The world's older population has been growing at an increasing rate and is expected to rise from 10% in 2022 to 16% in 2050 (World Population Prospects, 2022). Advances in health sciences and improvements in living conditions have led to an increase in life expectancy. While this is a positive development, it has given rise to issues as well. Prolonged lifespan is associated with age-related diseases (Li et al, 2021). This highlights the requirement for ongoing primary care services for the elderly, including monitoring of chronic conditions and follow ups. Many health organisations promote interdisciplinary teams with the predominant participation of nurses who are responsible for clinical nursing care including assisting with procedures, screening, risk assessment and patient education (Norful et al, 2017). Community nurses could play an important role in strengthening collaboration between primary care and public health for the benefit of vulnerable populations experiencing chronic conditions (Swanson et al, 2020).
One of the diseases commonly associated with the ageing process is sarcopenia. Sarcopenia is a muscle disease prevalent among older adults. Loss of muscle strength is the key characteristic of this health condition and decreased muscle mass confirms the presence of sarcopenia. Poor physical performance is also indicative of severe sarcopenia (Cruz-Jentoft et al, 2019). Sarcopenia is associated with many adverse outcomes in the geriatric population.
Falls are considered a widely accepted consequence of sarcopenia, regardless of its definition. Other serious consequences of sarcopenia in community-dwelling older adults include increased mortality, cognitive decline, osteoporosis, fractures, functional impairment, hospitalisation, metabolic syndrome, diabetes, liver disease, hypertension and depression. However, the reported findings vary depending on the diagnostic criteria used (Yuan and Larsson, 2023).
The Strength, assistance with walking, rising from a chair, climbing stairs and falls (SARC-F) questionnaire is a simple screening tool for sarcopenia. Latest studies conclude that SARC-F, or its modified versions (such as combination with the measurement of calf circumference), demonstrated high specificity and low to moderate sensitivity for sarcopenia diagnosis (Lu et al, 2021). Therefore, SARC-F primarily has the ability to detect only severe cases of sarcopenia (Cruz-Jentoft et al, 2019). SARC-F is an easy-to-use, practical and effective screening tool for sarcopenia among older adults (Lu et al 2021).
Optimal nutritional intake and exercise training are the frontline options for improving outcomes in individuals with sarcopenia (Rolland et al, 2023). Sleep is an important factor as it affects the wellbeing and quality of everyday life (Nielson et al, 2023). Fatigue is a common symptom of sarcopenia, leading to negative health outcomes in older adults (Knoop et al, 2021).
Functionality, defined by the ability to perform activities in daily life, is an important health indicator that predicts adverse outcomes in older adults (Pashmdarfard and Azad, 2020). Nurses could help manage factors such as sleep, fatigue and functionality that are related to the risk of sarcopenia, and optimise outcomes. However, the role of nurses in identifying people at risk of sarcopenia is not fully recognised in existing literature (Pana et al, 2022).
Moreover, the relationship between lifestyle factors and sarcopenia is still being researched. The serious consequences of sarcopenia and its effect on the quality of life make it essential to examine the potential factors in daily life associated with this condition.
The authors hypothesised that recognising and managing the potential associated factors could help prevent, enable early detection, delay progression or even reverse sarcopenia in older adults. This study investigates the relationship between the risk of sarcopenia, assessed by the SARC-F questionnaire, and health indicators and daily life factors among older adults in the community in Greece.
Methods
Design and participants
This is a pilot study for an ongoing larger multicentre study, in collaboration with the Hellenic Association of Gerontology and Geriatrics (HAGG), exploring the prevalence of sarcopenia among the older population in Greece.
For the current cross-sectional study, older adults were screened from July 2020 to October 2022. The study population consisted of a convenience sample of community-dwelling older adults living in the greater Athens conurbation.
Participants were recruited either as outpatients or their companions in a General Hospital in Athens, or from community settings and organisations such as a women's association, a choral group or a church.
Inclusion and exclusion criteria
Adults aged 65 years or older, able to walk with or without any walking aid, able to communicate in the Greek language, willing to complete the survey and who provided written consent to participate were included in the current study.
Older adults with severe cognitive impairment, an implanted pacemaker or defibrillator, bedridden, having an acute or chronic health disorder preventing a response to the interview, or lacking the ability to perform the required measurements were excluded from the study.
Demographic data, chronic health disorders, prescribed medication and clinical data, such as smoking status, alcohol consumption, history of falls, physical exercise, functionality in daily life, self-reported fatigue and sleep difficulties, were considered as potential predictors of risk for sarcopenia.
Ethical approval
The study protocol was approved by the Research Ethics Committee of the Nursing Department of the National and Kapodistrian University of Athens (number protocol 316/2020) and the Scientific Council of the involved hospital. The content of this research was posted to the national archive of PhD theses in July 2023.
Data collection and study parameters
All data were collected by a trained nurse with experience in caring for the older people.
Lifestyle, sociodemographic characteristics, and health indicators
These included age, sex, annual income, educational level, smoking status, medication use, medical history and conditions, Charlson Comorbidity Index (CCI), family history of osteoporosis and fractures, alcohol, coffee and tea consumption, exercise and walk frequency. Data were collected using a structured questionnaire developed by the researchers.
Anthropometric characteristics
These were measured using specific equipment: weight using a Bioelectrical impedance analysis (BIA) device; height using a stadiometer; calf circumference, middle arm, waist and pelvis circumferences using a millimetre-graded tape. Muscle strength was assessed by grip strength, measured using a digital handgrip dynamometer. Muscle mass was measured using the BIA device. The physical performance was estimated with the 4m gait speed test.
SARC-F questionnaire
The risk of sarcopenia was assessed using the SARC-F questionnaire, which consists of 5 questions (muscle strength, assistance with walking, rise from a chair, climb stairs and falls). A total score equal to or greater than 4 is predictive of sarcopenia and adverse outcomes (Malmstrom and Morley, 2013). SARC-F was translated to and validated in Greek for this study.
Functionality
To evaluate the functional status and the independence level of the participants, the Barthel index (BI) of activities of daily living was used. The BI consists of 10 items that relate dependence/independence to the ability for personal care and mobility (Mahoney and Barthel, 1965). The total score ranges from 0 (totally dependent) to 100 (totally independent). The BI has been translated and validated in Greek (Theofanidis, 2017).
Fatigue
Participants were asked to indicate how much fatigue they felt over the last two weeks on the visual analogue scale for fatigue (VAS-F). Zero represented no fatigue at all and 10 was the worst possible fatigue one could feel (Wewers and Lowe, 1990). The participants also reported the fatigue they felt over the last two weeks responding to the Fatigue Severity Scale (FSS). This scale consists of nine statements, each scored on a 7-point Likert scale from 1 (completely disagree) to 7 (completely agree) (Krupp et al, 1989). The FSS has been translated and validated in Greek (Bakalidou et al, 2013).
Sleep difficulties
The Athens Insomnia Scale (AIS) was used to evaluate sleep quality. It consists of 8 items that examine the sleep difficulties experienced at least three times per week during the last month, excluding particular cases such as the news of a sad event. The total score of AIS ranges from 0 (absence of any sleep difficulty) to 24 (the most severe degree of insomnia) (Soldatos et al, 2000; 2003).
The AIS had been translated and validated in Greek (Soldatos et al, 2000). The participants were also asked to report the usual total sleep duration by responding to the following question: ‘During the past month, how many hours of sleep did you get at night, from the time falling asleep until opening your eyes and not sleeping again (average hours for one night)?’
Statistical analysis
Lifestyle, sociodemographic factors and anthropometric characteristics were analysed by descriptive statistics and have been presented using mean and standard deviation for continuous variables; frequency and percentage were reported for dichotomous/string variables.
The characteristics of the participants were compared according to the SARC-F questionnaire using Student's T-test or Pearson's coefficient for continuous variables with normal distribution, Mann Whitney U test or Spearman's coefficient for continuous variables with asymmetric distribution, and Pearson's Chi-square test (or Fisher's Exact test or Anova test) for categorical variables. SARC-F was considered a dichotomous variable based on ≥4 cut-off point.
The variables significantly related to the SARC-F score at a statistical significance level of 0.20 (P<0.20) were included in multivariable logistic regression analysis and the results were reported as odds ratio and 95% confidence interval (OR; 95%(space)CI). Literature suggests a threshold of 0.20 in bivariate analysis in order to include all possible independent variables that could be statistically significant in the final multivariable model.
In the multivariable logistic regression, P value<0.05 was considered statistically significant. Statistical analyses were performed with the IBM SPSS Statistics software version 28.0.
Results
Adults aged ≥55 years old (n=119) were approached to participate in a larger multicentre study conducted by HAGG. A total of 111 adults accepted the invitation (response rate=93.3%).
For the purpose of the present study, data from 100 older adults, aged ≥65 years old and living in the community, were analysed. The age range for all the participants was 65–91 years. The median age of the whole study population was 72.50±9 years old, and 59 participants (59%) were women.
The prevalence rate of sarcopenia risk based on the SARC-F was 19%—6% in men and 13% in women. The baseline characteristics of the study population are presented in Table 1.
| Characteristics | Total (n =100) | Men (n =41) | Women (n =59) | P value |
|---|---|---|---|---|
| Age, mean (SD) | 73.05 (6.73) | 74.49 (7.42%) | 72.05 (6.07) | 0.114a |
| Education level | 0.115b | |||
| Primary school | 39 (39%) | 12 (29.3%) | 27 (45.8%) | |
| High school | 28 (28%) | 10 (24.4%) | 18 (30.5%) | |
| IEK** | 14 (14%) | 9 (22%) | 5 (8.5%) | |
| University/TEI** | 18 (18%) | 10 (24.4%) | 8 (13.6%) | |
| Master/PhD | 1 (1%) | 0 (0%) | 1 (1.7%) | |
| Annual income | <0.001 b | |||
| < €8000 | 36 (36%) | 6 (14.6%) | 30 (50.8%) | |
| €8000–15 | 42 (42%) | 21 (51.2%) | 21 (35.6%) | |
| >€15 | 22 (22%) | 14 (34.1%) | 8 (13.6%) | |
| CCI, mean (SD) | 0.57 (0.29) | 0.51 (0.33) | 0.62 (0.25) | 0.122a |
| Height (m), mean (SD) | 1.63 (0.09) | 1.71 (0.06) | 1.58 (0.06) | <0.001 c |
| Weight (kg), mean (SD) | 77.17 (14.70) | 82.16 (12.69) | 73.70 (15.09) | 0.004 c |
| BMI (kg/m2), mean (SD) | 28.99 (5.23) | 28.17 (3.97) | 29.56 (5.91) | 0.375a |
| Waist circumference (cm), mean (SD) | 98.13 (13.78) | 103.17(10.30) | 94.63 (14.86) | 0.002 c |
| Pelvis circumference (cm), mean (SD) | 109.36 (13.72) | 104.59 (6.83) | 112.68 (16.18) | 0.003 a |
| Calf circumference - CC (cm), mean (SD) | 36.87 (4.15) | 36.54 (3.52) | 37.10 (4.56) | 0.765 a |
| Middle arm circumference (cm), mean (SD) | 31.25 (4.35) | 30.66 (3.77) | 31.66 (4.71) | 0.354a |
| Muscle strength (kg), mean (SD) | 26.56 (9.33) | 34.21 (8.76) | 21.24 (5.05) | <0.001 a |
| Muscle mass – ASM/ht2 (kg/m2), mean (SD) | 6.31 (1.08) | 7.00 (0.83) | 5.83 (0.97) | <0.001 c |
| Physical performance (m/s), mean (SD) | 0.89 (0.30) | 0.94 (0.34) | 0.86 (0.27) | 0.213c |
| Smoking status | 0.447b | |||
| Never smoked | 61 (61%) | 22 (53.7%) | 39 (66.1%) | |
| Current | 22 (22%) | 11 (26.8%) | 11 (18.6%) | |
| Former | 17 (17%) | 8 (19.5%) | 9 (15.3%) | |
| Number of falls in the last year | 0.206b | |||
| 0 | 75 (75%) | 31 (75,6%) | 44 (74.6%) | |
| 1 | 21 (21%) | 10 (24.4%) | 11 (18.6) | |
| 2 or more | 4 (4%) | 0 (0%) | 4 (6.8%) | |
| Fractures | 20 (20%) | 6 (14.6%) | 14 (23.7%) | 0.263b |
| Fractures among those who experienced falls | 15 (75%) | 4 (66.7%) | 11 (78.6%) | 0.613d |
| Instability (the state of feeling unstable when someone walks) | 33 (33%) | 17 (41.5%) | 16 (27.1%) | 0.134b |
| Total number of medications, mean (SD) | 3.5 (2.58) | 3.07 (1.93) | 3.80 (2.92) | 0.409a |
| Polypharmacy (≥5 drugs daily) | 23 (23%) | 6 (14.6%) | 17 (28.8%) | 0.097b |
| Daily coffee consumption (cups), mean (SD) | 1.46±0.85 | 1.41±0.77 | 1.49 (0.90) | 0.797a |
| Daily tea consumption (cups), mean years (SD) | 0.35 (0.50) | 0.34 (0.48) | 0.36 (0.52) | 0.973a |
| Alcohol consumption per week (ml) | 0.012 b | |||
| >700 or 0 | 64 (64%) | 23 (56.1%) | 41 (69.5%) | |
| 600 | 12 (12%) | 7 (17.1%) | 5 (8.5%) | |
| 500 | 1 (1%) | 0 (0%) | 1 (1.7%) | |
| 400 | 2 (2%) | 2 (4.9%) | 0 (0%) | |
| 300 | 5 (5%) | 5 (12.2%) | 0 (0%) | |
| <300 | 16 (16%) | 4 (9.8%) | 12 (20.3%) | |
| Exercise frequency | 0.557b | |||
| Never | 69 (69%) | 26 (63.4%) | 43 (72.9%) | |
| Rarely | 4 (4%) | 1 (2.4%) | 3 (5.1%) | |
| 1.2 hours/per week | 10 (10%) | 5 (12.2%) | 5 (8.5%) | |
| More than 2 hours per week | 17 (17%) | 9 (22%) | 8 (13.6%) | |
| Walking frequency | 0.416b | |||
| Never | 41 (41%) | 20 (48.8%) | 21 (35.6%) | |
| Less than 3 times per week | 8 (8%) | 3 (7.3%) | 5 (8.5%) | |
| More than 3 times per week for at least 15 minutes | 51 (51%) | 18 (43.9%) | 33 (55.9%) |
=Mann-Whitney U Test;
=Pearson's Chi-square test;
=t-Test;
=Fisher's exact test
Statistically significant differences are marked in red.
appendicular skeletal mass (ASM); body mass index (BMI); Charlson comorbidity index (CCI); standard deviation (SD); Technological and Educational Institution (TEI) IEK: vocational institution
In the bivariate analysis between independent variables and SARC-F questionnaire, a statistically significant relationship at the 0.20 level was found between SARC-F and age (0.074), annual income (0.139), CCI (0.042), physical performance (<0.001), number of medications and polypharmacy (0.044 and 0.037, respectively), number of falls (0.019), BI (<0.001), FSS (<0.001), VAS-F (<0.001), AIS (<0.001), use of sleep medication (0.031), walking frequency (0.008), tea consumption per day (0.191) and instability (<0.001).
According to the multivariable logistic regression (P value<0.05) (Table 2), the decreased performance in daily activities according to the BI, increased self-reported fatigue according to VAS-F and increased sleep difficulties according to AIS were associated with a higher likelihood of risk of sarcopenia, based on the SARC-F questionnaire. The explained variation in the dependent variable based on this model was 56.6% (Nagelkerke R Square value).
| Independent variable | Odds ratio | 95% Confidence Interval for odds ratio | P value |
|---|---|---|---|
| BI Score | 0.725 | 0.595–0.884 | 0.001 |
| VAS-F | 1.435 | 1.064–1.936 | 0.018 |
| AIS Score | 1.306 | 1.053–1.620 | 0.015 |
Note: Control group refers to the older adults with SARC-F score<4, indicating no risk of sarcopenia. Statistically significant differences at the 0.05 level are noted in red Barthel Index (BI); Visual Analogue Scale for Fatigue (VAS-F); Athens Insomnia Scale (AIS); Strength, assistance with walking, rising from a chair, climbing stairs and falls (SARC-F)
Discussion
Given the lack of evidence regarding the potential risk factors in daily life for sarcopenia in Greece, this study examined a range of lifestyle factors and their associations with sarcopenia risk in a sample of older adults. A statistically significant association was found between functional status, self-reported fatigue and sleep quality, and the risk of sarcopenia based on the SARC-F cutoff point.
Functional impair ment is a widely accepted consequence of sarcopenia (Yuan and Larsson, 2023). However, it is unclear whether functional status is a risk factor for sarcopenia. Impaired functionality presented as limited physical mobility could lead to decreased muscle function and the development of sarcopenia. According to the findings of this research, an increased BI score was associated with a reduced risk of sarcopenia based on the SARC-F questionnaire.
Similarly, dependence in instrumental activities of daily living (assessed using the Lawton IADL scale) and dependence in daily living activities (assessed using BI) appear to be independent factors for sarcopenia among community-dwelling older adults in the Eastern Black Sea region, according to the results of the SARC-F questionnaire (Sahin et al, 2022). Lawton IADL scores were also associated with SARC-F in a sample of older people in China (Cao et al, 2014).
The Katz activities of daily living (ADL) scale emerged as the strongest predictor for sarcopenia risk in pre-frail community-dwelling older males in Saudi Arabia (Alodhayani, 2021).
Interestingly, the modified BI was not significantly associated with SARC-F among older outpatients, although robust individuals were generally more independent (Tan et al, 2017).
Although fatigue is one of the most prevalent complaints among community-dwelling older adults (Knoop et al, 2021) and sarcopenia is an age-related disease, evidence about the relationship between self-reported fatigue and sarcopenia is lacking. Perceived fatigue could explain decreased physical activity, which is an important risk factor for sarcopenia. Fatigue determined by the Fatigue Impact Scale was related to sarcopenia among older outpatients (Suzan et al, 2022).
The relationship between the risk for sarcopenia, defined by SARC-F, and fatigue in the older population is even less examined in literature. However, many researchers support the relationship between SARC-F and self-reported fatigue in individuals diagnosed with another disease eg cancer (Barreto et al, 2022) and stroke (Su et al, 2021).
The fact that in the present study, VAS-F rather than FSS was related to SARC-F may be explained by the widely accepted usefulness of FSS in patients other than older adults who have chronic diseases such as multiple sclerosis (Krupp et al, 1989). However, both VAS-F and FSS presented good psychometric properties in various conditions among older people (Knoop et al, 2023).
In the present study, a strong association emerged between poor sleep quality and increased risk for sarcopenia. Poor sleep quality presented as insomnia or fragmented sleep can lead to long hours of bed rest and reduced motivation for activities the next day, thus contributing to reduced muscle function and the development of sarcopenia. The study's findings align with those from other studies, although the relationship between SARC-F and sleep quality is not adequately documented in literature.
A statistically significant association between sarcopenia risk and sleep quality was found in older patients with diabetes (Ida et al, 2019) and older outpatients in physical medicine and rehabilitation clinics (Tuna et al, 2019). It is already well-recognised that sleep duration has an impact on sarcopenia prevalence, although the results on whether short or long sleep duration is a risk factor for sarcopenia are inconsistent (Pourmotabbed et al, 2020). In this study, sleep duration was not associated with the SARC-F questionnaire. This finding is also supported by a study among older adults in Taiwan (Tzeng et al, 2020). A positive association was found between SARC-F and wake time, but not with bedtime and midsleep time, among community-dwelling older adults (Huang et al, 2022). Therefore, the relationship between sleep duration and risk for sarcopenia remains controversial and merits exploration.
To the authors' knowledge, the existing evidence on the relationship between sarcopenia risk and related factors in daily life is limited. Therefore, the current study attempted to examine possible modifiable factors in daily life that are related to the SARC-F questionnaire among community-dwelling older adults. By recognising these factors, providing appropriate recommendations and implementing preventive strategies such as programmes for increasing physical activity and protein intake, community nurses may have the potential to avoid or delay the development of sarcopenia.
Moreover, recognition of these factors may aid in the early detection and management of sarcopenia, minimising adverse outcomes. Nurses play a key role in today's healthcare workforce, particularly in health promotion and prevention. Their close patient interactions, passion for promoting health and strong expertise and skills make them well-suited for this responsibility. This distinction is particularly evident in community and public health nursing, as well as among nurses in community-based environments (Iriarte-Roteta et al, 2020).
Limitations
The small sample size meant that the results could not be generalised to all older adults in Greece. Moreover, the study used a cross-sectional design, which meant a causal relationship could not be established. Longitudinal studies could contribute significant data on this field. Fatigue and sleep difficulties were self-reported, based on the participants' subjective perception.
Implications for practice
Impaired functionality, self-reported fatigue and sleep difficulties are related to sarcopenia risk among older adults. When older adults experience functional limitations, fatigue and poor sleep, their muscle health may deteriorate more rapidly, increasing the likelihood of developing sarcopenia. By using reliable and valid tools, community nurses could assess these factors and modify them in order to minimise the risk for sarcopenia or even delay or reverse this condition. This could contribute to reducing the adverse effects of sarcopenia and improving the quality of life of older people living in the community. These assessments can provide vital insights into the risk of sarcopenia and guide targeted interventions.
Conclusions
Everyday factors like functional status, self-reported fatigue and sleep difficulties may help predict the risk of sarcopenia in older adults living in the community, as assessed by the SARC-F questionnaire. Community nurses can play a key role in sarcopenia screening by identifying these factors in daily life and taking the steps to prevent them from exacerbating the condition.
Future research involving larger populations of older adults may help to better understand the potential connections between sarcopenia risk and factors such as demographic characteristics, chronic health conditions, prescribed medications and lifestyle habits. By expanding the scope of these studies, healthcare professionals can get advanced insight into how various elements interact to influence sarcopenia risk in the community.
Additionally, future studies would benefit from focusing on establishing causality between these everyday factors and sarcopenia. This will clarify the mechanisms that drive sarcopenia and pave the way for more targeted interventions. Research could also explore how specific chronic diseases or medications contribute to muscle loss in older adults and how it can be avoided.
Lifestyle changes, such as increasing physical activity and improving nutrition, may also prevent or slow the progression of sarcopenia. This area presents a significant opportunity for further research, as a deeper understanding of the most effective lifestyle interventions could help nurses develop targeted strategies for managing and reversing sarcopenia, ultimately enhancing quality of life for their patients.