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. 2016 Aug 26;38(5-6):525–533. doi: 10.1007/s11357-016-9935-9

Tinetti mobility test is related to muscle mass and strength in non-institutionalized elderly people

Francesco Curcio 1, Claudia Basile 1, Ilaria Liguori 1, David Della-Morte 2,3, Gaetano Gargiulo 4, Gianluigi Galizia 1,5, Gianluca Testa 1,6, Assunta Langellotto 1,7, Francesco Cacciatore 1, Domenico Bonaduce 1, Pasquale Abete 1,✉
PMCID: PMC5266213  PMID: 27566307

Abstract

Elderly people are characterized by a high prevalence of falls and sarcopenia. However, the relationship among Tinetti mobility test (TMT) score, a powerful tool to detect elderly people at risk of falls, and sarcopenia is still not thoroughly investigated. Thus, to determine the relationship between TMT score and muscle mass and strength, 337 elderly participants (mean age 77.1 ± 6.9 years) admitted to comprehensive geriatric assessment were enrolled. TMT score, muscle mass by bioimpedentiometer, and muscle strength by grip strength were evaluated. Muscle mass progressively decreased as TMT score decreased (from 15.3 ± 3.7 to 8.8 ± 1.8 kg/m2; p for trend <0.001). Similarly, muscle strength decreased progressively as Tinetti score decreased (from 34.7 ± 8.0 to 23.7 ± 8.7 kg; p for trend 0.001). Linear regression analysis demonstrated that TMT score is linearly related with muscle mass (y = 4.5x + 0.4, r = 0.61; p < 0.01) and strength (y = 14.0x + 0.8, r = 0.53; p < 0.01). Multivariate analysis confirms the strong relationship between the TMT score and muscle mass (r = 0.48, p = 0.024) and strength (r = 0.39, p = 0.046). The present study indicates that TMT score is significantly related to muscle mass and strength in non-institutionalized elderly participants. This evidence suggests that TMT score, together with evaluation of muscle mass and strength, may identify sarcopenic elderly participants at high risk of falls.

Keywords: Tinetti mobility test, Sarcopenia, Falls

Introduction

Sarcopenia is characterized by an age-related loss of muscle mass and strength and is highly prevalent in advancing age, especially in participants aged 80 years and older (Baumgartner et al. 1998; Iannuzzi-Sucich et al. 2002; Bijlsma et al. 2013). More specifically, sarcopenia is defined as appendicular skeletal muscle mass <7.26 kg/m2 in men and <5.5 kg/m2 in women (Baumgartner et al. 1998). Sarcopenia increases the risk of morbidity (Rantanen et al. 1994, 1999; Taekema et al., 2010) and mortality (Metter et al. 2002; Ling et al. 2010) in the elderly, especially in institutionalized elderly nursing home residents (Landi et al. 2012). The etiology and pathogenesis of sarcopenia is very complex and several factors, i.e., physical inactivity, hormonal, metabolic, and nutritional and inflammatory state, are involved (Cruz-Jentoft et al. 2010).

Thirty percent of community-dwelling people aged 65 years or older fall each year, and among people aged 85 years or older, the percentage increases to almost 40 % (Akyol 2007; Ganz et al. 2007). Falls frequently have severe consequences in this population, with significant effects on the health system (Close et al. 2012). Older community-dwelling people who fall will present a fall-related injury (from 12 to 42 %), and almost 20 % will require medical attention and 10 % experience a fracture secondary to osteoporosis (Yildiz et al. 2012).

Thus, it is important to identify risk factors for accidental falls in the community. Recently, in a systematic review, muscle strength, gait, and balance impairments were found to be the strongest risk factors for falls among non-institutionalized older adults (Moreland et al. 2004). In particular, reduction of muscle strength in lower or upper extremity significantly increased the risk for injurious falls (Moreland et al. 2004). However, very few data are available about the effect of age-related loss of skeletal muscle mass and strength on routine test for detecting the risk of falls in the elderly.

The Tinetti mobility test (TMT) or performance-oriented mobility assessment (POMA) is a reliable and valid clinical test to measure balance and gait in the elderly (Tinetti 1986; 2003; Raiche et al. 2000). It includes measures of static, dynamic, reactive, and anticipatory balance and of ambulation and transfer ability. The test can be quickly administered within 5 min, and it is frequently incorporated into a comprehensive geriatric assessment (CGA).

Thus, in the present study we aimed to investigate the relationship between muscle mass and strength and the risk of fall evaluated by TMT in elderly participants who underwent CGA, including several clinical and biochemical parameters.

Methods

Study population

The study enrolled 337 elderly (≥65 years) consecutive participants admitted to the “Comprehensive Geriatric Assessment Center” of the Azienda Ospedaliera Universitaria Federico II (Naples, Italy). The study received full ethical approval from the “Research Ethics Committee” in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. All participants signed an informed consent form, and the institutional review boards approved the study. Anthropometric measurements including age, sex, body mass index (BMI), and waist circumference (WC) were performed.

Comprehensive geriatric assessment

Elderly participants underwent a comprehensive geriatric multidimensional evaluation which included the following: cognitive function evaluation with mini-mental state examination (Cacciatore et al. 1997); depressive symptoms with geriatric depression scale (Testa et al., 2011); comorbility and comorbidity severity with a cumulative illness rating scale (CIRS-comorbidity and CIRS-severity) (Testa et al., 2009) and drug number; disability with basic and instrumental activity of daily living (BADL and IADL) (Katz et al. 1963; Lawton and Brody 1969); nutritional assessment by mini-nutritional assessment (MNA) (Kaiser et al. 2010); physical performance with 4-m gait speed (m/s) (Goldberg and Schepens 2011); physical activity with physical activity scale for the elderly (PASE) (Cacciatore et al. 2013); and social support evaluation with social support assessment (SSA) scored from 17 (participants with the lowest support) to 0 (participants with the highest support) (Mazzella et al. 2010).

Tinetti mobility test or performance-oriented mobility assessment

The TMT or POMA was employed to evaluate patients’ ability to walk and maintain balance. The total TMT scale (TMT-T) consists of a balance scale (TMT-B) and a gait scale (TMT-G). The TMT-B carries the subject through positions and changes in position, reflecting stability tasks that are related to daily activities. In the TMT-G, several qualitative aspects of the locomotion pattern are examined. Each item is scored on a 2- or 3-point scale, resulting in a maximum score of 28 on the TMT-T and maximum scores of 16 and 12 on the TMT-B and the TMT-G, respectively. The TMT score subdivides patients into three groups depending on the level of their dependence and the risk of falls. The group at the highest risk obtains the lowest scores (≤18). The group at moderate risk consists of people with scores of 19–23 points, which reflects moderate dependence and fall risk. The group at minimal risk is the one with scores of ≥24 points (Tinetti 1986; Tinetti et al. 1990; Tinetti 2003).

Assessment of muscle mass and strength

Muscle mass was measured by bioelectrical impedance analysis (BIA) using a Quantum/S Bioelectrical Body Composition Analyzer (Akern Srl, Florence, Italy). Whole-body BIA measurements were taken between the right wrist and ankle with the subject in a supine position. Muscle mass was calculated using the following BIA equation of Janssen and colleagues (Janssen et al. 2000). Skeletal muscle mass (kg) = ([height2/BIA resistance × 0.401] + [gender × 3.825] + [age × −0.71]) + 5.102 where height is measured in centimeters; BIA resistance is measured in ohms; for gender, men = 1 and women = 0; and age is measured in years. Absolute skeletal muscle mass (kg) was converted to skeletal muscle index standardizing by meters squared (kg/m2). Muscle strength was assessed by grip strength, measured using a handheld dynamometer (Mecmesin Advanced Force Gauge 500N, GDM, Italy). Body mass index-adjusted values were used as a cutoff point to classify low muscle strength (BMI ≤24, 24.1–28, <28 was 29, ≤30, and ≤32 kg for men and BMI ≤23, 23.1–26, 26.1–29, and <29 was 17, ≤17.3, ≤18, and ≤21 kg for women, respectively) (Volpato et al. 2014).

Statistical analysis

Baseline characteristics of the sample are expressed as mean ± standard deviation. Participants were stratified by tertiles of TMT (≤18, 19–23, and ≥24 points). Categorical variables were analyzed using chi-square testing and continuous variables using a one-way ANOVA. Univariate regression analysis was used to test a correlation among muscle mass and strength and TMT score with other variables such as age, BMI, WC, MMSE, GDS, CIRS-comorbidity, CIRS-severity, drug number, BADL, IADL MNA, 4-m walking speed, PASE, and social support score. Statistically significant variables were included into multivariate regression model as potential confounders. All statistical analyses were performed with SPSS software (version 15.0, SPSS Inc, Chicago, IL). A p value less than 0.05 was considered statistically significant.

Results

The sample consisted of 337 elderly participants, mean age 77.1 ± 6.9 years (median 75, range 65–100); 166 (49.3 %) were female and 171 (50.7 %) were men. Anthropometric measurements, geriatric multidimensional evaluation, and muscles stratified for different levels of TMT (≥24, 10–23, and ≤ 18) are presented in Table 1. As TMT score decreased, participants were progressively older and female sex was less prevalent. MMSE and PASE score decreased while GDS score, comorbidity severity score, BADL lost, MNA score, 4-min walking speed, and low social support increased as TMT score decreased. All biomarkers did not correlate with Tinetti score except for CRP which increases and butyryl-cholinesterase (b-CHE) which decreases as TMT score decreases.

Table 1.

Baseline characteristics of the 337 elderly participants enrolled in the study

Characteristics All Tinetti score p for trend
n = 337 ≥24 19–23 ≤18
n = 121 n = 66 n = 150
35.9 % 19.6 % 44.5 %
Anthropometric data
Age (years ± SD) 77.1 ± 6.9 74.2 ± 5.9 77.4 ± 6.0 78.9 ± 7.3* 0.001
Male sex (n,%) 171/50.7 89, 52.2 51, 30.0 30, 17.8* 0.001
Female sex 166/49.3 37, 22.5 35, 20.7 94, 56.8* 0.001
BMI (kg/m2) 26.0 ± 4.3 25.4 ± 4.0 26.6 ± 4.4 26.4 ± 4.4 0.249
Waist circumference (cm) 99.7 ± 13.5 98.1 ± 10.3 101.7 ± 10.4 100.3 ± 16.7 0.456
Geriatric evaluation
MMSE (score) 22.4 ± 6.0 25.2 ± 4.1 21.9 ± 6.2* 20.3 ± 6.4* 0.001
GDS (score) 7.6 ± 4.3 4.4 ± 3.1 7.6 ± 4.4* 10.1 ± 3.4* 0.001
CIRS-comorbidity (score) 4.47 ± 2.0 3.7 ± 2.0 4.5 ± 1.8 4.9 ± 2.1* 0.01
CIRS-severity (score) 1.94 ± 0.45 1.8 ± 0.3 1.9 ± 0.3 2.0 ± 0.5* 0.001
Drug number (n) 5.94 ± 2.94 5.1 ± 2.6 6.2 ± 2.9 6.1 ± 3.1* 0.265
BADL lost 1.7 ± 1.8 0.3 ± 0.8 1.2 ± 1.5* 2.7 ± 1.8 0.001
IADL lost 3.7 ± 2.7 1.8 ± 2.2 3.2 ± 2.5* 5.3 ± 2.2* 0.774
MNA (score) 21.2 ± 4.4 24.3 ± 3.0 21.7 ± 4.0 19.0 ± 4.1* 0.001
4-m walking speed (m/s) 0.33 ± 0.4 0.04 ± 0.1 0.18 ± 0.4* 0.62 ± 0.42* 0.001
PASE (score) 56.1 ± 65.2 101.6 ± 78.1 48.9 ± 39.9* 23.3 ± 35.4* 0.001
Social support (score) 8.2 ± 2.6 6.7 ± 2.3 8.5 ± 2.4 9.4 ± 2.2* 0.001
Frailty by Fried 3.3 ± 1.4 2.3 ± 1.1 3.0 ± 1.4 4.2 ± 1.0 0.001
Frailty by Rockwood 20.27 ± 8.63 13.2 ± 5.0 19.9 ± 5.8* 26.9 ± 5.8* 0.001
Biochemical measurements
Albumin (g/dL) 3.9 ± 0.5 4.0 ± 0.7 3.9 ± 0.5 3.8 ± 0.5 0.649
TIBC (μgr/dL) 275.8 ± 99.9 230.2± 350.3 ± 85.1 216.6 ± 89.9 0.197
Hemoglobin (g/dL) 12.5 ± 1.9 12.8 ± 1.9 12.5 ± 2.1 12.1 ± 1.7 0.210
Lymphocytes (×103) 2.1 ± 1.7 1.9 ± 1.3 3.0 ± 2.4 2.1 ± 1.7 0.587
CRP (mg/dL) 0.78 ± 0.53 0.75 ± 0.58 0.77 ± 0.56 0.81 ± 0.46 0.048
b-CHE (U/L) 7778 ± 2273 7880 ± 2162 7813 ± 2346 7618 ± 2223 0.042
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BMI body mass index, BADL basic activity of daily living, IADL instrumental activity of daily living, MNA mini-nutritional assessment, CIRS cumulative illness rating scale, MMSE mini-mental state examination; GDS geriatric depression scale, PASE physical activity scale for the elderly, TIBC total iron binding capacity, CRP C-reactive protein, b-CHE butyryl-cholinesterase

*p < 0.01 vs. Tinetti score ≥24

Figure 1 shows muscle mass and strength stratified by TMT score ≥24, 19–23, and ≤18 in non-institutionalized elderly people. Muscle mass decreased progressively as TMT score decreased (from 15.3 ± 3.7 to 8.8 ± 1.8 kg/m2; p for trend 0.001). Muscle mass at TMT score ≤18 was statistically significant vs. both TMT scores 19–23 and ≥ 24. Accordingly, muscle strength decreased progressively as TMT score decreased (from 34.7 ± 8.0 to 23.7 ± 8.7 kg; p for trend 0.001). Muscle strength at TMT score ≤18 was statistically significant vs. TMT score ≥ 24.

Fig. 1.

Fig. 1

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Muscle mass and strength stratified by Tinetti mobility test score ≥24, 19–23, and <18 in non-institutionalized elderly people. p for trend 0.001 for both muscle mass and strength vs. Tinetti score. *p < 0.001 vs. Tinetti score 19–23; # p < 0.00 vs. Tinetti score ≥24

When analyzing the skeletal muscle mass and TMT score (Table 2), univariate analysis demonstrates that age, CIRS-severity score, drug number, and BADL lost were negatively correlated while MNA, 4-m walking speed, PASE, hemoglobin and b-CHE, and more importantly TMT score were positively correlated with muscle mass. Multivariate analysis confirms this correlation except for BADL lost and PASE. In Fig. 2a, the positive linear relation between skeletal muscle mass and TMT score is shown (y = 4.5x + 0.4, r = 0.44; p < 0.01).

Table 2.

Uni- and multivariate linear regression analyses on “muscle strength” and “skeletal muscle mass”

Variable Muscle mass Muscle strength
Univariate Multivariate Univariate Multivariate
r p r p r p r p
Age −0.15 <0.01 −0.16 0.042 −0.14 0.023 −0.14 0.021
BMI 0.03 0.112 0.04 0.356
WC 0.03 0.410 0.05 0.552
MMSE 0.07 0.124 0.09 0.065
GDS −0.10 0.314 −0.12 0.321
CIRS-comorbidity 0.05 0.323 0.07 0.024 0.05 0.421
CIRS-Severity −0.07 0.041 −0.06 0.048 0.09 0.012 0.08 0.071
Drug number −0.08 0.028 −0.05 0.041 −0.07 0.035 −0.06 0.038
BADL −0.12 0.050 −0.10 0.048 −0.09 0.049
IADL −0.04 0.443 −0.03 0.542
MNA 0.08 0.045 0.05 0.687 0.09 0.052
Tinetti score 0.61 <0.01 0.048 0.024 0.53 <0.01 0.39 0.046
4-m walking speed 0.26 <0.01 0.25 0.042 0.24 0.025 0.27 0.045
PASE 0.15 0.034 0.13 0.064 0.18 0.015 0.13 0.065
Social support −0.04 0.231 −0.08 0.215
Albumin 0.14 0.075 0.14 0.074
TIBC 0.18 0.073 0.13 0.079
Hemoglobin 0.24 <0.01 0.23 <0.01 0.29 <0.01 0.26 0.024
Lymphocytes 0.13 0.052 0.14 0.064
CRP −0.26 <0.01 −0.09 0.421 −0.24 <0.01 −0.03 0.761
b-CHE 0.34 <0.01 0.30 <0.01 0.43 <0.01 0.34 0.041
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The data in bold indicate the parameters with a statistical significance

BMI body mass index, WC waist circumference, BADL basic activity of daily living, IADL instrumental activity of daily living, MNA mini-nutritional assessment, CIRS cumulative illness rating scale, MMSE mini-mental state examination, GDS geriatric depression scale, PASE physical activity scale for the elderly, TIBC total iron binding capacity, CRP C-reactive protein, b-CHE butyryl-cholinesterase

Fig. 2.

Fig. 2

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Regression linear relationship among muscle mass (a) and strength (b) and Tinetti mobility test score in non-institutionalized elderly people

Uni- and multivariate linear regression analyses on muscle strength are shown in Table 2. Age, CIRS-comorbidity and severity, drug number, and BADL lost positively correlated while 4-m walking speed, and TMT score were positively correlated with muscle strength. Except for CIRS-comorbidity and CIRS-severity and PASE, all linear relationship was confirmed at multivariate analysis. In Fig. 2b, the positive linear relation between muscle strength and TMT score is shown (y = 14.0x + 0.8, r = 0.34; p < 0.01).

Discussion

The present study indicates that TMT score is able to identify elderly participants at high risk of falls, relating to muscle mass and strength, both at univariate and multivariate analyses in non-institutionalized elderly participants. This evidence suggests that a reduction in muscle mass and strength, markers of sarcopenia in elderly participants, may represent a powerful marker to identify elderly participants at high risk of falls.

Sarcopenia

After the age of 50 years, muscle mass tends to be reduced at a rate of 1–2 % per year Marcell 2003). This muscle mass decline is defined as “sarcopenia” and it is mainly due to the progressive atrophy and loss of type II muscle fibers and motor neurons (Cruz-Jentoft et al. 2010). Sarcopenia-related fibrosis and infiltration of adipose take place in aging muscle (Goodpaster et al., 2008), leading to a reduction of functional capacity, to an increase of disability and mortality, and, therefore, to an elevated healthcare costs (Metter et al. 2002; Janssen et al. 2004; Ling et al. 2010; Rolland et al. 2008; Visser 2009). Many mechanisms have been hypothesized to explain the origin of age-related decline in muscle strength and mass, including malnutrition and inflammation (Morley and Baumgartner 2004; Soeters and Schols 2009).

Sarcopenia and falls

A number of studies have shown the relationship between sarcopenia and falls. Baumgartner et al. reported that people with lower appendicular SMI had a higher incidence of falls and lower body balance (Baumgartner et al. 1998). In a cohort study of 2148 English participants, Sayer et al. observed that patients with a history of falls presented with significantly lower muscle power (Sayer et al. 2006). In a recent study, in patients with hip fracture, sarcopenia was found in 44.7 % of female and 81.1 % of male patients (Holvik et al. 2010). In addition, sarcopenia prevalence was significantly higher in patients with hip fractures, than in those without hip fractures, even when adjusted for age and sex (Hida et al. 2013). A high prevalence of sarcopenia in fallers might reflect the poor general health or frail condition of the patient. Comorbidity, together with malnutrition, vitamin D insufficiency, and lack of physical activity, is common to sarcopenia and osteopenia (Bischoff et al. 2003). Thus, the presence of sarcopenia was a potential risk factor for an osteoporotic fracture. Simultaneous muscle and bone loss causes more severe instability in the frail elderly, which leads to falls and subsequent fracture. The combined effect of sarcopenia and osteoporosis is a devastating hazard to the old frail subject (Crepaldi and Maggi 2005). Hip fracture reduced life expectancy by 1.8 years or 25 % compared with an age- and sex-matched general population, and the development of deficits in ADLs after hip fracture resulted in substantial morbidity, mortality, and costs (Braithwaite et al. 2003). These findings emphasize the importance of developing clinical instruments to prevent the higher age-related incidence of hip fracture.

TMT and falls

Although several risk assessment tools have been developed to evaluate the risk of falling, a recent review reported that the TMT score is the most frequently cited assessment tool (Köpke and Meyer 2006). It has been also indicated to be the gold standard in assessing mobility dysfunctions in the elderly and an important fall risk assessment measure in various populations (Köpke and Meyer 2006). In an analytic review on fall risk assessment measures, TMT shows 90 % of interrater reliability, 80 % of sensitivity, and 74 % of specificity (Perell et al. 2001). Notably, in a prospective study of 225 community-dwelling people 75 years and older, the Tinetti balance scale was able to predict individuals who fell during the following year; 53 % of the individuals were screened positive and presented a twofold risk of falling (Perell et al. 2001). This evidence supports the use of this test to screen older people at risk of falling in order to include them in a preventive intervention.

Sarcopenia and TMT

To the best of our knowledge, this is the first report on the relationship between sarcopenia and TMT score. In our non-institutionalized elderly participant sample, TMT score was powerfully correlated to muscle strength and mass indices in both univariate (r = 0.61 and r = 0.53, respectively) and multivariate (r = 0.44 and r = 0.34, respectively) analyses. This relationship is particularly strong for TMT values equal to 18 or less. Interestingly, at this value several characteristics of frail elderly are present (i.e., low MMSE score, high GDS score, and ADL and IADL lost). Accordingly, the “frailty score” identified by Fried’s and Rockwood’s methods was 4.2 ± 1.0 (range 0–5) and 26.9 ± 5.8 (range 0–40), respectively. Notably, inflammatory markers such as CRP and b-CHE significantly increase for TMT values equals to 18 or less.

Limitations of the study

Two limitations should be considered. First, although the correlation between TMT score, as continuous variable, and muscle strength and mass has been clearly demonstrated, the relationship between TMT score and fall history and severity in our population is not available. Second, computed tomography, magnetic resonance imaging, and dual energy X-ray absorptiometry (DXA) are considered the gold standard in muscle mass detection. However, BIA may be used in clinical setting because of its lower cost and larger availability. Unfortunately, BIA is known to underestimate fat mass and overestimate muscle mass (Beaudart et al. 2015).

Conclusions

The use of TMT score, together with muscle strength and evaluation, is able to preventively detect sarcopenic elderly subject at risk of falls. Actually, TMT score is linearly related to muscle mass and strength, independently of several factors including age, and, therefore, represents an ideal and inexpensive tool to detect sarcopenic elderly participants at risk of falls.

Acknowledgments

We acknowledge all the participants included in the present study.

Authors’ contributions

B.C., L.I., D.D., Ga.G., Gi.G., G.T., and L.A. made the acquisition of data and the analysis and interpretation of data. C.F., B.D., and A.P. made substantial contributions to the conception and design, acquisition of data, analysis and interpretation of data, drafting the article or revising it critically for important intellectual content, and final approval of the version to be published. F.C made a substantial contribution to a revision of the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Funding

The study was financially supported by AIFA (Agenzia Italiana del Farmaco) of the Italian Minister of Health (cod. FARM7K7XZB).

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