The Relationship Between Neighborhood Environment,Health-Related Behaviors,and Self-Rated Health in Community-Dwelling Older Adults in Japan

Abstract

This cross-sectional study investigated the influence of neighborhood environments and health-related behaviors on self-rated health among older adults in Kitaibaraki City, Japan. A questionnaire was mailed to 5,000 individuals aged 65–85 years to collect data on demographics, social connections (Lubben Social Network Scale 6), social participation, and frequency of going out. Neighborhood walkability was assessed using Walk Score®. Path analysis with structural equation modeling was used to analyze 1,779 responses to evaluate direct and indirect effects on self-rated health. We found significant indirect effects of social connections on self-rated health via social participation (β = 0.058, p < .01) and frequency of going out (β = 0.051, p < .01). Direct effects of social participation (β = 0.194, p < .01) and frequency of going out (β = 0.194, p < .01) were also significant. Promoting social participation, encouraging outings, and strengthening social connections through community resources are crucial for increasing self-rated health.

Introduction

As global aging accelerates, supporting older individuals in maintaining their physical and mental well-being has become increasingly important. Promoting social participation in community activities and increasing opportunities to go out for exercise are crucial for older people to remain healthy (Ministry of Health, Labour and Welfare, 2023a; Szychowska & Drygas, 2022). Social participation and physical activity are associated with cognitive function (Oh et al., 2021), activities of daily living (ADL) (Ma et al., 2020), mental health (Hong & Morrow-Howell, 2010), and self-rated health (Opdal et al., 2020).

Neighborhood environments are significant in enhancing the health of older people. The World Health Organization (WHO) advocates policies that foster the development of neighborhood environments, promoting the health of older people (WHO, 2007). A previous study identified physical and social environments as the two main aspects of neighborhood environments (Diez Roux & Mair, 2010). The physical environment encompasses land use, transport, aesthetic quality, urban design, public spaces, and neighborhood walkability; walkability refers to access to resources such as grocery shops, exercise facilities, and parks, and is a crucial indicator for creating a city where older people can live while moving on foot (Kato & Kanki, 2017). The social environment includes local security, safety, and social connections. Although there is no consistent definition of social environment, it is essential to create an environment where older adults are not isolated by promoting active social participation in the community. Studies have shown that neighborhood walkability and social connections are associated with social participation and going out among older adults (Barnett et al., 2017; Colom et al., 2021; Holt-Lunstad, 2022; Moogoor et al., 2022; Moran et al., 2014; Zhou et al., 2024), making them critical interventions for promoting health. Neighborhood walkability and social connections are essential indicators when considering approaches to developing neighborhood environments to improve the health of community-dwelling older adults.

A prior study showed that the neighborhood environment of older people does not directly affect their health; however, various factors (including behaviors such as physical activity and social participation) interact to affect their health (Zheng & Yang, 2019). Several studies have reported that neighborhood walkability affects mood (Lu et al., 2021), subjective health (Zheng & Yang, 2019), and body mass index (Koohsari et al., 2019) through impacting social participation, going out, and physical activity among older adults. Researchers have suggested that developing neighborhood environments with a comprehensive perspective that combines different environmental factors, such as neighborhood walkability and social connections, is essential (Wang et al., 2023), underscoring the need for a holistic development approach.

Weakened social networks have been linked to higher mortality among older adults (Holt-Lunstad et al., 2010), highlighting the importance of social connections in their health. In Japan, a decline in local social networks and reciprocal support has been reported (Kawasaki et al., 2023; Sekiguchi et al., 2021). These social challenges are further exacerbated by the increase in the number of older adults living alone and the weakening of family support (Cabinet Office, Government of Japan, 2024). Such trends highlight the importance of fostering interpersonal connections not only within families but also communities; social isolation has been associated with unhealthy lifestyle habits (Yamaguchi et al., 2020), whereas close relationships and spousal support promote social participation (Horiguchi & Okawa, 2018). These findings suggest that relationships with others significantly influence health and health-related behaviors. Understanding how both physical and social neighborhood factors affect the health of older adults is essential for designing effective community-based strategies that support healthy aging and social reconnection.

This study investigated the effects of social participation, going out, neighborhood walkability, and social connections on the subjective health of community-dwelling older adults in Japan. We utilized path analysis with structural equation modeling (SEM) to test the complex association of the neighborhood environment influencing social participation and going out with subjective health. The results have the potential to provide significant scientific evidence for promoting social participation and going out to improve the subjective health of older people, and may offer valuable insights for considering efficient approaches for improving neighborhood environments.

Hypothesized Model

We constructed the hypothesized model of “neighborhood environment–health-related behaviors–self-rated health” (Figure 1), building upon the previously proposed model of “neighborhood environment–lifestyle–health of older people” (Zheng & Yang, 2019). This model is grounded in the socio-ecology theory (Kang et al., 2023), which suggests that individual behaviors are influenced not only by personal factors such as age, sex, and genetic predispositions but also by broader contextual factors, including the social environment. The previous model evaluated the neighborhood environment using only the physical environment; in response to the reported importance of both physical and social dimensions in promoting healthy aging-in-place (Wang et al., 2023), our study extends this framework by incorporating both aspects. We hypothesized that a comprehensive neighborhood environment encourages health-related behaviors, which increase self-rated health among older people.

Figure 1.

The hypothesized model of “neighborhood environment–health-related behaviors–self-rated health”.

In our extended model (Figure 1), we hypothesized that neighborhood walkability and social connections are key components of the neighborhood environment. These factors are important indicators for promoting social participation and going out among older adults (Barnett et al., 2017; Colom et al., 2021; Holt-Lunstad, 2022; Moogoor et al., 2022; Moran et al., 2014; Zhou et al., 2024). Neighborhood walkability is recognized as a key indicator in the WHO Guide to Age-Friendly Cities (WHO, 2007). In addition, Japanese policy emphasizes that improving the quality of the surrounding environment—such as ensuring access to health-promoting facilities and strengthening connections within local communities—can encourage health-related behaviors and improve health outcomes (Ministry of Health, Labour and Welfare, 2023b). From both academic and policy standpoints, neighborhood walkability and social connections are essential components to consider when designing environments that support the health of older adults.

We also hypothesized that social participation and frequency of going out are key components of health-related behaviors. Social participation and physical activity have been identified as key components of health-related behaviors that contribute to better health and quality of life in older adults (Feng et al., 2020). Among various forms of physical activity, going out does not require special equipment or facilities, and can be relatively easily incorporated into daily life. Frequency of going out has been recognized as a practical proxy for assessing physical activity (Wakayama et al., 2020), with more frequent outings contributing to higher levels of physical activity and the maintenance of better health. Increased opportunities to go out are linked to improvements in ADL as well as physical and mental health outcomes (Harada et al., 2018; Kono et al., 2004). Based on these previous findings, the present study included both social participation and the frequency of going out as key components of health-related behaviors.

Methods

Study Design and Participants

A cross-sectional questionnaire survey was conducted in Kitaibaraki City, Ibaraki Prefecture, Japan. The city has a population of 41,870, 36% of whom were aged ≥ 65 years as of April 2022 (Ibaraki Prefectural Government, 2024). In comparison, the proportion of Japan's total population aged ≥ 65 years is 29% (Cabinet Office, Government of Japan, 2023a).

The target population consisted of residents aged 65–85 years who were not certified under long-term care insurance as requiring long-term care. In April 2022, questionnaires were sent by mail to 5,000 people who were randomly selected by administrative city staff. The responses were collected by mail. Questionnaires were distributed to selected older adults for self-administration, with responses provided directly by the participants. We excluded those who did not respond to the questionnaire, and those with incorrect or missing data.

Measurement

The questionnaire survey collected information about the home postcode, the extent of social connections (using an abbreviated version of the Lubben Social Network Scale 6 [LSNS-6]) (Kurimoto et al., 2011); social participation; frequency of going out; subjective health status; age; gender, economic status (including satisfaction with economic status); residential status; working status; and medical history. In the hypothesized model of “neighborhood environment, health-related behaviors, and self-rated health” (Figure 1), neighborhood walkability and social connections were included. The Walk Score^® (Walk score, 2024) was calculated using postal codes to measure neighborhood walkability; the score evaluates neighborhood walkability based on the number of restaurants, grocery shops, parks, and other facilities within walking distance (1.6 km) of a specified point on Google Maps, and has been conﬁrmed as a valid measure (Koohsari et al., 2018). Neighborhood walkability was measured on a scale from 0 to 100 points and classified into four score categories: 0–49 = car dependent, 50–69 = somewhat walkable, 70–89 = very walkable, and 90–100 = walker's paradise (Walk score, 2024).

The LSNS-6 was used to assess social connections, similar to a previous study that used it to assess the social environment (Harada et al., 2019). It includes a set of three items on family and a comparable set of three items on friends, asking about frequency of contact and emotional closeness. The reliability and validity of the LSNS-6 were confirmed in a previous study (Kurimoto et al., 2011); scores range from 0 to 30, with a higher score indicating a wider social network (Kurimoto et al., 2011).

We included social participation and frequency of going out among health-related behaviors. Social participation was assessed by asking the following question: “Do you participate in any community or volunteer activities?” (Ozone et al., 2022). The frequency of going out was measured based on responses to a single question (“How many days a week do you go out?”) on a four-point Likert scale with the following options: “almost every day,” “2–3 times/week,” “1 time/week,” and “rarely” (Todo et al., 2015).

Self-rated health, a widely used measure of comprehensive health status, was assessed using a four-point Likert scale from “very good” to “very bad” (Bin & Hoshi, 2005). We also asked each respondent about their age, sex, degree of satisfaction with economic status (very satisfied, satisfied, not satisfied, or very dissatisfied), residential status (living alone or not), working status (working or not), and medical history (heart disease, stroke, hypertension, or diabetes).

Statistical Analysis

In the hypothesized model (Figure 1), the outcome variable was self-rated health, the exposure variables were neighborhood walkability (Walk Score^®) and social connections (LSNS-6), and the mediators were social participation and frequency of going out; the model was adjusted for age, gender, economic status, residential status, working status, and medical history. Using path analysis with SEM, the hypothesized model tested the direct and indirect effects of each factor. Self-rated health, used as the outcome variable, was an ordinal variable. The weighted least squares mean and variance adjusted estimator was used to test the association between variables (Muthén & Muthén, 2017), and the bias-corrected bootstrap method was used to examine the significance of the indirect effects.

Based on a previous study (Morgan et al., 2021), four goodness-of-fit indices of the hypothesized model were used: the chi-square test (χ²), comparative fit index (CFI), standardized root mean square residual (SRMR), and root mean square error of approximation (RMSEA). A non-significant χ², CFI > 0.90, and SRMR < 0.08 indicated an acceptable model fit (Hu & Bentler, 1999). An RMSEA of 0.05–0.08 represented a moderate fit, while that of 0.08–0.10 represented an acceptable fit (Yu et al., 2022). The significance threshold of the standardized coefficients was set at 5%. Statistical analyses were performed using Mplus8.0. This study was approved by the University of Tsukuba Medical Ethics Board (approval no. 1602).

Results

Participant Characteristics

Of the 5,000 individuals selected, 1,957 responded to the questionnaire (response rate: 39.1%). We excluded 178 respondents with incorrect or missing responses, leaving 1,779 responses for analysis (Figure 2). The mean age of the respondents was 73.2 (SD: 5.2) years, and 917 (51.5%) were female. Self-rated health was self-reported as “very good” by 145 participants (8.2%), “good” by 1,285 (72.2%), “bad” by 268 (15.1%), and “very bad” by 81 (4.6%). The average Walk Score^® was 25.8 (SD: 18.9), and the mean LSNS-6 was 14.4 (SD: 6.0). Social participation was reported by 526 (29.6%) participants; frequency of going out was self-reported as “almost every day” by 1,305 (73.4%), “2–3 times/week” by 371 (20.9%), “1 time/week” by 74 (4.2%), and “rarely” by 29 (1.6%) (Table 1).

Figure 2.

Flow chart of the study participants and response processing.

Table 1.

Characteristics of the Study Population (n = 1,779).

Characteristic		Overall
Age, mean ± SD (years)		73.2 ± 5.2
Gender, n (%)	Female	917 (51.5)
Self-rated health, n (%)	Very good	145 (8.2)
	Good	1,285 (72.2)
	Bad	268 (15.1)
	Very bad	81 (4.6)
Walk Score®, mean ± SD		25.8 ± 18.9
LSNS-6, mean ± SD (years)		14.4 ± 6.0
Social participation, n (%)	Yes	526 (29.6)
Frequency of going out, n (%)	Almost every day	1,305 (73.4)
	2-3 times/week	371 (20.9)
	1 time/week	74 (4.2)
	Rarely	29 (1.6)
Economic status, n (%)	Very satisfied	43 (2.4)
	Satisfied	844 (47.4)
	Not satisfied	787 (44.2)
	Very dissatisfied	105 (5.9)
Living alone, n (%)	Yes	265 (14.9)
Working, n (%)	Yes	548 (30.8)
Medical history	diabetes	285 (16.0)
	hypertension	815 (45.8)
	heart disease	135 (7.6)
	stroke	44 (2.5)

Note: LSNS-6, An abbreviated version of the Lubben social network scale 6.

Path Analysis

The goodness-of-fit indices of the hypothesized model were:χ² (1) = 12.8, p < .05, CFI = 0.978, SRMR = 0.02, and RMSEA = 0.081. We tested the hypothesized model, with Figure 3 presenting the overall results. The indirect effect of social connections on self-rated health via social participation was significant (β = 0.058), as was that of frequency of going (β = 0.051). The indirect effect of neighborhood walkability on self-rated health via social participation or frequency of going out was not significant (Table 2).

Figure 3.

Standardized coefficients of the hypothesized model. The solid lines represent statistically significant effects, while the dotted lines indicate effects which are not statistically significant. The goodness-of-fit indices of the hypothesized model: χ²(df) = 12.8(1), comparative fit index (CFI) = 0.978. Standardized root mean square residual (SRMR) = 0.02, root mean square error of approximation (RMSEA) = 0.081. The hypothesized model was adjusted for age, gender, economic status, residential status, working status, and medical history. **p < .01, *p < .05.

Table 2.

Direct and Indirect Effects of the Hypothesized Model.

Pathways	β	95% CI	P-value*
Direct Effect
Neighborhood walkability → Self-rated health	−0.028	−0.077–0.023	.284
Social connections → Self-rated health	0.071	0.012–0.138	<.05
Social participation → Self-rated health	0.194	0.12–0.273	<.01
Frequency of going out → Self-rated health	0.194	0.12–0.267	<.01
Neighborhood walkability → Social participation	−0.004	−0.066–0.056	.906
Neighborhood walkability → Frequency of going out	0.025	−0.030–0.088	.408
Social connections → Social participation	0.3	0.242–0.356	<.01
Social connections → Frequency of going out	0.264	0.208–0.321	<.01
Indirect Effect
Neighborhood walkability → Social participation → Self-rated health	−0.001	−0.013–0.011	.908
Neighborhood walkability → Frequency of going out → Self-rated health	0.005	−0.006–0.02	.433
Social connections → Social participation → Self-rated health	0.058	0.035–0.086	<.01
Social connections → Frequency of going out → Self-rated health	0.051	0.031–0.076	<.01

β: Standardized coefficients; CI: confidence interval.

*P-value for testing the direct and indirect effects of the hypothesized model using path analysis with SEM.

The direct effects of social connections (β = 0.071), social participation (β = 0.194), and frequency of going out (β = 0.194) on self-rated health were significant. In addition, the direct effects of social connections on social participation (β = 0.3) and frequency of going out (β = 0.264) were significant. The direct effects of neighborhood walkability on social participation and frequency of going out were not significant (Table 2).

Internal Consistency Reliability

The internal consistency reliability of the LSNS-6 was assessed using Cronbach's alpha. In our study, the Cronbach α values were 0.82.

Discussion

Referring to the existing model (Zheng & Yang, 2019), we constructed a hypothetical “neighborhood environment–health-related behaviors–self-rated health” model of the factors influencing self-rated health, and tested the direct and indirect effects of factors such as neighborhood environment (neighborhood walkability and social connections) and health-related behaviors (social participation and frequency of going out) on self-rated health among community-dwelling older adults. The indirect effect of social connections on self-rated health via social participation and frequency of going out was significant, whereas the indirect effect of neighborhood walkability on self-rated health via social participation or frequency of going out was not significant. Additionally, the direct effects of social participation and frequency of going out on self-rated health were significant. These results suggest that to improve the self-rated health of older people, it is necessary to consider not only the single causal effect of promoting social participation and frequency of going out but also the neighborhood environment, shaped through mechanisms such as social network development.

The indirect effects of social connections on self-rated health via social participation and the frequency of going out were comparable to the direct effects of social connections, indicating that enhancing social networks may increase social participation and frequency of going out, increasing self-rated health. The number of people who know and trust the neighborhood is associated with social participation (Bowling & Stafford, 2007), and the number of friends is associated with physical activity (Ho et al., 2018). In addition, a study conducted in China showed that good relationships with neighbors may promote social participation and increase self-rated health (Zheng et al., 2019); our results are similar to those of these studies from different countries and regions. A significant association exists between physical activity and perceived social support, such as having someone to consult or spend time with (Lieber et al., 2024), suggesting that interpersonal relationships may promote physical activity. The dissemination of health-related information within communities affects health-related behaviors (Hunter et al., 2019). This implies that engaging in and maintaining health-related behaviors is not solely a personal effort but is also shaped by the social environment, including family and community. Our findings suggest that older adults with stronger social connections within their local communities are more likely to obtain health-related information and receive support and encouragement, which may promote greater social participation and more frequent outings. As examples of commitments in Japan, residents, private corporations, and municipalities are working together to strengthen the monitoring of older people living alone (Cabinet Office, Government of Japan, 2023b) and provide opportunities for neighbors to engage with others by opening part of their homes to the public (Korenaga, 2022). As the populations in Japan and many other countries are aging, it is necessary to create ways to increase the self-rated health of older people while maximizing regional and country-wide resources.

The indirect effects of neighborhood walkability (as assessed by Walk Score^®) on self-rated health via social participation and frequency of going out were not significant. Previous studies have reported that Walk Scores are associated with well-being (Yoshino & Oshio, 2019), social participation (Matsumoto et al., 2022), and physical activity (Frehlich et al., 2019), indicating that the physical environment, such as neighborhood walkability, may influence quality of life and social participation. However, the present results indicate that neighborhood walkability is not associated with health-related behaviors and self-rated health. One reason for this could be the impact of the differences in the target areas. Previous studies have shown that the average Walk Score^® was 60–65 (Frehlich et al., 2019; Matsumoto et al., 2022; Yoshino & Oshio, 2019), whereas the average Walk Score^® in our study was 25.8. This corresponds to a car-dependent neighborhood (Walk score, 2024), with just a few destinations within easy walking range and driving or public transportation being required for most errands. This suggests that in areas with a poorly established physical environment (such as low-walkability neighborhoods), older adults may engage in social participation and go out regardless. A survey targeting older adults aged ≥ 65 years who held a driver's license found that 75.6% reported driving for at least 3 to 4 days per week (Cabinet Office, Government of Japan, 2021). In regions with limited public transportation infrastructure, a range of mobility support services (such as mobile shops, shopping assistance, and community-operated shuttle buses or taxis) has been increasingly implemented (Ministry of Economy, Trade and Industry, 2023). These services may support the mobility of older adults, potentially weakening the influence of neighborhood walkability on social participation and going out. Future research may need to employ indicators to measure neighborhood walkability in car-dependent environments.

The direct effects of social participation and frequency of going out on self-rated health among community-dwelling older adults were significant, indicating that they may increase self-rated health. Prior studies targeting older people have reported that social participation (such as attending neighborhood groups and hobbies clubs) and continuing to go out are associated with self-rated health (Opdal et al., 2020; Zheng & Yang, 2019). Several activities to increase social participation and the frequency of outings have been reported, including initiatives to encourage outings by providing information through leaflets and posters (Kamada et al., 2018), as well as commitments to create opportunities for older people to utilize their skills and knowledge (Tokyo Metropolitan Government Bureau of Social Welfare, 2023). It is considered necessary to not only rely on individual initiative but also collaborate with people from various backgrounds to share appropriate information, as well as to create opportunities for older people to play an active role.

This study had several limitations. The study was conducted in a single city in Japan, meaning that the findings are valuable for this region but may not be generalizable to other locations. Further research is needed to elicit findings that can be applied to more areas by including regions with different population densities and public transport networks. Additionally, the questionnaire response rate was 39.1%, which may have created selection bias because more health-conscious residents responded. Although we endeavored to reduce sampling bias by randomly selecting the target population, it may have included many members of the target population who were more willing to participate. Finally, the LSNS-6, which is used to assess social networks, focuses on quantitative aspects such as the number of social networks and does not include a questionnaire on the depth of relationships. A previous study reported that both quantitative and qualitative aspects are necessary for assessing social connections (Shin & Park, 2023), which should be included in future research.

Conclusion

Social participation and going out affect the self-rated health of older adults, and social connections (a key component of the social environment) positively affect self-rated health directly, and also indirectly through these behaviors. These findings underscore the importance of fostering social connections to promote health-related behaviors, particularly in communities with poorly established physical environments.

Footnotes

Acknowledgments

We thank the staff of the Elderly Welfare Division in Kitaibaraki City for their cooperation in conducting the survey. We also thank the residents who responded to the survey. We also thank Cosmin Mihail Florescu (Medical English Communications Center, University of Tsukuba) for the editorial assistance. Additionally, we would like to thank Editage () for English language editing.

ORCID iDs

Atsuhiro Yano

Ryohei Goto

Ayumi Takayashiki

Sachiko Ozone

Shoji Yokoya

Tetsuhiro Maeno

Ethical Considerations

All participants were informed about the study orally and in writing and provided written informed consent before enrollment in the study. This study was approved by the University of Tsukuba Medical Ethics Board (approval no: 1602).

Funding

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: This study was supported by JSPS KAKENHI Grant number 21K17223.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability

The datasets of the current study are not publicly available due to ethical restrictions.

Author Biographies

Atsuhiro Yano is a PhD Student in the Department of Comprehensive Human Sciences, University of Tsukuba. His research interests include elderly health, neighborhood environment, and rehabilitation.

Ryohei Goto is an Associate Professor in the Institute of Medicine at the University of Tsukuba. He received his PhD from the University of Tsukuba. His research interests include life sciences, healthcare management, and medical sociology.

Ayumi Takayashiki is an Assistant Professor in the Institute of Medicine at the University of Tsukuba. She received her PhD from Jichi Medical School. Her research interests include Social Determinants of Health and Medical Education.

Sachiko Ozone is an Assistant Professor in the Institute of Medicine at the University of Tsukuba. She received her PhD from the University of Tsukuba. Her research interests include life sciences and general internal medicine.

Shoji Yokoya is a Professor in the Institute of Medicine at the University of Tsukuba. He received his PhD in Medicine from the University of Tsukuba. His research interests include Medical Education, Interprofessional Work, Palliative Care, Health Education, Community-Based Medicine, General Practice, and Family Medicine.

Tetsuhiro Maeno is a Professor in the Institute of Medicine at the University of Tsukuba. He received his PhD from the University of Tsukuba. His research interests include life sciences, healthcare management, medical sociology, and general internal medicine.

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