Abstract
With the rapid aging of the Japanese population, loneliness, social isolation, and mental health decline have become major public health concerns. Leisure activities contribute to health and well-being in later life; however, associations with residential factors remain unclear. This study examined associations between leisure activity participation (frequency and number of activities) and the residential environment among community-dwelling older adults in Japan. A cross-sectional questionnaire survey was conducted on 324 adults aged ≥ 65 years in Fukushima Prefecture. Leisure activities were assessed using a leisure activity scale, and residential factors included housing type, mode of transportation, and neighborhood environment. Multiple and logistic regression analyses were conducted. The results indicated that greater participation was associated with living in a detached house, driving a private car, and access to public transport. Although associations with individual leisure activities were more limited. Nevertheless, overall leisure activity participation was associated with housing type, family composition, access to public transport and recreational facilities and driving a private car. Therefore, transportation access, family support, and community engagement may be related to leisure activity participation in later life. However, causal relationships and the direction of these associations cannot be determined. Further longitudinal and multifaceted studies are warranted.
Keywords: community-dwelling, leisure activities, older adults, residential environment
Introduction
Population aging has raised global concerns because of its association with various physical and psychological challenges, including loneliness, social isolation, and mental health decline. Although medical advancements have extended life expectancy, healthy life expectancy—the average number of years an individual is expected to live in good health without disability or illness—often fails to keep pace. To achieve healthy longevity, it is essential to not only maintain high levels of physical and cognitive function, but also engage in activities that enhance mental health and subjective well-being (Mak et al., 2023; Rowe & Kahn, 1997).
Older adulthood is a life stage characterized by relatively increased discretionary time, and the sense of fulfillment derived from leisure time significantly influences life satisfaction. Leisure activities, defined as activities performed independent of work or daily life activities for personal enjoyment and well-being, are reported to affect positive emotions, enhance well-being, and improve life satisfaction (Chao, 2016; Mak et al., 2023; Verghese et al., 2006; Zhang et al., 2017).
However, participation in leisure activities may be influenced by differences in living arrangements and the neighborhood environment. Previous studies have shown that older adults in rural areas tend to be less socially active than those in urban settings, and that individuals who drive, use public transportation, or walk participate in leisure activities more frequently than those who rely on passenger cars or taxis (Dahan-Oliel et al., 2010; Vogelsang, 2016). Regarding the neighborhood environment, good access to commercial facilities, public transportation, parks, and recreational spaces has been linked to higher physical activity levels, and recreational facilities, pedestrian-friendly features, and attractive scenery have been shown to have a positive influence on older adults’ participation in physical activities (Cerin et al., 2017; Van et al., 2018).
Although numerous studies have examined the health benefits of leisure activities and their associations with living arrangements and the neighborhood environment, relatively few studies have comprehensively examined how these factors relate to the frequency and number of leisure activities. Moreover, research on the neighborhood environment has primarily focused on physical activity, with limited attention paid to other forms of leisure. As older adults tend to engage often in activities near their homes, enhancing the neighborhood environment is crucial for promoting active lifestyles (World Health Organization, 2012).
Given this background, the present study aimed to examine the associations between the frequency and number of leisure activities and the residential environment among older Japanese adults. In this study, based on the framework of Mimura (2021), the residential environment refers to factors that may affect an individual’s daily life, such as family composition, usual means of transportation, and neighborhood features. The findings may provide fundamental insights into leisure activities and inform strategies to develop residential environments that facilitate active engagement in later life among Japanese older adults.
Methods
Study Design, Setting, and Participants
A self-administered questionnaire survey was conducted as part of a community health survey in three locations within Fukushima Prefecture: Minamisoma City, Kagamiishi Town, and Fukushima City. The study participants were recruited through advertisements published in local community newsletters. The inclusion criteria were: (1) age ≥ 65 years at the time of data collection, and (2) residing in the community. Eligibility was confirmed through a combination of questionnaire responses and interviews. A total of 324 participants were enrolled: 113 from Minamisoma City, 133 from Kagamiishi Town, and 78 from Fukushima City.
This study was approved by the Ethics Committee of Fukushima Medical University (approval No.: General 2022-123). All study procedures adhered to the ethical guidelines for medical and health research involving human participants in Japan. All individuals received both verbal and written explanations regarding this study. Written informed consent was obtained from all participants.
Measures
Leisure Activity Scale for Contemporary Older Adults (LASCO)
Participation in leisure activities was assessed using the Leisure Activity Scale for Contemporary Older adults (LASCO), which evaluates the frequency of engagement in 11 categories of leisure activities (Iwasa et al., 2019). The participants’ responses used a four-point Likert-type scale, from “0 = never” to “3 = frequently”. Total scores ranged from 0 to 33, with higher scores indicating more frequent participation in leisure activities.
Residential Environment
The residential environment was assessed by examining housing type, family composition, usual modes of transportation, and the neighborhood environment. Housing type represented the participant’s own residence and was dichotomized into detached houses and other housing types. Family composition was dichotomized into living alone and not living alone. Usual modes of transportation reflected actual transportation behavior and included private car driving and public transportation use (train and/or bus use).
The neighborhood environment was evaluated using the International Physical Activity Questionnaire-Environmental Module (IPAQ-E), a self-administered questionnaire that assesses environmental features within approximately a 10- to 15-minute walk from one’s residence (Alexander et al., 2006; Inoue et al., 2009). Based on previous studies, 11 items were used in this study. Residential density (Item 1) reflected the predominant housing characteristics of the surrounding neighborhood environment rather than the participant’s own housing type and was assessed according to the main type of housing in the neighborhood. Access to public transport reflected the perceived availability and accessibility of public transportation within the neighborhood environment rather than the participant’s actual use of public transportation. Items 2 through 10 were rated on a four-point Likert-type scale (dichotomized as “No” for “not at all true”/“somewhat untrue” and “Yes” for “somewhat true”/“very true”). Consistent with previous research, residential density was dichotomized into neighborhoods characterized primarily by detached houses and by other housing types. Items 2–10 were similarly dichotomized for analysis (Inoue et al., 2009).
Other Variables
Basic participant characteristics included age group (65–74, 75–84, and ≥ 85), sex (male, female), region (Minamisoma City, Kagamiishi Town, Fukushima City), subjective health status, presence of medical conditions, chronic pain, psychological distress (Japanese version of the Kessler 6-item Psychological Distress Scale [K6]), social isolation (Japanese version of the Lubben Social Network Scale-6 [LSNS-6]), and the basic checklist scores.
Subjective health status was assessed by asking, “How would you describe your current health status?” Responses were given on a four-point Likert-type scale. For the analysis, responses were dichotomized into “healthy” (categories 1 and 2), coded as 1, and “unhealthy” (categories 3 and 4), coded as 0.
Medical conditions were identified by the question, “Have you ever been diagnosed with any of the following diseases or conditions?”. “None” was coded as 0, and selecting conditions was coded as 1.
Chronic pain was assessed by asking, “Have you experienced pain lasting longer than 1 month?”. “No pain” was coded as 0, and the reporting of any pain was coded as 1.
Psychological distress was measured using the Japanese version of the K6, which is composed of six items assessing distress experienced on a five-point scale with total scores ranging from 0 to 24 (Furukawa et al., 2008). Higher scores indicate more severe depressive and anxiety symptoms. A K6 score ≥ 5 indicates moderate psychological distress (Prochaska et al., 2012). A K6 score ≥ 5 was used as the cutoff for mild psychological distress.
Social isolation was assessed using the Japanese version of the LSNS-6 (Lubben et al., 2006). The LSNS-6 consists of six items, where respondents indicate the number of contacts on a six-point scale, producing scores from 0 to 30. Higher scores indicate larger social networks, whereas scores < 12 indicate social isolation (Kurimoto et al., 2011).
The basic checklist score, developed by the Japanese Ministry of Health, Labour and Welfare, is a screening tool that predicts functional decline in older adults (Arai & Satake, 2015). It consists of 25 yes/no items covering activities of daily living, locomotor function, nutritional status, oral health, social withdrawal, cognitive function, and depressive symptoms. Scores range from 0 to 25, with higher scores indicating greater functional impairment.
Statistical Analysis
To clarify the association between the frequency of participation in leisure activities and the residential environment, a multiple linear regression analysis (forced entry method) was conducted, with the total LASCO score as the dependent variable, residential environment factors as independent variables, and other covariates as adjustment variables. Multicollinearity was assessed using the variance inflation factor (VIF), with a threshold of VIF < 2.0.
Additionally, to examine the relationship between participation in leisure activities and the residential environment, a multiple linear regression analysis (forced entry method) was performed using the total number of activities, scored as “2 = sometimes” or “3 = frequently”, on the 11 LASCO items as the dependent variable. The number of activities was operationally defined as the total count of LASCO items with scores of “2 = sometimes” or higher, with a maximum of 11 items.
Furthermore, to investigate the influence of the residential environment on the frequency of participation in each LASCO activity, ordinal logistic regression analyses (forced entry method) were conducted using the original four response categories for each LASCO item. To address multiple comparisons across the 11 LASCO items, the false discovery rate (FDR) method was applied. Residential environment factors were included as independent variables, and other covariates were entered as adjustment variables. Adjustment variables included age groups (65–74, 75–84, ≥ 85 years), sex (male, female), region (Minamisoma City, Kagamiishi Town, Fukushima City), subjective health status (healthy, unhealthy), presence of medical conditions (present, absent), pain status (present, absent), social isolation (socially isolated, not socially isolated), and the basic checklist score (treated as a continuous variable). Psychological distress (K6) was assessed as a participant characteristic; however, it was not included in the regression models because of its conceptual overlap with the basic checklist score. All statistical analyses were performed using SPSS Statistics 28 for Windows (IBM, Armonk, NY, USA). The level of statistical significance was set at p < 0.05.
Results
Participant Characteristics
Table 1 presents the basic characteristics, residential environment, and LASCO scores of the 324 participants (82 males and 242 females; mean age: 75.5 ± 5.2 years). Regarding overall trends in the residential environment, the majority of participants lived in detached houses, lived with family members (i.e., not living alone), and regularly drove private cars. In terms of neighborhood conditions assessed by the IPAQ-E, higher proportions were observed for “Residential density (detached houses)” and “Traffic safety”, whereas the proportions for “Presence of bike lanes” and “Access to recreational facilities” were relatively low. The mean total LASCO score was 18.3 ± 5.1, and the average number of activities participated in was 6.5 ± 2.0.
Table 1.
Characteristics of the Participants
| No. of participants | 324 |
|---|---|
| Age, years, n (%) | |
| 65–74 | 127 (39.2) |
| 75–84 | 178 (54.9) |
| ≥ 85 | 19 (5.9) |
| Mean age (mean ± SD) | 75.5 ± 5.2 |
| Sex, n (%) | |
| Female | 242 (74.7) |
| Region, n (%) | |
| Minamisoma City | 113 (34.9) |
| Kagamiishi Town | 133 (41.0) |
| Fukushima City | 78 (24.1) |
| Subjective health status, n (%) | |
| Unhealthy | 34 (10.5) |
| Medical conditions, n (%) | |
| Medical condition present | 265 (81.8) |
| Chronic pain, n (%) | |
| Presence of pain | 193 (59.6) |
| Psychological distress (K6), n (%) | |
| Moderate and severe | 55 (17.0) |
| Social isolation (LSNS-6), n (%) | |
| Social isolation | 70 (21.6) |
| Basic checklist (mean ± SD) | 4.7 ± 3.4 |
| Housing type, n (%) | |
| Detached houses | 302 (93.2) |
| Family composition, n (%) | |
| Living alone | 80 (24.7) |
| Modes of transportation, n (%) (multiple responses) | |
| Driving a private car | 269 (83.3) |
| Public transportation use | 66 (20.4) |
| IPAQ-E (somewhat true/very true), n (%) | |
| Residential density (detached houses) | 241 (74.4) |
| Access to shops | 171 (52.8) |
| Access to public transport | 216 (66.7) |
| Presence of sidewalks | 213 (66.7) |
| Presence of bike lanes | 111 (34.3) |
| Access to recreational facilities | 159 (49.1) |
| Crime safety (strongly disagree/somewhat disagree) | 211 (65.1) |
| Traffic safety (strongly disagree/somewhat disagree) | 235 (72.5) |
| Social environment | 194 (59.9) |
| Aesthetics | 165 (50.9) |
| Household motor vehicles (mean ± SD) | 2.1 ± 1.6 |
| LASCO | |
| Total score (mean ± SD) | 18.3 ± 5.1 |
| Number of activities (mean ± SD) | 6.5 ± 2.0 |
| LASCO (2 = sometimes/3 = often), n (%) | |
| Technology Use | 238 (73.5) |
| Social-Public | 226 (69.8) |
| Social-Private | 265 (81.8) |
| Physical | 268 (82.7) |
| Developmental | 248 (76.5) |
| Cultural | 95 (29.3) |
| Travel | 215 (66.4) |
| Creative | 62 (19.1) |
| Raising Plants | 281 (86.7) |
| Intellectual Games | 172 (53.1) |
| Competitive Games | 36 (11.1) |
SD, standard deviation; K6, Kessler 6-item Psychological Distress Scale; LSNS-6, Lubben social network scale-6; IPAQ-E, International Physical Activity Questionnaire-Environmental Module; LASCO, Leisure Activity Scale for Contemporary Older adults.
Association Between the Frequency and Number of Leisure Activities and the Residential Environment
The results of the multiple linear regression analysis with the total LASCO score as the dependent variable are presented in Table 2. The total LASCO score was significantly associated with living in a detached house (β = 0.11, p = 0.05), driving a private car as a mode of transportation (β = 0.14, p = 0.01), and access to public transport as measured by the IPAQ-E (β = 0.13, p = 0.02). Next, the results of the multiple linear regression analysis examining the number of activities answered as “2 = sometimes” or “3 = frequently” on the LASCO are shown in Table 3. The number of such activities was significantly associated with living in a detached house (β = 0.12, p = 0.04), driving a private car (β = 0.12, p = 0.03), and having access to public transport (β = 0.12, p = 0.03).
Table 2.
Association Between LASCO Total Scores and the Residential Environment: Multiple Regression Analysis (N = 324)
| Variable | β | t | p | 95% CI |
|---|---|---|---|---|
| Housing type | ||||
| Detached houses | 0.11 | 2.00 | 0.05 | 0.01 to 4.42 |
| Family composition | ||||
| Living alone | –0.08 | –1.54 | 0.13 | –2.17 to 0.27 |
| Modes of transportation | ||||
| Private car driving | 0.14 | 2.46 | 0.01 | 0.38 to 3.39 |
| Public transportation use | 0.07 | 1.16 | 0.25 | –0.60 to 2.35 |
| IPAQ-E | ||||
| Residential density (detached houses) | –0.05 | –1.04 | 0.30 | –1.83 to 0.56 |
| Access to shops | 0.03 | 0.58 | 0.56 | –0.74 to 1.36 |
| Access to public transport | 0.13 | 2.34 | 0.02 | 0.23 to 2.68 |
| Presence of sidewalks | –0.02 | –0.47 | 0.64 | –1.34 to 0.82 |
| Presence of bike lanes | –0.04 | –0.71 | 0.48 | –1.49 to 0.70 |
| Access to recreational facilities | 0.08 | 1.50 | 0.13 | –0.24 to 1.81 |
| Crime safety | 0.01 | 0.18 | 0.86 | –0.98 to 1.18 |
| Traffic safety | 0.00 | 0.03 | 1.00 | –1.12 to 1.16 |
| Social environment | 0.07 | 1.44 | 0.15 | –0.28 to 1.81 |
| Aesthetics | 0.07 | 1.37 | 0.17 | –0.31 to 1.75 |
| Household motor vehicles | 0.00 | 0.06 | 0.95 | –0.33 to 0.35 |
CI, confidence interval; LASCO, Leisure Activity Scale for Contemporary Older adults; IPAQ-E, International Physical Activity Questionnaire-Environmental Module.
Covariates: Age (65–74, 75–84, or ≥ 85 years), Sex (man or woman), Region (Minamisoma City, Kagamiishi Town, or Fukushima City), Subjective health status (healthy or not healthy), Medical conditions (yes or no), Chronic pain (yes or no), Basic checklist score (continuous variable), Social isolation (no social isolation or social isolation).
Table 3.
Association Between the Number of LASCO Activities and the Residential Environment: Multiple Regression Analysis (N = 324)
| Variable | β | t | p | 95% CI |
|---|---|---|---|---|
| Housing type | ||||
| Detached houses | 0.12 | 2.11 | 0.04 | 0.06 to 1.82 |
| Family composition | ||||
| Living alone | –0.09 | –1.63 | 0.10 | –0.89 to 0.08 |
| Modes of transportation | ||||
| Private car driving | 0.12 | 2.14 | 0.03 | 0.05 to 1.26 |
| Public transportation use | 0.08 | 1.33 | 0.19 | –0.19 to 0.99 |
| IPAQ-E | ||||
| Residential density (detached houses) | –0.03 | –0.53 | 0.60 | –0.61 to 0.35 |
| Access to shops | 0.06 | 1.04 | 0.30 | –0.20 to 0.64 |
| Access to public transport | 0.12 | 2.13 | 0.03 | 0.04 to 1.02 |
| Presence of sidewalks | –0.04 | –0.80 | 0.43 | –0.61 to 0.26 |
| Presence of bike lanes | –0.01 | –0.09 | 0.93 | –0.46 to 0.42 |
| Access to recreational facilities | 0.07 | 1.27 | 0.20 | –0.14 to 0.68 |
| Crime safety | –0.02 | –0.32 | 0.75 | –0.50 to 0.36 |
| Traffic safety | 0.01 | –0.12 | 0.90 | –0.49 to 0.43 |
| Social environment | 0.08 | 1.52 | 0.13 | –0.10 to 0.74 |
| Aesthetics | 0.02 | 0.40 | 0.70 | –0.33 to 0.50 |
| Household motor vehicles | –0.02 | –0.43 | 0.67 | –0.16 to 0.11 |
The number of LASCO activities refers to the number of activity items on the LASCO for which participants responded “2 = sometimes” or “3 = frequently.”
CI, confidence interval; LASCO, Leisure Activity Scale for Contemporary Older adults; IPAQ-E, International Physical Activity Questionnaire-Environmental Module.
Covariates: Age (65–74, 75–84, or ≥ 85 years), Sex (man or woman), Region (Minamisoma City, Kagamiishi Town, or Fukushima City), Subjective health status (healthy or not healthy), Medical conditions (yes or no), Chronic pain (yes or no), Basic checklist score (continuous variable), Social isolation (no social isolation or social isolation).
Associations Between the Frequency of Participation in Individual Leisure Activities and the Residential Environment
The results of the ordinal logistic regression analyses examining the associations between the frequency of participation in each LASCO leisure activity and the residential environmental factors after applying the FDR correction for multiple comparisons are presented below. Detailed ordinal logistic regression results, including odds ratios (ORs), 95% confidence intervals (CIs), and FDR-adjusted p-values for all LASCO activities, are provided in (Supplemental Materials 1 and 2). For (4) Physical, a significant association was found with access to public transport (odds ratio [OR] = 0.43, 95% confidence interval [CI]: 0.25–0.71). For (5) Developmental, a significant association was found with access to recreational facilities (OR = 0.49, 95% CI: 0.32–0.76). For (9) Raising Plants, significant associations were found with living in a detached house (OR = 0.08, 95% CI: 0.03–0.20), living alone (OR = 2.16, 95% CI: 1.29–3.63), driving a private car (OR = 0.35, 95% CI: 0.18–0.66), and residential density (OR = 0.52, 95% CI: 0.31–0.86).
Discussion
The present study surveyed 324 community-dwelling older adults in Fukushima Prefecture using a self-administered questionnaire regarding the frequency of participation in leisure activities, number of activities participated in, and the residential environment. The results showed that 93.2% of the participants lived in a detached house, while 24.7% lived alone. A high proportion reported driving a private car (83.3%), exceeding the national rate of licensed drivers aged ≥ 60 years in Japan (56.6%) (Cabinet Office, 2025). Furthermore, the mean total LASCO score was 18.3 ± 5.1, which is higher than the average score of 14.4 ± 7.1 reported by Iwasa et al. (2019). These findings suggest that the study participants were more likely to live in detached housing and to engage more frequently in leisure activities. In addition, the study area can be characterized as having a car-dependent transportation environment.
Association Between Leisure Activities and Housing Type
The results of the present study indicated that living in a detached house was associated with both the leisure activity frequency and the number of activities among older adults. In the item-specific analyses, living in a detached house was also significantly associated with raising plants. Previous studies have also reported that older adults living in detached houses are less sedentary and engage more frequently in activities such as sports and household chores, and especially outdoor activities involving gardens (Behe, 2006; McKee et al., 2015; Saidj et al., 2015). The results of the present study are consistent with these findings.
Association Between Leisure Activities and Usual Modes of Transportation
The results of the present study also suggest that driving a private car and having good access to public transport are associated with leisure activity frequency and the number of activities among older adults. Previous studies have similarly reported that older adults with independent mobility, including drivers and public transportation users, participate in leisure activities more frequently, and that private car use is an important factor supporting activity participation among those with physical limitations (Dahan-Oliel et al., 2010; Galenkamp et al., 2016; Siren & Hakamies-Blomqvist, 2009; Tsunoda et al., 2011). Furthermore, decreased physical function and driving cessation are known to reduce opportunities for social participation among older adults, while insufficient transportation alternatives may reduce outing frequency and negatively affect health and well-being (Latham-Mintus et al., 2022; Siren & Hakamies-Blomqvist, 2009). The present findings support these previous studies and suggest that access to both private and public transportation options may be associated with leisure activity participation among community-dwelling older adults. As the aging of the population progresses, the development of transportation systems and urban environments that address diverse mobility needs will become increasingly important.
Association Between Leisure Activities, Family Composition, and Social Environments
The findings of the present study also suggest that living with others (i.e., not living alone), and having good access to recreational facilities are associated with leisure activity frequency and the number of activities among older adults. A previous study similarly reported that older adults living alone tend to have fewer opportunities for activities because of limited family support and weaker social networks, resulting in lower participation in leisure activities (Dang et al., 2024). In addition, spousal physical activity has been shown to influence individuals’ own activity levels, indicating the importance of family composition (Satariano et al., 2002). Moreover, access to recreational facilities and supportive social environments has been identified as a key factor promoting physical activity and out-of-home participation, as social interactions and observational learning from peers can enhance motivation and self-efficacy (Giles-Corti & Donovan, 2002; Kim et al., 2021; Resnick et al., 2002; Van et al., 2016). These findings suggest that, in addition to household composition, social environmental factors may play an important role in leisure activity participation among older adults, which highlights the potential value of developing community environments that foster social interaction and intrinsic motivation.
Limitations
Several limitations of the present study should be noted. First, the participants were recruited from only three regions in Fukushima Prefecture, which may limit generalizability. In addition, because this study was conducted in Fukushima Prefecture, some participants may have experienced evacuation or residential relocation related to the 2011 Great East Japan Earthquake and Fukushima Daiichi Nuclear Power Plant accident. As no information regarding these experiences was collected, their potential influence could not be examined. Therefore, caution is warranted when generalizing the findings to other populations. Second, this study employed a cross-sectional design, which restricts the ability to examine long-term effects and potential bidirectional relationships between variables. Therefore, longitudinal studies are needed to investigate these aspects. Third, although ordinal logistic regression analyses and FDR correction were used for the item-specific LASCO analyses, the number of participants in some response categories may have been relatively small, and the stability of the estimates may be limited. Fourth, this study relied on self-reported questionnaires, which may be subject to recall bias and social desirability bias. To obtain a more comprehensive and precise understanding of the relationship between leisure activities and the residential environment, combining subjective measures with objective assessments is recommended. Future research should build on these findings by conducting comparative studies across regions with differing characteristics, employing longitudinal and multifaceted data, and collecting information on disaster-related experiences, evacuation history, and residential relocation to clarify further their influence on leisure activity participation among older adults.
Conclusion
This study examined the associations between the frequency and number of leisure activities and the residential environment among community-dwelling older adults in Fukushima Prefecture. The results indicated that mobility-related factors—such as residing in a detached house, driving a private car, and access to public transport—as well as social connection factors—including not living alone and access to recreational facilities—were associated with the frequency of participation in leisure activities. Access to transportation may be related to opportunities for out-of-home activities, whereas social and environmental factors, including family composition and community resources, may be associated with motivation and self-efficacy for participation. Although the cross-sectional design does not allow causal inferences or determination of the direction of these associations, the present findings suggest that residential environmental factors may be related to participation in leisure activities among older adults. Furthermore, this study provides evidence from a region characterized by a high prevalence of private car use and detached housing, offering a multifaceted perspective on the relationship between leisure activity participation and the residential environment. Future studies using longitudinal and multi-regional designs are needed to clarify these relationships further and examine potential causal pathways.
Supplemental Material
Supplemental Material for Association Between Leisure Activity Frequency, Number of Activities, and the Residential Environment Among Community-Dwelling Older Japanese Adults: A Questionnaire Survey in Fukushima Prefecture by Natsumi Kimura, Masataka Ando, Toshimasa Sone, Akihiko Asao, Maki Ogasawara, Masayuki Hoshi, Tatsuya Nakanowatari, Toshimi Sato, Yuko Horikoshi, Rie Sakuraba-Hirata, Yoshitaka Shiba in Sage Open Aging
Acknowledgments
The authors would like to express their sincere gratitude to Fukushima Medical University, Minamisoma General Hospital, the Department of Longevity Welfare in the Minamisoma City Health and Welfare Division, the Health and Environment Division of Kagamiishi town, and the Active Senior Center Aouze in Fukushima city for their cooperation with the data collection.
Author Contributions: NK, MA, TS, and YS were responsible for the conceptualization and design of this study. NK, TS, AA, MO, MH, TN, TS, YS, YH, and RS-H conducted the data collection. NK and TS contributed to the statistical analysis. NK, MA, TS, and YS contributed to the interpretation of the results, drafted the manuscript, and critically revised the manuscript for important intellectual content. All authors have read and approved the final manuscript.
Funding: The authors received no financial support for the research, authorship, and/or publication of this article.
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Supplemental Material: Supplemental material for this article is available online.
ORCID iDs
Natsumi Kimura https://orcid.org/0009-0003-3809-1980
Masataka Ando https://orcid.org/0000-0003-3706-8183
Maki Ogasawara https://orcid.org/0000-0002-7018-2538
Ethical Considerations
This study was approved by the Ethics Committee of Fukushima Medical University (approval No.: General 2022-123).
Consent to Participate
In accordance with ethical guidelines, explanations regarding the protection of personal information and research consent were provided both verbally and in writing.
Data Availability Statement
The data analyzed in this study are not publicly available.*
References
- Alexander A., Bergman P., Hagströmer M., Sjöström M. (2006). IPAQ environmental module: Reliability testing. Journal of Public Health, 14(2), 76–80. 10.1007/s10389-005-0016-2 [DOI] [Google Scholar]
- Arai H., Satake S. (2015). English translation of the Kihon Checklist. Geriatrics & Gerontology International, 15(4), 518–519. 10.1111/ggi.12397 [DOI] [PubMed] [Google Scholar]
- Behe B. K. (2006). Comparison of gardening activities and purchases of homeowners and renters. Journal of Environmental Horticulture, 24(4), 217–220. 10.24266/0738-2898-24.4.217 [DOI] [Google Scholar]
- Cabinet Office . (2025). Section 3: Special feature: Awareness of housing and living environments for the elderly (3) Situation regarding going out and driving. https://www8.cao.go.jp/kourei/whitepaper/w-2019/html/zenbun/s1_3_1_3.html
- Cerin E., Nathan A., Van Cauwenberg J., Barnett D. W., Barnett A., CEPA-Older Adults Working Group . (2017). The neighbourhood physical environment and active travel in older adults: A systematic review and meta-analysis. International Journal of Behavioral Nutrition and Physical Activity, 14(1), 15. 10.1186/s12966-017-0471-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chao S. F. (2016). Changes in leisure activities and dimensions of depressive symptoms in later life: A 12-year follow-up. The Gerontologist, 56(3), 397–407. 10.1093/geront/gnu052 [DOI] [PubMed] [Google Scholar]
- Dahan-Oliel N., Mazer B., Gélinas I., Dobbs B., Lefebvre H. (2010). Transportation use in community-dwelling older adults: Association with participation and leisure activities. Canadian Journal on Aging, 29(4), 491–502. 10.1017/S0714980810000516 [DOI] [PubMed] [Google Scholar]
- Dang M., Chen Y., Ji J. S., Zhang Y., Chen C., Zhang Z. (2024). The association between household and family composition and mental health of the elderly: Mediating role of lifestyle. BMC Public Health, 24(1), 2055. 10.1186/s12889-024-19516-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Furukawa T. A., Kawakami N., Saitoh M., Ono Y., Nakane Y., Nakamura Y., Tachimori H., Iwata N., Uda H., Nakane H., Watanabe M., Naganuma Y., Hata Y., Kobayashi M., Miyake Y., Takeshima T., Kikkawa T. (2008). The performance of the Japanese version of the K6 and K10 in the World Mental Health Survey Japan. International Journal of Methods in Psychiatric Research, 17(3), 152–158. 10.1002/mpr.257 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Galenkamp H., Gagliardi C., Principi A., Golinowska S., Moreira A., Schmidt E. A., Winkelmann J., Sowa A., Pas V.S., Deeg J. D. (2016). Predictors of social leisure activities in older Europeans with and without multimorbidity. European Journal of Ageing, 13(2), 129–143. 10.1007/s10433-016-0375-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Giles-Corti B., Donovan R. J. (2002). The relative influence of individual, social and physical environment determinants of physical activity. Social Science & Medicine, 54(12), 1793–1812. 10.2105/ajph.93.9.1583 [DOI] [PubMed] [Google Scholar]
- Inoue S., Murase N., Shimomitsu T., Ohya Y., Odagiri Y., Takamiya T., Ishii K., Katsumura T., Sallis J. F. (2009). Association of physical activity and neighborhood environment among Japanese adults. Preventive Medicine, 48(4), 321–325. 10.1016/j.ypmed.2009.01.014 [DOI] [PubMed] [Google Scholar]
- Iwasa H., Yoshida Y., Ishioka Y., Suzukamo Y. (2019). Development of a leisure activity scale for contemporary older adults: Examination of its association with cognitive function. Nihon Koshu Eisei Zasshi, 66(10), 617–628. 10.11236/jph.66.10_617 [DOI] [PubMed] [Google Scholar]
- Kim J., Eys M., Robertson-Wilson J. (2021). “If they do it, so can I”: A test of descriptive norms, self-efficacy, and perceived similarity for predicting physical activity. Psychology & Health, 36(6), 701–718. 10.1080/08870446.2020.1789641 [DOI] [PubMed] [Google Scholar]
- Kurimoto A., Awata S., Ohkubo T., Tsubota-Utsugi M., Asayama K., Takahashi K., Suenaga K., Satoh H., Imai U. (2011). Reliability and validity of the Japanese version of the abbreviated Lubben Social Network Scale. Nihon Ronen Igaku Zasshi, 48(2), 149–157. 10.3143/geriatrics.48.149 [DOI] [PubMed] [Google Scholar]
- Latham-Mintus K., Manierre M., Miller K. (2022). Staying connected: Alternative transportation use, neighborhoods, and social participation among older Americans. The Gerontologist, 62(1), 75–88. 10.1093/geront/gnab084 [DOI] [PubMed] [Google Scholar]
- Lubben J., Blozik E., Gillmann G., Illiffe S., Kruse R. W., Beck C. J., Stuck E. A. (2006). Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations. The Gerontologist, 46(4), 503–513. 10.1093/geront/46.4.503 [DOI] [PubMed] [Google Scholar]
- Mak W. H., Noguchi T., Bone J. K., Wels J., Gao Q., Kando K., Saito T., Fancourt D. (2023). Hobby engagement and mental wellbeing among people aged 65 years and older in 16 countries. Nature Medicine, 29(9), 2233–2240. 10.1038/s41591-023-02506-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- McKee G., Kearney P. M., Kenny R. A. (2015). The factors associated with self-reported physical activity in older adults living in the community. Age and Ageing, 44(4), 586–592. 10.1093/ageing/afv042 [DOI] [PubMed] [Google Scholar]
- Mimura Y. (2021). Activities and living environment of older adults: Toward improving life satisfaction and optimizing the use of medical services. Studies on Community Development for Welfare, 23, 1–13. [Google Scholar]
- Prochaska J. J., Sung H. Y., Max W., Shi Y., Ong M. (2012). Validity study of the K6 scale as a measure of moderate mental distress based on mental health treatment need and utilization. International Journal of Methods in Psychiatric Research, 21(2), 88–97. 10.1002/mpr.1349 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Resnick B., Orwig D., Magaziner J., Wynne C. (2002). The effect of social support on exercise behavior in older adults. Clinical Nursing Research, 11(1), 52–70. 10.1177/105477380201100105 [DOI] [PubMed] [Google Scholar]
- Rowe J. W., Kahn R. L. (1997). Successful aging. The Gerontologist, 37(4), 433–440. 10.1093/geront/37.4.433 [DOI] [PubMed] [Google Scholar]
- Saidj M., Jørgensen T., Jacobsen R. K., Linneberg A., Aadahl M. (2015). The influence of housing characteristics on leisure-time sitting. Preventive Medicine, 81, 58–62. 10.1016/j.ypmed.2015.08.001 [DOI] [PubMed] [Google Scholar]
- Satariano W. A., Haight T. J., Tager I. B. (2002). Living arrangements and participation in leisure-time physical activities in an older population. Journal of Aging and Health, 14(4), 427–451. 10.1177/089826402237177 [DOI] [PubMed] [Google Scholar]
- Siren A., Hakamies-Blomqvist L. (2009). Mobility and well-being in old age. Topics in Geriatric Rehabilitation, 25(1), 3–11. 10.1097/TGR.0b013e31819147bf [DOI] [Google Scholar]
- Tsunoda K., Mitsuishi Y., Tsuji T., Yoon J. Y., Muraki T., Hotta K., Okura T. (2011). Association of the physical activity of community-dwelling older adults with transportation modes, depression and social networks. Nihon Ronen Igakkai Zasshi, 48(5), 516–523. 10.3143/geriatrics.48.516 [DOI] [PubMed] [Google Scholar]
- Van C. J., Nathan A., Barnett A., Barnett D. W., Cerin E., CEPA-Older Adults Working Group . (2018). Relationships between neighbourhood physical environmental attributes and older adults’ leisure-time physical activity: A systematic review and meta-analysis. Sports Medicine, 48(7), 1635–1660. 10.1007/s40279-018-0917-1 [DOI] [PubMed] [Google Scholar]
- Van H. V., Van C. J., De B. I., Van D. D., Deforche B., Van Dyck D. (2016). Interactions between neighborhood social environment and walkability to explain Belgian older adults’ physical activity and sedentary time. International Journal of Environmental Research and Public Health, 13(6), 569. 10.3390/ijerph13060569 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Verghese J., LeValley A., Derby C., Kuslansky G., Katz M., Hall C., Buschke H., Lipton D. (2006). Leisure activities and the risk of amnestic mild cognitive impairment in the elderly. Neurology, 66(6), 821–827. 10.1212/01.wnl.0000202520.68987.48 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Vogelsang E. M. (2016). Older adult social participation and its relationship with health: Rural-urban differences. Health & Place, 42, 111–119. 10.1016/j.healthplace.2016.09.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- World Health Organization . (2012). Good health adds life to years: Global brief for World Health Day 2012. https://www.who.int/publications/i/item/WHO-DCO-WHD-2012.2
- Zhang W., Feng Q., Lacanienta J., Zhen Z. (2017). Leisure participation and subjective well-being: Exploring gender differences among elderly in Shanghai, China. Archives of Gerontology and Geriatrics, 69, 45–54. 10.1016/j.archger.2016.11.010 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplemental Material for Association Between Leisure Activity Frequency, Number of Activities, and the Residential Environment Among Community-Dwelling Older Japanese Adults: A Questionnaire Survey in Fukushima Prefecture by Natsumi Kimura, Masataka Ando, Toshimasa Sone, Akihiko Asao, Maki Ogasawara, Masayuki Hoshi, Tatsuya Nakanowatari, Toshimi Sato, Yuko Horikoshi, Rie Sakuraba-Hirata, Yoshitaka Shiba in Sage Open Aging
Data Availability Statement
The data analyzed in this study are not publicly available.*