Next Article in Journal
Impact of Life Stressors on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Symptoms: An Australian Longitudinal Study
Previous Article in Journal
Reflections Based on Pollution Changes Brought by COVID-19 Lockdown in Shanghai
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Short Physical Performance Battery as a Measure of Physical Performance and Mortality Predictor in Older Adults: A Comprehensive Literature Review

Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68900-000, Brazil
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(20), 10612; https://doi.org/10.3390/ijerph182010612
Submission received: 3 September 2021 / Revised: 5 October 2021 / Accepted: 6 October 2021 / Published: 10 October 2021

Abstract

:
The association between the Short Physical Performance Battery (SPPB) score and several adverse health outcomes, including mortality, has been reported in the scientific literature. We conducted a comprehensive literature review of studies on the relationship between SPPB and mortality. The current paper synthesizes the characteristics and main findings of longitudinal studies available in the literature that investigated the role of the SPPB in predicting mortality in older adults. The studies (n = 40) are from North America, South America, Europe, and Asia; the majority (n = 16) were conducted with community-dwelling older adults and reported an association between lower SPPB scores and a higher risk of mortality, and between higher SPPB scores and higher survival. Nevertheless, few studies have analyzed the accuracy of the instrument to predict mortality. The only study that established cut-off points was conducted with older adults discharged from an acute care hospital. Although an SPPB score lower than 10 seems to predict all-cause mortality, further studies showing cut-off points in specific settings and loco-regional specificities are still necessary.

1. Introduction

Over the last decades, the average life expectancy has greatly increased around the globe. In 2019, individuals aged 65 or above made up 9.1% of the worldwide population [1]. In developing countries such as Brazil, 10.8% of the population were individuals aged over 65 years in 2018, and it is expected that in 2060, older adults will comprise nearly 25.49% of the Brazilian population [2]. Nevertheless, the COVID-19 pandemic is expected to break the secular trend of increasing life expectancy [3,4,5,6]. Because of the presence of the severe acute respiratory syndrome coronavirus 2, deaths from other health conditions that were precipitated by COVID-19 and social and economic losses resulting from the pandemic are expected to be huge, meaning a rapid return to pre-COVID-19 life expectancy is unlikely [7]. Furthermore, long-term detrimental health impacts in those who recover from the virus will deserve attention, and public health policies focused on increasing the quality of life of older adults are already urgent. These policies, among several other factors, include aims to provide better understanding of the aging process and its repercussions.
At the biological level, aging results from the lifelong accumulation of cellular damage that leads to a gradual decline in physical and mental ability. Ultimately, these processes associated with aging result in increased susceptibility to conditions that lead to systemic impairments, as well as chronic diseases, frailty, sarcopenia, and a decline in physical capacity and functional ability [1,8].
Regarding physical capacity aspects, during senescence, there is a decrease in physical performance, mobility, flexibility, strength, and muscle mass [9,10,11]. Functional capacity and exercise tolerance also decrease with aging and may be associated with reduced protein synthesis and physical inactivity, or with chronic diseases, leading to functional limitations that increase the risk of disability and death [9,12].
Functional limitations and disabilities are multifactorial events, influenced by socio-demographic, clinical, and lifestyle factors [12] and therefore require early identification and preventive measures. In this regard, an important aspect in the context of geriatric clinical evaluation is the subject’s level of physical performance. Physical performance refers to the ability to integrate physiological mechanisms in coordinated movements to achieve a physical function, that is, the observable ability to perform tasks, such as getting up from or sitting on a chair [13,14].
Measures of physical performance can help to identify any risk or early stages of functional decline in older adults. Different measures are used to assess physical performance, which, in general, include mobility, balance, and muscle strength domains [15]. Using different physiological domains, these instruments usually generate a score and stratify the individual’s functional level [14]. The decline in physical performance is a dynamic and individual process. Physical performance changes according to intrapersonal alterations resulting from aging [15], and instruments for assessing physical performance have been shown to be important markers of general well-being, since they are not only parameters of mobility or strength but are also linked to the burden of chronic clinical conditions [16].
Several instruments have been cited for evaluating the physical performance of older adults. A systematic review conducted by Freiberger et al. [14] analyzed the psychometric properties of physical performance measurement tools in studies conducted with older community members, including: the Mobility-related Limitation Index (MOBLI Index), modified Timed Movement Battery (TMB), Physical Capacity Evaluation (PCE), Performance-based Physical Function test (PPF test), Physical Performance Test (PPT), and Short Physical Performance Battery (SPPB).
Two reviews [17,18] identified a number of instruments which are more frequently used to assess functional capacity and/or mobility in older adults, including the Timed Up and Go test (TUG), the 6-Minute Walk Test (6MWT), Berg Balance Scale (BBS), Shuttle Test (ST), Ergometric Test (ET), and sit to stand chair test. Of note, some instruments assess physical performance by measuring lower limb function, such as the SPPB, which has been frequently used in Brazilian studies with older adults.
The SPPB is highlighted as a diagnostic criterion for geriatric syndromes. Cesari et al. [19] in a multicenter study proposed an operational definition for physical frailty and sarcopenia using the SPPB (score ≥3 and ≤9) to detect low physical performance. The SPPB is also recommended by the European Working Group on Sarcopenia in Older People (EWGSO2) as a measure to identify declines in physical performance (SPPB score ≤ 8 points) as part of the algorithm for screening and diagnosing severe sarcopenia [20]. The Asian Working Group for Sarcopenia (AWGS) also suggests the SPPB for identifying declines in physical performance (SPPB score ≤ 9 points) as well as the 6MWT and sit to stand chair test [21].
Recent longitudinal studies have investigated multiple trajectories of physical performance measures in older adults. Hoekstra et al. [15] followed the trajectories of the physical performance of 440 subjects aged 60–70 years for 9 years, assessing balance, strength, and gait and found that there are different mechanisms involved in functional decline over time. The results of this study reinforce that, regardless of sex, physical performance incorporates individual factors (lifestyle, comorbidities, depressive symptoms, level of physical activity, among others), grouping heterogeneous aspects acquired throughout life. Mutambudzi et al. [22] followed community-dwelling older adults aged 75 years or older, also for 9 years, and classified them according to their physical performance trajectory. Participants were classified into three physical performance trajectory classes using the SPPB: low-declining, high-declining, and high-stable. The findings of the study showed a significant association between low-declining and high-declining trajectories and increased risk of mortality [22].
The burden of functional limitations and low physical performance still represents a challenging paradigm in the field of public health, and wider discussions on the health standards of the world’s populations are critical. That being said, physical performance measures are essential for not only assessing functional status, but also for monitoring the overall clinical evolution of older adults. It is worth noting that the SPPB is an easily applicable instrument, and its ability to predict adverse health events such as dependence in activities of daily living (ADLs), hospitalization, frailty syndrome, and death has been investigated in several studies conducted with community-dwelling and outpatient older populations [23,24]. However, the capacity of this tool to predict mortality and the existence of a cut-off point for discriminating older adults at risk are still little discussed. To address this gap, we conducted a comprehensive literature review of studies on the relationship between SPPB and mortality. A search using appropriate descriptors was performed in the databases MEDLINE, Embase, Lilacs, and Pedro on 22 February 2021.

2. Analysis of Physical Performance Using the SPPB

The SPPB assesses physical performance through balance, strength, and gait measurements and is made up of a set of three tests: standing static balance in three positions; lower limb strength and power through getting up and sitting on a chair; and walking speed at normal pace [25] (Figure 1). Balance is assessed by the ability to stand upright in three different positions for 10 seconds each: feet together; with one foot partially forward; and with one foot forward. Strength and gait are first evaluated by the ability to perform the tasks of getting up and sitting on a chair five consecutive times and performing the walking speed test (3 to 4 meters) and, second, by the time the individual takes to complete the tasks. Each test is scored from 0 (inability to perform the task) to 4 points (best test performance) [26]. The SPPB total score ranges from 0 (worst performance) to 12 points (best performance) and categorically evaluates performance in the tests using three or four classes of scores: three classes: 0–6 points (poor performance), 7–9 points (moderate performance), and 10–12 points (good performance); or four classes: 0–3 points (disability/very poor performance), 4–6 points (poor performance), 7–9 points (moderate performance), and 10–12 points (good performance) [27].
The three SPPB domains are directly related to the physical function of the older adults. The first domain is balance, which gradually decreases during senescence, mainly after the sixth decade of life [28], with a consequent decline in the ability to maintain homeostatic balance and adaptive reaction to environmental stressors. In older adults, the amplitude, frequency, and postural oscillation in the standing position is also greater than in younger subjects [28]. Declines in balance may be related to the decrease in neuromotor reactions and muscle contraction resulting from aging [29]. The SPPB assesses balance through maintenance of a static position for at least 10 seconds [25,30].
The second domain is strength. Muscle strength and power also decrease during aging and can be identified by difficulty in performing ADLs. The ability to perform ADLs is perceived in actions such as decreasing the speed at which tasks are performed or decreasing their complexity. Therefore, the functional limitation can be defined by the speed, manner, and ability to complete a task [31]. Strength is assessed in the SPPB by lower limb performance in the sit to stand chair test. Better performance in the strength test is related to less time taken to complete it, making this test essential to measure the functional capacity of older adults related to multiple daily tasks that require strength, mobility, and precision [30].
The third domain of the SPPB is gait. Walking is essential for independence in basic activities of daily living (BADL) and is an essential measure in geriatric assessments [32]. Walking speed gradually decreases with aging and at a faster pace from the age of 65, with the oldest older adults (>80 years) having a slower walking speed and shorter steps compared to younger elderly. A shorter stride length is associated with a greater decline in gait speed [33,34], and a walking speed of 0.8 m/s (meters per second) or less is a predictor of adverse clinical outcomes such as disability, cognitive decline, falls, and death [35]. As in the sit to stand chair test, better performance in the gait speed test is related to less time taken to complete the proposed task [25,30].
The SPPB was initially developed by Guralnik et al. [25] to screen older adults for the risk of disability, institutionalization, or death. The authors identified functional decline with aging and concluded that older adults with higher SPPB scores had lower functional losses compared to those with lower scores. The SPPB is a standardized and multidimensional instrument, sensitive to changes in older adult functionality [36], and that is largely associated with several health outcomes. For instance, recent longitudinal studies also found that the increase in one SPPB unit decreased the probability of falls by 15% and of recurrent falls by 17% over a two-year period. Of note, SPPB domains have not only been associated with falls [37,38,39] but also with sarcopenia [40], frailty [41], dyspnoea [42], postoperative complications [43], cardiovascular diseases [44], increased risk of mortality in chronic obstructive pulmonary disease (COPD) [45]., institutionalization, hospitalization and death [25,46,47,48]. It is also noteworthy that SPPB has been used as tool for predicting disability and physical functional impairment in discharged patients with severe COVID-19 [49].

3. SPPB, Mortality, and Survival in Older Adults

Studies on the association between physical performance assessed by the SPPB and mortality among older adults have been published since the 1990s. A systematic review with meta-analysis conducted by Pavasini et al. [36] analyzed the relationship between SPPB scores and all causes of mortality. The review included 17 observational studies, of which most were conducted with older people aged over 65 years. The authors analyzed all-cause mortality according to SPPB category scores. Lower SPPB scores (0–3, 4–6, and 7–9) were associated with an increased risk of death compared to higher values (scores of 10–12), and an SPPB score <10 was predictive of all-cause mortality [36].
Currently, the scientific production on longitudinal studies regarding SPPB and mortality in older adults comes from countries in North America, Europe, and Asia, with follow-ups ranging from 1 to 11 years (Figure 2). Among these studies, the majority were conducted with community-dwelling (n = 16) and hospitalized (n = 13) older adults. Only one study was conducted in South America [23], and it was conducted with older adults treated at an outpatient clinic. The characteristics of the studies are presented in Table 1.
Perera et al. [48], Rolland et al. [50], Cesari et al. [51], Legrand et al. [52], Tadjibaev et al. [53], Brown et al. [54], Fox et al. [55], Lattanzio et al. [56], Landi et al. [57], Stenholm et al. [58], Veronese et al. [59], Björkman et al. [60], and Mutambudzi et al. [22] conducted studies with community-dwelling older adults and investigated the prognostic value of the SPPB to predict mortality. In all of these studies, lower SPPB scores (range 0–6 points) significantly increased the risk of death, except for the studies by Rolland et al. [50], Verghese et al. [61], and Cesari et al. [51]. Table 2 displays the characteristics of the studies according to the SPPB classification and mortality outcome.
In the Rolland et al.’s study [50], the walking speed component was more strongly associated with mortality compared to the SPPB, with a risk ratio of 1.50 (95% CI: 0.97–2.33) versus 1.34 (95% CI: 1.04–1.73), respectively. Verghese et al. [61] reported similar results for the same variables, with a risk ratio of 1.38 (95% CI: 1.13–1.69) for walking speed versus 1.25 (95% CI: 1.06–1.47) for the SPPB score.
Cesari et al. [51] analyzed the SPPB components and found that the sit and stand test, with a risk ratio of 0.54 (95% CI: 0.38–0.76), was more strongly associated with mortality, compared to gait and balance tests, with 0.73 (95% CI: 0.54–1.01) and 0.78 (95% CI: 0.60–1.01), respectively. Verghese et al. [61] and Ensrud et al. [62] used the SPPB to assess mobility levels in community-dwelling older adults, and both studies showed an association between the lowest SPPB scores <3 and the highest risk of mortality.
In addition, some studies conducted in other settings such as with hospitalized [63,64,65,66,67,68,69,70,71,72] and institutionalized older adults [73,74]; outpatients [75]; and patients with cancer, liver injury, and those with cardiac disorders [76,77,78,79] also demonstrated an association between lower SPPB scores and an increased risk of death. In contrast, a study conducted by van Mourik et al. [80] with hospitalized older adults did not find a significant association between the SPPB and all-cause mortality (Table 2).
Regarding the survival analyses, Cesari et al. [51], Brown et al. [54], and Veronese et al. [59] conducted studies with community-dwelling older adults and found a positive relationship between SPPB scores (scores of 10-12) and survival rate, that is, older adults with better physical performance live longer when compared to those with lower performance. Similar results were found in studies with hospitalized and institutionalized older adults [63,65,73,74,81]. In the studies by Chiarantini et al. [63], Corsonello et al. [65], Charles et al. [73,74], and Arnau et al. [81], survival was significantly associated with better physical performance (SPPB scores ≥ 7), and the SPPB was found to be an independent predictor of long-term survival.
A Brazilian cohort [23] including 512 acutely ill older adults investigated the prognostic value of SPPB for dependence on basic activities of daily living—BADLs, hospitalization, and death over a one-year follow-up.
The findings were similar to international studies as they showed a higher incidence of death in patients with low (SPPB score 0–4) and intermediate (SPPB score 5–8) physical performance (risk ratio 2.70, 95% CI: 1.17–6.21, p = 0.042 versus 2.54; 95% CI: 1.17–5.53, p = 0.042) compared to patients with high performance (SPPB score ≥ 9). Figure 3 illustrates the association of SPPB scores with mortality and survival.

4. SPPB Accuracy for Predicting Mortality

Some studies analyzed the area under the ROC curve (Receiver Operating Characteristic Curve—AUC), and cut-off points were established to verify the accuracy of the SPPB to predict mortality in older adults from different settings. Three studies investigated the accuracy of the SPPB to predict mortality in community-dwelling older adults. Minneci et al. [82] compared the capacity of physical performance tests, including the SPPB, to predict mortality and other clinical outcomes among 561 older adults over a 7-year period. The SPPB was shown to be a better predictor of mortality compared to other measures of performance, with an area under the ROC curve of 0.63.
Landi et al. [57] verified the impact of sarcopenia and its relationship with functional decline on the risk of all-cause mortality in 354 community-dwelling older adults during a 10-year follow-up. Impairment in physical function in sarcopenic older adults as assessed by the SPPB was found to be a better predictor of mortality (AUC: 0.697; 95% CI: 0.639–0.755) than multimorbidity (AUC: 0.633; 95% CI: 0.572–0.695).
Cesari et al. [51] analyzed the predictive ability of the SPPB combined with self-rated health status during a 24-month follow-up and did not find significant differences between ability in the sit to stand chair test (AUC: 0.725; 95% CI: 0.661–0.789), self-rated health (AUC: 0.656; 95% CI: 0.582–0.730), and their combination (AUC: 0.751; 95% CI: 0.686–0.816) to predict mortality (AUC: 0.749; 95% CI: 0.683–0.814), and they reported similar results for the isolated analysis of SPPB scores (AUC: 0.743; 95% CI: 0.679–0.806). On the other hand, in 2013, the same authors measured the prognostic value of multiple screening tools for the assessment of 1-year mortality risk in 200 older women with gynecological cancer and found only borderline significance for the SPPB (AUC: 0.638; 95% CI: 0.483–0.792) in predicting mortality [83].
Two studies analyzed the association of the SPPB with all-cause mortality in older adults with cardiac disorders. Afilalo et al. [84] investigated the value of frailty scales (including SPPB) to predict one-year mortality in older adults undergoing surgical or transcatheter aortic valve replacement. The findings showed that SPPB is not the best scale to predict mortality (AUC: 0.734; 95% CI: 0.694−0.775) compared to other scales used to identify frailty. Campo et al. [85] described that the SPPB combined with the GRACE (Global Registry of Acute Coronary Events) (AUC:0.816, 95% CI: 0.777–859) and TIMI (Thrombolysis in Myocardial Infarction) (AUC: 0.879, 95% CI: 0.814–0.884) risk scores provided incremental improvements in risk stratification for death in 1 year of older adults after acute coronary syndrome.
Of note, only one study established cut-off points for the SPPB to predict mortality. Corsonello et al. [65] investigated the prognostic role of the SPPB to predict survival and mortality during a 1-year follow-up in 506 older adults discharged from an acute care hospital. The results showed that a score <5 in the SPPB was capable of predicting mortality (AUC: 0.66), with sensitivity and specificity values of 0.66 and 0.62, respectively.

5. Conclusions

The SPPB is an easily applicable and low-cost instrument that may be implemented in the routine health assessment of older adults for screening geriatric clinical conditions. It is associated with falls, sarcopenia, frailty, dyspnoea, postoperative complications, cardiovascular diseases, institutionalization, and ultimately, death. This research provides important information upon which to base future primary health care policies for older people aiming at preventing adverse health outcomes, especially death. Although an SPPB score lower than 10 seems to predict all-cause mortality, different configurations of SPPB scoring categories in diverse services and health settings could also provide predictive power for this outcome. Thus, further studies demonstrating cut-off points in specific settings and loco-regional specificities are still necessary.

Author Contributions

C.d.F.R.S. contributed to the conception and the writing of the article; M.S.P., C.d.F.R.S., D.G.O., A.P.M., and A.C.P.N.P. contributed to the conception and design of the study, its critical review, and approval of the version to be published. All authors have read and agreed to the published version of the manuscript.

Funding

Foundation for Research Support of the State of Amapá (FAPEAP, Concession no. 250.203.045/2019).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

There was no conflict of interest.

References

  1. United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects 2017: Volume II: Demographic Profiles; United Nations: New York, NY, USA, 2017. [Google Scholar]
  2. Instituto Brasileiro de Geografia e Estatística. Coordination of Population and Social Indicators. Population Projections: Brazil and Federation Units: Review, 2nd ed.; Instituto Brasileiro de Geografia e Estatística: Rio de Janeiro, Brasil, 2018. [Google Scholar]
  3. Andrasfay, T.; Goldman, N. Reductions in 2020 US life expectancy due to COVID-19 and the disproportionate impact on the Black and Latino populations. Proc. Natl. Acad. Sci. USA 2021, 118. [Google Scholar] [CrossRef]
  4. Pifarré i Arolas, H.; Acosta, E.; López-Casasnovas, G.; Lo, A.; Nicodemo, C.; Riffe, T.; Myrskylä, M. Years of life lost to COVID-19 in 81 countries. Sci. Rep. 2021, 11, 3504. [Google Scholar] [CrossRef]
  5. Marois, G.; Muttarak, R.; Scherbov, S. Assessing the potential impact of COVID-19 on life expectancy. PLoS ONE 2020, 15, e0238678. [Google Scholar] [CrossRef]
  6. Trias-Llimós, S.; Bilal, U. Impact of the COVID-19 pandemic on life expectancy in Madrid (Spain). J. Public Health 2020, 42, 635–636. [Google Scholar] [CrossRef] [PubMed]
  7. Brenner, M.H. Will There Be an Epidemic of Corollary Illnesses Linked to a COVID-19–Related Recession? Am. J. Public Health 2020, 110, 974–975. [Google Scholar] [CrossRef] [PubMed]
  8. Pan American Health Organization. Folha informative—Envelhecimento e saúde. 2020. Available online: https://www.paho.org/bra/index.php?option=com_content&view=article&id=5661:folha-informativa-envelhecimento-e-saude&Itemid=820 (accessed on 3 November 2020).
  9. Mckendry, J.; Breen, L.; Shad, B.J.; Greig, C.A. Muscle morphology and performance in master athletes: A systematic review and meta-analyses. Ageing Res. Rev. 2018, 45, 62–82. [Google Scholar] [CrossRef]
  10. Niccoli, T.; Partridge, L. Ageing as a Risk Factor for Disease. Curr. Biol. 2012, 22, R741–R752. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  11. Thom, J.; Morse, C.; Birch, K.; Narici, M.V. Influence of muscle architecture on the torque and power–velocity characteristics of young and elderly men. Eur. J. App. Phisiol. 2007, 100, 613–619. [Google Scholar] [CrossRef]
  12. Ikegami, É.M.; Souza, L.A.; Tavares, D.M.D.S.; Rodrigues, L.R. Functional capacity and physical performance of community-dwelling elderly: A longitudinal study. Ciênc. Saúde. Colet. 2020, 25, 1083–1090. [Google Scholar] [CrossRef] [PubMed]
  13. Cress, M.; Buchner, D.M.; Questad, K.A.; Esselman, P.C.; Delateur, B.J.; Schwartz, R.S. Continuous-scale physical functional performance in healthy older adults: A validation study. Arch. Phys. Med. Rehabilit. 1996, 77, 1243–1250. [Google Scholar] [CrossRef]
  14. Freiberger, E.; de Vreede, P.; Schoene, D.; Rydwik, E.; Mueller, V.; Frändin, K.; Hopman-Rock, M. Performance-based physical function in older community-dwelling persons: A systematic review of instruments. Age Ageing 2012, 41, 712–721. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Hoekstra, T.; Rojer, A.G.M.; van Schoor, N.M.; Maier, A.B.; Pijnappels, M. Distinct Trajectories of Individual Physical Performance Measures Across 9 Years in 60- to 70-Year-Old Adults. J. Gerontol. Ser. A Boil. Sci. Med Sci. 2020, 75, 1951–1959. [Google Scholar] [CrossRef]
  16. Patrizio, E.; Calvani, R.; Marzetti, E.; Cesari, M. Physical Functional Assessment in Older Adults. J. Frailty Aging. 2021, 10, 141–149. [Google Scholar] [PubMed]
  17. Nunciato, A.; Pereira, B.C.; Borghi-Silva, A. Methods for assessing physical capacity and quality of life in the elderly: A literature review. Saúde Rev. 2012, 12, 41–48. [Google Scholar] [CrossRef]
  18. Gomes, C.S.; Buranello, M.C.; Castro, S.S. Assessment instruments of functioning in Brazilian elderly and the ICF: A systematic review. Fisioter. Mov. 2017, 30, 625–637. [Google Scholar] [CrossRef] [Green Version]
  19. Cesari, M.; Landi, F.; Calvani, R.; Cherubini, A.; di Bari, M.; Kortebein, P.; del Signore, S.; Regis Le Lain, S.; Vellas, B.; Pahor, M.; et al. Rationale for a preliminary operational definition of physical frailty and sarcopenia in the SPRINTT trial. Aging Clin. Exp. Res. 2017, 29, 81–88. [Google Scholar] [CrossRef]
  20. Cruz-Jentoft, A.J.; Bahat, G.; Bauer, J.; Boirie, Y.; Bruyere, O.; Cederholm, T.; Cooper, C.; Landi, F.; Rolland, Y.; Sayer, A.A.; et al. Sarcopenia: Revised European consensus on definition and diagnosis. Age Ageing 2019, 48, 16–31. [Google Scholar] [CrossRef] [Green Version]
  21. Chen, L.-K.; Woo, J.; Assantachai, P.; Auyeung, T.-W.; Chou, M.-Y.; Iijima, K.; Jang, H.C.; Kang, L.; Kim, M.; Kim, S.; et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J. Am. Med Dir. Assoc. 2020, 21, 300–307. [Google Scholar] [CrossRef]
  22. Mutambudzi, M.; Chen, N.-W.; Howrey, B.; Garcia, M.A.; Markides, K.S. Physical Performance Trajectories and Mortality Among Older Mexican Americans. J. Gerontol. Ser. A Boil. Sci. Med Sci. 2018, 74, 233–239. [Google Scholar] [CrossRef] [Green Version]
  23. Fortes-Filho, S.Q.; Aliberti, M.; Apolinario, D.; Melo-Fortes, J.A.; Sitta, M.C.; Jacob-Filho, W.; Leme, L.G. Role of Gait Speed, Strength, and Balance in Predicting Adverse Outcomes of Acutely Ill Older Outpatients. J. Nutr. Health Aging 2019, 24, 113–118. [Google Scholar] [CrossRef]
  24. Perracini, M.R.; Mello, M.; Máximo, R.D.O.; Bilton, T.L.; Ferriolli, E.; Lustosa, L.P.; Alexandre, T. Diagnostic Accuracy of the Short Physical Performance Battery for Detecting Frailty in Older People. Phys. Ther. 2019, 100, 90–98. [Google Scholar] [CrossRef] [PubMed]
  25. Guralnik, J.M.; Simonsick, E.M.; Ferrucci, L.; Glynn, R.J.; Berkman, L.F.; Blazer, D.G.; Scherr, P.A.; Wallace, R.B. A Short Physical Performance Battery Assessing Lower Extremity Function: Association with Self-Reported Disability and Prediction of Mortality and Nursing Home Admission. J. Gerontol. 1994, 49, M85–M94. [Google Scholar] [CrossRef] [PubMed]
  26. Treacy, D.; Hassett, L. The Short Physical Performance Battery. J. Physiother. 2018, 64, 61. [Google Scholar] [CrossRef] [PubMed]
  27. Guralnik, J.M.; Ferrucci, L.; Pieper, C.F.; Leveille, S.G.; Markides, K.S.; Ostir, G.V.; Studenski, S.; Berkman, L.F.; Wallace, R.B. Lower Extremity Function and Subsequent Disability: Consistency Across Studies, Predictive Models, and Value of Gait Speed Alone Compared with the Short Physical Performance Battery. J. Gerontol. Ser. A Boil. Sci. Med Sci. 2000, 55, M221–M231. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Carvalho, J.; Soares, J. Aging and muscle strength: A brief review. Rev. Port. Ciênc. Desporto 2004, 4, 79–93. [Google Scholar] [CrossRef]
  29. Bushatsky, A.; Alves, L.C.; Duarte, Y.A.O.; Lebrão, M.L. Factors associated with balance desorders of elderly living in the city of São Paulo in 2006: Evidence from the Health, Well-Being and Aging (SABE) Study. Ver. Bras. Epidemiol. 2018, 21, e180016. [Google Scholar] [CrossRef] [Green Version]
  30. Nakano, M.M. Versão Brasileira da Short Physical Performance Battery—Sppb: Adaptação Cultural e Estudo da Confiabilidade. Master’s Thesis, Universidade Estadual de Campinas, Faculdade de Educação, Campinas, SP, Brasil. completion on 22 February 2007.
  31. Lamb, S.E.; Keene, D.J. Measuring physical capacity and performance in older people. Best Pract. Res. Clin. Rheumatol. 2017, 31, 243–254. [Google Scholar] [CrossRef]
  32. Peel, N.M.; Kuys, S.; Klein, K. Gait Speed as a Measure in Geriatric Assessment in Clinical Settings: A Systematic Review. J. Gerontol. Ser. A Boil. Sci. Med Sci. 2012, 68, 39–46. [Google Scholar] [CrossRef]
  33. Jerome, G.J.; Ko, S.U.; Kauffman, D.; Studenski, S.A.; Ferrucci, L.; Simonsick, E.M. Gait characteristics associated with walking speed decline in older adults: Results from the Baltimore Longitudinal Study of Aging. Arch. Gerontol. Geriatr. 2015, 60, 239–243. [Google Scholar] [CrossRef] [Green Version]
  34. Samson, M.M.; Crowe, A.; de Vreede, P.L.; Dessens, J.A.G.; Duursma, S.A.; Verhaar, H.J.J. Differences in gait parameters at a preferred walking speed in healthy subjects due to age, height and body weight. Aging Clin. Exp. Res. 2001, 13, 16–21. [Google Scholar] [CrossRef]
  35. Van Kan, G.A.; Rolland, Y.; Andrieu, S.; Bauer, J.; Beauchet, O.; Bonnefoy, M.; Cesari, M.; Donini, L.; Gillette-Guyonnet, S.; Inzitari, 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, 881–889. [Google Scholar] [CrossRef] [PubMed]
  36. Pavasini, R.; Guralnik, J.; Brown, J.C.; Di Bari, M.; Cesari, M.; Landi, F.; Vaes, B.; Legrand, D.; Verghese, J.; Wang, C.; et al. Short Physical Performance Battery and all-cause mortality: Systematic review and meta-analysis. BMC Med. 2016, 14, 1–9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Lauretani, F.; Ticinesi, A.; Gionti, L.; Prati, B.; Nouvenne, A.; Tana, C.; Meschi, T.; Maggio, M. Short-Physical Performance Battery (SPPB) score is associated with falls in older outpatients. Aging Clin. Exp. Res. 2018, 31, 1435–1442. [Google Scholar] [CrossRef] [PubMed]
  38. Kim, J.C.; Chon, J.; Kim, H.S.; Lee, J.H.; Yoo, S.D.; Kim, D.H.; Lee, S.A.; Han, Y.J.; Lee, H.S.; Lee, B.Y.; et al. The Association Between Fall History and Physical Performance Tests in the Community-Dwelling Elderly: A Cross-Sectional Analysis. Ann. Rehabilit. Med. 2017, 41, 239–247. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Lustosa, L.P.; da Silva, J.S.; Pereira, D.A.G.; Assis, M.G.; Pereira, L.S.M. Physiological risk of falls, physical and aerobic capacity in community-dwelling elderly. Fisioter. Mov. 2020, 33. [Google Scholar] [CrossRef]
  40. Phu, S.; Kirk, B.; Hassan, E.B.; Vogrin, S.; Zanker, J.; Bernardo, S.; Duque, G. The diagnostic value of the Short Physical Performance Battery for sarcopenia. BMC Geriatr. 2020, 20, 1–7. [Google Scholar] [CrossRef]
  41. Ramírez-Vélez, R.; de Asteasu, M.L.S.; Morley, J.E.; Cano-Gutierrez, C.A.; Izquierdo, M. Performance of the Short Physical Performance Battery in Identifying the Frailty Phenotype and Predicting Geriatric Syndromes in Community-Dwelling Elderly. J. Nutr. Health Aging 2020, 25, 209–217. [Google Scholar] [CrossRef]
  42. Silva, C.d.F.R.; Pegorari, M.S.; Matos, A.P.; Ohara, D.G. Dyspnea is associated with poor physical performance among community-dwelling older adults: A population-based cross-sectional study. Sao Paulo Med. J. 2020, 138, 112–117. [Google Scholar] [CrossRef]
  43. Hanada, M.; Yamauchi, K.; Miyazaki, S.; Oyama, Y.; Yanagita, Y.; Sato, S.; Miyazaki, T.; Nagayasu, T.; Kozu, R. Short-Physical Performance Battery (SPPB) score is associated with postoperative pulmonary complications in elderly patients undergoing lung resection surgery: A prospective multicenter cohort study. Chronic Respir. Dis. 2020, 17. [Google Scholar] [CrossRef]
  44. Bellettiere, J.; LaMonte, M.J.; Unkart, J.; Liles, S.; Laddu-Patel, D.; Manson, J.E.; Banack, H.; Seguin-Fowler, R.; Chavez, P.; Tinker, L.F.; et al. Short Physical Performance Battery and Incident Cardiovascular Events Among Older Women. J. Am. Heart Assoc. 2020, 9, e016845. [Google Scholar] [CrossRef]
  45. Fermont, J.M.; Mohan, D.; Fisk, M.; Bolton, C.E.; Macnee, W.; Cockcroft, J.R.; McEniery, C.; Fuld, J.; Cheriyan, J.; Tal-Singer, R.; et al. Short physical performance battery as a practical tool to assess mortality risk in chronic obstructive pulmonary disease. Age Aging 2021, 50, 795–801. [Google Scholar] [CrossRef]
  46. Studenski, S.; Perera, S.; Wallace, D.; Chandler, J.M.; Duncan, P.; Rooney, E.; Fox, M.; Guralnik, J.M. Physical Performance Measures in the Clinical Setting. J. Am. Geriatr. Soc. 2003, 51, 314–322. [Google Scholar] [CrossRef] [Green Version]
  47. Perera, S.; Mody, S.H.; Woodman, R.C.; Studenski, S.A. Meaningful Change and Responsiveness in Common Physical Performance Measures in Older Adults. J. Am. Geriatr. Soc. 2006, 54, 743–749. [Google Scholar] [CrossRef] [PubMed]
  48. Perera, S.; Studenski, S.; Chandler, J.M.; Guralnik, J.M. Magnitude and Patterns of Decline in Health and Function in 1 Year Affect Subsequent 5-Year Survival. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2005, 60, 894–900. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  49. Bellan, M.; Soddu, D.; Balbo, P.E.; Baricich, A.; Zeppegno, P.; Avanzi, G.C.; Baldon, G.; Bartolomei, G.; Battaglia, M.; Battistini, S.; et al. Respiratory and Psychophysical Sequelae Among Patients with COVID-19 Four Months After Hospital Discharge. JAMA Netw. Open 2021, 4, e2036142. [Google Scholar] [CrossRef] [PubMed]
  50. Rolland, Y.; Lauwers-Cances, V.; Cesari, M.; Vellas, B.; Pahor, M.; Grandjean, H. Physical Performance Measures as Predictors of Mortality in a Cohort of Community-dwelling Older French Women. Eur. J. Epidemiol. 2006, 21, 113–122. [Google Scholar] [CrossRef] [PubMed]
  51. Cesari, M.; Onder, G.; Zamboni, V.; Manini, T.; I Shorr, R.; Russo, A.; Bernabei, R.; Pahor, M.; Landi, F. Physical function and self-rated health status as predictors of mortality: Results from longitudinal analysis in the ilSIRENTE study. BMC Geriatr. 2008, 8, 34. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Legrand, D.; Vaes, B.; Matheï, C.; Adriaensen, W.; van Pottelbergh, G.; Degryse, J.-M. Muscle Strength and Physical Performance as Predictors of Mortality, Hospitalization, and Disability in the Oldest Old. J. Am. Geriatr. Soc. 2014, 62, 1030–1038. [Google Scholar] [CrossRef]
  53. Tadjibaev, P.; Frolova, E.; Gurina, N.; Degryse, J.-M.; Vaes, B. The relationship between physical performance and cardiac function in an elderly Russian cohort. Arch. Gerontol. Geriatr. 2014, 59, 554–561. [Google Scholar] [CrossRef] [Green Version]
  54. Brown, J.C.; Harhay, M. Physical function as a prognostic biomarker among cancer survivors. Br. J. Cancer 2014, 112, 194–198. [Google Scholar] [CrossRef] [Green Version]
  55. Fox, K.R.; Ku, P.-W.; Hillsdon, M.; Davis, M.G.; Simmonds, B.A.J.; Thompson, J.; Stathi, A.; Gray, S.F.; Sharp, D.; Coulson, J.C. Objectively assessed physical activity and lower limb function and prospective associations with mortality and newly diagnosed disease in UK older adults: An OPAL four-year follow-up study. Age Ageing 2014, 44, 261–268. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Lattanzio, F.; Corsonello, A.; Montesanto, A.; Abbatecola, A.M.; Lofaro, D.; Passarino, G.; Fusco, S.; Corica, F.; Pedone, C.; Maggio, M.; et al. Disentangling the Impact of Chronic Kidney Disease, Anemia, and Mobility Limitation on Mortality in Older Patients Discharged from Hospital. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2015, 70, 1120–1127. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Landi, F.; Calvani, R.; Tosato, M.; Martone, A.M.; Bernabei, R.; Onder, G.; Marzetti, E. Impact of physical function impairment and multimorbidity on mortality among community-living older persons with sarcopaenia: Results from the ilSIRENTE prospective cohort study. BMJ Open 2016, 6, e008281. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Stenholm, S.; Koster, A.; Valkeinen, H.; Patel, K.V.; Bandinelli, S.; Guralnik, J.M.; Ferrucci, L. Association of Physical Activity History with Physical Function and Mortality in Old Age. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2015, 71, 496–501. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  59. Veronese, N.; Stubbs, B.; Fontana, L.; Trevisan, C.; Bolzetta, F.; De Rui, M.; Sartori, L.; Musacchio, E.; Zambon, S.; Maggi, S.; et al. A Comparison of Objective Physical Performance Tests and Future Mortality in the Elderly People. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2016, 72, 362–368. [Google Scholar] [CrossRef] [Green Version]
  60. Björkman, M.P.; Pitkala, K.H.; Jyväkorpi, S.; Strandberg, T.E.; Tilvis, R.S. Bioimpedance analysis and physical functioning as mortality indicators among older sarcopenic people. Exp. Gerontol. 2019, 122, 42–46. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Verghese, J.; Holtzer, R.; Lipton, R.B.; Wang, C. Mobility Stress Test Approach to Predicting Frailty, Disability, and Mortality in High-Functioning Older Adults. J. Am. Geriatr. Soc. 2012, 60, 1901–1905. [Google Scholar] [CrossRef] [Green Version]
  62. Ensrud, K.E.; Lui, L.-Y.; Paudel, M.L.; Schousboe, J.T.; Kats, A.M.; Cauley, J.A.; McCulloch, C.E.; Yaffe, K.; Cawthon, P.M.; Hillier, T.A.; et al. Effects of Mobility and Cognition on Risk of Mortality in Women in Late Life: A Prospective Study. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2015, 71, 759–765. [Google Scholar] [CrossRef]
  63. Chiarantini, D.; Volpato, S.; Sioulis, F.; Bartalucci, F.; Del Bianco, L.; Mangani, I.; Pepe, G.; Tarantini, F.; Berni, A.; Marchionni, N.; et al. Lower Extremity Performance Measures Predict Long-Term Prognosis in Older Patients Hospitalized for Heart Failure. J. Card. Fail. 2010, 16, 390–395. [Google Scholar] [CrossRef]
  64. Comba, M.; Fonte, G.; Isaia, G.; Pricop, L.; Sciarrillo, I.; Michelis, G.; Bo, M. Cardiac and Inflammatory Biomarkers and In-hospital Mortality in Older Medical Patients. J. Am. Med. Dir. Assoc. 2014, 15, 68–72. [Google Scholar] [CrossRef]
  65. Corsonello, A.; Lattanzio, F.; Pedone, C.; Garasto, S.; Laino, I.; Bustacchini, S.; Pranno, L.; Mazzei, B.; Passarino, G.; Incalzi, R.A. Prognostic Significance of the Short Physical Performance Battery in Older Patients Discharged from Acute Care Hospitals. Rejuvenat. Res. 2012, 15, 41–48. [Google Scholar] [CrossRef] [Green Version]
  66. Fujita, K.; Nakashima, H.; Kako, M.; Shibata, A.; Yu-Ting, C.; Tanaka, S.; Nishida, Y.; Kuzuya, M. Short physical performance battery discriminates clinical outcomes in hospitalized patients aged 75 years and over. Arch. Gerontol. Geriatr. 2020, 90, 104155. [Google Scholar] [CrossRef] [PubMed]
  67. Lamers, S.; Degerickx, R.; Vandewoude, M.; Perkisas, S. The mortality determinants of sarcopenia and comorbidities in hospitalized geriatric patients. J. Frailty Sarcopenia Falls 2017, 2, 65–72. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Nastasi, A.J.; McAdams-DeMarco, M.A.; Schrack, J.; Ying, H.; Olorundare, I.; Warsame, F.; Mountford, A.; Haugen, C.E.; Fernández, M.G.; Norman, S.P.; et al. Pre-Kidney Transplant Lower Extremity Impairment and Post-Kidney Transplant Mortality. Arab. Archaeol. Epigr. 2017, 18, 189–196. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Saitoh, M.; Saji, M.; Kozono-Ikeya, A.; Arimitsu, T.; Sakuyama, A.; Ueki, H.; Nagayama, M.; Isobe, M. Hospital-Acquired Functional Decline and Clinical Outcomes in Older Patients Undergoing Transcatheter Aortic Valve Implantation. Circ. J. 2020, 84, 1083–1089. [Google Scholar] [CrossRef] [PubMed]
  70. Tonet, E.; Campo, G.; Maietti, E.; Formiga, F.; Martinez-Sellés, M.; Pavasini, R.; Biscaglia, S.; Serenelli, M.; Sanchis, J.; Diez-Villanueva, P.; et al. Nutritional status and all-cause mortality in older adults with acute coronary syndrome. Clin. Nutr. 2019, 39, 1572–1579. [Google Scholar] [CrossRef]
  71. Ungar, A.; Mannarino, G.; Van Der Velde, N.; Baan, J.; Thibodeau, M.-P.; Masson, J.-B.; Santoro, G.; Van Mourik, M.; Jansen, S.; Deutsch, C.; et al. Comprehensive geriatric assessment in patients undergoing transcatheter aortic valve implantation—Results from the CGA-TAVI multicentre registry. BMC Cardiovasc. Disord. 2018, 18, 1. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Volpato, S.; Cavalieri, M.; Sioulis, F.; Guerra, G.; Maraldi, C.; Zuliani, G.; Fellin, R.; Guralnik, J.M. Predictive Value of the Short Physical Performance Battery Following Hospitalization in Older Patients. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2010, 66A, 89–96. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Charles, A.; Buckinx, F.; Locquet, M.; Reginster, J.-Y.; Petermans, J.; Gruslin, B.; Bruyère, O. Prediction of Adverse Outcomes in Nursing Home Residents According to Intrinsic Capacity Proposed by the World Health Organization. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2019, 75, 1594–1599. [Google Scholar] [CrossRef]
  74. Charles, A.; Detilleux, J.; Buckinx, F.; Reginster, J.-Y.; Gruslin, B.; Bruyère, O. Physical performance trajectories and mortality among nursing home residents: Results of the SENIOR cohort. Age Ageing 2020, 49, 800–806. [Google Scholar] [CrossRef]
  75. Pamoukdjian, F.; Aparicio, T.; Zebachi, S.; Zelek, L.; Paillaud, E.; Canoui-Poitrine, F. Comparison of Mobility Indices for Predicting Early Death in Older Patients with Cancer: The Physical Frailty in Elderly Cancer Cohort Study. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2019, 75, 189–196. [Google Scholar] [CrossRef] [PubMed]
  76. Baldasseroni, S.; Pratesi, A.; Stefàno, P.; del Pace, S.; Campagnolo, V.; Baroncini, A.C.; Lo Forte, A.; Marella, A.G.; Ungar, A.; Di Bari, M.; et al. Italian Society of Geriatric C. Pre-operative physical performance as a predictor of in-hospital outcomes in older patients undergoing elective cardiac surgery. Eur. J. Intern. Med. 2021, 84, 80–87. [Google Scholar] [CrossRef] [PubMed]
  77. Klepin, H.D.; Geiger, A.M.; Tooze, J.A.; Kritchevsky, S.B.; Williamson, J.D.; Pardee, T.S.; Ellis, L.R.; Powell, B.L. Geriatric assessment predicts survival for older adults receiving induction chemotherapy for acute myelogenous leukemia. Blood 2013, 121, 4287–4294. [Google Scholar] [CrossRef] [PubMed]
  78. Pamoukdjian, F.; Lévy, V.; Sebbane, G.; Boubaya, M.; Landre, T.; Bloch-Queyrat, C.; Paillaud, E.; Zelek, L. Slow gait speed is an independent predictor of early death in older cancer outpatients: Results from a prospective cohort study. J. Nutr. Health Aging 2016, 21, 202–206. [Google Scholar] [CrossRef] [PubMed]
  79. WangBA, C.W.; Covinsky, K.E.; Feng, S.; Hayssen, H.; Segev, D.L.; Lai, J.C. Functional impairment in older liver transplantation candidates: From the functional assessment in liver transplantation study. Liver Transplant. 2015, 21, 1465–1470. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  80. Van Mourik, M.S.; van der Velde, N.; Mannarino, G.; Thibodeau, M.-P.; Masson, J.-B.; Santoro, G.; Baan, J.; Jansen, S.; Kurucova, J.; Thoenes, M.; et al. Value of a comprehensive geriatric assessment for predicting one-year outcomes in patients undergoing transcatheter aortic valve implantation: Results from the CGA-TAVI multicentre registry. J. Geriatr. Cardiol. 2019, 16, 468–477. [Google Scholar] [CrossRef] [PubMed]
  81. Arnau, A.; Espaulella, J.; Serrarols, M.; Canudas, J.; Formiga, F.; Ferrer, M.; Méndez, T. Lower limb function and 10-year survival in population aged 75 years and older. Fam. Pract. 2015, 33, 10–16. [Google Scholar] [CrossRef] [Green Version]
  82. Minneci, C.; Mello, A.M.; Mossello, E.; Baldasseroni, S.; Macchi, L.; Cipolletti, S.; Marchionni, N.; Di Bari, M. 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, 136–141. [Google Scholar] [CrossRef]
  83. Cesari, M.; Cerullo, F.; Zamboni, V.; Di Palma, R.; Scambia, G.; Balducci, L.; Incalzi, R.A.; Vellas, B.; Gambassi, G. Functional Status and Mortality in Older Women with Gynecological Cancer. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2013, 68, 1129–1133. [Google Scholar] [CrossRef] [Green Version]
  84. Afilalo, J.; Lauck, S.; Kim, D.H.; Lefèvre, T.; Piazza, N.; Lachapelle, K.; Martucci, G.; Lamy, A.; Labinaz, M.; Peterson, M.D.; et al. Frailty in Older Adults Undergoing Aortic Valve Replacement: The FRAILTY-AVR Study. J. Am. Coll. Cardiol. 2017, 70, 689–700. [Google Scholar] [CrossRef]
  85. Campo, G.; Maietti, E.; Tonet, E.; Biscaglia, S.; Ariza-Solè, A.; Pavasini, R.; Tebaldi, M.; Cimaglia, P.; Bugani, G.; Serenelli, M.; et al. The Assessment of Scales of Frailty and Physical Performance Improves Prediction of Major Adverse Cardiac Events in Older Adults with Acute Coronary Syndrome. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2019, 75, 1113–1119. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Short physical performance battery—SPPPB. Source: Wall chart courtesy of Dr. Jack Guralnik.
Figure 1. Short physical performance battery—SPPPB. Source: Wall chart courtesy of Dr. Jack Guralnik.
Ijerph 18 10612 g001
Figure 2. Distribution of longitudinal studies conducted with older adults on the SPPB and mortality according to research locations.
Figure 2. Distribution of longitudinal studies conducted with older adults on the SPPB and mortality according to research locations.
Ijerph 18 10612 g002
Figure 3. Association of mortality and survival according to SPPB categories (very low 0–3, low 4–6, intermediate 7–9, high 10–12).
Figure 3. Association of mortality and survival according to SPPB categories (very low 0–3, low 4–6, intermediate 7–9, high 10–12).
Ijerph 18 10612 g003
Table 1. Characteristics of longitudinal studies conducted with older adults on the relationship between the SPPB and mortality (n = 40).
Table 1. Characteristics of longitudinal studies conducted with older adults on the relationship between the SPPB and mortality (n = 40).
AuthorsCountrySample/SettingFollow-Up
Mutambudzi et al. [22]Mexico/United States1411 community-dwelling older adults9.5 years
Fortes-Filho et al. [23]Brazil512 acutely ill older outpatients1 year
Guralnik et al. [25]United States5174 community-dwelling and institutionalized older adults6 years
Perera et al. [48]United States439 community-dwelling older adults5 years
Rolland et al. [50]France7250 community-dwelling older women3.8 years
Cesari et al. [51]Italy335 community-dwelling older adults24 months
Legrand et al. [52]Belgium560 community-dwelling older adults33.5 months
Tadjibaev et al. [53]Russia284 community-dwelling older adults2.6 years
Brown et al. [54]United States413 older adult cancer survivors11 years
Fox et al. [55]England213 older adults living in suburban and urban sectors4 years
Lattanzio et al. [56]Italy487 community-dwelling older patients discharged from acute care hospitals1 year
Landi et al. [57]Italy364 community-dwelling older adults10 years
Stenholm et al. [58]Italy996 community-dwelling older adults10 years
Veronese et al. [59]Italy2096 community-dwelling older adults4.4 years
Björkman et al. [60]Finland428 community-dwelling older adults4 years
Verghese et al. [61]United States631 community-dwelling older adults32 months
Ensrud et al. [62]United States1495 community-dwelling older women4.9 years
Chiarantini et al. [63]Italy157 older subjects hospitalized for decompensated heart failure30 months
Comba et al. [64]Italy1621 hospitalized older adults7 months
Corsonello et al. [65]Italy506 older adults discharged from an acute care hospital1 year
Fujita et al. [66]Japan147 hospitalized older adults1 year
Lamers et al. [67]Belgium302 hospitalized older adults4 years
Nastasi et al. [68]United States142 hospitalized older adults5 years
Saitoh et al. [69]Japan463 hospitalized older adults3 years
Tonet et al. [70]Italy/Spain908 hospitalized older adults 288 days
Ungar et al. [71]Italy71 hospitalized older adults 3 months
Volpato et al. [72]Italy87 hospitalized older adults3 months
Charles et al. [73,74]Belgium604 institutionalized older adults3 years
Pamoukdjian et al. [75]France603 older adults with cancer6 months
Baldasseroni et al. [76]Italy235 hospitalized older adults5 years
Klepin et al. [77]United States74 older adults with acute myelogenous leukaemia30 days
Pamoukdjian et al. [78]France190 older adults with cancer6 months
Wang et al. [79]United States95 older adults on the liver transplant waiting list14 months
van Mourik et al. [80]Italy/Netherlands/Canada71 hospitalized older adults1 year
Arnau et al. [81]Spain315 of the oldest old population attending primary care10 years
Minneci et al. [82]Italy561 community-dwelling older adults7 years
Cesari et al. [83]Italy200 older women with gynaecological cancer1 year
Afilalo et al. [84]Canada/United States/France1020 older adult patients undergoing surgical or transcatheter aortic valve replacement1 year
Campo et al. [85]Italy402 hospitalized older adults1 year
Source: Authors.
Table 2. Characteristics of longitudinal studies according to the SPPB classification and mortality outcome (n = 40).
Table 2. Characteristics of longitudinal studies according to the SPPB classification and mortality outcome (n = 40).
AuthorsAge Range (years)SPPB ClassificationMortality Results
Mutambudzi et al. [22]81.1 ± 4.5Three trajectory classes of SPPB scores (low declining, high declining, and high stable)High-declining physical performance—HR: 1.64 (1.32–2.03)
Fortes-Filho et al. [23]79.4 ± 8.3Low (0–4), intermediate
(5–8), and high (9–12) performance
Low (0–4)—HR: 2.70 (1.17–6.21),
intermediate (5–8)—HR: 2.54 (1.17–5.53)
Guralnik et al. [25]>71SPPB scores 0–12, low (≤5) and high performance (8–12)Low ≤ 5, men—HR: 2.3 (1.8–2.9), women—HR: 2.6 (2.0–3.5)
Perera et al. [48]73.9 ± 5.6 SPPB score—continuous variableSPPB score persistently declined in 5 years (1 point change)—HR: 2.48 (1.36–4.50)
Rolland et al. [50]80.5 ± 3.76 Low (0–6), intermediate (7–9), and high performance (10–12)Low (0–6)—HR: 1.50 (0.97–2.33)
Cesari et al. [51]85.6 ± 4.8 SPPB score—continuous variableSPPB score—HR 0.64 (0.48–0.86)
Legrand et al. [52]84.7 ± 3.7Women—low (0–5), intermediate (6–8), and high performance (9–12)/men—low (0–7), intermediate (8–10), and high performance (11–12)SPPB highest tertiles were associated with less risk of death than the lowest tertiles—HR: 0.68 (0.48–0.98)
Tadjibaev et al. [53]70.7 ± 2.3 (65–74)
79.8 ± 3.4 (<75)
SPPB score—continuous variablePoor physical performance (SPPB score) aged 65–74—HR: 2.1 (0.59–7.7) and aged >75 HR: 4.2 (1.5–11.5)
Brown et al. [54]72.2 ± 0.47Low (0–6), intermediate (7–9), and high performance (10–12),
SPPB score—continuous variable
Intermediate (7-9) predicted reduction in mortality—HR: 0.57 (0.37–0.89) and high performance (10-12)—HR: 0.50 (0.32–0.77)
SPPB score (1-unit increase) predicted 12% reduction in mortality—HR: 0.88 (0.82–0.94)
Fox et al. [55]>70Low (≤6), intermediate (7–9), and high performance (10–12)Low (≤6)—HR: 5.30 (1.91–14.72) and intermediate (7-9)—HR: 2.58 (0.89–7.52)
Lattanzio et al. [56]80.1 ± 6.0Low (0–4), intermediate (5–8), and high performance (9–12)Low (0-4)—HR: 2.93 (1.07–8.63)
Landi et al. [57]84.2 (range 80–102)Very low (0–2), low (3–5), moderate (6–8), and high performance (≥9),
SPPB score to analyze physical function in sarcopenic older adults
Higher levels of physical function (SPPB score ≥ 9) were associated with longer survival in sarcopenic older adults
Stenholm et al. [58]Men 74.0 ± 7.0
Women 75.4 ± 7.5
SPPB score classified (inactive, Moderate, and active)Inactive—HR: 1.73 (0.78–3.82) and moderate—HR: 1.26 (0.57–2.79)
Veronese et al. [59]75.2 ± 6.1SPPB score—continuous variableTwo lowest quartiles of SPPB tests—HR: 2.06 (1.27–3.34) and HR: 1.84 (1.10–3.05)
Björkman et al. [60]83.4 ± 4.6SPPB score—continuous variableSPPB score—HR: 0.85 (0.79–0.72)
Verghese et al. [61]79.9 ± 5.3 SPPB score—continuous variableSPPB score (1 point change)—HR: 1.25 (1.06–1.47)
Ensrud et al. [62]87.6 ± 3.3Low (0–3), intermediate (4–9), and high performance (10–12)Low (0–3)—HR: 1.64 (1.24–2.16),
intermediate (4–9)—HR: 1.26 (1.02–1.57)
Chiarantini et al. [63]80 ± 0.5Incapacity (0), low (1–4), intermediate (5–8), and high performance (9–12)Incapacity (0)—HR: 6.06 (2.19–16.76), low (1–4) —HR: 4.78 (1.63–14.02), and intermediate (5–8)—HR: 1.95 (0.67-5.70)
Comba et al. [64]82.0 ± 7.7Low (0–6), intermediate (7–10), high (11–12)Low (0-6)—OR: 0.43 (p = 0.050)
Corsonello et al. [65]80.1 ± 5.9 Low (0–4), intermediate (5–8), and high performance (9–12)Intermediate (5-8)—HR: 0.76 (0.40–1.68) and high (9–12)—HR: 0.51 (0.30-1.05)
Fujita et al. [66]86.5 ± 4.7Incapacity (0), low (1–6), and high performance (7–12)
SPPB score—continuous variable
SPPB score, low—HR: 0.41 (0.22–0.79) and high—HR: 0.26 (0.12–0.58)
Lamers et al. [67]85.9 ± 6.3Low (0–4), intermediate (5–7), and high performance (8–12)Mortality risk higher 59.3% in low score (0–4) compared to high score (8–12)—HR: 0.40 (0.23–0.70) and intermediate—HR: 0.44 (0.29–0.67)
Nastasi et al. [68]Group ≥ 65 SPPB score—impairment (<10)SPPB impairment group—HR: 2.60 (1.00–6.80)
Saitoh et al. [69]85 (range 82–88)SPPB score—continuous variableSPPB score (1-unit decrease)—OR
2.10 (1.11–3.96)
Tonet et al. [70]82 ± 6SPPB score—continuous variableLower SPPB scores—HR: 0.88 (0.82–0.95)
Ungar et al. [71]85.4 ± 2.9SPPB score—continuous variableMortality or hospitalization risk in participants with low SPPB scores: OR: 1.15 (1.01–1.54); mortality or non-fatal stroke risk in participants with low SPPB scores—OR: 1.62 (1.08–2.43)
Volpato et al. [72]77.4 (range 65–93)Low (0–4), intermediate (5–7), and high performance (8–12)Low (0-4)—OR: 5.38 (1.82-15.9)
Charles et al. [73,74]82.9 ± 9.1SPPB score tests (balance, gait speed, and sit to stand chair)—continuous variable
SPPB score (fast decline and moderate decline)—continuous variable
Balance—HR: 0.88 (0.78–0.99), gait speed—HR: 0.89 (0.76–1.03), and sit to stand chair—HR: 0.97 (0.82–1.15)
Fast decline—HR: 1.78 (1.34–2.26) and moderate decline—HR: 1.37 (1.10–1.66)
Pamoukdjian et al. [75]81.2 ± 6.1Impaired mobility (<9), normal mobility (≥9)SPPB score (<9)—HR: 3.03 (1.93–4.76)
Baldasseroni et al. [76]79.6 ± 0.2SPPB score—impairment (<7)Mortality risk higher postoperative—OR 0.77 (0.66–0.89)
Klepin et al. [77]70 ± 6.2SPPB score—continuous variable,
low performance (<9), high performance (≥9)
SPPB score (2 point increase reduced the risk of death by 15%)—HR: 0.85 (0.72–1.01),
low (<9)—HR: 2.2 (1.1–4.6)
Pamoukdjian et al. [78]80.6 ± 5.6SPPB score—impairment (<9)SPPB score—HR: 5.8 (1.6–20.9)
Wang et al. [79]67 (range 66–69)SPPB score—continuous variable SPPB score (1-unit) ≥ 9—HR = 1.57 (0.81–3.05) and <9—HR= 2.36 (1.19–4.66)
van Mourik et al. [80]85.4 ± 2.9High risk (0–6), low risk (7–12)High risk (0–6)—OR: 7.09 (0.70–71.89)
Arnau et al. [81]81.9 ± 4.7SPPB score low (<7) and high performance (≥7)Mortality risk 10-years score (<7)—0.23 and (≥7) —0.37; survival 10-years, SPPB score <7—HR: 1.37 (1.01–1.86)
Minneci et al. [82]72.9 ± 0.3SPPB score—continuous variableSPPB score (1-unit)—HR: 0.92 (0.85– 0.99)
Cesari et al. [83]73.5 ± 6.2SPPB score—continuous variableSPPB score—HR: 0.54 (0.29–0.98)
Afilalo et al. [84]82 (77–86)SPPB score—continuous variableMortality 30 days after cardiac procedure—OR: 4.07 (1.43–11.60) and 1 year—OR: 2.96 (1.75–5.00)
Campo et al. [85]78 ± 6SPPB score—continuous variableSPPB score—OR: 0.74 (0.63–0.85)
Mean ± standard deviation; median (interquartile interval); HR: hazard ratio (95% CI: confidence interval); OR: odds ratio. Source: Authors.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

de Fátima Ribeiro Silva, C.; Ohara, D.G.; Matos, A.P.; Pinto, A.C.P.N.; Pegorari, M.S. Short Physical Performance Battery as a Measure of Physical Performance and Mortality Predictor in Older Adults: A Comprehensive Literature Review. Int. J. Environ. Res. Public Health 2021, 18, 10612. https://doi.org/10.3390/ijerph182010612

AMA Style

de Fátima Ribeiro Silva C, Ohara DG, Matos AP, Pinto ACPN, Pegorari MS. Short Physical Performance Battery as a Measure of Physical Performance and Mortality Predictor in Older Adults: A Comprehensive Literature Review. International Journal of Environmental Research and Public Health. 2021; 18(20):10612. https://doi.org/10.3390/ijerph182010612

Chicago/Turabian Style

de Fátima Ribeiro Silva, Caroline, Daniela Gonçalves Ohara, Areolino Pena Matos, Ana Carolina Pereira Nunes Pinto, and Maycon Sousa Pegorari. 2021. "Short Physical Performance Battery as a Measure of Physical Performance and Mortality Predictor in Older Adults: A Comprehensive Literature Review" International Journal of Environmental Research and Public Health 18, no. 20: 10612. https://doi.org/10.3390/ijerph182010612

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop