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Article

Association Between Neighborhood Built Environment and Mental Health: Differences Between Older Adults With and Without Restricted Mobility

by
Xinyu Kong
1,
Haoying Han
1,2,*,
Fangting Chi
1,
Mengyao Zhan
1 and
Xianfan Shu
3,*
1
College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
2
Faculty of Innovation and Design, City University of Macau, Macau 999078, China
3
School of Economics, Hangzhou Normal University, Hangzhou 311121, China
*
Authors to whom correspondence should be addressed.
Sustainability 2024, 16(21), 9226; https://doi.org/10.3390/su16219226
Submission received: 31 July 2024 / Revised: 19 October 2024 / Accepted: 22 October 2024 / Published: 24 October 2024
(This article belongs to the Topic Biophilic Cities and Communities: Human-Environment Interaction and Sustainable Governance)
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Abstract

:
The mobility restrictions faced by older adults pose significant challenges to understanding the association between the neighborhood built environment and their mental health. Neglecting the role of restricted mobility hinders a comprehensive analysis of how the built environment impacts older adults’ mental health. Furthermore, the differences in this association between older adults with and without restricted mobility remain unclear. Based on data from 1405 adults aged 60 and older in Hangzhou, China, this study explored the association between the neighborhood built environment and the mental health of older adults using multivariable linear regression, with multivariable logistic regression being employed for the sensitivity analysis. The results indicated that access to public canteens and outdoor fitness spaces were significantly positively associated with the mental health of older adults. Notably, the protective effect of outdoor fitness spaces was significant for older adults with restricted mobility, while the supportive effect of public canteens was significant for those without restricted mobility. This study demonstrated an association between the neighborhood built environment and mental health among older adults, highlighting differences in this effect between those with and without restricted mobility. These insights underscore the necessity of designing sustainable and inclusive neighborhoods that cater to the varied needs of older adults, ultimately fostering environments that promote healthy and active aging.

1. Introduction

The global challenge of population ageing is becoming increasingly critical [1]. By 2025, it is projected that over 20% of China’s population will be aged 60 and older [2]. As individuals age, life events such as the loss of a spouse, declining physical health, cognitive decline, and alterations in social networks can trigger psychological challenges. Consequently, the mental health (MH) of older adults has emerged as a pressing social issue. A systematic review has identified a global prevalence of major depression among older adults at 13.3% [3], while anxiety disorders are even more prevalent, affecting 50% of this population [4]. In China, the situation is similarly alarming, with a depression prevalence rate of 23.6% among older adults [5]. Therefore, addressing and preventing MH issues among older adults has become an urgent priority to promote active ageing.
Maintaining mobility in older adults is fundamental to achieving active ageing [6]. Mobility plays a crucial role in aligning individual needs with available resources for older adults. Those with better mobility tend to engage more frequently in physical exercise, recreational activities, and visits to attractive destinations [7,8]. As their life space expands, the variety of locations they visit increases, thereby enhancing their overall life satisfaction [9]. However, with advancing age and declining physical function, mobility often decreases, resulting in a reduced scope of daily activities [10,11,12]. Low levels of mobility can diminish the daily engagement of older adults, potentially leading to psychological issues [13]. A reduction in life space not only indicates a risk of frailty [12], but also heightens the risk of mental illness [14]. Nonetheless, some studies have found that many older adults maintain a high level of subjective well-being, even when their life space is severely restricted [15].
Previous studies have identified various cognitive-behavioral and compensatory strategies that older adults employ to mitigate the impact of a reduced living space, thereby enhancing their MH [16,17]. Internally, older adults often utilize mobility aids to maintain their daily activities [18]. Externally, age-friendly features of the built environment (BE) support older adults’ participation in daily activities [19], even when mobility is impaired [10]. For instance, the development of age-friendly communities [20,21] and the provision of sports and leisure facilities in residential areas [22] can promote daily activities among older adults, thereby improving their MH. Conversely, a restrictive BE may compel older adults to forgo certain outdoor activities [23]. It is important to recognize that older adults with and without mobility restrictions may experience the same BE features differently [24,25]. This variability can alter the relationship between the BE and the MH of older adults. To date, few studies have investigated the differential effects of the BE on the MH of older adults, based on their mobility status.
In China, residential neighborhoods serve as a unique living arrangement and a central gathering place for older adults to engage in daily activities. The age-friendliness of the neighborhood BE (NBE) plays a crucial role in determining social participation among older adults [26,27], which, in turn, impacts their MH [27,28,29]. Evidence from Hong Kong has identified positive associations between NBE elements, such as leisure seating, road paving, and crosswalks, and the MH of older adults [30]. However, other studies have found no significant direct correlation between the NBE and depression in older adults [27,31]. Furthermore, it remains unknown whether the relationship between the NBE and MH varies between older adults with and without mobility restrictions. Therefore, this study focuses on Hangzhou, China, to explore the association between the NBE and the MH of older adults, and to examine how this association differs between older adults with and without restricted mobility.
The remainder of this study is organized as follows: The second part introduces the materials and methods, including the study area, data collection, the definition of measures, and the construction of the statistical analysis. The third part summarizes the main results. The last two parts show the discussion and conclusion, respectively.

2. Materials and Methods

2.1. Study Area

Hangzhou, the capital city of Zhejiang Province, China, as well as the second largest city in the Yangtze River Delta, was selected as the study area for this research. By the end of 2021, Hangzhou had a permanent population of 12.2 million, with 17.3% aged 60 and older and 12.4% aged 65 and older. This demographic shift highlights the notable ageing population in Hangzhou. As a result, the elderly care services resources are relatively abundant in Hangzhou compared with other regions in China [32]. In recent years, Hangzhou has been actively developing age-friendly communities, with plans to achieve full urban and rural coverage by 2035 [33]. These made Hangzhou an ideal setting to explore the association between the NBE and MH among older adults.
For this study, we focused on urban areas, first screening administrative districts with 100% urbanization as the study area. Second, based on the proportion of the elderly residents, the more representative Shangcheng District, Gongshu District, and Xiacheng District (aged 60 and older: 33.09%, 27.53%, and 25.18%, respectively) were selected as the study areas. In terms of mortality rates, Shangcheng (6.15%) and Gongshu (5.65%) had slightly higher rates than the Hangzhou average (5.29%), while Xiacheng (4.86%) showed a lower rate. A stratified random sampling method was then used to select ten residential neighborhoods in each of three districts as study areas. Figure 1 displays the precise locations of the sampled neighborhoods and uses Xiaohejiayuan as an example to illustrate the specific indicators of an NBE.

2.2. Data Collection

In this study, data were collected at the individual level using a questionnaire method. The pre-survey was conducted in June 2022, followed by the formal survey from September to October 2022. The questionnaire survey was administered on working days with favorable weather conditions. Eight professional, trained students assisted in collecting the questionnaires as research assistants. Given the diverse educational backgrounds of the older adults, independently completing the questionnaire could have been challenging and potentially introduce information bias. Therefore, face-to-face interviews were conducted to gather relevant data from participants.
The surveys were conducted in 30 residential neighborhoods, mentioned earlier, with 50 questionnaires being randomly distributed in each neighborhood, resulting in a total of 1500 questionnaires. To be eligible for this survey, the participants had to meet the following criteria: be aged 60 or older, have resided in the neighborhood for at least six months, and exhibit no symptoms of cognitive impairment. Questionnaires that did not meet these criteria were deemed invalid. Ultimately, a total of 1405 valid questionnaires were obtained, yielding an overall response rate of 93.67%.
In this study, the process of data collecting using questionnaires complies with the relevant legal regulations [34]. No ethical approval was required since the present study involved no biomedical research on humans [34]. Prior to initiating the questionnaire survey, the researcher was required to disclose their identity, the purpose of the study, and the content of the survey to the participants. It was emphasized that the questionnaire was anonymous and no personal information would be disclosed in any subsequent scientific research. The collected data would be securely stored and protected, accessible only for scientific research purposes. Participation was voluntary, and the participants could withdraw at any time without penalty. It was essential to respect the participants’ rights, ensuring that the questionnaire did not involve any potential dangers. The questionnaire survey would only commence once the participants’ informed consent had been signed.

2.3. Measures

MH was the dependent variable, measured by the 12-item Short-form Health Survey (SF-12) scale. The SF-12 was a simplified version of the 36-item Short-form Health Survey (SF-36) scale, widely used in clinical health assessment due to its simplicity and high completion rate. Furthermore, the SF-12 has demonstrated high reliability and validity within the Chinese context [35]. The SF-12 involved 12 items: two items each from the domains of physical functioning, “role—physical”, “role—emotional”, and MH, and one item each from the domains of bodily pain, general health, vitality, and social functioning. The items related to “role—physical” and “role—emotional” were used to identify participants with restricted mobility. Scoring was conducted according to the standardized scoring manual [34]. The Mental Component Summary (MCS) score, ranging from 0 to 100, was used to evaluate MH, with higher scores indicating better MH. The MCS score was treated as a continuous variable in statistical models to explore the association between NBE and MH of older adults. In addition, the MCS score was used as a categorical variable for the sensitivity analysis. A cut-off score of 50 or above on the SF-12 indicated positive MH (SF-12 < 50 scored as “0”, SF-12 ≥ 50 scored as “1”) [36].
The NBE was the independent variable, measured by the age-friendly community standards published by the Chinese National Health Commission and the National Office on Aging in 2020 [37]. To comprehensively address the daily activity needs of older adults, this study selected 10 items as evaluation indicators of the NBE across three categories: daily travel (including barrier-free travel, elevators, rest seats, the diversion of pedestrians and vehicles, road surfaces, and public toilets), neighborhood services (including public canteens and elderly care), and social participation (including outdoor fitness spaces and indoor activity spaces). Researchers assessed and scored these ten indicators through on-site investigations. Table 1 showed the specific evaluation criteria. During the evaluation process, the variables were assigned a value of 1 if the NBE met the described criteria; otherwise, they were assigned a value of 0.
Eight covariates were used to control for individual-level variables, including gender (1 = female, 0 = male), age (1 = 60–69 years old, 2 = 70–79 years old, 3 = 80 years old and older), pension (1 ≤ 3000 RMB, 2 = 3000–5000 RMB, 3 = 5000–7000 RMB, 4 ≥ 7000 RMB), educational level (1 = secondary school and below, 2 = high school, 3 = college or undergraduate and above), household registration (1 = Hangzhou, 0 = other cities), lifestyle (1 = living alone, 0 = living with family), the length of residency (1 = more than 5 years, 0 = less than 5 years), and chronic disease (1 = no chronic diseases, 0 = suffering from chronic disease).
Descriptive statistics were performed to describe the main characteristics of the participants and the NBE. Multivariable linear regression models were used to examine the associations between the NBE and the MH of older adults. Model 1 included the indicators of the NBE and MH for all participants. Model 2 was additionally adjusted for covariates. Models 3 and 4 were constructed similarly for participants with unrestricted mobility, while Models 5 and 6 were built for participants with restricted mobility. Multivariable logistical regression models were used for the sensitivity analysis. All the statistical analyses were completed using Stata 17.0, with a significance criterion set at p < 0.05.

3. Results

3.1. Descriptive Statistics

The descriptive statistics of the study participants were summarized in Table 2. Among the total participants (n = 1405), the mean MH score was 56.30, with the majority of participants (85.20%) exhibiting positive MH. Demographically, a higher proportion of the participants were female (56.94%), aged between 70 and 79 years (36.72%), received a pension of 3000–5000 Chinese yuan (43.49%), and had an education level of junior high school or below (71.96%). The majority were registered residents of Hangzhou (79.72%), lived with family members (89.40%), had resided in their neighborhood for more than five years (87.76%), and had a chronic disease (70.89%).
For participants with restricted mobility (n = 346), their average MH score was significantly lower at 52.55 compared to those with unrestricted mobility. Furthermore, the proportion of individuals with negative MH was considerably higher (36.99%) among this group. A larger percentage of those with restricted mobility were aged 80 and older (41.04%), and over 90% had at least one chronic disease (90.17%).
The descriptive statistics of the NBE were presented in Table 3. More than half of the residential neighborhoods provided features such as barrier-free travel, rest seat, public toilet, elderly care, outdoor fitness space, and indoor activity space. Notably, over 70% of the neighborhoods provided barrier-free travel and outdoor fitness spaces, while features such as elevators, smooth road surfaces, and public canteens were less common, presented in only about 40% of the residential neighborhoods. Furthermore, only 10% of the neighborhoods provided the diversion of pedestrians and vehicles.

3.2. The Association Between the Neighborhood Built Environment and the Mental Health of Older Adults

The association between the NBE and the MH of older adults is illustrated in Figure A1. For the total participants group (Models 1 and 2), the availability of public canteens (β = 1.327, p = 0.004) and outdoor fitness spaces (β = 1.812, p = 0.008) was found to be significantly and positively associated with the MH of older adults, even after adjusting for the social-demographic characteristics. Among the older adults with unrestricted mobility (Models 3 and 4), after adjusting for the covariates, significant positive associations were observed for the presence of elevators (β = 0.919, p = 0.039), public toilets (β = 0.940, p = 0.037), and public canteens (β = 0.984, p = 0.004), while elderly care (β = −1.061, p = 0.029) showed a significantly negative association. In contrast, for older adults with restricted mobility (Models 5 and 6), the availability of outdoor fitness spaces (β = 5.959, p = 0.002) showed a significantly positive association with MH, whereas the public toilets (β = −4.663, p = 0.020) were significantly negatively associated.

3.3. Sensitive Analysis

The sensitivity analysis using multivariable logistic regression confirmed the robustness of the main findings (Figure A2). Specifically, the positive association between public canteens, outdoor fitness spaces, and the MH of older adults remained significant. Additionally, the association between public canteens and the MH of older adults without restricted mobility, as well as the association between public toilets, outdoor fitness spaces, and the MH of older adults with restricted mobility were consistent with the main analysis.

4. Discussion

Overall, the results demonstrated a significant association between the NBE and the MH of older adults. Specifically, both public canteens and outdoor fitness spaces were significantly positively associated with the MH of older adults. Notably, these associations varied between older adults with and without restricted mobility. For those with unrestricted mobility, public canteens exhibited a robust positive association with their MH, providing not only nutritional benefits but also essential social engagement opportunities. In contrast, older adults with restricted mobility showed greater benefits from outdoor fitness spaces, which play a crucial role in facilitating physical activity and enhancing social interactions. Conversely, public toilets were negatively associated with the MH of older adults with restricted mobility.
The protective effect of outdoor fitness spaces on the MH of older adults has been supported by other studies [22]. Exercise has been shown to release dopamine, which can enhance mood and foster positive emotions [38]. This explains why outdoor fitness spaces positively impact MH. For older adults with restricted mobility, exercise is one of the most effective intervention measures [39]. For example, for older adults with restricted mobility, these spaces often include equipment designed for rehabilitation, thus serving as convenient locations for necessary physical activity [40]. When their primary need for physical rehabilitation training is met, their MH improves. Additionally, the informal or non-contact social interactions that occur in these spaces can further bolster MH, as older adults engage with neighbors, creating both active and passive social influences [41]. However, older adults without restricted mobility may prefer more expansive venues, such as parks and squares, which may diminish the perceived benefits of nearby fitness facilities. Thus, the design of outdoor fitness spaces should consider the varying needs of older adults to maximize their MH benefits.
The positive impact of public canteens on the MH of older adults is similarly supported by prior studies [29,42]. While modern conveniences such as express delivery and takeout provide options for home dining, public canteens align more closely with the social and dietary habits of older adults. In China, public canteens often offer subsidies for seniors, promoting greater accessibility and enhancing community integration. Studies indicate that older adults residing in communities with public canteens report better MH compared to those in communities lacking such services [42]. In this study, the benefits of public canteens were significant, primarily for older adults with unrestricted mobility, likely due to their increased ability to access and utilize these facilities. Conversely, older adults with restricted mobility may face psychological barriers that limit their participation [14], thus reducing the potential positive impact of public canteens. This underscores the necessity of fostering social dining environments that are accessible and inviting for all older adults, regardless of their mobility status, to promote inclusivity and enhance MH.
A negative correlation between public toilets and MH among older adults with restricted mobility may stem from their heightened need for essential facilities during outdoor activities, such as public toilets [43]. As physiological functions decline with age, older adults may not engage in prolonged outdoor activities, especially for those with restricted mobility. Public toilets offer convenient services for physiological needs and extend their time outdoors [44]. However, public toilets are often prone to substandard sanitation due to their specific functional attributes, particularly in humid summers like those in Hangzhou. A study on the relationship between the BE and MH found that environmental sanitation mediated up to 55% of the impact on MH [45], underscoring that the effectiveness of even essential facilities like public toilets can be compromised by inadequate maintenance. Therefore, improving the sanitation and accessibility of public toilets is crucial for enhancing the outdoor experience and MH of older adults with mobility challenges.
This study has several limitations. First, as a cross-sectional study, this study cannot establish causal relationships between the NBE and MH. Second, while this study relies on objective evaluations to measure the NBE, future research could incorporate both subjective and objective measurement methods for a more comprehensive assessment. Third, this study assessed mobility restrictions among older adults through subjective evaluation. Future studies could utilize advancements in communication technology, such as GPS, to more objectively analyze the travel patterns of the elderly. Additionally, the sample size of participants with mobility restrictions was limited (346 out of 1405), which may affect the robustness of the findings related to this group.

5. Conclusions

This study explored the association between the NBE and MH among older adults, demonstrating that this association varied based on the participants’ mobility status. Specifically, the presence of public canteens and outdoor fitness spaces was significantly positively associated with the MH of older adults, but the association varied by mobility. The protective effect of public canteens was significant among older adults without restricted mobility, while the beneficial effect of outdoor fitness spaces was significant for those with restricted mobility. These findings highlight that the needs for neighborhood facilities differ among older adults in relation to their mobility, which in turn affects their MH in distinct ways. The results suggest that neighborhood facilities must be designed not only to meet the general supply and demand but also to address the specific needs of older adults, particularly in terms of mobility. For instance, age-friendly facilities are recommended to be implemented at the level of residential neighborhoods, such as public canteens and outdoor fitness locations, which may markedly enhance the MH of older adults. Specifically, outdoor fitness spaces should incorporate rehabilitation equipment that is tailored to the needs of older adults with restricted mobility. These findings have important implications for urban planners and policymakers, who should focus on developing age-friendly facilities that cater to diverse mobility needs.

Author Contributions

Conceptualization, X.K. and H.H.; methodology, X.K.; software, X.K.; formal analysis, X.K.; investigation, X.K., F.C., and M.Z.; data curation, X.K.; writing—original draft preparation, X.K.; writing—review and editing, H.H. and X.S.; visualization, X.K.; funding acquisition, H.H. and X.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Center for Balance Architecture of Zhejiang University (NO. K Heng 20203512-02B, Index and planning methods of resilient cities), the National Natural Science Foundation of China (NO. 72304081), and the Natural Science Foundation of Zhejiang Province (NO. LQ22D010002).

Institutional Review Board Statement

Ethical review and approval were waived for this study due to no biomedical research on humans, according to the Chinese government.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data used in this study are not available to other researchers for replication purposes. The analytic methods and materials are available to other researchers by sending requests to the authors via email. The study reported in the manuscript is a cross-sectional study and was not preregistered.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Sustainability 16 09226 g0a1
Figure A1. Multivariable linear regression models of the mental health of older adults.
Figure A1. Multivariable linear regression models of the mental health of older adults.
Sustainability 16 09226 g0a1
Sustainability 16 09226 g0a2
Figure A2. Multivariable logistic regression models of the mental health of older adults.
Figure A2. Multivariable logistic regression models of the mental health of older adults.
Sustainability 16 09226 g0a2

References

  1. United Nations. World Social Report 2023. 2023. Available online: https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/undesa_pd_2023_wsr-fullreport.pdf (accessed on 30 July 2024).
  2. Cheng, Z.; Si, W.; Xu, Z.; Xiang, K. Prediction of China’s population mortality under limited data. Int. J. Environ. Res. Public. Health 2022, 19, 12371. [Google Scholar] [CrossRef] [PubMed]
  3. Abdoli, N.; Salari, N.; Darvishi, N.; Jafarpour, S.; Solaymani, M.; Mohammadi, M.; Shohaimi, S. The global prevalence of major depressive disorder (MDD) among the elderly: A systematic review and meta-analysis. Neurosci. Biobehav. Rev. 2022, 132, 1067–1073. [Google Scholar] [CrossRef]
  4. Bryant, C.; Jackson, H.; Ames, D. The prevalence of anxiety in older adults: Methodological issues and a review of the literature. J. Affect. Disord. 2008, 109, 233–250. [Google Scholar] [CrossRef] [PubMed]
  5. Li, D.; Zhang, D.J.; Shao, J.J.; Qi, X.D.; Tian, L. A meta-analysis of the prevalence of depressive symptoms in Chinese older adults. Arch. Gerontol. Geriatr. 2014, 58, 1–9. [Google Scholar] [CrossRef]
  6. WHO. Global Age-Friendly Cities: A Guide. 2007. Available online: https://www.who.int/publications/i/item/9789241547307 (accessed on 30 July 2024).
  7. Tuomola, E.M.; Keskinen, K.E.; Rantanen, T.; Portegijs, E. Associations between walking limitations and reported activity destinations among older adults. Eur. J. Ageing 2024, 21, 16. [Google Scholar] [CrossRef]
  8. Tuomola, E.M.; Keskinen, K.E.; Viljanen, A.; Rantanen, T.; Portegijs, E. Neighborhood walkability, walking difficulties, and participation in leisure activities among older people: A cross-sectional study and 4-year follow-up of a subsample. J. Aging Health 2024, 36, 367–378. [Google Scholar] [CrossRef]
  9. Luo, M.; Kim, E.K.; Weibel, R.; Martin, M.; Rocke, C. GPS-derived daily mobility and daily well-being in community-dwelling older adults. Gerontology 2023, 69, 875–887. [Google Scholar] [CrossRef]
  10. Che Had, N.H.; Alavi, K.; Md Akhir, N.; Muhammad Nur, I.R.; Shuhaimi, M.S.Z.; Foong, H.F. A scoping review of the factor associated with older adults’ mobility barriers. Int. J. Environ. Res. Public. Health 2023, 20, 4243. [Google Scholar] [CrossRef]
  11. Fiske, A.; Wetherell, J.L.; Gatz, M. Depression in older adults. Annu. Rev. Clin. Psychol. 2009, 5, 363–389. [Google Scholar] [CrossRef]
  12. Arms, T.E.; Crane, P.B.; McNeill, C.; Horne, C.; Whited, M.C. Life-space constriction in aging adults. Geriatr. Nurs. 2021, 42, 421–426. [Google Scholar] [CrossRef]
  13. Demura, S.; Sato, S. Relationships between depression, lifestyle and quality of life in the community dwelling elderly: A comparison between gender and age groups. J. Physiol. Anthropol. Appl. Hum. Sci. 2003, 22, 159–166. [Google Scholar] [CrossRef] [PubMed]
  14. Polku, H.; Mikkola, T.M.; Portegijs, E.; Rantakokko, M.; Kokko, K.; Kauppinen, M.; Rantanen, T.; Viljanen, A. Life-space mobility and dimensions of depressive symptoms among community-dwelling older adults. Aging Ment. Health 2015, 19, 781–789. [Google Scholar] [CrossRef] [PubMed]
  15. Douma, L.; Steverink, N.; Meijering, L. Geographical life-space and subjective wellbeing in later life. Health Place. 2021, 70, 102608. [Google Scholar] [CrossRef]
  16. Lawton, M.P. Environment and other determinants of well-being in older people. Gerontologist 1983, 23, 349–357. [Google Scholar] [CrossRef]
  17. Lawton, M.P.; Nahemow, L. Ecology and the aging process. In The Psychology of Adult Development and Aging; American Psychological Association: Washington, DC, USA, 1973; pp. 619–674. [Google Scholar]
  18. Ahmed, T.; Curcio, C.L.; Auais, M.; Vafaei, A.; Pirkle, C.M.; Guerra, R.O.; Gomez, F. Falls and life-space mobility: Longitudinal analysis from The International Mobility in Aging Study. Aging Clin. Exp. Res. 2021, 33, 303–310. [Google Scholar] [CrossRef]
  19. Christman, Z.J.; Wilson-Genderson, M.; Heid, A.; Pruchno, R. The effects of neighborhood built environment on walking for leisure and for purpose among older people. Gerontologist 2020, 60, 651–660. [Google Scholar] [CrossRef]
  20. Zhou, J.-J.; Kang, R.; Bai, X. A meta-analysis on the influence of age-friendly environments on older adults’ physical and mental well-being. Int. J. Environ. Res. Public. Health 2022, 19, 13813. [Google Scholar] [CrossRef]
  21. Gibney, S.; Zhang, M.; Brennan, C. Age-friendly environments and psychosocial wellbeing: A study of older urban residents in Ireland. Aging Ment. Health 2020, 24, 2022–2033. [Google Scholar] [CrossRef]
  22. Mu, Y.; Yi, M.; Liu, Q. Association of neighborhood recreational facilities and depressive symptoms among Chinese older adults. BMC Geriatr. 2023, 23, 667. [Google Scholar] [CrossRef]
  23. Luoma-Halkola, H.; Häikiö, L. Independent living with mobility restrictions: Older people’s perceptions of their out-of-home mobility. Ageing Soc. 2020, 42, 249–270. [Google Scholar] [CrossRef]
  24. Sakari, R.; Rantakokko, M.; Portegijs, E.; Iwarsson, S.; Sipila, S.; Viljanen, A.; Rantanen, T. Do associations between perceived environmental and individual characteristics and walking limitations depend on lower extremity performance level? J. Aging Health 2017, 29, 640–656. [Google Scholar] [CrossRef] [PubMed]
  25. Vaughan, M.; LaValley, M.P.; AlHeresh, R.; Keysor, J.J. Which features of the environment impact community participation of older adults? A systematic review and meta-analysis. J. Aging Health 2016, 28, 957–978. [Google Scholar] [CrossRef]
  26. Fitzgerald, K.G.; Caro, F.G. An overview of age-friendly cities and communities around the world. J. Aging Soc. Policy 2014, 26, 1–18. [Google Scholar] [CrossRef]
  27. Park, S.-Y. Intergenerational differences in age-friendly environments and health outcomes: Social support as a mediator. J. Intergenerational Relatsh. 2021, 19, 124–143. [Google Scholar] [CrossRef]
  28. Kong, X.; Han, H.; Zhan, M.; Chi, F. The effects of the built environment on the mental health of older adults: A case study in Hangzhou, China. Innov. Aging 2024, 8, igae037. [Google Scholar] [CrossRef]
  29. Lei, P.; Feng, Z. Age-friendly neighbourhoods and depression among older people in China: Evidence from China Family Panel Studies. J. Affect. Disord. 2021, 286, 187–196. [Google Scholar] [CrossRef]
  30. Tang, J.Y.M.; Chui, C.H.K.; Lou, V.W.Q.; Chiu, R.L.H.; Kwok, R.; Tse, M.; Leung, A.Y.M.; Chau, P.H.; Lum, T.Y.S. The contribution of sense of community to the association between age-friendly built environment and health in a high-density city: A cross-sectional study of middle-aged and older adults in Hong Kong. J. Appl. Gerontol. 2021, 40, 1687–1696. [Google Scholar] [CrossRef]
  31. Park, S.Y.; Kim, M.; Chung, S. Age-friendly environments and depressive symptoms among Korean adults: The mediating effects of loneliness. Aging Ment. Health 2021, 25, 1060–1070. [Google Scholar] [CrossRef]
  32. Zhang, Y.; Zhang, M.; Hu, H.; He, X. Spatio-temporal characteristics of the supply and demand coupling coordination of elderly care service resources in China. Int. J. Environ. Res. Public Health 2022, 19, 10397. [Google Scholar] [CrossRef]
  33. Hangzhou City Goverment. Implementation Opinions on Strengthening Aging Work in the New Era to Create a Livable Paradise of “Healthy Aging, Happy Living”. 2023. Available online: https://www.hangzhou.gov.cn/art/2023/10/23/art_1229660579_59088779.html (accessed on 30 July 2024). (In Chinese)
  34. Chinese Government. Measures for Ethical Approval of Biomedical Research Involving Humans. 2016. Available online: https://www.gov.cn/gongbao/content/2017/content_5227817.htm (accessed on 30 July 2024). (In Chinese)
  35. Lam, C.L.; Tse, E.Y.; Gandek, B. Is the standard SF-12 Health Survey valid and equivalent for a Chinese population. Qual. Life Res. 2005, 14, 539–547. [Google Scholar] [CrossRef]
  36. Ware, J.E.; Keller, S.D.; Kosinski, M. SF-12: How to Score the SF-12 Physical and Mental Health Summary Scales; Health Institute, New England Medical Center: Boston, MA, USA, 1995. [Google Scholar]
  37. Chinese National Health Commission. Notice on the establishment of a model national age-friendly community. Bull. Natl. Health Comm. People’s Repub. China 2020, 12, 45–53. (In Chinese) [Google Scholar]
  38. Downward, P.; Rasciute, S. Does sport make you happy? An analysis of the well-being derived from sports participation. Int. Rev. Appl. Econ. 2011, 25, 331–348. [Google Scholar] [CrossRef]
  39. Freiberger, E.; Sieber, C.C.; Kob, R. Mobility in older community-dwelling persons: A narrative review. Front. Physiol. 2020, 11, 881. [Google Scholar] [CrossRef] [PubMed]
  40. Yan, W.; Dai, Z. A population-diversity-oriented survey on the adaptability of public facilities in urban community for the aged. Archit. J. 2014, 5, 60–64. (In Chinese) [Google Scholar]
  41. Gehl, J. Life Between Buildings; Danish Architectural Press: Copenhagen, Denmark, 2002. [Google Scholar]
  42. Wang, X.; Liu, M.; Li, Y.; Guo, C.; Yeh, C.H. Community canteen services for the rural elderly: Determining impacts on general mental health, nutritional status, satisfaction with life, and social capital. BMC Public Health 2020, 20, 230. [Google Scholar] [CrossRef]
  43. Wennberg, H.; Stahl, A.; Hyden, C. Older pedestrians’ perceptions of the outdoor environment in a year-round perspective. Eur. J. Ageing 2009, 6, 277. [Google Scholar] [CrossRef]
  44. Richard, L.; Gauvin, L.; Gosselin, C.; Laforest, S. Staying connected: Neighbourhood correlates of social participation among older adults living in an urban environment in Montreal, Quebec. Health Promot. Int. 2008, 24, 46–57. [Google Scholar] [CrossRef]
  45. Zhong, X.; Wang, F. The mediating effect of the built environment on the relationship between socioeconomic status and mental health: Findings from the 2019 Shanghai Community Survey. Interdiscip. Nurs. Res. 2023, 2, 172–179. [Google Scholar] [CrossRef]
Sustainability 16 09226 g001
Figure 1. Location map of sampled neighborhoods.
Figure 1. Location map of sampled neighborhoods.
Sustainability 16 09226 g001
Table 1. Evaluation indicators of the neighborhood built environment.
Table 1. Evaluation indicators of the neighborhood built environment.
Independent VariablesDescription
Daily travel1. Barrier-free travelProvide barrier-free travel at the ramps, stairs, and handrails in the public areas of the neighborhood.
2. ElevatorProvide elevators in residential buildings.
3. Rest seatPlace resting benches in key activity areas and passageways of older adults.
4. Diversion of pedestrian and vehicleSeparate driving and walking paths within the neighborhood.
5. Road surfaceThe pedestrian road surface is flat, and no illegal parking on the pedestrian road.
6. Public toiletProvide public toilets near places where the elderly gather together.
Neighborhood services7. Public canteenProvide public canteens.
8. Elderly careSet up medical and health institutions to provide rehabilitation, nursing, and other services for older adults.
Social participation9. Outdoor fitness spaceProvide outdoor fitness spaces.
10. Indoor activity spaceProvide indoor activity spaces.
Table 2. Descriptive statistics for study participants.
Table 2. Descriptive statistics for study participants.
VariablesMean (SD) or N (%)p a
Total
(n = 1405)		Unrestricted Mobility
(n = 1059)		Restricted Mobility
(n = 346)
Mental health (continuous)56.30 (7.17)57.52 (4.65)52.55 (11.12)<0.001
Mental health (categorical)
Positive1197 (85.20)979 (92.45)218 (63.01)<0.001
Negative208 (14.80)80 (7.55)128 (36.99)
Gender
Male605 (43.06)487 (45.99)118 (34.10)<0.001
Female800 (56.94)572 (54.01)228 (65.90)
Age (years old)
60–69461 (32.81)388 (36.64)73 (21.10)<0.001
70–79516 (36.72)385 (36.36)131 (37.86)
>80428 (30.46)286 (27.01)142 (41.04)
Pension (Chinese yuan)
<3000291 (20.71)226 (21.34)65 (18.79)0.415
3000–5000611 (43.49)450 (42.49)161 (46.53)
5000–7000360 (25.62)270 (25.50)90 (26.01)
>7000143 (10.18)113 (10.67)30 (8.67)
Educational level
Secondary school and below1011 (71.96)759 (71.67)252 (72.83)0.677
High school204 (14.52)152 (14.35)52 (15.03)
College and beyond190 (13.52)148 (13.98)42 (12.14)
Household registration
Hangzhou1120 (79.72)833 (78.66)287 (82.95)0.085
Other cities285 (20.28)226 (21.34)59 (17.05)
Lifestyle
Living with family1256 (89.40)960 (90.65)296 (85.55)0.007
Living alone149 (10.60)99 (9.35)50 (14.45)
Length of residency (year)
Living more than 5 years1233 (87.76)916 (86.50)317 (91.62)0.012
Living less than 5 years172 (12.24)143 (13.5)29 (8.38)
Chronic disease
No chronic diseases409 (29.11)375 (35.41)34 (9.83)<0.001
Suffering from chronic disease996 (70.89)684 (64.59)312 (90.17)
a Based on independent t-test or Chi-squared test.
Table 3. Descriptive statistics for neighborhood built environment.
Table 3. Descriptive statistics for neighborhood built environment.
VariablesN (%)
Barrier-free travel22 (73.33%)
Elevator11 (36.67%)
Rest seat17 (56.67%)
Diversion of pedestrian and vehicle3 (10.00%)
Road surface12 (40.00%)
Public toilet17 (56.67%)
Public canteen11 (36.67%)
Elderly care17 (56.67%)
Outdoor fitness space21 (70.00%)
Indoor activity space16 (53.33%)
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Kong, X.; Han, H.; Chi, F.; Zhan, M.; Shu, X. Association Between Neighborhood Built Environment and Mental Health: Differences Between Older Adults With and Without Restricted Mobility. Sustainability 2024, 16, 9226. https://doi.org/10.3390/su16219226

AMA Style

Kong X, Han H, Chi F, Zhan M, Shu X. Association Between Neighborhood Built Environment and Mental Health: Differences Between Older Adults With and Without Restricted Mobility. Sustainability. 2024; 16(21):9226. https://doi.org/10.3390/su16219226

Chicago/Turabian Style

Kong, Xinyu, Haoying Han, Fangting Chi, Mengyao Zhan, and Xianfan Shu. 2024. "Association Between Neighborhood Built Environment and Mental Health: Differences Between Older Adults With and Without Restricted Mobility" Sustainability 16, no. 21: 9226. https://doi.org/10.3390/su16219226

APA Style

Kong, X., Han, H., Chi, F., Zhan, M., & Shu, X. (2024). Association Between Neighborhood Built Environment and Mental Health: Differences Between Older Adults With and Without Restricted Mobility. Sustainability, 16(21), 9226. https://doi.org/10.3390/su16219226

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