Abstract
Context.
Several studies have addressed the impact of sarcopenia on various health outcomes. As the most critical issue is the early identification of individuals, a short screening tool may help clinicians to simply test for sarcopenia and start early management of the disease. Recently, a simple questionnaire, Sarc-F was provided that may adequately realize this aim.
Subjects and Methods.
To validate the questionnaire we translated the original Sarc-F according to the recommended methodology. A total of 80 people, aged 65+ were evaluated for sarcopenia. Muscle mass, strength, and physical performance were measured. Volunteers completed the Sarc-F as well as other two questionnaires. Discriminative power, reliability, construct validity analyses, specificity, sensitivity, negative and positive predictive value evaluations were made.
Results.
A good discriminative power and internal consistency were found. With the functional sarcopenia diagnostic criteria the test demonstrates a high specificity (84%). The positive and negative predictive values were: 78% and 77%. Using the more conservative diagnostic criteria the negative predictive value was: 85.4%, sufficient to rule out those not at risk of having sarcopenia and eliminate the need for further investigations.
Conclusions.
A valid Romanian Sarc-F questionnaire is now available to simply detect patients at risk/no risk of sarcopenia.
Keywords: screening, sarcopenia, muscle mass, older adults
INTRODUCTION
Independent ageing requires preserved function of the neuromuscular system. Sarcopenia can be one reason for not achieving independent ageing (1). The age-associated loss of skeletal muscle, termed sarcopenia, is characterized by a progressive and generalized muscle disorder associated with increased likelihood of adverse outcomes, including falls, fractures, physical disability and mortality (2). The loss of muscle mass, strength and physical performance can seriously compromise an individual’s state of health and reduce quality of life.
However, there are several different consensus definitions, algorithms and criteria to diagnose sarcopenia, they all agree in including the following parameters: the muscle strength, the physical performance and the muscle mass (3-12).
The European Working Group on Sarcopenia in Older People (EWGSOP) updated in 2018 their original definition published in 2010 to reflect scientific evidence built over the last decade, bringing to the forefront the muscle strength, as it is recognized that strength is better than mass in predicting adverse outcomes (2). Detection of low physical performance predicts adverse outcomes, so such measures are used to identify the severity of sarcopenia. The new EWGSOP definition uses low muscle strength as the primary parameter of sarcopenia. When low muscle strength, low muscle quantity or quality and low performance are all detected, sarcopenia is considered severe (2).
There are various validated tools available in the practice to detect sarcopenia. Skeletal muscle strength can be tested by measuring handgrip strength, physical performance is estimated with gait speed (4 or 400 m), timed-up-and-go test (TUG) or the Short Physical Performance Battery/SPPB). Muscle quantity can be reported as total body skeletal muscle mass (SMM), as appendicular skeletal muscle mass (ASMM), or as muscle cross-sectional area of specific muscle groups or body locations (2).
The cut-off values for each component to define sarcopenia range widely according to the different definitions and working groups (2, 5-7,13). The EWGSOP uses the following thresholds to differentiate sarcopenic patients: grip strength <27 and <16 kg; >15s for five chair rises; ASM <20 and 15 kg for males respectively for females (2).
However, magnetic resonance imaging (MRI) and computed tomography (CT) are mainly preferred in research studies, in clinical practice Dual-energy X ray absorptiometry (DXA) or Bioelectrical Impedance Analysis (BIA) are more often used. BIA, which calculates the muscle mass and fat mass based on different conduction of current through tissues, is low cost and simple to use (14). While these special medical devices (MRI, CT, DXA or BIA) are required for the traditional diagnosis of sarcopenia, the need for validated, simple tools to rapidly screen sarcopenia have emerged.
Sarcopenia seemed to be definable by easy functional questions too; this led to the concept that a simple questionnaire could be developed to diagnose sarcopenia and obviate the need for the measurement of muscle mass. As a result, the SARC-F, a 5 item- quick self-report sarcopenia screening tool has been developed, assessing an individual’s muscular strength, ability to walk, rise from a chair and climb stairs and fall status (11).
There are 5 SARC-F components: Strength, Assistance with walking, Rise from a chair, Climb stairs and Falls (Table 1. Romanian Sarc-F). The scores range from 0 to 10, as 0 to 2 points are given for each component. A score equal to or greater than 4 is predictive of sarcopenia (10).
Table 1.
SARC-F questionnaire
| Component | Question | Scoring |
|---|---|---|
| Strength | How much difficulty do you have in lifting and carrying 10 pounds? | None = 0 Some = 1 A lot or unable = 2 |
| Assistance in walking | How much difficulty do you have walking across a room? | None = 0 Some = 1 A lot, use aids, or unable = 2 |
| Rise from a chair | How much difficulty do you have transferring from a chair or bed? | None = 0 Some = 1 A lot or unable without help = 2 |
| Climb stairs | How much difficulty do you have climbing a flight of 10 stairs? | None = 0 Some = 1 A lot or unable = 2 |
| Falls | How many times have you fallen in the past year? | None = 0 1-3 falls = 1 4 or more falls = 2 |
The translation of a standard instrument needs to be meaningful to the target population in terms of the used concepts and how they are expressed. Simply translating into another language does not ensure cultural and conceptual equivalence (15-17).
In order to have a valid accurate tool for screening sarcopenia in community-dwelling Romanian older adults, we aimed to translate the Sarc-F questionnaire into Romanian language and assess its psychometric properties as well as its value to predict or exclude sarcopenia.
MATERIALS AND METHODS
We translated the original Sarc-F questionnaire according to the recommended methodology (18). After the forward translation to Romanian language by two independent translators, a text review of the consensual version took place by a bilingual expert panel, followed by the backward translation and pre-testing of the content accuracy and clarity.
As you cannot assume that the literal-linguistic equivalency guarantees for a valid, conceptually analogue tool, a clinical validation study is needed. Therefore, we analyzed the psychometric properties (reliability and validity), as well as the specificity, sensibility, and predictive values of the translated questionnaire. We assessed the performance of the SARC-F questionnaire according to various existing definitions of sarcopenia (including the new operational definitions of sarcopenia, EWGSOP2)(2).
Study population
To validate the questionnaire we recruited a sample of 80 volunteers of both sexes from the “Kálvin János” nursing home, Târgu Mureș, Nyárádszereda nursing home from Miercurea Nirajului and the Clinical County Hospital, Târgu Mureș. Inclusion criteria were: age > 65 years, a body mass index (BMI) < 30 kg/m2. We excluded individuals with a BMI > 30 kg/ m2, active tumor, heart failure, a history of cerebrovascular accident, mental illness, inability to understand the questionnaire or other comorbidities known to have an impact on muscle mass and strength (malabsorption syndrome, Parkinson’s disease, physical disabilities). We registered the following variables: age, gender (male/female), education level (secondary school/high school/college), residence (urban/rural).
Assessment of sarcopenia
Sarcopenia was defined according to the EWGSOP-proposed definitions: low muscle mass and either low physical performance and/or low muscle strength. The revised consensus definition, EWGSOP2 used also the Probable (functional) sarcopenia notion, with regard to affected muscle performance (2,19). For skeletal muscle mass (SMM) assessment, we used bioelectrical impedance (BIA) measurements, performed with a Tanita BC-420 device. To estimate body composition, this technique evaluates the impedance (or opposition) to the flow of an electric current through the body fluids contained mainly in the lean tissue, determining the values corresponding to the quantity (20).
For hand grip strength (HGS) measurement a hand dynamometer, Sammons Preston Jamar Hydraulic device was used. The strength of each hand was twice measured. We registered the highest values.
For muscle performance evaluation, as part of the short physical performance battery (SPPB) test, patients completed the gait speed test (GS) and the five-times chair stand test (CS).
Walking speed was registered with the length of time to cross a distance of 4 m at the participant’s usual walking pace. We evaluated the ability to rise from a chair with the time taken to complete 5 getting ups from sitting position.
Values under < 0.8 m/s in gait speed, and > 15s for the chair test and <27 kg (male) / 16 kg (female) for grip strength indicated poor physical performance.
Statistical methods
Patients were divided into two groups, based on the different, but well defined definitions of the European working group (EWGSOP and EWGSOP2)(5,2).
Sarc-F questionnaire was completed by all participants. We assessed the discriminative power, the internal consistency, the presence of floor and ceiling effects of the questionnaire, as well as the sensitivity, specificity and the predictive values (positive and negative) of the Sarc-F test as a screening tool.
Discriminative power
We assumed that Sarc-F total and domain scores are higher among subjects without a diagnosis of sarcopenia compared to sarcopenics.
Internal consistency
To measure the homogeneity of the questionnaire, we used Cronbach’s alpha coefficient. Correlation of each domain with the total score was assessed using Spearman’s correlations.
Floor and ceiling effects
No more than 15% of the population should have the lowest or the highest score (21).
For determining construct validity participants were asked to complete also other two questionnaires. Good correlations are supposed to be found between the Sarc-F score and those domains of the other quality of life questionnaires which measure similar dimensions (convergent validity), while weaker correlations should be between domains supposed to assess different dimensions (divergent validity).
All analyses described above were performed using SPSS 17.0, with a level of significance of α = 0.05.
RESULTS
The English version of Sarc-F was translated into Romanian (Table 1).
There were 80 participants, 25 men and 55 women. The mean age was 71.89±9.21 years. Table 2 presents the characteristics of the patients included in the study sample.
Table 2.
Baseline characteristics of the study population
| Men (n=25) | Women (n=55) | |
|---|---|---|
| Age | 72.24 ± 8.39 | 71.69 ± 9.63 |
| Height (m) | 1.72 ± 0.07 | 1.59 ± 0.07 |
| Weight (kg) | 82.88 ± 15.41 | 70.35 ± 11.64 |
| BMI (kg/m2) | 28.06 ± 4.1 | 27.11 ± 4.19 |
| Muscle mass index | 9.89 ± 1.20 | 8.63 ± 1.69 |
| HGS (Kg) | 35.56 ± 22.59 | 21.53 ± 10.80 |
| CS | 13.40 ± 7.46 | 14.26 ± 5.85 |
| GS | 5.99 ± 3.96 | 6.64 ± 4.11 |
| Provenience | ||
| Urban | 10 | 33 |
| Rural | 15 | 22 |
| Education level | ||
| Elementary school | 4 | 14 |
| High school | 15 | 27 |
| College | 6 | 14 |
| SF-36 total score | 61.56 ± 17.17 | 61.42 ± 19.86 |
| SarQol total score | 63.29 ± 11.86 | 62.09 ± 14.67 |
| Sarc-F total score | ||
| No sarcopenia | 1.56 ± 1.97 | 3.36 ± 1.93 |
| Sarcopenia | 3.56 ± 2.4 | 4.36 ± 2.94 |
As presented in Table 3, all domains showed a significant strong or moderate correlation (Spearman’s correlations) with the total Sarc-F score ranging from 0.822, P < 0.001 (domain 1. “strength”) to r = 0.578, P < 0.001 (domain 5. “falls”).
Table 3.
Correlation of the total Sarc-F score and the individual domains of Sarc-F, SarQol and SF-36 questionnaires
| Domain | Sarc-F total score | p-value |
|---|---|---|
| Sarc-F/ D1 | 0.822 | < 0.001 |
| Sarc-F/ D2 | 0.757 | < 0.001 |
| Sarc-F/ D3 | 0.651 | < 0.001 |
| Sarc-F/ D4 | 0.739 | < 0.001 |
| Sarc-F/ D5 | 0.578 | < 0.001 |
| SarQol/ Locomotion | 0.415 | 0.005 |
| SarQol/ Functionality | 0.503 | 0.001 |
| SarQol/ Activity of daily living | 0.537 | < 0.001 |
| SarQol/Leisure activities | 0.285 | 0.02 |
| SF-36/ Physical Functioning | 0.530 | < 0.001 |
| SF-36/ Pain | 0.396 | 0.007 |
| SF-36/ Vitality | 0.269 | 0.07 |
The prevalence of sarcopenia among our study population based on the EWGSOP2 definitions (sarcopenia and functional sarcopenia, with low HGS and/or CS) are summarized according to gender in Table 4.
Table 4.
Frequency of sarcopenia determined by the Romanian SARC-F, two EWGSOP2 definitions, muscle mass, strength and performance
| Men | Women | Total | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Sarcopenia | No sarcopenia | Sarcopenia | No sarcopenia | Sarcopenia | No sarcopenia | |||||||
| N | % | N | % | N | % | N | % | N | % | N | % | |
| Sarcopenia / EWGSOP2 | ||||||||||||
| Sarc-F < 4 | 4 | 21.05 | 15 | 78.95 | 3 | 10.34 | 26 | 89.66 | 7 | 14.59 | 41 | 85.42 |
| Sarc-F ≥ 4 | 5 | 83.33 | 1 | 16.67 | 8 | 30.77 | 18 | 69.23 | 13 | 40.62 | 19 | 59.38 |
| Probable Sarcopenia / EWGSOP2 | ||||||||||||
| Sarc-F < 4 | 5 | 26.32 | 14 | 73.68 | 6 | 20.69 | 23 | 79.31 | 11 | 22.92 | 37 | 77.08 |
| Sarc-F ≥ 4 | 5 | 83.33 | 1 | 16.67 | 20 | 76.92 | 6 | 23.08 | 25 | 78.12 | 7 | 21.88 |
| Muscle mass and strength | ||||||||||||
| BIA | 13 | 54.17 | 11 | 45.83 | 13 | 23.64 | 42 | 76.36 | 26 | 32.91 | 53 | 67.09 |
| HGS | 9 | 50 | 9 | 50 | 20 | 40.82 | 29 | 59.18 | 29 | 43.28 | 38 | 56.72 |
| Muscle performance | ||||||||||||
| CS | 3 | 20 | 12 | 80 | 11 | 26.19 | 31 | 73.81 | 14 | 24.56 | 43 | 75.44 |
| GS | 6 | 40 | 9 | 60 | 25 | 58.14 | 18 | 41.86 | 31 | 53.45 | 27 | 46.55 |
The cut-off point of SARC-F for identifying sarcopenia was a total score of ≥ 4. The prevalence determined by the Sarc-F test was 40%.
The sensitivity, specificity, positive and negative predictive values (PPV, NPV) of the Romanian SARC-F questionnaire for the variate sarcopenia definitions among the whole study population are included in Table 5.
Table 5.
Sarc-F – sensitivity, specificity, positive and negative predictive value and prevalence based on different sarcopenia definitions or other criteria
| Sensitivity % | Specificity % | PPV % | NPV % | Prevalence % | |
|---|---|---|---|---|---|
| Sarcopenia (EWGSOP2) | 65 | 68.3 | 40.6 | 85.4 | 25 |
| Probable sarcopenia (EWGSOP2) | 69.4 | 84 | 78 | 77 | 45 |
| Muscle strength (HGS) | 72.4 | 78.9 | 72.4 | 78.9 | 43.2 |
| BIA | 42.8 | 61.2 | 33.3 | 70.3 | 31 |
Internal consistency
Participants with a Sarc-F score ≥ 4 also had low handgrip strength, walking speed and chair test. The internal consistency was determined by the Spearman Correlation Coefficient, which validates a very strong association between the total score of Sarc-F and the domains of “Strength” (D1-0,822), “Assistance in walking” (D2-0.757), “Climb stairs’’ (D4-0.739), and a moderate association with “Rise from a chair” (D3-0.651) and “Falls” (D5-0.578) (Table 3).
The measurement of reliability was done using Cronbach’s alpha and had a value of 0.75. A value greater than 0.70 indicates a high level of internal consistency.
Discriminative power
There was a significant difference between the total score of sarcopenic and non-sarcopenic results. Facultatively, we also compared the average scores for each domain, as shown in Table 6.
Table 6.
Sarc-F total and domain scores, difference between sarcopenic and non-sarcopenic subjects (discriminative power)
| Sarc-F | Sarcopenia (n=20) mean ± SD | No sarcopenia (n=60) mean ± SD | p- value |
|---|---|---|---|
| Total score | 4.28 ± 2.2 | 2.25 ± 1.93 | < 0.001 |
| D1 – Strength | 1.17 ± 0.74 | 0.52 ± 0.59 | < 0.001 |
| D2 – Assistance of walking | 0.58 ± 0.55 | 0.14 ± 0.35 | < 0.001 |
| D3 – Rise from a chair | 0.86 ± 0.59 | 0.45 ± 0.55 | 0.002 |
| D4 – Climb stairs | 0.97 ± 0.74 | 0.7 ± 0.63 | 0.08 |
| D5- Falls | 0.69 ± 0.71 | 0.43 ± 0.62 | 0.08 |
No floor or ceiling effects were found for the questionnaire.
Convergent and divergent validity
We compared the total score of the Sarc-F questionnaire with similar and different domains of the SarQol and the SF-36 questionnaires. Domains of Functionality, Locomotion and Activity of Daily Living of the SarQol-, as well as Functionality domain of the SF-36 questionnaire were significantly correlated with the total Sarc-F score, while low correlations were found with the different domains of the other two questionnaires: Leisure Activities domain of the SarQol and Pain and Vitality domains of the SF-36 questionnaires (Table 3).
DISCUSSION
In order to obtain an equivalent, culturally responsible Romanian language translation of the original Sarc-F questionnaire, we followed a rigorous adaptation process.
To validate the equivalent questionnaire we analyzed the psychometric properties, and calculated the specificity, sensibility, negative and positive predictive values of the test.
We found a high power to discriminate sarcopenic subjects from the non sarcopenics (Sarc-F average total score: 4.28 vs. 2.25, p<0.001), specific domains also differ D1: 1.17 vs. 0.52, p<0.001; D2: 0.58 vs. 0.14, p<0.001; D3: 0.86 vs. 0.45, p=0.002, as shown in Table 6.
There was also a good internal consistency (Cronbach’s alpha=0.75).
The construct validity analysis proved that Sarc-F questionnaire significantly correlated with similar domains linked to strength of the SarQol questionnaire, another sarcopenia specific evaluation tool, or the SF-36, short form health status survey. We can thus confirm the convergent validity of the Sarc-F questionnaire. Meanwhile, there were low correlations with other different dimensions, such as: leisure activities (0.285) or pain (0.396) of these generic questionnaires, proving a divergence with neutral parameters.
We checked correlations between the Sarc-F score, handgrip and muscle mass. A significant correlation was found with the handgrip strength, but there was no statistical significance with the muscle mass. The regression analysis also shows Sarc-F score to be predicted by the handgrip strength only. This is why we insisted to include also the functional definitions of sarcopenia in our analyses.
With the EWGSOP2-probable sarcopenia diagnostic criteria (muscle performance) the Sarc-F test demonstrates a sensitivity of 69.4% and a specificity of 84%. The positive and negative predictive values were: 78% and 77%.
Using the more conservative EWGSOP2 diagnostic criteria (muscle mass and functional performance), we found a moderate sensitivity of 65%, specificity of 68.3%, PPV (40.6%) while the negative predictive value (“rule out” test) was: 85.4%, value useful to ruling out those not at risk of having sarcopenia and eliminate the need for further investigations.
When using hand-grip strength to define sarcopenia, we obtained high values for each: sensitivity, specificity, positive and negative predictive values (Table 5).
Due to the wide range of the results found in the literature, it is difficult to compare our results with other translated versions of the Sarc-F questionnaire. The Korean frailty cohort study finds for the translated SARC-F a low sensitivity (25.3), high specificity (91.2), high NPV (94.3) and low PPV (19.5) (22). While comparing Sarc-F with a shorter - 3 items - version test, Yang et al. demonstrated a sensitivity 13.1% of the SARC-F, considered in accordance with previous studies. On the basis of a study population of 4000 participants and using the European Working Group on Sarcopenia in Older People (EWGSOP) criteria as the “gold reference,” Woo et al. reported that SARC-F had a sensitivity of 4.2% in women and 9.9% in men. Another study reported that SARC-F had a sensitivity of 35.6% and a specificity of 82.2% against the EWGSOP criteria in 487 Mexican community-dwelling older adults (23). Another accurate research work shows for the translated Turkish test a sensitivity of 25%, a specificity of 81%, a PPV of 5.1%, and a NPV of 96.4% for all definitions used to diagnose sarcopenia (24); the Spanish version has a higher sensitivity (78.3%) and a lower specificity (50.8%) (25). The authors of the German Sarc-F validation found a low sensitivity and specificity of 63% and 47% for sarcopenia while values for functional sarcopenia were: 75% sensitivity and 67% specificity (26).
Summarising the international data we can only affirm that the SARC-F questionnaire has reasonable but varying values of validity and/or reliability when used with older adults across numerous countries and languages (27).
Considering that the Sarc-F questionnaire is supposed to screen large populations, as a simple-use tool, our translation with a good specificity and negative predictive value is accurate in appreciating risks, excluding people without sarcopenia, eliminating for this category of individuals the need for more sophisticated measurements. Thus, it is an effective tool for selecting subjects who should undergo further testing for confirming a possible diagnosis of sarcopenia.
Our study has some limitations. For financial and efficiency reasons, we applied BIA to estimate skeletal muscle mass instead of the more accurate but expensive methods, like DXA, CT, MRI.
In conclusion, we have a culturally equivalent, valid, consistent and reliable Romanian questionnaire, to rapidly and inexpensively screen sarcopenia on public health or GP setting level, precisely detecting (excluding) individuals without sarcopenia. This permits us to avoid avoidable radiation, useless cost and time consuming testing.
Conflict of interest
The authors declare that they have no conflict of interest.
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