Search Results (7)

Ikigai—a Japanese concept that includes elements such as life’s purpose and meaning—has been reported to be associated with various systemic health conditions, such as the risk of developing physical dysfunction or death in older adults. However, there are no reports that comprehensively examine the psychological and social aspects of Ikigai. We attempted to clarify the characteristics of Ikigai by examining it from a biopsychosocial model using physical, psychological, and social perspectives through a cross-sectional study on sarcopenia, frailty and healthy life expectancy in a hilly and mountainous area of Japan. Koyadaira in Mima City, which is located in a hilly and mountainous region on Shikoku Island in Japan, was targeted. This cross-sectional study included 105 outpatients aged 65 and over, with an average age of 79.02 ± 6.91 years. Ikigai (self-rating score on a scale of 0 (no Ikigai) to 5 (the highest Ikigai)) participants’ level of physical activity (the Physical Activity Scale for the Elderly, PASE), degree of depression (the Geriatric Depression-15 Scale, GDS-15), cognitive function (the Mini-Mental State Examination, MMSE) and social isolation (the abbreviated Lubben Social Network Scale, LSNS-6) was assessed. Significant positive correlations were found between PASE and MMSE. The LSNS-6 significantly correlated with the MMSE and GDS-15. In a path model, out of four paths from PASE, GDS-15, MMSE, and LSNS-6 to Ikigai, the path from the GDS-15 alone was significant (correlation coefficient −0.271, p < 0.01). The adaptability of this model was good. This study indicates that depressive status has a large impact on Ikigai, along with physical, cognitive, and social conditions; thus, it is appropriate to consider that an affective psychological status, such as depressive symptoms, is a fundamental condition for having Ikigai. Full article

Background: The rapidly aging global population has increased the demand for caregivers. Many caregivers simultaneously engage in paid employment, and the dual role makes the needs of caregiver employees conceivably more remarkable. However, there is a gap in the literature about the specific needs of caregiver employees. Method: Caregiver employees (n = 1205) across Hong Kong caring for those ≥65 years were recruited for a cross-sectional face-to-face survey from December 2021 to January 2022, to evaluate mental well-being measured by the Short Warwick –Edinburgh Mental Well-being Scale. Univariate and multivariate analyses were conducted; significant variables (p < 0.05) were included in multiple linear regression, along with caregiver-friendly workplace policies’ availability, to understand their association with their mental well-being. Findings: The mean score of the Short Warwick–Edinburgh Mental Well-being Scale among caregiver employees in this study was 24.9, with 7.2% indicative of probable clinical depression and 10.0% possible mild depression. In addition, the current study showed that 30.2% of the caregiver employees felt distressed about the caregiving role. Among external factors, family support (measured by the Lubben Social Network Scale) and workplace culture (measured by the Marshall Supervision Subscale) positively correlated with mental well-being with regression coefficients of 0.252 (p < 0.001) and 0.482 (p < 0.001), respectively. In the fully adjusted model, a negative regression coefficient was observed for overall spillover (−0.050, p < 0.001) and Short Warwick–Edinburgh Mental Well-being Scale scores, while positive regression coefficients were observed for overall self-rate (0.041, p < 0.001), Lubben (0.124, p < 0.001), and corporate culture (0.365, p < 0.001). Better Short Warwick–Edinburgh Mental Well-being Scale scores were observed when caregiver-friendly workplace policies were clearly stated than when they were made on a case-by-case discretionary basis. Conclusions: Caregiver-friendly workplace policies may be critical to Hong Kong’s sustainable future, both economically and socially, as they ensure a healthy and productive workforce to support an aging population. Full article

Objectives: Social isolation is recognised as a risk factor in the inflammatory process. This study explored the association between social isolation and the Dietary Inflammatory Index (DII) in community-dwelling older persons. Methods: This cross-sectional pilot study recruited 107 community-dwelling people aged over 55 years living in the Australian Capital Territory. Participants completed an extensive food frequency questionnaire and provided anthropometric and sociodemographic data. Social isolation was evaluated using the Lubben Social Network Scale (LSNS). Diet quality was assessed using DII. Results: Average age was 70.1 (±8.61) years and 62.8% were female. The average DII score was −1.10 (±1.21), indicating an anti-inflammatory diet. Higher LSNS was associated with lower DII (b (95% CI) = −0.041 (−0.066, −0.17); p < 0.01) and was positively influenced by the number of people in household (b (95% CI) = 5.731 (2.336, 9.127); p = 0.001). Conclusion: Increased risk of social isolation was associated with an increased tendency towards a more inflammatory diet. Reducing social isolation may decrease the inflammatory component of dietary intake for older persons living independently in the community. Full article

To develop effective dementia prevention strategies, it is necessary to understand risk factors, associated factors and early signs of dementia. Subjective cognitive decline (SCD) is the earliest form of dementia. The aim of this study is to assess depression as a factor that is significantly associated with SCD. The data of 1030 general practitioner patients from the AgeWell.de-study (60–77 years; CAIDE dementia risk score ≥ 9) were analysed. A descriptive analysis was conducted using validated instruments like the Geriatric depression scale (GDS), Lubben social network scale (LSNS-6) and education classes according to CASMIN (Comparative Analysis of Social Mobility in Industrial Nations). A multivariate regression model with the dependent variable SCD was calculated. Of the 1030 participants, 5.9% had depressive symptoms and 31.3% SCD. The group with depressive symptoms showed significantly higher body-mass-index (p = 0.005), lower education class (p = 0.022), lower LSNS-6 score (p < 0.001), higher sports activity (p < 0.001), and more sleeping problems (p = 0.026). In the regression model a higher GDS-score [Odds ratio (OR): 1.219 (p < 0.001)], more sleeping problems [OR: 1.550 (p = 0.017)] and higher education class [middle/high: OR: 1.474/1.875 (p = 0.037/0.004)] were significantly associated with SCD. This study identified depressive symptoms, sleeping problems, and higher education classes as factors associated with SCD, which can represent an early form of dementia. Full article

(1) Background: Social isolation and loneliness are determinants of healthy longevity. However, previous research has focused on either social isolation or loneliness and has not considered household types. This study sought to clarify loneliness and social isolation among older adults using single-person (ST) or multi-person (MT) household types. (2) Methods: We administered a national, anonymous, self-administered survey to 5351 Japanese older adults aged 65 years or older. The survey included subjects’ demographic characteristics and scores for loneliness (University of California Los Angeles (UCLA) Loneliness Scale version 3 (Cronbach’s α = 0.790)), social isolation (Lubben Social Network Scale (LSNS-6) (Cronbach’s α = 0.82)), and self-efficacy (GSES). (3) Results: After adjusting for age and gender, ST individuals had significantly lower LSNS-6 and significantly higher UCLA scores than MT individuals (p < 0.001). Lower LSNS-6 and higher UCLA scores were significantly associated with lower GSES scores, and the effect of GSES was greater for ST than for MT (LSNS-6, ST (β = 0.358, p < 0.001); MT (β = 0.295, p < 0.001)) (UCLA, ST (β = −0.476, p < 0.001); MT (β = −0.381, p < 0.001)). (4) Conclusions: Specific healthcare systems and programs based on self-efficacy should be developed by household type to reduce both social isolation and loneliness. Full article

Loneliness and social isolation are subjective measures associated with the feeling of discomfort and distress. Various factors associated with the feeling of loneliness or social isolation are: the built environment, long-term illnesses, the presence of disabilities or health problems, etc. One of the most important aspect which could impact feelings of loneliness is mobility. In this paper, we present a machine-learning based approach to classify the user loneliness levels using their indoor and outdoor mobility patterns. User mobility data has been collected based on indoor and outdoor sensors carried on by volunteers frequenting an elderly nursing house in Tampere region, Finland. The data was collected using Pozyx sensor for indoor data and Pico minifinder sensor for outdoor data. Mobility patterns such as the distance traveled indoors and outdoors, indoor and outdoor estimated speed, and frequently visited clusters were the most relevant features for classifying the user’s perceived loneliness levels.Three types of data used for classification task were indoor data, outdoor data and combined indoor-outdoor data. Indoor data consisted of indoor mobility data and statistical features from accelerometer data, outdoor data consisted of outdoor mobility data and other parameters such as speed recorded from sensors and course of a person whereas combined indoor-outdoor data had common mobility features from both indoor and outdoor data. We found that the machine-learning model based on XGBoost algorithm achieved the highest performance with accuracy between $90\%$ and $98\%$ for indoor, outdoor, and combined indoor-outdoor data. We also found that Lubben-scale based labelling of perceived loneliness works better for both indoor and outdoor data, whereas UCLA scale-based labelling works better with combined indoor-outdoor data. Full article

The aim of this study was to investigate the characteristics of social health and its association with resilience among older adults living alone excluded from the public care service due to their relatively good health. For this cross-sectional study, we surveyed older adults aged between 65 and 80 years using questionnaires to measure the social health status and levels of resilience of the participants. We conducted a hierarchical regression analysis to confirm the association between resilience and social network. Finally, data from 266 community-dwelling older adults were analyzed. We discovered that participants had social networks with a mean score on the Lubben Social Network Scale 18.13 ± 7.98, which means they were socially isolated. The network size (standardized β = −0.149, p < 0.05) and contact frequency (standardized β = 0.136, p < 0.05) correlated positively with higher levels of resilience. A hierarchical model accounted for 48.0% of the variance in resilience. The results suggested that interventions by the public health service to protect social health are needed for older adults living alone even when they are physically, emotionally, and cognitively healthy. In addition, smaller network size and higher frequency of contacts may be considered to strengthen resilience, which is a protective factor in social health. Full article