With great interest, we read the study by Tong et al. (2023), which is relevant for clinicians and researchers. The study by Tong et al. (2023) is a prospective study that aimed to determine which specific mobility tests were the most accurate for predicting falls in physically active older adults living in the community. Seventy-nine physically active older adults were assessed by 30-s sit-to-stand test, five times sit-to-stand test, single-task timed up and go (TUG) test, motor dual-task TUG, and cognitive dual-task TUG and were followed up for 12 months. The authors concluded that the dual-task TUG test was the most accurate to predict falls in healthy older adults.

The TUG test is a relatively simple and inexpensive test that consists of a patient rising from a chair without using the arms for assistance and walking to a turning point (3 m length), walking back, and sitting down on the same chair. The main outcome of the TUG test is time, that is, the faster the patient performs, the better the result is (Reynaud et al., 2019). The TUG test is very useful in clinical settings and research to assess mobility, functionality, fall risk level (Reynaud et al., 2019), and prognosis in selected patients (Chua et al., 2020; Son et al., 2020). Moreover, the TUG test performance is useful to compare before and after clinical interventions, such as rehabilitation programs.

However, reference values are useful to obtain a more accurate interpretation of the TUG test. If a clinician or a researcher uses a reference value from a different country (and, consequently, with different cultural, social, economic, and biological characteristics) to interpret the exam, a significant misinterpretation can happen (Table 1). Variations in the reported time of the TUG test are observed not only in terms of age group and sex but also in terms of countries and protocols. For that, other determinant variables were identified, such as weight, height, body mass index, socioeconomic status, and physical activity level, as influences on the time taken to perform the TUG test. Anthropometric and demographic indices add specific information about a population (Furlanetto et al., 2022; Kear et al., 2017; Tan et al., 2023). This is of great clinical relevance if we consider the minimally significant difference already established in several adult populations, such as 1.62 s for total hip arthroplasty (Yuksel et al., 2021) and 1.3 s for multiple sclerosis with mild disability (Valet et al., 2019; Table 2).

Table 1

Reference Values for the TUG Test in Healthy Individuals From Different Countries

StudyCountryAge (years)SampleTTUGTTUG difference from China (Chen & Tang, 2016)
Chen and Tang (2016)China>5064 (46 men)8.3 s
Nakhostin-Ansari et al. (2022)Iran18 to ≥70240 (120 men)8.1 s0.2 s
Tee et al. (2016)Philippines20–40276 (135 men)6.7 s1.6 s
Sundarakumar et al. (2022)India45 to ≥751,863 (870 men)12.5−4.2 s
Sivakumar et al. (2018)India19–70413 (161 men)10.1 s−1.8 s
Khant et al. (2018)India40–70520 (313 men)8.5 s−0.2 s
Kear et al. (2017)United States20–59200 (89 men)9 s−0.7 s
Hammarén et al. (2014)Sweden20–59220 (111 men)7.6 s0.7 s
Tsubaki et al. (2010)Japan50–79172 (80 men)5.8 s2.5 s
Isles et al. (2004)Australia20–79456 women6.5 s1.8 s
Abizanda Soler et al. (2012)Spain>70993 (392 men)12.7 s−4.4 s
Lihavainen et al. (2012)Finland>75668 (348 men)14.8−6.5
Long et al. (2020)Asia>608,9418.7−0.4
Europe10.1−1.8
South America9.5−1.2
Oceania7.80.5

Note. TUG = timed up and go; TTUG = time to complete timed up and go.

Table 2

Minimal Detectable Change for the TUG Test in Specific Clinical Conditions

StudyMethodsPopulationSampleAge (years)MDC TUG test (s)
Mean (SD)
Yuksel et al. (2021)TUGTotal hip arthroplasty37 (12 men)58.4 (12.9)1.62
Valet et al. (2019)TUGMultiple sclerosis with mild disability63 (14 men)43 (9)1.3
Chan et al. (2017)Mot-TUGStroke survivors33 (22 men)60.2 (6.4)3.53
Yuksel et al. (2017)TUGTotal knee arthroplasty48 (72.2% women)65.62 (9.66)2.27
Huang et al. (2011)TUGMild to moderately severe Parkinson disease72 (44 men)67.5 (11.6)3.5

Note. MDC = minimal detectable change; TUG = timed up and go; Mot-TUG = motor dual-task timed up and go.

In addition, the TUG test was shown to be a strong and independent predictor of short-term mortality among Chinese older adults (Chua et al., 2020). It was also demonstrated that slower TUG test speed among Korean older adults was associated with an increased risk of developing myocardial infarction, congestive heart failure, and mortality (Chun et al., 2019; Table 3). Hence, several countries have already established reference values for the time to complete the TUG test for older adults, such as China (Chen & Tang, 2016), Japan (Tsubaki et al., 2010), Australia (Isles et al., 2004), Philippines (Tee et al., 2016), India (Khant et al., 2018; Sivakumar et al., 2018; Sundarakumar et al., 2022), Iran (Nakhostin-Ansari et al., 2022), Sweden (Hammarén et al., 2014), United States (Kear et al., 2017), Spain (Abizanda Soler et al., 2012), and Finland (Lihavainen et al., 2012), and reference values have also been established for subgroups of continents (Asia, Europe, South America, and Oceania; Long et al., 2020; Table 1). In addition, TUGBrasil is a multicenter study that aims to establish reference values for the TUG test in Brazil with an estimated 3,000 healthy participants, equally distributed between age and gender groups according to the proportion of the population among the five Brazilian regions. The sample size of the TUGBrasil study is 1,500 participants aged 7–12 years (Phase 1) and 1,500 participants aged 13–18 years (Phase 2). From a methodological point of view, the TUGBrasil study has a design that represents all Brazilian regions as it is a country with great demographic, socioeconomic, and cultural diversity.

Table 3

Cutoff Point for the TUG Test in Specific Population

StudyMethodsPopulationSampleAge (years)PredictorCutoff point TTUG (s)
Mean (SD)
Tong et al. (2023)Cog-TUGPhysically active older adults79Falls10.98
Chun et al. (2019)TUGKorean older adults1,084,875 (46.3% men)66Myocardial infarction, congestive heart failure, and mortality20
Reynaud et al. (2019)TUGIndividuals with chronic obstructive pulmonary disease5066.2 (8.2)Falls11
Chua et al. (2020)TUGChinese older adults13,789 (59.0% women)74 (6)Short-term mortality25.4
Lee et al. (2020)TUGKorean older adults39,519 (46.7% men)66Functional dependency>10

Note. TUG = timed up and go; TTUG = time to complete TUG; Cog-TUG = cognitive dual-task timed up and go.

In this context, it is worth mentioning that the TUG test has been validated for older adults (Podsiadlo & Richardson, 1991) and modified for children and adolescents (Williams et al., 2005). However, there are variations in application methods of the TUG test that may influence the interpretation of the test in clinical practice, such as the use of the curve marker (e.g., line on the floor and a touch target on the wall or cone), speed instructions (e.g., generic instructions about conducting the test and walking at a normal or rapid speed), verbal commands (e.g., “go” or “get up from the chair, walk to a tape placed on the floor, turn, return back to the chair”), and number of attempts (most studies report two or three tests) (Bustam et al., 2019). In addition, the subtypes of TUG test are single task, dual motor (e.g., hold a glass of water and get a glass of water), or cognitive task (e.g., counting down to three, naming animals, and reciting months in reverse order), which can add heterogeneity when performing the TUG test. Attention in dual tasks matters and may affect the outcomes (Zijlstra et al., 2008). It is recommended that the task be chosen according to the individual’s ability limit without causing excessive stress. Thus, the particularities of each clinical condition (e.g., Parkinson’s disease and stroke) must be taken into account, which may require functional tests with different stimuli (cognitive and motor) for more accurate identification of functional performance (Dibble & Lange, 2006; Chan et al., 2017; Shumway-Cook et al., 2000; Table 4). Therefore, we reinforce the predictive value of the TUG test in dual tasks, including turns and other transfers, or cognitive tasks in selected patients.

Table 4

Reference Values for the TUG Test Subtypes in Healthy Individuals and Specific Clinical Conditions

StudyCountryAge (years)SampleType TUG testTime
Chen and Tang (2016)China>5064 (46 men) healthyTUG single task8.3 (4.6–14) s
Cog-TUG9.2 (5.4–18.8) s
Mot-TUG11.5 (5.9–35.4) s
Åhman et al. (2020)Sweden70 ± 11166 healthyTUG single task10.1 (9–11.4) s
TUGdt NA11 (9.8–13.8) s
TUGdt MB11.1 (9.6–14) s
Smith et al. (2017)Ireland73 ± 537 (14 men) healthyTUG single task9.3 ± 2.3 s
Cog-TUG11.2 ± 2.7 s
Mot-TUG10.4 ± 2.8 s
Dibble and Lange (2006)United States69.9 ± 11.255 idiopathic Parkinson diseaseTUG single task11.67 ± 5.51
Cog-TUG16.48 ± 11.63
Shumway-Cook et al. (2000)United States78 ± 615 without history of falls

15 with a history of two or more falls in the previous six months
TUG single taskNo fallers: 8.4 ± 1.7 s

Fallers: 22.2 ± 9.3 s
Cog-TUGNo fallers: 9.7 ± 2.3 s

Fallers: 27.7 ± 11.6 s
Mot-TUGNo fallers: 9.7 ± 1.6 s

Fallers: 27.2 ± 11 s
Chan et al. (2017)ChinaHealthy: 61.8 ± 4.5

Stroke: 60.1 ± 6.4
32 (11 men) healthy older adults and 32 (22 men) chronic stroke survivorsMot-TUGHealthy: 12 ± 2.3 s

Stroke: 18.3 ± 5.7 s

Note. TUG = timed up and go; Mot-TUG = motor dual-task timed up and go; Cog-TUG = cognitive dual-task timed up and go; TUGdt NA = timed up and go dual-task naming animals; TUGdt MB = timed up and go dual-task months backward.

It is important to pay attention to the conduct of studies when analyzing reference values for the TUG test. In this sense, metrics such as standard deviation can provide information on not only factors own to the person being assessed but also factors such as the lack of standardization of the protocols adopted. Furthermore, it is worth analyzing the possibility of bias due to inadequate sample size as very small samples may not accurately represent the population of interest. This may imply results observed by chance. In short, this editorial reinforces the possibility of variation in the time taken to perform the TUG test between countries and the need to establish local reference values considering the methods of applying the TUG test and its subtypes.

Finally, we congratulate the study by Tong et al. (2023) and the Journal of Aging and Physical Activity for the initiative, and we encourage researchers to establish reference values for the TUG test using a representative population.

Acknowledgments

All authors have made substantial contributions to the manuscript. All authors have read and accepted the final version of the manuscript.

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