The Associative Effects and Design Implications of Urban Built Environment on the Physical and Mental Recovery of Older Adults in China: Bibliometric and Meta-Analysis

Abstract

Against the backdrop of global population aging, the impact of urban built environments on the physical and mental health of older adults is receiving increasing attention. As the world’s largest developing nation, China, is simultaneously undergoing rapid urbanization and significant demographic aging. This dual trend makes it particularly imperative to investigate the relationship between the built environment and senior health. This study employs a meta-analysis methodology to quantitatively evaluate the relationship between urban built environment characteristics and physical and mental rehabilitation among older adults. Empirical studies were systematically screened from the CNKI and Web of Science databases using weighted Z-scores. Methodological quality, sample size, and heterogeneity were assessed to ensure the robustness of the analysis. Thirteen environmental indicators were categorized into objective built environment attributes and perceived environmental attributes. Results indicate that land use diversity and green coverage significantly correlate positively with better physical health outcomes, while safety, road quality, and environmental aesthetics significantly correlate positively with mental health. In contrast, some indicators, such as intersection density and NDVI, did not show significant correlations. This study explores the synergistic and complex effects of objective and perceived environmental characteristics in Chinese cities on the physical and mental rehabilitation of older adults within the context of dual-trend superposition. The findings not only provide scientific evidence for future urban planning and renewal in China but also offer valuable references for addressing the tension between urbanization and the health of older adults in Asia and other developing regions.

1. Introduction

1.1. Background

1.1.1. Aging and Urbanization in China

With the acceleration of global population aging and the continuous expansion of the older adult population, ensuring the physical and mental health of the older adults and improving their quality of life have become urgent issues that need to be addressed in urban public health and spatial planning.

China’s land area is approximately 9.6 million square kilometers, ranking third in the world. According to data from China’s seventh national census, China’s total population is 1.41178 billion, accounting for 18% of the world’s total population, making it the most populous country in the world. China’s aging population is particularly striking. According to global data on the aging population (Figure 1), the proportion of the elderly population in developing countries far exceeds that in developed countries and continues to grow. Among developing countries across continents, Asia has the largest share, and China, as the largest developing country, accounts for nearly half of this share (Figure 2). According to the United Nations’ definition, a society is considered aging when the proportion of the population aged 65 and above exceeds 7%, and China has already reached 14%, entering a stage of rapid aging. Meanwhile, China’s urbanization development has also shown rapid growth. Comparative data from 1994 to 2024 shows that China’s urban population has grown rapidly, with its urbanization rate increasing at a pace that ranks among the highest in the world and far exceeds that of other developed countries (Figure 3). During this period, large-scale population migration to cities has driven the rapid expansion and transformation of the built environment. However, the overlap of rapid aging and urbanization has also led to a mismatch between the built environment and health needs. Research indicates that urbanization in developing countries often prioritizes transportation and infrastructure expansion while neglecting human-centered needs, leading to potential health risks. For example, traffic chaos and pollution have limited the social activities and exercise of older adults, increasing the burden of chronic diseases [1]. Systematic reviews have also found that while rapid urbanization has improved some nutritional conditions, it has exacerbated the risks of obesity and chronic diseases [2]. Cross-regional studies further indicate that the urbanization process in developing countries is often accompanied by deepening poverty, inequality, and health disparities [3]. These studies indicate a systemic mismatch between the built environment and residents’ physical and psychological needs, particularly in the context of rapid urban expansion in developing countries, necessitating further research and policy attention.

Therefore, against this backdrop, systematically exploring the relationship between China’s built environment and the physical and mental health of older adults, starting from their health needs, can not only provide valuable insights for future urban planning, public space optimization, and community renewal in China but also contribute to the development of health-friendly cities. Additionally, as the most populous developing country with a rapidly aging population, China’s research findings can also serve as a reference and model for other developing countries at similar stages, helping them better address the contradictions between built environments and health needs during urbanization and aging processes.

1.1.2. Rationale for Meta-Analysis

Against this backdrop, this study aims to fill the gap in systematic quantitative analysis of the relationship between the built environment and the physical and mental health of older adults in China. Existing reviews on China are limited and primarily qualitative in nature, making it difficult to compare and integrate different research findings. Therefore, this study employs a meta-analysis method to systematically integrate empirical research on the relationship between the built environment and the physical and mental health of older adults in China, aiming to quantitatively assess its overall effects and reveal the unique influence pathways and mechanisms under China’s high-density, rapid urbanization context. The study results not only enrich the theoretical and empirical foundations of health environment research for older adults in developing countries but also provide practical references for other developing countries and regions undergoing similar demographic and spatial transformations. A deeper understanding of the role of the built environment in the physical and mental health of older adults is of great significance for building age-friendly cities, promoting their positive development, and guiding relevant planning and policies.

1.2. Urban Built Environment and Physical-Mental Recovery in Older Adults

1.2.1. Urban Built Environment

The urban built environment consists of human-made spaces and infrastructures—such as buildings, streets, green parks, and transportation facilities [4,5]—designed to support daily life, work, and recreational needs. Beyond shaping residents’ lifestyles, it also influences health behaviors and outcomes through its physical characteristics and social functionality. In the context of rapid urbanization, many cities have experienced fragmented spatial expansion and a lack of systematic planning, resulting in inefficient land use and increased environmental pressures. As a response, urban regeneration has become a critical global issue [6]. Improving existing spatial quality, optimizing land use, and enhancing urban livability and functionality are now key strategies in spatial planning and micro-regeneration, particularly in aging neighborhoods.

Different academic disciplines approach the built environment with distinct emphases, collectively enriching the field’s theoretical and methodological diversity. Urban planning focuses on overall spatial configuration, including neighborhood layout, transport networks, and green space distribution, aiming to optimize mobility patterns—often using geographic information systems (ArcGIS) for analysis [7]. Architecture emphasizes spatial functionality and comfort, aiming to enhance residents’ quality of life through barrier-free design, improved ventilation, natural lighting, and mobility-supportive indicators for older adults, such as handrails and ramps [8]. Research methods often combine field surveys with user feedback. Public health studies examine how the built environment affects health behaviors (e.g., physical activity) and chronic conditions (e.g., cardiovascular diseases), employing surveys and behavioral tracking to promote healthier lifestyles [9]. Environmental psychology investigates how physical settings influence emotional regulation, psychological well-being, and social cohesion, using psychometric scales and qualitative interviews to assess residents’ perceptions [10]. Sociology often explores how the environment fosters social interaction and neighborhood connectedness, especially focusing on how built indicators reduce loneliness among older adults [11,12].

Contemporary research generally adopts two major perspectives: subjective perception and objective characteristics [13,14]. Subjective perception refers to individuals’ evaluations and lived experiences of their surroundings, commonly measured via questionnaires or interviews. Objective characteristics refer to externally measurable indicators of the environment, captured through direct observation or multi-source data such as satellite imagery, GIS, and street-level visual data. Together, these dual perspectives provide a comprehensive understanding of how the built environment supports the physical and mental recovery of older adults and offers evidence-based guidance for creating more age-friendly cities.

1.2.2. Physical-Mental Recovery in Older Adults

Recovery encompasses both physical and psychological health, referring to the restoration of bodily functions and the alleviation of mental stress. As a vulnerable population, older adults commonly experience physical decline, cognitive impairment, and shifts in social roles—all of which pose significant challenges to their overall well-being. Therefore, enhancing the quality of the built environment has become an increasingly urgent priority to support the health and recovery needs of the aging population.

Physical recovery refers to the ability of older adults to restore or maintain stable bodily functions under appropriate conditions, encompassing the proper functioning of various physiological indicators. It primarily includes: (1) Chronic disease management: controlling or alleviating common chronic conditions among older adults—such as hypertension and diabetes—through medical treatment, rehabilitation, and physical activity interventions [15]. (2) Physical function recovery: enhancing physical fitness and mobility through therapeutic programs and appropriate health-promoting exercises, such as walking or Tai Chi. (3) Environmental support: creating safe and comfortable environments—incorporating elements such as fresh air, natural lighting, and age-friendly spatial design—to facilitate physical recovery by addressing the specific needs of older adults [16].

Mental recovery refers to the improvement of emotional well-being, mental balance, and social connectedness among older adults, aiming to restore a healthy psychological state [17]. This includes: (1) Emotional regulation: reducing negative emotions such as loneliness and anxiety to enhance happiness and psychological well-being. (2) Cognitive recovery: mitigating age-related declines in memory and attention through environmental stimuli, social interaction, or cognitive training. (3) Social integration: strengthening social participation and a sense of belonging through family support, community engagement, and interpersonal interaction opportunities [18].

Furthermore, there is a bidirectional relationship between physical and psychological health. Improvements in physical health can promote psychological recovery, while a positive mental state can, in turn, support the recovery of physical functioning.

1.2.3. Linking Urban Built Environments to Physical-Mental Recovery Among the Older Adults

The urban built environment serves as a crucial setting for the daily activities of older adults, with its design and functionality directly influencing physical recovery, psychological recovery, and social integration. The quality of environments such as communities, streets, and green spaces determines the sustainability of physical activities like walking, thereby affecting physical health [19]. Quiet and safe surroundings, along with well-maintained green spaces, contribute to improved emotional well-being by alleviating anxiety and depression [20]. Furthermore, well-designed public spaces [21] and barrier-free infrastructure [22] promote social interaction, enhance a sense of belonging and social participation, and support overall physical and psychological recovery. The urban built environment, integrating physical, natural, and social supports, plays a crucial role in promoting the holistic recovery of older adults. Optimizing environmental design not only enhances their quality of life but also offers sustainable solutions to address population aging.

At present, most review studies examining the relationship between the built environment and the health of older adults adopt a purely descriptive approach, relying heavily on subjective analysis. There is a relative lack of literature that quantitatively synthesizes this relationship. Moreover, existing reviews often focus on a single perspective—either physical or mental health—when exploring the links between environmental factors and health outcomes among older adults. In contrast, this review not only provides a descriptive analysis of the relevant literature but also incorporates a Meta-Analytic approach to statistically quantify the strength of evidence regarding the associations between built environment characteristics and the health and recovery of older adults.

1.3. Significance

Although the academic community has increasingly focused on the relationship between the built environment and the health of older adults, existing research still has several methodological and conceptual limitations. First, there is a lack of a systematic and quantitative framework that can integrate empirical research findings and identify the key environmental variables that consistently show significant associations across studies. The use of different indicators and analytical methods has led to high heterogeneity and limited comparability, hindering a comprehensive understanding of the impact of the built environment on recovery outcomes. Second, the interactive mechanisms between objective environmental characteristics and perceived remain under-explored. Although these factors may jointly influence older adults’ health through behavioral and psychological pathways, most studies examine them in isolation and lack comprehensive analytical models. Third, existing research often focuses on individual communities or cities, a design constrained by sample size and regional differences. This limits the generalizability of research findings and hinders the development of transferable evidence bases applicable to policy and planning. Finally, at the practical level, most studies remain theoretical, identifying statistical associations without translating findings into actionable design strategies. This disjunction poses challenges for planners and practitioners seeking to build evidence-based environments suitable for older adults.

In response to the aforementioned gaps, this study employs a meta-analysis approach to quantitatively integrate empirical evidence from the past two decades, systematically constructing a comprehensive framework for the relationship between the built environment and older adult health. Focusing on developing countries, particularly China’s rapid urbanization process and aging trends, we have established a unified evidence base by integrating perceived and objective urban environmental indicators, revealing the directional impact of different environmental characteristics on the physical and mental recovery of older adults. We identified key variables with significant positive impacts and proposed practical spatial intervention strategies—including the integration of micro-green spaces in high-density built-up areas, age-friendly pedestrian optimization, and public space design that enhances safety and social inclusion—to facilitate knowledge transfer from research to actual intervention measures. This study contributes to the theoretical foundation of the relationship between the built environment and health, expands the perspective on environmental recovery potential, and provides data-driven strategies to guide health-oriented urban revitalization and the development of spaces suitable for older adults.

The research findings and spatial strategies offer valuable references not only for China but also for other developing countries and regions undergoing similar urbanization and demographic transitions.

2. Methods

2.1. Meta-Analysis

This study adopts the Meta-analysis (MA) method initially proposed by Smith and later named by educational psychologist Gene Glass. MA is a statistical technique that integrates and quantifies data from multiple empirical studies [23]. Compared to traditional qualitative reviews, it allows for a more systematic and precise synthesis of findings on a specific topic [24]. With its structured procedures and statistical evaluation, MA reveals the consistency and variability across studies and has been widely applied in fields such as medicine, psychology, and public health [23]. For instance, Salameh proposed the PRISMA-DTA guideline to improve the reporting quality of diagnostic accuracy studies in medicine [25]; Amanda demonstrated the positive effects of physical activity on reducing depression and anxiety in non-clinical adult populations [26]; and Talic evaluated the effectiveness of public health interventions in controlling infectious disease transmission [27].

In recent years, MA has been widely applied in health-related research due to its clear analytical framework and robust statistical methodology. Incorporating diverse perspectives and quantitative evaluation, it enables the identification of underlying trends within specific research domains. For example, studies have examined the relationship between restorative indicators of the natural environment and mental health [28], and explored the pathways and effect sizes of urban blue and green spaces on mental well-being [29]. Other research has focused on community environments, highlighting the roles of walkability, aesthetic quality, and community support in shaping various health outcomes [30], while transportation-related studies have evaluated the health impacts of long-term exposure to traffic-related air pollution [31].

2.2. Analytical Procedures and Implementation

Following standard MA procedures, we first conducted a systematic literature search using predefined topics and keywords. The Latent Dirichlet Allocation (LDA) Topic model [32] was then applied to analyze the topic structures and thematic evolution of the retrieved studies from 2000 to 2024. Next, two independent researchers screened the identified studies based on established inclusion and exclusion criteria, with cross-validation to ensure consistency. Eligible studies were reviewed in full and assigned unique identification numbers. Relevant data were extracted from each study. Finally, appropriate effect size metrics were selected based on the characteristics of the extracted data, followed by statistical synthesis and quantitative analysis to assess the relationship between environmental factors and the physical and mental health outcomes of older adults (Figure 4).

2.3. Specific Process

2.3.1. Literature Search

This study aims to examine the relationship between the urban built environment and the physical and mental recovery of older adults in the context of China. A systematic literature search was conducted using China National Knowledge Infrastructure (CNKI) and the Web of Science (WOS) Core Collection. Boolean operators were employed to refine the search scope. The search was limited to peer-reviewed journal articles published between January 2000 and August 2024. A total of 1553 Chinese and English-language studies were identified (

Table 1. Search Strategy.

Classify	Search Keywords		Time	Number
	Main	Combined
Physical health	older/adults elder	physical; built environment; street; community; neighbor; walk	2000.01 —— 2024.08	735
Mental health		mental; built environment; street; community; neighbor; landscape; blue -green space; natural space; green space		818

).

2.3.2. Bibliometric Analysis

To clarify the research trends and emerging themes from 2000 to 2024, we applied the Latent Dirichlet Allocation (LDA) Topic model to the retrieved literature (n = 1553) for preliminary bibliometric analysis. Thematic structures were automatically identified and clustered, and visualizations such as word clouds and Sankey diagrams were used to present topic distribution and evolution.

2.3.3. Literature Selection

The preliminary screening of the literature involved four steps (Figure 5). First, studies that were irrelevant to the topic were excluded based on a review of titles and research themes (n = 872), and duplicate records were removed to ensure that each study was represented only once (n = 394). Second, citation analysis was conducted to exclude studies with low citation frequency (n = 50). Third, through abstract screening, we excluded review articles (n = 55) and studies conducted outside of China (n = 24). Finally, descriptive studies and those lacking accessible data were also removed (n = 23).

A total of 135 studies remained after the initial screening. To ensure the representativeness and scientific rigor of the included literature, we applied four secondary screening criteria. (1) The study must explicitly focus on the relationship between the built environment and the health of older adults. (2) It must include a clearly defined evaluation framework for objective characteristics of the built environment. (3) The study must report key health measurement details for older adults, including measurement methods, sample size, and age-related information. (4) The study must provide complete analytical data and results to allow for subsequent quantitative analysis. After applying these criteria, 52 studies met all the inclusion requirements and were retained for final analysis. The entire screening process was conducted simultaneously by two researchers. Any studies raising questions were flagged for subsequent discussion. After each round of screening, both researchers reviewed the selected papers again to ensure no potentially valuable literature was inadvertently excluded.

2.3.4. Data Extraction and Literature Coding

The 52 included studies were randomly coded, and relevant information was systematically extracted. The extracted data covered publication year, study region, and sample size; study design type (cross-sectional, longitudinal, or quasi-experimental); methods used to assess physical and mental health outcomes (standardized scales or self-developed questionnaires) and to measure built environment characteristics; as well as the statistical analysis methods applied in each study.

2.3.5. Selection and Quantification of Effect Size

Effect size selection: Effect size is a widely used metric in medical and health research for assessing differences between study outcomes [32]. However, most studies included in this review reported only regression coefficients (β), significance levels, or p-values, without providing the descriptive statistics (e.g., means and standard deviations) necessary to calculate standardized effect sizes such as Co-hen’s d. Addressing this limitation, this study employs weighted Z-score synthesis, which offers the following advantages in similar research contexts: (1) it converts disparate statistical measures (e.g., β, p-values) into a unified Z-score scale, enabling cross-study comparability; (2) it simultaneously accounts for sample size and study quality during weighting, enhancing the robustness of combined results; (3) It enables evidence synthesis without requiring complete descriptive statistics, thereby simplifying data extraction and reducing biases stemming from reporting discrepancies or inconsistent measurement tools. For statistically significant positive associations at the p < 0.05 level: Z = 1.96, for statistically significant negative associations at the p < 0.05 level: Z = –1.96. For statistically significant positive associations at the p < 0.10 level: Z = 1.64, for statistically significant negative associations at the p < 0.10 level: Z = –1.64. For highly significant positive associations (p < 0.01): Z = 2.575, for highly significant negative associations (p < 0.01): Z = –2.575. For non-significant results: Z = 0. This standardized framework enhances the comparability, consistency, and interpretability of the meta-analysis, making it particularly suitable for interdisciplinary evidence synthesis.

Quality assessment: For MA, we conducted a methodological quality assessment of the 52 included studies. Based on existing frameworks, we developed a set of seven evaluation criteria. These criteria encompassed study design, risk of bias, sample representativeness, and the appropriateness of data analysis methods (

Table 2. Methodological Quality and Sample Size Assessment (N = 52).

Quality Assessment Items		Sample Size Assessment
Items	Assessment Rules	Sample Size	Assessment Rules
(1). Study Design Type	Cross-sectional: 0; Longitudinal: 1; Quasi-experimental: 0.5	≤100	0.25
(2). Reported Response Rate	≥60%: 1; not reported or ≤60%: 0	101~300	0.5
(3). Analyses adjusted for sociodemographic and confounding variables	done: 1	301~500	1
(4). The study adjusts for self-selection bias	done: 1	501~1000	1.25
(5). The study uses valid and reliable health measures	done: 1	1001~2500	1.5
(6). The statistical analysis methods are appropriate and valid	appropriate: 0.5	>2500	1.75
(7). The study area includes diverse environmental exposure levels	covered: 1

). (1) Study design type (cross-sectional: 0; longitudinal: 1; quasi-experimental: 0.5); (2) studies should clearly report the response rate or participation rate for sample recruitment. A response rate ≥60% is considered acceptable to reduce the risk of nonresponse bias; (3) the model must statistically control for at least core demographic variables and other key confounding factors; (4) evaluate whether the study recognizes and attempts to statistically correct for self-selection bias; (5) measuring tools for health outcomes (such as scales or objective devices) must undergo Validity and Reliability verification, or be recognized as standard tools within the research field; (6) evaluate whether the selected statistical model is appropriate for the data type and research question, whether it correctly handles the distribution characteristics of the data, and whether the data is fully reported; and (7) the study area should exhibit sufficient variation in built environment indicators to ensure effective detection of associations between the environment and health outcomes. Each study was scored on a scale from 0 to 7, and classified into three quality levels accordingly: scores of 0–2 were rated as C (low quality), 3–4 as B (moderate quality), and 5–7 as A (high quality).

Sample size assessment: In addition, weight scores were assigned based on sample size. Studies with ≤100 participants received a weight of 0.25; those with 101–300 participants, 0.50; 301–500 participants, 1.00; 501–1000 participants, 1.25; 1001–2500 participants, 1.50; and studies with >2500 participants were assigned a weight of 1.75. The sample size range of 301–500 was considered typical within this field and thus assigned a baseline weight of 1.00. We simultaneously considered both the article’s quality score and sample size score, which were used to calculate the article’s weight.

Homogeneity test: In conducting a meta-analysis, it is essential to include studies with sufficient similarity to allow for meaningful pooling of results. Prior to aggregation, careful consideration must be given to the measurement approaches of both independent and dependent variables. Specifically, the environment indicators definitions and measurement methods should be consistent across studies, and the indicators used for key variables should be identical or highly comparable. Only under these conditions can effect sizes be validly combined, thereby ensuring the reliability of the synthesized results.

Quantification: The quality assessment scores, sample size evaluations, and standardized Z-scores of the included studies were combined for analysis. Built environment indicators appearing in four or more studies were eligible for grouped calculation. The overall weighted Z-value was obtained through the use of the following formula.

$$WeightedZ={\displaystyle \frac{\sum {weight}_j{z}_j}{\sqrt{\sum {weight}_j^2}}}$$

(1)

where ‘j’ stands for finding ‘j’.

3. Results

3.1. Results of Bibliometric Analysis

We conducted a temporal analysis of literature from 2000 to 2024 (1553 studies), revealing distinct developmental phases in the “built environment-health” research theme from an older adult perspective. Figure 6 illustrates the annual distribution of literature in this field, revealing its evolutionary pattern within the Chinese context. This provides intuitive evidence for understanding the historical trajectory of this research direction and supports subsequent quantitative analysis and meta-analysis.

Based on publication trends, the development process can be divided into two main phases. During the initial phase (2000–2010), the total annual publication volume remained at a relatively low level with slow growth, indicating that research was still in its exploratory stage. The acceleration phase (2010–2024) witnessed a significant and sustained increase in research volume, with particularly rapid growth after 2010. This reflects the growing attention this topic has received at both academic and policy levels.

Based on the results of LDA topic modeling and the generated word cloud, the core vocabulary clusters of this research field can be identified (Figure 7). Terms such as “older,” “health,” “physical,” “psychological,” “effects,” and “social” appear with high frequency, highlighting the main focus of the studies: investigating how specific indicators of the built environment (e.g., residential areas, community facilities, public spaces) influence the physical and mental health of older adults and their combined effects. In short, the research is highly concentrated on the mechanisms through which the urban built environment impacts the physiological and mental well-being of the older adults.

From 2000 to 2024, the evolution of research themes on older adults’ health (Figure 8) demonstrates a clear shift from a single-dimensional focus toward a multidimensional, interdisciplinary, and deeply integrated paradigm, reflecting the broadening of research perspectives and the deepening of content. In the early stage, studies primarily focused on individual physical indicators (such as chronic disease prevalence and physical function) and basic mental states (such as depression and anxiety), emphasizing measurement, assessment, and correlation analyses. The core aim was to identify health risks and disease prevention, with a relatively narrow perspective centered on the individual’s physical and mental conditions. In the middle stage, alongside the accelerated global aging process and the systemic pressures it brings (such as caregiving burdens and medical resource allocation), research significantly broadened its scope. The focus shifted to exploring effective behavioral interventions (such as promoting physical activity and improving nutrition) and diversified, specialized long-term care and social support models (such as home care support and caregiver training). This period marks a transition where research actively engages with macro social demands arising from demographic shifts, extending from the individual level to social support systems. In the later stage, research frontiers further deepened and integrated, centering on the physical attributes of the built environment (such as age-friendly design, green space accessibility, and walkability) and the community support networks they sustain (such as social interaction spaces, volunteer services, and mutual aid platforms). Studies increasingly emphasize not only the impact of environments on isolated health indicators but also their role in shaping health behaviors (e.g., encouraging outdoor activities), enhancing mental well-being (e.g., alleviating loneliness and strengthening belonging), and empowering social participation (e.g., fostering community integration). This evolution signifies a paradigm shift toward constructing a “human-environment-society” interactive health ecosystem.

3.2. Characteristics of Included Studies

A total of 1553 research articles were initially screened, and the full texts of 135 studies were reviewed. Of these, 52 studies met the inclusion criteria for this review. All 52 studies were cross-sectional in design (

Table 3. Characteristics of the selected studies (N = 52).

Characteristic		Number of Articles
Geographical region	First-tier cities	20
	New first-tier cities	22
	Second-tier cities	13
Research design type	Cross-sectional	52
	Longitudinal	0
	Quasi-experimental	0
Discipline	Public Health	7
	Architecture	12
	Urban Planning	11
	Transportation	2
	Geographic Information Science	9
	Landscape	2
	Sports Science	9
Health Classification	Physical	32
	Mental	14
	Physical and Mental	6
Environmental Feature Classification	Objective	20
	Perceived	14
	Objective and Perceived	18
Data Source (objective)	Multi-source Data (street view/POI/remote sensing/OSM/GIS)	26
	Field Survey	8
Data Source (perceived)	Questionnaire	30
	Machine Learning Model	1
Sample size	≤100	0
	101–300	6
	301–500	12
	501–1000	17
	1001–2500	8
	>2500	9
Quality assessment	0–2 (low quality)	0
	3–4 (moderate quality)	22
	5–7 (high quality)	30

Note: “First-tier cities” refer to the most developed and internationally influential urban centers in China, including Hong Kong, Beijing, Guangzhou, and Shanghai in this study; “New first-tier cities” are rapidly developing cities with strong economic performance and growing regional influence, including Nanjing, Chongqing, Hangzhou, Wuhan, Chengdu, Suzhou, Tianjin, Ningbo, and Hefei; “Second-tier cities” are mid-level cities with moderate development and regional importance, including Dalian, Xiamen, Jinhua, Wenzhou, Fuzhou, Zhongshan, and Harbin.

), with the majority conducted in economically and academically developed regions such as Beijing and Hong Kong (first-tier cities), as well as Nanjing and Wuhan (new first-tier cities). Most of the included studies originated from the fields of architecture and urban planning, followed by geographic information science and sports science (see Appendix A). Regarding health classification, 61.5% of the studies examined the relationship between the built environment and physical health in older adults, 26.9% focused on mental health, and only 11.5% addressed both dimensions (Table 3). In terms of built environment attributes, 38.5% of the studies focused on objective characteristics, 26.9% on perceived characteristics, and 34.6% considered both (Table 3). Environmental data were primarily obtained from multi-source datasets (for objective characteristics) and questionnaires (for perceived characteristics), while field surveys were used infrequently (see Appendix A).

We conducted a summary analysis of the publication years of the included studies (Figure 9). To better understand the research focus and developmental trends in this field over time, we further examined the studies about health classifications and environmental feature types. The overall number of publications has shown a significant upward trend. In terms of health focus, sustained attention has been given to the physical health of older adults, while interest in mental health has grown explosively since 2020. Regarding environmental characteristics, early studies primarily focused on objective indicators, but there has been a gradual shift toward incorporating both objective and perceived attributes.

3.3. Quality Assessment and Sample Size Evaluation

The sample sizes in most studies ranged between 301 and 1000 participants, with only six studies reporting fewer than 300 participants, which is considered a small sample size in this field (Table 3). In the quality assessment, 57.7% of the included studies were rated as high quality (Table 3).

3.4. Homogeneity Tests

Among the 52 included studies, the dependent variables used to assess physical and mental health in older adults were categorized into subgroups for MA (

Table 4. Results of Homogeneity Tests.

Health	Variable	Number of Studies Reporting (n)	Analysis	Reason
Physical Health	activity frequency	3	NO	Insufficient number of studies.
	activity intensity	27	YES	Most widely reported indicator with consistent measurement methods.
	self-rated health		NO	Insufficient number of studies.
Mental Health	self-rated mental health	4	NO	Insufficient number of studies.
	depression and anxiety assessment	7	NO	The number of environmental indicators available for calculation in these studies is insufficient.
	social interaction	9	YES	Most widely reported indicator with consistent measurement methods.

Notes. “YES” indicates that the variable was included in the meta-analysis. “NO” indicates that it was not included.

). (1) For physical health, the most commonly used outcome variables were physical activity frequency, physical activity intensity, and self-rated health status. In a small number of studies (n = 3), physical activity intensity was measured using triaxial accelerometers and GPS tracking to capture activity data and calculate intensity levels. However, due to the limited number of studies using this method, it did not meet the threshold for pooled analysis and was therefore excluded from further MA computation. Similarly, studies using self-rated health status as the dependent variable were too few to support a meaningful analysis. In contrast, physical activity frequency was used as the outcome variable in 27 studies, making it the most commonly adopted indicator for assessing the relationship between the built environment and physical health in older adults. Therefore, in analyzing the relationship between the built environment and physical health, we selected this grouping (Activity Frequency) as a proxy indicator for further statistical analysis. (2) For mental health, the most commonly used dependent variables were self-rated mental health status, depression and anxiety assessments, and social interaction, which were accordingly divided into subgroups for analysis. Only four studies used self-rated mental health status as the dependent variable, and the number of environmental indicators reported in these studies did not meet the minimum threshold required for subgroup analysis. Although depression and anxiety assessments appeared in seven studies, the number of environmental indicators eligible for pooled analysis within this subgroup was insufficient—e.g., greening rate (n = 2), intersection density (n = 1), perceived safety (n = 1), and environmental aesthetics (n = 2). Therefore, these two categories were excluded from further MA computation. In contrast, social interaction was used as an outcome variable in nine studies, and the associated environmental indicators met the required criteria for MA. Therefore, we selected this grouping (Social Interaction) as a proxy indicator for the relationship between the built environment and mental health for further statistical analysis. (Detailed calculation procedures are provided in Appendix B.1 and Appendix B.2).

3.5. Environmental Factors

We also found that the 5D theoretical framework is widely used in the reviewed literature to assess the built environment, focusing on five key attributes: Density, Diversity, Design, Destination Accessibility, and Distance to Transit [33]. In addition, some studies adopted the Ecological Model of Active Living proposed by James, which categorizes built environment attributes into Accessibility, Comfort, Safety, Convenience, and Aesthetics [34]. Based on these theoretical models, many studies have developed specific evaluation systems. For example, Leng [35] established a framework centered on Accessibility, Safety, and Aesthetics, while Chen [36] constructed an evaluation system based on Convenience, Safety, and Comfort. In this review, we systematically organized the environmental attributes reported in the literature and identified four core dimensions. Figure 10 was developed based on this framework to systematically present the environmental factors addressed in current domestic research, clearly illustrating the primary dimensions and logical framework of built environment studies within the Chinese context. This integration also provides a basis and support for categorizing and comparing environmental attributes in subsequent meta-analyses.

Accessibility refers to the ease or potential of reaching one location from another, encompassing factors such as land use diversity, proximity to service facilities, and street network connectivity, which support daily life and physical activity. Convenience reflects the ease with which older adults can access essential services and facilities, including well-planned street layouts, crossing infrastructure, public amenity density, and walkability—all of which influence mobility behaviors and travel willingness. Safety emphasizes the role of the built environment in minimizing risks during older adults’ activities, with key elements such as lighting, surveillance, and traffic conditions helping to build a sense of trust in the environment and indirectly supporting mental well-being. Comfort focuses on the positive physical and emotional experiences provided by the environment, involving indicators such as green space, noise and air quality, and resting facilities that can enhance quality of life and foster psychological satisfaction and happiness.

3.6. Correlation Analysis Results

Based on the comprehensive weighted Z-value calculations, we systematically analyzed the relationship between the built environment and physical and mental health outcomes among older adults. This analysis was conducted at two levels—objective environmental characteristics and perceived environmental characteristics—by integrating the framework presented in Section 3.5 (Figure 10), which encompasses four key attributes: accessibility, convenience, safety, and comfort.

Across these two subgroups, a total of 13 built environment indicators were eligible for MA. To ensure consistency, these indicators were required to have comparable definitions across studies, fall under the same environmental attribute classification, and appear in at least four studies. For objective indicators related to physical health, the number of times each feature appeared across the included studies was as follows: population density (n = 11), intersection density (n = 7), destination accessibility (n = 6), land use diversity (n = 15), greening rate (n = 9), and vegetation index (n = 4). For perceived indicators, the reported frequencies were street connectivity (n = 5), road quality (n = 6), aesthetic quality (n = 10), public safety (n = 10), traffic volume (n = 5), perceived safety (n = 4), and walkability (n = 4). These objective and perceived indicators were then regrouped and analyzed separately concerning physical and mental health outcomes. This approach allowed for a clearer identification of specific environmental factors associated with each dimension of older adults’ health. We also documented in detail the measurement methods of each environmental feature as reported in the included studies (

Table 5. Meta-analysis Results: Built Environment and Older Adults’ Health.

Health Dimension	Built Environment	Category	Indicator	P (n)	Ø (n)	N (n)	Total (n)	Z	p-Value	Direction (D)
Physical Health (Activity Frequency)	Object		population density	5	4	2	11	1.9744	0.0488	P
		Convenience	intersection density	3	3	1	7	1.2809	0.2005	Ø
		Accessibility	destination accessibility	2	3	1	6	0.8069	0.4179	Ø
			land use mix	6	3	1	10	3.1374	0.005	P
		Comfort	greening rate	6	2	0	8	3.2206	0.0013	P
	Perceived	Convenience	street connectivity	1	4	0	5	0.7238	0.4715	Ø
		Comfort	road quality	3	3	0	6	2.6642	0.0078	P
			aesthetics	7	3	0	10	3.1655	0.0015	P
		Safety	public security	5	4	0	9	3.0402	0.0024	P
			traffic	2	3	0	5	1.6278	0.1031	Ø
Mental Health (Social Interaction)	Object	Comfort	NDVI	0	3	1	4	−0.8423	0.4009	Ø
	Perceived	Safety	perceived safety	2	2	0	4	2.3301	0.0198	P
		Comfort	walkability	4	0	0	4	2.93	0.0034	P

Notes. P = positive association; Ø = nil association; N = negative association. Direction (D) refers to the significance direction of the index after meta-analysis.

).

3.6.1. The Association of Objective and Perceived Environmental Attributes with Physical Recovery (Activity Frequency) in Older Adults

Based on the results of the MA (Table 5), a total of five objective indicators and five perceived indicators were included in the subgroup examining the association between environmental characteristics and physical health in older adults. Among the objective indicators, population density showed a positive association (Z = 1.9744, p = 0.0488), while land use mix (Z = 3.1374, p = 0.005) and greening rate (Z = 3.2206, p = 0.0013) demonstrated significant positive associations. In contrast, intersection density (Z = 1.2809, p = 0.2005) and destination accessibility (Z = 0.8069, p = 0.4179) did not exhibit significant associations with physical health. Among the perceived indicators, road quality (Z = 2.6642, p = 0.0078), aesthetic (Z = 3.1655, p = 0.0015), and public security (Z = 3.0402, p = 0.0024) showed significant positive associations with physical health outcomes, whereas street connectivity (Z = 0.7238, p = 0.4715) and traffic (Z = 1.6278, p = 0.1031) were not significantly associated (Detailed calculation procedures are provided in Appendix C.1 and Appendix C.2).

3.6.2. The Association of Objective and Perceived Environmental Attributes with Mental Recovery (Social Interaction) in Older Adults

Following the MA, three environmental indicators were included in the analysis of associations with mental health in older adults (Table 5). Among them, only one objective feature—NDVI (Z = −0.8423, p = 0.4009)—was identified, but it did not show a significant association. Of the two perceived indicators, walkability (Z = 2.93, p = 0.0034) demonstrated a significant positive association, whereas perceived safety showed no significant relationship with mental health outcomes (Detailed calculation procedures are provided in Appendix C.1 and Appendix C.2).

4. Discussion

4.1. Built Environment Correlates of Physical Health Outcomes

4.1.1. Objective

In the MA results of this review, population density exhibited a positive but non-significant association with physical health among older adults.

This result may be related to the fact that the population density in the sample of this study was mostly at moderate or appropriate levels, and had not yet reached the critical point at which significant negative effects would occur [37]. Especially in the specific context of China’s rapid urbanization, population concentration has significantly improved access to healthcare services, social interaction, and public facilities, better aligning with the strong demand of the older adult for convenient living and social participation, thereby reinforcing the health-promoting effects of high-density environments to some extent. However, population density, as an environmental determinant, has health effects that are clearly complex and context-dependent. On the one hand, higher population density may promote outdoor physical activity among older adults through convenient service facilities, better walkability, and abundant social opportunities, thereby helping to form a healthy lifestyle [38,39]; on the other hand, high-density environments may also be accompanied by negative external factors such as traffic congestion, noise pollution, and deteriorating air quality, thereby suppressing the willingness to engage in outdoor activities and increasing health risks [40]. These seemingly contradictory effects suggest that the impact of population density on health is likely indirect and significantly moderated by other environmental and social factors. For example, the availability of green spaces, street-level safety design, perceived environmental quality, and community social support may all play key moderating roles in this relationship.

Land use diversity demonstrated a significant positive association with physical health among older adults in the present MA. This association operates through two primary mechanisms. First, functionally, mixed land use promotes health by reducing walking distances and increasing the attractiveness of destinations, thereby directly encouraging outdoor physical activity [41]. Second, from a behavioral reinforcement perspective, diverse land use patterns help older adults develop consistent and routine-based activity habits, which are essential for improving cardiopulmonary function and preventing metabolic disorders over time [42]. Notably, the strength of this association appears context-dependent. In highly urbanized areas, the positive effect of land use diversity on physical health is amplified by greater population density, whereas in low-density settings, the effect may be weaker or attenuated [43]. This variation underscores the complex interactive mechanisms—potentially involving density thresholds, transportation infrastructure, and neighborhood-level accessibility and safety—that shape the relationship between land use diversity and health outcomes among older adults.

The greening rate also exhibited a significant positive association with the physical health of older adults. Its health-promoting effects are primarily attributed to the multi-dimensional restorative qualities of green environments, including improved air quality [44], noise reduction [45], and enhanced visual landscapes. These indicators collectively enhance the perceptual experience of older adults during outdoor activities, thereby motivating the sustained adoption of health-related behaviors. This finding reinforces the therapeutic potential of green spaces as a nature-based intervention. Green environments not only help alleviate mental stress but also stimulate the senses and induce positive emotional states, which may indirectly support physical recovery through increased engagement in restorative activities.

In contrast, intersection density and destination accessibility showed no significant association with the physical health of older adults in this MA. The presumed benefits of these built environment indicators—such as improved street connectivity and travel efficiency—may not be fully realized in aging populations. A possible explanation is that higher intersection density and greater destination accessibility often correlate with increased traffic complexity and more frequent street-crossing requirements. For older adults, the perceived and actual safety of the walking environment often takes precedence over convenience. As a result, the potential benefits of these indicators may be diminished or even offset by environmental barriers such as high traffic volumes or inadequate pedestrian infrastructure.

4.1.2. Perceived

Dannenberg highlighted that older adults tend to exhibit heightened sensitivity to the safety of their external environment [46]. In communities with poor public security, they often restrict outdoor activities due to concerns about crime, theft, or other safety threats, which in turn limits their engagement in outdoor mobility. Conversely, a well-maintained and secure environment can significantly reduce fear and anxiety during outdoor activities, thereby encouraging sustained participation in daily walking, physical exercise, and social interaction [47]. This strong association between perceived safety and behavioral response underscores the pivotal role of environmental safety as a fundamental condition for outdoor activities among older adults.

Road quality has a significant impact, primarily reflected in surface smoothness and barrier-free design. Due to age-related physical limitations, older adults have heightened requirements for pavement conditions. Uneven surfaces or the presence of obstacles can increase the risk of falls and injuries, thereby reducing the frequency of outdoor activities and negatively affecting physical health. In contrast, high-quality road infrastructure encourages greater engagement in outdoor activities, particularly walking and other low-intensity physical exercises [48].

Environmental aesthetics, including greenery, landscape design, and overall cleanliness, enhance both visual and mental perceptions of space [49], thereby increasing older adults’ willingness to participate in outdoor activities. Aesthetic environments not only stimulate interest in outdoor engagement [50] but also provide pleasant natural surroundings and supportive social settings that promote walking behavior [51]. Older adults are particularly inclined to take daily walks in areas featuring abundant greenery and well-designed landscapes.

In addition, street connectivity and traffic-related indicators were not significantly associated with physical recovery among older adults. Street connectivity often pertains to a broader spatial scale, and its effects may not be directly perceived during routine mobility. Moreover, traffic safety is influenced by multiple interacting variables, including individual health status and the quality of transport infrastructure, which may dilute its observable impact on health-related behaviors in aging populations.

4.2. Built Environment Correlates of Mental Health Outcomes

4.2.1. Objective

Empirical studies have shown that exposure to greenery has a positive impact on residents’ mental health, including promoting psychological recovery and enhancing the experience of outdoor activities. However, this review did not find a significant association between NDVI and mental health in older adults. This result suggests that while the relationship between NDVI-represented green space exposure and health generally shows a positive trend, the actual mechanisms are complex and influenced by multiple factors. NDVI is based on remote sensing data and primarily reflects the “quantity” rather than the “quality” of vegetation cover, unable to distinguish between well-functioning urban parks and barren vacant lots. It also lacks information on human-centric dimensions such as visibility, accessibility, and social use quality. These factors are precisely the key determinants of older adults’ psychological experiences and behavioral patterns. Existing research has shown that green spaces yield the most significant health benefits when they combine safety, social functionality, and aesthetic quality. Additionally, the health effects of green spaces exhibit notable outcome heterogeneity and “population-region” differences. For example, green spaces are more strongly associated with self-reported health and psychological well-being than with physical indicators such as BMI [52]; their protective effects on cardiovascular health are often greater in rural areas than in urban areas [53]. Research also suggests that vegetation coverage may exhibit a threshold effect, as data from Shanghai indicate that green space proportions must fall within an optimal range to yield positive benefits [52].

Therefore, while NDVI offers convenience in large-scale green space assessments, its effects may be masked or diluted if not combined with contextual factors such as environmental quality, social support, and population behavior.

4.2.2. Perceived

Perceived safety is significantly and positively associated with mental well-being among older adults. Studies have shown that a lower perceived risk of crime and the presence of a friendly neighborhood environment can greatly enhance older adults’ sense of happiness and level of social engagement [54]. Engaging in activities such as walking, visiting friends, or participating in community events within a safe environment serves as a crucial mechanism for strengthening social connections, alleviating feelings of loneliness, and ultimately promoting mental health.

Walkability is a critical environmental factor that supports older adults in engaging in daily activities and social interactions [55]. In this review, a significant positive association was found between walking environment quality and mental well-being. High-quality walking environments—characterized by smooth pavements, adequate seating, and barrier-free design [56]—not only improve walking comfort for older adults but also facilitate outdoor social interactions. A well-designed walking environment can enhance older adults’ sense of comfort and mobility, increase their reliance on the community, and foster a stronger sense of belonging and life satisfaction.

4.3. Interaction

4.3.1. Interaction Between Perceived and the Objective Environment

Although the pathways through which perceived and objective characteristics affect health have different emphases, the two are not isolated from each other. Rather, they interact in complex ways to jointly influence and shape the physical and mental health of older adults (Figure 11).

Perceived—Objective Pathways of Action. Perceived environment plays a key moderating and amplifying role between the objective environment and health outcomes. Perceived safety and evaluations of the convenience of walking facilities directly enhance older adults’ mental comfort and willingness to engage in activities, thereby increasing social interaction and the frequency of outdoor activities [57,58]. Similarly, even if road facilities are objectively well-developed, if older adults lack a sense of safety or have doubts about the convenience of facilities, their health benefits may still be limited. This indicates that subjective perceptions determine whether the “opportunities” provided by the objective environment can truly be translated into healthy behaviors.

Objective—Perceived Pathways of Action. Objective environment indirectly influences older adults’ health perceptions and behaviors by shaping contextual conditions and sensory experiences. For example, high green space coverage not only improves air quality and reduces noise [59] but also enhances positive environmental aesthetics, reinforcing older adults’ positive perceptions of the environment and thereby promoting activity willingness [60]. Land use diversity indirectly enhances perceived convenience and safety by increasing accessibility and travel options. This suggests that objective conditions often require perceived interpretation to fully realize their health benefits.

Synergy and bidirectional interaction. Objective and perceived characteristics do not act independently but exhibit synergistic effects and complex coupling. A good walking environment and greenery provide external resources for older adults, while a positive sense of security and comfort further amplify the likelihood of social interaction and physical activity. This interaction is particularly prominent in the dimension of mental health: the objective environment creates space for social interaction and activities, while the subjective perceived motivation and persistence of participation are enhanced. Conversely, in areas with high population density and insufficient public resources, even if objective conditions have certain potential, negative subjective perceived outcomes may weaken health benefits.

4.3.2. Interaction Between Physical and Mental Health

Improvement in physical recovery—such as enhanced physical strength and functional rehabilitation—has been shown to significantly benefit the mental health of older adults [61]. For example, individuals with better joint health often experience greater vitality and reduced feelings of powerlessness or inferiority, thereby contributing to improved mental recovery outcomes. Moreover, engaging in outdoor activities during the day can improve sleep quality [62], which in turn promotes emotional stability and reduces the risk of anxiety and depression. Conversely, a positive mental attitude—such as optimism, hope, and confidence—can enhance self-management abilities, including participation in physical exercise and other health-promoting behaviors, thereby facilitating physical recovery [63]. Individual differences in psychological resilience—the capacity to cope with adversity—also play a critical role in this process. Older adults with higher resilience levels are more likely to maintain a positive outlook, which supports a faster and more effective physical recovery. This bidirectional relationship between physical and mental dimensions underscores the importance of integrated interventions that target both aspects to promote holistic recovery in aging populations.

In summary, improvements in the objective environment can directly influence the emotional states of older adults, thereby shaping their perceptions. This enhancement of emotional well-being consequently increases their willingness to engage in positive recovery behaviors, creating a reciprocal effect [18].

4.4. Strategic Implications

Against the backdrop of an aging population and rapid urban development, urban renewal—particularly micro-scale renewal practices—must holistically address both the physical recovery and mental health of older adults, thereby constructing genuinely age-friendly urban environments. This approach not only charts a new path for promoting healthy aging through planning and design but also concerns the re-establishment of the dynamic interplay between space, behavior, and health. How spatial interventions can guide positive behaviors to enhance health outcomes has become a central concern in urban renewal efforts. Building upon the preceding analysis of the relationship between the built environment and older adult health, we propose the following targeted renewal strategies across four dimensions: accessibility, convenience, comfort, and safety (Figure 12).

4.4.1. Facilitating Physical Recovery

To promote physical health, priority should be given to enhancing environmental Accessibility and Comfort. It is recommended to integrate medical, shopping, cultural, sports, and recreational facilities around older adult residential areas. Through multifunctional land use, create compact, convenient integrated service zones that effectively reduce travel distances. This encourages older adults to engage in daily non-destination-based outings and activities, thereby enhancing physical function. Simultaneously, systematically increase community green coverage by adding street-level green spaces, tree-lined avenues, and small parks to create shaded, clean outdoor environments. Ensure recreational pathways remain level and continuous to enhance the physical and mental comfort of outdoor activities. In terms of Safety, accessible pathways should be improved to reduce physical barriers, while enhancing lighting and slip-resistant flooring. These physical environment enhancements ensure the safety and confidence of older adults during travel, indirectly promoting their physical activity levels.

4.4.2. Fostering Mental Well-Being

In promoting mental health, emphasis should be placed on enhancing environmental Comfort and Safety. By enhancing street aesthetics, incorporating natural landscape elements, installing comfortable seating and social gathering points, we can create pleasant environments that encourage older adults to stroll outdoors and engage in conversation. Simultaneously, we must fully recognize the impact of perceived safety on mental health. This involves improving nighttime lighting, strengthening natural and social surveillance in public spaces, installing clear smart wayfinding signage and emergency assistance facilities. These measures significantly reduce environmental uncertainty and psychological stress, making older adults more willing and confident to venture out. Furthermore, from a Convenience perspective, daily service facilities should be strategically clustered. Promoting intelligent community information delivery will help older adults more easily and independently arrange social and leisure activities, synergistically enhancing their mental health across multiple dimensions.

4.5. Generalizability and Research Implications

Significance of the Study. This study focuses on China, the developing country experiencing the fastest and largest aging population globally. Its significance not only fills a gap in quantitative research on this topic within developing nations but also validates, through the Chinese case, the positive effects of built environment interventions on the health of older adults. It provides both theoretical foundations and practical paradigms for developing countries worldwide to address the dual challenges of demographic transition and urban spatial restructuring. At the academic level, existing research on the built environment and the health of older adults has largely focused on developed countries in Europe and America, making its conclusions difficult to directly apply to the unique contexts of developing nations. Developing countries commonly face the dilemma of rapid urbanization lagging behind planning, coupled with dramatic demographic shifts and inadequate public services, making the disconnect between the health needs of the elderly and the built environment even more pronounced. For instance, issues such as community spatial fragmentation and the imbalance between supply and demand for public facilities resulting from rapid urbanization significantly constrain the daily activities and health behaviors of the elderly [64]. However, systematic quantitative research on this demographic remains severely lacking, with most reviews relying on qualitative analysis that struggles to yield universally applicable conclusions. This study employs meta-analysis to synthesize empirical data from the Chinese context, quantifying the impact of the built environment on the physical and mental health of older adults from both objective and subjective dimensions. It provides a reference analytical framework for related research in developing countries. In practical terms, as developing countries undergo simultaneous urbanization and aging, there is a widespread tendency in planning to prioritize physical infrastructure over humanistic care, with the built environment’s supportive role for the health of the elderly being severely neglected [65]. The findings of this study provide concrete guidance for urban renewal and public space design in developing countries: optimizing the continuity and accessibility of pedestrian networks while leveraging smart technologies to offer clear navigation services for older adults; concentrating essential daily service facilities in convenient areas and synchronizing their operational information to household terminals via smart software. These strategies can effectively alleviate the pressure of insufficient public health resources in developing countries, offering a feasible pathway for low-cost enhancement of health and well-being among older adults.

Generalizability of the Analytical Framework. We have developed a comprehensive methodological framework for synthesizing quantitative evidence on the environment-health relationship within specific social contexts. This approach does not rely solely on qualitative summaries but integrates systematic literature searches, standardized variable categorization, and meta-analysis techniques to quantify results across studies. The core strength of this framework lies in its ability to contextualize environmental measures (e.g., distinguishing between objective and perceived attributes) and health proxies (e.g., frequency-based indicators of physical activity and social interaction) while maintaining analytical consistency. It is not limited by disciplinary boundaries; in fact, meta-analysis was initially widely applied in evidence-based medicine research and later expanded into the field of environment and health. Additionally, it provides a transferable logic for studying the interactions between environment and health across different climatic, geographical, and cultural contexts. By emphasizing contextualized and systematic evidence integration, this method supports cross-regional comparisons and promotes theoretical development in global research on the built environment and healthy aging across diverse contexts.

Limitations. Regarding the weighted Z-score method, we adopted it after thoroughly considering the common characteristics of the included studies. Since most literature did not provide data necessary for calculating conventional effect sizes, the weighted Z-score method effectively integrates significance levels under existing conditions and assesses the overall statistical robustness of research findings. We also recognize that future studies may further explore the feasibility of directly calculating actual effect sizes to obtain more precise estimates. In terms of health indicator selection, we employed “physical activity frequency” and “social interaction” as proxy measures for physical and mental health, respectively. This choice stems from these indicators exhibiting the highest consistency and comparability across the included literature, thereby ensuring the robustness of the review and meta-analysis findings. It should be noted that this selection does not imply neglect of other important indicators related to physical and mental health, such as activity intensity, depression, anxiety, and self-rated health. Rather, based on the standardized procedures of meta-analysis methodology and the common characteristics of the included studies, we ultimately focused our analysis on the aforementioned two proxy indicators. Although “physical activity frequency” and “social interaction” do not comprehensively cover all dimensions of older adults’ physical and mental health, they are widely recognized and highly reliable measurement approaches in existing research, making them highly applicable in this study. This methodological choice ensures comparability while also suggesting that future research should expand to include richer and more diverse health measurement indicators to deepen our understanding of the relationship between the built environment and older adults’ health.

In summary, this study systematically integrates evidence on the association between the built environment of Chinese cities and the physical and mental health of older adults, taking into account both objective and perceived dimensions. It not only provides new analytical insights for interdisciplinary research but also offers valuable references for other developing countries and regions undergoing rapid urbanization and aging.

5. Conclusions

This review applies a meta-analytic approach to systematically quantify the effects of both objective and perceived environmental characteristics on the physical and mental health of older adults. By calculating weighted Z-values, the study rigorously integrates data from multiple empirical studies, offering a statistically robust method for synthesizing existing evidence. This approach addresses limitations found in prior descriptive reviews and provides a new analytical framework for examining how various built environment factors influence health outcomes in older adults. The analysis distinguishes between objective environmental attributes—such as population density, land use diversity, and green coverage—and subjective perceptions, including public safety, road quality, and environmental aesthetics. In doing so, it reveals the nuanced interactions between environmental exposures and health outcomes.

Systematic Quantification. This study is among the first to apply a meta-analytic method to integrate data from multiple relevant studies, quantitatively evaluating how both objective and perceived environmental characteristics affect the physical and mental health of older adults. The results highlight the complexity of the interactions between environmental indicators and health.

Dual Analysis of Objective and Perceived Environments. By differentiating between objective and perceived environmental dimensions, the analysis demonstrates that land use diversity and green coverage (objective indicators) are significantly positively associated with health outcomes. Simultaneously, perceived characteristics such as public safety, road quality, and environmental aesthetics also show strong associations with better health. These findings offer a theoretical foundation for evidence-based environmental design.

Differentiated Effects of Environmental Comfort. Further analysis of comfort-related indicators revealed that the objective indicator NDVI has a complex mechanism of influence on mental health. In contrast, perceived indicators such as safety and pedestrian infrastructure show significant positive associations, underscoring the importance of subjective perceptions in health-related interventions.

Synergistic and Complex Interactions. The results point to a synergistic and complex interplay between objective and perceived environmental indicators. While objective characteristics create structural opportunities for health-supportive behaviors, perceived environments shape behavioral intentions and amplify health outcomes through subjective experience. These findings offer new insights into how interventions can be designed to maximize the health benefits of the built environment for older adults.

Policy and Design Implications. The findings provide a quantitative foundation for optimizing environments that promote healthy aging, highlighting the critical roles of comfort, safety, and accessibility. Future urban planning efforts should focus on increasing opportunities for outdoor physical activity and social engagement to holistically enhance the physical and mental well-being of older adults.

In conclusion, both objective and perceived environmental indicators show significant associations with the physical and mental well-being of older adults, particularly regarding comfort, safety, and accessibility. While objective indicators facilitate health-supportive behaviors, perceived environments influence motivation, perceived barriers, and behavioral engagement, ultimately enhancing the health benefits of the built environment. This study not only contributes theoretical and empirical evidence for age-friendly urban design but also underscores the importance of integrated strategies that address both structural and experiential dimensions. Future research should further investigate contextual differences across urban settings and promote personalized, evidence-based interventions to support the long-term health and quality of life of older adult populations.