Abstract
Objective
Social frailty is related to adverse health-related outcomes. However, the measurement thereof is controversial and research into the relationship between social frailty and physical functioning remains limited. This study aimed to determine social frailty status via developing a simple self-reported screening tool, termed the HALFT scale, and to examine the association between social frailty and physical functioning, cognition, depression, and mortality among community-dwelling older adults.
Design
Prospective cohort study.
Setting
Community.
Participants
1697 community-dwelling adults aged ≥60 years from Beijing Longitudinal Study of Aging were included.
Measurements
The HALFT scale was developed based on 5 items: unhelpful to others, limited social participation, loneliness, financial difficulty, and not having anyone to talk to. Socioeconomic and demographic data were collected, and physical functioning, frailty index, cognition, and depression were assessed.
Results
The prevalence of social frailty was 7.7% (weighted, 4.5%). Participants with physical frailty, low levels of physical activity, and poor physical functioning had a higher prevalence of social frailty. Social frailty was associated with dementia, subjective memory decline, depression, cognitive impairment, and having experienced a recent significant life event. After adjusting for age and sex, the 8-year mortality hazard ratios were 2.5-4.3 and 1.6-2.3, respectively, for those with social frailty or pre-social frailty. Each component of the HALFT scale predicted 8-year mortality.
Conclusion
Social frailty is associated with physical functioning, cognition, and depression, and predicts mortality. The HALFT scale could be a useful screening tool for determining social frailty in older adults. Interventions aimed at preventing or delaying social frailty are warranted.
Key words: Social frailty, physical functioning, cognition, mortality
Introduction
Physical frailty is related to adverse health outcomes such as disability and death (1). The relationship between sociodemographic factors and physical frailty has been described in the literature; socioeconomic status is inversely associated with physical frailty (2). The predominant definitions of physical frailty are the Fried frailty phenotype and the Rockwood frailty index. The frailty phenotype is partly determined by social inequalities across levels of education, home ownership, and seems to be mediated by comorbidities that occur more frequently among socially disadvantaged individuals (3). The frailty index is a composite of deficits comprising physical, psychological, social, and environmental factors (4). The social and psychological domains of frailty are often neglected (5) despite social relationships and support being viewed as determinants thereof (6).
Social frailty (SF) can be defined as the absence of social resources, social activities, and self-management abilities that are important for fulfilling basic social needs (7, 8). Although social factors are increasingly recognized as being relevant to frailty, research into the social influences of frailty remains limited. Social factors, which play a role in modulating the adverse health-related outcomes of frailty (9), are integral to the health of elderly people. However, how to measure SF and to determine its relationship with physical frailty is controversial—much work is needed to characterize SF.
SF increases the requirement for nursing care and assistance from other health care professionals (10). The combination of physical frailty and SF has the highest predictive value for disability, although SF is associated with impairment in performing activities of daily living, independent of physical frailty (11). Moreover, the operational definition of SF using simple questions has a strong impact on assessing the risk of future disability among community-dwelling older people (12). Few studies, however, have examined SF status, its association with physical functioning and cognition, and its predictive validity for death.
Given that identifying at-risk populations earlier in the process of declining health has significant implications for maintaining health, understanding the ability of SF to predict mortality could be helpful when developing interventions to promote healthy aging. Thus, the aims of this longitudinal study were to determine SF status by developing a simple selfreported SF screening tool—the HALFT scale—and to examine the association between SF and physical functioning, cognition, depression, and mortality among community-dwelling older adults.
Method
Study population
Data were obtained from the Beijing Longitudinal Study of Aging (BLSA). A clustering, stratification, and random selection method was used to conduct the cross-sectional survey in 2004 (13, 14). In total, 1865 older adults from the Beijing community were selected, 1697 of whom completed the HALFT scale assessment and were followed up annually for 8 years. The study was approved by Xuanwu Hospital's Committee on the Ethics of Human Experiments, and participants provided written informed consent prior to their participation in the study.
Sociodemographic variables and covariates
Face-to-face interviews were conducted by trained staff. Socioeconomic and demographic data regarding age, sex, residential area, occupation, marital status, whether living alone, educational level, and monthly income, were collected. Lifestyle habits examined included current smoking, current alcohol use, physical exercise, tea consumption, sleeping habits, and whether still actively working. Self-reported information on health, life satisfaction, and health satisfaction was also collected.
SF Screening Questionnaire: The HALFT scale
The HALFT scale comprises the following 5 items in Chinese: inability to help others, limited social participation, loneliness, financial difficultly, and not having anyone to talk to. The ability to help others was measured by asking participants if they were able to help their friends or family within the past 12 months. Limited social participation was assessed by asking participants if they had engaged in any social or leisure time activities in the previous 12 months. Loneliness was defined as feeling lonely, and it received a score of 1 if participants responded “yes to “I have felt lonely in the past week. Financial difficulty was measured by asking participants if their income was enough for living over the past 12 months. Less talk was defined as a negative response to the statement “I have someone who I can talk with every day. “HALFT is an acronym for the five components: Help, pArticipation, Loneliness, Financial and Talk. The HALFT scale score ranges from 0–5 points: a score of 0 was considered non-SF; 1–2 was considered pre-SF; and a score of ≥3 indicated SF.
Evaluation of physical frailty, physical functioning, and neuropsychological variables
Physical frailty was assessed using frailty index using 68 parameters, the details of which have been published elsewhere (14). Frailty was defined as a frailty index ≥0.25. Each participant underwent a balance test and chair-stand test. Activities of daily living and instrumental activities of daily living were also assessed. Physical activity was assessed by the following variables: walking, gardening, low-level exercise, and high-level exercise (15). Dementia was defined using a self-reported history of dementia having being diagnosed by a doctor. A life event was defined as a significantly stressful event occurring in the past 2 months. Those who complained of a decline in memory were considered to have subjective memory decline. The criteria used to define cognitive impairment and clinical depression were the same as those used in our previous publication (16). Cognition was measured using the mini-mental state examination and the Center for Epidemiologic Studies Depression Scale was used to assess symptoms of depression.
Statistical methods
SPSS software (version 11.5, SPSS, Inc., Chicago, IL, USA) was used to perform the data analysis. Chi-square tests were conducted to compare discrete variables, and ANOVA, with Tukey post hoc testing, was used to compare the continuous (normally-distributed) variables between groups. A Cox proportional hazards model was used to evaluate the effect of covariates on mortality. We considered P <0.05 (two-tailed) to be statistically significant.
Results
Prevalence of SF by socio-demographics variables
Using the HALFT scale, the crude prevalence of SF was 7.7% with a standard prevalence of 4.5% in both men and women. The crude prevalence of pre-SF was 45.6%, with a weighted prevalence of 41.6%. The prevalence of SF was 5 times higher among rural than urban elderly and increased sharply with age (Fig. 1). SF prevalence decreased with higher levels of education and monthly income. Those with poor selfreported health, life satisfaction, and health satisfaction were prone to SF. A high prevalence of SF was observed among participants who were widowed, living alone, and current smokers; who had worse sleep patterns, currently used alcohol, did not drink tea; and who engaged in heavy physical labor as their occupation, and were not currently engaged in some work (Table 1).
Figure 1.
Prevalence of social frailty in older adults by sex, area, and age
Table 1.
Demographic characteristics of SF
| Item | Total | Non-SF, n (%) | Pre-SF, n (%) | SF, n (%) | x2 | P value |
|---|---|---|---|---|---|---|
| Sociodemographic | ||||||
| Occupation | 1691 | 146.127 | <0.001 | |||
| White-collar | 428 | 279(65.2) | 141(32.9) | 8(1.9) | ||
| Light physical labor | 534 | 276(51.7) | 231(43.3) | 27(5.1) | ||
| Heavy physical labor | 729 | 236(32.4) | 397(54.5) | 96(13.2) | ||
| Education | 1697 | 200.072 | <0.001 | |||
| Illiterate | 718 | 227(31.6) | 389(54.2) | 102(14.2) | ||
| Elementary school | 449 | 207(46.1) | 221(49.2) | 21(4.7) | ||
| Middle school | 202 | 122(60.4) | 74(36.6) | 6(3.0) | ||
| High school | 118 | 84(71.2) | 33(28.0) | 1(0.8) | ||
| College and above | 210 | 152(72.4) | 57(27.1) | 1(0.5) | ||
| Monthly income | 1697 | 257.924 | <0.001 | |||
| <500 Yuan | 843 | 250(29.7) | 476(56.5) | 117(13.9) | ||
| 500-1000 Yuan | 409 | 221(54.0) | 178(43.5) | 10(2.4) | ||
| >1000 Yuan | 445 | 321(72.1) | 120(27.0) | 4(0.9) | ||
| Marital status | 1697 | 184.297 | <0.001 | |||
| Married | 1155 | 660(57.1) | 448(38.8) | 47(4.1) | ||
| Widowed | 542 | 132(24.4) | 326(60.1) | 84(15.5) | ||
| Living alone | 1697 | 58.631 | <0.001 | |||
| Yes | 181 | 43(23.8) | 105(58.0) | 33(18.2) | ||
| No | 1516 | 749(49.4) | 669(44.1) | 98(6.5) | ||
| Self-reported health | ||||||
| Health satisfaction | 1697 | 59.324 | <0.001 | |||
| Well | 781 | 434(55.6) | 316(40.5) | 31(4.0) | ||
| Bad | 916 | 358(39.1) | 458(50.0) | 100(10.9) | ||
| Life satisfaction | 23.612 | <0.001 | ||||
| Well | 1653 | 787(47.6) | 745(45.1) | 121(7.3) | ||
| Bad | 35 | 4(11.4) | 23(65.7) | 8(22.9) | ||
| Self-reported health | 1696 | 59.705 | <0.001 | |||
| Well | 1391 | |||||
| Bad | 305 | 708(50.9) | 593(42.6) | 90(6.5) | ||
| Life style | 84(27.5) | 180(59.0) | 41(13.4) | |||
| Current smoking | 1697 | 20.332 | <0.001 | |||
| Yes | 607 | 239(39.4) | 313(51.6) | 55(9.1) | ||
| No | 1090 | 553(50.7) | 461(42.3) | 76(7.0) | ||
| Sleep quality | 1697 | 29.180 | <0.001 | |||
| Well | 1251 | 619(49.5) | 558(44.6) | 74(5.9) | ||
| Bad | 446 | 173(38.8) | 216(48.4) | 57(12.8) | ||
| Weekly exercise | 1697 | 74.252 | <0.001 | |||
| >10 h | 607 | 329(54.2) | 257(42.3) | 21(3.5) | ||
| 6-10 h | 445 | 234(52.6) | 184(41.3) | 27(6.1) | ||
| <=5 h | 645 | 229(35.5) | 333(51.6) | 83(12.9) | ||
| Still work | 1696 | 50.182 | <0.001 | |||
| Yes | 616 | 354(57.5) | 235(38.1) | 27(4.4) | ||
| No | 1080 | 437(40.5) | 539(49.9) | 104(9.6) | ||
| Current alcohol use | 1695 | 12.971 | 0.002 | |||
| Yes | 527 | 212(40.2) | 267(50.7) | 48(9.1) | ||
| No | 1168 | 579(49.6) | 506(43.3) | 83(7.1) | ||
| Current tea use | 1695 | 23.204 | <0.001 | |||
| Yes | 864 | 448(51.9) | 366(42.4) | 50(5.8) | ||
| No | 831 | 342(41.2) | 408(49.1) | 81(9.7) |
SF, social frailty
SF and physical functioning
A high prevalence of SF was observed among participants who were physically frail. Participants who engaged in low levels of physical activity, with dependent physical functioning, poor results in the balance and chair-stand tests, dependency in terms of activities of daily living and instrumental activities of daily living displayed a higher prevalence of SF (Table 2).
Table 2.
The prevalence of social frailty in different physical function
| Item | Total | Non-SF, n (%) | Pre-SF, n (%) | SF, n (%) | x2 | P value |
|---|---|---|---|---|---|---|
| Frailty by frailty index | 1680 | 222.25 | <0.001 | |||
| Robust | 1456 | 767(52.7) | 621(42.7) | 68(4.7) | ||
| Frail | 224 | 22(9.8) | 141(62.9) | 61(27.2) | ||
| Physical activity | 1697 | 82.666 | <0.001 | |||
| Normal | 1379 | 706(51.2) | 595(43.1) | 78(5.7) | ||
| Low physical activity | 318 | 86(27.0) | 179(56.3) | 53(16.7) | ||
| Physical function | 1697 | 314.323 | <0.001 | |||
| Independent | 1168 | 687(58.8) | 448(38.4) | 33(2.8) | ||
| Dependent (light) | 451 | 101(22.4) | 279(61.9) | 71(15.7) | ||
| Dependent (medium) | 44 | 4(9.1) | 26(59.1) | 14(31.8) | ||
| Dependent (heavy) | 34 | 0 | 21(61.8) | 13(38.2) | ||
| Chair stand failure | 1667 | 125.307 | <0.001 | |||
| Yes | 374 | 87(23.3) | 229(61.2) | 58(15.5) | ||
| No | 1293 | 701(54.2) | 522(40.4) | 70(5.4) | ||
| Balance test failure | 1313 | 11.498 | 0.003 | |||
| Yes | 161 | 74(46.0) | 71(44.1) | 16(9.9) | ||
| No | 1152 | 636(55.2) | 466(40.5) | 50(4.3) | ||
| ADL dependency | 1697 | 133.291 | <0.001 | |||
| Yes | 148 | 14(9.5) | 95(64.2) | 39(26.4) | ||
| No | 1549 | 778(50.2) | 679(43.8) | 92(5.9) | ||
| IADL dependency | 1692 | 292.315 | <0.001 | |||
| Yes | 649 | 143(22.0) | 402(61.9) | 104(16.0) | ||
| No | 1043 | 647(62.0) | 369(35.4) | 27(2.6) |
SF, social frailty; ADL, activities of daily living; IADL, instrumental activities of daily living.
SF and neuropsychological status
A high prevalence of SF was observed among participants who had dementia, who had experienced a recent life event, subjective memory decline, depression, and cognitive impairment (Table 3).
Table 3.
The prevalence of social frailty in different neuropsychological status
| Diseases | Total | Non-SF, n (%) | Pre-SF, n (%) | SF, n (%) | x2 | P value |
|---|---|---|---|---|---|---|
| Dementia | 1697 | 99.453 | <0.001 | |||
| Yes | 78 | 9(11.5) | 42(53.8) | 27(34.6) | ||
| No | 1619 | 783(48.4) | 732(45.2) | 104(6.4) | ||
| Life event | 1686 | 23.303 | <0.001 | |||
| Yes | 717 | 290(40.4) | 357(49.8) | 70(9.8) | ||
| No | 969 | 498(51.4) | 414(42.7) | 57(5.9) | ||
| Subject memory | 1697 | 81.591 | <0.001 | |||
| Yes | 655 | 224(34.2) | 349(53.3) | 82(12.5) | ||
| No | 1042 | 568(54.5) | 425(40.8) | 49(4.7) | ||
| Cognition | 1684 | 172.060 | <0.001 | |||
| Normal | 1436 | 750(52.2) | 618(43.0) | 68(4.7) | ||
| Impairment | 248 | 41(16.5) | 148(59.7) | 59(23.8) | ||
| Depression | 1683 | 250.065 | <0.001 | |||
| Yes | 245 | 33(13.5) | 142(58.0) | 70(28.6) | ||
| No | 1438 | 755(52.5) | 628(43.7) | 55(3.8) |
SF, social frailty
SF predicted mortality at 8-year follow-up
Over the 8 years of follow-up, those who survived had a lower prevalence of SF at baseline (4.2% vs 15.1%, P <0.01). The Cox proportional hazards analysis showed that SF and pre- SF could predict mortality (hazard ratios 3.5–6.1 and 1.9–2.9, respectively). After adjusting for age and sex, the hazard ratios for 8-year mortality associated with SF and pre-SF were 2.5–4.3 and 1.6–2.3, respectively. Each component could predict 8-year mortality, with the components inability to help and limited social participation being the strongest predictors before and after adjustment, respectively. Moreover, the 5 components in combination were better able to predict mortality than each individual component could (Table 4; Figures 2, S1)
Table 4.
Predictive models of mortality at 8-year follow-up
| HR | Crude model95% CI | P value | HR | Adjusted model95% CI | P value | |
|---|---|---|---|---|---|---|
| SF | ||||||
| Pre-SF | 2.353 | 1.940-2.854 | <0.001 | 1.914 | 1.573-2.328 | <0.001 |
| SF | ||||||
| Five components | 4.635 | 3.547-6.057 | <0.001 | 3.273 | 2.486-4.307 | <0.001 |
| Unhelpful | 3.319 | 2.836-3.883 | <0.001 | 2.285 | 1.933-2.702 | <0.001 |
| Less participation | 3.216 | 2.705-3.824 | <0.001 | 2.422 | 2.019-2.906 | <0.001 |
| Loneliness | 1.370 | 1.117-1.681 | <0.001 | 1.246 | 1.015-1.530 | <0.001 |
| Financial difficulty | 1.596 | 1.300-1.961 | <0.001 | 1.847 | 1.501-2.272 | <0.001 |
| Less talk | 1.805 | 1.531-2.128 | <0.001 | 1.467 | 1.241-1.734 | <0.001 |
Reference: Non-SF. Crude model: Unadjusted Cox proportional hazard analysis. Adjusted model: Adjusted Cox proportional hazard analysis. Adjusted by age and sex. Abbreviations: SF, social frailty; HR, hazard ratio; CI, confidence interval.
Figure 2.
Survival curve for social frailty status and each component adjusts for age and sex
Discussion
The present study found that SF, as defined by the HALFT scale, was associated with physical functioning, cognition, and depression, and predicts mortality. The prevalence of SF was found to be 7.7% (weighted 4.5%); this is the first report of the prevalence of SF in a Chinese population. In Singapore, the percentage of high SF scores was 18.4% among older adults (11). A study in Japan reported the prevalence of SF and pre-SF to be 11.1% and 24.8% in older adults, respectively (17). The lower prevalence in China may be because of the traditional family-based support given to Chinese older adults.
Our study shows that SF measured by HALFT scale was associated with adverse health outcomes, indicating that the scale is a useful tool. However, the validity and utility of the HALFT scale remain unclear. We found that limited social participation was the strongest predictor of mortality after adjusting for age and sex. Similarly, previous studies have shown that social participation is negatively associated with both the onset and progression of disability, even after adjusting for health status (18), and that not participating socially is associated with worsening frailty (19). Furthermore, an increase in social engagement is associated with better subjective physical health (20) and could reduce the risk of disability among older adults (21, 22). The Coyoacán cohort study showed that not having a partner, not participating in making important decisions, and having a poor self-perceived economic situation are all associated with frailty (23). In the present study, inability to help friends or family was the strongest predictor of mortality before adjustment, consistent with the findings of a previous study found that a low level of social contribution could predict future functional decline among older people (24).
Our results show that participants with physical frailty or poorer physical functioning had a higher prevalence of SF, in keeping with findings of previous studies showing that SF status is negatively associated with physical functioning (17) and is associated with a higher incidence of disability among older people (25). Although the combination of physical frailty and SF identifies individuals at much higher risk of functional and severe disability than does a single index, single-domain indices remain useful when targeting unique sets of risk factors and desired outcomes of interventions (11). Physical activity is not the only mediator between SF and physical deficiency (17); smoking is associated with both frailty onset and its worsening. (6). We also found that participants with less healthy lifestyle habits had a higher prevalence of SF, providing evidence for the above hypothesis.
Participants with cognitive impairment and depression had a higher prevalence of SF in this study, which is consistent with findings in older Japanese adults (17). Less participation in social activities was found to be associated with a more rapid rate of motor function decline in older adults and an increased risk of cognitive decline (26, 27), while larger social networks had a protective effect against dementia (28), indicating that SF status might have an impact on the onset cognitive decline. Studies have also found that hormonal factors (29) and allostatic load (30) may contribute to the potential mechanisms between SF and cognition. These findings shed light on how preventing SF may slow the rate of future cognitive decline or the development of dementia (17).
Our study has several strengths. First, our operationalized definition of SF was based on self-reported information. This offers a simple way to assess SF, particularly considering its potential applicability to busy clinical settings. Second, our longitudinal approach strengthens the evidence for the association between SF and mortality. Lastly, the HALFT scale is the only tool specified for use among older Chinese adults. It appears to be a valid measure, as it predicts mortality and is associated with physical functioning; however, further research is warranted to strengthen our understanding of its validity and properties. This study also has some limitations. First, we could not identify whether a cause-and-effect relationship or a causal association exists between SF and cognitive impairment or a decline in physical functioning. The effect of SF on the incidence of future frailty, disability, cognitive impairment, and depression still needs to be determined. Second, we found the prevalence of SF in China was lower than that in other countries, the lack of a unified assessment tool and arbitrary nature of the cutoff for the HALFT might make the results from different studies uncomparable. As the HALFT scale is a new measure, its reliability and validity have yet to be quantified. Third, we chose FI as the tool to measure frailty, although our results showed patients with poor physical function had a higher prevalence of SF, the relationship between SF and physical frailty defined by Fried phenotype should be explored in further studies.
The HALFT scale is useful for identifying older people at risk of frailty, disability, depression, and cognitive impairment, and can predict mortality. This indicates that social factors, which are often ignored in the medical context, might represent risk factors for disability. SF has clinical relevance and the prevalence of SF has public health implications as it may be prevented or ameliorated. Therefore, SF should be assessed and taken into account in the implementation of multifaceted prevention strategies for older adults. Our results offer support for population-level interventions that target social frailty, physical frailty, and disability so as to enhance the health span.
Acknowledgements
We acknowledge all the people who participated in the cohort study.
Fundings
This work was supported by Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support (ZYLX201706), 2018 Milstein Medical Asian American Partnership Foundation Project Award in Geriatrics, and the United Nations Population Fund (CPR/90/P23).
Conflict of interest statement
The authors have no conflict of interests and no financial associations to disclosure.
Author Contributions
LM and ZT contributed to the design of the work. LM drafted the manuscript, and wrote it together with ZT. FS contributed to the data analysis. All the authors contributed to writing the paper and revising it critically and gave final approval of this version.
Ethical standard
The present study followed the ethical guideline of the Declaration of Helsinli and was approved by th Ethics Committee.
Electronic supplementary material
Supplementary material is available for this article at https://doi.org/10.1007/s12603-018-1054-0 and is accessible for authorized users.
Fig. S1. Survival curve for social frailty status and each component in older adults
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Associated Data
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Supplementary Materials
Fig. S1. Survival curve for social frailty status and each component in older adults