High density muscle size and muscle power are associated with both gait and sit-to-stand kinematic parameters in frail nonagenarians

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Abstract

Frailty is an important concept in clinical and demographic research in the elderly because of its incidence level and its relationship with adverse outcomes. Functional ability declines with advanced age, likely due to changes in muscle function. This study aimed to examine the relationship between muscle quality and muscle power with kinematics from functional tests in a population of 21 institutionalized frail nonagenarian (91.3 ± 3.1 years).

Here, muscle quality was measured by segmenting areas of high- and low-density fibers with computerized tomography. In addition, muscle strength and muscle power were obtained through maximal strength and power tests using resistance exercises. Finally, functional capacity outcomes (i.e., balance, gait velocity and sit-to-stand ability), as well as kinematic parameters, were evaluated from a tri-axial sensor used during a battery of functional tests.

Our results show that lower limb muscle quality, maximal strength and power output present statistically significant relationships with different kinematic parameters, especially during the sit-to-stand and gait tests (e.g. leg power and maximum power during sit-to-stand (r = 0.80) as well as quadriceps muscle mass and step asymmetry (r = -0,71). In particular, frail individuals with greater muscle quality needed less trunk range of motion to make the transition between sitting and standing, took less time to stand up, and exerted a major peak power of force.

As a conclusion, a loss of muscle quality and power may lead to motor control impairments such as gait, sit-to-stand and balance that can be the cause of adverse events such as falls.

Introduction

Promoting healthy aging is an important but challenging goal (Brown and Flood, 2013, Christensen et al., 2009), because it is known that while life expectancy is increasing, the number of healthful years is decreasing (Gray and Paulson, 2014). Indeed, 25% of individuals aged 65 years and over have mobility limitations (Guralnik et al., 1995), and 80% of older adults live with at least one mobility disability (Prevention, 2013). Impaired mobility is often a precursor of functional capacity decline, disability and the development of frailty, which places a greater demand on primary caregivers and healthcare providers (Zarzeczny et al., 2017). Accordingly, the cost of healthcare for elderly adults can be 3–5 times greater than that for an individual younger than 65 (Prevention, 2013). For these reasons, there is a keen interest in determining factors that influence mobility to maximize it as people age (Fried et al., 2001). To this aim, kinematic measurements of mobility (i.e., balance, gait and sit-to-stand) assessed through the use of inertial units (IU) have been investigated and associated to muscle mass and muscle power in frail adults (Martinikorena et al., 2016).

Both sarcopenia and frailty are important entities used, often interchangeably, to identify a threshold in the aging process. Sarcopenia is a condition of muscle mass loss and muscle weakness that results in poorer functionality status, and is one of the main causes of frailty syndrome (Hughes et al., 2001). Frailty is theoretically defined as a clinically recognizable state of increased vulnerability resulting from aging-associated decline in reserve and function across multiple physiologic systems such that the ability to cope with every day or acute stressors is comprised (Xue, 2011). This is an emerging concept that affects 25–50% of all people over 85 years, making them more prone to falls, disability, long-term care and death (Fried et al., 2001, Song et al., 2010). Low muscle mass is strongly associated with frailty syndrome (Bandeen-Roche et al., 2006, Garcia-Garcia et al., 2011, Izquierdo and Cadore, 2014). Muscle strength and muscle power output are neuromuscular outcomes that considerably decrease with age (Gray and Paulson, 2014) (i.e., muscle power declines by 3.5% per year and is a strong predictor of mobility disability) (de Vos et al., 2005). Muscle mass alone cannot fully explain the loss of muscle strength and physical function capacity in older adults (Auyeung et al., 2014, Goodpaster et al., 2006, Hughes et al., 2001, Schaap et al., 2013). Expert working groups recommend evaluating older adult muscle health in terms of mass, strength and functional abilities performance (Cruz-Jentoft et al., 2010). Notwithstanding, there is scarce data on the possible associations of muscle quality and mechanical muscle function capacity (i.e., strength and power) with kinematic parameters of mobility in frail adults.

Surveys on the functionality status of older populations include performance-based tests to stratify the risk of muscle weakness (Zarzeczny et al., 2017). Deterioration of the lower limb muscles can be observed through gait pattern disorders (Shin et al., 2012) and difficulties in rising from a chair (Moxley Scarborough et al., 1999, Schenkman et al., 1990). Both muscle mass and muscle power can be calculated, but methodologies are not ideal for field-based situations (Sands et al., 2004). Functional performance tests are used in these situations, but outputs tend to provide less information (e.g., time, distance, or number of repetitions). However, technological advances have made it possible to collect more detailed data (i.e., sit-to-stand (SiSt) and stand-to-sit (StSi) transitions, step time and variability, among others) through the use of inertial units (IU) (Grimm and Bolink, 2016, Sun et al., 2017). Numerous studies have demonstrated the validity of these tools to identify frail populations based on kinematic measurements (Martínez-Ramírez et al., 2015, Millor et al., 2013aa). Yet, muscle fat infiltration determined by low-density computerized tomography scans (i.e., muscle quality) has been scarcely investigated despite its important role in functional performance in older adults (Casas-Herrero et al., 2013).

The main purpose of this study was to assess the associations of muscle function and morphology with kinematics from a battery of functional tests (i.e., balance, gait and sit-to-stand) in a population of the oldest old. Our hypothesis was that kinematic outcomes assessed during functional tests would significantly correlate with muscle power, muscle strength and muscle quality.

Section snippets

Experimental design

We sought to examine for associations between lower limb muscle function capacity, in terms of quality, strength and power, and performance of several functional tests (SBT, 6-m GVT and 30-s CST), and relate them to kinematic parameters. Muscle quality, maximal strength and maximal power were measured through examination of computerized tomography (CT) images of the mid-thigh muscles, as well as leg strength and leg power tests, respectively. A single IU located at the center of mass at the

Results

The kinematic parameters from the SBT, 6-m GVT and 30-s CST as well as muscle quality and leg strength results are summarized in Table 2.

Discussion

A unique finding of the present study was the significant relationship between muscle quality and muscle power with functional test performance (i.e. SBT, 6-m GVT and 30-s CST) included in the SPPB evaluation used in geriatric studies. In particular, muscle quality was negatively associated with gait predictability and gait asymmetry; as well as trunk range of motion during sit-to-stand. On the other hand, maximal strength and maximal power output were positively associated with vertical gait

Conclusions

In summary, lower limb muscle quality, maximal strength and maximal power output were associated with different kinematic parameters, especially during gait and sit-to-stand tests.

Brief summary

Associations between lower limb muscle quality and kinematics during functional tests in frail population are observed. This kinematic information reflects motor control impairments and explain the degeneration attributed to aging. Therefore, it seems to be valuable information for clinicians.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported in part by a research grant PI17/01814 of the Ministerio de Economía, Industria y Competitividad de España (ISCIII, FEDER).

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