Social isolation in older adults is a major public health problem and associated with increased morbidity and mortality. There are limited data on the association between social isolation and physical function including gait speed. Hence, this study is to determine the prevalence of social isolation and its association with gait speed, frailty, cognition, depression and comorbidities amongst community-dwelling older adults.
Social isolation, depression, frailty and perceived general health were assessed using 6-item Lubben Social Network Scale (LSNS-6), Geriatric Depression Scale (GDS), FRAIL scale and EuroQol EQ-5D-5L questionnaire which includes EQ Visual Analogue Scale (EQ-VAS), respectively. Cognition was assessed using the Chinese Mini Mental State Examination (cMMSE), while physical performance test included gait speed and short physical performance battery test. Binary logistic regression was performed to determine the influence of socio-demographic, medical, functional and cognitive variables on social isolation.
Out of 202 participants, 27.7% were robust, 66.8% of participants were pre-frail, and 5.4% of participants were frail. Almost half (45.5%, n = 92) of the participants were found to be at risk of social isolation. A poor social network was negatively associated with mean gait speed (OR = 0.674, CI 0.464–0.979, p = 0.039), EQ-VAS (OR = 0.561, CI 0.390–0.806, p < 0.01) and cMMSE (OR = 0.630, 95% CI 0.413–0.960, p = 0.032).
Almost half of older adults in the community are at risk of social isolation with a very significant association with gait speed, cMMSE and EQ-VAS scores.
The world’s population is ageing especially in Asia where the number of persons aged 60 years and older is growing faster than all younger age group . Older adults aged 65 years and above in Singapore accounts for 13.7% of the total population, and will double by 2030 . Singapore is ranked third in global life expectancy ranking . Communities that facilitate healthy ageing in place are increasingly relevant in meeting these needs, especially with a growing trend of older adults preferring to live in their own homes and communities, even if this means living alone [4, 5].
In addition to being healthy and enabling an individual to age in place, strong social networks have a direct impact on health and well-being, with studies showing an association with increased quality of life  and a protective effect on cognition and the development of dementia . Conversely, social isolation in older adults has been shown to increase hospital readmission, disease morbidity and mortality rates [8, 9]. It has been debated that effect of social isolation on mortality is comparable to quitting smoking and exceeds many well-known risk factors such as obesity and physical inactivity . Older adults are particularly at risk for social isolation and poor social network due to retirement, mobility limitation, age related physiological changes such as vision and hearing impairments and increasing ill health. International institutions such as World Health Organization (WHO) have flagged social isolation as a key social and policy issue for ageing [11, 12]. There are numerous initiatives in place to address social isolation, and many countries are now looking into the age-friendly cities (AFC) and communities movement promoted by WHO. Such AFCs are adapted in various ways, for example, built-environment, to support the daily needs of the ageing population while promoting active ageing .
Social isolation and loneliness while related are two separate constructs. Social isolation can be defined objectively as having either reduced number of social contacts and frequency of interactions or subjectively as feeling isolated or low quality interactions. Loneliness is a state of emotion which is evaluated subjectively  and can result from perceived social isolation [15, 16]. A myriad of factors have been found to be associated with social isolation in old age; these includes low socioeconomic status , poor health status , impaired mobility [19, 20] as well as cognitive function [21, 22]. Amongst these factors, decline in gait speed has been found to be reversible by commonly used exercise interventions . While there have been an increasing number of studies looking at social isolation in older adults, there are limited data on association with physical measures including gait speed, frailty, medical comorbidities and cognition. This cross-sectional study aims to determine the prevalence of social isolation amongst community-dwelling older adults and its association with physical function including gait speed and frailty, cognition and comorbidities. Identifying such associations is of high importance for preventive measures to be implemented before other health aspects are implicated.
An observational cross-sectional study was performed of community-dwelling older adults aged 60 years and older. Recruitment of the seniors took place between August 2017 and December 2018 through network of grassroots volunteers, senior activity centres and words of peers who attended the screening program intended to identify seniors at risk, e.g. pre-frail, frail and those with cognitive impairment.
The screening consisted of an interview questionnaire and physical performance test. The interview questionnaire included questions on socio-demographics, physical activity, frailty using the FRAIL (Fatigue, Resistance, Ambulation, Illness, and Loss of Weight) scale , functional status, chronic diseases, polypharmacy and social isolation using the Lubben Social Network Scale (LSNS-6). Functional status was assessed using the Lawton IADL Scale  and perceived general health was assessed using EuroQol EQ-5D-5L questionnaire which comprises the EQ-5D-5L descriptive system and EQ Visual Analogue Scale (EQ-VAS) [26,27,28].
The 5-item FRAIL scale  has been extensively validated locally and in numerous populations across various continents and in different settings [29, 30]. The FRAIL scale is comparable in terms of function with the multidimensional deficit accumulation frailty index in predicting physical limitations and mortality . The scores range from 0 to 5, where scores of 3–5 represent frail and 1–2 pre-frail. Fear of falling (FOF) was identified by asking “Are you afraid of falling?’ . For those who replied yes, they were asked to choose between somewhat or very much afraid of falling. Depression was assessed using the Geriatric Depression Scale (GDS) and cognition was assessed using the Chinese Mini Mental State Examination (cMMSE).
The only dependent variable, risk of social isolation, was measured using the 6-item Lubben Social Network Scale (LSNS-6). LSNS-6 is a brief, validated instrument developed to measure social isolation in older adults including size, closeness and frequency of contact with friends and family members and correlates with self-perceived health and physical activity limitations . The total scale score ranges from 0 to 30 obtained by summing the six items and a score below 12 suggests at risk of social isolation. LSNS-6 has been validated in Asian populations including Malaysia, China, Japan and Korea [15, 34].
Following the interview, participants were invited to take part in several physical performance tests which were administered by trained staff. These tests were carried out in the neighbourhood community centre or senior activity centres. Physical performance screening included body mass index (BMI), 10 m gait speed with 1 m acceleration and deceleration, body mass index, Snellen test over 3 m (impairment if at least one eye was worse than 6/18) and Short Performance Physical Battery (SPPB) Test.
All statistical analyses were carried out using IBM SPSS Statistics 25.0. Descriptive statistics for numerical variables were presented as mean and standard deviations, and frequencies and percentages for categorical variables. Mann–Whitney U test (for quantitative) and chi-square test (categorical) were used to test for significant differences in demographics and health characteristics between those who are at risk of social isolation and those who are not. Principle components (PCA) were derived for these medical, functional and cognitive variables (number of chronic disease, cMMSE score, balance score, chair stand score, mean gait speed, GDS score and perceived health rating) to resolve multi-collinearity issues (which will dilute the significance of the variables) by creating uncorrelated surrogate variables to be used together with socio-demographic in the binary logistic regression to determine their influence on social isolation in three models. Statistical significance was set at p < 0.05.
Ethics approval was obtained from Domain-Specific Review Board of National Healthcare Group, Singapore. All participants provided signed consent.
A total of 202 community-dwelling older adults participated in the study. As shown in Table 1, 158 (78.2%) of the participants were female. The mean age of participants was 74.1 years. Participants reported an average of five years of education and approximately one in every five participants (18.8%) was living alone. Most of the participants in this study were pre-frail (66.8%, n = 135) or robust (27.7%, n = 56), with only 5.4% (n = 11) of participants being frail. About one in four had a lot of fear for fall (26.7%), seven in ten (67.5%, n = 131) participants had vision impairment and one in ten had at least two IADL impairment.
Almost one in two (45.5%) participants were found to be at risk of social isolation. Individual responses to LSNS-6 are shown in Annex 1. Three quarter (75.3%) of older adults hear from three or more friends a month but 47.0% (n = 95) and 46.0% (n = 93) do not have any friends they feel at ease to talk about personal matters or help them in difficulty, respectively. Significant differences between those at risk and not at risk of social isolation were only found for years of education and having at least two IADL impairment. There was a non-significantly higher prevalence of fear of falling in the older adults at risk of social isolation,
Tables 2 and 3 show factors associated with risk of social isolation. After adjusting for participants’ characteristics in Table 1 and confounding factors in Table 2, gait speed, cMMSE and EQ-VAS scores in Model 3 which had a marginal good fit with p = 0.078 (chi-sq = 12.1, df = 8) remained significantly associated with risk of social isolation. Older adults with slower gait speed were at 1.5 times risk of social isolation (adjusted OR = 0.674, CI 0.464–0.979) while those with lower EQ-VAS scores were at 1.8 times risk (adjusted OR = 0.561, CI 0.390–0.806). Those with lower cMMSE scores have 37% increased likelihood of being at risk of social isolation. For functional status, while non-significant, those at risk of social isolation had lower balance and chair stand scores.
Findings from this study suggest that nearly one in every two community-dwelling older adults (45.5%) is at risk of social isolation. The prevalence is similar to many other countries depending on the definition used ranging from 26.2 to 49.8% [15, 35, 36]. Almost half of the older adults felt they had no friends they could talk about personal matters (47.0%) with or help them in difficulty (46.0%). Older adults with declining function tend to rely more on friends, family and society for support where meaningful social contact is an important aspect of well-being and ageing well .
Data from this study indicate a strong association between social isolation and gait speed. Slow gait speed is a well-recognised predictor of poor clinical outcomes in community-dwelling older adults [38, 39]. Gait speed is also a useful diagnostic tool for sarcopenia and frailty . Older adults who are able to ambulate more easily in the community have more opportunity to engage with friends and family . A recent study published reported that social isolation was associated with a decrease in gait speed after 6 years, especially in participants from a lower social economic class . Data from the same study of 2817 older adults aged > 60 also showed that adults with loneliness were more likely to become frail over time . Although non-significant, our study did show a higher prevalence of frailty in those at risk of social isolation. While interventions to reduce social isolation and loneliness including senior clubs, befriending initiatives and psychosocial group have produced mixed results [44,45,46,47,48], a recent intervention on membership of a fitness program did show reduction in social isolation and loneliness  which further supports impact of function on social isolation. The importance of planning for appropriate physical environments and age-friendly communities in developing social networks and reducing the risk of social isolation cannot be understated .
Older adults at risk of being socially isolated had significantly poorer scores on the self-rated EQ-VAS scale of general health. This corroborates the observation of Coyle and Dugan (2012) where the likelihood of rating one’s health as fair/poor was as high as 39% for those who scored higher on the social isolation scale. Similar relationship was also documented in other studies [15, 51, 52]. Social isolation increases the risk of being diagnosed with chronic illness . In our study, older adults at risk of social isolation did have a slightly higher numbers of chronic diseases although it did not reach a significant level. The association between social isolation and poor health is consistent with available literature across various adult age groups, including a meta-analysis of 148 studies where participants with stronger social networks were shown to have a 50% increased likelihood of survival  and a systematic review of 128 papers  which showed that increased social isolation is consistently associated with poor cardiovascular health. The mechanisms and causal links through which increased disease morbidity is associated with poorer social networks is, however, still being investigated, with suggestions that this could be due to loneliness and depression.
There is evidence linking social isolation with cognition in later life [22, 34, 54, 55]. Our study also showed an overall lower cMMSE scores in those at risk of social isolation. Most of the evidence above was in longitudinal follow-up studies. Slow gait speed in those with mild cognitive impairment which is better known as Motoric Cognitive Risk Syndrome (MCR) is also a predictor of incident dementia in later life .
There was non-significant difference between the GDS mean scores amongst those at risk and not at risk of social isolation. This could be due to the overall prevalence of depression amongst older adults in Singapore being low at 5% . Many studies on the contrary have reported association of social isolation with depression [58, 59].
The findings from this study are important for Age Friendly Community Planning Committee, social and healthcare policy makers to create supportive and accessible environments, public awareness, educational program and effective intervention. While the other associations were not significant, longitudinal studies did highlight the adverse consequences of social isolation including increased healthcare utilization, depression and dementia .
While this study represents overall community-dwelling older adults, there are several minor limitations in this study. First, the study population involved a group of community-dwelling older adults who likely had pre-existing contacts with grassroots organisations, senior activity centres or a network of friends that enabled them to learn about participation in the study. This could lead to an under-representation of community-dwelling older adults who lack these social connections, suggesting that the prevalence of older adults with a poor social network could be even higher. Second, the cross-sectional nature of this study excludes the analysis of causal relationships between social isolation and other physical and social participant characteristics. As such, whether the association between gait speed and social isolation is bi-directional is unclear. Third, the gender ratio in this study population was skewed towards the female gender, with 4 female participants for every 1 male participant. Previous studies suggest that men are more likely to be socially isolated compared to women , suggesting again that the prevalence of socially isolated older adults is likely to be higher than amongst our population.
Opportunities for further research include other factors that have not been discussed in this study, such as subjective measures of loneliness, nutritional status and implications on physical health including rate of hospital readmissions and healthcare utilization. In addition to identifying individual characteristics associated with social isolation in older adults, further research is needed to understand broader barriers to fostering a good social network, such as financial or environmental constraints including monetary concerns or a lack of physical spaces to interact with friends or family. This would be important in aiding efforts at a population-based level to improve access to good social networks for older adults.
Social isolation is associated with many adverse outcomes including dementia, poor mobility, disease morbidity and mortality. Almost half of older adults in the community are at risk of social isolation with a very significant association with gait speed, cMMSE and EQ-VAS scores. Those at risk had overall lower education attainment and higher prevalence of at least two IADL impairment. The findings from this study are useful for future Age Friendly Community Planning Committee, and policy makers to create supportive and accessible environments, and build a sustainable community health ecosystem. The impact of functional screening with necessary interventions and enabling environment on social isolation needs to be studied in a larger population .
World Population Ageing Report: United Nation. (2015). https://www.un.org/en/development/desa/population/publications/pdf/ageing/WPA2015_Report.pdf. Accessed 21 October 2019.
Singapore Department of Statistics. (2018).
Institute for Health Metrics and Evaluation. (2018).
WHO | Global health and ageing. (2011). https://www.who.int/ageing/publications/global_health.pdf?ua=1. Accessed 21 October 2019.
WHO | World report on ageing and health. (2015). https://apps.who.int/iris/bitstream/handle/10665/186463/9789240694811_eng.pdf?sequence=1. Accessed 21 October 2019.
Robins, L. M., Brown, T., Lalor, A. F., Stolwyk, R., McDermott, F., & Haines, T. (2018). Social isolation, physical capacity, and physical activity in older community-dwelling adults post-hospitalization. Journal of Aging and Physical Activity, 26(2), 204–213.
Crooks, V. C., Lubben, J., Petitti, D. B., Little, D., & Chiu, V. (2008). Social network, cognitive function, and dementia incidence among elderly women. American Journal of Public Health, 98(7), 1221–1227.
Lee, D. A., Williams, C., Lalor, A. F., Brown, T., & Haines, T. P. (2018). Hospital readmission risks in older adults following inpatient subacute care: A six-month follow-up study. Archives of Gerontology and Geriatrics, 77, 142–149.
Nicholson, N. R. (2012). A review of social isolation: An important but underassessed condition in older adults. Journal of Prime and Prevention, 33(2–3), 137–152.
Holt-Lunstad, J., Smith, T. B., & Layton, J. B. (2010). Social relationships and mortality risk: A meta-analytic review. PLoS Medicine, 7(7), e1000316.
Gardiner, P. A., Mishra, G. D., & Dobson, A. J. (2015). Validity and responsiveness of the FRAIL scale in a longitudinal cohort study of older Australian women. J Am Med Dir Assoc, 16(9), 781–783.
International Federation on Ageing (IFA). (2012). Current and emerging issues facing older Canadians.
WHO. (2007). Global age-friendly cities: A guide. https://www.who.int/ageing/publications/Global_age_friendly_cities_Guide_English.pdf. Accessed 21 October 2019.
Beutel, M. E., Klein, E. M., Brähler, E., Reiner, I., Jünger, C., Michal, M., et al. (2017). Loneliness in the general population: Prevalence, determinants and relations to mental health. BMC Psychiatry, 17(1), 97.
Ibrahim, R., Abolfathi Momtaz, Y., & Hamid, T. A. (2013). Social isolation in older Malaysians: Prevalence and risk factors. Psychogeriatrics, 13(2), 71–79.
Kemperman, A., van den Berg, P., Weijs-Perree, M., & Uijtdewillegen, K. (2019). Loneliness of older adults: Social network and the living environment. International Journal on Environmental Research and Public Health, 16(3), E406.
Cudjoe, T. K. M., Roth, D. L., Szanton, S. L., Wolff, J. L., Boyd, C. M., & Thorpe, R. J. (2018). The epidemiology of social isolation: National Health & Aging Trends Study. Journal of Gerontology B. https://doi.org/10.1093/geronb/gby037.
Dickens, A. P., Richards, S. H., Greaves, C. J., & Campbell, J. L. (2011). Interventions targeting social isolation in older people: A systematic review. BMC Public Health, 11, 647.
Bien, B., & Bien-Barkowska, K. (2016). Objective drivers of subjective well-being in geriatric inpatients: mobility function and level of education are general predictors of self-evaluated health, feeling of loneliness, and severity of depression symptoms. Quality of Life Research, 25(12), 3047–3056.
Chatters, L. M., Taylor, H. O., Nicklett, E. J., & Taylor, R. J. (2018). Correlates of objective social isolation from family and friends among older adults. Healthcare (Basel), 6(1), E24.
Aartsen, M. J., van Tilburg, T., Smits, C. H. M., & Knipscheer, K. C. P. M. (2004). A longitudinal study of the impact of physical and cognitive decline on the personal network in old age. Journal of Social and Personal Relationship, 21(2), 249–266.
Evans, I. E. M., Martyr, A., Collins, R., Brayne, C., & Clare, L. (2019). Social isolation and cognitive function in later life: A systematic review and meta-analysis. Journal of Alzheimers Disease, 70(s1), S119–s144.
Hortobagyi, T., Lesinski, M., Gabler, M., VanSwearingen, J. M., Malatesta, D., & Granacher, U. (2015). Effects of three types of exercise interventions on healthy old adults' gait speed: A systematic review and meta-analysis. Sports Medicine (Auckland, N. Z.), 45(12), 1627–1643.
Morley, J. E., Malmstrom, T. K., & Miller, D. K. (2012). A simple frailty questionnaire (FRAIL) predicts outcomes in middle aged African Americans. Journal of Nutrition and Health Aging, 16(7), 601–608.
Lawton, M. P., & Brody, E. M. (1969). Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist, 9(3), 179–186.
Brooks, R. (1996). EuroQol: The current state of play. Health Policy, 37(1), 53–72.
Herdman, M., Gudex, C., Lloyd, A., Janssen, M., Kind, P., Parkin, D., et al. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727–1736.
Janssen, M. F., Pickard, A. S., Golicki, D., Gudex, C., Niewada, M., Scalone, L., et al. (2013). Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: A multi-country study. Quality of Life Research, 22(7), 1717–1727.
Woo, J., Yu, R., Wong, M., Yeung, F., Wong, M., & Lum, C. (2015). Frailty screening in the community using the FRAIL scale. Journal of American Medical Directors Association, 16(5), 412–419.
Merchant, R. A., Chen, M. Z., Tan, L. W. L., Lim, M. Y., Ho, H. K., & van Dam, R. M. (2017). Singapore Healthy Older People Everyday (HOPE) study: Prevalence of frailty and associated factors in older adults. Journal of American Medical Directors Association, 18(8), 734.e739–734.e714.
Woo, J., Leung, J., & Morley, J. E. (2012). Comparison of frailty indicators based on clinical phenotype and the multiple deficit approach in predicting mortality and physical limitation. Journal of the American Geriatrics Society, 60(8), 1478–1486.
Donoghue, O. A., Setti, A., O'Leary, N., & Kenny, R. A. (2017). Self-reported unsteadiness predicts fear of falling, activity restriction, falls, and disability. Journal of American Medical Directors Association, 18(7), 597–602.
Lubben, J., Blozik, E., Gillmann, G., Iliffe, S., von Renteln Kruse, W., Beck, J. C., et al. (2006). Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations. Gerontologist, 46(4), 503–513.
Shou, J., Du, Z., Wang, H., Ren, L., Liu, Y., & Zhu, S. (2018). Quality of life and its contributing factors in an elderly community-dwelling population in Shanghai, China. Psychogeriatrics, 18(2), 89–97.
Zhong, B. L., Liu, X. J., Chen, W. C., Chiu, H. F., & Conwell, Y. (2018). Loneliness in Chinese older adults in primary care: Prevalence and correlates. Psychogeriatrics, 18(5), 334–342.
Nyqvist, F., Cattan, M., Conradsson, M., Nasman, M., & Gustafsson, Y. (2017). Prevalence of loneliness over ten years among the oldest old. Scandinavian Journal of Public Health, 45(4), 411–418.
Holmen, K., & Furukawa, H. (2002). Loneliness, health and social network among elderly people: A follow-up study. Archives of Gerontology and Geriatrics, 35(3), 261–274.
Peel, N. M. (2018). Gait speed as a measure in geriatric assessment in clinical settings: A systematic review. The Journals of Gerontology: Series A, 68(1), 39–46.
Studenski, S., Perera, S., Patel, K., Rosano, C., Faulkner, K., Inzitari, M., et al. (2011). Gait speed and survival in older adults. JAMA, 305(1), 50–58.
Dent, E., Morley, J. E., Cruz-Jentoft, A. J., Arai, H., Kritchevsky, S. B., Guralnik, J., et al. (2018). International Clinical Practice Guidelines for Sarcopenia (ICFSR): Screening, diagnosis and management. Journal of Nutrition and Health Aging, 22(10), 1148–1161.
Middleton, A., Fritz, S. L., & Lusardi, M. (2015). Walking speed: The functional vital sign. Journal of Aging and Physical Activity, 23(2), 314–322.
Shankar, A., McMunn, A., Demakakos, P., Hamer, M., & Steptoe, A. (2017). Social isolation and loneliness: Prospective associations with functional status in older adults. Health Psychology, 36(2), 179–187.
Gale, C. R., Westbury, L., & Cooper, C. (2018). Social isolation and loneliness as risk factors for the progression of frailty: The English Longitudinal Study of Ageing. Age and Ageing, 47(3), 392–397.
Martina, C. M., & Stevens, N. L. (2006). Breaking the cycle of loneliness? Psychological effects of a friendship enrichment program for older women. Aging and Mental Health, 10(5), 467–475.
Courtin, E., & Knapp, M. (2017). Social isolation, loneliness and health in old age: A scoping review. Health and Social Care in the Community, 25(3), 799–812.
Franck, L., Molyneux, N., & Parkinson, L. (2016). Systematic review of interventions addressing social isolation and depression in aged care clients. Quality of Life Research, 25(6), 1395–1407.
Chipps, J., Jarvis, M. A., & Ramlall, S. (2017). The effectiveness of e-Interventions on reducing social isolation in older persons: A systematic review of systematic reviews. Journal of Telemedicine and Telecare, 23(10), 817–827.
Poscia, A., Stojanovic, J., La Milia, D. I., Duplaga, M., Grysztar, M., Moscato, U., et al. (2018). Interventions targeting loneliness and social isolation among the older people: An update systematic review. Experimental Gerontology, 102, 133–144.
Brady, S., D'Ambrosio, L. A., Felts, A., Rula, E. Y., Kell, K. P., & Coughlin, J. F. (2018). Reducing isolation and loneliness through membership in a fitness program for older adults: Implications for health. Journal of Applied Gerontology, 39, 301.
Syed, M. A., McDonald, L., Smirle, C., Lau, K., Mirza, R. M., & Hitzig, S. L. (2017). Social isolation in Chinese older adults: Scoping review for age-friendly community planning. Canadian Journal of Aging, 36(2), 223–245.
Sander, R. (2005). Preventing social isolation and loneliness among older people: A systematic review of health promotion interventions. Nursing Older People, 17(1), 40.
Simon, M. A., Chang, E. S., Zhang, M., Ruan, J., & Dong, X. (2014). The prevalence of loneliness among U.S. Chinese older adults. Journal of Aging Health, 26(7), 1172–1188.
Cantarero-Prieto, D., Pascual-Saez, M., & Blazquez-Fernandez, C. (2018). Social isolation and multiple chronic diseases after age 50: A European macro-regional analysis. PLoS ONE, 13(10), e0205062.
DiNapoli, E. A., Wu, B., & Scogin, F. (2014). Social isolation and cognitive function in Appalachian older adults. Research on Aging, 36(2), 161–179.
Bassuk, S. S., Glass, T. A., & Berkman, L. F. (1999). Social disengagement and incident cognitive decline in community-dwelling elderly persons. Annals of Internal Medicine, 131(3), 165–173.
Verghese, J., Annweiler, C., Ayers, E., Barzilai, N., Beauchet, O., Bennett, D. A., et al. (2014). Motoric cognitive risk syndrome: Multicountry prevalence and dementia risk. Neurology, 83(8), 718–726.
Subramaniam, M., Abdin, E., Sambasivam, R., Vaingankar, J. A., Picco, L., Pang, S., et al. (2016). Prevalence of depression among older adults-results from the well-being of the Singapore Elderly Study. Annals of the Academy of Medicine, Singapore, 45(4), 123–133.
Glass, T. A., De Leon, C. F., Bassuk, S. S., & Berkman, L. F. (2006). Social engagement and depressive symptoms in late life: Longitudinal findings. Journal of Aging Health, 18(4), 604–628.
Choi, H., Irwin, M. R., & Cho, H. J. (2015). Impact of social isolation on behavioral health in elderly: Systematic review. World Journal of Psychiatry, 5(4), 432–438.
Taylor, R. J., Taylor, H. O., & Chatters, L. M. (2016). Social isolation from extended family members and friends among African Americans: Findings from a National Survey. Journal of Family Social Work, 19(5), 443–461.
Ministry of Health, Singapore.
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Merchant, R.A., Liu, S.G., Lim, J.Y. et al. Factors associated with social isolation in community-dwelling older adults: a cross-sectional study. Qual Life Res 29, 2375–2381 (2020). https://doi.org/10.1007/s11136-020-02493-7
- Social isolation
- Older adults
- Gait speed
- Quality of life