The impact of residential environment on older people‘s capabilities to live independently: Evidence from Beijing

doi:10.21203/rs.3.rs-3250370/v1

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The impact of residential environment on older people‘s capabilities to live independently: Evidence from Beijing

https://doi.org/10.21203/rs.3.rs-3250370/v1

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published 17 Mar, 2024

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Noticing the deficiencies of the traditional successful aging model, this study proposes a community-based approach to promote healthy aging that enables older people to adapt and self-manage from the capability approach perspective. Using hierarchical multiple regression analysis of data from 650 older adults (60 years and older) surveyed in Beijing, this study aims to unravel how the residential environment supports Chinese older adults' capabilities to live independently. The results show that inequalities in residential environments cause differences in older adults’ capabilities between neighborhoods. Four environmental factors (namely: home accessibility, pleasant surroundings, meeting opportunities, and life convenience) positively affect older adults’ capabilities to live independently. Meeting opportunities are more relevant for frail older adults. This study contributes to the understanding of how the residential environment supports healthy aging from the capability approach perspective. Results can be used to develop effective community-based policies.

Sen’s capability approach

community-based intervention

residential environment

older people

Traditionally, a complete state of health and physical functioning has been identified as key elements of successful aging (Rowe and Kahn, 1987). Studies have examined environmental factors that influence older people’s health and functional limitations in the home and neighborhood because understanding these factors is critical to achieving successful aging (Choi, 2020; Wood et al., 2022). However, this study argues that the traditional successful aging model itself has its deficiencies because it defines health as an absence of disease. By definition, chronic conditions cannot be reversed through medical treatments. The notion that older adults with chronic conditions are ill underestimates the human capacity to maintain and restore one’s integrity and independence (Huber et al., 2011). Therefore, this study refers to Huber et al. (2011) positive health definition, arguing that health should be defined as the ability to adapt and self-manage in the face of physical, social, and emotional challenges. According to Huber, older adults with chronic conditions can maintain a healthy lifestyle (Huber et al., 2011). There is a need to develop a community-based approach to healthy aging that considers how the residential environment enables older adults to adapt and self-manage (or to live independently).

Sen’s capability approach offers a framework that suggests community-based environmental support that enables older adults to live independently. The fundamental insight of Sen’s capability approach is that the policy focus should be on people’s capabilities to achieve their valued functionings (Sen, 1995; Gopinath, 2018; Chiappero-Martinetti et al., 2020; Stephens et al., 2019; Grove, 2021). In the capability approach, Sen defines capabilities by distinguishing them from functionings. Whereas functionings are various “beings and doings”, capabilities refer to the opportunities of accessing valued functionings (Sen, 1995; Chiappero-Martinetti et al., 2020). The concept of capability emphasizes multiple dimensions of human development (Chiappero-Martinetti et al., 2020; Kimhur, 2022). This multidimensional view of health is relevant because it argues that aging is not (only) defined by declining physical health. Older adults can lead the lives they value despite having chronic conditions. More importantly, the capability approach emphasizes that the extent of freedom of older adults to live the life they value reflects a person’s access to resources. In the literature, there is a recognition that beyond the home, features of the neighborhood environment can support older adults (Stephens et al., 2019; Wood et al., 2022). However, specific ways that environmental factors affect older adults’ capabilities are unclear. This is because various features characterize the residential environment, and the choice of the valued option varies from person to person according to their valued capabilities (Kimhur, 2022). Such extensive diversity makes it difficult to compile a list of environmental features (Chiappero-Martinetti et al., 2020). It is, therefore, crucial to identify which factors of the residential environment enable older people's capabilities to live independently.

Notably, Sen’s capability approach has the advantage of addressing the issue of human diversity (Chiappero-Martinetti et al., 2020). In the capability approach, Sen addresses the concept of the conversion factor, acknowledging that different older adults with different characteristics have different abilities to convert resources into capabilities (Chiappero-Martinetti et al., 2020). Frailty may be one of the personal conversion factors. Frailty is a geriatric condition that makes an individual susceptible to external stressors (Den et al., 2016). Studies have shown that older adults’ needs for an environment are highly likely to vary depending on their frailty level (Van Dijk et al., 2015; Grove, 2021), which implies that the level of frailty as a personal conversion factor influences the degree to which residential environment affect older adults’ capabilities to live independently. Based on a survey of older adults in Beijing, we used hierarchical multiple regression analysis to answer the following research questions:

Which features of the residential environment support older adults’ capabilities to live independently? How do these impacts differ depending on older adults’ frailty levels?

2.1. Older people’s capabilities to live independently

The study distinguishes between physical (occupational performance), social (social networks), and psychological capabilities (mental health). First, older people may encounter physical impairments, such as tiredness and difficulty walking (Ainsworth & De Jonge, 2018). Physical capability refers to older people's ability to perform daily tasks and errands (e.g., work, education, housework, family, and leisure activities) without security concerns. Second, due to a decline in social networks, older adults have an increased risk of loneliness and lack of support (Gobbens et al., 2010). Social capability refers to the ability to connect with others and participate in community activities and public affairs. We consider being able to play a supportive role in the family as a valued social capability for Chinese older people. It is because Chinese older adults assume unlimited responsibility in terms of intergenerational relationships. Even in old age, Chinese older adults continue to care for the well-being of younger generations (Sheng & Settles, 2006). Third, older adults may suffer from depression and anxiety and have difficulty solving daily problems (Gobbens et al., 2010). Psychological capabilities have two dimensions: (1) emotional coping strategies such as "stopping unpleasant feelings and thoughts" (Chesney et al., 2006). (2) problem-based coping strategies (Chesney et al., 2006) that will enable them to deal with challenges.

Supporting these dimensions of capabilities requires attention to the community rather than the individual but communities vary considerably in the residential environment (Stephen et al., 2019). In China, the residential environment differs between four neighborhood types. These four neighborhood types are traditional neighborhoods, which are the oldest residential areas in the inner city; former danwei compounds, which were built for employers during the socialist period; commercial housing which private developers built; and urban villages which are self-built apartments (Madrazo Gonzalez, 2020). There has yet to examine to what extent the residential environment explains the capability differences between different neighborhood types.

2.2. The role of the residential environment

The selection of neighborhood environmental features was limited to those supporting older people’s capabilities to live independently. This study identifies four environmental factors (home accessibility; pleasant surroundings; meeting opportunities; and life convenience) that have the potential to support older people’s capabilities to live independently. First is home accessibility, which includes features such as ease of approach to the home, circulation, and ease of use in the kitchen and bathroom that enables disabled older adults to participate in physical activities (Iwarsson & Ståhl, 2003; Ainsworth & De Jonge, 2018). It has been shown that the home is an activity center where older adults perform meaningful occupations (like sleeping and eating) (Ainsworth & De Jonge, 2018; Afacan, 2019). It is also where family relationships are cultivated (Oswald et al., 2006), and unpleasant emotions can be dealt with (Ainsworth & De Jonge, 2018). Second is a pleasant environment, which is a comfortable and safe living environment within the neighborhood. Typically, older adults’ comfort and security concerns are affected by the status of aging-friendly design, crime, and traffic (Zhang et al., 2020). A tidy, well-maintained place offers older adults comfort, privacy, and security (Oswald et al., 2006). Exposure to the natural environment also stimulates this aspect. Studies have shown that a visual connection with nature and activity in natural green areas contributes to various psychological and health benefits (Sugiyama & Thompson, 2007; Feng et al., 2017). Older adults’ comfort and security concerns are also related to the prevalence of criminal activities such as mugging, attacks, and stealing. These illegal acts harm older adults in their daily lives (Yen et al., 2009). Many neighborhoods, especially those with high densities, also suffer from traffic hazards. Because older adults mostly walk within the community, crossing pedestrian and vehicular routes is dangerous due to personal injuries (Zhang et al., 2020). Third is the meeting opportunities that provide chances for interpersonal communication. Meeting opportunities help buffer loneliness, stress, and alienation and allow older adults to be physically active and socially connected (Feng et al., 2017; Finlay et al., 2019). It also enables people to develop coping strategies to live independently, including sharing information, informal monitoring, and care coordination (Yung et al., 2016). Public spaces can provide meeting opportunities since this is where older adults gather for formal and informal socialization and entertainment (Feng et al., 2017). Having helpful and trustworthy neighbors also stimulates this aspect (Yung et al., 2016). In addition, in China, residents’ committees are crucial institutions for promoting neighborliness, harmony, and cohesiveness; they are responsible for connecting with government authorities and making recommendations about the needs and aspirations of residents (Heberer & Göbel, 2011). Fourth, the neighborhood’s functional component revolves around proximity to services and amenities that support the daily needs of older adults. Studies have shown that urban facilities such as locations for physical exercise (Ruengtam, 2017), medical facilities (Zhang et al., 2020), public transportation, retail, and recreational services are crucial to improving the quality of life for older adults both physically and mentally (Ruengtam, 2017; Zhang et al., 2020). We explore how these aspects of the residential environment enable older people’s capabilities.

The concept of conversion factors acknowledges that older adults have different abilities to convert resources into capabilities (Chiappero-Martinetti et al., 2020; Kimhur, 2022). Frailty may be one of the conversion factors. Studies have shown that although frail and non-frail people share common desires for capabilities such as independence, security, and belonging, their meanings differ. A frail older person may feel independent with the support of home help, while a non-frail older person may feel independent by being able to clean their house by themselves (Van Dijk et al., 2015). The question is, therefore, whether frailty as a conversion factor influences the degree to which the residential environment affects older adults’ capabilities.

2.3. Individual characteristics

Several individual characteristics may also support older adults’ capabilities. First, research has shown that social networks and support from family and friends contribute to better health and well-being (Choi et al., 2018). Second, socioeconomic factors, such as level of education and income, influence older adults’ quality of life. For example, more educated older adults receive more generous pensions and have better access to healthcare facilities than their less educated counterparts (Feng et al., 2017). Third, hukou in China is a crucial institutional factor affecting older adults’ health and well-being. People with a non-local hukou (migrants) do not have the same access to welfare provisions as those with a local hukou (local people) (Liu et al., 2014). Fourth, literature has documented gender differences in resource ownership and control among older adults (Carmel, 2019). Finally, physical impairment is related to older adults’ ability to adapt and self-manage. Frail older adults are constrained to perform daily activities (Ainsworth & De Jonge, 2018). This study hypothesized that these individual characteristics affect older adults’ capabilities to live independently.

Figure 1 presents the conceptual framework to test the following hypotheses: Hypothesis 1. Differences between neighborhood types in older adults’ capabilities levels are attributed to the inequalities in the residential environment. Hypothesis 2. Four environmental factors may positively contribute to older adults’ capabilities to live independently. Hypothesis 3. Older adults’ frailty level may moderate the impact of the residential environment on older adults’ capabilities.

3.1. Data collection

Data for this study were derived from a questionnaire survey titled “community-based intervention for older adults in China.” Data should be collected from older adults to test the hypotheses of the conceptual framework. The first part of the questionnaire is about the general information of respondents, such as age, gender, education, hukou status, income, marital status, and instrumental support older people received from their adult children (a five-point scale ranging from 1 to 5), and social networks (measured by an abbreviated version of Lubben’s Social Network Scale that has six six-point scales ranging from 1 to 6) (Lubben et al., 2006). We also included the cardiovascular health study (CHS) index to measure frailty. The CHS index measures frailty based on older adults’ biophysical syndrome and has a solid foundation in biological theory (Dent et al., 2016). Weight loss, low physical activity, exhaustion, slowness, and weakness are the five indices of CHS. Using these five items, we formed a combination score.

The second part of the questionnaire quantifies the residential environment and capabilities (See Table 1 for measurable items). Participants were asked to rate each item on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The structure of the scale was confirmed based on a pilot survey of 220 respondents. For environmental factors, KMO (0.87) and Bartlett’s Test (χ2 = 2241.36, df = 136, p < 0.001) indicated that the scale was acceptable for factor analysis, and exploratory factor analysis (EFA) indicated a four-factor data structure. For capabilities, KMO (0.89) and Bartlett’s Test (χ2 = 1411.74, df = 66, p < 0.001) indicated that the scale was acceptable for factor analysis, and exploratory factor analysis (EFA) indicated a three-factor data structure. We used an aggregate score for each construct, a higher score denotes higher capability levels and a better residential environment.

Table 1

Measurement items and the results of the reliability and validity test
Measurement items
Capability
Physical capability	Being able to carry out daily tasks and errands (e.g., work, study, housework, family or leisure activities)
	Being able to take care of myself
	Being able to meet the daily demands of life
	Being able to get out and about with no security concerns
Social capability	Being able to find some people to communicate with
	Being able to be socially engaged in community life
	Being able to keep up with current affairs in the public and social domain
	Being able to act as a supportive role in the family
Psychological capability	Being able to take enjoyment from life
	Being able to maintain a cheerful outlook
	Being able to do things that I value
	Being able to cope with problems that occur with aging
Environmental resources
Home Accessibility	Ease of access to the home from the neighborhood
	Ease of activities within the home without any barriers
	Ease of reach to above and below cabinets
	Have a well-furnished bathroom
	Have a well-furnished kitchen
Pleasant surroundings	Have sufficient greening services
	No crossing of pedestrian and vehicular routes
	Efficient cleaning with well-maintained neighborhood facilities
	A safe environment with no crime activities
Meeting opportunities	Having open spaces such as parks and squares
	Having danwei or neighborhood committees to hold activities
	Having trustworthy neighbors
	Having helpful neighbors that help each other
	Having exercise and entertainment facilities nearby
Life convenience	Having the bus stop and subway stations nearby
	Having pharmacies and hospitals nearby
	Having supermarket and vegetable markets nearby
	Cronbach’s alpha	Composite Reliability	AVE
Capability	0.875
Physical capability	0.873	0.875	0.636
Social capability	0.801	0.801	0.503
Psychological capability	0.852	0.853	0.592
Environmental resources	0.859
Home Accessibility	0.879	0.881	0.602
Pleasant surroundings	0.868	0.870	0.628
Meeting opportunities	0.826	0.830	0.555
Life convenience	0.855	0.855	0.596
Discriminant validity score:
Capability	Physical capability	Social capability	Psychological capability
Physical capability	0.798
Social capability	0.455	0.709
Psychological capability	0.498	0.566	0.770
Environmental resources	Home accessibility	Pleasant surroundings	Meeting opportunities	Life convenience
Home Accessibility	0.776
Pleasant surroundings	0.562	0.792
Meeting opportunities	0.134	0.168	0.745
Life convenience	0.188	0.318	0.246	0.772

This paper selected Beijing as the study area. Beijing is one of the most populated cities and one of the big Chinese cities aging most rapidly. By 2030, 30% of its population will be over 60 (Yu & Rosenberg, 2020). We used a stratified sampling method to ensure the sample approximates the older population living in different residential environments (See Fig. 2). Each four types of residence (traditional neighborhoods, former danwei compounds, commercial housing, urban villages) was represented by two communities, and we sampled 100–200 older adults from eight communities. The objectives of this study require the respondents to be over 60 years old and to have some levels of frailty (preferably). 1,283 respondents were approached and 714 respondents completed the questionnaire. Some questionnaires were excluded from analyses due to some missing values. The final calculations are based on 650 respondents, meaning the net response rate is 50.7%.

3.2. Data analysis procedures

Figure 3 presents the methodological steps of the data analysis. The first part is the scale validation. We conducted reliability and validity tests to check the composite reliability and the construct validity (including convergent and discriminant validity) of the measurements (Hair et al., 2010). The second part included three hierarchical multiple regression models using physical (model 1a), social (model 1b), and psychological capabilities (model 1c) as dependent variables in R. Each hierarchical regression analysis included neighborhood type dummies in Model 1 to examine capability differences between different neighborhood types. Model 2 included individual characteristics. Age was not included since frailty is highly correlated with age. Model 3 included four environmental factors to examine the impact of the residential environment on older adults’ capabilities to live independently. Model 4 included the interaction terms between frailty and environmental factors to investigate the moderation effects of frailty.

4.1. Scale validation

The full measurement model shows a good model fit (For older adults’ capabilities to live independently, CFI = 0.991, TLI = 0.989, RMSEA = 0.030, SRMR = 0.031; For environmental factors, CFI = 0.965, TLI = 0.958, RMSEA = 0.051, SRMR = 0.050). In all cases, the factor loadings are above 0.6, indicating that the proposed items are valid indicators of the preconceived theoretical structure. A factor analysis with eigenvalues > 1 indicates a variance explained by the first factor lower than 50%, indicating no common method bias problem (Hair et al., 2010).

The reliability and validity of the items are confirmed (Table 1). First, Cronbach’s alpha coefficients are greater than 0.8 in all cases, and the composite reliability scores are higher than 0.8, indicating that measurable items have good internal and composite reliability (Hair et al., 2010). Second, the correlation test falls within an acceptable range (0.1–0.6), indicating that these dimensions measure different theoretical constructs but are correlated. Third, the AVE scores are higher than 0.5, and the square root of the AVE scores are higher than correlations between different dimensions (Hair et al., 2010). This finding indicates that the measurable items have good convergence and discriminate validity.

4.2. Hierarchical multiple regression

4.2.1. Capability differences between different neighborhood types

Table 2 presents the results of the hierarchical regression analysis. Model 1 confirmed differences between the neighborhood types with respect to the mean capability level. Such capability differences can only partly be attributed to a neighborhood’s socio-demographic composition. In Model 2, although adding individual characteristics resulted in a decrease in the regression coefficients for neighborhood dummies, almost all of them remained significant. The residential environment is dominant in explaining capability differences between neighborhood types. When Model 3 included environmental factors, the effects of neighborhood types on older adults’ capabilities were no longer significant.

Table 2

Results of the hierarchical multiple regression
Dependent Variable	Physical Capability					Social Capability					Psychological Capability
	Model 1a	Model 2a	Model 3a	Model 4a		Model 1b	Model 2b	Model 3b	Model 4b		Model 1c	Model 2c	Model 3c	Model 4c
	B	B	B	B	S.E.	B	B	B	B	S.E.	B	B	B	B	S.E.
(Intercept)	-0.463***	-0.171	0.162	0.150	0.147	-0.264***	-0.789***	-0.547***	-0.553***	0.111	-0.318***	-0.503***	-0.170	-0.162	0.139
Neighborhood type: (ref = traditional hutong)
Former Danwei	0.457***	0.281***	0.123	0.126	0.076	0.313***	0.145*	0.071	0.069	0.057	0.411***	0.243**	0.116	0.110	0.072
Commercial housing	0.694***	0.465***	0.160	0.161	0.089	0.366***	0.145*	0.019	0.013	0.067	0.437***	0.200*	-0.008	-0.018	0.084
Urban village	0.432***	0.237*	0.184	0.191*	0.095	0.195*	0.083	0.091	0.093	0.072	0.170	-0.010	0.018	0.016	0.091
Frailty		-0.302***	-0.275***	-0.275***	0.020		-0.098***	-0.077***	-0.075***	0.015		-0.149***	-0.120***	-0.118***	0.019
Male		0.030	0.038	0.038	0.047		0.000	0.011	0.014	0.036		-0.036	-0.017	-0.014	0.045
Local hukou		-0.068	-0.052	-0.058	0.063		0.109*	0.132**	0.129**	0.047		-0.079	-0.052	-0.052	0.060
Married		-0.010	-0.011	-0.013	0.047		-0.027	-0.024	-0.030	0.036		0.088	0.085	0.079	0.045
Education:(ref = max. primary school)
Junior high or senior high		0.082	0.069	0.068	0.056		0.106*	0.085*	0.084*	0.042		0.054	0.030	0.029	0.053
University or above		-0.017	-0.010	-0.014	0.077		0.139*	0.149*	0.149*	0.058		0.094	0.108	0.111	0.073
Income a: (ref = < 3000 yuan)
3000–5000 yuan		0.056	0.053	0.056	0.068		0.016	0.023	0.017	0.051		-0.029	-0.029	-0.038	0.064
≥ 5000 yuan		0.139	0.068	0.066	0.073		0.082	0.018	0.007	0.055		0.137	0.045	0.033	0.069
Social Network		0.019***	0.014***	0.014***	0.004		0.032***	0.023***	0.024***	0.003		0.023***	0.014***	0.014***	0.004
Instrumental help		0.046*	0.013	0.015	0.020		0.032*	0.015	0.018	0.015		0.064**	0.032	0.033	0.019
Home accessibility			0.238***	0.240***	0.046			0.126***	0.135***	0.035			0.195***	0.206***	0.044
Pleasant surroundings			0.079*	0.075*	0.037			0.065*	0.058*	0.028			0.066	0.060	0.035
Meeting opportunities			0.038	0.038	0.044			0.256***	0.252***	0.033			0.188***	0.185***	0.042
Life convenience			0.089*	0.091*	0.038			0.049	0.051	0.029			0.153***	0.155***	0.036
*Frailty Home accessibility**				-0.004	0.031				0.000	0.023				0.020	0.029
*Frailty Pleasant surroundings**				-0.024	0.027				-0.022	0.020				-0.018	0.025
*Frailty Meeting opportunities**				0.021	0.033				0.090***	0.025				0.086**	0.031
*Frailty Life convenience**				0.004	0.027				-0.001	0.021				-0.007	0.026
N (Observations)	650	650	650	650		650	650	650	650		650	650	650	650
Adjusted R²	0.076	0.387	0.452	0.450		0.041	0.293	0.417	0.426		0.050	0.242	0.362	0.366
Significance levels: * p < 0.05, p < 0.01; *p < 0.001

4.2.2. Determinants of capabilities

Of all of the included variables in Model 2, only three variables: frailty, social networks, and adult children’s instrumental help, were significant. The significant effects are all in the expected direction. According to the standardized BETA of Model 3 (not shown), frailty is the strongest predictor of older adults’ capabilities. As frailty measures physical aspects of health, it is unsurprising that frailty strongly affects physical capability (B= -0.302; p < 0.001). Notably, the effects of frailty from a biomedical perspective on social capability (B = -0.098; p < 0.001) and psychological capability (B = -0.149; p < 0.001) are also significant. The social network has a lower significance level in each of the models than instrumental help, and its effect is even stronger on social capability (B = 0.032; p < 0.001) than on psychological capability (B = 0.023; p < 0.001) and physical capability (B = 0.019; p < 0.001). There is no significant effect of gender, income, or being married or not. Surprisingly, socioeconomic status hardly affects the capabilities of older adults. Model 2b only reveals that people with higher education and local hukou (B = 0.109, p < 0.05) have higher social capabilities

The results of Model 3 indicate that four environmental factors positively affect older adults’ capabilities. The variance accounted for in the models is substantially increased by incorporating these environmental features. Home accessibility was the only factor to significantly impact each type of capability (physical, social, and psychological). Meeting opportunities have a greater impact on social and psychological capability (B = 0.256, p < 0.001; B = 0.188, p < 0.001; respectively). Pleasant surroundings affect physical and social capabilities (although the effects are weaker) but not psychological capabilities. Life convenience (access to facilities) is very important for psychological capability.

4.2.3. Moderation analysis

Two significant interaction terms show up in Model 4: the interaction effect of meeting opportunities and frailty on older adults’ social capability (B = 0.090, p < 0.001) and psychological capability (B = 0.086, p < 0.01). The interaction terms indicate that meeting opportunities have a stronger impact on the social and psychological capabilities of frail older adults.

Noticing the deficiencies successful aging model, this study refers to Huber’s (2011) positive health definition: “the ability to adapt and self-manage in the face of social, physical, and emotional challenges.” We suggest developing a community-based environmental support that enables older adults' capabilities to adapt and self-manage (or to live independently) from the capability approach perspective. Using hierarchical multiple regression analysis, this study discussed the differential impacts of four environmental factors that enable older adults’ capabilities to live independently. We also examined how frailty affects the degree to which the residential environment affects older people’s capabilities to live independently, acknowledging different older adults have different abilities to convert resources into capabilities.

The results show that four environmental factors positively affect older adults’ capabilities to live independently. This finding is consistent with other studies suggesting environment benefits older adults’ health and well-being (Oswald et al., 2006; Zhang et al., 2020). It should be noted that home accessibility was the only environmental factor to have a significant impact on each type (physical, social, and psychological) of capability. This finding aligns with previous research indicating that home modifications are essential in promoting independent living among older individuals (Iwarsson & Ståhl, 2003; Ainsworth & De Jonge, 2018; Afacan, 2019). Apart from home accessibility, this study highlights the role of meeting opportunities in supporting older adults’ capabilities. In line with studies discussing the crucial role that the social environment plays in supporting healthy aging (Yung et al., 2016; Finlay et al., 2019; Grove, 2021), we found that meeting opportunities do not affect the physical capability of older adults, but they significantly contribute to older adults’ social and psychological capabilities.

Four environmental factors we identified explain capability differences between different neighborhood types. The findings of this study suggest that capabilities differences between different neighborhood types can only be partially explained by the socio-demographic composition of the neighborhood. More importantly, the residential environment is dominant in explaining the capability differences between different neighborhood types. In the literature, health policy for older adults focuses on individual behaviors and circumstances, whereas less attention is paid to structural and material barriers that affect older adults’ capabilities (Scharlach, 2012). Our findings, however, support the argument that inequalities in capabilities are more likely explained by inequalities in the older adults’ residential environment rather than by individual behaviors or choices.

Using the concept of conversion factors highlight human diversity. Highlighting human diversity is crucial because it addresses a main criticism of mainstream frameworks: their inability to appreciate and incorporate diversity when examining experiences of aging (Gopinath, 2018). This study found no interaction effect for home accessibility, pleasant surroundings, and life convenience, implying that these environmental conversion factors are equally important for frail and non-frail older adults. That is to say; physical health declines are not the only problem associated with aging. Even non-frail older adults need environmental support. Nevertheless, in line with the literature that has already shown that older adults’ psychological and social needs vary greatly based on their frailty level (Van Dijk et al., 2015; Grove, 2021), the results of moderation analysis show that meeting opportunities significantly impact frail older adults’ psychological and social capabilities. It is possible that frail older people may cut out peripheral social relationships and show a greater focus on access to maintaining nearby relationships (Penningroth & Scott, 2012). Therefore, frail older adults are more susceptible to the impact of meeting opportunities.

This study has policy implications as Chinese policymakers are exploring effective community-based environmental support for older adults (Liu, 2014; Feng et al., 2017). The finding of this study suggests that the policy focus is to support older adults’ capabilities to live independently. The government is advised to consider the importance of the usability of a home, the landscape design of residential areas, the creation of meeting opportunities, and the establishment of urban infrastructure for life convenience. Since there are capability differences between different neighborhood types, community-based policy interventions need to consider contextual appropriateness. In particular, urban renewal programs are supposed to focus primarily on improving conditions in traditional neighborhoods. It is because results show that respondents living in traditional neighborhoods scored lower in capabilities than those living in former danwei compounds and commercial housing. Considering frail older adults are more sensitive to meeting opportunities, the Chinese government is responsible for collecting opinions and considering the social needs of frail older adults.

This study has limitations because the required capability set can vary depending on the cultural context. It may be hypothesized that, for example, Chinese older adults attach more importance to caring about society and making a meaningful contribution. It would be interesting to investigate how older adults in different cultural contexts value different forms of capabilities that enable them to live independently.

The study contributes to the literature by suggesting a community-based environmental support that enables older people’s ability to adapt and self-manage from the capability approach perspective. We found that inequalities in the residential environment explain the capability differences between different neighborhoods. More specifically, four aspects of environmental features (home accessibility, pleasant surroundings, meeting opportunities, and life convenience) positively affect older adults’ capabilities to live independently. Meeting opportunities are more relevant for frail older adults. Results can be used to develop effective community-based policies.

Funding

This work was supported by the Chinese Scholarship Council (Grant Number:201707720051).

Conflict of Interest

We have no conflict of interest to declare.

Acknowledgement

Data, analytic codes or study materials are available to other researchers for replication purposes. They can be accessed by contacting the authors through e-mail.

Afacan, Y. (2019). Extending the importance-performance analysis (IPA) approach to Turkish elderly people’s self-rated home accessibility. Journal of Housing and the Built Environment, 34(2), 619–642. https://doi.org/10.1007/s10901-019-09645-3

Ainsworth, E., & De Jonge, D. (2018). An occupational therapist’s guide to home modification practice (2nd ed.). Thorofare, USA: Slack Incorporated.
Carmel, S. (2019). Health and well-being in late life: Gender differences worldwide. Frontiers in medicine,
https://doi.org/10.3389/fmed.2019.00218
Chesney, M. A., Neilands, T. B., Chambers, D. B., Taylor, J. M., & Folkman, S. (2006). A validity and reliability study of the coping self-efficacy scale. British journal of health psychology, 11(3), 421-437. https://doi.org/10.1348/135910705x53155

Chiappero-Martinetti, E., Osmani, S., & Qizilbash, M. (Eds.). (2020). The Cambridge Handbook of the Capability Approach. Cambridge: Cambridge University Press.
Choi, Y., Kwon, Y. H., & Kim, J. (2018). The effect of the social networks of the elderly on housing choice in Korea. Habitat International, 74, 1–8. https://doi.org/10.1016/j.habitatint.2018.02.003
Choi, Y. J. (2020). Age-friendly features in home and community and the self-reported health and functional limitation of older adults: The role of supportive environments. Journal of Urban Health, 97(4), 471-485. https://doi.org/10.1007/s11524-020-00462-6
Dent, E., Kowal, P., & Hoogendijk, E. O. (2016). Frailty measurement in research and clinical practice: a review. European journal of internal medicine, 31, 3-10. https://doi.org/10.1016/j.ejim.2016.03.007
Feng, J., Tang, S., & Chuai, X. (2017). The impact of neighbourhood environments on quality of life of elderly people: Evidence from Nanjing, China. Urban Studies, 55(9), 2020-2039. https://doi.org/10.1177/0042098017702827

Finlay, J., Esposito, M., Kim, M. H., Gomez-Lopez, I., & Clarke, P. (2019). Closure of ‘third places? Exploring potential consequences for collective health and well-being. Health & place, 60, 102225. https://doi.org/10.1016/j.healthplace.2019.102225

Gobbens, R. J. J., Luijkx, K. G., Wijnen-Sponselee, M. T., & Schols, J. M. G. A. (2010). Towards an integral conceptual model of frailty. The journal of nutrition, health & aging, 14(3), 175-181. https://doi.org/10.1007/s12603-010-0045-6

Gopinath, M. (2018). Thinking about later life: insights from the capability approach. Ageing International, 43(2), 254–264. https://doi.org/10.1007/s12126-018-9323-0
Grove, H. (2021). Ageing as well as you can in place: Applying a geographical lens to the capability approach. Social Science & Medicine, 288, 113525.https://doi.org/10.1016/j.socscimed.2020.113525
Hair, J., Black, C., Babin, J. and Anderson, E. (2010). Multivariate Data Analysis (7th ed.). Upper Saddle River, USA: Prentice Hall Publisher.
Heberer, T., & Göbel, C. (2011). The politics of community building in urban China. New York: Routledge.
Iwarsson, S., & Ståhl, A. (2003). Accessibility, usability and universal design—positioning and definition of concepts describing person-environment relationships. Disability and Rehabilitation, 25(2), 57-66. https://doi.org/10.1080/dre.25.2.57.66

Kimhur, B. (2022). Approach to housing justice from a capability perspective: bridging the gap between ideals and policy practices. Housing Studies, 1-21. https://doi.org/10.1080/02673037.2022.2056148
Liu, Y., Dijst, M., & Geertman, S. (2014). Residential segregation and well-being inequality between local and migrant elderly in Shanghai. Habitat International, 42, 175-185. https://doi.org/10.1016/j.habitatint.2013.12.005

Lubben, J., Blozik, E., Gillmann, G., Iliffe, S., von Renteln Kruse, W., Beck, J. C., & Stuck, A. E. (2006). Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations. The Gerontologist, 46(4), 503-513. https://doi.org/10.1093/geront/46.4.503
Madrazo Gonzalez, B. L. (2020). The changing geography of urban China: social change and spatial re-division at the neighborhood level. Doctoral dissertation, Utrecht University, Utrecht.
Oswald, F., Schilling, O., Wahl, H. W., Fänge, A., Sixsmith, J., & Iwarsson, S. (2006). Homeward bound: Introducing a four-domain model of perceived housing in very old age. Journal of environmental psychology, 26(3), 187-201. https://doi.org/10.1016/j.jenvp.2006.07.002
Penningroth, S. L., & Scott, W. D. (2012). Age-related differences in goals: Testing predictions from selection, optimization, and compensation theory and socioemotional selectivity theory.
The International Journal of Aging and Human Development, 74(2), 87-111. https://doi.org/10.2190/ag.74.2.a

Rowe, J. W., & Kahn, R. L. (1987). Human aging: usual and successful. Science, 237(4811), 143-149.
Ruengtam, P. (2017). Factor analysis of built environment design and management of residential communities for enhancing the well-being of elderly people. Procedia Engineering, 180, 966-974. https://doi.org/10.1016/j.proeng.2017.04.256

Scharlach, A. (2012). Creating aging-friendly communities in the United States. Ageing international, 37, 25-38. https://doi.org/10.1007/s12126-011-9140-1
Sen, A. (1995). Inequality Reexamined. Cambridge: Harvard University Press. Cambridge, MA.
Sheng, X., & Settles, B. H. (2006). Intergenerational relationships and elderly care in China: A global perspective.Current Sociology, 54(2), 293-313. https://doi.org/10.1177/0011392106056747
Stephens, C., Szabó, Á., Allen, J., & Alpass, F. (2019). A capabilities approach to unequal trajectories of healthy aging: The importance of the environment. Journal of aging and health, 31(9), 1527-1548. https://doi.org/10.1177/0898264318779474

Sugiyama, T., & Thompson, C. W. (2007). Older adults’ health, outdoor activity and supportiveness of neighbourhood environments. Landscape and urban planning, 83(2-3), 168-175. https://doi.org/10.1016/j.landurbplan.2007.04.002

Van Dijk, H. M., Cramm, J. M., Van Exel, J. O. B., & Nieboer, A. P. (2015). The ideal neighbourhood for ageing in place as perceived by frail and non-frail community-dwelling older adults. Ageing & Society, 35(8), 1771-1795. https://doi.org/10.1017/S0144686X14000622
Wood, G. E. R., Pykett, J., Daw, P., Agyapong-Badu, S., Banchoff, A., King, A. C., & Stathi, A. (2022). The role of urban environments in promoting active and healthy aging: A systematic scoping review of citizen science approaches. Journal of Urban Health,99(3), 427-456. https://doi.org/10.1007/s11524-022-00622-w

Yen, I. H., Michael, Y. L., & Perdue, L. (2009). Neighborhood environment in studies of health of older adults: a systematic review. American journal of preventive medicine, 37(5), 455-463. https://doi.org/10.1016/j.amepre.2009.06.022

Yu, J., & Rosenberg, M. W. (2020). Aging and the changing urban environment: The relationship between older adults and the living environment in post-reform Beijing, China. Urban Geography, 41(1), 162-181. https://doi.org/10.1080/02723638.2019.1643172
Yung, E. H., Conejos, S., & Chan, E. H. (2016). Social needs of the elderly and active aging in public open spaces in urban renewal. Cities, 52, 114-122. https://doi.org/10.1016/j.cities.2015.11.022
Zhang, F., Li, D., & Chan, A. P. (2020). Diverse contributions of multiple mediators to the impact of perceived neighborhood environment on the overall quality of life of community-dwelling seniors: A cross-sectional study in Nanjing, China. Habitat International, 104, 102253. https://doi.org/10.1016/j.habitatint.2020.102253

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The impact of residential environment on older people‘s capabilities to live independently: Evidence from Beijing

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Abstract

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1. Introduction

2. Conceptual framework

2.1. Older people’s capabilities to live independently

2.2. The role of the residential environment

2.3. Individual characteristics

3. Materials and Methods

3.1. Data collection

3.2. Data analysis procedures

4. Results

4.1. Scale validation

4.2. Hierarchical multiple regression

4.2.1. Capability differences between different neighborhood types

4.2.2. Determinants of capabilities

4.2.3. Moderation analysis

5. Discussion and conclusion

Declarations

References

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