SPPB reference values and performance in assessing sarcopenia in community-dwelling Singaporeans – Yishun Study

doi:10.21203/rs.3.rs-242994/v1

Download PDF

Research Article

SPPB reference values and performance in assessing sarcopenia in community-dwelling Singaporeans – Yishun Study

https://doi.org/10.21203/rs.3.rs-242994/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background: The Short Physical Performance Battery (SPPB) is an established test of physical performance. We provide reference values for SPPB and determine SPPB performance and cut-offs in assessing sarcopenia for Asian community-dwelling older adults.

Methods: 538 (57.8% women) community-dwelling adults aged 21–90 years were recruited. SPPB and its subtest scores and timings (8ft gait speed (GS), five-times repeated chair sit-to-stand (STS) and balance) were determined. Appendicular lean mass divided by height-squared, muscle strength (handgrip) and physical performance (6m GS, STS and SPPB) were assessed to define sarcopenia for various Asian criteria. Area under the ROC curve (AUC) was used to assess performance of SPPB and subtests in discriminating sarcopenia. Optimal SPPB and GS subtest cut-offs for each sarcopenia criterion were determined by maximizing sensitivity and specificity.

Results: The mean SPPB score was 11.6(SD 1.1) in men and 11.5(SD1.2) in women. Majority of participants(≥50%) aged 21–80 years achieved the maximum SPPB score. SPPB total and subtest scores generally decreased with age (all p<0.001), but did not differ between sex. SPPB was limited in assessing sarcopenia (AUC 0.56–0.64) but had moderate-to-excellent performance in assessing severe sarcopenia (AUC 0.69–0.98), with optimal cut-off of ≤11points. SPPB GS subtest had moderate-to-excellent performance in assessing sarcopenia (AUC 0.62–0.72) and severe sarcopenia (AUC 0.81–0.95). The optimal GS cut-off for sarcopenia was 1.0m/s.

Conclusions: Population-specific normative SPPB values are important for use in diagnostic criteria and to interpret results of studies evaluating and establishing appropriate treatment goals. Performance on the SPPB should be reported in terms of the total sum score and registered time to complete the repeated-chair STS and 8-ft walk tests. An SPPB cut-off of ≤11points was optimal in assessing sarcopenia. GS subtest could be an independent criterion for discriminating sarcopenia in community-dwelling older adults.

Geriatrics & Gerontology

Short Physical Performance Battery

Older adults

Gait speed

Cut-off

Sit-to-stand

SPPB subtest

Physical function is an important marker for health especially in older adults. Poorer physical function is associated with poorer life quality and adverse health outcomes including cognitive impairment, institutionalization and mortality (1). Given the huge burden associated with age-related functional decline, early detection and intervention are important in mitigating poor physical function in community-dwelling adults, so as to delay functional disability and dependence (2).

The short physical performance battery (SPPB) is a valid and reliable measure of physical function in community and clinical settings (3-6). SPPB consists of three timed components (balance, five-times repeated chair sit-to-stand (STS) and usual-pace walk) which measure balance, lower body muscle strength and mobility (7). Lower SPPB scores have been shown to predict lower quality of life, loss in mobility, disability and mortality (6). Thus, SPPB could be useful for early stratification of community-dwelling individuals at risk of functional disability, as it requires minimal time, expertise and equipment to administer (8).

SPPB has also been used as a criterion of physical performance to define sarcopenia, which is the progressive loss of muscle mass, strength and function with age (9). Sarcopenia is associated with adverse health outcomes, such as frailty, hospitalization and mortality (9). Several definitions and cut-offs exist for the diagnosis of sarcopenia, including the European Working Group on Sarcopenia in Older People (EWGSOP) and Asian Working Group on Sarcopenia (AWGS) (10-12). Recently, the AWGS proposed new cut-offs for sarcopenia (AWGS19) (11), resulting in variations in sarcopenia prevalence observed (13). These different definitions and cut-offs for sarcopenia could affect diagnosis and management of sarcopenia in at-risk older adults. Additionally, the recommended diagnosis of sarcopenia requires costly equipment and trained individuals to administer, which might not be ideal for population-level screening of sarcopenia. Due to the increasing prevalence of sarcopenia with an ageing population, simple markers to assess sarcopenia (e.g., SPPB) can be useful towards wider detection and management of the condition.

Since genetic, lifestyle and socioeconomic factors could affect physical performance, population-specific reference values are needed to provide meaningful interpretation and comparisons of physical function (14-16). Therefore, the aim of this study was to provide sex- and age-specific reference values for SPPB in community-dwelling Singaporean adults aged ≥21 years. This study also determined the optimal cut-offs and performance of SPPB and individual subtests in assessing sarcopenia according to various AWGS19 definitions.

Participants

Participants were recruited from the Yishun Study (13). Briefly, community-dwelling adults aged 21 years and above who were independent in performing activities of daily living, had <5 poorly-controlled comorbidities, and no neuromuscular or cognitive disorders were recruited. Random sampling methodology was used to obtain a representative sample of approximately 300 male and 300 female participants, filling quotas of 20–40 participants in each sex and age group (i.e., 10-year age groups between 21–60 years old and 5-year age groups after 60 years). Ethics approval was obtained from the National Healthcare Group DSRB (2017/00212), in accordance with the relevant guidelines and regulations by the Declaration of Helsinki and the ethical principles in the Belmont Report. All participants gave written informed consent to participate in the study.

Assessments

Body weight and height were measured using an electronic scale and stadiometer respectively (SECA, Hamburg, Germany). Body mass index was calculated as body weight (kg) divided by height (m) squared. Participants declared their education level and medical conditions and comorbidities.

Handgrip strength was measured using the Jamar Plus+ Digital Hand Dynamometer (Patterson Medical, Cedarburg, WI). Participants were seated with arms in 90-degree abduction. The higher reading of two alternating trials per arm with 30s rest intervals was reported.

Usual gait speed (GS) was assessed using a 6m GAITRite Walkway (CIR Systems Inc, Sparta, NJ) with 2m lead in and out phase. Participants performed three trials and the average timing was recorded.

Body composition was determined using dual x-ray absorptiometry (Discovery WI, Hologic Inc, Marlborough, MA). Appendicular lean mass (ALM) was defined as the sum of lean mass in the upper and lower limbs. ALM corrected for height (ALM/h²) was calculated as ALM (kg) divided by height (m) squared.

SPPB

The SPPB assesses lower limb function, including balance, strength and mobility. SPPB consists of 3 subtests (i.e., balance, GS and STS time) (7, 17). The balance subtest composed of 3 parts with progressive difficulty, including unaided feet-together stand, semi-tandem stand and full-tandem stand. Participants were timed until they moved or 10s elapsed time. GS was assessed by participants walking 8ft at their usual pace, with a moving start. The average timing was recorded over two trials. To assess STS time, participants folded their arms across their chest and performed five chair stands as quickly as possible. Each of the 3 subtests was scored from 0–4 and the total score was the sum of 3 subtests, ranging from 0–12. Higher SPPB scores indicated better physical function(7).

Sarcopenia definitions

Sarcopenia was classified according to AWGS19 definitions in participants aged ≥60 years(11). Low muscle mass was defined as ALM/h² <7.0 and <5.4kg/m², and low muscle strength as handgrip strength <28 and <18kg, in men and women respectively. Poor physical performance was defined as GS (distance of 6m) <1.0m/s, STS timing of ≥12s or SPPB total score of ≤9. Participants were classified as sarcopenic according to 3 different AWGS19 physical performance criteria, based on cut-off fulfilment for low muscle mass (ALM/h²), and low muscle strength (handgrip) or poor physical performance (low GS, STS or SPPB). Participants with low muscle mass, strength and poor physical performance were classified as having severe sarcopenia.

Statistical analysis

All statistical analyses were performed using R version 3.6.2 (R Foundation for statistical computing, Vienna, Austria). Numerical variables are presented as mean (standard deviation, SD) in text and figures unless otherwise stated. Participant characteristics were analyzed using two-way ANOVA to assess potential differences between sex and age groups. Sex differences in SPPB subtests within each age group were evaluated using T-test. The performance of SPPB and individual subtests (STS and GS) in assessing sarcopenia and severe sarcopenia among a subset of older adults aged ≥60 years were determined by calculating the area under the receiver operating characteristics curve (AUC), for each AWGS19 sarcopenia definition in men and women. AUC of 0.7–0.8 and >0.8 were considered acceptable and excellent respectively(18). For each AWGS19 sarcopenia criterion, optimal cut-offs for SPPB score and GS subtest were determined by the Youden index (19). The sensitivity and specificity for each optimal cut-off value and corresponding 95% confidence intervals were reported. Age- and sex-specific smoothed centile curves for GS and STS were generated using standard analytical Lambda Mu Sigma (LMS) method with LMS ChartMakerPro v2.54 (The Institute of Health, London, United Kingdom) (4, 20-22). A value of p<0.05 was considered statistically significant.

Participant characteristics

A total of 538 participants (57.8% women) with a mean age of 59 years (SD 19 years, range 21–90 years) were included in the analysis. Participant demographics such as age, education level and anthropometric data are summarised in Table 1. Regardless of sex, 6m GS generally decreased with age (Table 1, p<0.001). Handgrip strength and ALM/h² decreased with age and were 53% and 27% higher on average in males than in females, respectively (Table 1, all p<0.001).

SPPB

The mean total SPPB score was approximately 12 points (maximum score) until ages 66–70 in men and 71–75 in women (Table 1). Apart from those aged >80 years, ≥50% of men and women in all age groups achieved the maximum SPPB score (Table 1).

SPPB total and subtest scores generally decreased with age (all p<0.001) but did not differ between sex (SPPB p=0.706;STS p=0.798;GS p=0.737;balance p=0.710) (Table 1). Individual SPPB subtest scores were also approximately 4 points (maximum score) until age 76–80 in both men and women (Table 1). The age-related decline in SPPB GS was apparent above ages ~70 and ~75 years in men and women respectively, with men showing a steeper decline in GS than women (Fig S1A). SPPB GS was generally 5% higher in men than women (Table 2, p=0.0171). Specifically, SPPB GS was 12% higher in men than in women aged 51–60 years (Table 2, p=0.0132). Compared with men, women had poorer performance in STS time until age ~70 years, while men performed worse after ~70 years (Fig S1B). STS time was 15% lower in men than in women aged 61–65 years (Table 2, p=0.029).

Sex- and age-specific percentile reference values for SPPB subtests GS and STS are presented in Supplementary Table S1.

Characteristics of participants ≥60 years with sarcopenia and severe sarcopenia

A total of 303 participants (55% women) aged ≥60 years were analysed separately to determine the ability of SPPB in assessing sarcopenia in our population. Sarcopenia prevalence ranged from 21–25% in males and 17–25% in females, with the highest prevalence evident in STS criteria in men and GS criteria in women (Table 3). Prevalence for sarcopenia was lowest in GS criteria in men and STS criteria in women. Prevalence of severe sarcopenia in the community ranged from 6–20% in men and 1–14% in women, with the highest prevalence evident in GS criteria and lowest prevalence in SPPB criteria in both sexes (Table 3).

Baseline characteristics of participants with sarcopenia and severe sarcopenia, classified according to 3 different AWGS19 criteria, are presented in Supplementary Table S2.

AUCs for sarcopenia and severe sarcopenia with SPPB and subtests

SPPB had limited ability in assessing sarcopenia according to different AWGS19 definitions, with AUC ranging from 0.46–0.58 in males (Fig 1A–C) and 0.46–0.64 in females (Fig 1D–F). SPPB performed the best using STS and SPPB as sarcopenia criteria in men and women respectively (Fig 1B&F). SPPB had the worst performance for assessing sarcopenia based on GS criteria in men and women (Fig 1A&D).

GS subtest had moderate performance in assessing sarcopenia, with AUC ranging from 0.65–0.72 in men and 0.62–0.67 in women, depending on AWGS19 criteria (Fig 1). GS subtest performed the best for SPPB criteria (Fig 1C&F) and worst for GS criteria (Fig 1A&D) in both men and women. STS subtest was not useful in assessing sarcopenia, with AUC ranging from 0.46–0.57 in men and 0.45–0.53 in women, depending on definitions (Fig 1).

In both sexes, SPPB had excellent ability in discriminating severe sarcopenia based on AWGS19 STS and SPPB definitions (AUC 0.86–0.98) and moderate performance for AWGS19 GS criteria (AUC 0.69–0.75) (Fig 2). GS subtest had excellent performance in assessing severe sarcopenia for all criteria (AUC 0.81–0.95, Fig 2A–D&F), except for STS criteria in women (AUC 0.73, Fig 2E). STS subtest had excellent ability in assessing severe sarcopenia for AWGS19 STS and SPPB definitions (AUC 0.86–0.96, Fig 2B–C&E–F) but was less useful in assessing severe sarcopenia for AWGS19 GS criteria (AUC 0.56–0.72, Fig 2A&D).

Performance of SPPB and GS cut-offs in assessing sarcopenia

The most commonly observed SPPB cut-offs for sarcopenia was ≤11 in men (sensitivity 42–44%, specificity 70–71%) and <10 (sensitivity 19–29%, specificity 82–84%) in women. SPPB cut-off of ≤11 points had the best sensitivity (44% and 58%) and specificity (71% and 69%) for STS sarcopenia criteria in men and SPPB sarcopenia criteria in women respectively (Table 3). For severe sarcopenia, the most commonly observed SPPB cut-off was ≤11 in both men and women (Table 3).

The most frequent GS cut-off for sarcopenia was ≤1.0 m/s in both men (sensitivity 68–70%, specificity 72%) and women (sensitivity 57–64%, specificity 68–71%) (Table 3). The GS cut-off at ≤1.0 m/s also gave the best sensitivity and specificity for the SPPB sarcopenia criteria in men and women (Table 3).

For severe sarcopenia, the most common GS cut-off was ≤0.9 m/s in men and ≤1.0 m/s in women (Table 3). In two women with severe sarcopenia based on SPPB criteria, SPPB and GS cut-off of ≤7 points and 0.7 m/s respectively gave the best sensitivity and specificity (Table 3).

The present study is the first to report sex-specific reference values for SPPB among community-dwelling adults aged 21–80+ years old in Singapore. Furthermore, SPPB cut-off score of ≤11 was optimal for discriminating sarcopenia in this Asian cohort of community-dwelling older adults, based on AWGS19 definitions. The study results also suggest that regardless of sex, the GS subtest could be useful in assessing sarcopenia in our population.

In our study population, more than half of participants aged 21–80 years and over a third participants aged >80 years achieved the maximum SPPB score of 12. This implies a ceiling effect for SPPB in our population, as >20% of men and women across all age groups achieved the highest possible score (23). Our findings agree with a Norwegian study which reported ceiling effects of SPPB, across age groups 40–80+ years (3). However, such a ceiling effect of SPPB was not observed in Colombian adults aged >80 years, with 19.8% of males and 7% of females with an SPPB score of 10–12 (4). Across ages 40–80+ years, mean SPPB scores in men and women were similar between our study participants and Norwegian adults (3). Compared with Colombian older adults (60–80+ years), the mean SPPB in our population was higher in both sexes (by ~2–3 points) (4). These findings suggest that SPPB scores differ by population and population-specific reference values are necessary. The presence of ceiling effects in our population support the need to report specific SPPB subtest values, rather than aggregated scores, in order to better classify physical performance in community-dwelling older adults with higher functional ability. The disparity in SPPB scores between populations could be due to socio-economic, racial or ethnicity differences. For example, poverty and lower education were associated with greater likelihood of physical functioning limitation among older adults aged >60 years (15). In older adults aged ≥65 years, non-Hispanic blacks had poorer SPPB scores and greater mobility disability than non-Hispanic whites, implying that race and genetic factors could also affect physical function (14). Therefore, it is important to report population-specific SPPB and individual subtest values in community-dwelling adults.

Sarcopenia is associated with functional decline, increased risk of frailty, falls and mortality (24), which contribute to huge personal, social and economic burdens (25). In our study, the prevalence of sarcopenia and severe sarcopenia combined was 30–41% in men and 23–40% in women, justifying the need for markers such as SPPB, to assess sarcopenia and poor physical function in a quicker and easier manner among the wider population. The present study showed that SPPB cut-point of 11 gave the optimal sensitivity (42–58%, 67–100%) and specificity (69–70%, 68–75%) for assessing sarcopenia and severe sarcopenia respectively, in community-dwelling adults ≥60 years. This cut-off was higher than the recommended SPPB cut-point of ≤8–9 suggested by EWGSOP and AWGS19 SPPB criteria for sarcopenia (10, 11, 26, 27). Other studies also reported SPPB cut-points of 7–9 being associated with higher mortality risk (28-30). Differences in study populations likely explain the disparity. Our study participants were community-dwelling older Asian adults with high functional ability, which differed from other studies involving Caucasians (29), outpatient or hospitalised individuals who might have limited physical function (28, 30). Furthermore, SPPB scores are commonly stratified into groups (0–3, 4–6, 7–9, 10–12), with a score of 10–12 as the reference (normal) group (7, 26, 31). Within individuals with SPPB score 10–12, varying physical function, risk of sarcopenia and mortality plausibly exist. Compared with individuals with maximum SPPB score, individuals with score of 11 were 1.4 times more likely to develop mobility disability in a 3-year follow-up study (32). These results suggest that a 1-point decrease in SPPB score could impact physical function (33). Therefore, in functional community-dwelling older adults, a higher SPPB cut-off can better discriminate sarcopenia.

We compared the performance of individual SPPB subtests in assessing sarcopenia. Our results demonstrate that GS, but not STS subtest, generally had better performance than total SPPB score in discriminating sarcopenia. Among our participants, GS cut-off of 1.0 m/s gave optimal sensitivity (57–70%) and specificity (68–72%) in assessing sarcopenia in men and women, and severe sarcopenia in women. GS cut-off of 0.9 m/s was optimal for severe sarcopenia in men. Our findings agree with the recommended AWGS19 cut-off for GS criteria, despite a different walk distance of 6m in AWGS19 and 8ft in the present study (11). Other studies also reported a GS of <1.0 m/s in sarcopenic older adults (34), and found greater dementia risk and poorer health outcomes in adults >80 years with GS of <1.0 m/s (35, 36). However, GS cut-off recommendations varied according to sarcopenia-associated health outcomes, such as hospitalisation, falls, mortality, cognitive impairment (37). For example, other studies including the EWGSOP recommended a GS cut-off of 0.8 m/s (10, 12, 38), due to its association with lower life expectancy (39) and disability (37). Nonetheless, GS cut-offs are dependent on health status and demographics, supporting the need for population-specific studies investigating the diagnostic value of GS in sarcopenia. Herein, we propose that the GS subtest of SPPB might be a useful, simple and accessible tool for assessing sarcopenia in functional community-dwelling older adults.

Our study used a well-established performance-based physical function assessment and recruited randomly from the general population, suggesting a good degree of generalisability. However, although associations can be drawn from the study results, the cross-sectional design does not prove causality. We are unable to assess the temporal dynamics of SPPB performance with age, nor the prognostic value of SPPB in diagnosing sarcopenia, given the lack of a longitudinal component. Furthermore, study findings cannot be generalised to people living in institutions.

Our study provides normative SPPB values in community-dwelling Singaporean adults aged 21–90 years, which is important due to differences in physiological and lifestyle factors between populations, and to provide comparative references with diseased states. Performance on the SPPB should be reported in terms of the total sum score and registered time to complete the repeated chair STS and 8-ft walk tests. We showed that a higher SPPB cut-off point of 11 had optimal performance in assessing sarcopenia. Our results suggest that GS subtest could be used as an independent criterion for assessing sarcopenia in the community.

SPPB	Short physical performance battery
STS	Sit-to-stand
EWGSOP	European Working Group on Sarcopenia in Older People
AWGS	Asian Working Group on Sarcopenia
GS	Gait speed
ALM	Appendicular lean mass
ALM/h²	Appendicular lean mass corrected for height
AUC	Area under the receiver operating characteristics curve
LMS	Lamda Mu Sigma

Ethics approval and consent to participate

Ethics approval was obtained from the National Healthcare Group DSRB (2017/00212). All participants gave written informed consent to participate in the study.

Consent for publication

Not applicable

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests

Funding

This research was supported by Geriatric Education and Research Institute (GERI) intramural funding - GERI 1609.

Authors contributions

SYL, PLC performed the data analysis, interpretation of results and wrote the manuscript. SLW, BWJP contributed to the study concept and design. BWJP, LKL, KAJ, WTS, KKC conducted the data collection. SLW, TPN contributed to the critical revision of the manuscript for important intellectual content. All authors read and approved the final manuscript.

Acknowledgements

The authors gratefully acknowledge the strong support of Prof. Pang Weng Sun in making this Yishun Study possible, and the support of Dr. Lilian Chye, Sylvia Ngu Siew Ching, Aizuriah Mohamed Ali, Mary Ng Pei Ern, Chua Xing Ying and Shermaine Thein in this study.

Zaninotto P, Batty GD, Allerhand M, Deary IJ. Cognitive function trajectories and their determinants in older people: 8 years of follow-up in the English Longitudinal Study of Ageing. J Epidemiol Community Health. 2018;72(8):685-94.
Gill TM. Assessment of function and disability in longitudinal studies. J Am Geriatr Soc. 2010;58 Suppl 2(Suppl 2):S308-12.
Bergland A, Strand BH. Norwegian reference values for the Short Physical Performance Battery (SPPB): the Tromsø Study. BMC Geriatr. 2019;19(1):216.
Ramírez-Vélez R, Pérez-Sousa MA, Venegas-Sanabria LC, Cano-Gutierrez CA, Hernández-Quiñonez PA, Rincón-Pabón D, et al. Normative Values for the Short Physical Performance Battery (SPPB) and Their Association With Anthropometric Variables in Older Colombian Adults. The SABE Study, 2015. Front Med (Lausanne). 2020;7:52.
Fisher S, Ottenbacher KJ, Goodwin JS, Graham JE, Ostir GV. Short Physical Performance Battery in hospitalized older adults. Aging Clin Exp Res. 2009;21(6):445-52.
Freiberger E, de Vreede P, Schoene D, Rydwik E, Mueller V, Frändin K, et al. Performance-based physical function in older community-dwelling persons: a systematic review of instruments. Age and Ageing. 2012;41(6):712-21.
Guralnik JM, Ferrucci L, Simonsick EM, Salive ME, Wallace RB. Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. N Engl J Med. 1995;332(9):556-61.
Minneci C, Mello AM, Mossello E, Baldasseroni S, Macchi L, Cipolletti S, et al. Comparative study of four physical performance measures as predictors of death, incident disability, and falls in unselected older persons: the insufficienza Cardiaca negli Anziani Residenti a Dicomano Study. J Am Geriatr Soc. 2015;63(1):136-41.
Liguori I, Russo G, Aran L, Bulli G, Curcio F, Della-Morte D, et al. Sarcopenia: assessment of disease burden and strategies to improve outcomes. Clin Interv Aging. 2018;13:913-27.
Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16-31.
Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J Am Med Dir Assoc. 2020;21(3):300-7.e2.
Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc. 2014;15(2):95-101.
Pang BWJ, Wee SL, Lau LK, Jabbar KA, Seah WT, Ng DHM, et al. Prevalence and Associated Factors of Sarcopenia in Singaporean Adults-The Yishun Study. J Am Med Dir Assoc. 2020.
Sun DQ, Huang J, Varadhan R, Agrawal Y. Race and fall risk: data from the National Health and Aging Trends Study (NHATS). Age and Ageing. 2016;45(1):120-7.
Louie GH, Ward MM. Socioeconomic and ethnic differences in disease burden and disparities in physical function in older adults. Am J Public Health. 2011;101(7):1322-9.
Edholm P, Nilsson A, Kadi F. Physical function in older adults: Impacts of past and present physical activity behaviors. Scand J Med Sci Sports. 2019;29(3):415-21.
Wong S. Management of Functional Decline in Older Adults: Physical Function. Journal of The Singapore Family Physician. 2011;37(2):8-17.
Mandrekar JN. Receiver Operating Characteristic Curve in Diagnostic Test Assessment. Journal of Thoracic Oncology. 2010;5(9):1315-6.
Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3(1):32-5.
Cole TJ, Green PJ. Smoothing reference centile curves: The lms method and penalized likelihood. Statistics in Medicine. 1992;11(10):1305-19.
Tudor-Locke C, Schuna JM, Jr., Barreira TV, Mire EF, Broyles ST, Katzmarzyk PT, et al. Normative steps/day values for older adults: NHANES 2005-2006. J Gerontol A Biol Sci Med Sci. 2013;68(11):1426-32.
Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, et al. 2000 CDC Growth Charts for the United States: methods and development. Vital Health Stat 11. 2002(246):1-190.
McHorney CA, Tarlov AR. Individual-patient monitoring in clinical practice: are available health status surveys adequate? Qual Life Res. 1995;4(4):293-307.
Cruz-Jentoft AJ, Sayer AA. Sarcopenia. The Lancet. 2019;393(10191):2636-46.
Mijnarends DM, Luiking YC, Halfens RJG, Evers S, Lenaerts ELA, Verlaan S, et al. Muscle, Health and Costs: A Glance at their Relationship. J Nutr Health Aging. 2018;22(7):766-73.
Pavasini R, Guralnik J, Brown JC, di Bari M, Cesari M, Landi F, et al. Short Physical Performance Battery and all-cause mortality: systematic review and meta-analysis. BMC Med. 2016;14(1):215.
Phu S, Kirk B, Bani Hassan E, Vogrin S, Zanker J, Bernardo S, et al. The diagnostic value of the Short Physical Performance Battery for sarcopenia. BMC Geriatr. 2020;20(1):242.
Chiarantini D, Volpato S, Sioulis F, Bartalucci F, Del Bianco L, Mangani I, et al. Lower extremity performance measures predict long-term prognosis in older patients hospitalized for heart failure. J Card Fail. 2010;16(5):390-5.
Ensrud KE, Lui LY, Paudel ML, Schousboe JT, Kats AM, Cauley JA, et al. Effects of Mobility and Cognition on Risk of Mortality in Women in Late Life: A Prospective Study. J Gerontol A Biol Sci Med Sci. 2016;71(6):759-65.
Arnau A, Espaulella J, Méndez T, Serrarols M, Canudas J, Formiga F, et al. Lower limb function and 10-year survival in population aged 75 years and older. Fam Pract. 2016;33(1):10-6.
Pritchard JM, Kennedy CC, Karampatos S, Ioannidis G, Misiaszek B, Marr S, et al. Measuring frailty in clinical practice: a comparison of physical frailty assessment methods in a geriatric out-patient clinic. BMC Geriatr. 2017;17(1):264.
Vasunilashorn S, Coppin AK, Patel KV, Lauretani F, Ferrucci L, Bandinelli S, et al. Use of the Short Physical Performance Battery Score to predict loss of ability to walk 400 meters: analysis from the InCHIANTI study. J Gerontol A Biol Sci Med Sci. 2009;64(2):223-9.
Perera S, Mody SH, Woodman RC, Studenski SA. Meaningful change and responsiveness in common physical performance measures in older adults. J Am Geriatr Soc. 2006;54(5):743-9.
Kim M, Won CW. Sarcopenia is associated with cognitive impairment mainly due to slow gait speed: Results from the Korean Frailty and Aging Cohort Study (KFACS). International journal of environmental research and public health. 2019;16(9):1491.
Taniguchi Y, Kitamura A, Seino S, Murayama H, Amano H, Nofuji Y, et al. Gait Performance Trajectories and Incident Disabling Dementia Among Community-Dwelling Older Japanese. Journal of the American Medical Directors Association. 2017;18(2):192.e13-.e20.
Cesari M, Kritchevsky SB, Penninx BW, Nicklas BJ, Simonsick EM, Newman AB, et al. Prognostic value of usual gait speed in well-functioning older people--results from the Health, Aging and Body Composition Study. J Am Geriatr Soc. 2005;53(10):1675-80.
Abellan van Kan G, Rolland Y, Andrieu S, Bauer J, Beauchet O, Bonnefoy M, et al. Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force. J Nutr Health Aging. 2009;13(10):881-9.
Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010;39(4):412-23.
Studenski S, Perera S, Patel K, Rosano C, Faulkner K, Inzitari M, et al. Gait speed and survival in older adults. Jama. 2011;305(1):50-8.

Table 1. Mean (SD) Participant characteristics according to age group and sex

Age Group	21-30	31-40	41-50	51-60	61-65	66-70	71-75	76-80	>80	All ages
Men
n	28	26	20	22	29	24	29	26	23	227
Age (years)	25 (3)	36 (3)	46 (3)	57 (2)	63 (1)	68 (1)	73 (2)	78 (1)	84 (2)	59 (19)
Education, n (%)
<=Primary	1 (3.5)	0 (0)	2 (10)	2 (9)	10 (34.4)	6 (25)	12 (41.3)	15 (57.6)	15 (65.2)	63 (27.7)
Secondary	2 (7.1)	3 (11.5)	4 (20)	14 (63.6)	13 (44.8)	12 (50)	14 (48.2)	6 (23)	5 (21.7)	73 (32.1)
Tertiary	13 (46.4)	11 (42.3)	3 (15)	1 (4.5)	6 (20.6)	5 (20.8)	2 (6.8)	2 (7.6)	1 (4.3)	44 (19.3)
>=Degree	6 (21.4)	10 (38.4)	7 (35)	4 (18.1)	0 (0)	0 (0)	0 (0)	3 (11.5)	2 (8.6)	32 (14)
Other qualification	6 (21.4)	2 (7.6)	4 (20)	1 (4.5)	0 (0)	1 (4.1)	1 (3.4)	0 (0)	0 (0)	15 (6.6)
Height (m)	1.73 (0.07)	1.7 (0.05)	1.68 (0.06)	1.69 (0.07)	1.66 (0.06)	1.65 (0.05)	1.65 (0.06)	1.63 (0.07)	1.62 (0.07)	1.67 (0.07)
Weight (kg)	80.4 (22.4)	81.2 (20)	76.8 (13.4)	73.5 (10.9)	66.2 (8)	65.9 (10.9)	65.4 (8.6)	63 (10.2)	61.6 (11.4)	70.3 (15.4)
BMI (kg/m²)	27.1 (8.2)	28 (6.7)	27.2 (3.8)	25.6 (3.2)	24 (2.9)	24 (3.4)	24.2 (3.2)	23.7 (3)	23.5 (4.1)	25.2 (4.9)
Gait Speed 6m (m/s)	1.14 (0.15)	1.12 (0.19)	1.14 (0.16)	1.14 (0.17)	1.12 (0.19)	1.11 (0.17)	0.99 (0.15)	0.95 (0.21)	0.83 (0.21)	1.06 (0.2)
ALM/h²	7.9 (1.4)	8.2 (1.3)	7.7 (1.1)	7.7 (1.1)	6.7 (0.7)	6.6 (0.7)	6.5 (0.7)	6.4 (0.7)	6.2 (1.0)	7.1 (1.2)
Hand Grip (kg)	42.3 (8.1)	44.6 (7.4)	42.1 (6.5)	40 (6.7)	35.5 (5.9)	32.9 (5.9)	29 (7)	28.3 (4.8)	24.4 (7.4)	35.3 (9.4)
Total SPPB Score	12 (0.2)	12 (0.2)	12 (0.2)	11.9 (0.3)	11.8 (0.6)	11.9 (0.3)	11.3 (1.1)	11.2 (1.0)	10.2 (2.3)	11.6 (1.1)
Max SPPB Score (%)	96	96	95	91	90	88	62	50	39	78
SPPB Subtest score
Balance	4 (0)	4 (0)	4 (0)	4 (0)	3.93 (0.37)	3.92 (0.28)	3.9 (0.41)	3.81 (0.49)	3.48 (0.85)	3.89 (0.41)
5x Sit-to-stand	4 (0)	4 (0)	3.95 (0.22)	3.91 (0.29)	3.9 (0.31)	3.96 (0.2)	3.48 (0.83)	3.58 (0.58)	3.3 (1.02)	3.78 (0.56)
Gait Speed 8 ft (m/s)	3.96 (0.19)	3.96 (0.2)	4 (0)	4 (0)	4 (0)	4 (0)	3.97 (0.19)	3.77 (0.59)	3.43 (0.79)	3.9 (0.38)
Women
n	32	35	39	37	31	35	31	34	37	311
Age (years)	25 (3)	36 (3)	46 (3)	55 (3)	63 (1)	68 (1)	72 (2)	78 (1)	83 (2)	58 (19)
Education, n (%)
<=Primary	0 (0)	0 (0)	3 (7.6)	9 (24.3)	11 (35.4)	19 (54.2)	17 (54.8)	23 (67.6)	29 (78.3)	111 (35.6)
Secondary	0 (0)	8 (22.8)	23 (58.9)	15 (40.5)	15 (48.3)	10 (28.5)	11 (35.4)	7 (20.5)	4 (10.8)	93 (29.9)
Tertiary	13 (40.6)	7 (20)	4 (10.2)	6 (16.2)	2 (6.4)	3 (8.5)	1 (3.2)	2 (5.8)	2 (5.4)	40 (12.8)
>=Degree	17 (53.1)	14 (40)	6 (15.3)	5 (13.5)	3 (9.6)	2 (5.7)	1 (3.2)	2 (5.8)	1 (2.7)	51 (16.3)
Other qualification	2 (6.2)	6 (17.1)	3 (7.6)	2 (5.4)	0 (0)	1 (2.8)	1 (3.2)	0 (0)	1 (2.7)	16 (5.1)
Height (m)	1.6 (0.05)	1.59 (0.05)	1.57 (0.07)	1.57 (0.06)	1.55 (0.05)	1.54 (0.05)	1.53 (0.05)	1.52 (0.05)	1.48 (0.04)	1.55 (0.06)
Weight (kg)	57.7 (11.7)	61.6 (12.3)	63.4 (11.7)	63.1 (14.1)	58.8 (8.7)	59.3 (7.6)	54 (8.4)	57.5 (8.2)	52.8 (8.6)	58.8 (10.9)
BMI (kg/m²)	22.5 (4.5)	24.5 (4.7)	25.7 (4.3)	25.6 (5.5)	24.4 (3.6)	25 (3)	23 (3.6)	25 (3.5)	24.2 (4)	24.5 (4.2)
Gait Speed 6m (m/s)	1.14 (0.18)	1.14 (0.13)	1.18 (0.2)	1.14 (0.16)	1.09 (0.14)	1.05 (0.18)	1.01 (0.14)	0.9 (0.17)	0.83 (0.16)	1.05 (0.2)
ALM/h²	5.4 (0.9)	5.8 (1.0)	6 (1.0)	6 (1.3)	5.5 (0.7)	5.6 (0.7)	5.2 (0.7)	5.4 (0.7)	5.2 (0.7)	5.6 (0.9)
Hand Grip (kg)	25.7 (4.7)	26.2 (4.6)	27.7 (5.3)	23.7 (4.1)	23.1 (3.7)	22.8 (4.5)	21 (4.1)	19.6 (4.1)	17.9 (3.4)	23.1 (5.3)
Total SPPB Score	12 (0.18)	11.9 (0.5)	12 (0)	11.8 (0.4)	11.6 (1.2)	11.6 (1.2)	11.6 (0.8)	11 (1.4)	10.4 (2.1)	11.5 (1.2)
Max SPPB Score (%)	97	94	100	84	81	83	77	50	32	77
SPPB Subtest score
Balance	4 (0)	4 (0)	4 (0)	4 (0)	3.84 (0.73)	3.97 (0.17)	3.87 (0.34)	3.79 (0.59)	3.43 (0.96)	3.88 (0.49)
5x Sit-to-stand	4 (0)	3.89 (0.53)	4 (0)	3.89 (0.31)	3.81 (0.54)	3.71 (0.71)	3.81 (0.54)	3.56 (0.82)	3.3 (0.97)	3.77 (0.62)
Gait Speed 8 ft (m/s)	3.97 (0.18)	4 (0)	4 (0)	3.95 (0.23)	3.94 (0.36)	3.91 (0.37)	3.97 (0.18)	3.65 (0.65)	3.62 (0.72)	3.89 (0.41)

Table 2. Mean (SD) of SPPB subtests (5 times repeated chair sit-to-stand time and gait speed) between men and women across different age groups.

	Men	Women	p value
Five times sit-to-stand, s
21-30	7.1 (1.1)	7.5 (1.1)	0.122
31-40	8 (1.2)	8.9 (2.8)	0.0855
41-50	7.7 (1.5)	8 (1.5)	0.502
51-60	8.4 (1.9)	9 (1.8)	0.237
61-65	8.3 (2)	9.6 (2.2)	0.029*
66-70	8.9 (1.5)	9.8 (2.8)	0.114
71-75	10.7 (4)	9.3 (2)	0.1
76-80	10.4 (2.1)	10.3 (2.7)	0.927
>80	11.4 (3.1)	10.9 (3)	0.523
All ages	9.0 (2.6)	9.3 (2.5)	0.255
Gait speed (8 ft), m/s
21-30	1.27 (0.21)	1.18 (0.16)	0.0831
31-40	1.25 (0.22)	1.19 (0.16)	0.263
41-50	1.22 (0.12)	1.24 (0.21)	0.732
51-60	1.28 (0.20)	1.14 (0.20)	0.0132*
61-65	1.18 (0.21)	1.13 (0.17)	0.276
66-70	1.19 (0.17)	1.1 (0.17)	0.0663
71-75	1.06 (0.17)	1.11 (0.16)	0.227
76-80	1.01 (0.31)	0.923 (0.19)	0.241
>80	0.887 (0.28)	0.878 (0.2)	0.893
All ages	1.15 (0.25)	1.1 (0.21)	0.0171*

*p < 0.05

Table 3. Optimal cut-off values and performance of SPPB and SPPB gait speed subtest in assessing sarcopenia and severe sarcopenia according to different AWGS19 definitions, in men and women aged ≥60 years.

	Prevalence (%)	SPPB (Total score)			Gait Speed 8 ft (m/s)
	Prevalence (%)	Cut-off	Sensitivity (95% CI)	Specificity (95% CI)	Cut-off	Sensitivity (95% CI)	Specificity (95% CI)
Male (total n = 136)
Sarcopenia
AWGS19 GS	21.3	6	7% (1, 23)	99% (95, 100)	1.2	86% (68, 96)	33% (24, 42)
AWGS19 STS	25.0	11	44% (27, 62)	71% (61, 79)	1.0	68% (49, 83)	72% (62, 80)
AWGS19 SPPB	24.3	11	42% (25, 61)	70% (60, 79)	1.0	70% (51, 84)	72% (62, 80)
Severe Sarcopenia
AWGS19 GS	19.9	11	67% (46, 83)	75% (66, 83)	0.9	70% (50, 86)	91% (84, 96)
AWGS19 STS	8.1	11	100% (72, 100)	73% (64, 80)	0.9	82% (48, 98)	84% (76, 90)
AWGS19 SPPB	5.9	9	100% (63, 100)	97% (92, 99)	0.9	100% (63, 100)	84% (76, 90)
Females (total n = 167)
Sarcopenia
AWGS19 GS	25.1	10	19% (9, 34)	82% (74, 88)	1.1	71% (55, 84)	42% (33, 51)
AWGS19 STS	16.9	10	29% (13, 49)	84% (77, 90)	1.0	57% (37, 76)	68% (60, 76)
AWGS19 SPPB	21.6	11	58% (41, 74)	69% (61, 77)	1.0	64% (46, 79)	71% (62,79)
Severe Sarcopenia
AWGS19 GS	14.4	11	71% (49, 87)	69% (61, 77)	1.0	83% (63, 95)	71% (63, 79)
AWGS19 STS	6.6	11	100% (72, 100)	68% (60, 76)	1.0	82% (48, 98)	67% (59, 74)
AWGS19 SPPB	1.2	7	100% (16, 100)	96% (91, 98)	0.7	100% (14, 100)	93% (88, 97)

GS = 6m gait speed, STS = sit-to-stand, SPPB = short physical performance battery criteria for sarcopenia and severe sarcopenia

SupplementaryTablesandFigures1.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

SPPB reference values and performance in assessing sarcopenia in community-dwelling Singaporeans – Yishun Study

Status:

Version 1

Abstract

Figures

Background

Methods

Participants

Assessments

SPPB

Sarcopenia definitions

Statistical analysis

Results

Participant characteristics

SPPB

Characteristics of participants ≥60 years with sarcopenia and severe sarcopenia

AUCs for sarcopenia and severe sarcopenia with SPPB and subtests

Performance of SPPB and GS cut-offs in assessing sarcopenia

Discussion

Conclusions

List of Abbreviations

Declarations

Ethics approval and consent to participate

Consent for publication

Availability of data and materials

Competing interests

Funding

Authors contributions

Acknowledgements

References

Tables

Supplementary Files

Status:

Version 1