Abstract
Objectives
To study the factors that influence the 6-minute walking distance (6MWD) among older patients with chronic heart failure.
Methods
This was a single-center, retrospective, observational study. A total of 123 patients from the First Affiliated Hospital of Nanjing Medical University was selected. The factors associated with the 6MWD were analyzed using Pearson correlation analysis and multivariate linear regression.
Results
The 6MWD of older patients was negatively correlated with age, fall risk, nutritional score, frailty, and depression but was positively correlated with educational level, fall efficacy, self-care ability, and plasma albumin. The results of independent variable multiple linear regression analysis showed that age (β = −0.098), fall risk (β = −0.262), fall efficacy (β = 0.011), self-care ability (β = −0.021), nutrition (β = −0.405), frailty (β = −0.653), and plasma albumin (β = 0.127) influenced the 6MWD.
Conclusions
The 6MWD of older patients with chronic heart failure was related to age, self-care ability, fall risk, nutrition, frailty, and depression.
Keywords: 6-minute walking distance, chronic heart failure, older adult, risk factor, fall risk, self-care ability, frailty, depression
Introduction
The 6-minute walk test (6MWT) is a simple and safe assessment that does not require expensive equipment or advanced training for technicians. 1 The test evaluates exercise endurance and involves asking the patient to walk the longest distance possible in a set period of 6 minutes. The 6MWT is regarded as an index of cardiac function in the guidelines for the diagnosis and treatment of chronic heart failure issued by the American Heart Association and the guidelines for the diagnosis and treatment of heart failure issued by the cardiovascular branch of the Chinese Medical Association. 2 In 2002, the 6MWT guideline issued by the American Thoracic Society highlighted that several factors affect the 6-minute walking distance (6MWD). 3 Some scholars have proposed that the 6MWD is influenced by multiple physiological and pathological factors including height, age, body mass, sex, region, race, coordination, cardiovascular disease, respiratory disease, skeletal muscle disease, learning effect, and medication use before the test.4,5 Therefore, these factors should be considered when using the 6MWT to evaluate cardiac function. Older patients have more risk factors because of the degradation of physiological function and the coexistence of a variety of pathological factors. This study focused on patients over 80 years of age to explore susceptibility factors affecting the 6MWD.
Methods
Participants and data collection
This was a single-center, retrospective, observational study performed in the geriatric cardiovascular department of the First Affiliated Hospital of Nanjing Medical University from June 2017 to July 2018. A total of 123 patients, most of whom were over 80 years of age, were enrolled in this study. These patients were not randomly selected but were enrolled in accordance with the inclusion and exclusion criteria. General patient data included age, sex, educational level, and presence of pre-existing disease. The case collection methods were based on an electronic medical record system and the main diagnosis at discharge. Chronic heart failure was diagnosed based on clinical signs and symptoms, echocardiographic parameters, and blood test results of B-type natriuretic peptide (BNP) or N-terminal pro-brain natural peptide (NT-pro-BNP). BNP and NT-ProBNP levels of patients with chronic heart failure in sinus rhythm should exceed 80 ng/L and 220 ng/L, respectively. However, BNP and NT-ProBNP levels of patients with chronic heart failure in atrial fibrillation are greater than 240 ng/L and 660 ng/L, respectively. The 6MWD was measured and recorded in accordance with the standards of the American Thoracic Society. Oral consent was obtained from the patient or caregiver, and the study was approved by the Ethics Committee of the First Affiliated Hospital of Nanjing Medical University (2022-SR-134). We de-identified patient details at the end of the study. The reporting of this study conforms to STROBE guidelines. 6
Exclusion criteria
Patients were excluded if they met any of the following criteria: age <75 years, unstable angina pectoris and acute myocardial infarction within the last month; systolic blood pressure >180 mmHg or diastolic blood pressure >100 mmHg; resting heart rate >120 beats per minute; ventricular tachycardia, second- and third-degree atrioventricular block, or other severe atrial or ventricular arrhythmias; serious nervous system disease, peripheral vascular disease, or critical lung disease; severe heart valve disease; end stage of various diseases; and other conditions that do not allow the completion of the 6MWT.
Fall risk and fall efficacy assessment
The St Thomas’s Risk Assessment Tool was used to evaluate the risk of falls in hospitalized older patients. The scale has a total score of 10 points. A score greater than two points indicates a high risk of falling. To assess fall efficacy, we adopted the revised Fall Efficacy Scale, a self-test belief scale with a Cronbach’s alpha of 0.97. This fall efficacy test measures whether participants have a fear of falling. Fall efficacy is the opposite of fall risk; therefore, the lower the fall efficacy score, the easier it is for the individual to fall.
Self-care ability assessment
The modified Barthel Index scale was used to evaluate self-care ability. The scale has a total score of 100 points, with ≥60 points indicating a basic level of self-care, 41 to 59 points indicating the need for assistance for living, 21 to 40 points indicating obvious dependence on assistance for living, and ≤20 points indicating complete dependence on assistance for living.
Nutritional status
To conduct nutritional screening and evaluation, we adapted the Mini Nutritional Assessment for use by older patients. The scale is divided into two parts: screening and evaluation. A screening score ≥12 indicates good nutritional status, whereas a score ≤11 requires advancing to nutritional evaluation. The evaluation method consists of adding the scores of the two parts. A total score of ≥24 indicates normal nutrition, a score between 17 and 23.5 indicates potential malnutrition, and a score <17 indicates malnutrition.
Frailty and depression assessment
Frailty was assessed using the FRAIL scale, which contains five items with a score of one for each item. A score >2 is defined as frailty. The Hamilton Depression Rating Scale was used to evaluate the state of depression. The scale consists of 24 items with a total score of 78 points; a score >35 points indicates severe depression, 20 to 35 points suggests obvious depression, 8 to 19 points indicates possible depression, and <8 points suggests no depression.
Measuring 6-minute walking distance
In accordance with the method specified in the 6MWT guide issued by the American Thoracic Association in 2002, the test was conducted indoors, and participants walked along a long, straight, flat corridor with a hard ground. The total length of the route was 30 m, included markings at 3-m intervals, and also featured eye-catching markings at the starting and turning back points. Participants’ vital signs were measured before the start of the test. The staff continuously encouraged participants once the test was started. Participants walked back and forth along the corridor as rapidly as possible for 6 minutes, and then the walking distance was measured.
Statistical methods
All statistical analyses were performed using SPSS version 19.0 statistical software (IBM Corp., Armonk, NY, USA). The measurement data in line with the normal distribution was expressed by the mean ± standard deviation. One-way analysis of variance was used for comparison between groups with normal and homogeneous variance data, and the least significant difference test was used for multiple comparisons. Counting data were expressed by frequency and percentage, and the chi-square test was used for comparison between groups. Pearson analysis was used for correlation analysis of continuous variables, whereas linear regression analysis was used for multivariate analysis. All P-values were two-tailed, and the threshold of significance was set at 0.05.
Results
Characteristics of the study population
Participants were divided into three groups according to their 6MWD. Among patients with heart failure who performed the 6MWT, participants who completed a short (<150 m) distance were older and mostly male. The results in Table 1 indicate that among hospitalized octogenarians who participated in the 6MWT, increasing patient age was statistically associated with a higher likelihood of complications from basic diseases, worse nutritional status, lower plasma albumin level, worse self-care ability, a higher fall risk, and a higher incidence of depression.
Table 1.
Characteristics of 123 patients over 80 years of age who performed the 6MWT.
| Characteristic | 6MWD |
χ2/F value | P-value | ||
|---|---|---|---|---|---|
| >450 m | 150–450 m | <150 m | |||
| Number of cases | 13 | 71 | 39 | ||
| Age (years, x ± s) | 77.62 ± 7.88 | 80.29 ± 8.36 | 85.47 ± 5.67 | 20.468 | 0.016 |
| Sex, n (%) | 0.977 | 0.613 | |||
| Male | 11 (84.6) | 55 (77.5) | 33 (84.6) | ||
| Female | 2 (15.4) | 16 (22.5) | 6 (15.4) | ||
| Educational attainments, n (%) | 7.857 | 0.097 | |||
| Elementary school or lower | 2 (15.4) | 15 (21.1) | 13 (33.3) | ||
| Junior and senior high school | 3 (23.1) | 33 (46.5) | 17 (43.6) | ||
| Bachelor degree or above | 8 (61.5) | 23 (32.4) | 9 (23.1) | ||
| Pre-existing diseases, n (%) | 7.849 | 0.644 | |||
| Respiratory diseases | 3 (23.1) | 14 (19.7) | 5 (12.8) | ||
| Circulatory diseases | 1 (7.7) | 18 (25.4) | 13 (33.3) | ||
| Neurological disease | 1 (7.7) | 13 (18.3) | 6 (15.4) | ||
| Endocrine diseases | 5 (38.5) | 11 (15.5) | 6 (15.4) | ||
| Digestive diseases | 2 (15.4) | 8 (11.3) | 5 (12.8) | ||
| Other diseases | 1 (7.7) | 7 (9.9) | 4 (10.3) | ||
| Nutritional status, n (%) | 23.998 | <0.001 | |||
| No malnutrition | 5 (12.8) | 33 (46.5) | 9 (69.2) | ||
| Potential malnutrition | 8 (20.5) | 13 (18.3) | 4 (30.8) | ||
| Malnutrition | 26 (66.7) | 25 (35.2) | 0 (0) | ||
| Plasma albumin (x ± s) | 38.93 ± 3.23 | 36.77 ± 3.69 | 35.14 ± 3.22 | 6.269 | 0.003 |
| Frailty assessment, n (%) | 28.919 | <0.001 | |||
| No frailty | 3 (23.1) | 5 (7.0) | 0 (0) | ||
| Early frailty | 6 (46.1) | 34 (47.9) | 6 (15.4) | ||
| Frailty | 4 (30.8) | 32 (45.1) | 33 (84.6) | ||
| Self-care ability (score, x ± s) | 84.00 ± 15.35 | 78.66 ± 19.24 | 65.18 ± 27.49 | 6.021 | 0.003 |
| Fall risk (score, x ± s) | 2.69 ± 0.95 | 3.07 ± 1.49 | 3.97 ± 1.51 | 6.239 | 0.003 |
| Fall efficacy (score, x ± s) | 131.15 ± 18.50 | 118.10 ± 30.93 | 98.85 ± 35.77 | 6.980 | 0.001 |
| Presence of depression (x ± s) | 7.00 ± 3.37 | 6.83 ± 4.70 | 11.56 ± 7.71 | 8.969 | <0.001 |
6MDW: six-minute walking distance.
Six-minute walk test and its clinical correlates
To identify factors that influence 6MWD in older patients with chronic heart failure, Pearson correlation analysis using 6MWD as the dependent variable was used to statistically analyze the data. The results in Table 2 indicate that older age, higher fall risk, worse nutritional status, more obvious frailty, and depression were negatively correlated with 6MWD (correlation coefficients: −0.619, −0.366, −0.434, −0.467, −0.273, respectively). In contrast, fall efficacy, self-care ability, and plasma albumin were positively correlated with 6MWD (correlation coefficients: 0.351, 0.344, and 0.361, respectively).
Table 2.
Pearson correlation analysis of 6MWD variables in older patients.
| Variable | R (Pearson correlation coefficient) | P-value |
|---|---|---|
| Age | −0.619 | <0.001 |
| Fall risk | −0.366 | <0.001 |
| Fall efficacy | 0.351 | <0.001 |
| Self-care ability | 0.344 | <0.001 |
| Nutritional status | −0.434 | <0.001 |
| Frailty | −0.467 | <0.001 |
| Depression | −0.273 | 0.002 |
| Plasma albumin | 0.361 | <0.001 |
6MWD: six-minute walking distance.
Multiple linear regression coefficients between 6MWD and influencing factors
As shown in Table 3, the results of multiple linear regression analysis showed that age, fall risk, fall efficacy, self-care ability, nutritional status, frailty, plasma albumin, and depression were independent influencing factors of 6MWD (P < 0.05), among which frailty (β = −0.653) had the strongest association with 6MWD, followed by nutritional status (β = −0.405) and fall risk (β = −0.262).
Table 3.
Multiple linear regression analysis of 6MWD in older adults with heart failure.
| Independent Variable | β-coefficient | SE | 95% CI | t-value | P-value |
|---|---|---|---|---|---|
| Age | −0.098 | 0.012 | −0.121, −0.075 | −8.347 | <0.001 |
| Fall risk | −0.262 | 0.090 | −0.440, −0.085 | −2.925 | 0.004 |
| Fall efficacy | 0.011 | 0.004 | 0.003, 0.019 | 2.652 | 0.009 |
| Self-care ability | 0.021 | 0.006 | 0.010, 0.032 | 3.782 | <0.001 |
| Nutritional status | −0.405 | 0.153 | −0.708, −0.101 | −2.643 | 0.009 |
| Frailty | −0.653 | 0.184 | −1.017, −0.290 | −3.559 | 0.001 |
| Depression | −0.245 | 0.198 | −0.637, 0.146 | −1.241 | 0.017 |
| Plasma albumin | 0.127 | 0.035 | 0.058, 0.197 | 3.610 | <0.001 |
6MWD: six-minute walking distance.
Discussion
Heart failure is the end stage of various heart diseases and is associated with growing morbidity and mortality. The prevalence of heart failure increases with age, and it is a major global health problem.7,8 The 6MWT is simple, low-cost, and convenient to administer and does not require sophisticated equipment. The test objectively evaluates a patient’s cardiopulmonary functional capacity, which is measured as part of the assessment of patients with chronic heart failure.9,10 The results of our study showed that 6MWD in older patients with heart failure was negatively correlated with age (β = −0.098) and was positively correlated with the patient's self-care ability (β = 0.021). Increasing age is usually accompanied by muscle atrophy, which is manifested as a reduction in muscle volume and the loss of strength. Muscle atrophy triggers anaerobic metabolism at a lower level of exercise, resulting in declining exercise ability and shortened walking distances. 11 Ha et al. 12 identified that age is a vital factor affecting the 6MWD in patients with heart failure. Furthermore, the decline in exercise ability and limited physical activity caused by age eventually lead to a decline in self-care ability, which also results in shortened walking distances. Moreover, Lainscak et al. 13 demonstrated that self-care ability noticeably differed across age groups of older adults. The self-care ability among adults aged 60 to 79 years was superior to that of older groups. The study further showed a remarkable downward trend in self-care ability with increasing age. Therefore, the older the patient, the poorer the self-care ability and the shorter the walking distance. In addition, a study 14 showed that patients’ 6MWD increased significantly with positive nursing interventions to improve self-care, confirming the positive correlation between self-care and 6MWD. Our results were consistent with these findings.
Our study results showed that 6MWD was negatively correlated with fall risk in older patients with heart failure (β = −0.262), and positively correlated with fall efficacy (β = 0.011). Falls are defined as sudden, involuntary, and unintentional changes in body posture. Every year, 30% of community-dwelling adults over 65 years of age fall, whereas 50% of older adults over 80 years of age fall annualy. 15 Falls can lead to a series of consequences such as fractures and disability that can limit the mobility of older adults and may lead to death in severe cases. Fall efficacy evaluates the self-confidence of patients who do not fall during an activity. 16 The higher the fall efficacy, the more confident patients are that they will not fall during the activity and the longer the walking distance. In contrast, patients with low fall efficacy have poor confidence in performing their daily activities and are more worried about falling. 17 These patients will subconsciously reduce the range and frequency of their activities, resulting in shortened walking distances. Therefore, fall risk and fall efficacy are important factors that affect 6MWD in older patients with chronic heart failure.
Significant associations between serum BNP levels and nutrition indices were observed, indicating worsening nutritional status with more severe heart failure. 18 The results of our study also indicated that nutritional status and frailty were independent factors of 6MWD in older patients with heart failure. The incidence of malnutrition is higher in older adults than in younger groups because of the reduction of food intake and the weakening of digestive and metabolic functions with increasing age. Malnutrition leads to insufficient energy supply, muscle atrophy, and a decline in plasma albumin, in turn causing decreased activity and shortened walking distance. 19 Furthermore, depression and frailty are pertinent health concerns associated with geriatric syndromes. 20 The results of this study showed that depression was a factor affecting 6MWD in older patients with heart failure and was negatively correlated with 6MWD (β = −0.245). Boxer et al.’s study 21 suggested that frailty was a risk factor for the development and persistence of depression, whereas Celano et al. 22 showed that depression increased the risk of frailty in older patients with chronic heart failure. Soysal et al.’s meta-analysis of 24 clinical studies 23 indicated a reciprocal interaction between depression and frailty in older adults. Specifically, each of these conditions was associated with an increased prevalence and incidence of the other condition and was a potential risk factor for the development of the other condition. Other studies24,25 have further suggested that older adults with depression were more prone to frailty than those without depression, that older men with depression were at a higher risk of frailty than older women, and that both depression and frailty reduced mobility and 6MWD.
Our study showed that old age, low self-care ability, falls, malnutrition, frailty, and depression were vital factors affecting 6MWD in older patients with heart failure. Our findings suggest that healthcare workers should conduct a comprehensive evaluation including influencing factors when using 6MWT to evaluate the cardiopulmonary function of older patients to ensure that results are accurate. Ensuring intervention measures to protect against these influencing factors is also valuable. Through multi-disciplinary cooperation, nutrition support, functional exercise, medication compatibility, psychological intervention, and other measures to delay the occurrence and development of frailty, improve the self-care ability, nutritional status, and 6MWD among older patients with chronic heart failure. In the exclusion criteria section, we listed some serious or dangerous conditions of the disease, which led to the patients being unable to cooperate well to complete the 6MWT. Therefore, we will not discuss the impact of these abnormal conditions on the 6MWD of patients with heart failure.
Limitations
Our results provided evidence for the logical relationship between 6MWD and relative risk factors among older patients with heart failure. While our data provided some novel insights, some limitations should be acknowledged. First, this was a retrospective observational study, and the sample size was not large enough. Therefore, a prospective, systematic study is needed to further prove various risk factors affecting the 6MWD of older patients with heart failure. Second, the relationship and mechanism between various risk factors and 6MWD were not clarified in detail. Third, there were multiple factors affecting the 6MWD among older patients with heart failure, but these factors were also interrelated and complex. Therefore, when evaluating 6MWD, it is necessary to comprehensively consider various risk factors and the weight of each factor.
Footnotes
The authors declare that there are no conflicts of interest.
Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Natural Science Foundation of Jiangsu Province (Grant No. BK20161057), the Scientific Research Project of Jiangsu Commission of Health (Z2019021, BJ20014), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (21KJA320003), and the Nursing Scientific Research Project of the First Affiliated Hospital of Nanjing Medical University (YHK201732).
ORCID iD: Jun Wu https://orcid.org/0000-0003-4605-1148
References
- 1.Enright PL, McBurnie MA, Bittner V, et al. ; Cardiovascular Health Study. The 6-min walk test is a quick measure of functional status in elderly. Chest 2003; 123: 387–398. [DOI] [PubMed] [Google Scholar]
- 2.Heidenreich PA, Bozkurt B, Aguilar D, et al. 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 2022; 145: e895–e1032. [DOI] [PubMed] [Google Scholar]
- 3.ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med 2002; 166: 111–117. [DOI] [PubMed] [Google Scholar]
- 4.Kervio G, Carre F, Ville N.Reliability and intensity of the six-minute walk test in healthy elderly subjects. Med Sci Sports Exerc 2003; 35: 169–174. [DOI] [PubMed] [Google Scholar]
- 5.Heinz P, Gulart AA, Klein SR, et al. A performance comparison of the 20 and 30 meter six-minute walk tests among middle-aged and older adults. Physiother Theory Pract 2021; 7: 817–825. [DOI] [PubMed] [Google Scholar]
- 6.Von Elm E, Altman DG, Egger M, et al. ; STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med 2007; 147: 573–577. [DOI] [PubMed] [Google Scholar]
- 7.Thomas S, Rich MW.Epidemiology, pathophysiology, and prognosis of heart failure in the elderly. Heart Fail Clin 2007; 3: 381–387. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Heinicke G, Clay R, DeCato TW.Six-Minute-Walk Testing. Am J Respir Crit Care Med 2021; 204: P5–P6. [DOI] [PubMed] [Google Scholar]
- 9.Ponikowski P, Voors AA, Anker SD, et al. ; ESC Scientific Document Group. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur. Heart J 2016; 37: 2129–2200. [DOI] [PubMed] [Google Scholar]
- 10.Agarwala P, Salzmer SH.Six-minute walk test: clinical role, technique, coding, and reimbursement. Chest 2020; 157: 603–611. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Forman DE, Cannon CP, Hernandez AF, et al. ; Get With the Guidelines Steering Committee and Hospitals. Influence of age on the management of heart failure: Findings from Get with the Guidelines-Heart Failure (GWTG-HF). Am Heart J 2009; 157: 1010–1017. [DOI] [PubMed] [Google Scholar]
- 12.Ha FJ, Toukhsati SR, Cameron JD, et al. Association between the 6-Minute Walk Test and exercise confidence in patients with heart failure: A prospective observational study. Heart Lung 2018; 47: 54–60. [DOI] [PubMed] [Google Scholar]
- 13.Lainscak M, Blue L, Clark AL, et al. Self-care management of heart failure: Practical recommendations from the Patient Care Committee of the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail 2011; 13: 115–126. [DOI] [PubMed] [Google Scholar]
- 14.Schnell-Hoehn KN, Naimark BJ, Tate RB.Determinants of self-care behaviors in community-dwelling patients with heart failure. J Cardiovasc Nurs 2009; 24: 40–47. [DOI] [PubMed] [Google Scholar]
- 15.Lusardi MM, Fritz S, Middleton A, et al. Determining Risk of Falls in Community Dwelling Older Adults: A Systematic Review and Meta-analysis Using Posttest Probability. J Geriatr Phys Ther 2017; 40: 1–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Kwok BC, Pua YH, Mamun K, et al. The minimal clinically important difference of six-minute walk in Asian older adults. BMC Geriatr 2013; 13: 23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Ozcan EB, Saglam M, Vardar-Yagli N, et al. Impaired Balance and Gait Characteristics in Patients with Chronic Heart Failure. Heart Lung Circ 2022; 31: 832–840. [DOI] [PubMed] [Google Scholar]
- 18.Yasuhara S, Maekawa M, Bamba S, et al. Energy Metabolism and Nutritional Status in Hospitalized Patients with Chronic Heart Failure. Ann Nutr Metab 2020; 76: 129–139. [DOI] [PubMed] [Google Scholar]
- 19.Wleklik M, Uchmanowicz I, Jankowska-Polańska B, et al. The Role of Nutritional Status in Elderly Patients with Heart Failure. J Nutr Health Aging 2018; 22: 581–588. [DOI] [PubMed] [Google Scholar]
- 20.Brown PJ, Roose SP, Fieo R, et al. Frailty and depression in older adults: a high-risk clinical population. Am J Geriatr Psychiatry 2014; 22: 1083–1095. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Boxer R, Kleppinger A, Ahmad A, et al. The 6-minute walk is associated with frailty and predicts mortality in older adults with heart failure. Congest Heart Fai 2010; 16: 208–213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Celano CM, Villegas AC, Albanese AM, et al. Depression and Anxiety in Heart Failure: A Review. Harv Rev Psychiatry 2018; 26: 175–184. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Soysal P, Veronese N, Thompson T, et al. Relationship between depression and frailty in older adults: A systematic review and meta-analysis. Ageing Res Rev 2017; 36: 78–87. [DOI] [PubMed] [Google Scholar]
- 24.Ji L, Qiao X, Jin Y, et al. Age differences in the relationship between frailty and depression among community-dwelling older adults. Geriatr Nurs 2020; 41: 485–489. [DOI] [PubMed] [Google Scholar]
- 25.Liu Y, Meng H, Tu N, et al. The Relationship Between Health Literacy, Social Support, Depression, and Frailty Among Community-Dwelling Older Patients with Hypertension and Diabetes in China. Front Public Health 2020; 8: 280. [DOI] [PMC free article] [PubMed] [Google Scholar]