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Abstract

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Aim

To determine normative values for the Timed Up and Go (TUG) test in typically developing children and adolescents and to validate its use in individuals with Down syndrome.

Method

Participants in this cross-sectional study were South Brazilian schoolchildren aged 3 to 18 years. In phase 1, 459 typically developing individuals (227 males, 232 females; mean age 10y 8mo (SD 4y 4mo) were included; and in phase 2, 40 individuals with Down syndrome (16 males, 24 females; mean age 10y 6mo (SD 4y 4mo). Anthropometric measurements, real leg length, TUG test scores, and Gross Motor Function Measure (GMFM) scores were evaluated. The association between the TUG test and possible predictive variables was analyzed.

Results

In phase 1, the mean time to perform the TUG test was 5.61 seconds (SD 1.06). Values were stratified in age groups that served as normative data for both sexes. A multiple linear regression analysis was conducted and the best variables to predict TUG scores were age and weight. The best model obtained presented an R2 of 0.25 and a standard error of the estimate of 0.92. Excellent intrasession reliability in the three tests performed (intraclass correlation coefficient [ICC] of 0.93, 0.94, and 0.95) and between the sessions (both with an ICC of 0.95) was demonstrated. In phase 2, the test also showed excellent reproducibility (ICC=0.82 between the two tests performed). The performance time was significantly longer (p<0.001) in individuals with Down syndrome compared with sex- age-, and weight-matched typically developing children with a mean difference of −3.53 (95% confidence interval −4.05 to −3.00). Dimension E of the GMFM (Walking, Running and Jumping) showed the highest correlation (r=−0.55, p<0.001) with the test.

Interpretation

This study provides normative values for the TUG test and shows that TUG scores can be predicted as a function of age and weight in typically developing individuals. The test can also be used for assessment of functional mobility in individuals with Down syndrome.

Abbreviation
TUG

Timed Up and Go

The Timed Up and Go (TUG) test was developed to evaluate alterations of functional mobility in elderly individuals while performing tasks that have the potential to cause falls. The original test measures the time (in seconds) an individual needs to rise from a standard armchair, walk a distance of 3m, turn, walk back to the chair, and sit down again.[1]

The TUG test has been used to assess functional mobility in children and adolescents with diagnoses such as cerebral palsy,[2-12] brain trauma,[3, 6, 7, 13-15] myelomeningocele,[10] leukaemia,[16, 17] sarcoma,[18, 19] cystic fibrosis,[20] and other diseases, who are undergoing rehabilitation. The test includes many of the mobility tasks specified by the International Classification of Functioning, Disability and Health (ICF), which are performed in everyday life by the individual, such as changing the basic position of the body, maintaining the position of the body, self-transfer of position, walking, and moving.[21] The advantage of the TUG test is its simplicity and usefulness in evaluating the functional mobility of patients before, during, and after treatment.

Previous studies evaluated typically developing children in Pakistan[22, 23] and the USA[10, 24] to determine reference values for functional mobility, but no data have been published on the influence of possible predictive values of the TUG test for healthy adolescents aged 13 to 18 years. For Down syndrome, a small sample of children and adolescents was evaluated using the TUG test, but the walking distance was changed to 9m, making it difficult to compare with other studies.[25] However, the mobility and functional balance of children and adolescents with Down syndrome should be evaluated, as they present with a delay in motor acquisitions and the development of balance that may persist in adulthood.[26] Besides, the development of functional independence requires balance during movements in sitting and biped postures, which are both assessed by the TUG test.

Considering the clinical relevance of the TUG test and the scarcity of studies on normalization values for the adolescent age group, we felt it would be useful to obtain parameters for typically developing children and adolescents from the age of 3 to 18 years. This would allow a more appropriate quantification of the performance achieved by children and adolescents with different types of impairment, such as Down syndrome. Thus, the purpose of this study was to determine normative values for the TUG test in typically developing children and adolescents, and to examine its validity in relation to the Gross Motor Functional Measure (GMFM) in a sample of individuals with Down syndrome.

Method

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

This was a cross-sectional observational study divided into two phases. The study was approved by the ethics committee of the Pontifical Catholic University of Rio Grande do Sul (PUCRS; number 11/05518). All the legal guardians of individuals, and individuals over the age of 18 read and signed informed consent forms before the study was performed.

In phase 1, typically developing children and adolescents aged 3 to 18 years, from five schools in the South Brazilian school system were evaluated, during the period from September 2011 to April 2012. Initially, a questionnaire was sent to the legal guardians of the students to document the individual's overall health, together with the consent form. After completing and returning these forms, the children who were healthy according to the questionnaire were selected by convenience sampling to undergo the evaluations at the school itself. Children and adolescents who had a fracture or who had undergone surgery of the lower limbs less than 6 months previously, who had cardiorespiratory and neuromuscular diseases, or intellectual disability, and those who did not perform the test tasks correctly were excluded from the study. TUG scores and age variations of the first 50 individuals included in the study were used to estimate the sample size for multiple linear regression models. Considering a 0.05 level of significance, a power of 90%, a minimum coefficient of determination of 0.22, and the need of a minimal sample for each age group, as well as a balanced distribution between males and females, we estimated that approximately 400 individuals needed to be included.

In phase 2, children and adolescents with a clinical diagnosis of Down syndrome, aged from 3 to 18 years, and recruited at educational institutions in the South of Brazil, were evaluated during the period December 2011 to April 2012. In order to perform comparisons with healthy individuals, those with Down syndrome were paired in a proportion of two typically developing individuals to one individual with Down syndrome according to sex, age, and weight. Consent forms were handed to the legal guardians and then the children and adolescents were selected by convenience sampling. In this phase, children who were unable to understand and perform the test tasks correctly were excluded. The sample size for phase 2 was estimated based on the first 26 participants with Down syndrome included in this study. Thus, it was estimated that 34 individuals had to be included in each group (healthy and Down syndrome) to identify differences in the TUG test of at least 2 seconds among typically developing children and adolescents and those with Down syndrome, with a significance of 0.05 and a power of 90%.

Procedures

The evaluations were performed in the following order: anthropometric measures (weight and height), measurement of real length of lower limbs, and the TUG test (phases 1 and 2). GMFM assessments were performed during phase 2, at the end of these evaluations, in order to determine TUG validity.

The anthropometric evaluation was done by measuring weight and height until two identical values were obtained. Weight was obtained with individuals in an orthostatic position, with a minimum of clothing, no shoes, and using a digital balance (Britannia; Sao Paulo, Brazil), previously calibrated to a 100g precision. Height was obtained with the participants barefoot, feet in a parallel position, arms extended along the body, with the head positioned so that the lower part of the ocular orbit was on the same level as the external orifice of the ear.[27] Height was measured using a portable stadiometer (Wiso; Sao Paulo, Brazil) with a 1mm precision. Real leg length was determined by measuring the distance between the anterosuperior iliac spine and the medial malleolus of each limb. The centiles of body mass index (BMI) for age were calculated according to the reference distribution of the Centers of Disease Control Prevention,[28] (available at: http://apps.nccd.cdc.gov/dnpabmi/Calculator.aspx?CalculatorType=Metric).

Physical activity was evaluated through a health questionnaire containing questions on the type, duration, and frequency of the activity which was confirmed with all the individuals or their teachers. All individuals performing exercise for 30 minutes, at least three times a week were considered as physically active.

The TUG test consists of rising from a chair positioned 3m from a wall, walking 3m, turning around, returning to the chair, and sitting down again.[1] The test was performed according to the modifications for children described in the study by Williams et al.[10] For each TUG evaluation, three measures are recommended and the final result is the shortest time obtained. The verbal command included instructions about velocity such as: ‘walk as fast as possible’. This adaptation was proposed because TUG results are less variable when instructions are given regarding velocity.[29] The modifications for the use of the TUG test in paediatrics are (1) using a specific task of touching a target on the wall; (2) instructions may be repeated during the test, (3) the chair used for the test must have a back but no arms and the height will be accepted when the angle measured with a goniometer is 90º (SD 10º) of knee flexion, with the feet supported on the floor; and (3) counting time must begin when the child gets up from the chair, and stop when the child sit in the chair.[10] TUG test evaluations were performed by the same rater, with more than 5 years of experience in paediatric physiotherapy, and the individuals were evaluated wearing comfortable clothes and shoes. First, the test was demonstrated to the participants who then performed it once as a training test in order to familiarize them with what was expected. As recommended,[10] the individuals performed the TUG test (TUG1) three times and the test done in the shortest time was taken as the final result. In order to evaluate test reproducibility, the TUG test was also performed after a 1 to 2-hour interval (TUG2), in all individuals and in both phases of the study. Finally, the TUG test was also performed after 1 week (TUG3) in a sub-sample of individuals from phase 1.

The GMFM, which was used in phase 2 of this study, is a measurement for the purpose of evaluating changes in gross motor function in children with cerebral palsy, but it has been used in studies of children with Down syndrome, and it has already been validated for this use.[30-33] The GMFM consists of 88 items grouped in five dimensions: (A) Lying and Rolling, (B) Sitting, (C) Crawling and Kneeling, (D) Standing, and (E) Walking, Running and Jumping. Each item is evaluated on a 4-point scale (0 – does not initiate, 1 – initiates, 2 – partially completes, and 3 – completes), and higher scores indicate better gross motor function. Each task was given a score according to the instructions in the GMFM-88 Manual.[34] The total score of each dimension is converted into percentages and the five dimensions have an equal weight in calculating the total score, which includes the sum of the percentages of the dimensions divided by five. In order to perform the GMFM items the child was wearing as few clothes as possible and did not wear shoes. The evaluation was performed by a physical therapist who had training in and experience of using the GMFM.

Statistical analysis

The Kolmogorov-Smirnov test was used to evaluate the normality of the data. The variable's distributions were consistent with a normal distribution and presented as mean and standard deviation (SD). The correlations were evaluated using Pearson's rank correlation coefficient test. Multiple linear regression analysis was performed to evaluate the contribution of weight, height, age, sex, race, BMI centile, physical activity, and leg length, in generating reference equations for the TUG test. The most significant factors were added to the model at each step and the process continued until no further significant contributing factor could be added. The best predictive model was then presented, as well as its standard error of the estimate. Test reproducibility was evaluated using the intraclass correlation coefficient (ICC), in which values above 0.75 indicate excellent reproducibility. For the comparisons between typically developing individuals and those with Down syndrome, they were paired in a proportion of two typically developing individuals to one individual with Down syndrome according to sex, age, and weight. Because of the limited number of individuals in one specific group, the Mann–Whitney U test was used to identify significant differences. Also, the effect size for the comparisons in each age group was calculated using the Effect Size Calculator tool available on the internet (http://www.cem.org/evidence-based-education/effect-size-calculator). The level of significance alpha was 5% (0.05). All analyses and the data processing were performed using the Statistical Package for Social Sciences, version 18.0 (IBM Corporation, NY, USA).

Results

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Phase 1: TUG test in typically developing children and adolescents

Five hundred and ninety-eight questionnaires on health and consent forms were delivered to the participating schools; 78 forms were not returned. Of the 520 that were returned, 48 were excluded because the child had some health problem, resulting in 472 children and adolescents selected through the health questionnaire. Thirteen of these children did not cooperate, therefore the study was composed of 459 participants (227 males, 232 females; 74% white). Table 1 shows the data characterizing the sample of this phase of the study, besides the normative values (mean and SD) of the TUG test for the entire sample and stratified by age group.

Table 1. Characterization of the sample and normative values for the Timed ‘Up and Go’ (TUG) test in typically developing children and adolescents according to age group
Variables3–5y (n=74)6–9y (n=130)10–13y (n=129)14–18y (n=126)Total (n=459)
  1. Variables expressed as mean (SD), except sex and physical activity, expressed as percentage. TUG 1 and TUG 2 are expressed as mean (SD, standard deviation/IR, interquartile range). BMI, body mass index; PA, physical activity; TUG1, first test; TUG2, retest on same day.

Age (y)4.6 (0.9)7.7 (1.2)12.0 (1.2)16.5 (1.4)10.8 (4.4)
Sex, (male/female)41/3366/6453/7667/59227/232
Weight, kg19.4 (4.0)27.8(7.1)47.1 (14.6)61.9 (12.0)41.2 (19.2)
Height, cm106.5 (8.1)126.0 (9.5)151.6 (10.2)167.3 (9.4)141.4 (23.8)
Right leg length, cm52.84 (5.02)64.87 (5.99)80.32 (5.78)87.55 (9.35)73.50 (14.31)
Centile BMI74.6 (21.5)63.7 (27.0)59.6 (30.1)55.0 (27.7)61.9 (28.0)
PA,%5.430.035.749.232.9
TUG1 (s)6.59 (1.36/1.71)5.69 (0.83/1.18)5.57 (0.75/0.94)4.99 (0.87/1.29)5.61 (1.06/1.25)
TUG2 (s)6.57 (1.28/1.67)5.65 (0.80/1.00)5.58 (0.72/0.93)4.97 (0.85/1.27)5.60 (1.02/1.16)
Table 2. Detailed results of the best model obtained
Dependent variable TUGCoef.95% CIStd. coef. p R 2
  1. TUG, Timed ‘Up & Go’ (seconds); Coef, unstandardized coefficient; CI, confidence interval; Std. coef., standardized coefficient; p, significance level; R2, coefficient of determination.

Independent variables
Constant6.8376.616–7.018  0.25
Age−0.166−0.204 to −0.129−0.702<0.001 
Weight0.0140.005–0.0220.2540.002 
Table 3. Characterization of the sample of children and adolescents with Down syndrome according to Dimension E of the GMFM
Variables50%–69% DimE (n=6)70%–89% DimE (n=16)9%–100% DimE (n=18)Total (n=40)
  1. Variables expressed as mean (SD), except sex expressed as percentage. GMFM, Gross Motor Function Measure; DimD, Dimension D of GMFM (standing); DimE, Dimension E of GMFM (Walking, Running and Jumping); TUG, Timed ‘Up & Go’; TUG1, first test (n=40); TUG2, retest same day (n=37).

  2. an=4; bn=15; cn=37.

Age (y)6.3 (4.6)9.3 (3.4)13.2 (3.6)10.6 (4.4)
Sex, (males/females)3/36/107/1116/24
Weight, kg26.1 (24.0)33.2 (14.1)48.0 (18.6)38.8 (19.5)
Height, cm106.1 (25.7)123.3 (18.9)136.0 (12.4)126.4 (20.0)
Right leg length, cm52.1 (14.8)63.3 (11.9)70.7 (7.2)64.9 (12.1)
GMFM DimD82.5 (14.2)92.0 (4.4)97.0 (4.1)92.8 (8.1)
GMFM DimE58.3 (3.5)77.7 (5.5)95.3 (3.3)82.7 (13.9)
GMFM total86.6 (3.5)93.3 (2.6)98.5 (1.2)94.6 (4.7)
TUG1 (s)11.24 (2.47)9.42 (1.15)8.26 (1.97)9.17 (2.01)
TUG2 (s)10.76 (1.85)a9.73 (2.01)b8.17 (1.84)9.08 (2.09)c
% of Predicted184.9 (52.6)165.0 (27.6)156.2 (39.8)164.0 (37.9)
z-score4.8 (2.6)3.5 (1.3)2.8 (1.9)3.4 (1.9)

The use of multiple linear regression analysis, with a 0.05 significance level, revealed that the best model obtained to predict TUG values included the variables age (r=−0.48; p<0.001) and weight (r=−0.35; p<0.001), explaining 25% of the variation of the TUG test (R2=0.25). The standard error of the estimate for this model was 0.92. Details of the model, including 95% confidence intervals, are presented in Table II. The procedure stops adding variables when the fit does not significantly improve, as measured by the p value, or change in likelihoods. Thus, other variables such as height (r=−0.44), lower limb length (r=−0.44), race, physical activity, sex, and BMI centile (r=0.19), were not included, as these did not improve the prediction power (R2) of the model. Based on these results and using age and weight as predictors, the TUG test can be predicted for this population using the following reference equation:

  • display math

Correlating the TUG values predicted by the equation proposed in this study and the absolute values (TUG1 and TUG2) obtained by the sample studied, a moderate and significant positive correlation was found (r=0.50; p<0.001), as shown in Figure 1.

image

Figure 1. Dispersion graphs showing values in seconds of Timed ‘Up & Go’ (TUG) test predicted by the equation proposed regarding the absolute values obtained in TUG1 (a) and TUG2 (b) in typically developing children and adolescents.

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Evaluating reproducibility, excellent intrasession (between the three measures performed in each test) reliability was demonstrated (n=459) for the three assays of TUG1, TUG2 (retest on the same day) and TUG3 (test and retest after 1wk) with ICCs of 0.93, 0.94, and 0.95 respectively. Besides this, the TUG test showed high inter-session reproducibility on the same day (TUG 1 × TUG 2; n=459) and after 1 week (TUG 1 × TUG 3; n=178), both with an ICC of 0.95. Figure 2 shows a Bland-Altman graph in which 96% of the differences were within 2SDs of the mean, demonstrating that the TUG1 and TUG2 tests (Fig. 2a) and TUG1 and TUG3 (Fig. 2b) are similar and present excellent reproducibility.

image

Figure 2. Bland-Altman graphs showing the differences between the ‘Timed ‘Up & Go’ (TUG) test phases 1 and 2 (a) test and retest on the same day, and between and between TUG1 and TUG3 (b) test and retest after 1 week, compared with the mean of these values in typically developing children and adolescents. The solid lines indicate the mean differences between measurements and the dotted lines, the 96% limits of concordance.

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Phase 2: TUG test in children and adolescents with Down syndrome

Forty-four of the 56 consent forms handed in at the educational institutions signaled agreement to participate. Three of these did not cooperate and one was not present on the day of the test. Thus, the final sample of phase 2 was composed of 40 participants, (age 3–18y; 16 males, 24 females). Table III shows the data characterizing the sample of this phase, as well as TUG values in the total sample stratified by percentage interval of Dimension E (Walking, Running and Jumping) of the GMFM.

Test reproducibility on the same day was evaluated in 37 participants and presented as excellent with an inter-session (TUG 1 × TUG 2) ICC of 0.82. The entire sample of children and adolescents with Down syndrome was tested concurrently using the GMFM. This analysis revealed a moderate negative correlation between the TUG scores and the total score of GMFM (r=−0.49; p=0.001), indicating that smaller values of the TUG test are associated with higher percentages of GMFM scores, i.e. that better functional mobility is associated with better gross motor function. Also, correlating Dimension E, which evaluates dynamic balance in walking, running, and jumping activities, with the values of the TUG test, a moderate negative correlation was also obtained (r=−0.55; p<0.001). The other independent variables, such as age (r=0.21; p=0.2), height (r=−0.29; p=0.07), and weight (r=−0.20; p=0.23) were also correlated with TUG scores, but showed weak correlations. In this way, stratification of the results was performed according to the percentage intervals of Dimension E of the GMFM.

Children and adolescents with Down syndrome demonstrated higher TUG scores than typically developing individuals, in other words, individuals with Down syndrome have less functional mobility. To demonstrate this difference a sample of 80 typically developing children and adolescents was used, paired by age, weight, and sex with 40 individuals with Down syndrome. The comparisons were performed according to age groups (3–5y; 6–9y; 10–13y; 14–18y), and no significant difference was found between age and weight. Forty per cent of the sample were male (32 for healthy and 16 for those with Down syndrome). The mean of the TUG values was significantly (p<0.001) higher in children and adolescents with Down syndrome compared with typically developing individuals in all age groups (Fig. 3a). The effect size for the difference in means of the TUG values between children with Down syndrome and typically developing individuals, in each age group, was: 3–5, 2.55; 6–9, 3.54; 10–13, 3.32; 14–18, 2.09. Indeed, only nine individuals performed the TUG test with values above a z-score of −2, reinforcing the functional mobility limitations (Fig. 3b).

image

Figure 3. (a) Box plot showing the comparison of values for the Timed ‘Up & Go’ (TUG) test, per age group and in the total sample, between typically developing children and adolescents (n=80) and in those with Down syndrome (n=40). *Indicates significant difference (p<0.05) compared with the control group in a same age group using the Mann–Whitney U test. The number above the boxes represents the sample size for each group. Rectangles represent 50% of participants, whiskers show range of values, and bold lines show median value. (b) Dispersion graph showing the absolute TUG test values in individuals with Down syndrome and the respective z-score classification according to the reference data. The dotted line indicates the −2.0 z-score limit.

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Calculating the TUG values predicted by the equation proposed in this study, a weak correlation was found with the absolute values of TUG1 (r=0.19; p=0.24) in individuals with Down syndrome (Fig. 4a). However, a moderate negative correlation (r=−0.55; p<0.001) was demonstrated in Dimension E of the GMFM (Fig. 4b), indicating that, for individuals with Down syndrome, the evaluation of gross motor function is more closely associated with functional mobility than the variations of age and body weight.

image

Figure 4. Dispersion graphs in children and adolescents with Down syndrome. (a) Correlation between the values in seconds of Timed ‘Up & Go’ (TUG) test predicted by the equation proposed and the absolute values obtained in TUG1; and (b) correlation between the scores of Dimension E of the Gross Motor Functional Measure (GMFM) in percentage and the absolute values in seconds obtained in TUG1.

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Discussion

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

The results of this study show normative values for the TUG test in typically developing children and adolescents demonstrating that the time to perform the test can be explained, at least in part, by age and body weight. The study also presents functional mobility data in a sample of individuals with Down syndrome, evidencing a longer time taken by these patients to perform the test.

This is the first study evaluating the influence of anthropometric variables on time to perform the TUG test in typically developing adolescents aged 13 to 18 years. The TUG test values stratified by age intervals and presented in Table 1 can be used as normative values for the paediatric population. Previous studies showed TUG data in children from Pakistan[22, 23] and the USA.[10, 24] In general, the TUG values of children of the same age group in our sample were similar to those presented by one each of the USA[10] and Pakistan[23] studies, without any differences higher than 0.8 seconds in the mean. However, when our results were compared with the study by Marchese et al.,[24] differences of up to 2 seconds were observed in means and medians. No difference between the sexes was found in the TUG values in our study, corroborating the findings of the US study.[10] On the other hand, the females in the Pakistani study had higher values than the males, but this result was ascribed by the authors to the fact that (1) the females wore a chador (head covering) which may have limited their mobility, and (2) to specific cultural and behavioral issues.[23]

This study also presents an equation generated from a multiple linear regression model to predict the value of the TUG test. This equation uses age and weight of children and adolescents as predictive variables, resulting in a predictive power of 25%. Although the power of the model presented is not very high, which is a limitation of the present study, it is still greater than in the only other study that used a similar regression model, demonstrating only age as a predictive variable and explaining only 18% of the behavior of the TUG test.[22] A major differential factor was that in the study by Habib et al.,[22] 180 children were evaluated, whereas our sample comprised 459 individuals. In spite of that, reference values allow individual data normalization for each patient in different ways, including the use of a z-score. Considering that significant variations usually include changes in 2 z-score units and that the TUG test standard deviation is approximately 1.05, results may be interpreted as clinically important when changes in the TUG results are around 2.01 seconds.

Considering that the TUG test is a practical tool to evaluate functional mobility and balance, these reference values may help in the evaluation of specific groups, such as individuals with Down syndrome. Our results indicate that children and adolescents with Down syndrome present higher TUG values compared with typically developing individuals. As far as we know, this is the first study to evaluate the TUG test in the paediatric population with Down syndrome without altering the original 3m distance. The study by Villamonte et al.,[25] which also evaluated individuals with Down syndrome, altered the walking distance of the test to 9m, making it difficult to compare their results, besides having studied a small and heterogeneous sample of 21 individuals aged 5 to 31 years. Another major concern is test reproducibility. Our results show excellent inter-session reproducibility in typically developing individuals (ICC=0.95) and, despite the lower value of ICC (0.82), the test was also reproducible in individuals with Down syndrome. In the only previous study with individuals who had Down syndrome, the reproducibility presented was at most 0.24. Thus, based on the data presented here, it is suggested that the TUG test is a valid tool to evaluate functional mobility and could be used as a screening test in children and adolescents with Down syndrome.

In individuals with Down syndrome, the correlations between the TUG and the anthropometric variables were smaller than the correlation found with the GMFM, showing that the TUG results (time in seconds) depend more on the gross motor function than on the anthropometric characteristics of individuals with Down syndrome. Further, the TUG test showed a better correlation with the scores of Dimension E of the GMFM, as this evaluates the dynamic balance of the walking, running, and jumping activities. Similar results were described for patients with cerebral palsy, in whom the TUG test was also correlated inversely and significantly with the total score and Dimension E of the GMFM.[4, 5, 10] These findings are important in clinical practice, as they indicate that a shorter time performing the TUG test is associated with higher scores in Dimension E, or even in the total of the GMFM. The GMFM assessment remains the criterion standard for investigating motor function in children with Down syndrome, as it includes analysis of how several tasks are performed (lying, rolling over, sitting, crawling, kneeling, standing, walking, running, and jumping). However, as it takes about 45 minutes, it is suggested that the TUG test, being quick and easy to perform, could be used as a screening test for the GMFM.

In conclusion, this study presents the time scores of the TUG test of a typically developing paediatric population, stratified by age intervals that can be used as normative values for children and adolescents. It also proposes an equation generated by multiple linear regression analysis in which it is possible to predict the values of the TUG test using the variables age and weight. Furthermore, it demonstrates that the TUG can be used as a screening test for functional mobility of children and adolescents with Down syndrome, and based on the TUG test outcome it can be decided whether further assessment with the GMFM is indicated. Taken together, these data can help evaluate and follow up children and adolescents with different functional impairments.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Renata D'Agostini Nicolini-Panisson was supported with a scholarship from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). The authors thank Professor Helio Radke Bittencourt for statistical advice. The authors have stated that they had no interests which might be perceived as posing a conflict or bias.

References

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
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