can have optimistic attitudes that enable them to cope effectively with life’s adversities and challenges, resulting in higher SWB. As for SWB, generally speaking, people with higher levels of SWB are found to lead a healthier life or live longer (68). The possibility is that positive SWB is a protective factor for health. Furthermore, prospective-epidemiological research suggests that positive life evaluations and hedonic states such as well-being predict lower future mortality and morbidity (69). In addition, SWB and mental health are closely linked to age while their relation is probably bidirectional which means SWB and mental health interrelate. Additionally, according to Baird’s point, the SWB follows a U-shaped trajectory, rising with age before declining, notably after 70 years (70).

Neighborhood environments have been identified as being relevant to promoting human health and enhancing well-being (71). Studies have shown that SWB as a crucial indicator is used for evaluating residents’ well-being, and Huppert et al. considered happiness to measure the characteristics of residents and communities (72). On this basis, the built environment and the social environment are two domains of neighborhood context that are related to mental health. In terms of the built environment, green space is a vital factor, and there is growing evidence that green space is beneficial for mental health. Especially among vulnerable groups (e.g., older adults), green space in cities can be associated with improved overall well-being and self-perceived health status, suppressed morbidity and increased life expectancy, and increased satisfaction with life prospects, among other ways to promote healthy aging in older adults (73). Green space not only provides a place for social activities and physical activities for older adults, but also its rich natural landscape can reduce loneliness and improve emotional health, thus promoting SWB (74). As for the social environments, neighborhood social environment such as community security, social trust, and other factors have a great influence on people’s interaction in the community, which plays a vital role in mental health and well-being. According to Ballas and Tranmer, the neighborhood with a high-security situation can often improve the SWB of individuals (75). Meanwhile, neighborhood ties lead to the creation of a friendly neighborhood atmosphere with high levels of trust and reciprocity, protecting residents from pathological mental states such as depression and anxiety which contributes to SWB (76). Although no study has clearly demonstrated the mediating role of SWB, most research approves of the viewpoint that neighborhood factors are significantly related to daily life, mental health, and SWB (53, 77). SWB has the potential to be an intermediate variable among these variables (13). Based on this, this study aims to explore pathways linking neighborhood social environment (neighborhood ties, social trust, and community security) to older adults’ mental health in the Chinese context. In the meanwhile, it particularly investigates the extent to which SWB mediates the linkage between neighborhood social environment and older adults’ mental health (Figure 1). What is more, it further explores the moderating role of green space and puts forward the following hypotheses:

Data for this study came from the 2018 CLDS, a large-scale, nationally representative tracking survey of labor force dynamics designed and implemented by the Center for Social Science Research at Sun Yat-sen University. The 2018 CLDS involved data gathered from 28 provinces in China, excluding Hong Kong, Macao, Taiwan, Tibet, Hainan, and Xinjiang. The database contains comprehensive data on 368 communities, 13,501 households, and 16,537 individuals in the labor force. The 2018 CLDS adopted multistage, multilevel probability sampling proportional to the size of the labor force, which minimizes sampling errors and ensures the randomness and scientific nature of sample selection. This study included men and women aged 60 and 55 years, respectively. The final sample comprised 3,315 individuals from 255 communities across 26 provinces (Figure 2).

Table 1 presents the descriptive statistics for all variables. The mean mental health score was 71.91 (SD ± 9.19), which is much higher than the cutoff (2/3 of the total score of 80), indicating that the participants had good mental health. The mean SWB score was 10.95 (SD ± 2.33), which is above the threshold, suggesting that the participants had a high level of SWB. The average levels of neighborhood ties, social trust, and community security were 7.66 (SD ± 1.58), 30.65 (SD ± 4.18), and 21.74 (SD ± 3.53), respectively. In terms of covariates, 59.4% of the respondents were female, 91.2% were not single, and 15.1% had suffered an illness or injury in the past 2 weeks. Their average age was 67.69 years old, and their average annual income in 2017 was 17,333.85 yuan.

This study used SEM to examine the mediating and moderating effects of neighborhood ties, social trust, community security, and the mental health of older adults in a neighborhood social environment. Notably, SEM can measure the total, direct, and indirect effects of one variable (such as neighborhood ties) on another (such as mental health) to explore the mechanisms underlying the ties between the neighborhood social environment and mental health in the community (92). This study tested the chain-mediation model using SEM. In the baseline model, mental health, SWB, neighborhood ties, social trust, and community security are continuous variables. In this study, green space, socio-demographic characteristics, and personal health characteristics were taken as exogenous variables, while neighborhood ties, social trust, community security, SWB, and mental health were taken as endogenous variables. At the same time, considering the possible collinearity between mental health and SWB variables, we used SPSS to conduct a collinearity test. The test results show that the VIF value between variables is less than 2 and the tolerance greater than 0.1, which alleviates the collinearity problem between variables. Additionally, we considered existing research to determine the fit parameters for SEM (93), which allowed us to test the proposed models. We used the following parameter criteria for model fit: the root mean square error of approximation (RMSEA) ≤ 0.05; the goodness-of-fit index (GFI) ≥ 0.90; the normed fit index (NFI) ≥ 0.80; the incremental fit index (IFI) ≥ 0.80; the Tucker-Lewis index (TLI) ≥0.80; and the comparative fit index (CFI) ≥ 0.80. We employed SPSS Amos 26 for SEM and STATA version 13.1 for basic pre-analysis data cleaning.

This study uses SEM models to investigate the association between neighborhood ties, social trust, community security, and mental health of older adults in the neighborhood social environment, exploring the mediating role played by SWB in this association, while adjusting for control variables at the sociodemographic and personal health levels of older adults. The fitting parameter criteria for the mediation effect model with moderation are shown in Section 3.3. The model path coefficients are shown in Table 2. Regarding sociodemographic characteristics control variables, older adults with younger age, higher annual income, and male gender were more likely to report better mental health status. At the level of personal health, older adults who have not been injured in the past 2 weeks are more likely to have good mental health. The direct path coefficient from social trust to the mental health of older adults is significant and positively correlated (β = 0.155, p < 0.05), which indicates that the improvement of social trust of older adults is helpful in promoting their mental health level. At the same time, the sense of community security of older adults also has a positive and direct impact on their psychological health (β = 0.098, p < 0.01). Therefore, Hypothesis 1 is partially supported. Additionally, there is a positive correlation between neighborhood ties, social trust, community security, and SWB. Closer neighborhood ties contributed to the improvement of SWB in older adults (β = 0.141, p < 0.01). Moreover, the improvement of older adults ‘s social trust also helps to maintain better SWB (β = 0.272, p < 0.01). A good sense of community security had a positive effect on the SWB of older adults (β = 0.039, p < 0.01). Furthermore, Older adults with better SWB also have a direct and positive impact on their mental health status (β = 0.445, p < 0.01).

Table 3 and Figure 2 present the results of the mediating effects. Among the mediating effects of neighborhood social environment-related indicators on mental health, neighborhood ties, social trust, and community security were all significant and positively correlated with the mental health path coefficients of SWB through the mediating variables (neighborhood ties: β = 0.061, p < 0.01; social trust: β = 0.127, p < 0.01; community security: β = 0.017, p < 0.01). Thus, Hypothesis 2 is supported. The neighborhood ties index showed a complete mediating effect. The higher the neighborhood ties index, the more frequent the contact and interaction between the individual and a neighbor, and the stronger the social bond. Such a connection is conducive to improving the SWB of older adults and thus has a positive impact on their mental health. Moreover, social trust and community security had partially mediating effects. Improving social trust in older adults can contribute to good mental health by promoting SWB. A high level of community security indicates that older adults are in a relatively safe community and are not troubled by the presence of community security, which also helps to improve their SWB and mental health (Figure 3).

We examined the moderating effect of green space on the mediating effect of the neighborhood social environment and the mental health of older adults. Table 4 shows the results of this model, which indicate that green space had no moderating effect on the direct relationship between neighborhood ties, social trust, community security, and the mental health of older adults. As for the mediating effect, we found that green space had a moderating effect on the mediating effect of neighborhood ties and mental health (β = 0.012, p < 0.01). Hence, Hypothesis 4 is partially supported. The improvement in the greenspace index helped enhance the positive, indirect correlation between neighborhood ties and mental health through SWB. Green Spaces not only play a role as places where ties are initially established but also where they are re-established. As leisure spaces, green spaces provide opportunities for social interaction, thereby contributing to developing new social connections and strengthening existing ones, thereby promoting neighborhood ties (94). Favorable and intimate neighborhood ties can enhance SWB. The improvement of green space coverage may provide a more possible social interaction space for the close neighborhood ties of older adults, enhance their SWB, and further promote the improvement of the mental health level of older adults. However, this study did not find that green spaces have a moderating effect on the indirect relationships between social trust, community security, and mental health. A possible explanation is that trust is promoted by the social function of green space (95). The measure of green space used in this study is green space coverage, which is insufficient in evaluating the social function of green space. Relevant studies also prove that the relationship between green space and trust is more likely to be related to the weekly use frequency and single-use duration (96). Secondly, the moderating effect of green space on community security and the mental health of older adults is not significant, which may be related to the complex relationship between green space and community security. To date, the evidence on the relationship between green Spaces and feelings of safety and crime is mixed. Some studies show that green space vegetation may provide convenience for crime (97), but other studies believe that green space vegetation can help reduce residents’ fear of crime and enhance their sense of security (98). In a more detailed study of the relationship between green space vegetation types and crime, a higher proportion of grassland was associated with a lower rate of crime only for areas with relatively low crime rates, while a higher proportion of woodland was associated with a lower rate of crime only for areas with relatively high crime rates (99). Therefore, many other factors may influence the relationship between green space and security, which could explain why the moderating effect of green space was not significant.