Abstract
Objective:
To determine the prevalence of sarcopenia in the pre-frail community dwelling older adults based on the Asian Workgroup for Sarcopenia (AWGS 2019) criteria. In addition, the utility of case finding using the SARC-F, SARC-CalF and calf circumference on impact of prevalence was explored.
Methods:
75 older adults ≥65 years old were recruited between October 2019 and March 2020. The algorithms of AWGS 2019 was applied retrospectively to pre-frail participants recruited for an intervention study in primary care setting. In addition to demographics, SARC-F, calf circumference (CC), muscle mass, grip strength, gait speed, 5-time chair stand timing and short physical performance battery test (SPPB) were measured, to determine sarcopenia using AWGS 2019. SARC-CalF was determined using SARC-F and CC.
Results:
The prevalence of sarcopenia based on AWGS 2019 algorithm was 16.0%, possible sarcopenia 73.3% and severe sarcopenia 12.0%. Using SARC-F for case finding reduced the overall prevalence of sarcopenia to 4.0%, possible sarcopenia to 12.0% and severe sarcopenia to 4.0%. Positive percentage agreement of case finding criteria of SARC-F, SARC-CaIF and calf circumference for sarcopenia was 33%, 42% and 58% respectively.
Conclusions:
Using the AWGS 2019 without case finding, the prevalence of sarcopenia was 16%. However, using SARC-F for case finding underestimated prevalence in this group by 75%. Utility of SARC-F for case finding in pre-frail requires further evaluation.
Keywords: Sarcopenia, Calf circumference, AWGS 2019, Case finding, Pre-frail
Introduction
Sarcopenia was first defined by Rosenberg in 1989 as age-related loss of skeletal muscle mass which subsequently evolved to low skeletal muscle mass and function, and most recently to low skeletal muscle mass, low muscle strength, and/or low physical performance by European Working Group on Sarcopenia in Older People 2 (EWGSOP2) and Asian Workgroup for Sarcopenia (AWGS 2019)[1-4]. Sarcopenia is associated with poor quality of life, depression, falls, functional decline, cognitive impairment and mortality[5-7]. The prevalence of sarcopenia varies depending on the diagnostic criteria and setting, from 5.5% to 25.7%[4,8-10]. Diagnosis and definition of sarcopenia is continuing to evolve and as yet, there is no single gold standard consensus which can used in both research and clinical environment. The most widely used definition of sarcopenia in Asia was first introduced by the Asian Working Group in 2014[11]. Following the release of EWGSOP2 in 2018 focussing on low muscle strength as key characteristic of sarcopenia, detection of low muscle quantity and quality to confirm diagnosis; and physical performance to stratify severe sarcopenia in addition to incorporating case finding[12]; the Asian Workgroup subsequently published the AWGS 2019 Consensus Update incorporating the Asian norms[4]. The objective of this cross-sectional analysis was to determine the prevalence of sarcopenia using revised AWGS guidelines in the pre-frail community dwelling older adults. In addition, the utility of proposed case-finding using SARC-F, CC and SARC-CalF in the population were also evaluated.
Methods
The algorithms of AWGS 2019 was applied retrospectively to older adults ≥65 years recruited for an ongoing intervention study in two primary care practices in Singapore between October 2019 and March 2020. Participants were pre-frail based on initial screening using the FRAIL questionnaire[13]. The exclusion criteria included known dementia, pacemaker, active cancer with/without treatment or unable to walk a distance of 100 m independently. The study protocol was approved by National Healthcare Group (NHG) Domain Specific Review Board (DSRB) and all participants sign an informed consent form. The study followed the ethical guidelines of the declaration of Helsinki.
The interview questionnaire included questions on demographics, physical and mental health including SARC-F. Muscle strength was measured using a handheld dynamometer (Jamar), taking the maximum of two trials on the dominant hand. Muscle mass was evaluated using a bioelectrical impedance (BIA) scale (Inbody S10 device) in the seated position. Appendicular skeletal muscle mass (ASM) was calculated by adding the lean mass of the four limbs and normalised by height by taking ASM divided by square of height in metres.
The SARC-F is a self-reported questionnaire and used as a rapid diagnostic tool for sarcopenia[14]. It consists of five questions including lifting and carrying 10 pounds, walking across a room, transferring from bed/chair, climbing a flight of 10 stairs and frequency of falls in the past one year. The scoring range from 0 to 10, with ≥4 suggesting sarcopenia.
In addition to SARC-F, SARC-F with calf-circumference (SARC-CalF) or calf circumference (CC) alone are recommended tools for case finding tool in sarcopenia[4,15,16]. CC was measured at the widest girth of the calf using an inelastic measuring tape with the participants seated with soles entirely in contact with the floor. As recommended by AWGS 19, CC <34 cm for men and <33 cm for women or SARC-CalF ≥11 was used for case finding for sarcopenia.
Based on AWGS 2019, “possible sarcopenia “ was defined as either low muscle strength or low physical performance, “sarcopenia” as low muscle mass with either low muscle strength or low physical performance and “severe sarcopenia” as presence of low muscle mass, low muscle strength and low physical performance.
Characteristics of participants with and without sarcopenia were compared using Mann-Whitney U Test and Chi-Square Test. Statistical analyses were conducted with the use of SPSS Version 25 and p-values less than 0.05 were considered statistically significant.
Results
Complete data was available for 75 participants. The prevalence of sarcopenia amongst the pre-frail older adults in primary care was 16.0%, possible sarcopenia 73.3% and severe sarcopenia 12% without case finding. The mean age of the participants was 73±6 years and slightly more than half were females (56.0%) (Table 1). The population was predominantly Chinese (80.0%), and the prevalence of sarcopenia was highest amongst the Indian followed by Malay ethnic group. There were significant differences between the sarcopenic and non-sarcopenic for SARC-F, SARC-CalF scores, calf-circumference and height adjusted appendicular muscle mass. While non-significant, sarcopenic participants had lower BMI, lower grip strength, slower gait speed, and longer 5-chair stand time.
Table 1.
Characteristics of participants.
Variable | All n=75 | Possible cases n=12 (16.0%) | No Sarcopenia n=63 (84.0%) | Sarcopenia n=10 (73.3%) | p-valuea |
---|---|---|---|---|---|
Age, years | 73 ± 6 | 74 ± 6 | 72 ± 6 | 75 ± 6 | 0.108 |
Gender | 0.859 | ||||
Female | 42 (56.0) | 32 (58.2) | 35 (55.6) | 7 (58.3) | |
Male | 33 (44.0) | 23 (41.8) | 28 (44.4) | 5 (41.7) | |
Ethnicity | 0.306 | ||||
Chinese | 60 (80.0) | 44 (80.0) | 53 (88.3)b | 7 (11.7) | |
Malay | 8 (10.7) | 5 (9.1) | 6 (75.0) | 2 (25.0) | |
Indian | 7 (9.3) | 6 (10.9) | 4 (57.1) | 3 (42.9) | |
BMI, kg/m2 | 25.5 ± 4.5 | 25.6 ± 4.8 | 25.7 ± 4.2 | 24.0 ± 5.9 | 0.066 |
Hand grip strength, kg | 22.4 ± 7.2 | 20.8 ± 6.3 | 23.1 ± 7.4 | 18.9 ± 4.8 | 0.066 |
Gait speed (mean), m/s | 0.9 ± 0.3 | 0.9 ± 0.3 | 1.0 ± 0.3 | 0.8 ± 0.2 | 0.056 |
5-Chair stand time (mean), s | 13.7 ± 4.8 | 15.3 ± 4.8 | 13.1 ± 3.5 | 17.0 ± 8.6 | 0.272 |
SPPB (mean) | 9.4 ± 2.2 | 8.8 ± 2.0 | 9.7 ± 2.0 | 8.3 ± 2.5 | 0.084 |
Height adjusted appendicular muscle mass (ASM), kg/m2 | 7.6 ± 2.3 | 7.7 ± 2.4 | 8.0 ± 2.3 | 5.8 ± 0.9 | <0.01 |
BMI adjusted ASM, kg/BMI | 0.76 ± 0.31 | 0.77 ± 0.35 | 0.80 ± 0.32 | 0.57 ± 0.15 | <0.01 |
SARC-F, (mean) | 1.5 ± 1.8 | 1.7 ± 1.8 | 1.3 ± 1.7 | 2.5 ± 1.9 | 0.029 |
Calf circumference (mean), cm | 35.6 ± 3.8 | 35.6 ± 3.9 | 36.0 ± 3.8 | 33.7 ± 2.8 | 0.026 |
SARC-CalF (mean) | 4.2 ± 4.7 | 4.5 ± 4.7 | 3.4 ± 4.2 | 8.3 ± 5.2 | <0.01 |
n (%) unless otherwise stated; mean ± SD;
Significant difference between those with and without sarcopenia;
Prevalence within the same ethnicity for sarcopenia and no sarcopenia.
As our study population were community dwelling ambulant older adults from primary care setting screened to be pre-frail with no prior complaints of functional decline, case finding using SARC-F would have reduced the prevalence of sarcopenia to 4.0%, possible sarcopenia to 12.0% and severe sarcopenia to 4.0%. The positive percentage agreement of case finding criteria of SARC-F, SARC-CaIF and CC was 33%, 42% and 58% for sarcopenia and 33%, 33% and 44% for severe sarcopenia respectively (Table 2).
Table 2.
Positive and negative agreement of case finding criteria in AWGS 2019.
POSSIBLE CASES n=55 (73.3%) | ALL SARCOPENIC CASES n=12 (16.0%) | SEVERE SARCOPENIC CASES n=9 (12.0%) | |||||
---|---|---|---|---|---|---|---|
Assessments | Prevalencea (%) | Positive percentage agreement (%) | Negative percentage agreement (%) | Positive percentage agreement (%) | Negative percentage agreement (%) | Positive percentage agreement (%) | Negative percentage agreement (%) |
SARC-F (≥4 points) | 33.3 | 16 | 85 | 33 | 87 | 33 | 86 |
Calf-circumference (Male <34cm; Female <33cm) | 58.3 | 28 | 75 | 58 | 79 | 44 | 75 |
SARC-calF (≥11 points) | 41.7 | 17 | 90 | 42 | 90 | 33 | 88 |
Prevalence amongst those diagnosed with sarcopenia.
Discussion
The prevalence of sarcopenia in our pre-frail participants was 16.0% which is similar if not slightly higher than usual prevalence amongst many Asian countries[10]. The overall prevalence of pre-frail older adult in Singapore is 37% and pre-frail are more likely to have sarcopenia than non-frail[17-19].
It is well known that sarcopenia is under-diagnosed and poorly managed, and applying the case finding approach using SARC-F will fail to identify sarcopenia in up to 75% of pre-frail older adults. Using SARC-F as a screening tool has a low sensitivity and high specificity, and this findings have been replicated in other studies using the EWGSOP2 algorithm with similar case finding approaches which may not necessarily be restricted to high prevalence settings[20-23]. The addition of calf circumference to SARC-F (SARC-CalF) did improve the positive agreement percentage from 33% to 42%. Studies have shown that SARC-CalF has a higher sensitivity and provides a greater diagnostic accuracy over SARC-F[24]. Among the proposed assessments for case finding, CC had the highest positive percentage agreement of 58% which was in keeping with previous studies that CC is a good estimate of appendicular skeletal muscle mass, functional status and a good indicator for sarcopenia[16,25,26]. One of the limitation of SARC-F and SARC-CalF is recall bias or due to poor judgement of their capability to execute the tasks in the SARC-F questionnaire especially for the question ‘Are you able to carry 10 pounds?’ where participants have responded to not have done so in a long time hence, response to this questions are often assumptive[27]. In addition, there would also be recall bias in cognitively impaired older adults.
The proportion of severe sarcopenia in our sarcopenic participants was 75% which is rather high but similar to EWGSOP2[20]. In many previous studies, severe sarcopenia has been associated with increased mortality and these older adults may benefit from immediate assessment and intervention[22].
The main limitation of our study is small sample size, however, despite that our results were reproducible with different sample sizes and our population is representative of community dwelling older adults.
Conclusions
Using AWGS 2019, the prevalence of sarcopenia in pre-frail community-dwelling older adults was found to be 16.0%. However, using SARC-F for case finding significantly underestimated prevalence in this group. It is not known to what extent will the AWGS 2019 with/without case finding will be useful in predicting adverse outcomes in these individuals. The benefit of the new guideline is seen in the identification of possible sarcopenia where early identification with recommended targeted intervention may improve muscle strength and/or performance. Utility of SARC-F for case finding in pre-frail requires further evaluation.
Authors’ contribution
RM: Study concept and design. LJY and NAL: Acquisition of data. RM and LJY: Analysis and Interpretation of data. RM, LJY and NAL: Drafting of the manuscript. RM: critical revision of the manuscript.
Acknowledgement
We thank Dr Richard Hui, Dr Kwek Sing Cheer, doctors, nurses and care-coordinators at the polyclinics for assisting in the recruitment of the participants. Also, we thank Jerome Derrick and Zhang Jinming for the collection of data. This study is funded by Ministry of Health under the Healthy Ageing Innovation Grant (Award No.: MOH/NIC/HAIG02/2017).
Footnotes
Edited by: Yannis Dionyssiotis
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