Enhancing Elderly Well-Being: Exploring Interactions between Neighborhood-Built Environment and Outdoor Activities in Old Urban Area

Abstract

China has the world’s largest and fastest-growing elderly population, primarily living in outdated urban residential communities. These aging populations face challenges in outdoor activities (OA) and quality of life (QoL) due to deteriorating neighborhood-built environments (NBE). While upgrading these environments is essential for urban renewal, the specific NBE factors affecting OA and QoL for the elderly are not well understood, creating a gap in existing research. This study addresses this gap by investigating how NBE elements influence the OA and QoL of elderly residents in these communities. This study investigates these interactions by conducting a comprehensive literature review, followed by a questionnaire survey, with data analyzed using factor analysis, correlation analysis, and regression analysis. The results reveal that supermarkets and subways significantly impact the physical health of older adults. Psychological health is primarily shaped by daily activities, social relationships, and self-care ability, with roads, hospitals, and bus stops further affecting daily activities. Social relationships are largely influenced by social activities, which are impacted by grocery markets, subways, and parks. Additionally, self-care ability is affected by leisure and daily activities, as well as the accessibility of supermarkets, grocery markets, subways, and buses. These findings offer valuable insights for government-led initiatives aimed at implementing age-friendly retrofitting of NBEs, ultimately enhancing the OA and QoL of the elderly population.

1. Introduction

According to the World Health Organization, between 2015 and 2050, the proportion of the world’s population (≥60 years old) will rise from 12% to 22% [1]. China, which entered an aging society in 2000, is particularly affected by this trend. By the end of 2023, China’s elderly population (≥60 years old) reached 296.97 million, accounting for 21.1% of the total population [2]. China’s large population base has led to a dramatic increase in the number of older adults, making it the only country with more than 200 million older adults, including 150 million aged 65 and over [3]. Projections indicate that the elderly population will reach 300 million by 2025 and 487 million by 2053 [4]. This rapid growth characterizes China’s aging population situation, marked by a decline in the natural population growth rate, a low total fertility rate, and increased life expectancy.

Population aging is a fundamental national condition for China and a global concern. In 2002, the World Health Organization emphasized the principles of active aging [5], which consider physical, psychological, behavioral, economic, social, and environmental factors to effectively assist governments in addressing aging societies. With the trend of aging becoming more pronounced, the quality of life (QoL) for the older adults is gaining increasing attention. In China, aging in place is prevalent, with most older adults residing in old residential communities [6]. However, the neighborhood-built environment (NBE) in these communities was often not designed and constructed with the older adults’ needs, leading to significant difficulties for them in their outdoor activities (OA) [7].

Despite China’s continuous economic development and rapid urban renewal in recent years, many old residential communities still exist, with NBE increasingly failing to accommodate the essential requirements of the older adults. Long-term exposure to such inadequate environments often results in diminished QoL for the older adults. The experience of developed countries shows that maintaining a sufficient and well-designed NBE greatly enhances the QoL for the older adults [8]. In fact, older adults are more dependent on their living environment than younger individuals are [9]. As older adults experience declines in both physical and psychological health, their need for a supportive living environment intensifies, highlighting the critical importance of NBE quality [10]. Therefore, the Chinese government has prioritized age-friendly retrofitting of old residential communities, aiming to make life more convenient, comfortable, and better for the older adults.

The interaction between neighborhood-built environments and outdoor activities has been extensively studied in urban planning and public health, particularly in aging urban populations. Research demonstrates that factors such as walkability, access to green spaces, and safety are crucial for promoting physical activity in older urban areas, where infrastructure may be deteriorating [11,12]. For instance, proximity to parks and well-maintained public spaces is positively associated with increased physical activity and social interaction, which contribute to improved QoL [13]. However, old urban areas present unique challenges, such as narrow streets, historical preservation, and limited open spaces, which can either facilitate or hinder outdoor activities. Traditional urban layouts often encourage walking and cycling due to mixed land use and close proximity to amenities, yet poor maintenance and high traffic density can create significant barriers [14].

A notable gap in the literature is the discrepancy between residents’ perceptions of their neighborhood environment and objective measures. This gap can significantly impact outdoor activity levels and, consequently, QoL. For instance, residents may perceive their neighborhoods as less safe or walkable than they actually are, leading to reduced outdoor activities [15]. This underscores the importance of integrating both subjective and objective data when studying the impact of the built environment on outdoor activities and QoL [16].

Moreover, the interaction between the built environment and outdoor activities is influenced by social, cultural, and socioeconomic factors. In older urban areas, socioeconomic disparities often result in unequal access to well-maintained public spaces, with lower-income neighborhoods facing more significant barriers [17]. Cultural norms also shape the use of public spaces, as evidenced by studies where culturally tailored interventions, such as community events, effectively encouraged outdoor activities [18]. Recent research has further explored the role of small-scale green spaces, technological innovations, and the specific needs of aging populations. For example, Chang (2023) found that even minor improvements in park amenities can significantly increase outdoor activities in dense urban neighborhoods [19].

Despite these advancements, most existing research focuses on the built environment within old residential communities or aged care facilities, with limited understanding of the key factors affecting the outdoor activities and QoL of older adults in NBEs in old urban areas. This study aims to address this research gap by investigating how NBE factors in older residential communities influence the QoL of older adults. Specifically, this research objectives are to: (1) identify the key NBE factors and OA and QoL constructs based on a literature review; (2) assess how different aspects of the NBE contribute to the OA and QoL of older adults; and (3) provide practical recommendations for the age-friendly transformation of these communities based on the findings. By examining these objectives, this study seeks to offer theoretical support and practical guidance for the age-friendly transformation of old residential communities.

The primary contributions of this study are threefold: (1) providing a detailed examination of how specific NBE components distinctly influence various aspects of older adults’ QoL and OA; (2) identifying how different types of outdoor activities are differently affected by specific NBE features, offering a nuanced understanding of the environment-behavior relationship in older adults; and (3) proposing actionable strategies for policymakers and urban planners to enhance the QoL of older adults through targeted NBE improvements.

2. Materials and Methods

2.1. Key Constructs of NBE, OA, and QoL

(1) Neighborhood-Built Environment Elements

The public transport system, including buses and bus stops, is vital for the daily travel needs of older individuals [20]. A convenient system can reduce the need for prolonged walking and ease travel [21]. However, many lack age-friendly designs, such as accessible bus stops, low steps for boarding, and adequate seating, which negatively affects older adults’ experiences [22]. Research shows that older adults are highly dependent on public transport, and the absence of age-friendly features reduces travel frequency, affecting their social participation and psychological health [23]. Enhancing accessibility, increasing special seating, and optimizing bus stop locations can improve convenience, comfort, and accessibility for older adults [24]. Cities investing in age-friendly renovations see higher travel rates and satisfaction among older adults.

The subway system, a crucial part of urban public transport, is favored by many older adults for its speed, punctuality, and coverage [25]. However, it often lacks adequate barrier-free facilities, clear signage, and appropriate service attitudes. Older passengers frequently face issues such as insufficient lifts, uncomfortable handrail heights, and unclear directional signs [26]. A survey found that some seniors struggle with unclear subway station signage, hindering their ability to navigate accessible routes [27]. Improving barrier-free facilities, installing clearer signs, and offering specialized services can greatly enhance the convenience and safety of subway travel for older adults.

Road design and maintenance directly affect the safety and convenience of older travelers [28]. Flat, spacious walking paths, proper signals at intersections, and barrier-free crossings are essential for older individuals [29]. However, many cities neglect these needs, resulting in uneven road surfaces, poorly marked crossings, and short signal times. Studies indicate that traffic accidents due to short signal times are significantly higher among older adults than other age groups [30]. Improving road design, increasing barrier-free facilities, maintaining road surfaces, and ensuring appropriate signal timings are crucial to enhancing road safety for older adults.

Parks are essential for older adults’ relaxation and exercise [31]. Well-designed parks with appropriate facilities promote relaxation, socialization, and physical activity [32]. However, many parks fail to meet the needs of older adults, featuring uneven walkways, insufficient seating, and a lack of toilets [33]. Research indicates that the levelness of trails and availability of seating directly affect the frequency and duration of park visits by older adults [31]. Improving walkway levelness, adding age-appropriate resting facilities, and installing accessible toilets and safe fitness equipment can greatly enhance the park experience for older adults.

Squares provide essential public spaces for seniors to gather, relax, and exercise [34]. Proper design should include flat surfaces, adequate seating, and shade [35]. However, many squares prioritize aesthetics and commercial uses over the needs of older adults [36]. Research shows that age-friendly square designs significantly boost older adults’ participation in community activities [37]. Enhancing designs, increasing barrier-free facilities, and providing more senior-friendly amenities are crucial to making squares more attractive to older adults.

Supermarkets are essential for seniors’ daily shopping needs, and a convenient layout can significantly enhance their experience [38]. Common issues for older shoppers include uncomfortable shelf heights, narrow aisles, and long checkout times [39]. Surveys show that seniors always prefer supermarkets with lower shelves and wider aisles for easier selection and trolley use [40]. Optimizing layouts, providing special aisles and checkout services, and installing lower shelves can greatly improve shopping convenience and comfort for older adults.

Grocery markets are crucial for older adults’ daily activities and socialization but often pose inconveniences and safety hazards due to their complex and congested environments [41,42]. While these markets offer fresh food and social opportunities, they also present high risks of falls and theft for older adults [43]. Improving accessibility, optimizing stall layouts, and creating special pathways and rest areas can enhance the safety and comfort of grocery markets for older adults.

Hospitals are essential for older adults, requiring convenient medical services and barrier-free facilities [44]. Older adults often face long queues, uncomfortable waiting areas, and unclear medical information [45]. Research shows that barrier-free facilities and age-friendly service attitudes significantly improve the medical experience and satisfaction of older adults [46]. Optimizing service flows, providing special registration and waiting lanes, and installing clear signs and barrier-free facilities can enhance the medical experience for older adults.

(2) Outdoor Activities

Leisure activities are vital for the physical and mental health of older adults [47]. Activities such as walking, fitness exercises, traveling, and gardening help maintain leisure vitality, improve mood, and foster social interaction [48]. Research shows that older adults who engage in leisure activities are less likely to experience depressive symptoms and cognitive decline [49]. However, physical deterioration often leads to challenges such as uncomfortable venues, inadequate facilities, and safety hazards [50]. Providing age-appropriate venues and facilities, diversifying community activities, and ensuring safe environments can promote active participation and enhance the QoL for older adults.

Social activities are crucial for the psychological health and social connections of older adults [51]. Engaging in community gatherings, interest groups, and volunteering helps them build and maintain social networks, reducing loneliness [52]. Research shows that older adults who frequently participate in social activities have a more positive mindset and higher life satisfaction [53]. However, they often face challenges such as inconvenient transportation, difficulty accessing information, and a lack of social venues [54]. Providing convenient transport, establishing information platforms, and increasing social venues and activities can help older adults integrate into society and improve their psychological health.

Daily activities such as shopping, household chores, and hobbies are integral to the lives of older adults [55]. They often encounter challenges due to physical limitations and discomfort with tools and equipment [56]. Research shows that older adults who can independently carry out these activities tend to have higher self-esteem and life satisfaction [57]. Offering community support services, providing age-appropriate tools and equipment, and organizing training can help older adults improve their self-care abilities and overall satisfaction with life.

(3) Quality of Life

Physical health is crucial for the QoL among older individuals, enabling them to engage actively and enjoy life [58]. However, aging often brings health challenges such as chronic diseases and mobility issues [59]. Research highlights the importance of OA for maintaining physical health in older adults [60]. Creating a supportive environment through targeted environmental modifications can further enhance their physical well-being and overall QoL.

Psychological health greatly affects the overall QoL for older individuals [61]. A positive state of psychological health helps older adults cope with life’s challenges and maintain an optimistic outlook [62]. However, older adults often face psychological issues such as loneliness, anxiety, and depression [63]. Research has shown that psychosocial health support services and participation in social activities are vital for enhancing psychological health [64]. Providing psychological counseling services, organizing community support activities, and establishing social networks for older adults can help maintain their psychological well-being and improve their QoL.

Strong social relationships are crucial for the well-being of older adults, providing them with support and connection [65]. Research shows that these relationships significantly enhance life satisfaction and psychological health [66]. Promoting interactions within families, creating community communication platforms, and organizing social activities can help older adults build and maintain meaningful social connections [67]. This fosters a sense of belonging and enhances their overall life satisfaction.

Self-care ability is crucial for older individuals’ independence and QoL, enabling them to navigate their environment independently [68]. However, this ability may decline with age. Research indicates that adaptive training and support services can effectively enhance self-care among older adults [69]. Providing adaptive community environments and offering assistive devices and services can support older adults in maintaining and improving their self-care ability [70]. This approach helps safeguard their independence and enhances their overall QoL.

2.2. Measurement Tool

To thoroughly investigate the neighborhood-built environments (NBE) of older residential communities and their impact on outdoor activities (OA) and quality of life (QoL) among older adults, a carefully designed measurement tool was employed. This tool, a comprehensive questionnaire, was meticulously crafted based on an extensive review of relevant literature to ensure it accurately captures the perceptions and experiences of older residents, as illustrated in

Table 1. Variables adopted in the questionnaire and their sources.

Category	Variables	No. of Questions	Key References
Neighbourhood built environment	Bus	3	[20,21,22]
	Bus stop	3	[22,23,24]
	Subway	4	[25,26,27]
	Road	3	[28,29,30]
	Park	3	[31,32,33]
	Square	2	[34,35,36,37]
	Supermarket	4	[38,39,40]
	Grocery market	5	[41,42,43]
	Hospital	3	[44,45,46]
Outdoor activity	Leisure activity	4	[47,48,49,50]
	Social activity	3	[51,52,53,54]
	Daily activity	3	[55,56,57]
Quality of life	Physical health	4	[58,59,60]
	Psychological health	3	[61,62,63,64]
	Social relationship	5	[65,66,67]
	Self-care ability	5	[68,69,70]

.

The questionnaire is composed of four key sections. The Section 1 collects demographic information, including age, gender, education, and income—variables essential for understanding how individuals interact with their environment and perceive their quality of life. The Section 2 focuses on NBE, covering factors such as accessibility, safety, and the availability of amenities, all of which are critical components of a supportive built environment for older adults. The Section 3 examines OA, exploring the frequency, type, and satisfaction with outdoor activities, which are crucial for maintaining both physical and mental well-being in later life. The Section 4 addresses QoL, employing established and validated measurement tools widely recognized in the field. This section assesses multiple dimensions of quality of life, including physical health, psychological health, social relationships, and self-care ability.

Utilizing a 5-point Likert scale, where respondents rate their satisfaction from 1 (very dissatisfied or strongly disagree) to 5 (very satisfied or strongly agree), the questionnaire offers nuanced insights into the degree of satisfaction with various aspects of their lives and environments.

2.3. Validation of Questionnaire Data

To obtain the valid questionnaire, a rigorous multi-step process was employed, as depicted in Figure 1. Initially, a comprehensive literature review was conducted to identify and synthesize key constructs relevant to this study’s objectives, ensuring that the questionnaire items were both theoretically sound and contextually appropriate. Pre-testing was then conducted with a pilot sample representative of the target population, allowing for the refinement of items based on feedback related to clarity, relevance, and interpretability. Rigorous screening criteria were applied to returned questionnaires to ensure data authenticity, excluding those with over 50% unanswered questions, identical responses throughout, duplicates, multiple responses to single-choice questions, and patterned responses. Finally, statistical analyses, including reliability analysis and exploratory factor analysis, were performed to assess the construct validity of the questionnaire, ensuring that the items reliably measured the underlying constructs and that the questionnaire as a whole was a valid tool for this research. This systematic approach to validation was essential to guarantee that the data collected would be both reliable and meaningful for addressing this research questions.

2.4. Data Collection and Statistical Analysis

A questionnaire survey was conducted from May 2023 to February 2024 among older residents living in old residential communities within urban Nanjing, Jiangsu Province, to understand their perceptions of the NBE. Stratified sampling was employed, targeting individuals: (1) aged 60 and above, (2) residing in communities built before 2000, (3) capable of self-care, and (4) frequently visiting their neighborhood environment. Due to considerations of cognitive abilities, paper questionnaires were distributed and collected offline by trained undergraduate and postgraduate students. Clear explanations were provided to ensure accurate responses.

A total of 356 valid questionnaires were collected and analyzed using SPSS 25.0 software. The primary methods of analysis included reliability analysis, factor analysis, correlation analysis, and regression analysis.

(1)

Reliability analysis

Reliability analysis is used to assess the stability and consistency of a measurement tool across different contexts or time points [71]. The reliability of the data were primarily evaluated through internal consistency using Cronbach’s Alpha, which is calculated as:

$$\mathsf{\alpha }={\displaystyle \frac{N\ast \overline{c}}{\overline{v}+\left(N-1\right)\ast \overline{c}}}$$

(1)

where:

-

N is the number of items (questions) in the questionnaire.

-

$\overline{c}$ is the average covariance between item pairs.

-

$\overline{v}$ is the average variance of each item.

Cronbach’s Alpha ranges from 0 to 1, with a value closer to 1 indicating higher reliability. In this study, a Cronbach’s Alpha of 0.8 or higher was required for overall reliability, with subscales needing at least 0.7 to be considered acceptable for internal consistency [72]. This step ensures the accuracy and validity of subsequent data analysis.

(2)

Factor analysis

Factor analysis, a data reduction technique, was utilized in this study to identify and extract latent variables from the data. The analysis began with the assessment of data suitability using the Kaiser–Meyer–Olkin (KMO) measure and Bartlett’s test of sphericity [73]. The KMO statistic is given by:

$$KMO={\displaystyle \frac{\sum \sum r_{ij}^2}{\sum \sum r_{ij}^2+\sum \sum a_{ij}^2}}$$

(2)

where:

-

$r_{ij}$ is the correlation between variables.

-

$a_{ij}$ is the partial correlation between variables.

A KMO value greater than 0.7 and a significant Bartlett’s test (p < 0.05) indicated the suitability of the data for factor analysis [73]. Factor extraction was conducted using Principal Component Analysis (PCA) or Maximum Likelihood (ML), where factors with eigenvalues greater than 1 were retained. Factor extraction methods, including principal component analysis or maximum likelihood, were appropriately selected, and the number of factors was determined using eigenvalues greater than one [74]. Varimax rotation was employed to facilitate factor interpretation, with factor loadings above 0.5 indicating strong associations [75].

(3)

Correlation analysis

Correlation analysis was performed to measure the strength and direction of the relationship between variables using Pearson’s correlation coefficient, calculated as:

$$r_{xy}={\displaystyle \frac{{\sum }_{i=1}^n(X_i-\overline{X})(Y_i-\overline{Y})}{\sqrt{{\sum }_{i=1}^n{(X_i-\overline{X})}^2}\times \sqrt{{\sum }_{i=1}^n{(Y_i-\overline{Y})}^2}}}$$

(3)

where:

-

X and Y are individual sample points.

-

$\overline{X}$ and $\overline{Y}$ are the means of the X and Y variables, respectively.

Both the correlation coefficient matrix and significance levels (p-values) were scrutinized. The Pearson correlation coefficient ranges from −1 to 1, with higher absolute values indicating stronger correlations [76]. A p-value less than 0.05 denoted a significant correlation [77].

(4)

Regression analysis

Regression analysis was conducted to assess the impact of independent variables on the dependent variable using linear regression models. The linear regression equation is:

$$Y={\beta }_0+{\beta }_1{X}_1+{\beta }_2{X}_2+\cdots +{\beta }_k{X}_k+ϵ$$

(4)

where:

-

Y is the dependent variable.

-

X₁, X₂, …, X_n are the independent variables.

-

β₀ is the intercept.

-

β₁, β₂, …, β_n are the regression coefficients.

-

ε is the error term.

Analysis included examination of the R-squared value for model fit, regression coefficients to determine effect size and direction, significance levels (p-values), and residual analysis [78]. A well-fitted model was indicated by an R-squared value exceeding 0.5, while p-values below 0.05 signified significant effects [79]. These analyses provided robust data support for this study’s conclusions.

3. Results

3.1. Demographic Information of the Respondents

A total of 356 valid questionnaires were collected for this study. Descriptive statistics were analyzed for respondents’ personal information (see

Table 2. Demographic information of the respondents.

Category	Items	Frequency	Percentage
Age	60–69	259	72.75%
	70–79	76	21.35%
	80–89	18	5.06%
	>90	3	0.84%
Gender	Male	171	48.03%
	Female	185	51.97%
Living period	≤1 year	5	1.40%
	1–5 years	55	15.45%
	6–10 years	73	20.51%
	11–15 years	119	33.43%
	≥16 years	104	29.21%
Education	Junior middle school and below	220	61.80%
	Senior middle school	87	24.44%
	Junior college	31	8.71%
	Bachelor and above	18	5.06%
Marital status	Unmarried	9	2.53%
	Married	302	84.83%
	Divorced	27	7.58%
	Widowed	18	5.06%
Living Arrangement	Without children	254	71.35%
	With children	102	28.65%

). The results showed that 72.75% of participants were aged 61–69, 21.35% were aged 70–79, 5.06% were aged 80–89, and 0.84% were over 90 years old. In terms of length of residency, the majority had lived in the neighborhood for 11–15 years (33.43%), followed by 16 or more years (29.21%). A minority had resided for less than one year (1.40%), suggesting respondents had sufficient tenure to provide reliable perceptions. Most respondents had completed junior high school or below (61.80%), while those with a high school education accounted for 24.44%. Secondary school graduates and those with a bachelor’s degree or higher comprised 8.71% and 5.06%, respectively.

3.2. Results of Factor Analysis

Factor analysis identified nine main dimensions within the neighborhood-built environment (NBE) category (see

Table 3. Results of factor analysis for the neighborhood-built environment.

NBE Factors	Items	Description	Factor Loading	Alpha
F1-Bus	1	Height of bus seats.	0.805	0.704
	2	Comfort of bus seats.	0.747
	3	Anti-slip design of bus seat surfaces.	0.727
F2-Bus stop	1	Real-time bus electronic information screens at bus stops.	0.857	0.759
	2	Night-time visibility of route signs at bus stops.	0.832
	3	Space at bus stops.	0.793
F3-Subway	1	Clarity of subway arrival signage.	0.853	0.764
	2	Clarity of subway arrival voice prompts.	0.714
	3	Handrail settings on subway seats.	0.697
	4	Subway entrance signage.	0.670
F4-Road	1	Accessibility of roads.	0.758	0.674
	2	Integrity of road manhole covers.	0.719
	3	Cleanliness of roadside areas.	0.666
F5-Park	1	Number of public leisure seats in parks.	0.821	0.724
	2	Shading facilities at public leisure seats in parks.	0.803
	3	Number of toilets in parks.	0.681
F6-Square	1	Number of leisure seats in squares.	0.883	0.721
	2	Public drinking facilities in squares.	0.800
F7-Supermarket	1	Elderly-friendliness of supermarket entrance thresholds.	0.805	0.712
	2	Gentle slope design at supermarket entrances.	0.796
	3	Accessibility design of stairs at supermarket entrances.	0.666
	4	Lack of handrails on stairs at supermarket entrances.	0.650
F8-Grocery market	1	Flatness of ground paving in grocery markets.	0.847	0.769
	2	Number of garbage bins in grocery markets.	0.663
	3	Anti-slip condition of grocery market grounds.	0.657
	4	Lighting quality in grocery markets.	0.646
	5	Environmental sanitation issues in grocery markets.	0.610
F9-Hospital	1	Gentle slope design at hospital entrances.	0.86	0.732
	2	Anti-slip treatment at hospital entrances.	0.778
	3	Handrail design on hospital stairs.	0.731

), each showing significant factor loadings and high reliability coefficients (alpha values). Factors such as bus (F1) focused on seating design (factor loadings 0.727–0.805, α = 0.704), bus stop (F2) on information and facility design (loadings 0.505–0.857, α = 0.759), subway (F3) on signage and seating (loadings 0.583–0.853, α = 0.764), and road (F4) on road facilities (loadings 0.591–0.758, α = 0.674). Public spaces such as parks (F5, loadings 0.681–0.821, α = 0.724) and squares (F6, loadings 0.800–0.883, α = 0.721) exhibited high reliability. Daily activity locations—supermarkets (F7), grocery markets (F8), and hospitals (F9)—also showed robust factor loadings with reliability coefficients above 0.7, confirming the validity and consistency of the factors in measuring public facility issues.

The factor analysis results indicated high reliability and significant factor loading values for all activities within the OA factor, as illustrated in

Table 4. Results of factor analysis for outdoor activities.

OA	Items	Description	Factor Loading	Alpha
OA1-Leisure activity	1	Tai Chi, Square Dancing, etc.	0.811	0.877
	2	Ball sports such as Ping Pong, Badminton, etc.	0.777
	3	Using fitness facilities.	0.769
	4	Playing cards/chess.	0.712
OA2-Social activity	1	Visiting children’s homes.	0.846	0.85
	2	Visiting neighbors.	0.765
	3	Visiting friends’ homes.	0.715
	4	Sunbathing.	0.635
OA3-Daily activity	1	Buying daily necessities.	0.801	0.748
	2	Shopping in malls.	0.778
	3	Picking up packages.	0.689

. For instance, in the leisure activity (OA1), activities such as exercise (Tai Chi, Square Dancing, etc.) showed factor loadings of 0.811 with an alpha value of 0.877, while playing ball games (ping-pong, badminton, etc.) had a loading of 0.777. Other activities such as housework (raising children), relaxation (playing cards/chess), and socializing (participating in public welfare) displayed loadings of 0.769, 0.712, and 0.621, respectively. In the social activity (OA2), socializing activities such as visiting children’s houses and neighbors, as well as relaxing and exercising, showed loadings ranging from 0.653 to 0.846, with an alpha value of 0.850. The daily activities (OA3) exhibited loadings of 0.801 for activities such as going to the post office, with other activities such as going to the library and walking pets showing loadings of 0.778 and 0.668, respectively. Overall, these findings indicate high consistency and reliability in the factor analysis, with factor loadings and alpha values demonstrating strong validity in measuring OA.

This study employed factor analysis to assess quality of life (QoL), identifying four main factors as shown in

Table 5. Results of factor analysis for quality of life.

QoL Factors	Items	Description	Factor Loading	Alpha
Q1-Physical health	1	My sleep quality is very good.	0.809	0.782
	2	My memory is very good.	0.775
	3	My appetite is very good.	0.747
	4	I feel my physical condition is very healthy.	0.721
Q2-Psychological health	1	I find life very interesting.	0.866	0.823
	2	I feel very happy.	0.847
	3	I feel very youthful.	0.810
Q3-Social relationship	1	I am very satisfied with the support I receive from my family.	0.836	0.815
	2	I am very satisfied with my social relationships.	0.707
	3	I have a pleasant relationship with my family.	0.801
	4	Friends often come to chat with me.	0.760
	5	I have a harmonious relationship with my neighbors.	0.628
Q4-Self-care ability	1	I can go out independently.	0.877	0.848
	2	I can arrange my daily meals.	0.820
	3	I can seek medical treatment for minor ailments by myself.	0.808
	4	I have ample energy to cope with daily life.	0.749
	5	I can drive non-motorized vehicles independently.	0.642

. Physical health (Q1) encompassed factors such as quality of sleep (loading 0.809), memory (loading 0.775), appetite (loading 0.747), and overall physical well-being (loading 0.721), with an alpha value of 0.782, indicating high internal consistency. Psychological health (Q2) included interest in life (loading 0.866), happiness (loading 0.847), and feeling youthful (loading 0.810), with an alpha value of 0.823, also demonstrating strong internal consistency. Social relationships (Q3) covered satisfaction with family support (loading 0.836), social relationships (loading 0.707), family harmony (loading 0.801), friendships (loading 0.760), and neighborhood relations (loading 0.628), with an alpha value of 0.815, indicating high reliability. Self-care ability (Q4) included independence in going out (loading 0.877), meal preparation (loading 0.820), managing medical care (loading 0.808), coping energy (loading 0.749), and vehicle operation (loading 0.642), with an alpha of 0.848, indicating good internal consistency.

3.3. Results of Correlation Analysis

To illustrate the correlation between the NBE in old residential communities, the OA of older adults, and their QoL, a series of correlation analyses were conducted. These analyses focused on three groups of factors: NBE, older adults’ OA, and QoL. The correlations were examined using Pearson correlation coefficients at a significance level of 0.01 and above.

The correlation analysis between NBE and OA (see Table 5) indicated significant associations. For leisure activities of the older adults, there were positive correlations with the bus stop (F2: 0.371), road (F4: 0.495), square (F6: 0.322), and grocery market (F8: 0.428) factors of the NBE. Social activities of the older adults showed correlations with the bus (F1: 0.302), bus stop (F2: 0.338), subway (F3: 0.299), road (F4: 0.411), park (F5: 0.339), and grocery market (F8: 0.545) factors. Daily activities of older adults were correlated with the bus stop (F2: 0.419), road (F4: 0.593), park (F5: 0.353), grocery market (F8: 0.420), and hospital (F9: 0.481). These results indicate that the OA of the older adults is closely related to various aspects of the NBE, as demonstrated in

Table 6. Result of correlation analysis between outdoor activities and Neighborhood built environment.

Factors	OA1-Leisure Activity	OA2-Social Activity	OA3-Daily Activity
F1-Bus	0.222	0.302 **	0.241 *
F2-Bus stop	0.371 **	0.338 **	0.419 **
F3-Subway	0.291 *	0.299 **	0.117
F4-Road	0.495 **	0.411 **	0.593 **
F5-Park	0.428 **	0.339 **	0.353 **
F6-Square	0.322 **	0.160	0.225
F7-Supermarket	0.152	0.088	0.203
F8-Grocery market	0.284 *	0.545 **	0.420 **
F9-Hospital	0.283 *	0.236 *	0.481 **

Note: **—Significantly correlated at the 0.01 level. *—Significantly correlated at the 0.05 level.

.

In the correlation analysis between QoL and OA factors of the older adults (see

Table 7. Result of correlation analysis between quality of life and outdoor activities.

Factors	OA1-Leisure Activity	OA2-Social Activity	OA3-Daily Activity
Q1-Physical health	0.406 **	0.354 **	0.348 **
Q2-Psychological health	0.514 **	0.592 **	0.532 **
Q3-Social relationship	0.381 **	0.641 **	0.220 *
Q4-Self-care ability	0.565 **	0.561 **	0.343 **

Note: **—Significantly correlated at the 0.01 level. *—Significantly correlated at the 0.05 level.

), it was found that leisure activities were positively correlated with physical health (Q1: 0.406), psychological health (Q2: 0.514), social relationships (Q3: 0.381), and self-care ability (Q4: 0.565). Social activities of older adults were correlated with physical health (Q1: 0.354), psychological health (Q2: 0.592), social relationships (Q3: 0.641), and self-care ability (Q4: 0.561). Daily activities of older adults showed correlations with physical health (Q1: 0.348), psychological health (Q2: 0.532), and self-care ability (Q4: 0.343). These findings suggest that the OA of the older adults are closely related to their QoL.

The correlation analysis between NBE and QoL factors of the older adults (see

Table 8. Result of correlation analysis between neighborhood-built environment and quality of life.

Factors	Q1-Physical Health	Q2-Psychological Health	Q3-Social Relationship	Q4-Self-Care Ability
F1-Bus	0.2	0.273 *	0.334 **	0.127
F2-Bus stop	0.182	0.289 *	0.305 **	0.262 *
F3-Subway	0.490 **	0.360 **	0.302 **	0.430 **
F4-Road	0.214	0.296 **	0.283 *	0.227
F5-Park	0.21	0.330 **	0.219	0.152
F6-Square	0.22	0.073	0.001	0.086
F7-Supermarket	0.317**	0.153	0.121	0.324 **
F8-Grocery market	0.01	0.256 *	0.307 **	0.367 **
F9-Hospital	0.204	0.283 *	0.159	0.206

Note: **—Significantly correlated at the 0.01 level. *—Significantly correlated at the 0.05 level.

) revealed several significant relationships. Physical health of the older adults was positively correlated with bus (F1: 0.352) and supermarket (F7: 0.317). Psychological health was correlated with subway (F3: −0.360), road (F4: 0.296), and Park (F5: −0.330). Social relationships were correlated with bus (F1: −0.334), bus stop (F2: −0.305), subway (F3: −0.302), and grocery market (F8: 0.307). Self-care ability was related to subway (F3: −0.430), supermarket (F7: 0.324), and grocery market (F8: 0.367). These results indicate that the QoL of the older adults is closely related to various factors of the NBE.

3.4. Results of Regression Analysis

3.4.1. Regression Analysis for Outdoor Activities

Through linear regression analysis of the NBE, older adults’ OA, and their QoL, several significant influences and relationships were identified, as shown in

Table 9. Results of regression analysis for outdoor activities.

Model		Factors	B	SE	t	Sig.	VIF	R	R2	Significance (ANOVA)
Leisure activity ← NBE, OA, QoL
1		(Constant)	0.131	0.952	0.137	0.891		0.725	0.526	0.000
	Q4	Self-care ability	0.701	0.118	5.923	0.000	1.148
	F4	Road	0.726	0.175	4.159	0.000	1.138
	F6	Square	0.374	0.134	2.796	0.007	1.152
	F7	Supermarket	0.374	0.182	2.054	0.044	1.258
Social activity ← NBE, OA, QoL
2		(Constant)	0.875	0.684	1.279	0.205		0.803	0.645	0.000
	Q3	Social relationship	0.537	0.120	4.478	0.000	1.352
	F8	Grocery market	0.700	0.119	5.894	0.000	1.203
	F3	Subway	0.333	0.099	3.360	0.001	1.205
	F5	Park	0.266	0.085	3.117	0.003	1.056
Daily activity ← NBE, OA, QoL
3		(Constant)	0.537	0.591	0.907	0.367		0.751	0.564	0.000
	F4	Road	0.456	0.110	4.153	0.000	1.269
	Q2	Psychological health	0.286	0.080	3.566	0.001	1.192
	F9	Hospital	0.232	0.097	2.388	0.020	1.234
	F2	Bus stop	0.200	0.087	2.290	0.025	1.138

. Model 1 analyzed the relationship between leisure activity and NBE, physical health, psychological health, social relationships, and self-care ability. The results showed that self-care ability (Q4) had a significant positive effect on leisure activity (B = 0.701, t = 5.923, p < 0.001). Similarly, road (F4) (B = 0.726, t = 4.159, p < 0.001), square (F6) (B = 0.374, t = 2.796, p = 0.007), and supermarket (F7) (B = 0.374, t = 2.054, p = 0.044) also had significant positive effects on leisure activity. The model had an R-value of 0.725, R² of 0.526, and significance (ANOVA) of 0.000, indicating a good fit.

Model 2 analyzed the relationship between social activity and NBE, physical health, psychological health, social relationships, and self-care ability. The results showed that social relationships (Q3) had a significant positive effect on social activity (B = 0.537, t = 4.478, p < 0.001). Additionally, grocery market (F8) (B = 0.700, t = 5.894, p < 0.001), subway (F3) (B = 0.333, t = 3.360, p = 0.001), and park (F5) (B = 0.266, t = 3.117, p = 0.003) also had significant positive effects on social activity. This model had an R-value of 0.803, an R² of 0.645, and a significance (ANOVA) of 0.000, indicating strong explanatory power.

Model 3 analyzed the relationship between NBE and OA, physical health, psychological health, social relationships, and self-care ability. The results showed that road (F4) (B = 0.456, t = 4.153, p < 0.001) and psychological health (Q2) (B = 0.286, t = 3.566, p = 0.001) had significant positive effects on daily activity. Additionally, hospital (F9) (B = 0.232, t = 2.388, p = 0.020) and bus stop (F2) (B = 0.200, t = 2.290, p = 0.025) also had significant positive effects. This model had an R-value of 0.751, an R² of 0.564, and a significance (ANOVA) of 0.000, indicating a good fit.

3.4.2. Regression Analysis for Quality of Life

By analyzing the linear regression between NBE, older adults’ OA, and their QoL, several significant influences and relationships were identified (see

Table 10. Results of regression analysis for elders’ quality of life.

Model		Factors	B	SE	t	Sig.	VIF	R	R2	Significance (ANOVA)
Physical health ← NBE, OA, QoL
4		(Constant)	1.026	0.462	2.219	0.030		0.789	0.623	0.000
	Q2	Psychological health	0.566	0.080	7.096	0.000	1.188
	F3	Subway	0.327	0.086	3.805	0.000	1.163
	F7	Supermarket	0.325	0.098	3.305	0.001	1.036
Psychological health ← NBE, OA, QoL
5		(Constant)	0.108	0.240	0.451	0.653		0.885	0.783	0.000
	Q4	Self-care ability	0.211	0.069	3.066	0.003	1.897
	Q3	Social relationship	0.477	0.084	5.643	0.000	1.492
	Q2	Physical health	0.362	0.072	5.063	0.000	1.669
	OA3	Daily activity	0.176	0.068	2.597	0.011	1.284
Social relationship ← NBE, OA, QoL
6		(Constant)	1.623	0.276	5.885	0.000		0.779	0.607	0.000
	Q2	Psychological health	0.452	0.077	5.886	0.000	1.647
	OA2	Social activities	0.202	0.065	3.091	0.003	1.622
	F7	Supermarket	0.191	0.082	2.336	0.022	1.078
Self-care ability ← NBE, OA, QoL
7		(Constant)	0.654	0.506	1.293	0.201		0.895	0.800	0.000
	Q2	Psychological health	0.361	0.111	3.258	0.002	3.204
	OA1	Leisure activity	0.269	0.065	4.118	0.000	2.508
	F7	Supermarket	0.418	0.093	4.488	0.000	1.305
	OA3	Daily activity	0.355	0.098	3.613	0.001	2.182
	F8	Grocery market	0.453	0.100	4.513	0.000	1.545
	Q3	Social relationship	0.272	0.124	2.190	0.032	2.604
	F1	Bus	0.256	0.086	2.973	0.004	1.732
	F3	Subway	0.240	0.105	2.284	0.026	2.442

).

In Model 4, physical health was influenced by NBE, OA, psychological health, social relationships, and self-care ability. The results indicated that psychological health (Q2) significantly positively affected physical health (B = 0.566, t = 7.096, p < 0.001). The subway system (F3) had a significant negative impact on physical health (B = −0.327, t = −3.805, p < 0.001), whereas supermarkets (F7) positively influenced physical health (B = 0.325, t = 3.305, p = 0.001). The model demonstrated an R-value of 0.789, an R² of 0.623, and a significant ANOVA value of 0.000, indicating a good model fit.

In Model 5, the results showed that self-care ability (Q4) (B = 0.211, t = 3.066, p = 0.003), social relationships (Q3) (B = 0.477, t = 5.643, p < 0.001), physical health (Q1) (B = 0.362, t = 5.063, p < 0.001), and daily activity (OA3) (B = 0.176, t = 2.597, p = 0.011) all had significant positive effects on psychological health. The model had an R-value of 0.885, an R² of 0.783, and a significance (ANOVA) of 0.000, indicating strong explanatory power.

In Model 6, the results indicated that psychological health (Q2) significantly positively influenced social relationships (B = 0.452, t = 5.886, p < 0.001). Social activities (OA2) also had a significant positive effect (B = 0.202, t = 3.091, p = 0.003), while supermarkets (F7) had a significant negative impact on social relationships (B = −0.191, t = −2.336, p = 0.022). The model had an R-value of 0.779, an R² of 0.607, and a significance (ANOVA) of 0.000, indicating a good fit.

In Model 7, the results showed that psychological health (Q2) (B = 0.361, t = 3.258, p = 0.002), leisure activity (OA1) (B = 0.269, t = 4.118, p < 0.001), supermarket (F7) (B = 0.418, t = 4.488, p < 0.001), grocery market (F8) (B = 0.453, t = 4.513, p < 0.001), social relationship (Q3) (B = 0.272, t = 2.190, p = 0.032), and bus (F1) (B = 0.256, t = 2.973, p = 0.004) all had significant positive effects on self-care ability. In contrast, daily activity (OA3) (B = −0.355, t = −3.613, p = 0.001) and subway system (F3) (B = −0.240, t = −2.284, p = 0.026) had significant negative effects on self-care ability. The model had an R-value of 0.895, an R² of 0.800, and a significance (ANOVA) of 0.000, indicating a good fit.

4. Discussion

4.1. Impact of Neighborhood Built Environment on Outdoor Activities

This study found that road quality in the neighborhood-built environment (NBE) of old residential communities directly influences the leisure and daily activities of elderly residents, while the conditions of parks and grocery markets directly affect their social activities (see Figure 2). The direct link between road quality and elderly activities underscores a critical yet often overlooked aspect of urban planning [29]. Poor road conditions can significantly hinder mobility, limiting elderly residents’ access to essential services and physical activity opportunities. This finding aligns with previous research, which associates mobility challenges with reduced physical activity levels and subsequent health declines among the elderly [80]. Additionally, the association between road quality and daily activities suggests that enhancing road conditions can boost the autonomy and independence of elderly residents, allowing them to sustain an active and fulfilling lifestyle [81].

This study also found that parks and grocery markets play a key role in facilitating social interactions among the elderly. This finding aligns with existing literature that identifies green spaces and local markets as critical venues for social activities, particularly for elderly individuals who may have limited access to other social networks [82]. The conditions of these spaces therefore directly affect the frequency and quality of social interactions, which are essential for psychological and emotional well-being [83]. Thus, improving the quality of parks and grocery markets can serve as a targeted intervention to promote social cohesion and reduce feelings of loneliness and isolation among the elderly.

4.2. Impact of Neighborhood Built Environment on Quality of Life

This study reveals the profound impact of elements such as supermarkets, subways, and buses in the NBE of old residential communities on elderly residents’ quality of life (QoL) (see Figure 3). These findings enrich our understanding of the determinants of elderly QoL and offer valuable insights for urban planning and public policy. This research shows that supermarkets significantly impact elderly individuals’ physical health, social relationships, and self-care ability. This highlights the critical role of supermarkets in the daily lives of the elderly [38], as they are not only essential for obtaining food and goods but also for physical activity and social interaction. For elderly individuals with limited mobility, the ability to walk to a supermarket or easily access essential goods is vital for maintaining physical health and self-care [39]. Additionally, supermarkets offer opportunities for social engagement, reducing loneliness and social isolation [84]. Thus, ensuring supermarket accessibility for elderly residents is crucial in urban planning and community design.

This study also finds that subways significantly influence the physical health and self-care abilities of the elderly. As an efficient public transportation mode, subways offer elderly individuals greater travel options and freedom [26]. This mobility encourages greater participation in social activities and healthcare access while improving physical health through increased activity. Buses are also identified as key factors affecting elderly self-care ability. Compared to subways, buses are generally more widespread, covering more communities and residential areas, making them essential for elderly daily travel [85]. Convenient bus services allow elderly individuals to better maintain independence in daily activities such as visiting hospitals, shopping, or engaging in social activities. The findings emphasize the importance of maintaining and improving bus service quality, especially in communities with dense elderly populations, to ensure elderly residents’ continued self-care ability.

4.3. Impact of Outdoor Activities on Quality of Life

This study reveals the critical role of daily and social activities in elderly residents’ QoL. This research shows that daily activities significantly impact psychological health and self-care ability, underscoring the importance of maintaining an active lifestyle. Daily activities contribute to physical health and positively affect the psychological state of the elderly. By engaging in daily activities, elderly individuals maintain self-efficacy and independence, crucial for self-esteem and overall psychological health [56]. Additionally, the richness and regularity of daily activities help elderly residents maintain cognitive function and life satisfaction, enhancing self-care ability and reducing dependency on others [57]. This finding supports interventions aimed at promoting daily activities to improve the psychological health and self-care abilities of the elderly.

The results also show that social activities significantly impact elderly social relationships. This finding aligns with previous research, supporting the view that social activities are key to alleviating loneliness and social isolation [86]. For the elderly, social activities are key to staying connected and building social support networks. Through active participation in social activities, elderly individuals strengthen interpersonal relationships, gain emotional support and practical help, and enhance life satisfaction and psychological health [53]. Encouraging elderly individuals to engage in more social activities, particularly through community programs that create social opportunities, is a crucial strategy for promoting social well-being.

Additionally, this study finds that psychological health significantly impacts elderly physical health. This result underscores the close connection between psychological and physical health. Good psychological health reduces stress, anxiety, and other negative emotions, which often adversely affect physical health [62]. Conversely, psychological health issues may lead to unhealthy behaviors, such as reduced physical activity and irregular healthcare, further compromising physical health. Therefore, improving elderly psychological health is key to enhancing both QoL and physical health. This suggests policymakers and healthcare providers should prioritize the accessibility and availability of psychological health services as a vital component of overall elderly health.

The quality of the NBE near old residential communities vary for older adults with different health conditions. Older adults choose travel modes based on their physical health and distance to their destination. Data analysis reveals that quality of bus, including the height and anti-slip issues in the bus, significantly influence older adults’ self-care ability. Therefore, bus seats should be equipped with anti-slip treatments and handrails at a reasonable height to prevent falls, especially during emergency braking [87].

The bus stop was found to significantly affect daily activities, which is caused when the information for older adults is insufficient in the bus stop and lacking real-time electronic information screens and platform shelters. Additionally, bus stop route signs without lighting affect night-time visibility. Equipping bus stops with shelters, real-time information screens, and illuminated road signs would improve night-time visibility and provide intuitive travel information [88].

Older adults’ OA, including leisure, social, and daily activities, influences their QoL, including physical and psychological health, social relationships, and self-care ability. Good psychological health positively affects physical health, creating a virtuous cycle. However, some NBE factors can have a direct impact on OA, such as roads and squares affecting leisure and daily activities and parks directly affecting socializing. Deficiencies in these NBE factors, such as uneven pavements, unsafe seating, poor hygiene, and insufficient protection, significantly impact the OA of older adults [88]. Improved paving and anti-slip treatments can reduce risks and enhance the OA of older adults [89].

Supermarkets significantly affect older adults’ physical health, social relationships, and self-care, while grocery markets primarily affect their social activities and self-care. In places frequented by older adults, such as supermarkets and grocery markets, poor accessibility (including inadequate anti-slip treatments, a lack of gentle slopes, and uneven floors) hinders their interest in visiting and reduces their quality of life [90]. Therefore, due consideration should be given to the physical abilities and needs of older adults. Priority should be given to anti-slip treatments, and gentle slopes should be installed where there are steps to improve safety and comfort [91].

5. Conclusions

This study investigated the impact of neighborhood-built environments (NBE) on the outdoor activities (OA) and quality of life (QoL) of older adults residing in old residential communities in Nanjing, Jiangsu Province. This research was motivated by the increasing need to improve living conditions for an aging population in urban settings. Using a designed questionnaire and statistical analysis, this study identified nine NBE factors, three OA factors, and four QoL factors, providing a comprehensive understanding of the interactions between these variables.

The findings of this research revealed several critical insights. Firstly, this study identified nine NBE factors, three OA factors, and four QoL factors. Secondly, this study highlighted that the physical design and amenities of neighborhood environments significantly affect the safety and comfort of older adults during outdoor activities. Thirdly, this research underscored the importance of accessible and well-maintained NBE spaces (road, square, park, subway, and so on) for leisure and social activities. Moreover, socially active older individuals exhibited better psychological health, highlighting the need for neighborhoods to foster social interaction through appropriate infrastructure and community programs.

From a managerial and practical perspective, this study offers actionable policy recommendations. First, urban planners and local governments should prioritize the strategic placement and accessibility improvements of supermarkets and grocery markets in proximity to these communities, ensuring that these facilities are equipped with age-friendly access points and services. Second, there should be a concerted effort to upgrade and maintain public transportation infrastructure, particularly subway and bus systems, by incorporating senior-friendly features such as priority seating and clear audio-visual cues. Additionally, the government should allocate resources to renovate and maintain public spaces and parks, providing safe and comfortable areas for seniors to engage in social and physical activities. Urban renewal plans should address all NBE factors affecting the elderly’s QoL, with community engagement to align improvements with their needs. Lastly, regular social activities should be encouraged within the community to reduce loneliness and enhance psychological well-being. These policies will enable effective enhancements to the living environment and overall QoL for the elderly.

The theoretical contributions of this research lie in its detailed examination of the specific NBE components that affect the QoL and OA of older adults. By identifying the distinct impacts of various NBE factors, this study adds depth to the existing literature on urban planning and public health, particularly concerning aging populations. The originality of this research is evident in its nuanced approach, which integrates subjective perceptions with objective measurements, providing a holistic understanding of the built environment’s role in the well-being of older adults.

Despite its contributions, this study has some limitations. This research is geographically confined to Nanjing, limiting the generalizability of the findings to other regions. Additionally, the cross-sectional design restricts the ability to infer causal relationships. Future research could expand the geographical scope, employ longitudinal designs, and explore the role of technological innovations, such as smart city solutions, in enhancing the QoL of older adults in aging urban environments.

In conclusion, enhancing the NBE with a focus on safety, accessibility, and social connectivity can significantly improve the quality of life for older adults. Urban planners and policymakers should prioritize these aspects in the development and renovation of residential communities to support the well-being and active participation of older adults in their neighborhoods.